diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 71a5330..8e83c47 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -2,283 +2,26 @@
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diff --git a/.ipynb_checkpoints/gaugeReader-checkpoint.ipynb b/.ipynb_checkpoints/gaugeReader-checkpoint.ipynb
deleted file mode 100644
index 28f6f89..0000000
--- a/.ipynb_checkpoints/gaugeReader-checkpoint.ipynb
+++ /dev/null
@@ -1,404 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Image Data Preparation:\n",
-    "\n",
-    "The data processing is implemented through the LoadImg module (modules/LoadImg.py). The images dataset is first split into train and validation datasets, and then the images size and color mode are adjusted (using keras.preprocessing package). The following code block shows how the train and validation datasets can be obtained via LoadImg module."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The image pre-processing is complete.\n"
-     ]
-    }
-   ],
-   "source": [
-    "from modules import LoadImg\n",
-    "\n",
-    "# The color_mode is either 'rgb' or 'grayscale' (default).\n",
-    "X_train, X_validation, y_train, y_validation, cls_indices = LoadImg.Dataset.prep_datasets(\n",
-    "    ver_ratio=0.2, container_path='data/ImageEveryUnit',\n",
-    "    final_img_width=79, final_img_height=79,\n",
-    "    color_mode=\"grayscale\", random_state=1911)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Data Exploration:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Train and Validation Datasets\n",
-    "After data preparation, there are 1315 images in the training dataset and 329 images in the validation dataset."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "There are 1315 images in the train dataset.\n",
-      "There are 329 images in the validation dataset.\n",
-      "The images shape is (79, 79, 3)\n"
-     ]
-    }
-   ],
-   "source": [
-    "print('There are {} images in the train dataset.'.format(X_train.shape[0]))\n",
-    "print('There are {} images in the validation dataset.'.format(X_validation.shape[0]))\n",
-    "print('The images shape is {}'.format(X_train.shape[1:]))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In this example, a width and height of 79 were chosen, so the images shape is (79, 79, 3). In the following code blocks, 12 images are randomly selected from train and validation datasets. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Training Data Samples:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1080x180 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "%matplotlib inline\n",
-    "\n",
-    "fig = plt.figure(figsize=(15,2.5))\n",
-    "imgs_num = np.random.choice(range(len(X_train)), 6)\n",
-    "\n",
-    "for i, img_num in enumerate(imgs_num):\n",
-    "    ax = fig.add_subplot(1, 6, i + 1, xticks=[], yticks=[])\n",
-    "    ax.imshow(X_train[img_num, :, :, 0], cmap='gray')\n",
-    "    ax.set_title('category {}_train'.format(np.argmax(y_train[img_num])))\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Validation Data Samples:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1080x180 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(15,2.5))\n",
-    "imgs_num = np.random.choice(range(len(X_validation)), 6)\n",
-    "\n",
-    "for i, img_num in enumerate(imgs_num):\n",
-    "    ax = fig.add_subplot(1, 6, i + 1, xticks=[], yticks=[])\n",
-    "    ax.imshow(X_validation[img_num, :, :, 0], cmap='gray')\n",
-    "    ax.set_title('category {}_val'.format(np.argmax(y_validation[img_num])))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Ensembling:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The objective of this work is to train multiple models (here, referred to as __primary models__) and eventually use them to construct an ensemble model (a two layer fully connected neural network) which can perform with higher validation accuracy than each individual primary models. To construct the ensemble model, first the primay models are trained and then the logits (i.e. the output of the last layer softmax activation functions) of all models are computed and stacked into a numpy array (1D tensor) which will be the input of the ensemble model, a two layer fully connected neural network. The ensemble model is a classifier that is to predict the same 31 categories. It is trained with the same training dataset and its performance is evaluated versus the same validation dataset as those used for the primary models."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Primary Models:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\n",
-    "\n",
-    "For each primary model, a Covolutional Neural Network (CNN) architechture is trained and used for predicting the gauge images categories. There are 30 categories that show the pressure level collected by the gauge with half of the pressure unit (here psi) increments and one NaN category (31 categories all together).\n",
-    "\n",
-    "The CNN model consists of three CNN and two Fully Connected (FC) layers (the layers are defined in the NewLayers module, _modules/NewLayers.py_, and are combined in the NeuralNet module, _modules/NeuralNet.py_). The activation function of all layers is Rectified Linear Unit (relu) except the last layer which is softmax.\n",
-    "\n",
-    "During the training, the cross-entropy function and Adam algorithm are employed as the cost function and optimizer, respectively. The model performance is evaluated via the accuracy of the validation dataset and the model checkpoint is saved (in the _logs/models/main_ folder) whenever the accuracy is improved. The models that have high validation accuracy for each specific category are also saved (in folders with the same name as the category name like _logs/models/psi_\\__2_); these models can be later used as primary models.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Custom Performance Metric:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The validation dataset accuracy is used as the metric to evaluate the model performance during the model training and the model checkpoint is saved whenever it increases. In tie cases where the performance metric does not change over training iterations, if the median of the true label logits (of the validation dataset) increases, the saved checkpoint is overwritten by the latest model chackpoint.\n",
-    "\n",
-    "In addition to the model evaluation using the whole validation dataset accuracy, the model perfomance for each specific category is also evaluated using the following equation:\n",
-    "\n",
-    "_catPerf = (number of true predictions in validation dataset for that category)/(total number of validation samples for that category)_\n",
-    "\n",
-    "The model checkpoints are also saved whenever the _catPerf_ increases during training in folders corresponding to categories such as _logs/models/psi_\\__2_.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Hyperparameter Tuning:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "For the primary models hyperparameter tuning, first a model was trained using images with the same width/height ratio as the original images, which is one here. The hyperparameters of this model were manually tunned and the ones that resulted better performance (i.e. validation dataset accuracy) were used for the subsequent models.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch 0 ... \n",
-      "train_acc: 0.0327   test_acc: 0.0243  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 1 ... \n",
-      "train_acc: 0.0190   test_acc: 0.0091  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 2 ... \n",
-      "train_acc: 0.0814   test_acc: 0.0942  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 3 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 4 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 5 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 6 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 7 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 8 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 9 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 10 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 11 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 12 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0320\n",
-      "\n",
-      "epoch 13 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 14 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 15 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 16 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 17 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 18 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "epoch 19 ... \n",
-      "train_acc: 0.0844   test_acc: 0.1003  best_logits_median: 0.0321\n",
-      "\n",
-      "Time usage: 0:03:29\n"
-     ]
-    }
-   ],
-   "source": [
-    "from modules import OptimizeAndLog\n",
-    "\n",
-    "##\n",
-    "OptimizeAndLog.OptimizerLogger. \\\n",
-    "    train_and_save_logs_three_CNN(filter_size1=17, num_filters1=45, strides_1=[1, 7, 7, 1],\n",
-    "                                  use_pooling_1=True, pooling_ksize_1=[1, 4, 4, 1], pooling_strides_1=[1, 4, 4, 1],\n",
-    "                                  ##\n",
-    "                                  filter_size2=7, num_filters2=17, strides_2=[1, 5, 5, 1],\n",
-    "                                  use_pooling_2=True, pooling_ksize_2=[1, 3, 3, 1], pooling_strides_2=[1, 3, 3, 1],\n",
-    "                                  ##\n",
-    "                                  filter_size3=1, num_filters3=7, strides_3=[1, 1, 1, 1],\n",
-    "                                  use_pooling_3=False, pooling_ksize_3=None, pooling_strides_3=None,\n",
-    "                                  ##\n",
-    "                                  fc_size=86,\n",
-    "                                  num_iterations=20,\n",
-    "                                  learning_rate=5e-4, momentum=None,\n",
-    "                                  X_train=X_train, y_train=y_train,\n",
-    "                                  X_test=X_validation, y_test=y_validation,\n",
-    "                                  models_log_path='./logs/models/',\n",
-    "                                  cls_indices=cls_indices,\n",
-    "                                  keep_best_model = True,\n",
-    "                                  padding='SAME',\n",
-    "                                  device_name=\"/cpu:0\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Feature Engineering:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Having trained the initial model, the width/height ratios of the images were changed and for each ratio a model was trained and its saved checkpoint was manually copy-pasted to the _logs/historical_\\__models_ for the final ensemble model."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The image pre-processing is complete.\n"
-     ]
-    }
-   ],
-   "source": [
-    "X_train_2, X_validation_2, y_train_2, y_validation_2, _ = LoadImg.Dataset.prep_datasets(\n",
-    "    ver_ratio=0.2, container_path='data/ImageEveryUnit',\n",
-    "    final_img_width=160, final_img_height=80,\n",
-    "    color_mode=\"grayscale\", random_state=1911)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1080x180 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(15,2.5))\n",
-    "imgs_num = np.random.choice(range(len(X_train_2)), 6)\n",
-    "\n",
-    "for i, img_num in enumerate(imgs_num):\n",
-    "    ax = fig.add_subplot(1, 6, i + 1, xticks=[], yticks=[])\n",
-    "    ax.imshow(X_train_2[img_num, :, :, 0], cmap='gray')\n",
-    "    ax.set_title('category {}_train'.format(np.argmax(y_train_2[img_num])))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "OCI_gaugeReader",
-   "language": "python",
-   "name": "oci_gaugereader"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/CustomEstimator/CLI_commands/copy_to_bucket.sh b/CustomEstimator/CLI_commands/copy_to_bucket.sh
new file mode 100644
index 0000000..752d0bb
--- /dev/null
+++ b/CustomEstimator/CLI_commands/copy_to_bucket.sh
@@ -0,0 +1,5 @@
+gsutil -m cp -r ./data/ImageEveryUnit/. gs://deep_gauge/data/
+gsutil -m cp -r ./trainer/. gs://deep_gauge
+
+## make a package
+tar -czvf ensemble_package.tar.gz /ensemble_package
diff --git a/CustomEstimator/CLI_commands/ens.sh b/CustomEstimator/CLI_commands/ens.sh
new file mode 100644
index 0000000..32dea65
--- /dev/null
+++ b/CustomEstimator/CLI_commands/ens.sh
@@ -0,0 +1,51 @@
+python customEstimator.py --dev=True --retrain_primary_models=False --hidden_units='[100, 200, 300, 500]' --verbosity=DEBUG
+
+
+#######
+gcloud ml-engine local train \
+          --module-name trainer_from_storage.task \
+          --package-path /home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage \
+          -- \
+          --primary_models_directory=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/primary_models \
+          --ensemble_architecture_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/temporary_models \
+          --path_to_images=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/data/ImageEveryUnit \
+          --bin_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/dumps/ \
+          --export_dir=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/exported_model
+
+
+
+
+####### on GCP
+gcloud ml-engine jobs submit training ensemble_training \
+          --scale-tier basic \
+          --package-path /home/khodayarim/PycharmProjects/ensamble_package.tar.gz  \
+          --module-name ensemble_package.task \
+          --job-dir gs://deep_gauge \
+          --region "us-east1"
+          -- \
+          --primary_models_directory=gs://deep_gauge/ensemble_package/misc/primary_models \
+
+
+
+
+
+
+          --staging-bucket gs://deep_gauge/ensemble_package \
+
+          --packages additional-dep1.tar.gz,dep2.whl
+          -- \
+          --primary_models_directory=gs://deep_gauge/ensemble_package/misc/primary_models \
+
+          --module-name trainer_from_storage.task \
+          --package-path gs://deep_gauge/ensemble_package \
+          -- \
+          --primary_models_directory=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/primary_models \
+          --ensemble_architecture_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/temporary_models \
+          --path_to_images=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/data/ImageEveryUnit \
+          --bin_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/dumps/ \
+          --export_dir=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/CustomEstimator/modules/ensemble_modules/trainer_from_storage/logs/exported_model
+
+
+
+
+
diff --git a/DeepGauge_ML-Demo.ipynb b/CustomEstimator/DeepGauge_ML-Demo.ipynb
similarity index 100%
rename from DeepGauge_ML-Demo.ipynb
rename to CustomEstimator/DeepGauge_ML-Demo.ipynb
diff --git a/README.md b/CustomEstimator/README.md
similarity index 100%
rename from README.md
rename to CustomEstimator/README.md
diff --git a/modules/__init__.py b/CustomEstimator/__init__.py
similarity index 100%
rename from modules/__init__.py
rename to CustomEstimator/__init__.py
diff --git a/customEstimator.py b/CustomEstimator/customEstimator.py
similarity index 100%
rename from customEstimator.py
rename to CustomEstimator/customEstimator.py
diff --git a/gaugeReader.ipynb b/CustomEstimator/gaugeReader.ipynb
similarity index 100%
rename from gaugeReader.ipynb
rename to CustomEstimator/gaugeReader.ipynb
diff --git a/modules/ensemble_modules/__init__.py b/CustomEstimator/modules/__init__.py
similarity index 100%
rename from modules/ensemble_modules/__init__.py
rename to CustomEstimator/modules/__init__.py
diff --git a/modules/__init__.pyc b/CustomEstimator/modules/__init__.pyc
similarity index 100%
rename from modules/__init__.pyc
rename to CustomEstimator/modules/__init__.pyc
diff --git a/modules/__pycache__/__init__.cpython-36.pyc b/CustomEstimator/modules/__pycache__/__init__.cpython-36.pyc
similarity index 100%
rename from modules/__pycache__/__init__.cpython-36.pyc
rename to CustomEstimator/modules/__pycache__/__init__.cpython-36.pyc
diff --git a/modules/ensemble_modules/trainer/__init__.py b/CustomEstimator/modules/ensemble_modules/__init__.py
similarity index 100%
rename from modules/ensemble_modules/trainer/__init__.py
rename to CustomEstimator/modules/ensemble_modules/__init__.py
diff --git a/modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc b/CustomEstimator/modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc
similarity index 100%
rename from modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc
rename to CustomEstimator/modules/ensemble_modules/__pycache__/CustomEnsembleEstimator.cpython-36.pyc
diff --git a/modules/ensemble_modules/CustomEnsembleEstimator.py b/CustomEstimator/modules/ensemble_modules/ensemble/CustomEnsembleEstimator.py
similarity index 100%
rename from modules/ensemble_modules/CustomEnsembleEstimator.py
rename to CustomEstimator/modules/ensemble_modules/ensemble/CustomEnsembleEstimator.py
diff --git a/modules/ensemble_modules/trainer_from_storage/__init__.py b/CustomEstimator/modules/ensemble_modules/ensemble/__init__.py
similarity index 100%
rename from modules/ensemble_modules/trainer_from_storage/__init__.py
rename to CustomEstimator/modules/ensemble_modules/ensemble/__init__.py
diff --git a/modules/ensemble_modules/ensemble_build.py b/CustomEstimator/modules/ensemble_modules/ensemble/ensemble_build.py
similarity index 67%
rename from modules/ensemble_modules/ensemble_build.py
rename to CustomEstimator/modules/ensemble_modules/ensemble/ensemble_build.py
index d171124..6676b84 100644
--- a/modules/ensemble_modules/ensemble_build.py
+++ b/CustomEstimator/modules/ensemble_modules/ensemble/ensemble_build.py
@@ -1,15 +1,18 @@
 import glob
+import numpy as np
 import os
-from tensorflow.python.framework import meta_graph
 import tensorflow as tf
-from modules import LoadImg
 import time
-import numpy as np
+from tensorflow.python.framework import meta_graph
+
+from CustomEstimator.modules.primary_models_modules import LoadImg
 
 X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
-    ver_ratio=0.2, container_path='data/ImageEveryUnit',
+    ver_ratio=0.2, container_path='./CustomEstimator/data/ImageEveryUnit',
     final_img_width=224, final_img_height=224,
-    color_mode="grayscale", random_state=1911, is_trial=True)
+    color_mode="grayscale", random_state=1911,
+    is_trial=True,
+    bin_path='./CustomEstimator/modules/ensemble_modules/ensemble/bin/')
 
 
 class Ensemble():
@@ -189,9 +192,9 @@ def new_fc_layer(inp,
         return raw_imgs, logits_fc
 
