3RNN/Lib/site-packages/tensorflow/python/tools/strip_unused_lib.py
2024-05-26 19:49:15 +02:00

122 lines
4.7 KiB
Python

# pylint: disable=g-bad-file-header
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Utilities to remove unneeded nodes from a GraphDefs."""
import copy
from google.protobuf import text_format
from tensorflow.core.framework import attr_value_pb2
from tensorflow.core.framework import graph_pb2
from tensorflow.core.framework import node_def_pb2
from tensorflow.python.framework import graph_util
from tensorflow.python.platform import gfile
def strip_unused(input_graph_def, input_node_names, output_node_names,
placeholder_type_enum):
"""Removes unused nodes from a GraphDef.
Args:
input_graph_def: A graph with nodes we want to prune.
input_node_names: A list of the nodes we use as inputs.
output_node_names: A list of the output nodes.
placeholder_type_enum: The AttrValue enum for the placeholder data type, or
a list that specifies one value per input node name.
Returns:
A `GraphDef` with all unnecessary ops removed.
Raises:
ValueError: If any element in `input_node_names` refers to a tensor instead
of an operation.
KeyError: If any element in `input_node_names` is not found in the graph.
"""
for name in input_node_names:
if ":" in name:
raise ValueError(f"Name '{name}' appears to refer to a Tensor, not an "
"Operation.")
# Here we replace the nodes we're going to override as inputs with
# placeholders so that any unused nodes that are inputs to them are
# automatically stripped out by extract_sub_graph().
not_found = {name for name in input_node_names}
inputs_replaced_graph_def = graph_pb2.GraphDef()
for node in input_graph_def.node:
if node.name in input_node_names:
not_found.remove(node.name)
placeholder_node = node_def_pb2.NodeDef()
placeholder_node.op = "Placeholder"
placeholder_node.name = node.name
if isinstance(placeholder_type_enum, list):
input_node_index = input_node_names.index(node.name)
placeholder_node.attr["dtype"].CopyFrom(
attr_value_pb2.AttrValue(type=placeholder_type_enum[
input_node_index]))
else:
placeholder_node.attr["dtype"].CopyFrom(
attr_value_pb2.AttrValue(type=placeholder_type_enum))
if "_output_shapes" in node.attr:
placeholder_node.attr["_output_shapes"].CopyFrom(node.attr[
"_output_shapes"])
if "shape" in node.attr:
placeholder_node.attr["shape"].CopyFrom(node.attr["shape"])
inputs_replaced_graph_def.node.extend([placeholder_node])
else:
inputs_replaced_graph_def.node.extend([copy.deepcopy(node)])
if not_found:
raise KeyError(f"The following input nodes were not found: {not_found}.")
output_graph_def = graph_util.extract_sub_graph(inputs_replaced_graph_def,
output_node_names)
return output_graph_def
def strip_unused_from_files(input_graph, input_binary, output_graph,
output_binary, input_node_names, output_node_names,
placeholder_type_enum):
"""Removes unused nodes from a graph file."""
if not gfile.Exists(input_graph):
print("Input graph file '" + input_graph + "' does not exist!")
return -1
if not output_node_names:
print("You need to supply the name of a node to --output_node_names.")
return -1
input_graph_def = graph_pb2.GraphDef()
mode = "rb" if input_binary else "r"
with gfile.GFile(input_graph, mode) as f:
if input_binary:
input_graph_def.ParseFromString(f.read())
else:
text_format.Merge(f.read(), input_graph_def)
output_graph_def = strip_unused(input_graph_def,
input_node_names.split(","),
output_node_names.split(","),
placeholder_type_enum)
if output_binary:
with gfile.GFile(output_graph, "wb") as f:
f.write(output_graph_def.SerializeToString())
else:
with gfile.GFile(output_graph, "w") as f:
f.write(text_format.MessageToString(output_graph_def))
print("%d ops in the final graph." % len(output_graph_def.node))