def testSpeechCommandsSum(self):
dataset_all = speechcommands.SPEECHCOMMANDS(self.root_dir)
dataset_train = speechcommands.SPEECHCOMMANDS(self.root_dir,
subset="training")
dataset_valid = speechcommands.SPEECHCOMMANDS(self.root_dir,
subset="validation")
dataset_test = speechcommands.SPEECHCOMMANDS(self.root_dir,
subset="testing")
assert len(dataset_train) + len(dataset_valid) + len(
dataset_test) == len(dataset_all)
def testSpeechCommandsNone(self):
dataset = speechcommands.SPEECHCOMMANDS(self.root_dir, subset=None)
num_samples = 0
for i, (data, sample_rate, label, speaker_id,
utterance_number) in enumerate(dataset):
self.assertEqual(data, self.samples[i][0], atol=5e-5, rtol=1e-8)
assert sample_rate == self.samples[i][1]
assert label == self.samples[i][2]
assert speaker_id == self.samples[i][3]
assert utterance_number == self.samples[i][4]
num_samples += 1
assert num_samples == len(self.samples)
def testSpeechCommandsSubsetTest(self):
dataset = speechcommands.SPEECHCOMMANDS(self.root_dir,
subset="testing")
self._testSpeechCommands(dataset, self.test_samples)
def testSpeechCommandsSubsetValid(self):
dataset = speechcommands.SPEECHCOMMANDS(self.root_dir,
subset="validation")
self._testSpeechCommands(dataset, self.valid_samples)
def testSpeechCommands_path(self):
dataset = speechcommands.SPEECHCOMMANDS(Path(self.root_dir))
self._testSpeechCommands(dataset, self.samples)