598 lines
24 KiB
Python
598 lines
24 KiB
Python
import json
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from moto.sagemaker.exceptions import AWSValidationException
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from moto.core.exceptions import AWSError
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from moto.core.responses import BaseResponse
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from moto.core.utils import amzn_request_id
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from .models import sagemaker_backends
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def format_enum_error(value, attribute, allowed):
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return f"Value '{value}' at '{attribute}' failed to satisfy constraint: Member must satisfy enum value set: {allowed}"
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class SageMakerResponse(BaseResponse):
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@property
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def sagemaker_backend(self):
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return sagemaker_backends[self.region]
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@property
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def request_params(self):
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try:
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return json.loads(self.body)
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except ValueError:
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return {}
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def describe_model(self):
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model_name = self._get_param("ModelName")
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model = self.sagemaker_backend.describe_model(model_name)
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return json.dumps(model.response_object)
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def create_model(self):
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model = self.sagemaker_backend.create_model(**self.request_params)
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return json.dumps(model.response_create)
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def delete_model(self):
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model_name = self._get_param("ModelName")
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response = self.sagemaker_backend.delete_model(model_name)
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return json.dumps(response)
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def list_models(self):
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models = self.sagemaker_backend.list_models(**self.request_params)
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return json.dumps({"Models": [model.response_object for model in models]})
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def _get_param(self, param_name, if_none=None):
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return self.request_params.get(param_name, if_none)
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@amzn_request_id
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def create_notebook_instance(self):
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sagemaker_notebook = self.sagemaker_backend.create_notebook_instance(
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notebook_instance_name=self._get_param("NotebookInstanceName"),
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instance_type=self._get_param("InstanceType"),
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subnet_id=self._get_param("SubnetId"),
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security_group_ids=self._get_param("SecurityGroupIds"),
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role_arn=self._get_param("RoleArn"),
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kms_key_id=self._get_param("KmsKeyId"),
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tags=self._get_param("Tags"),
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lifecycle_config_name=self._get_param("LifecycleConfigName"),
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direct_internet_access=self._get_param("DirectInternetAccess"),
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volume_size_in_gb=self._get_param("VolumeSizeInGB"),
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accelerator_types=self._get_param("AcceleratorTypes"),
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default_code_repository=self._get_param("DefaultCodeRepository"),
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additional_code_repositories=self._get_param("AdditionalCodeRepositories"),
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root_access=self._get_param("RootAccess"),
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)
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response = {
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"NotebookInstanceArn": sagemaker_notebook.arn,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_notebook_instance(self):
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notebook_instance_name = self._get_param("NotebookInstanceName")
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notebook_instance = self.sagemaker_backend.get_notebook_instance(
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notebook_instance_name
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)
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response = {
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"NotebookInstanceArn": notebook_instance.arn,
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"NotebookInstanceName": notebook_instance.notebook_instance_name,
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"NotebookInstanceStatus": notebook_instance.status,
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"Url": notebook_instance.url,
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"InstanceType": notebook_instance.instance_type,
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"SubnetId": notebook_instance.subnet_id,
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"SecurityGroups": notebook_instance.security_group_ids,
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"RoleArn": notebook_instance.role_arn,
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"KmsKeyId": notebook_instance.kms_key_id,
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# ToDo: NetworkInterfaceId
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"LastModifiedTime": str(notebook_instance.last_modified_time),
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"CreationTime": str(notebook_instance.creation_time),
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"NotebookInstanceLifecycleConfigName": notebook_instance.lifecycle_config_name,
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"DirectInternetAccess": notebook_instance.direct_internet_access,
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"VolumeSizeInGB": notebook_instance.volume_size_in_gb,
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"AcceleratorTypes": notebook_instance.accelerator_types,
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"DefaultCodeRepository": notebook_instance.default_code_repository,
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"AdditionalCodeRepositories": notebook_instance.additional_code_repositories,
