component release script (#694)

kubeflow · Jan 17, 2019 · a0d4be3 · a0d4be3
1 parent 2ed6010
commit a0d4be3
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Showing 7 changed files with 35 additions and 35 deletions.
diff --git a/components/kubeflow/launcher/kubeflow_tfjob_launcher_op.py b/components/kubeflow/launcher/kubeflow_tfjob_launcher_op.py
@@ -17,7 +17,7 @@
 def kubeflow_tfjob_launcher_op(container_image, command, number_of_workers: int, number_of_parameter_servers: int, tfjob_timeout_minutes: int, output_dir=None, step_name='TFJob-launcher'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--workers', number_of_workers,
             '--pss', number_of_parameter_servers,

diff --git a/components/kubeflow/launcher/src/train.template.yaml b/components/kubeflow/launcher/src/train.template.yaml
@@ -26,7 +26,7 @@ spec:
         spec:
           containers:
           - name: tensorflow
-            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:d3c4add0a95e930c70a330466d0923827784eb9a
+            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:2ed60100d1db9efeb38c6c358f90b21c144179be
             command:
               - python
               - -m
@@ -49,7 +49,7 @@ spec:
         spec:
           containers:
           - name: tensorflow
-            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:d3c4add0a95e930c70a330466d0923827784eb9a
+            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:2ed60100d1db9efeb38c6c358f90b21c144179be
             command:
               - python
               - -m
@@ -72,7 +72,7 @@ spec:
             spec:
               containers:
               - name: tensorflow
-                image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:d3c4add0a95e930c70a330466d0923827784eb9a
+                image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:2ed60100d1db9efeb38c6c358f90b21c144179be
                 command:
                   - python
                   - -m

diff --git a/samples/kubeflow-tf/kubeflow-training-classification.py b/samples/kubeflow-tf/kubeflow-training-classification.py
@@ -21,7 +21,7 @@
 def dataflow_tf_transform_op(train_data: 'GcsUri', evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]', project: 'GcpProject', preprocess_mode, preprocess_module: 'GcsUri[text/code/python]', transform_output: 'GcsUri[Directory]', step_name='preprocess'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--train', train_data,
             '--eval', evaluation_data,
@@ -38,7 +38,7 @@ def dataflow_tf_transform_op(train_data: 'GcsUri', evaluation_data: 'GcsUri', sc
 def kubeflow_tf_training_op(transformed_data_dir, schema: 'GcsUri[text/json]', learning_rate: float, hidden_layer_size: int, steps: int, target, preprocess_module: 'GcsUri[text/code/python]', training_output: 'GcsUri[Directory]', step_name='training', use_gpu=False):
     kubeflow_tf_training_op = dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--transformed-data-dir', transformed_data_dir,
             '--schema', schema,
@@ -52,15 +52,15 @@ def kubeflow_tf_training_op(transformed_data_dir, schema: 'GcsUri[text/json]', l
         file_outputs = {'train': '/output.txt'}
     )
     if use_gpu:
-        kubeflow_tf_training_op.image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer-gpu:d3c4add0a95e930c70a330466d0923827784eb9a'
+        kubeflow_tf_training_op.image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer-gpu:2ed60100d1db9efeb38c6c358f90b21c144179be'
         kubeflow_tf_training_op.set_gpu_limit(1)
 
     return kubeflow_tf_training_op
 
 def dataflow_tf_predict_op(evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]', target: str, model: 'TensorFlow model', predict_mode, project: 'GcpProject', prediction_output: 'GcsUri', step_name='prediction'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--data', evaluation_data,
             '--schema', schema,
@@ -76,7 +76,7 @@ def dataflow_tf_predict_op(evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]
 def confusion_matrix_op(predictions, output, step_name='confusionmatrix'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
           '--predictions', predictions,
           '--output', output,

