Add Resize/Scale operator to Dynamic Fusion interface

Resolves: COMPMID-5521

Change-Id: Id38a4ce18f9ea8805a151acb064e72795535d1a0
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8859
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

3 files changed, 808 insertions, 3 deletions

diff --git a/tests/datasets/ScaleValidationDataset.h b/tests/datasets/ScaleValidationDataset.h
index c6987c0908..8987c3a1c1 100644
--- a/tests/datasets/ScaleValidationDataset.h
+++ b/tests/datasets/ScaleValidationDataset.h
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_SCALE_VALIDATION_DATASET
-#define ARM_COMPUTE_TEST_SCALE_VALIDATION_DATASET
+#ifndef TESTS_DATASETS_SCALEVALIDATIONDATASET
+#define TESTS_DATASETS_SCALEVALIDATIONDATASET
 
 #include "arm_compute/core/Types.h"
 #include "tests/datasets/BorderModeDataset.h"
@@ -173,6 +173,11 @@ framework::dataset::make("AlignCorners", { true }));
                     datasets::BorderModes()),                   \
             samping_policy_set)
 
+#define ASSEMBLE_DATASET_DYNAMIC_FUSION(shape, samping_policy_set)                                  \
+    combine(combine(combine((shape), framework::dataset::make("DataLayout", { DataLayout::NHWC })), \
+                    ScaleInterpolationPolicySet),                                                   \
+            samping_policy_set)
+
 #define ASSEMBLE_S8_DATASET(shape, samping_policy_set)                                                           \
     combine(combine(combine(combine((shape), framework::dataset::make("DataLayout", DataLayout::NHWC)),          \
                             framework::dataset::make("InterpolationPolicy", { InterpolationPolicy::BILINEAR })), \
@@ -194,6 +199,13 @@ framework::dataset::make("AlignCorners", { true }));
                     datasets::BorderModes()),                                         \
             sampling_policy_set)
 
+#define ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(shape, sampling_policy_set, quantization_info_set) \
+    combine(combine(combine(combine(shape,                                                           \
+                                    quantization_info_set),                                          \
+                            framework::dataset::make("DataLayout", { DataLayout::NHWC })),           \
+                    ScaleInterpolationPolicySet),                                                    \
+            sampling_policy_set)
+
 /** Generating dataset for quantized data tyeps with the given shapes */
 #define ASSEMBLE_DIFFERENTLY_QUANTIZED_DATASET(shape, sampling_policy_set, input_quant_info_set, output_quant_info_set) \
     combine(combine(combine(combine(combine(combine(shape,                                                              \
@@ -207,4 +219,4 @@ framework::dataset::make("AlignCorners", { true }));
 } // namespace datasets
 } // namespace test
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_SCALE_VALIDATION_DATASET */
+#endif /* TESTS_DATASETS_SCALEVALIDATIONDATASET */
diff --git a/tests/validation/dynamic_fusion/gpu/cl/Resize.cpp b/tests/validation/dynamic_fusion/gpu/cl/Resize.cpp
new file mode 100644
index 0000000000..17c341b803
--- /dev/null
+++ b/tests/validation/dynamic_fusion/gpu/cl/Resize.cpp
@@ -0,0 +1,529 @@
+/*
+* Copyright (c) 2022 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/operators/GpuResize.h"
+
+#include "tests/CL/CLAccessor.h"
+#include "tests/datasets/ScaleValidationDataset.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/framework/Macros.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/dynamic_fusion/operators/ResizeFixture.h"
+
+using namespace arm_compute::experimental::dynamic_fusion;
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+using datasets::ScaleShapesBaseDataSet;
+using datasets::ScaleInterpolationPolicySet;
+using datasets::ScaleSamplingPolicySet;
+using datasets::ScaleAlignCornersSamplingPolicySet;
+
+/** We consider vector size in byte 16 since the maximum size of
+ * a vector used by @ref CLScaleKernel is currently 16-byte (float4).
