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tflite inference for melgan models

This commit is contained in:
erogol 2020-07-14 17:48:44 +02:00
parent 2d596aa140
commit b2cc256dab
2 changed files with 35 additions and 6 deletions
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17
vocoder/tf/models/melgan_generator.py
View File

@ -109,3 +109,20 @@ class MelganGenerator(tf.keras.models.Model):
def build_inference(self): def build_inference(self):
x = tf.random.uniform((1, self.in_channels, 4), dtype=tf.float32) x = tf.random.uniform((1, self.in_channels, 4), dtype=tf.float32)
self(x, training=False) self(x, training=False)
@tf.function(
experimental_relax_shapes=True,
input_signature=[
tf.TensorSpec([1, None, None], dtype=tf.float32),
],)
def inference_tflite(self, c):
c = tf.transpose(c, perm=[0, 2, 1])
c = tf.expand_dims(c, 2)
# FIXME: TF had no replicate padding as in Torch
# c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
o = c
for layer in self.model_layers:
o = layer(o)
# o = self.model_layers(c)
o = tf.transpose(o, perm=[0, 3, 2, 1])
return o[:, :, 0, :]

22
vocoder/tf/models/multiband_melgan_generator.py
View File

@ -30,11 +30,6 @@ class MultibandMelganGenerator(MelganGenerator):
def pqmf_synthesis(self, x): def pqmf_synthesis(self, x):
return self.pqmf_layer.synthesis(x) return self.pqmf_layer.synthesis(x)
# def call(self, c, training=False):
# if training:
# raise NotImplementedError()
# return self.inference(c)
def inference(self, c): def inference(self, c):
c = tf.transpose(c, perm=[0, 2, 1]) c = tf.transpose(c, perm=[0, 2, 1])
c = tf.expand_dims(c, 2) c = tf.expand_dims(c, 2)
@ -46,3 +41,20 @@ class MultibandMelganGenerator(MelganGenerator):
o = tf.transpose(o, perm=[0, 3, 2, 1]) o = tf.transpose(o, perm=[0, 3, 2, 1])
o = self.pqmf_layer.synthesis(o[:, :, 0, :]) o = self.pqmf_layer.synthesis(o[:, :, 0, :])
return o return o
@tf.function(
experimental_relax_shapes=True,
input_signature=[
tf.TensorSpec([1, 80, None], dtype=tf.float32),
],)
def inference_tflite(self, c):
c = tf.transpose(c, perm=[0, 2, 1])
c = tf.expand_dims(c, 2)
# FIXME: TF had no replicate padding as in Torch
# c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
o = c
for layer in self.model_layers:
o = layer(o)
o = tf.transpose(o, perm=[0, 3, 2, 1])
o = self.pqmf_layer.synthesis(o[:, :, 0, :])
return o