diff --git a/samples/notebooks/KubeFlow Pipeline Using TFX OSS Components.ipynb b/samples/notebooks/KubeFlow Pipeline Using TFX OSS Components.ipynb
@@ -43,13 +43,13 @@
     "EVAL_DATA = 'gs://ml-pipeline-playground/tfx/taxi-cab-classification/eval.csv'\n",
     "HIDDEN_LAYER_SIZE = '1500'\n",
     "STEPS = 3000\n",
-    "DATAFLOW_TFDV_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
-    "DATAFLOW_TFT_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
-    "DATAFLOW_TFMA_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
-    "DATAFLOW_TF_PREDICT_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
-    "KUBEFLOW_TF_TRAINER_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
-    "KUBEFLOW_TF_TRAINER_GPU_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer-gpu:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
-    "KUBEFLOW_DEPLOYER_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:d3c4add0a95e930c70a330466d0923827784eb9a'\n",
+    "DATAFLOW_TFDV_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
+    "DATAFLOW_TFT_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
+    "DATAFLOW_TFMA_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
+    "DATAFLOW_TF_PREDICT_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
+    "KUBEFLOW_TF_TRAINER_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
+    "KUBEFLOW_TF_TRAINER_GPU_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer-gpu:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
+    "KUBEFLOW_DEPLOYER_IMAGE = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:2ed60100d1db9efeb38c6c358f90b21c144179be'\n",
     "DEPLOYER_MODEL = 'notebook_tfx_taxi'\n",
     "DEPLOYER_VERSION_DEV = 'dev'\n",
     "DEPLOYER_VERSION_PROD = 'prod'"

diff --git a/samples/resnet-cmle/resnet-train-pipeline.py b/samples/resnet-cmle/resnet-train-pipeline.py
@@ -22,7 +22,7 @@ def resnet_preprocess_op(project_id: 'GcpProject', output: 'GcsUri', train_csv:
                          validation_csv: 'GcsUri[text/csv]', labels, step_name='preprocess'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/resnet-preprocess:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/resnet-preprocess:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--project_id', project_id,
             '--output', output,
@@ -38,7 +38,7 @@ def resnet_train_op(data_dir, output: 'GcsUri', region: 'GcpRegion', depth: int,
                     num_eval_images: int, num_label_classes: int, tf_version, step_name='train'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/resnet-train:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/resnet-train:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--data_dir', data_dir,
             '--output', output,
@@ -60,7 +60,7 @@ def resnet_deploy_op(model_dir, model, version, project_id: 'GcpProject', region
                      tf_version, step_name='deploy'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/resnet-deploy:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/resnet-deploy:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--model', model,
             '--version', version,

