121 lines
4.8 KiB
Python
121 lines
4.8 KiB
Python
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for speech commands models."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import tensorflow as tf
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from tensorflow.examples.speech_commands import models
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from tensorflow.python.framework import test_util
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from tensorflow.python.platform import test
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class ModelsTest(test.TestCase):
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def _modelSettings(self):
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return models.prepare_model_settings(
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label_count=10,
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sample_rate=16000,
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clip_duration_ms=1000,
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window_size_ms=20,
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window_stride_ms=10,
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feature_bin_count=40,
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preprocess="mfcc")
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def testPrepareModelSettings(self):
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self.assertIsNotNone(
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models.prepare_model_settings(
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label_count=10,
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sample_rate=16000,
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clip_duration_ms=1000,
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window_size_ms=20,
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window_stride_ms=10,
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feature_bin_count=40,
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preprocess="mfcc"))
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@test_util.run_deprecated_v1
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def testCreateModelConvTraining(self):
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model_settings = self._modelSettings()
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with self.cached_session() as sess:
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fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]])
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logits, dropout_rate = models.create_model(
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fingerprint_input, model_settings, "conv", True)
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self.assertIsNotNone(logits)
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self.assertIsNotNone(dropout_rate)
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self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
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self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_rate.name))
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@test_util.run_deprecated_v1
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def testCreateModelConvInference(self):
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model_settings = self._modelSettings()
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with self.cached_session() as sess:
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fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]])
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logits = models.create_model(fingerprint_input, model_settings, "conv",
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False)
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self.assertIsNotNone(logits)
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self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
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@test_util.run_deprecated_v1
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def testCreateModelLowLatencyConvTraining(self):
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model_settings = self._modelSettings()
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with self.cached_session() as sess:
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fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]])
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logits, dropout_rate = models.create_model(
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fingerprint_input, model_settings, "low_latency_conv", True)
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self.assertIsNotNone(logits)
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self.assertIsNotNone(dropout_rate)
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self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
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self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_rate.name))
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@test_util.run_deprecated_v1
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def testCreateModelFullyConnectedTraining(self):
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model_settings = self._modelSettings()
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with self.cached_session() as sess:
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fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]])
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logits, dropout_rate = models.create_model(
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fingerprint_input, model_settings, "single_fc", True)
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self.assertIsNotNone(logits)
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self.assertIsNotNone(dropout_rate)
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self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
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self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_rate.name))
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def testCreateModelBadArchitecture(self):
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model_settings = self._modelSettings()
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with self.cached_session():
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fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]])
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with self.assertRaises(Exception) as e:
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models.create_model(fingerprint_input, model_settings,
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"bad_architecture", True)
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self.assertIn("not recognized", str(e.exception))
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@test_util.run_deprecated_v1
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def testCreateModelTinyConvTraining(self):
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model_settings = self._modelSettings()
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with self.cached_session() as sess:
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fingerprint_input = tf.zeros([1, model_settings["fingerprint_size"]])
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logits, dropout_rate = models.create_model(
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fingerprint_input, model_settings, "tiny_conv", True)
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self.assertIsNotNone(logits)
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self.assertIsNotNone(dropout_rate)
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self.assertIsNotNone(sess.graph.get_tensor_by_name(logits.name))
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self.assertIsNotNone(sess.graph.get_tensor_by_name(dropout_rate.name))
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if __name__ == "__main__":
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test.main()
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