# Copyright 2016 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. # ============================================================================== """Graph post-processing logic. Used by both TensorBoard and mldash.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf def prepare_graph_for_ui(graph, limit_attr_size=1024, large_attrs_key='_too_large_attrs'): """Prepares (modifies in-place) the graph to be served to the front-end. For now, it supports filtering out attributes that are too large to be shown in the graph UI. Args: graph: The GraphDef proto message. limit_attr_size: Maximum allowed size in bytes, before the attribute is considered large. Default is 1024 (1KB). Must be > 0 or None. If None, there will be no filtering. large_attrs_key: The attribute key that will be used for storing attributes that are too large. Default is '_too_large_attrs'. Must be != None if `limit_attr_size` is != None. Raises: ValueError: If `large_attrs_key is None` while `limit_attr_size != None`. ValueError: If `limit_attr_size` is defined, but <= 0. """ # Check input for validity. if limit_attr_size is not None: if large_attrs_key is None: raise ValueError('large_attrs_key must be != None when limit_attr_size' '!= None.') if limit_attr_size <= 0: raise ValueError('limit_attr_size must be > 0, but is %d' % limit_attr_size) # Filter only if a limit size is defined. if limit_attr_size is not None: for node in graph.node: # Go through all the attributes and filter out ones bigger than the # limit. keys = list(node.attr.keys()) for key in keys: size = node.attr[key].ByteSize() if size > limit_attr_size or size < 0: del node.attr[key] # Add the attribute key to the list of "too large" attributes. # This is used in the info card in the graph UI to show the user # that some attributes are too large to be shown. node.attr[large_attrs_key].list.s.append(tf.compat.as_bytes(key))