linter fixes and test fixes

TTS/bin/synthesize.py

@@ -2,26 +2,15 @@
 # -*- coding: utf-8 -*-
 
 import argparse
-import json
 import os
 import sys
 import string
-import time
 from argparse import RawTextHelpFormatter
 # pylint: disable=redefined-outer-name, unused-argument
 from pathlib import Path
 
-import numpy as np
-import torch
-from TTS.tts.utils.generic_utils import is_tacotron, setup_model
-from TTS.tts.utils.synthesis import synthesis
-from TTS.tts.utils.text.symbols import make_symbols, phonemes, symbols
-from TTS.tts.utils.io import load_checkpoint
-from TTS.utils.audio import AudioProcessor
-from TTS.utils.io import load_config
 from TTS.utils.manage import ModelManager
 from TTS.utils.synthesizer import Synthesizer
-from TTS.vocoder.utils.generic_utils import setup_generator, interpolate_vocoder_input
 
 
 def str2bool(v):
@@ -29,17 +18,16 @@ def str2bool(v):
         return v
     if v.lower() in ('yes', 'true', 't', 'y', '1'):
         return True
-    elif v.lower() in ('no', 'false', 'f', 'n', '0'):
+    if v.lower() in ('no', 'false', 'f', 'n', '0'):
         return False
-    else:
+    raise argparse.ArgumentTypeError('Boolean value expected.')
-        raise argparse.ArgumentTypeError('Boolean value expected.')
 
 
 if __name__ == "__main__":
-
+    # pylint: disable=bad-continuation
     parser = argparse.ArgumentParser(description='''Synthesize speech on command line.\n\n'''
 
-    '''You can either use your trained model or choose a model from the provided list.\n'''
+    '''You can either use your trained model or choose a model from the provided list.\n'''\
 
     '''
     Example runs:

TTS/tts/models/glow_tts.py

@@ -224,7 +224,7 @@ class GlowTts(nn.Module):
     def store_inverse(self):
         self.decoder.store_inverse()
 
-    def load_checkpoint(self, config, checkpoint_path, eval=False):
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         if eval:

TTS/tts/models/speedy_speech.py

@@ -188,10 +188,10 @@ class SpeedySpeech(nn.Module):
         o_dr_log = self.duration_predictor(o_en_dp.detach(), x_mask)
         o_dr = self.format_durations(o_dr_log, x_mask).squeeze(1)
         y_lengths = o_dr.sum(1)
-        o_de, attn= self._forward_decoder(o_en, o_en_dp, o_dr, x_mask, y_lengths, g=g)
+        o_de, attn = self._forward_decoder(o_en, o_en_dp, o_dr, x_mask, y_lengths, g=g)
         return o_de, attn
 
-    def load_checkpoint(self, config, checkpoint_path, eval=False):
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         if eval:

TTS/tts/models/tacotron_abstract.py

@@ -121,7 +121,7 @@ class TacotronAbstract(ABC, nn.Module):
     def inference(self):
         pass
 
-    def load_checkpoint(self, config, checkpoint_path, eval=False):
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         self.decoder.set_r(state['r'])

TTS/tts/utils/visual.py

@@ -50,7 +50,7 @@ def plot_spectrogram(spectrogram,
     spectrogram_ = spectrogram_.astype(
         np.float32) if spectrogram_.dtype == np.float16 else spectrogram_
     if ap is not None:
-        spectrogram_ = ap._denormalize(spectrogram_)  # pylint: disable=protected-access
+        spectrogram_ = ap.denormalize(spectrogram_)  # pylint: disable=protected-access
     fig = plt.figure(figsize=fig_size)
     plt.imshow(spectrogram_, aspect="auto", origin="lower")
     plt.colorbar()

TTS/utils/synthesizer.py

@@ -17,7 +17,7 @@ from TTS.tts.utils.text import make_symbols, phonemes, symbols
 
 
 class Synthesizer(object):
-    def __init__(self, tts_checkpoint, tts_config, vocoder_checkpoint, vocoder_config, use_cuda):
+    def __init__(self, tts_checkpoint, tts_config, vocoder_checkpoint=None, vocoder_config=None, use_cuda=False):
         """Encapsulation of tts and vocoder models for inference.
 
