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Better chroma radiance vram estimation.
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fdebe18296
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@ -965,7 +965,7 @@ class CosmosT2IPredict2(supported_models_base.BASE):
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def __init__(self, unet_config):
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def __init__(self, unet_config):
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super().__init__(unet_config)
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super().__init__(unet_config)
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self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.9
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self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.95
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def get_model(self, state_dict, prefix="", device=None):
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def get_model(self, state_dict, prefix="", device=None):
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out = model_base.CosmosPredict2(self, device=device)
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out = model_base.CosmosPredict2(self, device=device)
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@ -1289,7 +1289,7 @@ class ChromaRadiance(Chroma):
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latent_format = comfy.latent_formats.ChromaRadiance
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latent_format = comfy.latent_formats.ChromaRadiance
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# Pixel-space model, no spatial compression for model input.
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# Pixel-space model, no spatial compression for model input.
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memory_usage_factor = 0.038
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memory_usage_factor = 0.044
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def get_model(self, state_dict, prefix="", device=None):
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def get_model(self, state_dict, prefix="", device=None):
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return model_base.ChromaRadiance(self, device=device)
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return model_base.ChromaRadiance(self, device=device)
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