formatting, sorting

.pre-commit-config.yaml

@@ -3,11 +3,14 @@ repos:
     # Ruff version.
     rev: v0.11.2
     hooks:
-      # Run the linter.
       - id: ruff
+        name: ruff linter
         args: [--fix]
-      # Run the formatter.
       - id: ruff-format
+        name: ruff formatter
+      - id: ruff
+        name: ruff sorter
+        args: [--select, I, --fix]
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v5.0.0
     hooks:

ruff.toml

@@ -6,5 +6,5 @@ target-version = "py310"
 dummy-variable-rgx = "^_.*$"
 
 [lint.isort]
-force-single-line = true
+force-single-line = false
 lines-after-imports = 2

src/f5_tts/api.py

@@ -9,13 +9,13 @@ from hydra.utils import get_class
 from omegaconf import OmegaConf
 
 from f5_tts.infer.utils_infer import (
+    infer_process,
     load_model,
     load_vocoder,
-    transcribe,
     preprocess_ref_audio_text,
-    infer_process,
     remove_silence_for_generated_wav,
     save_spectrogram,
+    transcribe,
 )
 from f5_tts.model.utils import seed_everything
 

src/f5_tts/eval/ecapa_tdnn.py

@@ -4,6 +4,7 @@
 # part of the code is borrowed from https://github.com/lawlict/ECAPA-TDNN
 
 import os
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

src/f5_tts/eval/eval_infer_batch.py

@@ -1,6 +1,7 @@
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import argparse
@@ -23,6 +24,7 @@ from f5_tts.infer.utils_infer import load_checkpoint, load_vocoder
 from f5_tts.model import CFM
 from f5_tts.model.utils import get_tokenizer
 
+
 accelerator = Accelerator()
 device = f"cuda:{accelerator.process_index}"
 

src/f5_tts/eval/eval_librispeech_test_clean.py

@@ -5,17 +5,16 @@ import json
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import multiprocessing as mp
 from importlib.resources import files
 
 import numpy as np
-from f5_tts.eval.utils_eval import (
-    get_librispeech_test,
-    run_asr_wer,
-    run_sim,
-)
+
+from f5_tts.eval.utils_eval import get_librispeech_test, run_asr_wer, run_sim
+
 
 rel_path = str(files("f5_tts").joinpath("../../"))
 

src/f5_tts/eval/eval_seedtts_testset.py

@@ -5,17 +5,16 @@ import json
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import multiprocessing as mp
 from importlib.resources import files
 
 import numpy as np
-from f5_tts.eval.utils_eval import (
-    get_seed_tts_test,
-    run_asr_wer,
-    run_sim,
-)
+
+from f5_tts.eval.utils_eval import get_seed_tts_test, run_asr_wer, run_sim
+
 
 rel_path = str(files("f5_tts").joinpath("../../"))
 

src/f5_tts/infer/infer_cli.py

@@ -14,20 +14,20 @@ from hydra.utils import get_class
 from omegaconf import OmegaConf
 
 from f5_tts.infer.utils_infer import (
-    mel_spec_type,
-    target_rms,
-    cross_fade_duration,
-    nfe_step,
     cfg_strength,
-    sway_sampling_coef,
-    speed,
-    fix_duration,
+    cross_fade_duration,
     device,
+    fix_duration,
     infer_process,
     load_model,
     load_vocoder,
+    mel_spec_type,
+    nfe_step,
     preprocess_ref_audio_text,
     remove_silence_for_generated_wav,
+    speed,
+    sway_sampling_coef,
+    target_rms,
 )
 
 

src/f5_tts/infer/infer_gradio.py

@@ -18,6 +18,7 @@ import torchaudio
 from cached_path import cached_path
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
+
 try:
     import spaces
 
@@ -33,15 +34,15 @@ def gpu_decorator(func):
         return func
 
 
-from f5_tts.model import DiT, UNetT
 from f5_tts.infer.utils_infer import (
-    load_vocoder,
+    infer_process,
     load_model,
+    load_vocoder,
     preprocess_ref_audio_text,
-    infer_process,
     remove_silence_for_generated_wav,
     save_spectrogram,
 )
+from f5_tts.model import DiT, UNetT
 
