...C:\Users\vlj\Documents\GitHub\caffe\python\caffe\test\test_coord_map.py:46: DeprecationWarning: Please use assertEqual instead.
self.assertEquals(ax, 1)
........E........WARNING: Logging before InitGoogleLogging() is written to STDERR
I0122 21:16:09.047402 24972 common.cpp:36] System entropy source not available, using fallback algorithm to generate seed instead.
I0122 21:16:09.047402 24972 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train_data
I0122 21:16:09.047402 24972 net.cpp:330] The NetState did not contain stage 'val' specified by a rule in layer val_data
I0122 21:16:09.047402 24972 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer loss
I0122 21:16:09.047402 24972 net.cpp:330] The NetState did not contain stage 'val' specified by a rule in layer loss
I0122 21:16:09.047402 24972 net.cpp:51] Initializing net from parameters:
state {
phase: TEST
level: 0
stage: "deploy"
}
layer {
name: "deploy_data"
type: "Input"
top: "data"
include {
phase: TEST
stage: "deploy"
}
input_param {
shape {
dim: 1
dim: 1
dim: 10
dim: 10
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "data"
top: "ip"
inner_product_param {
num_output: 2
}
}
layer {
name: "pred"
type: "Softmax"
bottom: "ip"
top: "pred"
include {
phase: TEST
stage: "deploy"
}
}
I0122 21:16:09.047402 24972 layer_factory.hpp:77] Creating layer deploy_data
I0122 21:16:09.047402 24972 net.cpp:84] Creating Layer deploy_data
I0122 21:16:09.047402 24972 net.cpp:380] deploy_data -> data
I0122 21:16:09.047402 24972 net.cpp:122] Setting up deploy_data
I0122 21:16:09.047402 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.047402 24972 net.cpp:137] Memory required for data: 400
I0122 21:16:09.047402 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.047402 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.047402 24972 net.cpp:406] ip <- data
I0122 21:16:09.047402 24972 net.cpp:380] ip -> ip
I0122 21:16:09.047402 24972 net.cpp:122] Setting up ip
I0122 21:16:09.047402 24972 net.cpp:129] Top shape: 1 2 (2)
I0122 21:16:09.047402 24972 net.cpp:137] Memory required for data: 408
I0122 21:16:09.047402 24972 layer_factory.hpp:77] Creating layer pred
I0122 21:16:09.047402 24972 net.cpp:84] Creating Layer pred
I0122 21:16:09.047402 24972 net.cpp:406] pred <- ip
I0122 21:16:09.047402 24972 net.cpp:380] pred -> pred
I0122 21:16:09.047402 24972 net.cpp:122] Setting up pred
I0122 21:16:09.047402 24972 net.cpp:129] Top shape: 1 2 (2)
I0122 21:16:09.047402 24972 net.cpp:137] Memory required for data: 416
I0122 21:16:09.047402 24972 net.cpp:200] pred does not need backward computation.
I0122 21:16:09.047402 24972 net.cpp:200] ip does not need backward computation.
I0122 21:16:09.047402 24972 net.cpp:200] deploy_data does not need backward computation.
