# flow_matching/src/debug_config.yml # Global settings out_dir: output/debug_run seed: 42 overwrite: true device: cpu # Use CPU for local debugging batch_size: 2 # Stage 1: Mean Anchor Generation (MultiSubjectConvLinearEncoder) stage1: epochs: 1 lr: 1e-3 weight_decay: 0.0 model: embed_dim: 16 encoder_kernel_size: 3 decoder_kernel_size: 0 hidden_model: null global_pool: avg encoder_causal: false encoder_positive: false encoder_blockwise: false pool_num_heads: 2 with_shared_decoder: true with_subject_decoders: true transformer: num_heads: 2 depth: 1 mlp_ratio: 2.0 conv1dnext: depth: 1 kernel_size: 3 causal: false # Stage 2: Neural Vector Field (Flow Matching) stage2: epochs: 1 lr: 1e-3 weight_decay: 0.0 n_timesteps: 10 # CFM and training regularization cfm: solver: euler kld_weight: 1.0 kld_target_std: 1.0 detach_ut: false time_dist_shift: 1.0 # DiT-style velocity model velocity_net: hidden_dim: 64 modality_dims: [1000] n_blocks: 2 n_heads: 4 dropout: 0.0 modality_dropout: 0.0 max_seq_len: 128 temporal_attn_layers: 1 # Source variational encoder source_ve: depth: 2 num_heads: 4 num_queries: 8 dropout: 0.0 use_variational: true init_logvar: 0.5 fixed_std: null # CSFM transport + sampler settings transport: path_type: Linear prediction: velocity loss_weight: null time_dist_type: uniform time_dist_shift: 1.0 # Dataset Configuration subjects: [1, 2, 3, 5] # Mock features list matches what the code expects to parse keys from features: mock_feat_1: model: mock_model_1 layers: layer1: layer1 mock_feat_2: model: mock_model_2 layers: layer2: layer2 include_features: - mock_feat_1/layer1 - mock_feat_2/layer2 datasets: train: filter: seasons: [] movies: [] sample_length: 10 num_samples: 4 shuffle: True seed: 42 val_debug: filter: seasons: [] movies: [] sample_length: null num_samples: null shuffle: false val_set_name: val_debug datasets_root: null