rename the project to old TTS

TTS/bin/compute_statistics.py

@@ -7,9 +7,9 @@ import argparse
 import numpy as np
 from tqdm import tqdm
 
-from mozilla_voice_tts.tts.datasets.preprocess import load_meta_data
+from TTS.tts.datasets.preprocess import load_meta_data
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
-from mozilla_voice_tts.utils.audio import AudioProcessor
+from TTS.utils.audio import AudioProcessor
 
 def main():
     """Run preprocessing process."""

TTS/bin/convert_melgan_tflite.py

@@ -2,10 +2,10 @@
 
 import argparse
 
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
-from mozilla_voice_tts.vocoder.tf.utils.generic_utils import setup_generator
+from TTS.vocoder.tf.utils.generic_utils import setup_generator
-from mozilla_voice_tts.vocoder.tf.utils.io import load_checkpoint
+from TTS.vocoder.tf.utils.io import load_checkpoint
-from mozilla_voice_tts.vocoder.tf.utils.tflite import convert_melgan_to_tflite
+from TTS.vocoder.tf.utils.tflite import convert_melgan_to_tflite
 
 
 parser = argparse.ArgumentParser()

TTS/bin/convert_melgan_torch_to_tf.py

@@ -6,13 +6,13 @@ import tensorflow as tf
 import torch
 from fuzzywuzzy import fuzz
 
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
-from mozilla_voice_tts.vocoder.tf.utils.convert_torch_to_tf_utils import (
+from TTS.vocoder.tf.utils.convert_torch_to_tf_utils import (
     compare_torch_tf, convert_tf_name, transfer_weights_torch_to_tf)
-from mozilla_voice_tts.vocoder.tf.utils.generic_utils import \
+from TTS.vocoder.tf.utils.generic_utils import \
     setup_generator as setup_tf_generator
-from mozilla_voice_tts.vocoder.tf.utils.io import save_checkpoint
+from TTS.vocoder.tf.utils.io import save_checkpoint
-from mozilla_voice_tts.vocoder.utils.generic_utils import setup_generator
+from TTS.vocoder.utils.generic_utils import setup_generator
 
 # prevent GPU use
 os.environ['CUDA_VISIBLE_DEVICES'] = ''

TTS/bin/convert_tacotron2_tflite.py

@@ -2,11 +2,11 @@
 
 import argparse
 
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
-from mozilla_voice_tts.tts.utils.text.symbols import symbols, phonemes
+from TTS.tts.utils.text.symbols import symbols, phonemes
-from mozilla_voice_tts.tts.tf.utils.generic_utils import setup_model
+from TTS.tts.tf.utils.generic_utils import setup_model
-from mozilla_voice_tts.tts.tf.utils.io import load_checkpoint
+from TTS.tts.tf.utils.io import load_checkpoint
-from mozilla_voice_tts.tts.tf.utils.tflite import convert_tacotron2_to_tflite
+from TTS.tts.tf.utils.tflite import convert_tacotron2_to_tflite
 
 
 parser = argparse.ArgumentParser()

TTS/bin/convert_tacotron2_torch_to_tf.py

@@ -11,13 +11,13 @@ import numpy as np
 import tensorflow as tf
 import torch
 from fuzzywuzzy import fuzz
-from mozilla_voice_tts.tts.tf.models.tacotron2 import Tacotron2
+from TTS.tts.tf.models.tacotron2 import Tacotron2
-from mozilla_voice_tts.tts.tf.utils.convert_torch_to_tf_utils import (
+from TTS.tts.tf.utils.convert_torch_to_tf_utils import (
     compare_torch_tf, convert_tf_name, transfer_weights_torch_to_tf)
-from mozilla_voice_tts.tts.tf.utils.generic_utils import save_checkpoint
+from TTS.tts.tf.utils.generic_utils import save_checkpoint
-from mozilla_voice_tts.tts.utils.generic_utils import setup_model
+from TTS.tts.utils.generic_utils import setup_model
-from mozilla_voice_tts.tts.utils.text.symbols import phonemes, symbols
+from TTS.tts.utils.text.symbols import phonemes, symbols
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
 
 sys.path.append('/home/erogol/Projects')
 os.environ['CUDA_VISIBLE_DEVICES'] = ''

