Beispiel #1
0
def _fill_meta_graph_def(meta_graph_def, obj, signature_functions,
                         object_saver):
    """Generates a MetaGraph which calls `signature_functions`.

  Args:
    meta_graph_def: The MetaGraphDef proto to fill.
    obj: The checkpointable object being exported.
    signature_functions: A dictionary mapping signature keys to concrete
      functions containing signatures to add to the MetaGraph.
    object_saver: A CheckpointableSaver to add to the MetaGraph.

  Returns:
    An _AssetInfo, which contains information to help creating the SavedModel.
  """
    signatures = {}
    # List objects from the eager context to make sure Optimizers give us the
    # right Graph-dependent variables.
    accessible_objects = util.list_objects(obj)
    resource_initializer_functions = _trace_resource_initializers(
        accessible_objects)
    exported_graph = ops.Graph()
    resource_initializer_ops = []
    with exported_graph.as_default():
        object_map, resource_map, asset_info = _map_resources(
            accessible_objects)
        for resource_initializer_function in resource_initializer_functions:
            asset_dependencies = []
            for capture in resource_initializer_function.graph.external_captures:
                asset_initializer = asset_info.asset_initializers_by_resource.get(
                    capture, None)
                if asset_initializer is not None:
                    asset_dependencies.append(asset_initializer)
            with ops.control_dependencies(asset_dependencies):
                resource_initializer_ops.append(
                    _call_function_with_mapped_captures(
                        resource_initializer_function, [], resource_map))
        with ops.control_dependencies(resource_initializer_ops):
            init_op = control_flow_ops.no_op()
        # Add the same op to the main_op collection and to the init_op
        # signature. The collection is for compatibility with older loader APIs;
        # only one will be executed.
        meta_graph_def.collection_def[
            constants.MAIN_OP_KEY].node_list.value.append(init_op.name)
        meta_graph_def.signature_def[constants.INIT_OP_SIGNATURE_KEY].CopyFrom(
            signature_def_utils.op_signature_def(
                init_op, constants.INIT_OP_SIGNATURE_KEY))

    # Saving an object-based checkpoint again gathers variables. We need to do the
    # gathering from the eager context so Optimizers save the right set of
    # variables, but want any operations associated with the save/restore to be in
    # the exported graph (thus the `to_graph` argument).
    saver = object_saver.freeze(object_map=object_map, to_graph=exported_graph)

    # We must resolve the concrete function to add to MetaGraph while in eager
    # mode.
    concrete_functions = []
    for accessible_object in accessible_objects:
        for function in function_serialization.list_all_polymorphic_functions(
                accessible_object).values():
            concrete_functions.extend(
                function_serialization.list_all_concrete_functions(function))

    with exported_graph.as_default():
        signatures = _generate_signatures(signature_functions, resource_map)
        for concrete_function in concrete_functions:
            concrete_function.add_to_graph()
        saver_def = saver.to_proto()
        meta_graph_def.saver_def.CopyFrom(saver_def)
    graph_def = exported_graph.as_graph_def(add_shapes=True)
    # Clean reference cycles so repeated export()s don't make work for the garbage
    # collector.
    ops.dismantle_graph(exported_graph)

    meta_graph_def.graph_def.CopyFrom(graph_def)
    meta_graph_def.meta_info_def.tags.append(tag_constants.SERVING)
    meta_graph_def.asset_file_def.extend(asset_info.asset_defs)
    for signature_key, signature in signatures.items():
        meta_graph_def.signature_def[signature_key].CopyFrom(signature)
    meta_graph.strip_graph_default_valued_attrs(meta_graph_def)
    return asset_info
Beispiel #2
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def _add_op_to_signature_def_map(signature_def_map, op, key):
  if op is not None:
    signature_def_map[key] = signature_def_utils.op_signature_def(op, key)
Beispiel #3
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def _fill_meta_graph_def(meta_graph_def, saveable_view, signature_functions,
                         namespace_whitelist):
  """Generates a MetaGraph which calls `signature_functions`.

  Args:
    meta_graph_def: The MetaGraphDef proto to fill.
    saveable_view: The _SaveableView being exported.
    signature_functions: A dictionary mapping signature keys to concrete
      functions containing signatures to add to the MetaGraph.
    namespace_whitelist: List of strings containing whitelisted op namespaces.

