Add Multiplication operator (FP only) to Dynamic Fusion Interface
Note: we use a separate test fixture for Multiplication op instead of reusing ElementwiseBinaryFixture to avoid exposing the internal enum ElementwiseOp to the public utils/TypePrinters.h as required by the data test case macros to print the test data. We also do not consider modifying the enum ArithmeticOp in the standard interface to include MUL without an implementation. Future work should consider refactoring this test fixture into the ElementwiseBinaryFixture to reduce the total number of fixtures/code duplication.
Resolves: COMPMID-5779
Change-Id: I84207658ce0407095b028fca0ab7bfa2950255ec
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9013
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/dynamic_fusion/gpu/cl/Add.cpp b/tests/validation/dynamic_fusion/gpu/cl/Add.cpp
index 0385407..52ba052 100644
--- a/tests/validation/dynamic_fusion/gpu/cl/Add.cpp
+++ b/tests/validation/dynamic_fusion/gpu/cl/Add.cpp
@@ -34,7 +34,6 @@
#include "tests/datasets/DynamicFusionDataset.h"
#include "tests/datasets/ShapeDatasets.h"
#include "tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h"
-#include "tests/validation/reference/ElementwiseOperations.h"
namespace arm_compute
{
@@ -42,6 +41,14 @@
{
namespace validation
{
+/* Synced with tests/validation/CL/ArithmeticAddition.cpp from the standard interface.
+ *
+ * Difference | Why the difference
+ * No quantized tests | Not supported yet
+ * No in place tests | Not supported yet
+ * No activation tests | Not needed in dynamic fusion interface
+ *
+ */
TEST_SUITE(CL)
TEST_SUITE(DYNAMIC_FUSION)
TEST_SUITE(ADD)
@@ -49,29 +56,33 @@
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
- framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ framework::dataset::make("LhsInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid data type combination
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), // S16 is valid data type for Add
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), // S32 is valid data type for Add
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes
TensorInfo(TensorShape(32U, 1U, 1U), 1, DataType::F32), // Broadcasting allowed for lhs
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), // Unsupported data type QASYMM8
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8_SIGNED), // Unsupported data type QASYMM8
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(15U, 23U, 3U), 1, DataType::F32), // Broadcast Y dimension is not allowed
TensorInfo(TensorShape( 3U, 8U, 9U), 1, DataType::S16), // Broadcast Z dimension is not allowed
TensorInfo(TensorShape(32U, 13U, 2U, 2), 1, DataType::F32), // Batching is allowed
}),
- framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ framework::dataset::make("RhsInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), // Unsupported data type QASYMM8
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8_SIGNED), // Unsupported data type QASYMM8
TensorInfo(TensorShape(32U, 1U, 1U), 1, DataType::F32), // Broadcasting allowed for rhs
TensorInfo(TensorShape(15U, 1U, 3U), 1, DataType::F32),
TensorInfo(TensorShape( 3U, 8U, 1U), 1, DataType::S16),
TensorInfo(TensorShape(32U, 13U, 2U, 2), 1, DataType::F32),
})),
- framework::dataset::make("Expected", { true, false, true, true, false, true, true, false, false, true})),
+ framework::dataset::make("Expected", { true, false, true, true, false, true, false, false, true, false, false, true})),
input1_info, input2_info, expected)
{
// Create a new workload sketch
@@ -79,7 +90,7 @@
auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx };
GpuWorkloadSketch sketch{ &gpu_ctx };
- // Fuse Elementwise Add
+ // Validate Elementwise Add
auto lhs_info = sketch.create_tensor_info(input1_info);
auto rhs_info = sketch.create_tensor_info(input2_info);
@@ -89,59 +100,73 @@
// clang-format on
// *INDENT-ON*
-RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
-RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.1)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
-constexpr float tolerance_num = 0.01f; /**< Tolerance number */
