/*
 * Copyright (c) 2018-2021 Arm Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#include "arm_compute/core/KernelDescriptors.h"
#include "arm_compute/core/Types.h"
#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/ClGemmMatrixMultiplyReshapedKernel.h"
#include "src/gpu/cl/kernels/ClGemmReshapeLhsMatrixKernel.h"
#include "src/gpu/cl/kernels/ClGemmReshapeRhsMatrixKernel.h"
#include "tests/CL/CLAccessor.h"
#include "tests/CL/Helper.h"
#include "tests/PaddingCalculator.h"
#include "tests/datasets/ShapeDatasets.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "tests/validation/Validation.h"
#include "tests/validation/fixtures/GEMMFixture.h"

namespace arm_compute
{
namespace test
{
namespace validation
{
using namespace arm_compute::misc::shape_calculator;
using namespace arm_compute::opencl::kernels;

// Create function for ClGemmReshapeLhsMatrixKernel
using CLGEMMReshapeLHSMatrix = CLSynthetizeOperator<ClGemmReshapeLhsMatrixKernel>;

// Create function for ClGemmReshapeRhsMatrixKernel
using CLGEMMReshapeRHSMatrix = CLSynthetizeOperator<ClGemmReshapeRhsMatrixKernel>;

// Create function for ClGemmMatrixMultiplyReshapedKernel
using CLGEMMMatrixMultiplyReshaped = CLSynthetizeOperator<ClGemmMatrixMultiplyReshapedKernel>;

// Fixture for CLGEMMMatrixMultiplyReshaped
template <typename T>
using CLGEMMMatrixMultiplyReshapedFixture = GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;

// Fixture for CLGEMMMatrixMultiplyReshaped with post ops
template <typename T>
using CLGEMMMatrixMultiplyReshapedWithPostOpsFixture =
    GEMMMatrixMultiplyReshapedWithPostOpsValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;

// Fixture for CLGEMMMatrixMultiplyReshaped mixed precision
template <typename T>
using CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture =
    GEMMMatrixMultiplyReshapedValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;

// Fixture for CLGEMMMatrixMultiplyReshaped mixed precision with post ops
template <typename T>
using CLGEMMMatrixMultiplyReshapedMixedPrecisionWithPostOpsFixture =
    GEMMMatrixMultiplyReshapedWithPostOpsValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;

// Fixture for CLGEMMMatrixMultiplyReshaped3D
template <typename T>
using CLGEMMMatrixMultiplyReshaped3DFixture = GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped>;

// Fixture for CLGEMMMatrixMultiplyReshaped3D mixed precision
template <typename T>
using CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture =
    GEMMMatrixMultiplyReshaped3DValidationFixture<CLTensor, CLAccessor, T, CLGEMMReshapeLHSMatrix, CLGEMMReshapeRHSMatrix, CLGEMMMatrixMultiplyReshaped, true>;

namespace
{
// *INDENT-OFF*
// clang-format off
RelativeTolerance<float> rel_tolerance_f32(0.001f);
constexpr float          abs_tolerance_f32(0.0001f);

RelativeTolerance<float> rel_tolerance_f16_mixed_precision(0.001f);
constexpr float          abs_tolerance_f16_mixed_precision(0.01f);

RelativeTolerance<float> rel_tolerance_f16(0.001f);
constexpr float          abs_tolerance_f16(0.01f);

/** M values to test */
const auto m_values = framework::dataset::make("M", 17);

/** M_W values to test */
const auto m_w_values = framework::dataset::make("M_W", 5);

/** M_H values to test */
const auto m_h_values = framework::dataset::make("M_H", 7);

/** N values to test */
const auto n_values = framework::dataset::make("N", 21);

/** K values to test */
const auto k_values = framework::dataset::make("K", 13);

/** Batch size values to test */
const auto b_values = framework::dataset::make("batch_size", 2, 3);

/** Activation values to test */
const auto act_values = framework::dataset::make("Activation",
{
    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
});

/** Alpha values to test - Precommit */
const auto a_values_precommit = framework::dataset::make("alpha", {-0.75f} );

