15 lines
1.3 KiB
Python
15 lines
1.3 KiB
Python
from vidxtend.models.attention_processor import Attention
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from vidxtend.models.attention import BasicTransformerBlock, FeedForward, GEGLU
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from vidxtend.models.conditioning import CrossAttention, ConditionalModel
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from vidxtend.models.controlnet import ControlNetModel, ControlNetOutput
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from vidxtend.models.conv_channels import Conv2DSubChannels, Conv2DExtendedChannels
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from vidxtend.models.image_embedder import FrozenOpenCLIPImageEmbedder, ImageEmbeddingContextResampler
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from vidxtend.models.mask_generator import MaskGenerator
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from vidxtend.models.noise_generator import NoiseGenerator
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from vidxtend.models.processor import set_use_memory_efficient_attention_xformers, XFormersAttnProcessor
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from vidxtend.models.transformer_2d import Transformer2DModelOutput, Transformer2DModel
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from vidxtend.models.transformer_temporal import TransformerTemporalModelOutput, TransformerTemporalModel
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from vidxtend.models.transformer_temporal_cross_attention import TransformerTemporalCrossAttentionModelOutput, TransformerTemporalCrossAttentionModel
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from vidxtend.models.unet_3d_blocks import get_down_block, get_up_block, UpBlock3D, CrossAttnUpBlock3D, UNetMidBlock3DCrossAttn, CrossAttnDownBlock3D, DownBlock3D
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from vidxtend.models.unet_3d_condition import UNet3DConditionModel, UNet3DConditionOutput
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