diff --git a/README.md b/README.md index 9f2366b36..a12292c15 100644 --- a/README.md +++ b/README.md @@ -40,7 +40,7 @@ to use more than one thread per core. When less than required cores are specifie limit execution of OpenMP threads to specified cores only. ## Best performance solution -Please read [release notes](https://github.com/intel/caffe/blob/master/docs/release_notes.md) for our recommendations and configuration to achieve best performance on Intel CPUs. +Please read [our Wiki](https://github.com/intel/caffe/wiki/Recommendations-to-achieve-best-performance) for our recommendations and configuration to achieve best performance on Intel CPUs. ## Multinode Training Intel® Distribution of Caffe* multi-node allows you to execute deep neural network training on multiple machines. diff --git a/docs/release_notes.md b/docs/release_notes.md index 16b2940a0..984272828 100644 --- a/docs/release_notes.md +++ b/docs/release_notes.md @@ -1,39 +1,37 @@ -# -# All modification made by Intel Corporation: © 2016 Intel Corporation -# -# All contributions by the University of California: -# Copyright (c) 2014, 2015, The Regents of the University of California (Regents) -# All rights reserved. -# -# All other contributions: -# Copyright (c) 2014, 2015, the respective contributors -# All rights reserved. -# For the list of contributors go to https://github.com/BVLC/caffe/blob/master/CONTRIBUTORS.md -# -# -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of Intel Corporation nor the names of its contributors -# may be used to endorse or promote products derived from this software -# without specific prior written permission. -# -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE -# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE -# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL -# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR -# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER -# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, -# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE -# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -# + All modification made by Intel Corporation: © 2016 Intel Corporation + + All contributions by the University of California: + Copyright (c) 2014, 2015, The Regents of the University of California (Regents) + All rights reserved. + + All other contributions: + Copyright (c) 2014, 2015, the respective contributors + All rights reserved. + For the list of contributors go to https://github.com/BVLC/caffe/blob/master/CONTRIBUTORS.md + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" + AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE + FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL + DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR + SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER + CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, + OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +--- --- title: Release Notes @@ -216,9 +214,14 @@ Berkeley Vision runs Caffe with K40s, K20s, and Titans including models at Image There is an unofficial Windows port of Caffe at [niuzhiheng/caffe:windows](https://github.com/niuzhiheng/caffe). Thanks [@niuzhiheng](https://github.com/niuzhiheng)! # Change log +03-11-2016 +* integration with MKL2017 update1 (providing better performance solution) +* minor changes to provide optimal performance on default prototxt files describing topologies (for AlexNet, GoogleNet v2). +* fixed Dockerfiles - for Ubuntu and Centos. + 1-09-2016 * added RNN support -* moved form MKL2017 beta update 1 engine to MKL2017 (providing better performance solution) +* moved form MKL2017 beta update 1 engine to MKL2017 * added official support for ResNet50, GoogleNet v2, VGG-19. (List of currenlty supported topologies: AlexNet, GoogleNet, GoogleNet v2, ResNet50, VGG-19) * added official support for multinode on GoogleNet with MKL2017 engine * added DataLayer optimizations @@ -234,12 +237,15 @@ Workaround: For older processors use MKL2017 GEMM engine: set USE_MKL2017_AS_DEF Workaround: Use GEMM engine in normalization layer (in prototxt file set `engine:=caffe` for that layer) for topologies that use LRN within channel like cifar. * Performance results may be lower when Data Layer is provided in txt files (uncompressed list of jpg files) -Workaround: We recommend to always use LMDB Data Layer +Workaround: We recommend to always use compressed LMDB Data Layer * LeNet, Cifar, Squeeznet currently are not optimized in terms of performance in Intel MKL2017 Workaround: better performance results might be achieved with GEMM engine: `set USE_MKL2017_AS_DEFAULT_ENGINE := 0` in `Makefile.config`. -* We observe convergence problems with some publicly presented hyper parameters (recommended for GPUs) for Googlenet and ResNet50. For CPU tuning of hyper parameters might be needed. +* We observe convergence problems with some publicly presented hyper parameters (recommended for GPUs) for Googlenet, ResNet50, VGG-19. For CPU tuning of hyper parameters might be needed. + +* MKL2017 doesn't allow access to mean & variance statistics in batch normalization layer which prohibits their accumulation (in global-stats mode). This is affecting batch 1 scoring accuracy with topologies using batch normalization layer (resnet50, googlenet v2). +Workaround: use batch 32 or higher for accuracy measurements. # Recommendations to achieve best performance @@ -296,4 +302,4 @@ In folder `/examples/imagenet/` we provide scripts and instructions `readme.md` Caffe is released under the [BSD 2-Clause license](https://github.com/BVLC/caffe/blob/master/LICENSE). The BVLC reference models are released for unrestricted use. *** - *Other names and brands may be claimed as the property of others + *Other names and brands may be claimed as the property of others \ No newline at end of file diff --git a/external/mkl/prepare_mkl.sh b/external/mkl/prepare_mkl.sh index e5ab67c19..936327542 100755 --- a/external/mkl/prepare_mkl.sh +++ b/external/mkl/prepare_mkl.sh @@ -56,10 +56,10 @@ echo $VERSION_LINE # Return Version Line # MKL DST=`dirname $0` OMP=0 -VERSION_MATCH=20160706 -ARCHIVE_BASENAME=mklml_lnx_2017.0.0.20160801.tgz +VERSION_MATCH=20160906 +ARCHIVE_BASENAME=mklml_lnx_2017.0.1.20161005.tgz MKL_CONTENT_DIR=`echo $ARCHIVE_BASENAME | rev | cut -d "." -f 2- | rev` -GITHUB_RELEASE_TAG=self_containted_MKLGOLD +GITHUB_RELEASE_TAG=self_containted_MKLGOLD_u1 MKLURL="https://github.com/intel/caffe/releases/download/$GITHUB_RELEASE_TAG/$ARCHIVE_BASENAME" # there are diffrent MKL lib to be used for GCC and for ICC reg='^[0-9]+$' diff --git a/models/mkl2017_alexnet/deploy.prototxt b/models/mkl2017_alexnet/deploy.prototxt deleted file mode 100644 index 6636f3ed2..000000000 --- a/models/mkl2017_alexnet/deploy.prototxt +++ /dev/null @@ -1,302 +0,0 @@ -name: "AlexNet" -layer { - name: "data" - type: "Input" - top: "data" - input_param { shape: { dim: 10 dim: 3 dim: 227 dim: 227 } } -} -layer { - name: "conv1" - type: "Convolution" - bottom: "data" - top: "conv1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 11 - stride: 4 - engine: MKL2017 - } -} -layer { - name: "relu1" - type: "ReLU" - bottom: "conv1" - top: "conv1" - relu_param { - engine: MKL2017 - } -} -layer { - name: "norm1" - type: "LRN" - bottom: "conv1" - top: "norm1" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - engine: MKL2017 - } -} -layer { - name: "pool1" - type: "Pooling" - bottom: "norm1" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - engine: MKL2017 - } -} -layer { - name: "conv2" - type: "Convolution" - bottom: "pool1" - top: "conv2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 2 - kernel_size: 5 - group: 2 - engine: MKL2017 - } -} -layer { - name: "relu2" - type: "ReLU" - bottom: "conv2" - top: "conv2" - relu_param { - engine: MKL2017 - } -} -layer { - name: "norm2" - type: "LRN" - bottom: "conv2" - top: "norm2" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - engine: MKL2017 - } -} -layer { - name: "pool2" - type: "Pooling" - bottom: "norm2" - top: "pool2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - engine: MKL2017 - } -} -layer { - name: "conv3" - type: "Convolution" - bottom: "pool2" - top: "conv3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - engine: MKL2017 - } -} -layer { - name: "relu3" - type: "ReLU" - bottom: "conv3" - top: "conv3" - relu_param { - engine: MKL2017 - } -} -layer { - name: "conv4" - type: "Convolution" - bottom: "conv3" - top: "conv4" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - group: 2 - engine: MKL2017 - } -} -layer { - name: "relu4" - type: "ReLU" - bottom: "conv4" - top: "conv4" - relu_param { - engine: MKL2017 - } -} -layer { - name: "conv5" - type: "Convolution" - bottom: "conv4" - top: "conv5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - group: 2 - engine: MKL2017 - } -} -layer { - name: "relu5" - type: "ReLU" - bottom: "conv5" - top: "conv5" - relu_param { - engine: MKL2017 - } -} -layer { - name: "pool5" - type: "Pooling" - bottom: "conv5" - top: "pool5" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - engine: MKL2017 - } -} -layer { - name: "fc6" - type: "InnerProduct" - bottom: "pool5" - top: "fc6" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "drop6" - type: "Dropout" - bottom: "fc6" - top: "fc6" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc7" - type: "InnerProduct" - bottom: "fc6" - top: "fc7" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "drop7" - type: "Dropout" - bottom: "fc7" - top: "fc7" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc8" - type: "InnerProduct" - bottom: "fc7" - top: "fc8" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - } -} -layer { - name: "prob" - type: "Softmax" - bottom: "fc8" - top: "prob" -} diff --git a/models/mkl2017_alexnet/solver.prototxt b/models/mkl2017_alexnet/solver.prototxt deleted file mode 100644 index 629cc6342..000000000 --- a/models/mkl2017_alexnet/solver.prototxt +++ /dev/null @@ -1,14 +0,0 @@ -net: "models/mkl2017_alexnet/train_val.prototxt" -test_iter: 1000 -test_interval: 1000 -base_lr: 0.01 -lr_policy: "step" -gamma: 0.1 -stepsize: 100000 -display: 20 -max_iter: 450000 -momentum: 0.9 -weight_decay: 0.0005 -snapshot: 10000 -snapshot_prefix: "models/mkl2017_alexnet/caffe_alexnet_train" -solver_mode: CPU diff --git a/models/mkl2017_alexnet/train_val.prototxt