/** Beta values to test - Precommit */
const auto beta_values_precommit = framework::dataset::make("beta", {-0.35f} );

/** M0 values to test - Precommit */
const auto m0_values_precommit = framework::dataset::make("M0", { 4 });

/** N0 values to test - Precommit */
const auto n0_values_precommit = framework::dataset::make("N0", { 4 });

/** K0 values to test - Precommit */
const auto k0_values_precommit = framework::dataset::make("K0", { 4 });

/** V0 values to test - Precommit */
const auto v0_values_precommit = framework::dataset::make("V0", 1, 3);

/** H0 values to test - Precommit */
const auto h0_values_precommit = framework::dataset::make("H0", 1, 3);

/** Alpha values to test - Nightly */
const auto a_values_nightly = framework::dataset::make("alpha", {1.0f} );

/** Beta values to test - Nightly */
const auto beta_values_nightly = framework::dataset::make("beta", {1.0f} );

/** M0 values to test - Nightly */
const auto m0_values_nightly = framework::dataset::make("M0", { 8 });

/** N0 values to test - Nightly */
const auto n0_values_nightly = framework::dataset::make("N0", { 8 });

/** K0 values to test - Nightly */
const auto k0_values_nightly = framework::dataset::make("K0", { 4 });

/** N0 values to test with export to OpenCL image object - Nightly */
const auto n0_export_to_cl_image_values_nightly = framework::dataset::make("N0", { 4, 8, 16 });

/** K0 values to test with export to OpenCL image object - Nightly */
const auto k0_export_to_cl_image_values_nightly = framework::dataset::make("K0", { 4, 8, 16 });

/** V0 values to test - Nightly */
const auto v0_values_nightly = framework::dataset::make("V0", 1, 3);

/** H0 values to test - Nightly */
const auto h0_values_nightly = framework::dataset::make("H0", 1, 3);

/** Interleave values to test with LHS matrix */
const auto i_values_lhs = framework::dataset::make("interleave_lhs", { true, false });

/** Interleave values to test with RHS matrix */
const auto i_values_rhs = framework::dataset::make("interleave_rhs", { true, false });

/** Broadcast bias from vector to matrix */
const auto broadcast_bias_values = framework::dataset::make("broadcast_bias", { false, true } );

/** LHS transposed values */
const auto lhs_transpose_values = framework::dataset::make("lhs_transpose", { false, true } );

/** Post Ops */
using PostOpArgBroadcast =  CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<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;
}
// To test that the output of the main op is the first parameter in prelu post op
experimental::PostOpList<PostOpArgBroadcast> post_ops_4()
{
    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::PostOpEltwisePRelu<PostOpArgBroadcast>>(
        std::make_tuple(false, false, true),   // If true, broadcast in corresponding dim: 0, 1 or 2
        0,
        ConvertPolicy::SATURATE);
    post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
    return post_ops;
}
// To test that the output of the main op is the second parameter in prelu post op i.e. it is the alpha_param
experimental::PostOpList<PostOpArgBroadcast> post_ops_5()
{
    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::PostOpEltwisePRelu<PostOpArgBroadcast>>(
        std::make_tuple(false, false, false),   // If true, broadcast in corresponding dim: 0, 1 or 2
        1,
        ConvertPolicy::SATURATE);
    post_ops.push_back_op<experimental::PostOpAct<PostOpArgBroadcast>>(ActivationLayerInfo{ActivationLayerInfo::ActivationFunction::RELU, 2.1F, 1.3F});
    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(),
    post_ops_4(),
    post_ops_5()
 } );

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_input0_info = input0_info.clone()->set_tensor_shape(misc::shape_calculator::compute_lhs_reshaped_shape(input0_info, lhs_info));
    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(ClGemmMatrixMultiplyReshapedKernel::validate(&reshaped_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));
}

} // namespace

TEST_SUITE(CL)
TEST_SUITE(GEMMMatrixMultiplyReshaped)

// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
               framework::dataset::make("Input0Info", { TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32),      // OK
                                                        TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16),      // OK
                                                        TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8),  // Data type not supported
                                                        TensorInfo(TensorShape(10U, 5U, 2U), 1, DataType::F32),      // Incorrect dimension bias
                                                        TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F32),      // Mismatching shapes
                                                        TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16),      // OK, do not broadcast bias
                                                        TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16),      // OK, wider accummulation
                                                        TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::F16),      // OK, RHS 4,4,2