 
-def build_model_and_train(primary_models_directory='./logs/primary_models/',
-                          writer_path='./trial/writer',
-                          save_model_path='./trial/best_model_main',
+def build_model_and_train(primary_models_directory='./CustomEstimator/logs/primary_models/',
+                          writer_path='./CustomEstimator/modules/ensemble_modules/ensemble/trial/writer',
+                          save_model_path='./CustomEstimator/modules/ensemble_modules/ensemble/trial/best_model_main',
                           images_shape=[None, 224, 224, 3],
                           hidden_units=[500, 100],
                           X_train=X_train, X_test=X_test,
@@ -203,77 +206,101 @@ def build_model_and_train(primary_models_directory='./logs/primary_models/',
         n_output=y_train.shape[1],
         primary_models_directory=primary_models_directory,
         images_shape=images_shape)
-    tf.reset_default_graph()
-    graph = tf.get_default_graph()
-
-    ## y
-    y_true_tf = tf.placeholder(tf.float64, shape=[None, y_train.shape[1]],
-                               name='y_true_tf')
-
-    y_pred = tf.nn.softmax(logits_fc)
-    y_pred_cls = tf.argmax(y_pred, axis=1)
-    y_true_cls = tf.argmax(y_true_tf, axis=1)
-    correct_prediction = tf.equal(y_pred_cls, y_true_cls)
-    accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
-
-    ## dataset
-    dataset = tf.data.Dataset.from_tensor_slices((raw_imgs, y_true_tf))
-    dataset = dataset.shuffle(buffer_size=100)
-    dataset = dataset.batch(batch_size)
-    dataset = dataset.repeat(epochs)
-    iter = dataset.make_initializable_iterator()
-    # iter = dataset.make_one_shot_iterator()
-    get_batch = iter.get_next()
-
-    ## cost
-    cost = tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits_fc,
-                                                      labels=y_true_tf,
-                                                      name='cost_fc')
-
-    trainable_variables = [v for v in tf.trainable_variables() if 'ensemble' in v.name]
-    optimizer = tf.train.AdamOptimizer(learning_rate=3e-4, name='adam_fc'). \
-        minimize(cost, var_list=trainable_variables)
-    # variables_list = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name]
-
-    feed_dict_train = {raw_imgs: X_train,
-                       y_true_tf: y_train}
-
-    feed_dict_test = {raw_imgs: X_test,
-                      y_true_tf: y_test}
+    # tf.reset_default_graph()
+    # graph = tf.get_default_graph()
+    #
+    # ## y
+    # y_true_tf = tf.placeholder(tf.float64, shape=[None, y_train.shape[1]],
+    #                            name='y_true_tf')
+    #
+    # y_pred = tf.nn.softmax(logits_fc)
+    # y_pred_cls = tf.argmax(y_pred, axis=1)
+    # y_true_cls = tf.argmax(y_true_tf, axis=1)
+    # correct_prediction = tf.equal(y_pred_cls, y_true_cls)
+    # accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+    #
+    # ## dataset
+    # dataset = tf.data.Dataset.from_tensor_slices((raw_imgs, y_true_tf))
+    # dataset = dataset.shuffle(buffer_size=100)
+    # dataset = dataset.batch(batch_size)
+    # dataset = dataset.repeat(epochs)
+    # iter = dataset.make_initializable_iterator()
+    # # iter = dataset.make_one_shot_iterator()
+    # get_batch = iter.get_next()
+    #
+    # ## cost
+    # cost = tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits_fc,
+    #                                                   labels=y_true_tf,
+    #                                                   name='cost_fc')
+    #
+    # trainable_variables = [v for v in tf.trainable_variables() if 'ensemble' in v.name]
+    # optimizer = tf.train.AdamOptimizer(learning_rate=3e-4, name='adam_fc'). \
+    #     minimize(cost, var_list=trainable_variables)
+    # # variables_list = [n.name for n in tf.get_default_graph().as_graph_def().node if 'raw_imgs' in n.name]
+    #
+    # feed_dict_train = {raw_imgs: X_train,
+    #                    y_true_tf: y_train}
+    #
+    # feed_dict_test = {raw_imgs: X_test,
+    #                   y_true_tf: y_test}
 
     # Start-time used for printing time-usage below.
-    start_time = time.time()
-
-    with tf.Session(graph=graph) as session:
-        # initialize weights and biases variables
-        session.run(tf.global_variables_initializer())
-        session.run(iter.initializer, feed_dict=feed_dict_train)
-        writer = tf.summary.FileWriter(writer_path, session.graph)
-
-        best_validation_accuracy=0
-
-        for i in range(200):
-            try:
-                print('batch {} ... '.format(i))
-                Xydata = session.run(get_batch)
-                session.run(optimizer, feed_dict={raw_imgs: Xydata[0],
-                                                  y_true_tf: Xydata[1]})
-                accuracy_train = session.run(accuracy, feed_dict=feed_dict_train)
-                print('train_acc = {} ... '.format(accuracy_train))
-                accuracy_validation = session.run(accuracy, feed_dict=feed_dict_test)
-                print('validation_acc = {} ... '.format(accuracy_validation))
-                if accuracy_validation > best_validation_accuracy:
-                    saver = tf.train.Saver(max_to_keep=1)
-                    saver.save(session, save_model_path)
-            except:
-                break
-
-        writer.close()
-
-    end_time = time.time()
-
-    print("Training took {}.".format(end_time-start_time))
+    # start_time = time.time()
+
+    # with tf.Session() as session:
+    #     # initialize weights and biases variables
+    #     session.run(tf.global_variables_initializer())
+        # session.run(iter.initializer, feed_dict=feed_dict_train)
+        # writer = tf.summary.FileWriter(writer_path, session.graph)
+
+        # best_validation_accuracy=0
+    #
+    #     for i in range(200):
+    #         try:
+    #             print('batch {} ... '.format(i))
+    #             Xydata = session.run(get_batch)
+    #             session.run(optimizer, feed_dict={raw_imgs: Xydata[0],
+    #                                               y_true_tf: Xydata[1]})
+    #             accuracy_train = session.run(accuracy, feed_dict=feed_dict_train)
+    #             print('train_acc = {} ... '.format(accuracy_train))
+    #             accuracy_validation = session.run(accuracy, feed_dict=feed_dict_test)
+    #             print('validation_acc = {} ... '.format(accuracy_validation))
+    #             if accuracy_validation > best_validation_accuracy:
+    #                 saver = tf.train.Saver(max_to_keep=1)
+    #                 saver.save(session, save_model_path)
+    #         except:
+    #             break
+    #
+    #     writer.close()
+    #
+    # end_time = time.time()
+    #
+    # print("Training took {}.".format(end_time-start_time))
 
     return
 
-build_model_and_train()
\ No newline at end of file
+build_model_and_train()
+
+graph_pred = tf.get_default_graph()
+a=tf.trainable_variables()
+trainable_variables = [v for v in tf.trainable_variables() if 'logits_tf' in v.name]
+
+
+
+with tf.Session() as session:
+    saver_3 = tf.train.import_meta_graph('./CustomEstimator/modules/ensemble_modules/ensemble/logs/primary_models/1st/best_model_main.meta',
+                                         clear_devices=True)
+    saver_3.restore(tf.get_default_session(),
+                    tf.train.latest_checkpoint('./CustomEstimator/modules/ensemble_modules/ensemble/logs/primary_models/1st/'))
+    graph_pred = tf.get_default_graph()
+    raw_imgs = graph_pred.get_tensor_by_name("raw_imgs:0")
+    logits_tf = graph_pred.get_tensor_by_name("logits_tf:0")
+    b = tf.trainable_variables()
+
+    c=b[0].eval()
+
+    ##
+    feed_dict_pred = {raw_imgs: X_train}
+
+    ##
+    # logits = session.run(b[0])
diff --git a/modules/ensemble_modules/funcs_backup.py b/CustomEstimator/modules/ensemble_modules/ensemble/funcs_backup.py
similarity index 100%
rename from modules/ensemble_modules/funcs_backup.py
rename to CustomEstimator/modules/ensemble_modules/ensemble/funcs_backup.py
diff --git a/modules/ensemble_modules/obsolete_EnsenmbleData.py b/CustomEstimator/modules/ensemble_modules/ensemble/obsolete_EnsenmbleData.py
similarity index 100%
rename from modules/ensemble_modules/obsolete_EnsenmbleData.py
rename to CustomEstimator/modules/ensemble_modules/ensemble/obsolete_EnsenmbleData.py
diff --git a/modules/ensemble_modules/trainer/CustomEnsembleEstimator.py b/CustomEstimator/modules/ensemble_modules/trainer_from_memory/CustomEnsembleEstimator.py
similarity index 100%
rename from modules/ensemble_modules/trainer/CustomEnsembleEstimator.py
rename to CustomEstimator/modules/ensemble_modules/trainer_from_memory/CustomEnsembleEstimator.py
diff --git a/modules/LoadImg.py b/CustomEstimator/modules/ensemble_modules/trainer_from_memory/LoadImg.py
similarity index 100%
rename from modules/LoadImg.py
rename to CustomEstimator/modules/ensemble_modules/trainer_from_memory/LoadImg.py
diff --git a/hyperParamOptimizer.py b/CustomEstimator/modules/ensemble_modules/trainer_from_memory/__init__.py
similarity index 100%
rename from hyperParamOptimizer.py
rename to CustomEstimator/modules/ensemble_modules/trainer_from_memory/__init__.py
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/modules/ensemble_modules/trainer_from_storage/__pycache__/__init__.cpython-36.pyc b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/__pycache__/__init__.cpython-36.pyc
similarity index 100%
rename from modules/ensemble_modules/trainer_from_storage/__pycache__/__init__.cpython-36.pyc
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/__pycache__/__init__.cpython-36.pyc
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/bucket_data.sh b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/bucket_data.sh
new file mode 100644
index 0000000..3a18387
--- /dev/null
+++ b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/bucket_data.sh
@@ -0,0 +1,7 @@
+BUCKET_NAME="tt_ttt"
+echo $BUCKET_NAME
+REGION=us-central1
+gsutil mb -l $REGION gs://$BUCKET_NAME/
+
+## to copy the data folder to your Cloud Storage bucket.
+gsutil cp -r data gs://$BUCKET_NAME/data
\ No newline at end of file
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/exported_model/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/exported_model/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/logs/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/logs/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/logs/dumps/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/logs/dumps/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models_original/1st_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models_original/1st_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models_original/1st_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/best_model_main.index
similarity index 100%
rename from logs/primary_models_original/1st_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/best_model_main.index
diff --git a/logs/primary_models_original/1st_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/best_model_main.meta
similarity index 100%
rename from logs/primary_models_original/1st_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/best_model_main.meta
diff --git a/logs/models/main/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/checkpoint
similarity index 100%
rename from logs/models/main/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/1st/checkpoint
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models/2nd_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models/2nd_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models/2nd_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/best_model_main.index
similarity index 100%
rename from logs/primary_models/2nd_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/best_model_main.index
diff --git a/logs/primary_models/2nd_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/best_model_main.meta
similarity index 100%
rename from logs/primary_models/2nd_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/best_model_main.meta
diff --git a/logs/primary_models/2nd_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/checkpoint
similarity index 100%
rename from logs/primary_models/2nd_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/2nd/checkpoint
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models_original/3rd_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models_original/3rd_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models_original/3rd_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/best_model_main.index
similarity index 100%
rename from logs/primary_models_original/3rd_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/best_model_main.index
diff --git a/logs/primary_models_original/3rd_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/best_model_main.meta
similarity index 100%
rename from logs/primary_models_original/3rd_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/best_model_main.meta
diff --git a/logs/primary_models_original/3rd_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/checkpoint
similarity index 100%
rename from logs/primary_models_original/3rd_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/checkpoint
diff --git a/logs/primary_models_original/3rd_good/hyper_params_main.json b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/hyper_params_main.json
similarity index 100%
rename from logs/primary_models_original/3rd_good/hyper_params_main.json
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/3rd/hyper_params_main.json
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models_original/4th_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models_original/4th_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models_original/4th_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/best_model_main.index
similarity index 100%
rename from logs/primary_models_original/4th_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/best_model_main.index
diff --git a/logs/primary_models_original/4th_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/best_model_main.meta
similarity index 100%
rename from logs/primary_models_original/4th_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/best_model_main.meta
diff --git a/logs/primary_models/8th_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/checkpoint
similarity index 100%
rename from logs/primary_models/8th_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/checkpoint
diff --git a/logs/primary_models_original/4th_good/hyper_params_main.json b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/hyper_params_main.json
similarity index 100%
rename from logs/primary_models_original/4th_good/hyper_params_main.json
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/4th/hyper_params_main.json
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models_original/5th_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models_original/5th_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models_original/5th_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/best_model_main.index
similarity index 100%
rename from logs/primary_models_original/5th_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/best_model_main.index
diff --git a/logs/primary_models_original/5th_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/best_model_main.meta
similarity index 100%
rename from logs/primary_models_original/5th_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/best_model_main.meta
diff --git a/logs/primary_models_original/1st_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/checkpoint
similarity index 100%
rename from logs/primary_models_original/1st_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/checkpoint
diff --git a/logs/primary_models_original/5th_good/hyper_params_main.json b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/hyper_params_main.json
similarity index 100%
rename from logs/primary_models_original/5th_good/hyper_params_main.json
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/5th/hyper_params_main.json
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models_original/6th_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models_original/6th_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models_original/6th_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/best_model_main.index
similarity index 100%
rename from logs/primary_models_original/6th_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/best_model_main.index
diff --git a/logs/primary_models_original/6th_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/best_model_main.meta
similarity index 100%
rename from logs/primary_models_original/6th_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/best_model_main.meta
diff --git a/logs/primary_models_original/2nd_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/checkpoint
similarity index 100%
rename from logs/primary_models_original/2nd_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/checkpoint
diff --git a/logs/primary_models_original/6th_good/hyper_params_main.json b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/hyper_params_main.json
similarity index 100%
rename from logs/primary_models_original/6th_good/hyper_params_main.json
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/6th/hyper_params_main.json
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/primary_models_original/7th_good/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/primary_models_original/7th_good/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/best_model_main.data-00000-of-00001
diff --git a/logs/primary_models_original/7th_good/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/best_model_main.index
similarity index 100%
rename from logs/primary_models_original/7th_good/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/best_model_main.index
diff --git a/logs/primary_models_original/7th_good/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/best_model_main.meta
similarity index 100%
rename from logs/primary_models_original/7th_good/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/best_model_main.meta
diff --git a/logs/primary_models_original/4th_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/checkpoint
similarity index 100%
rename from logs/primary_models_original/4th_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/checkpoint
diff --git a/logs/primary_models_original/7th_good/hyper_params_main.json b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/hyper_params_main.json
similarity index 100%
rename from logs/primary_models_original/7th_good/hyper_params_main.json
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/7th/hyper_params_main.json
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/logs/models/main/best_model_main.data-00000-of-00001 b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/best_model_main.data-00000-of-00001
similarity index 100%
rename from logs/models/main/best_model_main.data-00000-of-00001
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/best_model_main.data-00000-of-00001
diff --git a/logs/models/main/best_model_main.index b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/best_model_main.index
similarity index 100%
rename from logs/models/main/best_model_main.index
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/best_model_main.index
diff --git a/logs/models/main/best_model_main.meta b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/best_model_main.meta
similarity index 100%
rename from logs/models/main/best_model_main.meta
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/best_model_main.meta
diff --git a/logs/primary_models_original/5th_good/checkpoint b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/checkpoint
similarity index 100%
rename from logs/primary_models_original/5th_good/checkpoint
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/checkpoint
diff --git a/logs/models/main/hyper_params_main.json b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/hyper_params_main.json
similarity index 100%
rename from logs/models/main/hyper_params_main.json
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/8th/hyper_params_main.json
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/primary_models/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/temporary_models/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/misc/temporary_models/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/setup.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/setup.py
new file mode 100644
index 0000000..3b82eee
--- /dev/null
+++ b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/setup.py
@@ -0,0 +1,24 @@
+from setuptools import find_packages
+from setuptools import setup
+
+REQUIRED_PACKAGES = ['argparse',
+                     'tensorflow==1.10.0',
+                     'glob',
+                     'os',
+                     'sklearn==1.19.2',
+                     'numpy==1.14.5',
+                     'pandas==0.23.4',
+                     'MultiColProcessor',
+                     'pickle',
+                     'json',
+                     'collections',
+                     'multiprocessing']
+
+setup(
+    name='deepGauge_custom_estimator',
+    version='0.1',
+    install_requires=REQUIRED_PACKAGES,
+    packages=find_packages(),
+    include_package_data=True,
+    description=''
+)
\ No newline at end of file
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/train.sh b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/train.sh
new file mode 100644
index 0000000..91e4842
--- /dev/null
+++ b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/train.sh
@@ -0,0 +1,28 @@
+gcloud ml-engine jobs submit training "$JOB_ID" \
+  --stream-logs \
+  --module-name trainer.task \
+  --package-path trainer \
+  --staging-bucket "$BUCKET" \
+  --region us-central1 \
+  --runtime-version=1.4 \
+  -- \
+  --output_path "${GCS_PATH}/training" \
+  --eval_data_paths "${GCS_PATH}/preproc/eval*" \
+  --train_data_paths "${GCS_PATH}/preproc/train*"
+
+
+##
+REGION=us-central1
+JOB_NAME=deep_gauge_1
+BUCKET=gs://deep_gauge
+PACKAGE_PATH=CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer
+
+
+gcloud ml-engine jobs submit training $JOB_NAME \
+    --runtime-version 1.8 \
+    --module-name trainer.task \
+    --package-path "$PACKAGE_PATH" \
+    --staging-bucket "$BUCKET" \
+    --region $REGION \
+    -- \
+    --verbosity DEBUG
\ No newline at end of file
diff --git a/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/__init__.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/modules/ensemble_modules/trainer_from_storage/input.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/input.py
similarity index 59%
rename from modules/ensemble_modules/trainer_from_storage/input.py
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/input.py
index 749ea52..fe04bf9 100644
--- a/modules/ensemble_modules/trainer_from_storage/input.py
+++ b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/input.py
@@ -8,6 +8,7 @@
 from collections import OrderedDict
 import tensorflow as tf
 import multiprocessing
+import os
 
 
 class Dataset():
@@ -16,7 +17,7 @@ def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
         y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
         MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
         MultiColumnOneHotEncoder.fit(data=y_true_cat)
-        with open(bin_path + 'MultiColProcessor.pkl', 'wb') as pklFile:
+        with open(os.path.join(bin_path, 'MultiColProcessor.pkl'), 'wb') as pklFile:
             pickle.dump(MultiColumnOneHotEncoder, pklFile)
         return
 
@@ -78,25 +79,26 @@ def split_data_files(ver_ratio, path, random_state, is_trial, bin_path):
 
     @staticmethod
     def parse_function(filename, label):
+        filename = filename['file']
         image_string = tf.read_file(filename)
         image = tf.image.decode_jpeg(image_string, channels=3)
-        image = tf.expand_dims(image, 0)
-        image = tf.image.resize_bilinear(image, [224, 224])
-        image = tf.squeeze(image, 0)
+        image = tf.image.resize_images(image, [224, 224], method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
         image = tf.image.convert_image_dtype(image, tf.float32)
         return {'X': image}, label
 
     @classmethod
-    def prep_train_input_function(cls, ver_ratio, container_path,
-                                  prefetch_buffer_size,
-                                  color_mode='grayscale',
-                                  epochs_between_evals=None,
-                                  random_state=19,
-                                  is_trial=False,
-                                  bin_path=None,
-                                  multi_threading=True,
-                                  train_batch_size=None):
-        X_train_path_names, _, y_train, _ = \
+    def prep_input_function(cls, ver_ratio, container_path,
+                            prefetch_buffer_size=None,
+                            color_mode='grayscale',
+                            epochs_between_evals=None,
+                            random_state=19,
+                            is_trial=False,
+                            bin_path=None,
+                            multi_threading=True,
+                            train_batch_size=None,
+                            mode=None):
+
+        X_train_path_names, X_test_path_names, y_train, y_test = \
             cls.split_data_files(ver_ratio=ver_ratio,
                                  path=container_path,
                                  random_state=random_state,
@@ -111,56 +113,35 @@ def prep_train_input_function(cls, ver_ratio, container_path,
         y_train = MultiColumnOneHotEncoder.transform(data=y_train_cat)
         y_train = y_train.values
         ##
+        y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
+        y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
+        y_test = y_test.values
+        ##
         num_threads = multiprocessing.cpu_count() if multi_threading else 1
 
-        X_train_path_names_tf = tf.constant(X_train_path_names)
-        y_train_tf = tf.constant(y_train)
+        if mode == tf.estimator.ModeKeys.TRAIN:
 
-        dataset_train = tf.data.Dataset.from_tensor_slices((X_train_path_names_tf, y_train_tf))
+            dataset_train = tf.data.Dataset.from_tensor_slices(({'file': X_train_path_names}, y_train))
 
-        ##
-        dataset_train = dataset_train.apply(
-            tf.contrib.data.map_and_batch(
-                map_func=cls.parse_function,
-                batch_size=train_batch_size,
-                num_parallel_batches=num_threads))
-
-        dataset_train = dataset_train.\
-            cache().shuffle(len(X_train_path_names) + 10).repeat(epochs_between_evals)#.batch(batch_size)
-        #
-        dataset_train = dataset_train.prefetch(buffer_size=prefetch_buffer_size)
+            ##
+            dataset_train = dataset_train.apply(
+                tf.contrib.data.map_and_batch(
+                    map_func=cls.parse_function,
+                    batch_size=train_batch_size,
+                    num_parallel_batches=num_threads))
 
-        return dataset_train
+            dataset_train = dataset_train. \
+                cache().shuffle(len(X_train_path_names) + 10).repeat(epochs_between_evals)  # .batch(batch_size)
+            #
+            dataset_final = dataset_train.prefetch(buffer_size=prefetch_buffer_size)
 
-    @classmethod
-    def prep_eval_input_function(cls, ver_ratio, container_path,
-                                 random_state=19,
-                                 is_trial=False,
-                                 bin_path=None,
-                                 multi_threading=True):
-        _, X_test_path_names, _, y_test = \
-            cls.split_data_files(ver_ratio=ver_ratio,
-                                 path=container_path,
-                                 random_state=random_state,
-                                 is_trial=is_trial,
-                                 bin_path=bin_path)
-        ##
-        with open(bin_path + '/MultiColProcessor.pkl', 'rb') as handle:
-            MultiColumnOneHotEncoder = pickle.load(handle)
+        elif mode == tf.estimator.ModeKeys.EVAL:
 
-        y_test_cat = pd.DataFrame(data=y_test, columns=['y_true'], dtype='category')
-        y_test = MultiColumnOneHotEncoder.transform(data=y_test_cat)
-        y_test = y_test.values
-        ##
-        X_test_path_names_tf = tf.constant(X_test_path_names)
-        y_test_tf = tf.constant(y_test)
-
-        num_threads = multiprocessing.cpu_count() if multi_threading else 1
-        dataset_test = tf.data.Dataset.from_tensor_slices((X_test_path_names_tf, y_test_tf))
+            dataset_test = tf.data.Dataset.from_tensor_slices(({'file': X_test_path_names}, y_test))
 
-        dataset_test = dataset_test.map(map_func=cls.parse_function,
-                                        num_parallel_calls=num_threads)
+            dataset_test = dataset_test.map(map_func=cls.parse_function,
+                                            num_parallel_calls=num_threads)
 
-        dataset_test = dataset_test.batch(y_test.shape[0])
+            dataset_final = dataset_test.batch(y_test.shape[0])
 
-        return dataset_test
+        return dataset_final
diff --git a/modules/ensemble_modules/trainer_from_storage/model.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/model.py
similarity index 100%
rename from modules/ensemble_modules/trainer_from_storage/model.py
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/model.py
diff --git a/modules/ensemble_modules/trainer_from_storage/task.py b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/task.py
similarity index 90%
rename from modules/ensemble_modules/trainer_from_storage/task.py
rename to CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/task.py
index f5e3f27..e0e9f5b 100644
--- a/modules/ensemble_modules/trainer_from_storage/task.py
+++ b/CustomEstimator/modules/ensemble_modules/trainer_from_storage/trainer/task.py
@@ -1,5 +1,7 @@
 import argparse
 import tensorflow as tf
+import glob
+import os
 
 ## on
 from trainer_from_storage.input import Dataset
@@ -31,7 +33,7 @@ def initialise_hyper_params(parser):
                         default='False',
                         type=str)
     parser.add_argument('--batch_size',
-                        default=2,
+                        default=5,
                         type=int)
     parser.add_argument('--train_epochs',
                         default=1,
@@ -112,6 +114,8 @@ def main(argv):
                                        images_shape=images_shape,
                                        save_path=ensemble_architecture_path)
 
+    print('The ensemble architecture was made and is ready to be used.')
+
     classifier = tf.estimator.Estimator(
         model_fn=model.model_fn,
         params={
@@ -130,7 +134,7 @@ def main(argv):
     ##
     for i in range(train_epochs // epochs_between_evals):
         print('epoch {} .........'.format(i * epochs_between_evals + 1))
-        classifier.train(input_fn=lambda: Dataset.prep_train_input_function(
+        classifier.train(input_fn=lambda: Dataset.prep_input_function(
             ver_ratio=0.2,
             container_path=path_to_images,
             prefetch_buffer_size=prefetch_buffer_size,
@@ -139,20 +143,22 @@ def main(argv):
             is_trial=is_trial,
             bin_path=bin_path,
             multi_threading=image_processing_multi_threading,
-            train_batch_size=batch_size))
+            train_batch_size=batch_size,
+            mode=tf.estimator.ModeKeys.TRAIN))
 
-        eval_result = classifier.evaluate(input_fn=lambda: Dataset.prep_eval_input_function(
+        eval_result = classifier.evaluate(input_fn=lambda: Dataset.prep_input_function(
             ver_ratio=0.2,
             container_path=path_to_images,
             random_state=19,
             is_trial=is_trial,
             bin_path=bin_path,
-            multi_threading=image_processing_multi_threading))
+            multi_threading=image_processing_multi_threading,
+            mode=tf.estimator.ModeKeys.EVAL))
         print('')
         print('')
         print('current validation dataset accuracy is: {}'.format(eval_result['accuracy']))
         print('current highest validation dataset accuracy is: {}'.format(model_criteria))
-        if eval_result[metric] > model_criteria:
+        if eval_result[metric] >= model_criteria:
             model_criteria = eval_result[metric].copy()
             print('current highest validation dataset accuracy updated to: {}'.format(model_criteria))
             print('')
@@ -163,6 +169,12 @@ def main(argv):
         print('')
         print('')
 
+    ## to delete the ensemble graph created for the custom estimator
+    files = glob.glob(os.path.join(ensemble_architecture_path, '*'))
+    for f in files:
+        if 'ensemble_architecture_' in f:
+            os.remove(f)
+
 ##
 args_parser = argparse.ArgumentParser()
 HYPER_PARAMS = initialise_hyper_params(args_parser)
diff --git a/modules/ensemble_modules/trainer/LoadImg.py b/CustomEstimator/modules/primary_models_modules/LoadImg.py
similarity index 79%
rename from modules/ensemble_modules/trainer/LoadImg.py
rename to CustomEstimator/modules/primary_models_modules/LoadImg.py
index b7bd829..09a848c 100644
--- a/modules/ensemble_modules/trainer/LoadImg.py
+++ b/CustomEstimator/modules/primary_models_modules/LoadImg.py
@@ -7,6 +7,7 @@
 import pickle
 import json
 from collections import OrderedDict
+import os
 
 
 class Dataset(object):
@@ -18,7 +19,7 @@ def dump_pkl_MultiColProcessor(gauge_categories, bin_path):
         y_true_cat = pd.DataFrame(data=gauge_categories, columns=['y_true'], dtype='category')
         MultiColumnOneHotEncoder = mcp.MultiColomnOneHotEncoder()
         MultiColumnOneHotEncoder.fit(data=y_true_cat)
-        with open(bin_path+'MultiColProcessor.pkl', 'wb') as pklFile:
+        with open(os.path.join(bin_path, 'MultiColProcessor.pkl'), 'wb') as pklFile:
             pickle.dump(MultiColumnOneHotEncoder, pklFile)
         return
 
@@ -40,7 +41,7 @@ def dump_json_category_mapper(data, bin_path):
 
         Dataset.category_mapper = category_mapper
 
-        with open(bin_path+'category_mapper.json', 'w') as outfile:
+        with open(os.path.join(bin_path, 'category_mapper.json'), 'w') as outfile:
             json.dump(category_mapper, outfile)
         return
 
@@ -141,7 +142,7 @@ def prep_datasets(cls, ver_ratio, container_path, final_img_width, final_img_hei
                                      color_mode=color_mode)
 
         ## OneHot encoding of y_train and y_test
-        with open('dumps/MultiColProcessor.pkl', 'rb') as handle:
+        with open(os.path.join(bin_path, 'MultiColProcessor.pkl'), 'rb') as handle:
             MultiColumnOneHotEncoder = pickle.load(handle)
 
         y_train_cat = pd.DataFrame(data=y_train, columns=['y_true'], dtype='category')
@@ -154,30 +155,4 @@ def prep_datasets(cls, ver_ratio, container_path, final_img_width, final_img_hei
 
         print("The image pre-processing is complete.")
 
-        return X_train, X_test, y_train.values, y_test.values, cls_indices
-
-    # @classmethod
-    # def prep_datasets_for_ensemble(cls, ver_ratio, container_path, final_img_width, final_img_height,
-    #                   color_mode='grayscale',
-    #                   random_state=19, is_trial=False, bin_path='dump/'):
-    #     ##
-    #     X_train_path_names, X_test_path_names, y_train, y_test = \
-    #         cls.split_data_files(ver_ratio=ver_ratio,
-    #                              path=container_path,
-    #                              random_state=random_state,
-    #                              is_trial=is_trial,
-    #                              bin_path=bin_path)
-    #
-    #     X_train = cls.paths_to_tensor(imgs_path=X_train_path_names,
-    #                                   img_size_x=final_img_width,
-    #                                   img_size_y=final_img_height,
-    #                                   color_mode=color_mode)
-    #
-    #     X_test = cls.paths_to_tensor(imgs_path=X_test_path_names,
-    #                                  img_size_x=final_img_width,
-    #                                  img_size_y=final_img_height,
-    #                                  color_mode=color_mode)
-    #
-    #     print("The image pre-processing for ensemble is complete.")
-    #
-    #     return X_train, X_test, y_train, y_test
+        return X_train, X_test, y_train.values, y_test.values, cls_indices
\ No newline at end of file
diff --git a/modules/NeuralNet.py b/CustomEstimator/modules/primary_models_modules/NeuralNet.py
similarity index 100%
rename from modules/NeuralNet.py
rename to CustomEstimator/modules/primary_models_modules/NeuralNet.py
diff --git a/modules/NewLayers.py b/CustomEstimator/modules/primary_models_modules/NewLayers.py
similarity index 100%
rename from modules/NewLayers.py
rename to CustomEstimator/modules/primary_models_modules/NewLayers.py
diff --git a/modules/OptimizeAndLog.py b/CustomEstimator/modules/primary_models_modules/OptimizeAndLog.py
similarity index 100%
rename from modules/OptimizeAndLog.py
rename to CustomEstimator/modules/primary_models_modules/OptimizeAndLog.py
diff --git a/modules/PerfMeasures.py b/CustomEstimator/modules/primary_models_modules/PerfMeasures.py
similarity index 100%
rename from modules/PerfMeasures.py
rename to CustomEstimator/modules/primary_models_modules/PerfMeasures.py
diff --git a/CustomEstimator/modules/primary_models_modules/__init__.py b/CustomEstimator/modules/primary_models_modules/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/modules/prediction_modules/LoadImgPred.py b/CustomEstimator/modules/primary_models_modules/prediction_modules/LoadImgPred.py
similarity index 100%
rename from modules/prediction_modules/LoadImgPred.py
rename to CustomEstimator/modules/primary_models_modules/prediction_modules/LoadImgPred.py
diff --git a/modules/prediction_modules/PILimages.py b/CustomEstimator/modules/primary_models_modules/prediction_modules/PILimages.py
similarity index 100%
rename from modules/prediction_modules/PILimages.py
rename to CustomEstimator/modules/primary_models_modules/prediction_modules/PILimages.py
diff --git a/modules/prediction_modules/PerfMeasuresPred.py b/CustomEstimator/modules/primary_models_modules/prediction_modules/PerfMeasuresPred.py
similarity index 100%
rename from modules/prediction_modules/PerfMeasuresPred.py
rename to CustomEstimator/modules/primary_models_modules/prediction_modules/PerfMeasuresPred.py
diff --git a/modules/prediction_modules/Prediction.py b/CustomEstimator/modules/primary_models_modules/prediction_modules/Prediction.py
similarity index 100%
rename from modules/prediction_modules/Prediction.py
rename to CustomEstimator/modules/primary_models_modules/prediction_modules/Prediction.py
diff --git a/CustomEstimator/modules/primary_models_modules/prediction_modules/__init__.py b/CustomEstimator/modules/primary_models_modules/prediction_modules/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/performance_logs/pandas_final_result.csv b/CustomEstimator/performance_logs/pandas_final_result.csv
similarity index 100%
rename from performance_logs/pandas_final_result.csv
rename to CustomEstimator/performance_logs/pandas_final_result.csv
diff --git a/prediction_batch.py b/CustomEstimator/prediction_batch.py
similarity index 100%
rename from prediction_batch.py
rename to CustomEstimator/prediction_batch.py
diff --git a/prediction_online.py b/CustomEstimator/prediction_online.py
similarity index 100%
rename from prediction_online.py
rename to CustomEstimator/prediction_online.py
diff --git a/requirements.txt b/CustomEstimator/requirements.txt
similarity index 100%
rename from requirements.txt
rename to CustomEstimator/requirements.txt
diff --git a/train.py b/CustomEstimator/train.py
similarity index 96%
rename from train.py
rename to CustomEstimator/train.py
index e5ddf31..623652f 100644
--- a/train.py
+++ b/CustomEstimator/train.py
@@ -1,7 +1,8 @@
-from modules import LoadImg
-from modules import OptimizeAndLog
 import importlib
 
