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Types & classes40 in github.com/alibaba/animate-anything

⨍ Functions 387◇ Types & classes 40
↓ 4 callersClassFFC_BN_ACT
utils/lama.py:190
↓ 4 callersClassLoraInjectedLinear
utils/lora.py:33
↓ 2 callersClassLoraInjectedConv2d
utils/lora.py:77
↓ 2 callersClassLoraInjectedConv3d
utils/lora.py:162
↓ 2 callersClassP2PCrossAttnProcessor
utils/ptp_utils.py:273
↓ 1 callersClassAnimateController
app_svd.py:29
↓ 1 callersClassAnimateController
app.py:33
↓ 1 callersClassConcatTupleLayer
utils/lama.py:248
↓ 1 callersClassConv2d
stable_lora/lora.py:69
↓ 1 callersClassConv3d
stable_lora/lora.py:128
↓ 1 callersClassCrossAttnDownBlock3D
models/unet_3d_blocks.py:389
↓ 1 callersClassCrossAttnUpBlock3D
models/unet_3d_blocks.py:622
↓ 1 callersClassDownBlock3D
models/unet_3d_blocks.py:539
↓ 1 callersClassFFC
utils/lama.py:118
↓ 1 callersClassFFCResnetBlock
utils/lama.py:228
↓ 1 callersClassFourierUnit
utils/lama.py:54
↓ 1 callersClassLargeMaskInpainting
utils/lama.py:258
↓ 1 callersClassLatentTransparencyOffsetEncoder
models/layerdiffuse_VAE.py:17
↓ 1 callersClassLoraHandler
utils/lora_handler.py:69
↓ 1 callersClassScoreParams
utils/seq_aligner.py:18
↓ 1 callersClassUNet384
models/layerdiffuse_VAE.py:44
↓ 1 callersClassUNet3DConditionOutput
Args: sample (`torch.FloatTensor` of shape `(batch_size, num_frames, num_channels, height, width)`): Hidden states conditione
models/unet_3d_condition_mask.py:44
↓ 1 callersClassUNetMidBlock3DCrossAttn
models/unet_3d_blocks.py:234
↓ 1 callersClassUpBlock3D
models/unet_3d_blocks.py:768
ClassAttentionControl
utils/ptp_utils.py:176
ClassAttentionStore
utils/ptp_utils.py:214
ClassCachedDataset
utils/dataset.py:610
ClassConcatLatentToVideoPipeline
models/pipeline_stage2.py:339
ClassImageDataset
utils/dataset.py:358
ClassImageToVideoPipeline
models/pipeline_stage2.py:11
ClassLatentToVideoPipeline
models/pipeline.py:12
ClassMaskStableVideoDiffusionPipeline
models/pipeline.py:223
ClassMaskedLatentToVideoPipeline
models/pipeline_stage2.py:171
ClassSingleVideoDataset
utils/dataset.py:248
ClassSpectralTransform
utils/lama.py:93
ClassTextStableVideoDiffusionPipeline
models/pipeline.py:468
ClassUNet3DConditionModel
r""" UNet3DConditionModel is a conditional 2D UNet model that takes in a noisy sample, conditional state, and a timestep and returns sample sh
models/unet_3d_condition_mask.py:54
ClassVideoBLIPDataset
utils/dataset.py:121
ClassVideoFolderDataset
utils/dataset.py:443
ClassVideoJsonDataset
utils/dataset.py:533