name: "3layer_conv4_run3" model_type: FEED_FORWARD_NET seed: 42 hyperparams { base_epsilon: 0.001 epsilon_decay : INVERSE_T epsilon_decay_half_life : 100000 initial_momentum : 0.5 final_momentum : 0.95 momentum_change_steps : 10000 activation: RECTIFIED_LINEAR apply_weight_norm : true weight_norm : 4 dropout: true dropout_prob: 0.5 apply_l2_decay: false } layer { name: "input_layer" dimensions: 3072 is_input: true shape: 32 shape: 32 shape: 3 hyperparams{ dropout_prob: 0.1 activation: LINEAR normalize: false add_noise: false shift: false } data_field { train: "train_full_data" #validation: "valid_data" test: "test_data" } } layer { name: "output_layer" dimensions: 1 numlabels: 10 param { name: "bias" initialization: CONSTANT } hyperparams { dropout: false activation: SOFTMAX } is_output: true loss_function: CROSS_ENTROPY data_field { train: "train_full_labels" #validation: "valid_labels" test: "test_labels" } performance_stats { compute_cross_entropy: true compute_correct_preds: true } } layer { name: "hidden1" dimensions: 21600 #14400 # nloc = (x_width + 2*padding - size)/stride + 1 # = (32 + 2* 2- 5)/1 + 1 = 30 # pooling: # nloc = (nloc + 2*padding - size )/stride + 1 # = (32 + 2* 0 - 3)/2 + 1 = 15 # dims = num_filters * nloc**2 # dims = 96 * 15**2 param { name: "bias" initialization: CONSTANT } hyperparams { dropout_prob: 0.25 } } layer { name: "hidden2" dimensions: 6272 # nloc = (x_width + 2*padding - size)/stride + 1 # = (15 + 2* 2- 5)/1 + 1 = 15 # pooling: # nloc = (nloc + 2*padding - size )/stride + 1 # = (15 + 2* 0 - 3)/2 + 1 = 7 # dims = num_filters * nloc**2 # dims = 128 * 7**2 param { name: "bias" initialization: CONSTANT } hyperparams { dropout_prob: 0.25 } } layer { name: "hidden3" dimensions: 2304 # nloc = (x_width + 2*padding - size)/stride + 1 # = (7 + 2* 2- 5)/1 + 1 = 7 # pooling: # nloc = (nloc + 2*padding - size )/stride + 1 # = (7 + 2* 0 - 3)/2 + 1 = 3 # dims = num_filters * nloc**2 # dims = 256 * 3**2 param { name: "bias" initialization: CONSTANT } hyperparams { dropout_prob: 0.50 } } layer { name: "hidden4" dimensions: 2048 param { name: "bias" initialization: CONSTANT } } layer { name: "hidden5" dimensions: 2048 param { name: "bias" initialization: CONSTANT } } edge { node1: "input_layer" node2: "hidden1" param { name: "weight" conv: true conv_params { size: 5 stride: 1 padding: 2 num_filters: 96 num_colors: 3 max_pool: true pool_size: 3 pool_stride: 2 } initialization: DENSE_UNIFORM sigma: 0.01 } hyperparams { base_epsilon: 0.001 apply_l2_decay: true l2_decay: 0.001 } } edge { node1: "hidden1" node2: "hidden2" param { name: "weight" conv: true conv_params { size: 5 stride: 1 padding: 2 num_filters: 128 num_colors: 96 max_pool: true pool_size: 3 pool_stride: 2 } initialization: DENSE_UNIFORM sigma: 0.01 } hyperparams { base_epsilon: 0.001 apply_l2_decay: true l2_decay: 0.001 } } edge { node1: "hidden2" node2: "hidden3" param { name: "weight" conv: true conv_params { size: 5 stride: 1 padding: 2 num_filters: 256 num_colors: 128 max_pool: true pool_size: 3 pool_stride: 2 } initialization: DENSE_UNIFORM sigma: 0.01 } hyperparams { base_epsilon: 0.001 apply_l2_decay: true l2_decay: 0.001 } } edge { node1: "hidden3" node2: "hidden4" param { name: "weight" initialization: DENSE_UNIFORM_SQRT_FAN_IN sigma: 1.0 } hyperparams { base_epsilon: 0.1 } } edge { node1: "hidden4" node2: "hidden5" param { name: "weight" initialization: DENSE_UNIFORM_SQRT_FAN_IN sigma: 1.0 } hyperparams { base_epsilon: 0.1 } } edge { node1: "hidden5" node2: "output_layer" param { name: "weight" initialization: DENSE_UNIFORM_SQRT_FAN_IN sigma: 1.0 } hyperparams { base_epsilon: 0.1 apply_l2_decay: true l2_decay: 0.001 } }