Update to coqui-tts-trainer 0.1.4

.github/workflows/tests.yml

@@ -45,8 +45,11 @@ jobs:
           sed -i 's/https:\/\/coqui.gateway.scarf.sh\//https:\/\/github.com\/coqui-ai\/TTS\/releases\/download\//g' TTS/.models.json
       - name: Install TTS
         run: |
-          python3 -m uv pip install --system "coqui-tts[dev,server,languages] @ ."
-          python3 setup.py egg_info
+          resolution=highest
+          if [ "${{ matrix.python-version }}" == "3.9" ]; then
+            resolution=lowest-direct
+          fi
+          python3 -m uv pip install --resolution=$resolution --system "coqui-tts[dev,server,languages] @ ."
       - name: Unit tests
         run: make ${{ matrix.subset }}
       - name: Upload coverage data

TTS/bin/compute_attention_masks.py

@@ -8,14 +8,14 @@
 import torch
 from torch.utils.data import DataLoader
 from tqdm import tqdm
+from trainer.io import load_checkpoint
 
 from TTS.config import load_config
 from TTS.tts.datasets.TTSDataset import TTSDataset
 from TTS.tts.models import setup_model
 from TTS.tts.utils.text.characters import make_symbols, phonemes, symbols
 from TTS.utils.audio import AudioProcessor
 from TTS.utils.generic_utils import ConsoleFormatter, setup_logger
-from TTS.utils.io import load_checkpoint
 
 if __name__ == "__main__":
     setup_logger("TTS", level=logging.INFO, screen=True, formatter=ConsoleFormatter())

TTS/encoder/models/base_encoder.py

@@ -5,10 +5,10 @@
 import torchaudio
 from coqpit import Coqpit
 from torch import nn
+from trainer.io import load_fsspec
 
 from TTS.encoder.losses import AngleProtoLoss, GE2ELoss, SoftmaxAngleProtoLoss
 from TTS.utils.generic_utils import set_init_dict
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/encoder/utils/training.py

@@ -3,14 +3,13 @@
 
 from coqpit import Coqpit
 from trainer import TrainerArgs, get_last_checkpoint
-from trainer.generic_utils import get_experiment_folder_path
+from trainer.generic_utils import get_experiment_folder_path, get_git_branch
 from trainer.io import copy_model_files
 from trainer.logging import logger_factory
 from trainer.logging.console_logger import ConsoleLogger
 
 from TTS.config import load_config, register_config
 from TTS.tts.utils.text.characters import parse_symbols
-from TTS.utils.generic_utils import get_git_branch
 
 
 @dataclass
@@ -30,7 +29,7 @@ def process_args(args, config=None):
         args (argparse.Namespace or dict like): Parsed input arguments.
         config (Coqpit): Model config. If none, it is generated from `args`. Defaults to None.
     Returns:
-        c (TTS.utils.io.AttrDict): Config paramaters.
+        c (Coqpit): Config paramaters.
         out_path (str): Path to save models and logging.
         audio_path (str): Path to save generated test audios.
         c_logger (TTS.utils.console_logger.ConsoleLogger): Class that does

TTS/model.py

@@ -60,6 +60,7 @@ def load_checkpoint(
             checkpoint_path (str | os.PathLike): Path to the model checkpoint file.
             eval (bool, optional): If true, init model for inference else for training. Defaults to False.
             strict (bool, optional): Match all checkpoint keys to model's keys. Defaults to True.
-            cache (bool, optional): If True, cache the file locally for subsequent calls. It is cached under `get_user_data_dir()/tts_cache`. Defaults to False.
+            cache (bool, optional): If True, cache the file locally for subsequent calls.
+                It is cached under `trainer.io.get_user_data_dir()/tts_cache`. Defaults to False.
         """
         ...

TTS/tts/configs/bark_config.py

@@ -2,11 +2,12 @@
 from dataclasses import dataclass, field
 from typing import Dict
 
+from trainer.io import get_user_data_dir
+
 from TTS.tts.configs.shared_configs import BaseTTSConfig
 from TTS.tts.layers.bark.model import GPTConfig
 from TTS.tts.layers.bark.model_fine import FineGPTConfig
 from TTS.tts.models.bark import BarkAudioConfig
-from TTS.utils.generic_utils import get_user_data_dir
 
 
 @dataclass

TTS/tts/layers/xtts/hifigan_decoder.py

@@ -7,8 +7,8 @@
 from torch.nn import functional as F
 from torch.nn.utils.parametrizations import weight_norm
 from torch.nn.utils.parametrize import remove_parametrizations
+from trainer.io import load_fsspec
 
-from TTS.utils.io import load_fsspec
 from TTS.vocoder.models.hifigan_generator import get_padding
 
 logger = logging.getLogger(__name__)

TTS/tts/layers/xtts/trainer/gpt_trainer.py

@@ -7,6 +7,7 @@
 import torchaudio
 from coqpit import Coqpit
 from torch.utils.data import DataLoader
+from trainer.io import load_fsspec
 from trainer.torch import DistributedSampler
 from trainer.trainer_utils import get_optimizer, get_scheduler
 
@@ -18,7 +19,6 @@
 from TTS.tts.layers.xtts.trainer.dataset import XTTSDataset
 from TTS.tts.models.base_tts import BaseTTS
 from TTS.tts.models.xtts import Xtts, XttsArgs, XttsAudioConfig
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/tts/models/align_tts.py

@@ -4,6 +4,7 @@
 import torch
 from coqpit import Coqpit
 from torch import nn
+from trainer.io import load_fsspec
 
 from TTS.tts.layers.align_tts.mdn import MDNBlock
 from TTS.tts.layers.feed_forward.decoder import Decoder
@@ -15,7 +16,6 @@
 from TTS.tts.utils.speakers import SpeakerManager
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
-from TTS.utils.io import load_fsspec
 
 
 @dataclass

TTS/tts/models/base_tacotron.py

@@ -6,6 +6,7 @@
 import torch
 from coqpit import Coqpit
 from torch import nn
+from trainer.io import load_fsspec
 
 from TTS.tts.layers.losses import TacotronLoss
 from TTS.tts.models.base_tts import BaseTTS
@@ -15,7 +16,6 @@
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
 from TTS.utils.generic_utils import format_aux_input
-from TTS.utils.io import load_fsspec
 from TTS.utils.training import gradual_training_scheduler
 
 logger = logging.getLogger(__name__)
@@ -103,7 +103,8 @@ def load_checkpoint(
             config (Coqpi): model configuration.
             checkpoint_path (str): path to checkpoint file.
             eval (bool, optional): whether to load model for evaluation.
-            cache (bool, optional): If True, cache the file locally for subsequent calls. It is cached under `get_user_data_dir()/tts_cache`. Defaults to False.
+            cache (bool, optional): If True, cache the file locally for subsequent calls.
+                It is cached under `trainer.io.get_user_data_dir()/tts_cache`. Defaults to False.
         """
         state = load_fsspec(checkpoint_path, map_location=torch.device("cpu"), cache=cache)
         self.load_state_dict(state["model"])

TTS/tts/models/delightful_tts.py

@@ -16,6 +16,7 @@
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from torch.utils.data.sampler import WeightedRandomSampler
+from trainer.io import load_fsspec
 from trainer.torch import DistributedSampler, DistributedSamplerWrapper
 from trainer.trainer_utils import get_optimizer, get_scheduler
 
@@ -32,7 +33,6 @@
 from TTS.utils.audio.numpy_transforms import db_to_amp as db_to_amp_numpy
 from TTS.utils.audio.numpy_transforms import mel_to_wav as mel_to_wav_numpy
 from TTS.utils.audio.processor import AudioProcessor
-from TTS.utils.io import load_fsspec
 from TTS.vocoder.layers.losses import MultiScaleSTFTLoss
 from TTS.vocoder.models.hifigan_generator import HifiganGenerator
 from TTS.vocoder.utils.generic_utils import plot_results

TTS/tts/models/forward_tts.py

@@ -6,6 +6,7 @@
 from coqpit import Coqpit
 from torch import nn
 from torch.cuda.amp.autocast_mode import autocast
+from trainer.io import load_fsspec
 
 from TTS.tts.layers.feed_forward.decoder import Decoder
 from TTS.tts.layers.feed_forward.encoder import Encoder
@@ -17,7 +18,6 @@
 from TTS.tts.utils.speakers import SpeakerManager
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment, plot_avg_energy, plot_avg_pitch, plot_spectrogram
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/tts/models/glow_tts.py

@@ -7,6 +7,7 @@
 from torch import nn
 from torch.cuda.amp.autocast_mode import autocast
 from torch.nn import functional as F
+from trainer.io import load_fsspec
 
 from TTS.tts.configs.glow_tts_config import GlowTTSConfig
 from TTS.tts.layers.glow_tts.decoder import Decoder
@@ -17,7 +18,6 @@
 from TTS.tts.utils.synthesis import synthesis
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/tts/models/neuralhmm_tts.py