I0122 21:16:09.047402 24972 net.cpp:242] This network produces output pred
I0122 21:16:09.047402 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.054404 24972 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val_data
I0122 21:16:09.054404 24972 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer deploy_data
I0122 21:16:09.054404 24972 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer pred
I0122 21:16:09.054404 24972 net.cpp:51] Initializing net from parameters:
state {
phase: TRAIN
level: 0
stage: "train"
}
layer {
name: "train_data"
type: "DummyData"
top: "data"
top: "label"
include {
phase: TRAIN
stage: "train"
}
dummy_data_param {
shape {
dim: 1
dim: 1
dim: 10
dim: 10
}
shape {
dim: 1
dim: 1
dim: 1
dim: 1
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "data"
top: "ip"
inner_product_param {
num_output: 2
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip"
bottom: "label"
top: "loss"
include {
phase: TRAIN
stage: "train"
}
include {
phase: TEST
stage: "val"
}
}
I0122 21:16:09.054404 24972 layer_factory.hpp:77]. Creating layer train_data
I0122 21:16:09.055407 24972 net.cpp:84] Creating Layer train_data
I0122 21:16:09.055407 24972 net.cpp:380] train_data -> data
I0122 21:16:09.055407 24972 net.cpp:380] train_data -> label
I0122 21:16:09.055407 24972 net.cpp:122] Setting up train_data
I0122 21:16:09.055407 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.055407 24972 net.cpp:129] Top shape: 1 1 1 1 (1)
I0122 21:16:09.055407 24972 net.cpp:137] Memory required for data: 404
I0122 21:16:09.055407 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.055407 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.055407 24972 net.cpp:406] ip <- data
I0122 21:16:09.055407 24972 net.cpp:380] ip -> ip
I0122 21:16:09.055407 24972 net.cpp:122] Setting up ip
I0122 21:16:09.055407 24972 net.cpp:129] Top shape: 1 2 (2)
I0122 21:16:09.055407 24972 net.cpp:137] Memory required for data: 412
I0122 21:16:09.055407 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.055407 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.055407 24972 net.cpp:406] loss <- ip
I0122 21:16:09.055407 24972 net.cpp:406] loss <- label
I0122 21:16:09.055407 24972 net.cpp:380] loss -> loss
I0122 21:16:09.055407 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.055407 24972 net.cpp:122] Setting up loss
I0122 21:16:09.055407 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.055407 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.055407 24972 net.cpp:137] Memory required for data: 416
I0122 21:16:09.055407 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.055407 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.055407 24972 net.cpp:200] train_data does not need backward computation.
I0122 21:16:09.055407 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.055407 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.057404 24972 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train_data
I0122 21:16:09.057404 24972 net.cpp:330] The NetState did not contain stage 'deploy' specified by a rule in layer deploy_data
I0122 21:16:09.057404 24972 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer loss
I0122 21:16:09.057404 24972 net.cpp:330] The NetState did not contain stage 'deploy' specified by a rule in layer pred
I0122 21:16:09.057404 24972 net.cpp:51] Initializing net from parameters:
state {
phase: TEST
level: 0
stage: "val"
}
layer {
name: "val_data"
type: "DummyData"
top: "data"
top: "label"
include {
phase: TEST
stage: "val"
}
dummy_data_param {
shape {
dim: 1
dim: 1
dim: 10
dim: 10
}
shape {
dim: 1
dim: 1
dim: 1
dim: 1
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "data"
top: "ip"
inner_product_param {
num_output: 2
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip"
bottom: "label"
top: "loss"
include {
phase: TRAIN
stage: "train"
}
include {
phase: TEST
stage: "val"
}
}
I0122 21:16:09.057404 24972 layer_factory.hpp:77] Creating layer val_data
I0122 21:16:09.057404 24972 net.cpp:84] Creating Layer val_data
I0122 21:16:09.057404 24972 net.cpp:380] val_data -> data
I0122 21:16:09.057404 24972 net.cpp:380] val_data -> label
I0122 21:16:09.057404 24972 net.cpp:122] Setting up val_data
I0122 21:16:09.057404 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.057404 24972 net.cpp:129] Top shape: 1 1 1 1 (1)
I0122 21:16:09.057404 24972 net.cpp:137] Memory required for data: 404
I0122 21:16:09.057404 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.057404 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.057404 24972 net.cpp:406] ip <- data
I0122 21:16:09.057404 24972 net.cpp:380] ip -> ip
I0122 21:16:09.057404 24972 net.cpp:122] Setting up ip
I0122 21:16:09.057404 24972 net.cpp:129] Top shape: 1 2 (2)
I0122 21:16:09.057404 24972 net.cpp:137] Memory required for data: 412
I0122 21:16:09.057404 24972 layer_facto.ry.hpp:77] Creating layer loss
I0122 21:16:09.058401 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.058401 24972 net.cpp:406] loss <- ip
I0122 21:16:09.058401 24972 net.cpp:406] loss <- label
I0122 21:16:09.058401 24972 net.cpp:380] loss -> loss
I0122 21:16:09.058401 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.058401 24972 net.cpp:122] Setting up loss
I0122 21:16:09.058401 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.058401 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.058401 24972 net.cpp:137] Memory required for data: 416
I0122 21:16:09.058401 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.058401 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.058401 24972 net.cpp:200] val_data does not need backward computation.