                                                      }),
               framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 5U, 2U), 1, DataType::QASYMM8),
                                                       TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 6U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(128U, 3U, 2U), 1, DataType::F16),

                      })),
               framework::dataset::make("Input2Info", { TensorInfo(TensorShape(21U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(21U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(21U), 1, DataType::QASYMM8),
                                                        TensorInfo(TensorShape(21U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(21U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(21U,17U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(21U,17U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),

                                                      })),
               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::QASYMM8),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(21U,17U,2U), 1, DataType::F16),

                           })),
               framework::dataset::make("LHSMInfo",{
                                                          GEMMLHSMatrixInfo(4,4,1,false,true),
                                                          GEMMLHSMatrixInfo(4,4,1,false,true),
                                                          GEMMLHSMatrixInfo(4,4,1,false,true),
                                                          GEMMLHSMatrixInfo(4,2,4,false,false),
                                                          GEMMLHSMatrixInfo(4,2,4,false,false),
                                                          GEMMLHSMatrixInfo(4,4,1,false,true),
                                                          GEMMLHSMatrixInfo(4,4,1,false,true),
                                                          GEMMLHSMatrixInfo(4,4,1,false,true),

                                })),
               framework::dataset::make("RHSMInfo",{
                                                          GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                          GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                          GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                          GEMMRHSMatrixInfo(2,2,1,true,false,false),
                                                          GEMMRHSMatrixInfo(2,2,1,true,false,false),
                                                          GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                          GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                          GEMMRHSMatrixInfo(4,4,2,true,false,false),


                           })),


               framework::dataset::make("GEMMInfo",{
                                                            GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
                                                                            21 /**<N Number of RHS columns*/,
                                                                            13 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                                     1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                     1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                                     GEMMLHSMatrixInfo(4,4,1,false,true),
                                                                     GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                                     0  /**< Offset to be added to each element of the matrix A */,
                                                                     0 /**< Offset to be added to each element of the matrix B */),

                                                            GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
                                                                            21 /**<N Number of RHS columns*/,
                                                                            13 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                                     1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                     1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                                     GEMMLHSMatrixInfo(4,4,1,false,true),
                                                                     GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                                     0  /**< Offset to be added to each element of the matrix A */,
                                                                     0 /**< Offset to be added to each element of the matrix B */),
                                                            GEMMKernelInfo(),
                                                            GEMMKernelInfo(),
                                                            GEMMKernelInfo(),

                                                            GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
                                                                            21 /**<N Number of RHS columns*/,
                                                                            13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
                                                                     false /**< reinterpret the input as 3D */,
                                                                     false  /**< Flag used to broadcast the bias addition */,
                                                                     false /**< wider accumm */,
                                                                     false /**< has pad y */,
                                                                   ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                     1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                     1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                                     GEMMLHSMatrixInfo(4,4,1,false,true),
                                                                     GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                                     0  /**< Offset to be added to each element of the matrix A */,
                                                                     0 /**< Offset to be added to each element of the matrix B */),


                                                            GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
                                                                            21 /**<N Number of RHS columns*/,
                                                                            13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
                                                                     false /**< reinterpret the input as 3D */,
                                                                     false  /**< Flag used to broadcast the bias addition */,
                                                                     true /**< wider accumm */,
                                                                     true /**< has pad y */,
                                                                   ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                     1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                     1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                                     GEMMLHSMatrixInfo(4,4,1,false,true),
                                                                     GEMMRHSMatrixInfo(4,4,1,true,true,false),
                                                                     0  /**< Offset to be added to each element of the matrix A */,
                                                                     0 /**< Offset to be added to each element of the matrix B */),

