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April 24, 2018 17:06
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cifar10 caffe
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name: "CIFAR10_quick" | |
layer { | |
name: "cifar" | |
type: "Data" | |
top: "data" | |
top: "label" | |
include { | |
phase: TRAIN | |
} | |
transform_param { | |
mean_file: "examples/cifar10/mean.binaryproto" | |
} | |
data_param { | |
source: "examples/cifar10/cifar10_train_lmdb" | |
batch_size: 100 | |
backend: LMDB | |
} | |
} | |
layer { | |
name: "cifar" | |
type: "Data" | |
top: "data" | |
top: "label" | |
include { | |
phase: TEST | |
} | |
transform_param { | |
mean_file: "examples/cifar10/mean.binaryproto" | |
} | |
data_param { | |
source: "examples/cifar10/cifar10_test_lmdb" | |
batch_size: 100 | |
backend: LMDB | |
} | |
} | |
layer { | |
name: "conv1" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1" | |
param { | |
lr_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
} | |
convolution_param { | |
num_output: 32 | |
pad: 2 | |
kernel_size: 5 | |
stride: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.0001 | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layer { | |
name: "pool1" | |
type: "Pooling" | |
bottom: "conv1" | |
top: "pool1" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "relu1" | |
type: "ReLU" | |
bottom: "pool1" | |
top: "pool1" | |
} | |
layer { | |
name: "conv2" | |
type: "Convolution" | |
bottom: "pool1" | |
top: "conv2" | |
param { | |
lr_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
} | |
convolution_param { | |
num_output: 32 | |
pad: 2 | |
kernel_size: 5 | |
stride: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layer { | |
name: "relu2" | |
type: "ReLU" | |
bottom: "conv2" | |
top: "conv2" | |
} | |
layer { | |
name: "pool2" | |
type: "Pooling" | |
bottom: "conv2" | |
top: "pool2" | |
pooling_param { | |
pool: AVE | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "conv3" | |
type: "Convolution" | |
bottom: "pool2" | |
top: "conv3" | |
param { | |
lr_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
stride: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layer { | |
name: "relu3" | |
type: "ReLU" | |
bottom: "conv3" | |
top: "conv3" | |
} | |
layer { | |
name: "pool3" | |
type: "Pooling" | |
bottom: "conv3" | |
top: "pool3" | |
pooling_param { | |
pool: AVE | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "ip1" | |
type: "InnerProduct" | |
bottom: "pool3" | |
top: "ip1" | |
param { | |
lr_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
} | |
inner_product_param { | |
num_output: 64 | |
weight_filler { | |
type: "gaussian" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layer { | |
name: "ip2" | |
type: "InnerProduct" | |
bottom: "ip1" | |
top: "ip2" | |
param { | |
lr_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
} | |
inner_product_param { | |
num_output: 10 | |
weight_filler { | |
type: "gaussian" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
} | |
} | |
} | |
layer { | |
name: "accuracy" | |
type: "Accuracy" | |
bottom: "ip2" | |
bottom: "label" | |
top: "accuracy" | |
include { | |
phase: TEST | |
} | |
} | |
layer { | |
name: "loss" | |
type: "SoftmaxWithLoss" | |
bottom: "ip2" | |
bottom: "label" | |
top: "loss" | |
} |
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