         TODO: handle multi-speaker and GST inference.
@@ -25,9 +25,9 @@ class Synthesizer(object):
         Args:
             tts_checkpoint (str): path to the tts model file.
             tts_config (str): path to the tts config file.
-            vocoder_checkpoint (str): path to the vocoder model file.
+            vocoder_checkpoint (str, optional): path to the vocoder model file. Defaults to None.
-            vocoder_config (str): path to the vocoder config file.
+            vocoder_config (str, optional): path to the vocoder config file. Defaults to None.
-            use_cuda (bool): enable/disable cuda.
+            use_cuda (bool, optional): enable/disable cuda. Defaults to False.
         """
         self.tts_checkpoint = tts_checkpoint
         self.tts_config = tts_config
@@ -38,6 +38,7 @@ class Synthesizer(object):
         self.vocoder_model = None
         self.num_speakers = 0
         self.tts_speakers = None
+        self.speaker_embedding_dim = None
         self.seg = self.get_segmenter("en")
         self.use_cuda = use_cuda
         if self.use_cuda:
@@ -116,7 +117,7 @@ class Synthesizer(object):
         print(sens)
 
         speaker_embedding = self.init_speaker(speaker_idx)
-        use_gl = not hasattr(self, 'vocoder_model')
+        use_gl = self.vocoder_model is None
 
         for sen in sens:
             # synthesize voice
@@ -134,17 +135,17 @@ class Synthesizer(object):
                 speaker_embedding=speaker_embedding)
             if not use_gl:
                 # denormalize tts output based on tts audio config
-                mel_postnet_spec = self.ap._denormalize(mel_postnet_spec.T).T
+                mel_postnet_spec = self.ap.denormalize(mel_postnet_spec.T).T
                 device_type = "cuda" if self.use_cuda else "cpu"
                 # renormalize spectrogram based on vocoder config
-                vocoder_input = self.vocoder_ap._normalize(mel_postnet_spec.T)
+                vocoder_input = self.vocoder_ap.normalize(mel_postnet_spec.T)
                 # compute scale factor for possible sample rate mismatch
-                scale_factor = [1,  self.vocoder_config['audio']['sample_rate'] / self.ap.sample_rate]
+                scale_factor = [1, self.vocoder_config['audio']['sample_rate'] / self.ap.sample_rate]
                 if scale_factor[1] != 1:
                     print(" > interpolating tts model output.")
                     vocoder_input = interpolate_vocoder_input(scale_factor, vocoder_input)
                 else:
-                    vocoder_input = torch.tensor(vocoder_input).unsqueeze(0)
+                    vocoder_input = torch.tensor(vocoder_input).unsqueeze(0)  # pylint: disable=not-callable
                 # run vocoder model
                 # [1, T, C]
                 waveform = self.vocoder_model.inference(vocoder_input.to(device_type))

TTS/vocoder/models/melgan_generator.py

@@ -96,7 +96,7 @@ class MelganGenerator(nn.Module):
                 except ValueError:
                     layer.remove_weight_norm()
 
-    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         if eval:

TTS/vocoder/models/parallel_wavegan_generator.py

@@ -158,7 +158,7 @@ class ParallelWaveganGenerator(torch.nn.Module):
         return self._get_receptive_field_size(self.layers, self.stacks,
                                               self.kernel_size)
 
-    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         if eval:

TTS/vocoder/models/wavegrad.py

@@ -177,7 +177,7 @@ class Wavegrad(nn.Module):
         self.y_conv = weight_norm(self.y_conv)
 
 
-    def load_checkpoint(self, config, checkpoint_path, eval=False):
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         if eval:

TTS/vocoder/models/wavernn.py

@@ -500,7 +500,7 @@ class WaveRNN(nn.Module):
 
         return unfolded
 
-     def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument
+    def load_checkpoint(self, config, checkpoint_path, eval=False):  # pylint: disable=unused-argument, redefined-builtin
         state = torch.load(checkpoint_path, map_location=torch.device('cpu'))
         self.load_state_dict(state['model'])
         if eval:

TTS/vocoder/utils/generic_utils.py

@@ -20,7 +20,7 @@ def interpolate_vocoder_input(scale_factor, spec):
         torch.tensor: interpolated spectrogram.
     """
     print(" > before interpolation :", spec.shape)
-    spec = torch.tensor(spec).unsqueeze(0).unsqueeze(0)
+    spec = torch.tensor(spec).unsqueeze(0).unsqueeze(0)  # pylint: disable=not-callable
     spec = torch.nn.functional.interpolate(spec,
                                            scale_factor=scale_factor,
                                            recompute_scale_factor=True,

tests/test_demo_server.py

@@ -2,7 +2,7 @@ import os
 import unittest
 
 from tests import get_tests_input_path, get_tests_output_path
-from TTS.server.synthesizer import Synthesizer
+from TTS.utils.synthesizer import Synthesizer
 from TTS.tts.utils.generic_utils import setup_model
 from TTS.tts.utils.io import save_checkpoint
 from TTS.tts.utils.text.symbols import make_symbols, phonemes, symbols
@@ -29,7 +29,7 @@ class DemoServerTest(unittest.TestCase):
         tts_root_path = get_tests_output_path()
         config['tts_checkpoint'] = os.path.join(tts_root_path, config['tts_checkpoint'])
         config['tts_config'] = os.path.join(tts_root_path, config['tts_config'])
-        synthesizer = Synthesizer(config)
+        synthesizer = Synthesizer(config['tts_checkpoint'], config['tts_config'], None, None)
         synthesizer.tts("Better this test works!!")
 
     def test_split_into_sentences(self):