From 67b011f2280b1e05277288f176c60978788a005a Mon Sep 17 00:00:00 2001
From: Pascal Vicaire <25757005+vicaire@users.noreply.github.com>
Date: Fri, 2 Nov 2018 16:57:37 -0700
Subject: [PATCH] Upgrading the container versions to 0.0.42, the version of
 the first release of kubeflow/pipelines.

---
 .../samples/resnet_training_pipeline.yaml        |  6 +++---
 .../taxi_cab_classification_pipeline.yaml        | 10 +++++-----
 .../apiserver/samples/xgboost_training_cm.yaml   | 16 ++++++++--------
 bootstrapper.yaml                                |  2 +-
 .../launcher/kubeflow_tfjob_launcher_op.py       |  2 +-
 components/kubeflow/launcher/train.template.yaml |  6 +++---
 frontend/mock-backend/mock-template.yaml         | 16 ++++++++--------
 .../ml-pipeline/prototypes/ml-pipeline.jsonnet   |  8 ++++----
 .../kubeflow-training-classification.py          |  8 ++++----
 samples/resnet-cmle/resnet-train-pipeline.py     |  6 +++---
 samples/tfma/taxi-cab-classification-pipeline.py | 12 ++++++------
 samples/xgboost-spark/xgboost-training-cm.py     | 16 ++++++++--------
 .../dsl/components/kubeflow_tfjob_launcher_op.py |  2 +-
 uninstaller.yaml                                 |  2 +-
 14 files changed, 56 insertions(+), 56 deletions(-)

diff --git a/backend/src/apiserver/samples/resnet_training_pipeline.yaml b/backend/src/apiserver/samples/resnet_training_pipeline.yaml
index 851ff803d9c..0eecea31bb5 100644
--- a/backend/src/apiserver/samples/resnet_training_pipeline.yaml
+++ b/backend/src/apiserver/samples/resnet_training_pipeline.yaml
@@ -54,7 +54,7 @@ spec:
       - '{{inputs.parameters.train-trained}}'
       - --TFVERSION
       - '{{inputs.parameters.tf-version}}'
-      image: gcr.io/ml-pipeline/resnet-deploy:0.0.18
+      image: gcr.io/ml-pipeline/resnet-deploy:0.0.42
     inputs:
       parameters:
       - name: model
@@ -104,7 +104,7 @@ spec:
       - '{{inputs.parameters.validation-csv}}'
       - --labels
       - '{{inputs.parameters.labels}}'
-      image: gcr.io/ml-pipeline/resnet-preprocess:0.0.18
+      image: gcr.io/ml-pipeline/resnet-preprocess:0.0.42
     inputs:
       parameters:
       - name: bucket
@@ -255,7 +255,7 @@ spec:
       - '{{inputs.parameters.num-label-classes}}'
       - --TFVERSION
       - '{{inputs.parameters.tf-version}}'
-      image: gcr.io/ml-pipeline/resnet-train:0.0.18
+      image: gcr.io/ml-pipeline/resnet-train:0.0.42
     inputs:
       parameters:
       - name: bucket
diff --git a/backend/src/apiserver/samples/taxi_cab_classification_pipeline.yaml b/backend/src/apiserver/samples/taxi_cab_classification_pipeline.yaml
index d07911eb71e..e621a9ad0d1 100644
--- a/backend/src/apiserver/samples/taxi_cab_classification_pipeline.yaml
+++ b/backend/src/apiserver/samples/taxi_cab_classification_pipeline.yaml
@@ -50,7 +50,7 @@ spec:
       - '{{inputs.parameters.analyze-slice-column}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/analysis'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:0.0.42
     inputs:
       parameters:
       - name: analyze-mode
@@ -99,7 +99,7 @@ spec:
       - '{{inputs.parameters.training-train}}'
       - --server-name
       - taxi-cab-classification-model-{{workflow.name}}
-      image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:0.0.42
     inputs:
       parameters:
       - name: training-train
@@ -148,7 +148,7 @@ spec:
       - '{{inputs.parameters.project}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/predict'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:0.0.42
     inputs:
       parameters:
       - name: evaluation
@@ -207,7 +207,7 @@ spec:
       - '{{inputs.parameters.preprocess-module}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/transformed'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:0.0.42
     inputs:
       parameters:
       - name: evaluation
@@ -375,7 +375,7 @@ spec:
       - '{{inputs.parameters.preprocess-module}}'
       - --job-dir
       - '{{inputs.parameters.output}}/{{workflow.name}}/train'
-      image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:dev
+      image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42
     inputs:
       parameters:
       - name: hidden-layer-size
diff --git a/backend/src/apiserver/samples/xgboost_training_cm.yaml b/backend/src/apiserver/samples/xgboost_training_cm.yaml
index b7e101ae4b7..885e7e63bd2 100644
--- a/backend/src/apiserver/samples/xgboost_training_cm.yaml
+++ b/backend/src/apiserver/samples/xgboost_training_cm.yaml
@@ -41,7 +41,7 @@ spec:
       - '{{inputs.parameters.train-data}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/analysis'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:0.0.42
     inputs:
       parameters:
       - name: create-cluster-output
@@ -89,7 +89,7 @@ spec:
       - '{{inputs.parameters.output}}/{{workflow.name}}/confusionmatrix'
