COMPMID-415: Move GEMM to new validation

Change-Id: Ie32f981c86fa1b01905d2776b0d0a0a47b228f0b
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/82538
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

8 files changed, 0 insertions, 582 deletions

diff --git a/tests/validation/CL/GEMM.cpp b/tests/validation/CL/GEMM.cpp
deleted file mode 100644
index a39cdfd2e3..0000000000
--- a/tests/validation/CL/GEMM.cpp
+++ /dev/null
@@ -1,201 +0,0 @@
-/*
- * Copyright (c) 2017 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 "AssetsLibrary.h"
-#include "CL/CLAccessor.h"
-#include "TypePrinter.h"
-#include "dataset/GEMMDataset.h"
-#include "tests/Globals.h"
-#include "tests/Utils.h"
-#include "validation/Datasets.h"
-#include "validation/Reference.h"
-#include "validation/Validation.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/functions/CLGEMM.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "boost_wrapper.h"
-
-#include <random>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
-const float tolerance_q   = 1.0f;   /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
-
-CLTensor compute_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3,
-                      const TensorShape &out_shape, float alpha, float beta, DataType dt, int fixed_point_position = 0)
-{
-    // Create tensors
-    CLTensor src1 = create_tensor<CLTensor>(src_shape1, dt, 1, fixed_point_position);
-    CLTensor src2 = create_tensor<CLTensor>(src_shape2, dt, 1, fixed_point_position);
-    CLTensor src3 = create_tensor<CLTensor>(src_shape3, dt, 1, fixed_point_position);
-    CLTensor dst  = create_tensor<CLTensor>(out_shape, dt, 1, fixed_point_position);
-
-    // Create and configure function
-    CLGEMM gemm;
-    gemm.configure(&src1, &src2, &src3, &dst, alpha, beta);
-
-    // Allocate tensors
-    src1.allocator()->allocate();
-    src2.allocator()->allocate();
-    src3.allocator()->allocate();
-    dst.allocator()->allocate();
-
-    BOOST_TEST(!src1.info()->is_resizable());
-    BOOST_TEST(!src2.info()->is_resizable());
-    BOOST_TEST(!src3.info()->is_resizable());
-    BOOST_TEST(!dst.info()->is_resizable());
-
-    // Fill tensors
-    if(dt == DataType::F32)
-    {
-        std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
-        library->fill(CLAccessor(src1), distribution, 0);
-        library->fill(CLAccessor(src2), distribution, 1);
-        library->fill(CLAccessor(src3), distribution, 2);
-    }
-    else
-    {
-        library->fill_tensor_uniform(CLAccessor(src1), 0);
-        library->fill_tensor_uniform(CLAccessor(src2), 1);
-        library->fill_tensor_uniform(CLAccessor(src3), 2);
-    }
-
-    // Compute function
-    gemm.run();
-
-    return dst;
-}
-} // namespace
-
-#ifndef DOXYGEN_SKIP_THIS
-BOOST_AUTO_TEST_SUITE(CL)
-BOOST_AUTO_TEST_SUITE(GEMM)
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(Configuration,
-                     SmallGEMMDataset() * boost::unit_test::data::make({ DataType::F32, DataType::QS8, DataType::QS16 }),
-                     gemm_set, dt)
-{
-    // Set fixed point position data type allowed
-    int fixed_point_position = (dt == DataType::F32) ? 0 : 3;
-
-    // Create tensors
-    CLTensor src1 = create_tensor<CLTensor>(gemm_set.shape_a, dt, 1, fixed_point_position);
-    CLTensor src2 = create_tensor<CLTensor>(gemm_set.shape_b, dt, 1, fixed_point_position);
-    CLTensor src3 = create_tensor<CLTensor>(gemm_set.shape_c, dt, 1, fixed_point_position);
-    CLTensor dst  = create_tensor<CLTensor>(gemm_set.shape_d, dt, 1, fixed_point_position);
-
-    BOOST_TEST(src1.info()->is_resizable());
-    BOOST_TEST(src2.info()->is_resizable());
-    BOOST_TEST(src3.info()->is_resizable());
-    BOOST_TEST(dst.info()->is_resizable());
-
-    // Create and configure function
-    CLGEMM gemm;
-    gemm.configure(&src1, &src2, &src3, &dst, gemm_set.alpha, gemm_set.beta);
-
-    // Validate valid region
-    const ValidRegion src1_valid_region = shape_to_valid_region(gemm_set.shape_a);
-    const ValidRegion src2_valid_region = shape_to_valid_region(gemm_set.shape_b);
-    const ValidRegion src3_valid_region = shape_to_valid_region(gemm_set.shape_c);
-    const ValidRegion dst_valid_region  = shape_to_valid_region(gemm_set.shape_d);
-
-    validate(src1.info()->valid_region(), src1_valid_region);
-    validate(src2.info()->valid_region(), src2_valid_region);
-    validate(src3.info()->valid_region(), src3_valid_region);
-    validate(dst.info()->valid_region(), dst_valid_region);
-}
-
-BOOST_AUTO_TEST_SUITE(Float)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(SmallGEMM, SmallGEMMDataset() * boost::unit_test::data::make(DataType::F32),
-                     gemm_set, dt)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Compute function
-    CLTensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, tolerance_f32);
