Make endpoint_url None (#3374)

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Kartik Kalamadi 2020-04-07 13:19:43 -07:00 committed by GitHub
parent c0fb46aa1b
commit 942be78bfe
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8 changed files with 15 additions and 8 deletions

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@ -74,7 +74,7 @@ outputs:
- {name: output_location, description: 'S3 URI of the transform job results.'}
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
batch_transform.py,

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@ -52,9 +52,16 @@ built_in_algos = {
# Get current directory to open templates
__cwd__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))
def nullable_string_argument(value):
value = value.strip()
if not value:
return None
return value
def add_default_client_arguments(parser):
parser.add_argument('--region', type=str.strip, required=True, help='The region where the training job launches.')
parser.add_argument('--endpoint_url', type=str.strip, required=False, help='The URL to use when communicating with the Sagemaker service.')
parser.add_argument('--endpoint_url', type=nullable_string_argument, required=False, help='The URL to use when communicating with the Sagemaker service.')
def get_sagemaker_client(region, endpoint_url=None):
"""Builds a client to the AWS SageMaker API."""

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@ -79,7 +79,7 @@ outputs:
- {name: endpoint_name, description: 'Endpoint name'}
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
deploy.py,

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@ -88,7 +88,7 @@ outputs:
- {name: active_learning_model_arn, description: 'The ARN for the most recent Amazon SageMaker model trained as part of automated data labeling.'}
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
ground_truth.py,

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@ -139,7 +139,7 @@ outputs:
description: 'The registry path of the Docker image that contains the training algorithm'
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
hyperparameter_tuning.py,

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@ -45,7 +45,7 @@ outputs:
- {name: model_name, description: 'The model name Sagemaker created'}
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
create_model.py,

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@ -103,7 +103,7 @@ outputs:
- {name: training_image, description: 'The registry path of the Docker image that contains the training algorithm'}
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
train.py,

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@ -27,7 +27,7 @@ outputs:
- {name: workteam_arn, description: 'The ARN of the workteam.'}
implementation:
container:
image: redbackthomson/aws-kubeflow-sagemaker:20191003
image: redbackthomson/aws-kubeflow-sagemaker:20200402
command: ['python']
args: [
workteam.py,