Implement OpenCL MatMul for Lhs NT Rhs T/NT FP32/16

 - Implement ClNativeMatMulKernel class
 - Implement opencl kernel for LHS non-transposed and RHS non-transposed
 - Implement opencl kernel for LHS non-transposed and RHS transposed
 - Add test fixture and dataset for matmul
 - Implement transpose_tensor() for reference implementation to transpose high dimensional tensors

Resolves: COMPMID-5944, COMPMID-5951

Co-authored-by: Gunes Bayir <gunes.bayir@arm.com>
Co-authored-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I1d5b8978f41be27baddb3153ade880472141573f
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9333
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 239 insertions, 0 deletions

diff --git a/tests/validation/CL/BatchMatMul.cpp b/tests/validation/CL/BatchMatMul.cpp
new file mode 100644
index 0000000000..fd84526000
--- /dev/null
+++ b/tests/validation/CL/BatchMatMul.cpp
@@ -0,0 +1,239 @@
+/*
+ * Copyright (c) 2023 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/runtime/CL/CLTensor.h"
+#include "src/gpu/cl/kernels/ClNativeMatMulKernel.h"
+#include "tests/datasets/LargeBatchMatMulDataset.h"
+#include "tests/datasets/SmallBatchMatMulDataset.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/BatchMatMulFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
+constexpr float          abs_tolerance_f32(
+    0.0001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for floating point data types in case using relative tolerance fails because of small values */
+constexpr float abs_tolerance_f16(
+    0.001f);                                                   /**< Absolute tolerance value for comparing reference's output against implementation's output for fp16  data types in case using relative tolerance fails because of small values */
+RelativeTolerance<half_float::half> tolerance_f16(half(0.01)); /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
+} // namespace
+
+/** M0 values to test --precommit*/
+const auto m0_values_precommit = framework::dataset::make("M0", { 1, 3 });
+
+/** N0 values to test --precommit*/
+const auto n0_values_precommit = framework::dataset::make("N0", { 2, 4 });
+
+/** K0 values to test --precommit*/
+const auto k0_values_precommit = framework::dataset::make("K0", { 2, 3 });
+
+/** M0 values to test --nightly*/
+const auto m0_values_nightly_lhs_nt = framework::dataset::make("M0", { 1, 2, 3, 4, 5, 6, 7, 8 });
+// const auto m0_values_nightly_lhs_t = framework::dataset::make("M0", { 1, 2, 3, 4, 8 }); // To be enabled
+
+/** N0 values to test --nightly*/
+const auto n0_values_nightly_rhs_nt = framework::dataset::make("N0", { 1, 2, 3, 4, 8, 16 });
+const auto n0_values_nightly_rhs_t  = framework::dataset::make("N0", { 1, 2, 3, 4, 8 });
+
+/** K0 values to test --nightly*/
+const auto k0_values_nightly_lhs_nt_rhs_nt = framework::dataset::make("K0", { 1, 2, 3, 4, 8, 16 });
+const auto k0_values_nightly_lhs_nt_rhs_t  = framework::dataset::make("K0", { 1, 2, 3, 4, 8 });
+// const auto k0_values_nightly_lhs_t_rhs_nt = framework::dataset::make("K0", { 1, 2, 3, 4, 5, 6, 7, 8 }); // To be enabled
+
+template <typename T>
+using CLBatchMatMulFixture = BatchMatMulValidationFixture<T>;
+
+TEST_SUITE(CL)
+TEST_SUITE(BatchMatMul)
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
+                                                                      framework::dataset::make("LhsInfo",
+{
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::S32), // Unsupported data type
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+    TensorInfo(TensorShape(27U, 13U), 1, DataType::F32),
+}),
+framework::dataset::make("RhsInfo",
+{
+    TensorInfo(TensorShape(8U, 27U), 1, DataType::S32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32), TensorInfo(TensorShape(8U, 27U), 1, DataType::F32),
+})),
+framework::dataset::make("OutputInfo",
+{
+    TensorInfo(TensorShape(8U, 13U), 1, DataType::S32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32), TensorInfo(TensorShape(8U, 13U), 1, DataType::F32),
+})),
+framework::dataset::make("MatMulInfo",
+{
+    MatMulKernelInfo(false, false, 2, 2, 2, false), MatMulKernelInfo(false, false, 2, 2, 2, false), MatMulKernelInfo(false, false, 9, 2, 2, false), MatMulKernelInfo(false, false, 0, 2, 2, false), // M0 cannot be < 1
+    MatMulKernelInfo(false, true, 4, 5, 2, false),                                                                                                                                                  // For LHS NT RHS NT: N0 cannot be 5
+    MatMulKernelInfo(false, true, 4, 6, 2, false),                                                                                                                                                  // For LHS NT RHS NT: N0 cannot be 6
+    MatMulKernelInfo(false, true, 4, 9, 2, false),                                                                                                                                                  // For LHS NT RHS NT: N0 cannot be 9
+    MatMulKernelInfo(false, true, 4, 10, 2, false),                                                                                                                                                 // For LHS NT RHS NT: N0 cannot be 10
+    MatMulKernelInfo(false, true, 4, 11, 2, false),                                                                                                                                                 // For LHS NT RHS NT: N0 cannot be 11
+    MatMulKernelInfo(false, true, 4, 17, 2, false),                                                                                                                                                 // For LHS NT RHS NT: N0 cannot be 17
+})),
+framework::dataset::make("Expected", { false, true, true, false, false, false, false, false, false, false })),
+lhs_info, rhs_info, output_info, matmul_info, expected)
+{
+    bool is_valid = bool(ClNativeMatMulKernel::validate(&lhs_info, &rhs_info, &output_info, matmul_info));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmallNoTranspose, CLBatchMatMulFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::SmallBatchMatMulDataset(),
+                                                                                                                      framework::dataset::make("pretransose_A", { false })),
+                                                                                                                      framework::dataset::make("pretransose_B", { false })),
+                                                                                                                      m0_values_precommit),
+                                                                                                                      n0_values_precommit),
+                                                                                                                      k0_values_precommit),
+                                                                                                              framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunSmallRhsTransposed, CLBatchMatMulFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::SmallBatchMatMulDataset(),
+                                                                                                                        framework::dataset::make("pretransose_A", { false })),
+                                                                                                                        framework::dataset::make("pretransose_B", { true })),
+                                                                                                                        m0_values_precommit),
+                                                                                                                        n0_values_precommit),
+                                                                                                                        k0_values_precommit),
+                                                                                                                framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLargeNoTranspose, CLBatchMatMulFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(datasets::LargeBatchMatMulDataset(),
+                                                                                                                  framework::dataset::make("pretransose_A", { false })),
+                                                                                                                  framework::dataset::make("pretransose_B", { false })),