 
 DEFAULT_TTS_MODEL = "F5-TTS_v1"

src/f5_tts/infer/speech_edit.py

@@ -1,5 +1,6 @@
 import os
 
+
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"  # for MPS device compatibility
 
 from importlib.resources import files
@@ -7,14 +8,15 @@ from importlib.resources import files
 import torch
 import torch.nn.functional as F
 import torchaudio
+from cached_path import cached_path
 from hydra.utils import get_class
 from omegaconf import OmegaConf
-from cached_path import cached_path
 
 from f5_tts.infer.utils_infer import load_checkpoint, load_vocoder, save_spectrogram
 from f5_tts.model import CFM
 from f5_tts.model.utils import convert_char_to_pinyin, get_tokenizer
 
+
 device = (
     "cuda"
     if torch.cuda.is_available()

src/f5_tts/infer/utils_infer.py

@@ -4,6 +4,7 @@ import os
 import sys
 from concurrent.futures import ThreadPoolExecutor
 
+
 os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"  # for MPS device compatibility
 sys.path.append(f"{os.path.dirname(os.path.abspath(__file__))}/../../third_party/BigVGAN/")
 
@@ -14,6 +15,7 @@ from importlib.resources import files
 
 import matplotlib
 
+
 matplotlib.use("Agg")
 
 import matplotlib.pylab as plt
@@ -27,10 +29,8 @@ from transformers import pipeline
 from vocos import Vocos
 
 from f5_tts.model import CFM
-from f5_tts.model.utils import (
-    get_tokenizer,
-    convert_char_to_pinyin,
-)
+from f5_tts.model.utils import convert_char_to_pinyin, get_tokenizer
+
 
 _ref_audio_cache = {}
 

src/f5_tts/model/__init__.py

@@ -1,9 +1,7 @@
-from f5_tts.model.cfm import CFM
-
-from f5_tts.model.backbones.unett import UNetT
 from f5_tts.model.backbones.dit import DiT
 from f5_tts.model.backbones.mmdit import MMDiT
-
+from f5_tts.model.backbones.unett import UNetT
+from f5_tts.model.cfm import CFM
 from f5_tts.model.trainer import Trainer
 
 

src/f5_tts/model/backbones/dit.py

@@ -10,19 +10,18 @@ d - dimension
 from __future__ import annotations
 
 import torch
-from torch import nn
 import torch.nn.functional as F
-
+from torch import nn
 from x_transformers.x_transformers import RotaryEmbedding
 
 from f5_tts.model.modules import (
-    TimestepEmbedding,
+    AdaLayerNorm_Final,
     ConvNeXtV2Block,
     ConvPositionEmbedding,
     DiTBlock,
-    AdaLayerNorm_Final,
-    precompute_freqs_cis,
+    TimestepEmbedding,
     get_pos_embed_indices,
+    precompute_freqs_cis,
 )
 
 

src/f5_tts/model/backbones/mmdit.py

@@ -11,16 +11,15 @@ from __future__ import annotations
 
 import torch
 from torch import nn
-
 from x_transformers.x_transformers import RotaryEmbedding
 
 from f5_tts.model.modules import (
-    TimestepEmbedding,
+    AdaLayerNorm_Final,
     ConvPositionEmbedding,
     MMDiTBlock,
-    AdaLayerNorm_Final,
-    precompute_freqs_cis,
+    TimestepEmbedding,
     get_pos_embed_indices,
+    precompute_freqs_cis,
 )
 
 

src/f5_tts/model/backbones/unett.py

@@ -8,24 +8,24 @@ d - dimension
 """
 
 from __future__ import annotations
+
 from typing import Literal
 
 import torch
-from torch import nn
 import torch.nn.functional as F
-
+from torch import nn
 from x_transformers import RMSNorm
 from x_transformers.x_transformers import RotaryEmbedding
 
 from f5_tts.model.modules import (
-    TimestepEmbedding,
-    ConvNeXtV2Block,
-    ConvPositionEmbedding,
     Attention,
     AttnProcessor,
+    ConvNeXtV2Block,
+    ConvPositionEmbedding,
     FeedForward,
-    precompute_freqs_cis,
+    TimestepEmbedding,
     get_pos_embed_indices,
+    precompute_freqs_cis,
 )
 