       - --predictions
       - '{{inputs.parameters.predict-output}}'
-      image: gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.0.42
     inputs:
       parameters:
       - name: output
@@ -133,7 +133,7 @@ spec:
       - xgb-{{workflow.name}}
       - --staging
       - '{{inputs.parameters.output}}'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:0.0.42
     inputs:
       parameters:
       - name: output
@@ -180,7 +180,7 @@ spec:
       - '{{inputs.parameters.region}}'
       - --name
       - xgb-{{workflow.name}}
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:0.0.42
     inputs:
       parameters:
       - name: project
@@ -375,7 +375,7 @@ spec:
       - '{{inputs.parameters.train-output}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/predict'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:0.0.42
     inputs:
       parameters:
       - name: analyze-output
@@ -427,7 +427,7 @@ spec:
       - '{{inputs.parameters.predict-output}}'
       - --trueclass
       - '{{inputs.parameters.true-label}}'
-      image: gcr.io/ml-pipeline/ml-pipeline-local-roc:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-local-roc:0.0.42
     inputs:
       parameters:
       - name: output
@@ -488,7 +488,7 @@ spec:
       - gs://ml-pipeline-playground/trainconfcla.json
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/model'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-train:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-train:0.0.42
     inputs:
       parameters:
       - name: analyze-output
@@ -552,7 +552,7 @@ spec:
       - '{{inputs.parameters.target}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/transform'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:0.0.42
     inputs:
       parameters:
       - name: analyze-output
diff --git a/bootstrapper.yaml b/bootstrapper.yaml
index 6a6bb0c7732..221d66cf090 100644
--- a/bootstrapper.yaml
+++ b/bootstrapper.yaml
@@ -65,7 +65,7 @@ spec:
     spec:
       containers:
       - name: deploy
-        image: gcr.io/ml-pipeline/bootstrapper:0.0.20
+        image: gcr.io/ml-pipeline/bootstrapper:0.0.42
         imagePullPolicy: 'Always'
         # Additional parameter available:
         args: [
diff --git a/components/kubeflow/launcher/kubeflow_tfjob_launcher_op.py b/components/kubeflow/launcher/kubeflow_tfjob_launcher_op.py
index dba5b14859a..1d690bc67df 100644
--- 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 mlp.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.0.18', #TODO: Update the name in next release.
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.0.42', #TODO: Update the name in next release.
         arguments = [
             '--workers', number_of_workers,
             '--pss', number_of_parameter_servers,
diff --git a/components/kubeflow/launcher/train.template.yaml b/components/kubeflow/launcher/train.template.yaml
index c3757c4ff3e..dfa5789e273 100644
--- a/components/kubeflow/launcher/train.template.yaml
+++ b/components/kubeflow/launcher/train.template.yaml
@@ -26,7 +26,7 @@ spec:
         spec:
           containers:
           - name: tensorflow
-            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.16
+            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42
             command:
               - python
               - -m
@@ -38,7 +38,7 @@ spec:
         spec:
           containers:
           - name: tensorflow
-            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.16
+            image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42
             command:
               - python
               - -m
@@ -50,7 +50,7 @@ spec:
             spec:
               containers:
               - name: tensorflow
-                image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.16
+                image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42
                 command:
                   - python
                   - -m
diff --git a/frontend/mock-backend/mock-template.yaml b/frontend/mock-backend/mock-template.yaml
index e83e06d8729..aaaf245b9b8 100644
--- a/frontend/mock-backend/mock-template.yaml
+++ b/frontend/mock-backend/mock-template.yaml
@@ -54,7 +54,7 @@ spec:
       - '{{inputs.parameters.train-data}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/analysis'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:0.0.42
     inputs:
       parameters:
       - name: create-cluster-output
@@ -89,7 +89,7 @@ spec:
       - '{{inputs.parameters.output}}/{{workflow.name}}/confusionmatrix'
       - --predictions
       - '{{inputs.parameters.predict-output}}'
-      image: gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.0.42
     inputs:
       parameters:
       - name: output
@@ -120,7 +120,7 @@ spec:
       - xgb-{{workflow.name}}
       - --staging
