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Diffstat (limited to 'tests/validation/reference/GEMM.cpp')
| -rw-r--r-- | tests/validation/reference/GEMM.cpp | 70 |
1 files changed, 0 insertions, 70 deletions
diff --git a/tests/validation/reference/GEMM.cpp b/tests/validation/reference/GEMM.cpp index 7378ada4ab..2feab89950 100644 --- a/tests/validation/reference/GEMM.cpp +++ b/tests/validation/reference/GEMM.cpp @@ -24,7 +24,6 @@ #include "GEMM.h" #include "arm_compute/core/Types.h" -#include "tests/validation/FixedPoint.h" namespace arm_compute { @@ -85,75 +84,6 @@ SimpleTensor<T> gemm(const SimpleTensor<T> &a, const SimpleTensor<T> &b, const S return dst; } -template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type> -SimpleTensor<T> gemm(const SimpleTensor<T> &a, const SimpleTensor<T> &b, const SimpleTensor<T> &c, float alpha, float beta) -{ - using namespace fixed_point_arithmetic; - - // Create reference - SimpleTensor<T> dst{ c.shape(), c.data_type(), 1 }; - - // Compute reference - using promoted_type = fixed_point_arithmetic::traits::promote_t<T>; - - const int M = dst.shape().y(); - const int N = dst.shape().x(); - const int K = a.shape().x(); - const int D = a.shape().z(); // Number of matrices in a batch - const int W = a.shape()[3]; // Number of batched-gemm (Winograd case) - - const int a_stride_z = K * M; - const int a_stride_w = K * M * D; - - const int b_stride_z = b.shape().num_dimensions() > 2 ? N * K : 0; // Do not slide the matrix B along the 3th dimension in case matrix B has less than 3 dimensions - const int b_stride_w = b.shape().num_dimensions() > 3 ? K * N * D : 0; // Do not slide the matrix B along the 4th dimension in case matrix B has less than 4 dimensions - - const int c_stride_z = N * M; - const int c_stride_w = N * M * D; - - const int fixed_point_position = a.fixed_point_position(); - const fixed_point<T> alpha_q(alpha, fixed_point_position); - const fixed_point<T> beta_q(beta, fixed_point_position); - - for(int w = 0; w < W; ++w) - { - for(int depth = 0; depth < D; ++depth) - { - const int base_addr_a = depth * a_stride_z + w * a_stride_w; - const int base_addr_b = depth * b_stride_z + w * b_stride_w; - const int base_addr_c = depth * c_stride_z + w * c_stride_w; - - for(int row = 0; row < M; ++row) - { - for(int col = 0; col < N; ++col) - { - fixed_point<promoted_type> acc_q(0, fixed_point_position); - - for(int k = 0; k < K; ++k) - { - const fixed_point<promoted_type> a0_q(a[base_addr_a + row * K + k], fixed_point_position, true); - const fixed_point<promoted_type> b0_q(b[base_addr_b + k * N + col], fixed_point_position, true); - - acc_q = acc_q + (a0_q * b0_q); - } - - // Finalize the result: alpha * A * B + beta * C - const fixed_point<T> c0_q(c[base_addr_c + col + row * N], fixed_point_position, true); - - fixed_point<T> res_q(acc_q); - res_q = alpha_q * res_q; - res_q = res_q + (beta_q * c0_q); - - // Store the result - dst[base_addr_c + col + row * N] = res_q.raw(); - } - } - } - } - - return dst; -} - template SimpleTensor<float> gemm(const SimpleTensor<float> &a, const SimpleTensor<float> &b, const SimpleTensor<float> &c, float alpha, float beta); template SimpleTensor<half> gemm(const SimpleTensor<half> &a, const SimpleTensor<half> &b, const SimpleTensor<half> &c, float alpha, float beta); } // namespace reference |