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"RootAccess": notebook_instance.root_access,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def start_notebook_instance(self):
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notebook_instance_name = self._get_param("NotebookInstanceName")
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self.sagemaker_backend.start_notebook_instance(notebook_instance_name)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def stop_notebook_instance(self):
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notebook_instance_name = self._get_param("NotebookInstanceName")
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self.sagemaker_backend.stop_notebook_instance(notebook_instance_name)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def delete_notebook_instance(self):
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notebook_instance_name = self._get_param("NotebookInstanceName")
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self.sagemaker_backend.delete_notebook_instance(notebook_instance_name)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def list_tags(self):
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arn = self._get_param("ResourceArn")
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try:
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if ":notebook-instance/" in arn:
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tags = self.sagemaker_backend.get_notebook_instance_tags(arn)
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elif ":endpoint/" in arn:
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tags = self.sagemaker_backend.get_endpoint_tags(arn)
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elif ":training-job/" in arn:
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tags = self.sagemaker_backend.get_training_job_tags(arn)
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elif ":experiment/" in arn:
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tags = self.sagemaker_backend.get_experiment_tags(arn)
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elif ":experiment-trial/" in arn:
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tags = self.sagemaker_backend.get_trial_tags(arn)
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elif ":experiment-trial-component/" in arn:
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tags = self.sagemaker_backend.get_trial_component_tags(arn)
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else:
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tags = []
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except AWSError:
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tags = []
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response = {"Tags": tags}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def add_tags(self):
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arn = self._get_param("ResourceArn")
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tags = self._get_param("Tags")
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if ":experiment/" in arn:
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self.sagemaker_backend.add_tags_to_experiment(arn, tags)
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elif ":experiment-trial/" in arn:
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self.sagemaker_backend.add_tags_to_trial(arn, tags)
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elif ":experiment-trial-component/" in arn:
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self.sagemaker_backend.add_tags_to_trial_component(arn, tags)
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return 200, {}, json.dumps({})
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@amzn_request_id
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def delete_tags(self):
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arn = self._get_param("ResourceArn")
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tag_keys = self._get_param("TagKeys")
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if ":experiment/" in arn:
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self.sagemaker_backend.delete_tags_from_experiment(arn, tag_keys)
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elif ":experiment-trial/" in arn:
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self.sagemaker_backend.delete_tags_from_trial(arn, tag_keys)
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elif ":experiment-trial-component/" in arn:
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self.sagemaker_backend.delete_tags_from_trial_component(arn, tag_keys)
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return 200, {}, json.dumps({})
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@amzn_request_id
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def create_endpoint_config(self):
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endpoint_config = self.sagemaker_backend.create_endpoint_config(
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endpoint_config_name=self._get_param("EndpointConfigName"),
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production_variants=self._get_param("ProductionVariants"),
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data_capture_config=self._get_param("DataCaptureConfig"),
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tags=self._get_param("Tags"),
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kms_key_id=self._get_param("KmsKeyId"),
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)
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response = {
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"EndpointConfigArn": endpoint_config.endpoint_config_arn,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_endpoint_config(self):
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endpoint_config_name = self._get_param("EndpointConfigName")
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response = self.sagemaker_backend.describe_endpoint_config(endpoint_config_name)
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return json.dumps(response)
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@amzn_request_id
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def delete_endpoint_config(self):
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endpoint_config_name = self._get_param("EndpointConfigName")
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self.sagemaker_backend.delete_endpoint_config(endpoint_config_name)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def create_endpoint(self):
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endpoint = self.sagemaker_backend.create_endpoint(
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endpoint_name=self._get_param("EndpointName"),
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endpoint_config_name=self._get_param("EndpointConfigName"),
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tags=self._get_param("Tags"),
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)
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response = {
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"EndpointArn": endpoint.endpoint_arn,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_endpoint(self):
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endpoint_name = self._get_param("EndpointName")
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response = self.sagemaker_backend.describe_endpoint(endpoint_name)