I0122 21:16:09.058401 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.058401 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.059403 24972 net.cpp:304] The NetState level (0) is above the min_level (1) specified by a rule in layer Level1Only
I0122 21:16:09.059403 24972 net.cpp:304] The NetState level (0) is above the min_level (1) specified by a rule in layer Level>=1
I0122 21:16:09.059403 24972 net.cpp:51] Initializing net from parameters:
state {
phase: TEST
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
dummy_data_param {
shape {
dim: 1
dim: 1
dim: 10
dim: 10
}
}
}
layer {
name: "NoLevel"
type: "InnerProduct"
bottom: "data"
top: "NoLevel"
inner_product_param {
num_output: 1
}
}
layer {
name: "Level0Only"
type: "InnerProduct"
bottom: "data"
top: "Level0Only"
include {
min_level: 0
max_level: 0
}
inner_product_param {
num_output: 1
}
}
layer {
name: "Level>=0"
type: "InnerProduct"
bottom: "data"
top: "Level>=0"
include {
min_level: 0
}
inner_product_param {
num_output: 1
}
}
I0122 21:16:09.059403 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.059403 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.059403 24972 net.cpp:380] data -> data
I0122 21:16:09.059403 24972 net.cpp:122] Setting up data
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.059403 24972 net.cpp:137] Memory required for data: 400
I0122 21:16:09.059403 24972 layer_factory.hpp:77] Creating layer data_data_0_split
I0122 21:16:09.059403 24972 net.cpp:84] Creating Layer data_data_0_split
I0122 21:16:09.059403 24972 net.cpp:406] data_data_0_split <- data
I0122 21:16:09.059403 24972 net.cpp:380] data_data_0_split -> data_data_0_split_0
I0122 21:16:09.059403 24972 net.cpp:380] data_data_0_split -> data_data_0_split_1
I0122 21:16:09.059403 24972 net.cpp:380] data_data_0_split -> data_data_0_split_2
I0122 21:16:09.059403 24972 net.cpp:122] Setting up data_data_0_split
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.059403 24972 net.cpp:137] Memory required for data: 1600
I0122 21:16:09.059403 24972 layer_factory.hpp:77] Creating layer NoLevel
I0122 21:16:09.059403 24972 net.cpp:84] Creating Layer NoLevel
I0122 21:16:09.059403 24972 net.cpp:406] NoLevel <- data_data_0_split_0
I0122 21:16:09.059403 24972 net.cpp:380] NoLevel -> NoLevel
I0122 21:16:09.059403 24972 net.cpp:122] Setting up NoLevel
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.059403 24972 net.cpp:137] Memory required for data: 1604
I0122 21:16:09.059403 24972 layer_factory.hpp:77] Creating layer Level0Only
I0122 21:16:09.059403 24972 net.cpp:84] Creating Layer Level0Only
I0122 21:16:09.059403 24972 net.cpp:406] Level0Only <- data_data_0_split_1
I0122 21:16:09.059403 24972 net.cpp:380] Level0Only -> Level0Only
I0122 21:16:09.059403 24972 net.cpp:122] Setting up Level0Only
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.059403 24972 net.cpp:137] Memory required for data: 1608
I0122 .21:16:09.059403 24972 layer_factory.hpp:77] Creating layer Level>=0
I0122 21:16:09.059403 24972 net.cpp:84] Creating Layer Level>=0
I0122 21:16:09.059403 24972 net.cpp:406] Level>=0 <- data_data_0_split_2
I0122 21:16:09.059403 24972 net.cpp:380] Level>=0 -> Level>=0
I0122 21:16:09.059403 24972 net.cpp:122] Setting up Level>=0
I0122 21:16:09.059403 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.059403 24972 net.cpp:137] Memory required for data: 1612
I0122 21:16:09.059403 24972 net.cpp:200] Level>=0 does not need backward computation.