diff --git a/samples/tfx/taxi-cab-classification-pipeline.py b/samples/tfx/taxi-cab-classification-pipeline.py
@@ -21,7 +21,7 @@
 def dataflow_tf_data_validation_op(inference_data: 'GcsUri', validation_data: 'GcsUri', column_names: 'GcsUri[text/json]', key_columns, project: 'GcpProject', mode, validation_output: 'GcsUri[Directory]', step_name='validation'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--csv-data-for-inference', inference_data,
             '--csv-data-to-validate', validation_data,
@@ -40,7 +40,7 @@ def dataflow_tf_data_validation_op(inference_data: 'GcsUri', validation_data: 'G
 def dataflow_tf_transform_op(train_data: 'GcsUri', evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]', project: 'GcpProject', preprocess_mode, preprocess_module: 'GcsUri[text/code/python]', transform_output: 'GcsUri[Directory]', step_name='preprocess'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--train', train_data,
             '--eval', evaluation_data,
@@ -57,7 +57,7 @@ def dataflow_tf_transform_op(train_data: 'GcsUri', evaluation_data: 'GcsUri', sc
 def tf_train_op(transformed_data_dir, schema: 'GcsUri[text/json]', learning_rate: float, hidden_layer_size: int, steps: int, target: str, preprocess_module: 'GcsUri[text/code/python]', training_output: 'GcsUri[Directory]', step_name='training'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--transformed-data-dir', transformed_data_dir,
             '--schema', schema,
@@ -74,7 +74,7 @@ def tf_train_op(transformed_data_dir, schema: 'GcsUri[text/json]', learning_rate
 def dataflow_tf_model_analyze_op(model: 'TensorFlow model', evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]', project: 'GcpProject', analyze_mode, analyze_slice_column, analysis_output: 'GcsUri', step_name='analysis'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--model', model,
             '--eval', evaluation_data,
@@ -91,7 +91,7 @@ def dataflow_tf_model_analyze_op(model: 'TensorFlow model', evaluation_data: 'Gc
 def dataflow_tf_predict_op(evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]', target: str, model: 'TensorFlow model', predict_mode, project: 'GcpProject', prediction_output: 'GcsUri', step_name='prediction'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--data', evaluation_data,
             '--schema', schema,
@@ -108,7 +108,7 @@ def dataflow_tf_predict_op(evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]
 def confusion_matrix_op(predictions: 'GcsUri', output: 'GcsUri', step_name='confusion_matrix'):
   return dsl.ContainerOp(
       name=step_name,
-      image='gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
         '--output', '%s/{{workflow.name}}/confusionmatrix' % output,
         '--predictions', predictions,
@@ -119,7 +119,7 @@ def confusion_matrix_op(predictions: 'GcsUri', output: 'GcsUri', step_name='conf
 def roc_op(predictions: 'GcsUri', output: 'GcsUri', step_name='roc'):
   return dsl.ContainerOp(
       name=step_name,
-      image='gcr.io/ml-pipeline/ml-pipeline-local-roc:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-local-roc:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
         '--output', '%s/{{workflow.name}}/roc' % output,
         '--predictions', predictions,
@@ -130,7 +130,7 @@ def roc_op(predictions: 'GcsUri', output: 'GcsUri', step_name='roc'):
 def kubeflow_deploy_op(model: 'TensorFlow model', tf_server_name, step_name='deploy'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:d3c4add0a95e930c70a330466d0923827784eb9a',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:2ed60100d1db9efeb38c6c358f90b21c144179be',
         arguments = [
             '--model-path', model,
             '--server-name', tf_server_name

diff --git a/samples/xgboost-spark/xgboost-training-cm.py b/samples/xgboost-spark/xgboost-training-cm.py
@@ -26,7 +26,7 @@ class CreateClusterOp(dsl.ContainerOp):
   def __init__(self, name, project, region, staging):
     super(CreateClusterOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
           '--project', project,
           '--region', region,
@@ -41,7 +41,7 @@ class DeleteClusterOp(dsl.ContainerOp):
   def __init__(self, name, project, region):
     super(DeleteClusterOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
           '--project', project,
           '--region', region,
@@ -55,7 +55,7 @@ class AnalyzeOp(dsl.ContainerOp):
   def __init__(self, name, project, region, cluster_name, schema, train_data, output):
     super(AnalyzeOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
           '--project', project,
           '--region', region,
@@ -73,7 +73,7 @@ def __init__(self, name, project, region, cluster_name, train_data, eval_data,
                target, analysis, output):
     super(TransformOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
           '--project', project,
           '--region', region,
@@ -98,7 +98,7 @@ def __init__(self, name, project, region, cluster_name, train_data, eval_data,
 
     super(TrainerOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-train:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-train:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
           '--project', project,
           '--region', region,
@@ -121,7 +121,7 @@ class PredictOp(dsl.ContainerOp):
   def __init__(self, name, project, region, cluster_name, data, model, target, analysis, output):
     super(PredictOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
           '--project', project,
           '--region', region,
@@ -141,7 +141,7 @@ class ConfusionMatrixOp(dsl.ContainerOp):
   def __init__(self, name, predictions, output):
     super(ConfusionMatrixOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
         '--output', output,
         '--predictions', predictions
@@ -153,7 +153,7 @@ class RocOp(dsl.ContainerOp):
   def __init__(self, name, predictions, trueclass, output):
     super(RocOp, self).__init__(
       name=name,
-      image='gcr.io/ml-pipeline/ml-pipeline-local-roc:d3c4add0a95e930c70a330466d0923827784eb9a',
+      image='gcr.io/ml-pipeline/ml-pipeline-local-roc:2ed60100d1db9efeb38c6c358f90b21c144179be',
       arguments=[
         '--output', output,
         '--predictions', predictions,