Refactor: Format Code with Ruff and Update Deprecated G2PW Link (#2255)

* ruff check --fix

* ruff format --line-length 120 --target-version py39

* Change the link for G2PW Model

* update pytorch version and colab

GPT_SoVITS/utils.py

@@ -1,17 +1,15 @@
-import os
-import glob
-import sys
 import argparse
-import logging
+import glob
 import json
+import logging
+import os
 import subprocess
+import sys
 import traceback
 
 import librosa
 import numpy as np
-from scipy.io.wavfile import read
 import torch
-import logging
 
 logging.getLogger("numba").setLevel(logging.ERROR)
 logging.getLogger("matplotlib").setLevel(logging.ERROR)
@@ -27,11 +25,7 @@ def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimizer=False
     checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
     iteration = checkpoint_dict["iteration"]
     learning_rate = checkpoint_dict["learning_rate"]
-    if (
-        optimizer is not None
-        and not skip_optimizer
-        and checkpoint_dict["optimizer"] is not None
-    ):
+    if optimizer is not None and not skip_optimizer and checkpoint_dict["optimizer"] is not None:
         optimizer.load_state_dict(checkpoint_dict["optimizer"])
     saved_state_dict = checkpoint_dict["model"]
     if hasattr(model, "module"):
@@ -50,9 +44,7 @@ def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimizer=False
             )
         except:
             traceback.print_exc()
-            print(
-                "error, %s is not in the checkpoint" % k
-            )  # shape不对也会，比如text_embedding当cleaner修改时
+            print("error, %s is not in the checkpoint" % k)  # shape不对也会，比如text_embedding当cleaner修改时
             new_state_dict[k] = v
     if hasattr(model, "module"):
         model.module.load_state_dict(new_state_dict)
@@ -60,25 +52,28 @@ def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimizer=False
         model.load_state_dict(new_state_dict)
     print("load ")
     logger.info(
-        "Loaded checkpoint '{}' (iteration {})".format(checkpoint_path, iteration)
+        "Loaded checkpoint '{}' (iteration {})".format(
+            checkpoint_path,
+            iteration,
+        )
     )
     return model, optimizer, learning_rate, iteration
 
-from time import time as ttime
+
 import shutil
-def my_save(fea,path):#####fix issue: torch.save doesn't support chinese path
-    dir=os.path.dirname(path)
-    name=os.path.basename(path)
-    tmp_path="%s.pth"%(ttime())
-    torch.save(fea,tmp_path)
-    shutil.move(tmp_path,"%s/%s"%(dir,name))
+from time import time as ttime
+
+
+def my_save(fea, path):  #####fix issue: torch.save doesn't support chinese path
+    dir = os.path.dirname(path)
+    name = os.path.basename(path)
+    tmp_path = "%s.pth" % (ttime())
+    torch.save(fea, tmp_path)
+    shutil.move(tmp_path, "%s/%s" % (dir, name))
+
 
 def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path):
-    logger.info(
-        "Saving model and optimizer state at iteration {} to {}".format(
-            iteration, checkpoint_path
-        )
-    )
+    logger.info("Saving model and optimizer state at iteration {} to {}".format(iteration, checkpoint_path))
     if hasattr(model, "module"):
         state_dict = model.module.state_dict()
     else:
@@ -132,7 +127,6 @@ def plot_spectrogram_to_numpy(spectrogram):
         mpl_logger = logging.getLogger("matplotlib")
         mpl_logger.setLevel(logging.WARNING)
     import matplotlib.pylab as plt
-    import numpy as np
 
     fig, ax = plt.subplots(figsize=(10, 2))
     im = ax.imshow(spectrogram, aspect="auto", origin="lower", interpolation="none")
@@ -158,11 +152,13 @@ def plot_alignment_to_numpy(alignment, info=None):
         mpl_logger = logging.getLogger("matplotlib")
         mpl_logger.setLevel(logging.WARNING)
     import matplotlib.pylab as plt
-    import numpy as np
 
     fig, ax = plt.subplots(figsize=(6, 4))
     im = ax.imshow(
-        alignment.transpose(), aspect="auto", origin="lower", interpolation="none"
+        alignment.transpose(),
+        aspect="auto",
+        origin="lower",
+        interpolation="none",
     )
     fig.colorbar(im, ax=ax)
     xlabel = "Decoder timestep"
@@ -199,9 +195,7 @@ def get_hparams(init=True, stage=1):
         default="./configs/s2.json",
         help="JSON file for configuration",
     )
-    parser.add_argument(
-        "-p", "--pretrain", type=str, required=False, default=None, help="pretrain dir"
-    )
+    parser.add_argument("-p", "--pretrain", type=str, required=False, default=None, help="pretrain dir")
     parser.add_argument(
         "-rs",
         "--resume_step",
@@ -250,11 +244,7 @@ def clean_checkpoints(path_to_models="logs/44k/", n_ckpts_to_keep=2, sort_by_tim
     """
     import re
 
-    ckpts_files = [
-        f
-        for f in os.listdir(path_to_models)
-        if os.path.isfile(os.path.join(path_to_models, f))
-    ]
+    ckpts_files = [f for f in os.listdir(path_to_models) if os.path.isfile(os.path.join(path_to_models, f))]
     name_key = lambda _f: int(re.compile("._(\d+)\.pth").match(_f).group(1))
     time_key = lambda _f: os.path.getmtime(os.path.join(path_to_models, _f))
     sort_key = time_key if sort_by_time else name_key
@@ -263,8 +253,7 @@ def clean_checkpoints(path_to_models="logs/44k/", n_ckpts_to_keep=2, sort_by_tim
         key=sort_key,
     )
     to_del = [
-        os.path.join(path_to_models, fn)
-        for fn in (x_sorted("G")[:-n_ckpts_to_keep] + x_sorted("D")[:-n_ckpts_to_keep])
+        os.path.join(path_to_models, fn) for fn in (x_sorted("G")[:-n_ckpts_to_keep] + x_sorted("D")[:-n_ckpts_to_keep])
     ]
     del_info = lambda fn: logger.info(f".. Free up space by deleting ckpt {fn}")
     del_routine = lambda x: [os.remove(x), del_info(x)]
@@ -296,7 +285,7 @@ def check_git_hash(model_dir):
     if not os.path.exists(os.path.join(source_dir, ".git")):
         logger.warn(
             "{} is not a git repository, therefore hash value comparison will be ignored.".format(
-                source_dir
+                source_dir,
             )
         )
         return
@@ -309,7 +298,8 @@ def check_git_hash(model_dir):
         if saved_hash != cur_hash:
             logger.warn(
                 "git hash values are different. {}(saved) != {}(current)".format(
-                    saved_hash[:8], cur_hash[:8]
+                    saved_hash[:8],
+                    cur_hash[:8],
                 )
             )
     else:
@@ -366,6 +356,6 @@ class HParams:
 if __name__ == "__main__":
     print(
         load_wav_to_torch(
-            "/home/fish/wenetspeech/dataset_vq/Y0000022499_wHFSeHEx9CM/S00261.flac"
+            "/home/fish/wenetspeech/dataset_vq/Y0000022499_wHFSeHEx9CM/S00261.flac",
         )
     )