95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
# Copyright 2017 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.
|
|
# ==============================================================================
|
|
"""A python interface for Grappler items."""
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
from tensorflow.core.grappler.costs import op_performance_data_pb2
|
|
from tensorflow.core.protobuf import meta_graph_pb2
|
|
from tensorflow.python import _pywrap_tf_item as tf_item
|
|
|
|
|
|
class Item(object):
|
|
"""GrapplerItem."""
|
|
|
|
def __init__(self,
|
|
metagraph,
|
|
ignore_colocation=True,
|
|
ignore_user_placement=False):
|
|
"""Creates an Item.
|
|
|
|
Args:
|
|
metagraph: a TensorFlow metagraph.
|
|
ignore_colocation: if set, the tool will ignore all the colocation
|
|
constraints generated by TensorFlow.
|
|
ignore_user_placement: if set, all the placement annotations annotated in
|
|
the metagraph will be ignored.
|
|
Raises:
|
|
ValueError: the metagraph is incomplete or invalid.
|
|
"""
|
|
self._metagraph = metagraph
|
|
self._item_graph = meta_graph_pb2.MetaGraphDef()
|
|
self._item_graph.CopyFrom(metagraph)
|
|
self._ignore_colocation = ignore_colocation
|
|
self._ignore_user_placement = ignore_user_placement
|
|
self._tf_item = None
|
|
self._BuildTFItem()
|
|
|
|
def IdentifyImportantOps(self, sort_topologically=False):
|
|
return tf_item.TF_IdentifyImportantOps(self.tf_item, sort_topologically)
|
|
|
|
def GetOpProperties(self):
|
|
"""Get Op properties."""
|
|
props = tf_item.TF_GetOpProperties(self.tf_item)
|
|
properties = {}
|
|
for key, values in props.items():
|
|
prop = []
|
|
for value in values:
|
|
# TODO(petebu): Make this conversion to a dictionary be done in the C++
|
|
# wrapper for performance.
|
|
prop.append(
|
|
op_performance_data_pb2.OpInfo.TensorProperties.FromString(value))
|
|
properties[key] = prop
|
|
return properties
|
|
|
|
def GetColocationGroups(self):
|
|
"""Return a list of hard colocation constraints.
|
|
|
|
All the nodes in a colocation tuple must be placed on the same device for
|
|
the model to work.
|
|
|
|
Returns:
|
|
A list of colocation tuples.
|
|
"""
|
|
return tf_item.TF_GetColocationGroups(self.tf_item)
|
|
|
|
@property
|
|
def metagraph(self):
|
|
return self._metagraph
|
|
|
|
@property
|
|
def tf_item(self):
|
|
if self._item_graph != self._metagraph:
|
|
self._BuildTFItem()
|
|
self._item_graph.CopyFrom(self._metagraph)
|
|
return self._tf_item
|
|
|
|
def _BuildTFItem(self):
|
|
self._tf_item = tf_item.TF_NewItem(self._metagraph.SerializeToString(),
|
|
self._ignore_colocation,
|
|
self._ignore_user_placement)
|