                                                            GEMMKernelInfo( 17 /**<M Number of LHS rows*/,
                                                                            21 /**<N Number of RHS columns*/,
                                                                            13 /**<K Number of LHS columns or RHS rows */, 0 /**< Depth of the output tensor in case is reinterpreted as 3D */,
                                                                     false /**< reinterpret the input as 3D */,
                                                                     false  /**< Flag used to broadcast the bias addition */,
                                                                     false /**< wider accumm */,
                                                                     false /**< has pad y */,
                                                                   ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
                                                                     1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                                     1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                                     GEMMLHSMatrixInfo(4,4,1,false,true),
                                                                     GEMMRHSMatrixInfo(4,4,2,true,false,false),
                                                                     0  /**< Offset to be added to each element of the matrix A */,
                                                                     0 /**< Offset to be added to each element of the matrix B */),
                                                    })),
               framework::dataset::make("Expected", { true, true, false, false, false, true, true,true})),
                    input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
{
    ARM_COMPUTE_EXPECT(bool(ClGemmMatrixMultiplyReshapedKernel::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)) == expected, 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 = 13;
    const unsigned int batch = 2;
    TensorShape post_op_arg_shape(n + 4, m, batch); // output's X dimension (n) 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)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
                combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}

FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::DISABLED,
                combine(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_nightly),
                                                                   n0_values_nightly),
                                                                   k0_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}

FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_precommit),
                                                                   n0_values_precommit),
                                                                   k0_values_precommit),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}

FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::DISABLED,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_nightly),
                                                                   n0_values_nightly),
                                                                   k0_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}
TEST_SUITE(FusedPostOps)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>, framework::DatasetMode::ALL,
                combine(combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   framework::dataset::make("interleave_lhs", { false })),
                                                                   framework::dataset::make("interleave_rhs", { false })),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   framework::dataset::make("broadcast_bias", { true } )),
                                                                   lhs_transpose_values),
                                                                   act_values),
                                                                   post_op_lists)
                                                                   )
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
}

TEST_SUITE_END() //  FusedPostOps

TEST_SUITE(ExportToCLImage)
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
               framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),  // OK or incorrect if cl_khr_image2d_from_buffer not supported
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),  // OK or incorrect if cl_khr_image2d_from_buffer not supported
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),  // OK or incorrect if cl_khr_image2d_from_buffer not supported
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),  // Incorrect k0
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),  // Incorrect n0

                                                      }),
               framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F32),

                      })),
               framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F32),

                                                      })),
               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F32),

                           })),
               framework::dataset::make("LHSMInfo",{
                                                          GEMMLHSMatrixInfo(4, 4, 1, false, true),
                                                          GEMMLHSMatrixInfo(4, 8, 1, false, true),
                                                          GEMMLHSMatrixInfo(4, 4, 1, false, true),
                                                          GEMMLHSMatrixInfo(4, 2, 1, false, false),
                                                          GEMMLHSMatrixInfo(4, 4, 1, false, false),

                                })),
               framework::dataset::make("RHSMInfo",{
                                                          GEMMRHSMatrixInfo(4, 4, 1, true, true, true),
                                                          GEMMRHSMatrixInfo(4, 8, 1, true, true, true),
                                                          GEMMRHSMatrixInfo(8, 4, 1, true, true, true),
                                                          GEMMRHSMatrixInfo(4, 2, 1, true, false, true),
                                                          GEMMRHSMatrixInfo(2, 4, 1, true, false, true),
                           })),
               framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),
                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),
                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),

                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),
                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */)
                                                    })),
               framework::dataset::make("Expected", { true,
                                                      true,
                                                      true,
                                                      false,
                                                      false})),
                    input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
{
   ARM_COMPUTE_EXPECT(bool(ClGemmMatrixMultiplyReshapedKernel::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)) == (expected && image2d_from_buffer_supported(CLKernelLibrary::get().get_device())), framework::LogLevel::ERRORS);
}

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::ALL,
                combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
     // Validate output only if validate() is successful
    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();
    }

}

FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<float>, framework::DatasetMode::NIGHTLY,
                combine(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_nightly),
                                                                   n0_export_to_cl_image_values_nightly),
                                                                   k0_export_to_cl_image_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
     // Validate output only if validate() is successful
    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();
    }
}

FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::ALL,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_precommit),
                                                                   n0_values_precommit),
                                                                   k0_values_precommit),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
     // Validate output only if validate() is successful
    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();
    }
}

FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<float>, framework::DatasetMode::NIGHTLY,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_nightly),
                                                                   n0_export_to_cl_image_values_nightly),
                                                                   k0_export_to_cl_image_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output only if validate() is successful
    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(FusedPostOps)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<float>, framework::DatasetMode::ALL,
                combine(combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   framework::dataset::make("interleave_lhs", { false })),
                                                                   framework::dataset::make("interleave_rhs", { false })),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F32)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   framework::dataset::make("broadcast_bias", { true } )),
                                                                   lhs_transpose_values),
                                                                   act_values),
                                                                   post_op_lists)
                                                                   )
{
    // Validate output only if validate() is successful
    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() // ExportToCLImage
TEST_SUITE_END() // FP32

TEST_SUITE(FP16)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
                combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}

FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::DISABLED,
                combine(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_nightly),
                                                                   n0_values_nightly),
                                                                   k0_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}

FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_precommit),
                                                                   n0_values_precommit),
                                                                   k0_values_precommit),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}

FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::DISABLED,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_nightly),
                                                                   n0_values_nightly),
                                                                   k0_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}

TEST_SUITE(FusedPostOps)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<half>, framework::DatasetMode::ALL,
                combine(combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   framework::dataset::make("interleave_lhs", { false })),
                                                                   framework::dataset::make("interleave_rhs", { false })),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   framework::dataset::make("broadcast_bias", { true } )),
                                                                   lhs_transpose_values),
                                                                   act_values),
                                                                   post_op_lists)
                                                                   )
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16, 0.f, abs_tolerance_f16);
}

TEST_SUITE_END() //  FusedPostOps

TEST_SUITE(ExportToCLImage)
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
               framework::dataset::make("Input0Info", { TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),  // OK or incorrect if cl_khr_image2d_from_buffer not supported
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),  // OK or incorrect if cl_khr_image2d_from_buffer not supported
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),  // OK or incorrect if cl_khr_image2d_from_buffer not supported
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),  // Incorrect k0
                                                        TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),  // Incorrect n0

                                                      }),
               framework::dataset::make("Input1Info",{ TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(512U, 8U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(256U, 16U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(128U, 32U, 2U), 1, DataType::F16),

                      })),
               framework::dataset::make("Input2Info", { TensorInfo(TensorShape(64U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(64U), 1, DataType::F16),

                                                      })),
               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),
                                                       TensorInfo(TensorShape(64U, 64U, 2U), 1, DataType::F16),

                           })),
               framework::dataset::make("LHSMInfo",{
                                                          GEMMLHSMatrixInfo(4, 4, 1, false, true),
                                                          GEMMLHSMatrixInfo(4, 8, 1, false, true),
                                                          GEMMLHSMatrixInfo(4, 4, 1, false, true),
                                                          GEMMLHSMatrixInfo(4, 2, 1, false, false),
                                                          GEMMLHSMatrixInfo(4, 4, 1, false, false),

                                })),
               framework::dataset::make("RHSMInfo",{
                                                          GEMMRHSMatrixInfo(4, 4, 1, true, true, true),
                                                          GEMMRHSMatrixInfo(4, 8, 1, true, true, true),
                                                          GEMMRHSMatrixInfo(8, 4, 1, true, true, true),
                                                          GEMMRHSMatrixInfo(4, 2, 1, true, false, true),
                                                          GEMMRHSMatrixInfo(2, 4, 1, true, false, true),
                           })),
               framework::dataset::make("GEMMInfo",{GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),
                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),
                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),

                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */),
                                                    GEMMKernelInfo( 64 /**<M Number of LHS rows*/,
                                                                    64 /**<N Number of RHS columns*/,
                                                                    64 /**<K Number of LHS columns or RHS rows */, 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::LU_BOUNDED_RELU,
                                                             1   /**< Multiplication factor for the width of the 1xW transposed block */,
                                                             1   /**< Multiplication factor for the height of the 4x4 interleaved block */,
                                                             GEMMLHSMatrixInfo(),
                                                             GEMMRHSMatrixInfo(),
                                                             0  /**< Offset to be added to each element of the matrix A */,
                                                             0 /**< Offset to be added to each element of the matrix B */)
                                                    })),
               framework::dataset::make("Expected", { true,
                                                      true,
                                                      true,
                                                      false,
                                                      false})),
                    input0_info ,input1_info, input2_info, output_info, lhs_info, rhs_info, gemm_info, expected)
{
   ARM_COMPUTE_EXPECT(bool(ClGemmMatrixMultiplyReshapedKernel::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)) == (expected && image2d_from_buffer_supported(CLKernelLibrary::get().get_device())), framework::LogLevel::ERRORS);
}