TTS/bin/synthesize.py

@@ -10,12 +10,12 @@ import time
 
 import torch
 
-from mozilla_voice_tts.tts.utils.generic_utils import setup_model
+from TTS.tts.utils.generic_utils import setup_model
-from mozilla_voice_tts.tts.utils.synthesis import synthesis
+from TTS.tts.utils.synthesis import synthesis
-from mozilla_voice_tts.tts.utils.text.symbols import make_symbols, phonemes, symbols
+from TTS.tts.utils.text.symbols import make_symbols, phonemes, symbols
-from mozilla_voice_tts.utils.audio import AudioProcessor
+from TTS.utils.audio import AudioProcessor
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
-from mozilla_voice_tts.vocoder.utils.generic_utils import setup_generator
+from TTS.vocoder.utils.generic_utils import setup_generator
 
 
 def tts(model, vocoder_model, text, CONFIG, use_cuda, ap, use_gl, speaker_fileid, speaker_embedding=None, gst_style=None):

TTS/bin/train_encoder.py

@@ -10,21 +10,21 @@ import traceback
 import torch
 from torch.utils.data import DataLoader
 
-from mozilla_voice_tts.speaker_encoder.dataset import MyDataset
+from TTS.speaker_encoder.dataset import MyDataset
-from mozilla_voice_tts.speaker_encoder.generic_utils import save_best_model
+from TTS.speaker_encoder.generic_utils import save_best_model
-from mozilla_voice_tts.speaker_encoder.losses import GE2ELoss, AngleProtoLoss
+from TTS.speaker_encoder.losses import GE2ELoss, AngleProtoLoss
-from mozilla_voice_tts.speaker_encoder.model import SpeakerEncoder
+from TTS.speaker_encoder.model import SpeakerEncoder
-from mozilla_voice_tts.speaker_encoder.visual import plot_embeddings
+from TTS.speaker_encoder.visual import plot_embeddings
-from mozilla_voice_tts.tts.datasets.preprocess import load_meta_data
+from TTS.tts.datasets.preprocess import load_meta_data
-from mozilla_voice_tts.utils.generic_utils import (
+from TTS.utils.generic_utils import (
     create_experiment_folder, get_git_branch, remove_experiment_folder,
     set_init_dict)
-from mozilla_voice_tts.utils.io import copy_config_file, load_config
+from TTS.utils.io import copy_config_file, load_config
-from mozilla_voice_tts.utils.audio import AudioProcessor
+from TTS.utils.audio import AudioProcessor
-from mozilla_voice_tts.utils.generic_utils import count_parameters
+from TTS.utils.generic_utils import count_parameters
-from mozilla_voice_tts.utils.radam import RAdam
+from TTS.utils.radam import RAdam
-from mozilla_voice_tts.utils.tensorboard_logger import TensorboardLogger
+from TTS.utils.tensorboard_logger import TensorboardLogger
-from mozilla_voice_tts.utils.training import NoamLR, check_update
+from TTS.utils.training import NoamLR, check_update
 
 torch.backends.cudnn.enabled = True
 torch.backends.cudnn.benchmark = True

TTS/bin/train_tts.py

@@ -11,39 +11,30 @@ import traceback
 import numpy as np
 import torch
 from torch.utils.data import DataLoader
-
+from TTS.tts.datasets.preprocess import load_meta_data
-from mozilla_voice_tts.tts.datasets.preprocess import load_meta_data
+from TTS.tts.datasets.TTSDataset import MyDataset
-from mozilla_voice_tts.tts.datasets.TTSDataset import MyDataset
+from TTS.tts.layers.losses import TacotronLoss
-from mozilla_voice_tts.tts.layers.losses import TacotronLoss
+from TTS.tts.utils.distribute import (DistributedSampler,
-from mozilla_voice_tts.tts.utils.distribute import (DistributedSampler,
                                       apply_gradient_allreduce,
-                                                    init_distributed,
+                                      init_distributed, reduce_tensor)
-                                                    reduce_tensor)
+from TTS.tts.utils.generic_utils import check_config, setup_model
-from mozilla_voice_tts.tts.utils.generic_utils import check_config, setup_model
+from TTS.tts.utils.io import save_best_model, save_checkpoint
-from mozilla_voice_tts.tts.utils.io import save_best_model, save_checkpoint
+from TTS.tts.utils.measures import alignment_diagonal_score
-from mozilla_voice_tts.tts.utils.measures import alignment_diagonal_score
+from TTS.tts.utils.speakers import (get_speakers, load_speaker_mapping,
-from mozilla_voice_tts.tts.utils.speakers import (get_speakers,
-                                                  load_speaker_mapping,
                                     save_speaker_mapping)
-from mozilla_voice_tts.tts.utils.synthesis import synthesis
+from TTS.tts.utils.synthesis import synthesis
-from mozilla_voice_tts.tts.utils.text.symbols import (make_symbols, phonemes,
+from TTS.tts.utils.text.symbols import make_symbols, phonemes, symbols
-                                                      symbols)
+from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
-from mozilla_voice_tts.tts.utils.visual import plot_alignment, plot_spectrogram
+from TTS.utils.audio import AudioProcessor
-from mozilla_voice_tts.utils.audio import AudioProcessor
+from TTS.utils.console_logger import ConsoleLogger
-from mozilla_voice_tts.utils.console_logger import ConsoleLogger
+from TTS.utils.generic_utils import (KeepAverage, count_parameters,
-from mozilla_voice_tts.utils.generic_utils import (KeepAverage,
+                                     create_experiment_folder, get_git_branch,
-                                                   count_parameters,
+                                     remove_experiment_folder, set_init_dict)
-                                                   create_experiment_folder,
+from TTS.utils.io import copy_config_file, load_config
-                                                   get_git_branch,
+from TTS.utils.radam import RAdam
-                                                   remove_experiment_folder,
+from TTS.utils.tensorboard_logger import TensorboardLogger
-                                                   set_init_dict)
+from TTS.utils.training import (NoamLR, adam_weight_decay, check_update,
-from mozilla_voice_tts.utils.io import copy_config_file, load_config
+                                gradual_training_scheduler, set_weight_decay,
-from mozilla_voice_tts.utils.radam import RAdam
-from mozilla_voice_tts.utils.tensorboard_logger import TensorboardLogger
-from mozilla_voice_tts.utils.training import (NoamLR, adam_weight_decay,
-                                              check_update,
-                                              gradual_training_scheduler,
-                                              set_weight_decay,
                                 setup_torch_training_env)
 
 use_cuda, num_gpus = setup_torch_training_env(True, False)

TTS/bin/train_vocoder.py

@@ -8,30 +8,23 @@ from inspect import signature
 
 import torch
 from torch.utils.data import DataLoader
-
+from TTS.utils.audio import AudioProcessor
-from mozilla_voice_tts.utils.audio import AudioProcessor
+from TTS.utils.console_logger import ConsoleLogger
-from mozilla_voice_tts.utils.console_logger import ConsoleLogger
+from TTS.utils.generic_utils import (KeepAverage, count_parameters,
-from mozilla_voice_tts.utils.generic_utils import (KeepAverage,
+                                     create_experiment_folder, get_git_branch,
-                                                   count_parameters,
+                                     remove_experiment_folder, set_init_dict)
-                                                   create_experiment_folder,
+from TTS.utils.io import copy_config_file, load_config
-                                                   get_git_branch,
+from TTS.utils.radam import RAdam
-                                                   remove_experiment_folder,
+from TTS.utils.tensorboard_logger import TensorboardLogger
-                                                   set_init_dict)
+from TTS.utils.training import setup_torch_training_env
-from mozilla_voice_tts.utils.io import copy_config_file, load_config
+from TTS.vocoder.datasets.gan_dataset import GANDataset
-from mozilla_voice_tts.utils.radam import RAdam
+from TTS.vocoder.datasets.preprocess import load_wav_data, load_wav_feat_data
-from mozilla_voice_tts.utils.tensorboard_logger import TensorboardLogger
-from mozilla_voice_tts.utils.training import setup_torch_training_env
-from mozilla_voice_tts.vocoder.datasets.gan_dataset import GANDataset
-from mozilla_voice_tts.vocoder.datasets.preprocess import (load_wav_data,
-                                                           load_wav_feat_data)
 # from distribute import (DistributedSampler, apply_gradient_allreduce,
 #                         init_distributed, reduce_tensor)
-from mozilla_voice_tts.vocoder.layers.losses import (DiscriminatorLoss,
+from TTS.vocoder.layers.losses import DiscriminatorLoss, GeneratorLoss
-                                                     GeneratorLoss)
+from TTS.vocoder.utils.generic_utils import (plot_results, setup_discriminator,
-from mozilla_voice_tts.vocoder.utils.generic_utils import (plot_results,
-                                                           setup_discriminator,
                                              setup_generator)
-from mozilla_voice_tts.vocoder.utils.io import save_best_model, save_checkpoint
+from TTS.vocoder.utils.io import save_best_model, save_checkpoint
 
