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dataset: |
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dataset_name: "sevirlr" |
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img_height: 128 |
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img_width: 128 |
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in_len: 7 |
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out_len: 6 |
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seq_len: 13 |
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plot_stride: 1 |
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interval_real_time: 10 |
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sample_mode: "sequent" |
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stride: 6 |
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layout: "NTHWC" |
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start_date: null |
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train_test_split_date: [2019, 6, 1] |
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end_date: null |
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val_ratio: 0.1 |
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metrics_mode: "0" |
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metrics_list: ['csi', 'pod', 'sucr', 'bias'] |
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threshold_list: [16, 74, 133, 160, 181, 219] |
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aug_mode: "2" |
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layout: |
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in_len: 7 |
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out_len: 6 |
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in_step: &in_step 1 |
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out_step: &out_step 1 |
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in_out_diff: &in_out_diff 1 |
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img_height: 128 |
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img_width: 128 |
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data_channels: 1 |
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layout: "NTHWC" |
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optim: |
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total_batch_size: 8 |
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micro_batch_size: 2 |
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seed: 0 |
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float32_matmul_precision: "high" |
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method: "adamw" |
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lr: 1.0e-3 |
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wd: 1.0e-5 |
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betas: [0.9, 0.999] |
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gradient_clip_val: 1.0 |
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max_epochs: 2000 |
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loss_type: "l2" |
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warmup_percentage: 0.1 |
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lr_scheduler_mode: "cosine" |
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min_lr_ratio: 1.0e-3 |
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warmup_min_lr_ratio: 0.1 |
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monitor: "val/loss" |
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early_stop: false |
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early_stop_mode: "min" |
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early_stop_patience: 100 |
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save_top_k: 3 |
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logging: |
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logging_prefix: "PreDiff" |
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monitor_lr: true |
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monitor_device: false |
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track_grad_norm: -1 |
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use_wandb: false |
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profiler: null |
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save_npy: true |
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trainer: |
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check_val_every_n_epoch: 50 |
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log_step_ratio: 0.001 |
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precision: 32 |
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find_unused_parameters: false |
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num_sanity_val_steps: 2 |
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eval: |
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train_example_data_idx_list: [0, ] |
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val_example_data_idx_list: [0, 16, 32, 48, 64, 72, 96, 108, 128] |
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test_example_data_idx_list: [0, 16, 32, 48, 64, 72, 96, 108, 128] |
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eval_example_only: true |
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eval_aligned: true |
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eval_unaligned: true |
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num_samples_per_context: 1 |
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fs: 20 |
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label_offset: [-0.5, 0.5] |
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label_avg_int: false |
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fvd_features: 400 |
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model: |
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diffusion: |
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data_shape: [6, 128, 128, 1] |
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beta_schedule: "linear" |
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use_ema: true |
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log_every_t: 100 |
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clip_denoised: false |
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linear_start: 1e-4 |
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linear_end: 2e-2 |
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cosine_s: 8e-3 |
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given_betas: null |
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original_elbo_weight: 0. |
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v_posterior: 0. |
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l_simple_weight: 1. |
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parameterization: "eps" |
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learn_logvar: true |
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logvar_init: 0. |
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latent_shape: [6, 16, 16, 64] |
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cond_stage_model: "__is_first_stage__" |
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num_timesteps_cond: null |
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cond_stage_trainable: false |
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cond_stage_forward: null |
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scale_by_std: false |
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scale_factor: 1.0 |
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latent_cond_shape: [7, 16, 16, 64] |
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align: |
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alignment_type: "avg_x" |
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guide_scale: 50.0 |
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model_type: "cuboid" |
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model_args: |
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input_shape: [6, 16, 16, 64] |
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out_channels: 1 |
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base_units: 128 |
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scale_alpha: 1.0 |
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depth: [1, 1] |
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downsample: 2 |
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downsample_type: "patch_merge" |
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block_attn_patterns: "axial" |
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num_heads: 4 |
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attn_drop: 0.1 |
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proj_drop: 0.1 |
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ffn_drop: 0.1 |
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ffn_activation: "gelu" |
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gated_ffn: false |
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norm_layer: "layer_norm" |
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use_inter_ffn: true |
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hierarchical_pos_embed: false |
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pos_embed_type: "t+h+w" |
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padding_type: "zeros" |
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checkpoint_level: 0 |
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use_relative_pos: true |
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self_attn_use_final_proj: true |
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num_global_vectors: 0 |
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use_global_vector_ffn: true |
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use_global_self_attn: false |
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separate_global_qkv: false |
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global_dim_ratio: 1 |
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attn_linear_init_mode: "0" |
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ffn_linear_init_mode: "0" |
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ffn2_linear_init_mode: "2" |
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attn_proj_linear_init_mode: "2" |
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conv_init_mode: "0" |
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down_linear_init_mode: "0" |
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global_proj_linear_init_mode: "2" |
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norm_init_mode: "0" |
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time_embed_channels_mult: 4 |
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time_embed_use_scale_shift_norm: false |
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time_embed_dropout: 0.0 |
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pool: "attention" |
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readout_seq: true |
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out_len: 6 |
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model_ckpt_path: "pretrained_sevirlr_alignment_avg_x_cuboid_v1.pt" |
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latent_model: |
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input_shape: [7, 16, 16, 64] |
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target_shape: [6, 16, 16, 64] |
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base_units: 256 |
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scale_alpha: 1.0 |
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num_heads: 4 |
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attn_drop: 0.1 |
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proj_drop: 0.1 |
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ffn_drop: 0.1 |
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downsample: 2 |
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downsample_type: "patch_merge" |
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upsample_type: "upsample" |
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upsample_kernel_size: 3 |
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depth: [4, 4] |
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self_pattern: "axial" |
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num_global_vectors: 0 |
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use_dec_self_global: false |
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dec_self_update_global: true |
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use_dec_cross_global: false |
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use_global_vector_ffn: false |
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use_global_self_attn: true |
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separate_global_qkv: true |
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global_dim_ratio: 1 |
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ffn_activation: "gelu" |
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gated_ffn: false |
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norm_layer: "layer_norm" |
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padding_type: "zeros" |
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pos_embed_type: "t+h+w" |
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checkpoint_level: 0 |
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use_relative_pos: true |
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self_attn_use_final_proj: true |
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attn_linear_init_mode: "0" |
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ffn_linear_init_mode: "0" |
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ffn2_linear_init_mode: "2" |
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attn_proj_linear_init_mode: "2" |
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conv_init_mode: "0" |
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down_up_linear_init_mode: "0" |
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global_proj_linear_init_mode: "2" |
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norm_init_mode: "0" |
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time_embed_channels_mult: 4 |
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time_embed_use_scale_shift_norm: false |
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time_embed_dropout: 0.0 |
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unet_res_connect: true |
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vae: |
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pretrained_ckpt_path: "pretrained_sevirlr_vae_8x8x64_v1_2.pt" |
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data_channels: 1 |
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down_block_types: ['DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D'] |
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in_channels: 1 |
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block_out_channels: [128, 256, 512, 512] |
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act_fn: 'silu' |
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latent_channels: 64 |
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up_block_types: ['UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D'] |
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norm_num_groups: 32 |
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layers_per_block: 2 |
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out_channels: 1 |
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