Neural network 使用'；caffe时间'；用于alexnet测试的基准测试

我是caffe的新手，目前我正在尝试与Alexnet一起使用它。当我说使用时，我的意思是我不想训练网络，因此，我得到了前面提到的Alexnet的

'.caffemodel'

现在，我想使用caffe的时间特性来查看在测试阶段执行每个层所需的时间（我正在做的是获取推理期间每个层的执行时间）

根据caffe的选择

usage: caffe <command> <args>

commands:
  train           train or finetune a model
  test            score a model
  ------------
  time            benchmark model execution time
  collect         collects layer data on specified device
  compare         collects layer data using inputs from other device

  Flags from tools/caffe.cpp:
      ---------------------
    -phase (Optional; network phase (TRAIN or TEST). Only used for 'time'.)
      type: string default: ""
    -sampling (Optional; Caffe test with sampling mode) type: bool
      default: false
     -------------------------

但当我这样做时，我会得到以下错误：

I0304 17:37:26.183619 29987 net.cpp:409] label_data_1_split does not need backward computation.
I0304 17:37:26.183625 29987 net.cpp:409] data does not need backward computation.
I0304 17:37:26.183629 29987 net.cpp:451] This network produces output accuracy
I0304 17:37:26.183635 29987 net.cpp:451] This network produces output loss
I0304 17:37:26.183647 29987 net.cpp:491] Network initialization done.
I0304 17:37:26.183732 29987 caffe.cpp:556] Performing Forward
I0304 17:37:26.287747 29987 caffe.cpp:561] Initial loss: 6.92452
I0304 17:37:26.287784 29987 caffe.cpp:563] Performing Backward
F0304 17:37:26.385227 29987 mkldnn_pooling_layer.cpp:464] Check failed: poolingBwd_pd 
*** Check failure stack trace: ***
    @     0x7fe03e3980cd  google::LogMessage::Fail()
    @     0x7fe03e399f33  google::LogMessage::SendToLog()
    @     0x7fe03e397c28  google::LogMessage::Flush()
    @     0x7fe03e39a999  google::LogMessageFatal::~LogMessageFatal()
    @     0x7fe03ead741c  caffe::MKLDNNPoolingLayer<>::InitPoolingBwd()
    @     0x7fe03eac4ec2  caffe::MKLDNNPoolingLayer<>::Backward_cpu()
    @     0x7fe03e8f9b19  caffe::Net<>::Backward()
    @     0x5622d81a2530  (unknown)
    @     0x5622d8199353  (unknown)
    @     0x7fe03ab09b97  __libc_start_main
    @     0x5622d8198e1a  (unknown)

I0304 17:37:26.183619 29987 net.cpp:409]标签数据分割不需要反向计算。
I0304 17:37:26.183625 29987 net.cpp:409]数据不需要反向计算。
I0304 17:37:26.183629 29987 net.cpp:451]此网络产生输出精度
I0304 17:37:26.183635 29987 net.cpp:451]此网络产生输出损耗
I0304 17:37:26.183647 29987 net.cpp:491]网络初始化已完成。
I0304 17:37:26.183732 29987 caffe.cpp:556]正在向前执行
I0304 17:37:26.287747 29987 caffe.cpp:561]初始损失：6.92452
I0304 17:37:26.287784 29987 caffe.cpp:563]正在向后执行
F0304 17:37:26.385227 29987 mkldnn_池_层。cpp:464]检查失败：pooligbwd_pd
***检查故障堆栈跟踪：***
@0x7fe03e3980cd谷歌：：日志消息：：失败（）
@0x7fe03e399f33 google:：LogMessage:：SendToLog（）
@0x7fe03e397c28 google:：LogMessage:：Flush（）
@0x7fe03e39a999谷歌：：LogMessageFatal:：~LogMessageFatal（）
@0x7fe03ead741c caffe:：MKLDNNPoolingLayer:：InitPoolingBwd（）
@0x7fe03eac4ec2 caffe:：mkldnnpoolglayer:：Backward_cpu（）
@0x7fe03e8f9b19 caffe:：Net:：Backward（）
@0x5622d81a2530（未知）
@0x5622d8199353（未知）
@0x7fe03ab09b97自由启动主
@0x5622d8198e1a（未知）

我猜我使用该命令的方式存在一些问题，为此我可能必须更改

.prototxt

文件

如果有人能为我指出正确的方向，告诉我如何在测试阶段获得Alexnet的基准数据，我将不胜感激

附言：如果你只是运行caffe时间而没有指定阶段，我无法发现会发生什么。它是否对测试和训练阶段进行基准测试

I0304 17:37:26.183619 29987 net.cpp:409] label_data_1_split does not need backward computation.
I0304 17:37:26.183625 29987 net.cpp:409] data does not need backward computation.
I0304 17:37:26.183629 29987 net.cpp:451] This network produces output accuracy
I0304 17:37:26.183635 29987 net.cpp:451] This network produces output loss
I0304 17:37:26.183647 29987 net.cpp:491] Network initialization done.
I0304 17:37:26.183732 29987 caffe.cpp:556] Performing Forward
I0304 17:37:26.287747 29987 caffe.cpp:561] Initial loss: 6.92452
I0304 17:37:26.287784 29987 caffe.cpp:563] Performing Backward
F0304 17:37:26.385227 29987 mkldnn_pooling_layer.cpp:464] Check failed: poolingBwd_pd 
*** Check failure stack trace: ***
    @     0x7fe03e3980cd  google::LogMessage::Fail()
    @     0x7fe03e399f33  google::LogMessage::SendToLog()
    @     0x7fe03e397c28  google::LogMessage::Flush()
    @     0x7fe03e39a999  google::LogMessageFatal::~LogMessageFatal()
    @     0x7fe03ead741c  caffe::MKLDNNPoolingLayer<>::InitPoolingBwd()
    @     0x7fe03eac4ec2  caffe::MKLDNNPoolingLayer<>::Backward_cpu()
    @     0x7fe03e8f9b19  caffe::Net<>::Backward()
    @     0x5622d81a2530  (unknown)
    @     0x5622d8199353  (unknown)
    @     0x7fe03ab09b97  __libc_start_main
    @     0x5622d8198e1a  (unknown)