+constexpr AbsoluteTolerance<float> tolerance_f16(0.0001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr AbsoluteTolerance<float> tolerance_f32(0.0001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+constexpr float tolerance_num = 0.0001f; /**< Tolerance number */
template <typename T>
-using DynamicFusionAddOpFixture = DynamicFusionGpuElementwiseBinaryOneOpValidationFixture<CLTensor, CLAccessor, GpuAdd, T>;
+using DynamicFusionCLAddFixture = DynamicFusionGpuElementwiseBinaryOneOpValidationFixture<CLTensor, CLAccessor, GpuAdd, T>;
template <typename T>
-using DynamicFusionAddOpBroadcastFixture = DynamicFusionGpuElementwiseBinaryBroadcastOneOpValidationFixture<CLTensor, CLAccessor, GpuAdd, T>;
+using DynamicFusionCLAddBroadcastFixture = DynamicFusionGpuElementwiseBinaryBroadcastOneOpValidationFixture<CLTensor, CLAccessor, GpuAdd, T>;
template <typename T>
-using DynamicFusionGpuFuseTwoAddOpsFixture = DynamicFusionGpuElementwiseBinaryTwoOpsValidationFixture<CLTensor, CLAccessor, GpuAdd, T>;
+using DynamicFusionCLAddTwoOpsFixture = DynamicFusionGpuElementwiseBinaryTwoOpsValidationFixture<CLTensor, CLAccessor, GpuAdd, T>;
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmallOneOp, DynamicFusionAddOpFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(
- framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::SmallShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::F32 })),
- framework::dataset::make("InPlace", { false, true })))
+FIXTURE_DATA_TEST_CASE(RunSmallOneOp,
+ DynamicFusionCLAddFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::SmallShapes()),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLargeOneOp, DynamicFusionAddOpFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(
- framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::LargeShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::F32 })),
- framework::dataset::make("InPlace", { false, true })))
+FIXTURE_DATA_TEST_CASE(RunLargeOneOp,
+ DynamicFusionCLAddFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::LargeShapes()),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunSmallBroadcastOneOp, DynamicFusionAddOpBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::TemporaryLimitedSmallShapesBroadcast()),
- framework::dataset::make("DataType", { DataType::F32 })),
- framework::dataset::make("InPlace", { false, true })))
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcastOneOp,
+ DynamicFusionCLAddBroadcastFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::TemporaryLimitedSmallShapesBroadcast()),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLargeBroadcastOneOp, DynamicFusionAddOpBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::TemporaryLimitedLargeShapesBroadcast()),
- framework::dataset::make("DataType", { DataType::F32 })),
- framework::dataset::make("InPlace", { false, true })))
+FIXTURE_DATA_TEST_CASE(RunLargeBroadcastOneOp,
+ DynamicFusionCLAddBroadcastFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::TemporaryLimitedLargeShapesBroadcast()),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunSmallTwoOps, DynamicFusionGpuFuseTwoAddOpsFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::DynamicFusionElementwiseBinaryTwoOpsSmallShapes()),
- framework::dataset::make("DataType", { DataType::F32 })),
- framework::dataset::make("InPlace", { false })))
+FIXTURE_DATA_TEST_CASE(RunSmallTwoOps,
+ DynamicFusionCLAddTwoOpsFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::DynamicFusionElementwiseBinaryTwoOpsSmallShapes()),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })),
+ framework::dataset::make("FuseTwoOps", { true })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
@@ -149,19 +174,25 @@
TEST_SUITE_END() // FP32
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmallOneOp, DynamicFusionAddOpFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::SmallShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::F16 })),
- framework::dataset::make("InPlace", { false, true })))
+FIXTURE_DATA_TEST_CASE(RunSmallOneOp,
+ DynamicFusionCLAddFixture<half>,
+ framework::DatasetMode::ALL,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::SmallShapes()),
+ framework::dataset::make("DataType", { DataType::F16 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
}
-FIXTURE_DATA_TEST_CASE(RunSmallBroadcastOneOp, DynamicFusionAddOpBroadcastFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::TemporaryLimitedSmallShapesBroadcast()),
- framework::dataset::make("DataType", { DataType::F16 })),
- framework::dataset::make("InPlace", { false })))
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcastOneOp,
+ DynamicFusionCLAddBroadcastFixture<half>,
+ framework::DatasetMode::ALL,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::TemporaryLimitedSmallShapesBroadcast()),
+ framework::dataset::make("DataType", { DataType::F16 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
@@ -170,10 +201,13 @@
TEST_SUITE_END() // FP16
TEST_SUITE(S32)
-FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionAddOpFixture<int32_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::SmallShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::S32 })),
- framework::dataset::make("InPlace", { false })))
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ DynamicFusionCLAddFixture<int32_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::SmallShapes()),
+ framework::dataset::make("DataType", { DataType::S32 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference);
@@ -181,18 +215,24 @@
TEST_SUITE_END() // S32
TEST_SUITE(S16)
-FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionAddOpFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::SmallShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::S16 })),
- framework::dataset::make("InPlace", { false })))
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ DynamicFusionCLAddFixture<int16_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::SmallShapes()),
+ framework::dataset::make("DataType", { DataType::S16 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionAddOpFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::LargeShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::S16 })),
- framework::dataset::make("InPlace", { false })))
+FIXTURE_DATA_TEST_CASE(RunLarge,
+ DynamicFusionCLAddFixture<int16_t>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::LargeShapes()),
+ framework::dataset::make("DataType", { DataType::S16 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference);
@@ -200,10 +240,13 @@
TEST_SUITE_END() // S16
TEST_SUITE(U8)
-FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionAddOpFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
- datasets::SmallShapesNoBatches()),
- framework::dataset::make("DataType", { DataType::U8 })),
- framework::dataset::make("InPlace", { false })))
+FIXTURE_DATA_TEST_CASE(RunSmall,
+ DynamicFusionCLAddFixture<uint8_t>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(framework::dataset::make("ElementwiseOp", { ArithmeticOperation::ADD }),
+ datasets::SmallShapes()),
+ framework::dataset::make("DataType", { DataType::U8 })),
+ framework::dataset::make("InPlace", { false })))
{
// Validate output
validate(CLAccessor(_target), _reference);
diff --git a/tests/validation/dynamic_fusion/gpu/cl/Mul.cpp b/tests/validation/dynamic_fusion/gpu/cl/Mul.cpp
new file mode 100644
index 0000000..a9e8f9c
--- /dev/null
+++ b/tests/validation/dynamic_fusion/gpu/cl/Mul.cpp
@@ -0,0 +1,223 @@
+/*
+ * 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/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h"
+#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuMul.h"
+
+#include "tests/CL/CLAccessor.h"
+#include "tests/framework/Fixture.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+
+#include "tests/datasets/DynamicFusionDataset.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/validation/fixtures/dynamic_fusion/operators/MulFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+/* Synced with tests/validation/CL/PixelwiseMultiplication.cpp from the standard interface.
+ *
+ * Difference | Why the difference
+ * No integer tests | Not supported yet
+ * No quantized tests | Not supported yet
+ * No convert policy tests | Not needed as convert policy is ignored by floating types
+ * No scale tests | Not supported yet
+ * No rounding modes tests | Not supported yet
+ * No in place tests | Not supported yet
+ * No activation tests | Not needed in dynamic fusion interface
+ *
+ */
+namespace
+{
+constexpr AbsoluteTolerance<float> tolerance_f16(0.0001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr AbsoluteTolerance<float> tolerance_f32(0.0001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+} // namespace
