optimize: no json config writeback

infer/lib/train/utils.py

@@ -5,7 +5,7 @@ import logging
 import os
 import subprocess
 import sys
-import traceback
+import shutil
 
 import numpy as np
 import torch
@@ -297,7 +297,6 @@ def get_hparams(init=True):
       -c不要了
     """
     parser = argparse.ArgumentParser()
-    # parser.add_argument('-c', '--config', type=str, default="configs/40k.json",help='JSON file for configuration')
     parser.add_argument(
         "-se",
         "--save_every_epoch",
@@ -360,23 +359,9 @@ def get_hparams(init=True):
     name = args.experiment_dir
     experiment_dir = os.path.join("./logs", args.experiment_dir)
 
-    if not os.path.exists(experiment_dir):
-        os.makedirs(experiment_dir)
-
-    if args.version == "v1" or args.sample_rate == "40k":
-        config_path = "configs/v1/%s.json" % args.sample_rate
-    else:
-        config_path = "configs/v2/%s.json" % args.sample_rate
     config_save_path = os.path.join(experiment_dir, "config.json")
-    if init:
-        with open(config_path, "r") as f:
-            data = f.read()
-        with open(config_save_path, "w") as f:
-            f.write(data)
-    else:
-        with open(config_save_path, "r") as f:
-            data = f.read()
-    config = json.loads(data)
+    with open(config_save_path, "r") as f:
+        config = json.load(f)
 
     hparams = HParams(**config)
     hparams.model_dir = hparams.experiment_dir = experiment_dir

infer/modules/train/preprocess.py

@@ -12,6 +12,7 @@ sr = int(sys.argv[2])
 n_p = int(sys.argv[3])
 exp_dir = sys.argv[4]
 noparallel = sys.argv[5] == "True"
+per = float(sys.argv[6])
 import multiprocessing
 import os
 import traceback
@@ -36,7 +37,7 @@ def println(strr):
 
 
 class PreProcess:
-    def __init__(self, sr, exp_dir):
+    def __init__(self, sr, exp_dir, per=3.7):
         self.slicer = Slicer(
             sr=sr,
             threshold=-42,
@@ -47,7 +48,7 @@ class PreProcess:
         )
         self.sr = sr
         self.bh, self.ah = signal.butter(N=5, Wn=48, btype="high", fs=self.sr)
-        self.per = 3.0
+        self.per = per
         self.overlap = 0.3
         self.tail = self.per + self.overlap
         self.max = 0.9
@@ -134,8 +135,8 @@ class PreProcess:
             println("Fail. %s" % traceback.format_exc())
 
 
-def preprocess_trainset(inp_root, sr, n_p, exp_dir):
-    pp = PreProcess(sr, exp_dir)
+def preprocess_trainset(inp_root, sr, n_p, exp_dir, per):
+    pp = PreProcess(sr, exp_dir, per)
     println("start preprocess")
     println(sys.argv)
     pp.pipeline_mp_inp_dir(inp_root, n_p)
@@ -143,4 +144,4 @@ def preprocess_trainset(inp_root, sr, n_p, exp_dir):
 
 
 if __name__ == "__main__":
-    preprocess_trainset(inp_root, sr, n_p, exp_dir)
+    preprocess_trainset(inp_root, sr, n_p, exp_dir, per)

infer/modules/vc/modules.py

@@ -210,12 +210,12 @@ class VC:
             if self.tgt_sr != resample_sr >= 16000:
                 self.tgt_sr = resample_sr
             index_info = (
-                "Using index:%s." % file_index
+                "Index:\n%s." % file_index
                 if os.path.exists(file_index)
                 else "Index not used."
             )
             return (
-                f"Success.\n {index_info}\nTime:\n npy:{times[0]}s, f0:{times[1]}s, infer:{times[2]}s",
+                "Success.\n%s\nTime:\nnpy: %.2fs, f0: %.2fs, infer: %.2fs." % (index_info, *times),
                 (self.tgt_sr, audio_opt),
             )
         except: