1 # Copyright 2017 The TensorFlow Authors. All Rights Reserved. 2 # 3 # Licensed under the Apache License, Version 2.0 (the "License"); 4 # you may not use this file except in compliance with the License. 5 # You may obtain a copy of the License at 6 # 7 # http://www.apache.org/licenses/LICENSE-2.0 8 # 9 # Unless required by applicable law or agreed to in writing, software 10 # distributed under the License is distributed on an "AS IS" BASIS, 11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 # See the License for the specific language governing permissions and 13 # limitations under the License. 14 # ============================================================================== 15 """Common values and methods for TensorFlow Debugger.""" 16 from __future__ import absolute_import 17 from __future__ import division 18 from __future__ import print_function 19 20 import collections 21 import json 22 23 GRPC_URL_PREFIX = "grpc://" 24 25 # A key for a Session.run() call. 26 RunKey = collections.namedtuple("RunKey", ["feed_names", "fetch_names"]) 27 28 29 def get_graph_element_name(elem): 30 """Obtain the name or string representation of a graph element. 31 32 If the graph element has the attribute "name", return name. Otherwise, return 33 a __str__ representation of the graph element. Certain graph elements, such as 34 `SparseTensor`s, do not have the attribute "name". 35 36 Args: 37 elem: The graph element in question. 38 39 Returns: 40 If the attribute 'name' is available, return the name. Otherwise, return 41 str(fetch). 42 """ 43 44 return elem.name if hasattr(elem, "name") else str(elem) 45 46 47 def get_flattened_names(feeds_or_fetches): 48 """Get a flattened list of the names in run() call feeds or fetches. 49 50 Args: 51 feeds_or_fetches: Feeds or fetches of the `Session.run()` call. It maybe 52 a Tensor, an Operation or a Variable. It may also be nested lists, tuples 53 or dicts. See doc of `Session.run()` for more details. 54 55 Returns: 56 (list of str) A flattened list of fetch names from `feeds_or_fetches`. 57 """ 58 59 lines = [] 60 if isinstance(feeds_or_fetches, (list, tuple)): 61 for item in feeds_or_fetches: 62 lines.extend(get_flattened_names(item)) 63 elif isinstance(feeds_or_fetches, dict): 64 for key in feeds_or_fetches: 65 lines.extend(get_flattened_names(feeds_or_fetches[key])) 66 else: 67 # This ought to be a Tensor, an Operation or a Variable, for which the name 68 # attribute should be available. (Bottom-out condition of the recursion.) 69 lines.append(get_graph_element_name(feeds_or_fetches)) 70 71 return lines 72 73 74 def get_run_key(feed_dict, fetches): 75 """Summarize the names of feeds and fetches as a RunKey JSON string. 76 77 Args: 78 feed_dict: The feed_dict given to the `Session.run()` call. 79 fetches: The fetches from the `Session.run()` call. 80 81 Returns: 82 A JSON Array consisting of two items. They first items is a flattened 83 Array of the names of the feeds. The second item is a flattened Array of 84 the names of the fetches. 85 """ 86 return json.dumps(RunKey(get_flattened_names(feed_dict), 87 get_flattened_names(fetches))) 88
