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12b90ee736
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@ -456,9 +456,8 @@ class LTXVModel(torch.nn.Module):
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x = self.patchify_proj(x)
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timestep = timestep * 1000.0
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attention_mask = 1.0 - attention_mask.to(x.dtype).reshape((attention_mask.shape[0], 1, -1, attention_mask.shape[-1]))
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attention_mask = attention_mask.masked_fill(attention_mask.to(torch.bool), float("-inf")) # not sure about this
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# attention_mask = (context != 0).any(dim=2).to(dtype=x.dtype)
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if attention_mask is not None and not torch.is_floating_point(attention_mask):
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attention_mask = (attention_mask - 1).to(x.dtype).reshape((attention_mask.shape[0], 1, -1, attention_mask.shape[-1])) * torch.finfo(x.dtype).max
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pe = precompute_freqs_cis(indices_grid, dim=self.inner_dim, out_dtype=x.dtype)
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2
nodes.py
2
nodes.py
@ -1578,7 +1578,7 @@ class SaveImage:
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return {
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"required": {
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"images": ("IMAGE", {"tooltip": "The images to save."}),
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"filename_prefix": ("STRING", {"default": "ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
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"filename_prefix": ("STRING", {"default": "%date:yyyy-MM-dd%/%date:hhmmss%", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
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},
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"hidden": {
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"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"
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