[pre-commit.ci] pre-commit autoupdate (#80)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/psf/black: 23.12.1 → 24.1.1](psf/black@23.12.1...24.1.1)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.pre-commit-config.yaml

@@ -9,7 +9,7 @@ repos:
         args: [--profile=black]
 
   - repo: https://github.com/psf/black
-    rev: 23.12.1
+    rev: 24.1.1
     hooks:
       - id: black
 

fish_speech/datasets/text.py

@@ -325,9 +325,9 @@ def augment(self):
 
             tokens = torch.tensor(tokens, dtype=torch.long)
             labels = tokens.clone()
-            labels[
-                1:, : len(encoded) + 1
-            ] = -100  # Mask out the <s> tokens for semantic
+            labels[1:, : len(encoded) + 1] = (
+                -100
+            )  # Mask out the <s> tokens for semantic
 
         return {
             "tokens": tokens[:, :-1],

fish_speech/models/vqgan/modules/encoders.py

@@ -303,9 +303,11 @@ def __init__(
             in_channels, vq_channels, kernel_size=downsample, stride=downsample
         )
         self.conv_out = nn.Sequential(
-            nn.Upsample(scale_factor=downsample, mode="nearest")
-            if downsample > 1
-            else nn.Identity(),
+            (
+                nn.Upsample(scale_factor=downsample, mode="nearest")
+                if downsample > 1
+                else nn.Identity()
+            ),
             nn.Conv1d(vq_channels, in_channels, kernel_size=1, stride=1),
         )
 

fish_speech/text/parser.py

@@ -236,4 +236,8 @@ def g2p(text, order=None):
     )
     print(segments)
 
-    print(clean_text("测试一下 Hugging face, BGM声音很大吗？那我改一下. 世界、こんにちは。<p:123> <p:aH>"))
+    print(
+        clean_text(
+            "测试一下 Hugging face, BGM声音很大吗？那我改一下. 世界、こんにちは。<p:123> <p:aH>"
+        )
+    )

fish_speech/text/tone_sandhi.py

@@ -107,7 +107,10 @@ def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> List[str]:
         # 个做量词
         elif (
             ge_idx >= 1
-            and (word[ge_idx - 1].isnumeric() or word[ge_idx - 1] in "几有两半多各整每做是")
+            and (
+                word[ge_idx - 1].isnumeric()
+                or word[ge_idx - 1] in "几有两半多各整每做是"
+            )
         ) or word == "个":
             finals[ge_idx] = finals[ge_idx][:-1] + "5"
         else:

fish_speech/utils/rich_utils.py

@@ -43,9 +43,13 @@ def print_config_tree(
 
     # add fields from `print_order` to queue
     for field in print_order:
-        queue.append(field) if field in cfg else log.warning(
-            f"Field '{field}' not found in config. "
-            + f"Skipping '{field}' config printing..."
+        (
+            queue.append(field)
+            if field in cfg
+            else log.warning(
+                f"Field '{field}' not found in config. "
+                + f"Skipping '{field}' config printing..."
+            )
         )
 
     # add all the other fields to queue (not specified in `print_order`)

fish_speech/webui/app.py

@@ -157,10 +157,14 @@ def build_model_config_block():
     llama_ckpt_path = gr.Textbox(
         label="Llama 模型路径", value="checkpoints/text2semantic-400m-v0.2-4k.pth"
     )
-    llama_config_name = gr.Textbox(label="Llama 配置文件", value="text2semantic_finetune")
+    llama_config_name = gr.Textbox(
+        label="Llama 配置文件", value="text2semantic_finetune"
+    )
     tokenizer = gr.Textbox(label="Tokenizer", value="fishaudio/speech-lm-v1")
 
-    vqgan_ckpt_path = gr.Textbox(label="VQGAN 模型路径", value="checkpoints/vqgan-v1.pth")
+    vqgan_ckpt_path = gr.Textbox(
+        label="VQGAN 模型路径", value="checkpoints/vqgan-v1.pth"
+    )
     vqgan_config_name = gr.Textbox(label="VQGAN 配置文件", value="vqgan_pretrain")
 
     load_model_btn = gr.Button(value="加载模型", variant="primary")
@@ -269,7 +273,9 @@ def inference(
 
                 with gr.Row():
                     with gr.Tab(label="合成参数"):
-                        gr.Markdown("配置常见合成参数. 自动音素会在推理时自动将文本转换为音素.")
+                        gr.Markdown(
+                            "配置常见合成参数. 自动音素会在推理时自动将文本转换为音素."
+                        )
 
                         input_mode = gr.Dropdown(
                             choices=["文本", "自动音素"],

tools/llama/generate.py

@@ -115,9 +115,9 @@ def decode_one_token(
             codebooks.append(
                 sample(
                     logits.codebook_logits[:, :, i],
-                    previous_tokens=previous_tokens[i + 1]
-                    if previous_tokens is not None
-                    else None,
+                    previous_tokens=(
+                        previous_tokens[i + 1] if previous_tokens is not None else None
+                    ),
                     **sampling_kwargs,
                 )[0]
             )
@@ -362,7 +362,11 @@ def load_model(config_name, checkpoint_path, device, precision):
 
 
 @click.command()
-@click.option("--text", type=str, default="你说的对, 但是原神是一款由米哈游自主研发的开放世界手游.")
+@click.option(
+    "--text",
+    type=str,
+    default="你说的对, 但是原神是一款由米哈游自主研发的开放世界手游.",
+)
 @click.option("--prompt-text", type=str, default=None)
 @click.option(
     "--prompt-tokens", type=click.Path(path_type=Path, exists=True), default=None

tools/merge_asr_files.py

@@ -48,4 +48,6 @@ def merge_and_delete_files(save_dir, original_files):
 
 
 if __name__ == "__main__":
-    merge_and_delete_files("/home/spicysama/fish-speech/data/demo/首次揭秘B站百大是怎么选出来的")
+    merge_and_delete_files(
+        "/home/spicysama/fish-speech/data/demo/首次揭秘B站百大是怎么选出来的"
+    )

tools/whisper_asr.py

@@ -21,6 +21,7 @@
 
 Note: Be aware of your audio sample rate, which defaults to 44.1kHz.
 """
+
 from pathlib import Path
 
 import click