code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
def delete_endpoint_config(self):
"""
Handler for the SageMaker "DeleteEndpointConfig" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpointConfig.html.
"""
config_name = self.request_params["EndpointConfigName"]
self.sagemaker_backe... |
Handler for the SageMaker "DeleteEndpointConfig" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpointConfig.html.
| delete_endpoint_config | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_endpoint(self):
"""
Handler for the SageMaker "CreateEndpoint" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html.
"""
endpoint_name = self.request_params["EndpointName"]
endpoint_config_name = self.request_params[... |
Handler for the SageMaker "CreateEndpoint" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html.
| create_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def update_endpoint(self):
"""
Handler for the SageMaker "UpdateEndpoint" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_UpdateEndpoint.html.
"""
endpoint_name = self.request_params["EndpointName"]
new_config_name = self.request_params["Endp... |
Handler for the SageMaker "UpdateEndpoint" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_UpdateEndpoint.html.
| update_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def delete_endpoint(self):
"""
Handler for the SageMaker "DeleteEndpoint" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpoint.html.
"""
endpoint_name = self.request_params["EndpointName"]
self.sagemaker_backend.delete_endpoint(endp... |
Handler for the SageMaker "DeleteEndpoint" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpoint.html.
| delete_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_endpoints(self):
"""
Handler for the SageMaker "ListEndpoints" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpoints.html.
This function does not support pagination. All endpoint configs are returned in a
single response.
""... |
Handler for the SageMaker "ListEndpoints" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpoints.html.
This function does not support pagination. All endpoint configs are returned in a
single response.
| list_endpoints | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_endpoint_configs(self):
"""
Handler for the SageMaker "ListEndpointConfigs" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpointConfigs.html.
This function does not support pagination. All endpoint configs are returned in a
single r... |
Handler for the SageMaker "ListEndpointConfigs" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpointConfigs.html.
This function does not support pagination. All endpoint configs are returned in a
single response.
| list_endpoint_configs | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_models(self):
"""
Handler for the SageMaker "ListModels" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListModels.html.
This function does not support pagination. All endpoint configs are returned in a
single response.
"""
... |
Handler for the SageMaker "ListModels" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListModels.html.
This function does not support pagination. All endpoint configs are returned in a
single response.
| list_models | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_model(self):
"""
Handler for the SageMaker "CreateModel" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateModel.html.
"""
model_name = self.request_params["ModelName"]
primary_container = self.request_params["PrimaryContainer"... |
Handler for the SageMaker "CreateModel" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateModel.html.
| create_model | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def describe_model(self):
"""
Handler for the SageMaker "DescribeModel" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeModel.html.
"""
model_name = self.request_params["ModelName"]
model_description = self.sagemaker_backend.describe_... |
Handler for the SageMaker "DescribeModel" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeModel.html.
| describe_model | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def delete_model(self):
"""
Handler for the SageMaker "DeleteModel" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteModel.html.
"""
model_name = self.request_params["ModelName"]
self.sagemaker_backend.delete_model(model_name)
re... |
Handler for the SageMaker "DeleteModel" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteModel.html.
| delete_model | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_tags(self):
"""
Handler for the SageMaker "ListTags" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTags.html
"""
arn = self.request_params["ResourceArn"]
sagemaker_resource = (
"models" if "model" in arn e... |
Handler for the SageMaker "ListTags" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTags.html
| list_tags | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_transform_job(self):
"""
Handler for the SageMaker "CreateTransformJob" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html.
"""
job_name = self.request_params["TransformJobName"]
model_name = self.req... |
Handler for the SageMaker "CreateTransformJob" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html.
| create_transform_job | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def stop_transform_job(self):
"""
Handler for the SageMaker "StopTransformJob" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StopTransformJob.html.
"""
job_name = self.request_params["TransformJobName"]
self.sagemaker_backend.stop... |
Handler for the SageMaker "StopTransformJob" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StopTransformJob.html.
| stop_transform_job | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def describe_transform_job(self):
"""
Handler for the SageMaker "DescribeTransformJob" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTransformJob.html.
"""
job_name = self.request_params["TransformJobName"]
transform_job_d... |
Handler for the SageMaker "DescribeTransformJob" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTransformJob.html.
| describe_transform_job | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_transform_jobs(self):
"""
Handler for the SageMaker "ListTransformJobs" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTransformJobs.html.
This function does not support pagination. All transform jobs are returned in a
single... |
Handler for the SageMaker "ListTransformJobs" API call documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTransformJobs.html.
This function does not support pagination. All transform jobs are returned in a
single response.
| list_transform_jobs | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def _url_module(self):
"""
Required override from the Moto "BaseBackend" object that reroutes requests from the
specified SageMaker URLs to the mocked SageMaker backend.
"""
urls_module_name = "tests.sagemaker.mock.mock_sagemaker_urls"
return __import__(urls_module_name, ... |
Required override from the Moto "BaseBackend" object that reroutes requests from the
specified SageMaker URLs to the mocked SageMaker backend.
| _url_module | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def _get_base_arn(self, region_name):
"""
Returns:
A SageMaker ARN prefix that can be prepended to a resource name.
"""
return SageMakerBackend.BASE_SAGEMAKER_ARN.format(
region_name=region_name, account_id=DEFAULT_ACCOUNT_ID
) |
Returns:
A SageMaker ARN prefix that can be prepended to a resource name.
| _get_base_arn | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_endpoint_config(
self, config_name, production_variants, tags, region_name, async_inference_config
):
"""
Modifies backend state during calls to the SageMaker "CreateEndpointConfig" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndp... |
Modifies backend state during calls to the SageMaker "CreateEndpointConfig" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpointConfig.html.
| create_endpoint_config | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def describe_endpoint_config(self, config_name):
"""
Modifies backend state during calls to the SageMaker "DescribeEndpointConfig" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeEndpointConfig.html.