  Returns:
    A tuple of (_AssetInfo, Graph) containing the captured assets and
    exported Graph generated from tracing the saveable_view.
  """
  # List objects from the eager context to make sure Optimizers give us the
  # right Graph-dependent variables.
  accessible_objects = saveable_view.nodes
  resource_initializer_functions = _trace_resource_initializers(
      accessible_objects)
  exported_graph = ops.Graph()
  resource_initializer_ops = []
  with exported_graph.as_default():
    object_map, resource_map, asset_info = saveable_view.map_resources()
    for resource_initializer_function in resource_initializer_functions:
      asset_dependencies = []
      for capture in resource_initializer_function.graph.external_captures:
        asset_initializer = asset_info.asset_initializers_by_resource.get(
            capture, None)
        if asset_initializer is not None:
          asset_dependencies.append(asset_initializer)
      with ops.control_dependencies(asset_dependencies):
        resource_initializer_ops.append(
            _call_function_with_mapped_captures(
                resource_initializer_function, [], resource_map))
    resource_initializer_ops.extend(
        asset_info.asset_initializers_by_resource.values())
    with ops.control_dependencies(resource_initializer_ops):
      init_op = control_flow_ops.no_op()
    # Add the same op to the main_op collection and to the init_op
    # signature. The collection is for compatibility with older loader APIs;
    # only one will be executed.
    meta_graph_def.collection_def[constants.MAIN_OP_KEY].node_list.value.append(
        init_op.name)
    meta_graph_def.signature_def[constants.INIT_OP_SIGNATURE_KEY].CopyFrom(
        signature_def_utils.op_signature_def(
            init_op, constants.INIT_OP_SIGNATURE_KEY))

  # Saving an object-based checkpoint again gathers variables. We need to do the
  # gathering from the eager context so Optimizers save the right set of
  # variables, but want any operations associated with the save/restore to be in
  # the exported graph (thus the `to_graph` argument).
  saver = functional_saver.MultiDeviceSaver(
      saveable_view.checkpoint_view.frozen_saveable_objects(
          object_map=object_map, to_graph=exported_graph))

  with exported_graph.as_default():
    signatures = _generate_signatures(signature_functions, resource_map)
    for concrete_function in saveable_view.concrete_functions:
      concrete_function.add_to_graph()
    saver_def = saver.to_proto()
    meta_graph_def.saver_def.CopyFrom(saver_def)
  graph_def = exported_graph.as_graph_def(add_shapes=True)
  _verify_ops(graph_def, namespace_whitelist)

  meta_graph_def.graph_def.CopyFrom(graph_def)
  meta_graph_def.meta_info_def.tags.append(tag_constants.SERVING)
  meta_graph_def.meta_info_def.tensorflow_version = versions.__version__
  meta_graph_def.meta_info_def.tensorflow_git_version = (
      versions.__git_version__)
  # We currently always strip default attributes.
  meta_graph_def.meta_info_def.stripped_default_attrs = True
  meta_graph_def.meta_info_def.stripped_op_list.MergeFrom(
      meta_graph.stripped_op_list_for_graph(meta_graph_def.graph_def))
  meta_graph_def.asset_file_def.extend(asset_info.asset_defs)
  for signature_key, signature in signatures.items():
    meta_graph_def.signature_def[signature_key].CopyFrom(signature)
  meta_graph.strip_graph_default_valued_attrs(meta_graph_def)
  return asset_info, exported_graph
Beispiel #4
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def _fill_meta_graph_def(meta_graph_def, saveable_view, signature_functions,
                         object_saver):
  """Generates a MetaGraph which calls `signature_functions`.

  Args:
    meta_graph_def: The MetaGraphDef proto to fill.
    saveable_view: The _SaveableView being exported.
    signature_functions: A dictionary mapping signature keys to concrete
      functions containing signatures to add to the MetaGraph.
    object_saver: A CheckpointableSaver to add to the MetaGraph.

  Returns:
    An _AssetInfo, which contains information to help creating the SavedModel.
  """
  # List objects from the eager context to make sure Optimizers give us the
  # right Graph-dependent variables.
  accessible_objects = saveable_view.nodes
  resource_initializer_functions = _trace_resource_initializers(
      accessible_objects)
  exported_graph = ops.Graph()
  resource_initializer_ops = []
  with exported_graph.as_default():
    object_map, resource_map, asset_info = _map_resources(accessible_objects)
    for resource_initializer_function in resource_initializer_functions:
      asset_dependencies = []
      for capture in resource_initializer_function.graph.external_captures:
        asset_initializer = asset_info.asset_initializers_by_resource.get(
            capture, None)
        if asset_initializer is not None:
          asset_dependencies.append(asset_initializer)
      with ops.control_dependencies(asset_dependencies):
        resource_initializer_ops.append(
            _call_function_with_mapped_captures(
                resource_initializer_function, [], resource_map))
    with ops.control_dependencies(resource_initializer_ops):
      init_op = control_flow_ops.no_op()
    # Add the same op to the main_op collection and to the init_op
    # signature. The collection is for compatibility with older loader APIs;
    # only one will be executed.
    meta_graph_def.collection_def[constants.MAIN_OP_KEY].node_list.value.append(
        init_op.name)
    meta_graph_def.signature_def[constants.INIT_OP_SIGNATURE_KEY].CopyFrom(
        signature_def_utils.op_signature_def(
            init_op, constants.INIT_OP_SIGNATURE_KEY))

