Aitron Emper commited on
Commit
889c346
1 Parent(s): c5d2a9e

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rvc/configs/config.py CHANGED
@@ -137,6 +137,7 @@ class Config:
137
 
138
  return x_pad, x_query, x_center, x_max
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  def max_vram_gpu(gpu):
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  if torch.cuda.is_available():
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  gpu_properties = torch.cuda.get_device_properties(gpu)
@@ -144,7 +145,8 @@ def max_vram_gpu(gpu):
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  return total_memory_gb
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  else:
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  return "0"
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-
 
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  def get_gpu_info():
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  ngpu = torch.cuda.device_count()
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  gpu_infos = []
@@ -159,7 +161,5 @@ def get_gpu_info():
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  if len(gpu_infos) > 0:
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  gpu_info = "\n".join(gpu_infos)
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  else:
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- gpu_info = (
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- "Unfortunately, there is no compatible GPU available to support your training."
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- )
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- return gpu_info
 
137
 
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  return x_pad, x_query, x_center, x_max
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+
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  def max_vram_gpu(gpu):
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  if torch.cuda.is_available():
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  gpu_properties = torch.cuda.get_device_properties(gpu)
 
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  return total_memory_gb
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  else:
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  return "0"
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+
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+
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  def get_gpu_info():
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  ngpu = torch.cuda.device_count()
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  gpu_infos = []
 
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  if len(gpu_infos) > 0:
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  gpu_info = "\n".join(gpu_infos)
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  else:
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+ gpu_info = "Unfortunately, there is no compatible GPU available to support your training."
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+ return gpu_info
 
 
rvc/train/extract/extract_f0_print.py CHANGED
@@ -48,9 +48,11 @@ class FeatureInput:
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  torch_device = (
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  torch.device(f"cuda:{torch_device_index % torch.cuda.device_count()}")
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  if torch.cuda.is_available()
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- else torch.device("mps")
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- if torch.backends.mps.is_available()
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- else torch.device("cpu")
 
 
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  )
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  audio = torch.from_numpy(x.astype(np.float32)).to(torch_device, copy=True)
 
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  torch_device = (
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  torch.device(f"cuda:{torch_device_index % torch.cuda.device_count()}")
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  if torch.cuda.is_available()
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+ else (
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+ torch.device("mps")
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+ if torch.backends.mps.is_available()
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+ else torch.device("cpu")
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+ )
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  )
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  audio = torch.from_numpy(x.astype(np.float32)).to(torch_device, copy=True)
rvc/train/losses.py CHANGED
@@ -1,5 +1,6 @@
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  import torch
2
 
 
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  def feature_loss(fmap_r, fmap_g):
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  loss = 0
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  for dr, dg in zip(fmap_r, fmap_g):
 
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  import torch
2
 
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+
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  def feature_loss(fmap_r, fmap_g):
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  loss = 0
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  for dr, dg in zip(fmap_r, fmap_g):
rvc/train/process/change_info.py CHANGED
@@ -1,6 +1,7 @@
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  import os
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  import torch
3
 
 
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  def change_info(path, info, name):
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  try:
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  ckpt = torch.load(path, map_location="cpu")
@@ -10,4 +11,4 @@ def change_info(path, info, name):
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  torch.save(ckpt, f"logs/{name}/{name}")
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  return "Success."
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  except Exception as error:
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- print(error)
 
1
  import os
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  import torch
3
 
4
+
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  def change_info(path, info, name):
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  try:
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  ckpt = torch.load(path, map_location="cpu")
 
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  torch.save(ckpt, f"logs/{name}/{name}")
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  return "Success."
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  except Exception as error:
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+ print(error)