"""
if config_name not in self.endpoint... |
Modifies backend state during calls to the SageMaker "DescribeEndpointConfig" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeEndpointConfig.html.
| describe_endpoint_config | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def delete_endpoint_config(self, config_name):
"""
Modifies backend state during calls to the SageMaker "DeleteEndpointConfig" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpointConfig.html.
"""
if config_name not in self.endpoint_confi... |
Modifies backend state during calls to the SageMaker "DeleteEndpointConfig" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpointConfig.html.
| delete_endpoint_config | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_endpoint(self, endpoint_name, endpoint_config_name, tags, region_name):
"""
Modifies backend state during calls to the SageMaker "CreateEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html.
"""
if endpoint_name ... |
Modifies backend state during calls to the SageMaker "CreateEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html.
| create_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def describe_endpoint(self, endpoint_name):
"""
Modifies backend state during calls to the SageMaker "DescribeEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeEndpoint.html.
"""
if endpoint_name not in self.endpoints:
... |
Modifies backend state during calls to the SageMaker "DescribeEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeEndpoint.html.
| describe_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def update_endpoint(self, endpoint_name, new_config_name):
"""
Modifies backend state during calls to the SageMaker "UpdateEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_UpdateEndpoint.html.
"""
if endpoint_name not in self.endpoints:
... |
Modifies backend state during calls to the SageMaker "UpdateEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_UpdateEndpoint.html.
| update_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def delete_endpoint(self, endpoint_name):
"""
Modifies backend state during calls to the SageMaker "DeleteEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpoint.html.
"""
if endpoint_name not in self.endpoints:
raise ... |
Modifies backend state during calls to the SageMaker "DeleteEndpoint" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteEndpoint.html.
| delete_endpoint | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_endpoints(self):
"""
Modifies backend state during calls to the SageMaker "ListEndpoints" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpoints.html.
"""
summaries = []
for _, endpoint in self.endpoints.items():
... |
Modifies backend state during calls to the SageMaker "ListEndpoints" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpoints.html.
| list_endpoints | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_endpoint_configs(self):
"""
Modifies backend state during calls to the SageMaker "ListEndpointConfigs" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpointConfigs.html.
"""
summaries = []
for _, endpoint_config in self.end... |
Modifies backend state during calls to the SageMaker "ListEndpointConfigs" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListEndpointConfigs.html.
| list_endpoint_configs | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_models(self):
"""
Modifies backend state during calls to the SageMaker "ListModels" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListModels.html.
"""
summaries = []
for _, model in self.models.items():
summary = Mod... |
Modifies backend state during calls to the SageMaker "ListModels" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_ListModels.html.
| list_models | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_tags(self, resource_arn, region_name, resource_type):
"""
Modifies backend state during calls to the SageMaker "ListTags" API
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTags.html
"""
resource_values = getattr(self, resource_type).values()
f... |
Modifies backend state during calls to the SageMaker "ListTags" API
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTags.html
| list_tags | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_model(
self, model_name, primary_container, execution_role_arn, tags, region_name, vpc_config=None
):
"""
Modifies backend state during calls to the SageMaker "CreateModel" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateModel.html.
... |
Modifies backend state during calls to the SageMaker "CreateModel" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateModel.html.
| create_model | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def describe_model(self, model_name):
"""
Modifies backend state during calls to the SageMaker "DescribeModel" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeModel.html.
"""
if model_name not in self.models:
raise ValueError(
... |
Modifies backend state during calls to the SageMaker "DescribeModel" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeModel.html.
| describe_model | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def delete_model(self, model_name):
"""
Modifies backend state during calls to the SageMaker "DeleteModel" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteModel.html.
"""
if model_name not in self.models:
raise ValueError(
... |
Modifies backend state during calls to the SageMaker "DeleteModel" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/dg/API_DeleteModel.html.
| delete_model | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def create_transform_job(
self,
job_name,
model_name,
transform_input,
transform_output,
transform_resources,
data_processing,
tags,
region_name,
):
"""
Modifies backend state during calls to the SageMaker "CreateTransformJob" A... |
Modifies backend state during calls to the SageMaker "CreateTransformJob" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html.
| create_transform_job | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def describe_transform_job(self, job_name):
"""
Modifies backend state during calls to the SageMaker "DescribeTransformJob" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTransformJob.html.
"""
if job_name not in self.transform_... |
Modifies backend state during calls to the SageMaker "DescribeTransformJob" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTransformJob.html.
| describe_transform_job | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def stop_transform_job(self, job_name):
"""
Modifies backend state during calls to the SageMaker "StopTransformJob" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StopTransformJob.html.
"""
if job_name not in self.transform_jobs:
... |
Modifies backend state during calls to the SageMaker "StopTransformJob" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StopTransformJob.html.
| stop_transform_job | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def list_transform_jobs(self):
"""
Modifies backend state during calls to the SageMaker "ListTransformJobs" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTransformJobs.html.
"""
summaries = []
for _, transform_job in self.t... |
Modifies backend state during calls to the SageMaker "ListTransformJobs" API
documented here:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTransformJobs.html.
| list_transform_jobs | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def __init__(self, endpoint_name, config_name, tags, latest_operation):
"""
Args:
endpoint_name: The name of the Endpoint.
config_name: The name of the EndpointConfiguration to associate with the Endpoint.
tags: Arbitrary tags to associate with the endpoint.
