mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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f166868df6
maybe... some invalid interrupt method? move to paper implementation fix descriptions, KeyError handle sgm for XL fix ruff, change default for out_block Implement Deepcache Optimization
64 lines
2.9 KiB
Python
64 lines
2.9 KiB
Python
from modules import scripts
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from modules.shared import opts
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xyz_grid = [x for x in scripts.scripts_data if x.script_class.__module__ == "xyz_grid.py"][0].module
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def int_applier(value_name:str, min_range:int = -1, max_range:int = -1):
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"""
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Returns a function that applies the given value to the given value_name in opts.data.
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"""
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def validate(value_name:str, value:str):
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value = int(value)
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# validate value
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if not min_range == -1:
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assert value >= min_range, f"Value {value} for {value_name} must be greater than or equal to {min_range}"
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if not max_range == -1:
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assert value <= max_range, f"Value {value} for {value_name} must be less than or equal to {max_range}"
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def apply_int(p, x, xs):
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validate(value_name, x)
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opts.data[value_name] = int(x)
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return apply_int
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def bool_applier(value_name:str):
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"""
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Returns a function that applies the given value to the given value_name in opts.data.
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"""
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def validate(value_name:str, value:str):
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assert value.lower() in ["true", "false"], f"Value {value} for {value_name} must be either true or false"
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def apply_bool(p, x, xs):
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validate(value_name, x)
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value_boolean = x.lower() == "true"
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opts.data[value_name] = value_boolean
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return apply_bool
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def float_applier(value_name:str, min_range:float = -1, max_range:float = -1):
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"""
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Returns a function that applies the given value to the given value_name in opts.data.
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"""
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def validate(value_name:str, value:str):
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value = float(value)
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# validate value
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if not min_range == -1:
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assert value >= min_range, f"Value {value} for {value_name} must be greater than or equal to {min_range}"
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if not max_range == -1:
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assert value <= max_range, f"Value {value} for {value_name} must be less than or equal to {max_range}"
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def apply_float(p, x, xs):
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validate(value_name, x)
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opts.data[value_name] = float(x)
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return apply_float
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def add_axis_options():
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extra_axis_options = [
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xyz_grid.AxisOption("[DeepCache] Enabled", str, bool_applier("deepcache_enable"), choices=xyz_grid.boolean_choice(reverse=True)),
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xyz_grid.AxisOption("[DeepCache] Cache Resnet level", int, int_applier("deepcache_cache_resnet_level", 0, 10)),
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xyz_grid.AxisOption("[DeepCache] Cache Disable initial step percentage", float, float_applier("deepcache_cache_enable_step_percentage", 0, 1)),
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xyz_grid.AxisOption("[DeepCache] Cache Refresh Rate", int, int_applier("deepcache_full_run_step_rate", 0, 1000)),
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xyz_grid.AxisOption("[DeepCache] HR Reuse", str, bool_applier("deepcache_hr_reuse"), choices=xyz_grid.boolean_choice(reverse=True)),
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]
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set_a = {opt.label for opt in xyz_grid.axis_options}
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set_b = {opt.label for opt in extra_axis_options}
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if set_a.intersection(set_b):
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return
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xyz_grid.axis_options.extend(extra_axis_options)
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