       - '{{inputs.parameters.output}}'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:0.0.42
     inputs:
       parameters:
       - name: output
@@ -154,7 +154,7 @@ spec:
       - '{{inputs.parameters.region}}'
       - --name
       - xgb-{{workflow.name}}
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:0.0.42
     inputs:
       parameters:
       - name: project
@@ -336,7 +336,7 @@ spec:
       - '{{inputs.parameters.train-output}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/predict'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:0.0.42
     inputs:
       parameters:
       - name: analyze-output
@@ -375,7 +375,7 @@ spec:
       - '{{inputs.parameters.predict-output}}'
       - --trueclass
       - '{{inputs.parameters.true-label}}'
-      image: gcr.io/ml-pipeline/ml-pipeline-local-roc:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-local-roc:0.0.42
     inputs:
       parameters:
       - name: output
@@ -423,7 +423,7 @@ spec:
       - gs://ml-pipeline-playground/trainconfcla.json
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/model'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-train:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-train:0.0.42
     inputs:
       parameters:
       - name: analyze-output
@@ -474,7 +474,7 @@ spec:
       - '{{inputs.parameters.target}}'
       - --output
       - '{{inputs.parameters.output}}/{{workflow.name}}/transform'
-      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:0.0.18
+      image: gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:0.0.42
     inputs:
       parameters:
       - name: analyze-output
diff --git a/ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet b/ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet
index 0073ff72f02..59be71c5df2 100644
--- a/ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet
+++ b/ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet
@@ -4,10 +4,10 @@
 // @shortDescription ML pipeline
 // @param name string Name to give to each of the components
 // @optionalParam namespace string default Namespace
-// @optionalParam api_image string gcr.io/ml-pipeline/api-server:0.0.20 API docker image
-// @optionalParam scheduledworkflow_image string gcr.io/ml-pipeline/scheduledworkflow:0.0.20 schedule workflow docker image
-// @optionalParam persistenceagent_image string gcr.io/ml-pipeline/persistenceagent:0.0.20 persistence agent docker image
-// @optionalParam ui_image string gcr.io/ml-pipeline/frontend:0.0.20 UI docker image
+// @optionalParam api_image string gcr.io/ml-pipeline/api-server:0.0.42 API docker image
+// @optionalParam scheduledworkflow_image string gcr.io/ml-pipeline/scheduledworkflow:0.0.42 schedule workflow docker image
+// @optionalParam persistenceagent_image string gcr.io/ml-pipeline/persistenceagent:0.0.42 persistence agent docker image
+// @optionalParam ui_image string gcr.io/ml-pipeline/frontend:0.0.42 UI docker image
 // @optionalParam deploy_argo string false flag to deploy argo
 // @optionalParam report_usage string false flag to report usage
 
diff --git a/samples/kubeflow-tf/kubeflow-training-classification.py b/samples/kubeflow-tf/kubeflow-training-classification.py
index 109b416b912..f6615053dc9 100755
--- a/samples/kubeflow-tf/kubeflow-training-classification.py
+++ b/samples/kubeflow-tf/kubeflow-training-classification.py
@@ -20,7 +20,7 @@
 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:0.0.42',
         arguments = [
             '--train', train_data,
             '--eval', evaluation_data,
@@ -37,7 +37,7 @@ 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'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:dev',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42',
         arguments = [
             '--transformed-data-dir', transformed_data_dir,
             '--schema', schema,
@@ -54,7 +54,7 @@ def kubeflow_tf_training_op(transformed_data_dir, schema: 'GcsUri[text/json]', l
 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:0.0.42',
         arguments = [
             '--data', evaluation_data,
             '--schema', schema,
@@ -70,7 +70,7 @@ 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.0.42',
         arguments = [
           '--predictions', predictions,
           '--output', output,
diff --git a/samples/resnet-cmle/resnet-train-pipeline.py b/samples/resnet-cmle/resnet-train-pipeline.py
index edc70894c13..81b1e81fffd 100755
--- a/samples/resnet-cmle/resnet-train-pipeline.py
+++ b/samples/resnet-cmle/resnet-train-pipeline.py
@@ -20,7 +20,7 @@
 def resnet_preprocess_op(project_id: 'GcpProject', output: 'GcsUri', train_csv: 'GcsUri[text/csv]', validation_csv: 'GcsUri[text/csv]', labels, step_name='preprocess'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/resnet-preprocess:dev', # TODO: update it with a version number after a new release.
+        image = 'gcr.io/ml-pipeline/resnet-preprocess:0.0.42', # TODO: update it with a version number after a new release.
         arguments = [
             '--project_id', project_id,
             '--output', output,
@@ -34,7 +34,7 @@ def resnet_preprocess_op(project_id: 'GcpProject', output: 'GcsUri', train_csv:
 def resnet_train_op(data_dir, output: 'GcsUri', region: 'GcpRegion', depth: int, train_batch_size: int, eval_batch_size: int, steps_per_eval: int, train_steps: int, num_train_images: 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/resnet-train:0.0.42',
         arguments = [
             '--data_dir', data_dir,
             '--output', output,
@@ -55,7 +55,7 @@ def resnet_train_op(data_dir, output: 'GcsUri', region: 'GcpRegion', depth: int,
 def resnet_deploy_op(model_dir, model, version, project_id: 'GcpProject', region: 'GcpRegion', tf_version, step_name='deploy'):
     return dsl.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/resnet-deploy:0.0.18',
+        image = 'gcr.io/ml-pipeline/resnet-deploy:0.0.42',
         arguments = [
             '--model', model,
             '--version', version,
diff --git a/samples/tfma/taxi-cab-classification-pipeline.py b/samples/tfma/taxi-cab-classification-pipeline.py
index b3ad8eca290..47e79ca241d 100755
--- a/samples/tfma/taxi-cab-classification-pipeline.py
+++ b/samples/tfma/taxi-cab-classification-pipeline.py
@@ -20,7 +20,7 @@
 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:0.0.24',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:0.0.42',
         arguments = [
             '--csv-data-for-inference', inference_data,
             '--csv-data-to-validate', validation_data,
@@ -39,7 +39,7 @@ 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:0.0.42',
         arguments = [
             '--train', train_data,
             '--eval', evaluation_data,
@@ -56,7 +56,7 @@ 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:dev',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42',
         arguments = [
             '--transformed-data-dir', transformed_data_dir,
             '--schema', schema,
@@ -73,7 +73,7 @@ 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:0.0.42',
         arguments = [
             '--model', model,
             '--eval', evaluation_data,
@@ -90,7 +90,7 @@ 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:0.0.42',
         arguments = [
             '--data', evaluation_data,
             '--schema', schema,
@@ -106,7 +106,7 @@ def dataflow_tf_predict_op(evaluation_data: 'GcsUri', schema: 'GcsUri[text/json]
 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:0.0.18',
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:0.0.42',
         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
index a3215443cd2..b1cf27280cb 100755
--- a/samples/xgboost-spark/xgboost-training-cm.py
+++ b/samples/xgboost-spark/xgboost-training-cm.py
@@ -25,7 +25,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:0.0.42',
       arguments=[
           '--project', project,
           '--region', region,
@@ -40,7 +40,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:0.0.42',
       arguments=[
           '--project', project,
           '--region', region,
@@ -54,7 +54,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:0.0.42',
       arguments=[
           '--project', project,
           '--region', region,
@@ -72,7 +72,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:0.0.42',
       arguments=[
           '--project', project,
           '--region', region,
@@ -97,7 +97,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-train:0.0.42',
       arguments=[
           '--project', project,
           '--region', region,
@@ -120,7 +120,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:0.0.42',
       arguments=[
           '--project', project,
           '--region', region,
@@ -140,7 +140,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.0.42',
       arguments=[
         '--output', output,
         '--predictions', predictions
@@ -152,7 +152,7 @@ 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:0.0.18',
+      image='gcr.io/ml-pipeline/ml-pipeline-local-roc:0.0.42',
       arguments=[
         '--output', output,
         '--predictions', predictions,
diff --git a/sdk/python/kfp/dsl/components/kubeflow_tfjob_launcher_op.py b/sdk/python/kfp/dsl/components/kubeflow_tfjob_launcher_op.py
index dba5b14859a..1d690bc67df 100644
--- a/sdk/python/kfp/dsl/components/kubeflow_tfjob_launcher_op.py
+++ b/sdk/python/kfp/dsl/components/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 mlp.ContainerOp(
         name = step_name,
-        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.0.18', #TODO: Update the name in next release.
+        image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.0.42', #TODO: Update the name in next release.
         arguments = [
             '--workers', number_of_workers,
             '--pss', number_of_parameter_servers,
diff --git a/uninstaller.yaml b/uninstaller.yaml
index 881f92aaa3c..3f187fd74b8 100644
--- a/uninstaller.yaml
+++ b/uninstaller.yaml
@@ -24,7 +24,7 @@ spec:
     spec:
       containers:
       - name: uninstaller
-        image: gcr.io/ml-pipeline/bootstrapper:0.0.19
+        image: gcr.io/ml-pipeline/bootstrapper:0.0.42
         imagePullPolicy: 'Always'
         # Additional parameter available:
         args: [