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Merge branch 'comfyanonymous:master' into master
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commit
9a0f99ba71
@ -151,8 +151,8 @@ class Flux(nn.Module):
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h_len = ((h + (patch_size // 2)) // patch_size)
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w_len = ((w + (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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img_ids[..., 1] = img_ids[..., 1] + torch.linspace(0, h_len - 1, steps=h_len, device=x.device, dtype=x.dtype)[:, None]
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img_ids[..., 2] = img_ids[..., 2] + torch.linspace(0, w_len - 1, steps=w_len, device=x.device, dtype=x.dtype)[None, :]
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img_ids[:, :, 1] = torch.linspace(0, h_len - 1, steps=h_len, device=x.device, dtype=x.dtype).unsqueeze(1)
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img_ids[:, :, 2] = torch.linspace(0, w_len - 1, steps=w_len, device=x.device, dtype=x.dtype).unsqueeze(0)
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img_ids = repeat(img_ids, "h w c -> b (h w) c", b=bs)
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txt_ids = torch.zeros((bs, context.shape[1], 3), device=x.device, dtype=x.dtype)
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@ -88,8 +88,12 @@ class LowVramPatch:
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self.key = key
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self.patches = patches
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def __call__(self, weight):
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return comfy.lora.calculate_weight(self.patches[self.key], weight, self.key, intermediate_dtype=weight.dtype)
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intermediate_dtype = weight.dtype
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if intermediate_dtype not in [torch.float32, torch.float16, torch.bfloat16]: #intermediate_dtype has to be one that is supported in math ops
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intermediate_dtype = torch.float32
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return comfy.float.stochastic_rounding(comfy.lora.calculate_weight(self.patches[self.key], weight.to(intermediate_dtype), self.key, intermediate_dtype=intermediate_dtype), weight.dtype, seed=string_to_seed(self.key))
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return comfy.lora.calculate_weight(self.patches[self.key], weight, self.key, intermediate_dtype=intermediate_dtype)
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class ModelPatcher:
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def __init__(self, model, load_device, offload_device, size=0, weight_inplace_update=False):
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self.size = size
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