  # Saving an object-based checkpoint again gathers variables. We need to do the
  # gathering from the eager context so Optimizers save the right set of
  # variables, but want any operations associated with the save/restore to be in
  # the exported graph (thus the `to_graph` argument).
  saver = object_saver.freeze(object_map=object_map, to_graph=exported_graph)

  # We must instantiate and list all concrete functions of `Function`s while in
  # eager mode so they end up added to the graph and can later be used by the
  # object based saved model.
  concrete_functions = []
  for obj in accessible_objects:
    for function in saveable_view.functions[obj].values():
      if isinstance(function, defun.ConcreteFunction):
        concrete_functions.append(function)
      else:
        concrete_functions.extend(
            function._list_all_concrete_functions_for_serialization())  # pylint: disable=protected-access

  with exported_graph.as_default():
    signatures = _generate_signatures(signature_functions, resource_map)
    for concrete_function in concrete_functions:
      concrete_function.add_to_graph()
    saver_def = saver.to_proto()
    meta_graph_def.saver_def.CopyFrom(saver_def)
  graph_def = exported_graph.as_graph_def(add_shapes=True)
  # Clean reference cycles so repeated export()s don't make work for the garbage
  # collector.
  ops.dismantle_graph(exported_graph)

  meta_graph_def.graph_def.CopyFrom(graph_def)
  meta_graph_def.meta_info_def.tags.append(tag_constants.SERVING)
  meta_graph_def.asset_file_def.extend(asset_info.asset_defs)
  for signature_key, signature in signatures.items():
    meta_graph_def.signature_def[signature_key].CopyFrom(signature)
  meta_graph.strip_graph_default_valued_attrs(meta_graph_def)
  return asset_info
Beispiel #5
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def _fill_meta_graph_def(meta_graph_def, saveable_view, signature_functions):
  """Generates a MetaGraph which calls `signature_functions`.

  Args:
    meta_graph_def: The MetaGraphDef proto to fill.
    saveable_view: The _SaveableView being exported.
    signature_functions: A dictionary mapping signature keys to concrete
      functions containing signatures to add to the MetaGraph.

  Returns:
    An _AssetInfo, which contains information to help creating the SavedModel.
  """
  # List objects from the eager context to make sure Optimizers give us the
  # right Graph-dependent variables.
  accessible_objects = saveable_view.nodes
  resource_initializer_functions = _trace_resource_initializers(
      accessible_objects)
  exported_graph = ops.Graph()
  resource_initializer_ops = []
  with exported_graph.as_default():
    object_map, resource_map, asset_info = saveable_view.map_resources()
    for resource_initializer_function in resource_initializer_functions:
      asset_dependencies = []
      for capture in resource_initializer_function.graph.external_captures:
        asset_initializer = asset_info.asset_initializers_by_resource.get(
            capture, None)
        if asset_initializer is not None:
          asset_dependencies.append(asset_initializer)
      with ops.control_dependencies(asset_dependencies):
        resource_initializer_ops.append(
            _call_function_with_mapped_captures(
                resource_initializer_function, [], resource_map))
    resource_initializer_ops.extend(
        asset_info.asset_initializers_by_resource.values())
    with ops.control_dependencies(resource_initializer_ops):
      init_op = control_flow_ops.no_op()
    # Add the same op to the main_op collection and to the init_op
    # signature. The collection is for compatibility with older loader APIs;
    # only one will be executed.
    meta_graph_def.collection_def[constants.MAIN_OP_KEY].node_list.value.append(
        init_op.name)
    meta_graph_def.signature_def[constants.INIT_OP_SIGNATURE_KEY].CopyFrom(
        signature_def_utils.op_signature_def(
            init_op, constants.INIT_OP_SIGNATURE_KEY))

