Francesco Gatti
126 lines
6.6 KiB
C++
126 lines
6.6 KiB
C++
#include<iostream>
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#include "tkdnn.h"
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const char *input_bin = "../tests/yolo/layers/input.bin";
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const char *c0_bin = "../tests/yolo/layers/c0.bin";
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const char *c2_bin = "../tests/yolo/layers/c2.bin";
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const char *c4_bin = "../tests/yolo/layers/c4.bin";
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const char *c5_bin = "../tests/yolo/layers/c5.bin";
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const char *c6_bin = "../tests/yolo/layers/c6.bin";
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const char *c8_bin = "../tests/yolo/layers/c8.bin";
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const char *c9_bin = "../tests/yolo/layers/c9.bin";
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const char *c10_bin = "../tests/yolo/layers/c10.bin";
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const char *c12_bin = "../tests/yolo/layers/c12.bin";
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const char *c13_bin = "../tests/yolo/layers/c13.bin";
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const char *c14_bin = "../tests/yolo/layers/c14.bin";
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const char *c15_bin = "../tests/yolo/layers/c15.bin";
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const char *c16_bin = "../tests/yolo/layers/c16.bin";
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const char *c18_bin = "../tests/yolo/layers/c18.bin";
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const char *c19_bin = "../tests/yolo/layers/c19.bin";
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const char *c20_bin = "../tests/yolo/layers/c20.bin";
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const char *c21_bin = "../tests/yolo/layers/c21.bin";
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const char *c22_bin = "../tests/yolo/layers/c22.bin";
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const char *c23_bin = "../tests/yolo/layers/c23.bin";
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const char *c24_bin = "../tests/yolo/layers/c24.bin";
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const char *c26_bin = "../tests/yolo/layers/c26.bin";
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const char *c29_bin = "../tests/yolo/layers/c29.bin";
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const char *c30_bin = "../tests/yolo/layers/c30.bin";
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const char *output_bin = "../tests/yolo/layers/output.bin";
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int main() {
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// Network layout
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tkDNN::Network net;
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tkDNN::dataDim_t dim(1, 3, 608, 608, 1);
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tkDNN::Layer *l;
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l = new tkDNN::Conv2d (&net, dim, 32, 3, 3, 1, 1, 1, 1, c0_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Pooling (&net, l->output_dim, 2, 2, 2, 2, tkDNN::POOLING_MAX);
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l = new tkDNN::Conv2d (&net, l->output_dim, 64, 3, 3, 1, 1, 1, 1, c2_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Pooling (&net, l->output_dim, 2, 2, 2, 2, tkDNN::POOLING_MAX);
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l = new tkDNN::Conv2d (&net, l->output_dim, 128, 3, 3, 1, 1, 1, 1, c4_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 64, 1, 1, 1, 1, 0, 0, c5_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 128, 3, 3, 1, 1, 1, 1, c6_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Pooling (&net, l->output_dim, 2, 2, 2, 2, tkDNN::POOLING_MAX);
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l = new tkDNN::Conv2d (&net, l->output_dim, 256, 3, 3, 1, 1, 1, 1, c8_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 128, 1, 1, 1, 1, 0, 0, c9_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 256, 3, 3, 1, 1, 1, 1, c10_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Pooling (&net, l->output_dim, 2, 2, 2, 2, tkDNN::POOLING_MAX);
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l = new tkDNN::Conv2d (&net, l->output_dim, 512, 3, 3, 1, 1, 1, 1, c12_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 256, 1, 1, 1, 1, 0, 0, c13_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 512, 3, 3, 1, 1, 1, 1, c14_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 256, 1, 1, 1, 1, 0, 0, c15_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 512, 3, 3, 1, 1, 1, 1, c16_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY); //29
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l = new tkDNN::Pooling (&net, l->output_dim, 2, 2, 2, 2, tkDNN::POOLING_MAX);
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l = new tkDNN::Conv2d (&net, l->output_dim, 1024, 3, 3, 1, 1, 1, 1, c18_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 512, 1, 1, 1, 1, 0, 0, c19_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 1024, 3, 3, 1, 1, 1, 1, c20_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 512, 1, 1, 1, 1, 0, 0, c21_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 1024, 3, 3, 1, 1, 1, 1, c22_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 1024, 3, 3, 1, 1, 1, 1, c23_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 1024, 3, 3, 1, 1, 1, 1, c24_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY); //44
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int rlayers[1] = {29};
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l = new tkDNN::Route (&net, rlayers, 1);
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l = new tkDNN::Conv2d (&net, l->output_dim, 64, 1, 1, 1, 1, 0, 0, c26_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Reorg (&net, l->output_dim, 2); //48
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int rlayers2[2] = {48,44};
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l = new tkDNN::Route (&net, rlayers2, 2);
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l = new tkDNN::Conv2d (&net, l->output_dim, 1024, 3, 3, 1, 1, 1, 1, c29_bin, true);
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l = new tkDNN::Activation (&net, l->output_dim, tkDNN::ACTIVATION_LEAKY);
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l = new tkDNN::Conv2d (&net, l->output_dim, 425, 1, 1, 1, 1, 0, 0, c30_bin, false);
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l = new tkDNN::Region (&net, l->output_dim, 80, 4, 5, 0.6f);
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// Load input
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value_type *data;
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value_type *input_h;
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readBinaryFile(input_bin, dim.tot(), &input_h, &data);
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dim.print(); //print initial dimension
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TIMER_START
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// Inference
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data = net.infer(dim, data);
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TIMER_STOP
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dim.print();
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// Print real test
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std::cout<<"\n==== CHECK RESULT ====\n";
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value_type *out;
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value_type *out_h;
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readBinaryFile(output_bin, dim.tot(), &out_h, &out);
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int diff = checkResult(dim.tot(), data, out);
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printf("Output diffs: %d\n", diff);
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return 0;
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}
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