+from CustomEstimator.modules.primary_models_modules import LoadImg
+from modules import OptimizeAndLog
+
 ## load data
 # The color_mode is either 'rgb' or 'grayscale' (default).
 X_train, X_test, y_train, y_test, cls_indices = LoadImg.Dataset.prep_datasets(
diff --git a/train_ensemble.py b/CustomEstimator/train_ensemble.py
similarity index 92%
rename from train_ensemble.py
rename to CustomEstimator/train_ensemble.py
index 244a2eb..d7c2dd6 100644
--- a/train_ensemble.py
+++ b/CustomEstimator/train_ensemble.py
@@ -1,7 +1,8 @@
-from modules.ensemble_modules import obsolete_EnsenmbleData
-from modules import OptimizeAndLog
 import importlib
 
+from CustomEstimator.modules.primary_models_modules import OptimizeAndLog
+from modules.ensemble_modules import obsolete_EnsenmbleData
+
 ## load data
 X_train, X_test, y_train, y_test, cls_indices = \
     obsolete_EnsenmbleData.load_ensemble_data(data_path='./data/ensembleDatasets/pre_ensembleData_final.pkl')
diff --git a/trial.py b/CustomEstimator/trial.py
similarity index 93%
rename from trial.py
rename to CustomEstimator/trial.py
index e0fcbb4..1a2d6e1 100644
--- a/trial.py
+++ b/CustomEstimator/trial.py
@@ -1,8 +1,9 @@
 import os
 import tensorflow as tf
-from modules import LoadImg
 from tensorflow.python.framework import meta_graph
 
+from CustomEstimator.modules.primary_models_modules import LoadImg
+
 graph_model = tf.Graph()
 with graph_model.as_default():
     ##################################
@@ -259,3 +260,30 @@
     multi_threading='False',
     train_batch_size=4)
 