+ */
+constexpr uint32_t vector_byte = 16;
+
+template <typename T>
+constexpr uint32_t num_elements_per_vector()
+{
+    return vector_byte / sizeof(T);
+}
+
+/** Quantization information data set */
+const auto QuantizationInfoSet = framework::dataset::make("QuantizationInfo",
+{
+    QuantizationInfo(0.5f, -1),
+});
+
+/** Tolerance */
+constexpr AbsoluteTolerance<uint8_t> tolerance_q8(1);
+constexpr AbsoluteTolerance<int8_t>  tolerance_qs8(1);
+constexpr AbsoluteTolerance<int16_t> tolerance_s16(1);
+constexpr float                      tolerance_f32_absolute(0.001f);
+
+RelativeTolerance<float> tolerance_f32(0.05);
+constexpr float          abs_tolerance_f16(0.1f);
+RelativeTolerance<half>  tolerance_f16(half(0.1));
+
+constexpr float tolerance_num_f32(0.01f);
+
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(DYNAMIC_FUSION)
+TEST_SUITE(RESIZE)
+
+TEST_SUITE(Validate)
+
+const auto default_input_shape  = TensorShape{ 2, 3, 3, 2 };
+const auto default_output_shape = TensorShape{ 4, 6, 3, 2 };
+
+constexpr auto default_data_type            = DataType::U8;
+constexpr auto default_data_layout          = DataLayout::NHWC;
+constexpr auto default_interpolation_policy = InterpolationPolicy::NEAREST_NEIGHBOR;
+constexpr bool default_use_padding          = false;
+
+TEST_CASE(NullPtr, framework::DatasetMode::ALL)
+{
+    const TensorInfo input_info  = TensorInfo{ default_input_shape, 1, default_data_type, default_data_layout };
+    const TensorInfo output_info = TensorInfo{ default_output_shape, 1, default_data_type, default_data_layout };
+
+    CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+    GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+    GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+    const TensorInfo sketch_input_info  = sketch.create_tensor_info(input_info);
+    const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+    // nullptr is given as input
+    Status status = GpuResize::validate_op(sketch, nullptr, &sketch_output_info, ResizeAttributes());
+    ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+
+    // nullptr is given as output
+    status = GpuResize::validate_op(sketch, &sketch_input_info, nullptr, ResizeAttributes());
+    ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+}
+
+TEST_CASE(SupportDataType, framework::DatasetMode::ALL)
+{
+    const std::map<DataType, bool> supported_data_types =
+    {
+        { DataType::U8, true },
+        { DataType::S8, false },
+        { DataType::QSYMM8, false },
+        { DataType::QASYMM8, true },
+        { DataType::QASYMM8_SIGNED, true },
+        { DataType::QSYMM8_PER_CHANNEL, false },
+        { DataType::U16, false },
+        { DataType::S16, true },
+        { DataType::QSYMM16, false },
+        { DataType::QASYMM16, false },
+        { DataType::U32, false },
+        { DataType::S32, false },
+        { DataType::U64, false },
+        { DataType::S64, false },
+        { DataType::BFLOAT16, false },
+        { DataType::F16, true },
+        { DataType::F32, true },
+        { DataType::F64, false },
+        { DataType::SIZET, false },
+    };
+
+    for(auto &kv : supported_data_types)
+    {
+        const TensorInfo input_info  = TensorInfo{ default_input_shape, 1, kv.first, default_data_layout };
+        const TensorInfo output_info = TensorInfo{ default_output_shape, 1, kv.first, default_data_layout };
+
+        CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+        GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+        GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+        const TensorInfo sketch_input_info  = sketch.create_tensor_info(input_info);
+        const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+        // nullptr is given as input
+        Status status = GpuResize::validate_op(sketch, &sketch_input_info, &sketch_output_info, ResizeAttributes());
+        ARM_COMPUTE_EXPECT(bool(status) == kv.second, framework::LogLevel::ERRORS);
+    }
+}
+
+TEST_CASE(MismatchingDataType, framework::DatasetMode::ALL)
+{
+    constexpr DataType non_default_data_type = DataType::F32;
+
+    const TensorInfo input_info  = TensorInfo{ default_input_shape, 1, default_data_type, default_data_layout };
+    const TensorInfo output_info = TensorInfo{ default_output_shape, 1, non_default_data_type, default_data_layout };
+
+    CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+    GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+    GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+    const TensorInfo sketch_input_info  = sketch.create_tensor_info(input_info);
+    const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+    Status status = GpuResize::validate_op(sketch, &sketch_input_info, &sketch_output_info, ResizeAttributes());
+    ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+}
+
+TEST_CASE(AlignedCornerNotSupported, framework::DatasetMode::ALL)
+{
+    // Aligned corners require sampling policy to be TOP_LEFT.
