Caffe CNN切片层:第二层产生未知的底部斑点
我有2个切片层(见proto文件)。第一个看起来工作得很好,而第二个的底部给出了“未知的底部斑点错误”,如下所示:
事实上,我不确定错误是否与切片或展平有关!?
这是Proto文件:
layer {
name: "data"
type: "HDF5Data"
top: "data"
top: "label_b4_noise"
include {
phase: TEST
}
hdf5_data_param {
source: "data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s_val_list.txt"
batch_size: 25
shuffle: true
}
}
layer {
name: "data"
type: "HDF5Data"
top: "data"
top: "label_b4_noise"
include {
phase: TRAIN
}
hdf5_data_param {
source: "data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s_train_list.txt"
batch_size: 25
shuffle: true
}
}
layer {
name: "slic0"
type: "Slice"
bottom: "data"
top: "data1"
top: "data2"
slice_param {
axis: 1
slice_point: 1
}
}
layer {
name: "conv_u0d-score_New"
type: "Convolution"
bottom: "data1"
top: "conv_last"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1
pad: 0
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "flat"
type: "Flatten"
bottom: "conv_last"
top: "ampl"
}
layer {
name: "slic1"
type: "Slice"
bottom: "label_b4_noise"
top: "label_b4_noise1"
top: "label_b4_noise2"
slice_param {
axis: 1
slice_point: 1
}
}
layer {
name: "flatdata"
type: "Flatten"
bottom: "label_b4_noise1"
top: "flatdata"
}
layer {
name: "loss"
type: "EuclideanLoss"
bottom: "ampl"
bottom: "flatdata"
top: "loss"
softmax_param {engine: CAFFE}
}
GL ----------------------------------------------------------------
res/4removal_nAmp3nData2_2e5/unet_bs10/unet data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s .
res/4removal_nAmp3nData2_2e5/unet_bs10/unet data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s .
WARNING: Logging before InitGoogleLogging() is written to STDERR
I1018 11:40:22.930601 104201 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: res/4removal_nAmp3nData2_2e5/unet_bs10/unet_tmp/unet_deploy.txt
I1018 11:40:22.930654 104201 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W1018 11:40:22.930658 104201 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I1018 11:40:23.237383 104201 net.cpp:51] Initializing net from parameters:
name: "unet"
state {
phase: TEST
level: 0
}
layer {
name: "input"
type: "Input"
top: "data"
input_param {
shape {
dim: 1
dim: 2
dim: 1
dim: 2048
}
}
}
layer {
name: "slic0"
type: "Slice"
bottom: "data"
top: "data1"
top: "data2"
slice_param {
slice_point: 1
axis: 1
}
}
layer {
name: "conv_u0d-score_New"
type: "Convolution"
bottom: "data1"
top: "conv_last"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1
pad: 0
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "flat"
type: "Flatten"
bottom: "conv_last"
top: "ampl"
}
layer {
name: "flatdata"
type: "Flatten"
bottom: "label_b4_noise1"
top: "flatdata"
}
F1018 11:40:23.237546 104201 insert_splits.cpp:29] Unknown bottom blob 'label_b4_noise1' (layer 'flatdata', bottom index 0)
*** Check failure stack trace: ***
/pbs/home/n/nhatami/sps/spectro/trainAndTest_4removal: line 101: 104201 Aborted $pydir/dumpLayersSize.py ${tmp_root}_deploy.txt ${oroot}
/pbs/home/n/nhatami/sps/spectro/trainAndTest_4removal: line 101: 104201 Aborted $pydir/dumpLayersSize.py ${tmp_root}_deploy.txt ${oroot}
Thu Oct 18 11:40:23 CEST 2018
/usr/bin/time -v caffe -gpu 0 --log_dir=res/4removal_nAmp3nData2_2e5/unet_bs10/unet_tmp train -solver res/4removal_nAmp3nData2_2e5/unet_bs10/unet_tmp/unet_solver.txt
Thu Oct 18 11:41:26 CEST 2018
/pbs/home/n/nhatami/sps/spectro/trainAndTest_4removal: line 206: gnuplot: command not found
/pbs/home/n/nhatami/sps/spectro/trainAndTest_4removal: line 225: gnuplot: command not found
/usr/bin/time -v -o res/4removal_nAmp3nData2_2e5/unet_bs10/unet_time_test.txt python /pbs/home/n/nhatami/sps/spectro/python/test_4removal.py -eg hist -l label -mf=data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s_met.txt res/4removal_nAmp3nData2_2e5/unet_bs10/unet_deploy.txt res/4removal_nAmp3nData2_2e5/unet_bs10/unet.caffemodel data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s_test.h5 res/4removal_nAmp3nData2_2e5/unet_bs10/restest/unet_test
WARNING: Logging before InitGoogleLogging() is written to STDERR
W1018 11:41:42.595289 105177 _caffe.cpp:139] DEPRECATION WARNING - deprecated use of Python interface
W1018 11:41:42.595335 105177 _caffe.cpp:140] Use this instead (with the named "weights" parameter):
W1018 11:41:42.595338 105177 _caffe.cpp:142] Net('res/4removal_nAmp3nData2_2e5/unet_bs10/unet_deploy.txt', 1, weights='res/4removal_nAmp3nData2_2e5/unet_bs10/unet.caffemodel')
I1018 11:41:42.597472 105177 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: res/4removal_nAmp3nData2_2e5/unet_bs10/unet_deploy.txt
I1018 11:41:42.597497 105177 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W1018 11:41:42.597501 105177 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I1018 11:41:42.597535 105177 net.cpp:51] Initializing net from parameters:
name: "unet"
state {
phase: TEST
level: 0
}
layer {
name: "input"
type: "Input"
top: "data"
input_param {
shape {
dim: 1
dim: 2
dim: 1
dim: 2048
}
}
}
layer {
name: "slic0"
type: "Slice"
bottom: "data"
top: "data1"
top: "data2"
slice_param {
slice_point: 1
axis: 1
}
}
layer {
name: "conv_u0d-score_New"
type: "Convolution"
bottom: "data1"
top: "conv_last"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1
pad: 0
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "flat"
type: "Flatten"
bottom: "conv_last"
top: "ampl"
}
layer {
name: "flatdata"
type: "Flatten"
bottom: "label_b4_noise1"
top: "flatdata"
}
F1018 11:41:42.597617 105177 insert_splits.cpp:29] Unknown bottom blob 'label_b4_noise1' (layer 'flatdata', bottom index 0)
*** Check failure stack trace: ***
('res/4removal_nAmp3nData2_2e5/unet_bs10/unet_deploy.txt', 'res/4removal_nAmp3nData2_2e5/unet_bs10/unet.caffemodel', 'data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s_test.h5', 'data/4removal_nAmp3nData2_2e5/2048_2e5_0.01_s_met.txt')
以下是h5disp:
Dataset 'label_b4_noise'
Size: 2048x1x2x10000
MaxSize: 2048x1x2xInf
Datatype: H5T_IEEE_F32LE (single)
ChunkSize: 2048x1x2x100
Filters: none
FillValue: 0.000000
Dataset 'data'
Size: 2048x1x2x10000
MaxSize: 2048x1x2xInf
Datatype: H5T_IEEE_F32LE (single)
ChunkSize: 2048x1x2x100
Filters: none
FillValue: 0.000000
