├── Cifar ├── 1cycsolver.prototxt ├── architectures │ ├── c100Resnet56.prototxt │ ├── cifar100.prototxt │ ├── cifar3.prototxt │ ├── gResnet56.prototxt │ ├── genDensenet40.prototxt │ ├── genResnet56.prototxt │ └── wide32cifar.prototxt ├── clrsolver.prototxt ├── jsub.sh ├── results │ ├── c100Resnet56_C100Res1CycLR.1001.2CM0.95.85WD1e-4Epoch145BS256g_1 │ ├── cifar100_C100CycLR.0020.02CM0.95.8WD6e-4Epoch50BS128l_1 │ ├── gResnet56_ResTBS512LR.0800.8M.95WD1e-4Epoch95BS128b_1 │ ├── genDensenet40_Den1CycLR.1004M0.9WD1e-6Epoch50BS128c_1 │ ├── genDensenet40_DenOrigLR0.10.1M0.9WD1e-4Epoch400BS128c_1 │ ├── wide32cifar_Wide1CycLR.1001CM0.95.85WD1e-4Epoch50BS128a_1 │ └── wide32cifar_Wide1CycLR.1001M0.95WD1e-5Epoch100BS128j_1 ├── solver.prototxt ├── train.sh └── x4.sh ├── Imagenet ├── architectures │ ├── inception-resnet-v2.prototxt │ └── resnet50.prototxt ├── inception │ ├── a2qsub1.pbs │ ├── a2train1.sh │ ├── aqsub1.pbs │ ├── asolver1.prototxt │ ├── atrain1.sh │ ├── b2qsub1.pbs │ ├── b2qsub2.pbs │ ├── b2train1.sh │ ├── b2train2.sh │ ├── bqsub1.pbs │ ├── bqsub2.pbs │ ├── bqsub35.pbs │ ├── bqsub36.pbs │ ├── bqsub5.pbs │ ├── bqsub6.pbs │ ├── bsolver1.prototxt │ ├── bsolver2.prototxt │ ├── bsolver35.prototxt │ ├── bsolver36.prototxt │ ├── bsolver5.prototxt │ ├── bsolver6.prototxt │ ├── btrain1.sh │ ├── btrain2.sh │ ├── btrain3.sh │ ├── btrain35.sh │ ├── btrain36.sh │ ├── btrain4.sh │ ├── btrain5.sh │ ├── btrain6.sh │ ├── ma2qsub1.pbs │ ├── maqsub1.pbs │ ├── mb2qsub1.pbs │ ├── mbqsub1.pbs │ ├── qsub2.pbs │ └── sub.sh ├── resnet │ ├── a2qsub1.pbs │ ├── a2train1.sh │ ├── aqsub1.pbs │ ├── asolver1.prototxt │ ├── atrain1.sh │ ├── b2qsub1.pbs │ ├── b2qsub2.pbs │ ├── b2qsub3.pbs │ ├── b2qsub4.pbs │ ├── b2train1.sh │ ├── b2train2.sh │ ├── b2train3.sh │ ├── b2train4.sh │ ├── bqsub1.pbs │ ├── bqsub2.pbs │ ├── bqsub3.pbs │ ├── bqsub35.pbs │ ├── bqsub36.pbs │ ├── bqsub4.pbs │ ├── bsolver1.prototxt │ ├── bsolver2.prototxt │ ├── bsolver3.prototxt │ ├── bsolver35.prototxt │ ├── bsolver36.prototxt │ ├── bsolver4.prototxt │ ├── btrain1.sh │ ├── btrain2.sh │ ├── btrain3.sh │ ├── btrain35.sh │ ├── btrain36.sh │ ├── btrain4.sh │ ├── ma2qsub1.pbs │ ├── maqsub1.pbs │ ├── mb2qsub1.pbs │ ├── mbqsub1.pbs │ ├── qsub2.pbs │ ├── resnet.pbs │ ├── resnet.prototxt │ ├── resnetNoRelus.pbs │ ├── resnetNoRelus.prototxt │ └── sub.sh └── results │ ├── inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs_1 │ ├── inception-resnetCM9585CLR.051WD1e-6BS28_20Epochs_1 │ ├── inception-resnetCM9585CLR.051WD1e-6BS28_20Epochs_2 │ ├── inception-resnetCM9585CLR.051WD3e-6BS28_20Epochs_1 │ ├── inception-resnetCM9585CLR.051WD3e-6BS28_20Epochs_2 │ ├── inception-resnetM9LR.1WD1e-4BS28_145Epochs_1 │ ├── inception-resnetM9LR.1WD1e-4BS28_145Epochs_2 │ ├── resnetCM9585CLR.051WD1e-6BS32_20Epochs_1 │ ├── resnetCM9585CLR.051WD3e-6BS32_20Epochs_1 │ └── resnetM9LR1WD1e-4BS32_145Epochs_1 └── README.md /Cifar/1cycsolver.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/skipConnections/architectures/aarch.prototxt" 2 | #net: "examples/skipConnections/architectures/resnet56.prototxt" 3 | #net: "examples/skipConnections/architectures/2ndOrder56.prototxt" 4 | # 5 | test_iter: 200 6 | test_interval: 100 7 | display: 100 8 | test_initialization: false 9 | 10 | lr_policy: "1cycle" # "triangular" 11 | base_lr: xLR2 12 | max_lr: xLR1 13 | stepsize: xStep 14 | max_iter: xIter 15 | 16 | snapshot: xIter 17 | snapshot_prefix: "examples/skipConnections/snapshots/xResnet56" 18 | #snapshot_prefix: "examples/skipConnections/snapshots/range2ndOrder56Mom7" 19 | solver_mode: GPU 20 | 21 | weight_decay: xwd 22 | #decrease_weight_decay: xSV1 23 | momentum: xmom1 24 | cyclical_momentum: xmom2 25 | cyclical_momentum: xmom3 26 | 27 | #regularization_type: "L1" 28 | type: "Nesterov" # "RMSProp" # "Adam" # "AdaGrad" # 29 | #type: "Adam" # "AdaDelta" # 30 | #rms_decay: 0.9 31 | #clip_gradients: 10 32 | #iter_size: 4 33 | #debug_info: true 34 | -------------------------------------------------------------------------------- /Cifar/architectures/cifar100.prototxt: -------------------------------------------------------------------------------- 1 | name: "CIFAR10_full" 2 | layer { 3 | name: "cifar" 4 | type: "Data" 5 | top: "data" 6 | top: "label" 7 | include { 8 | phase: TRAIN 9 | } 10 | transform_param { 11 | mean_file: "data/cifar100/mean.binaryproto" 12 | } 13 | data_param { 14 | source: "data/cifar100/cifar100_train_lmdb" 15 | batch_size: xBS 16 | backend: LMDB 17 | } 18 | } 19 | layer { 20 | name: "cifar" 21 | type: "Data" 22 | top: "data" 23 | top: "label" 24 | include { 25 | phase: TEST 26 | } 27 | transform_param { 28 | mean_file: "data/cifar100/mean.binaryproto" 29 | } 30 | data_param { 31 | source: "data/cifar100/cifar100_test_lmdb" 32 | batch_size: 100 33 | backend: LMDB 34 | } 35 | } 36 | layer { 37 | name: "conv1" 38 | type: "Convolution" 39 | bottom: "data" 40 | top: "conv1" 41 | param { 42 | lr_mult: 1 43 | } 44 | param { 45 | lr_mult: 2 46 | } 47 | convolution_param { 48 | num_output: 32 49 | pad: 2 50 | kernel_size: 5 51 | stride: 1 52 | weight_filler { 53 | # type: "msra" 54 | type: "gaussian" 55 | std: 0.0001 56 | } 57 | bias_filler { 58 | type: "constant" 59 | } 60 | } 61 | } 62 | layer { 63 | name: "pool1" 64 | type: "Pooling" 65 | bottom: "conv1" 66 | top: "pool1" 67 | pooling_param { 68 | pool: MAX 69 | kernel_size: 3 70 | stride: 2 71 | } 72 | } 73 | layer { 74 | name: "relu1" 75 | type: "ReLU" 76 | bottom: "pool1" 77 | top: "pool1" 78 | } 79 | layer { 80 | name: "norm1" 81 | type: "LRN" 82 | bottom: "pool1" 83 | top: "norm1" 84 | lrn_param { 85 | local_size: 3 86 | alpha: 5e-05 87 | beta: 0.75 88 | norm_region: WITHIN_CHANNEL 89 | } 90 | } 91 | layer { 92 | name: "conv2" 93 | type: "Convolution" 94 | bottom: "norm1" 95 | top: "conv2" 96 | param { 97 | lr_mult: 1 98 | } 99 | param { 100 | lr_mult: 2 101 | } 102 | convolution_param { 103 | num_output: 32 104 | pad: 2 105 | kernel_size: 5 106 | stride: 1 107 | weight_filler { 108 | # type: "msra" 109 | type: "gaussian" 110 | std: 0.01 111 | } 112 | bias_filler { 113 | type: "constant" 114 | } 115 | } 116 | } 117 | layer { 118 | name: "relu2" 119 | type: "ReLU" 120 | bottom: "conv2" 121 | top: "conv2" 122 | } 123 | layer { 124 | name: "pool2" 125 | type: "Pooling" 126 | bottom: "conv2" 127 | top: "pool2" 128 | pooling_param { 129 | pool: AVE 130 | kernel_size: 3 131 | stride: 2 132 | } 133 | } 134 | layer { 135 | name: "norm2" 136 | type: "LRN" 137 | bottom: "pool2" 138 | top: "norm2" 139 | lrn_param { 140 | local_size: 3 141 | alpha: 5e-05 142 | beta: 0.75 143 | norm_region: WITHIN_CHANNEL 144 | } 145 | } 146 | layer { 147 | name: "conv3" 148 | type: "Convolution" 149 | bottom: "norm2" 150 | top: "conv3" 151 | convolution_param { 152 | num_output: 64 153 | pad: 2 154 | kernel_size: 5 155 | stride: 1 156 | weight_filler { 157 | # type: "msra" 158 | type: "gaussian" 159 | std: 0.01 160 | } 161 | bias_filler { 162 | type: "constant" 163 | } 164 | } 165 | } 166 | layer { 167 | name: "relu3" 168 | type: "ReLU" 169 | bottom: "conv3" 170 | top: "conv3" 171 | } 172 | layer { 173 | name: "pool3" 174 | type: "Pooling" 175 | bottom: "conv3" 176 | top: "pool3" 177 | pooling_param { 178 | pool: AVE 179 | kernel_size: 3 180 | stride: 2 181 | } 182 | } 183 | layer { 184 | name: "ip1" 185 | type: "InnerProduct" 186 | bottom: "pool3" 187 | top: "ip1" 188 | param { 189 | lr_mult: 1 190 | decay_mult: 250 191 | } 192 | param { 193 | lr_mult: 2 194 | decay_mult: 0 195 | } 196 | inner_product_param { 197 | num_output: 100 198 | weight_filler { 199 | # type: "msra" 200 | type: "gaussian" 201 | std: 0.01 202 | } 203 | bias_filler { 204 | type: "constant" 205 | } 206 | } 207 | } 208 | layer { 209 | name: "accuracy" 210 | type: "Accuracy" 211 | bottom: "ip1" 212 | bottom: "label" 213 | top: "accuracy" 214 | # include { 215 | # phase: TEST 216 | # } 217 | } 218 | layer { 219 | name: "loss" 220 | type: "SoftmaxWithLoss" 221 | bottom: "ip1" 222 | bottom: "label" 223 | top: "loss" 224 | } 225 | -------------------------------------------------------------------------------- /Cifar/architectures/cifar3.prototxt: -------------------------------------------------------------------------------- 1 | name: "CIFAR10_full" 2 | layer { 3 | name: "cifar" 4 | type: "Data" 5 | top: "data" 6 | top: "label" 7 | include { 8 | phase: TRAIN 9 | } 10 | transform_param { 11 | mean_file: "examples/cifar10/mean.binaryproto" 12 | } 13 | data_param { 14 | source: "examples/cifar10/cifar10_train_lmdb" 15 | batch_size: xBS 16 | backend: LMDB 17 | } 18 | } 19 | layer { 20 | name: "cifar" 21 | type: "Data" 22 | top: "data" 23 | top: "label" 24 | include { 25 | phase: TEST 26 | } 27 | transform_param { 28 | mean_file: "examples/cifar10/mean.binaryproto" 29 | } 30 | data_param { 31 | source: "examples/cifar10/cifar10_test_lmdb" 32 | batch_size: 100 33 | backend: LMDB 34 | } 35 | } 36 | layer { 37 | name: "conv1" 38 | type: "Convolution" 39 | bottom: "data" 40 | top: "conv1" 41 | param { 42 | lr_mult: 1 43 | } 44 | param { 45 | lr_mult: 2 46 | } 47 | convolution_param { 48 | num_output: 32 49 | pad: 2 50 | kernel_size: 5 51 | stride: 1 52 | weight_filler { 53 | type: "gaussian" 54 | std: 0.0001 55 | } 56 | bias_filler { 57 | type: "constant" 58 | } 59 | } 60 | } 61 | layer { 62 | name: "pool1" 63 | type: "Pooling" 64 | bottom: "conv1" 65 | top: "pool1" 66 | pooling_param { 67 | pool: MAX 68 | kernel_size: 3 69 | stride: 2 70 | } 71 | } 72 | layer { 73 | name: "relu1" 74 | type: "ReLU" 75 | bottom: "pool1" 76 | top: "pool1" 77 | } 78 | layer { 79 | name: "norm1" 80 | type: "LRN" 81 | bottom: "pool1" 82 | top: "norm1" 83 | lrn_param { 84 | local_size: 3 85 | alpha: 5e-05 86 | beta: 0.75 87 | norm_region: WITHIN_CHANNEL 88 | } 89 | } 90 | layer { 91 | name: "conv2" 92 | type: "Convolution" 93 | bottom: "norm1" 94 | top: "conv2" 95 | param { 96 | lr_mult: 1 97 | } 98 | param { 99 | lr_mult: 2 100 | } 101 | convolution_param { 102 | num_output: 32 103 | pad: 2 104 | kernel_size: 5 105 | stride: 1 106 | weight_filler { 107 | type: "gaussian" 108 | std: 0.01 109 | } 110 | bias_filler { 111 | type: "constant" 112 | } 113 | } 114 | } 115 | layer { 116 | name: "relu2" 117 | type: "ReLU" 118 | bottom: "conv2" 119 | top: "conv2" 120 | } 121 | layer { 122 | name: "pool2" 123 | type: "Pooling" 124 | bottom: "conv2" 125 | top: "pool2" 126 | pooling_param { 127 | pool: AVE 128 | kernel_size: 3 129 | stride: 2 130 | } 131 | } 132 | layer { 133 | name: "norm2" 134 | type: "LRN" 135 | bottom: "pool2" 136 | top: "norm2" 137 | lrn_param { 138 | local_size: 3 139 | alpha: 5e-05 140 | beta: 0.75 141 | norm_region: WITHIN_CHANNEL 142 | } 143 | } 144 | layer { 145 | name: "conv3" 146 | type: "Convolution" 147 | bottom: "norm2" 148 | top: "conv3" 149 | convolution_param { 150 | num_output: 64 151 | pad: 2 152 | kernel_size: 5 153 | stride: 1 154 | weight_filler { 155 | type: "gaussian" 156 | std: 0.01 157 | } 158 | bias_filler { 159 | type: "constant" 160 | } 161 | } 162 | } 163 | layer { 164 | name: "relu3" 165 | type: "ReLU" 166 | bottom: "conv3" 167 | top: "conv3" 168 | } 169 | layer { 170 | name: "pool3" 171 | type: "Pooling" 172 | bottom: "conv3" 173 | top: "pool3" 174 | pooling_param { 175 | pool: AVE 176 | kernel_size: 3 177 | stride: 2 178 | } 179 | } 180 | layer { 181 | name: "ip1" 182 | type: "InnerProduct" 183 | bottom: "pool3" 184 | top: "ip1" 185 | param { 186 | lr_mult: 1 187 | decay_mult: 250 188 | } 189 | param { 190 | lr_mult: 2 191 | decay_mult: 0 192 | } 193 | inner_product_param { 194 | num_output: 10 195 | weight_filler { 196 | type: "gaussian" 197 | std: 0.01 198 | } 199 | bias_filler { 200 | type: "constant" 201 | } 202 | } 203 | } 204 | layer { 205 | name: "accuracy" 206 | type: "Accuracy" 207 | bottom: "ip1" 208 | bottom: "label" 209 | top: "accuracy" 210 | # include { 211 | # phase: TEST 212 | # } 213 | } 214 | layer { 215 | name: "loss" 216 | type: "SoftmaxWithLoss" 217 | bottom: "ip1" 218 | bottom: "label" 219 | top: "loss" 220 | } 221 | -------------------------------------------------------------------------------- /Cifar/architectures/wide32cifar.prototxt: -------------------------------------------------------------------------------- 1 | name: "widenet32 with k=4-cifar10" 2 | layer { 3 | name: "dataLayer" 4 | type: "Data" 5 | top: "data" 6 | top: "label" 7 | include { 8 | phase: TRAIN 9 | } 10 | transform_param { 11 | mirror: true 12 | crop_size: 32 13 | mean_file: "examples/cifar10/mean.binaryproto" 14 | } 15 | data_param { 16 | source: "examples/cifar10/cifar10_train_lmdb" 17 | batch_size: xBS 18 | backend: LMDB 19 | } 20 | image_data_param { 21 | shuffle: true 22 | } 23 | } 24 | layer { 25 | name: "dataLayer" 26 | type: "Data" 27 | top: "data" 28 | top: "label" 29 | include { 30 | phase: TEST 31 | } 32 | transform_param { 33 | mirror: true 34 | crop_size: 32 35 | mean_file: "examples/cifar10/mean.binaryproto" 36 | } 37 | data_param { 38 | source: "examples/cifar10/cifar10_test_lmdb" 39 | batch_size: 32 40 | backend: LMDB 41 | } 42 | image_data_param { 43 | shuffle: false 44 | } 45 | } 46 | layer { 47 | name: "first_conv" 48 | type: "Convolution" 49 | bottom: "data" 50 | top: "first_conv" 51 | param { 52 | lr_mult: 1 53 | decay_mult: 1 54 | } 55 | convolution_param { 56 | num_output: 16 57 | pad: 1 58 | kernel_size: 3 59 | stride: 1 60 | weight_filler { 61 | type: "msra" 62 | } 63 | } 64 | } 65 | layer { 66 | name: "first_conv_bn" 67 | type: "BatchNorm" 68 | bottom: "first_conv" 69 | top: "first_conv" 70 | param { 71 | lr_mult: 0 72 | decay_mult: 0 73 | } 74 | param { 75 | lr_mult: 0 76 | decay_mult: 0 77 | } 78 | param { 79 | lr_mult: 0 80 | decay_mult: 0 81 | } 82 | batch_norm_param { 83 | moving_average_fraction: 0.9 84 | } 85 | } 86 | layer { 87 | name: "first_conv_scale" 88 | type: "Scale" 89 | bottom: "first_conv" 90 | top: "first_conv" 91 | scale_param { 92 | bias_term: true 93 | } 94 | } 95 | layer { 96 | name: "first_conv_relu" 97 | type: "ReLU" 98 | bottom: "first_conv" 99 | top: "first_conv" 100 | } 101 | layer { 102 | name: "group0_block0_conv0" 103 | type: "Convolution" 104 | bottom: "first_conv" 105 | top: "group0_block0_conv0" 106 | param { 107 | lr_mult: 1 108 | decay_mult: 1 109 | } 110 | convolution_param { 111 | num_output: 16 112 | pad: 1 113 | kernel_size: 3 114 | stride: 1 115 | weight_filler { 116 | type: "msra" 117 | } 118 | } 119 | } 120 | layer { 121 | name: "group0_block0_conv0_bn" 122 | type: "BatchNorm" 123 | bottom: "group0_block0_conv0" 124 | top: "group0_block0_conv0" 125 | param { 126 | lr_mult: 0 127 | decay_mult: 0 128 | } 129 | param { 130 | lr_mult: 0 131 | decay_mult: 0 132 | } 133 | param { 134 | lr_mult: 0 135 | decay_mult: 0 136 | } 137 | batch_norm_param { 138 | moving_average_fraction: 0.9 139 | } 140 | } 141 | layer { 142 | name: "group0_block0_conv0_scale" 143 | type: "Scale" 144 | bottom: "group0_block0_conv0" 145 | top: "group0_block0_conv0" 146 | scale_param { 147 | bias_term: true 148 | } 149 | } 150 | layer { 151 | name: "group0_block0_conv0_relu" 152 | type: "ReLU" 153 | bottom: "group0_block0_conv0" 154 | top: "group0_block0_conv0" 155 | } 156 | layer { 157 | name: "group0_block0_conv1" 158 | type: "Convolution" 159 | bottom: "group0_block0_conv0" 160 | top: "group0_block0_conv1" 161 | param { 162 | lr_mult: 1 163 | decay_mult: 1 164 | } 165 | convolution_param { 166 | num_output: 16 167 | pad: 1 168 | kernel_size: 3 169 | stride: 1 170 | weight_filler { 171 | type: "msra" 172 | } 173 | } 174 | } 175 | layer { 176 | name: "group0_block0_conv1_bn" 177 | type: "BatchNorm" 178 | bottom: "group0_block0_conv1" 179 | top: "group0_block0_conv1" 180 | param { 181 | lr_mult: 0 182 | decay_mult: 0 183 | } 184 | param { 185 | lr_mult: 0 186 | decay_mult: 0 187 | } 188 | param { 189 | lr_mult: 0 190 | decay_mult: 0 191 | } 192 | batch_norm_param { 193 | moving_average_fraction: 0.9 194 | } 195 | } 196 | layer { 197 | name: "group0_block0_conv1_scale" 198 | type: "Scale" 199 | bottom: "group0_block0_conv1" 200 | top: "group0_block0_conv1" 201 | scale_param { 202 | bias_term: true 203 | } 204 | } 205 | layer { 206 | name: "group0_block0_sum" 207 | type: "Eltwise" 208 | bottom: "group0_block0_conv1" 209 | bottom: "first_conv" 210 | top: "group0_block0_sum" 211 | eltwise_param { 212 | operation: SUM 213 | } 214 | } 215 | layer { 216 | name: "group0_block1_conv0" 217 | type: "Convolution" 218 | bottom: "group0_block0_sum" 219 | top: "group0_block1_conv0" 220 | param { 221 | lr_mult: 1 222 | decay_mult: 1 223 | } 224 | convolution_param { 225 | num_output: 16 226 | pad: 1 227 | kernel_size: 3 228 | stride: 1 229 | weight_filler { 230 | type: "msra" 231 | } 232 | } 233 | } 234 | layer { 235 | name: "group0_block1_conv0_bn" 236 | type: "BatchNorm" 237 | bottom: "group0_block1_conv0" 238 | top: "group0_block1_conv0" 239 | param { 240 | lr_mult: 0 241 | decay_mult: 0 242 | } 243 | param { 244 | lr_mult: 0 245 | decay_mult: 0 246 | } 247 | param { 248 | lr_mult: 0 249 | decay_mult: 0 250 | } 251 | batch_norm_param { 252 | moving_average_fraction: 0.9 253 | } 254 | } 255 | layer { 256 | name: "group0_block1_conv0_scale" 257 | type: "Scale" 258 | bottom: "group0_block1_conv0" 259 | top: "group0_block1_conv0" 260 | scale_param { 261 | bias_term: true 262 | } 263 | } 264 | layer { 265 | name: "group0_block1_conv0_relu" 266 | type: "ReLU" 267 | bottom: "group0_block1_conv0" 268 | top: "group0_block1_conv0" 269 | } 270 | layer { 271 | name: "group0_block1_conv1" 272 | type: "Convolution" 273 | bottom: "group0_block1_conv0" 274 | top: "group0_block1_conv1" 275 | param { 276 | lr_mult: 1 277 | decay_mult: 1 278 | } 279 | convolution_param { 280 | num_output: 16 281 | pad: 1 282 | kernel_size: 3 283 | stride: 1 284 | weight_filler { 285 | type: "msra" 286 | } 287 | } 288 | } 289 | layer { 290 | name: "group0_block1_conv1_bn" 291 | type: "BatchNorm" 292 | bottom: "group0_block1_conv1" 293 | top: "group0_block1_conv1" 294 | param { 295 | lr_mult: 0 296 | decay_mult: 0 297 | } 298 | param { 299 | lr_mult: 0 300 | decay_mult: 0 301 | } 302 | param { 303 | lr_mult: 0 304 | decay_mult: 0 305 | } 306 | batch_norm_param { 307 | moving_average_fraction: 0.9 308 | } 309 | } 310 | layer { 311 | name: "group0_block1_conv1_scale" 312 | type: "Scale" 313 | bottom: "group0_block1_conv1" 314 | top: "group0_block1_conv1" 315 | scale_param { 316 | bias_term: true 317 | } 318 | } 319 | layer { 320 | name: "group0_block1_sum" 321 | type: "Eltwise" 322 | bottom: "group0_block1_conv1" 323 | bottom: "group0_block0_sum" 324 | top: "group0_block1_sum" 325 | eltwise_param { 326 | operation: SUM 327 | } 328 | } 329 | layer { 330 | name: "group0_block2_conv0" 331 | type: "Convolution" 332 | bottom: "group0_block1_sum" 333 | top: "group0_block2_conv0" 334 | param { 335 | lr_mult: 1 336 | decay_mult: 1 337 | } 338 | convolution_param { 339 | num_output: 16 340 | pad: 1 341 | kernel_size: 3 342 | stride: 1 343 | weight_filler { 344 | type: "msra" 345 | } 346 | } 347 | } 348 | layer { 349 | name: "group0_block2_conv0_bn" 350 | type: "BatchNorm" 351 | bottom: "group0_block2_conv0" 352 | top: "group0_block2_conv0" 353 | param { 354 | lr_mult: 0 355 | decay_mult: 0 356 | } 357 | param { 358 | lr_mult: 0 359 | decay_mult: 0 360 | } 361 | param { 362 | lr_mult: 0 363 | decay_mult: 0 364 | } 365 | batch_norm_param { 366 | moving_average_fraction: 0.9 367 | } 368 | } 369 | layer { 370 | name: "group0_block2_conv0_scale" 371 | type: "Scale" 372 | bottom: "group0_block2_conv0" 373 | top: "group0_block2_conv0" 374 | scale_param { 375 | bias_term: true 376 | } 377 | } 378 | layer { 379 | name: "group0_block2_conv0_relu" 380 | type: "ReLU" 381 | bottom: "group0_block2_conv0" 382 | top: "group0_block2_conv0" 383 | } 384 | layer { 385 | name: "group0_block2_conv1" 386 | type: "Convolution" 387 | bottom: "group0_block2_conv0" 388 | top: "group0_block2_conv1" 389 | param { 390 | lr_mult: 1 391 | decay_mult: 1 392 | } 393 | convolution_param { 394 | num_output: 16 395 | pad: 1 396 | kernel_size: 3 397 | stride: 1 398 | weight_filler { 399 | type: "msra" 400 | } 401 | } 402 | } 403 | layer { 404 | name: "group0_block2_conv1_bn" 405 | type: "BatchNorm" 406 | bottom: "group0_block2_conv1" 407 | top: "group0_block2_conv1" 408 | param { 409 | lr_mult: 0 410 | decay_mult: 0 411 | } 412 | param { 413 | lr_mult: 0 414 | decay_mult: 0 415 | } 416 | param { 417 | lr_mult: 0 418 | decay_mult: 0 419 | } 420 | batch_norm_param { 421 | moving_average_fraction: 0.9 422 | } 423 | } 424 | layer { 425 | name: "group0_block2_conv1_scale" 426 | type: "Scale" 427 | bottom: "group0_block2_conv1" 428 | top: "group0_block2_conv1" 429 | scale_param { 430 | bias_term: true 431 | } 432 | } 433 | layer { 434 | name: "group0_block2_sum" 435 | type: "Eltwise" 436 | bottom: "group0_block2_conv1" 437 | bottom: "group0_block1_sum" 438 | top: "group0_block2_sum" 439 | eltwise_param { 440 | operation: SUM 441 | } 442 | } 443 | layer { 444 | name: "group0_block3_conv0" 445 | type: "Convolution" 446 | bottom: "group0_block2_sum" 447 | top: "group0_block3_conv0" 448 | param { 449 | lr_mult: 1 450 | decay_mult: 1 451 | } 452 | convolution_param { 453 | num_output: 16 454 | pad: 1 455 | kernel_size: 3 456 | stride: 1 457 | weight_filler { 458 | type: "msra" 459 | } 460 | } 461 | } 462 | layer { 463 | name: "group0_block3_conv0_bn" 464 | type: "BatchNorm" 465 | bottom: "group0_block3_conv0" 466 | top: "group0_block3_conv0" 467 | param { 468 | lr_mult: 0 469 | decay_mult: 0 470 | } 471 | param { 472 | lr_mult: 0 473 | decay_mult: 0 474 | } 475 | param { 476 | lr_mult: 0 477 | decay_mult: 0 478 | } 479 | batch_norm_param { 480 | moving_average_fraction: 0.9 481 | } 482 | } 483 | layer { 484 | name: "group0_block3_conv0_scale" 485 | type: "Scale" 486 | bottom: "group0_block3_conv0" 487 | top: "group0_block3_conv0" 488 | scale_param { 489 | bias_term: true 490 | } 491 | } 492 | layer { 493 | name: "group0_block3_conv0_relu" 494 | type: "ReLU" 495 | bottom: "group0_block3_conv0" 496 | top: "group0_block3_conv0" 497 | } 498 | layer { 499 | name: "group0_block3_conv1" 500 | type: "Convolution" 501 | bottom: "group0_block3_conv0" 502 | top: "group0_block3_conv1" 503 | param { 504 | lr_mult: 1 505 | decay_mult: 1 506 | } 507 | convolution_param { 508 | num_output: 16 509 | pad: 1 510 | kernel_size: 3 511 | stride: 1 512 | weight_filler { 513 | type: "msra" 514 | } 515 | } 516 | } 517 | layer { 518 | name: "group0_block3_conv1_bn" 519 | type: "BatchNorm" 520 | bottom: "group0_block3_conv1" 521 | top: "group0_block3_conv1" 522 | param { 523 | lr_mult: 0 524 | decay_mult: 0 525 | } 526 | param { 527 | lr_mult: 0 528 | decay_mult: 0 529 | } 530 | param { 531 | lr_mult: 0 532 | decay_mult: 0 533 | } 534 | batch_norm_param { 535 | moving_average_fraction: 0.9 536 | } 537 | } 538 | layer { 539 | name: "group0_block3_conv1_scale" 540 | type: "Scale" 541 | bottom: "group0_block3_conv1" 542 | top: "group0_block3_conv1" 543 | scale_param { 544 | bias_term: true 545 | } 546 | } 547 | layer { 548 | name: "group0_block3_sum" 549 | type: "Eltwise" 550 | bottom: "group0_block3_conv1" 551 | bottom: "group0_block2_sum" 552 | top: "group0_block3_sum" 553 | eltwise_param { 554 | operation: SUM 555 | } 556 | } 557 | layer { 558 | name: "group0_block8_conv0" 559 | type: "Convolution" 560 | bottom: "group0_block3_sum" 561 | top: "group0_block8_conv0" 562 | param { 563 | lr_mult: 1 564 | decay_mult: 1 565 | } 566 | convolution_param { 567 | num_output: 16 568 | pad: 1 569 | kernel_size: 3 570 | stride: 1 571 | weight_filler { 572 | type: "msra" 573 | } 574 | } 575 | } 576 | layer { 577 | name: "group0_block8_conv0_bn" 578 | type: "BatchNorm" 579 | bottom: "group0_block8_conv0" 580 | top: "group0_block8_conv0" 581 | param { 582 | lr_mult: 0 583 | decay_mult: 0 584 | } 585 | param { 586 | lr_mult: 0 587 | decay_mult: 0 588 | } 589 | param { 590 | lr_mult: 0 591 | decay_mult: 0 592 | } 593 | batch_norm_param { 594 | moving_average_fraction: 0.9 595 | } 596 | } 597 | layer { 598 | name: "group0_block8_conv0_scale" 599 | type: "Scale" 600 | bottom: "group0_block8_conv0" 601 | top: "group0_block8_conv0" 602 | scale_param { 603 | bias_term: true 604 | } 605 | } 606 | layer { 607 | name: "group0_block8_conv0_relu" 608 | type: "ReLU" 609 | bottom: "group0_block8_conv0" 610 | top: "group0_block8_conv0" 611 | } 612 | layer { 613 | name: "group0_block8_conv1" 614 | type: "Convolution" 615 | bottom: "group0_block8_conv0" 616 | top: "group0_block8_conv1" 617 | param { 618 | lr_mult: 1 619 | decay_mult: 1 620 | } 621 | convolution_param { 622 | num_output: 16 623 | pad: 1 624 | kernel_size: 3 625 | stride: 1 626 | weight_filler { 627 | type: "msra" 628 | } 629 | } 630 | } 631 | layer { 632 | name: "group0_block8_conv1_bn" 633 | type: "BatchNorm" 634 | bottom: "group0_block8_conv1" 635 | top: "group0_block8_conv1" 636 | param { 637 | lr_mult: 0 638 | decay_mult: 0 639 | } 640 | param { 641 | lr_mult: 0 642 | decay_mult: 0 643 | } 644 | param { 645 | lr_mult: 0 646 | decay_mult: 0 647 | } 648 | batch_norm_param { 649 | moving_average_fraction: 0.9 650 | } 651 | } 652 | layer { 653 | name: "group0_block8_conv1_scale" 654 | type: "Scale" 655 | bottom: "group0_block8_conv1" 656 | top: "group0_block8_conv1" 657 | scale_param { 658 | bias_term: true 659 | } 660 | } 661 | layer { 662 | name: "group0_block8_sum" 663 | type: "Eltwise" 664 | bottom: "group0_block8_conv1" 665 | bottom: "group0_block3_sum" 666 | top: "group0_block8_sum" 667 | eltwise_param { 668 | operation: SUM 669 | } 670 | } 671 | layer { 672 | name: "group1_block0_conv0" 673 | type: "Convolution" 674 | bottom: "group0_block8_sum" 675 | top: "group1_block0_conv0" 676 | param { 677 | lr_mult: 1 678 | decay_mult: 1 679 | } 680 | convolution_param { 681 | num_output: 64 682 | pad: 1 683 | kernel_size: 3 684 | stride: 2 685 | weight_filler { 686 | type: "msra" 687 | } 688 | } 689 | } 690 | layer { 691 | name: "group1_block0_conv0_bn" 692 | type: "BatchNorm" 693 | bottom: "group1_block0_conv0" 694 | top: "group1_block0_conv0" 695 | param { 696 | lr_mult: 0 697 | decay_mult: 0 698 | } 699 | param { 700 | lr_mult: 0 701 | decay_mult: 0 702 | } 703 | param { 704 | lr_mult: 0 705 | decay_mult: 0 706 | } 707 | batch_norm_param { 708 | moving_average_fraction: 0.9 709 | } 710 | } 711 | layer { 712 | name: "group1_block0_conv0_scale" 713 | type: "Scale" 714 | bottom: "group1_block0_conv0" 715 | top: "group1_block0_conv0" 716 | scale_param { 717 | bias_term: true 718 | } 719 | } 720 | layer { 721 | name: "group1_block0_conv0_relu" 722 | type: "ReLU" 723 | bottom: "group1_block0_conv0" 724 | top: "group1_block0_conv0" 725 | } 726 | layer { 727 | name: "group1_block0_conv1" 728 | type: "Convolution" 729 | bottom: "group1_block0_conv0" 730 | top: "group1_block0_conv1" 731 | param { 732 | lr_mult: 1 733 | decay_mult: 1 734 | } 735 | convolution_param { 736 | num_output: 64 737 | pad: 1 738 | kernel_size: 3 739 | stride: 1 740 | weight_filler { 741 | type: "msra" 742 | } 743 | } 744 | } 745 | layer { 746 | name: "group1_block0_conv1_bn" 747 | type: "BatchNorm" 748 | bottom: "group1_block0_conv1" 749 | top: "group1_block0_conv1" 750 | param { 751 | lr_mult: 0 752 | decay_mult: 0 753 | } 754 | param { 755 | lr_mult: 0 756 | decay_mult: 0 757 | } 758 | param { 759 | lr_mult: 0 760 | decay_mult: 0 761 | } 762 | batch_norm_param { 763 | moving_average_fraction: 0.9 764 | } 765 | } 766 | layer { 767 | name: "group1_block0_conv1_scale" 768 | type: "Scale" 769 | bottom: "group1_block0_conv1" 770 | top: "group1_block0_conv1" 771 | scale_param { 772 | bias_term: true 773 | } 774 | } 775 | layer { 776 | name: "group1_block0_proj" 777 | type: "Convolution" 778 | bottom: "group0_block8_sum" 779 | top: "group1_block0_proj" 780 | param { 781 | lr_mult: 1 782 | decay_mult: 1 783 | } 784 | convolution_param { 785 | num_output: 64 786 | pad: 0 787 | kernel_size: 2 788 | stride: 2 789 | weight_filler { 790 | type: "msra" 791 | } 792 | } 793 | } 794 | layer { 795 | name: "group1_block0_proj_bn" 796 | type: "BatchNorm" 797 | bottom: "group1_block0_proj" 798 | top: "group1_block0_proj" 799 | param { 800 | lr_mult: 0 801 | decay_mult: 0 802 | } 803 | param { 804 | lr_mult: 0 805 | decay_mult: 0 806 | } 807 | param { 808 | lr_mult: 0 809 | decay_mult: 0 810 | } 811 | batch_norm_param { 812 | moving_average_fraction: 0.9 813 | } 814 | } 815 | layer { 816 | name: "group1_block0_proj_scale" 817 | type: "Scale" 818 | bottom: "group1_block0_proj" 819 | top: "group1_block0_proj" 820 | scale_param { 821 | bias_term: true 822 | } 823 | } 824 | layer { 825 | name: "group1_block0_sum" 826 | type: "Eltwise" 827 | bottom: "group1_block0_proj" 828 | bottom: "group1_block0_conv1" 829 | top: "group1_block0_sum" 830 | eltwise_param { 831 | operation: SUM 832 | } 833 | } 834 | layer { 835 | name: "group1_block1_conv0" 836 | type: "Convolution" 837 | bottom: "group1_block0_sum" 838 | top: "group1_block1_conv0" 839 | param { 840 | lr_mult: 1 841 | decay_mult: 1 842 | } 843 | convolution_param { 844 | num_output: 64 845 | pad: 1 846 | kernel_size: 3 847 | stride: 1 848 | weight_filler { 849 | type: "msra" 850 | } 851 | } 852 | } 853 | layer { 854 | name: "group1_block1_conv0_bn" 855 | type: "BatchNorm" 856 | bottom: "group1_block1_conv0" 857 | top: "group1_block1_conv0" 858 | param { 859 | lr_mult: 0 860 | decay_mult: 0 861 | } 862 | param { 863 | lr_mult: 0 864 | decay_mult: 0 865 | } 866 | param { 867 | lr_mult: 0 868 | decay_mult: 0 869 | } 870 | batch_norm_param { 871 | moving_average_fraction: 0.9 872 | } 873 | } 874 | layer { 875 | name: "group1_block1_conv0_scale" 876 | type: "Scale" 877 | bottom: "group1_block1_conv0" 878 | top: "group1_block1_conv0" 879 | scale_param { 880 | bias_term: true 881 | } 882 | } 883 | layer { 884 | name: "group1_block1_conv0_relu" 885 | type: "ReLU" 886 | bottom: "group1_block1_conv0" 887 | top: "group1_block1_conv0" 888 | } 889 | layer { 890 | name: "group1_block1_conv1" 891 | type: "Convolution" 892 | bottom: "group1_block1_conv0" 893 | top: "group1_block1_conv1" 894 | param { 895 | lr_mult: 1 896 | decay_mult: 1 897 | } 898 | convolution_param { 899 | num_output: 64 900 | pad: 1 901 | kernel_size: 3 902 | stride: 1 903 | weight_filler { 904 | type: "msra" 905 | } 906 | } 907 | } 908 | layer { 909 | name: "group1_block1_conv1_bn" 910 | type: "BatchNorm" 911 | bottom: "group1_block1_conv1" 912 | top: "group1_block1_conv1" 913 | param { 914 | lr_mult: 0 915 | decay_mult: 0 916 | } 917 | param { 918 | lr_mult: 0 919 | decay_mult: 0 920 | } 921 | param { 922 | lr_mult: 0 923 | decay_mult: 0 924 | } 925 | batch_norm_param { 926 | moving_average_fraction: 0.9 927 | } 928 | } 929 | layer { 930 | name: "group1_block1_conv1_scale" 931 | type: "Scale" 932 | bottom: "group1_block1_conv1" 933 | top: "group1_block1_conv1" 934 | scale_param { 935 | bias_term: true 936 | } 937 | } 938 | layer { 939 | name: "group1_block1_sum" 940 | type: "Eltwise" 941 | bottom: "group1_block1_conv1" 942 | bottom: "group1_block0_sum" 943 | top: "group1_block1_sum" 944 | eltwise_param { 945 | operation: SUM 946 | } 947 | } 948 | layer { 949 | name: "group1_block2_conv0" 950 | type: "Convolution" 951 | bottom: "group1_block1_sum" 952 | top: "group1_block2_conv0" 953 | param { 954 | lr_mult: 1 955 | decay_mult: 1 956 | } 957 | convolution_param { 958 | num_output: 64 959 | pad: 1 960 | kernel_size: 3 961 | stride: 1 962 | weight_filler { 963 | type: "msra" 964 | } 965 | } 966 | } 967 | layer { 968 | name: "group1_block2_conv0_bn" 969 | type: "BatchNorm" 970 | bottom: "group1_block2_conv0" 971 | top: "group1_block2_conv0" 972 | param { 973 | lr_mult: 0 974 | decay_mult: 0 975 | } 976 | param { 977 | lr_mult: 0 978 | decay_mult: 0 979 | } 980 | param { 981 | lr_mult: 0 982 | decay_mult: 0 983 | } 984 | batch_norm_param { 985 | moving_average_fraction: 0.9 986 | } 987 | } 988 | layer { 989 | name: "group1_block2_conv0_scale" 990 | type: "Scale" 991 | bottom: "group1_block2_conv0" 992 | top: "group1_block2_conv0" 993 | scale_param { 994 | bias_term: true 995 | } 996 | } 997 | layer { 998 | name: "group1_block2_conv0_relu" 999 | type: "ReLU" 1000 | bottom: "group1_block2_conv0" 1001 | top: "group1_block2_conv0" 1002 | } 1003 | layer { 1004 | name: "group1_block2_conv1" 1005 | type: "Convolution" 1006 | bottom: "group1_block2_conv0" 1007 | top: "group1_block2_conv1" 1008 | param { 1009 | lr_mult: 1 1010 | decay_mult: 1 1011 | } 1012 | convolution_param { 1013 | num_output: 64 1014 | pad: 1 1015 | kernel_size: 3 1016 | stride: 1 1017 | weight_filler { 1018 | type: "msra" 1019 | } 1020 | } 1021 | } 1022 | layer { 1023 | name: "group1_block2_conv1_bn" 1024 | type: "BatchNorm" 1025 | bottom: "group1_block2_conv1" 1026 | top: "group1_block2_conv1" 1027 | param { 1028 | lr_mult: 0 1029 | decay_mult: 0 1030 | } 1031 | param { 1032 | lr_mult: 0 1033 | decay_mult: 0 1034 | } 1035 | param { 1036 | lr_mult: 0 1037 | decay_mult: 0 1038 | } 1039 | batch_norm_param { 1040 | moving_average_fraction: 0.9 1041 | } 1042 | } 1043 | layer { 1044 | name: "group1_block2_conv1_scale" 1045 | type: "Scale" 1046 | bottom: "group1_block2_conv1" 1047 | top: "group1_block2_conv1" 1048 | scale_param { 1049 | bias_term: true 1050 | } 1051 | } 1052 | layer { 1053 | name: "group1_block2_sum" 1054 | type: "Eltwise" 1055 | bottom: "group1_block2_conv1" 1056 | bottom: "group1_block1_sum" 1057 | top: "group1_block2_sum" 1058 | eltwise_param { 1059 | operation: SUM 1060 | } 1061 | } 1062 | layer { 1063 | name: "group1_block3_conv0" 1064 | type: "Convolution" 1065 | bottom: "group1_block2_sum" 1066 | top: "group1_block3_conv0" 1067 | param { 1068 | lr_mult: 1 1069 | decay_mult: 1 1070 | } 1071 | convolution_param { 1072 | num_output: 64 1073 | pad: 1 1074 | kernel_size: 3 1075 | stride: 1 1076 | weight_filler { 1077 | type: "msra" 1078 | } 1079 | } 1080 | } 1081 | layer { 1082 | name: "group1_block3_conv0_bn" 1083 | type: "BatchNorm" 1084 | bottom: "group1_block3_conv0" 1085 | top: "group1_block3_conv0" 1086 | param { 1087 | lr_mult: 0 1088 | decay_mult: 0 1089 | } 1090 | param { 1091 | lr_mult: 0 1092 | decay_mult: 0 1093 | } 1094 | param { 1095 | lr_mult: 0 1096 | decay_mult: 0 1097 | } 1098 | batch_norm_param { 1099 | moving_average_fraction: 0.9 1100 | } 1101 | } 1102 | layer { 1103 | name: "group1_block3_conv0_scale" 1104 | type: "Scale" 1105 | bottom: "group1_block3_conv0" 1106 | top: "group1_block3_conv0" 1107 | scale_param { 1108 | bias_term: true 1109 | } 1110 | } 1111 | layer { 1112 | name: "group1_block3_conv0_relu" 1113 | type: "ReLU" 1114 | bottom: "group1_block3_conv0" 1115 | top: "group1_block3_conv0" 1116 | } 1117 | layer { 1118 | name: "group1_block3_conv1" 1119 | type: "Convolution" 1120 | bottom: "group1_block3_conv0" 1121 | top: "group1_block3_conv1" 1122 | param { 1123 | lr_mult: 1 1124 | decay_mult: 1 1125 | } 1126 | convolution_param { 1127 | num_output: 64 1128 | pad: 1 1129 | kernel_size: 3 1130 | stride: 1 1131 | weight_filler { 1132 | type: "msra" 1133 | } 1134 | } 1135 | } 1136 | layer { 1137 | name: "group1_block3_conv1_bn" 1138 | type: "BatchNorm" 1139 | bottom: "group1_block3_conv1" 1140 | top: "group1_block3_conv1" 1141 | param { 1142 | lr_mult: 0 1143 | decay_mult: 0 1144 | } 1145 | param { 1146 | lr_mult: 0 1147 | decay_mult: 0 1148 | } 1149 | param { 1150 | lr_mult: 0 1151 | decay_mult: 0 1152 | } 1153 | batch_norm_param { 1154 | moving_average_fraction: 0.9 1155 | } 1156 | } 1157 | layer { 1158 | name: "group1_block3_conv1_scale" 1159 | type: "Scale" 1160 | bottom: "group1_block3_conv1" 1161 | top: "group1_block3_conv1" 1162 | scale_param { 1163 | bias_term: true 1164 | } 1165 | } 1166 | layer { 1167 | name: "group1_block3_sum" 1168 | type: "Eltwise" 1169 | bottom: "group1_block3_conv1" 1170 | bottom: "group1_block2_sum" 1171 | top: "group1_block3_sum" 1172 | eltwise_param { 1173 | operation: SUM 1174 | } 1175 | } 1176 | layer { 1177 | name: "group1_block8_conv0" 1178 | type: "Convolution" 1179 | bottom: "group1_block3_sum" 1180 | top: "group1_block8_conv0" 1181 | param { 1182 | lr_mult: 1 1183 | decay_mult: 1 1184 | } 1185 | convolution_param { 1186 | num_output: 64 1187 | pad: 1 1188 | kernel_size: 3 1189 | stride: 1 1190 | weight_filler { 1191 | type: "msra" 1192 | } 1193 | } 1194 | } 1195 | layer { 1196 | name: "group1_block8_conv0_bn" 1197 | type: "BatchNorm" 1198 | bottom: "group1_block8_conv0" 1199 | top: "group1_block8_conv0" 1200 | param { 1201 | lr_mult: 0 1202 | decay_mult: 0 1203 | } 1204 | param { 1205 | lr_mult: 0 1206 | decay_mult: 0 1207 | } 1208 | param { 1209 | lr_mult: 0 1210 | decay_mult: 0 1211 | } 1212 | batch_norm_param { 1213 | moving_average_fraction: 0.9 1214 | } 1215 | } 1216 | layer { 1217 | name: "group1_block8_conv0_scale" 1218 | type: "Scale" 1219 | bottom: "group1_block8_conv0" 1220 | top: "group1_block8_conv0" 1221 | scale_param { 1222 | bias_term: true 1223 | } 1224 | } 1225 | layer { 1226 | name: "group1_block8_conv0_relu" 1227 | type: "ReLU" 1228 | bottom: "group1_block8_conv0" 1229 | top: "group1_block8_conv0" 1230 | } 1231 | layer { 1232 | name: "group1_block8_conv1" 1233 | type: "Convolution" 1234 | bottom: "group1_block8_conv0" 1235 | top: "group1_block8_conv1" 1236 | param { 1237 | lr_mult: 1 1238 | decay_mult: 1 1239 | } 1240 | convolution_param { 1241 | num_output: 64 1242 | pad: 1 1243 | kernel_size: 3 1244 | stride: 1 1245 | weight_filler { 1246 | type: "msra" 1247 | } 1248 | } 1249 | } 1250 | layer { 1251 | name: "group1_block8_conv1_bn" 1252 | type: "BatchNorm" 1253 | bottom: "group1_block8_conv1" 1254 | top: "group1_block8_conv1" 1255 | param { 1256 | lr_mult: 0 1257 | decay_mult: 0 1258 | } 1259 | param { 1260 | lr_mult: 0 1261 | decay_mult: 0 1262 | } 1263 | param { 1264 | lr_mult: 0 1265 | decay_mult: 0 1266 | } 1267 | batch_norm_param { 1268 | moving_average_fraction: 0.9 1269 | } 1270 | } 1271 | layer { 1272 | name: "group1_block8_conv1_scale" 1273 | type: "Scale" 1274 | bottom: "group1_block8_conv1" 1275 | top: "group1_block8_conv1" 1276 | scale_param { 1277 | bias_term: true 1278 | } 1279 | } 1280 | layer { 1281 | name: "group1_block8_sum" 1282 | type: "Eltwise" 1283 | bottom: "group1_block8_conv1" 1284 | bottom: "group1_block3_sum" 1285 | top: "group1_block8_sum" 1286 | eltwise_param { 1287 | operation: SUM 1288 | } 1289 | } 1290 | layer { 1291 | name: "group2_block0_conv0" 1292 | type: "Convolution" 1293 | bottom: "group1_block8_sum" 1294 | top: "group2_block0_conv0" 1295 | param { 1296 | lr_mult: 1 1297 | decay_mult: 1 1298 | } 1299 | convolution_param { 1300 | num_output: 256 1301 | pad: 1 1302 | kernel_size: 3 1303 | stride: 2 1304 | weight_filler { 1305 | type: "msra" 1306 | } 1307 | } 1308 | } 1309 | layer { 1310 | name: "group2_block0_conv0_bn" 1311 | type: "BatchNorm" 1312 | bottom: "group2_block0_conv0" 1313 | top: "group2_block0_conv0" 1314 | param { 1315 | lr_mult: 0 1316 | decay_mult: 0 1317 | } 1318 | param { 1319 | lr_mult: 0 1320 | decay_mult: 0 1321 | } 1322 | param { 1323 | lr_mult: 0 1324 | decay_mult: 0 1325 | } 1326 | batch_norm_param { 1327 | moving_average_fraction: 0.9 1328 | } 1329 | } 1330 | layer { 1331 | name: "group2_block0_conv0_scale" 1332 | type: "Scale" 1333 | bottom: "group2_block0_conv0" 1334 | top: "group2_block0_conv0" 1335 | scale_param { 1336 | bias_term: true 1337 | } 1338 | } 1339 | layer { 1340 | name: "group2_block0_conv0_relu" 1341 | type: "ReLU" 1342 | bottom: "group2_block0_conv0" 1343 | top: "group2_block0_conv0" 1344 | } 1345 | layer { 1346 | name: "group2_block0_conv1" 1347 | type: "Convolution" 1348 | bottom: "group2_block0_conv0" 1349 | top: "group2_block0_conv1" 1350 | param { 1351 | lr_mult: 1 1352 | decay_mult: 1 1353 | } 1354 | convolution_param { 1355 | num_output: 256 1356 | pad: 1 1357 | kernel_size: 3 1358 | stride: 1 1359 | weight_filler { 1360 | type: "msra" 1361 | } 1362 | } 1363 | } 1364 | layer { 1365 | name: "group2_block0_conv1_bn" 1366 | type: "BatchNorm" 1367 | bottom: "group2_block0_conv1" 1368 | top: "group2_block0_conv1" 1369 | param { 1370 | lr_mult: 0 1371 | decay_mult: 0 1372 | } 1373 | param { 1374 | lr_mult: 0 1375 | decay_mult: 0 1376 | } 1377 | param { 1378 | lr_mult: 0 1379 | decay_mult: 0 1380 | } 1381 | batch_norm_param { 1382 | moving_average_fraction: 0.9 1383 | } 1384 | } 1385 | layer { 1386 | name: "group2_block0_conv1_scale" 1387 | type: "Scale" 1388 | bottom: "group2_block0_conv1" 1389 | top: "group2_block0_conv1" 1390 | scale_param { 1391 | bias_term: true 1392 | } 1393 | } 1394 | layer { 1395 | name: "group2_block0_proj" 1396 | type: "Convolution" 1397 | bottom: "group1_block8_sum" 1398 | top: "group2_block0_proj" 1399 | param { 1400 | lr_mult: 1 1401 | decay_mult: 1 1402 | } 1403 | convolution_param { 1404 | num_output: 256 1405 | pad: 0 1406 | kernel_size: 2 1407 | stride: 2 1408 | weight_filler { 1409 | type: "msra" 1410 | } 1411 | } 1412 | } 1413 | layer { 1414 | name: "group2_block0_proj_bn" 1415 | type: "BatchNorm" 1416 | bottom: "group2_block0_proj" 1417 | top: "group2_block0_proj" 1418 | param { 1419 | lr_mult: 0 1420 | decay_mult: 0 1421 | } 1422 | param { 1423 | lr_mult: 0 1424 | decay_mult: 0 1425 | } 1426 | param { 1427 | lr_mult: 0 1428 | decay_mult: 0 1429 | } 1430 | batch_norm_param { 1431 | moving_average_fraction: 0.9 1432 | } 1433 | } 1434 | layer { 1435 | name: "group2_block0_proj_scale" 1436 | type: "Scale" 1437 | bottom: "group2_block0_proj" 1438 | top: "group2_block0_proj" 1439 | scale_param { 1440 | bias_term: true 1441 | } 1442 | } 1443 | layer { 1444 | name: "group2_block0_sum" 1445 | type: "Eltwise" 1446 | bottom: "group2_block0_proj" 1447 | bottom: "group2_block0_conv1" 1448 | top: "group2_block0_sum" 1449 | eltwise_param { 1450 | operation: SUM 1451 | } 1452 | } 1453 | layer { 1454 | name: "group2_block1_conv0" 1455 | type: "Convolution" 1456 | bottom: "group2_block0_sum" 1457 | top: "group2_block1_conv0" 1458 | param { 1459 | lr_mult: 1 1460 | decay_mult: 1 1461 | } 1462 | convolution_param { 1463 | num_output: 256 1464 | pad: 1 1465 | kernel_size: 3 1466 | stride: 1 1467 | weight_filler { 1468 | type: "msra" 1469 | } 1470 | } 1471 | } 1472 | layer { 1473 | name: "group2_block1_conv0_bn" 1474 | type: "BatchNorm" 1475 | bottom: "group2_block1_conv0" 1476 | top: "group2_block1_conv0" 1477 | param { 1478 | lr_mult: 0 1479 | decay_mult: 0 1480 | } 1481 | param { 1482 | lr_mult: 0 1483 | decay_mult: 0 1484 | } 1485 | param { 1486 | lr_mult: 0 1487 | decay_mult: 0 1488 | } 1489 | batch_norm_param { 1490 | moving_average_fraction: 0.9 1491 | } 1492 | } 1493 | layer { 1494 | name: "group2_block1_conv0_scale" 1495 | type: "Scale" 1496 | bottom: "group2_block1_conv0" 1497 | top: "group2_block1_conv0" 1498 | scale_param { 1499 | bias_term: true 1500 | } 1501 | } 1502 | layer { 1503 | name: "group2_block1_conv0_relu" 1504 | type: "ReLU" 1505 | bottom: "group2_block1_conv0" 1506 | top: "group2_block1_conv0" 1507 | } 1508 | layer { 1509 | name: "group2_block1_conv1" 1510 | type: "Convolution" 1511 | bottom: "group2_block1_conv0" 1512 | top: "group2_block1_conv1" 1513 | param { 1514 | lr_mult: 1 1515 | decay_mult: 1 1516 | } 1517 | convolution_param { 1518 | num_output: 256 1519 | pad: 1 1520 | kernel_size: 3 1521 | stride: 1 1522 | weight_filler { 1523 | type: "msra" 1524 | } 1525 | } 1526 | } 1527 | layer { 1528 | name: "group2_block1_conv1_bn" 1529 | type: "BatchNorm" 1530 | bottom: "group2_block1_conv1" 1531 | top: "group2_block1_conv1" 1532 | param { 1533 | lr_mult: 0 1534 | decay_mult: 0 1535 | } 1536 | param { 1537 | lr_mult: 0 1538 | decay_mult: 0 1539 | } 1540 | param { 1541 | lr_mult: 0 1542 | decay_mult: 0 1543 | } 1544 | batch_norm_param { 1545 | moving_average_fraction: 0.9 1546 | } 1547 | } 1548 | layer { 1549 | name: "group2_block1_conv1_scale" 1550 | type: "Scale" 1551 | bottom: "group2_block1_conv1" 1552 | top: "group2_block1_conv1" 1553 | scale_param { 1554 | bias_term: true 1555 | } 1556 | } 1557 | layer { 1558 | name: "group2_block1_sum" 1559 | type: "Eltwise" 1560 | bottom: "group2_block1_conv1" 1561 | bottom: "group2_block0_sum" 1562 | top: "group2_block1_sum" 1563 | eltwise_param { 1564 | operation: SUM 1565 | } 1566 | } 1567 | layer { 1568 | name: "group2_block2_conv0" 1569 | type: "Convolution" 1570 | bottom: "group2_block1_sum" 1571 | top: "group2_block2_conv0" 1572 | param { 1573 | lr_mult: 1 1574 | decay_mult: 1 1575 | } 1576 | convolution_param { 1577 | num_output: 256 1578 | pad: 1 1579 | kernel_size: 3 1580 | stride: 1 1581 | weight_filler { 1582 | type: "msra" 1583 | } 1584 | } 1585 | } 1586 | layer { 1587 | name: "group2_block2_conv0_bn" 1588 | type: "BatchNorm" 1589 | bottom: "group2_block2_conv0" 1590 | top: "group2_block2_conv0" 1591 | param { 1592 | lr_mult: 0 1593 | decay_mult: 0 1594 | } 1595 | param { 1596 | lr_mult: 0 1597 | decay_mult: 0 1598 | } 1599 | param { 1600 | lr_mult: 0 1601 | decay_mult: 0 1602 | } 1603 | batch_norm_param { 1604 | moving_average_fraction: 0.9 1605 | } 1606 | } 1607 | layer { 1608 | name: "group2_block2_conv0_scale" 1609 | type: "Scale" 1610 | bottom: "group2_block2_conv0" 1611 | top: "group2_block2_conv0" 1612 | scale_param { 1613 | bias_term: true 1614 | } 1615 | } 1616 | layer { 1617 | name: "group2_block2_conv0_relu" 1618 | type: "ReLU" 1619 | bottom: "group2_block2_conv0" 1620 | top: "group2_block2_conv0" 1621 | } 1622 | layer { 1623 | name: "group2_block2_conv1" 1624 | type: "Convolution" 1625 | bottom: "group2_block2_conv0" 1626 | top: "group2_block2_conv1" 1627 | param { 1628 | lr_mult: 1 1629 | decay_mult: 1 1630 | } 1631 | convolution_param { 1632 | num_output: 256 1633 | pad: 1 1634 | kernel_size: 3 1635 | stride: 1 1636 | weight_filler { 1637 | type: "msra" 1638 | } 1639 | } 1640 | } 1641 | layer { 1642 | name: "group2_block2_conv1_bn" 1643 | type: "BatchNorm" 1644 | bottom: "group2_block2_conv1" 1645 | top: "group2_block2_conv1" 1646 | param { 1647 | lr_mult: 0 1648 | decay_mult: 0 1649 | } 1650 | param { 1651 | lr_mult: 0 1652 | decay_mult: 0 1653 | } 1654 | param { 1655 | lr_mult: 0 1656 | decay_mult: 0 1657 | } 1658 | batch_norm_param { 1659 | moving_average_fraction: 0.9 1660 | } 1661 | } 1662 | layer { 1663 | name: "group2_block2_conv1_scale" 1664 | type: "Scale" 1665 | bottom: "group2_block2_conv1" 1666 | top: "group2_block2_conv1" 1667 | scale_param { 1668 | bias_term: true 1669 | } 1670 | } 1671 | layer { 1672 | name: "group2_block2_sum" 1673 | type: "Eltwise" 1674 | bottom: "group2_block2_conv1" 1675 | bottom: "group2_block1_sum" 1676 | top: "group2_block2_sum" 1677 | eltwise_param { 1678 | operation: SUM 1679 | } 1680 | } 1681 | layer { 1682 | name: "group2_block3_conv0" 1683 | type: "Convolution" 1684 | bottom: "group2_block2_sum" 1685 | top: "group2_block3_conv0" 1686 | param { 1687 | lr_mult: 1 1688 | decay_mult: 1 1689 | } 1690 | convolution_param { 1691 | num_output: 256 1692 | pad: 1 1693 | kernel_size: 3 1694 | stride: 1 1695 | weight_filler { 1696 | type: "msra" 1697 | } 1698 | } 1699 | } 1700 | layer { 1701 | name: "group2_block3_conv0_bn" 1702 | type: "BatchNorm" 1703 | bottom: "group2_block3_conv0" 1704 | top: "group2_block3_conv0" 1705 | param { 1706 | lr_mult: 0 1707 | decay_mult: 0 1708 | } 1709 | param { 1710 | lr_mult: 0 1711 | decay_mult: 0 1712 | } 1713 | param { 1714 | lr_mult: 0 1715 | decay_mult: 0 1716 | } 1717 | batch_norm_param { 1718 | moving_average_fraction: 0.9 1719 | } 1720 | } 1721 | layer { 1722 | name: "group2_block3_conv0_scale" 1723 | type: "Scale" 1724 | bottom: "group2_block3_conv0" 1725 | top: "group2_block3_conv0" 1726 | scale_param { 1727 | bias_term: true 1728 | } 1729 | } 1730 | layer { 1731 | name: "group2_block3_conv0_relu" 1732 | type: "ReLU" 1733 | bottom: "group2_block3_conv0" 1734 | top: "group2_block3_conv0" 1735 | } 1736 | layer { 1737 | name: "group2_block3_conv1" 1738 | type: "Convolution" 1739 | bottom: "group2_block3_conv0" 1740 | top: "group2_block3_conv1" 1741 | param { 1742 | lr_mult: 1 1743 | decay_mult: 1 1744 | } 1745 | convolution_param { 1746 | num_output: 256 1747 | pad: 1 1748 | kernel_size: 3 1749 | stride: 1 1750 | weight_filler { 1751 | type: "msra" 1752 | } 1753 | } 1754 | } 1755 | layer { 1756 | name: "group2_block3_conv1_bn" 1757 | type: "BatchNorm" 1758 | bottom: "group2_block3_conv1" 1759 | top: "group2_block3_conv1" 1760 | param { 1761 | lr_mult: 0 1762 | decay_mult: 0 1763 | } 1764 | param { 1765 | lr_mult: 0 1766 | decay_mult: 0 1767 | } 1768 | param { 1769 | lr_mult: 0 1770 | decay_mult: 0 1771 | } 1772 | batch_norm_param { 1773 | moving_average_fraction: 0.9 1774 | } 1775 | } 1776 | layer { 1777 | name: "group2_block3_conv1_scale" 1778 | type: "Scale" 1779 | bottom: "group2_block3_conv1" 1780 | top: "group2_block3_conv1" 1781 | scale_param { 1782 | bias_term: true 1783 | } 1784 | } 1785 | layer { 1786 | name: "group2_block3_sum" 1787 | type: "Eltwise" 1788 | bottom: "group2_block3_conv1" 1789 | bottom: "group2_block2_sum" 1790 | top: "group2_block3_sum" 1791 | eltwise_param { 1792 | operation: SUM 1793 | } 1794 | } 1795 | layer { 1796 | name: "group2_block8_conv0" 1797 | type: "Convolution" 1798 | bottom: "group2_block3_sum" 1799 | top: "group2_block8_conv0" 1800 | param { 1801 | lr_mult: 1 1802 | decay_mult: 1 1803 | } 1804 | convolution_param { 1805 | num_output: 256 1806 | pad: 1 1807 | kernel_size: 3 1808 | stride: 1 1809 | weight_filler { 1810 | type: "msra" 1811 | } 1812 | } 1813 | } 1814 | layer { 1815 | name: "group2_block8_conv0_bn" 1816 | type: "BatchNorm" 1817 | bottom: "group2_block8_conv0" 1818 | top: "group2_block8_conv0" 1819 | param { 1820 | lr_mult: 0 1821 | decay_mult: 0 1822 | } 1823 | param { 1824 | lr_mult: 0 1825 | decay_mult: 0 1826 | } 1827 | param { 1828 | lr_mult: 0 1829 | decay_mult: 0 1830 | } 1831 | batch_norm_param { 1832 | moving_average_fraction: 0.9 1833 | } 1834 | } 1835 | layer { 1836 | name: "group2_block8_conv0_scale" 1837 | type: "Scale" 1838 | bottom: "group2_block8_conv0" 1839 | top: "group2_block8_conv0" 1840 | scale_param { 1841 | bias_term: true 1842 | } 1843 | } 1844 | layer { 1845 | name: "group2_block8_conv0_relu" 1846 | type: "ReLU" 1847 | bottom: "group2_block8_conv0" 1848 | top: "group2_block8_conv0" 1849 | } 1850 | layer { 1851 | name: "group2_block8_conv1" 1852 | type: "Convolution" 1853 | bottom: "group2_block8_conv0" 1854 | top: "group2_block8_conv1" 1855 | param { 1856 | lr_mult: 1 1857 | decay_mult: 1 1858 | } 1859 | convolution_param { 1860 | num_output: 256 1861 | pad: 1 1862 | kernel_size: 3 1863 | stride: 1 1864 | weight_filler { 1865 | type: "msra" 1866 | } 1867 | } 1868 | } 1869 | layer { 1870 | name: "group2_block8_conv1_bn" 1871 | type: "BatchNorm" 1872 | bottom: "group2_block8_conv1" 1873 | top: "group2_block8_conv1" 1874 | param { 1875 | lr_mult: 0 1876 | decay_mult: 0 1877 | } 1878 | param { 1879 | lr_mult: 0 1880 | decay_mult: 0 1881 | } 1882 | param { 1883 | lr_mult: 0 1884 | decay_mult: 0 1885 | } 1886 | batch_norm_param { 1887 | moving_average_fraction: 0.9 1888 | } 1889 | } 1890 | layer { 1891 | name: "group2_block8_conv1_scale" 1892 | type: "Scale" 1893 | bottom: "group2_block8_conv1" 1894 | top: "group2_block8_conv1" 1895 | scale_param { 1896 | bias_term: true 1897 | } 1898 | } 1899 | layer { 1900 | name: "group2_block8_sum" 1901 | type: "Eltwise" 1902 | bottom: "group2_block8_conv1" 1903 | bottom: "group2_block3_sum" 1904 | top: "group2_block8_sum" 1905 | eltwise_param { 1906 | operation: SUM 1907 | } 1908 | } 1909 | layer { 1910 | name: "global_avg_pool" 1911 | type: "Pooling" 1912 | bottom: "group2_block8_sum" 1913 | top: "global_avg_pool" 1914 | pooling_param { 1915 | pool: AVE 1916 | global_pooling: true 1917 | } 1918 | } 1919 | layer { 1920 | name: "fc" 1921 | type: "InnerProduct" 1922 | bottom: "global_avg_pool" 1923 | top: "fc" 1924 | param { 1925 | lr_mult: 1 1926 | decay_mult: 1 1927 | } 1928 | param { 1929 | lr_mult: 2 1930 | decay_mult: 0 1931 | } 1932 | inner_product_param { 1933 | num_output: 10 1934 | weight_filler { 1935 | type: "msra" 1936 | } 1937 | bias_filler { 1938 | type: "constant" 1939 | value: 0 1940 | } 1941 | } 1942 | } 1943 | layer { 1944 | name: "loss" 1945 | type: "SoftmaxWithLoss" 1946 | bottom: "fc" 1947 | bottom: "label" 1948 | top: "loss" 1949 | } 1950 | layer { 1951 | name: "softmax" 1952 | type: "Softmax" 1953 | bottom: "fc" 1954 | top: "softmax" 1955 | } 1956 | layer { 1957 | name: "Accuracy" 1958 | type: "Accuracy" 1959 | bottom: "softmax" 1960 | bottom: "label" 1961 | top: "Accuracy" 1962 | } -------------------------------------------------------------------------------- /Cifar/clrsolver.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/skipConnections/architectures/aarch.prototxt" 2 | #net: "examples/skipConnections/architectures/resnet56.prototxt" 3 | #net: "examples/skipConnections/architectures/2ndOrder56.prototxt" 4 | # 5 | test_iter: 200 6 | test_interval: 200 7 | display: 200 8 | test_initialization: false 9 | 10 | lr_policy: "1cycle" # "triangular" 11 | base_lr: xLR1 12 | max_lr: xLR2 13 | stepsize: 20000 14 | max_iter: 20000 15 | 16 | snapshot: 20000 17 | snapshot_prefix: "examples/skipConnections/snapshots/xResnet56" 18 | #snapshot_prefix: "examples/skipConnections/snapshots/range2ndOrder56Mom7" 19 | solver_mode: GPU 20 | 21 | weight_decay: xwd 22 | momentum: xmom 23 | 24 | #regularization_type: "L1" 25 | type: "Nesterov" # "RMSProp" # "Adam" # "AdaGrad" # 26 | #type: "Adam" # "AdaDelta" # 27 | #rms_decay: 0.9 28 | #clip_gradients: 10 29 | #iter_size: 4 30 | #debug_info: true 31 | -------------------------------------------------------------------------------- /Cifar/jsub.