... |
Args:
endpoint_name: The name of the Endpoint.
config_name: The name of the EndpointConfiguration to associate with the Endpoint.
tags: Arbitrary tags to associate with the endpoint.
latest_operation: The most recent operation that was invoked on the endpoint,
... | __init__ | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def __init__(
self,
job_name,
model_name,
transform_input,
transform_output,
transform_resources,
data_processing,
tags,
latest_operation,
):
"""
Args:
job_name: The name of the TransformJob.
model_name: ... |
Args:
job_name: The name of the TransformJob.
model_name: The name of the model to associate with the TransformJob.
transform_input: The input data source and the way transform job consumes it.
transform_output: The output results of the transform job.
... | __init__ | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def __init__(self, latency_seconds, pending_status, completed_status):
"""
Args:
latency_seconds: The latency of the operation, in seconds. Before the time window
specified by this latency elapses, the operation will have the status specified by
``pending_stat... |
Args:
latency_seconds: The latency of the operation, in seconds. Before the time window
specified by this latency elapses, the operation will have the status specified by
``pending_status``. After the time window elapses, the operation will
have the s... | __init__ | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def __init__(self, latency_seconds, pending_status, completed_status):
"""
Args:
latency_seconds: The latency of the operation, in seconds. Before the time window
specified by this latency elapses, the operation will have the status
specified by ``pending_stat... |
Args:
latency_seconds: The latency of the operation, in seconds. Before the time window
specified by this latency elapses, the operation will have the status
specified by ``pending_status``. After the time window elapses, the
operation will have the s... | __init__ | python | mlflow/mlflow | tests/sagemaker/mock/__init__.py | https://github.com/mlflow/mlflow/blob/master/tests/sagemaker/mock/__init__.py | Apache-2.0 |
def test_search_runs_default_view_type(mock_get_request_message, mock_tracking_store):
"""
Search Runs default view type is filled in as ViewType.ACTIVE_ONLY
"""
mock_get_request_message.return_value = SearchRuns(experiment_ids=["0"])
mock_tracking_store.search_runs.return_value = PagedList([], None... |
Search Runs default view type is filled in as ViewType.ACTIVE_ONLY
| test_search_runs_default_view_type | python | mlflow/mlflow | tests/server/test_handlers.py | https://github.com/mlflow/mlflow/blob/master/tests/server/test_handlers.py | Apache-2.0 |
def test_search_experiments(client, monkeypatch):
"""
Use user1 to create 10 experiments,
grant READ permission to user2 on experiments [0, 3, 4, 5, 6, 8].
Test whether user2 can search only and all the readable experiments,
both paged and un-paged.
"""
username1, password1 = create_user(cli... |
Use user1 to create 10 experiments,
grant READ permission to user2 on experiments [0, 3, 4, 5, 6, 8].
Test whether user2 can search only and all the readable experiments,
both paged and un-paged.
| test_search_experiments | python | mlflow/mlflow | tests/server/auth/test_auth.py | https://github.com/mlflow/mlflow/blob/master/tests/server/auth/test_auth.py | Apache-2.0 |
def test_search_registered_models(client, monkeypatch):
"""
Use user1 to create 10 registered_models,
grant READ permission to user2 on registered_models [0, 3, 4, 5, 6, 8].
Test whether user2 can search only and all the readable registered_models,
both paged and un-paged.
"""
username1, pas... |
Use user1 to create 10 registered_models,
grant READ permission to user2 on registered_models [0, 3, 4, 5, 6, 8].
Test whether user2 can search only and all the readable registered_models,
both paged and un-paged.
| test_search_registered_models | python | mlflow/mlflow | tests/server/auth/test_auth.py | https://github.com/mlflow/mlflow/blob/master/tests/server/auth/test_auth.py | Apache-2.0 |
def test_sklearn_log_explainer():
"""
Tests mlflow.shap log_explainer with mlflow serialization of the underlying model
"""
with mlflow.start_run() as run:
run_id = run.info.run_id
X, y = get_housing_data()
model = sklearn.ensemble.RandomForestRegressor(n_estimators=100)
... |
Tests mlflow.shap log_explainer with mlflow serialization of the underlying model
| test_sklearn_log_explainer | python | mlflow/mlflow | tests/shap/test_log.py | https://github.com/mlflow/mlflow/blob/master/tests/shap/test_log.py | Apache-2.0 |
def test_sklearn_log_explainer_self_serialization():
"""
Tests mlflow.shap log_explainer with SHAP internal serialization of the underlying model
"""
with mlflow.start_run() as run:
run_id = run.info.run_id
X, y = get_housing_data()
model = sklearn.ensemble.RandomForestRegress... |
Tests mlflow.shap log_explainer with SHAP internal serialization of the underlying model
| test_sklearn_log_explainer_self_serialization | python | mlflow/mlflow | tests/shap/test_log.py | https://github.com/mlflow/mlflow/blob/master/tests/shap/test_log.py | Apache-2.0 |
def test_sklearn_log_explainer_pyfunc():
"""
Tests mlflow.shap log_explainer with mlflow
serialization of the underlying model using pyfunc flavor
"""
with mlflow.start_run() as run:
run_id = run.info.run_id
X, y = get_housing_data()
model = sklearn.ensemble.RandomForestRe... |
Tests mlflow.shap log_explainer with mlflow
serialization of the underlying model using pyfunc flavor
| test_sklearn_log_explainer_pyfunc | python | mlflow/mlflow | tests/shap/test_log.py | https://github.com/mlflow/mlflow/blob/master/tests/shap/test_log.py | Apache-2.0 |
def yield_artifacts(run_id, path=None):
"""
Yields all artifacts in the specified run.
"""
client = MlflowClient()
for item in client.list_artifacts(run_id, path):
if item.is_dir:
yield from yield_artifacts(run_id, item.path)
else:
yield item.path |
Yields all artifacts in the specified run.
| yield_artifacts | python | mlflow/mlflow | tests/shap/test_shap.py | https://github.com/mlflow/mlflow/blob/master/tests/shap/test_shap.py | Apache-2.0 |
def test_log_explanation_with_small_features():
"""
Verifies that `log_explanation` does not fail even when `features` has less records than
`_MAXIMUM_BACKGROUND_DATA_SIZE`.
