Resolve messages formatting issues (#13095)

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
This commit is contained in:
Emmanuel Ferdman 2025-05-15 11:46:52 +03:00 committed by GitHub
parent 35b49e4d91
commit 1e4e1353a0
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6 changed files with 8 additions and 8 deletions

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@ -470,7 +470,7 @@ if __name__ == "__main__":
if args.gpus:
invalidInputError(len(args.gpus.split(",")) > args.num_gpus, f"Larger --num-gpus "
"({args.num_gpus}) than --gpus {args.gpus}!")
f"({args.num_gpus}) than --gpus {args.gpus}!")
os.environ["CUDA_VISIBLE_DEVICES"] = args.gpus
gptq_config = GptqConfig(

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@ -672,7 +672,7 @@ class _BaseAutoModelClass:
else:
invalidInputError(False,
f'`torch_dtype` can be either `torch.dtype` or `"auto"`,'
'but received {torch_dtype}')
f'but received {torch_dtype}')
dtype_orig = model_class._set_default_torch_dtype(torch_dtype)
# Pretrained Model

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@ -217,7 +217,7 @@ class _BaseAutoModelClass:
max_prompt_len < max_context_len,
(
f"max_prompt_len ({max_prompt_len}) should be less"
" than max_context_len ({max_context_len})"
f" than max_context_len ({max_context_len})"
),
)
optimize_kwargs = {
@ -553,7 +553,7 @@ class _BaseAutoModelClass:
invalidInputError(
False,
f'`torch_dtype` can be either `torch.dtype` or `"auto"`,'
"but received {torch_dtype}",
f"but received {torch_dtype}",
)
dtype_orig = model_class._set_default_torch_dtype(torch_dtype)
@ -588,7 +588,7 @@ class _BaseAutoModelClass:
max_prompt_len < max_context_len,
(
f"max_prompt_len ({max_prompt_len}) should be less"
" than max_context_len ({max_context_len})"
f" than max_context_len ({max_context_len})"
),
)
from ipex_llm.transformers.npu_models.convert_mp import optimize_llm_pre

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@ -127,7 +127,7 @@ def phi3_attention_forward(
invalidInputError(
False,
f"Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)},"
" but is {attention_mask.size()}"
f" but is {attention_mask.size()}"
)
attn_weights = attn_weights + attention_mask

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@ -92,7 +92,7 @@ def load_state_dict(checkpoint_file: Union[str, os.PathLike]):
except Exception as e:
invalidInputError(False,
f"Unable to load weights"
"from pytorch checkpoint file for '{checkpoint_file}' "
f"from pytorch checkpoint file for '{checkpoint_file}' "
f"at '{checkpoint_file}'. ")

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@ -112,7 +112,7 @@ def _load(pickle_fp, map_location, picklemoudle, pickle_file='data.pkl', zip_fil
data = fp.read(size)
return torch.frombuffer(bytearray(data), dtype=dtype)
description = f'storage data_type={data_type} ' \
'path-in-zip={filename} path={self.zip_file.filename}'
f'path-in-zip={filename} path={self.zip_file.filename}'
return LazyStorage(load=load, kind=pid[1], description=description)
@staticmethod