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Reuse disk-cache-dir parameter for flexgen

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oobabooga 2023-02-21 22:11:05 -03:00
parent f3c75bbd64
commit 311404e258
1 changed files with 3 additions and 3 deletions
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6
server.py
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@ -42,7 +42,7 @@ parser.add_argument('--load-in-8bit', action='store_true', help='Load the model
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.')
parser.add_argument('--disk', action='store_true', help='If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk.')
parser.add_argument('--disk-cache-dir', type=str, help='Directory to save the disk cache to. Defaults to "cache/".')
parser.add_argument('--disk-cache-dir', type=str, default="cache", help='Directory to save the disk cache to. Defaults to "cache".')
parser.add_argument('--gpu-memory', type=int, help='Maximum GPU memory in GiB to allocate. This is useful if you get out of memory errors while trying to generate text. Must be an integer number.')
parser.add_argument('--cpu-memory', type=int, help='Maximum CPU memory in GiB to allocate for offloaded weights. Must be an integer number. Defaults to 99.')
parser.add_argument('--flexgen', action='store_true', help='Enable the use of FlexGen offloading.')
@ -122,7 +122,7 @@ def load_model(model_name):
elif args.flexgen:
gpu = TorchDevice("cuda:0")
cpu = TorchDevice("cpu")
disk = TorchDisk("cache")
disk = TorchDisk(args.disk_cache_dir)
env = Env(gpu=gpu, cpu=cpu, disk=disk, mixed=TorchMixedDevice([gpu, cpu, disk]))
# Offloading policy
@ -178,7 +178,7 @@ def load_model(model_name):
print(f"\033[1;32;1mAuto-assiging --gpu-memory {suggestion} for your GPU to try to prevent out-of-memory errors.\nYou can manually set other values.\033[0;37;0m")
params.append(f"max_memory={{0: '{suggestion}GiB', 'cpu': '{args.cpu_memory or '99'}GiB'}}")
if args.disk:
params.append(f"offload_folder='{args.disk_cache_dir or 'cache'}'")
params.append(f"offload_folder='{args.disk_cache_dir}'")
command = f"{command}(Path(f'models/{model_name}'), {', '.join(set(params))})"
model = eval(command)