"""
num_rows = 50
assert num_rows < mlflow.shap._MAXIMUM_BACKGROUND_DATA_SIZE
X, y = get_diabetes()
X, y = X.iloc... |
Verifies that `log_explanation` does not fail even when `features` has less records than
`_MAXIMUM_BACKGROUND_DATA_SIZE`.
| test_log_explanation_with_small_features | python | mlflow/mlflow | tests/shap/test_shap.py | https://github.com/mlflow/mlflow/blob/master/tests/shap/test_shap.py | Apache-2.0 |
def _get_model_uri(name: str = MODEL_DIR) -> str:
"""
Search for the model with the given name and return its URI.
"""
if uri := next(
m.model_uri for m in mlflow.search_logged_models(output_format="list") if m.name == name
):
return uri
raise ValueError(f"Model with name {name:... |
Search for the model with the given name and return its URI.
| _get_model_uri | python | mlflow/mlflow | tests/sklearn/test_sklearn_autolog.py | https://github.com/mlflow/mlflow/blob/master/tests/sklearn/test_sklearn_autolog.py | Apache-2.0 |
def test_autolog_emits_warning_message_when_metric_fails():
"""
Take precision_score metric from SVC as an example to test metric logging failure
"""
mlflow.sklearn.autolog()
model = sklearn.svm.SVC()
@functools.wraps(sklearn.metrics.precision_score)
def throwing_metrics(y_true, y_pred):
... |
Take precision_score metric from SVC as an example to test metric logging failure
| test_autolog_emits_warning_message_when_metric_fails | python | mlflow/mlflow | tests/sklearn/test_sklearn_autolog.py | https://github.com/mlflow/mlflow/blob/master/tests/sklearn/test_sklearn_autolog.py | Apache-2.0 |
def test_autolog_emits_warning_message_when_model_prediction_fails():
"""
Take GridSearchCV as an example, whose base class is "classifier" and will go
through classifier's metric logging. When refit=False, the model will never get
refitted, while during the metric logging what ".predict()" expects is a... |
Take GridSearchCV as an example, whose base class is "classifier" and will go
through classifier's metric logging. When refit=False, the model will never get
refitted, while during the metric logging what ".predict()" expects is a fitted model.
Thus, a warning will be logged.
| test_autolog_emits_warning_message_when_model_prediction_fails | python | mlflow/mlflow | tests/sklearn/test_sklearn_autolog.py | https://github.com/mlflow/mlflow/blob/master/tests/sklearn/test_sklearn_autolog.py | Apache-2.0 |
def test_autolog_does_not_capture_runs_for_preprocessing_or_feature_manipulation_estimators():
"""
Verifies that preprocessing and feature manipulation estimators, which represent data
manipulation steps (e.g., normalization, label encoding) rather than ML models, do not
produce runs when their fit_* op... |
Verifies that preprocessing and feature manipulation estimators, which represent data
manipulation steps (e.g., normalization, label encoding) rather than ML models, do not
produce runs when their fit_* operations are invoked independently of an ML pipeline
| test_autolog_does_not_capture_runs_for_preprocessing_or_feature_manipulation_estimators | python | mlflow/mlflow | tests/sklearn/test_sklearn_autolog.py | https://github.com/mlflow/mlflow/blob/master/tests/sklearn/test_sklearn_autolog.py | Apache-2.0 |
def test_autolog_produces_expected_results_for_estimator_when_parent_also_defines_fit():
"""
Test to prevent recurrences of https://github.com/mlflow/mlflow/issues/3574
"""
mlflow.sklearn.autolog()
# Construct two mock models - `ParentMod` and `ChildMod`, where ChildMod's fit() function
# calls... |
Test to prevent recurrences of https://github.com/mlflow/mlflow/issues/3574
| test_autolog_produces_expected_results_for_estimator_when_parent_also_defines_fit | python | mlflow/mlflow | tests/sklearn/test_sklearn_autolog.py | https://github.com/mlflow/mlflow/blob/master/tests/sklearn/test_sklearn_autolog.py | Apache-2.0 |
def test_metric_computation_handles_absent_labels():
"""
Verifies that autologging metric computation does not fail For models that do not require
labels as inputs to training, such as clustering models and other unsupervised techniques.
"""
mlflow.sklearn.autolog()
model = sklearn.cluster.KMea... |
Verifies that autologging metric computation does not fail For models that do not require
labels as inputs to training, such as clustering models and other unsupervised techniques.
| test_metric_computation_handles_absent_labels | python | mlflow/mlflow | tests/sklearn/test_sklearn_autolog.py | https://github.com/mlflow/mlflow/blob/master/tests/sklearn/test_sklearn_autolog.py | Apache-2.0 |
def assert_tag_value_meets_requirements(run_id):
"""
Verify that the Spark Datasource tag set on the run has been truncated to the maximum
tag value length allowed by MLflow
"""
run = mlflow.get_run(run_id)
assert _SPARK_TABLE_INFO_TAG_NAME in run.data.tags
table_... |
Verify that the Spark Datasource tag set on the run has been truncated to the maximum
tag value length allowed by MLflow
| assert_tag_value_meets_requirements | python | mlflow/mlflow | tests/spark/autologging/datasource/test_spark_datasource_autologging.py | https://github.com/mlflow/mlflow/blob/master/tests/spark/autologging/datasource/test_spark_datasource_autologging.py | Apache-2.0 |
def test_download_artifacts_awaits_download_completion(base_uri, download_arg, list_return_val):
"""
Verifies that all asynchronous artifact downloads are joined before `download_artifacts()`
returns a result to the caller
"""
def list_artifacts(path):
fullpath = posixpath.join(base_uri, pa... |
Verifies that all asynchronous artifact downloads are joined before `download_artifacts()`
returns a result to the caller
| test_download_artifacts_awaits_download_completion | python | mlflow/mlflow | tests/store/artifact/test_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_artifact_repo.py | Apache-2.0 |
def get_mock_listing(*args, **kwargs):
"""
Produces a mock listing that only contains content if the
specified prefix is the artifact root. This allows us to mock
`list_artifacts` during the `_download_artifacts_into` subroutine
without recursively listing the same artifacts at e... |
Produces a mock listing that only contains content if the
specified prefix is the artifact root. This allows us to mock
`list_artifacts` during the `_download_artifacts_into` subroutine
without recursively listing the same artifacts at every level of the
directory traversal.
... | get_mock_listing | python | mlflow/mlflow | tests/store/artifact/test_azure_blob_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_azure_blob_artifact_repo.py | Apache-2.0 |
def get_mock_listing(*args, **kwargs):
"""
Produces a mock listing that only contains content if the specified prefix is the artifact
root or a relevant subdirectory. This allows us to mock `list_artifacts` during the
`_download_artifacts_into` subroutine without recursively listing the ... |
Produces a mock listing that only contains content if the specified prefix is the artifact
root or a relevant subdirectory. This allows us to mock `list_artifacts` during the
`_download_artifacts_into` subroutine without recursively listing the same artifacts at
every level of the direc... | get_mock_listing | python | mlflow/mlflow | tests/store/artifact/test_azure_blob_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_azure_blob_artifact_repo.py | Apache-2.0 |
def _run_download_artifact_command(args) -> pathlib.Path: # noqa: D417
"""
Args:
command: An `mlflow artifacts` command list.
Returns:
Path to the downloaded artifact.
"""
runner = CliRunner()
resp = runner.invoke(download_artifacts, args=args, catch_exceptions=False)
asser... |
Args:
command: An `mlflow artifacts` command list.
Returns:
Path to the downloaded artifact.
| _run_download_artifact_command | python | mlflow/mlflow | tests/store/artifact/test_cli.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_cli.py | Apache-2.0 |
def test_get_read_credential_infos_handles_pagination(databricks_artifact_repo):
"""
Verifies that the `get_read_credential_infos` method, which is used to resolve read access
credentials for a collection of artifacts, handles paginated responses properly, issuing
incremental requests until all pages ha... |
Verifies that the `get_read_credential_infos` method, which is used to resolve read access
credentials for a collection of artifacts, handles paginated responses properly, issuing
incremental requests until all pages have been consumed
| test_get_read_credential_infos_handles_pagination | python | mlflow/mlflow | tests/store/artifact/test_databricks_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_databricks_artifact_repo.py | Apache-2.0 |
def test_get_read_credential_infos_respects_max_request_size(databricks_artifact_repo):
"""
Verifies that the `_get_read_credential_infos` method, which is used to resolve read access
credentials for a collection of artifacts, handles paginated responses properly, issuing
incremental requests until all ... |
Verifies that the `_get_read_credential_infos` method, which is used to resolve read access
credentials for a collection of artifacts, handles paginated responses properly, issuing
incremental requests until all pages have been consumed
| test_get_read_credential_infos_respects_max_request_size | python | mlflow/mlflow | tests/store/artifact/test_databricks_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_databricks_artifact_repo.py | Apache-2.0 |
def test_get_write_credential_infos_handles_pagination(databricks_artifact_repo):
"""
Verifies that the `_get_write_credential_infos` method, which is used to resolve write
access credentials for a collection of artifacts, handles paginated responses properly,
issuing incremental requests until all page... |
Verifies that the `_get_write_credential_infos` method, which is used to resolve write
access credentials for a collection of artifacts, handles paginated responses properly,
issuing incremental requests until all pages have been consumed
| test_get_write_credential_infos_handles_pagination | python | mlflow/mlflow | tests/store/artifact/test_databricks_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_databricks_artifact_repo.py | Apache-2.0 |
def test_get_write_credential_infos_respects_max_request_size(databricks_artifact_repo):
"""
Verifies that the `_get_write_credential_infos` method, which is used to resolve write
access credentials for a collection of artifacts, batches requests according to a maximum
request size configured by the bac... |
Verifies that the `_get_write_credential_infos` method, which is used to resolve write
access credentials for a collection of artifacts, batches requests according to a maximum
request size configured by the backend
| test_get_write_credential_infos_respects_max_request_size | python | mlflow/mlflow | tests/store/artifact/test_databricks_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_databricks_artifact_repo.py | Apache-2.0 |
def test_artifact_logging(databricks_artifact_repo, tmp_path):
"""
Verifies that `log_artifact()` and `log_artifacts()` initiate all expected asynchronous
artifact uploads and await their completion before returning results to the caller
"""
src_dir = tmp_path.joinpath("src")
src_dir.mkdir()
... |
Verifies that `log_artifact()` and `log_artifacts()` initiate all expected asynchronous
artifact uploads and await their completion before returning results to the caller
| test_artifact_logging | python | mlflow/mlflow | tests/store/artifact/test_databricks_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_databricks_artifact_repo.py | Apache-2.0 |
def test_artifact_logging_chunks_upload_list(databricks_artifact_repo, tmp_path):
"""
Verifies that write credentials are fetched in chunks rather than all at once.
"""
src_dir = tmp_path.joinpath("src")
src_dir.mkdir()
for i in range(10):
src_dir.joinpath(f"file_{i}.txt").write_text(f"f... |
Verifies that write credentials are fetched in chunks rather than all at once.
| test_artifact_logging_chunks_upload_list | python | mlflow/mlflow | tests/store/artifact/test_databricks_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_databricks_artifact_repo.py | Apache-2.0 |
def test_download_artifacts_does_not_copy(local_artifact_repo):
"""
The LocalArtifactRepository.download_artifact function should not copy the artifact if
the ``dst_path`` argument is None.