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return json.dumps(response)
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@amzn_request_id
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def delete_endpoint(self):
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endpoint_name = self._get_param("EndpointName")
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self.sagemaker_backend.delete_endpoint(endpoint_name)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def create_processing_job(self):
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processing_job = self.sagemaker_backend.create_processing_job(
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app_specification=self._get_param("AppSpecification"),
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experiment_config=self._get_param("ExperimentConfig"),
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network_config=self._get_param("NetworkConfig"),
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processing_inputs=self._get_param("ProcessingInputs"),
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processing_job_name=self._get_param("ProcessingJobName"),
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processing_output_config=self._get_param("ProcessingOutputConfig"),
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role_arn=self._get_param("RoleArn"),
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stopping_condition=self._get_param("StoppingCondition"),
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)
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response = {
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"ProcessingJobArn": processing_job.processing_job_arn,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_processing_job(self):
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processing_job_name = self._get_param("ProcessingJobName")
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response = self.sagemaker_backend.describe_processing_job(processing_job_name)
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return json.dumps(response)
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@amzn_request_id
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def create_training_job(self):
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training_job = self.sagemaker_backend.create_training_job(
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training_job_name=self._get_param("TrainingJobName"),
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hyper_parameters=self._get_param("HyperParameters"),
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algorithm_specification=self._get_param("AlgorithmSpecification"),
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role_arn=self._get_param("RoleArn"),
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input_data_config=self._get_param("InputDataConfig"),
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output_data_config=self._get_param("OutputDataConfig"),
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resource_config=self._get_param("ResourceConfig"),
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vpc_config=self._get_param("VpcConfig"),
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stopping_condition=self._get_param("StoppingCondition"),
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tags=self._get_param("Tags"),
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enable_network_isolation=self._get_param("EnableNetworkIsolation", False),
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enable_inter_container_traffic_encryption=self._get_param(
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"EnableInterContainerTrafficEncryption", False
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),
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enable_managed_spot_training=self._get_param(
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"EnableManagedSpotTraining", False
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),
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checkpoint_config=self._get_param("CheckpointConfig"),
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debug_hook_config=self._get_param("DebugHookConfig"),
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debug_rule_configurations=self._get_param("DebugRuleConfigurations"),
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tensor_board_output_config=self._get_param("TensorBoardOutputConfig"),
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experiment_config=self._get_param("ExperimentConfig"),
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)
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response = {
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"TrainingJobArn": training_job.training_job_arn,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_training_job(self):
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training_job_name = self._get_param("TrainingJobName")
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response = self.sagemaker_backend.describe_training_job(training_job_name)
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return json.dumps(response)
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@amzn_request_id
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def delete_training_job(self):
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training_job_name = self._get_param("TrainingJobName")
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self.sagemaker_backend.delete_training_job(training_job_name)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def create_notebook_instance_lifecycle_config(self):
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lifecycle_configuration = (
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self.sagemaker_backend.create_notebook_instance_lifecycle_config(
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notebook_instance_lifecycle_config_name=self._get_param(
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"NotebookInstanceLifecycleConfigName"
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),
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on_create=self._get_param("OnCreate"),
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on_start=self._get_param("OnStart"),
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)
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)
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response = {
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"NotebookInstanceLifecycleConfigArn": lifecycle_configuration.notebook_instance_lifecycle_config_arn,
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}
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_notebook_instance_lifecycle_config(self):
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response = self.sagemaker_backend.describe_notebook_instance_lifecycle_config(
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notebook_instance_lifecycle_config_name=self._get_param(
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"NotebookInstanceLifecycleConfigName"
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)
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)
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return json.dumps(response)
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@amzn_request_id
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def delete_notebook_instance_lifecycle_config(self):
