1
我有一個HDF5類型的數據層。它包含火車和測試階段如期如何在同一個原型文件中生成數據層(HDF5)進行培訓和測試?
name: "LogisticRegressionNet"
layer {
name: "data"
type: "HDF5Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
hdf5_data_param {
source: "examples/hdf5_classification/data/train.txt"
batch_size: 10
}
}
layer {
name: "data"
type: "HDF5Data"
top: "data"
top: "label"
include {
phase: TEST
}
hdf5_data_param {
source: "examples/hdf5_classification/data/test.txt"
batch_size: 10
}
}
我想用python來生成它。這是我的代碼
import caffe
from caffe import layers as L # pseudo module using __getattr__ magic to generate protobuf messages
from caffe import params as P # pseudo module using __getattr__ magic to generate protobuf messages
n = caffe.NetSpec()
n.data, n.label = L.HDF5Data(batch_size=batch_size, source='examples/hdf5_classification/data/train.txt', ntop=2, include={'phase': caffe.TRAIN})
n.data, n.label = L.HDF5Data(batch_size=batch_size, source='examples/hdf5_classification/data/test.txt',ntop=2, include={'phase': caffe.TEST})
但是,我的輸出只是測試階段。我該如何解決它?謝謝
layer {
name: "data"
type: "HDF5Data"
top: "data"
top: "label"
include {
phase: TEST
}
hdf5_data_param {
source: "examples/hdf5_classification/data/test.txt"
batch_size: 2
}
}