mirror of
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69 lines
1.5 KiB
Python
69 lines
1.5 KiB
Python
import argparse
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p = argparse.ArgumentParser(
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description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter
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)
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p.add_argument(
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"--prompt",
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type=str,
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default="a photograph of an astronaut riding a horse",
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help="the text to generate image of.",
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)
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p.add_argument(
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"--device", type=str, default="cpu", help="device to run the model."
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)
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p.add_argument(
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"--steps",
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type=int,
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default=10,
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help="the no. of steps to do the sampling.",
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)
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p.add_argument(
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"--seed",
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type=int,
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default=42,
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help="the seed to use.",
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)
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p.add_argument(
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"--guidance_scale",
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type=float,
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default=7.5,
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help="the value to be used for guidance scaling.",
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)
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p.add_argument(
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"--import_mlir",
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default=False,
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action=argparse.BooleanOptionalAction,
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help="imports the model from torch module to shark_module otherwise downloads the model from shark_tank.",
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)
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p.add_argument(
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"--precision", type=str, default="fp32", help="precision to run the model."
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)
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p.add_argument(
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"--max_length",
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type=int,
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default=77,
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help="max length of the tokenizer output.",
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)
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p.add_argument(
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"--load_vmfb",
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default=True,
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action=argparse.BooleanOptionalAction,
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help="attempts to load the model from a precompiled flatbuffer and compiles + saves it if not found.",
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)
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p.add_argument(
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"--save_vmfb",
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default=False,
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action=argparse.BooleanOptionalAction,
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help="saves the compiled flatbuffer to the local directory",
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)
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args = p.parse_args()
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