Delete tf_export_model.py

tool/tf_export_model.py

-#   Copyright (c) 2019  PaddlePaddle 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.
-
-from tensorflow.python.framework import graph_util
-import tensorflow as tf
-
-
-def freeze_model(sess, output_tensor_names, freeze_model_path):
-    out_graph = graph_util.convert_variables_to_constants(
-        sess, sess.graph.as_graph_def(), output_tensor_names)
-    with tf.gfile.GFile(freeze_model_path, 'wb') as f:
-        f.write(out_graph.SerializeToString())
-
-    print("freeze model saved in {}".format(freeze_model_path))
-
-
-import tensorflow.contrib.slim as slim
-from tensorflow.contrib.slim.nets import vgg
-import numpy
-
-with tf.Session() as sess:
-    inputs = tf.placeholder(dtype=tf.float32,
-                            shape=[None, None, None, 3],
-                            name="inputs")
-    logits, endpoint = vgg.vgg_16(inputs, num_classes=1000, is_training=False)
-    load_model = slim.assign_from_checkpoint_fn(
-        "vgg_16.ckpt", slim.get_model_variables("vgg_16"))
-    load_model(sess)
-
-    numpy.random.seed(13)
-    data = numpy.random.rand(5, 224, 224, 3)
-    input_tensor = sess.graph.get_tensor_by_name("inputs:0")
-    output_tensor = sess.graph.get_tensor_by_name("vgg_16/fc8/squeezed:0")
-    result = sess.run([output_tensor], {input_tensor: data})
-    numpy.save("tensorflow.npy", numpy.array(result))
-
-    freeze_model(sess, ["vgg_16/fc8/squeezed"], "vgg16_None.pb")