+TEST_SUITE(CL)
+TEST_SUITE(DYNAMIC_FUSION)
+TEST_SUITE(MUL)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
+ framework::dataset::make("LhsInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid data type combination
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Unsupported data type U8
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S8), // Unsupported data type S8
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), // Unsupported data type S16
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), // Unsupported data type S32
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), // Unsupported data type QASYMM8
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8_SIGNED), // Unsupported data type QASYMM8_SIGNED
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes
+ TensorInfo(TensorShape(32U, 1U, 1U), 1, DataType::F32), // Broadcasting allowed for lhs
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 23U, 3U), 1, DataType::F32), // Broadcast Y dimension is not allowed
+ TensorInfo(TensorShape( 3U, 8U, 9U), 1, DataType::F32), // Broadcast Z dimension is not allowed
+ TensorInfo(TensorShape(32U, 13U, 2U, 2), 1, DataType::F32), // Batching is allowed
+ }),
+ framework::dataset::make("RhsInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S8),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8_SIGNED),
+ TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 1U, 1U), 1, DataType::F32), // Broadcasting allowed for rhs
+ TensorInfo(TensorShape(15U, 1U, 3U), 1, DataType::F32),
+ TensorInfo(TensorShape( 3U, 8U, 1U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 13U, 2U, 2), 1, DataType::F32),
+ })),
+ framework::dataset::make("Expected", { true, true, false, false, false, false, false, false, false, false, true, true, false, false, true })),
+ input1_info, input2_info, expected)
+{
+ // Create a new workload sketch
+ auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+ auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx };
+ GpuWorkloadSketch sketch{ &gpu_ctx };
+
+ // Validate Elementwise Mul
+ auto lhs_info = sketch.create_tensor_info(input1_info);
+ auto rhs_info = sketch.create_tensor_info(input2_info);
+
+ bool res = bool(GpuMul::validate_op(sketch, &lhs_info, &rhs_info));
+ ARM_COMPUTE_EXPECT(res == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using DynamicFusionCLMulFixture = DynamicFusionMulOneOpValidationFixture<CLTensor, CLAccessor, GpuMul, T>;
+template <typename T>
+using DynamicFusionCLMulBroadcastFixture = DynamicFusionMulBroadcastValidationFixture<CLTensor, CLAccessor, GpuMul, T>;
+template <typename T>
+using DynamicFusionCLMulTwoOpsFixture = DynamicFusionMulTwoOpsValidationFixture<CLTensor, CLAccessor, GpuMul, T>;
+
+TEST_SUITE(F16)
+FIXTURE_DATA_TEST_CASE(RunSmallOneOp,
+ DynamicFusionCLMulFixture<half>,
+ framework::DatasetMode::ALL,
+ combine(combine(datasets::SmallShapes(),
+ framework::dataset::make("DataType", { DataType::F16 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcastOneOp,
+ DynamicFusionCLMulBroadcastFixture<half>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::TemporaryLimitedSmallShapesBroadcast(),
+ framework::dataset::make("DataType", { DataType::F16 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeBroadcastOneOp,
+ DynamicFusionCLMulBroadcastFixture<half>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(datasets::TemporaryLimitedLargeShapesBroadcast(),
+ framework::dataset::make("DataType", { DataType::F16 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+TEST_SUITE_END() // F16
+
+TEST_SUITE(F32)
+FIXTURE_DATA_TEST_CASE(RunSmallOneOp,
+ DynamicFusionCLMulFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::SmallShapes(),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeOneOp,
+ DynamicFusionCLMulFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(datasets::LargeShapes(),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcastOneOp,
+ DynamicFusionCLMulBroadcastFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(datasets::TemporaryLimitedSmallShapesBroadcast(),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeBroadcastOneOp,
+ DynamicFusionCLMulBroadcastFixture<float>,
