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This logic was checking comfy_cast_weights, and going straight to to the forward_comfy_cast_weights implementation without attempting to downscale input to fp8 in the event comfy_cast_weights is set. The main reason comfy_cast_weights would be set would be for async offload, which is not a good reason to nix FP8MM. So instead, and together the underlying exclusions for FP8MM which are: * having a weight_function (usually LowVramPatch) * force_cast_weights (compute dtype override) * the weight is not Quantized * the input is already quantized * the model or layer has MM explictily disabled. If you get past all of those exclusions, quantize the input tensor. Then hand the new input, quantized or not off to forward_comfy_cast_weights to handle it. If the weight is offloaded but input is quantized you will get an offloaded MM8.
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