diff --git a/bootstrapper.yaml b/bootstrapper.yaml index 221d66cf090..a2abcda02f2 100644 --- a/bootstrapper.yaml +++ b/bootstrapper.yaml @@ -65,7 +65,7 @@ spec: spec: containers: - name: deploy - image: gcr.io/ml-pipeline/bootstrapper:0.0.42 + image: gcr.io/ml-pipeline/bootstrapper:0.1.0 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 84ad76372d3..42fa0f7456e 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 dsl.ContainerOp( name = step_name, - image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.0.42', #TODO: Update the name in next release. + image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.1.0', 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 dfa5789e273..bb64e532524 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:0.0.42 + image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.1.0 command: - python - -m @@ -38,7 +38,7 @@ spec: spec: containers: - name: tensorflow - image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42 + image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.1.0 command: - python - -m @@ -50,7 +50,7 @@ spec: spec: containers: - name: tensorflow - image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.0.42 + image: gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.1.0 command: - python - -m diff --git a/ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet b/ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet index 59be71c5df2..c96f324e0b4 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:0.0.42 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 api_image string gcr.io/ml-pipeline/api-server:0.1.0 API docker image +// @optionalParam scheduledworkflow_image string gcr.io/ml-pipeline/scheduledworkflow:0.1.0 schedule workflow docker image +// @optionalParam persistenceagent_image string gcr.io/ml-pipeline/persistenceagent:0.1.0 persistence agent docker image +// @optionalParam ui_image string gcr.io/ml-pipeline/frontend:0.1.0 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 f6615053dc9..e0571fe3dbf 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.1.0', arguments = [ '--predictions', predictions, '--output', output, diff --git a/samples/tfx/taxi-cab-classification-pipeline.py b/samples/tfx/taxi-cab-classification-pipeline.py index d253b6d8ef5..8b54bd4e6b2 100755 --- a/samples/tfx/taxi-cab-classification-pipeline.py +++ b/samples/tfx/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:dev', + image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tft:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf-trainer:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tfma:0.1.0', 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:0.0.42', + image = 'gcr.io/ml-pipeline/ml-pipeline-dataflow-tf-predict:0.1.0', 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:dev', #TODO: change the tag to the release versions when new releases are built with the updated image + image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-deployer:0.1.0', 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 b1cf27280cb..c96f0f1bc5f 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-dataproc-create-cluster:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-dataproc-delete-cluster:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-dataproc-analyze:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-dataproc-transform:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-dataproc-train:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-dataproc-predict:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:0.1.0', 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:0.0.42', + image='gcr.io/ml-pipeline/ml-pipeline-local-roc:0.1.0', 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 84ad76372d3..4d0d6ac5997 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 dsl.ContainerOp( name = step_name, - image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.0.42', #TODO: Update the name in next release. + image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.1.0', arguments = [ '--workers', number_of_workers, '--pss', number_of_parameter_servers, diff --git a/uninstaller.yaml b/uninstaller.yaml index 3f187fd74b8..736059db0c7 100644 --- a/uninstaller.yaml +++ b/uninstaller.yaml @@ -24,7 +24,7 @@ spec: spec: containers: - name: uninstaller - image: gcr.io/ml-pipeline/bootstrapper:0.0.42 + image: gcr.io/ml-pipeline/bootstrapper:0.1.0 imagePullPolicy: 'Always' # Additional parameter available: args: [