I0122 21:16:09.059403 24972 net.cpp:200] Level0Only does not need backward computation.
I0122 21:16:09.059403 24972 net.cpp:200] NoLevel does not need backward computation.
I0122 21:16:09.059403 24972 net.cpp:200] data_data_0_split does not need backward computation.
I0122 21:16:09.059403 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.059403 24972 net.cpp:242] This network produces output Level0Only
I0122 21:16:09.059403 24972 net.cpp:242] This network produces output Level>=0
I0122 21:16:09.060402 24972 net.cpp:242] This network produces output NoLevel
I0122 21:16:09.060402 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.061404 24972 net.cpp:314] The NetState level (1) is above the max_level (0) specified by a rule in layer Level0Only
I0122 21:16:09.061404 24972 net.cpp:51] Initializing net from parameters:
state {
phase: TEST
level: 1
}
layer {
name: "data"
type: "DummyData"
top: "data"
dummy_data_param {
shape {
dim: 1
dim: 1
dim: 10
dim: 10
}
}
}
layer {
name: "NoLevel"
type: "InnerProduct"
bottom: "data"
top: "NoLevel"
inner_product_param {
num_output: 1
}
}
layer {
name: "Level1Only"
type: "InnerProduct"
bottom: "data"
top: "Level1Only"
include {
min_level: 1
max_level: 1
}
inner_product_param {
num_output: 1
}
}
layer {
name: "Level>=0"
type: "InnerProduct"
bottom: "data"
top: "Level>=0"
include {
min_level: 0
}
inner_product_param {
num_output: 1
}
}
layer {
name: "Level>=1"
type: "InnerProduct"
bottom: "data"
top: "Level>=1"
include {
min_level: 1
}
inner_product_param {
num_output: 1
}
}
I0122 21:16:09.061404 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.061404 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.061404 24972 net.cpp:380] data -> data
I0122 21:16:09.061404 24972 net.cpp:122] Setting up data
I0122 21:16:09.061404 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.061404 24972 net.cpp:137] Memory required for data: 400
I0122 21:16:09.061404 24972 layer_factory.hpp:77] Creating layer data_data_0_split
I0122 21:16:09.061404 24972 net.cpp:84] Creating Layer data_data_0_split
I0122 21:16:09.061404 24972 net.cpp:406] data_data_0_split <- data
I0122 21:16:09.061404 24972 net.cpp:380] data_data_0_split -> data_data_0_split_0
I0122 21:16:09.061404 24972 net.cpp:380] data_data_0_split -> data_data_0_split_1
I0122 21:16:09.061404 24972 net.cpp:380] data_data_0_split -> data_data_0_split_2
I0122 21:16:09.061404 24972 net.cpp:380] data_data_0_split -> data_data_0_split_3
I0122 21:16:09.061404 24972 net.cpp:122] Setting up data_data_0_split
I0122 21:16:09.061404 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.061404 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.061404 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.061404 24972 net.cpp:129] Top shape: 1 1 10 10 (100)
I0122 21:16:09.061404 24972 net.cpp:137] Memory required for data: 2000
I0122 21:16:09.061404 24972 layer_factory.hpp:77] Creating layer NoLevel
I0122 21:16:09.062405 24972 net.cpp:84] Creating Layer NoLevel
I0122 21:16:09.062405 24972 net.cpp:406] NoLevel <- data_data_0_split_0
I0122 21:16:09.062405 24972 net.cpp:380] NoLevel -> NoLevel
I0122 21:16:09.062405 24972 net.cpp:122] Setting up NoLevel
I0122 21:16:09.062405 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.062405 24972 net.cpp:137] Memory required for data: 2004
