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| globals: | |
| target_fps: 32 | |
| target_nframes: 64 | |
| unet: | |
| _class_name: UNetSpatioTemporalConditionModel | |
| addition_time_embed_dim: 1 | |
| block_out_channels: | |
| - 128 | |
| - 256 | |
| - 256 | |
| - 512 | |
| cross_attention_dim: 1 | |
| down_block_types: | |
| - CrossAttnDownBlockSpatioTemporal | |
| - CrossAttnDownBlockSpatioTemporal | |
| - CrossAttnDownBlockSpatioTemporal | |
| - DownBlockSpatioTemporal | |
| in_channels: 8 | |
| layers_per_block: 2 | |
| num_attention_heads: | |
| - 8 | |
| - 16 | |
| - 16 | |
| - 32 | |
| num_frames: ${globals.target_nframes} | |
| out_channels: 4 | |
| projection_class_embeddings_input_dim: 1 | |
| sample_size: 14 | |
| transformer_layers_per_block: 1 | |
| up_block_types: | |
| - UpBlockSpatioTemporal | |
| - CrossAttnUpBlockSpatioTemporal | |
| - CrossAttnUpBlockSpatioTemporal | |
| - CrossAttnUpBlockSpatioTemporal | |
| noise_scheduler: | |
| _class_name: DDPMScheduler | |
| num_train_timesteps: 1000 | |
| beta_start: 0.0001 | |
| beta_end: 0.02 | |
| beta_schedule: linear # linear, scaled_linear, or squaredcos_cap_v2 | |
| variance_type: fixed_small # fixed_small, fixed_small_log, fixed_large, fixed_large_log, learned or learned_range | |
| clip_sample: true | |
| clip_sample_range: 4.0 # default 1 | |
| prediction_type: v_prediction # epsilon, sample, v_prediction | |
| thresholding: false # do not touch | |
| dynamic_thresholding_ratio: 0.995 # unused | |
| sample_max_value: 1.0 # unused | |
| timestep_spacing: "leading" # | |
| steps_offset: 0 # unused |