+
+
+#######################
+import tensorflow as tf
+import cv2
+from PIL import Image
+import numpy as np
+import matplotlib.pyplot as plt
+
+image_string = tf.read_file('./modules/ensemble_modules/trainer_from_storage/data/ImageEveryUnit/psi_0/gauge_scale_0.jpg')
+image = tf.image.decode_jpeg(image_string, channels=3)
+# image = tf.expand_dims(image, 0)
+image = tf.image.resize_images(image, [224, 224], method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
+# image = tf.image.resize_images(image, [224, 224])
+# image = tf.squeeze(image, 0)
+image = tf.image.convert_image_dtype(image, tf.float32)
+
+with tf.Session() as sess:
+    im = sess.run(image)
+
+im.shape
+
+# cv2.imshow("output", im)
+plt.imshow(im)
+
+img = Image.fromarray(im, 'RGB')
+img.show()
diff --git a/FlaskApp_DeepGauge/Prediction.py b/FlaskApp_DeepGauge/Prediction.py
old mode 100755
new mode 100644
diff --git a/cloud-functions/background/main.py b/cloud-functions/background/main.py
old mode 100755
new mode 100644
diff --git a/cloud-functions/background/requirements.txt b/cloud-functions/background/requirements.txt
old mode 100755
new mode 100644
diff --git a/copy_to_bucket.sh b/copy_to_bucket.sh
deleted file mode 100644
index a00e620..0000000
--- a/copy_to_bucket.sh
+++ /dev/null
@@ -1,2 +0,0 @@
-gsutil -m cp -r ./data/ImageEveryUnit/. gs://deep_gauge/data/
-gsutil -m cp -r ./trainer/. gs://deep_gauge
\ No newline at end of file
diff --git a/dumps/MultiColProcessor.pkl b/dumps/MultiColProcessor.pkl
deleted file mode 100644
index 6d20fe7..0000000
Binary files a/dumps/MultiColProcessor.pkl and /dev/null differ
diff --git a/dumps/best_models_info.pkl b/dumps/best_models_info.pkl
deleted file mode 100644
index 5182eb9..0000000
Binary files a/dumps/best_models_info.pkl and /dev/null differ
diff --git a/dumps/category_mapper.json b/dumps/category_mapper.json
deleted file mode 100644
index 7938065..0000000
--- a/dumps/category_mapper.json
+++ /dev/null
@@ -1 +0,0 @@
-{"num_to_cat": {"0": "psi-NAN", "1": "psi_0", "2": "psi_1", "3": "psi_10", "4": "psi_10_5", "5": "psi_11", "6": "psi_11_5", "7": "psi_12", "8": "psi_12_5", "9": "psi_13", "10": "psi_13_5", "11": "psi_14", "12": "psi_14_5", "13": "psi_15", "14": "psi_1_5", "15": "psi_2", "16": "psi_2_5", "17": "psi_3", "18": "psi_3_5", "19": "psi_4", "20": "psi_4_5", "21": "psi_5", "22": "psi_5_5", "23": "psi_6", "24": "psi_6_5", "25": "psi_7", "26": "psi_7_5", "27": "psi_8", "28": "psi_8_5", "29": "psi_9", "30": "psi_9_5"}, "cat_to_num": {"psi-NAN": 0, "psi_0": 1, "psi_1": 2, "psi_10": 3, "psi_10_5": 4, "psi_11": 5, "psi_11_5": 6, "psi_12": 7, "psi_12_5": 8, "psi_13": 9, "psi_13_5": 10, "psi_14": 11, "psi_14_5": 12, "psi_15": 13, "psi_1_5": 14, "psi_2": 15, "psi_2_5": 16, "psi_3": 17, "psi_3_5": 18, "psi_4": 19, "psi_4_5": 20, "psi_5": 21, "psi_5_5": 22, "psi_6": 23, "psi_6_5": 24, "psi_7": 25, "psi_7_5": 26, "psi_8": 27, "psi_8_5": 28, "psi_9": 29, "psi_9_5": 30}, "num_classes": 31}
\ No newline at end of file
diff --git a/dumps/ensemble_models_dims.pkl b/dumps/ensemble_models_dims.pkl
deleted file mode 100644
index 009dae7..0000000
Binary files a/dumps/ensemble_models_dims.pkl and /dev/null differ
diff --git a/ens.sh b/ens.sh
deleted file mode 100644
index 0f51880..0000000
--- a/ens.sh
+++ /dev/null
@@ -1,16 +0,0 @@
-python customEstimator.py --dev=True --retrain_primary_models=False --hidden_units='[100, 200, 300, 500]' --verbosity=DEBUG
-
-
-#######
-gcloud ml-engine local train --module-name trainer_from_storage.task \
-          --package-path /home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage \
-          -- --primary_models_directory=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/primary_models \
-          --ensemble_architecture_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/temporary_models \
-          --path_to_images=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/data/ImageEveryUnit \
-          --bin_path=/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/dumps
-
-
-
-
-
-
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diff --git a/logs/models/psi-NAN/checkpoint b/logs/models/psi-NAN/checkpoint
deleted file mode 100644
index 72cf729..0000000
--- a/logs/models/psi-NAN/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "best_model_psi-NAN"
diff --git a/logs/models/psi-NAN/hyper_params_psi-NAN.json b/logs/models/psi-NAN/hyper_params_psi-NAN.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi-NAN/hyper_params_psi-NAN.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_0/best_model_psi_0.data-00000-of-00001 b/logs/models/psi_0/best_model_psi_0.data-00000-of-00001
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index 6c38e4e..0000000
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diff --git a/logs/models/psi_0/best_model_psi_0.meta b/logs/models/psi_0/best_model_psi_0.meta
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diff --git a/logs/models/psi_0/checkpoint b/logs/models/psi_0/checkpoint
deleted file mode 100644
index 1edff7d..0000000
--- a/logs/models/psi_0/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_0"
diff --git a/logs/models/psi_0/hyper_params_psi_0.json b/logs/models/psi_0/hyper_params_psi_0.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_0/hyper_params_psi_0.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_1/best_model_psi_1.data-00000-of-00001 b/logs/models/psi_1/best_model_psi_1.data-00000-of-00001
deleted file mode 100644
index 2126dfc..0000000
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deleted file mode 100644
index 22ae3af..0000000
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diff --git a/logs/models/psi_1/best_model_psi_1.meta b/logs/models/psi_1/best_model_psi_1.meta
deleted file mode 100644
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diff --git a/logs/models/psi_1/checkpoint b/logs/models/psi_1/checkpoint
deleted file mode 100644
index 79f0dc5..0000000
--- a/logs/models/psi_1/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_1"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "best_model_psi_1"
diff --git a/logs/models/psi_1/hyper_params_psi_1.json b/logs/models/psi_1/hyper_params_psi_1.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_1/hyper_params_psi_1.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_10/best_model_psi_10.data-00000-of-00001 b/logs/models/psi_10/best_model_psi_10.data-00000-of-00001
deleted file mode 100644
index 94ed22a..0000000
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deleted file mode 100644
index e7ed56f..0000000
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diff --git a/logs/models/psi_10/best_model_psi_10.meta b/logs/models/psi_10/best_model_psi_10.meta
deleted file mode 100644
index 5685fbb..0000000
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diff --git a/logs/models/psi_10/checkpoint b/logs/models/psi_10/checkpoint
deleted file mode 100644
index 88c4e82..0000000
--- a/logs/models/psi_10/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "best_model_psi_10"
diff --git a/logs/models/psi_10/hyper_params_psi_10.json b/logs/models/psi_10/hyper_params_psi_10.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_10/hyper_params_psi_10.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_10_5/best_model_psi_10_5.data-00000-of-00001 b/logs/models/psi_10_5/best_model_psi_10_5.data-00000-of-00001
deleted file mode 100644
index eec951d..0000000
Binary files a/logs/models/psi_10_5/best_model_psi_10_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_10_5/best_model_psi_10_5.index b/logs/models/psi_10_5/best_model_psi_10_5.index
deleted file mode 100644
index 45f38b4..0000000
Binary files a/logs/models/psi_10_5/best_model_psi_10_5.index and /dev/null differ
diff --git a/logs/models/psi_10_5/best_model_psi_10_5.meta b/logs/models/psi_10_5/best_model_psi_10_5.meta
deleted file mode 100644
index c73cd54..0000000
Binary files a/logs/models/psi_10_5/best_model_psi_10_5.meta and /dev/null differ
diff --git a/logs/models/psi_10_5/checkpoint b/logs/models/psi_10_5/checkpoint
deleted file mode 100644
index 85dec4b..0000000
--- a/logs/models/psi_10_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "best_model_psi_10_5"
diff --git a/logs/models/psi_10_5/hyper_params_psi_10_5.json b/logs/models/psi_10_5/hyper_params_psi_10_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_10_5/hyper_params_psi_10_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_11/best_model_psi_11.data-00000-of-00001 b/logs/models/psi_11/best_model_psi_11.data-00000-of-00001
deleted file mode 100644
index c5f7319..0000000
Binary files a/logs/models/psi_11/best_model_psi_11.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_11/best_model_psi_11.index b/logs/models/psi_11/best_model_psi_11.index
deleted file mode 100644
index 92ac305..0000000
Binary files a/logs/models/psi_11/best_model_psi_11.index and /dev/null differ
diff --git a/logs/models/psi_11/best_model_psi_11.meta b/logs/models/psi_11/best_model_psi_11.meta
deleted file mode 100644
index 61abfd8..0000000
Binary files a/logs/models/psi_11/best_model_psi_11.meta and /dev/null differ
diff --git a/logs/models/psi_11/checkpoint b/logs/models/psi_11/checkpoint
deleted file mode 100644
index 36e178e..0000000
--- a/logs/models/psi_11/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "best_model_psi_11"
diff --git a/logs/models/psi_11/hyper_params_psi_11.json b/logs/models/psi_11/hyper_params_psi_11.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_11/hyper_params_psi_11.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_11_5/best_model_psi_11_5.data-00000-of-00001 b/logs/models/psi_11_5/best_model_psi_11_5.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_11_5/best_model_psi_11_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_11_5/best_model_psi_11_5.index b/logs/models/psi_11_5/best_model_psi_11_5.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_11_5/best_model_psi_11_5.index and /dev/null differ
diff --git a/logs/models/psi_11_5/best_model_psi_11_5.meta b/logs/models/psi_11_5/best_model_psi_11_5.meta
deleted file mode 100644
index 71a351a..0000000
Binary files a/logs/models/psi_11_5/best_model_psi_11_5.meta and /dev/null differ
diff --git a/logs/models/psi_11_5/checkpoint b/logs/models/psi_11_5/checkpoint
deleted file mode 100644
index 79c6410..0000000
--- a/logs/models/psi_11_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "best_model_psi_11_5"
diff --git a/logs/models/psi_11_5/hyper_params_psi_11_5.json b/logs/models/psi_11_5/hyper_params_psi_11_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_11_5/hyper_params_psi_11_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_12/best_model_psi_12.data-00000-of-00001 b/logs/models/psi_12/best_model_psi_12.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_12/best_model_psi_12.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_12/best_model_psi_12.index b/logs/models/psi_12/best_model_psi_12.index
deleted file mode 100644
index 46fc378..0000000
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diff --git a/logs/models/psi_12/best_model_psi_12.meta b/logs/models/psi_12/best_model_psi_12.meta
deleted file mode 100644
index b03af56..0000000
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diff --git a/logs/models/psi_12/checkpoint b/logs/models/psi_12/checkpoint
deleted file mode 100644
index 6d299b2..0000000
--- a/logs/models/psi_12/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "best_model_psi_12"
diff --git a/logs/models/psi_12/hyper_params_psi_12.json b/logs/models/psi_12/hyper_params_psi_12.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_12/hyper_params_psi_12.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_12_5/best_model_psi_12_5.data-00000-of-00001 b/logs/models/psi_12_5/best_model_psi_12_5.data-00000-of-00001
deleted file mode 100644
index 807a69c..0000000
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diff --git a/logs/models/psi_12_5/best_model_psi_12_5.index b/logs/models/psi_12_5/best_model_psi_12_5.index
deleted file mode 100644
index 07f4bda..0000000
Binary files a/logs/models/psi_12_5/best_model_psi_12_5.index and /dev/null differ
diff --git a/logs/models/psi_12_5/best_model_psi_12_5.meta b/logs/models/psi_12_5/best_model_psi_12_5.meta
deleted file mode 100644
index 2e474b2..0000000
Binary files a/logs/models/psi_12_5/best_model_psi_12_5.meta and /dev/null differ
diff --git a/logs/models/psi_12_5/checkpoint b/logs/models/psi_12_5/checkpoint
deleted file mode 100644
index aaf73f2..0000000
--- a/logs/models/psi_12_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_12_5"
diff --git a/logs/models/psi_12_5/hyper_params_psi_12_5.json b/logs/models/psi_12_5/hyper_params_psi_12_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_12_5/hyper_params_psi_12_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_13/best_model_psi_13.data-00000-of-00001 b/logs/models/psi_13/best_model_psi_13.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_13/best_model_psi_13.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_13/best_model_psi_13.index b/logs/models/psi_13/best_model_psi_13.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_13/best_model_psi_13.index and /dev/null differ
diff --git a/logs/models/psi_13/best_model_psi_13.meta b/logs/models/psi_13/best_model_psi_13.meta
deleted file mode 100644
index bb89c43..0000000
Binary files a/logs/models/psi_13/best_model_psi_13.meta and /dev/null differ
diff --git a/logs/models/psi_13/checkpoint b/logs/models/psi_13/checkpoint
deleted file mode 100644
index 55ed2a0..0000000
--- a/logs/models/psi_13/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_13"
diff --git a/logs/models/psi_13/hyper_params_psi_13.json b/logs/models/psi_13/hyper_params_psi_13.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_13/hyper_params_psi_13.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_13_5/best_model_psi_13_5.data-00000-of-00001 b/logs/models/psi_13_5/best_model_psi_13_5.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_13_5/best_model_psi_13_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_13_5/best_model_psi_13_5.index b/logs/models/psi_13_5/best_model_psi_13_5.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_13_5/best_model_psi_13_5.index and /dev/null differ
diff --git a/logs/models/psi_13_5/best_model_psi_13_5.meta b/logs/models/psi_13_5/best_model_psi_13_5.meta
deleted file mode 100644
index 156e2fe..0000000
Binary files a/logs/models/psi_13_5/best_model_psi_13_5.meta and /dev/null differ
diff --git a/logs/models/psi_13_5/checkpoint b/logs/models/psi_13_5/checkpoint
deleted file mode 100644
index 77cddd7..0000000
--- a/logs/models/psi_13_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "best_model_psi_13_5"
diff --git a/logs/models/psi_13_5/hyper_params_psi_13_5.json b/logs/models/psi_13_5/hyper_params_psi_13_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_13_5/hyper_params_psi_13_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_14/best_model_psi_14.data-00000-of-00001 b/logs/models/psi_14/best_model_psi_14.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_14/best_model_psi_14.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_14/best_model_psi_14.index b/logs/models/psi_14/best_model_psi_14.index
deleted file mode 100644
index 46fc378..0000000
Binary files a/logs/models/psi_14/best_model_psi_14.index and /dev/null differ
diff --git a/logs/models/psi_14/best_model_psi_14.meta b/logs/models/psi_14/best_model_psi_14.meta
deleted file mode 100644
index e8e01d1..0000000
Binary files a/logs/models/psi_14/best_model_psi_14.meta and /dev/null differ
diff --git a/logs/models/psi_14/checkpoint b/logs/models/psi_14/checkpoint
deleted file mode 100644
index e1f89b8..0000000
--- a/logs/models/psi_14/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "best_model_psi_14"
diff --git a/logs/models/psi_14/hyper_params_psi_14.json b/logs/models/psi_14/hyper_params_psi_14.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_14/hyper_params_psi_14.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_14_5/best_model_psi_14_5.data-00000-of-00001 b/logs/models/psi_14_5/best_model_psi_14_5.data-00000-of-00001
deleted file mode 100644
index c5f7319..0000000
Binary files a/logs/models/psi_14_5/best_model_psi_14_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_14_5/best_model_psi_14_5.index b/logs/models/psi_14_5/best_model_psi_14_5.index
deleted file mode 100644
index 92ac305..0000000
Binary files a/logs/models/psi_14_5/best_model_psi_14_5.index and /dev/null differ
diff --git a/logs/models/psi_14_5/best_model_psi_14_5.meta b/logs/models/psi_14_5/best_model_psi_14_5.meta
deleted file mode 100644
index abfb54d..0000000
Binary files a/logs/models/psi_14_5/best_model_psi_14_5.meta and /dev/null differ
diff --git a/logs/models/psi_14_5/checkpoint b/logs/models/psi_14_5/checkpoint
deleted file mode 100644
index efe01c3..0000000
--- a/logs/models/psi_14_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "best_model_psi_14_5"
diff --git a/logs/models/psi_14_5/hyper_params_psi_14_5.json b/logs/models/psi_14_5/hyper_params_psi_14_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_14_5/hyper_params_psi_14_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_15/best_model_psi_15.data-00000-of-00001 b/logs/models/psi_15/best_model_psi_15.data-00000-of-00001
deleted file mode 100644
index c5f7319..0000000
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diff --git a/logs/models/psi_15/best_model_psi_15.index b/logs/models/psi_15/best_model_psi_15.index
deleted file mode 100644
index 92ac305..0000000
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diff --git a/logs/models/psi_15/best_model_psi_15.meta b/logs/models/psi_15/best_model_psi_15.meta
deleted file mode 100644
index 0c1dfb6..0000000
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diff --git a/logs/models/psi_15/checkpoint b/logs/models/psi_15/checkpoint
deleted file mode 100644
index 7a3b829..0000000
--- a/logs/models/psi_15/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_15"
diff --git a/logs/models/psi_15/hyper_params_psi_15.json b/logs/models/psi_15/hyper_params_psi_15.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_15/hyper_params_psi_15.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_1_5/best_model_psi_1_5.data-00000-of-00001 b/logs/models/psi_1_5/best_model_psi_1_5.data-00000-of-00001
deleted file mode 100644
index 9c1d70f..0000000
Binary files a/logs/models/psi_1_5/best_model_psi_1_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_1_5/best_model_psi_1_5.index b/logs/models/psi_1_5/best_model_psi_1_5.index
deleted file mode 100644
index eca0f59..0000000
Binary files a/logs/models/psi_1_5/best_model_psi_1_5.index and /dev/null differ
diff --git a/logs/models/psi_1_5/best_model_psi_1_5.meta b/logs/models/psi_1_5/best_model_psi_1_5.meta
deleted file mode 100644
index 9670103..0000000
Binary files a/logs/models/psi_1_5/best_model_psi_1_5.meta and /dev/null differ
diff --git a/logs/models/psi_1_5/checkpoint b/logs/models/psi_1_5/checkpoint
deleted file mode 100644
index 8c39492..0000000
--- a/logs/models/psi_1_5/checkpoint
+++ /dev/null
@@ -1,16 +0,0 @@
-model_checkpoint_path: "best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "best_model_psi_1_5"
diff --git a/logs/models/psi_1_5/hyper_params_psi_1_5.json b/logs/models/psi_1_5/hyper_params_psi_1_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_1_5/hyper_params_psi_1_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_2/best_model_psi_2.data-00000-of-00001 b/logs/models/psi_2/best_model_psi_2.data-00000-of-00001
deleted file mode 100644
index 6c38e4e..0000000
Binary files a/logs/models/psi_2/best_model_psi_2.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_2/best_model_psi_2.index b/logs/models/psi_2/best_model_psi_2.index
deleted file mode 100644
index da707b5..0000000
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diff --git a/logs/models/psi_2/best_model_psi_2.meta b/logs/models/psi_2/best_model_psi_2.meta
deleted file mode 100644
index d6050d4..0000000
Binary files a/logs/models/psi_2/best_model_psi_2.meta and /dev/null differ
diff --git a/logs/models/psi_2/checkpoint b/logs/models/psi_2/checkpoint
deleted file mode 100644
index 5f4ec62..0000000
--- a/logs/models/psi_2/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "best_model_psi_2"
diff --git a/logs/models/psi_2/hyper_params_psi_2.json b/logs/models/psi_2/hyper_params_psi_2.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_2/hyper_params_psi_2.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_2_5/best_model_psi_2_5.data-00000-of-00001 b/logs/models/psi_2_5/best_model_psi_2_5.data-00000-of-00001
deleted file mode 100644
index debcdc9..0000000
Binary files a/logs/models/psi_2_5/best_model_psi_2_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_2_5/best_model_psi_2_5.index b/logs/models/psi_2_5/best_model_psi_2_5.index
deleted file mode 100644
index bf883de..0000000
Binary files a/logs/models/psi_2_5/best_model_psi_2_5.index and /dev/null differ
diff --git a/logs/models/psi_2_5/best_model_psi_2_5.meta b/logs/models/psi_2_5/best_model_psi_2_5.meta
deleted file mode 100644
index d4bdf6b..0000000
Binary files a/logs/models/psi_2_5/best_model_psi_2_5.meta and /dev/null differ
diff --git a/logs/models/psi_2_5/checkpoint b/logs/models/psi_2_5/checkpoint
deleted file mode 100644
index be80a7b..0000000
--- a/logs/models/psi_2_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "best_model_psi_2_5"
diff --git a/logs/models/psi_2_5/hyper_params_psi_2_5.json b/logs/models/psi_2_5/hyper_params_psi_2_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_2_5/hyper_params_psi_2_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_3/best_model_psi_3.data-00000-of-00001 b/logs/models/psi_3/best_model_psi_3.data-00000-of-00001
deleted file mode 100644
index 347357e..0000000
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diff --git a/logs/models/psi_3/best_model_psi_3.index b/logs/models/psi_3/best_model_psi_3.index
deleted file mode 100644
index 155e072..0000000
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diff --git a/logs/models/psi_3/best_model_psi_3.meta b/logs/models/psi_3/best_model_psi_3.meta
deleted file mode 100644
index 989bd4a..0000000
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diff --git a/logs/models/psi_3/checkpoint b/logs/models/psi_3/checkpoint
deleted file mode 100644
index 8b7b6ab..0000000
--- a/logs/models/psi_3/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "best_model_psi_3"
diff --git a/logs/models/psi_3/hyper_params_psi_3.json b/logs/models/psi_3/hyper_params_psi_3.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_3/hyper_params_psi_3.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_3_5/best_model_psi_3_5.data-00000-of-00001 b/logs/models/psi_3_5/best_model_psi_3_5.data-00000-of-00001
deleted file mode 100644
index 94ed22a..0000000
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diff --git a/logs/models/psi_3_5/best_model_psi_3_5.index b/logs/models/psi_3_5/best_model_psi_3_5.index
deleted file mode 100644
index e7ed56f..0000000
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diff --git a/logs/models/psi_3_5/best_model_psi_3_5.meta b/logs/models/psi_3_5/best_model_psi_3_5.meta
deleted file mode 100644
index 46bd44a..0000000
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diff --git a/logs/models/psi_3_5/checkpoint b/logs/models/psi_3_5/checkpoint
deleted file mode 100644
index e63f29a..0000000
--- a/logs/models/psi_3_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "best_model_psi_3_5"
diff --git a/logs/models/psi_3_5/hyper_params_psi_3_5.json b/logs/models/psi_3_5/hyper_params_psi_3_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_3_5/hyper_params_psi_3_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_4/best_model_psi_4.data-00000-of-00001 b/logs/models/psi_4/best_model_psi_4.data-00000-of-00001
deleted file mode 100644
index 1320279..0000000
Binary files a/logs/models/psi_4/best_model_psi_4.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_4/best_model_psi_4.index b/logs/models/psi_4/best_model_psi_4.index
deleted file mode 100644
index f24952d..0000000
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diff --git a/logs/models/psi_4/best_model_psi_4.meta b/logs/models/psi_4/best_model_psi_4.meta
deleted file mode 100644
index 0e93b88..0000000
Binary files a/logs/models/psi_4/best_model_psi_4.meta and /dev/null differ
diff --git a/logs/models/psi_4/checkpoint b/logs/models/psi_4/checkpoint
deleted file mode 100644
index 02c97fb..0000000
--- a/logs/models/psi_4/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "best_model_psi_4"
diff --git a/logs/models/psi_4/hyper_params_psi_4.json b/logs/models/psi_4/hyper_params_psi_4.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_4/hyper_params_psi_4.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_4_5/best_model_psi_4_5.data-00000-of-00001 b/logs/models/psi_4_5/best_model_psi_4_5.data-00000-of-00001
deleted file mode 100644
index 807a69c..0000000
Binary files a/logs/models/psi_4_5/best_model_psi_4_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_4_5/best_model_psi_4_5.index b/logs/models/psi_4_5/best_model_psi_4_5.index
deleted file mode 100644
index 07f4bda..0000000
Binary files a/logs/models/psi_4_5/best_model_psi_4_5.index and /dev/null differ
diff --git a/logs/models/psi_4_5/best_model_psi_4_5.meta b/logs/models/psi_4_5/best_model_psi_4_5.meta
deleted file mode 100644
index 08f0668..0000000
Binary files a/logs/models/psi_4_5/best_model_psi_4_5.meta and /dev/null differ
diff --git a/logs/models/psi_4_5/checkpoint b/logs/models/psi_4_5/checkpoint
deleted file mode 100644
index 02ac17f..0000000
--- a/logs/models/psi_4_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "best_model_psi_4_5"
diff --git a/logs/models/psi_4_5/hyper_params_psi_4_5.json b/logs/models/psi_4_5/hyper_params_psi_4_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_4_5/hyper_params_psi_4_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_5/best_model_psi_5.data-00000-of-00001 b/logs/models/psi_5/best_model_psi_5.data-00000-of-00001
deleted file mode 100644
index 2642dc4..0000000
Binary files a/logs/models/psi_5/best_model_psi_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_5/best_model_psi_5.index b/logs/models/psi_5/best_model_psi_5.index
deleted file mode 100644
index 3309ded..0000000
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diff --git a/logs/models/psi_5/best_model_psi_5.meta b/logs/models/psi_5/best_model_psi_5.meta
deleted file mode 100644
index 1edc74a..0000000
Binary files a/logs/models/psi_5/best_model_psi_5.meta and /dev/null differ
diff --git a/logs/models/psi_5/checkpoint b/logs/models/psi_5/checkpoint
deleted file mode 100644
index e85086e..0000000
--- a/logs/models/psi_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "best_model_psi_5"
diff --git a/logs/models/psi_5/hyper_params_psi_5.json b/logs/models/psi_5/hyper_params_psi_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_5/hyper_params_psi_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_5_5/best_model_psi_5_5.data-00000-of-00001 b/logs/models/psi_5_5/best_model_psi_5_5.data-00000-of-00001
deleted file mode 100644
index 347357e..0000000
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diff --git a/logs/models/psi_5_5/best_model_psi_5_5.index b/logs/models/psi_5_5/best_model_psi_5_5.index
deleted file mode 100644
index 155e072..0000000
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diff --git a/logs/models/psi_5_5/best_model_psi_5_5.meta b/logs/models/psi_5_5/best_model_psi_5_5.meta
deleted file mode 100644
index 39da836..0000000
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diff --git a/logs/models/psi_5_5/checkpoint b/logs/models/psi_5_5/checkpoint
deleted file mode 100644
index 680db61..0000000
--- a/logs/models/psi_5_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_5_5"
diff --git a/logs/models/psi_5_5/hyper_params_psi_5_5.json b/logs/models/psi_5_5/hyper_params_psi_5_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_5_5/hyper_params_psi_5_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_6/best_model_psi_6.data-00000-of-00001 b/logs/models/psi_6/best_model_psi_6.data-00000-of-00001
deleted file mode 100644
index 5a67e0e..0000000
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diff --git a/logs/models/psi_6/best_model_psi_6.index b/logs/models/psi_6/best_model_psi_6.index
deleted file mode 100644
index d2a312e..0000000
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diff --git a/logs/models/psi_6/best_model_psi_6.meta b/logs/models/psi_6/best_model_psi_6.meta
deleted file mode 100644
index c355e8a..0000000
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diff --git a/logs/models/psi_6/checkpoint b/logs/models/psi_6/checkpoint
deleted file mode 100644
index 9c8aa1f..0000000
--- a/logs/models/psi_6/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_6"
diff --git a/logs/models/psi_6/hyper_params_psi_6.json b/logs/models/psi_6/hyper_params_psi_6.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_6/hyper_params_psi_6.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_6_5/best_model_psi_6_5.data-00000-of-00001 b/logs/models/psi_6_5/best_model_psi_6_5.data-00000-of-00001
deleted file mode 100644
index 8d2e5b8..0000000
Binary files a/logs/models/psi_6_5/best_model_psi_6_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_6_5/best_model_psi_6_5.index b/logs/models/psi_6_5/best_model_psi_6_5.index
deleted file mode 100644
index 46fc378..0000000
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diff --git a/logs/models/psi_6_5/best_model_psi_6_5.meta b/logs/models/psi_6_5/best_model_psi_6_5.meta
deleted file mode 100644
index 6828b03..0000000
Binary files a/logs/models/psi_6_5/best_model_psi_6_5.meta and /dev/null differ
diff --git a/logs/models/psi_6_5/checkpoint b/logs/models/psi_6_5/checkpoint
deleted file mode 100644
index 10a8ec4..0000000
--- a/logs/models/psi_6_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "best_model_psi_6_5"
diff --git a/logs/models/psi_6_5/hyper_params_psi_6_5.json b/logs/models/psi_6_5/hyper_params_psi_6_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_6_5/hyper_params_psi_6_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_7/best_model_psi_7.data-00000-of-00001 b/logs/models/psi_7/best_model_psi_7.data-00000-of-00001
deleted file mode 100644
index 347357e..0000000
Binary files a/logs/models/psi_7/best_model_psi_7.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_7/best_model_psi_7.index b/logs/models/psi_7/best_model_psi_7.index
deleted file mode 100644
index 155e072..0000000
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diff --git a/logs/models/psi_7/best_model_psi_7.meta b/logs/models/psi_7/best_model_psi_7.meta
deleted file mode 100644
index 361c47f..0000000
Binary files a/logs/models/psi_7/best_model_psi_7.meta and /dev/null differ
diff --git a/logs/models/psi_7/checkpoint b/logs/models/psi_7/checkpoint
deleted file mode 100644
index 8c2ef92..0000000
--- a/logs/models/psi_7/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_7"
diff --git a/logs/models/psi_7/hyper_params_psi_7.json b/logs/models/psi_7/hyper_params_psi_7.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_7/hyper_params_psi_7.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_7_5/best_model_psi_7_5.data-00000-of-00001 b/logs/models/psi_7_5/best_model_psi_7_5.data-00000-of-00001
deleted file mode 100644
index c5af541..0000000
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diff --git a/logs/models/psi_7_5/best_model_psi_7_5.index b/logs/models/psi_7_5/best_model_psi_7_5.index
deleted file mode 100644
index 791e3bc..0000000
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diff --git a/logs/models/psi_7_5/best_model_psi_7_5.meta b/logs/models/psi_7_5/best_model_psi_7_5.meta
deleted file mode 100644
index f8f68e1..0000000
Binary files a/logs/models/psi_7_5/best_model_psi_7_5.meta and /dev/null differ
diff --git a/logs/models/psi_7_5/checkpoint b/logs/models/psi_7_5/checkpoint
deleted file mode 100644
index 206d0c7..0000000
--- a/logs/models/psi_7_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_7_5"
diff --git a/logs/models/psi_7_5/hyper_params_psi_7_5.json b/logs/models/psi_7_5/hyper_params_psi_7_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_7_5/hyper_params_psi_7_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_8/best_model_psi_8.data-00000-of-00001 b/logs/models/psi_8/best_model_psi_8.data-00000-of-00001
deleted file mode 100644
index acd84c8..0000000
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diff --git a/logs/models/psi_8/best_model_psi_8.index b/logs/models/psi_8/best_model_psi_8.index
deleted file mode 100644
index 1f6e7ba..0000000
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diff --git a/logs/models/psi_8/best_model_psi_8.meta b/logs/models/psi_8/best_model_psi_8.meta
deleted file mode 100644
index 98e645d..0000000
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diff --git a/logs/models/psi_8/checkpoint b/logs/models/psi_8/checkpoint
deleted file mode 100644
index 3f2a75e..0000000
--- a/logs/models/psi_8/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_8"
diff --git a/logs/models/psi_8/hyper_params_psi_8.json b/logs/models/psi_8/hyper_params_psi_8.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_8/hyper_params_psi_8.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_8_5/best_model_psi_8_5.data-00000-of-00001 b/logs/models/psi_8_5/best_model_psi_8_5.data-00000-of-00001
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diff --git a/logs/models/psi_8_5/best_model_psi_8_5.index b/logs/models/psi_8_5/best_model_psi_8_5.index
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index 2ec02ea..0000000
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diff --git a/logs/models/psi_8_5/best_model_psi_8_5.meta b/logs/models/psi_8_5/best_model_psi_8_5.meta
deleted file mode 100644
index 7b6e760..0000000
Binary files a/logs/models/psi_8_5/best_model_psi_8_5.meta and /dev/null differ
diff --git a/logs/models/psi_8_5/checkpoint b/logs/models/psi_8_5/checkpoint
deleted file mode 100644
index 8104558..0000000
--- a/logs/models/psi_8_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_8_5"
diff --git a/logs/models/psi_8_5/hyper_params_psi_8_5.json b/logs/models/psi_8_5/hyper_params_psi_8_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_8_5/hyper_params_psi_8_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_9/best_model_psi_9.data-00000-of-00001 b/logs/models/psi_9/best_model_psi_9.data-00000-of-00001
deleted file mode 100644
index dd05062..0000000
Binary files a/logs/models/psi_9/best_model_psi_9.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_9/best_model_psi_9.index b/logs/models/psi_9/best_model_psi_9.index
deleted file mode 100644
index dee3901..0000000
Binary files a/logs/models/psi_9/best_model_psi_9.index and /dev/null differ
diff --git a/logs/models/psi_9/best_model_psi_9.meta b/logs/models/psi_9/best_model_psi_9.meta
deleted file mode 100644
index 82c1331..0000000
Binary files a/logs/models/psi_9/best_model_psi_9.meta and /dev/null differ
diff --git a/logs/models/psi_9/checkpoint b/logs/models/psi_9/checkpoint
deleted file mode 100644
index b18da7b..0000000
--- a/logs/models/psi_9/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "best_model_psi_9"
diff --git a/logs/models/psi_9/hyper_params_psi_9.json b/logs/models/psi_9/hyper_params_psi_9.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_9/hyper_params_psi_9.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models/psi_9_5/best_model_psi_9_5.data-00000-of-00001 b/logs/models/psi_9_5/best_model_psi_9_5.data-00000-of-00001
deleted file mode 100644
index 6c38e4e..0000000
Binary files a/logs/models/psi_9_5/best_model_psi_9_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models/psi_9_5/best_model_psi_9_5.index b/logs/models/psi_9_5/best_model_psi_9_5.index
deleted file mode 100644
index da707b5..0000000
Binary files a/logs/models/psi_9_5/best_model_psi_9_5.index and /dev/null differ
diff --git a/logs/models/psi_9_5/best_model_psi_9_5.meta b/logs/models/psi_9_5/best_model_psi_9_5.meta
deleted file mode 100644
index 8009941..0000000
Binary files a/logs/models/psi_9_5/best_model_psi_9_5.meta and /dev/null differ
diff --git a/logs/models/psi_9_5/checkpoint b/logs/models/psi_9_5/checkpoint
deleted file mode 100644
index 5a0292b..0000000
--- a/logs/models/psi_9_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "best_model_psi_9_5"
diff --git a/logs/models/psi_9_5/hyper_params_psi_9_5.json b/logs/models/psi_9_5/hyper_params_psi_9_5.json
deleted file mode 100644
index d4439d0..0000000
--- a/logs/models/psi_9_5/hyper_params_psi_9_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 100, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/models_ensemble/main/best_model_main.data-00000-of-00001 b/logs/models_ensemble/main/best_model_main.data-00000-of-00001
deleted file mode 100644
index 8a4d81d..0000000
Binary files a/logs/models_ensemble/main/best_model_main.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/main/best_model_main.index b/logs/models_ensemble/main/best_model_main.index
deleted file mode 100644
index 7817183..0000000
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diff --git a/logs/models_ensemble/main/best_model_main.meta b/logs/models_ensemble/main/best_model_main.meta
deleted file mode 100644
index ee52f11..0000000
Binary files a/logs/models_ensemble/main/best_model_main.meta and /dev/null differ
diff --git a/logs/models_ensemble/main/checkpoint b/logs/models_ensemble/main/checkpoint
deleted file mode 100644
index a960832..0000000
--- a/logs/models_ensemble/main/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/logs/models_ensemble/main/hyper_params_main.json b/logs/models_ensemble/main/hyper_params_main.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/main/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.data-00000-of-00001 b/logs/models_ensemble/psi-NAN/best_model_psi-NAN.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
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diff --git a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.index b/logs/models_ensemble/psi-NAN/best_model_psi-NAN.index
deleted file mode 100644
index 9049170..0000000
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diff --git a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.meta b/logs/models_ensemble/psi-NAN/best_model_psi-NAN.meta
deleted file mode 100644
index 7d53d2f..0000000
Binary files a/logs/models_ensemble/psi-NAN/best_model_psi-NAN.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi-NAN/checkpoint b/logs/models_ensemble/psi-NAN/checkpoint
deleted file mode 100644
index 9e183c6..0000000
--- a/logs/models_ensemble/psi-NAN/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "best_model_psi-NAN"
diff --git a/logs/models_ensemble/psi-NAN/hyper_params_psi-NAN.json b/logs/models_ensemble/psi-NAN/hyper_params_psi-NAN.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi-NAN/hyper_params_psi-NAN.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_0/best_model_psi_0.data-00000-of-00001 b/logs/models_ensemble/psi_0/best_model_psi_0.data-00000-of-00001
deleted file mode 100644
index 63fa39f..0000000
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diff --git a/logs/models_ensemble/psi_0/best_model_psi_0.index b/logs/models_ensemble/psi_0/best_model_psi_0.index
deleted file mode 100644
index 7940d43..0000000
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diff --git a/logs/models_ensemble/psi_0/best_model_psi_0.meta b/logs/models_ensemble/psi_0/best_model_psi_0.meta
deleted file mode 100644
index 19e7da3..0000000
Binary files a/logs/models_ensemble/psi_0/best_model_psi_0.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_0/checkpoint b/logs/models_ensemble/psi_0/checkpoint
deleted file mode 100644
index 9bd0ad9..0000000
--- a/logs/models_ensemble/psi_0/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_0"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_0"
diff --git a/logs/models_ensemble/psi_0/hyper_params_psi_0.json b/logs/models_ensemble/psi_0/hyper_params_psi_0.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_0/hyper_params_psi_0.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_1/best_model_psi_1.data-00000-of-00001 b/logs/models_ensemble/psi_1/best_model_psi_1.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_1/best_model_psi_1.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_1/best_model_psi_1.index b/logs/models_ensemble/psi_1/best_model_psi_1.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_1/best_model_psi_1.meta b/logs/models_ensemble/psi_1/best_model_psi_1.meta
deleted file mode 100644
index 296c5be..0000000
Binary files a/logs/models_ensemble/psi_1/best_model_psi_1.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_1/checkpoint b/logs/models_ensemble/psi_1/checkpoint
deleted file mode 100644
index 26afb89..0000000
--- a/logs/models_ensemble/psi_1/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_1"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "best_model_psi_1"