"""
artifact_rel_path = "test.txt"
artifact_text = "hello world!"
with TempDir(chdr=True) as local_dir... |
The LocalArtifactRepository.download_artifact function should not copy the artifact if
the ``dst_path`` argument is None.
| test_download_artifacts_does_not_copy | python | mlflow/mlflow | tests/store/artifact/test_local_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_local_artifact_repo.py | Apache-2.0 |
def test_models_artifact_repo_uses_repo_download_artifacts(tmp_path):
"""
`ModelsArtifactRepository` should delegate `download_artifacts` to its
`self.repo.download_artifacts` function.
"""
artifact_location = "s3://blah_bucket/"
dummy_file = tmp_path / "dummy_file.txt"
dummy_file.touch()
... |
`ModelsArtifactRepository` should delegate `download_artifacts` to its
`self.repo.download_artifacts` function.
| test_models_artifact_repo_uses_repo_download_artifacts | python | mlflow/mlflow | tests/store/artifact/test_models_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_models_artifact_repo.py | Apache-2.0 |
def test_runs_artifact_repo_uses_repo_download_artifacts():
"""
The RunsArtifactRepo should delegate `download_artifacts` to it's self.repo.download_artifacts
function
"""
artifact_location = "s3://blah_bucket/"
experiment_id = mlflow.create_experiment("expr_abcd", artifact_location)
with ml... |
The RunsArtifactRepo should delegate `download_artifacts` to it's self.repo.download_artifacts
function
| test_runs_artifact_repo_uses_repo_download_artifacts | python | mlflow/mlflow | tests/store/artifact/test_runs_artifact_repo.py | https://github.com/mlflow/mlflow/blob/master/tests/store/artifact/test_runs_artifact_repo.py | Apache-2.0 |
def test_mysql_ssl_params(monkeypatch):
"""Test that MySQL SSL certificate params are correctly passed to create_engine."""
monkeypatch.setenv("MLFLOW_MYSQL_SSL_CA", "/path/to/ca.pem")
monkeypatch.setenv("MLFLOW_MYSQL_SSL_CERT", "/path/to/cert.pem")
monkeypatch.setenv("MLFLOW_MYSQL_SSL_KEY", "/path/to/k... | Test that MySQL SSL certificate params are correctly passed to create_engine. | test_mysql_ssl_params | python | mlflow/mlflow | tests/store/db/test_utils.py | https://github.com/mlflow/mlflow/blob/master/tests/store/db/test_utils.py | Apache-2.0 |
def test_mysql_ssl_params_partial(monkeypatch):
"""Test that MySQL SSL certificate params work with only CA certificate."""
monkeypatch.setenv("MLFLOW_MYSQL_SSL_CA", "/path/to/ca.pem")
monkeypatch.delenv("MLFLOW_MYSQL_SSL_CERT", raising=False)
monkeypatch.delenv("MLFLOW_MYSQL_SSL_KEY", raising=False)
... | Test that MySQL SSL certificate params work with only CA certificate. | test_mysql_ssl_params_partial | python | mlflow/mlflow | tests/store/db/test_utils.py | https://github.com/mlflow/mlflow/blob/master/tests/store/db/test_utils.py | Apache-2.0 |
def test_non_mysql_no_ssl_params(monkeypatch):
"""Test that non-MySQL connections don't get SSL params."""
monkeypatch.setenv("MLFLOW_MYSQL_SSL_CA", "/path/to/ca.pem")
monkeypatch.setenv("MLFLOW_MYSQL_SSL_CERT", "/path/to/cert.pem")
monkeypatch.setenv("MLFLOW_MYSQL_SSL_KEY", "/path/to/key.pem")
monk... | Test that non-MySQL connections don't get SSL params. | test_non_mysql_no_ssl_params | python | mlflow/mlflow | tests/store/db/test_utils.py | https://github.com/mlflow/mlflow/blob/master/tests/store/db/test_utils.py | Apache-2.0 |
def set_model_version_tag(self, name: str, version: int, tag: ModelVersionTag):
"""Mock implementation to set model version tags."""
mv = self.get_model_version(name, version)
if isinstance(mv.tags, dict):
mv.tags[tag.key] = tag.value
else:
# Convert to dict if it... | Mock implementation to set model version tags. | set_model_version_tag | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def add_prompt_version(self, name: str, version: str):
"""Helper method to add prompt versions for testing."""
# Convert version to integer for PromptVersion
version_int = int(version[1:]) if version.startswith("v") else int(version)
# Store using both formats to handle version lookups
... | Helper method to add prompt versions for testing. | add_prompt_version | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_success(store, mock_tracking_store):
"""Test successful linking of prompt version to model."""
# Setup
store.add_prompt_version("test_prompt", "1")
model_id = "model_123"
# Mock logged model with no existing linked prompts
logged_model = LoggedModel(
... | Test successful linking of prompt version to model. | test_link_prompt_version_to_model_success | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_append_to_existing(store, mock_tracking_store):
"""Test linking prompt version when other prompts are already linked."""
# Setup
store.add_prompt_version("test_prompt", "1")
model_id = "model_123"
existing_prompts = [{"name": "existing_prompt", "version": "v1"}... | Test linking prompt version when other prompts are already linked. | test_link_prompt_version_to_model_append_to_existing | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_no_model_found(store, mock_tracking_store):
"""Test error when model is not found."""
