Run `make style` & re-enable it in CI

.github/workflows/style_check.yml

@@ -42,6 +42,5 @@ jobs:
         run: |
           python3 -m pip install .[all]
           python3 setup.py egg_info
-      # - name: Lint check
+      - name: Style check
-      #   run: |
+        run: make style
-      #     make lint

TTS/api.py

@@ -264,7 +264,7 @@ class TTS(nn.Module):
         language: str = None,
         emotion: str = None,
         speed: float = 1.0,
-        pipe_out = None,
+        pipe_out=None,
         file_path: str = None,
     ) -> Union[np.ndarray, str]:
         """Convert text to speech using Coqui Studio models. Use `CS_API` class if you are only interested in the API.
@@ -359,7 +359,7 @@ class TTS(nn.Module):
         speaker_wav: str = None,
         emotion: str = None,
         speed: float = 1.0,
-        pipe_out = None,
+        pipe_out=None,
         file_path: str = "output.wav",
         **kwargs,
     ):
@@ -460,7 +460,7 @@ class TTS(nn.Module):
         """
         with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
             # Lazy code... save it to a temp file to resample it while reading it for VC
-            self.tts_to_file(text=text, speaker=None, language=language, file_path=fp.name,speaker_wav=speaker_wav)
+            self.tts_to_file(text=text, speaker=None, language=language, file_path=fp.name, speaker_wav=speaker_wav)
         if self.voice_converter is None:
             self.load_vc_model_by_name("voice_conversion_models/multilingual/vctk/freevc24")
         wav = self.voice_converter.voice_conversion(source_wav=fp.name, target_wav=speaker_wav)

TTS/bin/synthesize.py

@@ -427,7 +427,9 @@ def main():
                 tts_path = model_path
                 tts_config_path = config_path
                 if "default_vocoder" in model_item:
-                    args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name
+                    args.vocoder_name = (
+                        model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name
+                    )
 
             # voice conversion model
             if model_item["model_type"] == "voice_conversion_models":

TTS/tts/layers/xtts/tokenizer.py

@@ -1,12 +1,12 @@
+import json
 import os
 import re
-import json
-
-import torch
-from tokenizers import Tokenizer
 
 import pypinyin
+import torch
 from num2words import num2words
+from tokenizers import Tokenizer
+
 from TTS.tts.layers.xtts.zh_num2words import TextNorm as zh_num2words
 
 _whitespace_re = re.compile(r"\s+")
@@ -87,7 +87,7 @@ _abbreviations = {
     "it": [
         (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
         for x in [
-            #("sig.ra", "signora"),
+            # ("sig.ra", "signora"),
             ("sig", "signore"),
             ("dr", "dottore"),
             ("st", "santo"),
@@ -157,13 +157,15 @@ _abbreviations = {
     ],
 }
 
-def expand_abbreviations_multilingual(text, lang='en'):
+
+def expand_abbreviations_multilingual(text, lang="en"):
     for regex, replacement in _abbreviations[lang]:
         text = re.sub(regex, replacement, text)
     return text
 
