0%|                                                 | 0/1000 [00:00<?, ?it/s]
  0%|                                                 | 0/1000 [00:00<?, ?it/s]Traceback (most recent call last):
  File "main.py", line 444, in <module>
    main()
  File "main.py", line 383, in main
    train_result = trainer.train(resume_from_checkpoint=checkpoint)
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 1635, in train
    return inner_training_loop(
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 1904, in _inner_training_loop
    tr_loss_step = self.training_step(model, inputs)
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 2647, in training_step
    loss = self.compute_loss(model, inputs)
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 2679, in compute_loss
    outputs = model(**inputs)
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 1191, in forward
    transformer_outputs = self.transformer(
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 986, in forward
    layer_ret = torch.utils.checkpoint.checkpoint(
  File "D:\Program\Python38\lib\site-packages\torch\utils\checkpoint.py", line 249, in checkpoint
    return CheckpointFunction.apply(function, preserve, *args)
  File "D:\Program\Python38\lib\site-packages\torch\autograd\function.py", line 506, in apply
    return super().apply(*args, **kwargs)  # type: ignore[misc]
  File "D:\Program\Python38\lib\site-packages\torch\utils\checkpoint.py", line 107, in forward
    outputs = run_function(*args)
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 627, in forward
    attention_outputs = self.attention(
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 460, in forward
    cos, sin = self.rotary_emb(q1, seq_len=position_ids.max() + 1)
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 201, in forward
    if self.max_seq_len_cached is None or (seq_len > self.max_seq_len_cached):
KeyboardInterrupt
Error in sys.excepthook:
Traceback (most recent call last):
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1694, in print
    extend(render(renderable, render_options))
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1330, in render
    yield from self.render(render_output, _options)
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1326, in render
    for render_output in iter_render:
  File "D:\Program\Python38\lib\site-packages\rich\constrain.py", line 29, in __rich_console__
    yield from console.render(self.renderable, child_options)
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1326, in render
    for render_output in iter_render:
  File "D:\Program\Python38\lib\site-packages\rich\panel.py", line 220, in __rich_console__
    lines = console.render_lines(renderable, child_options, style=style)
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1366, in render_lines
    lines = list(
  File "D:\Program\Python38\lib\site-packages\rich\segment.py", line 292, in split_and_crop_lines
    for segment in segments:
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1326, in render
    for render_output in iter_render:
  File "D:\Program\Python38\lib\site-packages\rich\padding.py", line 97, in __rich_console__
    lines = console.render_lines(
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1366, in render_lines
    lines = list(
  File "D:\Program\Python38\lib\site-packages\rich\segment.py", line 292, in split_and_crop_lines
    for segment in segments:
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1330, in render
    yield from self.render(render_output, _options)
  File "D:\Program\Python38\lib\site-packages\rich\console.py", line 1326, in render
    for render_output in iter_render:
  File "D:\Program\Python38\lib\site-packages\rich\syntax.py", line 609, in __rich_console__
    segments = Segments(self._get_syntax(console, options))
  File "D:\Program\Python38\lib\site-packages\rich\segment.py", line 668, in __init__
    self.segments = list(segments)
  File "D:\Program\Python38\lib\site-packages\rich\syntax.py", line 637, in _get_syntax
    text = self.highlight(processed_code, self.line_range)
  File "D:\Program\Python38\lib\site-packages\rich\syntax.py", line 509, in highlight
    text.append_tokens(tokens_to_spans())
  File "D:\Program\Python38\lib\site-packages\rich\text.py", line 995, in append_tokens
    for content, style in tokens:
  File "D:\Program\Python38\lib\site-packages\rich\syntax.py", line 497, in tokens_to_spans
    _token_type, token = next(tokens)
  File "D:\Program\Python38\lib\site-packages\rich\syntax.py", line 484, in line_tokenize
    for token_type, token in lexer.get_tokens(code):
  File "D:\Program\Python38\lib\site-packages\pygments\lexer.py", line 190, in streamer
    for _, t, v in self.get_tokens_unprocessed(text):
  File "D:\Program\Python38\lib\site-packages\pygments\lexer.py", line 632, in get_tokens_unprocessed
    m = rexmatch(text, pos)
KeyboardInterrupt
Original exception was:
Traceback (most recent call last):
  File "main.py", line 444, in <module>
    main()
  File "main.py", line 383, in main
    train_result = trainer.train(resume_from_checkpoint=checkpoint)
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 1635, in train
    return inner_training_loop(
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 1904, in _inner_training_loop
    tr_loss_step = self.training_step(model, inputs)
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 2647, in training_step
    loss = self.compute_loss(model, inputs)
  File "E:\Documents\Desktop\ChatGLM-6B\ptuning\trainer.py", line 2679, in compute_loss
    outputs = model(**inputs)
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 1191, in forward
    transformer_outputs = self.transformer(
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 986, in forward
    layer_ret = torch.utils.checkpoint.checkpoint(
  File "D:\Program\Python38\lib\site-packages\torch\utils\checkpoint.py", line 249, in checkpoint
    return CheckpointFunction.apply(function, preserve, *args)
  File "D:\Program\Python38\lib\site-packages\torch\autograd\function.py", line 506, in apply
    return super().apply(*args, **kwargs)  # type: ignore[misc]
  File "D:\Program\Python38\lib\site-packages\torch\utils\checkpoint.py", line 107, in forward
    outputs = run_function(*args)
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 627, in forward
    attention_outputs = self.attention(
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 460, in forward
    cos, sin = self.rotary_emb(q1, seq_len=position_ids.max() + 1)
  File "D:\Program\Python38\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\Users\Lenovo/.cache\huggingface\modules\transformers_modules\chatglm-6b-int4\modeling_chatglm.py", line 201, in forward
    if self.max_seq_len_cached is None or (seq_len > self.max_seq_len_cached):
KeyboardInterrupt