TFlite file generator for FLOOR, PAD, SQUEEZE, TRANSPOSE (#2609)

This python script generates four tflite files for FLOOR, PAD, SQUEEZE and TRANSPOSE respectively.

Signed-off-by: Hyun Sik Yoon <hyunsik.yoon@samsung.com>

diff --git a/tools/tensorflow_model_freezer/sample/Operation_gen.py b/tools/tensorflow_model_freezer/sample/Operation_gen.py
new file mode 100644 (file)
index 0000000..be4d74b
--- /dev/null
+++ b/tools/tensorflow_model_freezer/sample/Operation_gen.py
@@ -0,0 +1,214 @@
+#!/usr/bin/python
+
+# Copyright (c) 2018 Samsung Electronics Co., Ltd. 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.
+
+import os
+import sys
+import platform
+import tensorflow as tf
+import argparse
+
+import base_freezer as base
+import model_freezer_util as util
+
+
+# see MUL_gen.py for details usage and sample
+class GenFloor(base.BaseFreezer):
+    def __init__(self, path):
+        super(self.__class__, self).__init__(path)
+
+    def getOutputDirectory(self):
+        return os.path.join(self.root_output_path,
+                            'floor')  # the root path of generated files
+
+    def getTestCases(self):
+        return {"floor_4d_4d": [base.Tensor([1, 2, 2, 1]), base.Tensor([1, 2, 2, 1])]}
+
+    def buildModel(self, sess, test_case_tensor, tc_name):
+
+        input_list = []
+
+        x_tensor = self.createTFInput(test_case_tensor[0], input_list)
+
+        output_node = tf.floor(x_tensor, name=tc_name)
+
+        # ------ modify UNTIL here for your model -------#
+
+        # Note if don't have any CONST value, creating checkpoint file fails.
+        # The next lines insert such (CONST) to prevent such error.
+        # So, Graph.pb/pbtxt contains this garbage info,
+        # but this garbage info will be removed in Graph_frozen.pb/pbtxt
+        garbage = tf.get_variable(
+            "garbage", [1], dtype=tf.float32, initializer=tf.zeros_initializer())
+        init_op = tf.global_variables_initializer()
+        garbage_value = [0]
+        sess.run(tf.assign(garbage, garbage_value))
+
+        sess.run(init_op)
+
+        # ------ modify appropriate return value  -------#
+
+        # returning (input_node_list, output_node_list)
+        return (input_list, [output_node])
+
+
+class GenPad(base.BaseFreezer):
+    def __init__(self, path):
+        super(self.__class__, self).__init__(path)
+
+    def getOutputDirectory(self):
+        return os.path.join(self.root_output_path,
+                            'pad')  # the root path of generated files
+
+    def getTestCases(self):
+        return {
+            "pad_4d_2d": [
+                base.Tensor([1, 2, 2, 1]),
+                base.Tensor([4, 2], dtype=tf.int32, const_val=[0, 0, 1, 1, 1, 1, 0, 0])
+            ]
+        }
+
+    def buildModel(self, sess, test_case_tensor, tc_name):
+
+        input_list = []
+
+        input_tensor = self.createTFInput(test_case_tensor[0], input_list)
+        pad_tensor = self.createTFInput(test_case_tensor[1], input_list)
+
+        output_node = tf.pad(input_tensor, pad_tensor, name=tc_name)
+
+        # ------ modify UNTIL here for your model -------#
+
+        # Note if don't have any CONST value, creating checkpoint file fails.
+        # The next lines insert such (CONST) to prevent such error.
+        # So, Graph.pb/pbtxt contains this garbage info,
+        # but this garbage info will be removed in Graph_frozen.pb/pbtxt
+        garbage = tf.get_variable(
+            "garbage", [1], dtype=tf.float32, initializer=tf.zeros_initializer())
+        init_op = tf.global_variables_initializer()
+        garbage_value = [0]
+        sess.run(tf.assign(garbage, garbage_value))
+
+        sess.run(init_op)
+
+        # ------ modify appropriate return value  -------#
+
+        # returning (input_node_list, output_node_list)
