diff options
Diffstat (limited to 'config.py')
| -rw-r--r-- | config.py | 38 |
1 files changed, 4 insertions, 34 deletions
@@ -7,9 +7,9 @@ config: Configuration = { # GPU(s) used in training or testing if available 'CUDA_VISIBLE_DEVICES': '0', # Directory used in training or testing for temporary storage - 'save_dir': 'runs', + 'save_dir': 'runs/dis_only', # Recorde disentangled image or not - 'image_log_on': False + 'image_log_on': True }, # Dataset settings 'dataset': { @@ -37,7 +37,7 @@ config: Configuration = { # Batch size (pr, k) # `pr` denotes number of persons # `k` denotes number of sequences per person - 'batch_size': (4, 8), + 'batch_size': (2, 2), # Number of workers of Dataloader 'num_workers': 4, # Faster data transfer from RAM to GPU if enabled @@ -49,35 +49,10 @@ config: Configuration = { # Auto-encoder feature channels coefficient 'ae_feature_channels': 64, # Appearance, canonical and pose feature dimensions - 'f_a_c_p_dims': (128, 128, 64), - # Use 1x1 convolution in dimensionality reduction - 'hpm_use_1x1conv': False, - # HPM pyramid scales, of which sum is number of parts - 'hpm_scales': (1, 2, 4), - # Global pooling method - 'hpm_use_avg_pool': True, - 'hpm_use_max_pool': False, - # FConv feature channels coefficient - 'fpfe_feature_channels': 32, - # FConv blocks kernel sizes - 'fpfe_kernel_sizes': ((5, 3), (3, 3), (3, 3)), - # FConv blocks paddings - 'fpfe_paddings': ((2, 1), (1, 1), (1, 1)), - # FConv blocks halving - 'fpfe_halving': (0, 2, 3), - # Attention squeeze ratio - 'tfa_squeeze_ratio': 4, - # Number of parts after Part Net - 'tfa_num_parts': 16, - # Embedding dimension for each part - 'embedding_dims': 256, - # Triplet loss margins for HPM and PartNet - 'triplet_margins': (0.2, 0.2), + 'f_a_c_p_dims': (192, 192, 96), }, 'optimizer': { # Global parameters - # Iteration start to optimize non-disentangling parts - # 'start_iter': 0, # Initial learning rate of Adam Optimizer 'lr': 1e-4, # Coefficients used for computing running averages of @@ -89,11 +64,6 @@ config: Configuration = { # 'weight_decay': 0, # Use AMSGrad or not # 'amsgrad': False, - - # Local parameters (override global ones) - 'auto_encoder': { - 'weight_decay': 0.001 - }, }, 'scheduler': { # Period of learning rate decay |