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import argparse
def parse_args():
parser = argparse.ArgumentParser(description="Process Reward Optimization.")
# update paths here!
parser.add_argument(
"--cache_dir",
type=str,
help="HF cache directory",
default="/shared-local/aoq951/HF_CACHE/",
)
parser.add_argument(
"--save_dir",
type=str,
help="Directory to save images",
default="/shared-local/aoq951/ReNO/outputs",
)
# model and optim
parser.add_argument("--model", type=str, help="Model to use", default="sdxl-turbo")
parser.add_argument("--lr", type=float, help="Learning rate", default=5.0)
parser.add_argument("--n_iters", type=int, help="Number of iterations", default=50)
parser.add_argument(
"--n_inference_steps", type=int, help="Number of iterations", default=1
)
parser.add_argument(
"--optim",
choices=["sgd", "adam", "lbfgs"],
default="sgd",
help="Optimizer to be used",
)
parser.add_argument("--nesterov", default=True, action="store_false")
parser.add_argument(
"--grad_clip", type=float, help="Gradient clipping", default=0.1
)
parser.add_argument("--seed", type=int, help="Seed to use", default=0)
# reward losses
parser.add_argument(
"--disable_hps", default=True, action="store_false", dest="enable_hps"
)
parser.add_argument(
"--hps_weighting", type=float, help="Weighting for HPS", default=5.0
)
parser.add_argument(
"--disable_imagereward",
default=True,
action="store_false",
dest="enable_imagereward",
)
parser.add_argument(
"--imagereward_weighting",
type=float,
help="Weighting for ImageReward",
default=1.0,
)
parser.add_argument(
"--disable_clip", default=True, action="store_false", dest="enable_clip"
)
parser.add_argument(
"--clip_weighting", type=float, help="Weighting for CLIP", default=0.01
)
parser.add_argument(
"--disable_pickscore",
default=True,
action="store_false",
dest="enable_pickscore",
)
parser.add_argument(
"--pickscore_weighting",
type=float,
help="Weighting for PickScore",
default=0.05,
)
parser.add_argument(
"--disable_aesthetic",
default=False,
action="store_false",
dest="enable_aesthetic",
)
parser.add_argument(
"--aesthetic_weighting",
type=float,
help="Weighting for Aesthetic",
default=0.0,
)
parser.add_argument(
"--disable_reg", default=True, action="store_false", dest="enable_reg"
)
parser.add_argument(
"--reg_weight", type=float, help="Regularization weight", default=0.01
)
# task specific
parser.add_argument(
"--task",
type=str,
help="Task to run",
default="single",
choices=[
"t2i-compbench",
"single",
"parti-prompts",
"geneval",
"example-prompts",
],
)
parser.add_argument(
"--prompt",
type=str,
help="Prompt to run",
default="A red dog and a green cat",
)
parser.add_argument(
"--benchmark_reward",
help="Reward to benchmark on",
default="total",
choices=["ImageReward", "PickScore", "HPS", "CLIP", "total"],
)
# general
parser.add_argument("--save_all_images", default=False, action="store_true")
parser.add_argument("--no_optim", default=False, action="store_true")
parser.add_argument("--imageselect", default=False, action="store_true")
parser.add_argument("--memsave", default=False, action="store_true")
parser.add_argument("--dtype", type=str, help="Data type to use", default="float16")
parser.add_argument("--device_id", type=str, help="Device ID to use", default=None)
parser.add_argument(
"--cpu_offloading",
help="Enable CPU offloading",
default=False,
action="store_true",
)
# optional multi-step model
parser.add_argument("--enable_multi_apply", default=False, action="store_true")
parser.add_argument(
"--multi_step_model", type=str, help="Model to use", default="flux"
)
args = parser.parse_args()
return args |