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(LargeGEMM, LargeGEMMDataset() * boost::unit_test::data::make(DataType::F32),
-                     gemm_set, dt)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Compute function
-    CLTensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, tolerance_f32);
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE(Quantized)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(SmallGEMM, SmallGEMMDataset() * boost::unit_test::data::make({ DataType::QS8, DataType::QS16 }) * boost::unit_test::data::xrange(4, 7),
-                     gemm_set, dt, fixed_point_position)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Compute function
-    CLTensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, tolerance_q);
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(LargeGEMM, LargeGEMMDataset() * boost::unit_test::data::make({ DataType::QS8, DataType::QS16 }) * boost::unit_test::data::xrange(4, 7),
-                     gemm_set, dt, fixed_point_position)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Compute function
-    CLTensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, tolerance_q);
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE_END()
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* DOXYGEN_SKIP_THIS */
diff --git a/tests/validation/NEON/GEMM.cpp b/tests/validation/NEON/GEMM.cpp
deleted file mode 100644
index 8747f0ab72..0000000000
--- a/tests/validation/NEON/GEMM.cpp
+++ /dev/null
@@ -1,219 +0,0 @@
-/*
- * Copyright (c) 2017 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 "AssetsLibrary.h"
-#include "Globals.h"
-#include "NEON/Accessor.h"
-#include "TypePrinter.h"
-#include "Utils.h"
-#include "dataset/GEMMDataset.h"
-#include "validation/Datasets.h"
-#include "validation/Reference.h"
-#include "validation/Validation.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "boost_wrapper.h"
-
-#include <random>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
-const float tolerance_q   = 1.0f;   /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
-
-Tensor compute_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3,
-                    const TensorShape &out_shape, float alpha, float beta, DataType dt, int fixed_point_position = 0)
-{
-    // Create tensors
-    Tensor src1 = create_tensor<Tensor>(src_shape1, dt, 1, fixed_point_position);
-    Tensor src2 = create_tensor<Tensor>(src_shape2, dt, 1, fixed_point_position);
-    Tensor src3 = create_tensor<Tensor>(src_shape3, dt, 1, fixed_point_position);
-    Tensor dst  = create_tensor<Tensor>(out_shape, dt, 1, fixed_point_position);
-
-    // Create and configure function
-    NEGEMM gemm;
-    gemm.configure(&src1, &src2, &src3, &dst, alpha, beta);
-
-    // Allocate tensors
-    src1.allocator()->allocate();
-    src2.allocator()->allocate();
-    src3.allocator()->allocate();
-    dst.allocator()->allocate();
-
-    BOOST_TEST(!src1.info()->is_resizable());
-    BOOST_TEST(!src2.info()->is_resizable());
-    BOOST_TEST(!src3.info()->is_resizable());
-    BOOST_TEST(!dst.info()->is_resizable());
-
-    // Fill tensors
-    if(dt == DataType::F16 || dt == DataType::F32)
-    {
-        std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
-        library->fill(Accessor(src1), distribution, 0);
-        library->fill(Accessor(src2), distribution, 1);
-        library->fill(Accessor(src3), distribution, 2);
-    }
-    else
-    {
-        library->fill_tensor_uniform(Accessor(src1), 0);
-        library->fill_tensor_uniform(Accessor(src2), 1);
-        library->fill_tensor_uniform(Accessor(src3), 2);
-    }
-
-    // Compute function
-    gemm.run();
-
-    return dst;
-}
-} // namespace
-
-#ifndef DOXYGEN_SKIP_THIS
-BOOST_AUTO_TEST_SUITE(NEON)
-BOOST_AUTO_TEST_SUITE(GEMM)
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(Configuration,
-                     SmallGEMMDataset() * boost::unit_test::data::make({ DataType::F32, DataType::QS8, DataType::QS16 }),
-                     gemm_set, dt)
-{
-    // Set fixed point position data type allowed
-    int fixed_point_position = (dt == DataType::F32) ? 0 : 3;
-
-    // Create tensors
-    Tensor src1 = create_tensor<Tensor>(gemm_set.shape_a, dt, 1, fixed_point_position);
-    Tensor src2 = create_tensor<Tensor>(gemm_set.shape_b, dt, 1, fixed_point_position);
-    Tensor src3 = create_tensor<Tensor>(gemm_set.shape_c, dt, 1, fixed_point_position);
-    Tensor dst  = create_tensor<Tensor>(gemm_set.shape_d, dt, 1, fixed_point_position);
-
-    BOOST_TEST(src1.info()->is_resizable());
-    BOOST_TEST(src2.info()->is_resizable());
-    BOOST_TEST(src3.info()->is_resizable());
-    BOOST_TEST(dst.info()->is_resizable());
-
-    // Create and configure function
-    NEGEMM gemm;