+
 _symbols_multilingual = {
-    'en': [
+    "en": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " and "),
@@ -172,10 +174,10 @@ _symbols_multilingual = {
             ("#", " hash "),
             ("$", " dollar "),
             ("£", " pound "),
-            ("°", " degree ")
+            ("°", " degree "),
         ]
     ],
-    'es': [
+    "es": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " y "),
@@ -184,10 +186,10 @@ _symbols_multilingual = {
             ("#", " numeral "),
             ("$", " dolar "),
             ("£", " libra "),
-            ("°", " grados ")
+            ("°", " grados "),
         ]
     ],
-    'fr': [
+    "fr": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " et "),
@@ -196,10 +198,10 @@ _symbols_multilingual = {
             ("#", " dièse "),
             ("$", " dollar "),
             ("£", " livre "),
-            ("°", " degrés ")
+            ("°", " degrés "),
         ]
     ],
-    'de': [
+    "de": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " und "),
@@ -208,10 +210,10 @@ _symbols_multilingual = {
             ("#", " raute "),
             ("$", " dollar "),
             ("£", " pfund "),
-            ("°", " grad ")
+            ("°", " grad "),
         ]
     ],
-    'pt': [
+    "pt": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " e "),
@@ -220,10 +222,10 @@ _symbols_multilingual = {
             ("#", " cardinal "),
             ("$", " dólar "),
             ("£", " libra "),
-            ("°", " graus ")
+            ("°", " graus "),
         ]
     ],
-    'it': [
+    "it": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " e "),
@@ -232,10 +234,10 @@ _symbols_multilingual = {
             ("#", " cancelletto "),
             ("$", " dollaro "),
             ("£", " sterlina "),
-            ("°", " gradi ")
+            ("°", " gradi "),
         ]
     ],
-    'pl': [
+    "pl": [
         (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
         for x in [
             ("&", " i "),
@@ -244,7 +246,7 @@ _symbols_multilingual = {
             ("#", " krzyżyk "),
             ("$", " dolar "),
             ("£", " funt "),
-            ("°", " stopnie ")
+            ("°", " stopnie "),
         ]
     ],
     "ar": [
@@ -257,7 +259,7 @@ _symbols_multilingual = {
             ("#", " رقم "),
             ("$", " دولار "),
             ("£", " جنيه "),
-            ("°", " درجة ")
+            ("°", " درجة "),
         ]
     ],
     "zh-cn": [
@@ -270,7 +272,7 @@ _symbols_multilingual = {
             ("#", " 号 "),
             ("$", " 美元 "),
             ("£", " 英镑 "),
-            ("°", " 度 ")
+            ("°", " 度 "),
         ]
     ],
     "cs": [
@@ -283,7 +285,7 @@ _symbols_multilingual = {
             ("#", " křížek "),
             ("$", " dolar "),
             ("£", " libra "),
-            ("°", " stupně ")
+            ("°", " stupně "),
         ]
     ],
     "ru": [
@@ -296,7 +298,7 @@ _symbols_multilingual = {
             ("#", " номер "),
             ("$", " доллар "),
             ("£", " фунт "),
-            ("°", " градус ")
+            ("°", " градус "),
         ]
     ],
     "nl": [
@@ -309,7 +311,7 @@ _symbols_multilingual = {
             ("#", " hekje "),
             ("$", " dollar "),
             ("£", " pond "),
-            ("°", " graden ")
+            ("°", " graden "),
         ]
     ],
     "tr": [
@@ -321,15 +323,16 @@ _symbols_multilingual = {
             ("#", " diyez "),
             ("$", " dolar "),
             ("£", " sterlin "),
-            ("°", " derece ")
+            ("°", " derece "),
         ]
     ],
 }
 
-def expand_symbols_multilingual(text, lang='en'):
+
+def expand_symbols_multilingual(text, lang="en"):
     for regex, replacement in _symbols_multilingual[lang]:
         text = re.sub(regex, replacement, text)
-        text = text.replace('  ', ' ')  # Ensure there are no double spaces
+        text = text.replace("  ", " ")  # Ensure there are no double spaces
     return text.strip()
 
 
@@ -349,34 +352,38 @@ _ordinal_re = {
 }
 _number_re = re.compile(r"[0-9]+")
 _currency_re = {
-    'USD': re.compile(r"((\$[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+\$))"),
+    "USD": re.compile(r"((\$[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+\$))"),
-    'GBP': re.compile(r"((£[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+£))"),
+    "GBP": re.compile(r"((£[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+£))"),
-    'EUR': re.compile(r"(([0-9\.\,]*[0-9]+€)|((€[0-9\.\,]*[0-9]+)))")
+    "EUR": re.compile(r"(([0-9\.\,]*[0-9]+€)|((€[0-9\.\,]*[0-9]+)))"),
 }
 
 _comma_number_re = re.compile(r"\b\d{1,3}(,\d{3})*(\.\d+)?\b")
 _dot_number_re = re.compile(r"\b\d{1,3}(.\d{3})*(\,\d+)?\b")
 _decimal_number_re = re.compile(r"([0-9]+[.,][0-9]+)")
 
+
 def _remove_commas(m):
     text = m.group(0)
     if "," in text:
         text = text.replace(",", "")
     return text
 
+
 def _remove_dots(m):
     text = m.group(0)
     if "." in text:
         text = text.replace(".", "")
     return text
 
-def _expand_decimal_point(m, lang='en'):
+
+def _expand_decimal_point(m, lang="en"):
     amount = m.group(1).replace(",", ".")
     return num2words(float(amount), lang=lang if lang != "cs" else "cz")
 
-def _expand_currency(m, lang='en', currency='USD'):
+
-    amount = float((re.sub(r'[^\d.]', '', m.group(0).replace(",", "."))))
+def _expand_currency(m, lang="en", currency="USD"):
-    full_amount = num2words(amount, to='currency', currency=currency, lang=lang if lang != "cs" else "cz")
+    amount = float((re.sub(r"[^\d.]", "", m.group(0).replace(",", "."))))
+    full_amount = num2words(amount, to="currency", currency=currency, lang=lang if lang != "cs" else "cz")
 
     and_equivalents = {
         "en": ", ",
@@ -400,13 +407,16 @@ def _expand_currency(m, lang='en', currency='USD'):
 
     return full_amount
 
-def _expand_ordinal(m, lang='en'):
+
+def _expand_ordinal(m, lang="en"):
     return num2words(int(m.group(1)), ordinal=True, lang=lang if lang != "cs" else "cz")
 
-def _expand_number(m, lang='en'):
+
+def _expand_number(m, lang="en"):
     return num2words(int(m.group(0)), lang=lang if lang != "cs" else "cz")
 
-def expand_numbers_multilingual(text, lang='en'):
+
+def expand_numbers_multilingual(text, lang="en"):
     if lang == "zh-cn":
         text = zh_num2words()(text)
     else:
@@ -415,9 +425,9 @@ def expand_numbers_multilingual(text, lang='en'):
         else:
             text = re.sub(_dot_number_re, _remove_dots, text)
         try:
-            text = re.sub(_currency_re['GBP'], lambda m: _expand_currency(m, lang, 'GBP'), text)
+            text = re.sub(_currency_re["GBP"], lambda m: _expand_currency(m, lang, "GBP"), text)
-            text = re.sub(_currency_re['USD'], lambda m: _expand_currency(m, lang, 'USD'), text)
+            text = re.sub(_currency_re["USD"], lambda m: _expand_currency(m, lang, "USD"), text)
-            text = re.sub(_currency_re['EUR'], lambda m: _expand_currency(m, lang, 'EUR'), text)
+            text = re.sub(_currency_re["EUR"], lambda m: _expand_currency(m, lang, "EUR"), text)
         except:
             pass
         if lang != "tr":
@@ -426,15 +436,18 @@ def expand_numbers_multilingual(text, lang='en'):
         text = re.sub(_number_re, lambda m: _expand_number(m, lang), text)
     return text
 
+
 def lowercase(text):
     return text.lower()
 
+
 def collapse_whitespace(text):
     return re.sub(_whitespace_re, " ", text)
 
+
 def multilingual_cleaners(text, lang):
-    text = text.replace('"', '')
+    text = text.replace('"', "")
-    if lang=="tr":
+    if lang == "tr":
         text = text.replace("İ", "i")
         text = text.replace("Ö", "ö")
         text = text.replace("Ü", "ü")
@@ -445,20 +458,26 @@ def multilingual_cleaners(text, lang):
     text = collapse_whitespace(text)
     return text
 
+
 def basic_cleaners(text):
     """Basic pipeline that lowercases and collapses whitespace without transliteration."""
     text = lowercase(text)
     text = collapse_whitespace(text)
     return text
 
+
 def chinese_transliterate(text):
-    return "".join([p[0] for p in pypinyin.pinyin(text, style=pypinyin.Style.TONE3, heteronym=False, neutral_tone_with_five=True)])
+    return "".join(
+        p[0] for p in pypinyin.pinyin(text, style=pypinyin.Style.TONE3, heteronym=False, neutral_tone_with_five=True)
+    )
+
 
 def japanese_cleaners(text, katsu):
     text = katsu.romaji(text)
     text = lowercase(text)
     return text
 
+
 class VoiceBpeTokenizer:
     def __init__(self, vocab_file=None, preprocess=None):
         self.tokenizer = None
@@ -485,6 +504,7 @@ class VoiceBpeTokenizer:
         elif lang == "ja":
             if self.katsu is None:
                 import cutlet
+
                 self.katsu = cutlet.Cutlet()
             txt = japanese_cleaners(txt, self.katsu)
         else:

TTS/tts/layers/xtts/zh_num2words.py

@@ -2,9 +2,14 @@
 #   2019.5 Zhiyang Zhou (https://github.com/Joee1995/chn_text_norm.git)
 #   2019.9 - 2022 Jiayu DU
 
-import sys, os, argparse
+import argparse
-import string, re
 import csv
+import os
+import re
+import string
+import sys
+
+# fmt: off
 
 # ================================================================================ #
 #                                    basic constant

TTS/tts/models/xtts.py

@@ -2,10 +2,10 @@ import os
 from contextlib import contextmanager
 from dataclasses import dataclass
 
