mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
124 lines
3.2 KiB
124 lines
3.2 KiB
from colossalai import get_default_parser
|
|
|
|
def parse_demo_args():
|
|
|
|
parser = get_default_parser()
|
|
parser.add_argument(
|
|
"--model_name_or_path",
|
|
type=str,
|
|
default="google/vit-base-patch16-224",
|
|
help="Path to pretrained model or model identifier from huggingface.co/models."
|
|
)
|
|
parser.add_argument(
|
|
"--output_path",
|
|
type=str,
|
|
default="./output_model.bin",
|
|
help="The path of your saved model after finetuning."
|
|
)
|
|
parser.add_argument(
|
|
"--plugin",
|
|
type=str,
|
|
default="gemini",
|
|
help="Plugin to use. Valid plugins include 'torch_ddp','torch_ddp_fp16','gemini','low_level_zero'."
|
|
)
|
|
parser.add_argument(
|
|
"--num_epoch",
|
|
type=int,
|
|
default=3,
|
|
help="Number of epochs."
|
|
)
|
|
parser.add_argument(
|
|
"--batch_size",
|
|
type=int,
|
|
default=32,
|
|
help="Batch size (per dp group) for the training dataloader."
|
|
)
|
|
parser.add_argument(
|
|
"--learning_rate",
|
|
type=float,
|
|
default=3e-4,
|
|
help="Initial learning rate (after the potential warmup period) to use."
|
|
)
|
|
parser.add_argument(
|
|
"--warmup_ratio",
|
|
type=float,
|
|
default=0.3,
|
|
help="Ratio of warmup steps against total training steps."
|
|
)
|
|
parser.add_argument(
|
|
"--weight_decay",
|
|
type=float,
|
|
default=0.1,
|
|
help="Weight decay to use."
|
|
)
|
|
parser.add_argument(
|
|
"--seed",
|
|
type=int,
|
|
default=42,
|
|
help="A seed for reproducible training."
|
|
)
|
|
|
|
args = parser.parse_args()
|
|
return args
|
|
|
|
def parse_benchmark_args():
|
|
|
|
parser = get_default_parser()
|
|
|
|
parser.add_argument(
|
|
"--model_name_or_path",
|
|
type=str,
|
|
default="google/vit-base-patch16-224",
|
|
help="Path to a pretrained model or model identifier from huggingface.co/models."
|
|
)
|
|
parser.add_argument(
|
|
"--plugin",
|
|
type=str,
|
|
default="gemini",
|
|
help="Plugin to use. Valid plugins include 'torch_ddp','torch_ddp_fp16','gemini','low_level_zero'."
|
|
)
|
|
parser.add_argument(
|
|
"--batch_size",
|
|
type=int,
|
|
default=8,
|
|
help="Batch size (per dp group) for the training dataloader."
|
|
)
|
|
parser.add_argument(
|
|
"--num_labels",
|
|
type=int,
|
|
default=10,
|
|
help="Number of labels for classification."
|
|
)
|
|
parser.add_argument(
|
|
"--learning_rate",
|
|
type=float,
|
|
default=5e-5,
|
|
help="Initial learning rate (after the potential warmup period) to use."
|
|
)
|
|
parser.add_argument(
|
|
"--weight_decay",
|
|
type=float,
|
|
default=0.0,
|
|
help="Weight decay to use."
|
|
)
|
|
parser.add_argument(
|
|
"--max_train_steps",
|
|
type=int,
|
|
default=20,
|
|
help="Total number of training steps to perform."
|
|
)
|
|
parser.add_argument(
|
|
"--seed",
|
|
type=int,
|
|
default=42,
|
|
help="A seed for reproducible training."
|
|
)
|
|
parser.add_argument(
|
|
"--mem_cap",
|
|
type=int,
|
|
default=0,
|
|
help="Limit on the usage of space for each GPU (in GB)."
|
|
)
|
|
args = parser.parse_args()
|
|
|
|
return args |