1 files changed, 119 insertions, 0 deletions
diff --git a/tools/tensorflow_model_freezer/sample/TOPK_gen.py b/tools/tensorflow_model_freezer/sample/TOPK_gen.py
new file mode 100755
index 000000000..0c16d5b75
--- /dev/null
+++ b/tools/tensorflow_model_freezer/sample/TOPK_gen.py
@@ -0,0 +1,119 @@
+#!/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
+
+
+class Gen(base.BaseFreezer):
+    '''
+    class to generate tflite file for TOPK
+    '''
+
+    def __init__(self, path):
+        super(self.__class__, self).__init__(path)
+
+    def getOutputDirectory(self):
+        return os.path.join(self.root_output_path,
+                            'topk')  # the root path of generated files
+
+    def getTestCases(self):
+        '''
+        this returns a hash of test case (= set of input type), for example:
+            [1.2, -2.3] : two input, both are scalar. one is 1.2, another is -2.3
+            [[5,3], [5,4,3]] : two input, both are shapes. one is [5.3], another is [5,4,3]
+
+        test name (key of hash) is used as
+            - prefix of file name to be generated
+            - output node name pf graph
+        '''
+        return {
+            "topk_2d": [
+                base.Tensor(shape=[2, 3], dtype=tf.float32),
+                base.Tensor(shape=[], const_val=2, dtype=tf.int32)
+            ],
+            "topk_3d": [
+                base.Tensor(shape=[2, 3, 4], dtype=tf.float32),
+                base.Tensor(shape=[], const_val=2, dtype=tf.int32)
+            ],
+        }
+
+    def buildModel(self, sess, test_case_tensor, tc_name):
+        '''
+        please, refer to the comment in MUL_gen.py to see how to rewrite this method
+        '''
+
+        input_list = []
+
+        # ------ modify below for your model FROM here -------#
+
+        x_tensor = self.createTFInput(test_case_tensor[0], input_list)
+        y_tensor = self.createTFInput(test_case_tensor[1], input_list)
+
+        # defining output node and input list
+        output_node = tf.nn.top_k(
+            x_tensor,
+            y_tensor,  # add your input here
+            name=tc_name)  # do not modify 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
+
+    Gen(root_output_path).createSaveFreezeModel()