+ framework::DatasetMode::NIGHTLY,
+ combine(combine(datasets::TemporaryLimitedLargeShapesBroadcast(),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmallTwoOps,
+ DynamicFusionCLMulTwoOpsFixture<float>,
+ framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(datasets::DynamicFusionElementwiseBinaryTwoOpsSmallShapes(),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ framework::dataset::make("InPlace", { false })),
+ framework::dataset::make("FuseTwoOps", { true })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END() // F32
+
+TEST_SUITE_END() // MUL
+TEST_SUITE_END() // DYNAMIC_FUSION
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
index faed610..b0680c0 100644
--- a/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
+++ b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
@@ -31,12 +31,9 @@
#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h"
#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h"
-#include "tests/CL/CLAccessor.h"
#include "tests/framework/Fixture.h"
#include "tests/framework/Macros.h"
-#include "tests/validation/Validation.h"
#include "tests/validation/reference/ElementwiseOperations.h"
-#include "tests/validation/reference/Permute.h"
using namespace arm_compute::experimental::dynamic_fusion;
@@ -51,12 +48,13 @@
{
public:
template <typename...>
- void setup(ArithmeticOperation op, TensorShape shape0, TensorShape shape1, TensorShape shape2, const DataType data_type, const bool is_inplace)
+ void setup(ArithmeticOperation ref_op, const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2, DataType data_type, bool is_inplace, bool fuse_two_ops = false)
{
- _op = op;
+ _ref_op = ref_op;
_is_inplace = is_inplace;
_data_type = data_type;
- _fuse = shape2.total_size() != 0;
+ _fuse = fuse_two_ops;
+ ARM_COMPUTE_ERROR_ON_MSG(_fuse && shape2.total_size() == 0, "No shape2 provided for fusion of two ops.");
ARM_COMPUTE_ERROR_ON_MSG(_fuse && _is_inplace, "In place for fusing case not supported yet.");
_target = compute_target(shape0, shape1, shape2);
_reference = compute_reference(shape0, shape1, shape2);
@@ -68,7 +66,7 @@
{
if(is_data_type_float(tensor.data_type()))
{
- switch(_op)
+ switch(_ref_op)
{
case ArithmeticOperation::DIV:
library->fill_tensor_uniform_ranged(tensor, i, { std::pair<float, float>(-0.001f, 0.001f) });
@@ -82,7 +80,7 @@
}
else if(tensor.data_type() == DataType::S32)
{
- switch(_op)
+ switch(_ref_op)
{
case ArithmeticOperation::DIV:
library->fill_tensor_uniform_ranged(tensor, i, { std::pair<int32_t, int32_t>(-1U, 1U) });
@@ -97,7 +95,7 @@
}
}
- TensorType compute_target(TensorShape shape0, TensorShape shape1, TensorShape shape2)
+ TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2)
{
// Create a new workload sketch
auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
@@ -105,7 +103,7 @@
GpuWorkloadSketch sketch{ &gpu_ctx };
// Fuse first element wise binary Op
- TensorInfo lhs_info = sketch.create_tensor_info(shape0, 1, _data_type);
+ TensorInfo lhs_info = sketch.create_tensor_info(TensorInfo(shape0, 1, _data_type));
TensorInfo rhs_info = sketch.create_tensor_info(TensorInfo(shape1, 1, _data_type));
TensorInfo dst_info = sketch.create_tensor_info();
@@ -115,7 +113,7 @@
if(_fuse)
{
- rhs_info_fuse = sketch.create_tensor_info(shape2, 1, _data_type);
+ rhs_info_fuse = sketch.create_tensor_info(TensorInfo(shape2, 1, _data_type));
ITensorInfo *ans2_info = FunctionType::create_op(sketch, ans_info, &rhs_info_fuse);
GpuOutput::create_op(sketch, ans2_info, &dst_info);
}
@@ -183,7 +181,7 @@
return t_dst;
}
- SimpleTensor<T> compute_reference(TensorShape shape0, TensorShape shape1, TensorShape shape2)
+ SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2)
{
const TensorShape out_shape = TensorShape::broadcast_shape(shape0, shape1);
const TensorShape out_shape_fuse = TensorShape::broadcast_shape(out_shape, shape1);
@@ -194,21 +192,22 @@
SimpleTensor<T> ref_rhs_fuse{ shape2, _data_type, 1, QuantizationInfo() };
SimpleTensor<T> ref_dst{ out_shape, _data_type, 1, QuantizationInfo() };
SimpleTensor<T> ref_dst_fuse{ out_shape_fuse, _data_type, 1, QuantizationInfo() };
+
// Fill reference
fill(ref_lhs, 0);
fill(ref_rhs, 1);
- reference::arithmetic_operation<T>(_op, ref_lhs, ref_rhs, ref_dst, ConvertPolicy::WRAP);