 use_cuda, num_gpus = setup_torch_training_env(True, True)
 

TTS/server/README.md

@@ -15,7 +15,7 @@ If you have the environment set already for TTS, then you can directly call ```s
 3. source /tmp/venv/bin/activate
 4. pip install -U pip setuptools wheel
 5. pip install -U https//example.com/url/to/python/package.whl
-6. python -m mozilla_voice_tts.server.server
+6. python -m TTS.server.server
 
 You can now open http://localhost:5002 in a browser
 

TTS/server/server.py

@@ -3,7 +3,7 @@ import argparse
 import os
 
 from flask import Flask, request, render_template, send_file
-from mozilla_voice_tts.server.synthesizer import Synthesizer
+from TTS.server.synthesizer import Synthesizer
 
 
 def create_argparser():
@@ -18,8 +18,8 @@ def create_argparser():
     parser.add_argument('--wavernn_checkpoint', type=str, default=None, help='path to WaveRNN checkpoint file.')
     parser.add_argument('--wavernn_config', type=str, default=None, help='path to WaveRNN config file.')
     parser.add_argument('--is_wavernn_batched', type=convert_boolean, default=False, help='true to use batched WaveRNN.')
-    parser.add_argument('--vocoder_config', type=str, default=None, help='path to mozilla_voice_tts.vocoder config file.')
+    parser.add_argument('--vocoder_config', type=str, default=None, help='path to TTS.vocoder config file.')
-    parser.add_argument('--vocoder_checkpoint', type=str, default=None, help='path to mozilla_voice_tts.vocoder checkpoint file.')
+    parser.add_argument('--vocoder_checkpoint', type=str, default=None, help='path to TTS.vocoder checkpoint file.')
     parser.add_argument('--port', type=int, default=5002, help='port to listen on.')
     parser.add_argument('--use_cuda', type=convert_boolean, default=False, help='true to use CUDA.')
     parser.add_argument('--debug', type=convert_boolean, default=False, help='true to enable Flask debug mode.')

TTS/server/synthesizer.py

@@ -6,16 +6,16 @@ import numpy as np
 import torch
 import pysbd
 
-from mozilla_voice_tts.utils.audio import AudioProcessor
+from TTS.utils.audio import AudioProcessor
-from mozilla_voice_tts.utils.io import load_config
+from TTS.utils.io import load_config
-from mozilla_voice_tts.tts.utils.generic_utils import setup_model
+from TTS.tts.utils.generic_utils import setup_model
-from mozilla_voice_tts.tts.utils.speakers import load_speaker_mapping
+from TTS.tts.utils.speakers import load_speaker_mapping
-from mozilla_voice_tts.vocoder.utils.generic_utils import setup_generator
+from TTS.vocoder.utils.generic_utils import setup_generator
 # pylint: disable=unused-wildcard-import
 # pylint: disable=wildcard-import
-from mozilla_voice_tts.tts.utils.synthesis import *
+from TTS.tts.utils.synthesis import *
 
-from mozilla_voice_tts.tts.utils.text import make_symbols, phonemes, symbols
+from TTS.tts.utils.text import make_symbols, phonemes, symbols
 
 
 class Synthesizer(object):

TTS/speaker_encoder/README.md

@@ -10,7 +10,7 @@ Below is an example showing embedding results of various speakers. You can gener
 
 Download a pretrained model from [Released Models](https://github.com/mozilla/TTS/wiki/Released-Models) page.
 
-To run the code, you need to follow the same flow as in mozilla_voice_tts.
+To run the code, you need to follow the same flow as in TTS.
 
