Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- layer{
- name: "relu1"
- type: "ReLU"
- bottom: "pool1"
- top: "relu1"
- }
- I0319 09:41:09.484148 6909 solver.cpp:44] Initializing solver from parameters:
- test_iter: 10
- test_interval: 1000
- base_lr: 0.001
- display: 20
- max_iter: 800
- lr_policy: "step"
- gamma: 0.1
- momentum: 0.9
- weight_decay: 0.04
- stepsize: 200
- snapshot: 10000
- snapshot_prefix: "models/train"
- solver_mode: GPU
- net: "train_val.prototxt"
- I0319 09:41:09.484392 6909 solver.cpp:87] Creating training net from net file: train_val.prototxt
- I0319 09:41:09.485164 6909 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer feed2
- I0319 09:41:09.485183 6909 net.cpp:51] Initializing net from parameters:
- name: "CaffeNet"
- state {
- phase: TRAIN
- }
- layer {
- name: "feed"
- type: "HDF5Data"
- top: "data"
- top: "label"
- include {
- phase: TRAIN
- }
- hdf5_data_param {
- source: "train_h5_list.txt"
- batch_size: 50
- }
- }
- layer {
- name: "conv1"
- type: "Convolution"
- bottom: "data"
- top: "conv1"
- param {
- lr_mult: 1
- }
- param {
- lr_mult: 2
- }
- convolution_param {
- num_output: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- }
- bias_filler {
- type: "constant"
- }
- }
- }
- layer {
- name: "pool1"
- type: "Pooling"
- bottom: "conv1"
- top: "pool1"
- pooling_param {
- pool: MAX
- kernel_size: 2
- stride: 1
- }
- }
- layer {
- name: "relu1"
- type: "ReLU"
- bottom: "pool1"
- top: "relu1"
- }
- layer {
- name: "conv2"
- type: "Convolution"
- bottom: "relu1"
- top: "conv2"
- param {
- lr_mult: 1
- }
- param {
- lr_mult: 2
- }
- convolution_param {
- num_output: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- }
- bias_filler {
- type: "constant"
- }
- }
- }
- layer {
- name: "ip2"
- type: "InnerProduct"
- bottom: "conv2"
- top: "ip2"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- inner_product_param {
- num_output: 1
- weight_filler {
- type: "gaussian"
- std: 0.01
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "sig1"
- type: "Sigmoid"
- bottom: "ip2"
- top: "sig1"
- }
- layer {
- name: "loss"
- type: "EuclideanLoss"
- bottom: "sig1"
- bottom: "label"
- top: "loss"
- }
- I0319 09:41:09.485752 6909 layer_factory.hpp:77] Creating layer feed
- I0319 09:41:09.485780 6909 net.cpp:84] Creating Layer feed
- I0319 09:41:09.485792 6909 net.cpp:380] feed -> data
- I0319 09:41:09.485819 6909 net.cpp:380] feed -> label
- I0319 09:41:09.485836 6909 hdf5_data_layer.cpp:80] Loading list of HDF5 filenames from: train_h5_list.txt
- I0319 09:41:09.485860 6909 hdf5_data_layer.cpp:94] Number of HDF5 files: 1
- I0319 09:41:09.486469 6909 hdf5.cpp:32] Datatype class: H5T_FLOAT
- I0319 09:41:09.500986 6909 net.cpp:122] Setting up feed
- I0319 09:41:09.501011 6909 net.cpp:129] Top shape: 50 227 227 3 (7729350)
- I0319 09:41:09.501027 6909 net.cpp:129] Top shape: 50 1 (50)
- I0319 09:41:09.501039 6909 net.cpp:137] Memory required for data: 30917600
- I0319 09:41:09.501051 6909 layer_factory.hpp:77] Creating layer conv1
- I0319 09:41:09.501080 6909 net.cpp:84] Creating Layer conv1
- I0319 09:41:09.501087 6909 net.cpp:406] conv1 <- data
- I0319 09:41:09.501101 6909 net.cpp:380] conv1 -> conv1
- I0319 09:41:09.880740 6909 net.cpp:122] Setting up conv1
- I0319 09:41:09.880765 6909 net.cpp:129] Top shape: 50 1 225 1 (11250)
- I0319 09:41:09.880781 6909 net.cpp:137] Memory required for data: 30962600
- I0319 09:41:09.880808 6909 layer_factory.hpp:77] Creating layer pool1
- I0319 09:41:09.880836 6909 net.cpp:84] Creating Layer pool1
- I0319 09:41:09.880846 6909 net.cpp:406] pool1 <- conv1
- I0319 09:41:09.880861 6909 net.cpp:380] pool1 -> pool1
- I0319 09:41:09.880888 6909 net.cpp:122] Setting up pool1
- I0319 09:41:09.880899 6909 net.cpp:129] Top shape: 50 1 224 0 (0)
- I0319 09:41:09.880913 6909 net.cpp:137] Memory required for data: 30962600
- I0319 09:41:09.880921 6909 layer_factory.hpp:77] Creating layer relu1
- I0319 09:41:09.880934 6909 net.cpp:84] Creating Layer relu1
- I0319 09:41:09.880941 6909 net.cpp:406] relu1 <- pool1
- I0319 09:41:09.880952 6909 net.cpp:380] relu1 -> relu1
- F0319 09:41:09.881192 6909 cudnn.hpp:80] Check failed: status == CUDNN_STATUS_SUCCESS (3 vs. 0) CUDNN_STATUS_BAD_PARAM
Add Comment
Please, Sign In to add comment