+ reference::arithmetic_operation<T>(_ref_op, ref_lhs, ref_rhs, ref_dst, ConvertPolicy::WRAP);
if(_fuse)
{
fill(ref_rhs_fuse, 2);
- reference::arithmetic_operation<T>(_op, ref_dst, ref_rhs_fuse, ref_dst_fuse, ConvertPolicy::WRAP);
+ reference::arithmetic_operation<T>(_ref_op, ref_dst, ref_rhs_fuse, ref_dst_fuse, ConvertPolicy::WRAP);
}
SimpleTensor<T> *ret = _fuse ? &ref_dst_fuse : &ref_dst;
return *ret;
}
- ArithmeticOperation _op{ ArithmeticOperation::ADD };
+ ArithmeticOperation _ref_op{ ArithmeticOperation::ADD };
TensorType _target{};
SimpleTensor<T> _reference{};
DataType _data_type{};
@@ -222,9 +221,9 @@
{
public:
template <typename...>
- void setup(ArithmeticOperation op, TensorShape shape, const DataType data_type, const bool is_inplace)
+ void setup(ArithmeticOperation ref_op, const TensorShape &shape0, DataType data_type, bool is_inplace)
{
- DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(op, shape, shape, TensorShape(), data_type, is_inplace);
+ DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ref_op, shape0, shape0, TensorShape(), data_type, is_inplace);
}
};
@@ -233,9 +232,9 @@
{
public:
template <typename...>
- void setup(ArithmeticOperation op, TensorShape shape0, TensorShape shape1, const DataType data_type, const bool is_inplace)
+ void setup(ArithmeticOperation ref_op, const TensorShape &shape0, const TensorShape &shape1, DataType data_type, bool is_inplace)
{
- DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(op, shape0, shape1, TensorShape(), data_type, is_inplace);
+ DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ref_op, shape0, shape1, TensorShape(), data_type, is_inplace);
}
};
@@ -244,9 +243,9 @@
{
public:
template <typename...>
- void setup(ArithmeticOperation op, TensorShape shape0, TensorShape shape1, TensorShape shape2, const DataType data_type, const bool is_inplace)
+ void setup(ArithmeticOperation ref_op, const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2, DataType data_type, bool is_inplace, bool fuse_two_ops)
{
- DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(op, shape0, shape1, shape2, data_type, is_inplace);
+ DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ref_op, shape0, shape1, shape2, data_type, is_inplace, fuse_two_ops);
}
};
diff --git a/tests/validation/fixtures/dynamic_fusion/operators/MulFixture.h b/tests/validation/fixtures/dynamic_fusion/operators/MulFixture.h
new file mode 100644
index 0000000..0530707
--- /dev/null
+++ b/tests/validation/fixtures/dynamic_fusion/operators/MulFixture.h
@@ -0,0 +1,235 @@
+/*
+* 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.
+*/
+#ifndef TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_MULFIXTURE
+#define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_MULFIXTURE
+
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h"
+#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h"
+#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h"
+
+#include "tests/Globals.h"
+#include "tests/framework/Fixture.h"
+#include "tests/framework/Macros.h"
+#include "tests/validation/reference/PixelWiseMultiplication.h"
+
+using namespace arm_compute::experimental::dynamic_fusion;
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+/* We use a separate test fixture for Multiplication op instead of reusing ElementwiseBinaryFixture to avoid exposing
+ * the internal enum ElementwiseOp to the public utils/TypePrinters.h as required by the data test case macros
+ * to print the test data.
+ */
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DynamicFusionMulValidationFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2, DataType data_type, bool is_inplace, bool fuse_two_ops = false)
+ {
+ _data_type = data_type;
+ _is_inplace = is_inplace;
+ _fuse = fuse_two_ops;
+ ARM_COMPUTE_ERROR_ON_MSG(_fuse && shape2.total_size() == 0, "No shape2 provided for fusion of two ops.");
+ ARM_COMPUTE_ERROR_ON_MSG(_fuse && _is_inplace, "In place for fusing case not supported yet.");
+ _target = compute_target(shape0, shape1, shape2);
+ _reference = compute_reference(shape0, shape1, shape2);
+ }
+
+protected:
+ template <typename U>
+ void fill(U &&tensor, int i)
+ {
+ library->fill_tensor_uniform(tensor, i);
+ }
+
+ TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2)
+ {