 - Define 'config.json' for your needs. Note that, audio parameters should match your TTS model.
 - Example training call ```python speaker_encoder/train.py --config_path speaker_encoder/config.json --data_path ~/Data/Libri-TTS/train-clean-360```

TTS/speaker_encoder/compute_embeddings.py

@@ -6,9 +6,9 @@ import numpy as np
 from tqdm import tqdm
 
 import torch
-from mozilla_voice_tts.speaker_encoder.model import SpeakerEncoder
+from TTS.speaker_encoder.model import SpeakerEncoder
-from mozilla_voice_tts.tts.utils.audio import AudioProcessor
+from TTS.tts.utils.audio import AudioProcessor
-from mozilla_voice_tts.tts.utils.generic_utils import load_config
+from TTS.tts.utils.generic_utils import load_config
 
 parser = argparse.ArgumentParser(
     description='Compute embedding vectors for each wav file in a dataset. ')

TTS/speaker_encoder/dataset.py

@@ -9,7 +9,7 @@ class MyDataset(Dataset):
                  num_utter_per_speaker=10, skip_speakers=False, verbose=False):
         """
         Args:
-            ap (mozilla_voice_tts.tts.utils.AudioProcessor): audio processor object.
+            ap (TTS.tts.utils.AudioProcessor): audio processor object.
             meta_data (list): list of dataset instances.
             seq_len (int): voice segment length in seconds.
             verbose (bool): print diagnostic information.

TTS/tts/datasets/TTSDataset.py

@@ -5,8 +5,8 @@ import torch
 import random
 from torch.utils.data import Dataset
 
-from mozilla_voice_tts.tts.utils.text import text_to_sequence, phoneme_to_sequence, pad_with_eos_bos
+from TTS.tts.utils.text import text_to_sequence, phoneme_to_sequence, pad_with_eos_bos
-from mozilla_voice_tts.tts.utils.data import prepare_data, prepare_tensor, prepare_stop_target
+from TTS.tts.utils.data import prepare_data, prepare_tensor, prepare_stop_target
 
 
 class MyDataset(Dataset):
@@ -31,7 +31,7 @@ class MyDataset(Dataset):
             outputs_per_step (int): number of time frames predicted per step.
             text_cleaner (str): text cleaner used for the dataset.
             compute_linear_spec (bool): compute linear spectrogram if True.
-            ap (mozilla_voice_tts.tts.utils.AudioProcessor): audio processor object.
+            ap (TTS.tts.utils.AudioProcessor): audio processor object.
             meta_data (list): list of dataset instances.
             batch_group_size (int): (0) range of batch randomization after sorting
                 sequences by length.

TTS/tts/datasets/preprocess.py

@@ -2,7 +2,7 @@ import os
 from glob import glob
 import re
 import sys
-from mozilla_voice_tts.tts.utils.generic_utils import split_dataset
+from TTS.tts.utils.generic_utils import split_dataset
 
 
 def load_meta_data(datasets):

TTS/tts/layers/losses.py

@@ -2,7 +2,7 @@ import numpy as np
 import torch
 from torch import nn
 from torch.nn import functional
-from mozilla_voice_tts.tts.utils.generic_utils import sequence_mask
+from TTS.tts.utils.generic_utils import sequence_mask
 
 
 class L1LossMasked(nn.Module):

TTS/tts/models/tacotron.py

@@ -2,9 +2,9 @@
 import torch
 from torch import nn
 
-from mozilla_voice_tts.tts.layers.gst_layers import GST
+from TTS.tts.layers.gst_layers import GST
-from mozilla_voice_tts.tts.layers.tacotron import Decoder, Encoder, PostCBHG
+from TTS.tts.layers.tacotron import Decoder, Encoder, PostCBHG
-from mozilla_voice_tts.tts.models.tacotron_abstract import TacotronAbstract
+from TTS.tts.models.tacotron_abstract import TacotronAbstract
 
 
 class Tacotron(TacotronAbstract):

TTS/tts/models/tacotron2.py

@@ -1,9 +1,9 @@
 import torch
 from torch import nn
 
-from mozilla_voice_tts.tts.layers.gst_layers import GST
+from TTS.tts.layers.gst_layers import GST
-from mozilla_voice_tts.tts.layers.tacotron2 import Decoder, Encoder, Postnet
+from TTS.tts.layers.tacotron2 import Decoder, Encoder, Postnet
-from mozilla_voice_tts.tts.models.tacotron_abstract import TacotronAbstract
+from TTS.tts.models.tacotron_abstract import TacotronAbstract
 
