diff options
Diffstat (limited to 'tests/validation/CL')
| -rw-r--r-- | tests/validation/CL/GEMMMatrixMultiplyNative.cpp | 218 | ||||
| -rw-r--r-- | tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp | 270 |
2 files changed, 488 insertions, 0 deletions
diff --git a/tests/validation/CL/GEMMMatrixMultiplyNative.cpp b/tests/validation/CL/GEMMMatrixMultiplyNative.cpp index dc5fbc36ba..e3f151a2ca 100644 --- a/tests/validation/CL/GEMMMatrixMultiplyNative.cpp +++ b/tests/validation/CL/GEMMMatrixMultiplyNative.cpp @@ -53,6 +53,11 @@ using CLGEMMMatrixMultiplyNative = CLSynthetizeOperator<ClGemmMatrixMultiplyNati template <typename T> using CLGEMMMatrixMultiplyNativeFixture = GEMMMatrixMultiplyNativeValidationFixture<CLTensor, CLAccessor, T, CLGEMMMatrixMultiplyNative>; +// Fixture for CLGEMMMatrixMultiplyNative with post ops +template <typename T> +using CLGEMMMatrixMultiplyNativeWithPostOpsFixture = + GEMMMatrixMultiplyNativeWithPostOpsValidationFixture<CLTensor, CLAccessor, T, CLGEMMMatrixMultiplyNative>; + // Fixture for CLGEMMMatrixMultiplyNative3D template <typename T> using CLGEMMMatrixMultiplyNative3DFixture = GEMMMatrixMultiplyNative3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMMatrixMultiplyNative>; @@ -141,6 +146,80 @@ const auto boundary_handling_cases = combine(combine(combine(combine(combine(com broadcast_bias_values), framework::dataset::make("Activation", ActivationLayerInfo())); +/** Post Ops */ +using PostOpArgBroadcast = CLGEMMMatrixMultiplyNativeWithPostOpsFixture<float>::PostOpArgBroadcast; +experimental::PostOpList<PostOpArgBroadcast> post_ops_1() +{ + experimental::PostOpList<PostOpArgBroadcast> post_ops{}; + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F}); + post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( + std::make_tuple(true, true, false), // If broadcast in dims 0, 1 and 2 + 0, + ConvertPolicy::SATURATE); + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); + return post_ops; +} +experimental::PostOpList<PostOpArgBroadcast> post_ops_2() +{ + experimental::PostOpList<PostOpArgBroadcast> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( + std::make_tuple(false, true, true), // If broadcast in dims 0, 1 and 2 + 1, + ConvertPolicy::SATURATE); + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); + return post_ops; +} +experimental::PostOpList<PostOpArgBroadcast> post_ops_3() +{ + experimental::PostOpList<PostOpArgBroadcast> post_ops{}; + // post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); + post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( + std::make_tuple(false, false, false), // If broadcast in dims 0, 1 and 2 + 1, + ConvertPolicy::SATURATE); + return post_ops; +} + +/** Different Post Op Lists */ +const auto post_op_lists = framework::dataset::make("post_op_lists", { + post_ops_1(), + post_ops_2(), + post_ops_3(), +} ); + +bool is_post_op_list_valid(unsigned int m, unsigned int n, unsigned int k, unsigned int batch, DataType data_type, const experimental::PostOpList<ITensorInfo*>& post_ops) +{ + const auto lhs_info = GEMMLHSMatrixInfo(4,4,1,false,true); + const auto rhs_info = GEMMRHSMatrixInfo(4,4,1,true,true,false); + + // Create TensorInfo for post op arguments + TensorInfo input0_info(TensorShape(k, m, batch), 1, data_type); + TensorInfo input1_info(TensorShape(n, k, batch), 1, data_type); + TensorInfo input2_info(TensorShape(n), 1, data_type); + TensorInfo output_info(TensorShape(n, m, batch), 1, data_type); + + GEMMKernelInfo gemm_info(m, n, k, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, + false /**< reinterpret the input as 3D */, + true /**< Flag used to broadcast the bias addition */, + false /**< wider accumm */, + false /**< has pad y */, + ActivationLayerInfo::ActivationFunction::IDENTITY, + 1 /**< Multiplication factor for the width of the 1xW transposed block */, + 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, + lhs_info, + rhs_info, + 0 /**< Offset to be added to each element of the matrix A */, + 0 /**< Offset to be added to each element of the matrix B */, + post_ops); + return bool(ClGemmMatrixMultiplyNativeKernel::validate(&input0_info.clone()->set_is_resizable(true), + &input1_info.clone()->set_is_resizable(true), + &input2_info.clone()->set_is_resizable(true), + &output_info.clone()->set_is_resizable(true),1.f,1.f, + lhs_info, + rhs_info, + gemm_info)); +} + /** Configuration test */ void