Add dynamic tensor support to CpuElementwise

The kernels and operators for binary and unary operations
are now capable of being configured with dynamic shapes and
computing windows at run-time.

Additionally, changing arguments' names is done
for consistency.

Partially Implements: COMPMID-4127

Change-Id: I48e5038692db667dec7cb2b2906fe5683214fe19
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4973
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 19 insertions, 0 deletions

diff --git a/tests/validation/NEON/ElementwiseRsqrtLayer.cpp b/tests/validation/NEON/ElementwiseRsqrtLayer.cpp
index f41500cc0b..1591b76cd7 100644
--- a/tests/validation/NEON/ElementwiseRsqrtLayer.cpp
+++ b/tests/validation/NEON/ElementwiseRsqrtLayer.cpp
@@ -50,6 +50,25 @@ RelativeTolerance<float> tolerance_fp16(0.01f);
 TEST_SUITE(NEON)
 TEST_SUITE(RsqrtLayer)
 
+// Test test cases will execute the function with dynamic-stated shapes
+// Since other elementwise unary operations share the same kernel, this tests are added only here.
+// Also, only FP32 is tested since data type doesn't/shouldn't matter with dynamic shapes.
+TEST_SUITE(DynamicShape)
+TEST_SUITE(FP32)
+
+template <typename T>
+using CpuRsqrtDynamicShapeFixture = RsqrtDynamicShapeValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CpuRsqrtDynamicShapeFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                          DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp32);
+}
+
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // DynamicShape
+
 template <typename T>
 using NERsqrtLayerFixture = RsqrtValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;