From d9d52b7e2c972310a09c8e84766067576fc4bd75 Mon Sep 17 00:00:00 2001 From: Daisy Deng Date: Tue, 5 Sep 2017 00:35:35 +0800 Subject: [PATCH] add googlenet v2 8 nodes solver --- .../googlenet_16nodes/solver.prototxt | 27 - .../googlenet_16nodes/train_val.prototxt | 2434 ----------------- .../googlenet_v2_4nodes/solver.prototxt | 24 - .../googlenet_v2_8nodes/solver.prototxt | 15 + .../train_val.prototxt | 0 .../resnet_50_16_nodes/solver.prototxt | 15 - .../resnet_50_16_nodes/train_val.prototxt | 2306 ---------------- 7 files changed, 15 insertions(+), 4806 deletions(-) delete mode 100644 models/intel_optimized_models/multinode/googlenet_16nodes/solver.prototxt delete mode 100644 models/intel_optimized_models/multinode/googlenet_16nodes/train_val.prototxt delete mode 100644 models/intel_optimized_models/multinode/googlenet_v2_4nodes/solver.prototxt create mode 100644 models/intel_optimized_models/multinode/googlenet_v2_8nodes/solver.prototxt rename models/intel_optimized_models/multinode/{googlenet_v2_4nodes => googlenet_v2_8nodes}/train_val.prototxt (100%) delete mode 100644 models/intel_optimized_models/multinode/resnet_50_16_nodes/solver.prototxt delete mode 100644 models/intel_optimized_models/multinode/resnet_50_16_nodes/train_val.prototxt diff --git a/models/intel_optimized_models/multinode/googlenet_16nodes/solver.prototxt b/models/intel_optimized_models/multinode/googlenet_16nodes/solver.prototxt deleted file mode 100644 index 4c9b59fc4..000000000 --- a/models/intel_optimized_models/multinode/googlenet_16nodes/solver.prototxt +++ /dev/null @@ -1,27 +0,0 @@ -#This is Intel(R) optimized (in terms of time to train) version of solver for model described in the [GoogLeNet](http://arxiv.org/abs/1409.4842) publication. -#Original solver.prototxt can be found in /models/bvlc_googlenet/ directory of this repository. -#Differences: -#- base_lr is set to 0.065 -#- max_iter is set to 100000 -# -#- bias_filler value changed to 0.1 -# -#Top-5 and Top-1 results achieved with this version of solver: -#Top-5: 88.74% -#Top-1: 68.35% -#Training was performed using server equipped with Intel(R) Xeon Phi(TM) CPU 7250 processor. -net: "models/intel_optimized_models/multinode/googlenet_16nodes/train_val.prototxt" -#test_iter: 1000 -#test_interval: 10000 -#test_initialization: false -display: 40 -average_loss: 40 -base_lr: 0.065 -lr_policy: "poly" -power: 0.5 -max_iter: 100000 -momentum: 0.9 -weight_decay: 0.0002 -snapshot: 50000 -snapshot_prefix: "models/intel_optimized_models/multinode/googlenet_16nodes/googlenet" -solver_mode: CPU diff --git a/models/intel_optimized_models/multinode/googlenet_16nodes/train_val.prototxt b/models/intel_optimized_models/multinode/googlenet_16nodes/train_val.prototxt deleted file mode 100644 index f5276ab97..000000000 --- a/models/intel_optimized_models/multinode/googlenet_16nodes/train_val.prototxt +++ /dev/null @@ -1,2434 +0,0 @@ -name: "GoogleNet" -layer { - name: "data" - type: "Data" - top: "data" - top: "label" - include { - phase: TRAIN - } - transform_param { - mirror: true - crop_size: 224 - mean_value: 104 - mean_value: 117 - mean_value: 123 - } - data_param { - source: "examples/imagenet/ilsvrc12_train_lmdb" - batch_size: 64 - backend: LMDB - shuffle: true - } -} -layer { - name: "data" - type: "Data" - top: "data" - top: "label" - include { - phase: TEST - } - transform_param { - mirror: false - crop_size: 224 - mean_value: 104 - mean_value: 117 - mean_value: 123 - } - data_param { - source: "examples/imagenet/ilsvrc12_val_lmdb" - batch_size: 50 - backend: LMDB - } -} -layer { - name: "conv1/7x7_s2" - type: "Convolution" - bottom: "data" - top: "conv1/7x7_s2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 3 - kernel_size: 7 - stride: 2 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "conv1/relu_7x7" - type: "ReLU" - bottom: "conv1/7x7_s2" - top: "conv1/7x7_s2" -} -layer { - name: "pool1/3x3_s2" - type: "Pooling" - bottom: "conv1/7x7_s2" - top: "pool1/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "pool1/norm1" - type: "LRN" - bottom: "pool1/3x3_s2" - top: "pool1/norm1" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "conv2/3x3_reduce" - type: "Convolution" - bottom: "pool1/norm1" - top: "conv2/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "conv2/relu_3x3_reduce" - type: "ReLU" - bottom: "conv2/3x3_reduce" - top: "conv2/3x3_reduce" -} -layer { - name: "conv2/3x3" - type: "Convolution" - bottom: "conv2/3x3_reduce" - top: "conv2/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "conv2/relu_3x3" - type: "ReLU" - bottom: "conv2/3x3" - top: "conv2/3x3" -} -layer { - name: "conv2/norm2" - type: "LRN" - bottom: "conv2/3x3" - top: "conv2/norm2" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - } -} -layer { - name: "pool2/3x3_s2" - type: "Pooling" - bottom: "conv2/norm2" - top: "pool2/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "inception_3a/1x1" - type: "Convolution" - bottom: "pool2/3x3_s2" - top: "inception_3a/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3a/relu_1x1" - type: "ReLU" - bottom: "inception_3a/1x1" - top: "inception_3a/1x1" -} -layer { - name: "inception_3a/3x3_reduce" - type: "Convolution" - bottom: "pool2/3x3_s2" - top: "inception_3a/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3a/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_3a/3x3_reduce" - top: "inception_3a/3x3_reduce" -} -layer { - name: "inception_3a/3x3" - type: "Convolution" - bottom: "inception_3a/3x3_reduce" - top: "inception_3a/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3a/relu_3x3" - type: "ReLU" - bottom: "inception_3a/3x3" - top: "inception_3a/3x3" -} -layer { - name: "inception_3a/5x5_reduce" - type: "Convolution" - bottom: "pool2/3x3_s2" - top: "inception_3a/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3a/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_3a/5x5_reduce" - top: "inception_3a/5x5_reduce" -} -layer { - name: "inception_3a/5x5" - type: "Convolution" - bottom: "inception_3a/5x5_reduce" - top: "inception_3a/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3a/relu_5x5" - type: "ReLU" - bottom: "inception_3a/5x5" - top: "inception_3a/5x5" -} -layer { - name: "inception_3a/pool" - type: "Pooling" - bottom: "pool2/3x3_s2" - top: "inception_3a/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_3a/pool_proj" - type: "Convolution" - bottom: "inception_3a/pool" - top: "inception_3a/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3a/relu_pool_proj" - type: "ReLU" - bottom: "inception_3a/pool_proj" - top: "inception_3a/pool_proj" -} -layer { - name: "inception_3a/output" - type: "Concat" - bottom: "inception_3a/1x1" - bottom: "inception_3a/3x3" - bottom: "inception_3a/5x5" - bottom: "inception_3a/pool_proj" - top: "inception_3a/output" -} -layer { - name: "inception_3b/1x1" - type: "Convolution" - bottom: "inception_3a/output" - top: "inception_3b/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3b/relu_1x1" - type: "ReLU" - bottom: "inception_3b/1x1" - top: "inception_3b/1x1" -} -layer { - name: "inception_3b/3x3_reduce" - type: "Convolution" - bottom: "inception_3a/output" - top: "inception_3b/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3b/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_3b/3x3_reduce" - top: "inception_3b/3x3_reduce" -} -layer { - name: "inception_3b/3x3" - type: "Convolution" - bottom: "inception_3b/3x3_reduce" - top: "inception_3b/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3b/relu_3x3" - type: "ReLU" - bottom: "inception_3b/3x3" - top: "inception_3b/3x3" -} -layer { - name: "inception_3b/5x5_reduce" - type: "Convolution" - bottom: "inception_3a/output" - top: "inception_3b/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3b/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_3b/5x5_reduce" - top: "inception_3b/5x5_reduce" -} -layer { - name: "inception_3b/5x5" - type: "Convolution" - bottom: "inception_3b/5x5_reduce" - top: "inception_3b/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3b/relu_5x5" - type: "ReLU" - bottom: "inception_3b/5x5" - top: "inception_3b/5x5" -} -layer { - name: "inception_3b/pool" - type: "Pooling" - bottom: "inception_3a/output" - top: "inception_3b/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_3b/pool_proj" - type: "Convolution" - bottom: "inception_3b/pool" - top: "inception_3b/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_3b/relu_pool_proj" - type: "ReLU" - bottom: "inception_3b/pool_proj" - top: "inception_3b/pool_proj" -} -layer { - name: "inception_3b/output" - type: "Concat" - bottom: "inception_3b/1x1" - bottom: "inception_3b/3x3" - bottom: "inception_3b/5x5" - bottom: "inception_3b/pool_proj" - top: "inception_3b/output" -} -layer { - name: "pool3/3x3_s2" - type: "Pooling" - bottom: "inception_3b/output" - top: "pool3/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "inception_4a/1x1" - type: "Convolution" - bottom: "pool3/3x3_s2" - top: "inception_4a/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4a/relu_1x1" - type: "ReLU" - bottom: "inception_4a/1x1" - top: "inception_4a/1x1" -} -layer { - name: "inception_4a/3x3_reduce" - type: "Convolution" - bottom: "pool3/3x3_s2" - top: "inception_4a/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4a/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4a/3x3_reduce" - top: "inception_4a/3x3_reduce" -} -layer { - name: "inception_4a/3x3" - type: "Convolution" - bottom: "inception_4a/3x3_reduce" - top: "inception_4a/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 208 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4a/relu_3x3" - type: "ReLU" - bottom: "inception_4a/3x3" - top: "inception_4a/3x3" -} -layer { - name: "inception_4a/5x5_reduce" - type: "Convolution" - bottom: "pool3/3x3_s2" - top: "inception_4a/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 16 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4a/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4a/5x5_reduce" - top: "inception_4a/5x5_reduce" -} -layer { - name: "inception_4a/5x5" - type: "Convolution" - bottom: "inception_4a/5x5_reduce" - top: "inception_4a/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 48 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4a/relu_5x5" - type: "ReLU" - bottom: "inception_4a/5x5" - top: "inception_4a/5x5" -} -layer { - name: "inception_4a/pool" - type: "Pooling" - bottom: "pool3/3x3_s2" - top: "inception_4a/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4a/pool_proj" - type: "Convolution" - bottom: "inception_4a/pool" - top: "inception_4a/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4a/relu_pool_proj" - type: "ReLU" - bottom: "inception_4a/pool_proj" - top: "inception_4a/pool_proj" -} -layer { - name: "inception_4a/output" - type: "Concat" - bottom: "inception_4a/1x1" - bottom: "inception_4a/3x3" - bottom: "inception_4a/5x5" - bottom: "inception_4a/pool_proj" - top: "inception_4a/output" -} -layer { - name: "loss1/ave_pool" - type: "Pooling" - bottom: "inception_4a/output" - top: "loss1/ave_pool" - pooling_param { - pool: AVE - kernel_size: 5 - stride: 3 - } -} -layer { - name: "loss1/conv" - type: "Convolution" - bottom: "loss1/ave_pool" - top: "loss1/conv" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "loss1/relu_conv" - type: "ReLU" - bottom: "loss1/conv" - top: "loss1/conv" -} -layer { - name: "loss1/fc" - type: "InnerProduct" - bottom: "loss1/conv" - top: "loss1/fc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1024 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "loss1/relu_fc" - type: "ReLU" - bottom: "loss1/fc" - top: "loss1/fc" -} -layer { - name: "loss1/drop_fc" - type: "Dropout" - bottom: "loss1/fc" - top: "loss1/fc" - dropout_param { - dropout_ratio: 0.7 - } -} -layer { - name: "loss1/classifier" - type: "InnerProduct" - bottom: "loss1/fc" - top: "loss1/classifier" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "loss1/loss" - type: "SoftmaxWithLoss" - bottom: "loss1/classifier" - bottom: "label" - top: "loss1/loss1" - loss_weight: 0.3 -} -layer { - name: "loss1/top-1" - type: "Accuracy" - bottom: "loss1/classifier" - bottom: "label" - top: "loss1/top-1" - include { - phase: TEST - } -} -layer { - name: "loss1/top-5" - type: "Accuracy" - bottom: "loss1/classifier" - bottom: "label" - top: "loss1/top-5" - include { - phase: TEST - } - accuracy_param { - top_k: 5 - } -} -layer { - name: "inception_4b/1x1" - type: "Convolution" - bottom: "inception_4a/output" - top: "inception_4b/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 160 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4b/relu_1x1" - type: "ReLU" - bottom: "inception_4b/1x1" - top: "inception_4b/1x1" -} -layer { - name: "inception_4b/3x3_reduce" - type: "Convolution" - bottom: "inception_4a/output" - top: "inception_4b/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 112 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4b/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4b/3x3_reduce" - top: "inception_4b/3x3_reduce" -} -layer { - name: "inception_4b/3x3" - type: "Convolution" - bottom: "inception_4b/3x3_reduce" - top: "inception_4b/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 224 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4b/relu_3x3" - type: "ReLU" - bottom: "inception_4b/3x3" - top: "inception_4b/3x3" -} -layer { - name: "inception_4b/5x5_reduce" - type: "Convolution" - bottom: "inception_4a/output" - top: "inception_4b/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4b/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4b/5x5_reduce" - top: "inception_4b/5x5_reduce" -} -layer { - name: "inception_4b/5x5" - type: "Convolution" - bottom: "inception_4b/5x5_reduce" - top: "inception_4b/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4b/relu_5x5" - type: "ReLU" - bottom: "inception_4b/5x5" - top: "inception_4b/5x5" -} -layer { - name: "inception_4b/pool" - type: "Pooling" - bottom: "inception_4a/output" - top: "inception_4b/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4b/pool_proj" - type: "Convolution" - bottom: "inception_4b/pool" - top: "inception_4b/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4b/relu_pool_proj" - type: "ReLU" - bottom: "inception_4b/pool_proj" - top: "inception_4b/pool_proj" -} -layer { - name: "inception_4b/output" - type: "Concat" - bottom: "inception_4b/1x1" - bottom: "inception_4b/3x3" - bottom: "inception_4b/5x5" - bottom: "inception_4b/pool_proj" - top: "inception_4b/output" -} -layer { - name: "inception_4c/1x1" - type: "Convolution" - bottom: "inception_4b/output" - top: "inception_4c/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4c/relu_1x1" - type: "ReLU" - bottom: "inception_4c/1x1" - top: "inception_4c/1x1" -} -layer { - name: "inception_4c/3x3_reduce" - type: "Convolution" - bottom: "inception_4b/output" - top: "inception_4c/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4c/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4c/3x3_reduce" - top: "inception_4c/3x3_reduce" -} -layer { - name: "inception_4c/3x3" - type: "Convolution" - bottom: "inception_4c/3x3_reduce" - top: "inception_4c/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4c/relu_3x3" - type: "ReLU" - bottom: "inception_4c/3x3" - top: "inception_4c/3x3" -} -layer { - name: "inception_4c/5x5_reduce" - type: "Convolution" - bottom: "inception_4b/output" - top: "inception_4c/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 24 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4c/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4c/5x5_reduce" - top: "inception_4c/5x5_reduce" -} -layer { - name: "inception_4c/5x5" - type: "Convolution" - bottom: "inception_4c/5x5_reduce" - top: "inception_4c/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4c/relu_5x5" - type: "ReLU" - bottom: "inception_4c/5x5" - top: "inception_4c/5x5" -} -layer { - name: "inception_4c/pool" - type: "Pooling" - bottom: "inception_4b/output" - top: "inception_4c/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4c/pool_proj" - type: "Convolution" - bottom: "inception_4c/pool" - top: "inception_4c/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4c/relu_pool_proj" - type: "ReLU" - bottom: "inception_4c/pool_proj" - top: "inception_4c/pool_proj" -} -layer { - name: "inception_4c/output" - type: "Concat" - bottom: "inception_4c/1x1" - bottom: "inception_4c/3x3" - bottom: "inception_4c/5x5" - bottom: "inception_4c/pool_proj" - top: "inception_4c/output" -} -layer { - name: "inception_4d/1x1" - type: "Convolution" - bottom: "inception_4c/output" - top: "inception_4d/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 112 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4d/relu_1x1" - type: "ReLU" - bottom: "inception_4d/1x1" - top: "inception_4d/1x1" -} -layer { - name: "inception_4d/3x3_reduce" - type: "Convolution" - bottom: "inception_4c/output" - top: "inception_4d/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 144 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4d/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4d/3x3_reduce" - top: "inception_4d/3x3_reduce" -} -layer { - name: "inception_4d/3x3" - type: "Convolution" - bottom: "inception_4d/3x3_reduce" - top: "inception_4d/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 288 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4d/relu_3x3" - type: "ReLU" - bottom: "inception_4d/3x3" - top: "inception_4d/3x3" -} -layer { - name: "inception_4d/5x5_reduce" - type: "Convolution" - bottom: "inception_4c/output" - top: "inception_4d/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4d/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4d/5x5_reduce" - top: "inception_4d/5x5_reduce" -} -layer { - name: "inception_4d/5x5" - type: "Convolution" - bottom: "inception_4d/5x5_reduce" - top: "inception_4d/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4d/relu_5x5" - type: "ReLU" - bottom: "inception_4d/5x5" - top: "inception_4d/5x5" -} -layer { - name: "inception_4d/pool" - type: "Pooling" - bottom: "inception_4c/output" - top: "inception_4d/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4d/pool_proj" - type: "Convolution" - bottom: "inception_4d/pool" - top: "inception_4d/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 64 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4d/relu_pool_proj" - type: "ReLU" - bottom: "inception_4d/pool_proj" - top: "inception_4d/pool_proj" -} -layer { - name: "inception_4d/output" - type: "Concat" - bottom: "inception_4d/1x1" - bottom: "inception_4d/3x3" - bottom: "inception_4d/5x5" - bottom: "inception_4d/pool_proj" - top: "inception_4d/output" -} -layer { - name: "loss2/ave_pool" - type: "Pooling" - bottom: "inception_4d/output" - top: "loss2/ave_pool" - pooling_param { - pool: AVE - kernel_size: 5 - stride: 3 - } -} -layer { - name: "loss2/conv" - type: "Convolution" - bottom: "loss2/ave_pool" - top: "loss2/conv" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "loss2/relu_conv" - type: "ReLU" - bottom: "loss2/conv" - top: "loss2/conv" -} -layer { - name: "loss2/fc" - type: "InnerProduct" - bottom: "loss2/conv" - top: "loss2/fc" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1024 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "loss2/relu_fc" - type: "ReLU" - bottom: "loss2/fc" - top: "loss2/fc" -} -layer { - name: "loss2/drop_fc" - type: "Dropout" - bottom: "loss2/fc" - top: "loss2/fc" - dropout_param { - dropout_ratio: 0.7 - } -} -layer { - name: "loss2/classifier" - type: "InnerProduct" - bottom: "loss2/fc" - top: "loss2/classifier" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "loss2/loss" - type: "SoftmaxWithLoss" - bottom: "loss2/classifier" - bottom: "label" - top: "loss2/loss1" - loss_weight: 0.3 -} -layer { - name: "loss2/top-1" - type: "Accuracy" - bottom: "loss2/classifier" - bottom: "label" - top: "loss2/top-1" - include { - phase: TEST - } -} -layer { - name: "loss2/top-5" - type: "Accuracy" - bottom: "loss2/classifier" - bottom: "label" - top: "loss2/top-5" - include { - phase: TEST - } - accuracy_param { - top_k: 5 - } -} -layer { - name: "inception_4e/1x1" - type: "Convolution" - bottom: "inception_4d/output" - top: "inception_4e/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4e/relu_1x1" - type: "ReLU" - bottom: "inception_4e/1x1" - top: "inception_4e/1x1" -} -layer { - name: "inception_4e/3x3_reduce" - type: "Convolution" - bottom: "inception_4d/output" - top: "inception_4e/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 160 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4e/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_4e/3x3_reduce" - top: "inception_4e/3x3_reduce" -} -layer { - name: "inception_4e/3x3" - type: "Convolution" - bottom: "inception_4e/3x3_reduce" - top: "inception_4e/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 320 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4e/relu_3x3" - type: "ReLU" - bottom: "inception_4e/3x3" - top: "inception_4e/3x3" -} -layer { - name: "inception_4e/5x5_reduce" - type: "Convolution" - bottom: "inception_4d/output" - top: "inception_4e/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4e/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_4e/5x5_reduce" - top: "inception_4e/5x5_reduce" -} -layer { - name: "inception_4e/5x5" - type: "Convolution" - bottom: "inception_4e/5x5_reduce" - top: "inception_4e/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4e/relu_5x5" - type: "ReLU" - bottom: "inception_4e/5x5" - top: "inception_4e/5x5" -} -layer { - name: "inception_4e/pool" - type: "Pooling" - bottom: "inception_4d/output" - top: "inception_4e/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_4e/pool_proj" - type: "Convolution" - bottom: "inception_4e/pool" - top: "inception_4e/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_4e/relu_pool_proj" - type: "ReLU" - bottom: "inception_4e/pool_proj" - top: "inception_4e/pool_proj" -} -layer { - name: "inception_4e/output" - type: "Concat" - bottom: "inception_4e/1x1" - bottom: "inception_4e/3x3" - bottom: "inception_4e/5x5" - bottom: "inception_4e/pool_proj" - top: "inception_4e/output" -} -layer { - name: "pool4/3x3_s2" - type: "Pooling" - bottom: "inception_4e/output" - top: "pool4/3x3_s2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - name: "inception_5a/1x1" - type: "Convolution" - bottom: "pool4/3x3_s2" - top: "inception_5a/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5a/relu_1x1" - type: "ReLU" - bottom: "inception_5a/1x1" - top: "inception_5a/1x1" -} -layer { - name: "inception_5a/3x3_reduce" - type: "Convolution" - bottom: "pool4/3x3_s2" - top: "inception_5a/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 160 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5a/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_5a/3x3_reduce" - top: "inception_5a/3x3_reduce" -} -layer { - name: "inception_5a/3x3" - type: "Convolution" - bottom: "inception_5a/3x3_reduce" - top: "inception_5a/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 320 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5a/relu_3x3" - type: "ReLU" - bottom: "inception_5a/3x3" - top: "inception_5a/3x3" -} -layer { - name: "inception_5a/5x5_reduce" - type: "Convolution" - bottom: "pool4/3x3_s2" - top: "inception_5a/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 32 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5a/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_5a/5x5_reduce" - top: "inception_5a/5x5_reduce" -} -layer { - name: "inception_5a/5x5" - type: "Convolution" - bottom: "inception_5a/5x5_reduce" - top: "inception_5a/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5a/relu_5x5" - type: "ReLU" - bottom: "inception_5a/5x5" - top: "inception_5a/5x5" -} -layer { - name: "inception_5a/pool" - type: "Pooling" - bottom: "pool4/3x3_s2" - top: "inception_5a/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_5a/pool_proj" - type: "Convolution" - bottom: "inception_5a/pool" - top: "inception_5a/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5a/relu_pool_proj" - type: "ReLU" - bottom: "inception_5a/pool_proj" - top: "inception_5a/pool_proj" -} -layer { - name: "inception_5a/output" - type: "Concat" - bottom: "inception_5a/1x1" - bottom: "inception_5a/3x3" - bottom: "inception_5a/5x5" - bottom: "inception_5a/pool_proj" - top: "inception_5a/output" -} -layer { - name: "inception_5b/1x1" - type: "Convolution" - bottom: "inception_5a/output" - top: "inception_5b/1x1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5b/relu_1x1" - type: "ReLU" - bottom: "inception_5b/1x1" - top: "inception_5b/1x1" -} -layer { - name: "inception_5b/3x3_reduce" - type: "Convolution" - bottom: "inception_5a/output" - top: "inception_5b/3x3_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 192 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5b/relu_3x3_reduce" - type: "ReLU" - bottom: "inception_5b/3x3_reduce" - top: "inception_5b/3x3_reduce" -} -layer { - name: "inception_5b/3x3" - type: "Convolution" - bottom: "inception_5b/3x3_reduce" - top: "inception_5b/3x3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5b/relu_3x3" - type: "ReLU" - bottom: "inception_5b/3x3" - top: "inception_5b/3x3" -} -layer { - name: "inception_5b/5x5_reduce" - type: "Convolution" - bottom: "inception_5a/output" - top: "inception_5b/5x5_reduce" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 48 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5b/relu_5x5_reduce" - type: "ReLU" - bottom: "inception_5b/5x5_reduce" - top: "inception_5b/5x5_reduce" -} -layer { - name: "inception_5b/5x5" - type: "Convolution" - bottom: "inception_5b/5x5_reduce" - top: "inception_5b/5x5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - pad: 2 - kernel_size: 5 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5b/relu_5x5" - type: "ReLU" - bottom: "inception_5b/5x5" - top: "inception_5b/5x5" -} -layer { - name: "inception_5b/pool" - type: "Pooling" - bottom: "inception_5a/output" - top: "inception_5b/pool" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - name: "inception_5b/pool_proj" - type: "Convolution" - bottom: "inception_5b/pool" - top: "inception_5b/pool_proj" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 128 - kernel_size: 1 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "inception_5b/relu_pool_proj" - type: "ReLU" - bottom: "inception_5b/pool_proj" - top: "inception_5b/pool_proj" -} -layer { - name: "inception_5b/output" - type: "Concat" - bottom: "inception_5b/1x1" - bottom: "inception_5b/3x3" - bottom: "inception_5b/5x5" - bottom: "inception_5b/pool_proj" - top: "inception_5b/output" -} -layer { - name: "pool5/7x7_s1" - type: "Pooling" - bottom: "inception_5b/output" - top: "pool5/7x7_s1" - pooling_param { - pool: AVE - kernel_size: 7 - stride: 1 - } -} -layer { - name: "pool5/drop_7x7_s1" - type: "Dropout" - bottom: "pool5/7x7_s1" - top: "pool5/7x7_s1" - dropout_param { - dropout_ratio: 0.4 - } -} -layer { - name: "loss3/classifier" - type: "InnerProduct" - bottom: "pool5/7x7_s1" - top: "loss3/classifier" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - weight_filler { - type: "xavier" - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "loss3/loss3" - type: "SoftmaxWithLoss" - bottom: "loss3/classifier" - bottom: "label" - top: "loss3/loss3" - loss_weight: 1 -} -layer { - name: "loss3/top-1" - type: "Accuracy" - bottom: "loss3/classifier" - bottom: "label" - top: "loss3/top-1" - include { - phase: TEST - } -} -layer { - name: "loss3/top-5" - type: "Accuracy" - bottom: "loss3/classifier" - bottom: "label" - top: "loss3/top-5" - include { - phase: TEST - } - accuracy_param { - top_k: 5 - } -} diff --git a/models/intel_optimized_models/multinode/googlenet_v2_4nodes/solver.prototxt b/models/intel_optimized_models/multinode/googlenet_v2_4nodes/solver.prototxt deleted file mode 100644 index dda5240f3..000000000 --- a/models/intel_optimized_models/multinode/googlenet_v2_4nodes/solver.prototxt +++ /dev/null @@ -1,24 +0,0 @@ -#This is Intel(R) optimized (in terms of time to train) version of solver for model GoogLeNet v2. -#Original solver.prototxt can be found in /models/default_resnet_50/ directory of this repository. -#Differences: -#- lr_policy is set to poly instead of step -#- base_lr is set to 0.05 -#- max_iter is decreased to 100000 -# -#Top-5 and Top-1 results achieved with this version of solver: -#Top-5: 89.40% -#Top-1: 69.02% -#Training was performed using server equipped with Intel(R) Xeon Phi(TM) CPU 7250 processor. - -net: "models/intel_optimized_models/multinode/googlenet_v2_4nodes/train_val.prototxt" -base_lr: 0.05 -display: 40 -max_iter: 100000 -lr_policy: "poly" -power: 0.5 -momentum: 0.9 -weight_decay: 0.0002 -snapshot: 10000 -snapshot_prefix: "models/intel_optimized_models/multinode/googlenet_v2_4nodes/default_googlenet_v2" -solver_mode: CPU -average_loss: 40 \ No newline at end of file diff --git a/models/intel_optimized_models/multinode/googlenet_v2_8nodes/solver.prototxt b/models/intel_optimized_models/multinode/googlenet_v2_8nodes/solver.prototxt new file mode 100644 index 000000000..a39aedfe5 --- /dev/null +++ b/models/intel_optimized_models/multinode/googlenet_v2_8nodes/solver.prototxt @@ -0,0 +1,15 @@ +net: "models/intel_optimized_models/multinode/googlenet_v2_8nodes/train_val.prototxt" +test_iter: 1000 +test_interval: 10000 +test_initialization: false +base_lr: 0.06 +display: 40 +max_iter: 182000 +lr_policy: "poly" +power: 0.5 +momentum: 0.9 +weight_decay: 0.0002 +snapshot: 10000 +snapshot_prefix: "models/intel_optimized_models/multinode/googlenet_v2_8nodes/default_googlenet_v2" +solver_mode: CPU +average_loss: 40 diff --git a/models/intel_optimized_models/multinode/googlenet_v2_4nodes/train_val.prototxt b/models/intel_optimized_models/multinode/googlenet_v2_8nodes/train_val.prototxt similarity index 100% rename from models/intel_optimized_models/multinode/googlenet_v2_4nodes/train_val.prototxt rename to models/intel_optimized_models/multinode/googlenet_v2_8nodes/train_val.prototxt diff --git a/models/intel_optimized_models/multinode/resnet_50_16_nodes/solver.prototxt b/models/intel_optimized_models/multinode/resnet_50_16_nodes/solver.prototxt deleted file mode 100644 index a66f60dfa..000000000 --- a/models/intel_optimized_models/multinode/resnet_50_16_nodes/solver.prototxt +++ /dev/null @@ -1,15 +0,0 @@ -#This solver is described by Computer Vision Group Jena (CVGJ) in [ImageNet pre-trained models with batch normalization] (https://arxiv.org/pdf/1612.01452.pdf) -net: "models/intel_optimized_models/multinode/resnet_50_16_nodes/train_val.prototxt" -#test_iter: 5000 -#test_interval: 15000 -#test_initialization: false -base_lr: 0.1 -display: 20 -max_iter: 320000 -lr_policy: "poly" -power: 1 -momentum: 0.9 -weight_decay: 0.0001 -snapshot: 30000 -snapshot_prefix: "caffe-resnet50" -solver_mode: CPU diff --git a/models/intel_optimized_models/multinode/resnet_50_16_nodes/train_val.prototxt b/models/intel_optimized_models/multinode/resnet_50_16_nodes/train_val.prototxt deleted file mode 100644 index 71b07d00a..000000000 --- a/models/intel_optimized_models/multinode/resnet_50_16_nodes/train_val.prototxt +++ /dev/null @@ -1,2306 +0,0 @@ -#This is Intel(R) optimized (in terms of time to train) version of topology described in the [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) publication. -# -#Top-5 and Top-1 results achieved with this topology: -#Top-5: 92% -#Top-1: 73.9% -#Training was performed using server equipped with Intel(R) Xeon Phi(TM) CPU 7250 processor. - -layer { -name: "data" -type: "Data" -top: "data" -top: "label" -include { - phase: TRAIN -} -transform_param { - scale: 0.0078125 - mirror: true - crop_size: 224 - mean_value: 104 - mean_value: 117 - mean_value: 123 -} - data_param { - source: "examples/imagenet/ilsvrc12_train_lmdb" - batch_size: 16 - backend: LMDB - shuffle: true - } - -} -layer { -name: "data" -type: "Data" -top: "data" -top: "label" -include { - phase: TEST -} -transform_param { - scale: 0.0078125 - mirror: false - crop_size: 224 - mean_value: 104 - mean_value: 117 - mean_value: 123 -} - data_param { - source: "examples/imagenet/ilsvrc12_val_lmdb" - batch_size: 10 - backend: LMDB - } - -} - -layer { -name: "conv1" -type: "Convolution" -bottom: "data" -top: "conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -param { - lr_mult: 2.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - pad: 3 - kernel_size: 7 - stride: 2 - weight_filler { - type: "msra" - variance_norm: FAN_OUT - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "conv1_bn" -type: "BatchNorm" -bottom: "conv1" -top: "conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "conv1_relu" -type: "ReLU" -bottom: "conv1_pcs_arm_sim" -top: "conv1_pcs_arm_sim" - -} -layer { -name: "conv1_pool" -type: "Pooling" -bottom: "conv1_pcs_arm_sim" -top: "conv1_pool" -pooling_param { - kernel_size: 3 - stride: 2 -} - -} -layer { -name: "layer_64_1_conv1" -type: "Convolution" -bottom: "conv1_pool" -top: "layer_64_1_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_1_bn2" -type: "BatchNorm" -bottom: "layer_64_1_conv1" -top: "layer_64_1_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_1_relu2" -type: "ReLU" -bottom: "layer_64_1_conv1_pcs_arm_sim" -top: "layer_64_1_conv1_pcs_arm_sim" - -} -layer { -name: "layer_64_1_conv2" -type: "Convolution" -bottom: "layer_64_1_conv1_pcs_arm_sim" -top: "layer_64_1_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_1_bn3" -type: "BatchNorm" -bottom: "layer_64_1_conv2" -top: "layer_64_1_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_1_relu3" -type: "ReLU" -bottom: "layer_64_1_conv2_pcs_arm_sim" -top: "layer_64_1_conv2_pcs_arm_sim" - -} -layer { -name: "layer_64_1_conv3" -type: "Convolution" -bottom: "layer_64_1_conv2_pcs_arm_sim" -top: "layer_64_1_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_1_conv_expand" -type: "Convolution" -bottom: "layer_64_1_conv1_pcs_arm_sim" -top: "layer_64_1_conv_expand" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_1_sum" -type: "Eltwise" -bottom: "layer_64_1_conv3" -bottom: "layer_64_1_conv_expand" -top: "layer_64_1_sum" - -} -layer { -name: "layer_64_2_bn1" -type: "BatchNorm" -bottom: "layer_64_1_sum" -top: "layer_64_2_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_2_relu1" -type: "ReLU" -bottom: "layer_64_2_bn1_pcs_arm_sim" -top: "layer_64_2_bn1_pcs_arm_sim" - -} -layer { -name: "layer_64_2_conv1" -type: "Convolution" -bottom: "layer_64_2_bn1_pcs_arm_sim" -top: "layer_64_2_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_2_bn2" -type: "BatchNorm" -bottom: "layer_64_2_conv1" -top: "layer_64_2_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_2_relu2" -type: "ReLU" -bottom: "layer_64_2_conv1_pcs_arm_sim" -top: "layer_64_2_conv1_pcs_arm_sim" - -} -layer { -name: "layer_64_2_conv2" -type: "Convolution" -bottom: "layer_64_2_conv1_pcs_arm_sim" -top: "layer_64_2_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_2_bn3" -type: "BatchNorm" -bottom: "layer_64_2_conv2" -top: "layer_64_2_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_2_relu3" -type: "ReLU" -bottom: "layer_64_2_conv2_pcs_arm_sim" -top: "layer_64_2_conv2_pcs_arm_sim" - -} -layer { -name: "layer_64_2_conv3" -type: "Convolution" -bottom: "layer_64_2_conv2_pcs_arm_sim" -top: "layer_64_2_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_2_sum" -type: "Eltwise" -bottom: "layer_64_2_conv3" -bottom: "layer_64_1_sum" -top: "layer_64_2_sum" - -} -layer { -name: "layer_64_3_bn1" -type: "BatchNorm" -bottom: "layer_64_2_sum" -top: "layer_64_3_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_3_relu1" -type: "ReLU" -bottom: "layer_64_3_bn1_pcs_arm_sim" -top: "layer_64_3_bn1_pcs_arm_sim" - -} -layer { -name: "layer_64_3_conv1" -type: "Convolution" -bottom: "layer_64_3_bn1_pcs_arm_sim" -top: "layer_64_3_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_3_bn2" -type: "BatchNorm" -bottom: "layer_64_3_conv1" -top: "layer_64_3_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_3_relu2" -type: "ReLU" -bottom: "layer_64_3_conv1_pcs_arm_sim" -top: "layer_64_3_conv1_pcs_arm_sim" - -} -layer { -name: "layer_64_3_conv2" -type: "Convolution" -bottom: "layer_64_3_conv1_pcs_arm_sim" -top: "layer_64_3_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 64 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_3_bn3" -type: "BatchNorm" -bottom: "layer_64_3_conv2" -top: "layer_64_3_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_64_3_relu3" -type: "ReLU" -bottom: "layer_64_3_conv2_pcs_arm_sim" -top: "layer_64_3_conv2_pcs_arm_sim" - -} -layer { -name: "layer_64_3_conv3" -type: "Convolution" -bottom: "layer_64_3_conv2_pcs_arm_sim" -top: "layer_64_3_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_64_3_sum" -type: "Eltwise" -bottom: "layer_64_3_conv3" -bottom: "layer_64_2_sum" -top: "layer_64_3_sum" - -} -layer { -name: "layer_128_1_bn1" -type: "BatchNorm" -bottom: "layer_64_3_sum" -top: "layer_128_1_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_1_relu1" -type: "ReLU" -bottom: "layer_128_1_bn1_pcs_arm_sim" -top: "layer_128_1_bn1_pcs_arm_sim" - -} -layer { -name: "layer_128_1_conv1" -type: "Convolution" -bottom: "layer_128_1_bn1_pcs_arm_sim" -top: "layer_128_1_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_1_bn2" -type: "BatchNorm" -bottom: "layer_128_1_conv1" -top: "layer_128_1_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_1_relu2" -type: "ReLU" -bottom: "layer_128_1_conv1_pcs_arm_sim" -top: "layer_128_1_conv1_pcs_arm_sim" - -} -layer { -name: "layer_128_1_conv2" -type: "Convolution" -bottom: "layer_128_1_conv1_pcs_arm_sim" -top: "layer_128_1_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_1_bn3" -type: "BatchNorm" -bottom: "layer_128_1_conv2" -top: "layer_128_1_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_1_relu3" -type: "ReLU" -bottom: "layer_128_1_conv2_pcs_arm_sim" -top: "layer_128_1_conv2_pcs_arm_sim" - -} -layer { -name: "layer_128_1_conv3" -type: "Convolution" -bottom: "layer_128_1_conv2_pcs_arm_sim" -top: "layer_128_1_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_1_conv_expand" -type: "Convolution" -bottom: "layer_128_1_bn1_pcs_arm_sim" -top: "layer_128_1_conv_expand" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_1_sum" -type: "Eltwise" -bottom: "layer_128_1_conv3" -bottom: "layer_128_1_conv_expand" -top: "layer_128_1_sum" - -} -layer { -name: "layer_128_2_bn1" -type: "BatchNorm" -bottom: "layer_128_1_sum" -top: "layer_128_2_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_2_relu1" -type: "ReLU" -bottom: "layer_128_2_bn1_pcs_arm_sim" -top: "layer_128_2_bn1_pcs_arm_sim" - -} -layer { -name: "layer_128_2_conv1" -type: "Convolution" -bottom: "layer_128_2_bn1_pcs_arm_sim" -top: "layer_128_2_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_2_bn2" -type: "BatchNorm" -bottom: "layer_128_2_conv1" -top: "layer_128_2_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_2_relu2" -type: "ReLU" -bottom: "layer_128_2_conv1_pcs_arm_sim" -top: "layer_128_2_conv1_pcs_arm_sim" - -} -layer { -name: "layer_128_2_conv2" -type: "Convolution" -bottom: "layer_128_2_conv1_pcs_arm_sim" -top: "layer_128_2_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_2_bn3" -type: "BatchNorm" -bottom: "layer_128_2_conv2" -top: "layer_128_2_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_2_relu3" -type: "ReLU" -bottom: "layer_128_2_conv2_pcs_arm_sim" -top: "layer_128_2_conv2_pcs_arm_sim" - -} -layer { -name: "layer_128_2_conv3" -type: "Convolution" -bottom: "layer_128_2_conv2_pcs_arm_sim" -top: "layer_128_2_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_2_sum" -type: "Eltwise" -bottom: "layer_128_2_conv3" -bottom: "layer_128_1_sum" -top: "layer_128_2_sum" - -} -layer { -name: "layer_128_3_bn1" -type: "BatchNorm" -bottom: "layer_128_2_sum" -top: "layer_128_3_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_3_relu1" -type: "ReLU" -bottom: "layer_128_3_bn1_pcs_arm_sim" -top: "layer_128_3_bn1_pcs_arm_sim" - -} -layer { -name: "layer_128_3_conv1" -type: "Convolution" -bottom: "layer_128_3_bn1_pcs_arm_sim" -top: "layer_128_3_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_3_bn2" -type: "BatchNorm" -bottom: "layer_128_3_conv1" -top: "layer_128_3_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_3_relu2" -type: "ReLU" -bottom: "layer_128_3_conv1_pcs_arm_sim" -top: "layer_128_3_conv1_pcs_arm_sim" - -} -layer { -name: "layer_128_3_conv2" -type: "Convolution" -bottom: "layer_128_3_conv1_pcs_arm_sim" -top: "layer_128_3_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_3_bn3" -type: "BatchNorm" -bottom: "layer_128_3_conv2" -top: "layer_128_3_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_3_relu3" -type: "ReLU" -bottom: "layer_128_3_conv2_pcs_arm_sim" -top: "layer_128_3_conv2_pcs_arm_sim" - -} -layer { -name: "layer_128_3_conv3" -type: "Convolution" -bottom: "layer_128_3_conv2_pcs_arm_sim" -top: "layer_128_3_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_3_sum" -type: "Eltwise" -bottom: "layer_128_3_conv3" -bottom: "layer_128_2_sum" -top: "layer_128_3_sum" - -} -layer { -name: "layer_128_4_bn1" -type: "BatchNorm" -bottom: "layer_128_3_sum" -top: "layer_128_4_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_4_relu1" -type: "ReLU" -bottom: "layer_128_4_bn1_pcs_arm_sim" -top: "layer_128_4_bn1_pcs_arm_sim" - -} -layer { -name: "layer_128_4_conv1" -type: "Convolution" -bottom: "layer_128_4_bn1_pcs_arm_sim" -top: "layer_128_4_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_4_bn2" -type: "BatchNorm" -bottom: "layer_128_4_conv1" -top: "layer_128_4_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_4_relu2" -type: "ReLU" -bottom: "layer_128_4_conv1_pcs_arm_sim" -top: "layer_128_4_conv1_pcs_arm_sim" - -} -layer { -name: "layer_128_4_conv2" -type: "Convolution" -bottom: "layer_128_4_conv1_pcs_arm_sim" -top: "layer_128_4_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 128 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_4_bn3" -type: "BatchNorm" -bottom: "layer_128_4_conv2" -top: "layer_128_4_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_128_4_relu3" -type: "ReLU" -bottom: "layer_128_4_conv2_pcs_arm_sim" -top: "layer_128_4_conv2_pcs_arm_sim" - -} -layer { -name: "layer_128_4_conv3" -type: "Convolution" -bottom: "layer_128_4_conv2_pcs_arm_sim" -top: "layer_128_4_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_128_4_sum" -type: "Eltwise" -bottom: "layer_128_4_conv3" -bottom: "layer_128_3_sum" -top: "layer_128_4_sum" - -} -layer { -name: "layer_256_1_bn1" -type: "BatchNorm" -bottom: "layer_128_4_sum" -top: "layer_256_1_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_1_relu1" -type: "ReLU" -bottom: "layer_256_1_bn1_pcs_arm_sim" -top: "layer_256_1_bn1_pcs_arm_sim" - -} -layer { -name: "layer_256_1_conv1" -type: "Convolution" -bottom: "layer_256_1_bn1_pcs_arm_sim" -top: "layer_256_1_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_1_bn2" -type: "BatchNorm" -bottom: "layer_256_1_conv1" -top: "layer_256_1_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_1_relu2" -type: "ReLU" -bottom: "layer_256_1_conv1_pcs_arm_sim" -top: "layer_256_1_conv1_pcs_arm_sim" - -} -layer { -name: "layer_256_1_conv2" -type: "Convolution" -bottom: "layer_256_1_conv1_pcs_arm_sim" -top: "layer_256_1_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_1_bn3" -type: "BatchNorm" -bottom: "layer_256_1_conv2" -top: "layer_256_1_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_1_relu3" -type: "ReLU" -bottom: "layer_256_1_conv2_pcs_arm_sim" -top: "layer_256_1_conv2_pcs_arm_sim" - -} -layer { -name: "layer_256_1_conv3" -type: "Convolution" -bottom: "layer_256_1_conv2_pcs_arm_sim" -top: "layer_256_1_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_1_conv_expand" -type: "Convolution" -bottom: "layer_256_1_bn1_pcs_arm_sim" -top: "layer_256_1_conv_expand" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_1_sum" -type: "Eltwise" -bottom: "layer_256_1_conv3" -bottom: "layer_256_1_conv_expand" -top: "layer_256_1_sum" - -} -layer { -name: "layer_256_2_bn1" -type: "BatchNorm" -bottom: "layer_256_1_sum" -top: "layer_256_2_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_2_relu1" -type: "ReLU" -bottom: "layer_256_2_bn1_pcs_arm_sim" -top: "layer_256_2_bn1_pcs_arm_sim" - -} -layer { -name: "layer_256_2_conv1" -type: "Convolution" -bottom: "layer_256_2_bn1_pcs_arm_sim" -top: "layer_256_2_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_2_bn2" -type: "BatchNorm" -bottom: "layer_256_2_conv1" -top: "layer_256_2_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_2_relu2" -type: "ReLU" -bottom: "layer_256_2_conv1_pcs_arm_sim" -top: "layer_256_2_conv1_pcs_arm_sim" - -} -layer { -name: "layer_256_2_conv2" -type: "Convolution" -bottom: "layer_256_2_conv1_pcs_arm_sim" -top: "layer_256_2_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_2_bn3" -type: "BatchNorm" -bottom: "layer_256_2_conv2" -top: "layer_256_2_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_2_relu3" -type: "ReLU" -bottom: "layer_256_2_conv2_pcs_arm_sim" -top: "layer_256_2_conv2_pcs_arm_sim" - -} -layer { -name: "layer_256_2_conv3" -type: "Convolution" -bottom: "layer_256_2_conv2_pcs_arm_sim" -top: "layer_256_2_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_2_sum" -type: "Eltwise" -bottom: "layer_256_2_conv3" -bottom: "layer_256_1_sum" -top: "layer_256_2_sum" - -} -layer { -name: "layer_256_3_bn1" -type: "BatchNorm" -bottom: "layer_256_2_sum" -top: "layer_256_3_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_3_relu1" -type: "ReLU" -bottom: "layer_256_3_bn1_pcs_arm_sim" -top: "layer_256_3_bn1_pcs_arm_sim" - -} -layer { -name: "layer_256_3_conv1" -type: "Convolution" -bottom: "layer_256_3_bn1_pcs_arm_sim" -top: "layer_256_3_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_3_bn2" -type: "BatchNorm" -bottom: "layer_256_3_conv1" -top: "layer_256_3_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_3_relu2" -type: "ReLU" -bottom: "layer_256_3_conv1_pcs_arm_sim" -top: "layer_256_3_conv1_pcs_arm_sim" - -} -layer { -name: "layer_256_3_conv2" -type: "Convolution" -bottom: "layer_256_3_conv1_pcs_arm_sim" -top: "layer_256_3_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_3_bn3" -type: "BatchNorm" -bottom: "layer_256_3_conv2" -top: "layer_256_3_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_3_relu3" -type: "ReLU" -bottom: "layer_256_3_conv2_pcs_arm_sim" -top: "layer_256_3_conv2_pcs_arm_sim" - -} -layer { -name: "layer_256_3_conv3" -type: "Convolution" -bottom: "layer_256_3_conv2_pcs_arm_sim" -top: "layer_256_3_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_3_sum" -type: "Eltwise" -bottom: "layer_256_3_conv3" -bottom: "layer_256_2_sum" -top: "layer_256_3_sum" - -} -layer { -name: "layer_256_4_bn1" -type: "BatchNorm" -bottom: "layer_256_3_sum" -top: "layer_256_4_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_4_relu1" -type: "ReLU" -bottom: "layer_256_4_bn1_pcs_arm_sim" -top: "layer_256_4_bn1_pcs_arm_sim" - -} -layer { -name: "layer_256_4_conv1" -type: "Convolution" -bottom: "layer_256_4_bn1_pcs_arm_sim" -top: "layer_256_4_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_4_bn2" -type: "BatchNorm" -bottom: "layer_256_4_conv1" -top: "layer_256_4_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_4_relu2" -type: "ReLU" -bottom: "layer_256_4_conv1_pcs_arm_sim" -top: "layer_256_4_conv1_pcs_arm_sim" - -} -layer { -name: "layer_256_4_conv2" -type: "Convolution" -bottom: "layer_256_4_conv1_pcs_arm_sim" -top: "layer_256_4_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_4_bn3" -type: "BatchNorm" -bottom: "layer_256_4_conv2" -top: "layer_256_4_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_4_relu3" -type: "ReLU" -bottom: "layer_256_4_conv2_pcs_arm_sim" -top: "layer_256_4_conv2_pcs_arm_sim" - -} -layer { -name: "layer_256_4_conv3" -type: "Convolution" -bottom: "layer_256_4_conv2_pcs_arm_sim" -top: "layer_256_4_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_4_sum" -type: "Eltwise" -bottom: "layer_256_4_conv3" -bottom: "layer_256_3_sum" -top: "layer_256_4_sum" - -} -layer { -name: "layer_256_5_bn1" -type: "BatchNorm" -bottom: "layer_256_4_sum" -top: "layer_256_5_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_5_relu1" -type: "ReLU" -bottom: "layer_256_5_bn1_pcs_arm_sim" -top: "layer_256_5_bn1_pcs_arm_sim" - -} -layer { -name: "layer_256_5_conv1" -type: "Convolution" -bottom: "layer_256_5_bn1_pcs_arm_sim" -top: "layer_256_5_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_5_bn2" -type: "BatchNorm" -bottom: "layer_256_5_conv1" -top: "layer_256_5_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_5_relu2" -type: "ReLU" -bottom: "layer_256_5_conv1_pcs_arm_sim" -top: "layer_256_5_conv1_pcs_arm_sim" - -} -layer { -name: "layer_256_5_conv2" -type: "Convolution" -bottom: "layer_256_5_conv1_pcs_arm_sim" -top: "layer_256_5_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_5_bn3" -type: "BatchNorm" -bottom: "layer_256_5_conv2" -top: "layer_256_5_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_5_relu3" -type: "ReLU" -bottom: "layer_256_5_conv2_pcs_arm_sim" -top: "layer_256_5_conv2_pcs_arm_sim" - -} -layer { -name: "layer_256_5_conv3" -type: "Convolution" -bottom: "layer_256_5_conv2_pcs_arm_sim" -top: "layer_256_5_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_5_sum" -type: "Eltwise" -bottom: "layer_256_5_conv3" -bottom: "layer_256_4_sum" -top: "layer_256_5_sum" - -} -layer { -name: "layer_256_6_bn1" -type: "BatchNorm" -bottom: "layer_256_5_sum" -top: "layer_256_6_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_6_relu1" -type: "ReLU" -bottom: "layer_256_6_bn1_pcs_arm_sim" -top: "layer_256_6_bn1_pcs_arm_sim" - -} -layer { -name: "layer_256_6_conv1" -type: "Convolution" -bottom: "layer_256_6_bn1_pcs_arm_sim" -top: "layer_256_6_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_6_bn2" -type: "BatchNorm" -bottom: "layer_256_6_conv1" -top: "layer_256_6_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_6_relu2" -type: "ReLU" -bottom: "layer_256_6_conv1_pcs_arm_sim" -top: "layer_256_6_conv1_pcs_arm_sim" - -} -layer { -name: "layer_256_6_conv2" -type: "Convolution" -bottom: "layer_256_6_conv1_pcs_arm_sim" -top: "layer_256_6_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 256 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_6_bn3" -type: "BatchNorm" -bottom: "layer_256_6_conv2" -top: "layer_256_6_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_256_6_relu3" -type: "ReLU" -bottom: "layer_256_6_conv2_pcs_arm_sim" -top: "layer_256_6_conv2_pcs_arm_sim" - -} -layer { -name: "layer_256_6_conv3" -type: "Convolution" -bottom: "layer_256_6_conv2_pcs_arm_sim" -top: "layer_256_6_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 1024 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_256_6_sum" -type: "Eltwise" -bottom: "layer_256_6_conv3" -bottom: "layer_256_5_sum" -top: "layer_256_6_sum" - -} -layer { -name: "layer_512_1_bn1" -type: "BatchNorm" -bottom: "layer_256_6_sum" -top: "layer_512_1_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_1_relu1" -type: "ReLU" -bottom: "layer_512_1_bn1_pcs_arm_sim" -top: "layer_512_1_bn1_pcs_arm_sim" - -} -layer { -name: "layer_512_1_conv1" -type: "Convolution" -bottom: "layer_512_1_bn1_pcs_arm_sim" -top: "layer_512_1_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_1_bn2" -type: "BatchNorm" -bottom: "layer_512_1_conv1" -top: "layer_512_1_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_1_relu2" -type: "ReLU" -bottom: "layer_512_1_conv1_pcs_arm_sim" -top: "layer_512_1_conv1_pcs_arm_sim" - -} -layer { -name: "layer_512_1_conv2" -type: "Convolution" -bottom: "layer_512_1_conv1_pcs_arm_sim" -top: "layer_512_1_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_1_bn3" -type: "BatchNorm" -bottom: "layer_512_1_conv2" -top: "layer_512_1_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_1_relu3" -type: "ReLU" -bottom: "layer_512_1_conv2_pcs_arm_sim" -top: "layer_512_1_conv2_pcs_arm_sim" - -} -layer { -name: "layer_512_1_conv3" -type: "Convolution" -bottom: "layer_512_1_conv2_pcs_arm_sim" -top: "layer_512_1_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 2048 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_1_conv_expand" -type: "Convolution" -bottom: "layer_512_1_bn1_pcs_arm_sim" -top: "layer_512_1_conv_expand" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 2048 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 2 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_1_sum" -type: "Eltwise" -bottom: "layer_512_1_conv3" -bottom: "layer_512_1_conv_expand" -top: "layer_512_1_sum" - -} -layer { -name: "layer_512_2_bn1" -type: "BatchNorm" -bottom: "layer_512_1_sum" -top: "layer_512_2_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_2_relu1" -type: "ReLU" -bottom: "layer_512_2_bn1_pcs_arm_sim" -top: "layer_512_2_bn1_pcs_arm_sim" - -} -layer { -name: "layer_512_2_conv1" -type: "Convolution" -bottom: "layer_512_2_bn1_pcs_arm_sim" -top: "layer_512_2_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_2_bn2" -type: "BatchNorm" -bottom: "layer_512_2_conv1" -top: "layer_512_2_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_2_relu2" -type: "ReLU" -bottom: "layer_512_2_conv1_pcs_arm_sim" -top: "layer_512_2_conv1_pcs_arm_sim" - -} -layer { -name: "layer_512_2_conv2" -type: "Convolution" -bottom: "layer_512_2_conv1_pcs_arm_sim" -top: "layer_512_2_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_2_bn3" -type: "BatchNorm" -bottom: "layer_512_2_conv2" -top: "layer_512_2_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_2_relu3" -type: "ReLU" -bottom: "layer_512_2_conv2_pcs_arm_sim" -top: "layer_512_2_conv2_pcs_arm_sim" - -} -layer { -name: "layer_512_2_conv3" -type: "Convolution" -bottom: "layer_512_2_conv2_pcs_arm_sim" -top: "layer_512_2_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 2048 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_2_sum" -type: "Eltwise" -bottom: "layer_512_2_conv3" -bottom: "layer_512_1_sum" -top: "layer_512_2_sum" - -} -layer { -name: "layer_512_3_bn1" -type: "BatchNorm" -bottom: "layer_512_2_sum" -top: "layer_512_3_bn1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_3_relu1" -type: "ReLU" -bottom: "layer_512_3_bn1_pcs_arm_sim" -top: "layer_512_3_bn1_pcs_arm_sim" - -} -layer { -name: "layer_512_3_conv1" -type: "Convolution" -bottom: "layer_512_3_bn1_pcs_arm_sim" -top: "layer_512_3_conv1" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_3_bn2" -type: "BatchNorm" -bottom: "layer_512_3_conv1" -top: "layer_512_3_conv1_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_3_relu2" -type: "ReLU" -bottom: "layer_512_3_conv1_pcs_arm_sim" -top: "layer_512_3_conv1_pcs_arm_sim" - -} -layer { -name: "layer_512_3_conv2" -type: "Convolution" -bottom: "layer_512_3_conv1_pcs_arm_sim" -top: "layer_512_3_conv2" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 512 - bias_term: false - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_3_bn3" -type: "BatchNorm" -bottom: "layer_512_3_conv2" -top: "layer_512_3_conv2_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "layer_512_3_relu3" -type: "ReLU" -bottom: "layer_512_3_conv2_pcs_arm_sim" -top: "layer_512_3_conv2_pcs_arm_sim" - -} -layer { -name: "layer_512_3_conv3" -type: "Convolution" -bottom: "layer_512_3_conv2_pcs_arm_sim" -top: "layer_512_3_conv3" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -convolution_param { - num_output: 2048 - bias_term: false - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "msra" - } - bias_filler { - type: "constant" - value: 0.0 - } -} - -} -layer { -name: "layer_512_3_sum" -type: "Eltwise" -bottom: "layer_512_3_conv3" -bottom: "layer_512_2_sum" -top: "layer_512_3_sum" - -} -layer { -name: "last_bn" -type: "BatchNorm" -bottom: "layer_512_3_sum" -top: "layer_512_3_sum_pcs_arm_sim" - batch_norm_param { - } -} -layer { -name: "last_relu" -type: "ReLU" -bottom: "layer_512_3_sum_pcs_arm_sim" -top: "layer_512_3_sum_pcs_arm_sim" - -} -layer { -name: "global_pool" -type: "Pooling" -bottom: "layer_512_3_sum_pcs_arm_sim" -top: "global_pool" -pooling_param { - pool: AVE - global_pooling: true -} - -} -layer { -name: "score" -type: "InnerProduct" -bottom: "global_pool" -top: "score" -param { - lr_mult: 1.0 - decay_mult: 1.0 -} -param { - lr_mult: 2.0 - decay_mult: 1.0 -} -inner_product_param { - num_output: 1000 -} - -} -layer { -name: "loss" -type: "SoftmaxWithLoss" -bottom: "score" -bottom: "label" -top: "loss" - -} -layer { -name: "accuracy" -type: "Accuracy" -bottom: "score" -bottom: "label" -top: "accuracy" -include { - phase: TEST -} - -}