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70 lines
1.9 KiB
70 lines
1.9 KiB
11 months ago
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RNN_STATE_DIM: 512 # the feature dimension for RNNs
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RNN_CELL_DEPTH: 2 # the depth for RNNs
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EMBEDDING_VECOTR_SIZE: 200 # the size of embedding vector in the network
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LEAK_VALUE: 0.05 # the value of leak relu
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CUBE_LEN: 32 # used to describe the resolution of the voxelization map
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BOUNDING_BOX_SIZE: 6 # the size of feature vector of bounding box
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TRAIN:
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BATCH_SIZE: 10 # mini batch size
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GPU_ID: [0] # the gpus for training
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# Loss hyperparameters
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VOXEL_BBOX_LOSS_RATIO: 0.4 # The training loss weight
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GRAPH_REC_KL_LOSS_RATIO: 0.99
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RECON_GEN_INITIAL_LOSS_RATIO: 1.0 # control the influence between reconstruction and generation loss
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RECON_GEN_RATIO_GAMMA: 0.9
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RECON_GEN_DECAY_STEP: 1500
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KL_ANNEAL_ITER: 72000
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FINAL_KL_RATIO: 0.8
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# Learning rate
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VERT_LEARNING_RATE: 0.6 # Learning rate decay
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VERT_GAMMA: 0.9
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VERT_LR_DECAY_STEP: 2300
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EDGE_LEARNING_RATE: 0.1
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EDGE_GAMMA: 0.9
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EDGE_LR_DECAY_STEP: 1850
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GRAPH_GEN_LEARNING_RATE: 0.1
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GRAPH_GEN_GAMMA: 0.9
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GRAPH_GEN_LR_DECAY_STEP: 1600
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ITER_NUM: 80000
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SNAPSHOT_FREQ: 2000 # The frequency to save model snapshot and summary
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SUMMARY_FREQ: 20
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EXCHANGE_NUM: 3 # The iteration number when exchange geometry and structure information
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DROPOUT_KEEP_PROB: 0.5
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MAX_GRADIENT_NORM: 0.5
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MOMENTUM_VALUE: 0.9
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RANDOM_SEED: 20
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OPTIMIZER_TYPE: "momentum"
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VOXEL_DEFAULT_VALUE: 0.1
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DIR_PATH: '../../data/SAG/training_data/'
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RESULTS_DIRECTORY: 'nn_exp_results/reconstruction_results/'
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LOG_DIRECTORY: 'nn_exp_results/logs/'
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MODEL_DIRECTORY: 'nn_exp_results/models/'
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PRETRAINED_MODEL_PATH: ''
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SHAPE_NAME: 'chair'
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TEST:
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GPU_ID: [0] # the gpus for testing
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SAMPLE_SIZE: 100
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RESULTS_DIRECTORY: 'nn_exp_results/testing_results/'
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# PRETRAINED_MODEL_PATH: 'nn_exp_results/models/motorbike_2019_08_18_01_25_33/motorbike_79999.ckpt'
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PRETRAINED_MODEL_PATH: 'nn_exp_results/models/chair_2023_09_20_00_16_45/checkpoint'
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