RuntimeError: use_libuv was requested but PyTorch was build without libuv support

[babymonie]

Bug Description When i try to train a model i get RuntimeError: use_libuv was requested but PyTorch was build without libuv support

Steps to Reproduce Outline the steps to replicate the issue:

1. Go to 'Train'
2. Enter any parameters
3. Click train
4. Observe the error.

Expected Behavior It should train correctly

Desktop Details:

• Operating System: [e.g., Windows 10]
• Browser: [e.g.,Opera]

here's a log: Theme Loaded: Applio Running on local URL: http://127.0.0.1:6969

To create a public link, set share=True in launch(). E:\ApplioV3.0.9\rvc\infer\infer.py:303: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. torch.load(weight_root, map_location="cpu") Starting preprocess with 12 cores... Preprocess completed in 31.11 seconds. Starting extraction with 12 cores and rmvpe... F0 Extraction: 100%|█████████████████████████████████████████████████████████████████| 615/615 [00:12<00:00, 47.80it/s] F0 extraction completed in 12.89 seconds. Starting feature extraction... E:\ApplioV3.0.9\env\lib\site-packages\fairseq\checkpoint_utils.py:315: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. state = torch.load(f, map_location=torch.device("cpu")) E:\ApplioV3.0.9\env\lib\site-packages\torch\nn\utils\weight_norm.py:134: FutureWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm. WeightNorm.apply(module, name, dim) 0%| | 0/615 [00:00<?, ?it/s] Feature extraction completed in 2.26 seconds. Downloading Pretrained Model... 100% [......................................................................] 438156650 / 438156650Process Process-1: Traceback (most recent call last): File "E:\ApplioV3.0.9\env\lib\multiprocessing\process.py", line 315, in _bootstrap self.run() File "E:\ApplioV3.0.9\env\lib\multiprocessing\process.py", line 108, in run self._target(*self._args, self._kwargs) File "E:\ApplioV3.0.9\rvc\train\train.py", line 242, in run dist.init_process_group( File "E:\ApplioV3.0.9\env\lib\site-packages\torch\distributed\c10d_logger.py", line 79, in wrapper return func(*args, *kwargs) File "E:\ApplioV3.0.9\env\lib\site-packages\torch\distributed\c10d_logger.py", line 93, in wrapper func_return = func(args, kwargs) File "E:\ApplioV3.0.9\env\lib\site-packages\torch\distributed\distributed_c10d.py", line 1361, in init_process_group store, rank, world_size = next(rendezvous_iterator) File "E:\ApplioV3.0.9\env\lib\site-packages\torch\distributed\rendezvous.py", line 258, in _env_rendezvous_handler store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout, use_libuv) File "E:\ApplioV3.0.9\env\lib\site-packages\torch\distributed\rendezvous.py", line 185, in _create_c10d_store return TCPStore( RuntimeError: use_libuv was requested but PyTorch was build without libuv support Saved index file 'E:\ApplioV3.0.9\logs\Sir Bloody Daryl\added_Sir Bloody Daryl_v2.index'

cuda version 12.1 torch version:121

[blaisewf]

use the latest compiled

[babymonie]

As in?

[blaisewf]

https://huggingface.co/IAHispano/Applio/resolve/main/Compiled/ApplioV3.2.4.zip?download=true