text: # Copyright 2018 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 AudioMicrofrontend."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import tensorflow as tf
  
  from tensorflow.lite.experimental.microfrontend.python.ops import audio_microfrontend_op as frontend_op
  
  SAMPLE_RATE = 1000
  WINDOW_SIZE = 25
  WINDOW_STEP = 10
  NUM_CHANNELS = 2
  UPPER_BAND_LIMIT = 450.0
  LOWER_BAND_LIMIT = 8.0
  SMOOTHING_BITS = 10
  
  
  class AudioFeatureGenerationTest(tf.test.TestCase):
  
    def testSimple(self):
      with self.test_session():
        audio = tf.constant(
            [0, 32767, 0, -32768] * ((WINDOW_SIZE + 4 * WINDOW_STEP) // 4),
            tf.int16)
        filterbanks = frontend_op.audio_microfrontend(
            audio,
            sample_rate=SAMPLE_RATE,
            window_size=WINDOW_SIZE,
            window_step=WINDOW_STEP,
            num_channels=NUM_CHANNELS,
            upper_band_limit=UPPER_BAND_LIMIT,
            lower_band_limit=LOWER_BAND_LIMIT,
            smoothing_bits=SMOOTHING_BITS,
            enable_pcan=True)
        self.assertAllEqual(filterbanks.eval(),
                            [[479, 425], [436, 378], [410, 350], [391, 325]])
  
    def testSimpleFloatScaled(self):
      with self.test_session():
        audio = tf.constant(
            [0, 32767, 0, -32768] * ((WINDOW_SIZE + 4 * WINDOW_STEP) // 4),
            tf.int16)
        filterbanks = frontend_op.audio_microfrontend(
            audio,
            sample_rate=SAMPLE_RATE,
            window_size=WINDOW_SIZE,
            window_step=WINDOW_STEP,
            num_channels=NUM_CHANNELS,
            upper_band_limit=UPPER_BAND_LIMIT,
            lower_band_limit=LOWER_BAND_LIMIT,
            smoothing_bits=SMOOTHING_BITS,
            enable_pcan=True,
            out_scale=64,
            out_type=tf.float32)
        self.assertAllEqual(filterbanks.eval(),
                            [[7.484375, 6.640625], [6.8125, 5.90625],
                             [6.40625, 5.46875], [6.109375, 5.078125]])
  
    def testStacking(self):
      with self.test_session():
        audio = tf.constant(
            [0, 32767, 0, -32768] * ((WINDOW_SIZE + 4 * WINDOW_STEP) // 4),
            tf.int16)
        filterbanks = frontend_op.audio_microfrontend(
            audio,
            sample_rate=SAMPLE_RATE,
            window_size=WINDOW_SIZE,
            window_step=WINDOW_STEP,
            num_channels=NUM_CHANNELS,
            upper_band_limit=UPPER_BAND_LIMIT,
            lower_band_limit=LOWER_BAND_LIMIT,
            smoothing_bits=SMOOTHING_BITS,
            enable_pcan=True,
            right_context=1,
            frame_stride=2)
        self.assertAllEqual(filterbanks.eval(),
                            [[479, 425, 436, 378], [410, 350, 391, 325]])
  
    def testStackingWithOverlap(self):
      with self.test_session():
        audio = tf.constant(
            [0, 32767, 0, -32768] * ((WINDOW_SIZE + 4 * WINDOW_STEP) // 4),
            tf.int16)
        filterbanks = frontend_op.audio_microfrontend(
            audio,
            sample_rate=SAMPLE_RATE,
            window_size=WINDOW_SIZE,
            window_step=WINDOW_STEP,
            num_channels=NUM_CHANNELS,
            upper_band_limit=UPPER_BAND_LIMIT,
            lower_band_limit=LOWER_BAND_LIMIT,
            smoothing_bits=SMOOTHING_BITS,
            enable_pcan=True,
            left_context=1,
            right_context=1)
        self.assertAllEqual(
            self.evaluate(filterbanks),
            [[479, 425, 479, 425, 436, 378], [479, 425, 436, 378, 410, 350],
             [436, 378, 410, 350, 391, 325], [410, 350, 391, 325, 391, 325]])
  
    def testStackingDropFrame(self):
      with self.test_session():
        audio = tf.constant(
            [0, 32767, 0, -32768] * ((WINDOW_SIZE + 4 * WINDOW_STEP) // 4),
            tf.int16)
        filterbanks = frontend_op.audio_microfrontend(
            audio,
            sample_rate=SAMPLE_RATE,
            window_size=WINDOW_SIZE,
            window_step=WINDOW_STEP,
            num_channels=NUM_CHANNELS,
            upper_band_limit=UPPER_BAND_LIMIT,
            lower_band_limit=LOWER_BAND_LIMIT,
            smoothing_bits=SMOOTHING_BITS,
            enable_pcan=True,
            left_context=1,
            frame_stride=2)
        self.assertAllEqual(filterbanks.eval(),
                            [[479, 425, 479, 425], [436, 378, 410, 350]])
  
    def testZeroPadding(self):
      with self.test_session():
        audio = tf.constant(
            [0, 32767, 0, -32768] * ((WINDOW_SIZE + 7 * WINDOW_STEP) // 4),
            tf.int16)
        filterbanks = frontend_op.audio_microfrontend(
            audio,
            sample_rate=SAMPLE_RATE,
            window_size=WINDOW_SIZE,
            window_step=WINDOW_STEP,
            num_channels=NUM_CHANNELS,
            upper_band_limit=UPPER_BAND_LIMIT,
            lower_band_limit=LOWER_BAND_LIMIT,
            smoothing_bits=SMOOTHING_BITS,
            enable_pcan=True,
            left_context=2,
            frame_stride=3,
            zero_padding=True)
        self.assertAllEqual(
            self.evaluate(filterbanks),
            [[0, 0, 0, 0, 479, 425], [436, 378, 410, 350, 391, 325],
             [374, 308, 362, 292, 352, 275]])
  
  
  if __name__ == '__main__':
    tf.test.main()
  