Files
SHARK-Studio/web/models/stable_diffusion/stable_args.py
2023-01-16 18:37:36 +05:30

257 lines
6.4 KiB
Python

import argparse
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
##############################################################################
### Stable Diffusion Params
##############################################################################
p.add_argument(
"--prompts",
nargs="+",
default=["cyberpunk forest by Salvador Dali"],
help="text of which images to be generated.",
)
p.add_argument(
"--negative-prompts",
nargs="+",
default=[""],
help="text you don't want to see in the generated image.",
)
p.add_argument(
"--steps",
type=int,
default=50,
help="the no. of steps to do the sampling.",
)
p.add_argument(
"--seed",
type=int,
default=42,
help="the seed to use.",
)
p.add_argument(
"--guidance_scale",
type=float,
default=7.5,
help="the value to be used for guidance scaling.",
)
p.add_argument(
"--max_length",
type=int,
default=64,
help="max length of the tokenizer output, options are 64 and 77.",
)
##############################################################################
### Model Config and Usage Params
##############################################################################
p.add_argument(
"--device", type=str, default="vulkan", help="device to run the model."
)
p.add_argument(
"--version",
type=str,
default="v2_1base",
help="Specify version of stable diffusion model",
)
p.add_argument(
"--precision", type=str, default="fp16", help="precision to run the model."
)
p.add_argument(
"--import_mlir",
default=False,
action=argparse.BooleanOptionalAction,
help="imports the model from torch module to shark_module otherwise downloads the model from shark_tank.",
)
p.add_argument(
"--load_vmfb",
default=True,
action=argparse.BooleanOptionalAction,
help="attempts to load the model from a precompiled flatbuffer and compiles + saves it if not found.",
)
p.add_argument(
"--save_vmfb",
default=False,
action=argparse.BooleanOptionalAction,
help="saves the compiled flatbuffer to the local directory",
)
p.add_argument(
"--use_tuned",
default=True,
action=argparse.BooleanOptionalAction,
help="Download and use the tuned version of the model if available",
)
p.add_argument(
"--use_base_vae",
default=False,
action=argparse.BooleanOptionalAction,
help="Do conversion from the VAE output to pixel space on cpu.",
)
p.add_argument(
"--variant",
default="stablediffusion",
help="We now support multiple vairants of SD finetuned for different dataset. you can use the following anythingv3, ...", # TODO add more once supported
)
p.add_argument(
"--scheduler",
type=str,
default="SharkEulerDiscrete",
help="other supported schedulers are [PNDM, DDIM, LMSDiscrete, EulerDiscrete, DPMSolverMultistep]",
)
p.add_argument(
"--output_img_format",
type=str,
default="png",
help="specify the format in which output image is save. Supported options: jpg / png",
)
p.add_argument(
"--output_dir",
type=str,
default=None,
help="Directory path to save the output images and json",
)
##############################################################################
### IREE - Vulkan supported flags
##############################################################################
p.add_argument(
"--iree-vulkan-target-triple",
type=str,
default="",
help="Specify target triple for vulkan",
)
p.add_argument(
"--vulkan_debug_utils",
default=False,
action=argparse.BooleanOptionalAction,
help="Profiles vulkan device and collects the .rdc info",
)
p.add_argument(
"--vulkan_large_heap_block_size",
default="4147483648",
help="flag for setting VMA preferredLargeHeapBlockSize for vulkan device, default is 4G",
)
p.add_argument(
"--vulkan_validation_layers",
default=False,
action=argparse.BooleanOptionalAction,
help="flag for disabling vulkan validation layers when benchmarking",
)
##############################################################################
### Misc. Debug and Optimization flags
##############################################################################
p.add_argument(
"--use_compiled_scheduler",
default=True,
action=argparse.BooleanOptionalAction,
help="use the default scheduler precompiled into the model if available",
)
p.add_argument(
"--local_tank_cache",
default="",
help="Specify where to save downloaded shark_tank artifacts. If this is not set, the default is ~/.local/shark_tank/.",
)
p.add_argument(
"--dump_isa",
default=False,
action="store_true",
help="When enabled call amdllpc to get ISA dumps. use with dispatch benchmarks.",
)
p.add_argument(
"--dispatch_benchmarks",
default=None,
help='dispatches to return benchamrk data on. use "All" for all, and None for none.',
)
p.add_argument(
"--dispatch_benchmarks_dir",
default="temp_dispatch_benchmarks",
help='directory where you want to store dispatch data generated with "--dispatch_benchmarks"',
)
p.add_argument(
"--enable_rgp",
default=False,
action=argparse.BooleanOptionalAction,
help="flag for inserting debug frames between iterations for use with rgp.",
)
p.add_argument(
"--hide_steps",
default=True,
action=argparse.BooleanOptionalAction,
help="flag for hiding the details of iteration/sec for each step.",
)
p.add_argument(
"--warmup_count",
type=int,
default=0,
help="flag setting warmup count for clip and vae [>= 0].",
)
p.add_argument(
"--clear_all",
default=False,
action=argparse.BooleanOptionalAction,
help="flag to clear all mlir and vmfb from common locations. Recompiling will take several minutes",
)
##############################################################################
### Web UI flags
##############################################################################
p.add_argument(
"--progress_bar",
default=True,
action=argparse.BooleanOptionalAction,
help="flag for removing the pregress bar animation during image generation",
)
p.add_argument(
"--share",
default=False,
action=argparse.BooleanOptionalAction,
help="flag for generating a public URL",
)
p.add_argument(
"--server_port",
type=int,
default=8080,
help="flag for setting server port",
)
##############################################################################
args = p.parse_args()