model: target: vtdm.vtdm_gen_v01.VideoLDM base_learning_rate: 1.0e-05 params: input_key: video scale_factor: 0.18215 log_keys: caption num_samples: 25 #frame_rate trained_param_keys: - diffusion_model.label_emb.0.0.weight - .emb_layers. - .time_stack. en_and_decode_n_samples_a_time: 25 #frame_rate disable_first_stage_autocast: true denoiser_config: target: sgm.modules.diffusionmodules.denoiser.Denoiser params: scaling_config: target: sgm.modules.diffusionmodules.denoiser_scaling.VScalingWithEDMcNoise network_config: target: sgm.modules.diffusionmodules.video_model.VideoUNet params: adm_in_channels: 768 num_classes: sequential use_checkpoint: true in_channels: 8 out_channels: 4 model_channels: 320 attention_resolutions: - 4 - 2 - 1 num_res_blocks: 2 channel_mult: - 1 - 2 - 4 - 4 num_head_channels: 64 use_linear_in_transformer: true transformer_depth: 1 context_dim: 1024 spatial_transformer_attn_type: softmax-xformers extra_ff_mix_layer: true use_spatial_context: true merge_strategy: learned_with_images video_kernel_size: - 3 - 1 - 1 conditioner_config: target: sgm.modules.GeneralConditioner params: emb_models: - is_trainable: false input_key: cond_frames_without_noise ucg_rate: 0.1 target: sgm.modules.encoders.modules.FrozenOpenCLIPImagePredictionEmbedder params: n_cond_frames: 1 n_copies: 1 open_clip_embedding_config: target: sgm.modules.encoders.modules.FrozenOpenCLIPImageEmbedder params: version: ckpts/open_clip_pytorch_model.bin freeze: true - is_trainable: false input_key: video ucg_rate: 0.0 target: vtdm.encoders.AesEmbedder - is_trainable: false input_key: elevation target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND params: outdim: 256 - input_key: cond_frames is_trainable: false ucg_rate: 0.1 target: sgm.modules.encoders.modules.VideoPredictionEmbedderWithEncoder params: disable_encoder_autocast: true n_cond_frames: 1 n_copies: 25 #frame_rate is_ae: true encoder_config: target: sgm.models.autoencoder.AutoencoderKLModeOnly params: embed_dim: 4 monitor: val/rec_loss ddconfig: 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 num_res_blocks: 2 attn_resolutions: [] dropout: 0.0 lossconfig: target: torch.nn.Identity - input_key: cond_aug is_trainable: false target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND params: outdim: 256 first_stage_config: target: sgm.models.autoencoder.AutoencoderKL params: embed_dim: 4 monitor: val/rec_loss ddconfig: 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 num_res_blocks: 2 attn_resolutions: [] dropout: 0.0 lossconfig: target: torch.nn.Identity loss_fn_config: target: sgm.modules.diffusionmodules.loss.StandardDiffusionLoss params: num_frames: 25 #frame_rate batch2model_keys: - num_video_frames - image_only_indicator sigma_sampler_config: target: sgm.modules.diffusionmodules.sigma_sampling.EDMSampling params: p_mean: 1.0 p_std: 1.6 loss_weighting_config: target: sgm.modules.diffusionmodules.loss_weighting.VWeighting sampler_config: target: sgm.modules.diffusionmodules.sampling.LinearMultistepSampler params: num_steps: 50 verbose: True discretization_config: target: sgm.modules.diffusionmodules.discretizer.EDMDiscretization params: sigma_max: 700.0 guider_config: target: sgm.modules.diffusionmodules.guiders.LinearPredictionGuider params: num_frames: 25 #frame_rate max_scale: 2.5 min_scale: 1.0