validate_configuration(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, bool broadcast_bias, DataType data_type, const ActivationLayerInfo &act_info) { @@ -191,6 +270,119 @@ void validate_configuration(unsigned int m_value, unsigned int n_value, unsigned TEST_SUITE(CL) TEST_SUITE(GEMMMatrixMultiplyNative) +TEST_SUITE(ValidateFusedPostOpsConfigs) +TEST_SUITE(Invalid) +TEST_CASE(UnsupportedPostOpSequence, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 17; + const unsigned int n = 1; + const unsigned int k = 13; + const unsigned int batch = 2; + TensorShape post_op_arg0_shape(n, m, batch); + TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); + auto post_op_arg1_info = post_op_arg_info.clone(); + + // Unsupported sequence of post ops + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( + &post_op_arg_info, + 1, + ConvertPolicy::SATURATE); + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( + post_op_arg1_info.get(), + 0, + ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); +} +TEST_CASE(OutputWidened, framework::DatasetMode::ALL) +{ + // Invalid broadcast: post op tensors "widen" the output tensor + const auto data_type = DataType::F32; + const unsigned int m = 1; + const unsigned int n = 18; + const unsigned int k = 13; + const unsigned int batch = 2; + TensorShape post_op_arg_shape(n, m + 1, batch); // output's Y dimension (m) is "widened", which is not allowed + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInXDimOnly, framework::DatasetMode::ALL) +{ + // Invalid broadcast: post op tensors broadcast in the first dimension (X) only + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(1, m, batch); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); +} +TEST_SUITE_END() // Invalid +TEST_SUITE(Valid) +TEST_CASE(EmptyPostOpList, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + experimental::PostOpList<ITensorInfo*> post_ops{}; + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInYDimOnly, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(n, 1, batch); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInBothXandYDims, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(1, 1, batch); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInAllDims, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(1, 1, 1); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_SUITE_END() // Valid +TEST_SUITE_END() // ValidateFusedPostOps TEST_SUITE(Float) TEST_SUITE(FP32) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine( @@ -323,6 +515,32 @@ FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyNative3DFixture<float>, f // Validate output validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); } + +TEST_SUITE(FusedPostOps) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyNativeWithPostOpsFixture<float>, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + framework::dataset::make("M0", { 4 })), + n0_values_precommit), + k0_values_precommit), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("alpha", {1.0f} )), + framework::dataset::make("beta", {1.0f} )), + framework::dataset::make("broadcast_bias", { false, true } )), + framework::dataset::make("Activation", { ActivationLayerInfo() })), + post_op_lists) + ) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); +} + +TEST_SUITE_END() // FusedPostOps + TEST_SUITE_END() // FP32 TEST_SUITE_END() // Float TEST_SUITE_END() // GEMMMatrixMulipltyNative diff --git a/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp b/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp index 0f86a70e0f..9e1a185a10 100644 --- a/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp +++ b/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp @@ -26,6 +26,7 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "src/core/experimental/PostOp.h" #include "src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h" #include "src/gpu/cl/kernels/ClGemmReshapeRhsMatrixKernel.h" #include "tests/CL/CLAccessor.h" @@ -61,6 +62,11 @@ using CLGEMMMatrixMultiplyReshapedOnlyRHSFixture = GEMMMatrixMultiplyReshapedOnl template <typename T> using CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture = GEMMMatrixMultiplyReshapedOnlyRHS3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshapedOnlyRHS>; +// Fixture for CLGEMMMatrixMultiplyReshapedOnlyRHS with post ops +template <typename T> +using CLGEMMMatrixMultiplyReshapedOnlyRHSWithPostOpsFixture = + GEMMMatrixMultiplyReshapedOnlyRHSWithPostOpsValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshapedOnlyRHS>; + namespace { // *INDENT-OFF* @@ -157,6 +163,81 @@ const auto boundary_handling_cases = combine(combine(combine(combine(combine(com broadcast_bias_values), framework::dataset::make("Activation", ActivationLayerInfo())); +/** Post Ops */ +using PostOpArgBroadcast = CLGEMMMatrixMultiplyReshapedOnlyRHSWithPostOpsFixture<float>::PostOpArgBroadcast; +experimental::PostOpList<PostOpArgBroadcast> post_ops_1() +{ + experimental::PostOpList<PostOpArgBroadcast> post_ops{}; + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::LINEAR, 0.5F, 0.0F}); + post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( + std::make_tuple(true, true, false), // If broadcast in dims 0, 1 and 2 + 0, + ConvertPolicy::SATURATE); + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); + return post_ops; +} +experimental::PostOpList<PostOpArgBroadcast> post_ops_2() +{ + experimental::PostOpList<PostOpArgBroadcast> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( + std::make_tuple(false, true, true), // If broadcast in dims 0, 1 and 2 + 1, + ConvertPolicy::SATURATE); + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); + return post_ops; +} +experimental::PostOpList<PostOpArgBroadcast> post_ops_3() +{ + experimental::PostOpList<PostOpArgBroadcast> post_ops{}; + post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F}); + post_ops.push_back_op<experimental::PostOpEltwiseAdd<PostOpArgBroadcast>>( + std::make_tuple(false, false, true), // If broadcast in dims 0, 1 and 2 + 1, + ConvertPolicy::SATURATE); + return post_ops; +} + +/** Different Post Op Lists */ +const auto post_op_lists = framework::dataset::make("post_op_lists", { + post_ops_1(), + post_ops_2(), + post_ops_3(), + } ); + + bool is_post_op_list_valid(unsigned int m, unsigned int n, unsigned int k, unsigned int batch, DataType data_type, const experimental::PostOpList<ITensorInfo*>& post_ops) +{ + const auto lhs_info = GEMMLHSMatrixInfo(4,4,1,false,true); + const auto rhs_info = GEMMRHSMatrixInfo(4,4,1,true,true,false); + + // Create TensorInfo for post op arguments + TensorInfo input0_info(TensorShape(k, m, batch), 1, data_type); + TensorInfo input1_info(TensorShape(n, k, batch), 1, data_type); + TensorInfo input2_info(TensorShape(n), 1, data_type); + TensorInfo output_info(TensorShape(n, m, batch), 1, data_type); + + const TensorInfo reshaped_input1_info = input1_info.clone()->set_tensor_shape(misc::shape_calculator::compute_rhs_reshaped_shape(input1_info, rhs_info)); + + GEMMKernelInfo gemm_info(m, n, k, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */, + false /**< reinterpret the input as 3D */, + true /**< Flag used to broadcast the bias addition */, + false /**< wider accumm */, + false /**< has pad y */, + ActivationLayerInfo::ActivationFunction::IDENTITY, + 1 /**< Multiplication factor for the width of the 1xW transposed block */, + 1 /**< Multiplication factor for the height of the 4x4 interleaved block */, + lhs_info, + rhs_info, + 0 /**< Offset to be added to each element of the matrix A */, + 0 /**< Offset to be added to each element of the matrix B */, + post_ops); + return bool(ClGemmMatrixMultiplyReshapedOnlyRhsKernel::validate(&input0_info.clone()->set_is_resizable(true), + &reshaped_input1_info.clone()->set_is_resizable(true), + &input2_info.clone()->set_is_resizable(true), + &output_info.clone()->set_is_resizable(true),1.f,1.f, + lhs_info, + rhs_info, + gemm_info)); +} /** Configuration test */ bool validate_configuration(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, @@ -211,6 +292,7 @@ bool validate_configuration(unsigned int m_value, unsigned int n_value, unsigned CLGEMMMatrixMultiplyReshapedOnlyRHS gemm; return bool(gemm.validate(&lhs, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info)); } + } // namespace TEST_SUITE(CL) @@ -262,6 +344,119 @@ b_value, m0_value, n0_value, k0_value, broadcast_bias, input_as_3d, depth_output ARM_COMPUTE_EXPECT(status == expected_value, framework::LogLevel::ERRORS); } +TEST_SUITE(ValidateFusedPostOpsConfigs) +TEST_SUITE(Invalid) +TEST_CASE(UnsupportedPostOpSequence, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 17; + const unsigned int n = 1; + const unsigned int k = 13; + const unsigned int batch = 2; + TensorShape post_op_arg0_shape(n, m, batch); + TensorInfo post_op_arg_info(post_op_arg0_shape, 1, data_type); + auto post_op_arg1_info = post_op_arg_info.clone(); + + // Unsupported