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self.sagemaker_backend.delete_notebook_instance_lifecycle_config(
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notebook_instance_lifecycle_config_name=self._get_param(
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"NotebookInstanceLifecycleConfigName"
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)
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)
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return 200, {}, json.dumps("{}")
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@amzn_request_id
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def search(self):
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response = self.sagemaker_backend.search(
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resource=self._get_param("Resource"),
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search_expression=self._get_param("SearchExpression"),
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)
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def list_experiments(self):
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MaxResults = self._get_param("MaxResults")
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NextToken = self._get_param("NextToken")
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paged_results, next_token = self.sagemaker_backend.list_experiments(
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MaxResults=MaxResults, NextToken=NextToken
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)
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experiment_summaries = [
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{
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"ExperimentName": experiment_data.experiment_name,
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"ExperimentArn": experiment_data.experiment_arn,
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"CreationTime": experiment_data.creation_time,
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"LastModifiedTime": experiment_data.last_modified_time,
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}
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for experiment_data in paged_results
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]
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response = {
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"ExperimentSummaries": experiment_summaries,
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}
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if next_token:
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response["NextToken"] = next_token
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def delete_experiment(self):
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self.sagemaker_backend.delete_experiment(
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experiment_name=self._get_param("ExperimentName")
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)
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return 200, {}, json.dumps({})
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@amzn_request_id
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def create_experiment(self):
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response = self.sagemaker_backend.create_experiment(
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experiment_name=self._get_param("ExperimentName")
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)
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_experiment(self):
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response = self.sagemaker_backend.describe_experiment(
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experiment_name=self._get_param("ExperimentName")
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)
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def list_trials(self):
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MaxResults = self._get_param("MaxResults")
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NextToken = self._get_param("NextToken")
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paged_results, next_token = self.sagemaker_backend.list_trials(
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NextToken=NextToken,
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MaxResults=MaxResults,
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experiment_name=self._get_param("ExperimentName"),
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trial_component_name=self._get_param("TrialComponentName"),
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)
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trial_summaries = [
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{
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"TrialName": trial_data.trial_name,
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"TrialArn": trial_data.trial_arn,
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"CreationTime": trial_data.creation_time,
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"LastModifiedTime": trial_data.last_modified_time,
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}
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for trial_data in paged_results
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]
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response = {
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"TrialSummaries": trial_summaries,
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}
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if next_token:
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response["NextToken"] = next_token
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def create_trial(self):
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response = self.sagemaker_backend.create_trial(
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trial_name=self._get_param("TrialName"),
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experiment_name=self._get_param("ExperimentName"),
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)
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def list_trial_components(self):
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MaxResults = self._get_param("MaxResults")
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NextToken = self._get_param("NextToken")
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paged_results, next_token = self.sagemaker_backend.list_trial_components(
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NextToken=NextToken,
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MaxResults=MaxResults,
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trial_name=self._get_param("TrialName"),
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)
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trial_component_summaries = [
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{
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"TrialComponentName": trial_component_data.trial_component_name,
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"TrialComponentArn": trial_component_data.trial_component_arn,
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"CreationTime": trial_component_data.creation_time,
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"LastModifiedTime": trial_component_data.last_modified_time,
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}
