def test_num_spectrogram_bins_dynamic(self):
num_spectrogram_bins = array_ops.placeholder_with_default(
ops.convert_to_tensor(129, dtype=dtypes.int32), shape=())
mel_matrix_np = spectrogram_to_mel_matrix(20, 129, 8000.0, 125.0,
3800.0)
mel_matrix = mel_ops.linear_to_mel_weight_matrix(
20, num_spectrogram_bins, 8000.0, 125.0, 3800.0)
self.assertAllClose(mel_matrix_np, mel_matrix, atol=3e-6)
def test_constant_folding(self):
"""Mel functions should be constant foldable."""
# TODO(rjryan): tf.bloat16 cannot be constant folded by Grappler.
for dtype in (dtypes.float32, dtypes.float64):
g = ops.Graph()
with g.as_default():
mel_matrix = mel_ops.linear_to_mel_weight_matrix(dtype=dtype)
rewritten_graph = test_util.grappler_optimize(g, [mel_matrix])
self.assertEqual(1, len(rewritten_graph.node))
def test_num_spectrogram_bins_dynamic(self):
with self.session(use_gpu=True):
num_spectrogram_bins = array_ops.placeholder(shape=(),
dtype=dtypes.int32)
mel_matrix_np = spectrogram_to_mel_matrix(
20, 129, 8000.0, 125.0, 3800.0)
mel_matrix = mel_ops.linear_to_mel_weight_matrix(
20, num_spectrogram_bins, 8000.0, 125.0, 3800.0)
self.assertAllClose(
mel_matrix_np,
mel_matrix.eval(feed_dict={num_spectrogram_bins: 129}), atol=3e-6)
def test_constant_folding(self, dtype):
"""Mel functions should be constant foldable."""
if context.executing_eagerly():
return
# TODO(rjryan): tf.bfloat16 cannot be constant folded by Grappler.
g = ops.Graph()
with g.as_default():
mel_matrix = mel_ops.linear_to_mel_weight_matrix(
sample_rate=constant_op.constant(8000.0, dtype=dtypes.float32),
dtype=dtype)
rewritten_graph = test_util.grappler_optimize(g, [mel_matrix])
self.assertLen(rewritten_graph.node, 1)
def test_matches_reference_implementation(
self, num_mel_bins, num_spectrogram_bins, sample_rate,
use_tensor_sample_rate, lower_edge_hertz, upper_edge_hertz, dtype):
if use_tensor_sample_rate:
sample_rate = constant_op.constant(sample_rate)
mel_matrix_np = spectrogram_to_mel_matrix(
num_mel_bins, num_spectrogram_bins, sample_rate, lower_edge_hertz,
upper_edge_hertz, dtype)
mel_matrix = mel_ops.linear_to_mel_weight_matrix(
num_mel_bins, num_spectrogram_bins, sample_rate, lower_edge_hertz,
upper_edge_hertz, dtype)
self.assertAllClose(mel_matrix_np, mel_matrix, atol=3e-6)
def test_matches_reference_implementation(self):
# Tuples of (num_mel_bins, num_spectrogram_bins, sample_rate,
# lower_edge_hertz, upper_edge_hertz) to test.
configs = [
# Defaults.
(20, 129, 8000.0, 125.0, 3800.0, dtypes.float64),
# Settings used by Tacotron (https://arxiv.org/abs/1703.10135).
(80, 1025, 24000.0, 80.0, 12000.0, dtypes.float64)
]
with self.session(use_gpu=True):
for config in configs:
mel_matrix_np = spectrogram_to_mel_matrix(*config)
mel_matrix = mel_ops.linear_to_mel_weight_matrix(*config)
self.assertAllClose(mel_matrix_np, mel_matrix.eval(), atol=3e-6)
def test_matches_reference_implementation(self):
# Tuples of (num_mel_bins, num_spectrogram_bins, sample_rate,
# lower_edge_hertz, upper_edge_hertz) to test.
configs = [
# Defaults.
(20, 129, 8000.0, 125.0, 3800.0, dtypes.float64),
# Same as above, but with a constant Tensor sample rate.
(20, 129, constant_op.constant(8000.0), 125.0, 3800.0,
dtypes.float64),
# Settings used by Tacotron (https://arxiv.org/abs/1703.10135).
(80, 1025, 24000.0, 80.0, 12000.0, dtypes.float64),
]
for config in configs:
mel_matrix_np = spectrogram_to_mel_matrix(*config)
mel_matrix = mel_ops.linear_to_mel_weight_matrix(*config)
self.assertAllClose(mel_matrix_np, mel_matrix, atol=3e-6)
def test_error(self):
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(num_mel_bins=0)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(num_spectrogram_bins=0)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(sample_rate=0.0)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(lower_edge_hertz=-1)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(lower_edge_hertz=100,
upper_edge_hertz=10)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(upper_edge_hertz=1000,
sample_rate=800)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(dtype=dtypes.int32)
def test_dtypes(self):
# LinSpace is not supported for tf.float16.
for dtype in (dtypes.bfloat16, dtypes.float32, dtypes.float64):
self.assertEqual(dtype,
mel_ops.linear_to_mel_weight_matrix(dtype=dtype).dtype)
def test_error(self):
# TODO(rjryan): Error types are different under eager.
if context.executing_eagerly():
return
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(num_mel_bins=0)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(sample_rate=0.0)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(lower_edge_hertz=-1)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(lower_edge_hertz=100,
upper_edge_hertz=10)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(upper_edge_hertz=1000,
sample_rate=800)
with self.assertRaises(ValueError):
mel_ops.linear_to_mel_weight_matrix(dtype=dtypes.int32)
def test_dtypes(self, dtype):
# LinSpace is not supported for tf.float16.
self.assertEqual(
dtype,
mel_ops.linear_to_mel_weight_matrix(dtype=dtype).dtype)
