data: name: trajectory_nba_filling full_seq_len: 30 delta_len: 30 num_agents: 11 coord_dim: 2 court_width: 94.0 court_height: 50.0 params: train_batch_size: 128 val_batch_size: 512 full_seq_len: 30 num_agents: 11 coord_dim: 2 court_width: 94.0 court_height: 50.0 train_path: data/nba_train.npy val_path: data/nba_test.npy trajectory_key: trajectory context_key: context mask_key: obs_mask position_0_key: position_0 context_fill: - -4.0 - -4.0 include_delta_in_context: true delta_context_fill: - 0.0 - 0.0 delta_shift: - 0.0 - 0.0 delta_scale: - 1.0 - 1.0 masking: train: mixture: - weight: 0.35 even: mode: random prefix_min: 1 prefix_max: 20 - weight: 0.35 agent: mode: random n_masked_min: 5 n_masked_max: 11 - weight: 0.3 hybrid: combine: union a: even: mode: random prefix_min: 1 prefix_max: 20 b: agent: mode: random n_masked_min: 5 n_masked_max: 11 val_mask_path: /root/code/gameplay-trajectory-diffusion/data/nba_test_mask_v1.npy num_workers: 0 max_val_samples: 5120 model: name: trajectory_filling_ddpm trajectory_key: trajectory context_key: context mask_key: obs_mask position_0_key: position_0 guidance_scale: 2.0 p_uncond: 0.1 log_blend_trajectory_video: false timesteps: 1000 beta_schedule: linear linear_start: 0.0001 linear_end: 0.02 cosine_s: 0.008 parameterization: eps loss_type: l2 diffusion_loss_type: rescaled_mse log_diagnostic_vb: true vb_decoder_nll: continuous model_var_type: learned clip_denoised: false legacy_posterior_log_variance: false backbone: _target_: src.modules.backbones.dit_backbone.DITBackbone max_seq_len: 30 num_agents: 11 coord_dim: 2 context_channels: 2 context_dim: 256 n_temporal_layer: 4 d_model_temporal: 256 nhead_temporal: 8 d_ff_temporal: 512 n_spatial_layer: 4 d_model_spatial: 256 nhead_spatial: 8 d_ff_spatial: 512 num_timesteps: 1000 patch_size: 5 learn_sigma: true seed: 42 hardware: use_gpu: true gpu_devices: 1 wandb: enabled: true project: trajectory-filling-ddpm entity: null name: dit-learnsigma-mixedmask-lr=1e-4 save_dir: ./wandb log_model: false logging: backend: null tensorboard: save_dir: ./tensorboard_logs name: null trainer: lightning: max_epochs: 1500 accelerator: auto devices: 1 precision: 32 log_every_n_steps: 50 check_val_every_n_epoch: 20 val_check_interval: null limit_val_batches: null deterministic: false fast_dev_run: false val_logging: enabled: true num_samples: 6 log_every_n_val_epochs: 1 optim: learning_rate: 0.0001 betas: - 0.9 - 0.999 weight_decay: 0.0 ema: enabled: true decay: 0.9999 use_num_updates: true checkpoint: monitor: val/jade_min_30frames mode: min save_top_k: 4 val_trajectory_metrics: enabled: true max_samples: 512 every_n_val_epochs: 1 num_paths: 20 horizon_stride: 30 metrics_start_t: 0 prediction_mode: pure guidance_scale_override: 2.0 verbose: false sampling: method: dpm dpm: steps: 40 order: 3 skip_type: time_uniform algorithm_type: dpmsolver++ solver_method: singlestep lower_order_final: true denoise_to_zero: false sampling: method: ancestral