| layout: |
| in_len: &in_len 4 |
| out_len: &out_len 1 |
| in_step: &in_step 1 |
| out_step: &out_step 1 |
| in_out_diff: &in_out_diff 18 |
|
|
| img_height: &img_height 128 |
| img_width: &img_width 128 |
| data_channels: 1 |
| layout: "NTHWC" |
| dataset: |
| dataset_name: "sevirlr" |
| img_height: *img_height |
| img_width: *img_width |
|
|
| in_len: *in_len |
| out_len: *out_len |
| in_step: *in_step |
| out_step: *out_step |
| in_out_diff: *in_out_diff |
| seq_len: &seq_len 22 |
|
|
| plot_stride: 1 |
| interval_real_time: 10 |
| sample_mode: "sequent" |
| stride: 3 |
| layout: "NTHWC" |
| start_date: null |
| train_test_split_date: [2019, 6, 1] |
| end_date: null |
| val_ratio: 0.1 |
| metrics_mode: "0" |
| metrics_list: ['csi', 'pod', 'sucr', 'bias'] |
| threshold_list: [16, 74, 133, 160, 181, 219] |
| aug_mode: "2" |
| optim: |
| total_batch_size: 128 |
| micro_batch_size: 128 |
| seed: 0 |
| float32_matmul_precision: "high" |
| method: "adamw" |
| lr: 1.0e-3 |
| wd: 1.0e-2 |
| betas: [0.9, 0.999] |
| gradient_clip_val: 1.0 |
| max_epochs: 1000 |
| loss_type: "l2" |
| |
| warmup_percentage: 0.1 |
| lr_scheduler_mode: "cosine" |
| min_lr_ratio: 1.0e-3 |
| warmup_min_lr_ratio: 0.1 |
| plateau_patience: 10 |
| |
| monitor: "val_loss_epoch" |
| early_stop: true |
| early_stop_mode: "min" |
| early_stop_patience: 100 |
| save_top_k: 3 |
| logging: |
| logging_name: "alignment_weird_file_test" |
| run_id: null |
| logging_prefix: "SEVIR-LR_AvgX" |
| monitor_lr: true |
| monitor_device: false |
| track_grad_norm: -1 |
| use_wandb: true |
| profiler: null |
| trainer: |
| check_val_every_n_epoch: 3 |
| log_step_ratio: 0.001 |
| precision: 32 |
| find_unused_parameters: false |
| num_sanity_val_steps: 2 |
| eval: |
| train_example_data_idx_list: [] |
| val_example_data_idx_list: [] |
| test_example_data_idx_list: [] |
| eval_example_only: false |
| num_samples_per_context: 1 |
| save_gif: false |
| gif_fps: 2.0 |
| model: |
| diffusion: |
| timesteps: 1000 |
| beta_schedule: "linear" |
| linear_start: 1e-4 |
| linear_end: 2e-2 |
| cosine_s: 8e-3 |
| given_betas: null |
| |
| cond_stage_model: "__is_first_stage__" |
| num_timesteps_cond: null |
| cond_stage_trainable: false |
| cond_stage_forward: null |
| scale_by_std: false |
| scale_factor: 1.0 |
| align: |
| alignment_type: "avg_x" |
| model_type: "cuboid" |
| model_args: |
| input_shape: [*out_len, 16, 16, 64 ] |
| out_channels: 1 |
| base_units: 128 |
| scale_alpha: 1.0 |
| depth: [ 1, 1 ] |
| downsample: 2 |
| downsample_type: "patch_merge" |
| block_attn_patterns: "axial" |
| num_heads: 4 |
| attn_drop: 0.1 |
| proj_drop: 0.1 |
| ffn_drop: 0.1 |
| ffn_activation: "gelu" |
| gated_ffn: false |
| norm_layer: "layer_norm" |
| use_inter_ffn: true |
| hierarchical_pos_embed: false |
| pos_embed_type: "t+h+w" |
| padding_type: "zeros" |
| checkpoint_level: 0 |
| use_relative_pos: true |
| self_attn_use_final_proj: true |
| |
| num_global_vectors: 0 |
| use_global_vector_ffn: true |
| use_global_self_attn: false |
| separate_global_qkv: false |
| global_dim_ratio: 1 |
| |
| attn_linear_init_mode: "0" |
| ffn_linear_init_mode: "0" |
| ffn2_linear_init_mode: "2" |
| attn_proj_linear_init_mode: "2" |
| conv_init_mode: "0" |
| down_linear_init_mode: "0" |
| global_proj_linear_init_mode: "2" |
| norm_init_mode: "0" |
| |
| time_embed_channels_mult: 4 |
| time_embed_use_scale_shift_norm: false |
| time_embed_dropout: 0.0 |
| |
| pool: "attention" |
| readout_seq: true |
| out_len: *out_len |
| vae: |
| pretrained_ckpt_path: "pretrained_sevirlr_vae_8x8x64_v1_2.pt" |
| data_channels: 1 |
| down_block_types: ['DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D'] |
| in_channels: 1 |
| block_out_channels: [128, 256, 512, 512] |
| act_fn: 'silu' |
| latent_channels: 64 |
| up_block_types: ['UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D'] |
| norm_num_groups: 32 |
| layers_per_block: 2 |
| out_channels: 1 |
|
|