I0122 21:16:09.062405 24972 layer_factor.y.hpp:77] Creating layer Level1Only
I0122 21:16:09.062405 24972 net.cpp:84] Creating Layer Level1Only
I0122 21:16:09.062405 24972 net.cpp:406] Level1Only <- data_data_0_split_1
I0122 21:16:09.062405 24972 net.cpp:380] Level1Only -> Level1Only
I0122 21:16:09.062405 24972 net.cpp:122] Setting up Level1Only
I0122 21:16:09.062405 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.062405 24972 net.cpp:137] Memory required for data: 2008
I0122 21:16:09.062405 24972 layer_factory.hpp:77] Creating layer Level>=0
I0122 21:16:09.062405 24972 net.cpp:84] Creating Layer Level>=0
I0122 21:16:09.062405 24972 net.cpp:406] Level>=0 <- data_data_0_split_2
I0122 21:16:09.062405 24972 net.cpp:380] Level>=0 -> Level>=0
I0122 21:16:09.062405 24972 net.cpp:122] Setting up Level>=0
I0122 21:16:09.062405 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.062405 24972 net.cpp:137] Memory required for data: 2012
I0122 21:16:09.062405 24972 layer_factory.hpp:77] Creating layer Level>=1
I0122 21:16:09.062405 24972 net.cpp:84] Creating Layer Level>=1
I0122 21:16:09.062405 24972 net.cpp:406] Level>=1 <- data_data_0_split_3
I0122 21:16:09.062405 24972 net.cpp:380] Level>=1 -> Level>=1
I0122 21:16:09.062405 24972 net.cpp:122] Setting up Level>=1
I0122 21:16:09.062405 24972 net.cpp:129] Top shape: 1 1 (1)
I0122 21:16:09.062405 24972 net.cpp:137] Memory required for data: 2016
I0122 21:16:09.062405 24972 net.cpp:200] Level>=1 does not need backward computation.
I0122 21:16:09.062405 24972 net.cpp:200] Level>=0 does not need backward computation.
I0122 21:16:09.062405 24972 net.cpp:200] Level1Only does not need backward computation.
I0122 21:16:09.062405 24972 net.cpp:200] NoLevel does not need backward computation.
I0122 21:16:09.062405 24972 net.cpp:200] data_data_0_split does not need backward computation.
I0122 21:16:09.062405 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.062405 24972 net.cpp:242] This network produces output Level1Only
I0122 21:16:09.062405 24972 net.cpp:242] This network produces output Level>=0
I0122 21:16:09.062405 24972 net.cpp:242] This network produces output Level>=1
I0122 21:16:09.062405 24972 net.cpp:242] This network produces output NoLevel
I0122 21:16:09.062405 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.063402 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.063402 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.063402 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.063402 24972 net.cpp:380] data -> data
I0122 21:16:09.063402 24972 net.cpp:380] data -> label
I0122 21:16:09.063402 24972 net.cpp:122] Setting up data
I0122 21:16:09.063402 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.063402 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.063402 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.063402 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.063402 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.063402 24972 ne.t.cpp:406] conv <- data
I0122 21:16:09.064405 24972 net.cpp:380] conv -> conv
I0122 21:16:09.064405 24972 common.cpp:36] System entropy source not available, using fallback algorithm to generate seed instead.