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | ./x4.sh g C100Res1Cyc c100Resnet56 1.2 145 70 1e-4 256 0.95 5 | exit 6 | ./x4.sh f C100Res1Cyc c100Resnet56 0.5 25 12 1e-4 128 0.95 7 | exit 8 | ./x4.sh e C100Res1Cyc c100Resnet56 0.5 50 23 1e-4 128 0.95 9 | exit 10 | ./x4.sh c C100Res1Cyc c100Resnet56 1 145 70 1e-4 256 0.95 11 | exit 12 | ./x4.sh b C100Res1Cyc c100Resnet56 0.5 85 41 1e-4 64 0.95 13 | exit 14 | ./x4.sh d C100Res1Cyc c100Resnet56 0.5 50 23 1e-4 128 0.95 15 | exit 16 | ./x4.sh c C100Res1Cyc c100Resnet56 0.9 145 70 1e-4 256 0.95 17 | exit 18 | ./x4.sh p C100Res1024 c100Resnet56 1 150 150 1e-4 256 0.95 19 | exit 20 | ./x4.sh a C100Res1Cyc c100Resnet56 0.9 100 45 1e-4 128 0.95 21 | exit 22 | ./x4.sh m C100Res256 c100Resnet56 1 55 55 1e-4 64 0.95 23 | sleep 30 24 | ./x4.sh n C100Res1024 c100Resnet56 1 130 130 1e-4 256 0.95 25 | sleep 30 26 | ./x4.sh o C100Res512 c100Resnet56 1 100 100 1e-4 128 0.95 27 | exit 28 | ./x4.sh l C100Res512 c100Resnet56 1 50 50 1e-4 128 0.95 29 | exit 30 | ./x4.sh k C100Res256 c100Resnet56 1 75 75 1e-4 64 0.95 31 | sleep 30 32 | ./x4.sh j C100Res1024 c100Resnet56 1 40 40 1e-4 256 0.95 33 | sleep 30 34 | ./x4.sh a C100Res512 c100Resnet56 1 40 40 1e-4 128 0.95 35 | sleep 30 36 | ./x4.sh l C100ResHP c100Resnet56 1 50 50 1e-4 128 0.9 37 | exit 38 | ./x4.sh k C100Res256 c100Resnet56 1 75 75 1e-4 64 0.95 39 | exit 40 | ./x4.sh j C100Res1024 c100Resnet56 1 40 40 1e-4 256 0.95 41 | exit 42 | ./x4.sh i C100ResHP c100Resnet56 1 50 50 1e-4 128 0.97 43 | exit 44 | ./x4.sh h C100ResHP c100Resnet56 1 50 50 3e-4 128 0.95 45 | exit 46 | ./x4.sh g C100ResHP c100Resnet56 1 50 50 1e-6 128 0.95 47 | exit 48 | ./x4.sh f C100ResHP c100Resnet56 1 50 50 1e-5 128 0.95 49 | exit 50 | ./x4.sh e C100ResHP c100Resnet56 1 50 50 1e-4 128 0.95 51 | exit 52 | ./x4.sh d C100ResHP c100Resnet56 0.1 50 50 1e-4 128 0.9 53 | exit 54 | ./x4.sh c C100ResHP c100Resnet56 0.1 50 50 1e-4 128 0.95 55 | exit 56 | ./x4.sh b C100ResHP c100Resnet56 0.1 50 50 1e-4 128 0.97 57 | exit 58 | ./x4.sh a C100ResHP c100Resnet56 0.1 50 50 1e-4 128 0.99 59 | exit 60 | ./x4.sh d C100ResStp c100Resnet56 0.1 800 800 1e-4 128 0.9 61 | exit 62 | ./x4.sh c C100ResStp c100Resnet56 0.1 400 400 1e-4 128 0.9 63 | exit 64 | ./x4.sh b C100ResStp c100Resnet56 0.1 200 200 1e-4 128 0.9 65 | exit 66 | ./x4.sh a C100ResStp c100Resnet56 0.1 100 100 1e-4 128 0.9 67 | exit 68 | ./x4.sh e C100Cyc cifar100 0.01 50 23 3e-3 128 0.95 69 | sleep 30 70 | ./x4.sh f C100Cyc cifar100 0.01 25 12 3e-3 128 0.95 71 | exit 72 | ./x4.sh d C100Step cifar100 0.005 800 800 3e-3 128 0.9 73 | exit 74 | ./x4.sh c C100Step cifar100 0.005 400 400 3e-3 128 0.9 75 | exit 76 | ./x4.sh c C100Step cifar100 0.005 200 200 3e-3 128 0.9 77 | exit 78 | ./x4.sh b C100Step cifar100 0.005 100 100 3e-3 128 0.9 79 | exit 80 | ./x4.sh a C100Step cifar100 0.005 50 50 3e-3 128 0.9 81 | exit 82 | ./x4.sh m C100Cyc cifar100 0.01 50 23 6e-4 128 0.95 83 | exit 84 | ./x4.sh l C100Cyc cifar100 0.02 50 23 6e-4 128 0.95 85 | exit 86 | ./x4.sh j C100Cyc cifar100 0.01 50 23 6e-4 128 0.95 87 | exit 88 | ./x4.sh k C100Cyc cifar100 0.01 25 12 6e-4 128 0.95 89 | exit 90 | ./x4.sh i C100Cyc cifar100 0.01 100 47 6e-4 128 0.95 91 | exit 92 | ./x4.sh h C100Cyc cifar100 0.01 200 95 6e-4 128 0.95 93 | exit 94 | ./x4.sh g C100Cyc cifar100 0.007 200 95 6e-4 128 0.95 95 | exit 96 | ./x4.sh f C100Cyc cifar100 0.01 200 95 6e-4 128 0.95 97 | exit 98 | ./x4.sh e C100Cyc cifar100 0.04 200 95 6e-4 128 0.95 99 | exit 100 | ./x4.sh d C100Cyc cifar100 0.02 200 95 6e-4 128 0.9 101 | exit 102 | ./x4.sh c C100Cyc cifar100 0.02 200 95 6e-4 128 0.97 103 | exit 104 | ./x4.sh b C100Cyc cifar100 0.02 200 95 6e-4 128 0.99 105 | exit 106 | ./x4.sh a C100Cyc cifar100 0.02 200 95 6e-4 128 0.95 107 | exit 108 | ./x4.sh n C100TBS cifar100 0.02 125 125 6e-4 512 0.95 109 | exit 110 | ./x4.sh m C100TBS cifar100 0.02 150 150 6e-4 512 0.95 111 | exit 112 | OA./x4.sh l C100TBS cifar100 0.02 125 125 6e-4 256 0.95 113 | exit 114 | ./x4.sh k C100TBS cifar100 0.02 75 75 6e-4 64 0.95 115 | exit 116 | ./x4.sh j C100CLR cifar100 0.02 100 100 1e-4 128 0.95 117 | exit 118 | ./x4.sh i C100CLR cifar100 0.02 100 100 3e-3 128 0.95 119 | exit 120 | ./x4.sh h C100CLR cifar100 0.02 100 100 6e-4 128 0.95 121 | exit 122 | ./x4.sh g C100CLR cifar100 0.04 100 100 6e-4 128 0.95 123 | exit 124 | ./x4.sh f C100CLR cifar100 0.04 100 100 3e-4 128 0.95 125 | exit 126 | ./x4.sh e C100CLR cifar100 0.04 100 100 3e-3 128 0.95 127 | exit 128 | ./x4.sh d C100CLR cifar100 0.04 100 100 1e-3 128 0.95 129 | exit 130 | ./x4.sh c C100CLR cifar100 0.02 100 100 1e-3 128 0.95 131 | exit 132 | ./x4.sh d Wide1Cyc wide32cifar 0.5 25 12 1e-4 128 0.95 133 | exit 134 | ./x4.sh c Wide1Cyc wide32cifar 1 25 12 3e-5 128 0.95 135 | exit 136 | ./x4.sh a Wide1Cyc wide32cifar 1 50 23 1e-4 128 0.95 137 | exit 138 | ./x4.sh c DenOrig genDensenet40 0.1 400 400 1e-4 128 0.9 139 | exit 140 | ./x4.sh b DenOrig genDensenet40 0.1 200 200 1e-4 128 0.9 141 | exit 142 | ./x4.sh a DenOrig genDensenet40 0.1 100 100 1e-4 128 0.9 143 | exit 144 | ./x4.sh d WideOrig wide32cifar 0.1 800 800 1e-4 128 0.9 145 | exit 146 | ./x4.sh c WideOrig wide32cifar 0.1 400 400 1e-4 128 0.9 147 | exit 148 | ./x4.sh b WideOrig wide32cifar 0.1 200 200 1e-4 128 0.9 149 | exit 150 | ./x4.sh a WideOrig wide32cifar 0.1 100 100 1e-4 128 0.9 151 | exit 152 | ./x4.sh a DenTBS512 genDensenet40 4 75 75 1e-6 128 0.9 153 | exit 154 | ./x4.sh j ResCM91 gResnet56 0.1 95 41 1e-4 128 0.9 155 | exit 156 | ./x4.sh i ResCM9585 gResnet56 0.1 95 41 1e-4 128 0.95 157 | exit 158 | ./x4.sh h ResM95 gResnet56 0.1 95 41 1e-4 128 0.95 159 | exit 160 | ./x4.sh g ResM9 gResnet56 0.1 95 41 1e-4 128 0.9 161 | exit 162 | ./x4.sh f ResM85 gResnet56 0.1 95 41 1e-4 128 0.85 163 | exit 164 | ./x4.sh e ResM85 gResnet56 0.8 95 41 1e-4 128 0.85 165 | exit 166 | ./x4.sh d ResM9 gResnet56 0.8 95 41 1e-4 128 0.9 167 | exit 168 | ./x4.sh c ResM95 gResnet56 0.8 95 41 1e-4 128 0.95 169 | exit 170 | ./x4.sh b ResCM91 gResnet56 0.8 95 41 1e-4 128 0.9 171 | exit 172 | ./x4.sh a ResTBS512 gResnet56 0.8 95 41 1e-4 128 0.95 173 | exit 174 | ./x4.sh o 3layCM9785 cifar3 0.005 25 11 3e-3 32 0.95 175 | exit 176 | ./x4.sh p 3layCM91 cifar3 0.005 25 11 3e-3 32 0.9 177 | exit 178 | ./x4.sh l 3layM95 cifar3 0.005 25 11 3e-3 32 0.95 179 | sleep 30 180 | ./x4.sh m 3layM9 cifar3 0.005 25 11 3e-3 32 0.9 181 | sleep 30 182 | ./x4.sh n 3layM85 cifar3 0.005 25 11 3e-3 32 0.85 183 | exit 184 | ./x4.sh h 3layCM91 cifar3 0.005 25 11 3e-3 32 0.9 185 | exit 186 | ./x4.sh f 3layTBS512 cifar3 0.007 50 23 3e-3 128 0.95 187 | exit 188 | ./x4.sh g 3layTBS128 cifar3 0.005 25 11 3e-3 32 0.95 189 | exit 190 | ./x4.sh e 3layTBS512 cifar3 0.01 100 45 3e-3 128 0.95 191 | exit 192 | ./x4.sh d 3layTBS128 cifar3 0.005 50 22 3e-3 32 0.95 193 | exit 194 | ./x4.sh b 3layTBS1024 cifar3 0.005 130 60 3e-3 256 0.95 195 | exit 196 | ./x4.sh a 3layTBS512 cifar3 0.005 100 45 3e-3 128 0.95 197 | exit 198 | ./x4.sh b 3layTBS1024 cifar3 0.005 150 70 3e-3 256 0.95 199 | sleep 20 200 | ./x4.sh c 3layTBS256 cifar3 0.005 75 34 3e-3 64 0.95 201 | exit 202 | ./x4.sh c Den1Cyc genDensenet40 4 50 22 1e-6 128 0.9 203 | exit 204 | ./x4.sh b Den1Cyc genDensenet40 4 75 34 1e-6 128 0.9 205 | exit 206 | ./x4.sh a Den1Cyc genDensenet40 4 100 45 1e-6 128 0.9 207 | exit 208 | ./x4.sh k Den1Cyc genDensenet40 4 150 70 1e-6 128 0.9 209 | exit 210 | ./x4.sh j Den1Cyc genDensenet40 4 100 45 1e-6 64 0.9 211 | sleep 20 212 | ./x4.sh l Den1Cyc genDensenet40 4 150 55 1e-6 128 0.9 213 | exit 214 | ./x4.sh i DenCLR4 genDensenet40 4 50 50 1e-7 64 0.9 215 | sleep 20 216 | ./x4.sh k Den1Cyc genDensenet40 1 100 45 1e-4 64 0.95 217 | exit 218 | ./x4.sh h DenCLR4 genDensenet40 4 50 50 1e-6 64 0.9 219 | exit 220 | ./x4.sh h DenCLRWD6 genDensenet40 1 50 50 1e-6 64 0.95 221 | exit 222 | ./x4.sh g DenCLRM9 genDensenet40 1 50 50 1e-5 64 0.9 223 | exit 224 | ./x4.sh f DenCLR4 genDensenet40 4 50 50 1e-4 64 0.95 225 | exit 226 | ./x4.sh d DenCLRm99 genDensenet40 1 50 50 1e-4 64 0.99 227 | sleep 20 228 | ./x4.sh e DenCLRM97 genDensenet40 1 50 50 1e-4 64 0.97 229 | exit 230 | ./x4.sh a DenCLRWD4 genDensenet40 1 50 50 1e-4 64 0.95 231 | sleep 20 232 | ./x4.sh b DenCLRWD5 genDensenet40 1 50 50 1e-5 64 0.95 233 | sleep 20 234 | ./x4.sh c DenCLRWD3 genDensenet40 1 50 50 1e-3 64 0.95 235 | exit 236 | ./x4.sh i Wide1Cyc wide32cifar 1 100 45 1e-4 128 0.95 237 | sleep 20 238 | ./x4.sh j Wide1Cyc wide32cifar 1 100 45 1e-5 128 0.95 239 | exit 240 | ./x4.sh h WideCLR2 wide32cifar 2 100 100 1e-4 128 0.95 241 | exit 242 | ./x4.sh g WideCLRWD5 wide32cifar 1 100 100 3e-5 128 0.95 243 | exit 244 | ./x4.sh f WideCLRM97 wide32cifar 1 100 100 1e-4 128 0.97 245 | exit 246 | ./x4.sh e WideCLRM99 wide32cifar 1 100 100 1e-4 128 0.99 247 | exit 248 | ./x4.sh b WideCLRWD4 wide32cifar 1 100 100 1e-4 128 0.95 249 | sleep 20 250 | ./x4.sh c WideCLRWD3 wide32cifar 1 100 100 1e-3 128 0.95 251 | sleep 20 252 | ./x4.sh d WideCLRWD5 wide32cifar 1 100 100 1e-5 128 0.95 253 | exit 254 | ./x4.sh a ResWDsnap gResnet56 0.8 20 40 1e-4 128 0.95 255 | exit 256 | ./x4.sh j 3layWDsnap cifar3 0.005 35 35 1e-3 512 0.95 257 | exit 258 | ./x4.sh d ResTBS128 gResnet56 0.4 48 21 1e-4 32 259 | exit 260 | ./x4.sh a ResTBS1024 gResnet56 1 120 51 1e-4 256 261 | sleep 20 262 | ./x4.sh b ResTBS512 gResnet56 0.8 95 41 1e-4 128 263 | sleep 20 264 | ./x4.sh c ResTBS256 gResnet56 0.4 70 31 1e-4 64 265 | exit 266 | ./x4.sh a ResTBS256 gResnet56 0.6 70 31 1e-4 64 267 | exit 268 | ./x4.sh q ResTBS1024 gResnet56 1 120 51 1e-4 256 269 | exit 270 | ./x4.sh p ResTBS1024 gResnet56 0.8 120 51 1e-4 256 271 | exit 272 | ./x4.sh o ResTBS512 gResnet56 0.8 95 41 1e-4 128 273 | exit 274 | ./x4.sh m ResTBS512 gResnet56 0.4 95 41 1e-4 128 275 | exit 276 | ./x4.sh n ResTBS1024 gResnet56 1 75 75 1e-4 256 277 | exit 278 | ./x4.sh l ResTBS512 gResnet56 1 60 60 1e-4 128 279 | exit 280 | ./x4.sh k ResTBS256 gResnet56 0.4 70 31 1e-4 64 281 | exit 282 | ./x4.sh j ResTBS64 gResnet56 1 21 21 1e-4 16 283 | exit 284 | ./x4.sh i ResTBS256 gResnet56 1 45 45 1e-4 64 285 | exit 286 | ./x4.sh e ResTBS128 gResnet56 0.4 40 17 1e-4 32 287 | exit 288 | ./x4.sh h ResTBS64 gResnet56 1 32 32 1e-4 16 289 | exit 290 | ./x4.sh g ResTBS256 gResnet56 1 32 32 1e-4 64 291 | exit 292 | ./x4.sh f ResTBS128 gResnet56 1 32 32 1e-4 32 293 | exit 294 | ./x4.sh e ResTBS128 gResnet56 0.4 48 21 1e-4 32 295 | exit 296 | ./x4.sh d ResTBS128 gResnet56 0.4 64 28 1e-4 32 297 | exit 298 | ./x4.sh c ResTBS128 gResnet56 0.4 8 3 1e-4 32 299 | exit 300 | ./x4.sh b ResTBS128 gResnet56 0.4 16 7 1e-4 32 301 | exit 302 | ./x4.sh a ResTBS128 gResnet56 0.4 32 14 1e-4 32 303 | sleep 20 304 | ./x4.sh b ResTBS128 gResnet56 0.4 16 7 1e-4 32 305 | exit 306 | ./x4.sh a ResTBS64 gResnet56 0.4 20000 9000 1e-4 16 307 | sleep 20 308 | ./x4.sh b ResTBS128 gResnet56 0.4 20000 9000 1e-4 32 309 | sleep 20 310 | ./x4.sh c ResTBS256 gResnet56 0.4 20000 9000 1e-4 64 311 | exit 312 | ./x4.sh f 3layTBS256 cifar3 0.01 10000 10000 3e-3 64 313 | sleep 20 314 | ./x4.sh g 3layTBS128 cifar3 0.01 10000 10000 3e-3 32 315 | sleep 20 316 | ./x4.sh h 3layTBS512 cifar3 0.01 10000 10000 3e-3 128 317 | sleep 20 318 | ./x4.sh i 3layTBS1024 cifar3 0.01 10000 10000 3e-3 256 319 | sleep 20 320 | ./x4.sh j 3layTBS2048 cifar3 0.01 10000 10000 3e-3 512 321 | exit 322 | ./x4.sh d 3layTBS256 cifar3 0.005 10000 4500 3e-3 64 323 | sleep 20 324 | ./x4.sh e 3layTBS128 cifar3 0.005 10000 4500 3e-3 32 325 | exit 326 | ./x4.sh a 3layTBS512 cifar3 0.005 10000 4500 3e-3 128 327 | sleep 20 328 | ./x4.sh b 3layTBS1024 cifar3 0.005 10000 4500 3e-3 256 329 | sleep 20 330 | ./x4.sh c 3layTBS2048 cifar3 0.005 10000 4500 3e-3 512 331 | exit 332 | ./x4.sh n ResTBS32 gResnet56 0.25 10000 4500 1e-4 8 333 | exit 334 | ./x4.sh m ResTBS64 gResnet56 0.25 10000 4500 1e-4 16 335 | exit 336 | ./x4.sh l ResTBS128 gResnet56 0.25 10000 4500 1e-4 32 337 | exit 338 | ./x4.sh k ResTBS256 gResnet56 0.25 10000 4500 1e-4 64 339 | exit 340 | ./x4.sh j 3layTBS64 cifar3 0.005 10000 4500 3e-3 16 341 | exit 342 | ./x4.sh i 3layTBS128 cifar3 0.005 10000 4500 3e-3 32 343 | exit 344 | ./x4.sh h 3layTBS512 cifar3 0.005 10000 4500 3e-3 128 345 | exit 346 | ./x4.sh g 3layTBS1024 cifar3 0.005 10000 4500 3e-3 256 347 | exit 348 | ./x4.sh f 3layTBS1024 cifar3 0.005 10000 10000 3e-3 256 349 | exit 350 | ./x4.sh e 3layTBS512 cifar3 0.005 10000 10000 3e-3 128 351 | exit 352 | ./x4.sh a 3layTBS256 cifar3 0.005 10000 10000 3e-3 64 353 | sleep 30 354 | ./x4.sh b 3layTBS128 cifar3 0.005 10000 10000 3e-3 32 355 | sleep 30 356 | ./x4.sh c 3layTBS64 cifar3 0.005 10000 10000 3e-3 16 357 | sleep 30 358 | ./x4.sh d 3layTBS32 cifar3 0.005 10000 10000 3e-3 8 359 | exit 360 | ./x4.sh k ResTBS256 gResnet56 0.7 10000 4500 1e-4 64 361 | exit 362 | ./x4.sh l ResTBS128 gResnet56 0.4 20000 9000 1e-4 32 363 | sleep 10 364 | ./x4.sh k ResTBS256 gResnet56 0.8 10000 4500 1e-4 64 365 | exit 366 | ./x4.sh i ResTBS128 gResnet56 0.4 10000 4500 1e-4 32 367 | sleep 10 368 | ./x4.sh j ResTBS64 gResnet56 0.25 10000 4500 1e-4 16 369 | exit 370 | ./x4.sh g ResLRTBS64 gResnet56 0.5 5000 5000 1e-5 16 371 | sleep 10 372 | ./x4.sh h ResLRTBS64 gResnet56 0.5 5000 5000 1e-6 16 373 | exit 374 | ./x4.sh e ResLRTBS16 gResnet56 0.5 10000 10000 1e-4 4 375 | sleep 10 376 | ./x4.sh f ResLRTBS32 gResnet56 0.5 5000 5000 1e-4 8 377 | exit 378 | ./x4.sh c ResLRTBS64 gResnet56 0.5 10000 10000 1e-4 16 379 | sleep 10 380 | ./x4.sh d ResLRTBS32 gResnet56 0.5 10000 10000 1e-4 8 381 | exit 382 | ./x4.sh a ResLRTBS128 gResnet56 1 10000 10000 1e-4 32 383 | sleep 10 384 | ./x4.sh b ResLRTBS128 gResnet56 1 5000 5000 1e-4 32 385 | exit 386 | ./x4.sh d ResBS128 gResnet56 1 100 100 1e-4 0.95 0.85 387 | exit 388 | ./x4.sh c ResBS128 gResnet56 1 200 200 1e-4 0.95 0.85 389 | exit 390 | ./x4.sh b ResBS256 gResnet56 1 200 200 1e-4 0.95 0.85 391 | exit 392 | ./x4.sh a ResBS256 gResnet56 1 400 400 1e-4 0.95 0.85 393 | exit 394 | sleep 10 395 | ./x4.sh b ResBS256 gResnet56 1 200 90 1e-4 0.95 0.85 396 | exit 397 | ./x4.sh g ResBS256 gResnet56 1 200 200 1e-4 0.95 0.9 398 | sleep 10 399 | ./x4.sh h ResBS256 gResnet56 1 400 400 1e-4 0.95 0.95 400 | exit 401 | ./x4.sh a 3LayBS64 cifar3 0.01 100 100 4e-3 0.95 0.95 402 | exit 403 | ./x4.sh c 3LayBS64 cifar3 0.02 16000 16000 4e-3 0.95 0.95 404 | exit 405 | ./x4.sh a ResDecCM gResnet56 0.1 16000 16000 1e-4 0.95 0.75 406 | sleep 20 407 | ./x4.sh b ResCycCM gResnet56 0.1 16000 8000 1e-4 0.95 0.85 408 | exit 409 | ./x4.sh c RngWideM95 wide32cifar 1.0 20000 20000 1e-4 0.95 0.95 410 | exit 411 | ./x4.sh b RngWideM97 wide32cifar 1.0 20000 20000 1e-4 0.97 0.97 412 | exit 413 | ./x4.sh a RngWideM99 wide32cifar 1.0 20000 20000 1e-4 0.99 0.99 414 | exit 415 | ./x4.sh e ResDecWD16k gResnet56 0.1 16000 -8000 1e-4 0.95 0.95 416 | sleep 30 417 | ./x4.sh f ResIncWD16k gResnet56 0.1 16000 8000 1e-4 0.95 0.95 418 | exit 419 | ./x4.sh d ResCLRWD3e4 gResnet56 1 10000 10000 3.2e-4 0.97 0.8 420 | exit 421 | ./x4.sh a ResCLRWD4 gResnet56 2 20000 20000 1e-4 0.97 0.8 422 | ./x4.sh b ResCLRWD5 gResnet56 2 20000 20000 1e-5 0.97 0.8 423 | sleep 30 424 | ./x4.sh c ResCLRWD6 gResnet56 2 20000 20000 1e-6 0.97 0.8 425 | exit 426 | ./x4.sh g Res1C4kM95 gResnet56 1 4000 1800 1e-4 0.97 0.9 427 | sleep 30 428 | ./x4.sh h Res1C8kM95 gResnet56 1 8000 3600 1e-4 0.97 0.9 429 | sleep 30 430 | ./x4.sh i Res1C16kM95 gResnet56 1 16000 7200 1e-4 0.97 0.9 431 | exit 432 | ./x4.sh a 2ndCLR2CMWD4 gen2ndOrder56 1 20000 20000 1e-4 0.9 0.9 433 | exit 434 | ./x4.sh g Res1C4kM95 gResnet56 1 4000 1800 1e-4 0.95 0.95 435 | exit 436 | ./x4.sh d Den1CycM85 genDensenet40 0.4 20000 9000 1e-4 0.85 0.85 437 | exit 438 | ./x4.sh c Den1CycM9 genDensenet40 0.4 20000 10000 1e-4 0.9 0.9 439 | sleep 30 440 | ./x4.sh a Den1CycCM genDensenet40 0.4 20000 10000 1e-4 0.9 0.8 441 | sleep 30 442 | ./x4.sh b Den1CycCM genDensenet40 0.4 20000 10000 1e-4 0.8 0.95 443 | exit 444 | ./x4.sh h Den1CycCM genDensenet40 2 20000 9000 1e-4 0.9 0.8 445 | exit 446 | ./x4.sh g Den1CycCM genDensenet40 2 20000 9000 1e-4 0.8 0.95 447 | exit 448 | ./x4.sh f Den1CycCM genDensenet40 2 20000 9000 1e-4 0.95 0.8 449 | #./x4.sh g Den1CycCM genDensenet40 2 20000 9000 1e-4 0.97 0.9 450 | exit 451 | ./x4.sh h Den1CycWD5 genDensenet40 2 20000 9000 1e-5 0.9 0.9 452 | exit 453 | ./x4.sh e Den1CycCM genDensenet40 2 20000 9000 1e-4 0.8 0.95 454 | exit 455 | ./x4.sh d Den1CycM85 genDensenet40 2 20000 9000 1e-4 0.85 0.85 456 | exit 457 | ./x4.sh a 2ndCLR2CMWD4 gen2ndOrder56 2 20000 20000 1e-4 0.98 0.9 458 | exit 459 | ./x4.sh c 2ndCLR2CMWD5 2ndOrder56 2 20000 20000 1e-5 0.98 0.9 460 | exit 461 | ./x4.sh b 2ndCLR2CMWD0 2ndOrder56 2 20000 20000 0 0.98 0.9 462 | exit 463 | ./x4.sh n Den1CycM97 genDensenet40 2 20000 9000 1e-4 0.97 0.97 464 | exit 465 | ./x4.sh m Den1CycM9 genDensenet40 2 20000 9000 1e-4 0.9 0.9 466 | exit 467 | ./x4.sh k Den1CycM95 genDensenet40 2 20000 9000 1e-4 0.95 0.95 468 | sleep 20 469 | ./x4.sh l Den1CycCM genDensenet40 2 20000 9000 1e-4 0.97 0.9 470 | exit 471 | ./x4.sh a Res1CycM99 gResnet56 1 4000 1800 1e-6 0.99 0.99 472 | exit 473 | ./x4.sh a 3Lay4k cifar3 0.005 4000 2000 4e-3 0.9 0.9 474 | sleep 20 475 | ./x4.sh b 3Lay8k cifar3 0.005 8000 4000 4e-3 0.9 0.9 476 | sleep 20 477 | ./x4.sh c 3Lay16k cifar3 0.005 16000 8000 4e-3 0.9 0.9 478 | exit 479 | ./x4.sh d 3LayCM4k cifar3 0.005 4000 4000 4e-3 0.9 1 480 | sleep 20 481 | ./x4.sh e 3LayCM8k cifar3 0.005 8000 8000 4e-3 0.9 1 482 | sleep 20 483 | ./x4.sh f 3LayCM16k cifar3 0.005 16000 16000 4e-3 0.9 1 484 | exit 485 | ./x4.sh g 3LayCM4k cifar3 0.005 4000 2000 4e-3 0.97 0.9 486 | sleep 20 487 | ./x4.sh h 3LayCM8k cifar3 0.005 8000 4000 