зеркало из https://github.com/microsoft/caffe.git
58 строки
1.6 KiB
C++
58 строки
1.6 KiB
C++
// Copyright 2014 BVLC and contributors.
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//
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// This is a simple script that allows one to quickly test a network whose
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// structure is specified by text format protocol buffers, and whose parameter
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// are loaded from a pre-trained network.
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// Usage:
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// test_net net_proto pretrained_net_proto iterations [CPU/GPU]
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#include <cuda_runtime.h>
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#include <cstring>
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#include <cstdlib>
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#include <vector>
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#include "caffe/caffe.hpp"
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using namespace caffe; // NOLINT(build/namespaces)
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int main(int argc, char** argv) {
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if (argc < 4 || argc > 5) {
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LOG(ERROR) << "test_net net_proto pretrained_net_proto iterations "
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<< "[CPU/GPU]";
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return 1;
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}
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cudaSetDevice(0);
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Caffe::set_phase(Caffe::TEST);
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if (argc == 5 && strcmp(argv[4], "GPU") == 0) {
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LOG(ERROR) << "Using GPU";
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Caffe::set_mode(Caffe::GPU);
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} else {
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LOG(ERROR) << "Using CPU";
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Caffe::set_mode(Caffe::CPU);
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}
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Net<float> caffe_test_net(argv[1]);
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NetParameter trained_net_param;
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ReadProtoFromBinaryFile(argv[2], &trained_net_param);
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caffe_test_net.CopyTrainedLayersFrom(trained_net_param);
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int total_iter = atoi(argv[3]);
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LOG(ERROR) << "Running " << total_iter << "Iterations.";
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double test_accuracy = 0;
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vector<Blob<float>*> dummy_blob_input_vec;
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for (int i = 0; i < total_iter; ++i) {
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const vector<Blob<float>*>& result =
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caffe_test_net.Forward(dummy_blob_input_vec);
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test_accuracy += result[0]->cpu_data()[0];
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LOG(ERROR) << "Batch " << i << ", accuracy: " << result[0]->cpu_data()[0];
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}
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test_accuracy /= total_iter;
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LOG(ERROR) << "Test accuracy:" << test_accuracy;
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return 0;
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}
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