From 668ccdcfb81bfab3a2d44cd1ddd956e83a2dfb09 Mon Sep 17 00:00:00 2001
From: Sang-Hoon Park <sang-hoon.park@arm.com>
Date: Wed, 3 Feb 2021 10:32:59 +0000
Subject: 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>
---
 tests/validation/NEON/ElementwiseDivision.cpp   | 28 +++++++++++++++++++++++++
 tests/validation/NEON/ElementwiseRsqrtLayer.cpp | 19 +++++++++++++++++
 2 files changed, 47 insertions(+)

(limited to 'tests/validation/NEON')

diff --git a/tests/validation/NEON/ElementwiseDivision.cpp b/tests/validation/NEON/ElementwiseDivision.cpp
index 3656560281..8abccb2ed6 100644
--- a/tests/validation/NEON/ElementwiseDivision.cpp
+++ b/tests/validation/NEON/ElementwiseDivision.cpp
@@ -93,6 +93,34 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
 // clang-format on
 // *INDENT-ON*
 
+// Test test cases will execute the function with dynamic-stated shapes
+// Since other elementwise 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)
+template <typename T>
+using CpuElementwiseDivisionDynamicShapeFixture = ArithmeticDivisionDynamicShapeValidationFixture<Tensor, Accessor, NEElementwiseDivision, T>;
+
+template <typename T>
+using CpuElementwiseDivisionBroadcastDynamicShapeFixture = ArithmeticDivisionBroadcastDynamicShapeValidationFixture<Tensor, Accessor, NEElementwiseDivision, T>;
+
+TEST_SUITE(F32)
+
+FIXTURE_DATA_TEST_CASE(RunSmall, CpuElementwiseDivisionDynamicShapeFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseDivisionFP32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CpuElementwiseDivisionBroadcastDynamicShapeFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapesBroadcast(),
+                       ElementwiseDivisionFP32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+
+TEST_SUITE_END() // F32
+TEST_SUITE_END() // DynamicShape
+
 TEST_SUITE(Float)
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 TEST_SUITE(F16)
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>;
 
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