4e-3 0.97 0.9 488 | sleep 20 489 | ./x4.sh i 3LayCM16k cifar3 0.005 16000 8000 4e-3 0.97 0.9 490 | exit 491 | ./x4.sh i Den1CycM9 genDensenet40 1 20000 9000 1e-4 0.9 0.9 492 | sleep 20 493 | ./x4.sh j Den1CycCM genDensenet40 1 20000 9000 1e-4 0.95 0.8 494 | exit 495 | ./x4.sh a 3Lay1CycCM cifar3 0.007 20000 10000 4e-3 0.95 0.8 496 | sleep 20 497 | ./x4.sh b 3Lay1CycCM cifar3 0.007 20000 10000 4e-3 0.9 1 498 | exit 499 | ./x4.sh a 3Lay1CycCM cifar3 0.007 20000 10000 4e-3 0.95 0.85 500 | sleep 20 501 | ./x4.sh b 3Lay1CycCM cifar3 0.007 20000 10000 4e-3 0.9 0.95 502 | sleep 20 503 | ./x4.sh c 3Lay1CycM85 cifar3 0.007 20000 10000 4e-3 0.85 0.85 504 | sleep 20 505 | ./x4.sh d 3Lay1CycM9 cifar3 0.007 20000 10000 4e-3 0.9 0.9 506 | sleep 20 507 | ./x4.sh e 3Lay1CycM93 cifar3 0.007 20000 10000 4e-3 0.93 0.93 508 | sleep 20 509 | ./x4.sh f 3Lay1CycM95 cifar3 0.007 20000 10000 4e-3 0.95 0.95 510 | sleep 20 511 | ./x4.sh g 3Lay1CycM97 cifar3 0.007 20000 10000 4e-3 0.97 0.97 512 | exit 513 | ./x4.sh a 3Lay1CycCM cifar3 0.007 20000 9000 4e-3 0.95 0.85 514 | sleep 20 515 | ./x4.sh b 3Lay1CycCM cifar3 0.007 20000 9000 4e-3 0.9 0.95 516 | sleep 20 517 | ./x4.sh c 3Lay1CycM85 cifar3 0.007 20000 9000 4e-3 0.85 0.85 518 | sleep 20 519 | ./x4.sh d 3Lay1CycM9 cifar3 0.007 20000 9000 4e-3 0.9 0.9 520 | sleep 20 521 | ./x4.sh e 3Lay1CycM93 cifar3 0.007 20000 9000 4e-3 0.93 0.93 522 | sleep 20 523 | ./x4.sh f 3Lay1CycM95 cifar3 0.007 20000 9000 4e-3 0.95 0.95 524 | sleep 20 525 | ./x4.sh g 3Lay1CycM97 cifar3 0.007 20000 9000 4e-3 0.97 0.97 526 | exit 527 | ./x4.sh a 3Lay1CycCM cifar3 0.008 20000 9000 4e-3 0.95 0.85 528 | sleep 20 529 | ./x4.sh b 3Lay1CycCM cifar3 0.008 20000 9000 4e-3 0.9 0.95 530 | sleep 20 531 | ./x4.sh c 3Lay1CycM85 cifar3 0.008 20000 9000 4e-3 0.85 0.85 532 | sleep 20 533 | ./x4.sh d 3Lay1CycM9 cifar3 0.008 20000 9000 4e-3 0.9 0.9 534 | sleep 20 535 | ./x4.sh e 3Lay1CycM93 cifar3 0.008 20000 9000 4e-3 0.93 0.93 536 | sleep 20 537 | ./x4.sh f 3Lay1CycM95 cifar3 0.008 20000 9000 4e-3 0.95 0.95 538 | sleep 20 539 | ./x4.sh g 3Lay1CycM97 cifar3 0.008 20000 9000 4e-3 0.97 0.97 540 | exit 541 | ./x4.sh a 3Lay1CycCM cifar3 0.01 20000 9000 4e-3 0.95 0.85 542 | sleep 20 543 | ./x4.sh b 3Lay1CycCM cifar3 0.01 20000 9000 4e-3 0.9 0.95 544 | sleep 20 545 | ./x4.sh c 3Lay1CycM85 cifar3 0.01 20000 9000 4e-3 0.85 0.85 546 | sleep 20 547 | ./x4.sh d 3Lay1CycM95 cifar3 0.01 20000 9000 4e-3 0.95 0.95 548 | sleep 20 549 | ./x4.sh f 3Lay1CycM9 cifar3 0.01 20000 9000 4e-3 0.9 0.9 550 | sleep 20 551 | ./x4.sh e 3Lay1CycM97 cifar3 0.01 20000 9000 4e-3 0.97 0.97 552 | sleep 20 553 | ./x4.sh g 3Lay1CycM93 cifar3 0.01 20000 9000 4e-3 0.93 0.93 554 | exit 555 | ./x4.sh a Den1CycM9 genDensenet40 4 20000 9000 1e-4 0.9 0.9 556 | exit 557 | ./x4.sh g ResStdCM gResnet56 0.1 60000 60000 1e-4 0.93 1 558 | exit 559 | ./x4.sh e ResStdCM gResnet56 0.1 60000 30000 1e-4 0.97 0.93 560 | sleep 20 561 | ./x4.sh f ResStdCM gResnet56 0.1 60000 30000 1e-4 0.93 1 562 | exit 563 | ./x4.sh b 3LayCM9s cifar3 0.005 20000 10000 4e-3 0.97 0.9 564 | sleep 20 565 | ./x4.sh c 3LayCM9s cifar3 0.005 20000 10000 4e-3 0.9 0.97 566 | sleep 20 567 | ./x4.sh d 3LayCM9s cifar3 0.005 20000 20000 4e-3 0.9 0.97 568 | exit 569 | ./x4.sh a ResCLRWD3-4 gResnet56 2 20000 20000 3e-4 0.95 0.9 570 | exit 571 | ./x4.sh g Res1CycWD4 gResnet56 .7 20000 9000 1e-4 0.95 0.9 572 | sleep 20 573 | ./x4.sh h Res1CycWD5 gResnet56 1 20000 9000 1e-5 0.95 0.9 574 | sleep 20 575 | ./x4.sh i Res1CycWD6 gResnet56 1 20000 9000 1e-6 0.95 0.9 576 | exit 577 | ./x4.sh f Res1CycWD0 gResnet56 2 20000 9000 0 0.95 0.9 578 | exit 579 | ./x4.sh e ResCLRWD4 gResnet56 2 20000 20000 1e-4 0.95 0.9 580 | exit 581 | ./x4.sh d ResCLRWD6 gResnet56 2 20000 20000 1e-6 0.95 0.9 582 | exit 583 | ./x4.sh c ResCLRWD5 gResnet56 2 20000 20000 1e-5 0.95 0.9 584 | exit 585 | ./x4.sh b ResCLRWD0 gResnet56 2 20000 20000 0 0.95 0.9 586 | exit 587 | sleep 20 588 | ./x4.sh a 3LayWD0CLR cifar3 0.02 10000 10000 0 0.95 0.8 589 | exit 590 | ./x4.sh p 3LayWD0CLR cifar3 0.02 10000 10000 0 0.95 0.95 591 | exit 592 | ./x4.sh a 3LayCM9585 cifar3 0.005 20000 20000 4e-3 0.95 0.85 593 | sleep 10 594 | ./x4.sh b 3LayCM9-1 cifar3 0.005 20000 20000 4e-3 0.9 1 595 | sleep 20 596 | ./x4.sh c 3LayM85 cifar3 0.005 20000 10000 4e-3 0.85 0.85 597 | sleep 10 598 | ./x4.sh d 3LayM95 cifar3 0.005 20000 10000 4e-3 0.95 0.95 599 | sleep 10 600 | ./x4.sh f 3LayM9 cifar3 0.005 20000 10000 4e-3 0.9 0.9 601 | sleep 20 602 | ./x4.sh e 3LayM97 cifar3 0.005 20000 10000 4e-3 0.97 0.97 603 | sleep 10 604 | ./x4.sh g 3LayM93 cifar3 0.005 20000 10000 4e-3 0.93 0.93 605 | exit 606 | ./x4.sh j ResStdM97 gResnet56 0.1 60000 9000 1e-4 0.97 0.97 607 | exit 608 | ./x4.sh h ResStdM9 gResnet56 0.1 60000 9000 1e-4 0.9 0.9 609 | sleep 10 610 | ./x4.sh i ResStdM95 gResnet56 0.1 60000 9000 1e-4 0.95 0.95 611 | exit 612 | ./x4.sh f 3LayM9585 cifar3 0.01 20000 20000 4e-3 0.95 0.85 613 | sleep 10 614 | ./x4.sh g 3LayCM9-1 cifar3 0.01 20000 20000 4e-3 0.9 1 615 | exit 616 | ./x4.sh d 3LayM85 cifar3 0.01 20000 10000 4e-3 0.85 0.85 617 | sleep 10 618 | ./x4.sh b 3LayM95 cifar3 0.01 20000 10000 4e-3 0.95 0.95 619 | sleep 10 620 | ./x4.sh e 3LayM9 cifar3 0.01 20000 10000 4e-3 0.9 0.9 621 | exit 622 | ./x4.sh a 3LayM97 cifar3 0.01 20000 10000 4e-3 0.97 0.97 623 | sleep 10 624 | ./x4.sh c 3LayM93 cifar3 0.01 20000 10000 4e-3 0.93 0.93 625 | exit 626 | ./x4.sh k Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.93 0.8 627 | sleep 10 628 | ./x4.sh l Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.95 0.9 629 | sleep 10 630 | ./x4.sh m Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.95 0.85 631 | exit 632 | ./x4.sh h Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.97 0.85 633 | sleep 10 634 | ./x4.sh i Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.93 0.85 635 | sleep 10 636 | ./x4.sh j Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.99 0.85 637 | exit 638 | ./x4.sh e 3LayCLR cifar3 0.005 20000 10000 4e-3 0.95 0.8 639 | sleep 10 640 | ./x4.sh f 3LayCLR cifar3 0.005 20000 10000 4e-3 0.95 0.9 641 | sleep 10 642 | ./x4.sh g 3LayCLR cifar3 0.005 20000 10000 4e-3 0.95 0.95 643 | exit 644 | ./x4.sh a 3LayCLR cifar3 0.005 20000 10000 4e-3 0.99 0.85 645 | sleep 10 646 | ./x4.sh b 3LayCLR cifar3 0.005 20000 10000 4e-3 0.97 0.85 647 | sleep 10 648 | ./x4.sh c 3LayCLR cifar3 0.005 20000 10000 4e-3 0.95 0.85 649 | sleep 10 650 | ./x4.sh d 3LayCLR cifar3 0.005 20000 10000 4e-3 0.93 0.85 651 | exit 652 | ./x4.sh l 3LayCLR cifar3 0.007 20000 10000 4e-3 0.97 0.9 653 | sleep 10 654 | ./x4.sh m 3LayCLR cifar3 0.007 20000 10000 4e-3 0.97 0.85 655 | sleep 10 656 | ./x4.sh n 3LayCLR cifar3 0.007 20000 10000 4e-3 0.97 0.95 657 | exit 658 | ./x4.sh j 3LayCLR cifar3 0.007 20000 10000 4e-3 0.99 0.8 659 | sleep 10 660 | ./x4.sh k 3LayCLR cifar3 0.007 20000 10000 4e-3 0.97 0.8 661 | exit 662 | ./x4.sh h DenCMCLR genDensenet40 4 20000 20000 1e-4 0.97 0.9 663 | sleep 10 664 | ./x4.sh i DenCMCLR genDensenet40 4 20000 20000 1e-4 0.97 0.85 665 | exit 666 | ./x4.sh h Den1Cyc9k genDensenet40 4 20000 9000 1e-4 0.97 0.7 667 | exit 668 | ./x4.sh g Res1Cyc9k gResnet56 0.4 20000 9000 5e-4 0.95 0.8 669 | exit 670 | ./x4.sh f 3LayCLR cifar3 0.02 10000 10000 4e-3 0.99 0.99 671 | exit 672 | ./x4.sh e 3LayCLR cifar3 0.01 10000 10000 4e-3 0.7 1 673 | exit 674 | ./x4.sh c 3LayCLR cifar3 0.02 10000 10000 4e-3 0.7 0.7 675 | sleep 10 676 | ./x4.sh d 3LayCLR cifar3 0.02 10000 10000 4e-3 0.9 0.9 677 | exit 678 | ./x4.sh a Den1Cyc9k genDensenet40 1.5 20000 9000 2e-4 0.97 0.7 679 | sleep 10 680 | ./x4.sh b Den1Cyc9k genDensenet40 4 20000 9000 1e-4 0.97 0.7 681 | 682 | exit 683 | ./x4.sh e Res1Cyc9k gResnet56 0.4 20000 9000 5e-4 0.95 0.8 684 | exit 685 | ./x4.sh f DenCMCLR genDensenet40 4 20000 20000 5e-5 0.97 0.7 686 | exit 687 | ./x4.sh d ResCLRCM gResnet56 2 20000 20000 5e-4 0.95 0.8 688 | exit 689 | ./x4.sh a DenCMCLR genDensenet40 4 20000 20000 1e-4 0.97 0.7 690 | sleep 10 691 | ./x4.sh b DenCMCLR genDensenet40 4 20000 20000 2e-4 0.97 0.7 692 | sleep 10 693 | ./x4.sh c DenCMCLR genDensenet40 4 20000 20000 5e-4 0.97 0.7 694 | exit 695 | 696 | ./x4.sh n Res1Cyc9k gResnet56 0.7 20000 9000 2e-4 0.95 0.8 697 | sleep 10 698 | ./x4.sh o Res1Cyc9k gResnet56 1.0 20000 9000 1e-4 0.95 0.8 699 | sleep 10 700 | ./x4.sh p Res1Cyc9k gResnet56 1.2 20000 9000 5e-5 0.95 0.8 701 | exit 702 | ./x4.sh m ResCLRCM gResnet56 2 20000 20000 2e-4 0.95 0.8 703 | sleep 10 704 | ./x4.sh k ResCLRCM gResnet56 2 20000 20000 1e-4 0.95 0.8 705 | sleep 10 706 | ./x4.sh l ResCLRCM gResnet56 2 20000 20000 5e-5 0.95 0.8 707 | exit 708 | 709 | ./x4.sh j 3LayCMCLR cifar3 0.008 20000 10000 4e-3 0.95 0.8 710 | exit 711 | ./x4.sh i 3LayCMCLR cifar3 0.007 20000 10000 4e-3 0.97 0.7 712 | exit 713 | ./x4.sh h 3LayCMCLR cifar3 0.007 20000 20000 4e-3 0.9 0.9 714 | exit 715 | ./x4.sh g 3LayCMCLR cifar3 0.007 20000 10000 4e-3 0.95 0.8 716 | exit 717 | ./x4.sh a Res1Cyc9k gResnet56 1 20000 9000 1e-4 0.95 0.8 718 | exit 719 | ./x4.sh f 3LayCMCLR cifar3 0.02 10000 10000 4e-3 0.97 0.7 720 | 721 | exit 722 | ./x4.sh c 3LayCMCLR cifar3 0.02 10000 10000 4e-3 0.9 0.9 723 | sleep 10 724 | ./x4.sh d 3LayCMCLR cifar3 0.02 10000 10000 4e-3 0.8 1 725 | sleep 10 726 | ./x4.sh e 3LayCMCLR cifar3 0.02 10000 10000 4e-3 0.95 0.8 727 | sleep 10 728 | exit 729 | ./x4.sh b 3LayCMCLR cifar3 0.01 40000 40000 4e-3 0.95 0.8 730 | exit 731 | ./x4.sh j 3LayCMCLR cifar3 0.01 40000 40000 4e-3 0.8 1 732 | exit 733 | ./x4.sh g 3LayCMCLR cifar3 0.01 40000 40000 4e-3 0.5 1 734 | sleep 10 735 | ./x4.sh h 3LayCMCLR cifar3 0.01 40000 40000 1e-2 0.9 0.9 736 | sleep 10 737 | ./x4.sh i 3LayCMCLR cifar3 0.01 40000 40000 1e-3 0.9 0.9 738 | exit 739 | ./x4.sh a Res1Cyc9k gResnet56 1 20000 9000 5e-5 1 0.75 740 | exit 741 | ./x4.sh f 3LayCM cifar3 0.005 40000 40000 4e-3 0.5 1 742 | exit 743 | ./x4.sh e 3Layer cifar3 0.01 40000 40000 4e-3 0.9 0.9 744 | exit 745 | ./x4.sh d Res1Cyc9k gResnet56 1 20000 9000 5e-5 0.85 0.95 746 | exit 747 | ./x4.sh c GresLR gResnet56 1 20000 20000 1e-4 0.8 0.8 748 | exit 749 | ./x4.sh b Res1Cyc9k gResnet56 1 20000 9000 5e-5 0.9 0.9 750 | exit 751 | ./x4.sh a Res1Cyc9k gResnet56 1 20000 9000 5e-5 0.95 0.75 752 | exit 753 | ./x4.sh m Res1Cyc9k gResnet56 1 20000 9000 5e-5 0.95 0.85 754 | exit 755 | ./x4.sh l Res1Cyc9k gResnet56 1 20000 9000 5e-5 0.9 1 756 | exit 757 | ./x4.sh k ResCM93 gResnet56 4 20000 20000 5e-5 0.93 0.8 758 | exit 759 | ./x4.sh j ResCM1LR gResnet56 4 20000 20000 5e-5 0.9 1 760 | exit 761 | ./x4.sh i ResCM1LR gResnet56 1 20000 20000 1e-5 0.9 1 762 | exit 763 | ./x4.sh d Res60kCM gResnet56 0.1 60000 30000 1e-4 0.88 1 764 | exit 765 | ./x4.sh h ResCMLR gResnet56 1 20000 20000 5e-5 0.9 1 766 | exit 767 | ./x4.sh g ResCM4 gResnet56 0.1 20000 20000 1e-4 0.9 4 768 | exit 769 | ./x4.sh e Res1Cyc gResnet56 1 20000 9000 5e-5 0.9 0.9 770 | sleep 10 771 | ./x4.sh f Res1Cyc gResnet56 1 20000 9000 1e-4 0.9 0.9 772 | exit 773 | ./x4.sh b GresCM gResnet56 0.1 20000 20000 1e-4 0.8 1 774 | sleep 10 775 | ./x4.sh c GresCM gResnet56 0.1 20000 20000 5e-5 0.8 1 776 | exit 777 | ./x4.sh a GresLR gResnet56 1 20000 20000 5e-5 0.9 0.9 778 | exit 779 | ./x4.sh e DenLR genDensenet40 4 20000 20000 1e-4 0.9 0.9 780 | sleep 10 781 | ./x4.sh f DenLR genDensenet40 4 20000 20000 2e-4 0.9 0.9 782 | sleep 10 783 | ./x4.sh g DenLR genDensenet40 4 20000 20000 5e-4 0.9 0.9 784 | exit 785 | ./x4.sh h GresLR gResnet56 1 20000 20000 1e-4 0.9 0.9 786 | sleep 10 787 | ./x4.sh i GresLR gResnet56 1 20000 20000 2e-4 0.9 0.9 788 | sleep 10 789 | ./x4.sh j GresLR gResnet56 1 20000 20000 5e-4 0.9 0.9 790 | exit 791 | ./x4.sh b GresLR gResnet56 1 20000 20000 1e-4 0.8 1 792 | sleep 10 793 | ./x4.sh c GresLR gResnet56 1 20000 20000 2e-4 0.8 1 794 | sleep 10 795 | ./x4.sh d GresLR gResnet56 1 20000 20000 5e-4 0.8 1 796 | exit 797 | 798 | ./x4.sh a DenLRCM genDensenet40 4 20000 20000 2e-5 0.8 1 799 | exit 800 | ./x4.sh n DenLRCM genDensenet40 4 20000 20000 1e-5 0.8 1 801 | exit 802 | ./x4.sh l DenLRCM genDensenet40 4 20000 20000 5e-4 0.8 1 803 | sleep 10 804 | ./x4.sh m DenLRCM genDensenet40 4 20000 20000 2e-4 0.8 1 805 | exit 806 | ./x4.sh k GresLR gResnet56 1 20000 20000 2e-5 0.8 1 807 | exit 808 | ./x4.sh i DenLRCM genDensenet40 4 20000 20000 5e-5 0.8 1 809 | sleep 10 810 | ./x4.sh j DenLRCM genDensenet40 4 20000 20000 1e-4 0.8 1 811 | exit 812 | ./x4.sh h GresLR gResnet56 1 20000 20000 5e-5 0.8 1 813 | exit 814 | ./x4.sh f GresLR gResnet56 1 20000 20000 5e-5 0.9 0.9 815 | exit 816 | ./x4.sh a GresLR gResnet56 1 20000 20000 1e-4 0.9 0.9 817 | exit 818 | ./x4.sh b GresLR gResnet56 1 20000 20000 2e-4 0.9 0.9 819 | exit 820 | ./x4.sh f GresLR gResnet56 1 20000 20000 1e-4 0.8 1 821 | exit 822 | ./x4.sh c GresLR gResnet56 1 20000 20000 1e-3 0.8 1 823 | exit 824 | ./x4.sh d GresLR gResnet56 1 20000 20000 5e-4 0.8 1 825 | exit 826 | ./x4.sh e GresLR gResnet56 1 20000 20000 2e-4 0.8 1 827 | exit 828 | sleep 10 829 | ./x4.sh b GresLR gResnet56 1 20000 20000 1e-3 0.9 0.9 830 | exit 831 | ./x4.sh a GresLR gResnet56 1 20000 20000 5e-4 0.9 0.9 832 | exit 833 | ./x4.sh e GenRes60 gResnet56 0.1 60000 8000 5e-4 0.9 0.9 834 | exit 835 | ./x4.sh d Res60k resnet56 0.1 60000 8000 5e-4 0.9 0.9 836 | exit 837 | ./x4.sh b Res60k resnet56 0.1 60000 8000 1e-4 0.9 0.9 838 | exit 839 | ./x4.sh e 3layerWD cifar3 0.0035 60000 60000 1e-2 0.9 0.9 840 | exit 841 | ./x4.sh a ResWD5 resnet56 0.1 60000 8000 5e-4 0.9 0.9 842 | exit 843 | ./x4.sh d ResWD5 resnet56 0.4 20000 8000 5e-4 0.9 0.9 844 | exit 845 | ./x4.sh c rng3layer cifar3 0.01 20000 20000 1e-2 0.9 0.9 846 | exit 847 | ./x4.sh f 3layer1 cifar3 0.001 60000 60000 4e-3 0.9 0.9 848 | sleep 20 849 | ./x4.sh e 3layer55 cifar3 0.0055 60000 60000 4e-3 0.9 0.9 850 | qstat 851 | exit 852 | ./x4.sh e rng3layer cifar3 0.01 20000 20000 4e-3 0.9 0.9 853 | exit 854 | ./x4.sh f 3layer1 cifar3 0.001 60000 60000 1e-4 0.9 0.9 855 | exit 856 | ./x4.sh e 3layer cifar3 0.0025 60000 60000 1e-4 0.9 0.9 857 | qstat 858 | sleep 10 859 | 860 | ./x4.sh c GenDense genDensenet22 0.1 60000 8000 1e-4 0.9 0.9 861 | sleep 30 862 | ./x4.sh d GenDenRes genDenseResnet22 0.1 60000 8000 1e-4 0.9 0.9 863 | 864 | exit 865 | ./x4.sh a GenDense genDensenet22 1.0 20000 8000 1e-4 0.88 0.98 866 | sleep 30 867 | ./x4.sh b GenDenRes genDenseResnet22 1.0 20000 8000 1e-4 0.88 0.98 868 | 869 | exit 870 | 871 | ./x4.sh e GenDenRes genDensenet40 1.0 20000 8000 1e-4 0.85 0.95 872 | 873 | exit 874 | 875 | ./x1.sh c Den40 densenet40 1.0 20000 20000 1e-4 0.9 0.9 876 | sleep 10 877 | ./x1.sh d GenDen genDensenet40 1.0 20000 20000 1e-4 0.9 0.9 878 | 879 | exit 880 | ./x.sh b DenseCLR densenet40 0.01 0.4 0.0001 0.9 881 | exit 882 | ./x.sh a DenRes denseResnet40 0.01 0.4 0.0001 0.9 883 | exit 884 | ./x.sh b 2ndM9 2ndOrder56 0.01 0.4 0.0001 0.9 885 | exit 886 | ./x1.sh h rngWideM98 wide32cifar 1.0 20000 20000 1e-4 0.98 0.99 887 | exit 888 | ./x1.sh g rngWideM95 wide32cifar 1.0 20000 20000 1e-4 0.95 0.95 889 | exit 890 | ./x1.sh f rngWideM85 wide32cifar 1.0 20000 20000 1e-4 0.85 0.85 891 | exit 892 | ./x1.sh d DenStep8k densenet40 1.0 20000 8000 1e-4 0.9 0.9 893 | exit 894 | ./x1.sh b DenStep8k densenet40 1.0 20000 8000 1e-4 0.9 0.9 895 | exit 896 | ./x1.sh b DenLR2 densenet40 1.0 20000 8500 1e-4 0.9 0.9 897 | 898 | exit 899 | ./x1.sh e DenAvgWD2-4 densenet40 1.0 20000 9950 2e-4 0.9 0.8 900 | 901 | exit 902 | ./x1.sh d DenWD1-4 densenet40 1.0 20000 9950 1e-4 0.9 0.8 903 | 904 | exit 905 | ./x1.sh c 2ndM7 2ndOrder56R2 1.0 20000 9950 1e-4 0.9 0.7 906 | 907 | ./x1.sh a 2ndM7 2ndOrder56ReLU 1.0 20000 9950 5e-5 0.9 0.7 908 | exit 909 | ./x1.sh r 2ndM85 lin2ndOrder56 0.9 20000 9950 5e-5 0.7 0.7 910 | exit 911 | ./x1.sh q Rng2nd lin2ndOrder56 1.0 20000 20000 1e-4 0.7 0.95 912 | exit 913 | ./x1.sh m RngDen densenet40 1.0 20000 20000 5e-5 0.7 0.98 914 | 915 | exit 916 | ./x1.sh o Rng2nd lin2ndOrder56 1.0 20000 20000 5e-4 0.7 0.95 917 | exit 918 | ./x1.sh p WideM95 wide32cifar 1.0 20000 9950 1e-4 0.92 0.92 919 | exit 920 | sleep 30 921 | ./x1.sh k ResM9 resnet56 1.0 20000 9950 5e-5 0.9 0.9 922 | exit 923 | ./x1.sh l rngWide wide32cifar 1.0 20000 20000 1e-4 0.7 0.95 924 | sleep 40 925 | ./x1.sh m rngDen densenet40 1.0 20000 20000 1e-4 0.7 0.95 926 | 927 | exit 928 | 929 | ./x1.sh j CM7CLR1sc densenet40 1.0 20000 10000 1e-4 0.9 0.7 930 | 931 | exit 932 | 933 | ./x1.sh i CM7CLR1sc wide32cifar 1.0 20000 10000 1e-4 0.9 0.7 934 | sleep 40 935 | ./x1.sh i CM7CLR1sc wide32cifar 1.0 20000 9950 1e-4 0.9 0.7 936 | 937 | exit 938 | ./x1.sh h ResSC_CMR resnet56 1.0 20000 10000 5e-5 0.9 0.7 939 | exit 940 | sleep 40 941 | ./x1.sh f ResSC_CMR resnet56 1.0 20000 9950 5e-5 0.9 0.7 942 | sleep 40 943 | ./x1.sh g ResSC_CMR resnet56 1.0 20000 9900 5e-5 0.9 0.7 944 | 945 | 946 | exit 947 | ./x.sh b WideUnder wide32cifar 0.0 0.05 0.0001 0.85 948 | 949 | 950 | exit 951 | ./x3.sh p DensCL densenet40 0.4 0.0001 0.8 0.0005 0.9 0.95 952 | sleep 40 953 | ./x3.sh d DensCL densenet40 0.1 0.0001 0.8 0.0005 0.9 0.95 954 | exit 955 | ./x3.sh b DensRev densenet40 0.1 0.0005 0.95 0.0002 0.9 0.85 956 | exit 957 | ./x.sh a DensBS37 densenet40 0.0 0.1 0.0002 0.9 958 | exit 959 | ./x.sh a ResLR2 resnet56 0.0 0.2 0.0005 0.95 960 | exit 961 | 962 | ./x.sh d DensM97 densenet40 0.0 0.05 0.005 0.97 963 | exit 964 | ./x.sh m WideM9 wide32cifar 0.0 0.2 0.0001 0.9 965 | sleep 40 966 | ./x.sh n WideLR4 wide32cifar 0.0 0.4 0.0001 0.9 967 | 968 | exit 969 | ./x.sh l DensM8 densenet40 0.0 0.05 0.0001 0.8 970 | exit 971 | ./x.sh k DensBS37 densenet40 0.0 0.05 0.0002 0.9 972 | exit 973 | ./x.sh j DensLR4 densenet40 0.0 0.4 0.0001 0.9 974 | exit 975 | ./x.sh f ResLR1 resnet56 0.0 0.1 0.0005 0.95 976 | sleep 40 977 | ./x.sh g ResLR4 resnet56 0.0 0.4 0.0005 0.95 978 | sleep 40 979 | ./x.sh h ResM9 resnet56 0.0 0.1 0.0001 0.9 980 | sleep 40 981 | ./x.sh i ResM97 resnet56 0.0 0.1 0.001 0.97 982 | 983 | exit 