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Diffstat (limited to 'tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp')
| -rw-r--r-- | tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp | 89 |
1 files changed, 0 insertions, 89 deletions
diff --git a/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp b/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp index 0a0a1fc397..95979b3131 100644 --- a/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp +++ b/tests/validation/CL/GEMMMatrixMultiplyReshaped.cpp @@ -171,100 +171,11 @@ const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", { /** LHS transposed values */ const auto lhs_transpose_values = framework::dataset::make("lhs_transpose", { false, true } ); -/** Zero padding test */ -bool validate_zero_padding(unsigned int m_value, unsigned int n_value, unsigned int k_value, unsigned int b_value, - unsigned int m0_value, unsigned int n0_value, unsigned int k0_value, unsigned int h0_value, - bool i_value_rhs, bool t_value_rhs, bool export_to_cl_image, bool broadcast_bias, unsigned int depth_output_gemm3d, const ActivationLayerInfo &act_info, - DataType dt_input0, DataType dt_input1, DataType dt_input2, DataType dt_output, float alpha, float beta) -{ - const unsigned int M = m_value; - const unsigned int N = n_value; - const unsigned int K = k_value; - - GEMMLHSMatrixInfo lhs_info; - lhs_info.m0 = m0_value; - lhs_info.k0 = k0_value; - - GEMMRHSMatrixInfo rhs_info; - rhs_info.n0 = n0_value; - rhs_info.k0 = k0_value; - rhs_info.h0 = h0_value; - rhs_info.interleave = i_value_rhs; - rhs_info.transpose = t_value_rhs; - rhs_info.export_to_cl_image = export_to_cl_image; - - GEMMKernelInfo kernel_info; - kernel_info.m = M; - kernel_info.n = N; - kernel_info.k = K; - kernel_info.depth_output_gemm3d = depth_output_gemm3d; - kernel_info.reinterpret_input_as_3d = false; - kernel_info.broadcast_bias = broadcast_bias; - kernel_info.activation_info = act_info; - - const TensorShape lhs_shape(K, M, b_value); - const TensorShape rhs_shape(N, K, b_value); - const TensorShape lhs_shape_reshaped = compute_lhs_reshaped_shape(TensorInfo(lhs_shape, 1, dt_input0), - lhs_info); - const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, dt_input1), - rhs_info); - - const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape_reshaped, 1, dt_input0), - TensorInfo(rhs_shape_reshaped, 1, dt_input1), - kernel_info); - - const TensorShape bias_shape(N, - M, // Correct calculation should be: broadcast_bias? 1 : M, it's wrong here on purpose just for validation test - broadcast_bias? 1 : b_value); - - // Create tensors - CLTensor lhs_reshaped = create_tensor<CLTensor>(lhs_shape_reshaped, dt_input0); - CLTensor rhs_reshaped = create_tensor<CLTensor>(rhs_shape_reshaped, dt_input1); - CLTensor bias = create_tensor<CLTensor>(bias_shape, dt_input2); - CLTensor dst = create_tensor<CLTensor>(dst_shape, dt_output); - - ARM_COMPUTE_EXPECT(lhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Validate zero-padding - CLGEMMMatrixMultiplyReshaped gemm; - - gemm.configure(&lhs_reshaped, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info); - - // Padding can be added along rhs and bias's X/Y dimension - return dst.info()->padding().empty() && lhs_reshaped.info()->padding().empty(); -} } // namespace TEST_SUITE(CL) TEST_SUITE(GEMMMatrixMultiplyReshaped) -/** Validate zero padding tests - * - * A series of validation tests to check the zero padding requirement - * - * Checks performed in order: - * - No partial blocks in both x and y dimensions - * - Partial blocks in x dimension - * - Partial blocks in y dimension - * - Partial blocks in both x and y dimensions - * - Special case: partial_n0 == 9 (vstore1 should be invoked instead of vstore_partial_1) - */ -DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip(zip(zip( -framework::dataset::make("M", { 24, 64, 101, 1, 103 }), -framework::dataset::make("N", { 48, 29, 16, 121, 41 })), -framework::dataset::make("M0", { 4, 8, 4, 2, 4 })), -framework::dataset::make("N0", { 4, 4, 16, 2, 16 })), -m_value, n_value, m0_value, n0_value) -{ - constexpr DataType dt = DataType::F32; - - bool status = validate_zero_padding(m_value, n_value, 23, 1, m0_value, n0_value, 4, 1, false, false, false, 0, 0, ActivationLayerInfo(), dt, dt, dt, dt, 1.0f, 1.0f); - ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS); -} - // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( |