STT-tensorflow/tensorflow/examples/speech_commands/freeze_test.py
Pete Warden 314b503bd2 Add SavedModel support to speech commands training
PiperOrigin-RevId: 307691321
Change-Id: Ib52d1bf5537835ce56db11b074a0f3df9c3f9206
2020-04-21 15:24:55 -07:00

134 lines
5.0 KiB
Python

# 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.
# ==============================================================================
"""Tests for data input for speech commands."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os.path
from tensorflow.examples.speech_commands import freeze
from tensorflow.python.framework import graph_util
from tensorflow.python.framework import test_util
from tensorflow.python.ops.variables import global_variables_initializer
from tensorflow.python.platform import test
class FreezeTest(test.TestCase):
@test_util.run_deprecated_v1
def testCreateInferenceGraphWithMfcc(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
wanted_words='a,b,c,d',
sample_rate=16000,
clip_duration_ms=1000.0,
clip_stride_ms=30.0,
window_size_ms=30.0,
window_stride_ms=10.0,
feature_bin_count=40,
model_architecture='conv',
preprocess='mfcc')
self.assertIsNotNone(sess.graph.get_tensor_by_name('wav_data:0'))
self.assertIsNotNone(
sess.graph.get_tensor_by_name('decoded_sample_data:0'))
self.assertIsNotNone(sess.graph.get_tensor_by_name('labels_softmax:0'))
ops = [node.op for node in sess.graph_def.node]
self.assertEqual(1, ops.count('Mfcc'))
@test_util.run_deprecated_v1
def testCreateInferenceGraphWithoutMfcc(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
wanted_words='a,b,c,d',
sample_rate=16000,
clip_duration_ms=1000.0,
clip_stride_ms=30.0,
window_size_ms=30.0,
window_stride_ms=10.0,
feature_bin_count=40,
model_architecture='conv',
preprocess='average')
self.assertIsNotNone(sess.graph.get_tensor_by_name('wav_data:0'))
self.assertIsNotNone(
sess.graph.get_tensor_by_name('decoded_sample_data:0'))
self.assertIsNotNone(sess.graph.get_tensor_by_name('labels_softmax:0'))
ops = [node.op for node in sess.graph_def.node]
self.assertEqual(0, ops.count('Mfcc'))
@test_util.run_deprecated_v1
def testCreateInferenceGraphWithMicro(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
wanted_words='a,b,c,d',
sample_rate=16000,
clip_duration_ms=1000.0,
clip_stride_ms=30.0,
window_size_ms=30.0,
window_stride_ms=10.0,
feature_bin_count=40,
model_architecture='conv',
preprocess='micro')
self.assertIsNotNone(sess.graph.get_tensor_by_name('wav_data:0'))
self.assertIsNotNone(
sess.graph.get_tensor_by_name('decoded_sample_data:0'))
self.assertIsNotNone(sess.graph.get_tensor_by_name('labels_softmax:0'))
@test_util.run_deprecated_v1
def testFeatureBinCount(self):
with self.cached_session() as sess:
freeze.create_inference_graph(
wanted_words='a,b,c,d',
sample_rate=16000,
clip_duration_ms=1000.0,
clip_stride_ms=30.0,
window_size_ms=30.0,
window_stride_ms=10.0,
feature_bin_count=80,
model_architecture='conv',
preprocess='average')
self.assertIsNotNone(sess.graph.get_tensor_by_name('wav_data:0'))
self.assertIsNotNone(
sess.graph.get_tensor_by_name('decoded_sample_data:0'))
self.assertIsNotNone(sess.graph.get_tensor_by_name('labels_softmax:0'))
ops = [node.op for node in sess.graph_def.node]
self.assertEqual(0, ops.count('Mfcc'))
@test_util.run_deprecated_v1
def testCreateSavedModel(self):
tmp_dir = self.get_temp_dir()
saved_model_path = os.path.join(tmp_dir, 'saved_model')
with self.cached_session() as sess:
input_tensor, output_tensor = freeze.create_inference_graph(
wanted_words='a,b,c,d',
sample_rate=16000,
clip_duration_ms=1000.0,
clip_stride_ms=30.0,
window_size_ms=30.0,
window_stride_ms=10.0,
feature_bin_count=40,
model_architecture='conv',
preprocess='micro')
global_variables_initializer().run()
graph_util.convert_variables_to_constants(
sess, sess.graph_def, ['labels_softmax'])
freeze.save_saved_model(saved_model_path, sess, input_tensor,
output_tensor)
if __name__ == '__main__':
test.main()