+    constexpr InterpolationPolicy interpolation_policy = InterpolationPolicy::BILINEAR;
+    constexpr bool                align_corners        = true;
+    constexpr SamplingPolicy      sampling_policy      = SamplingPolicy::CENTER;
+
+    const TensorInfo input_info  = TensorInfo{ default_input_shape, 1, default_data_type, default_data_layout };
+    const TensorInfo output_info = TensorInfo{ default_output_shape, 1, default_data_type, default_data_layout };
+
+    CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+    GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+    GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+    const TensorInfo sketch_input_info  = sketch.create_tensor_info(input_info);
+    const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+    ResizeAttributes attributes{};
+    attributes.interpolation_policy(interpolation_policy)
+    .sampling_policy(sampling_policy)
+    .align_corners(align_corners);
+
+    Status status = GpuResize::validate_op(sketch, &sketch_input_info, &sketch_output_info, attributes);
+    ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+}
+
+TEST_CASE(UnsupportedInterpolationPolicy, framework::DatasetMode::ALL)
+{
+    const TensorInfo input_info           = TensorInfo{ TensorShape(28U, 33U, 2U), 1, DataType::F32, default_data_layout };
+    const TensorInfo output_info          = TensorInfo{ TensorShape(26U, 21U, 2U), 1, DataType::F32, default_data_layout };
+    constexpr auto   interpolation_policy = InterpolationPolicy::AREA;
+
+    CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+    GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+    GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+    const TensorInfo sketch_input_info  = sketch.create_tensor_info(input_info);
+    const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+    ResizeAttributes attributes{};
+    attributes.interpolation_policy(interpolation_policy);
+
+    Status status = GpuResize::validate_op(sketch, &sketch_input_info, &sketch_output_info, attributes);
+    ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+}
+
+TEST_CASE(UnsupportedLayout, framework::DatasetMode::ALL)
+{
+    const TensorInfo input_info           = TensorInfo{ default_input_shape, 1, default_data_type, DataLayout::NCHW };
+    const TensorInfo output_info          = TensorInfo{ default_output_shape, 1, default_data_type, DataLayout::NCHW };
+    constexpr auto   interpolation_policy = InterpolationPolicy::BILINEAR;
+
+    CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+    GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+    GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+    const TensorInfo sketch_input_info  = sketch.create_tensor_info(input_info);
+    const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+    ResizeAttributes attributes{};
+    attributes.interpolation_policy(interpolation_policy);
+
+    Status status = GpuResize::validate_op(sketch, &sketch_input_info, &sketch_output_info, attributes);
+    ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
+}
+
+TEST_SUITE_END() // Validate
+
+template <typename T>
+using DynamicFusionResizeFixture = DynamicFusionResizeValidationFixture<CLTensor, CLAccessor, GpuResize, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+
+const auto f32_shape = combine((SCALE_PRECOMMIT_SHAPE_DATASET(num_elements_per_vector<float>())), framework::dataset::make("DataType", DataType::F32));
+
+FIXTURE_DATA_TEST_CASE(Run, DynamicFusionResizeFixture<float>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(f32_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f32, tolerance_num_f32, tolerance_f32_absolute);
+}
+
+FIXTURE_DATA_TEST_CASE(RunAlignCorners, DynamicFusionResizeFixture<float>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(f32_shape, ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f32, tolerance_num_f32, tolerance_f32_absolute);
+}
+const auto f32_nightly_shape = combine((SCALE_NIGHTLY_SHAPE_DATASET(num_elements_per_vector<float>())), framework::dataset::make("DataType", DataType::F32));
+FIXTURE_DATA_TEST_CASE(RunNightly, DynamicFusionResizeFixture<float>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(f32_nightly_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f32, tolerance_num_f32, tolerance_f32_absolute);
+}
+FIXTURE_DATA_TEST_CASE(RunNightlyAlignCorners, DynamicFusionResizeFixture<float>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(f32_nightly_shape,
+                       ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f32, tolerance_num_f32, tolerance_f32_absolute);
+}
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(FP16)
+const auto f16_shape = combine((SCALE_PRECOMMIT_SHAPE_DATASET(num_elements_per_vector<half>())), framework::dataset::make("DataType", DataType::F16));
+FIXTURE_DATA_TEST_CASE(Run, DynamicFusionResizeFixture<half>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(f16_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f16, 0.0f, abs_tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunAlignCorners, DynamicFusionResizeFixture<half>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(f16_shape, ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f16, 0.0f, abs_tolerance_f16);
+}
+const auto f16_nightly_shape = combine((SCALE_NIGHTLY_SHAPE_DATASET(num_elements_per_vector<half>())), framework::dataset::make("DataType", DataType::F16));
+FIXTURE_DATA_TEST_CASE(RunNightly, DynamicFusionResizeFixture<half>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(f16_nightly_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f16, 0.0f, abs_tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunNightlyAlignCorners, DynamicFusionResizeFixture<half>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(f16_nightly_shape,
+                       ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_f16, 0.0f, abs_tolerance_f16);
+}
+TEST_SUITE_END() // FP16
+TEST_SUITE_END() // Float
+
+TEST_SUITE(Integer)
+TEST_SUITE(U8)
+const auto u8_shape = combine((SCALE_PRECOMMIT_SHAPE_DATASET(num_elements_per_vector<uint8_t>())), framework::dataset::make("DataType", DataType::U8));
+FIXTURE_DATA_TEST_CASE(Run, DynamicFusionResizeFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(u8_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+FIXTURE_DATA_TEST_CASE(RunAlignCorners, DynamicFusionResizeFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(u8_shape, ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+const auto u8_nightly_shape = combine((SCALE_NIGHTLY_SHAPE_DATASET(num_elements_per_vector<uint8_t>())), framework::dataset::make("DataType", DataType::U8));
+FIXTURE_DATA_TEST_CASE(RunNightly, DynamicFusionResizeFixture<uint8_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(u8_nightly_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+FIXTURE_DATA_TEST_CASE(RunNightlyAlignCorners, DynamicFusionResizeFixture<uint8_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(u8_nightly_shape,
+                       ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+TEST_SUITE_END() // U8
+
+TEST_SUITE(S16)
+const auto s16_shape = combine((SCALE_PRECOMMIT_SHAPE_DATASET(num_elements_per_vector<int16_t>())), framework::dataset::make("DataType", DataType::S16));
+FIXTURE_DATA_TEST_CASE(Run, DynamicFusionResizeFixture<int16_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(s16_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_s16);
+}
+FIXTURE_DATA_TEST_CASE(RunAlignCorners, DynamicFusionResizeFixture<int16_t>, framework::DatasetMode::ALL, ASSEMBLE_DATASET_DYNAMIC_FUSION(s16_shape, ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_s16);
+}
+const auto s16_nightly_shape = combine((SCALE_NIGHTLY_SHAPE_DATASET(num_elements_per_vector<int16_t>())), framework::dataset::make("DataType", DataType::S16));
+FIXTURE_DATA_TEST_CASE(RunNightly, DynamicFusionResizeFixture<int16_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(s16_nightly_shape, ScaleSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_s16);
+}
+FIXTURE_DATA_TEST_CASE(RunNightlyAlignCorners, DynamicFusionResizeFixture<int16_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_DATASET_DYNAMIC_FUSION(s16_nightly_shape,
+                       ScaleAlignCornersSamplingPolicySet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_s16);
+}
+TEST_SUITE_END() // S16
+TEST_SUITE_END() // Integer
+
+template <typename T>
+using DynamicFusionResizeQuantizedFixture = DynamicFusionResizeQuantizedValidationFixture<CLTensor, CLAccessor, GpuResize, T>;
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+const auto qasymm8_shape = combine((SCALE_PRECOMMIT_SHAPE_DATASET(num_elements_per_vector<uint8_t>())), framework::dataset::make("DataType", DataType::QASYMM8));
+FIXTURE_DATA_TEST_CASE(Run, DynamicFusionResizeQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_shape, ScaleSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+FIXTURE_DATA_TEST_CASE(RunAlignCorners, DynamicFusionResizeQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_shape,
+                       ScaleAlignCornersSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+const auto qasymm8_nightly_shape = combine((SCALE_NIGHTLY_SHAPE_DATASET(num_elements_per_vector<uint8_t>())), framework::dataset::make("DataType", DataType::QASYMM8));
+FIXTURE_DATA_TEST_CASE(RunNightly, DynamicFusionResizeQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_nightly_shape,
+                       ScaleSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+FIXTURE_DATA_TEST_CASE(RunNightlyAlignCorners, DynamicFusionResizeQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_nightly_shape,
+                       ScaleAlignCornersSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_q8);
+}
+TEST_SUITE_END() // QASYMM8
+
+TEST_SUITE(QASYMM8_SIGNED)
+const auto qasymm8_signed_shape = combine((SCALE_PRECOMMIT_SHAPE_DATASET(num_elements_per_vector<int8_t>())), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED));
+FIXTURE_DATA_TEST_CASE(Run, DynamicFusionResizeQuantizedFixture<int8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_signed_shape, ScaleSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_qs8);
+}
+FIXTURE_DATA_TEST_CASE(RunAlignCorners, DynamicFusionResizeQuantizedFixture<int8_t>, framework::DatasetMode::ALL, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_signed_shape,
+                       ScaleAlignCornersSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_qs8);
+}
+const auto qasymm8_signed_nightly_shape = combine((SCALE_NIGHTLY_SHAPE_DATASET(num_elements_per_vector<int8_t>())), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED));
+FIXTURE_DATA_TEST_CASE(RunNightly, DynamicFusionResizeQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_signed_nightly_shape,
+                       ScaleSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_qs8);
+}
+FIXTURE_DATA_TEST_CASE(RunNightlyAlignCorners, DynamicFusionResizeQuantizedFixture<int8_t>, framework::DatasetMode::NIGHTLY, ASSEMBLE_QUANTIZED_DATASET_DYNAMIC_FUSION(qasymm8_signed_nightly_shape,
+                       ScaleAlignCornersSamplingPolicySet,
+                       QuantizationInfoSet))
+{
+    //Create valid region
+    TensorInfo        src_info(_shape, 1, _data_type);
+    const ValidRegion valid_region = calculate_valid_region_scale(src_info, _reference.shape(), _interpolation_policy, _sampling_policy, false);
+
+    // Validate output
+    validate(CLAccessor(_target), _reference, valid_region, tolerance_qs8);
+}
+TEST_SUITE_END() // QASYMM8_SIGNED
+
+TEST_SUITE_END() // Quantized
+
+TEST_SUITE_END() // RESIZE
+TEST_SUITE_END() // DYNAMIC_FUSION
+TEST_SUITE_END() // CL
+
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/dynamic_fusion/operators/ResizeFixture.h b/tests/validation/fixtures/dynamic_fusion/operators/ResizeFixture.h
new file mode 100644
index 0000000000..5cdf52e62b
--- /dev/null
+++ b/tests/validation/fixtures/dynamic_fusion/operators/ResizeFixture.h
@@ -0,0 +1,264 @@
+/*
+* Copyright (c) 2022 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_RESIZEFIXTURE
+#define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_RESIZEFIXTURE
+
+#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/attributes/ResizeAttributes.h"
+#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/SimpleTensor.h"
+#include "tests/framework/Fixture.h"
+#include "tests/framework/Macros.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/reference/Permute.h"
+#include "tests/validation/reference/Scale.h"
+
+using namespace arm_compute::experimental::dynamic_fusion;
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DynamicFusionResizeGenericValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout,
+               InterpolationPolicy interpolation_policy, SamplingPolicy sampling_policy,
+               bool align_corners, QuantizationInfo output_quantization_info)
+    {
+        _shape                    = shape;
+        _interpolation_policy     = interpolation_policy;
+        _sampling_policy          = sampling_policy;
+        _data_type                = data_type;
+        _input_quantization_info  = quantization_info;
+        _output_quantization_info = output_quantization_info;
+        _align_corners            = align_corners;
+        _data_layout              = data_layout;
+
+        ARM_COMPUTE_ERROR_ON(data_layout != DataLayout::NHWC); // Dynamic fusion resize supports only NHWC layout
+
+        generate_scale(shape);
+
+        std::mt19937                            generator(library->seed());
+        std::uniform_int_distribution<uint32_t> distribution_u8(0, 255);
+
+        _target    = compute_target(shape);
+        _reference = compute_reference(shape);
+    }
+
+protected:
+    void generate_scale(const TensorShape &shape)
+    {
+        static constexpr float _min_scale{ 0.25f };
+        static constexpr float _max_scale{ 3.f };
+
+        constexpr float max_width{ 8192.0f };
+        constexpr float max_height{ 6384.0f };
+        constexpr float min_width{ 1.f };
+        constexpr float min_height{ 1.f };
+
+        std::mt19937                          generator(library->seed());
+        std::uniform_real_distribution<float> distribution_float(_min_scale, _max_scale);
+
+        auto generate = [&](size_t input_size, float min_output, float max_output) -> int
+        {
+            const float generated_scale = distribution_float(generator);
+            const int   output_size     = static_cast<int>(utility::clamp(static_cast<float>(input_size) * generated_scale, min_output, max_output));
+            return output_size;
+        };
+
+        // Input shape is always given in NCHW layout. NHWC is dealt by permute in compute_target()
+        const int idx_width  = get_data_layout_dimension_index(DataLayout::NCHW, DataLayoutDimension::WIDTH);
+        const int idx_height = get_data_layout_dimension_index(DataLayout::NCHW, DataLayoutDimension::HEIGHT);
+
+        _output_width  = generate(shape[idx_width], min_width, max_width);
+        _output_height = generate(shape[idx_height], min_height, max_height);
+    }
+
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        if(tensor.data_type() == DataType::F32)
+        {
+            std::uniform_real_distribution<float> distribution(-5.0f, 5.0f);
+            library->fill(tensor, distribution, 0);
+        }
+        else if(tensor.data_type() == DataType::F16)
+        {
+            arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -5.0f, 5.0f };
+            library->fill(tensor, distribution, 0);
+        }
+        else if(is_data_type_quantized(tensor.data_type()))
+        {
+            std::uniform_int_distribution<> distribution(0, 100);
+            library->fill(tensor, distribution, 0);
+        }
+        else
+        {
+            library->fill_tensor_uniform(tensor, 0);
+        }
+    }
+
+    TensorType compute_target(TensorShape shape)
+    {
+        // Our test shapes are assumed in NCHW data layout, thus the permutation
+        permute(shape, PermutationVector(2U, 0U, 1U));
+
+        // Create a new workload sketch
+        CLCompileContext   cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+        GpuWorkloadContext gpu_ctx        = GpuWorkloadContext{ &cl_compile_ctx };
+        GpuWorkloadSketch  sketch{ &gpu_ctx };
+
+        // Create sketch tensors
+        TensorInfo src_info = sketch.create_tensor_info(TensorInfo(shape, 1, _data_type, _data_layout));
+        src_info.set_quantization_info(_input_quantization_info);
+        TensorInfo dst_info = sketch.create_tensor_info();
+
+        ResizeAttributes attributes;
+        attributes.align_corners(_align_corners).sampling_policy(_sampling_policy).interpolation_policy(_interpolation_policy).output_width(_output_width).output_height(_output_height);
+
+        TensorInfo scale_result_info = sketch.create_tensor_info();
+
+        FunctionType::create_op(sketch, &src_info, &scale_result_info, attributes);
+        GpuOutput::create_op(sketch, &scale_result_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())
+        {
+            auto       tensor      = data.first;
+            const auto aux_mem_req = data.second;
+            tensor->allocator()->init(*data.first->info(), aux_mem_req.alignment);
+            tensor->allocator()->allocate();
+        }
+
+        // Construct user tensors
+        TensorType t_src{};
+        TensorType t_dst{};
+
+        // Initialize user tensors
