我想运行反卷积网络在我的数据上,但是它似乎是为另一个版本编写的caffe
。有谁知道如何改变batch_params
?
Deconvnet 中的那个
layers { bottom: 'conv1_1' top: 'conv1_1' name: 'bn1_1' type: BN
bn_param { scale_filler { type: 'constant' value: 1 }
shift_filler { type: 'constant' value: 0.001 }
bn_mode: INFERENCE } }
Caffe 提供的那个cifar10
例子:
layer {
name: "bn1"
type: "BatchNorm"
bottom: "pool1"
top: "bn1"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
include {
phase: TEST
}
}
一旦我想运行它,首先会显示以下错误:
I1029 13:46:47.156885 11601 solver.cpp:87] Creating training net from net file: train_val.prototxt
[libprotobuf ERROR google/protobuf/text_format.cc:299] Error parsing text-format caffe.NetParameter: 59:3: Unknown enumeration value of "BN" for field "type".
F1029 13:46:47.157971 11601 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param)
和改变之后BN
into BatchNorm
,它显示有关参数的新错误:
I1029 14:03:38.497725 12097 solver.cpp:87] Creating training net from net file: train_val.prototxt
[libprotobuf ERROR google/protobuf/text_format.cc:299] Error parsing text-format caffe.NetParameter: 59:3: Unknown enumeration value of "BatchNorm" for field "type".
F1029 14:03:38.503345 12097 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param)
有人尝试过训练 Deconvnet 吗?如果是的话,你能指导我吗?
谢谢
您能否告诉我这样的更改是否正确?
layer {
name: "bn1_1"
type: "BatchNorm"
bottom: "conv1_1"
top: "conv1_1"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
include {
phase: TEST
}
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "scale_conv1_1"
type: "Scale"
bottom: "conv1_1"
top: "conv1_1"
scale_param {
bias_term: true
bias_filler {
type: "constant"
value: 0.001
}
}
}
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