Question

我试图在我自己的数据上训练一个LeNet（37个由1024个类别组成的37个灰度图像）。

我创建了lmdb文件，并将输出图层的大小更改为1024.当我使用我的解算器文件运行caffe train时，程序在打印后卡住了

...
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "score"
  bottom: "label"
  top: "loss"
}
I0713 17:11:13.334890  9595 layer_factory.hpp:77] Creating layer data
I0713 17:11:13.334939  9595 net.cpp:91] Creating Layer data
I0713 17:11:13.334950  9595 net.cpp:399] data -> data
I0713 17:11:13.334961  9595 net.cpp:399] data -> label

可能是什么问题？
我是caffe的新人，任何帮助都会受到赞赏。

solver.prototxt

net: "lenet_auto_train.prototxt"
test_iter: 100
test_interval: 500
base_lr: 0.01
momentum: 0.9
weight_decay: 0.0005
lr_policy: "inv"
gamma: 0.0001
power: 0.75
display: 100
max_iter: 10000
snapshot: 5000
snapshot_prefix: "lenet"

lenet.prototxt

layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    scale: 0.00392156862745
  }
  data_param {
    source: "dir/dat/1024_37*37_gray_lmdb"
    batch_size: 64
    backend: LMDB
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 20
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  convolution_param {
    num_output: 50
    kernel_size: 5
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "pool2"
  top: "fc1"
  inner_product_param {
    num_output: 500
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "fc1"
  top: "fc1"
}
layer {
  name: "score"
  type: "InnerProduct"
  bottom: "fc1"
  top: "score"
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "score"
  bottom: "label"
  top: "loss"
}

Answer 1

在我的情况下，当相同的LMDB用于训练和测试时，就会发生这种情况。

Answer 2

似乎caffe试图读取lmdb然后遇到问题我的猜测是您的数据库名称"dir/dat/1024_37*37_gray_lmdb"导致了问题：文件名中包含"*"字符不是一个好习惯。
将数据库名称更改为"dir/dat/1024_37x37_gray_lmdb"，然后重试（不要忘记更改原型文本）

Answer 3

问题是，我将选项test_iter: 100和test_interval: 500放在求解器文件中，但我没有在网络文件中指定测试网络或测试数据层。

Caffe在打印数据后挂起 - ＆gt;标签

3 个答案: