Adding GPU support to XGBoost

auto_ts/__version__.py

@@ -5,6 +5,6 @@
 __author__ = "Ram Seshadri"
 __description__ = "Build time series models for any data set, any size. Now using dask."
 __url__ = "https://github.com/Auto_ViML/Auto_TS.git"
-__version__ = "0.0.82"
+__version__ = "0.0.90"
 __license__ = "Apache License 2.0"
 __copyright__ = "2020-22 Google"

auto_ts/utils/eda.py

@@ -2,6 +2,8 @@
 import numpy as np  # type: ignore
 import pandas as pd  # type: ignore
 import seaborn as sns  # type: ignore
+from itertools import cycle
+import matplotlib.pyplot as plt
 
 # This gives an error when running from a python script.
 # Maybe, this should be set in the jupyter notebook directly.

auto_ts/utils/etl.py

@@ -11,7 +11,7 @@
 import numpy as np
 import pandas as pd  # type: ignore
 from sklearn.model_selection import TimeSeriesSplit  # type: ignore
-
+import pdb
 
 ##### This function loads a time series data and sets the index as a time series
 def load_ts_data(filename, ts_column, sep, target, dask_xgboost_flag=0):

setup.py

@@ -26,10 +26,11 @@
         "prophet",
         "scikit-learn>=0.24.0",
         "statsmodels",
-        "xgboost>=1.5.1",
+        "xgboost>=2.0",
         "prettytable",
         "dask>=2022.1.0",
         "pyyaml>=5.4.1",
+        "GPUtil>=1.4.0",
         "distributed>=2022.2.0",
     ],
     classifiers=[

updates.md

@@ -1,5 +1,8 @@
 <h1 id="updates">Latest Updates about Auto_TS library Page:</h1>
 
+<h2 id="jan-update">January 2024 Update:</h2>
+<p style="font-family:verdana">We have now added `XGBoost with GPU` support to Auto_TS. Auto_TS will automatically detect if there is a GPU in your Kaggle kernel or your local machine and will run XGBoost with GPU support. Hope this speeds up your computations!. 
+
 <h2 id="nov-update">November 2023 Update:</h2>
 <p style="font-family:verdana">We have now added `Google Cloud Run` support to Auto_TS. You can simply use the instructions in this <a href="https://github.com/AutoViML/Auto_TS/blob/master/cloud_run.txt">page</a> to deploy Auto_TS models on Google Cloud Run. Many thanks to <a href="https://github.com/abdulrahman305"> abdulrahman305</a> for providing a Pull Request to add this functionality to Auto_TS. <br>