I0122 21:16:09.064405 24972 net.cpp:122] Setting up conv
I0122 21:16:09.064405 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.064405 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.064405 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.064405 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.064405 24972 net.cpp:406] ip <- conv
I0122 21:16:09.064405 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.064405 24972 net.cpp:122] Setting up ip
I0122 21:16:09.064405 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.064405 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.064405 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.064405 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.064405 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.064405 24972 net.cpp:406] loss <- label
I0122 21:16:09.064405 24972 net.cpp:380] loss -> loss
I0122 21:16:09.064405 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.064405 24972 net.cpp:122] Setting up loss
I0122 21:16:09.064405 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.064405 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.064405 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.064405 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.064405 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.064405 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.064405 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.064405 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.064405 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.067404 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.067404 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.067404 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.067404 24972 net.cpp:380] data -> data
I0122 21:16:09.067404 24972 net.cpp:380] data -> label
I0122 21:16:09.067404 24972 net.cpp:122] Setting up data
I0122 21:16:09.067404 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.067404 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.067404 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.067404 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.067404 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.067404 24972 net.cpp:406] conv <- data
I0122 21:16:09.067404 24972 net.cpp:380] conv -> conv
I0122 21:16:09.067404 24972 net.cpp:122] Setting up conv
I0122 21:16:09.067404 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.067404 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.067404 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.067404 24972 net.cpp:84] Cr.eating Layer ip
I0122 21:16:09.067404 24972 net.cpp:406] ip <- conv
I0122 21:16:09.067404 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.067404 24972 net.cpp:122] Setting up ip
I0122 21:16:09.067404 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.067404 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.067404 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.067404 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.067404 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.067404 24972 net.cpp:406] loss <- label
I0122 21:16:09.067404 24972 net.cpp:380] loss -> loss
I0122 21:16:09.067404 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.067404 24972 net.cpp:122] Setting up loss
I0122 21:16:09.067404 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.067404 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.067404 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.067404 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.067404 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.067404 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.067404 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.067404 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.067404 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.069402 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.069402 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.069402 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.069402 24972 net.cpp:380] data -> data
I0122 21:16:09.069402 24972 net.cpp:380] data -> label
I0122 21:16:09.069402 24972 net.cpp:122] Setting up data
I0122 21:16:09.069402 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.069402 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.069402 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.069402 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.069402 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.069402 24972 net.cpp:406] conv <- data
I0122 21:16:09.069402 24972 net.cpp:380] conv -> conv
I0122 21:16:09.069402 24972 net.cpp:122] Setting up conv
I0122 21:16:09.069402 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.069402 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.069402 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.069402 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.069402 24972 net.cpp:406] ip <- conv
I0122 21:16:09.069402 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.069402 24972 net.cpp:122] Setting up ip
I0122 21:16:09.069402 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.069402 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.069402 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.069402 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.069402 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.06.9402 24972 net.cpp:406] loss <- label
I0122 21:16:09.069402 24972 net.cpp:380] loss -> loss
I0122 21:16:09.069402 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.069402 24972 net.cpp:122] Setting up loss
I0122 21:16:09.069402 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.069402 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.069402 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.069402 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.069402 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.069402 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.069402 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.069402 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.069402 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.071403 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.071403 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.071403 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.071403 24972 net.cpp:380] data -> data
I0122 21:16:09.071403 24972 net.cpp:380] data -> label
I0122 21:16:09.071403 24972 net.cpp:122] Setting up data
I0122 21:16:09.071403 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.071403 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.071403 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.071403 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.071403 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.071403 24972 net.cpp:406] conv <- data
I0122 21:16:09.071403 24972 net.cpp:380] conv -> conv
I0122 21:16:09.071403 24972 net.cpp:122] Setting up conv
I0122 21:16:09.071403 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.071403 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.071403 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.071403 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.071403 24972 net.cpp:406] ip <- conv
I0122 21:16:09.071403 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.071403 24972 net.cpp:122] Setting up ip
I0122 21:16:09.071403 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.071403 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.071403 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.071403 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.071403 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.071403 24972 net.cpp:406] loss <- label
I0122 21:16:09.071403 24972 net.cpp:380] loss -> loss
I0122 21:16:09.071403 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.071403 24972 net.cpp:122] Setting up loss
I0122 21:16:09.071403 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.072402 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.072402 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.072402 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.072402 24972 net...cpp:198] ip needs backward computation.