sequence of post ops + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( + &post_op_arg_info, + 1, + ConvertPolicy::SATURATE); + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( + post_op_arg1_info.get(), + 0, + ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); +} +TEST_CASE(OutputWidened, framework::DatasetMode::ALL) +{ + // Invalid broadcast: post op tensors "widen" the output tensor + const auto data_type = DataType::F32; + const unsigned int m = 17; + const unsigned int n = 1; + const unsigned int k = 1; + const unsigned int batch = 1; + TensorShape post_op_arg_shape(n, m, batch + 4); // output's batch dimension is "widened", which is not allowed + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInXDimOnly, framework::DatasetMode::ALL) +{ + // Invalid broadcast: post op tensors broadcast in the first dimension (X) only + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(1, m, batch); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == false, framework::LogLevel::ERRORS); +} +TEST_SUITE_END() // Invalid +TEST_SUITE(Valid) +TEST_CASE(EmptyPostOpList, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + experimental::PostOpList<ITensorInfo*> post_ops{}; + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInYDimOnly, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(n, 1, batch); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInBothXandYDims, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(1, 1, batch); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_CASE(BroadcastInAllDims, framework::DatasetMode::ALL) +{ + const auto data_type = DataType::F32; + const unsigned int m = 22; + const unsigned int n = 16; + const unsigned int k = 15; + const unsigned int batch = 3; + TensorShape post_op_arg_shape(1, 1, 1); + TensorInfo post_op_arg_info(post_op_arg_shape, 1, data_type); + experimental::PostOpList<ITensorInfo*> post_ops{}; + post_ops.push_back_op<experimental::PostOpEltwiseAdd<ITensorInfo*>>( &post_op_arg_info, 0, ConvertPolicy::SATURATE); + + ARM_COMPUTE_EXPECT(is_post_op_list_valid(m, n, k, batch, data_type, post_ops) == true, framework::LogLevel::ERRORS); +} +TEST_SUITE_END() // Valid +TEST_SUITE_END() // ValidateFusedPostOps TEST_SUITE(Float) TEST_SUITE(FP32) @@ -462,6 +657,44 @@ FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixtur framework::ARM_COMPUTE_PRINT_INFO(); } } + +TEST_SUITE(FusedPostOps) + +FIXTURE_DATA_TEST_CASE(RunPrecommit, CLGEMMMatrixMultiplyReshapedOnlyRHSWithPostOpsFixture<float>, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + framework::dataset::make("H0", {1})), + framework::dataset::make("interleave_rhs", { true })), + t_values_rhs), + framework::dataset::make("export_to_cl_image_rhs", false, true)), + framework::dataset::make("DataType", DataType::F32)), + a_values), + beta_values), + framework::dataset::make("broadcast_bias", { false } )), + act_values), + post_op_lists) + ) +{ + // Validate output only if the target platform supports the OpenCL cl_khr_image2d_from_buffer extension + if(validate_result) + { + validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); + } + else + { + ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); + framework::ARM_COMPUTE_PRINT_INFO(); + } +} + +TEST_SUITE_END() // FusedPostOps + TEST_SUITE_END() // FP32 TEST_SUITE(FP16) @@ -590,6 +823,43 @@ FIXTURE_DATA_TEST_CASE(RunNightly3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixtur framework::ARM_COMPUTE_PRINT_INFO(); } } +TEST_SUITE(FusedPostOps) + +FIXTURE_DATA_TEST_CASE(RunPrecommit, CLGEMMMatrixMultiplyReshapedOnlyRHSWithPostOpsFixture<half>, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + framework::dataset::make("H0", {1})), + framework::dataset::make("interleave_rhs", { true })), + t_values_rhs), + framework::dataset::make("export_to_cl_image_rhs", true)), + framework::dataset::make("DataType", DataType::F16)), + a_values), + beta_values), + framework::dataset::make("broadcast_bias", { false } )), + act_values), + post_op_lists) + ) +{ + // Validate output only if the target platform supports the OpenCL cl_khr_image2d_from_buffer extension + if(validate_result) + { + validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16); + } + else + { + ARM_COMPUTE_TEST_INFO("cl_khr_image2d_from_buffer not supported. TEST skipped"); + framework::ARM_COMPUTE_PRINT_INFO(); + } +} + +TEST_SUITE_END() // FusedPostOps + TEST_SUITE_END() // FP16 TEST_SUITE_END() // Float |