+ // Create a new workload sketch
+ auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+ auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx };
+ GpuWorkloadSketch sketch{ &gpu_ctx };
+
+ // Fuse first multiplication op
+ TensorInfo lhs_info = sketch.create_tensor_info(TensorInfo(shape0, 1, _data_type));
+ TensorInfo rhs_info = sketch.create_tensor_info(TensorInfo(shape1, 1, _data_type));
+ TensorInfo dst_info = sketch.create_tensor_info();
+
+ TensorInfo rhs_info_fuse;
+
+ ITensorInfo *ans_info = FunctionType::create_op(sketch, &lhs_info, &rhs_info);
+
+ if(_fuse)
+ {
+ rhs_info_fuse = sketch.create_tensor_info(TensorInfo(shape2, 1, _data_type));
+ ITensorInfo *ans2_info = FunctionType::create_op(sketch, ans_info, &rhs_info_fuse);
+ GpuOutput::create_op(sketch, ans2_info, &dst_info);
+ }
+ else
+ {
+ GpuOutput::create_op(sketch, ans_info, &dst_info);
+ }
+
+ // Configure runtime
+ ClWorkloadRuntime runtime;
+ runtime.configure(sketch);
+
+ // (Important) Allocate auxiliary tensor memory if there are any
+ for(auto &data : runtime.get_auxiliary_tensors())
+ {
+ CLTensor *tensor = std::get<0>(data);
+ TensorInfo info = std::get<1>(data);
+ AuxMemoryInfo aux_mem_req = std::get<2>(data);
+ tensor->allocator()->init(info, aux_mem_req.alignment);
+ tensor->allocator()->allocate(); // Use ACL allocated memory
+ }
+
+ // Construct user tensors
+ TensorType t_lhs{};
+ TensorType t_rhs{};
+ TensorType t_rhs_fuse{};
+ TensorType t_dst{};
+
+ // Initialize user tensors
+ t_lhs.allocator()->init(lhs_info);
+ t_rhs.allocator()->init(rhs_info);
+ t_dst.allocator()->init(dst_info);
+ if(_fuse)
+ {
+ t_rhs_fuse.allocator()->init(rhs_info_fuse);
+ }
+
+ // Allocate and fill user tensors
+ // Instead of using ACL allocator, the user can choose to import memory into the tensors
+ t_lhs.allocator()->allocate();
+ t_rhs.allocator()->allocate();
+ t_dst.allocator()->allocate();
+ if(_fuse)
+ {
+ t_rhs_fuse.allocator()->allocate();
+ }
+
+ fill(AccessorType(t_lhs), 0);
+ fill(AccessorType(t_rhs), 1);
+ if(_fuse)
+ {
+ fill(AccessorType(t_rhs_fuse), 2);
+ }
+
+ // Run runtime
+ if(_fuse)
+ {
+ runtime.run({ &t_lhs, &t_rhs, &t_rhs_fuse, &t_dst });
+ }
+ else
+ {
+ runtime.run({ &t_lhs, &t_rhs, &t_dst });
+ }
+
+ return t_dst;
+ }
+
+ SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2)
+ {
+ // Create reference
+ SimpleTensor<T> ref_lhs{ shape0, _data_type, 1, QuantizationInfo() };
+ SimpleTensor<T> ref_rhs{ shape1, _data_type, 1, QuantizationInfo() };
+ SimpleTensor<T> ref_rhs_fuse{ shape2, _data_type, 1, QuantizationInfo() };
+
+ // Fill reference
+ fill(ref_lhs, 0);
+ fill(ref_rhs, 1);
+ SimpleTensor<T> ref_dst = reference::pixel_wise_multiplication<T, T, T>(ref_lhs,
+ ref_rhs,
+ 1.f,
+ ConvertPolicy::SATURATE,
+ RoundingPolicy::TO_NEAREST_UP,
+ _data_type,
+ QuantizationInfo());
+ if(_fuse)
+ {
+ fill(ref_rhs_fuse, 2);
+ SimpleTensor<T> ref_dst_fuse = reference::pixel_wise_multiplication<T, T, T>(ref_dst,
+ ref_rhs_fuse,
+ 1.f,
+ ConvertPolicy::SATURATE,
+ RoundingPolicy::TO_NEAREST_UP,
+ _data_type,
+ QuantizationInfo());
+ return ref_dst_fuse;
+ }
+ return ref_dst;
+ }
+
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+ DataType _data_type{};
+ bool _is_inplace{ false };
+ bool _fuse{ false };
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DynamicFusionMulOneOpValidationFixture : public DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(const TensorShape &shape0, DataType data_type, bool is_inplace)
+ {
+ DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape0, TensorShape(), data_type, is_inplace);
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DynamicFusionMulBroadcastValidationFixture : public DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type, bool is_inplace)
+ {
+ DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, TensorShape(), data_type, is_inplace);
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DynamicFusionMulTwoOpsValidationFixture : public DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2, DataType data_type, bool is_inplace, bool fuse_two_ops)
+ {
+ DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, shape2, data_type, is_inplace, fuse_two_ops);
+ }
+};
+
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_MULFIXTURE */