Created
July 15, 2015 03:32
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name: "Clafifai" | |
# --------------------- Data Layer -------------------------- | |
# input dimension is 36x36x3 | |
layers { | |
name: "data" | |
type: DATA | |
top: "data" | |
top: "label" | |
data_param { | |
source: "cache/lsp/LMDB_train" | |
backend: LMDB | |
batch_size: 512 | |
} | |
transform_param { | |
mean_value: 128 | |
mean_value: 128 | |
mean_value: 128 | |
mirror: false | |
} | |
include: { phase: TRAIN } | |
} | |
layers { | |
name: "data" | |
type: DATA | |
top: "data" | |
top: "label" | |
data_param { | |
source: "cache/lsp/LMDB_train" | |
backend: LMDB | |
batch_size: 512 | |
} | |
transform_param { | |
mean_value: 128 | |
mean_value: 128 | |
mean_value: 128 | |
mirror: false | |
} | |
include: { phase: TEST } | |
} | |
# --------------------- conv 1 -------------------------- | |
layers { | |
bottom: "data" | |
top: "conv1" | |
name: "conv1" | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
num_output: 96 | |
kernel_size: 7 | |
stride: 2 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layers { | |
bottom: "conv1" | |
top: "conv1" | |
name: "relu1" | |
type: RELU | |
} | |
layers { | |
bottom: "conv1" | |
top: "pool1" | |
name: "pool1" | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layers { | |
bottom: "pool1" | |
top: "norm1" | |
name: "norm1" | |
type: LRN | |
lrn_param { | |
local_size: 5 | |
alpha: 0.0001 | |
beta: 0.75 | |
} | |
} | |
# --------------------- conv 2 -------------------------- | |
layers { | |
bottom: "norm1" | |
top: "conv2" | |
name: "conv2" | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 5 | |
stride: 2 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layers { | |
bottom: "conv2" | |
top: "conv2" | |
name: "relu2" | |
type: RELU | |
} | |
layers { | |
bottom: "conv2" | |
top: "pool2" | |
name: "pool2" | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layers { | |
bottom: "pool2" | |
top: "norm2" | |
name: "norm2" | |
type: LRN | |
lrn_param { | |
local_size: 5 | |
alpha: 0.0001 | |
beta: 0.75 | |
} | |
} | |
# --------------------- conv 3 -------------------------- | |
layers { | |
bottom: "norm2" | |
top: "conv3" | |
name: "conv3" | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
num_output: 384 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layers { | |
bottom: "conv3" | |
top: "conv3" | |
name: "relu3" | |
type: RELU | |
} | |
# --------------------- conv 4 -------------------------- | |
layers { | |
bottom: "conv3" | |
top: "conv4" | |
name: "conv4" | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
num_output: 384 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layers { | |
bottom: "conv4" | |
top: "conv4" | |
name: "relu4" | |
type: RELU | |
} | |
# --------------------- conv 5 -------------------------- | |
layers { | |
bottom: "conv4" | |
top: "conv5" | |
name: "conv5" | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layers { | |
bottom: "conv5" | |
top: "conv5" | |
name: "relu5" | |
type: RELU | |
} | |
layers { | |
bottom: "conv5" | |
top: "pool5" | |
name: "pool5" | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
# -------------------- fully connected 1 ------------------ | |
layers { | |
bottom: "pool5" | |
top: "fc6" | |
name: "fc6" | |
type: INNER_PRODUCT | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
inner_product_param { | |
num_output: 4096 | |
weight_filler { | |
type: "gaussian" | |
std: 0.005 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layers { | |
bottom: "fc6" | |
top: "fc6" | |
name: "relu6" | |
type: RELU | |
} | |
layers { | |
bottom: "fc6" | |
top: "fc6" | |
name: "drop6" | |
type: DROPOUT | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
# -------------------- fully connected 2 ------------------ | |
layers { | |
bottom: "fc6" | |
top: "fc7" | |
name: "fc7" | |
type: INNER_PRODUCT | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
inner_product_param { | |
num_output: 4096 | |
weight_filler { | |
type: "gaussian" | |
std: 0.005 | |
} | |
bias_filler { | |
type: "constant" | |
value: 1 | |
} | |
} | |
} | |
layers { | |
bottom: "fc7" | |
top: "fc7" | |
name: "relu7" | |
type: RELU | |
} | |
layers { | |
bottom: "fc7" | |
top: "fc7" | |
name: "drop7" | |
type: DROPOUT | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
# -------------------- output layer ------------------ | |
layers { | |
bottom: "fc7" | |
top: "fc8" | |
name: "fc8" | |
type: INNER_PRODUCT | |
blobs_lr: 10 | |
blobs_lr: 20 | |
weight_decay: 1 | |
weight_decay: 0 | |
inner_product_param { | |
num_output: 9699 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
# -------------------- loss layer ------------------ | |
layers { | |
name: "accuracy" | |
type: ACCURACY | |
bottom: "fc8" | |
bottom: "label" | |
top: "accuracy" | |
include: { phase: TEST } | |
} | |
layers { | |
name: "loss" | |
type: SOFTMAX_LOSS | |
bottom: "fc8" | |
bottom: "label" | |
top: "loss" | |
} |
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