+        return (input_list, [output_node])
+
+
+class GenSqueeze(base.BaseFreezer):
+    def __init__(self, path):
+        super(self.__class__, self).__init__(path)
+
+    def getOutputDirectory(self):
+        return os.path.join(self.root_output_path,
+                            'squeeze')  # the root path of generated files
+
+    def getTestCases(self):
+        return {"squeeze_3d": [base.Tensor([1, 5, 1])]}
+
+    def buildModel(self, sess, test_case_tensor, tc_name):
+
+        input_list = []
+
+        input_tensor = self.createTFInput(test_case_tensor[0], input_list)
+
+        output_node = tf.squeeze(input_tensor, [2], name=tc_name)
+
+        # ------ modify UNTIL here for your model -------#
+
+        # Note if don't have any CONST value, creating checkpoint file fails.
+        # The next lines insert such (CONST) to prevent such error.
+        # So, Graph.pb/pbtxt contains this garbage info,
+        # but this garbage info will be removed in Graph_frozen.pb/pbtxt
+        garbage = tf.get_variable(
+            "garbage", [1], dtype=tf.float32, initializer=tf.zeros_initializer())
+        init_op = tf.global_variables_initializer()
+        garbage_value = [0]
+        sess.run(tf.assign(garbage, garbage_value))
+
+        sess.run(init_op)
+
+        # ------ modify appropriate return value  -------#
+
+        # returning (input_node_list, output_node_list)
+        return (input_list, [output_node])
+
+
+class GenTranspose(base.BaseFreezer):
+    def __init__(self, path):
+        super(self.__class__, self).__init__(path)
+
+    def getOutputDirectory(self):
+        return os.path.join(self.root_output_path,
+                            'transpose')  # the root path of generated files
+
+    def getTestCases(self):
+        return {"transpose_4d": [base.Tensor([1, 2, 2, 1])]}
+
+    def buildModel(self, sess, test_case_tensor, tc_name):
+
+        input_list = []
+
+        input_tensor = self.createTFInput(test_case_tensor[0], input_list)
+
+        output_node = tf.transpose(input_tensor, [0, 2, 1, 3], name=tc_name)
+
+        # ------ modify UNTIL here for your model -------#
+
+        # Note if don't have any CONST value, creating checkpoint file fails.
+        # The next lines insert such (CONST) to prevent such error.
+        # So, Graph.pb/pbtxt contains this garbage info,
+        # but this garbage info will be removed in Graph_frozen.pb/pbtxt
+        garbage = tf.get_variable(
+            "garbage", [1], dtype=tf.float32, initializer=tf.zeros_initializer())
+        init_op = tf.global_variables_initializer()
+        garbage_value = [0]
+        sess.run(tf.assign(garbage, garbage_value))
+
+        sess.run(init_op)
+
+        # ------ modify appropriate return value  -------#
+
+        # returning (input_node_list, output_node_list)
+        return (input_list, [output_node])
+
+
+'''
+How to run
+$ chmod +x tools/tensorflow_model_freezer/sample/name_of_this_file.py
+$ PYTHONPATH=$PYTHONPATH:./tools/tensorflow_model_freezer/ \
+      tools/tensorflow_model_freezer/sample/name_of_this_file.py \
+      ~/temp  # directory where model files are saved
+'''
+# --------
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser(
+        description='Converted Tensorflow model in python to frozen model.')
+    parser.add_argument(
+        "out_dir",
+        help=
+        "directory where generated pb, pbtxt, checkpoint and Tensorboard log files are stored."
+    )
+
+    args = parser.parse_args()
+    root_output_path = args.out_dir
+
+    GenFloor(root_output_path).createSaveFreezeModel()
+    GenPad(root_output_path).createSaveFreezeModel()
+    GenSqueeze(root_output_path).createSaveFreezeModel()
+    GenTranspose(root_output_path).createSaveFreezeModel()