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for trial_component_data in paged_results
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]
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response = {
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"TrialComponentSummaries": trial_component_summaries,
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}
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if next_token:
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response["NextToken"] = next_token
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def create_trial_component(self):
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response = self.sagemaker_backend.create_trial_component(
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trial_component_name=self._get_param("TrialComponentName"),
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trial_name=self._get_param("TrialName"),
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)
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return 200, {}, json.dumps(response)
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@amzn_request_id
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def describe_trial(self):
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trial_name = self._get_param("TrialName")
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response = self.sagemaker_backend.describe_trial(trial_name)
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return json.dumps(response)
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@amzn_request_id
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def delete_trial(self):
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trial_name = self._get_param("TrialName")
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self.sagemaker_backend.delete_trial(trial_name)
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return 200, {}, json.dumps({})
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@amzn_request_id
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def delete_trial_component(self):
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trial_component_name = self._get_param("TrialComponentName")
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self.sagemaker_backend.delete_trial_component(trial_component_name)
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return 200, {}, json.dumps({})
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@amzn_request_id
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def describe_trial_component(self):
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trial_component_name = self._get_param("TrialComponentName")
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response = self.sagemaker_backend.describe_trial_component(trial_component_name)
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return json.dumps(response)
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@amzn_request_id
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def associate_trial_component(self):
|
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response = self.sagemaker_backend.associate_trial_component(self.request_params)
|
|
return 200, {}, json.dumps(response)
|
|
|
|
@amzn_request_id
|
|
def disassociate_trial_component(self):
|
|
response = self.sagemaker_backend.disassociate_trial_component(
|
|
self.request_params
|
|
)
|
|
return 200, {}, json.dumps(response)
|
|
|
|
@amzn_request_id
|
|
def list_associations(self, *args, **kwargs): # pylint: disable=unused-argument
|
|
response = self.sagemaker_backend.list_associations(self.request_params)
|
|
return 200, {}, json.dumps(response)
|
|
|
|
@amzn_request_id
|
|
def list_processing_jobs(self):
|
|
max_results_range = range(1, 101)
|
|
allowed_sort_by = ["Name", "CreationTime", "Status"]
|
|
allowed_sort_order = ["Ascending", "Descending"]
|
|
allowed_status_equals = [
|
|
"Completed",
|
|
"Stopped",
|
|
"InProgress",
|
|
"Stopping",
|
|
"Failed",
|
|
]
|
|
|
|
max_results = self._get_int_param("MaxResults")
|
|
sort_by = self._get_param("SortBy", "CreationTime")
|
|
sort_order = self._get_param("SortOrder", "Ascending")
|
|
status_equals = self._get_param("StatusEquals")
|
|
next_token = self._get_param("NextToken")
|
|
errors = []
|
|
if max_results and max_results not in max_results_range:
|
|
errors.append(
|
|
"Value '{0}' at 'maxResults' failed to satisfy constraint: Member must have value less than or equal to {1}".format(
|
|
max_results, max_results_range[-1]
|
|
)
|
|
)
|
|
|
|
if sort_by not in allowed_sort_by:
|
|
errors.append(format_enum_error(sort_by, "sortBy", allowed_sort_by))
|
|
if sort_order not in allowed_sort_order:
|
|
errors.append(
|
|
format_enum_error(sort_order, "sortOrder", allowed_sort_order)
|
|
)
|
|
|
|
if status_equals and status_equals not in allowed_status_equals:
|
|
errors.append(
|
|
format_enum_error(status_equals, "statusEquals", allowed_status_equals)
|
|
)
|
|
|
|
if errors != []:
|
|
raise AWSValidationException(
|
|
f"{len(errors)} validation errors detected: {';'.join(errors)}"
|
|
)
|
|
|
|
response = self.sagemaker_backend.list_processing_jobs(
|
|
next_token=next_token,
|
|
max_results=max_results,
|
|
creation_time_after=self._get_param("CreationTimeAfter"),
|
|
creation_time_before=self._get_param("CreationTimeBefore"),
|
|
last_modified_time_after=self._get_param("LastModifiedTimeAfter"),
|
|
last_modified_time_before=self._get_param("LastModifiedTimeBefore"),
|
|
name_contains=self._get_param("NameContains"),
|
|
status_equals=status_equals,
|
|
)
|
|
return 200, {}, json.dumps(response)
|
|
|
|
@amzn_request_id
|
|
def list_training_jobs(self):
|
|
max_results_range = range(1, 101)
|
|
allowed_sort_by = ["Name", "CreationTime", "Status"]
|
|
allowed_sort_order = ["Ascending", "Descending"]
|
|
allowed_status_equals = [
|
|
"Completed",
|
|
"Stopped",
|
|
"InProgress",
|
|
"Stopping",
|
|
"Failed",
|
|
]
|
|
|
|
max_results = self._get_int_param("MaxResults")
|
|
sort_by = self._get_param("SortBy", "CreationTime")
|
|
sort_order = self._get_param("SortOrder", "Ascending")
|
|
status_equals = self._get_param("StatusEquals")
|
|
next_token = self._get_param("NextToken")
|
|
errors = []
|
|
if max_results and max_results not in max_results_range:
|
|
errors.append(
|
|
"Value '{0}' at 'maxResults' failed to satisfy constraint: Member must have value less than or equal to {1}".format(
|
|
max_results, max_results_range[-1]
|
|
)
|
|
)
|
|
|
|
if sort_by not in allowed_sort_by:
|
|
errors.append(format_enum_error(sort_by, "sortBy", allowed_sort_by))
|
|
if sort_order not in allowed_sort_order:
|
|
errors.append(
|
|
format_enum_error(sort_order, "sortOrder", allowed_sort_order)
|
|
)
|
|
|
|
if status_equals and status_equals not in allowed_status_equals:
|
|
errors.append(
|
|
format_enum_error(status_equals, "statusEquals", allowed_status_equals)
|
|
)
|
|
|
|
if errors != []:
|
|
raise AWSValidationException(
|
|
f"{len(errors)} validation errors detected: {';'.join(errors)}"
|
|
)
|
|
|
|
response = self.sagemaker_backend.list_training_jobs(
|
|
next_token=next_token,
|
|
max_results=max_results,
|
|
creation_time_after=self._get_param("CreationTimeAfter"),
|
|
creation_time_before=self._get_param("CreationTimeBefore"),
|
|
last_modified_time_after=self._get_param("LastModifiedTimeAfter"),
|
|
last_modified_time_before=self._get_param("LastModifiedTimeBefore"),
|
|
name_contains=self._get_param("NameContains"),
|
|
status_equals=status_equals,
|
|
)
|
|
return 200, {}, json.dumps(response)
|