-    gemm.configure(&src1, &src2, &src3, &dst, gemm_set.alpha, gemm_set.beta);
-
-    // Validate valid region
-    const ValidRegion src1_valid_region = shape_to_valid_region(gemm_set.shape_a);
-    const ValidRegion src2_valid_region = shape_to_valid_region(gemm_set.shape_b);
-    const ValidRegion src3_valid_region = shape_to_valid_region(gemm_set.shape_c);
-    const ValidRegion dst_valid_region  = shape_to_valid_region(gemm_set.shape_d);
-
-    validate(src1.info()->valid_region(), src1_valid_region);
-    validate(src2.info()->valid_region(), src2_valid_region);
-    validate(src3.info()->valid_region(), src3_valid_region);
-    validate(dst.info()->valid_region(), dst_valid_region);
-}
-
-#ifdef ARM_COMPUTE_ENABLE_FP16
-BOOST_AUTO_TEST_SUITE(Float16)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(SmallGEMM, SmallGEMMDataset() * boost::unit_test::data::make(DataType::F16),
-                     gemm_set, dt)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Compute function
-    Tensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, tolerance_f32);
-}
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* ARM_COMPUTE_ENABLE_FP16 */
-
-BOOST_AUTO_TEST_SUITE(Float)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(SmallGEMM, SmallGEMMDataset() * boost::unit_test::data::make(DataType::F32),
-                     gemm_set, dt)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Compute function
-    Tensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, tolerance_f32);
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(LargeGEMM, LargeGEMMDataset() * boost::unit_test::data::make(DataType::F32),
-                     gemm_set, dt)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Compute function
-    Tensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, tolerance_f32);
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE(Quantized)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(SmallGEMM, SmallGEMMDataset() * boost::unit_test::data::make({ DataType::QS8, DataType::QS16 }) * boost::unit_test::data::xrange(1, 7),
-                     gemm_set, dt, fixed_point_position)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Compute function
-    Tensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, tolerance_q);
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(LargeGEMM, LargeGEMMDataset() * boost::unit_test::data::make({ DataType::QS8, DataType::QS16 }) * boost::unit_test::data::xrange(1, 7),
-                     gemm_set, dt, fixed_point_position)
-{
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Compute function
-    Tensor dst = compute_gemm(gemm_set.shape_a, gemm_set.shape_b, gemm_set.shape_c, gemm_set.shape_d, gemm_set.alpha, gemm_set.beta, dt, fixed_point_position);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, tolerance_q);
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE_END()
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* DOXYGEN_SKIP_THIS */
diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp
index 99e3095007..e5bbdf2f2e 100644
--- a/tests/validation/Reference.cpp
+++ b/tests/validation/Reference.cpp
@@ -340,35 +340,6 @@ RawTensor Reference::compute_reference_gaussian5x5(const TensorShape &shape, Bor
     return ref_dst;
 }
 
-RawTensor Reference::compute_reference_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3,
-                                            const TensorShape &dst_shape, float alpha, float beta, DataType dt, int fixed_point_position)
-{
-    RawTensor src1(src_shape1, dt, 1, fixed_point_position);
-    RawTensor src2(src_shape2, dt, 1, fixed_point_position);
-    RawTensor src3(src_shape3, dt, 1, fixed_point_position);
-    RawTensor dst(dst_shape, dt, 1, fixed_point_position);
-
-    // Fill reference
-    if(dt == DataType::F16 || dt == DataType::F32)
-    {
-        std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
-        library->fill(src1, distribution, 0);
-        library->fill(src2, distribution, 1);
-        library->fill(src3, distribution, 2);
-    }
-    else
-    {
-        library->fill_tensor_uniform(src1, 0);
-        library->fill_tensor_uniform(src2, 1);
-        library->fill_tensor_uniform(src3, 2);
-    }
-
-    // Compute reference
-    ReferenceCPP::gemm(src1, src2, src3, dst, alpha, beta);
-
-    return dst;
-}
-
 RawTensor Reference::compute_reference_non_linear_filter(const TensorShape &shape, NonLinearFilterFunction function, unsigned int mask_size,
                                                          MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value)
 {
diff --git a/tests/validation/Reference.h b/tests/validation/Reference.h
index f3216fbaf9..9bcbdf7418 100644
--- a/tests/validation/Reference.h
+++ b/tests/validation/Reference.h
@@ -215,21 +215,6 @@ public:
      * @return Computed raw tensor.