  # Saving an object-based checkpoint again gathers variables. We need to do the
  # gathering from the eager context so Optimizers save the right set of
  # variables, but want any operations associated with the save/restore to be in
  # the exported graph (thus the `to_graph` argument).
  saver = functional_saver.MultiDeviceSaver(
      saveable_view.checkpoint_view.frozen_saveable_objects(
          object_map=object_map, to_graph=exported_graph))

  with exported_graph.as_default():
    signatures = _generate_signatures(signature_functions, resource_map)
    for concrete_function in saveable_view.concrete_functions:
      concrete_function.add_to_graph()
    saver_def = saver.to_proto()
    meta_graph_def.saver_def.CopyFrom(saver_def)
  graph_def = exported_graph.as_graph_def(add_shapes=True)

  meta_graph_def.graph_def.CopyFrom(graph_def)
  meta_graph_def.meta_info_def.tags.append(tag_constants.SERVING)
  meta_graph_def.meta_info_def.tensorflow_version = versions.__version__
  meta_graph_def.meta_info_def.tensorflow_git_version = (
      versions.__git_version__)
  # We currently always strip default attributes.
  meta_graph_def.meta_info_def.stripped_default_attrs = True
  meta_graph_def.meta_info_def.stripped_op_list.MergeFrom(
      meta_graph.stripped_op_list_for_graph(meta_graph_def.graph_def))
  meta_graph_def.asset_file_def.extend(asset_info.asset_defs)
  for signature_key, signature in signatures.items():
    meta_graph_def.signature_def[signature_key].CopyFrom(signature)
  meta_graph.strip_graph_default_valued_attrs(meta_graph_def)
  return asset_info, exported_graph
Beispiel #6
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def _add_op_to_signature_def_map(signature_def_map, op, key):
  if op is not None:
    signature_def_map[key] = signature_def_utils.op_signature_def(op, key)
Beispiel #7
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def _fill_meta_graph_def(meta_graph_def, obj, signature_functions,
                         object_saver):
  """Generates a MetaGraph which calls `signature_functions`.

  Args:
    meta_graph_def: The MetaGraphDef proto to fill.
    obj: The checkpointable object being exported.
    signature_functions: A dictionary mapping signature keys to concrete
      functions containing signatures to add to the MetaGraph.
    object_saver: A CheckpointableSaver to add to the MetaGraph.

  Returns:
    asset_filename_map, a dictionary mapping from asset base names to
    user-specified full asset paths, which should be copied to the SavedModel's
    assets/ directory.
  """
  signatures = {}
  # List objects from the eager context to make sure Optimizers give us the
  # right Graph-dependent variables.
  accessible_objects = util.list_objects(obj)
  resource_initializer_functions = _trace_resource_initializers(
      accessible_objects)
  exported_graph = ops.Graph()
  resource_initializer_ops = []
  with exported_graph.as_default():
    object_map, resource_map, asset_info = _map_resources(accessible_objects)
    for resource_initializer_function in resource_initializer_functions:
      asset_dependencies = []
      for capture in resource_initializer_function.graph.external_captures:
        asset_initializer = asset_info.asset_initializers_by_resource.get(
            capture, None)
        if asset_initializer is not None:
          asset_dependencies.append(asset_initializer)
      with ops.control_dependencies(asset_dependencies):
        resource_initializer_ops.append(
            _call_function_with_mapped_captures(
                resource_initializer_function, [], resource_map))
    with ops.control_dependencies(resource_initializer_ops):
      init_op = control_flow_ops.no_op()
    # Add the same op to the main_op collection and to the init_op
    # signature. The collection is for compatibility with older loader APIs;
    # only one will be executed.
    meta_graph_def.collection_def[constants.MAIN_OP_KEY].node_list.value.append(
        init_op.name)
    meta_graph_def.signature_def[constants.INIT_OP_SIGNATURE_KEY].CopyFrom(
        signature_def_utils.op_signature_def(
            init_op, constants.INIT_OP_SIGNATURE_KEY))

  # Saving an object-based checkpoint again gathers variables. We need to do the
  # gathering from the eager context so Optimizers save the right set of
  # variables, but want any operations associated with the save/restore to be in
  # the exported graph (thus the `to_graph` argument).
  saver = object_saver.freeze(object_map=object_map, to_graph=exported_graph)
  with exported_graph.as_default():
    signatures = _generate_signatures(signature_functions, resource_map)
    saver_def = saver.to_proto()
    meta_graph_def.saver_def.CopyFrom(saver_def)
  graph_def = exported_graph.as_graph_def(add_shapes=True)
  # Clean reference cycles so repeated export()s don't make work for the garbage
  # collector.
  ops.dismantle_graph(exported_graph)

  meta_graph_def.graph_def.CopyFrom(graph_def)
  meta_graph_def.meta_info_def.tags.append(tag_constants.SERVING)
  meta_graph_def.asset_file_def.extend(asset_info.asset_defs)
  for signature_key, signature in signatures.items():
    meta_graph_def.signature_def[signature_key].CopyFrom(signature)
  meta_graph.strip_graph_default_valued_attrs(meta_graph_def)
  return asset_info.asset_filename_map