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33 lines
995 B
Python
33 lines
995 B
Python
from dataclasses import dataclass
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import torch
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from invokeai.backend.stable_diffusion.diffusion.conditioning_data import Range
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@dataclass
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class FluxTextConditioning:
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t5_embeddings: torch.Tensor
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clip_embeddings: torch.Tensor
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mask: torch.Tensor
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@dataclass
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class FluxRegionalTextConditioning:
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# Concatenated text embeddings.
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t5_embeddings: torch.Tensor
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clip_embeddings: torch.Tensor
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t5_txt_ids: torch.Tensor
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# A binary mask indicating the regions of the image that the prompt should be applied to.
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# Shape: (1, num_prompts, height, width)
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# Dtype: torch.bool
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image_masks: torch.Tensor
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# List of ranges that represent the embedding ranges for each mask.
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# t5_embedding_ranges[i] contains the range of the t5 embeddings that correspond to image_masks[i].
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# clip_embedding_ranges[i] contains the range of the clip embeddings that correspond to image_masks[i].
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t5_embedding_ranges: list[Range]
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clip_embedding_ranges: list[Range]
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