diff --git a/logs/models_ensemble/psi_1/hyper_params_psi_1.json b/logs/models_ensemble/psi_1/hyper_params_psi_1.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_1/hyper_params_psi_1.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_10/best_model_psi_10.data-00000-of-00001 b/logs/models_ensemble/psi_10/best_model_psi_10.data-00000-of-00001
deleted file mode 100644
index 38a5ea0..0000000
Binary files a/logs/models_ensemble/psi_10/best_model_psi_10.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_10/best_model_psi_10.index b/logs/models_ensemble/psi_10/best_model_psi_10.index
deleted file mode 100644
index ebe0d59..0000000
Binary files a/logs/models_ensemble/psi_10/best_model_psi_10.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_10/best_model_psi_10.meta b/logs/models_ensemble/psi_10/best_model_psi_10.meta
deleted file mode 100644
index cce597b..0000000
Binary files a/logs/models_ensemble/psi_10/best_model_psi_10.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_10/checkpoint b/logs/models_ensemble/psi_10/checkpoint
deleted file mode 100644
index 691f777..0000000
--- a/logs/models_ensemble/psi_10/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "best_model_psi_10"
diff --git a/logs/models_ensemble/psi_10/hyper_params_psi_10.json b/logs/models_ensemble/psi_10/hyper_params_psi_10.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_10/hyper_params_psi_10.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.data-00000-of-00001 b/logs/models_ensemble/psi_10_5/best_model_psi_10_5.data-00000-of-00001
deleted file mode 100644
index 9aaca8a..0000000
Binary files a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.index b/logs/models_ensemble/psi_10_5/best_model_psi_10_5.index
deleted file mode 100644
index c9f02b2..0000000
Binary files a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.meta b/logs/models_ensemble/psi_10_5/best_model_psi_10_5.meta
deleted file mode 100644
index 4ab6bc0..0000000
Binary files a/logs/models_ensemble/psi_10_5/best_model_psi_10_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_10_5/checkpoint b/logs/models_ensemble/psi_10_5/checkpoint
deleted file mode 100644
index c6b134c..0000000
--- a/logs/models_ensemble/psi_10_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "best_model_psi_10_5"
diff --git a/logs/models_ensemble/psi_10_5/hyper_params_psi_10_5.json b/logs/models_ensemble/psi_10_5/hyper_params_psi_10_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_10_5/hyper_params_psi_10_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_11/best_model_psi_11.data-00000-of-00001 b/logs/models_ensemble/psi_11/best_model_psi_11.data-00000-of-00001
deleted file mode 100644
index da14e33..0000000
Binary files a/logs/models_ensemble/psi_11/best_model_psi_11.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_11/best_model_psi_11.index b/logs/models_ensemble/psi_11/best_model_psi_11.index
deleted file mode 100644
index f6f69f4..0000000
Binary files a/logs/models_ensemble/psi_11/best_model_psi_11.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_11/best_model_psi_11.meta b/logs/models_ensemble/psi_11/best_model_psi_11.meta
deleted file mode 100644
index d46e08d..0000000
Binary files a/logs/models_ensemble/psi_11/best_model_psi_11.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_11/checkpoint b/logs/models_ensemble/psi_11/checkpoint
deleted file mode 100644
index 16551a4..0000000
--- a/logs/models_ensemble/psi_11/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "best_model_psi_11"
diff --git a/logs/models_ensemble/psi_11/hyper_params_psi_11.json b/logs/models_ensemble/psi_11/hyper_params_psi_11.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_11/hyper_params_psi_11.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.data-00000-of-00001 b/logs/models_ensemble/psi_11_5/best_model_psi_11_5.data-00000-of-00001
deleted file mode 100644
index cc1158e..0000000
Binary files a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.index b/logs/models_ensemble/psi_11_5/best_model_psi_11_5.index
deleted file mode 100644
index 0b182e1..0000000
Binary files a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.meta b/logs/models_ensemble/psi_11_5/best_model_psi_11_5.meta
deleted file mode 100644
index 05f7581..0000000
Binary files a/logs/models_ensemble/psi_11_5/best_model_psi_11_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_11_5/checkpoint b/logs/models_ensemble/psi_11_5/checkpoint
deleted file mode 100644
index 862a11e..0000000
--- a/logs/models_ensemble/psi_11_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "best_model_psi_11_5"
diff --git a/logs/models_ensemble/psi_11_5/hyper_params_psi_11_5.json b/logs/models_ensemble/psi_11_5/hyper_params_psi_11_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_11_5/hyper_params_psi_11_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_12/best_model_psi_12.data-00000-of-00001 b/logs/models_ensemble/psi_12/best_model_psi_12.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_12/best_model_psi_12.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_12/best_model_psi_12.index b/logs/models_ensemble/psi_12/best_model_psi_12.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_12/best_model_psi_12.meta b/logs/models_ensemble/psi_12/best_model_psi_12.meta
deleted file mode 100644
index d47d806..0000000
Binary files a/logs/models_ensemble/psi_12/best_model_psi_12.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_12/checkpoint b/logs/models_ensemble/psi_12/checkpoint
deleted file mode 100644
index 450959a..0000000
--- a/logs/models_ensemble/psi_12/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "best_model_psi_12"
diff --git a/logs/models_ensemble/psi_12/hyper_params_psi_12.json b/logs/models_ensemble/psi_12/hyper_params_psi_12.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_12/hyper_params_psi_12.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.data-00000-of-00001 b/logs/models_ensemble/psi_12_5/best_model_psi_12_5.data-00000-of-00001
deleted file mode 100644
index 246e06e..0000000
Binary files a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.index b/logs/models_ensemble/psi_12_5/best_model_psi_12_5.index
deleted file mode 100644
index 37f72aa..0000000
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diff --git a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.meta b/logs/models_ensemble/psi_12_5/best_model_psi_12_5.meta
deleted file mode 100644
index b387415..0000000
Binary files a/logs/models_ensemble/psi_12_5/best_model_psi_12_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_12_5/checkpoint b/logs/models_ensemble/psi_12_5/checkpoint
deleted file mode 100644
index 85a4085..0000000
--- a/logs/models_ensemble/psi_12_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "best_model_psi_12_5"
diff --git a/logs/models_ensemble/psi_12_5/hyper_params_psi_12_5.json b/logs/models_ensemble/psi_12_5/hyper_params_psi_12_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_12_5/hyper_params_psi_12_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_13/best_model_psi_13.data-00000-of-00001 b/logs/models_ensemble/psi_13/best_model_psi_13.data-00000-of-00001
deleted file mode 100644
index 7dfc9d3..0000000
Binary files a/logs/models_ensemble/psi_13/best_model_psi_13.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_13/best_model_psi_13.index b/logs/models_ensemble/psi_13/best_model_psi_13.index
deleted file mode 100644
index 9f00019..0000000
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diff --git a/logs/models_ensemble/psi_13/best_model_psi_13.meta b/logs/models_ensemble/psi_13/best_model_psi_13.meta
deleted file mode 100644
index ed8575f..0000000
Binary files a/logs/models_ensemble/psi_13/best_model_psi_13.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_13/checkpoint b/logs/models_ensemble/psi_13/checkpoint
deleted file mode 100644
index 919c875..0000000
--- a/logs/models_ensemble/psi_13/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_13"
diff --git a/logs/models_ensemble/psi_13/hyper_params_psi_13.json b/logs/models_ensemble/psi_13/hyper_params_psi_13.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_13/hyper_params_psi_13.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.data-00000-of-00001 b/logs/models_ensemble/psi_13_5/best_model_psi_13_5.data-00000-of-00001
deleted file mode 100644
index 83d8909..0000000
Binary files a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.index b/logs/models_ensemble/psi_13_5/best_model_psi_13_5.index
deleted file mode 100644
index 8abdfe0..0000000
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diff --git a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.meta b/logs/models_ensemble/psi_13_5/best_model_psi_13_5.meta
deleted file mode 100644
index 4b1d663..0000000
Binary files a/logs/models_ensemble/psi_13_5/best_model_psi_13_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_13_5/checkpoint b/logs/models_ensemble/psi_13_5/checkpoint
deleted file mode 100644
index 8c3882d..0000000
--- a/logs/models_ensemble/psi_13_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_13_5"
diff --git a/logs/models_ensemble/psi_13_5/hyper_params_psi_13_5.json b/logs/models_ensemble/psi_13_5/hyper_params_psi_13_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_13_5/hyper_params_psi_13_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_14/best_model_psi_14.data-00000-of-00001 b/logs/models_ensemble/psi_14/best_model_psi_14.data-00000-of-00001
deleted file mode 100644
index 3e11730..0000000
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diff --git a/logs/models_ensemble/psi_14/best_model_psi_14.index b/logs/models_ensemble/psi_14/best_model_psi_14.index
deleted file mode 100644
index b51214b..0000000
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diff --git a/logs/models_ensemble/psi_14/best_model_psi_14.meta b/logs/models_ensemble/psi_14/best_model_psi_14.meta
deleted file mode 100644
index 678fcb4..0000000
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diff --git a/logs/models_ensemble/psi_14/checkpoint b/logs/models_ensemble/psi_14/checkpoint
deleted file mode 100644
index f8ba349..0000000
--- a/logs/models_ensemble/psi_14/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "best_model_psi_14"
diff --git a/logs/models_ensemble/psi_14/hyper_params_psi_14.json b/logs/models_ensemble/psi_14/hyper_params_psi_14.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_14/hyper_params_psi_14.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.data-00000-of-00001 b/logs/models_ensemble/psi_14_5/best_model_psi_14_5.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
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diff --git a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.index b/logs/models_ensemble/psi_14_5/best_model_psi_14_5.index
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index 9049170..0000000
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diff --git a/logs/models_ensemble/psi_14_5/best_model_psi_14_5.meta b/logs/models_ensemble/psi_14_5/best_model_psi_14_5.meta
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index ae377e3..0000000
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diff --git a/logs/models_ensemble/psi_14_5/checkpoint b/logs/models_ensemble/psi_14_5/checkpoint
deleted file mode 100644
index 111570d..0000000
--- a/logs/models_ensemble/psi_14_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "best_model_psi_14_5"
diff --git a/logs/models_ensemble/psi_14_5/hyper_params_psi_14_5.json b/logs/models_ensemble/psi_14_5/hyper_params_psi_14_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_14_5/hyper_params_psi_14_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_15/best_model_psi_15.data-00000-of-00001 b/logs/models_ensemble/psi_15/best_model_psi_15.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
Binary files a/logs/models_ensemble/psi_15/best_model_psi_15.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_15/best_model_psi_15.index b/logs/models_ensemble/psi_15/best_model_psi_15.index
deleted file mode 100644
index 9049170..0000000
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diff --git a/logs/models_ensemble/psi_15/best_model_psi_15.meta b/logs/models_ensemble/psi_15/best_model_psi_15.meta
deleted file mode 100644
index 9030f8d..0000000
Binary files a/logs/models_ensemble/psi_15/best_model_psi_15.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_15/checkpoint b/logs/models_ensemble/psi_15/checkpoint
deleted file mode 100644
index 5cc2467..0000000
--- a/logs/models_ensemble/psi_15/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_15"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_15"
diff --git a/logs/models_ensemble/psi_15/hyper_params_psi_15.json b/logs/models_ensemble/psi_15/hyper_params_psi_15.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_15/hyper_params_psi_15.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.data-00000-of-00001 b/logs/models_ensemble/psi_1_5/best_model_psi_1_5.data-00000-of-00001
deleted file mode 100644
index 3e11730..0000000
Binary files a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.index b/logs/models_ensemble/psi_1_5/best_model_psi_1_5.index
deleted file mode 100644
index b51214b..0000000
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diff --git a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.meta b/logs/models_ensemble/psi_1_5/best_model_psi_1_5.meta
deleted file mode 100644
index 14f4a1f..0000000
Binary files a/logs/models_ensemble/psi_1_5/best_model_psi_1_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_1_5/checkpoint b/logs/models_ensemble/psi_1_5/checkpoint
deleted file mode 100644
index 9420406..0000000
--- a/logs/models_ensemble/psi_1_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "best_model_psi_1_5"
diff --git a/logs/models_ensemble/psi_1_5/hyper_params_psi_1_5.json b/logs/models_ensemble/psi_1_5/hyper_params_psi_1_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_1_5/hyper_params_psi_1_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_2/best_model_psi_2.data-00000-of-00001 b/logs/models_ensemble/psi_2/best_model_psi_2.data-00000-of-00001
deleted file mode 100644
index 63fa39f..0000000
Binary files a/logs/models_ensemble/psi_2/best_model_psi_2.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_2/best_model_psi_2.index b/logs/models_ensemble/psi_2/best_model_psi_2.index
deleted file mode 100644
index 7940d43..0000000
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diff --git a/logs/models_ensemble/psi_2/best_model_psi_2.meta b/logs/models_ensemble/psi_2/best_model_psi_2.meta
deleted file mode 100644
index 1a5a083..0000000
Binary files a/logs/models_ensemble/psi_2/best_model_psi_2.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_2/checkpoint b/logs/models_ensemble/psi_2/checkpoint
deleted file mode 100644
index 764b42a..0000000
--- a/logs/models_ensemble/psi_2/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_2"
diff --git a/logs/models_ensemble/psi_2/hyper_params_psi_2.json b/logs/models_ensemble/psi_2/hyper_params_psi_2.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_2/hyper_params_psi_2.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.data-00000-of-00001 b/logs/models_ensemble/psi_2_5/best_model_psi_2_5.data-00000-of-00001
deleted file mode 100644
index 7ff134c..0000000
Binary files a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.index b/logs/models_ensemble/psi_2_5/best_model_psi_2_5.index
deleted file mode 100644
index 9049170..0000000
Binary files a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.index and /dev/null differ
diff --git a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.meta b/logs/models_ensemble/psi_2_5/best_model_psi_2_5.meta
deleted file mode 100644
index 9f031d6..0000000
Binary files a/logs/models_ensemble/psi_2_5/best_model_psi_2_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_2_5/checkpoint b/logs/models_ensemble/psi_2_5/checkpoint
deleted file mode 100644
index a66b641..0000000
--- a/logs/models_ensemble/psi_2_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "best_model_psi_2_5"
diff --git a/logs/models_ensemble/psi_2_5/hyper_params_psi_2_5.json b/logs/models_ensemble/psi_2_5/hyper_params_psi_2_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_2_5/hyper_params_psi_2_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_3/best_model_psi_3.data-00000-of-00001 b/logs/models_ensemble/psi_3/best_model_psi_3.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_3/best_model_psi_3.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_3/best_model_psi_3.index b/logs/models_ensemble/psi_3/best_model_psi_3.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_3/best_model_psi_3.meta b/logs/models_ensemble/psi_3/best_model_psi_3.meta
deleted file mode 100644
index cce7400..0000000
Binary files a/logs/models_ensemble/psi_3/best_model_psi_3.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_3/checkpoint b/logs/models_ensemble/psi_3/checkpoint
deleted file mode 100644
index 8ba06e2..0000000
--- a/logs/models_ensemble/psi_3/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "best_model_psi_3"
diff --git a/logs/models_ensemble/psi_3/hyper_params_psi_3.json b/logs/models_ensemble/psi_3/hyper_params_psi_3.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_3/hyper_params_psi_3.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.data-00000-of-00001 b/logs/models_ensemble/psi_3_5/best_model_psi_3_5.data-00000-of-00001
deleted file mode 100644
index 6657699..0000000
Binary files a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.index b/logs/models_ensemble/psi_3_5/best_model_psi_3_5.index
deleted file mode 100644
index cf077e3..0000000
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diff --git a/logs/models_ensemble/psi_3_5/best_model_psi_3_5.meta b/logs/models_ensemble/psi_3_5/best_model_psi_3_5.meta
deleted file mode 100644
index 968dec4..0000000
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diff --git a/logs/models_ensemble/psi_3_5/checkpoint b/logs/models_ensemble/psi_3_5/checkpoint
deleted file mode 100644
index aa461ba..0000000
--- a/logs/models_ensemble/psi_3_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "best_model_psi_3_5"
diff --git a/logs/models_ensemble/psi_3_5/hyper_params_psi_3_5.json b/logs/models_ensemble/psi_3_5/hyper_params_psi_3_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_3_5/hyper_params_psi_3_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_4/best_model_psi_4.data-00000-of-00001 b/logs/models_ensemble/psi_4/best_model_psi_4.data-00000-of-00001
deleted file mode 100644
index 9aaca8a..0000000
Binary files a/logs/models_ensemble/psi_4/best_model_psi_4.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_4/best_model_psi_4.index b/logs/models_ensemble/psi_4/best_model_psi_4.index
deleted file mode 100644
index c9f02b2..0000000
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diff --git a/logs/models_ensemble/psi_4/best_model_psi_4.meta b/logs/models_ensemble/psi_4/best_model_psi_4.meta
deleted file mode 100644
index 144a689..0000000
Binary files a/logs/models_ensemble/psi_4/best_model_psi_4.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_4/checkpoint b/logs/models_ensemble/psi_4/checkpoint
deleted file mode 100644
index f93e6c1..0000000
--- a/logs/models_ensemble/psi_4/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "best_model_psi_4"
diff --git a/logs/models_ensemble/psi_4/hyper_params_psi_4.json b/logs/models_ensemble/psi_4/hyper_params_psi_4.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_4/hyper_params_psi_4.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.data-00000-of-00001 b/logs/models_ensemble/psi_4_5/best_model_psi_4_5.data-00000-of-00001
deleted file mode 100644
index ad56b60..0000000
Binary files a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.index b/logs/models_ensemble/psi_4_5/best_model_psi_4_5.index
deleted file mode 100644
index ef49308..0000000
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diff --git a/logs/models_ensemble/psi_4_5/best_model_psi_4_5.meta b/logs/models_ensemble/psi_4_5/best_model_psi_4_5.meta
deleted file mode 100644
index 5f3cc19..0000000
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diff --git a/logs/models_ensemble/psi_4_5/checkpoint b/logs/models_ensemble/psi_4_5/checkpoint
deleted file mode 100644
index 0232826..0000000
--- a/logs/models_ensemble/psi_4_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "best_model_psi_4_5"
diff --git a/logs/models_ensemble/psi_4_5/hyper_params_psi_4_5.json b/logs/models_ensemble/psi_4_5/hyper_params_psi_4_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_4_5/hyper_params_psi_4_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_5/best_model_psi_5.data-00000-of-00001 b/logs/models_ensemble/psi_5/best_model_psi_5.data-00000-of-00001
deleted file mode 100644