 

src/f5_tts/model/trainer.py

@@ -19,6 +19,7 @@ from f5_tts.model import CFM
 from f5_tts.model.dataset import DynamicBatchSampler, collate_fn
 from f5_tts.model.utils import default, exists
 
+
 # trainer
 
 

src/f5_tts/model/utils.py

@@ -5,12 +5,11 @@ import random
 from collections import defaultdict
 from importlib.resources import files
 
+import jieba
 import torch
+from pypinyin import Style, lazy_pinyin
 from torch.nn.utils.rnn import pad_sequence
 
-import jieba
-from pypinyin import lazy_pinyin, Style
-
 
 # seed everything
 

src/f5_tts/runtime/triton_trtllm/benchmark.py

@@ -30,26 +30,27 @@ import argparse
 import json
 import os
 import time
-from typing import List, Dict, Union
+from typing import Dict, List, Union
 
+import datasets
+import jieba
+import tensorrt as trt
 import torch
 import torch.distributed as dist
 import torch.nn.functional as F
-from torch.nn.utils.rnn import pad_sequence
 import torchaudio
-import jieba
-from pypinyin import Style, lazy_pinyin
 from datasets import load_dataset
-import datasets
+from f5_tts_trtllm import F5TTS
 from huggingface_hub import hf_hub_download
+from pypinyin import Style, lazy_pinyin
+from tensorrt_llm._utils import trt_dtype_to_torch
+from tensorrt_llm.logger import logger
+from tensorrt_llm.runtime.session import Session, TensorInfo
+from torch.nn.utils.rnn import pad_sequence
 from torch.utils.data import DataLoader, DistributedSampler
 from tqdm import tqdm
 from vocos import Vocos
-from f5_tts_trtllm import F5TTS
-import tensorrt as trt
-from tensorrt_llm.runtime.session import Session, TensorInfo
-from tensorrt_llm.logger import logger
-from tensorrt_llm._utils import trt_dtype_to_torch
+
 
 torch.manual_seed(0)
 
@@ -381,8 +382,8 @@ def main():
         import sys
 
         sys.path.append(f"{os.path.dirname(os.path.abspath(__file__))}/../../../../src/")
-        from f5_tts.model import DiT
         from f5_tts.infer.utils_infer import load_model
+        from f5_tts.model import DiT
 
         F5TTS_model_cfg = dict(
             dim=1024,

src/f5_tts/runtime/triton_trtllm/client_grpc.py

@@ -44,7 +44,6 @@ python3 client_grpc.py \
 import argparse
 import asyncio
 import json
-
 import os
 import time
 import types

src/f5_tts/runtime/triton_trtllm/client_http.py

@@ -23,10 +23,11 @@
 # OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+import argparse
+
+import numpy as np
 import requests
 import soundfile as sf
-import numpy as np
-import argparse
 
 
 def get_args():

src/f5_tts/runtime/triton_trtllm/model_repo_f5_tts/f5_tts/1/f5_tts_trtllm.py

@@ -1,18 +1,17 @@
-import tensorrt as trt
-import os
 import math
+import os
 import time
-from typing import List, Optional
 from functools import wraps
+from typing import List, Optional
 
+import tensorrt as trt
 import tensorrt_llm
-from tensorrt_llm._utils import str_dtype_to_torch, trt_dtype_to_torch
-from tensorrt_llm.logger import logger
-from tensorrt_llm.runtime.session import Session
-
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
+from tensorrt_llm._utils import str_dtype_to_torch, trt_dtype_to_torch
+from tensorrt_llm.logger import logger
+from tensorrt_llm.runtime.session import Session
 
 
 def remove_tensor_padding(input_tensor, input_tensor_lengths=None):

