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-rw-r--r--ml/dlib/dlib/test/cublas.cpp198
1 files changed, 0 insertions, 198 deletions
diff --git a/ml/dlib/dlib/test/cublas.cpp b/ml/dlib/dlib/test/cublas.cpp
deleted file mode 100644
index 3f3cb09dc..000000000
--- a/ml/dlib/dlib/test/cublas.cpp
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@@ -1,198 +0,0 @@
-// Copyright (C) 2015 Davis E. King (davis@dlib.net)
-// License: Boost Software License See LICENSE.txt for the full license.
-
-
-#include <dlib/matrix.h>
-#include <sstream>
-#include <string>
-#include <cstdlib>
-#include <ctime>
-#include <vector>
-#include "../dnn/tensor_tools.h"
-
-#include "tester.h"
-
-// We only do these tests if CUDA is available to test in the first place.
-#ifdef DLIB_USE_CUDA
-
-namespace
-{
-
- using namespace test;
- using namespace dlib;
- using namespace std;
-
- logger dlog("test.cublas");
-
-
- void test_inv()
- {
- tt::tensor_rand rnd;
- dlib::tt::inv tinv;
- dlib::cuda::inv cinv;
- resizable_tensor minv1, minv2;
- for (int n = 1; n < 20; ++n)
- {
- print_spinner();
- resizable_tensor m(n,n);
- rnd.fill_uniform(m);
-
- tinv(m, minv1);
- cinv(m, minv2);
- matrix<float> mref = inv(mat(m));
- DLIB_TEST_MSG(mean(abs(mref-mat(minv1)))/mean(abs(mref)) < 1e-5, mean(abs(mref-mat(minv1)))/mean(abs(mref)) <<" n: " << n);
- DLIB_TEST_MSG(mean(abs(mref-mat(minv2)))/mean(abs(mref)) < 1e-5, mean(abs(mref-mat(minv2)))/mean(abs(mref)) <<" n: " << n);
- }
- }
-
-
- class cublas_tester : public tester
- {
- public:
- cublas_tester (
- ) :
- tester ("test_cublas",
- "Runs tests on the cuBLAS bindings.")
- {}
-
- void perform_test (
- )
- {
- test_inv();
- {
- resizable_tensor a(4,3), b(3,4), c(3,3);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+trans(mat(a))*trans(mat(b));
-
- a.async_copy_to_device(); b.async_copy_to_device(); c.async_copy_to_device();
- cuda::gemm(2, c, 1, a, true, b, true);
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(4,3), b(4,3), c(3,3);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+trans(mat(a))*mat(b);
-
- a.async_copy_to_device(); b.async_copy_to_device(); c.async_copy_to_device();
- cuda::gemm(2, c, 1, a, true, b, false);
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(3,4), b(3,4), c(3,3);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+mat(a)*trans(mat(b));
-
- a.async_copy_to_device(); b.async_copy_to_device(); c.async_copy_to_device();
- cuda::gemm(2, c, 1, a, false, b, true);
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(3,4), b(3,4), c(3,3);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = mat(c)+mat(a)*trans(mat(b));
-
- a.async_copy_to_device(); b.async_copy_to_device(); c.async_copy_to_device();
- cuda::gemm(1, c, 1, a, false, b, true);
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(3,4), b(4,3), c(3,3);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+mat(a)*mat(b);
-
- a.async_copy_to_device(); b.async_copy_to_device(); c.async_copy_to_device();
- cuda::gemm(2, c, 1, a, false, b, false);
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(3,4), b(4,3), c(3,3);
-
- c = std::numeric_limits<float>::infinity();
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
- a.async_copy_to_device(); b.async_copy_to_device(); c.async_copy_to_device();
-
- matrix<float> truth = mat(a)*mat(b);
-
- cuda::gemm(0, c, 1, a, false, b, false);
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(3,4), b(4,4), c(3,4);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+mat(a)*mat(b);
-
- cuda::gemm(2, c, 1, a, false, b, false);
- DLIB_TEST(get_rect(truth) == get_rect(mat(c)));
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(4,3), b(4,4), c(3,4);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+trans(mat(a))*mat(b);
-
- cuda::gemm(2, c, 1, a, true, b, false);
- DLIB_TEST(get_rect(truth) == get_rect(mat(c)));
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(4,3), b(4,5), c(3,5);
-
- c = 1;
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = 2*mat(c)+trans(mat(a))*mat(b);
-
- cuda::gemm(2, c, 1, a, true, b, false);
- DLIB_TEST(get_rect(truth) == get_rect(mat(c)));
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- {
- resizable_tensor a(4,3), b(4,5), c(3,5);
-
- c = std::numeric_limits<float>::infinity();
- a = matrix_cast<float>(gaussian_randm(a.num_samples(),a.size()/a.num_samples()));
- b = matrix_cast<float>(gaussian_randm(b.num_samples(),b.size()/b.num_samples()));
-
- matrix<float> truth = trans(mat(a))*mat(b);
-
- cuda::gemm(0, c, 1, a, true, b, false);
- DLIB_TEST(get_rect(truth) == get_rect(mat(c)));
- DLIB_TEST(max(abs(truth-mat(c))) < 1e-6);
- }
- }
- } a;
-
-}
-
-#endif // DLIB_USE_CUDA
-
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