      */
     static RawTensor compute_reference_gaussian5x5(const TensorShape &shape, BorderMode border_mode, uint8_t constant_border_value);
-    /** Compute matrix multiply function.
-     *
-     * @param[in]  src_shape1           First input tensor shape
-     * @param[in]  src_shape2           Second input tensor shape
-     * @param[in]  src_shape3           Third input tensor shape
-     * @param[out] dst_shape            Output tensor.
-     * @param[in]  alpha                Weight of the matrix product
-     * @param[in]  beta                 Weight of the third matrix
-     * @param[in]  dt                   Tensor's data type
-     * @param[in]  fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers
-     *
-     * @return Computed output tensor.
-     */
-    static RawTensor compute_reference_gemm(const TensorShape &src_shape1, const TensorShape &src_shape2, const TensorShape &src_shape3,
-                                            const TensorShape &dst_shape, float alpha, float beta, DataType dt, int fixed_point_position = 0);
     /** Compute reference non linear filter function
      *
      * @param[in] shape                 Shape of the input and output tensors.Data type supported: U8
diff --git a/tests/validation/ReferenceCPP.cpp b/tests/validation/ReferenceCPP.cpp
index 6b902ae3f2..0364e75ce3 100644
--- a/tests/validation/ReferenceCPP.cpp
+++ b/tests/validation/ReferenceCPP.cpp
@@ -222,17 +222,6 @@ void ReferenceCPP::gaussian5x5(const RawTensor &src, RawTensor &dst, BorderMode
     tensor_operations::gaussian5x5(s, d, border_mode, constant_border_value);
 }
 
-// GEMM
-void ReferenceCPP::gemm(const RawTensor &src1, const RawTensor &src2, const RawTensor &src3,
-                        RawTensor &dst, float alpha, float beta)
-{
-    const TensorVariant s1 = TensorFactory::get_tensor(src1);
-    const TensorVariant s2 = TensorFactory::get_tensor(src2);
-    const TensorVariant s3 = TensorFactory::get_tensor(src3);
-    TensorVariant       d  = TensorFactory::get_tensor(dst);
-
-    boost::apply_visitor(tensor_visitors::gemm_visitor(s1, s2, s3, alpha, beta), d);
-}
 // Non linear filter
 void ReferenceCPP::non_linear_filter(const RawTensor &src, RawTensor &dst, NonLinearFilterFunction function, unsigned int mask_size,
                                      MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value)
diff --git a/tests/validation/ReferenceCPP.h b/tests/validation/ReferenceCPP.h
index d289e8e57e..7ae45f0dac 100644
--- a/tests/validation/ReferenceCPP.h
+++ b/tests/validation/ReferenceCPP.h
@@ -190,17 +190,6 @@ public:
      * @param[in]  constant_border_value Constant border value if @p border_mode is BorderMode::CONSTANT
      */
     static void gaussian5x5(const RawTensor &src, RawTensor &dst, BorderMode border_mode, uint8_t constant_border_value);
-    /** Compute GEMM function.
-     *
-     * @param[in]  src1  First input tensor
-     * @param[in]  src2  Second input tensor
-     * @param[in]  src3  Third input tensor
-     * @param[out] dst   Output tensr
-     * @param[in]  alpha Weight of the matrix product
-     * @param[in]  beta  Weight of the third matrix
-     */
-    static void gemm(const RawTensor &src1, const RawTensor &src2, const RawTensor &src3,
-                     RawTensor &dst, float alpha, float beta);
     /** Compute non linear filter function.