I0122 21:16:09.072402 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.072402 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.072402 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.072402 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.074409 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.074409 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.074409 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.074409 24972 net.cpp:380] data -> data
I0122 21:16:09.074409 24972 net.cpp:380] data -> label
I0122 21:16:09.074409 24972 net.cpp:122] Setting up data
I0122 21:16:09.074409 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.074409 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.074409 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.074409 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.074409 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.074409 24972 net.cpp:406] conv <- data
I0122 21:16:09.074409 24972 net.cpp:380] conv -> conv
I0122 21:16:09.074409 24972 net.cpp:122] Setting up conv
I0122 21:16:09.074409 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.074409 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.074409 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.074409 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.074409 24972 net.cpp:406] ip <- conv
I0122 21:16:09.074409 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.074409 24972 net.cpp:122] Setting up ip
I0122 21:16:09.074409 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.074409 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.074409 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.074409 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.074409 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.074409 24972 net.cpp:406] loss <- label
I0122 21:16:09.074409 24972 net.cpp:380] loss -> loss
I0122 21:16:09.074409 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.074409 24972 net.cpp:122] Setting up loss
I0122 21:16:09.074409 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.074409 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.074409 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.074409 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.074409 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.074409 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.074409 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.074409 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.074409 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.075400 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
ty.pe: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.076402 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.076402 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.076402 24972 net.cpp:380] data -> data
I0122 21:16:09.076402 24972 net.cpp:380] data -> label
I0122 21:16:09.076402 24972 net.cpp:122] Setting up data
I0122 21:16:09.076402 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.076402 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.076402 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.076402 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.076402 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.076402 24972 net.cpp:406] conv <- data
I0122 21:16:09.076402 24972 net.cpp:380] conv -> conv
I0122 21:16:09.076402 24972 net.cpp:122] Setting up conv
I0122 21:16:09.076402 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.076402 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.076402 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.076402 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.076402 24972 net.cpp:406] ip <- conv
I0122 21:16:09.076402 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.076402 24972 net.cpp:122] Setting up ip
I0122 21:16:09.076402 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.076402 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.076402 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.076402 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.076402 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.076402 24972 net.cpp:406] loss <- label
I0122 21:16:09.076402 24972 net.cpp:380] loss -> loss
I0122 21:16:09.076402 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.076402 24972 net.cpp:122] Setting up loss
I0122 21:16:09.076402 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.076402 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.076402 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.076402 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.076402 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.076402 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.076402 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.076402 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.076402 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.077399 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {.
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.077399 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.077399 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.077399 24972 net.cpp:380] data -> data
I0122 21:16:09.077399 24972 net.cpp:380] data -> label
I0122 21:16:09.078402 24972 net.cpp:122] Setting up data
I0122 21:16:09.078402 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.078402 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.078402 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.078402 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.078402 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.078402 24972 net.cpp:406] conv <- data
I0122 21:16:09.078402 24972 net.cpp:380] conv -> conv
I0122 21:16:09.078402 24972 net.cpp:122] Setting up conv
I0122 21:16:09.078402 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.078402 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.078402 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.078402 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.078402 24972 net.cpp:406] ip <- conv
I0122 21:16:09.078402 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.078402 24972 net.cpp:122] Setting up ip
I0122 21:16:09.078402 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.078402 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.078402 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.078402 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.078402 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.078402 24972 net.cpp:406] loss <- label
I0122 21:16:09.078402 24972 net.cpp:380] loss -> loss
I0122 21:16:09.078402 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.078402 24972 net.cpp:122] Setting up loss
I0122 21:16:09.078402 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.078402 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.078402 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.078402 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.078402 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.078402 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.078402 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.078402 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.078402 24972 net.cpp:255] Network initialization done.
