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Allow FlexGen to use locally downloaded models #111

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Allow FlexGen to use locally downloaded models #111

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2260924
change the index to allow local models
Vinkle-hzt Apr 24, 2023
800b45b
support local models
Vinkle-hzt Apr 24, 2023
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13 changes: 10 additions & 3 deletions flexgen/flex_opt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -584,14 +584,18 @@ def __init__(self,
config: Union[str, OptConfig],
env: ExecutionEnv,
path: str,
policy: Policy):
policy: Policy,
local: bool = False,
local_path: str = None):
if isinstance(config, str):
config = get_opt_config(config)
self.config = config
self.env = env
self.path = path
self.policy = policy
self.num_gpu_batches = policy.num_gpu_batches
self.local = local
self.local_path = local_path

layers = []
layers.append(InputEmbed(self.config, self.env, self.policy))
Expand Down Expand Up @@ -646,7 +650,7 @@ def init_weight(self, j):
os.path.join(self.path, f"{self.config.name}-np")))
check_path = os.path.join(expanded_path, "decoder.embed_positions.weight")
if not os.path.exists(check_path) and DUMMY_WEIGHT not in check_path:
download_opt_weights(self.config.name, self.path)
download_opt_weights(self.config.name, self.path, self.local, self.local_path)

self.layers[j].init_weight(self.weight_home[j], expanded_path)

Expand Down Expand Up @@ -1216,7 +1220,7 @@ def run_flexgen(args):
f"hidden size (prefill): {hidden_size/GB:.3f} GB")

print("init weight...")
model = OptLM(opt_config, env, args.path, policy)
model = OptLM(opt_config, env, args.path, policy, args.local, args.model)

try:
print("warmup - generate")
Expand Down Expand Up @@ -1316,6 +1320,9 @@ def add_parser_arguments(parser):
parser.add_argument("--overlap", type=str2bool, nargs='?',
const=True, default=True)

parser.add_argument("--local", action="store_true",
help="Whether to use local copy of the model weights. ")


if __name__ == "__main__":
parser = argparse.ArgumentParser()
Expand Down
28 changes: 17 additions & 11 deletions flexgen/opt_config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ def hidden_bytes(self, batch_size, seq_len):

def get_opt_config(name, **kwargs):
if "/" in name:
name = name.split("/")[1]
name = name.split("/")[-1]
name = name.lower()

# Handle opt-iml-30b and opt-iml-max-30b
Expand Down Expand Up @@ -216,21 +216,27 @@ def disable_hf_opt_init():
"_init_weights", lambda *args, **kwargs: None)


def download_opt_weights(model_name, path):
def download_opt_weights(model_name, path, local = False, local_path = None):
from huggingface_hub import snapshot_download
import torch

print(f"Load the pre-trained pytorch weights of {model_name} from huggingface. "
f"The downloading and cpu loading can take dozens of minutes. "
f"If it seems to get stuck, you can monitor the progress by "
f"checking the memory usage of this process.")
if not local:
print(f"Load the pre-trained pytorch weights of {model_name} from huggingface. "
f"The downloading and cpu loading can take dozens of minutes. "
f"If it seems to get stuck, you can monitor the progress by "
f"checking the memory usage of this process.")

if "opt" in model_name:
hf_model_name = "facebook/" + model_name
elif "galactica" in model_name:
hf_model_name = "facebook/" + model_name
if "opt" in model_name:
hf_model_name = "facebook/" + model_name
elif "galactica" in model_name:
hf_model_name = "facebook/" + model_name

folder = snapshot_download(hf_model_name, allow_patterns="*.bin")
else:
print(f"Load the pre-trained pytorch weights of {model_name} from local path: "
f"{local_path}. The loading can take dozens of minutes.")
folder = local_path

folder = snapshot_download(hf_model_name, allow_patterns="*.bin")
bin_files = glob.glob(os.path.join(folder, "*.bin"))

if "/" in model_name:
Expand Down