src/f5_tts/runtime/triton_trtllm/model_repo_f5_tts/f5_tts/1/model.py

@@ -24,16 +24,17 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 import json
+import os
+
+import jieba
 import torch
-from torch.nn.utils.rnn import pad_sequence
 import torch.nn.functional as F
-from torch.utils.dlpack import from_dlpack, to_dlpack
 import torchaudio
-import jieba
 import triton_python_backend_utils as pb_utils
-from pypinyin import Style, lazy_pinyin
-import os
 from f5_tts_trtllm import F5TTS
+from pypinyin import Style, lazy_pinyin
+from torch.nn.utils.rnn import pad_sequence
+from torch.utils.dlpack import from_dlpack, to_dlpack
 
 
 def get_tokenizer(vocab_file_path: str):

src/f5_tts/runtime/triton_trtllm/patch/__init__.py

@@ -34,6 +34,7 @@ from .deepseek_v2.model import DeepseekV2ForCausalLM
 from .dit.model import DiT
 from .eagle.model import EagleForCausalLM
 from .enc_dec.model import DecoderModel, EncoderModel, WhisperEncoder
+from .f5tts.model import F5TTS
 from .falcon.config import FalconConfig
 from .falcon.model import FalconForCausalLM, FalconModel
 from .gemma.config import GEMMA2_ARCHITECTURE, GEMMA_ARCHITECTURE, GemmaConfig
@@ -54,12 +55,12 @@ from .modeling_utils import PretrainedConfig, PretrainedModel, SpeculativeDecodi
 from .mpt.model import MPTForCausalLM, MPTModel
 from .nemotron_nas.model import DeciLMForCausalLM
 from .opt.model import OPTForCausalLM, OPTModel
-from .phi3.model import Phi3ForCausalLM, Phi3Model
 from .phi.model import PhiForCausalLM, PhiModel
+from .phi3.model import Phi3ForCausalLM, Phi3Model
 from .qwen.model import QWenForCausalLM
 from .recurrentgemma.model import RecurrentGemmaForCausalLM
 from .redrafter.model import ReDrafterForCausalLM
-from .f5tts.model import F5TTS
+
 
 __all__ = [
     "BertModel",

src/f5_tts/runtime/triton_trtllm/patch/f5tts/model.py

@@ -1,23 +1,20 @@
 from __future__ import annotations
-import sys
+
 import os
+import sys
+from collections import OrderedDict
 
 import tensorrt as trt
-from collections import OrderedDict
+from tensorrt_llm._common import default_net
+
 from ..._utils import str_dtype_to_trt
-from ...plugin import current_all_reduce_helper
-from ..modeling_utils import PretrainedConfig, PretrainedModel
 from ...functional import Tensor, concat
-from ...module import Module, ModuleList
-from tensorrt_llm._common import default_net
 from ...layers import Linear
+from ...module import Module, ModuleList
+from ...plugin import current_all_reduce_helper
+from ..modeling_utils import PretrainedConfig, PretrainedModel
+from .modules import AdaLayerNormZero_Final, ConvPositionEmbedding, DiTBlock, TimestepEmbedding
 
-from .modules import (
-    TimestepEmbedding,
-    ConvPositionEmbedding,
-    DiTBlock,
-    AdaLayerNormZero_Final,
-)
 
 current_file_path = os.path.abspath(__file__)
 parent_dir = os.path.dirname(current_file_path)

src/f5_tts/runtime/triton_trtllm/patch/f5tts/modules.py

@@ -3,33 +3,35 @@ from __future__ import annotations
 import math
 from typing import Optional
 
+import numpy as np
 import torch
 import torch.nn.functional as F
-
-import numpy as np
 from tensorrt_llm._common import default_net
-from ..._utils import trt_dtype_to_np, str_dtype_to_trt
+
+from ..._utils import str_dtype_to_trt, trt_dtype_to_np
 from ...functional import (
     Tensor,
+    bert_attention,
+    cast,
     chunk,
     concat,
     constant,
     expand,
+    expand_dims,
+    expand_dims_like,
+    expand_mask,
+    gelu,
+    matmul,
+    permute,
     shape,
     silu,
     slice,
-    permute,
-    expand_mask,
-    expand_dims_like,
-    unsqueeze,
-    matmul,
     softmax,
     squeeze,
-    cast,
-    gelu,
+    unsqueeze,
+    view,
 )
-from ...functional import expand_dims, view, bert_attention
-from ...layers import LayerNorm, Linear, Conv1d, Mish, RowLinear, ColumnLinear
+from ...layers import ColumnLinear, Conv1d, LayerNorm, Linear, Mish, RowLinear
 from ...module import Module
 
