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model: |
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target: sgm.models.diffusion.DiffusionEngine |
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params: |
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scale_factor: 0.18215 |
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disable_first_stage_autocast: True |
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ckpt_path: checkpoints/svd.safetensors |
|
|
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denoiser_config: |
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target: sgm.modules.diffusionmodules.denoiser.Denoiser |
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params: |
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scaling_config: |
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target: sgm.modules.diffusionmodules.denoiser_scaling.VScalingWithEDMcNoise |
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|
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network_config: |
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target: sgm.modules.diffusionmodules.video_model.VideoUNet |
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params: |
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adm_in_channels: 768 |
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num_classes: sequential |
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use_checkpoint: True |
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in_channels: 8 |
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out_channels: 4 |
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model_channels: 320 |
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attention_resolutions: [4, 2, 1] |
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num_res_blocks: 2 |
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channel_mult: [1, 2, 4, 4] |
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num_head_channels: 64 |
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use_linear_in_transformer: True |
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transformer_depth: 1 |
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context_dim: 1024 |
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spatial_transformer_attn_type: softmax-xformers |
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extra_ff_mix_layer: True |
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use_spatial_context: True |
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merge_strategy: learned_with_images |
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video_kernel_size: [3, 1, 1] |
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|
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conditioner_config: |
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target: sgm.modules.GeneralConditioner |
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params: |
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emb_models: |
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- is_trainable: False |
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input_key: cond_frames_without_noise |
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target: sgm.modules.encoders.modules.FrozenOpenCLIPImagePredictionEmbedder |
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params: |
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n_cond_frames: 1 |
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n_copies: 1 |
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open_clip_embedding_config: |
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target: sgm.modules.encoders.modules.FrozenOpenCLIPImageEmbedder |
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params: |
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freeze: True |
|
|
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- input_key: fps_id |
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is_trainable: False |
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target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND |
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params: |
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outdim: 256 |
|
|
|
- input_key: motion_bucket_id |
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is_trainable: False |
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target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND |
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params: |
|
outdim: 256 |
|
|
|
- input_key: cond_frames |
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is_trainable: False |
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target: sgm.modules.encoders.modules.VideoPredictionEmbedderWithEncoder |
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params: |
|
disable_encoder_autocast: True |
|
n_cond_frames: 1 |
|
n_copies: 1 |
|
is_ae: True |
|
encoder_config: |
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target: sgm.models.autoencoder.AutoencoderKLModeOnly |
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params: |
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embed_dim: 4 |
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monitor: val/rec_loss |
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ddconfig: |
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attn_type: vanilla-xformers |
|
double_z: True |
|
z_channels: 4 |
|
resolution: 256 |
|
in_channels: 3 |
|
out_ch: 3 |
|
ch: 128 |
|
ch_mult: [1, 2, 4, 4] |
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num_res_blocks: 2 |
|
attn_resolutions: [] |
|
dropout: 0.0 |
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lossconfig: |
|
target: torch.nn.Identity |
|
|
|
- input_key: cond_aug |
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is_trainable: False |
|
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND |
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params: |
|
outdim: 256 |
|
|
|
first_stage_config: |
|
target: sgm.models.autoencoder.AutoencodingEngine |
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params: |
|
loss_config: |
|
target: torch.nn.Identity |
|
regularizer_config: |
|
target: sgm.modules.autoencoding.regularizers.DiagonalGaussianRegularizer |
|
encoder_config: |
|
target: sgm.modules.diffusionmodules.model.Encoder |
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params: |
|
attn_type: vanilla |
|
double_z: True |
|
z_channels: 4 |
|
resolution: 256 |
|
in_channels: 3 |
|
out_ch: 3 |
|
ch: 128 |
|
ch_mult: [1, 2, 4, 4] |
|
num_res_blocks: 2 |
|
attn_resolutions: [] |
|
dropout: 0.0 |
|
decoder_config: |
|
target: sgm.modules.autoencoding.temporal_ae.VideoDecoder |
|
params: |
|
attn_type: vanilla |
|
double_z: True |
|
z_channels: 4 |
|
resolution: 256 |
|
in_channels: 3 |
|
out_ch: 3 |
|
ch: 128 |
|
ch_mult: [1, 2, 4, 4] |
|
num_res_blocks: 2 |
|
attn_resolutions: [] |
|
dropout: 0.0 |
|
video_kernel_size: [3, 1, 1] |
|
|
|
sampler_config: |
|
target: sgm.modules.diffusionmodules.sampling.EulerEDMSampler |
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params: |
|
discretization_config: |
|
target: sgm.modules.diffusionmodules.discretizer.EDMDiscretization |
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params: |
|
sigma_max: 700.0 |
|
|
|
guider_config: |
|
target: sgm.modules.diffusionmodules.guiders.LinearPredictionGuider |
|
params: |
|
max_scale: 2.5 |
|
min_scale: 1.0 |