# Setup
store.add_prompt_version("test_prompt", "1")
mock_tracking_store.get_logged_model.return_value = None
# Execute & Verify
with pytest.raises(MlflowException, match=... | Test error when model is not found. | test_link_prompt_version_to_model_no_model_found | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_prompt_not_found(store, mock_tracking_store):
"""Test error when prompt version is not found."""
# Setup
model_id = "model_123"
logged_model = LoggedModel(
experiment_id="exp_123",
model_id=model_id,
name="test_model",
artifact_locati... | Test error when prompt version is not found. | test_link_prompt_version_to_model_prompt_not_found | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_invalid_json_tag(store, mock_tracking_store):
"""Test error when existing linked prompts tag has invalid JSON."""
# Setup
store.add_prompt_version("test_prompt", "1")
model_id = "model_123"
logged_model = LoggedModel(
experiment_id="exp_123",
mo... | Test error when existing linked prompts tag has invalid JSON. | test_link_prompt_version_to_model_invalid_json_tag | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_invalid_format_tag(store, mock_tracking_store):
"""Test error when existing linked prompts tag has invalid format (not a list)."""
# Setup
store.add_prompt_version("test_prompt", "1")
model_id = "model_123"
logged_model = LoggedModel(
experiment_id="exp... | Test error when existing linked prompts tag has invalid format (not a list). | test_link_prompt_version_to_model_invalid_format_tag | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_duplicate_prevention(store, mock_tracking_store):
"""Test that linking the same prompt version twice doesn't create duplicates."""
# Setup
store.add_prompt_version("test_prompt", "1")
model_id = "model_123"
# Create a logged model that will be updated by the mo... | Test that linking the same prompt version twice doesn't create duplicates. | test_link_prompt_version_to_model_duplicate_prevention | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_model_thread_safety(store, mock_tracking_store):
"""Test thread safety of linking prompt versions to models."""
# Setup
store.add_prompt_version("test_prompt_1", "1")
store.add_prompt_version("test_prompt_2", "1")
model_id = "model_123"
# Create a shared logged m... | Test thread safety of linking prompt versions to models. | test_link_prompt_version_to_model_thread_safety | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_success(store, mock_tracking_store):
"""Test successful linking of prompt versions to a trace."""
# Setup
store.add_prompt_version("test_prompt", "1")
trace_id = "trace_123"
# Mock trace info
mock_trace_info = mock.Mock()
mock_trace_info.tags = {}
mock_tr... | Test successful linking of prompt versions to a trace. | test_link_prompts_to_trace_success | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_append_to_existing(store, mock_tracking_store):
"""Test linking prompt versions when other prompts are already linked to the trace."""
# Setup
store.add_prompt_version("test_prompt", "1")
trace_id = "trace_123"
existing_prompts = [{"name": "existing_prompt", "version"... | Test linking prompt versions when other prompts are already linked to the trace. | test_link_prompts_to_trace_append_to_existing | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_nonexistent_trace(store, mock_tracking_store):
"""Test error handling when trace is not found."""
# Setup
store.add_prompt_version("test_prompt", "1")
mock_tracking_store.get_trace_info.return_value = None
# Execute & Verify
prompt_version = store.get_prompt_versi... | Test error handling when trace is not found. | test_link_prompts_to_trace_nonexistent_trace | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_multiple_prompts(store, mock_tracking_store):
"""Test linking multiple prompt versions to a trace at once."""
# Setup
store.add_prompt_version("test_prompt_1", "v1")
store.add_prompt_version("test_prompt_2", "v2")
trace_id = "trace_123"
mock_trace_info = mock.Mock... | Test linking multiple prompt versions to a trace at once. | test_link_prompts_to_trace_multiple_prompts | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_thread_safety(store, mock_tracking_store):
"""Test thread safety of linking prompt versions to traces."""
# Setup
store.add_prompt_version("test_prompt_1", "1")
store.add_prompt_version("test_prompt_2", "1")
trace_id = "trace_123"
# Create shared trace info that w... | Test thread safety of linking prompt versions to traces. | test_link_prompts_to_trace_thread_safety | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_no_change_optimization(store, mock_tracking_store):
"""Test that tag is not updated when no change is needed."""
# Setup
store.add_prompt_version("test_prompt", "1")
trace_id = "trace_123"
existing_prompts = [{"name": "test_prompt", "version": "1"}]
mock_trace_inf... | Test that tag is not updated when no change is needed. | test_link_prompts_to_trace_no_change_optimization | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompts_to_trace_unsupported_store(store, mock_tracking_store):
"""Test error handling when tracking store doesn't support get_trace_info."""
# Setup
store.add_prompt_version("test_prompt", "1")
# Mock tracking store that doesn't have get_trace_info method
del mock_tracking_store.get_t... | Test error handling when tracking store doesn't support get_trace_info. | test_link_prompts_to_trace_unsupported_store | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_run_success(store, mock_tracking_store):
"""Test successful linking of prompt version to run."""
# Setup
store.add_prompt_version("test_prompt", "1")
run_id = "run_123"
# Mock run with no existing linked prompts
run_data = RunData(metrics=[], params=[], tags={})
... | Test successful linking of prompt version to run. | test_link_prompt_version_to_run_success | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_run_append_to_existing(store, mock_tracking_store):
"""Test linking prompt version when other prompts are already linked to the run."""
# Setup
store.add_prompt_version("test_prompt_1", "1")
store.add_prompt_version("test_prompt_2", "1")
run_id = "run_123"
# Mock... | Test linking prompt version when other prompts are already linked to the run. | test_link_prompt_version_to_run_append_to_existing | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_run_no_run_found(store, mock_tracking_store):
"""Test error when run is not found."""
# Setup
store.add_prompt_version("test_prompt", "1") # Use "1" instead of "v1"
run_id = "nonexistent_run"
mock_tracking_store.get_run.return_value = None
# Execute and verify ... | Test error when run is not found. | test_link_prompt_version_to_run_no_run_found | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_run_duplicate_prevention(store, mock_tracking_store):
"""Test that duplicate prompt linkings are prevented."""
# Setup
store.add_prompt_version("test_prompt", "1")
run_id = "run_123"
# Mock run with existing prompt already linked
existing_prompts = [{"name": "tes... | Test that duplicate prompt linkings are prevented. | test_link_prompt_version_to_run_duplicate_prevention | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_link_prompt_version_to_run_thread_safety(store, mock_tracking_store):
"""Test thread safety of linking prompt versions to runs."""
# Setup
store.add_prompt_version("test_prompt_1", "1")
store.add_prompt_version("test_prompt_2", "1")
run_id = "run_123"
# Create a shared run that will be... | Test thread safety of linking prompt versions to runs. | test_link_prompt_version_to_run_thread_safety | python | mlflow/mlflow | tests/store/model_registry/test_abstract_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/model_registry/test_abstract_store.py | Apache-2.0 |
def test_get_deleted_run(store):
"""
Getting metrics/tags/params/run info should be allowed on deleted runs.
"""
experiments, exp_data, _ = _create_root(store)
exp_id = experiments[random_int(0, len(experiments) - 1)]
run_id = exp_data[exp_id]["runs"][0]
store.delete_run(run_id)
assert s... |
Getting metrics/tags/params/run info should be allowed on deleted runs.
| test_get_deleted_run | python | mlflow/mlflow | tests/store/tracking/test_file_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_file_store.py | Apache-2.0 |
def test_set_deleted_run(store):
"""
Setting metrics/tags/params/updating run info should not be allowed on deleted runs.
"""
experiments, exp_data, _ = _create_root(store)
exp_id = experiments[random_int(0, len(experiments) - 1)]
run_id = exp_data[exp_id]["runs"][0]
store.delete_run(run_id)... |
Setting metrics/tags/params/updating run info should not be allowed on deleted runs.
| test_set_deleted_run | python | mlflow/mlflow | tests/store/tracking/test_file_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_file_store.py | Apache-2.0 |
def test_log_inputs_uses_expected_input_and_dataset_ids_for_storage(store):
"""
This test verifies that the FileStore uses expected IDs as folder names to represent datasets
and run inputs. This is very important because the IDs are used to deduplicate inputs and
datasets if the same dataset is logged t... |
This test verifies that the FileStore uses expected IDs as folder names to represent datasets
and run inputs. This is very important because the IDs are used to deduplicate inputs and
datasets if the same dataset is logged to multiple runs or the same dataset is logged
multiple times as an input to the... | test_log_inputs_uses_expected_input_and_dataset_ids_for_storage | python | mlflow/mlflow | tests/store/tracking/test_file_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_file_store.py | Apache-2.0 |
def _verify_requests(
http_request, host_creds, endpoint, method, json_body, use_v3=False, retry_timeout_seconds=None
):
"""
Verify HTTP requests in tests.
Args:
http_request: The mocked HTTP request object
host_creds: MlflowHostCreds object
endpoint: The endpoint being called (... |
Verify HTTP requests in tests.
Args:
http_request: The mocked HTTP request object
host_creds: MlflowHostCreds object
endpoint: The endpoint being called (e.g., "traces/123")
method: The HTTP method (e.g., "GET", "POST")
json_body: The request body as a JSON string
... | _verify_requests | python | mlflow/mlflow | tests/store/tracking/test_rest_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_rest_store.py | Apache-2.0 |
def test_search_traces():
"""Test the search_traces method with default behavior using SearchTracesV3Request."""
creds = MlflowHostCreds("https://hello")
store = RestStore(lambda: creds)
response = mock.MagicMock()
response.status_code = 200
# Format the response
response.text = json.dumps(... | Test the search_traces method with default behavior using SearchTracesV3Request. | test_search_traces | python | mlflow/mlflow | tests/store/tracking/test_rest_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_rest_store.py | Apache-2.0 |
def test_search_unified_traces():
"""Test the search_traces method when using SearchUnifiedTraces with sql_warehouse_id."""
creds = MlflowHostCreds("https://hello")
store = RestStore(lambda: creds)
response = mock.MagicMock()
response.status_code = 200
# Format the response (using TraceInfo for... | Test the search_traces method when using SearchUnifiedTraces with sql_warehouse_id. | test_search_unified_traces | python | mlflow/mlflow | tests/store/tracking/test_rest_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_rest_store.py | Apache-2.0 |
def test_get_artifact_uri_for_trace_compatibility():
"""Test that get_artifact_uri_for_trace works with both TraceInfo and TraceInfoV3 objects."""
from mlflow.tracing.utils.artifact_utils import get_artifact_uri_for_trace
# Create a TraceInfo (v2) object
trace_info_v2 = TraceInfoV2(
request_id=... | Test that get_artifact_uri_for_trace works with both TraceInfo and TraceInfoV3 objects. | test_get_artifact_uri_for_trace_compatibility | python | mlflow/mlflow | tests/store/tracking/test_rest_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_rest_store.py | Apache-2.0 |
def test_get_trace_info_v3_api():
"""
Test that get_trace_info with should_query_v3=True correctly extracts the trace_info
from the nested structure in the V3 API response.
"""
# Generate a sample trace in v3 format
with mlflow.start_span(name="test_span") as span:
span.set_inputs({"inpu... |
Test that get_trace_info with should_query_v3=True correctly extracts the trace_info
from the nested structure in the V3 API response.
| test_get_trace_info_v3_api | python | mlflow/mlflow | tests/store/tracking/test_rest_store.py | https://github.com/mlflow/mlflow/blob/master/tests/store/tracking/test_rest_store.py | Apache-2.0 |
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