 

src/f5_tts/runtime/triton_trtllm/scripts/conv_stft.py

@@ -40,6 +40,7 @@ import torch as th
 import torch.nn.functional as F
 from scipy.signal import check_COLA, get_window
 
+
 support_clp_op = None
 if th.__version__ >= "1.7.0":
     from torch.fft import rfft as fft

src/f5_tts/runtime/triton_trtllm/scripts/convert_checkpoint.py

@@ -8,7 +8,6 @@ from concurrent.futures import ThreadPoolExecutor, as_completed
 
 import safetensors.torch
 import torch
-
 from tensorrt_llm import str_dtype_to_torch
 from tensorrt_llm.mapping import Mapping
 from tensorrt_llm.models.convert_utils import split, split_matrix_tp

src/f5_tts/runtime/triton_trtllm/scripts/export_vocoder_to_onnx.py

@@ -12,13 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import argparse
+
 import torch
 import torch.nn as nn
-from huggingface_hub import hf_hub_download
-
 from conv_stft import STFT
+from huggingface_hub import hf_hub_download
 from vocos import Vocos
-import argparse
+
 
 opset_version = 17
 

src/f5_tts/scripts/count_params_gflops.py

@@ -1,12 +1,13 @@
-import sys
 import os
+import sys
 
-sys.path.append(os.getcwd())
 
-from f5_tts.model import CFM, DiT
+sys.path.append(os.getcwd())
 
-import torch
 import thop
+import torch
+
+from f5_tts.model import CFM, DiT
 
 
 """ ~155M """

src/f5_tts/socket_client.py

@@ -1,10 +1,12 @@
-import socket
 import asyncio
-import pyaudio
-import numpy as np
 import logging
+import socket
 import time
 
+import numpy as np
+import pyaudio
+
+
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 

src/f5_tts/socket_server.py

@@ -1,7 +1,6 @@
 import argparse
 import gc
 import logging
-import numpy as np
 import queue
 import socket
 import struct
@@ -10,6 +9,7 @@ import traceback
 import wave
 from importlib.resources import files
 
+import numpy as np
 import torch
 import torchaudio
 from huggingface_hub import hf_hub_download
@@ -18,12 +18,13 @@ from omegaconf import OmegaConf
 
 from f5_tts.infer.utils_infer import (
     chunk_text,
-    preprocess_ref_audio_text,
-    load_vocoder,
-    load_model,
     infer_batch_process,
+    load_model,
+    load_vocoder,
+    preprocess_ref_audio_text,
 )
 
+
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 

src/f5_tts/train/datasets/prepare_csv_wavs.py

@@ -1,12 +1,13 @@
+import concurrent.futures
+import multiprocessing
 import os
-import sys
+import shutil
 import signal
 import subprocess  # For invoking ffprobe
-import shutil
-import concurrent.futures
-import multiprocessing
+import sys
 from contextlib import contextmanager
 
+
 sys.path.append(os.getcwd())
 
 import argparse
@@ -16,12 +17,10 @@ from importlib.resources import files
 from pathlib import Path
 
 import torchaudio
-from tqdm import tqdm
 from datasets.arrow_writer import ArrowWriter
+from tqdm import tqdm
 
-from f5_tts.model.utils import (
-    convert_char_to_pinyin,
-)
+from f5_tts.model.utils import convert_char_to_pinyin
 