+import librosa
 import torch
 import torch.nn.functional as F
 import torchaudio
-import librosa
 from coqpit import Coqpit
 
 from TTS.tts.layers.tortoise.audio_utils import denormalize_tacotron_mel, wav_to_univnet_mel
@@ -386,9 +386,11 @@ class Xtts(BaseTTS):
     @torch.inference_mode()
     def get_speaker_embedding(self, audio, sr):
         audio_16k = torchaudio.functional.resample(audio, sr, 16000)
-        return self.hifigan_decoder.speaker_encoder.forward(
+        return (
-            audio_16k.to(self.device), l2_norm=True
+            self.hifigan_decoder.speaker_encoder.forward(audio_16k.to(self.device), l2_norm=True)
-        ).unsqueeze(-1).to(self.device)
+            .unsqueeze(-1)
+            .to(self.device)
+        )
 
     @torch.inference_mode()
     def get_conditioning_latents(
@@ -647,13 +649,19 @@ class Xtts(BaseTTS):
                     break
 
             if decoder == "hifigan":
-                assert hasattr(self, "hifigan_decoder"), "You must enable hifigan decoder to use it by setting config `use_hifigan: true`"
+                assert hasattr(
+                    self, "hifigan_decoder"
+                ), "You must enable hifigan decoder to use it by setting config `use_hifigan: true`"
                 wav = self.hifigan_decoder(gpt_latents, g=speaker_embedding)
             elif decoder == "ne_hifigan":
-                assert hasattr(self, "ne_hifigan_decoder"), "You must enable ne_hifigan decoder to use it by setting config `use_ne_hifigan: true`"
+                assert hasattr(
+                    self, "ne_hifigan_decoder"
+                ), "You must enable ne_hifigan decoder to use it by setting config `use_ne_hifigan: true`"
                 wav = self.ne_hifigan_decoder(gpt_latents, g=speaker_embedding)
             else:
-                assert hasattr(self, "diffusion_decoder"), "You must disable hifigan decoders to use difffusion by setting config `use_ne_hifigan: false` and `use_hifigan: false`"
+                assert hasattr(
+                    self, "diffusion_decoder"
+                ), "You must disable hifigan decoders to use difffusion by setting config `use_ne_hifigan: false` and `use_hifigan: false`"
                 mel = do_spectrogram_diffusion(
                     self.diffusion_decoder,
                     diffuser,
@@ -742,10 +750,14 @@ class Xtts(BaseTTS):
             if is_end or (stream_chunk_size > 0 and len(last_tokens) >= stream_chunk_size):
                 gpt_latents = torch.cat(all_latents, dim=0)[None, :]
                 if decoder == "hifigan":
-                    assert hasattr(self, "hifigan_decoder"), "You must enable hifigan decoder to use it by setting config `use_hifigan: true`"
+                    assert hasattr(
+                        self, "hifigan_decoder"
+                    ), "You must enable hifigan decoder to use it by setting config `use_hifigan: true`"
                     wav_gen = self.hifigan_decoder(gpt_latents, g=speaker_embedding.to(self.device))
                 elif decoder == "ne_hifigan":
-                    assert hasattr(self, "ne_hifigan_decoder"), "You must enable ne_hifigan decoder to use it by setting config `use_ne_hifigan: true`"
+                    assert hasattr(
+                        self, "ne_hifigan_decoder"
+                    ), "You must enable ne_hifigan decoder to use it by setting config `use_ne_hifigan: true`"
                     wav_gen = self.ne_hifigan_decoder(gpt_latents, g=speaker_embedding.to(self.device))
                 else:
                     raise NotImplementedError("Diffusion for streaming inference not implemented.")
@@ -756,10 +768,14 @@ class Xtts(BaseTTS):
                 yield wav_chunk
 
     def forward(self):
-        raise NotImplementedError("XTTS has a dedicated trainer, please check the XTTS docs: https://tts.readthedocs.io/en/dev/models/xtts.html#training")
+        raise NotImplementedError(
+            "XTTS has a dedicated trainer, please check the XTTS docs: https://tts.readthedocs.io/en/dev/models/xtts.html#training"
+        )
 
     def eval_step(self):
-        raise NotImplementedError("XTTS has a dedicated trainer, please check the XTTS docs: https://tts.readthedocs.io/en/dev/models/xtts.html#training")
+        raise NotImplementedError(
+            "XTTS has a dedicated trainer, please check the XTTS docs: https://tts.readthedocs.io/en/dev/models/xtts.html#training"
+        )
 
