babysor / babysor/MockingBird

训练时报错 PytorchStreamReader failed reading zip archive: failed finding central directory

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Description

**Summary[问题简述(一句话)]**
A clear and concise description of what the issue is.
训练时报错 PytorchStreamReader failed reading zip archive: failed finding central directory
**Env & To Reproduce[复现与环境]**
描述你用的环境、代码版本、模型
gtx1060
py3.9.7
![image](https://user-images.githubusercontent.com/56624923/166243083-3579bf7f-c3bb-4815-8168-07977ac66445.png)

**Screenshots[截图(如有)]**
If applicable, add screenshots to help
![image](https://user-images.githubusercontent.com/56624923/166242383-3cd170ed-349f-410d-b18c-add2a7684743.png)

`(mygui) PS D:\video\MockingBird> python synthesizer_train.py mandarin D:\video/SV2TTS/synthesizer
Arguments:
run_id: mandarin
syn_dir: D:\video/SV2TTS/synthesizer
models_dir: synthesizer/saved_models/
save_every: 1000
backup_every: 25000
log_every: 200
force_restart: False
hparams:

Checkpoint path: synthesizer\saved_models\mandarin\mandarin.pt
Loading training data from: D:\video\SV2TTS\synthesizer\train.txt
Using model: Tacotron
Using device: cuda

Initialising Tacotron Model...

Traceback (most recent call last):
File "D:\video\MockingBird\synthesizer_train.py", line 37, in
train(**vars(args))
File "D:\video\MockingBird\synthesizer\train.py", line 75, in train
loaded_shape = torch.load(str(weights_fpath), map_location=device)["model_state"]["encoder.embedding.weight"].shape
File "E:\Anaconda3\envs\mygui\lib\site-packages\torch\serialization.py", line 705, in load
with _open_zipfile_reader(opened_file) as opened_zipfile:
File "E:\Anaconda3\envs\mygui\lib\site-packages\torch\serialization.py", line 243, in __init__
super(_open_zipfile_reader, self).__init__(torch._C.PyTorchFileReader(name_or_buffer))
RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory`

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Research direction

Start with synthesizer_train.py and synthesizer/train.py, then reproduce the provided command and inspect the checkpoint at synthesizer\saved_models\mandarin\mandarin.pt. Verify the checkpoint and model-loading path around torch.load; the issue is done when the failure's cause is confirmed and an actionable resolution is documented.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
28/100

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