984 | 985 | ./x.sh a DensLR2 densenet40 0.0 0.2 0.001 0.95 986 | sleep 40 987 | ./x.sh b DensLR05 densenet40 0.0 0.05 0.001 0.95 988 | sleep 40 989 | ./x.sh c DensLR01 densenet40 0.0 0.01 0.001 0.95 990 | sleep 40 991 | ./x.sh d DensM97 densenet40 0.0 0.05 0.005 0.97 992 | sleep 40 993 | ./x.sh e DensM9 densenet40 0.0 0.05 0.0002 0.9 994 | sleep 4 995 | exit 996 | 997 | ./x.sh g DensLR06 densenet40 0.06 0.03 0.005 0.97 998 | exit 999 | ./x.sh g 2ndDDO 2ndOrder56a 0.4 0.2 0.0005 0.95 1000 | exit 1001 | ./x.sh a 2ndM85 2ndOrder56 0.4 0.2 0.0001 0.85 1002 | sleep 40 1003 | ./x.sh b ResWD1 resnet56 0.4 0.2 0.0001 0.9 1004 | sleep 40 1005 | ./x.sh c ResFCDO97 resnet56b 0.4 0.2 0.0001 0.97 1006 | sleep 40 1007 | ./x.sh d ResDO97 resnet56c 0.4 0.2 0.0001 0.97 1008 | sleep 4 1009 | ./x.sh e ResFCDO9 resnet56b 0.4 0.2 0.0005 0.9 1010 | sleep 40 1011 | ./x.sh f ResDO9 resnet56c 0.4 0.2 0.0005 0.9 1012 | sleep 4 1013 | exit 1014 | 1015 | ./x.sh r DensLR1 densenet40 0.1 0.05 0.005 0.97 1016 | sleep 40 1017 | ./x.sh s DensLR06 densenet40 0.06 0.03 0.005 0.97 1018 | sleep 4 1019 | exit 1020 | ./x.sh p WideLR4 wide32cifar 0.4 0.2 0.001 0.95 1021 | sleep 40 1022 | ./x.sh q WideLR2 wide32cifar 0.2 0.1 0.001 0.95 1023 | exit 1024 | ./x.sh o 2ndDO 2ndOrder56c 0.4 0.2 0.0005 0.95 1025 | exit 1026 | 1027 | ./x.sh e 2ndDDO 2ndOrder56a 0.4 0.2 0.0005 0.95 1028 | sleep 40 1029 | ./x.sh f 2ndFCDO 2ndOrder56b 0.4 0.2 0.0005 0.95 1030 | sleep 40 1031 | ./x.sh g 2ndDO 2ndOrder56c 0.4 0.2 0.0005 0.95 1032 | sleep 40 1033 | ./x.sh h ResDDO resnet56a 0.4 0.2 0.0005 0.95 1034 | sleep 40 1035 | ./x.sh i ResFCDO resnet56b 0.4 0.2 0.0005 0.95 1036 | sleep 40 1037 | ./x.sh j ResDO resnet56c 0.4 0.2 0.0005 0.95 1038 | sleep 4 1039 | 1040 | exit 1041 | ./x.sh k 2ndM95 2ndOrder56 0.4 0.2 0.0005 0.95 1042 | sleep 40 1043 | ./x.sh a 2ndM9 2ndOrder56 0.4 0.2 0.0005 0.9 1044 | sleep 40 1045 | ./x.sh b 2ndWD10 2ndOrder56 0.4 0.2 0.001 0.95 1046 | sleep 40 1047 | ./x.sh c ResWD10 resnet56 0.4 0.2 0.001 0.95 1048 | sleep 40 1049 | ./x.sh d ResWD5 resnet56 0.4 0.2 0.0005 0.95 1050 | sleep 4 1051 | 1052 | exit 1053 | ./x.sh g ResAdam resnet56 0.004 0.002 0.0005 0.95 1054 | sleep 4 1055 | 1056 | exit 1057 | ./x.sh f ResNest resnet56 0.4 0.2 0.0005 0.95 1058 | sleep 4 1059 | 1060 | exit 1061 | ./x.sh i ResL1 resnet56 0.4 0.2 0.0005 0.95 1062 | sleep 4 1063 | 1064 | exit 1065 | ./x.sh i ResMOM98 resnet56 0.4 0.2 0.98 1066 | sleep 4 1067 | exit 1068 | ./x.sh j ResWD100 resnet56 0.8 0.4 0.001 1069 | sleep 4 1070 | exit 1071 | ./x.sh f ResMOM98 resnet56 0.4 0.2 0.98 1072 | sleep 40 1073 | qstat 1074 | ./x.sh g ResMOM99 resnet56 0.4 0.2 0.99 1075 | sleep 40 1076 | qstat 1077 | ./x.sh h ResWD100 resnet56 0.8 0.4 0.001 1078 | sleep 4 1079 | qstat 1080 | exit 1081 | 1082 | ./x.sh b ResMOM97 resnet56 0.4 0.2 0.97 1083 | sleep 40 1084 | qstat 1085 | ./x.sh d ResMOM95 resnet56 0.4 0.2 0.95 1086 | sleep 40 1087 | qstat 1088 | ./x.sh e ResMOM85 resnet56 0.4 0.2 0.85 1089 | sleep 4 1090 | qstat 1091 | exit 1092 | ./x.sh c ResWD10 resnet56 0.2 0.1 0.0001 1093 | sleep 4 1094 | qstat 1095 | exit 1096 | ./x.sh f ResWD10 resnet56 0.1 0.05 0.0001 1097 | sleep 40 1098 | qstat 1099 | ./x.sh g ResWD25 resnet56 0.1 0.05 0.00025 1100 | sleep 40 1101 | qstat 1102 | ./x.sh h ResWD50 resnet56 0.2 0.1 0.0005 1103 | sleep 4 1104 | qstat 1105 | exit 1106 | ./x.sh a ResWD1 resnet56 0.1 0.05 0.00001 1107 | sleep 40 1108 | qstat 1109 | ./x.sh b ResWD5 resnet56 0.2 0.1 0.00005 1110 | sleep 40 1111 | qstat 1112 | ./x.sh c ResWD10 resnet56 0.2 0.1 0.0001 1113 | sleep 40 1114 | qstat 1115 | ./x.sh d ResWD50 resnet56 0.4 0.2 0.0005 1116 | sleep 40 1117 | qstat 1118 | ./x.sh e ResWD100 resnet56 0.4 0.2 0.001 1119 | sleep 4 1120 | qstat 1121 | exit 1122 | 1123 | ./x.sh j MOM95LR4 cifar3 0.008 0.004 0.004 1124 | sleep 4 1125 | qstat -u lnsmith 1126 | exit 1127 | ./x.sh k CWD2LR4 cifar3 0.004 0.002 0.002 1128 | sleep 4 1129 | qstat -u lnsmith 1130 | exit 1131 | ./x.sh k CWD8LR2 cifar3 0.002 0.001 0.008 1132 | sleep 4 1133 | qstat -u lnsmith 1134 | exit 1135 | ./x.sh g CWD4LR6 cifar3 0.006 0.003 0.004 1136 | sleep 4 1137 | qstat -u lnsmith 1138 | exit 1139 | ./x.sh h CWD1LR4 cifar3 0.002 0.001 0.001 1140 | sleep 40 1141 | qstat -u lnsmith 1142 | ./x.sh i CWD05LR2 cifar3 0.001 0.0005 0.0005 1143 | sleep 4 1144 | qstat -u lnsmith 1145 | exit 1146 | ./x.sh g CWD4LR8 cifar3 0.008 0.004 0.004 1147 | sleep 4 1148 | qstat -u lnsmith 1149 | exit 1150 | ./x.sh g CWD4LR8 cifar3 0.008 0.004 0 1151 | sleep 4 1152 | qstat -u lnsmith 1153 | exit 1154 | ./x.sh g Sig cifar_sigmoid 0.002 0.001 0 1155 | sleep 40 1156 | qstat -u lnsmith 1157 | ./x.sh h SigBN cifar_sigmoidBN 0.002 0.001 0 1158 | sleep 4 1159 | qstat -u lnsmith 1160 | exit 1161 | ./x.sh f Dens densenet40 0.4 0.2 0 1162 | sleep 40 1163 | qstat -u lnsmith 1164 | ./x.sh g Cifar cifar3 0.002 0.001 0 1165 | sleep 4 1166 | qstat -u lnsmith 1167 | exit 1168 | ./x.sh e Res56FCDO resnet56c 0.4 0.2 0 1169 | sleep 40 1170 | qstat -u lnsmith 1171 | ./x.sh d 2nd56FCDO 2ndOrder56c 0.4 0.2 0 1172 | sleep 4 1173 | qstat -u lnsmith 1174 | exit 1175 | ./x.sh c Res56DDO resnet56a 0.4 0.2 0 1176 | sleep 40 1177 | qstat -u lnsmith 1178 | ./x.sh d 2nd56DDO 2ndOrder56a 0.4 0.2 0 1179 | sleep 4 1180 | qstat -u lnsmith 1181 | exit 1182 | ./x.sh e Res56LR1 resnet56 solver 0.1 0 1183 | sleep 40 1184 | qstat 1185 | ./x.sh f 2nd56LR1 2ndOrder56 solver 0.1 0 1186 | sleep 4 1187 | qstat 1188 | exit 1189 | 1190 | ./x.sh d 2nd56 lin2ndOrder56 clrsolver 0.4 0 1191 | sleep 4 1192 | qstat 1193 | exit 1194 | 1195 | ./x.sh a Res56 resnet56 clrsolver 0.4 0 1196 | sleep 40 1197 | qstat 1198 | ./x.sh b Res56 genResnet56 clrsolver 0.4 0 1199 | sleep 40 1200 | qstat 1201 | ./x.sh c 2nd56 2ndOrder56 clrsolver 0.4 0 1202 | sleep 40 1203 | qstat 1204 | ./x.sh d 2nd56 linear2ndOrder56 clrsolver 0.4 0 1205 | sleep 4 1206 | qstat 1207 | exit 1208 | -------------------------------------------------------------------------------- /Cifar/solver.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/skipConnections/architectures/aarch.prototxt" 2 | #net: "examples/skipConnections/architectures/resnet56.prototxt" 3 | #net: "examples/skipConnections/architectures/2ndOrder56.prototxt" 4 | 5 | test_iter: 200 6 | test_interval: 200 7 | display: 200 8 | max_iter: xIter 9 | test_initialization: false 10 | 11 | # The base learning rate, momentum and the weight decay of the network. 12 | lr_policy: "multistep" 13 | base_lr: xLR1 14 | stepvalue: xSV1 # 30000 15 | stepvalue: xSV2 #45000 16 | stepvalue: xSV3 #52000 17 | stepvalue: xSV4 #56000 18 | stepvalue: xSV5 #58500 19 | gamma: 0.316 20 | 21 | weight_decay: xwd 22 | momentum: xmom1 23 | #decrease_weight_decay: xWD 24 | cyclical_momentum: xmom2 25 | cyclical_momentum: xStep 26 | 27 | # snapshot intermediate results 28 | snapshot: xIter 29 | snapshot_prefix: "examples/skipConnections/snapshots/xResnet56" 30 | #snapshot_prefix: "examples/skipConnections/snapshots/2ndOrder" 31 | 32 | solver_mode: GPU 33 | #regularization_type: "L1" 34 | type: "Nesterov" # "RMSProp" # "Adam" # "AdaGrad" # 35 | #type: "Adam" # "AdaDelta" # 36 | #rms_decay: 0.9 37 | #clip_gradients: 10 38 | #iter_size: 4 39 | #debug_info: true 40 | #average_loss: 50 41 | 42 | -------------------------------------------------------------------------------- /Cifar/train.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | echo "Entering train" 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | #rm -f examples/skipConnections/results/xResnet56_1 8 | 9 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 10 | 11 | echo "Calling Caffe once" 12 | $TOOLS/caffe.bin train \ 13 | --gpu=all --solver=examples/skipConnections/queues/xsolver.prototxt $@ 2>&1 | tee examples/skipConnections/results/xResnet56 14 | echo "Sold. Life after Caffe" 15 | 16 | exit 17 | $TOOLS/caffe.bin train \ 18 | --snapshot=examples/skipConnections/snapshots/xsnapshot_iter_20000.solverstate \ 19 | --gpu=all --solver=examples/skipConnections/clrsolver.prototxt $@ 2>&1 | tee examples/skipConnections/results/range2ndOrder56Mom7 20 | 21 | exit 22 | # --weights=examples/skipConnections/snapshots/range2ndOrder_iter_15000.caffemodel \ 23 | # --weights=examples/skipConnections/snapshots/rangeResnet56_iter_15000.caffemodel \ 24 | 25 | 26 | $TOOLS/caffe train \ 27 | --gpu=0 --solver=examples/skipConnections/init_solver.prototxt $@ 2>&1 | tee examples/skipConnections/results/initTaylor 28 | 29 | exit 30 | 31 | -------------------------------------------------------------------------------- /Cifar/x4.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | #echo "x.sh fileChar jobname architecture LR1 max_epochs step WD Mom1 Mom2” 5 | #echo "x.sh $1 " " $2 " " $3 " " $4 " " $5 " " $6 " " $7 " " $8 " " $9 6 | echo "x.sh fileChar jobname architecture LR1 max_epoch step WD BS Mom1” 7 | echo "x.sh $1 " " $2 " " $3 " " $4 " " $5 " " $6 " " $7 " " $8 " " $9 8 | 9 | JOB=$2 10 | ARCH=$3 11 | PLATFORM=Hokulea 12 | 13 | # 1 Batch size and compute iterations 14 | BS=$8 15 | #BS=256 # Resnet or 2ndOrder or wide32 16 | #BS=128 # Densenet or Cifar3 17 | #BS=64 # Cifar3 test 18 | BS4=`echo "$BS * 4" | bc` # 4 GPUS 19 | 20 | DATASIZE=50000 21 | MAXITER=`echo "$5 * $DATASIZE / $BS4" | bc` 22 | STEP=`echo "$6 * $DATASIZE / $BS4" | bc` 23 | #MAXITER=$5 24 | #STEP=$6 25 | echo 'max iter= ' $MAXITER 26 | echo 'step= ' $STEP 27 | 28 | # 2 29 | #LR=$4 30 | #LR=`echo "scale=3; $4 / 10.0" | bc` 31 | LR=`echo "scale=3; $4 / 12.0" | bc` 32 | echo 'learning rate= ' $LR 33 | #STEP=`echo "scale=2; $STEP / 2.0 " | bc` 34 | 35 | # 4 36 | WD=$MAXITER # 5 is max-iter, 6 is step 37 | 38 | IT1=`echo " $MAXITER / 2" | bc` 39 | IT2=`echo " $IT1 + $IT1 / 2" | bc` 40 | IT3=`echo " $IT2 + $IT1 / 4" | bc` 41 | IT4=`echo " $IT3 + $IT1 / 8" | bc` 42 | IT5=`echo " $IT3 + $IT1 /16" | bc` 43 | echo $IT1 44 | echo $IT2 45 | echo $IT3 46 | echo $IT4 47 | 48 | # 5 49 | MOM1=$9 50 | #MOM2=$9 51 | MOM2=0.85 52 | O1=$3_$2LR$LR$4CM$9.85WD$7Epoch$5BS$BS$1 53 | echo $O1 54 | sed s/xOut/$O1/g ptemp.sh >> process.sh 55 | sed s/xOut/$O1/g ptemp.sh >> history.sh 56 | O1=$3_$2LR$LR$4CM$9.85WD$7Epoch$5BS$BS$1_1 57 | 58 | BS1=`echo "$BS + 3" | bc` 59 | #BS1=$BS 60 | echo 'batch size= ' $BS1 61 | 62 | sed s/xout/$O1/g s1.sh >> status.sh 63 | sed s/xout/$O1/g s1.sh >> history.sh 64 | 65 | # 6 Wallclock Time 66 | WTIME=16 67 | 68 | sed s/xResnet/$2/g qsub.pbs > xqsub.pbs 69 | sed s/xTime/$WTIME/g xqsub.pbs > tmp 70 | sed s/train/$1train1/g tmp > xqsub.pbs 71 | 72 | sed s/xResnet56/$O1/g train.sh > queues/$1train1.sh 73 | sed s/xsnapshot/$2_$3/g queues/$1train1.sh > tmp 74 | #sed s/xclrsolver/$1clrsolver1/g queues/$1train1.sh > tmp 75 | sed s/xsolver/$1solver1/g tmp > queues/$1train1.sh 76 | 77 | # 3 78 | sed s/xResnet56/$2_$3/g 1cycsolver.prototxt > tmp # queues/$1solver1.prototxt 79 | #sed s/xResnet56/$2_$3/g solver.prototxt > tmp # queues/$1solver1.prototxt 80 | #sed s/xResnet56/$2_$3/g cifarsolver.prototxt > tmp # queues/$1solver1.prototxt 81 | sed s/xStep/$STEP/g tmp > queues/$1solver1.prototxt 82 | sed s/xIter/$MAXITER/g queues/$1solver1.prototxt > tmp 83 | sed s/xwd/$7/g tmp > queues/$1solver1.prototxt 84 | sed s/xmom1/$MOM1/g queues/$1solver1.prototxt > tmp 85 | sed s/xmom2/$MOM2/g tmp > queues/$1solver1.prototxt 86 | sed s/xWD/$WD/g queues/$1solver1.prototxt > tmp 87 | sed s/xSV5/$IT5/g tmp > queues/$1solver1.prototxt 88 | #sed s/aarch/$3/g queues/$1solver1.prototxt > tmp 89 | sed s/xLR2/$LR/g queues/$1solver1.prototxt > tmp 90 | sed s/xLR1/$4/g tmp > queues/$1solver1.prototxt 91 | sed s/xSV1/$IT1/g queues/$1solver1.prototxt > tmp 92 | sed s/xSV2/$IT2/g tmp > queues/$1solver1.prototxt 93 | sed s/xSV3/$IT3/g queues/$1solver1.prototxt > tmp 94 | sed s/xSV4/$IT4/g tmp > queues/$1solver1.prototxt 95 | sed s/xSV5/$IT5/g queues/$1solver1.prototxt > tmp 96 | sed s/xmom3/$STEP/g tmp > queues/$1solver1.prototxt 97 | 98 | #sed s/aarch/aarch/g tmp > queues/$1solver1.prototxt 99 | sed s/xBS/$BS1/g architectures/$3.prototxt > tmp # architectures/aarch.prototxt 100 | sed s/msra/xavier/g tmp > architectures/aarch.prototxt 101 | 102 | qsub xqsub.pbs 103 | sleep 10 104 | date 105 | qstat 106 | #exit 107 | sleep 30 108 | 109 | BS1=`echo "$BS + 2" | bc` 110 | #BS1=$BS 111 | echo $BS1 112 | 113 | O1=$3_$2LR$LR$4CM$9.85WD$7Epoch$5BS$BS$1_2 114 | sed s/xout/$O1/g s1.sh >> status.sh 115 | 116 | sed s/xResnet/$2/g qsub.pbs > xqsub.pbs 117 | sed s/xTime/$WTIME/g xqsub.pbs > tmp 118 | sed s/train/$1train2/g tmp > xqsub.pbs 119 | 120 | sed s/xResnet56/$O1/g train.sh > queues/$1train2.sh 121 | sed s/xsnapshot/$2_$3/g queues/$1train2.sh > tmp 122 | sed s/xsolver/$1solver1/g tmp > queues/$1train2.sh 123 | 124 | sed s/xBS/$BS1/g architectures/$3.prototxt > tmp # architectures/aarch.prototxt 125 | sed s/msra/msra/g tmp > architectures/aarch.prototxt 126 | 127 | qsub xqsub.pbs 128 | sleep 10 129 | date 130 | qstat 131 | #exit 132 | sleep 30 133 | 134 | BS1=`echo "$BS + 1" | bc` 135 | #BS1=$BS 136 | echo $BS1 137 | 138 | O1=$3_$2LR$LR$4CM$9.85WD$7Epoch$5BS$BS$1_3 139 | sed s/xout/$O1/g s1.sh >> status.sh 140 | 141 | sed s/xResnet/$2/g qsub.pbs > xqsub.pbs 142 | sed s/xTime/$WTIME/g xqsub.pbs > tmp 143 | sed s/train/$1train3/g tmp > xqsub.pbs 144 | 145 | sed s/xResnet56/$O1/g train.sh > queues/$1train3.sh 146 | sed s/xsnapshot/$2_$3/g queues/$1train3.sh > tmp 147 | sed s/xsolver/$1solver1/g tmp > queues/$1train3.sh 148 | 149 | sed s/aarch/arch/g queues/$1solver1.prototxt > tmp 150 | sed s/xLR1/$4/g tmp > queues/$1solver1.prototxt 151 | 152 | sed s/xBS/$BS1/g architectures/$3.prototxt > tmp # architectures/aarch.prototxt 153 | sed s/msra/xavier/g tmp > architectures/arch.prototxt 154 | 155 | qsub xqsub.pbs 156 | sleep 10 157 | date 158 | qstat 159 | sleep 30 160 | echo $BS 161 | 162 | O1=$3_$2LR$LR$4CM$9.85WD$7Epoch$5BS$BS$1_4 163 | sed s/xout/$O1/g s1.sh >> status.sh 164 | 165 | sed s/xResnet/$2/g qsub.pbs > xqsub.pbs 166 | sed s/xTime/$WTIME/g xqsub.pbs > tmp 167 | sed s/train/$1train4/g tmp > xqsub.pbs 168 | 169 | sed s/xResnet56/$O1/g train.sh > queues/$1train4.sh 170 | sed s/xsnapshot/$2_$3/g queues/$1train4.sh > tmp 171 | sed s/xsolver/$1solver1/g tmp > queues/$1train4.sh 172 | 173 | sed s/xBS/$BS/g architectures/$3.prototxt > tmp # architectures/aarch.prototxt 174 | sed s/msra/msra/g tmp > architectures/arch.prototxt 175 | 176 | qsub xqsub.pbs 177 | sleep 10 178 | date 179 | qstat 180 | 181 | 182 | -------------------------------------------------------------------------------- /Imagenet/inception/a2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncImOrig2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/a2train1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/ma2qsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/a2train1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetM9LR.1WD1e-4BS28_145Epochs5_2 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetM9LR1WD1e-4BS28_iter_600000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/asolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # 19 | -------------------------------------------------------------------------------- /Imagenet/inception/aqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncImOrig1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/atrain1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/maqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/asolver1.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.1 16 | #max_lr: 0.2 17 | lr_policy: "step" # "multistep" 18 | gamma: 0.94 19 | stepsize: 20000 20 | max_iter: 1600000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.9 27 | #cyclical_momentum: 0.93 28 | #cyclical_momentum: 100000 29 | weight_decay: 1e-4 30 | 31 | snapshot: 20000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetM9LR1WD1e-4BS28" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/atrain1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetM9LR.1WD1e-4BS28_145Epochs10_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetM9LR1WD1e-4BS28_iter_880000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/asolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # 19 | -------------------------------------------------------------------------------- /Imagenet/inception/b2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncIm100E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/b2train1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mb2qsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/b2qsub2.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncIm50E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/b2train2.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/b2train1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs5_2 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs_iter_700000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 19 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 20 | -------------------------------------------------------------------------------- /Imagenet/inception/b2train2.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-7BS28_50Epochs3_2 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_50Epochs_iter_160000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver2.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs_iter_100000.solverstate \ 19 | 20 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 21 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 22 | -------------------------------------------------------------------------------- /Imagenet/inception/bqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncIm100E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/btrain1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/bqsub2.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncIm50E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/btrain2.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/bqsub35.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncWD5Im20E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/btrain35.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/bqsub36.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncWD36Im20E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/btrain36.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/bqsub5.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=52:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncWD5Im20E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/btrain5.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/bqsub6.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncWD6Im20E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/inception/btrain6.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/inception/mbqsub1.pbs 23 | 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/inception/bsolver1.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.05 16 | max_lr: 1.0 17 | lr_policy: "1cycle" # "step" # "multistep" 18 | #gamma: 0.94 19 | stepsize: 500000 20 | max_iter: 1100000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.95 27 | cyclical_momentum: 0.85 28 | cyclical_momentum: 500000 29 | weight_decay: 1e-7 30 | 31 | snapshot: 25000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/bsolver2.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.05 16 | max_lr: 1.0 17 | lr_policy: "1cycle" # "step" # "multistep" 18 | #gamma: 0.94 19 | stepsize: 240000 20 | max_iter: 550000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.95 27 | cyclical_momentum: 0.85 28 | cyclical_momentum: 240000 29 | weight_decay: 1e-7 30 | 31 | snapshot: 20000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_50Epochs" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/bsolver35.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.05 16 | max_lr: 1.0 17 | lr_policy: "1cycle" # "step" # "multistep" 18 | #gamma: 0.94 19 | stepsize: 108000 20 | max_iter: 220000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.95 27 | cyclical_momentum: 0.85 28 | cyclical_momentum: 1080000 29 | weight_decay: 1e-5 30 | 31 | snapshot: 20000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/bsolver36.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.05 16 | max_lr: 1.0 17 | lr_policy: "1cycle" # "step" # "multistep" 18 | #gamma: 0.94 19 | stepsize: 108000 20 | max_iter: 220000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.95 27 | cyclical_momentum: 0.85 28 | cyclical_momentum: 1080000 29 | weight_decay: 3e-6 30 | 31 | snapshot: 25000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD3e-6BS28_20Epochs" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/bsolver5.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.05 16 | max_lr: 1.0 17 | lr_policy: "1cycle" # "step" # "multistep" 18 | #gamma: 0.94 19 | stepsize: 108000 20 | max_iter: 220000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.95 27 | cyclical_momentum: 0.85 28 | cyclical_momentum: 1080000 29 | weight_decay: 1e-5 30 | 31 | snapshot: 25000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/bsolver6.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 3 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 5 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 6 | net: "examples/bk_imagenet/architectures/inception-resnet-v2.prototxt" 7 | #net: "examples/bk_imagenet/architectures/inception-2ndOrder.prototxt" 8 | 9 | test_iter: 1000 10 | test_interval: 500 11 | display: 500 12 | average_loss: 500 13 | test_initialization: false 14 | 15 | base_lr: 0.05 16 | max_lr: 1.0 17 | lr_policy: "1cycle" # "step" # "multistep" 18 | #gamma: 0.94 19 | stepsize: 108000 20 | max_iter: 220000 21 | 22 | #stepvalue: 700000 23 | #stepvalue: 1000000 24 | #stepvalue: 1100000 25 | 26 | momentum: 0.95 27 | cyclical_momentum: 0.85 28 | cyclical_momentum: 1080000 29 | weight_decay: 1e-6 30 | 31 | snapshot: 20000 32 | snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-6BS28_20Epochs" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/inception-resnetCM9893CLR1WD1e-7" 34 | #snapshot_prefix: "examples/bk_imagenet/snapshots/ResnetCycMom" 35 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 36 | 37 | solver_mode: GPU 38 | type: "Nesterov" 39 | #type: "Adam" 40 | #clip_gradients: 1.0 41 | #iter_size: 4 42 | #debug_info: true 43 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs5_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs_iter_575000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 19 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 20 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain2.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-7BS28_50Epochs3_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_50Epochs_iter_180000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver2.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs_iter_100000.solverstate \ 19 | 20 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 21 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 22 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain3.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs2_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs_iter_100000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 19 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 20 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain35.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs2_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs_iter_100000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver35.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | # 18 | exit 19 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain36.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD3e-6BS28_20Epochs2_2 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD3e-6BS28_20Epochs_iter_125000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver36.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | # 18 | 19 | exit 20 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 21 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 22 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain4.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs2_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-7BS28_100Epochs_iter_100000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | exit 18 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 19 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 20 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain5.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs3_2 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-5BS28_20Epochs_iter_50000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver5.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | # 18 | exit 19 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | -------------------------------------------------------------------------------- /Imagenet/inception/btrain6.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | OUT=inception-resnetCM9585CLR.051WD1e-6BS28_20Epochs2_1 5 | 6 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 7 | 8 | TOOLS=/gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/build/tools 9 | #TOOLS=./build/tools 10 | 11 | #rm -f examples/bk_imagenet/results/$OUT 12 | 13 | $TOOLS/caffe.bin train \ 14 | --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD1e-6BS28_20Epochs_iter_180000.solverstate \ 15 | --gpu=all --solver=examples/bk_imagenet/queues/inception/bsolver6.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/$OUT 16 | 17 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetCM9585CLR.051WD3e-6BS28_20Epochs_iter_80000.solverstate \ 18 | 19 | 20 | exit 21 | # --snapshot=examples/bk_imagenet/snapshots/inception-resnetM95CLR2WD1e-7_iter_50000.solverstate \ 22 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 23 | -------------------------------------------------------------------------------- /Imagenet/inception/ma2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncImOrig2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/inception/a2train1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/inception/a2qsub1.pbs 24 | 25 | 26 | exit 27 | #module use $PROJECTS_HOME/datools/modulefiles 28 | #module load anaconda/2 29 | #module load caffe/5.0 30 | #module list 31 | 32 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 33 | 34 | #./examples/bk_imagenet/train.sh 35 | 36 | -------------------------------------------------------------------------------- /Imagenet/inception/maqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncImOrig1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/inception/atrain1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/inception/aqsub1.pbs 24 | 25 | 26 | exit 27 | #module use $PROJECTS_HOME/datools/modulefiles 28 | #module load anaconda/2 29 | #module load caffe/5.0 30 | #module list 31 | 32 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 33 | 34 | #./examples/bk_imagenet/train.sh 35 | 36 | -------------------------------------------------------------------------------- /Imagenet/inception/mb2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncIm100E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | exit 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/inception/b2train1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/inception/b2qsub1.pbs 24 | 25 | 26 | exit 27 | #module use $PROJECTS_HOME/datools/modulefiles 28 | #module load anaconda/2 29 | #module load caffe/5.0 30 | #module list 31 | 32 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 33 | 34 | #./examples/bk_imagenet/train.sh 35 | 36 | -------------------------------------------------------------------------------- /Imagenet/inception/mbqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncIm100E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/inception/btrain1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/inception/bqsub1.pbs 24 | 25 | 26 | exit 27 | #module use $PROJECTS_HOME/datools/modulefiles 28 | #module load anaconda/2 29 | #module load caffe/5.0 30 | #module list 31 | 32 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 33 | 34 | #./examples/bk_imagenet/train.sh 35 | 36 | -------------------------------------------------------------------------------- /Imagenet/inception/qsub2.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N IncImWD7 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | exit 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/incept.sh 22 | 23 | #qsub ./examples/bk_imagenet/queues/incept.pbs 24 | 25 | 26 | exit 27 | #module use $PROJECTS_HOME/datools/modulefiles 28 | #module load anaconda/2 29 | #module load caffe/5.0 30 | #module list 31 | 32 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 33 | 34 | #./examples/bk_imagenet/train.sh 35 | 36 | -------------------------------------------------------------------------------- /Imagenet/inception/sub.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | qsub aqsub1.pbs 5 | sleep 5 6 | qsub a2qsub1.pbs 7 | sleep 5 8 | qsub bqsub1.pbs 9 | sleep 5 10 | qsub b2qsub1.pbs 11 | 12 | 13 | 14 | 15 | exit 16 | 17 | -------------------------------------------------------------------------------- /Imagenet/resnet/a2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResImOrig2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/a2train1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet/ma2qsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/a2train1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --snapshot=examples/bk_imagenet/snapshots/resnetM9LR1WD1e-4BS32_iter_700000.solverstate \ 10 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/asolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetM9LR1WD1e-4BS32_145Epochs6_2 11 | 12 | exit 13 | 14 | -------------------------------------------------------------------------------- /Imagenet/resnet/aqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResImOrig1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/atrain1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet/maqsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/asolver1.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.1 13 | #max_lr: 0.2 14 | lr_policy: "step" # "multistep" 15 | gamma: 0.94 16 | stepsize: 20000 17 | max_iter: 1600000 18 | 19 | #stepvalue: 700000 20 | #stepvalue: 950000 21 | #stepvalue: 1100000 22 | #stepvalue: 1150000 23 | 24 | momentum: 0.9 25 | #cyclical_momentum: 0.93 26 | #cyclical_momentum: 100000 27 | weight_decay: 1e-4 28 | 29 | snapshot: 25000 30 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetM9LR1WD1e-4BS32" 31 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 33 | 34 | solver_mode: GPU 35 | type: "Nesterov" 36 | #type: "Adam" 37 | #iter_size: 2 38 | -------------------------------------------------------------------------------- /Imagenet/resnet/atrain1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --snapshot=examples/bk_imagenet/snapshots/resnetM9LR1WD1e-4BS32_iter_1300000.solverstate \ 10 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/asolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetM9LR1WD1e-4BS32_145Epochs10_1 11 | 12 | exit 13 | 14 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm100E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/b2train1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet/maqsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2qsub2.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm50E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/b2train2.sh 21 | 22 | qsub ./examples/bk_imagenet/queues/resnet/maqsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2qsub3.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm100E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/b2train1.sh 21 | 22 | qsub ./examples/bk_imagenet/queues/resnet/maqsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2qsub4.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm100E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/b2train1.sh 21 | 22 | qsub ./examples/bk_imagenet/queues/resnet/maqsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2train1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --snapshot=examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-7BS32_100Epochs_iter_875000.solverstate \ 10 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_100Epochs6_2 11 | 12 | exit 13 | # 14 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2train2.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver2.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_50Epochs1_2 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | 15 | $TOOLS/caffe.bin train \ 16 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 17 | 18 | exit 19 | 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 22 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 23 | 24 | 25 | $TOOLS/caffe train \ 26 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 27 | 28 | exit 29 | 30 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2train3.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver3.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_20Epochs1_2 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | 15 | $TOOLS/caffe.bin train \ 16 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 17 | 18 | exit 19 | 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 22 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 23 | 24 | 25 | $TOOLS/caffe train \ 26 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 27 | 28 | exit 29 | 30 | -------------------------------------------------------------------------------- /Imagenet/resnet/b2train4.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver4.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_10Epochs1_2 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | 15 | $TOOLS/caffe.bin train \ 16 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 17 | 18 | exit 19 | 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 22 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 23 | 24 | 25 | $TOOLS/caffe train \ 26 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 27 | 28 | exit 29 | 30 | -------------------------------------------------------------------------------- /Imagenet/resnet/bqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm100E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/btrain1.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet/mbqsub1.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/bqsub2.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm50E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/btrain2.sh 21 | 22 | qsub ./examples/bk_imagenet/queues/resnet/mbqsub2.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/bqsub3.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm20E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/btrain3.sh 21 | 22 | qsub ./examples/bk_imagenet/queues/resnet/mbqsub3.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/bqsub35.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResWD5Im20E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/btrain35.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet/mbqsub3.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/bqsub36.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResWD36Im20E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/btrain36.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet/mbqsub3.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/bqsub4.