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20 hours ago •
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meta-llama
LLaMA 13B and 70B fail on CPU with BF16
LLaMA 7B runs well on CPU with both BF16 and FP32. But LLaMA 13B and 70B only work on CPU with FP32.
The error for LLaMA 13B and 70B with BF16 comes from embedding and the RuntimeError is Invalid scalar type.
Traceback (most recent call last):
File "/data1/llama-cpu/example_text_completion.py", line 70, in <module>
fire.Fire(main)
File "/home/anaconda3/lib/python3.9/site-packages/fire/core.py", line 141, in Fire
component_trace = _Fire(component, args, parsed_flag_args, context, name)
File "/home/anaconda3/lib/python3.9/site-packages/fire/core.py", line 475, in _Fire
component, remaining_args = _CallAndUpdateTrace(
File "/home/anaconda3/lib/python3.9/site-packages/fire/core.py", line 691, in _CallAndUpdateTrace
component = fn(*varargs, **kwargs)
File "/data1/llama-cpu/example_text_completion.py", line 57, in main
results = generator.text_completion(
File "/data1/llama-cpu/llama/generation.py", line 264, in text_completion
generation_tokens, generation_logprobs = self.generate(
File "/data1/llama-cpu/llama/generation.py", line 181, in generate
logits = self.model.forward(tokens[:, prev_pos:cur_pos], prev_pos)
File "/data1/llama-cpu/llama/model.py", line 471, in forward
h = self.tok_embeddings(tokens)
File "/home/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/home/anaconda3/lib/python3.9/site-packages/fairscale/nn/model_parallel/layers.py", line 214, in forward
output = gather_from_model_parallel_region(output_parallel)
File "/home/anaconda3/lib/python3.9/site-packages/fairscale/nn/model_parallel/mappings.py", line 156, in gather_from_model_parallel_region
return _GatherFromModelParallelRegion.apply(input_)
File "/home/anaconda3/lib/python3.9/site-packages/fairscale/nn/model_parallel/mappings.py", line 131, in forward
return _gather(input_)
File "/home/anaconda3/lib/python3.9/site-packages/fairscale/nn/model_parallel/mappings.py", line 82, in _gather
torch.distributed.all_gather(tensor_list, input_, group=group)
File "/home/anaconda3/lib/python3.9/site-packages/torch/distributed/distributed_c10d.py", line 2075, in all_gather
work.wait()
RuntimeError: Invalid scalar type
Just FYI. I was able to run both 13B and 70B with bfloat16 on CPU. I had tried the Llama2 Chat Model from Hugging Face.
