Module pagers (1.9.0)

Version 1.9.0

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API documentation for aiplatform_v1.services.model_service.pagers module.

Classes

ListModelEvaluationSlicesAsyncPager

ListModelEvaluationSlicesAsyncPager(
    method: Callable[
        [...],
        Awaitable[
            google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationSlicesResponse
        ],
    ],
    request: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationSlicesRequest,
    response: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationSlicesResponse,
    *,
    metadata: Sequence[Tuple[str, str]] = ()
)

A pager for iterating through list_model_evaluation_slices requests.

This class thinly wraps an initial ListModelEvaluationSlicesResponse object, and provides an __aiter__ method to iterate through its model_evaluation_slices field.

If there are more pages, the __aiter__ method will make additional ListModelEvaluationSlices requests and continue to iterate through the model_evaluation_slices field on the corresponding responses.

All the usual ListModelEvaluationSlicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

ListModelEvaluationSlicesPager

ListModelEvaluationSlicesPager(
    method: Callable[
        [...],
        google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationSlicesResponse,
    ],
    request: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationSlicesRequest,
    response: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationSlicesResponse,
    *,
    metadata: Sequence[Tuple[str, str]] = ()
)

A pager for iterating through list_model_evaluation_slices requests.

This class thinly wraps an initial ListModelEvaluationSlicesResponse object, and provides an __iter__ method to iterate through its model_evaluation_slices field.

If there are more pages, the __iter__ method will make additional ListModelEvaluationSlices requests and continue to iterate through the model_evaluation_slices field on the corresponding responses.

All the usual ListModelEvaluationSlicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

ListModelEvaluationsAsyncPager

ListModelEvaluationsAsyncPager(
    method: Callable[
        [...],
        Awaitable[
            google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationsResponse
        ],
    ],
    request: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationsRequest,
    response: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationsResponse,
    *,
    metadata: Sequence[Tuple[str, str]] = ()
)

A pager for iterating through list_model_evaluations requests.

This class thinly wraps an initial ListModelEvaluationsResponse object, and provides an __aiter__ method to iterate through its model_evaluations field.

If there are more pages, the __aiter__ method will make additional ListModelEvaluations requests and continue to iterate through the model_evaluations field on the corresponding responses.

All the usual ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

ListModelEvaluationsPager

ListModelEvaluationsPager(
    method: Callable[
        [...],
        google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationsResponse,
    ],
    request: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationsRequest,
    response: google.cloud.aiplatform_v1.types.model_service.ListModelEvaluationsResponse,
    *,
    metadata: Sequence[Tuple[str, str]] = ()
)

A pager for iterating through list_model_evaluations requests.

This class thinly wraps an initial ListModelEvaluationsResponse object, and provides an __iter__ method to iterate through its model_evaluations field.

If there are more pages, the __iter__ method will make additional ListModelEvaluations requests and continue to iterate through the model_evaluations field on the corresponding responses.

All the usual ListModelEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

ListModelsAsyncPager

ListModelsAsyncPager(
    method: Callable[
        [...],
        Awaitable[google.cloud.aiplatform_v1.types.model_service.ListModelsResponse],
    ],
    request: google.cloud.aiplatform_v1.types.model_service.ListModelsRequest,
    response: google.cloud.aiplatform_v1.types.model_service.ListModelsResponse,
    *,
    metadata: Sequence[Tuple[str, str]] = ()
)

A pager for iterating through list_models requests.

This class thinly wraps an initial ListModelsResponse object, and provides an __aiter__ method to iterate through its models field.

If there are more pages, the __aiter__ method will make additional ListModels requests and continue to iterate through the models field on the corresponding responses.

All the usual ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

ListModelsPager

ListModelsPager(
    method: Callable[
        [...], google.cloud.aiplatform_v1.types.model_service.ListModelsResponse
    ],
    request: google.cloud.aiplatform_v1.types.model_service.ListModelsRequest,
    response: google.cloud.aiplatform_v1.types.model_service.ListModelsResponse,
    *,
    metadata: Sequence[Tuple[str, str]] = ()
)

A pager for iterating through list_models requests.

This class thinly wraps an initial ListModelsResponse object, and provides an __iter__ method to iterate through its models field.

If there are more pages, the __iter__ method will make additional ListModels requests and continue to iterate through the models field on the corresponding responses.

All the usual ListModelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.