 # TODO: match function arguments with tacotron
 class Tacotron2(TacotronAbstract):

TTS/tts/models/tacotron_abstract.py

@@ -4,7 +4,7 @@ from abc import ABC, abstractmethod
 import torch
 from torch import nn
 
-from mozilla_voice_tts.tts.utils.generic_utils import sequence_mask
+from TTS.tts.utils.generic_utils import sequence_mask
 
 
 class TacotronAbstract(ABC, nn.Module):

TTS/tts/tf/layers/tacotron2.py

@@ -1,7 +1,7 @@
 import tensorflow as tf
 from tensorflow import keras
-from mozilla_voice_tts.tts.tf.utils.tf_utils import shape_list
+from TTS.tts.tf.utils.tf_utils import shape_list
-from mozilla_voice_tts.tts.tf.layers.common_layers import Prenet, Attention
+from TTS.tts.tf.layers.common_layers import Prenet, Attention
 # from tensorflow_addons.seq2seq import AttentionWrapper
 
 # NOTE: linter has a problem with the current TF release

TTS/tts/tf/models/tacotron2.py

@@ -1,8 +1,8 @@
 import tensorflow as tf
 from tensorflow import keras
 
-from mozilla_voice_tts.tts.tf.layers.tacotron2 import Encoder, Decoder, Postnet
+from TTS.tts.tf.layers.tacotron2 import Encoder, Decoder, Postnet
-from mozilla_voice_tts.tts.tf.utils.tf_utils import shape_list
+from TTS.tts.tf.utils.tf_utils import shape_list
 
 
 #pylint: disable=too-many-ancestors, abstract-method

TTS/tts/tf/utils/generic_utils.py

@@ -77,7 +77,7 @@ def count_parameters(model, c):
 
 def setup_model(num_chars, num_speakers, c, enable_tflite=False):
     print(" > Using model: {}".format(c.model))
-    MyModel = importlib.import_module('mozilla_voice_tts.tts.tf.models.' + c.model.lower())
+    MyModel = importlib.import_module('TTS.tts.tf.models.' + c.model.lower())
     MyModel = getattr(MyModel, c.model)
     if c.model.lower() in "tacotron":
         raise NotImplementedError(' [!] Tacotron model is not ready.')

TTS/tts/utils/generic_utils.py

@@ -3,7 +3,7 @@ import importlib
 import numpy as np
 from collections import Counter
 
-from mozilla_voice_tts.utils.generic_utils import check_argument
+from TTS.utils.generic_utils import check_argument
 
 
 def split_dataset(items):
@@ -46,7 +46,7 @@ def sequence_mask(sequence_length, max_len=None):
 
 def setup_model(num_chars, num_speakers, c, speaker_embedding_dim=None):
     print(" > Using model: {}".format(c.model))
-    MyModel = importlib.import_module('mozilla_voice_tts.tts.models.' + c.model.lower())
+    MyModel = importlib.import_module('TTS.tts.models.' + c.model.lower())
     MyModel = getattr(MyModel, c.model)
     if c.model.lower() in "tacotron":
         model = MyModel(num_chars=num_chars,
@@ -197,7 +197,7 @@ def check_config(c):
 
     # dataloading
     # pylint: disable=import-outside-toplevel
-    from mozilla_voice_tts.tts.utils.text import cleaners
+    from TTS.tts.utils.text import cleaners
     check_argument('text_cleaner', c, restricted=True, val_type=str, enum_list=dir(cleaners))
     check_argument('enable_eos_bos_chars', c, restricted=True, val_type=bool)
     check_argument('num_loader_workers', c, restricted=True, val_type=int, min_val=0)

TTS/tts/utils/synthesis.py

@@ -183,11 +183,11 @@ def synthesis(model,
     """Synthesize voice for the given text.
 
