From b2cc256dabca983f417204ae3a2b382e6d1d5cc9 Mon Sep 17 00:00:00 2001 From: erogol Date: Tue, 14 Jul 2020 17:48:44 +0200 Subject: [PATCH] tflite inference for melgan models --- vocoder/tf/models/melgan_generator.py | 19 +++++++++++++++- .../tf/models/multiband_melgan_generator.py | 22 ++++++++++++++----- 2 files changed, 35 insertions(+), 6 deletions(-) diff --git a/vocoder/tf/models/melgan_generator.py b/vocoder/tf/models/melgan_generator.py index bf67f3d2..168fd29e 100644 --- a/vocoder/tf/models/melgan_generator.py +++ b/vocoder/tf/models/melgan_generator.py @@ -108,4 +108,21 @@ class MelganGenerator(tf.keras.models.Model): def build_inference(self): x = tf.random.uniform((1, self.in_channels, 4), dtype=tf.float32) - self(x, training=False) \ No newline at end of file + 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, :] \ No newline at end of file diff --git a/vocoder/tf/models/multiband_melgan_generator.py b/vocoder/tf/models/multiband_melgan_generator.py index c63ed06a..bdd333ed 100644 --- a/vocoder/tf/models/multiband_melgan_generator.py +++ b/vocoder/tf/models/multiband_melgan_generator.py @@ -30,11 +30,6 @@ class MultibandMelganGenerator(MelganGenerator): def pqmf_synthesis(self, 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): c = tf.transpose(c, perm=[0, 2, 1]) c = tf.expand_dims(c, 2) @@ -46,3 +41,20 @@ class MultibandMelganGenerator(MelganGenerator): o = tf.transpose(o, perm=[0, 3, 2, 1]) o = self.pqmf_layer.synthesis(o[:, :, 0, :]) 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