index 3e11730..0000000
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diff --git a/logs/models_ensemble/psi_5/best_model_psi_5.index b/logs/models_ensemble/psi_5/best_model_psi_5.index
deleted file mode 100644
index b51214b..0000000
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diff --git a/logs/models_ensemble/psi_5/best_model_psi_5.meta b/logs/models_ensemble/psi_5/best_model_psi_5.meta
deleted file mode 100644
index 3383595..0000000
Binary files a/logs/models_ensemble/psi_5/best_model_psi_5.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_5/checkpoint b/logs/models_ensemble/psi_5/checkpoint
deleted file mode 100644
index 3ddf378..0000000
--- a/logs/models_ensemble/psi_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "best_model_psi_5"
diff --git a/logs/models_ensemble/psi_5/hyper_params_psi_5.json b/logs/models_ensemble/psi_5/hyper_params_psi_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_5/hyper_params_psi_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_5_5/best_model_psi_5_5.data-00000-of-00001 b/logs/models_ensemble/psi_5_5/best_model_psi_5_5.data-00000-of-00001
deleted file mode 100644
index 40afdab..0000000
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diff --git a/logs/models_ensemble/psi_5_5/best_model_psi_5_5.index b/logs/models_ensemble/psi_5_5/best_model_psi_5_5.index
deleted file mode 100644
index 1771939..0000000
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diff --git a/logs/models_ensemble/psi_5_5/best_model_psi_5_5.meta b/logs/models_ensemble/psi_5_5/best_model_psi_5_5.meta
deleted file mode 100644
index 514e6f0..0000000
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diff --git a/logs/models_ensemble/psi_5_5/checkpoint b/logs/models_ensemble/psi_5_5/checkpoint
deleted file mode 100644
index 2775a1e..0000000
--- a/logs/models_ensemble/psi_5_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_5_5"
diff --git a/logs/models_ensemble/psi_5_5/hyper_params_psi_5_5.json b/logs/models_ensemble/psi_5_5/hyper_params_psi_5_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_5_5/hyper_params_psi_5_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_6/best_model_psi_6.data-00000-of-00001 b/logs/models_ensemble/psi_6/best_model_psi_6.data-00000-of-00001
deleted file mode 100644
index 78b4595..0000000
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diff --git a/logs/models_ensemble/psi_6/best_model_psi_6.index b/logs/models_ensemble/psi_6/best_model_psi_6.index
deleted file mode 100644
index d245728..0000000
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diff --git a/logs/models_ensemble/psi_6/best_model_psi_6.meta b/logs/models_ensemble/psi_6/best_model_psi_6.meta
deleted file mode 100644
index 690057d..0000000
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diff --git a/logs/models_ensemble/psi_6/checkpoint b/logs/models_ensemble/psi_6/checkpoint
deleted file mode 100644
index 6903078..0000000
--- a/logs/models_ensemble/psi_6/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "best_model_psi_6"
diff --git a/logs/models_ensemble/psi_6/hyper_params_psi_6.json b/logs/models_ensemble/psi_6/hyper_params_psi_6.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_6/hyper_params_psi_6.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_6_5/best_model_psi_6_5.data-00000-of-00001 b/logs/models_ensemble/psi_6_5/best_model_psi_6_5.data-00000-of-00001
deleted file mode 100644
index fb49107..0000000
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diff --git a/logs/models_ensemble/psi_6_5/best_model_psi_6_5.index b/logs/models_ensemble/psi_6_5/best_model_psi_6_5.index
deleted file mode 100644
index cdd8368..0000000
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diff --git a/logs/models_ensemble/psi_6_5/best_model_psi_6_5.meta b/logs/models_ensemble/psi_6_5/best_model_psi_6_5.meta
deleted file mode 100644
index a97137b..0000000
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diff --git a/logs/models_ensemble/psi_6_5/checkpoint b/logs/models_ensemble/psi_6_5/checkpoint
deleted file mode 100644
index eedcfee..0000000
--- a/logs/models_ensemble/psi_6_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_6_5"
diff --git a/logs/models_ensemble/psi_6_5/hyper_params_psi_6_5.json b/logs/models_ensemble/psi_6_5/hyper_params_psi_6_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_6_5/hyper_params_psi_6_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_7/best_model_psi_7.data-00000-of-00001 b/logs/models_ensemble/psi_7/best_model_psi_7.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
Binary files a/logs/models_ensemble/psi_7/best_model_psi_7.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_7/best_model_psi_7.index b/logs/models_ensemble/psi_7/best_model_psi_7.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_7/best_model_psi_7.meta b/logs/models_ensemble/psi_7/best_model_psi_7.meta
deleted file mode 100644
index c700e61..0000000
Binary files a/logs/models_ensemble/psi_7/best_model_psi_7.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_7/checkpoint b/logs/models_ensemble/psi_7/checkpoint
deleted file mode 100644
index 21eb900..0000000
--- a/logs/models_ensemble/psi_7/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "best_model_psi_7"
diff --git a/logs/models_ensemble/psi_7/hyper_params_psi_7.json b/logs/models_ensemble/psi_7/hyper_params_psi_7.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_7/hyper_params_psi_7.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.data-00000-of-00001 b/logs/models_ensemble/psi_7_5/best_model_psi_7_5.data-00000-of-00001
deleted file mode 100644
index da14e33..0000000
Binary files a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.data-00000-of-00001 and /dev/null differ
diff --git a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.index b/logs/models_ensemble/psi_7_5/best_model_psi_7_5.index
deleted file mode 100644
index f6f69f4..0000000
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diff --git a/logs/models_ensemble/psi_7_5/best_model_psi_7_5.meta b/logs/models_ensemble/psi_7_5/best_model_psi_7_5.meta
deleted file mode 100644
index eca8975..0000000
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diff --git a/logs/models_ensemble/psi_7_5/checkpoint b/logs/models_ensemble/psi_7_5/checkpoint
deleted file mode 100644
index b237b83..0000000
--- a/logs/models_ensemble/psi_7_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "best_model_psi_7_5"
diff --git a/logs/models_ensemble/psi_7_5/hyper_params_psi_7_5.json b/logs/models_ensemble/psi_7_5/hyper_params_psi_7_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_7_5/hyper_params_psi_7_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_8/best_model_psi_8.data-00000-of-00001 b/logs/models_ensemble/psi_8/best_model_psi_8.data-00000-of-00001
deleted file mode 100644
index 02e6414..0000000
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diff --git a/logs/models_ensemble/psi_8/best_model_psi_8.index b/logs/models_ensemble/psi_8/best_model_psi_8.index
deleted file mode 100644
index 8a36ce3..0000000
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diff --git a/logs/models_ensemble/psi_8/best_model_psi_8.meta b/logs/models_ensemble/psi_8/best_model_psi_8.meta
deleted file mode 100644
index 4ed963f..0000000
Binary files a/logs/models_ensemble/psi_8/best_model_psi_8.meta and /dev/null differ
diff --git a/logs/models_ensemble/psi_8/checkpoint b/logs/models_ensemble/psi_8/checkpoint
deleted file mode 100644
index 0cddb16..0000000
--- a/logs/models_ensemble/psi_8/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "best_model_psi_8"
diff --git a/logs/models_ensemble/psi_8/hyper_params_psi_8.json b/logs/models_ensemble/psi_8/hyper_params_psi_8.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_8/hyper_params_psi_8.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_8_5/best_model_psi_8_5.data-00000-of-00001 b/logs/models_ensemble/psi_8_5/best_model_psi_8_5.data-00000-of-00001
deleted file mode 100644
index 0dee234..0000000
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diff --git a/logs/models_ensemble/psi_8_5/best_model_psi_8_5.index b/logs/models_ensemble/psi_8_5/best_model_psi_8_5.index
deleted file mode 100644
index cd7a619..0000000
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diff --git a/logs/models_ensemble/psi_8_5/best_model_psi_8_5.meta b/logs/models_ensemble/psi_8_5/best_model_psi_8_5.meta
deleted file mode 100644
index 19273fe..0000000
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diff --git a/logs/models_ensemble/psi_8_5/checkpoint b/logs/models_ensemble/psi_8_5/checkpoint
deleted file mode 100644
index d4984e8..0000000
--- a/logs/models_ensemble/psi_8_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "best_model_psi_8_5"
diff --git a/logs/models_ensemble/psi_8_5/hyper_params_psi_8_5.json b/logs/models_ensemble/psi_8_5/hyper_params_psi_8_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_8_5/hyper_params_psi_8_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_9/best_model_psi_9.data-00000-of-00001 b/logs/models_ensemble/psi_9/best_model_psi_9.data-00000-of-00001
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index a9bcb18..0000000
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diff --git a/logs/models_ensemble/psi_9/best_model_psi_9.index b/logs/models_ensemble/psi_9/best_model_psi_9.index
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diff --git a/logs/models_ensemble/psi_9/best_model_psi_9.meta b/logs/models_ensemble/psi_9/best_model_psi_9.meta
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diff --git a/logs/models_ensemble/psi_9/checkpoint b/logs/models_ensemble/psi_9/checkpoint
deleted file mode 100644
index 27b5452..0000000
--- a/logs/models_ensemble/psi_9/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "best_model_psi_9"
diff --git a/logs/models_ensemble/psi_9/hyper_params_psi_9.json b/logs/models_ensemble/psi_9/hyper_params_psi_9.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_9/hyper_params_psi_9.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
diff --git a/logs/models_ensemble/psi_9_5/best_model_psi_9_5.data-00000-of-00001 b/logs/models_ensemble/psi_9_5/best_model_psi_9_5.data-00000-of-00001
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diff --git a/logs/models_ensemble/psi_9_5/checkpoint b/logs/models_ensemble/psi_9_5/checkpoint
deleted file mode 100644
index 199998e..0000000
--- a/logs/models_ensemble/psi_9_5/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../main/best_model_main"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "best_model_psi_9_5"
diff --git a/logs/models_ensemble/psi_9_5/hyper_params_psi_9_5.json b/logs/models_ensemble/psi_9_5/hyper_params_psi_9_5.json
deleted file mode 100644
index b22e006..0000000
--- a/logs/models_ensemble/psi_9_5/hyper_params_psi_9_5.json
+++ /dev/null
@@ -1 +0,0 @@
-{"fc_size_1": 500, "fc_size_2": 100, "use_drop_out_1": true, "use_drop_out_2": true, "num_iterations": 250, "learning_rate": 0.0003, "momentum": null}
\ No newline at end of file
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+++ /dev/null
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-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 160, "img_size_y": 80, "num_channels": 3}
\ No newline at end of file
diff --git a/logs/primary_models_original/2nd_good/best_model_main.data-00000-of-00001 b/logs/primary_models_original/2nd_good/best_model_main.data-00000-of-00001
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diff --git a/logs/primary_models_original/6th_good/checkpoint b/logs/primary_models_original/6th_good/checkpoint
deleted file mode 100644
index 6e74726..0000000
--- a/logs/primary_models_original/6th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/logs/primary_models_original/7th_good/checkpoint b/logs/primary_models_original/7th_good/checkpoint
deleted file mode 100644
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+++ /dev/null
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/logs/primary_models_original/8th_good/best_model_main.data-00000-of-00001 b/logs/primary_models_original/8th_good/best_model_main.data-00000-of-00001
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deleted file mode 100644
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--- a/logs/primary_models_original/8th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/logs/primary_models_original/8th_good/hyper_params_main.json b/logs/primary_models_original/8th_good/hyper_params_main.json
deleted file mode 100644
index 1cdbb46..0000000
--- a/logs/primary_models_original/8th_good/hyper_params_main.json
+++ /dev/null
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-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 160, "img_size_y": 80, "num_channels": 3}
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-model_checkpoint_path: "ensemble_architecture_main"
-all_model_checkpoint_paths: "ensemble_architecture_main"
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@@ -1 +0,0 @@
-{"num_to_cat": {"0": "psi-NAN", "1": "psi_0", "2": "psi_1", "3": "psi_10", "4": "psi_10_5", "5": "psi_11", "6": "psi_11_5", "7": "psi_12", "8": "psi_12_5", "9": "psi_13", "10": "psi_13_5", "11": "psi_14", "12": "psi_14_5", "13": "psi_15", "14": "psi_1_5", "15": "psi_2", "16": "psi_2_5", "17": "psi_3", "18": "psi_3_5", "19": "psi_4", "20": "psi_4_5", "21": "psi_5", "22": "psi_5_5", "23": "psi_6", "24": "psi_6_5", "25": "psi_7", "26": "psi_7_5", "27": "psi_8", "28": "psi_8_5", "29": "psi_9", "30": "psi_9_5"}, "cat_to_num": {"psi-NAN": 0, "psi_0": 1, "psi_1": 2, "psi_10": 3, "psi_10_5": 4, "psi_11": 5, "psi_11_5": 6, "psi_12": 7, "psi_12_5": 8, "psi_13": 9, "psi_13_5": 10, "psi_14": 11, "psi_14_5": 12, "psi_15": 13, "psi_1_5": 14, "psi_2": 15, "psi_2_5": 16, "psi_3": 17, "psi_3_5": 18, "psi_4": 19, "psi_4_5": 20, "psi_5": 21, "psi_5_5": 22, "psi_6": 23, "psi_6_5": 24, "psi_7": 25, "psi_7_5": 26, "psi_8": 27, "psi_8_5": 28, "psi_9": 29, "psi_9_5": 30}, "num_classes": 31}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/best_model_main.data-00000-of-00001
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/2nd_good/checkpoint
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/best_model_main.data-00000-of-00001
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models/8th_good/hyper_params_main.json
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-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 160, "img_size_y": 80, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/1st_good/best_model_main.data-00000-of-00001
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/best_model_main.data-00000-of-00001
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/2nd_good/checkpoint
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/checkpoint
deleted file mode 100644
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/checkpoint
+++ /dev/null
@@ -1,33 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "../psi-NAN/best_model_psi-NAN"
-all_model_checkpoint_paths: "../psi_11_5/best_model_psi_11_5"
-all_model_checkpoint_paths: "../psi_3_5/best_model_psi_3_5"
-all_model_checkpoint_paths: "../psi_7/best_model_psi_7"
-all_model_checkpoint_paths: "../psi_13/best_model_psi_13"
-all_model_checkpoint_paths: "../psi_2/best_model_psi_2"
-all_model_checkpoint_paths: "../psi_7_5/best_model_psi_7_5"
-all_model_checkpoint_paths: "../psi_9_5/best_model_psi_9_5"
-all_model_checkpoint_paths: "../psi_9/best_model_psi_9"
-all_model_checkpoint_paths: "../psi_3/best_model_psi_3"
-all_model_checkpoint_paths: "../psi_12_5/best_model_psi_12_5"
-all_model_checkpoint_paths: "../psi_4/best_model_psi_4"
-all_model_checkpoint_paths: "../psi_10_5/best_model_psi_10_5"
-all_model_checkpoint_paths: "../psi_14/best_model_psi_14"
-all_model_checkpoint_paths: "../psi_1_5/best_model_psi_1_5"
-all_model_checkpoint_paths: "../psi_5_5/best_model_psi_5_5"
-all_model_checkpoint_paths: "../psi_11/best_model_psi_11"
-all_model_checkpoint_paths: "../psi_6_5/best_model_psi_6_5"
-all_model_checkpoint_paths: "../psi_13_5/best_model_psi_13_5"
-all_model_checkpoint_paths: "../psi_15/best_model_psi_15"
-all_model_checkpoint_paths: "../psi_6/best_model_psi_6"
-all_model_checkpoint_paths: "../psi_1/best_model_psi_1"
-all_model_checkpoint_paths: "../psi_8_5/best_model_psi_8_5"
-all_model_checkpoint_paths: "../psi_0/best_model_psi_0"
-all_model_checkpoint_paths: "../psi_10/best_model_psi_10"
-all_model_checkpoint_paths: "../psi_12/best_model_psi_12"
-all_model_checkpoint_paths: "../psi_14_5/best_model_psi_14_5"
-all_model_checkpoint_paths: "../psi_2_5/best_model_psi_2_5"
-all_model_checkpoint_paths: "../psi_4_5/best_model_psi_4_5"
-all_model_checkpoint_paths: "../psi_5/best_model_psi_5"
-all_model_checkpoint_paths: "../psi_8/best_model_psi_8"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/3rd_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 500, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 237, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
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deleted file mode 100644
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/hyper_params_main.json
deleted file mode 100644
index c2ef0b8..0000000
--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/4th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 158, "img_size_y": 79, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/hyper_params_main.json
deleted file mode 100644
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/5th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0005, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 158, "num_channels": 3}
\ No newline at end of file
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/best_model_main.data-00000-of-00001
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/checkpoint
+++ /dev/null
@@ -1,2 +0,0 @@
-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/6th_good/hyper_params_main.json
+++ /dev/null
@@ -1 +0,0 @@
-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 79, "img_size_y": 237, "num_channels": 3}
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/best_model_main.data-00000-of-00001
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/checkpoint
+++ /dev/null
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/7th_good/hyper_params_main.json
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-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 80, "img_size_y": 160, "num_channels": 3}
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/best_model_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/best_model_main.data-00000-of-00001
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/checkpoint
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/hyper_params_main.json b/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/hyper_params_main.json
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--- a/modules/ensemble_modules/trainer_from_storage/logs/primary_models_original/8th_good/hyper_params_main.json
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-{"filter_size1": 17, "num_filters1": 45, "strides_1": [1, 7, 7, 1], "filter_size2": 7, "num_filters2": 17, "strides_2": [1, 5, 5, 1], "filter_size3": 1, "num_filters3": 7, "strides_3": [1, 1, 1, 1], "fc_size": 86, "num_iterations": 800, "learning_rate": 0.0002, "momentum": null, "use_pooling_1": true, "pooling_ksize_1": [1, 4, 4, 1], "pooling_strides_1": [1, 4, 4, 1], "use_pooling_2": true, "pooling_ksize_2": [1, 3, 3, 1], "pooling_strides_2": [1, 3, 3, 1], "use_pooling_3": false, "pooling_ksize_3": null, "pooling_strides_3": null, "padding": "SAME", "img_size_x": 160, "img_size_y": 80, "num_channels": 3}
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diff --git a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/checkpoint b/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/checkpoint
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--- a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/checkpoint
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-model_checkpoint_path: "/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main"
-all_model_checkpoint_paths: "/home/khodayarim/PycharmProjects/DeepGauge-ML-Demo/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main"
diff --git a/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.data-00000-of-00001 b/modules/ensemble_modules/trainer_from_storage/logs/temporary_models/ensemble_architecture_main.data-00000-of-00001
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-model_checkpoint_path: "best_model_main"
-all_model_checkpoint_paths: "best_model_main"
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