 
 PRETRAINED_VOCAB_PATH = files("f5_tts").joinpath("../../data/Emilia_ZH_EN_pinyin/vocab.txt")

src/f5_tts/train/datasets/prepare_emilia.py

@@ -7,20 +7,18 @@
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import json
 from concurrent.futures import ProcessPoolExecutor
 from importlib.resources import files
 from pathlib import Path
-from tqdm import tqdm
 
 from datasets.arrow_writer import ArrowWriter
+from tqdm import tqdm
 
-from f5_tts.model.utils import (
-    repetition_found,
-    convert_char_to_pinyin,
-)
+from f5_tts.model.utils import convert_char_to_pinyin, repetition_found
 
 
 out_zh = {

src/f5_tts/train/datasets/prepare_emilia_v2.py

@@ -1,17 +1,17 @@
 # put in src/f5_tts/train/datasets/prepare_emilia_v2.py
 # prepares Emilia dataset with the new format w/ Emilia-YODAS
 
-import os
 import json
+import os
 from concurrent.futures import ProcessPoolExecutor
+from importlib.resources import files
 from pathlib import Path
-from tqdm import tqdm
+
 from datasets.arrow_writer import ArrowWriter
-from importlib.resources import files
+from tqdm import tqdm
+
+from f5_tts.model.utils import repetition_found
 
-from f5_tts.model.utils import (
-    repetition_found,
-)
 
 # Define filters for exclusion
 out_en = set()

src/f5_tts/train/datasets/prepare_libritts.py

@@ -1,15 +1,17 @@
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import json
 from concurrent.futures import ProcessPoolExecutor
 from importlib.resources import files
 from pathlib import Path
-from tqdm import tqdm
+
 import soundfile as sf
 from datasets.arrow_writer import ArrowWriter
+from tqdm import tqdm
 
 
 def deal_with_audio_dir(audio_dir):

src/f5_tts/train/datasets/prepare_ljspeech.py

@@ -1,14 +1,16 @@
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import json
 from importlib.resources import files
 from pathlib import Path
-from tqdm import tqdm
+
 import soundfile as sf
 from datasets.arrow_writer import ArrowWriter
+from tqdm import tqdm
 
 
 def main():

src/f5_tts/train/datasets/prepare_wenetspeech4tts.py

@@ -4,15 +4,16 @@
 import os
 import sys
 
+
 sys.path.append(os.getcwd())
 
 import json
 from concurrent.futures import ProcessPoolExecutor
 from importlib.resources import files
-from tqdm import tqdm
 
 import torchaudio
 from datasets import Dataset
+from tqdm import tqdm
 
 from f5_tts.model.utils import convert_char_to_pinyin
 

src/f5_tts/train/finetune_cli.py

@@ -5,9 +5,9 @@ from importlib.resources import files
 
 from cached_path import cached_path
 
-from f5_tts.model import CFM, UNetT, DiT, Trainer
-from f5_tts.model.utils import get_tokenizer
+from f5_tts.model import CFM, DiT, Trainer, UNetT
 from f5_tts.model.dataset import load_dataset
+from f5_tts.model.utils import get_tokenizer
 
 
 # -------------------------- Dataset Settings --------------------------- #

src/f5_tts/train/finetune_gradio.py

@@ -1,14 +1,12 @@
 import gc
 import json
-import numpy as np
 import os
 import platform
-import psutil
 import queue
 import random
 import re
-import signal
 import shutil
+import signal
 import subprocess
 import sys
 import tempfile
@@ -16,21 +14,23 @@ import threading
 import time
 from glob import glob
 from importlib.resources import files
-from scipy.io import wavfile
 
 import click
 import gradio as gr
 import librosa
+import numpy as np
+import psutil
 import torch
 import torchaudio
 from cached_path import cached_path
 from datasets import Dataset as Dataset_
 from datasets.arrow_writer import ArrowWriter
 from safetensors.torch import load_file, save_file
+from scipy.io import wavfile
 
 from f5_tts.api import F5TTS
-from f5_tts.model.utils import convert_char_to_pinyin
 from f5_tts.infer.utils_infer import transcribe
+from f5_tts.model.utils import convert_char_to_pinyin
 
 
 training_process = None

src/f5_tts/train/train.py

@@ -10,6 +10,7 @@ from f5_tts.model import CFM, Trainer
 from f5_tts.model.dataset import load_dataset
 from f5_tts.model.utils import get_tokenizer
 
+
 os.chdir(str(files("f5_tts").joinpath("../..")))  # change working directory to root of project (local editable)