91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ================================
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"""Imports a protobuf model as a graph in Tensorboard."""
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import argparse
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import sys
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from absl import app
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from tensorflow.python.client import session
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from tensorflow.python.framework import importer
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from tensorflow.python.framework import ops
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from tensorflow.python.summary import summary
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from tensorflow.python.tools import saved_model_utils
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# Try importing TensorRT ops if available
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# TODO(aaroey): ideally we should import everything from contrib, but currently
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# tensorrt module would cause build errors when being imported in
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# tensorflow/contrib/__init__.py. Fix it.
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# pylint: disable=unused-import,g-import-not-at-top,wildcard-import
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try:
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from tensorflow.contrib.tensorrt.ops.gen_trt_engine_op import *
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except ImportError:
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pass
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# pylint: enable=unused-import,g-import-not-at-top,wildcard-import
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def import_to_tensorboard(model_dir, log_dir, tag_set):
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"""View an SavedModel as a graph in Tensorboard.
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Args:
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model_dir: The directory containing the SavedModel to import.
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log_dir: The location for the Tensorboard log to begin visualization from.
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tag_set: Group of tag(s) of the MetaGraphDef to load, in string format,
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separated by ','. For tag-set contains multiple tags, all tags must be
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passed in.
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Usage: Call this function with your SavedModel location and desired log
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directory. Launch Tensorboard by pointing it to the log directory. View your
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imported SavedModel as a graph.
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"""
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with session.Session(graph=ops.Graph()) as sess:
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input_graph_def = saved_model_utils.get_meta_graph_def(model_dir,
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tag_set).graph_def
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importer.import_graph_def(input_graph_def)
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pb_visual_writer = summary.FileWriter(log_dir)
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pb_visual_writer.add_graph(sess.graph)
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print("Model Imported. Visualize by running: "
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"tensorboard --logdir={}".format(log_dir))
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def main(_):
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import_to_tensorboard(FLAGS.model_dir, FLAGS.log_dir, FLAGS.tag_set)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.register("type", "bool", lambda v: v.lower() == "true")
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parser.add_argument(
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"--model_dir",
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type=str,
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default="",
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required=True,
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help="The directory containing the SavedModel to import.")
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parser.add_argument(
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"--log_dir",
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type=str,
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default="",
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required=True,
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help="The location for the Tensorboard log to begin visualization from.")
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parser.add_argument(
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"--tag_set",
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type=str,
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default="serve",
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required=False,
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help='tag-set of graph in SavedModel to load, separated by \',\'')
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FLAGS, unparsed = parser.parse_known_args()
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app.run(main=main, argv=[sys.argv[0]] + unparsed)
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