b/models/mkl2017_alexnet/train_val.prototxt deleted file mode 100644 index d2e0c4e24..000000000 --- a/models/mkl2017_alexnet/train_val.prototxt +++ /dev/null @@ -1,409 +0,0 @@ -name: "AlexNet" -layer { - name: "data" - type: "Data" - top: "data" - top: "label" - include { - phase: TRAIN - } - transform_param { - mirror: true - crop_size: 227 - mean_file: "data/ilsvrc12/imagenet_mean.binaryproto" - } - data_param { - source: "examples/imagenet/ilsvrc12_train_lmdb" - batch_size: 256 - backend: LMDB - } -} -layer { - name: "data" - type: "Data" - top: "data" - top: "label" - include { - phase: TEST - } - transform_param { - mirror: false - crop_size: 227 - mean_file: "data/ilsvrc12/imagenet_mean.binaryproto" - } - data_param { - source: "examples/imagenet/ilsvrc12_val_lmdb" - batch_size: 256 - backend: LMDB - } -} -layer { - name: "conv1" - type: "Convolution" - bottom: "data" - top: "conv1" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 96 - kernel_size: 11 - stride: 4 - engine: MKL2017 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu1" - type: "ReLU" - bottom: "conv1" - top: "conv1" - relu_param { - engine: MKL2017 - } -} -layer { - name: "norm1" - type: "LRN" - bottom: "conv1" - top: "norm1" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - engine: MKL2017 - } -} -layer { - name: "pool1" - type: "Pooling" - bottom: "norm1" - top: "pool1" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - engine: MKL2017 - } -} -layer { - name: "conv2" - type: "Convolution" - bottom: "pool1" - top: "conv2" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 2 - kernel_size: 5 - group: 2 - engine: MKL2017 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "relu2" - type: "ReLU" - bottom: "conv2" - top: "conv2" - relu_param { - engine: MKL2017 - } -} -layer { - name: "norm2" - type: "LRN" - bottom: "conv2" - top: "norm2" - lrn_param { - local_size: 5 - alpha: 0.0001 - beta: 0.75 - engine: MKL2017 - } -} -layer { - name: "pool2" - type: "Pooling" - bottom: "norm2" - top: "pool2" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - engine: MKL2017 - } -} -layer { - name: "conv3" - type: "Convolution" - bottom: "pool2" - top: "conv3" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - engine: MKL2017 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "relu3" - type: "ReLU" - bottom: "conv3" - top: "conv3" - relu_param { - engine: MKL2017 - } -} -layer { - name: "conv4" - type: "Convolution" - bottom: "conv3" - top: "conv4" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 384 - pad: 1 - kernel_size: 3 - group: 2 - engine: MKL2017 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "relu4" - type: "ReLU" - bottom: "conv4" - top: "conv4" - relu_param { - engine: MKL2017 - } -} -layer { - name: "conv5" - type: "Convolution" - bottom: "conv4" - top: "conv5" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - convolution_param { - num_output: 256 - pad: 1 - kernel_size: 3 - group: 2 - engine: MKL2017 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "relu5" - type: "ReLU" - bottom: "conv5" - top: "conv5" - relu_param { - engine: MKL2017 - } -} -layer { - name: "pool5" - type: "Pooling" - bottom: "conv5" - top: "pool5" - pooling_param { - pool: MAX - kernel_size: 3 - stride: 2 - engine: MKL2017 - } -} -layer { - name: "fc6" - type: "InnerProduct" - bottom: "pool5" - top: "fc6" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - weight_filler { - type: "gaussian" - std: 0.005 - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "relu6" - type: "ReLU" - bottom: "fc6" - top: "fc6" -} -layer { - name: "drop6" - type: "Dropout" - bottom: "fc6" - top: "fc6" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc7" - type: "InnerProduct" - bottom: "fc6" - top: "fc7" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 4096 - weight_filler { - type: "gaussian" - std: 0.005 - } - bias_filler { - type: "constant" - value: 0.1 - } - } -} -layer { - name: "relu7" - type: "ReLU" - bottom: "fc7" - top: "fc7" -} -layer { - name: "drop7" - type: "Dropout" - bottom: "fc7" - top: "fc7" - dropout_param { - dropout_ratio: 0.5 - } -} -layer { - name: "fc8" - type: "InnerProduct" - bottom: "fc7" - top: "fc8" - param { - lr_mult: 1 - decay_mult: 1 - } - param { - lr_mult: 2 - decay_mult: 0 - } - inner_product_param { - num_output: 1000 - weight_filler { - type: "gaussian" - std: 0.01 - } - bias_filler { - type: "constant" - value: 0 - } - } -} -layer { - name: "accuracy" - type: "Accuracy" - bottom: "fc8" - bottom: "label" - top: "accuracy" - include { - phase: TEST - } -} -layer { - name: "loss" - type: "SoftmaxWithLoss" - bottom: "fc8" - bottom: "label" - top: "loss" -} diff --git a/models/mkl2017_googlenet_v2/solver.prototxt b/models/mkl2017_googlenet_v2/solver.prototxt deleted file mode 100644 index 9f7972ea0..000000000 --- a/models/mkl2017_googlenet_v2/solver.prototxt +++ /dev/null @@ -1,16 +0,0 @@ -net: "models/mkl2017_googlenet_v2/train_val.prototxt" -test_iter: 1000 -test_interval: 10000 -test_initialization: false -display: 40 -average_loss: 40 -base_lr: 0.045 -lr_policy: "step" -stepsize: 6400 -gamma: 0.96 -max_iter: 1200000 -momentum: 0.9 -weight_decay: 0.0002 -snapshot: 50000 -snapshot_prefix: "models/mkl2017_googlenet_v2/mkldnn_googlenet_v2" -solver_mode: CPU diff --git a/models/mkl2017_googlenet_v2/train_val.prototxt b/models/mkl2017_googlenet_v2/train_val.prototxt deleted file mode 100644 index 1a176c0c4..000000000 --- a/models/mkl2017_googlenet_v2/train_val.prototxt +++ /dev/null @@ -1,3364 +0,0 @@ -name: "InceptionNetwork" - layer { - top: "data" - top: "label" - name: "data" - type: "Data" - data_param { - source: "examples/imagenet/ilsvrc12_train_lmdb" - batch_size: 32 - backend: LMDB -# shuffle: true - } - include { - phase: TRAIN - } - transform_param { - mirror: true - crop_size: 224 -# mean_file: "data/ilsvrc12/imagenet_mean.binaryproto" - mean_value: 104 - mean_value: 117 - mean_value: 123 - } -} -layer { - bottom: "data" - top: "conv1/7x7_s2" - name: "conv1/7x7_s2" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 3 - kernel_size: 7 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "conv1/7x7_s2" - name: "conv1/7x7_s2/bn" - top: "conv1/7x7_s2/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "conv1/7x7_s2/bn" - top: "conv1/7x7_s2/bn" - name: "conv1/7x7_s2/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "conv1/7x7_s2/bn" - top: "pool1/3x3_s2" - name: "pool1/3x3_s2" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "pool1/3x3_s2" - top: "conv2/3x3_reduce" - name: "conv2/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "conv2/3x3_reduce" - name: "conv2/3x3_reduce/bn" - top: "conv2/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3_reduce/bn" - top: "conv2/3x3_reduce/bn" - name: "conv2/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3_reduce/bn" - top: "conv2/3x3" - name: "conv2/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "conv2/3x3" - name: "conv2/3x3/bn" - top: "conv2/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3/bn" - top: "conv2/3x3/bn" - name: "conv2/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3/bn" - top: "pool2/3x3_s2" - name: "pool2/3x3_s2" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/1x1" - name: "inception_3a/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/1x1" - name: "inception_3a/1x1/bn" - top: "inception_3a/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/1x1/bn" - top: "inception_3a/1x1/bn" - name: "inception_3a/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/3x3_reduce" - name: "inception_3a/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/3x3_reduce" - name: "inception_3a/3x3_reduce/bn" - top: "inception_3a/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/3x3_reduce/bn" - top: "inception_3a/3x3_reduce/bn" - name: "inception_3a/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/3x3_reduce/bn" - top: "inception_3a/3x3" - name: "inception_3a/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/3x3" - name: "inception_3a/3x3/bn" - top: "inception_3a/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/3x3/bn" - top: "inception_3a/3x3/bn" - name: "inception_3a/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/double3x3_reduce" - name: "inception_3a/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/double3x3_reduce" - name: "inception_3a/double3x3_reduce/bn" - top: "inception_3a/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3_reduce/bn" - top: "inception_3a/double3x3_reduce/bn" - name: "inception_3a/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3_reduce/bn" - top: "inception_3a/double3x3a" - name: "inception_3a/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/double3x3a" - name: "inception_3a/double3x3a/bn" - top: "inception_3a/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} - -layer { - bottom: "inception_3a/double3x3a/bn" - top: "inception_3a/double3x3a/bn" - name: "inception_3a/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3a/bn" - top: "inception_3a/double3x3b" - name: "inception_3a/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/double3x3b" - name: "inception_3a/double3x3b/bn" - top: "inception_3a/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3b/bn" - top: "inception_3a/double3x3b/bn" - name: "inception_3a/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/pool" - name: "inception_3a/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_3a/pool" - top: "inception_3a/pool_proj" - name: "inception_3a/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 32 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/pool_proj" - name: "inception_3a/pool_proj/bn" - top: "inception_3a/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/pool_proj/bn" - top: "inception_3a/pool_proj/bn" - name: "inception_3a/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/1x1/bn" - bottom: "inception_3a/3x3/bn" - bottom: "inception_3a/double3x3b/bn" - bottom: "inception_3a/pool_proj/bn" - top: "inception_3a/output" - name: "inception_3a/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/1x1" - name: "inception_3b/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/1x1" - name: "inception_3b/1x1/bn" - top: "inception_3b/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/1x1/bn" - top: "inception_3b/1x1/bn" - name: "inception_3b/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/3x3_reduce" - name: "inception_3b/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/3x3_reduce" - name: "inception_3b/3x3_reduce/bn" - top: "inception_3b/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} - -layer { - bottom: "inception_3b/3x3_reduce/bn" - top: "inception_3b/3x3_reduce/bn" - name: "inception_3b/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/3x3_reduce/bn" - top: "inception_3b/3x3" - name: "inception_3b/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/3x3" - name: "inception_3b/3x3/bn" - top: "inception_3b/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/3x3/bn" - top: "inception_3b/3x3/bn" - name: "inception_3b/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/double3x3_reduce" - name: "inception_3b/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/double3x3_reduce" - name: "inception_3b/double3x3_reduce/bn" - top: "inception_3b/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3_reduce/bn" - top: "inception_3b/double3x3_reduce/bn" - name: "inception_3b/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3_reduce/bn" - top: "inception_3b/double3x3a" - name: "inception_3b/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/double3x3a" - name: "inception_3b/double3x3a/bn" - top: "inception_3b/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3a/bn" - top: "inception_3b/double3x3a/bn" - name: "inception_3b/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3a/bn" - top: "inception_3b/double3x3b" - name: "inception_3b/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/double3x3b" - name: "inception_3b/double3x3b/bn" - top: "inception_3b/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3b/bn" - top: "inception_3b/double3x3b/bn" - name: "inception_3b/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/pool" - name: "inception_3b/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_3b/pool" - top: "inception_3b/pool_proj" - name: "inception_3b/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/pool_proj" - name: "inception_3b/pool_proj/bn" - top: "inception_3b/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/pool_proj/bn" - top: "inception_3b/pool_proj/bn" - name: "inception_3b/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/1x1/bn" - bottom: "inception_3b/3x3/bn" - bottom: "inception_3b/double3x3b/bn" - bottom: "inception_3b/pool_proj/bn" - top: "inception_3b/output" - name: "inception_3b/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/output" - top: "inception_3c/3x3_reduce" - name: "inception_3c/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/3x3_reduce" - name: "inception_3c/3x3_reduce/bn" - top: "inception_3c/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/3x3_reduce/bn" - top: "inception_3c/3x3_reduce/bn" - name: "inception_3c/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/3x3_reduce/bn" - top: "inception_3c/3x3" - name: "inception_3c/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/3x3" - name: "inception_3c/3x3/bn" - top: "inception_3c/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/3x3/bn" - top: "inception_3c/3x3/bn" - name: "inception_3c/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/output" - top: "inception_3c/double3x3_reduce" - name: "inception_3c/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/double3x3_reduce" - name: "inception_3c/double3x3_reduce/bn" - top: "inception_3c/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3_reduce/bn" - top: "inception_3c/double3x3_reduce/bn" - name: "inception_3c/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3_reduce/bn" - top: "inception_3c/double3x3a" - name: "inception_3c/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/double3x3a" - name: "inception_3c/double3x3a/bn" - top: "inception_3c/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} - -layer { - bottom: "inception_3c/double3x3a/bn" - top: "inception_3c/double3x3a/bn" - name: "inception_3c/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3a/bn" - top: "inception_3c/double3x3b" - name: "inception_3c/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/double3x3b" - name: "inception_3c/double3x3b/bn" - top: "inception_3c/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3b/bn" - top: "inception_3c/double3x3b/bn" - name: "inception_3c/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/output" - top: "inception_3c/pool" - name: "inception_3c/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "inception_3c/3x3/bn" - bottom: "inception_3c/double3x3b/bn" - bottom: "inception_3c/pool" - top: "inception_3c/output" - name: "inception_3c/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "pool3/5x5_s3" - name: "pool3/5x5_s3" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 5 - stride: 3 - } -} -layer { - bottom: "pool3/5x5_s3" - top: "loss1/conv" - name: "loss1/conv" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss1/conv" - name: "loss1/conv/bn" - top: "loss1/conv/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/conv/bn" - top: "loss1/conv/bn" - name: "loss1/conv/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/conv/bn" - top: "loss1/fc" - name: "loss1/fc" - type: "InnerProduct" - param { - lr_mult: 1 - decay_mult: 1 - } - inner_product_param { - num_output: 1024 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss1/fc" - name: "loss1/fc/bn" - top: "loss1/fc/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/fc/bn" - top: "loss1/fc/bn" - name: "loss1/fc/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/fc/bn" - top: "loss1/classifier" - name: "loss1/classifier" - type: "InnerProduct" - 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 { - bottom: "loss1/classifier" - bottom: "label" - top: "loss1/loss" - name: "loss1/loss" - type: "SoftmaxWithLoss" - loss_weight: 0.3 -} -layer { - bottom: "loss1/classifier" - top: "loss1/prob" - name: "loss1/prob" - type: "Softmax" - include { - phase: TEST - } -} -layer { - bottom: "loss1/prob" - bottom: "label" - top: "loss1/top-1" - name: "loss1/top-1" - type: "Accuracy" - include { - phase: TEST - } -} -layer { - bottom: "loss1/prob" - bottom: "label" - top: "loss1/top-5" - name: "loss1/top-5" - type: "Accuracy" - accuracy_param { - top_k: 5 - } - include { - phase: TEST - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/1x1" - name: "inception_4a/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/1x1" - name: "inception_4a/1x1/bn" - top: "inception_4a/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/1x1/bn" - top: "inception_4a/1x1/bn" - name: "inception_4a/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/3x3_reduce" - name: "inception_4a/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/3x3_reduce" - name: "inception_4a/3x3_reduce/bn" - top: "inception_4a/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/3x3_reduce/bn" - top: "inception_4a/3x3_reduce/bn" - name: "inception_4a/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/3x3_reduce/bn" - top: "inception_4a/3x3" - name: "inception_4a/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/3x3" - name: "inception_4a/3x3/bn" - top: "inception_4a/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/3x3/bn" - top: "inception_4a/3x3/bn" - name: "inception_4a/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/double3x3_reduce" - name: "inception_4a/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/double3x3_reduce" - name: "inception_4a/double3x3_reduce/bn" - top: "inception_4a/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3_reduce/bn" - top: "inception_4a/double3x3_reduce/bn" - name: "inception_4a/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3_reduce/bn" - top: "inception_4a/double3x3a" - name: "inception_4a/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/double3x3a" - name: "inception_4a/double3x3a/bn" - top: "inception_4a/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3a/bn" - top: "inception_4a/double3x3a/bn" - name: "inception_4a/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3a/bn" - top: "inception_4a/double3x3b" - name: "inception_4a/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/double3x3b" - name: "inception_4a/double3x3b/bn" - top: "inception_4a/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3b/bn" - top: "inception_4a/double3x3b/bn" - name: "inception_4a/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/pool" - name: "inception_4a/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4a/pool" - top: "inception_4a/pool_proj" - name: "inception_4a/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/pool_proj" - name: "inception_4a/pool_proj/bn" - top: "inception_4a/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/pool_proj/bn" - top: "inception_4a/pool_proj/bn" - name: "inception_4a/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/1x1/bn" - bottom: "inception_4a/3x3/bn" - bottom: "inception_4a/double3x3b/bn" - bottom: "inception_4a/pool_proj/bn" - top: "inception_4a/output" - name: "inception_4a/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/1x1" - name: "inception_4b/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/1x1" - name: "inception_4b/1x1/bn" - top: "inception_4b/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/1x1/bn" - top: "inception_4b/1x1/bn" - name: "inception_4b/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/3x3_reduce" - name: "inception_4b/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/3x3_reduce" - name: "inception_4b/3x3_reduce/bn" - top: "inception_4b/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/3x3_reduce/bn" - top: "inception_4b/3x3_reduce/bn" - name: "inception_4b/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/3x3_reduce/bn" - top: "inception_4b/3x3" - name: "inception_4b/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/3x3" - name: "inception_4b/3x3/bn" - top: "inception_4b/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/3x3/bn" - top: "inception_4b/3x3/bn" - name: "inception_4b/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/double3x3_reduce" - name: "inception_4b/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/double3x3_reduce" - name: "inception_4b/double3x3_reduce/bn" - top: "inception_4b/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3_reduce/bn" - top: "inception_4b/double3x3_reduce/bn" - name: "inception_4b/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3_reduce/bn" - top: "inception_4b/double3x3a" - name: "inception_4b/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/double3x3a" - name: "inception_4b/double3x3a/bn" - top: "inception_4b/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3a/bn" - top: "inception_4b/double3x3a/bn" - name: "inception_4b/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3a/bn" - top: "inception_4b/double3x3b" - name: "inception_4b/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/double3x3b" - name: "inception_4b/double3x3b/bn" - top: "inception_4b/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3b/bn" - top: "inception_4b/double3x3b/bn" - name: "inception_4b/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/pool" - name: "inception_4b/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4b/pool" - top: "inception_4b/pool_proj" - name: "inception_4b/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/pool_proj" - name: "inception_4b/pool_proj/bn" - top: "inception_4b/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/pool_proj/bn" - top: "inception_4b/pool_proj/bn" - name: "inception_4b/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/1x1/bn" - bottom: "inception_4b/3x3/bn" - bottom: "inception_4b/double3x3b/bn" - bottom: "inception_4b/pool_proj/bn" - top: "inception_4b/output" - name: "inception_4b/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/1x1" - name: "inception_4c/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/1x1" - name: "inception_4c/1x1/bn" - top: "inception_4c/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/1x1/bn" - top: "inception_4c/1x1/bn" - name: "inception_4c/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/3x3_reduce" - name: "inception_4c/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/3x3_reduce" - name: "inception_4c/3x3_reduce/bn" - top: "inception_4c/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/3x3_reduce/bn" - top: "inception_4c/3x3_reduce/bn" - name: "inception_4c/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/3x3_reduce/bn" - top: "inception_4c/3x3" - name: "inception_4c/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/3x3" - name: "inception_4c/3x3/bn" - top: "inception_4c/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/3x3/bn" - top: "inception_4c/3x3/bn" - name: "inception_4c/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/double3x3_reduce" - name: "inception_4c/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/double3x3_reduce" - name: "inception_4c/double3x3_reduce/bn" - top: "inception_4c/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3_reduce/bn" - top: "inception_4c/double3x3_reduce/bn" - name: "inception_4c/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3_reduce/bn" - top: "inception_4c/double3x3a" - name: "inception_4c/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/double3x3a" - name: "inception_4c/double3x3a/bn" - top: "inception_4c/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3a/bn" - top: "inception_4c/double3x3a/bn" - name: "inception_4c/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3a/bn" - top: "inception_4c/double3x3b" - name: "inception_4c/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/double3x3b" - name: "inception_4c/double3x3b/bn" - top: "inception_4c/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3b/bn" - top: "inception_4c/double3x3b/bn" - name: "inception_4c/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/pool" - name: "inception_4c/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4c/pool" - top: "inception_4c/pool_proj" - name: "inception_4c/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/pool_proj" - name: "inception_4c/pool_proj/bn" - top: "inception_4c/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/pool_proj/bn" - top: "inception_4c/pool_proj/bn" - name: "inception_4c/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/1x1/bn" - bottom: "inception_4c/3x3/bn" - bottom: "inception_4c/double3x3b/bn" - bottom: "inception_4c/pool_proj/bn" - top: "inception_4c/output" - name: "inception_4c/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/1x1" - name: "inception_4d/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/1x1" - name: "inception_4d/1x1/bn" - top: "inception_4d/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/1x1/bn" - top: "inception_4d/1x1/bn" - name: "inception_4d/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/3x3_reduce" - name: "inception_4d/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/3x3_reduce" - name: "inception_4d/3x3_reduce/bn" - top: "inception_4d/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/3x3_reduce/bn" - top: "inception_4d/3x3_reduce/bn" - name: "inception_4d/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/3x3_reduce/bn" - top: "inception_4d/3x3" - name: "inception_4d/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/3x3" - name: "inception_4d/3x3/bn" - top: "inception_4d/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/3x3/bn" - top: "inception_4d/3x3/bn" - name: "inception_4d/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/double3x3_reduce" - name: "inception_4d/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/double3x3_reduce" - name: "inception_4d/double3x3_reduce/bn" - top: "inception_4d/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3_reduce/bn" - top: "inception_4d/double3x3_reduce/bn" - name: "inception_4d/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3_reduce/bn" - top: "inception_4d/double3x3a" - name: "inception_4d/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/double3x3a" - name: "inception_4d/double3x3a/bn" - top: "inception_4d/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3a/bn" - top: "inception_4d/double3x3a/bn" - name: "inception_4d/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3a/bn" - top: "inception_4d/double3x3b" - name: "inception_4d/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/double3x3b" - name: "inception_4d/double3x3b/bn" - top: "inception_4d/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3b/bn" - top: "inception_4d/double3x3b/bn" - name: "inception_4d/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/pool" - name: "inception_4d/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4d/pool" - top: "inception_4d/pool_proj" - name: "inception_4d/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/pool_proj" - name: "inception_4d/pool_proj/bn" - top: "inception_4d/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/pool_proj/bn" - top: "inception_4d/pool_proj/bn" - name: "inception_4d/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/1x1/bn" - bottom: "inception_4d/3x3/bn" - bottom: "inception_4d/double3x3b/bn" - bottom: "inception_4d/pool_proj/bn" - top: "inception_4d/output" - name: "inception_4d/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/output" - top: "inception_4e/3x3_reduce" - name: "inception_4e/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/3x3_reduce" - name: "inception_4e/3x3_reduce/bn" - top: "inception_4e/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/3x3_reduce/bn" - top: "inception_4e/3x3_reduce/bn" - name: "inception_4e/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/3x3_reduce/bn" - top: "inception_4e/3x3" - name: "inception_4e/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/3x3" - name: "inception_4e/3x3/bn" - top: "inception_4e/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/3x3/bn" - top: "inception_4e/3x3/bn" - name: "inception_4e/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/output" - top: "inception_4e/double3x3_reduce" - name: "inception_4e/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/double3x3_reduce" - name: "inception_4e/double3x3_reduce/bn" - top: "inception_4e/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3_reduce/bn" - top: "inception_4e/double3x3_reduce/bn" - name: "inception_4e/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3_reduce/bn" - top: "inception_4e/double3x3a" - name: "inception_4e/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/double3x3a" - name: "inception_4e/double3x3a/bn" - top: "inception_4e/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3a/bn" - top: "inception_4e/double3x3a/bn" - name: "inception_4e/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3a/bn" - top: "inception_4e/double3x3b" - name: "inception_4e/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/double3x3b" - name: "inception_4e/double3x3b/bn" - top: "inception_4e/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3b/bn" - top: "inception_4e/double3x3b/bn" - name: "inception_4e/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/output" - top: "inception_4e/pool" - name: "inception_4e/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "inception_4e/3x3/bn" - bottom: "inception_4e/double3x3b/bn" - bottom: "inception_4e/pool" - top: "inception_4e/output" - name: "inception_4e/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "pool4/5x5_s3" - name: "pool4/5x5_s3" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 5 - stride: 3 - } -} -layer { - bottom: "pool4/5x5_s3" - top: "loss2/conv" - name: "loss2/conv" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss2/conv" - name: "loss2/conv/bn" - top: "loss2/conv/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/conv/bn" - top: "loss2/conv/bn" - name: "loss2/conv/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/conv/bn" - top: "loss2/fc" - name: "loss2/fc" - type: "InnerProduct" - param { - lr_mult: 1 - decay_mult: 1 - } - inner_product_param { - num_output: 1024 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss2/fc" - name: "loss2/fc/bn" - top: "loss2/fc/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/fc/bn" - top: "loss2/fc/bn" - name: "loss2/fc/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/fc/bn" - top: "loss2/classifier" - name: "loss2/classifier" - type: "InnerProduct" - 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 { - bottom: "loss2/classifier" - bottom: "label" - top: "loss2/loss" - name: "loss2/loss" - type: "SoftmaxWithLoss" - loss_weight: 0.3 -} -layer { - bottom: "loss2/classifier" - top: "loss2/prob" - name: "loss2/prob" - type: "Softmax" - include { - phase: TEST - } -} -layer { - bottom: "loss2/prob" - bottom: "label" - top: "loss2/top-1" - name: "loss2/top-1" - type: "Accuracy" - include { - phase: TEST - } -} -layer { - bottom: "loss2/prob" - bottom: "label" - top: "loss2/top-5" - name: "loss2/top-5" - type: "Accuracy" - accuracy_param { - top_k: 5 - } - include { - phase: TEST - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/1x1" - name: "inception_5a/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 352 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/1x1" - name: "inception_5a/1x1/bn" - top: "inception_5a/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/1x1/bn" - top: "inception_5a/1x1/bn" - name: "inception_5a/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/3x3_reduce" - name: "inception_5a/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/3x3_reduce" - name: "inception_5a/3x3_reduce/bn" - top: "inception_5a/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/3x3_reduce/bn" - top: "inception_5a/3x3_reduce/bn" - name: "inception_5a/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/3x3_reduce/bn" - top: "inception_5a/3x3" - name: "inception_5a/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 320 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/3x3" - name: "inception_5a/3x3/bn" - top: "inception_5a/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/3x3/bn" - top: "inception_5a/3x3/bn" - name: "inception_5a/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/double3x3_reduce" - name: "inception_5a/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/double3x3_reduce" - name: "inception_5a/double3x3_reduce/bn" - top: "inception_5a/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3_reduce/bn" - top: "inception_5a/double3x3_reduce/bn" - name: "inception_5a/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3_reduce/bn" - top: "inception_5a/double3x3a" - name: "inception_5a/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/double3x3a" - name: "inception_5a/double3x3a/bn" - top: "inception_5a/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3a/bn" - top: "inception_5a/double3x3a/bn" - name: "inception_5a/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3a/bn" - top: "inception_5a/double3x3b" - name: "inception_5a/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/double3x3b" - name: "inception_5a/double3x3b/bn" - top: "inception_5a/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3b/bn" - top: "inception_5a/double3x3b/bn" - name: "inception_5a/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/pool" - name: "inception_5a/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_5a/pool" - top: "inception_5a/pool_proj" - name: "inception_5a/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/pool_proj" - name: "inception_5a/pool_proj/bn" - top: "inception_5a/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/pool_proj/bn" - top: "inception_5a/pool_proj/bn" - name: "inception_5a/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/1x1/bn" - bottom: "inception_5a/3x3/bn" - bottom: "inception_5a/double3x3b/bn" - bottom: "inception_5a/pool_proj/bn" - top: "inception_5a/output" - name: "inception_5a/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/1x1" - name: "inception_5b/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 352 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/1x1" - name: "inception_5b/1x1/bn" - top: "inception_5b/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/1x1/bn" - top: "inception_5b/1x1/bn" - name: "inception_5b/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/3x3_reduce" - name: "inception_5b/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/3x3_reduce" - name: "inception_5b/3x3_reduce/bn" - top: "inception_5b/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/3x3_reduce/bn" - top: "inception_5b/3x3_reduce/bn" - name: "inception_5b/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/3x3_reduce/bn" - top: "inception_5b/3x3" - name: "inception_5b/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 320 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/3x3" - name: "inception_5b/3x3/bn" - top: "inception_5b/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/3x3/bn" - top: "inception_5b/3x3/bn" - name: "inception_5b/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/double3x3_reduce" - name: "inception_5b/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/double3x3_reduce" - name: "inception_5b/double3x3_reduce/bn" - top: "inception_5b/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3_reduce/bn" - top: "inception_5b/double3x3_reduce/bn" - name: "inception_5b/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3_reduce/bn" - top: "inception_5b/double3x3a" - name: "inception_5b/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/double3x3a" - name: "inception_5b/double3x3a/bn" - top: "inception_5b/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3a/bn" - top: "inception_5b/double3x3a/bn" - name: "inception_5b/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3a/bn" - top: "inception_5b/double3x3b" - name: "inception_5b/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/double3x3b" - name: "inception_5b/double3x3b/bn" - top: "inception_5b/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3b/bn" - top: "inception_5b/double3x3b/bn" - name: "inception_5b/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/pool" - name: "inception_5b/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_5b/pool" - top: "inception_5b/pool_proj" - name: "inception_5b/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/pool_proj" - name: "inception_5b/pool_proj/bn" - top: "inception_5b/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/pool_proj/bn" - top: "inception_5b/pool_proj/bn" - name: "inception_5b/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/1x1/bn" - bottom: "inception_5b/3x3/bn" - bottom: "inception_5b/double3x3b/bn" - bottom: "inception_5b/pool_proj/bn" - top: "inception_5b/output" - name: "inception_5b/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/output" - top: "pool5/7x7_s1" - name: "pool5/7x7_s1" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 7 - stride: 1 - } -} -layer { - bottom: "pool5/7x7_s1" - top: "loss3/classifier" - name: "loss3/classifier" - type: "InnerProduct" - 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 { - bottom: "loss3/classifier" - bottom: "label" - top: "loss3/loss" - name: "loss3/loss" - type: "SoftmaxWithLoss" - loss_weight: 1 -} -layer { - bottom: "loss3/classifier" - top: "loss3/prob" - name: "loss3/prob" - type: "Softmax" - include { - phase: TEST - } -} -layer { - bottom: "loss3/prob" - bottom: "label" - top: "loss3/top-1" - name: "loss3/top-1" - type: "Accuracy" - include { - phase: TEST - } -} -layer { - bottom: "loss3/prob" - bottom: "label" - top: "loss3/top-5" - name: "loss3/top-5" - type: "Accuracy" - accuracy_param { - top_k: 5 - } - include { - phase: TEST - } -} diff --git a/models/mkl2017_googlenet_v2/train_val_batch1.prototxt b/models/mkl2017_googlenet_v2/train_val_batch1.prototxt deleted file mode 100644 index ade4f3ab2..000000000 --- a/models/mkl2017_googlenet_v2/train_val_batch1.prototxt +++ /dev/null @@ -1,3388 +0,0 @@ -name: "InceptionNetwork" -layer { - top: "data" - top: "label" - name: "data" - type: "Data" - data_param { - source: "examples/imagenet/ilsvrc12_train_lmdb" - batch_size: 1 - backend: LMDB - shuffle: true - } - include { - phase: TRAIN - } - transform_param { - mirror: true - crop_size: 224 -# mean_file: "examples/imagenet/ilsvrc12_val_lmdb" - mean_value: 104 - mean_value: 117 - mean_value: 123 - } -} -### Validation Set -layer { - top: "data" - top: "label" - name: "data" - type: "Data" - data_param { - source: "/media/data0/image/ilsvrc15/ilsvrc12_val_lmdb" - batch_size: 32 - backend: LMDB - } - include { - phase: TEST - } - transform_param { - mirror: false - crop_size: 224 -# mean_file: "/media/data0/image/ilsvrc15/imagenet_mean.binaryproto" - mean_value: 104 - mean_value: 117 - mean_value: 123 - } -} - -layer { - bottom: "data" - top: "conv1/7x7_s2" - name: "conv1/7x7_s2" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 3 - kernel_size: 7 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "conv1/7x7_s2" - name: "conv1/7x7_s2/bn" - top: "conv1/7x7_s2/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "conv1/7x7_s2/bn" - top: "conv1/7x7_s2/bn" - name: "conv1/7x7_s2/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "conv1/7x7_s2/bn" - top: "pool1/3x3_s2" - name: "pool1/3x3_s2" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "pool1/3x3_s2" - top: "conv2/3x3_reduce" - name: "conv2/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "conv2/3x3_reduce" - name: "conv2/3x3_reduce/bn" - top: "conv2/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3_reduce/bn" - top: "conv2/3x3_reduce/bn" - name: "conv2/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3_reduce/bn" - top: "conv2/3x3" - name: "conv2/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "conv2/3x3" - name: "conv2/3x3/bn" - top: "conv2/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3/bn" - top: "conv2/3x3/bn" - name: "conv2/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "conv2/3x3/bn" - top: "pool2/3x3_s2" - name: "pool2/3x3_s2" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/1x1" - name: "inception_3a/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/1x1" - name: "inception_3a/1x1/bn" - top: "inception_3a/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/1x1/bn" - top: "inception_3a/1x1/bn" - name: "inception_3a/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/3x3_reduce" - name: "inception_3a/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/3x3_reduce" - name: "inception_3a/3x3_reduce/bn" - top: "inception_3a/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/3x3_reduce/bn" - top: "inception_3a/3x3_reduce/bn" - name: "inception_3a/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/3x3_reduce/bn" - top: "inception_3a/3x3" - name: "inception_3a/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/3x3" - name: "inception_3a/3x3/bn" - top: "inception_3a/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/3x3/bn" - top: "inception_3a/3x3/bn" - name: "inception_3a/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/double3x3_reduce" - name: "inception_3a/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/double3x3_reduce" - name: "inception_3a/double3x3_reduce/bn" - top: "inception_3a/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3_reduce/bn" - top: "inception_3a/double3x3_reduce/bn" - name: "inception_3a/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3_reduce/bn" - top: "inception_3a/double3x3a" - name: "inception_3a/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/double3x3a" - name: "inception_3a/double3x3a/bn" - top: "inception_3a/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} - -layer { - bottom: "inception_3a/double3x3a/bn" - top: "inception_3a/double3x3a/bn" - name: "inception_3a/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3a/bn" - top: "inception_3a/double3x3b" - name: "inception_3a/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/double3x3b" - name: "inception_3a/double3x3b/bn" - top: "inception_3a/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/double3x3b/bn" - top: "inception_3a/double3x3b/bn" - name: "inception_3a/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "pool2/3x3_s2" - top: "inception_3a/pool" - name: "inception_3a/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_3a/pool" - top: "inception_3a/pool_proj" - name: "inception_3a/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 32 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3a/pool_proj" - name: "inception_3a/pool_proj/bn" - top: "inception_3a/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/pool_proj/bn" - top: "inception_3a/pool_proj/bn" - name: "inception_3a/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/1x1/bn" - bottom: "inception_3a/3x3/bn" - bottom: "inception_3a/double3x3b/bn" - bottom: "inception_3a/pool_proj/bn" - top: "inception_3a/output" - name: "inception_3a/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/1x1" - name: "inception_3b/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/1x1" - name: "inception_3b/1x1/bn" - top: "inception_3b/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/1x1/bn" - top: "inception_3b/1x1/bn" - name: "inception_3b/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/3x3_reduce" - name: "inception_3b/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/3x3_reduce" - name: "inception_3b/3x3_reduce/bn" - top: "inception_3b/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} - -layer { - bottom: "inception_3b/3x3_reduce/bn" - top: "inception_3b/3x3_reduce/bn" - name: "inception_3b/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/3x3_reduce/bn" - top: "inception_3b/3x3" - name: "inception_3b/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/3x3" - name: "inception_3b/3x3/bn" - top: "inception_3b/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/3x3/bn" - top: "inception_3b/3x3/bn" - name: "inception_3b/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/double3x3_reduce" - name: "inception_3b/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/double3x3_reduce" - name: "inception_3b/double3x3_reduce/bn" - top: "inception_3b/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3_reduce/bn" - top: "inception_3b/double3x3_reduce/bn" - name: "inception_3b/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3_reduce/bn" - top: "inception_3b/double3x3a" - name: "inception_3b/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/double3x3a" - name: "inception_3b/double3x3a/bn" - top: "inception_3b/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3a/bn" - top: "inception_3b/double3x3a/bn" - name: "inception_3b/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3a/bn" - top: "inception_3b/double3x3b" - name: "inception_3b/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/double3x3b" - name: "inception_3b/double3x3b/bn" - top: "inception_3b/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/double3x3b/bn" - top: "inception_3b/double3x3b/bn" - name: "inception_3b/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3a/output" - top: "inception_3b/pool" - name: "inception_3b/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_3b/pool" - top: "inception_3b/pool_proj" - name: "inception_3b/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3b/pool_proj" - name: "inception_3b/pool_proj/bn" - top: "inception_3b/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/pool_proj/bn" - top: "inception_3b/pool_proj/bn" - name: "inception_3b/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/1x1/bn" - bottom: "inception_3b/3x3/bn" - bottom: "inception_3b/double3x3b/bn" - bottom: "inception_3b/pool_proj/bn" - top: "inception_3b/output" - name: "inception_3b/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/output" - top: "inception_3c/3x3_reduce" - name: "inception_3c/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/3x3_reduce" - name: "inception_3c/3x3_reduce/bn" - top: "inception_3c/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/3x3_reduce/bn" - top: "inception_3c/3x3_reduce/bn" - name: "inception_3c/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/3x3_reduce/bn" - top: "inception_3c/3x3" - name: "inception_3c/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/3x3" - name: "inception_3c/3x3/bn" - top: "inception_3c/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/3x3/bn" - top: "inception_3c/3x3/bn" - name: "inception_3c/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/output" - top: "inception_3c/double3x3_reduce" - name: "inception_3c/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/double3x3_reduce" - name: "inception_3c/double3x3_reduce/bn" - top: "inception_3c/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3_reduce/bn" - top: "inception_3c/double3x3_reduce/bn" - name: "inception_3c/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3_reduce/bn" - top: "inception_3c/double3x3a" - name: "inception_3c/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/double3x3a" - name: "inception_3c/double3x3a/bn" - top: "inception_3c/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} - -layer { - bottom: "inception_3c/double3x3a/bn" - top: "inception_3c/double3x3a/bn" - name: "inception_3c/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3a/bn" - top: "inception_3c/double3x3b" - name: "inception_3c/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_3c/double3x3b" - name: "inception_3c/double3x3b/bn" - top: "inception_3c/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/double3x3b/bn" - top: "inception_3c/double3x3b/bn" - name: "inception_3c/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3b/output" - top: "inception_3c/pool" - name: "inception_3c/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "inception_3c/3x3/bn" - bottom: "inception_3c/double3x3b/bn" - bottom: "inception_3c/pool" - top: "inception_3c/output" - name: "inception_3c/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "pool3/5x5_s3" - name: "pool3/5x5_s3" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 5 - stride: 3 - } -} -layer { - bottom: "pool3/5x5_s3" - top: "loss1/conv" - name: "loss1/conv" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss1/conv" - name: "loss1/conv/bn" - top: "loss1/conv/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/conv/bn" - top: "loss1/conv/bn" - name: "loss1/conv/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/conv/bn" - top: "loss1/fc" - name: "loss1/fc" - type: "InnerProduct" - param { - lr_mult: 1 - decay_mult: 1 - } - inner_product_param { - num_output: 1024 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss1/fc" - name: "loss1/fc/bn" - top: "loss1/fc/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/fc/bn" - top: "loss1/fc/bn" - name: "loss1/fc/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss1/fc/bn" - top: "loss1/classifier" - name: "loss1/classifier" - type: "InnerProduct" - 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 { - bottom: "loss1/classifier" - bottom: "label" - top: "loss1/loss" - name: "loss1/loss" - type: "SoftmaxWithLoss" - loss_weight: 0.3 -} -layer { - bottom: "loss1/classifier" - top: "loss1/prob" - name: "loss1/prob" - type: "Softmax" - include { - phase: TEST - } -} -layer { - bottom: "loss1/prob" - bottom: "label" - top: "loss1/top-1" - name: "loss1/top-1" - type: "Accuracy" - include { - phase: TEST - } -} -layer { - bottom: "loss1/prob" - bottom: "label" - top: "loss1/top-5" - name: "loss1/top-5" - type: "Accuracy" - accuracy_param { - top_k: 5 - } - include { - phase: TEST - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/1x1" - name: "inception_4a/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/1x1" - name: "inception_4a/1x1/bn" - top: "inception_4a/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/1x1/bn" - top: "inception_4a/1x1/bn" - name: "inception_4a/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/3x3_reduce" - name: "inception_4a/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 64 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/3x3_reduce" - name: "inception_4a/3x3_reduce/bn" - top: "inception_4a/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/3x3_reduce/bn" - top: "inception_4a/3x3_reduce/bn" - name: "inception_4a/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/3x3_reduce/bn" - top: "inception_4a/3x3" - name: "inception_4a/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/3x3" - name: "inception_4a/3x3/bn" - top: "inception_4a/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/3x3/bn" - top: "inception_4a/3x3/bn" - name: "inception_4a/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/double3x3_reduce" - name: "inception_4a/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/double3x3_reduce" - name: "inception_4a/double3x3_reduce/bn" - top: "inception_4a/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3_reduce/bn" - top: "inception_4a/double3x3_reduce/bn" - name: "inception_4a/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3_reduce/bn" - top: "inception_4a/double3x3a" - name: "inception_4a/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/double3x3a" - name: "inception_4a/double3x3a/bn" - top: "inception_4a/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3a/bn" - top: "inception_4a/double3x3a/bn" - name: "inception_4a/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3a/bn" - top: "inception_4a/double3x3b" - name: "inception_4a/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/double3x3b" - name: "inception_4a/double3x3b/bn" - top: "inception_4a/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/double3x3b/bn" - top: "inception_4a/double3x3b/bn" - name: "inception_4a/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_3c/output" - top: "inception_4a/pool" - name: "inception_4a/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4a/pool" - top: "inception_4a/pool_proj" - name: "inception_4a/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4a/pool_proj" - name: "inception_4a/pool_proj/bn" - top: "inception_4a/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/pool_proj/bn" - top: "inception_4a/pool_proj/bn" - name: "inception_4a/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/1x1/bn" - bottom: "inception_4a/3x3/bn" - bottom: "inception_4a/double3x3b/bn" - bottom: "inception_4a/pool_proj/bn" - top: "inception_4a/output" - name: "inception_4a/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/1x1" - name: "inception_4b/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/1x1" - name: "inception_4b/1x1/bn" - top: "inception_4b/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/1x1/bn" - top: "inception_4b/1x1/bn" - name: "inception_4b/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/3x3_reduce" - name: "inception_4b/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/3x3_reduce" - name: "inception_4b/3x3_reduce/bn" - top: "inception_4b/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/3x3_reduce/bn" - top: "inception_4b/3x3_reduce/bn" - name: "inception_4b/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/3x3_reduce/bn" - top: "inception_4b/3x3" - name: "inception_4b/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/3x3" - name: "inception_4b/3x3/bn" - top: "inception_4b/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/3x3/bn" - top: "inception_4b/3x3/bn" - name: "inception_4b/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/double3x3_reduce" - name: "inception_4b/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/double3x3_reduce" - name: "inception_4b/double3x3_reduce/bn" - top: "inception_4b/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3_reduce/bn" - top: "inception_4b/double3x3_reduce/bn" - name: "inception_4b/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3_reduce/bn" - top: "inception_4b/double3x3a" - name: "inception_4b/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/double3x3a" - name: "inception_4b/double3x3a/bn" - top: "inception_4b/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3a/bn" - top: "inception_4b/double3x3a/bn" - name: "inception_4b/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3a/bn" - top: "inception_4b/double3x3b" - name: "inception_4b/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/double3x3b" - name: "inception_4b/double3x3b/bn" - top: "inception_4b/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/double3x3b/bn" - top: "inception_4b/double3x3b/bn" - name: "inception_4b/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4a/output" - top: "inception_4b/pool" - name: "inception_4b/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4b/pool" - top: "inception_4b/pool_proj" - name: "inception_4b/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4b/pool_proj" - name: "inception_4b/pool_proj/bn" - top: "inception_4b/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/pool_proj/bn" - top: "inception_4b/pool_proj/bn" - name: "inception_4b/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/1x1/bn" - bottom: "inception_4b/3x3/bn" - bottom: "inception_4b/double3x3b/bn" - bottom: "inception_4b/pool_proj/bn" - top: "inception_4b/output" - name: "inception_4b/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/1x1" - name: "inception_4c/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/1x1" - name: "inception_4c/1x1/bn" - top: "inception_4c/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/1x1/bn" - top: "inception_4c/1x1/bn" - name: "inception_4c/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/3x3_reduce" - name: "inception_4c/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/3x3_reduce" - name: "inception_4c/3x3_reduce/bn" - top: "inception_4c/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/3x3_reduce/bn" - top: "inception_4c/3x3_reduce/bn" - name: "inception_4c/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/3x3_reduce/bn" - top: "inception_4c/3x3" - name: "inception_4c/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/3x3" - name: "inception_4c/3x3/bn" - top: "inception_4c/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/3x3/bn" - top: "inception_4c/3x3/bn" - name: "inception_4c/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/double3x3_reduce" - name: "inception_4c/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/double3x3_reduce" - name: "inception_4c/double3x3_reduce/bn" - top: "inception_4c/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3_reduce/bn" - top: "inception_4c/double3x3_reduce/bn" - name: "inception_4c/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3_reduce/bn" - top: "inception_4c/double3x3a" - name: "inception_4c/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/double3x3a" - name: "inception_4c/double3x3a/bn" - top: "inception_4c/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3a/bn" - top: "inception_4c/double3x3a/bn" - name: "inception_4c/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3a/bn" - top: "inception_4c/double3x3b" - name: "inception_4c/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/double3x3b" - name: "inception_4c/double3x3b/bn" - top: "inception_4c/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/double3x3b/bn" - top: "inception_4c/double3x3b/bn" - name: "inception_4c/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4b/output" - top: "inception_4c/pool" - name: "inception_4c/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4c/pool" - top: "inception_4c/pool_proj" - name: "inception_4c/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4c/pool_proj" - name: "inception_4c/pool_proj/bn" - top: "inception_4c/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/pool_proj/bn" - top: "inception_4c/pool_proj/bn" - name: "inception_4c/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/1x1/bn" - bottom: "inception_4c/3x3/bn" - bottom: "inception_4c/double3x3b/bn" - bottom: "inception_4c/pool_proj/bn" - top: "inception_4c/output" - name: "inception_4c/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/1x1" - name: "inception_4d/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/1x1" - name: "inception_4d/1x1/bn" - top: "inception_4d/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/1x1/bn" - top: "inception_4d/1x1/bn" - name: "inception_4d/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/3x3_reduce" - name: "inception_4d/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/3x3_reduce" - name: "inception_4d/3x3_reduce/bn" - top: "inception_4d/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/3x3_reduce/bn" - top: "inception_4d/3x3_reduce/bn" - name: "inception_4d/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/3x3_reduce/bn" - top: "inception_4d/3x3" - name: "inception_4d/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/3x3" - name: "inception_4d/3x3/bn" - top: "inception_4d/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/3x3/bn" - top: "inception_4d/3x3/bn" - name: "inception_4d/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/double3x3_reduce" - name: "inception_4d/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/double3x3_reduce" - name: "inception_4d/double3x3_reduce/bn" - top: "inception_4d/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3_reduce/bn" - top: "inception_4d/double3x3_reduce/bn" - name: "inception_4d/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3_reduce/bn" - top: "inception_4d/double3x3a" - name: "inception_4d/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/double3x3a" - name: "inception_4d/double3x3a/bn" - top: "inception_4d/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3a/bn" - top: "inception_4d/double3x3a/bn" - name: "inception_4d/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3a/bn" - top: "inception_4d/double3x3b" - name: "inception_4d/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/double3x3b" - name: "inception_4d/double3x3b/bn" - top: "inception_4d/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/double3x3b/bn" - top: "inception_4d/double3x3b/bn" - name: "inception_4d/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4c/output" - top: "inception_4d/pool" - name: "inception_4d/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_4d/pool" - top: "inception_4d/pool_proj" - name: "inception_4d/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 96 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4d/pool_proj" - name: "inception_4d/pool_proj/bn" - top: "inception_4d/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/pool_proj/bn" - top: "inception_4d/pool_proj/bn" - name: "inception_4d/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/1x1/bn" - bottom: "inception_4d/3x3/bn" - bottom: "inception_4d/double3x3b/bn" - bottom: "inception_4d/pool_proj/bn" - top: "inception_4d/output" - name: "inception_4d/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/output" - top: "inception_4e/3x3_reduce" - name: "inception_4e/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/3x3_reduce" - name: "inception_4e/3x3_reduce/bn" - top: "inception_4e/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/3x3_reduce/bn" - top: "inception_4e/3x3_reduce/bn" - name: "inception_4e/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/3x3_reduce/bn" - top: "inception_4e/3x3" - name: "inception_4e/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/3x3" - name: "inception_4e/3x3/bn" - top: "inception_4e/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/3x3/bn" - top: "inception_4e/3x3/bn" - name: "inception_4e/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/output" - top: "inception_4e/double3x3_reduce" - name: "inception_4e/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/double3x3_reduce" - name: "inception_4e/double3x3_reduce/bn" - top: "inception_4e/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3_reduce/bn" - top: "inception_4e/double3x3_reduce/bn" - name: "inception_4e/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3_reduce/bn" - top: "inception_4e/double3x3a" - name: "inception_4e/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/double3x3a" - name: "inception_4e/double3x3a/bn" - top: "inception_4e/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3a/bn" - top: "inception_4e/double3x3a/bn" - name: "inception_4e/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3a/bn" - top: "inception_4e/double3x3b" - name: "inception_4e/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 256 - pad: 1 - kernel_size: 3 - stride: 2 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_4e/double3x3b" - name: "inception_4e/double3x3b/bn" - top: "inception_4e/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/double3x3b/bn" - top: "inception_4e/double3x3b/bn" - name: "inception_4e/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4d/output" - top: "inception_4e/pool" - name: "inception_4e/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 2 - } -} -layer { - bottom: "inception_4e/3x3/bn" - bottom: "inception_4e/double3x3b/bn" - bottom: "inception_4e/pool" - top: "inception_4e/output" - name: "inception_4e/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "pool4/5x5_s3" - name: "pool4/5x5_s3" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 5 - stride: 3 - } -} -layer { - bottom: "pool4/5x5_s3" - top: "loss2/conv" - name: "loss2/conv" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss2/conv" - name: "loss2/conv/bn" - top: "loss2/conv/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/conv/bn" - top: "loss2/conv/bn" - name: "loss2/conv/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/conv/bn" - top: "loss2/fc" - name: "loss2/fc" - type: "InnerProduct" - param { - lr_mult: 1 - decay_mult: 1 - } - inner_product_param { - num_output: 1024 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "loss2/fc" - name: "loss2/fc/bn" - top: "loss2/fc/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/fc/bn" - top: "loss2/fc/bn" - name: "loss2/fc/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "loss2/fc/bn" - top: "loss2/classifier" - name: "loss2/classifier" - type: "InnerProduct" - 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 { - bottom: "loss2/classifier" - bottom: "label" - top: "loss2/loss" - name: "loss2/loss" - type: "SoftmaxWithLoss" - loss_weight: 0.3 -} -layer { - bottom: "loss2/classifier" - top: "loss2/prob" - name: "loss2/prob" - type: "Softmax" - include { - phase: TEST - } -} -layer { - bottom: "loss2/prob" - bottom: "label" - top: "loss2/top-1" - name: "loss2/top-1" - type: "Accuracy" - include { - phase: TEST - } -} -layer { - bottom: "loss2/prob" - bottom: "label" - top: "loss2/top-5" - name: "loss2/top-5" - type: "Accuracy" - accuracy_param { - top_k: 5 - } - include { - phase: TEST - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/1x1" - name: "inception_5a/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 352 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/1x1" - name: "inception_5a/1x1/bn" - top: "inception_5a/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/1x1/bn" - top: "inception_5a/1x1/bn" - name: "inception_5a/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/3x3_reduce" - name: "inception_5a/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/3x3_reduce" - name: "inception_5a/3x3_reduce/bn" - top: "inception_5a/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/3x3_reduce/bn" - top: "inception_5a/3x3_reduce/bn" - name: "inception_5a/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/3x3_reduce/bn" - top: "inception_5a/3x3" - name: "inception_5a/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 320 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/3x3" - name: "inception_5a/3x3/bn" - top: "inception_5a/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/3x3/bn" - top: "inception_5a/3x3/bn" - name: "inception_5a/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/double3x3_reduce" - name: "inception_5a/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 160 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/double3x3_reduce" - name: "inception_5a/double3x3_reduce/bn" - top: "inception_5a/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3_reduce/bn" - top: "inception_5a/double3x3_reduce/bn" - name: "inception_5a/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3_reduce/bn" - top: "inception_5a/double3x3a" - name: "inception_5a/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/double3x3a" - name: "inception_5a/double3x3a/bn" - top: "inception_5a/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3a/bn" - top: "inception_5a/double3x3a/bn" - name: "inception_5a/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3a/bn" - top: "inception_5a/double3x3b" - name: "inception_5a/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/double3x3b" - name: "inception_5a/double3x3b/bn" - top: "inception_5a/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/double3x3b/bn" - top: "inception_5a/double3x3b/bn" - name: "inception_5a/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_4e/output" - top: "inception_5a/pool" - name: "inception_5a/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_5a/pool" - top: "inception_5a/pool_proj" - name: "inception_5a/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5a/pool_proj" - name: "inception_5a/pool_proj/bn" - top: "inception_5a/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/pool_proj/bn" - top: "inception_5a/pool_proj/bn" - name: "inception_5a/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/1x1/bn" - bottom: "inception_5a/3x3/bn" - bottom: "inception_5a/double3x3b/bn" - bottom: "inception_5a/pool_proj/bn" - top: "inception_5a/output" - name: "inception_5a/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/1x1" - name: "inception_5b/1x1" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 352 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/1x1" - name: "inception_5b/1x1/bn" - top: "inception_5b/1x1/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/1x1/bn" - top: "inception_5b/1x1/bn" - name: "inception_5b/1x1/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/3x3_reduce" - name: "inception_5b/3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/3x3_reduce" - name: "inception_5b/3x3_reduce/bn" - top: "inception_5b/3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/3x3_reduce/bn" - top: "inception_5b/3x3_reduce/bn" - name: "inception_5b/3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/3x3_reduce/bn" - top: "inception_5b/3x3" - name: "inception_5b/3x3" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 320 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/3x3" - name: "inception_5b/3x3/bn" - top: "inception_5b/3x3/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/3x3/bn" - top: "inception_5b/3x3/bn" - name: "inception_5b/3x3/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/double3x3_reduce" - name: "inception_5b/double3x3_reduce" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 192 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/double3x3_reduce" - name: "inception_5b/double3x3_reduce/bn" - top: "inception_5b/double3x3_reduce/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3_reduce/bn" - top: "inception_5b/double3x3_reduce/bn" - name: "inception_5b/double3x3_reduce/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3_reduce/bn" - top: "inception_5b/double3x3a" - name: "inception_5b/double3x3a" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/double3x3a" - name: "inception_5b/double3x3a/bn" - top: "inception_5b/double3x3a/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3a/bn" - top: "inception_5b/double3x3a/bn" - name: "inception_5b/double3x3a/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3a/bn" - top: "inception_5b/double3x3b" - name: "inception_5b/double3x3b" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 224 - pad: 1 - kernel_size: 3 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/double3x3b" - name: "inception_5b/double3x3b/bn" - top: "inception_5b/double3x3b/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/double3x3b/bn" - top: "inception_5b/double3x3b/bn" - name: "inception_5b/double3x3b/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5a/output" - top: "inception_5b/pool" - name: "inception_5b/pool" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: MAX - kernel_size: 3 - stride: 1 - pad: 1 - } -} -layer { - bottom: "inception_5b/pool" - top: "inception_5b/pool_proj" - name: "inception_5b/pool_proj" - type: "Convolution" - param { - lr_mult: 1 - decay_mult: 1 - } - convolution_param { - engine: MKL2017 - num_output: 128 - pad: 0 - kernel_size: 1 - stride: 1 - weight_filler { - type: "xavier" - } - bias_term: false - } -} -layer { - bottom: "inception_5b/pool_proj" - name: "inception_5b/pool_proj/bn" - top: "inception_5b/pool_proj/bn" - type: "BatchNorm" - batch_norm_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/pool_proj/bn" - top: "inception_5b/pool_proj/bn" - name: "inception_5b/pool_proj/bn/relu" - type: "ReLU" - relu_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/1x1/bn" - bottom: "inception_5b/3x3/bn" - bottom: "inception_5b/double3x3b/bn" - bottom: "inception_5b/pool_proj/bn" - top: "inception_5b/output" - name: "inception_5b/output" - type: "Concat" - concat_param { - engine: MKL2017 - } -} -layer { - bottom: "inception_5b/output" - top: "pool5/7x7_s1" - name: "pool5/7x7_s1" - type: "Pooling" - pooling_param { - engine: MKL2017 - pool: AVE - kernel_size: 7 - stride: 1 - } -} -layer { - bottom: "pool5/7x7_s1" - top: "loss3/classifier" - name: "loss3/classifier" - type: "InnerProduct" - 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 { - bottom: "loss3/classifier" - bottom: "label" - top: "loss3/loss" - name: "loss3/loss" - type: "SoftmaxWithLoss" - loss_weight: 1 -} -layer { - bottom: "loss3/classifier" - top: "loss3/prob" - name: "loss3/prob" - type: "Softmax" - include { - phase: TEST - } -} -layer { - bottom: "loss3/prob" - bottom: "label" - top: "loss3/top-1" - name: "loss3/top-1" - type: "Accuracy" - include { - phase: TEST - } -} -layer { - bottom: "loss3/prob" - bottom: "label" - top: "loss3/top-5" - name: "loss3/top-5" - type: "Accuracy" - accuracy_param { - top_k: 5 - } - include { - phase: TEST - } -}