     @staticmethod
     def init_from_config(config: "XttsConfig", **kwargs):  # pylint: disable=unused-argument
@@ -835,12 +851,18 @@ class Xtts(BaseTTS):
             self.load_state_dict(checkpoint, strict=strict)
 
         if eval:
-            if hasattr(self, "hifigan_decoder"): self.hifigan_decoder.eval()
+            if hasattr(self, "hifigan_decoder"):
-            if hasattr(self, "ne_hifigan_decoder"): self.hifigan_decoder.eval()
+                self.hifigan_decoder.eval()
-            if hasattr(self, "diffusion_decoder"): self.diffusion_decoder.eval()
+            if hasattr(self, "ne_hifigan_decoder"):
-            if hasattr(self, "vocoder"): self.vocoder.eval()
+                self.hifigan_decoder.eval()
+            if hasattr(self, "diffusion_decoder"):
+                self.diffusion_decoder.eval()
+            if hasattr(self, "vocoder"):
+                self.vocoder.eval()
             self.gpt.init_gpt_for_inference(kv_cache=self.args.kv_cache, use_deepspeed=use_deepspeed)
             self.gpt.eval()
 
     def train_step(self):
-        raise NotImplementedError("XTTS has a dedicated trainer, please check the XTTS docs: https://tts.readthedocs.io/en/dev/models/xtts.html#training")
+        raise NotImplementedError(
+            "XTTS has a dedicated trainer, please check the XTTS docs: https://tts.readthedocs.io/en/dev/models/xtts.html#training"
+        )

TTS/utils/audio/numpy_transforms.py

@@ -428,7 +428,7 @@ def load_wav(*, filename: str, sample_rate: int = None, resample: bool = False,
     return x
 
 
-def save_wav(*, wav: np.ndarray, path: str, sample_rate: int = None, pipe_out = None, **kwargs) -> None:
+def save_wav(*, wav: np.ndarray, path: str, sample_rate: int = None, pipe_out=None, **kwargs) -> None:
     """Save float waveform to a file using Scipy.
 
     Args:

TTS/utils/audio/processor.py

@@ -694,7 +694,7 @@ class AudioProcessor(object):
             x = self.rms_volume_norm(x, self.db_level)
         return x
 
-    def save_wav(self, wav: np.ndarray, path: str, sr: int = None, pipe_out = None) -> None:
+    def save_wav(self, wav: np.ndarray, path: str, sr: int = None, pipe_out=None) -> None:
         """Save a waveform to a file using Scipy.
 
         Args:

TTS/utils/synthesizer.py

@@ -235,7 +235,7 @@ class Synthesizer(nn.Module):
         """
         return self.seg.segment(text)
 
-    def save_wav(self, wav: List[int], path: str, pipe_out = None) -> None:
+    def save_wav(self, wav: List[int], path: str, pipe_out=None) -> None:
         """Save the waveform as a file.
 
         Args:

recipes/ljspeech/xtts_v1/train_gpt_xtts.py

@@ -7,7 +7,6 @@ from TTS.tts.datasets import load_tts_samples
 from TTS.tts.layers.xtts.trainer.gpt_trainer import GPTArgs, GPTTrainer, GPTTrainerConfig, XttsAudioConfig
 from TTS.utils.manage import ModelManager
 
-
 # Logging parameters
 RUN_NAME = "GPT_XTTS_LJSpeech_FT"
 PROJECT_NAME = "XTTS_trainer"
@@ -66,7 +65,9 @@ XTTS_CHECKPOINT = os.path.join(CHECKPOINTS_OUT_PATH, XTTS_CHECKPOINT_LINK.split(
 # download XTTS v1.1 files if needed
 if not os.path.isfile(TOKENIZER_FILE) or not os.path.isfile(XTTS_CHECKPOINT):
     print(" > Downloading XTTS v1.1 files!")
-    ModelManager._download_model_files([TOKENIZER_FILE_LINK, XTTS_CHECKPOINT_LINK], CHECKPOINTS_OUT_PATH, progress_bar=True)
+    ModelManager._download_model_files(
+        [TOKENIZER_FILE_LINK, XTTS_CHECKPOINT_LINK], CHECKPOINTS_OUT_PATH, progress_bar=True
+    )
 
 
 # Training sentences generations

tests/api_tests/test_synthesize_api.py

@@ -22,7 +22,4 @@ def test_synthesize():
     )
 
     # test pipe_out command
-    run_cli(
+    run_cli(f'tts --text "test." --pipe_out --out_path "{output_path}" | aplay')
-        'tts --text "test." --pipe_out '
-        f'--out_path "{output_path}" | aplay'
-    )