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perf(config): change default png_compress_level to 1

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This substantially reduces the time spent encoding PNGs. In workflows with many image outputs, this is a drastic improvement.

For a tiled upscaling workflow going from 512x512 to a scale factor of 4, this can provide over 15% speed increase.
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psychedelicious 2024-02-01 08:35:29 +11:00
parent a1a611f8cb
commit e9558f97c4
1 changed files with 1 additions and 1 deletions
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invokeai/app/services/config/config_default.py
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@ -274,7 +274,7 @@ class InvokeAIAppConfig(InvokeAISettings):
attention_type : Literal["auto", "normal", "xformers", "sliced", "torch-sdp"] = Field(default="auto", description="Attention type", json_schema_extra=Categories.Generation)
attention_slice_size: Literal["auto", "balanced", "max", 1, 2, 3, 4, 5, 6, 7, 8] = Field(default="auto", description='Slice size, valid when attention_type=="sliced"', json_schema_extra=Categories.Generation)
force_tiled_decode : bool = Field(default=False, description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty)", json_schema_extra=Categories.Generation)
png_compress_level : int = Field(default=6, description="The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = fastest, largest filesize, 9 = slowest, smallest filesize", json_schema_extra=Categories.Generation)
png_compress_level : int = Field(default=1, description="The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = fastest, largest filesize, 9 = slowest, smallest filesize", json_schema_extra=Categories.Generation)
# QUEUE
max_queue_size : int = Field(default=10000, gt=0, description="Maximum number of items in the session queue", json_schema_extra=Categories.Queue)