@@ -5,6 +5,7 @@
 import torch
 from coqpit import Coqpit
 from torch import nn
+from trainer.io import load_fsspec
 from trainer.logging.tensorboard_logger import TensorboardLogger
 
 from TTS.tts.layers.overflow.common_layers import Encoder, OverflowUtils
@@ -18,7 +19,6 @@
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
 from TTS.utils.generic_utils import format_aux_input
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/tts/models/overflow.py

@@ -5,6 +5,7 @@
 import torch
 from coqpit import Coqpit
 from torch import nn
+from trainer.io import load_fsspec
 from trainer.logging.tensorboard_logger import TensorboardLogger
 
 from TTS.tts.layers.overflow.common_layers import Encoder, OverflowUtils
@@ -19,7 +20,6 @@
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
 from TTS.utils.generic_utils import format_aux_input
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/tts/models/vits.py

@@ -16,6 +16,7 @@
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from torch.utils.data.sampler import WeightedRandomSampler
+from trainer.io import load_fsspec
 from trainer.torch import DistributedSampler, DistributedSamplerWrapper
 from trainer.trainer_utils import get_optimizer, get_scheduler
 
@@ -34,7 +35,6 @@
 from TTS.tts.utils.text.characters import BaseCharacters, BaseVocabulary, _characters, _pad, _phonemes, _punctuations
 from TTS.tts.utils.text.tokenizer import TTSTokenizer
 from TTS.tts.utils.visual import plot_alignment
-from TTS.utils.io import load_fsspec
 from TTS.utils.samplers import BucketBatchSampler
 from TTS.vocoder.models.hifigan_generator import HifiganGenerator
 from TTS.vocoder.utils.generic_utils import plot_results

TTS/tts/models/xtts.py

@@ -7,14 +7,14 @@
 import torch.nn.functional as F
 import torchaudio
 from coqpit import Coqpit
+from trainer.io import load_fsspec
 
 from TTS.tts.layers.xtts.gpt import GPT
 from TTS.tts.layers.xtts.hifigan_decoder import HifiDecoder
 from TTS.tts.layers.xtts.stream_generator import init_stream_support
 from TTS.tts.layers.xtts.tokenizer import VoiceBpeTokenizer, split_sentence
 from TTS.tts.layers.xtts.xtts_manager import LanguageManager, SpeakerManager
 from TTS.tts.models.base_tts import BaseTTS
-from TTS.utils.io import load_fsspec
 
 logger = logging.getLogger(__name__)
 

TTS/utils/generic_utils.py

@@ -2,29 +2,13 @@
 import datetime
 import importlib
 import logging
-import os
 import re
-import subprocess
-import sys
 from pathlib import Path
 from typing import Dict, Optional
 
 logger = logging.getLogger(__name__)
 
 
-# TODO: This method is duplicated in Trainer but out of date there
-def get_git_branch():
-    try:
-        out = subprocess.check_output(["git", "branch"]).decode("utf8")
-        current = next(line for line in out.split("\n") if line.startswith("*"))
-        current.replace("* ", "")
-    except subprocess.CalledProcessError:
-        current = "inside_docker"
-    except (FileNotFoundError, StopIteration) as e:
-        current = "unknown"
-    return current
-
-
 def to_camel(text):
     text = text.capitalize()
     text = re.sub(r"(?!^)_([a-zA-Z])", lambda m: m.group(1).upper(), text)
@@ -67,28 +51,6 @@ def get_import_path(obj: object) -> str:
     return ".".join([type(obj).__module__, type(obj).__name__])
 
 
-def get_user_data_dir(appname):
-    TTS_HOME = os.environ.get("TTS_HOME")
-    XDG_DATA_HOME = os.environ.get("XDG_DATA_HOME")
-    if TTS_HOME is not None:
-        ans = Path(TTS_HOME).expanduser().resolve(strict=False)
-    elif XDG_DATA_HOME is not None:
-        ans = Path(XDG_DATA_HOME).expanduser().resolve(strict=False)
-    elif sys.platform == "win32":
-        import winreg  # pylint: disable=import-outside-toplevel
-
-        key = winreg.OpenKey(
-            winreg.HKEY_CURRENT_USER, r"Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders"
-        )
-        dir_, _ = winreg.QueryValueEx(key, "Local AppData")
-        ans = Path(dir_).resolve(strict=False)
-    elif sys.platform == "darwin":
-        ans = Path("~/Library/Application Support/").expanduser()
-    else:
-        ans = Path.home().joinpath(".local/share")
-    return ans.joinpath(appname)
-
-
 def set_init_dict(model_dict, checkpoint_state, c):
     # Partial initialization: if there is a mismatch with new and old layer, it is skipped.
     for k, v in checkpoint_state.items():