         Args:
-            model (mozilla_voice_tts.tts.models): model to synthesize.
+            model (TTS.tts.models): model to synthesize.
             text (str): target text
             CONFIG (dict): config dictionary to be loaded from config.json.
             use_cuda (bool): enable cuda.
-            ap (mozilla_voice_tts.tts.utils.audio.AudioProcessor): audio processor to process
+            ap (TTS.tts.utils.audio.AudioProcessor): audio processor to process
                 model outputs.
             speaker_id (int): id of speaker
             style_wav (str): Uses for style embedding of GST.

TTS/tts/utils/text/__init__.py

@@ -4,8 +4,8 @@ import re
 from packaging import version
 import phonemizer
 from phonemizer.phonemize import phonemize
-from mozilla_voice_tts.tts.utils.text import cleaners
+from TTS.tts.utils.text import cleaners
-from mozilla_voice_tts.tts.utils.text.symbols import make_symbols, symbols, phonemes, _phoneme_punctuations, _bos, \
+from TTS.tts.utils.text.symbols import make_symbols, symbols, phonemes, _phoneme_punctuations, _bos, \
     _eos
 
 # pylint: disable=unnecessary-comprehension

TTS/tts/utils/visual.py

@@ -3,7 +3,7 @@ import librosa
 import matplotlib
 matplotlib.use('Agg')
 import matplotlib.pyplot as plt
-from mozilla_voice_tts.tts.utils.text import phoneme_to_sequence, sequence_to_phoneme
+from TTS.tts.utils.text import phoneme_to_sequence, sequence_to_phoneme
 
 
 def plot_alignment(alignment, info=None, fig_size=(16, 10), title=None, output_fig=False):

TTS/utils/audio.py

@@ -5,7 +5,7 @@ import scipy.io.wavfile
 import scipy.signal
 import pyworld as pw
 
-from mozilla_voice_tts.tts.utils.data import StandardScaler
+from TTS.tts.utils.data import StandardScaler
 
 #pylint: disable=too-many-public-methods
 class AudioProcessor(object):

TTS/utils/console_logger.py

@@ -1,5 +1,5 @@
 import datetime
-from mozilla_voice_tts.utils.io import AttrDict
+from TTS.utils.io import AttrDict
 
 
 tcolors = AttrDict({

TTS/vocoder/models/melgan_generator.py

@@ -2,7 +2,7 @@ import torch
 from torch import nn
 from torch.nn.utils import weight_norm
 
-from mozilla_voice_tts.vocoder.layers.melgan import ResidualStack
+from TTS.vocoder.layers.melgan import ResidualStack
 
 
 class MelganGenerator(nn.Module):

TTS/vocoder/models/melgan_multiscale_discriminator.py

@@ -1,6 +1,6 @@
 from torch import nn
 
-from mozilla_voice_tts.vocoder.models.melgan_discriminator import MelganDiscriminator
+from TTS.vocoder.models.melgan_discriminator import MelganDiscriminator
 
 
 class MelganMultiscaleDiscriminator(nn.Module):

TTS/vocoder/models/multiband_melgan_generator.py

@@ -1,7 +1,7 @@
 import torch
 
-from mozilla_voice_tts.vocoder.models.melgan_generator import MelganGenerator
+from TTS.vocoder.models.melgan_generator import MelganGenerator
-from mozilla_voice_tts.vocoder.layers.pqmf import PQMF
+from TTS.vocoder.layers.pqmf import PQMF
 
 
 class MultibandMelganGenerator(MelganGenerator):

TTS/vocoder/models/parallel_wavegan_discriminator.py

@@ -2,7 +2,7 @@ import math
 import torch
 from torch import nn
 
-from mozilla_voice_tts.vocoder.layers.parallel_wavegan import ResidualBlock
+from TTS.vocoder.layers.parallel_wavegan import ResidualBlock
 
 
 class ParallelWaveganDiscriminator(nn.Module):

TTS/vocoder/models/parallel_wavegan_generator.py

@@ -2,8 +2,8 @@ import math
 import numpy as np
 import torch
 
-from mozilla_voice_tts.vocoder.layers.parallel_wavegan import ResidualBlock
+from TTS.vocoder.layers.parallel_wavegan import ResidualBlock
-from mozilla_voice_tts.vocoder.layers.upsample import ConvUpsample
+from TTS.vocoder.layers.upsample import ConvUpsample
 
 
 class ParallelWaveganGenerator(torch.nn.Module):