Allow sample_rate to be a constant-value Tensor.

PiperOrigin-RevId: 257024106

tensorflow/python/kernel_tests/signal/mel_ops_test.py

@@ -20,8 +20,10 @@ from __future__ import print_function
 
 import numpy as np
 
+from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_util
 from tensorflow.python.framework import test_util as tf_test_util
 from tensorflow.python.kernel_tests.signal import test_util
 from tensorflow.python.ops import array_ops
@@ -95,6 +97,7 @@ def spectrogram_to_mel_matrix(num_mel_bins=20,
   Raises:
     ValueError: if frequency edges are incorrectly ordered.
   """
+  audio_sample_rate = tensor_util.constant_value(audio_sample_rate)
   nyquist_hertz = audio_sample_rate / 2.
   if lower_edge_hertz >= upper_edge_hertz:
     raise ValueError("lower_edge_hertz %.1f >= upper_edge_hertz %.1f" %
@@ -135,8 +138,10 @@ class LinearToMelTest(test.TestCase):
     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)
+        (80, 1025, 24000.0, 80.0, 12000.0, dtypes.float64),
     ]
     with self.session(use_gpu=True):
       for config in configs:
@@ -159,6 +164,9 @@ class LinearToMelTest(test.TestCase):
       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(
+          sample_rate=array_ops.placeholder(dtypes.float32))
     with self.assertRaises(ValueError):
       mel_ops.linear_to_mel_weight_matrix(lower_edge_hertz=-1)
     with self.assertRaises(ValueError):

tensorflow/python/ops/signal/mel_ops.py

@@ -20,6 +20,7 @@ from __future__ import print_function
 
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.signal import shape_ops
@@ -143,11 +144,21 @@ def linear_to_mel_weight_matrix(num_mel_bins=20,
   Raises:
     ValueError: If `num_mel_bins`/`num_spectrogram_bins`/`sample_rate` are not
       positive, `lower_edge_hertz` is negative, frequency edges are incorrectly
-      ordered, or `upper_edge_hertz` is larger than the Nyquist frequency.
+      ordered, `upper_edge_hertz` is larger than the Nyquist frequency, or
+      `sample_rate` is neither a Python float nor a constant Tensor.
 
   [mel]: https://en.wikipedia.org/wiki/Mel_scale
   """
   with ops.name_scope(name, 'linear_to_mel_weight_matrix') as name:
+    # Convert Tensor `sample_rate` to float, if possible.
+    if isinstance(sample_rate, ops.Tensor):
+      maybe_const_val = tensor_util.constant_value(sample_rate)
+      if maybe_const_val is not None:
+        sample_rate = maybe_const_val
+      else:
+        raise ValueError('`sample_rate` was a non-constant Tensor. Must be a '
+                         'Python float or a constant Tensor.')
+
     # Note: As num_spectrogram_bins is passed to `math_ops.linspace`
     # and the validation is already done in linspace (both in shape function
     # and in kernel), there is no need to validate num_spectrogram_bins here.