예제 #1
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    def _get_output_to_inputs_map(self, output_signature):
        # TODO(b/160550490): Remove local import.
        from tensorflow_transform import graph_tools  # pylint: disable=g-import-not-at-top

        result = {}
        for name, output in six.iteritems(output_signature):
            components = self._get_component_tensors(output)
            sinks = [self._as_operation(component) for component in components]
            result[name] = graph_tools.retrieve_sources(sinks)
        return result
예제 #2
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 def _get_output_to_inputs_map(self, output_signature):
     """Get all graph inputs that the tensors in output_signature depend on."""
     result = {}
     for name, output in six.iteritems(output_signature):
         components = self._get_component_tensors(output)
         sinks = [self._as_operation(component) for component in components]
         # Ignore control dependencies when walking the graph as we only care about
         # which user defined inputs this output depends on.
         result[name] = graph_tools.retrieve_sources(
             sinks, ignore_control_dependencies=True)
     return result
예제 #3
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def _get_output_to_inputs_map(
    output_signature: Mapping[str, common_types.TensorType]
) -> Dict[str, Iterable[tf.Tensor]]:
  """Gets all graph inputs that the tensors in output_signature depend on."""
  result = {}
  for name, output in output_signature.items():
    components = _get_component_tensors(output)
    sinks = [_as_operation(component) for component in components]
    # Ignore control dependencies when walking the graph as we only care about
    # which user defined inputs this output depends on.
    result[name] = graph_tools.retrieve_sources(
        sinks, ignore_control_dependencies=True)
  return result
    def _get_output_to_inputs_map(self, output_signature):
        """Get all graph inputs that the tensors in output_signature depend on."""
        # TODO(b/160550490): Remove local import.
        from tensorflow_transform import graph_tools  # pylint: disable=g-import-not-at-top

        result = {}
        for name, output in six.iteritems(output_signature):
            components = self._get_component_tensors(output)
            sinks = [self._as_operation(component) for component in components]
            # Ignore control dependencies when walking the graph as we only care about
            # which user defined inputs this output depends on.
            result[name] = graph_tools.retrieve_sources(
                sinks, ignore_control_dependencies=True)
        return result