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https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2025-12-09 05:54:24 +08:00
Make ScaleROPE node work on Flux. (#10686)
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@ -210,7 +210,7 @@ class Flux(nn.Module):
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img = self.final_layer(img, vec) # (N, T, patch_size ** 2 * out_channels)
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return img
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def process_img(self, x, index=0, h_offset=0, w_offset=0):
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def process_img(self, x, index=0, h_offset=0, w_offset=0, transformer_options={}):
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bs, c, h, w = x.shape
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patch_size = self.patch_size
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x = comfy.ldm.common_dit.pad_to_patch_size(x, (patch_size, patch_size))
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@ -222,10 +222,22 @@ class Flux(nn.Module):
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h_offset = ((h_offset + (patch_size // 2)) // patch_size)
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w_offset = ((w_offset + (patch_size // 2)) // patch_size)
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img_ids = torch.zeros((h_len, w_len, 3), device=x.device, dtype=x.dtype)
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steps_h = h_len
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steps_w = w_len
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rope_options = transformer_options.get("rope_options", None)
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if rope_options is not None:
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h_len = (h_len - 1.0) * rope_options.get("scale_y", 1.0) + 1.0
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w_len = (w_len - 1.0) * rope_options.get("scale_x", 1.0) + 1.0
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index += rope_options.get("shift_t", 0.0)
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h_offset += rope_options.get("shift_y", 0.0)
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w_offset += rope_options.get("shift_x", 0.0)
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img_ids = torch.zeros((steps_h, steps_w, 3), device=x.device, dtype=x.dtype)
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img_ids[:, :, 0] = img_ids[:, :, 1] + index
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img_ids[:, :, 1] = img_ids[:, :, 1] + torch.linspace(h_offset, h_len - 1 + h_offset, steps=h_len, device=x.device, dtype=x.dtype).unsqueeze(1)
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img_ids[:, :, 2] = img_ids[:, :, 2] + torch.linspace(w_offset, w_len - 1 + w_offset, steps=w_len, device=x.device, dtype=x.dtype).unsqueeze(0)
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img_ids[:, :, 1] = img_ids[:, :, 1] + torch.linspace(h_offset, h_len - 1 + h_offset, steps=steps_h, device=x.device, dtype=x.dtype).unsqueeze(1)
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img_ids[:, :, 2] = img_ids[:, :, 2] + torch.linspace(w_offset, w_len - 1 + w_offset, steps=steps_w, device=x.device, dtype=x.dtype).unsqueeze(0)
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return img, repeat(img_ids, "h w c -> b (h w) c", b=bs)
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def forward(self, x, timestep, context, y=None, guidance=None, ref_latents=None, control=None, transformer_options={}, **kwargs):
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@ -241,7 +253,7 @@ class Flux(nn.Module):
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h_len = ((h_orig + (patch_size // 2)) // patch_size)
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w_len = ((w_orig + (patch_size // 2)) // patch_size)
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img, img_ids = self.process_img(x)
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img, img_ids = self.process_img(x, transformer_options=transformer_options)
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img_tokens = img.shape[1]
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if ref_latents is not None:
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h = 0
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