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image tag update for release #114

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merged 4 commits into from
Nov 7, 2018
Merged

image tag update for release #114

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12a1e52
update image tag for new releases
gaoning777 Nov 7, 2018
a29ef6f
add more
gaoning777 Nov 7, 2018
0ffc77e
Merge branch 'master' into ngao/component-image-update-for-release
gaoning777 Nov 7, 2018
08dd800
delete the accidentaly added sample
gaoning777 Nov 7, 2018
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2 changes: 1 addition & 1 deletion bootstrapper.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -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: [
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2 changes: 1 addition & 1 deletion components/kubeflow/launcher/kubeflow_tfjob_launcher_op.py
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Expand Up @@ -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.
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image = 'gcr.io/ml-pipeline/ml-pipeline-kubeflow-tf:0.1.0',
arguments = [
'--workers', number_of_workers,
'--pss', number_of_parameter_servers,
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6 changes: 3 additions & 3 deletions components/kubeflow/launcher/train.template.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand All @@ -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
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8 changes: 4 additions & 4 deletions ml-pipeline/ml-pipeline/prototypes/ml-pipeline.jsonnet
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Expand Up @@ -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

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8 changes: 4 additions & 4 deletions samples/kubeflow-tf/kubeflow-training-classification.py
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Expand Up @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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,
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12 changes: 6 additions & 6 deletions samples/tfx/taxi-cab-classification-pipeline.py
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Expand Up @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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
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16 changes: 8 additions & 8 deletions samples/xgboost-spark/xgboost-training-cm.py
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Expand Up @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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,
Expand All @@ -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
Expand All @@ -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,
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2 changes: 1 addition & 1 deletion sdk/python/kfp/dsl/components/kubeflow_tfjob_launcher_op.py
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Expand Up @@ -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,
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2 changes: 1 addition & 1 deletion uninstaller.yaml
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Expand Up @@ -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: [
Expand Down