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::ALL,
                combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output only if validate() is successful
    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();
    }

}

FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedFixture<half>, framework::DatasetMode::NIGHTLY,
                combine(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_nightly),
                                                                   n0_export_to_cl_image_values_nightly),
                                                                   k0_export_to_cl_image_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output only if validate() is successful
    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();
    }
}

FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::ALL,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_precommit),
                                                                   n0_values_precommit),
                                                                   k0_values_precommit),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output only if validate() is successful
    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();
    }
}

FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DFixture<half>, framework::DatasetMode::NIGHTLY,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_nightly),
                                                                   n0_export_to_cl_image_values_nightly),
                                                                   k0_export_to_cl_image_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output only if validate() is successful
    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(FusedPostOps)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedWithPostOpsFixture<half>, framework::DatasetMode::ALL,
                combine(combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   framework::dataset::make("interleave_lhs", { false })),
                                                                   framework::dataset::make("interleave_rhs", { false })),
                                                                   framework::dataset::make("export_to_cl_image_rhs", true)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   framework::dataset::make("broadcast_bias", { true } )),
                                                                   lhs_transpose_values),
                                                                   act_values),
                                                                   post_op_lists)
                                                                   )
{
    // Validate output only if validate() is successful
    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() // ExportToCLImage
TEST_SUITE_END() // FP16

TEST_SUITE(MixedPrecision)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::ALL,
                combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}

FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED,
                combine(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_nightly),
                                                                   n0_values_nightly),
                                                                   k0_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   broadcast_bias_values),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}

FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::ALL,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_precommit),
                                                                   n0_values_precommit),
                                                                   k0_values_precommit),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}

FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshaped3DMixedPrecisionFixture<half>, framework::DatasetMode::DISABLED,
                combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(
                                                                   m_w_values,
                                                                   m_h_values),
                                                                   n_values),
                                                                   k_values),
                                                                   b_values),
                                                                   m0_values_nightly),
                                                                   n0_values_nightly),
                                                                   k0_values_nightly),
                                                                   v0_values_nightly),
                                                                   h0_values_nightly),
                                                                   i_values_lhs),
                                                                   i_values_rhs),
                                                                   framework::dataset::make("export_to_cl_image_rhs", false)),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_nightly),
                                                                   beta_values_nightly),
                                                                   lhs_transpose_values),
                                                                   act_values))
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}

TEST_SUITE(FusedPostOps)

FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedMixedPrecisionWithPostOpsFixture<half>, framework::DatasetMode::ALL,
                combine(combine(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),
                                                                   v0_values_precommit),
                                                                   h0_values_precommit),
                                                                   framework::dataset::make("interleave_lhs", { false })),
                                                                   framework::dataset::make("interleave_rhs", { false })),
                                                                   framework::dataset::make("export_to_cl_image_rhs", { true, false })),
                                                                   framework::dataset::make("DataType", DataType::F16)),
                                                                   a_values_precommit),
                                                                   beta_values_precommit),
                                                                   framework::dataset::make("broadcast_bias", { true } )),
                                                                   lhs_transpose_values),
                                                                   act_values),
                                                                   post_op_lists)
                                                                   )
{
    // Validate output
    validate(CLAccessor(_target), _reference, rel_tolerance_f16_mixed_precision, 0.f, abs_tolerance_f16_mixed_precision);
}

TEST_SUITE_END() // FusedPostOps

TEST_SUITE_END() // MixedPrecision
TEST_SUITE_END() // Float
TEST_SUITE_END() // GEMMMatrixMultiplyReshaped
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute