COMPMID-617 Add validation methods to Kernels

- NEActivationLayer
- NESoftmax
- NEDirectConvolutionLayer
- NENormalizationLayer
- NEPoolingLayer

Change-Id: Ib279f1c1b7f9247679b0d6593aed7393da8fe87b
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111335
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp
index 52e2b2c..cd23ce4 100644
--- a/tests/validation/NEON/DirectConvolutionLayer.cpp
+++ b/tests/validation/NEON/DirectConvolutionLayer.cpp
@@ -91,6 +91,68 @@
 TEST_SUITE(NEON)
 TEST_SUITE(DirectConvolutionLayer)
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
+        framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching input feature maps
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Unsupported kernel width
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Non-rectangular weights dimensions
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid weights dimensions
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid stride
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid biases size
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid biases dimensions
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid output size
+                                              }),
+        framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16, 0),
+                                                 TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(9U, 9U, 2U, 4U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(3U, 3U, 2U, 4U, 3U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0),
+                                                 TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0),
+                                              })),
+        framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(3U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U, 2U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+                                              })),
+        framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, 0),
+                                                TensorInfo(TensorShape(26U, 11U, 4U), 1, DataType::F32, 0),
+                                              })),
+        framework::dataset::make("ConvInfo",  { PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(3, 3, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                                PadStrideInfo(1, 1, 0, 0),
+                                               })),
+        framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false })),
+        input_info, weights_info, biases_info, output_info, conv_info, expected)
+{
+        bool is_valid = bool(NEDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info));
+        ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 //TODO(COMPMID-415): Configuration tests?
 
 template <typename T>