+                                                                                                                  m0_values_nightly_lhs_nt),
+                                                                                                                  n0_values_nightly_rhs_nt),
+                                                                                                                  k0_values_nightly_lhs_nt_rhs_nt),
+                                                                                                                  framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32);
+}
+// Running High Dimensional test is enough for FP32, because we're stressing the number of dimensions, not data type or M0/N0/K0
+// It's a good idea to test for each Lhs/Rhs T/NT combinations because they're different CL kernels
+FIXTURE_DATA_TEST_CASE(RunHighDimNoTranspose, CLBatchMatMulFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::HighDimensionalBatchMatMulDataset(),
+                                                                                                                        framework::dataset::make("pretransose_A", { false })),
+                                                                                                                        framework::dataset::make("pretransose_B", { false })),
+                                                                                                                        framework::dataset::make("M0", { 2 })),
+                                                                                                                        framework::dataset::make("N0", { 2 })),
+                                                                                                                        framework::dataset::make("K0", { 2 })),
+                                                                                                                framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLargeRhsTransposed, CLBatchMatMulFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(datasets::LargeBatchMatMulDataset(),
+                                                                                                                    framework::dataset::make("pretransose_A", { false })),
+                                                                                                                    framework::dataset::make("pretransose_B", { true })),
+                                                                                                                    m0_values_nightly_lhs_nt),
+                                                                                                                    n0_values_nightly_rhs_t),
+                                                                                                                    k0_values_nightly_lhs_nt_rhs_t),
+                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunHighDimRhsTransposed, CLBatchMatMulFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::HighDimensionalBatchMatMulDataset(),
+                                                                                                                  framework::dataset::make("pretransose_A", { false })),
+                                                                                                                  framework::dataset::make("pretransose_B", { true })),
+                                                                                                                  framework::dataset::make("M0", { 2 })),
+                                                                                                                  framework::dataset::make("N0", { 2 })),
+                                                                                                                  framework::dataset::make("K0", { 2 })),
+                                                                                                                  framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32);
+}
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmallNoTranspose, CLBatchMatMulFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::SmallBatchMatMulDataset(),
+                                                                                                                     framework::dataset::make("pretransose_A", { false })),
+                                                                                                                     framework::dataset::make("pretransose_B", { false })),
+                                                                                                                     m0_values_precommit),
+                                                                                                                     n0_values_precommit),
+                                                                                                                     k0_values_precommit),
+                                                                                                             framework::dataset::make("DataType", DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunSmallRhsTransposed, CLBatchMatMulFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(datasets::SmallBatchMatMulDataset(),
+                                                                                                                       framework::dataset::make("pretransose_A", { false })),
+                                                                                                                       framework::dataset::make("pretransose_B", { true })),
+                                                                                                                       m0_values_precommit),
+                                                                                                                       n0_values_precommit),
+                                                                                                                       k0_values_precommit),
+                                                                                                               framework::dataset::make("DataType", DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunLargeNoTranspose, CLBatchMatMulFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(datasets::LargeBatchMatMulDataset(),
+                                                                                                                 framework::dataset::make("pretransose_A", { false })),
+                                                                                                                 framework::dataset::make("pretransose_B", { false })),
+                                                                                                                 m0_values_nightly_lhs_nt),
+                                                                                                                 n0_values_nightly_rhs_nt),
+                                                                                                                 k0_values_nightly_lhs_nt_rhs_nt),
+                                                                                                                 framework::dataset::make("DataType", DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunLargeRhsTransposed, CLBatchMatMulFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(datasets::LargeBatchMatMulDataset(),
+                                                                                                                   framework::dataset::make("pretransose_A", { false })),
+                                                                                                                   framework::dataset::make("pretransose_B", { true })),
+                                                                                                                   m0_values_nightly_lhs_nt),
+                                                                                                                   n0_values_nightly_rhs_t),
+                                                                                                                   k0_values_nightly_lhs_nt_rhs_t),
+                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16);
+}
+TEST_SUITE_END() // FP16
+
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // BatchMatMul
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute