We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
在跑您的ddp_trainer.py时 accelerate launch --config_file defualt_config.yaml ddp_trainer.py
Traceback (most recent call last): [rank0]: File "/root/LLM_test/ddp_trainer.py", line 105, in [rank0]: trainer.train() [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/transformers/trainer.py", line 2164, in train [rank0]: return inner_training_loop( [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/transformers/trainer.py", line 2323, in _inner_training_loop [rank0]: model, self.optimizer = self.accelerator.prepare(self.model, self.optimizer) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/accelerate/accelerator.py", line 1333, in prepare [rank0]: result = self._prepare_deepspeed(*args) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/accelerate/accelerator.py", line 1849, in _prepare_deepspeed [rank0]: engine, optimizer, _, lr_scheduler = ds_initialize(**kwargs) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/init.py", line 193, in initialize [rank0]: engine = DeepSpeedEngine(args=args, [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 271, in init [rank0]: self._configure_distributed_model(model) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1213, in _configure_distributed_model [rank0]: self._broadcast_model() [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1131, in _broadcast_model [rank0]: dist.broadcast(p.data, groups._get_broadcast_src_rank(), group=self.seq_data_parallel_group) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper [rank0]: return func(*args, **kwargs) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 224, in broadcast [rank0]: return cdb.broadcast(tensor=tensor, src=src, group=group, async_op=async_op) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 632, in _fn [rank0]: return fn(*args, **kwargs) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 200, in broadcast [rank0]: return torch.distributed.broadcast(tensor=tensor, src=src, group=group, async_op=async_op) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper [rank0]: return func(*args, **kwargs) [rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 2421, in broadcast [rank0]: work = group.broadcast([tensor], opts) [rank0]: ValueError: Tensors must be contiguous 这应该如何解决
The text was updated successfully, but these errors were encountered:
No branches or pull requests
在跑您的ddp_trainer.py时 accelerate launch --config_file defualt_config.yaml ddp_trainer.py
Traceback (most recent call last):
[rank0]: File "/root/LLM_test/ddp_trainer.py", line 105, in
[rank0]: trainer.train()
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/transformers/trainer.py", line 2164, in train
[rank0]: return inner_training_loop(
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/transformers/trainer.py", line 2323, in _inner_training_loop
[rank0]: model, self.optimizer = self.accelerator.prepare(self.model, self.optimizer)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/accelerate/accelerator.py", line 1333, in prepare
[rank0]: result = self._prepare_deepspeed(*args)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/accelerate/accelerator.py", line 1849, in _prepare_deepspeed
[rank0]: engine, optimizer, _, lr_scheduler = ds_initialize(**kwargs)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/init.py", line 193, in initialize
[rank0]: engine = DeepSpeedEngine(args=args,
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 271, in init
[rank0]: self._configure_distributed_model(model)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1213, in _configure_distributed_model
[rank0]: self._broadcast_model()
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1131, in _broadcast_model
[rank0]: dist.broadcast(p.data, groups._get_broadcast_src_rank(), group=self.seq_data_parallel_group)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank0]: return func(*args, **kwargs)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 224, in broadcast
[rank0]: return cdb.broadcast(tensor=tensor, src=src, group=group, async_op=async_op)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 632, in _fn
[rank0]: return fn(*args, **kwargs)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 200, in broadcast
[rank0]: return torch.distributed.broadcast(tensor=tensor, src=src, group=group, async_op=async_op)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank0]: return func(*args, **kwargs)
[rank0]: File "/root/anaconda3/envs/liuyu_llm/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 2421, in broadcast
[rank0]: work = group.broadcast([tensor], opts)
[rank0]: ValueError: Tensors must be contiguous
这应该如何解决
The text was updated successfully, but these errors were encountered: