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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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@ -36,9 +36,14 @@ a111:
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# models/diffusion_models
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# models/unet
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# embeddings: models/embeddings/
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# gligen: models/gligen/
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# hypernetworks: models/hypernetworks/
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# loras: models/loras/
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# photomaker: models/photomaker/
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# style_models: models/style_models/
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# upscale_models: models/upscale_models/
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# vae: models/vae/
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# vae_approx: models/vae_approx/
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#other_ui:
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# base_path: path/to/ui
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