2023-11-16 18:23:25 +00:00
|
|
|
import torch
|
|
|
|
|
|
|
|
class PatchModelAddDownscale:
|
|
|
|
@classmethod
|
|
|
|
def INPUT_TYPES(s):
|
|
|
|
return {"required": { "model": ("MODEL",),
|
|
|
|
"block_number": ("INT", {"default": 3, "min": 1, "max": 32, "step": 1}),
|
|
|
|
"downscale_factor": ("FLOAT", {"default": 2.0, "min": 0.1, "max": 9.0, "step": 0.001}),
|
|
|
|
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
|
|
|
|
"end_percent": ("FLOAT", {"default": 0.35, "min": 0.0, "max": 1.0, "step": 0.001}),
|
2023-11-16 20:26:28 +00:00
|
|
|
"downscale_after_skip": ("BOOLEAN", {"default": True}),
|
2023-11-16 18:23:25 +00:00
|
|
|
}}
|
|
|
|
RETURN_TYPES = ("MODEL",)
|
|
|
|
FUNCTION = "patch"
|
|
|
|
|
|
|
|
CATEGORY = "_for_testing"
|
|
|
|
|
2023-11-16 20:26:28 +00:00
|
|
|
def patch(self, model, block_number, downscale_factor, start_percent, end_percent, downscale_after_skip):
|
2023-11-19 04:20:29 +00:00
|
|
|
sigma_start = model.model.model_sampling.percent_to_sigma(start_percent)
|
|
|
|
sigma_end = model.model.model_sampling.percent_to_sigma(end_percent)
|
2023-11-16 18:23:25 +00:00
|
|
|
|
|
|
|
def input_block_patch(h, transformer_options):
|
|
|
|
if transformer_options["block"][1] == block_number:
|
|
|
|
sigma = transformer_options["sigmas"][0].item()
|
|
|
|
if sigma <= sigma_start and sigma >= sigma_end:
|
|
|
|
h = torch.nn.functional.interpolate(h, scale_factor=(1.0 / downscale_factor), mode="bicubic", align_corners=False)
|
|
|
|
return h
|
|
|
|
|
|
|
|
def output_block_patch(h, hsp, transformer_options):
|
|
|
|
if h.shape[2] != hsp.shape[2]:
|
|
|
|
h = torch.nn.functional.interpolate(h, size=(hsp.shape[2], hsp.shape[3]), mode="bicubic", align_corners=False)
|
|
|
|
return h, hsp
|
|
|
|
|
|
|
|
m = model.clone()
|
2023-11-16 20:26:28 +00:00
|
|
|
if downscale_after_skip:
|
|
|
|
m.set_model_input_block_patch_after_skip(input_block_patch)
|
|
|
|
else:
|
|
|
|
m.set_model_input_block_patch(input_block_patch)
|
2023-11-16 18:23:25 +00:00
|
|
|
m.set_model_output_block_patch(output_block_patch)
|
|
|
|
return (m, )
|
|
|
|
|
|
|
|
NODE_CLASS_MAPPINGS = {
|
|
|
|
"PatchModelAddDownscale": PatchModelAddDownscale,
|
|
|
|
}
|
|
|
|
|
|
|
|
NODE_DISPLAY_NAME_MAPPINGS = {
|
|
|
|
# Sampling
|
|
|
|
"PatchModelAddDownscale": "PatchModelAddDownscale (Kohya Deep Shrink)",
|
|
|
|
}
|