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Required. The Endpoint which replaces the resource on
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the server. Currently we only support updating the
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``client_connection_config`` field, all the other
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fields' update will be blocked.
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This corresponds to the ``endpoint`` field
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on the ``request`` instance; if ``request`` is provided, this
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should not be set.
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retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
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should be retried.
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timeout (float): The timeout for this request.
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metadata (Sequence[Tuple[str, str]]): Strings which should be
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sent along with the request as metadata.
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Returns:
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google.api_core.operation_async.AsyncOperation:
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.aiplatform_v1.types.Endpoint` Models are deployed into it, and afterwards Endpoint is called to obtain
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predictions and explanations.
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"""
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# Create or coerce a protobuf request object.
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# - Quick check: If we got a request object, we should *not* have
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# gotten any keyword arguments that map to the request.
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has_flattened_params=any([endpoint])
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ifrequestisnotNoneandhas_flattened_params:
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raiseValueError(
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"If the `request` argument is set, then none of "
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"the individual field arguments should be set."
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)
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# - Use the request object if provided (there's no risk of modifying the input as
Required. The Endpoint which replaces the resource on
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the server. Currently we only support updating the
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``client_connection_config`` field, all the other
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fields' update will be blocked.
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This corresponds to the ``endpoint`` field
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on the ``request`` instance; if ``request`` is provided, this
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should not be set.
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retry (google.api_core.retry.Retry): Designation of what errors, if any,
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should be retried.
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timeout (float): The timeout for this request.
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metadata (Sequence[Tuple[str, str]]): Strings which should be
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sent along with the request as metadata.
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Returns:
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google.api_core.operation.Operation:
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.aiplatform_v1.types.Endpoint` Models are deployed into it, and afterwards Endpoint is called to obtain
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predictions and explanations.
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"""
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# Create or coerce a protobuf request object.
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# - Quick check: If we got a request object, we should *not* have
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# gotten any keyword arguments that map to the request.
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has_flattened_params=any([endpoint])
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ifrequestisnotNoneandhas_flattened_params:
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raiseValueError(
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"If the `request` argument is set, then none of "
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"the individual field arguments should be set."
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)
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# - Use the request object if provided (there's no risk of modifying the input as
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