      *
      * @param[in]  src                   First input tensor
diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h
index f4d2110387..6e6d1f5115 100644
--- a/tests/validation/TensorOperations.h
+++ b/tests/validation/TensorOperations.h
@@ -592,79 +592,6 @@ void gaussian5x5(const Tensor<T> &in, Tensor<T> &out, BorderMode border_mode, T
     }
 }
 
-// Matrix multiplication for floating point type
-template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
-void gemm(const Tensor<T> &in1, const Tensor<T> &in2, const Tensor<T> &in3, Tensor<T> &out, float alpha, float beta)
-{
-    const int M = out.shape().y();
-    const int N = out.shape().x();
-    const int K = in1.shape().x();
-
-    for(int r = 0; r < M; ++r)
-    {
-        for(int c = 0; c < N; ++c)
-        {
-            T acc(0);
-
-            for(int k = 0; k < K; ++k)
-            {
-                const T a0 = in1[r * K + k];
-                const T b0 = in2[k * N + c];
-
-                acc += a0 * b0;
-            }
-
-            // Finalize the result: A * B * alpha + C * beta
-            const T c0     = in3[c + r * N];
-            out[c + r * N] = alpha * acc + beta * c0;
-        }
-    }
-}
-
-// Matrix multiplication for fixed point type
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
-void gemm(const Tensor<T> &in1, const Tensor<T> &in2, const Tensor<T> &in3, Tensor<T> &out, float alpha, float beta)
-{
-    using namespace fixed_point_arithmetic;
-
-    using promoted_type = typename fixed_point_arithmetic::traits::promote<T>::type;
-
-    const int    M                    = out.shape().y();
-    const int    N                    = out.shape().x();
-    const int    K                    = in1.shape().x();
-    const int8_t fixed_point_position = static_cast<int8_t>(in1.fixed_point_position());
-
-    const fixed_point<T> alpha_q(alpha, fixed_point_position);
-    const fixed_point<T> beta_q(beta, fixed_point_position);
-
-    for(int r = 0; r < M; ++r)
-    {
-        for(int c = 0; c < N; ++c)
-        {
-            fixed_point<promoted_type> acc_q(0, fixed_point_position);
-
-            for(int k = 0; k < K; ++k)
-            {
-                const fixed_point<promoted_type> a0_q(in1[r * K + k], fixed_point_position, true);
-                const fixed_point<promoted_type> b0_q(in2[k * N + c], fixed_point_position, true);
-                const fixed_point<promoted_type> axb_q = a0_q * b0_q;
-
-                acc_q = axb_q + acc_q;
-            }
-
-            // Finalize the result: A * B * alpha + C * beta
-            const fixed_point<T> c0_q(in3[c + r * N], fixed_point_position, true);
-
-            fixed_point<T> res_q(acc_q);
-            res_q = alpha_q * res_q;
-            res_q = (c0_q * beta_q) + res_q;
-
-            // Store the result
-            out[c + r * N] = res_q.raw();
-        }
-    }
-}
-
 // Non linear filter
 template <typename T>
 void non_linear_filter(const Tensor<T> &in, Tensor<T> &out, NonLinearFilterFunction function, unsigned int mask_size,
diff --git a/tests/validation/TensorVisitors.h b/tests/validation/TensorVisitors.h
index 67f1d8a001..5ee7ae3a9f 100644
--- a/tests/validation/TensorVisitors.h
+++ b/tests/validation/TensorVisitors.h
@@ -132,29 +132,6 @@ private:
     ConvertPolicy _policy;
     uint32_t      _shift;
 };
-// GEMM visitor
-struct gemm_visitor : public boost::static_visitor<>
-{
-public:
-    explicit gemm_visitor(const TensorVariant &in1, const TensorVariant &in2, const TensorVariant &in3, float alpha, float beta)
-        : _in1(in1), _in2(in2), _in3(in3), _alpha(alpha), _beta(beta)
-    {
-    }
-
-    template <typename T>
-    void operator()(Tensor<T> &out) const
-    {
-        const Tensor<T> &in1 = boost::get<Tensor<T>>(_in1);
-        const Tensor<T> &in2 = boost::get<Tensor<T>>(_in2);
-        const Tensor<T> &in3 = boost::get<Tensor<T>>(_in3);
-        tensor_operations::gemm(in1, in2, in3, out, _alpha, _beta);
-    }
-
-private:
-    const TensorVariant &_in1, &_in2, &_in3;
-    float                _alpha;
-    float                _beta;
-};
 // Pixel-wise Multiplication visitor
 struct pixel_wise_multiplication_visitor : public boost::static_visitor<>
 {