# 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.
# ================================
"""Imports a protobuf model as a graph in Tensorboard."""

import argparse
import sys

from absl import app

from tensorflow.python.client import session
from tensorflow.python.framework import importer
from tensorflow.python.framework import ops
from tensorflow.python.summary import summary
from tensorflow.python.tools import saved_model_utils

# Try importing TensorRT ops if available
# TODO(aaroey): ideally we should import everything from contrib, but currently
# tensorrt module would cause build errors when being imported in
# tensorflow/contrib/__init__.py. Fix it.
# pylint: disable=unused-import,g-import-not-at-top,wildcard-import
try:
  from tensorflow.contrib.tensorrt.ops.gen_trt_engine_op import *
except ImportError:
  pass
# pylint: enable=unused-import,g-import-not-at-top,wildcard-import


def import_to_tensorboard(model_dir, log_dir, tag_set):
  """View an SavedModel as a graph in Tensorboard.

  Args:
    model_dir: The directory containing the SavedModel to import.
    log_dir: The location for the Tensorboard log to begin visualization from.
    tag_set: Group of tag(s) of the MetaGraphDef to load, in string format,
      separated by ','. For tag-set contains multiple tags, all tags must be
      passed in.
  Usage: Call this function with your SavedModel location and desired log
    directory. Launch Tensorboard by pointing it to the log directory. View your
    imported SavedModel as a graph.
  """
  with session.Session(graph=ops.Graph()) as sess:
    input_graph_def = saved_model_utils.get_meta_graph_def(model_dir,
                                                           tag_set).graph_def
    importer.import_graph_def(input_graph_def)

    pb_visual_writer = summary.FileWriter(log_dir)
    pb_visual_writer.add_graph(sess.graph)
    print("Model Imported. Visualize by running: "
          "tensorboard --logdir={}".format(log_dir))


def main(_):
  import_to_tensorboard(FLAGS.model_dir, FLAGS.log_dir, FLAGS.tag_set)


if __name__ == "__main__":
  parser = argparse.ArgumentParser()
  parser.register("type", "bool", lambda v: v.lower() == "true")
  parser.add_argument(
      "--model_dir",
      type=str,
      default="",
      required=True,
      help="The directory containing the SavedModel to import.")
  parser.add_argument(
      "--log_dir",
      type=str,
      default="",
      required=True,
      help="The location for the Tensorboard log to begin visualization from.")
  parser.add_argument(
      "--tag_set",
      type=str,
      default="serve",
      required=False,
      help='tag-set of graph in SavedModel to load, separated by \',\'')
  FLAGS, unparsed = parser.parse_known_args()
  app.run(main=main, argv=[sys.argv[0]] + unparsed)