I0122 21:16:09.079403 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.079403 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.080401 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.080401 24972 net.cpp:380] data -> data
I0122 21:16:09.080401 24972 net.cpp:380] data -> label
I0122 21:16:09.080401 24972 net.cpp:122] Setting up data
I0122 21:16:09.080401 24972 net.cpp:129] Top shape: 5 2 3 4 (120)
I0122 21:16:09.080401 24972 net.cpp:129] Top shape: 5 1 1 1 (5)
I0122 21:16:09.080401 24972 net.cpp:137] Memory required for data: 500
I0122 21:16:09.080401 24972 layer_factory.hpp:77] Creating layer conv
I0122 21:16:09.080401 24972 net.cpp:84] Creating Layer conv
I0122 21:16:09.080401 24972 net.cpp:406] conv <- data
I0122 21:16:09.080401 24972 net.cpp:380] conv -> conv
I0122 21:16:09.080401 24972 net.cpp:122] Setting up conv
I0122 21:16:09.080401 24972 net.cpp:129] Top shape: 5 11 8 9 (3960)
I0122 21:16:09.080401 24972 net.cpp:137] Memory required for data: 16340
I0122 21:16:09.080401 24972 layer_factory.hpp:77] Creating layer ip
I0122 21:16:09.080401 24972 net.cpp:84] Creating Layer ip
I0122 21:16:09.080401 24972 net.cpp:406] ip <- conv
I0122 21:16:09.080401 24972 net.cpp:380] ip -> ip_blob
I0122 21:16:09.080401 24972 net.cpp:122] Setting up ip
I0122 21:16:09.080401 24972 net.cpp:129] Top shape: 5 13 (65)
I0122 21:16:09.080401 24972 net.cpp:137] Memory required for data: 16600
I0122 21:16:09.080401 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.080401 24972 net.cpp:84] Creating Layer loss
I0122 21:16:09.080401 24972 net.cpp:406] loss <- ip_blob
I0122 21:16:09.080401 24972 net.cpp:406] loss <- label
I0122 21:16:09.080401 24972 net.cpp:380] loss -> loss
I0122 21:16:09.080401 24972 layer_factory.hpp:77] Creating layer loss
I0122 21:16:09.080401 24972 net.cpp:122] Setting up loss
I0122 21:16:09.080401 24972 net.cpp:129] Top shape: (1)
I0122 21:16:09.080401 24972 net.cpp:132] with loss weight 1
I0122 21:16:09.080401 24972 net.cpp:137] Memory required for data: 16604
I0122 21:16:09.080401 24972 net.cpp:198] loss needs backward computation.
I0122 21:16:09.080401 24972 net.cpp:198] ip needs backward computation.
I0122 21:16:09.080401 24972 net.cpp:198] conv needs backward computation.
I0122 21:16:09.080401 24972 net.cpp:200] data does not need backward computation.
I0122 21:16:09.080401 24972 net.cpp:242] This network produces output loss
I0122 21:16:09.080401 24972 net.cpp:255] Network initialization done.
W0122 21:16:09.081403 24972 _caffe.cpp:141] DEPRECATION WARNING - deprecated use of Python interface
W0122 21:16:09.081403 24972 _caffe.cpp:142] Use this instead (with the named "weights" parameter):
W0122 21:16:09.081403 24972 _caffe.cpp:144] Net('C:\Users\vlj\AppData\Local\Temp\tmpnym432ck', 0, weights='C:\Users\vlj\AppData\Local\Temp\tmp93bss3xr')
I0122 21:16:09.082403 24972 net.cpp:51] Initializing net from parameters:
name: "testnet"
force_backward: true
state {
phase: TRAIN
level: 0
}
layer {
name: "data"
type: "DummyData"
top: "data"
top: "label"
dummy_data_param {
data_filler {
type: "gaussian"
std: 1
}
data_filler {
type: "constant"
}
num: 5
num: 5
channels: 2
channels: 1
height: 3
height: 1
width: 4
width: 1
}
}
layer {
name: "conv"
type: "Convolution"
bottom: "data"
top: "conv"
param {
decay_mult: 1
}
param {
decay_mult: 0
}
convolution_param {
num_output: 11
pad: 3
kernel_size: 2
weight_filler {
type: "gaussian"
std: 1
}
bias_filler {
type: "constant"
value: 2
}
}
}
layer {
name: "ip"
type: "InnerProduct"
bottom: "conv"
top: "ip_blob"
inner_product_param {
num_output: 13
weight_filler {
type: "gaussian"
std: 2.5
}
bias_filler {
type: "constant"
value: -3
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "ip_blob"
bottom: "label"
top: "loss"
}
I0122 21:16:09.082403 24972 layer_factory.hpp:77] Creating layer data
I0122 21:16:09.082403 24972 net.cpp:84] Creating Layer data
I0122 21:16:09.082403 24972 net.cpp:380] data -> data
I0122 21:16:09.082403 24972 n*** Check failure stack trace: ***