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add tqdm when loading checkpoint shards #6569

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merged 5 commits into from
Jul 23, 2024
Merged

add tqdm when loading checkpoint shards #6569

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3cde6e6
add tqdm when loading checkpoint shards
Jul 19, 2024
496dc59
Merge branch 'vllm-project:main' into add-tqdm-loading-checkpoint
zhaotyer Jul 23, 2024
92dae54
add tqdm to each loading format
Jul 23, 2024
dd19e86
fix format
youkaichao Jul 23, 2024
8dfe250
fix format
youkaichao Jul 23, 2024
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2 changes: 1 addition & 1 deletion vllm/logger.py
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Original file line number Diff line number Diff line change
Expand Up @@ -151,4 +151,4 @@ def enable_trace_function_call(log_file_path: str,
if root_dir is None:
# by default, this is the vllm root directory
root_dir = os.path.dirname(os.path.dirname(__file__))
sys.settrace(partial(_trace_calls, log_file_path, root_dir))
sys.settrace(partial(_trace_calls, log_file_path, root_dir))
3 changes: 3 additions & 0 deletions vllm/model_executor/model_loader/weight_utils.py
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Expand Up @@ -331,6 +331,7 @@ def np_cache_weights_iterator(
with get_lock(model_name_or_path, cache_dir):
if not os.path.exists(weight_names_file):
weight_names: List[str] = []
hf_weights_files = tqdm(hf_weights_files,desc="Loading np_cache checkpoint shards")
for bin_file in hf_weights_files:
state = torch.load(bin_file, map_location="cpu")
for name, param in state.items():
Expand All @@ -355,6 +356,7 @@ def safetensors_weights_iterator(
hf_weights_files: List[str]
) -> Generator[Tuple[str, torch.Tensor], None, None]:
"""Iterate over the weights in the model safetensor files."""
hf_weights_files = tqdm(hf_weights_files,desc="Loading safetensors checkpoint shards")
for st_file in hf_weights_files:
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the common practice would be:

for st_file in tqdm(hf_weights_files, desc="Loading safetensors checkpoint shards"):

with safe_open(st_file, framework="pt") as f:
for name in f.keys(): # noqa: SIM118
Expand All @@ -366,6 +368,7 @@ def pt_weights_iterator(
hf_weights_files: List[str]
) -> Generator[Tuple[str, torch.Tensor], None, None]:
"""Iterate over the weights in the model bin/pt files."""
hf_weights_files = tqdm(hf_weights_files,desc="Loading pt checkpoint shards")
for bin_file in hf_weights_files:
state = torch.load(bin_file, map_location="cpu")
for name, param in state.items():
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