diff options
Diffstat (limited to 'config.py')
| -rw-r--r-- | config.py | 34 |
1 files changed, 18 insertions, 16 deletions
@@ -5,7 +5,7 @@ config: Configuration = { # Disable accelerator 'disable_acc': False, # GPU(s) used in training or testing if available - 'CUDA_VISIBLE_DEVICES': '0', + 'CUDA_VISIBLE_DEVICES': '0,1', # Directory used in training or testing for temporary storage 'save_dir': 'runs', # Recorde disentangled image or not @@ -30,14 +30,14 @@ config: Configuration = { # Resolution after resize, can be divided 16 'frame_size': (64, 48), # Cache dataset or not - 'cache_on': False, + 'cache_on': True, }, # Dataloader settings 'dataloader': { # Batch size (pr, k) # `pr` denotes number of persons # `k` denotes number of sequences per person - 'batch_size': (4, 6), + 'batch_size': (6, 8), # Number of workers of Dataloader 'num_workers': 4, # Faster data transfer from RAM to GPU if enabled @@ -53,7 +53,7 @@ config: Configuration = { # 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), + 'hpm_scales': (1, 2, 4, 8), # Global pooling method 'hpm_use_avg_pool': True, 'hpm_use_max_pool': True, @@ -63,13 +63,15 @@ config: Configuration = { 'tfa_num_parts': 16, # Embedding dimension for each part 'embedding_dims': 256, - # Triplet loss margins for HPM and PartNet - 'triplet_margins': (1.5, 1.5), + # Batch Hard or Batch All + 'triplet_is_hard': True, + # Use non-zero mean or sum + 'triplet_is_mean': True, + # Triplet loss margins for HPM and PartNet, None for soft margin + 'triplet_margins': None, }, '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 @@ -83,15 +85,15 @@ config: Configuration = { # 'amsgrad': False, # Local parameters (override global ones) - # 'auto_encoder': { - # 'weight_decay': 0.001 - # }, + 'auto_encoder': { + 'weight_decay': 0.001 + }, }, 'scheduler': { - # Period of learning rate decay - 'step_size': 500, - # Multiplicative factor of decay - 'gamma': 1, + # Step start to decay + 'start_step': 15_000, + # Multiplicative factor of decay in the end + 'final_gamma': 0.001, } }, # Model metadata @@ -105,6 +107,6 @@ config: Configuration = { # Restoration iteration (multiple models, e.g. nm, bg and cl) 'restore_iters': (0, 0, 0), # Total iteration for training (multiple models) - 'total_iters': (80_000, 80_000, 80_000), + 'total_iters': (25_000, 25_000, 25_000), }, } |