+        t_src.allocator()->init(src_info);
+        t_dst.allocator()->init(dst_info);
+
+        // Allocate and fill user tensors
+        t_src.allocator()->allocate();
+        t_dst.allocator()->allocate();
+
+        fill(AccessorType(t_src));
+
+        // Run runtime
+        runtime.run({ &t_src, &t_dst });
+
+        return t_dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, _data_type, 1, _input_quantization_info };
+
+        // Reference code is NCHW, so the input shapes are NCHW
+        const int idx_width  = get_data_layout_dimension_index(DataLayout::NCHW, DataLayoutDimension::WIDTH);
+        const int idx_height = get_data_layout_dimension_index(DataLayout::NCHW, DataLayoutDimension::HEIGHT);
+
+        const float scale_x = static_cast<float>(_output_width) / shape[idx_width];
+        const float scale_y = static_cast<float>(_output_height) / shape[idx_height];
+
+        // Fill reference
+        fill(src);
+
+        return reference::scale<T>(src, scale_x, scale_y, _interpolation_policy,
+                                   BorderMode::REPLICATE, static_cast<T>(0), _sampling_policy, /* ceil_policy_scale */ false,
+                                   _align_corners, _output_quantization_info);
+    }
+
+    TensorType          _target{};
+    SimpleTensor<T>     _reference{};
+    TensorShape         _shape{};
+    InterpolationPolicy _interpolation_policy{};
+    SamplingPolicy      _sampling_policy{};
+    DataType            _data_type{};
+    DataLayout          _data_layout{};
+    QuantizationInfo    _input_quantization_info{};
+    QuantizationInfo    _output_quantization_info{};
+    bool                _align_corners{ false };
+    int                 _output_width{ 0 };
+    int                 _output_height{ 0 };
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DynamicFusionResizeValidationFixture : public DynamicFusionResizeGenericValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, DataLayout data_layout, InterpolationPolicy policy, SamplingPolicy sampling_policy, bool align_corners)
+    {
+        DynamicFusionResizeGenericValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape,
+                                                                                                      data_type,
+                                                                                                      QuantizationInfo(),
+                                                                                                      data_layout,
+                                                                                                      policy,
+                                                                                                      sampling_policy,
+                                                                                                      align_corners,
+                                                                                                      QuantizationInfo());
+    }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
+class DynamicFusionResizeQuantizedValidationFixture : public DynamicFusionResizeGenericValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout, InterpolationPolicy policy, SamplingPolicy sampling_policy,
+               bool align_corners)
+    {
+        DynamicFusionResizeGenericValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape,
+                                                                                                      data_type,
+                                                                                                      quantization_info,
+                                                                                                      data_layout,
+                                                                                                      policy,
+                                                                                                      sampling_policy,
+                                                                                                      align_corners,
+                                                                                                      quantization_info);
+    }
+};
+
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+
+#endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_RESIZEFIXTURE */