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm10E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet/btrain4.sh 21 | 22 | qsub ./examples/bk_imagenet/queues/resnet/mbqsub4.pbs 23 | 24 | exit 25 | #module use $PROJECTS_HOME/datools/modulefiles 26 | #module load anaconda/2 27 | #module load caffe/5.0 28 | #module list 29 | 30 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 31 | 32 | #./examples/bk_imagenet/train.sh 33 | 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/bsolver1.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.05 13 | max_lr: 1.0 14 | lr_policy: "1cycle" # "step" # "multistep" 15 | #gamma: 0.94 16 | stepsize: 440000 17 | max_iter: 980000 18 | #max_iter: 1200000 19 | 20 | #stepvalue: 700000 21 | #stepvalue: 950000 22 | #stepvalue: 1100000 23 | #stepvalue: 1150000 24 | 25 | momentum: 0.95 26 | cyclical_momentum: 0.85 27 | cyclical_momentum: 440000 28 | weight_decay: 1e-7 29 | 30 | snapshot: 25000 31 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-7BS32_100Epochs" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 34 | 35 | solver_mode: GPU 36 | type: "Nesterov" 37 | #type: "Adam" 38 | #iter_size: 2 39 | -------------------------------------------------------------------------------- /Imagenet/resnet/bsolver2.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.05 13 | max_lr: 1.0 14 | lr_policy: "1cycle" # "step" # "multistep" 15 | #gamma: 0.94 16 | stepsize: 210000 17 | max_iter: 490000 18 | 19 | #max_iter: 1200000 20 | #stepvalue: 700000 21 | #stepvalue: 950000 22 | #stepvalue: 1100000 23 | #stepvalue: 1150000 24 | 25 | momentum: 0.95 26 | cyclical_momentum: 0.85 27 | cyclical_momentum: 210000 28 | weight_decay: 1e-7 29 | 30 | snapshot: 25000 31 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-7BS32_50Epochs" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 34 | 35 | solver_mode: GPU 36 | type: "Nesterov" 37 | #type: "Adam" 38 | #iter_size: 2 39 | -------------------------------------------------------------------------------- /Imagenet/resnet/bsolver3.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.05 13 | max_lr: 1.0 14 | lr_policy: "1cycle" # "step" # "multistep" 15 | #gamma: 0.94 16 | stepsize: 75000 17 | max_iter: 200000 # 20 epochs 18 | 19 | #max_iter: 1200000 20 | #stepvalue: 700000 21 | #stepvalue: 950000 22 | #stepvalue: 1100000 23 | #stepvalue: 1150000 24 | 25 | momentum: 0.95 26 | cyclical_momentum: 0.85 27 | cyclical_momentum: 75000 28 | weight_decay: 1e-5 29 | 30 | snapshot: 20000 31 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-5BS32_20Epochs" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 34 | 35 | solver_mode: GPU 36 | type: "Nesterov" 37 | #type: "Adam" 38 | #iter_size: 2 39 | -------------------------------------------------------------------------------- /Imagenet/resnet/bsolver35.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.05 13 | max_lr: 1 14 | lr_policy: "1cycle" # "step" # "multistep" 15 | #gamma: 0.94 16 | stepsize: 95000 17 | max_iter: 200000 # 20 epochs 18 | 19 | #max_iter: 1200000 20 | #stepvalue: 700000 21 | #stepvalue: 950000 22 | #stepvalue: 1100000 23 | #stepvalue: 1150000 24 | 25 | momentum: 0.95 26 | cyclical_momentum: 0.85 27 | cyclical_momentum: 95000 28 | weight_decay: 1e-5 29 | 30 | snapshot: 25000 31 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-5BS32_20Epochs" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 34 | 35 | solver_mode: GPU 36 | type: "Nesterov" 37 | #type: "Adam" 38 | #iter_size: 2 39 | -------------------------------------------------------------------------------- /Imagenet/resnet/bsolver36.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.05 13 | max_lr: 1.0 14 | lr_policy: "1cycle" # "step" # "multistep" 15 | #gamma: 0.94 16 | stepsize: 95000 17 | max_iter: 200000 # 20 epochs 18 | 19 | #max_iter: 1200000 20 | #stepvalue: 700000 21 | #stepvalue: 950000 22 | #stepvalue: 1100000 23 | #stepvalue: 1150000 24 | 25 | momentum: 0.95 26 | cyclical_momentum: 0.85 27 | cyclical_momentum: 95000 28 | weight_decay: 3e-6 29 | 30 | snapshot: 20000 31 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD3e-6BS32_20Epochs" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 34 | 35 | solver_mode: GPU 36 | type: "Nesterov" 37 | #type: "Adam" 38 | #iter_size: 2 39 | -------------------------------------------------------------------------------- /Imagenet/resnet/bsolver4.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/256/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | test_initialization: false 11 | 12 | base_lr: 0.05 13 | max_lr: 1.0 14 | lr_policy: "1cycle" # "step" # "multistep" 15 | #gamma: 0.94 16 | stepsize: 35000 17 | max_iter: 100000 # 10 epochs 18 | 19 | #max_iter: 1200000 20 | #stepvalue: 700000 21 | #stepvalue: 950000 22 | #stepvalue: 1100000 23 | #stepvalue: 1150000 24 | 25 | momentum: 0.95 26 | cyclical_momentum: 0.85 27 | cyclical_momentum: 35000 28 | weight_decay: 1e-7 29 | 30 | snapshot: 25000 31 | snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-7BS32_10Epochs" 32 | #snapshot_prefix: "examples/bk_imagenet/snapshots/resnetCM9893CLR1WD1e-7" 33 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 34 | 35 | solver_mode: GPU 36 | type: "Nesterov" 37 | #type: "Adam" 38 | #iter_size: 2 39 | -------------------------------------------------------------------------------- /Imagenet/resnet/btrain1.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --snapshot=examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-7BS32_100Epochs_iter_525000.solverstate \ 10 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver1.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_100Epochs4_1 11 | 12 | exit 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | -------------------------------------------------------------------------------- /Imagenet/resnet/btrain2.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver2.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_50Epochs1_1 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | 15 | $TOOLS/caffe.bin train \ 16 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 17 | 18 | exit 19 | 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 22 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 23 | 24 | 25 | $TOOLS/caffe train \ 26 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 27 | 28 | exit 29 | 30 | -------------------------------------------------------------------------------- /Imagenet/resnet/btrain3.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver3.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-5BS32_20Epochs1_1 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | 15 | $TOOLS/caffe.bin train \ 16 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 17 | 18 | exit 19 | 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 22 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 23 | 24 | 25 | $TOOLS/caffe train \ 26 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 27 | 28 | exit 29 | 30 | -------------------------------------------------------------------------------- /Imagenet/resnet/btrain35.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver35.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-5BS32_20Epochs1_2 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD1e-6BS32_20Epochs_iter_20000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 15 | 16 | $TOOLS/caffe.bin train \ 17 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 18 | 19 | exit 20 | 21 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 22 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 23 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 24 | 25 | 26 | $TOOLS/caffe train \ 27 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 28 | 29 | exit 30 | 31 | -------------------------------------------------------------------------------- /Imagenet/resnet/btrain36.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --snapshot=examples/bk_imagenet/snapshots/resnetCM9585CLR.051WD3e-6BS32_20Epochs_iter_80000.solverstate \ 10 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver36.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD3e-6BS32_20Epochs2_1 11 | 12 | exit 13 | # 14 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 15 | 16 | $TOOLS/caffe.bin train \ 17 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 18 | 19 | exit 20 | 21 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 22 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 23 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 24 | 25 | 26 | $TOOLS/caffe train \ 27 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 28 | 29 | exit 30 | 31 | -------------------------------------------------------------------------------- /Imagenet/resnet/btrain4.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64 5 | 6 | TOOLS=./build/tools 7 | 8 | $TOOLS/caffe.bin train \ 9 | --gpu=all --solver=examples/bk_imagenet/queues/resnet/bsolver4.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/resnetCM9585CLR.051WD1e-7BS32_10Epochs1_1 10 | 11 | exit 12 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 13 | # --snapshot=examples/bk_imagenet/snapshots/resnetM95CLR1WD1e-7_iter_50000.solverstate \ 14 | 15 | $TOOLS/caffe.bin train \ 16 | --gpu=all --solver=examples/bk_imagenet/clrsolver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/range2ndOrder50NoReLUs 17 | 18 | exit 19 | 20 | # --weights=examples/bk_imagenet/snapshots/range2ndOrder_iter_15000.caffemodel \ 21 | # --weights=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.caffemodel \ 22 | # --snapshot=examples/bk_imagenet/snapshots/rangeResnet56_iter_15000.solverstate \ 23 | 24 | 25 | $TOOLS/caffe train \ 26 | --gpu=0 --solver=examples/bk_imagenet/init_solver.prototxt $@ 2>&1 | tee examples/bk_imagenet/results/initTaylor 27 | 28 | exit 29 | 30 | -------------------------------------------------------------------------------- /Imagenet/resnet/ma2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResImOrig2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/resnet/a2train1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/resnet/a2qsub1.pbs 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/maqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResImOrig2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | exit 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/resnet/atrain1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/resnet/aqsub1.pbs 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/mb2qsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm100E2 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/resnet/b2train1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/resnet/b2qsub1.pbs 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/mbqsub1.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResIm100E1 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | exit 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/resnet/btrain1.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/resnet/bqsub1.pbs 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/qsub2.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4:powerai=on 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResImOrig 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | exit 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/resnet/asolver1.sh 22 | 23 | #qsub ./examples/bk_imagenet/queues/resnet256.pbs 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/resnet.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=24:mpiprocs=24:ngpus=4 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResImM95 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | 12 | . /usr/share/Modules/init/sh 13 | module load glog/0.3.3 14 | module load gflags/2.2.0 15 | 16 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 17 | 18 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 19 | 20 | ./examples/bk_imagenet/queues/resnet.sh 21 | 22 | #qsub ./examples/bk_imagenet/queues/resnet.pbs 23 | 24 | exit 25 | #PBS -q R17906 26 | 27 | #module use $PROJECTS_HOME/datools/modulefiles 28 | #module load anaconda/2 29 | #module load caffe/5.0 30 | #module list 31 | 32 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 33 | 34 | #./examples/bk_imagenet/train.sh 35 | 36 | -------------------------------------------------------------------------------- /Imagenet/resnet/resnet.prototxt: -------------------------------------------------------------------------------- 1 | net: "examples/bk_imagenet/architectures/resnet50.prototxt" 2 | #net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 500 8 | display: 500 9 | average_loss: 500 10 | 11 | base_lr: 0 12 | max_lr: 0.1 13 | lr_policy: "triangular" # "multistep" 14 | gamma: 0.1 15 | stepsize: 100000 16 | max_iter: 100000 17 | #max_iter: 1200000 18 | 19 | stepvalue: 700000 20 | stepvalue: 950000 21 | stepvalue: 1100000 22 | stepvalue: 1150000 23 | 24 | momentum: 0.95 25 | weight_decay: 1e-4 26 | 27 | snapshot: 50000 28 | snapshot_prefix: "examples/bk_imagenet/snapshots/Resnet50" 29 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 30 | 31 | solver_mode: GPU 32 | #type: "Nesterov" 33 | #type: "Adam" 34 | -------------------------------------------------------------------------------- /Imagenet/resnet/resnetNoRelus.pbs: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | #PBS -l walltime=72:00:00 3 | #PBS -l select=1:ncpus=160:mpiprocs=160:ngpus=4 4 | #PBS -l place=scatter:excl 5 | #PBS -N ResnetNoRIm 6 | #PBS -j oe 7 | #PBS -V 8 | #PBS -q standard 9 | #PBS -A MHPCC96650NRL 10 | 11 | exit 12 | 13 | . /usr/share/Modules/init/sh 14 | module load glog/0.3.3 15 | module load gflags/2.2.0 16 | 17 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/gpfs/pkgs/mhpcc/protobuf/lib:/gpfs/pkgs/mhpcc/boost/lib:/gpfs/pkgs/mhpcc/lmdb/lib:/gpfs/pkgs/mhpcc/leveldb/lib:/gpfs/pkgs/mhpcc/opencv-3.4.0/lib64 18 | 19 | cd /gpfs/scratch/lnsmith/deepLearning/caffe/9-11-17/ 20 | 21 | ./examples/bk_imagenet/queues/resnetNoRelus.sh 22 | 23 | qsub ./examples/bk_imagenet/queues/resnetNoRelus.pbs 24 | 25 | exit 26 | #module use $PROJECTS_HOME/datools/modulefiles 27 | #module load anaconda/2 28 | #module load caffe/5.0 29 | #module list 30 | 31 | #cd /gpfs/scratch/lnsmith/deepLearning/fewTrainingData/imagenet 32 | 33 | #./examples/bk_imagenet/train.sh 34 | 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/resnetNoRelus.prototxt: -------------------------------------------------------------------------------- 1 | #net: "examples/bk_imagenet/architectures/fullResnet50.prototxt" 2 | net: "examples/bk_imagenet/architectures/resnet50noReLU.prototxt" 3 | #net: "examples/bk_imagenet/architectures/2ndOrder50Imagenet.prototxt" 4 | #net: "examples/bk_imagenet/architectures/2ndOrder50noReLU.prototxt" 5 | 6 | test_iter: 1000 7 | test_interval: 1000 8 | display: 200 9 | average_loss: 1000 10 | 11 | base_lr: .1 12 | #max_lr: 0.15 13 | lr_policy: "multistep" 14 | gamma: 0.1 15 | stepsize: 100000 16 | 17 | max_iter: 300000 18 | #max_iter: 1200000 19 | 20 | stepvalue: 700000 21 | stepvalue: 950000 22 | stepvalue: 1100000 23 | stepvalue: 1150000 24 | 25 | momentum: 0.9 26 | weight_decay: 0.0001 27 | 28 | snapshot: 50000 29 | snapshot_prefix: "examples/bk_imagenet/snapshots/Resnet56NoReLUs" 30 | #snapshot_prefix: "examples/bk_imagenet/snapshots/2ndOrder" 31 | 32 | solver_mode: GPU 33 | #type: "Nesterov" 34 | #type: "Adam" 35 | -------------------------------------------------------------------------------- /Imagenet/resnet/sub.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env sh 2 | set -e 3 | 4 | qsub aqsub1.pbs 5 | sleep 5 6 | qsub a2qsub1.pbs 7 | sleep 5 8 | qsub bqsub1.pbs 9 | sleep 5 10 | qsub b2qsub1.pbs 11 | 12 | 13 | 14 | 15 | exit 16 | 17 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # hyperParam1 2 | 3 | Here are some of the Caffe files of my recent NRL Technical Report : Smith, Leslie N. "A disciplined approach to neural network hyper-parameters: Part 1 - learning rate, batch size, momentum, and weight decay" arXiv preprint arXiv:1803.09820 (2018). Please read the report for details. The report is based on over a thousand experiments, with each experiment consisting of four runs to determine the mean and standard deviation of the reported results. Due to the large number of experiments, all the files are not included but the basic files that enable replication of the results should be present. 4 | 5 | This repository contains two folders: Cifar and Imagenet. By far, most of the experiments were with Cifar and there are results for both Cifar-10 and Cifar-100. In this folder are a few versions of the train.sh script, solver.prototxt file, and the scripts used for modifying and submitting the jobs on my system. While the submission scripts are tailored only for my system/environment, they can provide guidance as to the jobs run. In this folder is the architectures folder that contains the architectures used for the experiments. Also included is a few of the output files in the folder called results. These output files might help in replicating my work. 6 | 7 | The Imagenet folder contains 4 folders: architectures, inception, resnet, and results. The resnet and inception prototxt files are in the architectures folder. The inception folder contains my system's submission files, the train.sh scripts, and the solver.prototxt files for running the inception experiments. The resnet folder contains my system's submission files, the train.sh scripts, and the solver.prototxt files for running the resnet experiments. Some of the outputs are contained in the results folder. 8 | 9 | The files in this repository are not sufficient to replicate all of the results in the report but they do contain the information that makes replication possible. 10 | --------------------------------------------------------------------------------