COMPMID-617: Add validation methods to ML CL functions.

Adds validation support to:
- CLDirectConvolution
- CLNormalizationLayer
- CLSoftmaxLayer

Change-Id: I9bd1e925e6db057c799169405f82ed21d20b87ee
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/95939
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index 2986369..08d53d5 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -79,6 +79,73 @@
 
 //TODO(COMPMID-415): Configuration tests?
 
+// *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
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+                                                     }),
+               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),
+                                                        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),
+                                                       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),
+                                                       TensorInfo(TensorShape(25U, 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),
+                                                       PadStrideInfo(1, 1, 0, 0),
+                                                      })),
+               framework::dataset::make("Expected", { true, true, true, true, true, true, true, true, true, false })),
+               input_info, weights_info, biases_info, output_info, conv_info, expected)
+{
+    bool is_error = bool(CLDirectConvolutionLayer::validate(&input_info, &weights_info, &biases_info, &output_info, conv_info));
+    ARM_COMPUTE_EXPECT(is_error == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 template <typename T>
 using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
 
diff --git a/tests/validation/CL/NormalizationLayer.cpp b/tests/validation/CL/NormalizationLayer.cpp
index 18f0c37..caf7e2a 100644
--- a/tests/validation/CL/NormalizationLayer.cpp
+++ b/tests/validation/CL/NormalizationLayer.cpp
@@ -67,6 +67,38 @@
 
 //TODO(COMPMID-415): Missing configuration?
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+               framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type input/output
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching shapes
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Even normalization
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Non implemented IN_MAP_2D
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 4), // Mismatching fixed point position
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+                                                     }),
+               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16, 0),
+                                                       TensorInfo(TensorShape(27U, 11U, 2U), 1, DataType::F32, 0),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+                                                     })),
+               framework::dataset::make("NormInfo",  { NormalizationLayerInfo(NormType::IN_MAP_1D, 5),
+                                                       NormalizationLayerInfo(NormType::IN_MAP_1D, 5),
+                                                       NormalizationLayerInfo(NormType::IN_MAP_1D, 4),
+                                                       NormalizationLayerInfo(NormType::IN_MAP_2D, 5),
+                                                       NormalizationLayerInfo(NormType::IN_MAP_1D, 5),
+                                                       NormalizationLayerInfo(NormType::IN_MAP_1D, 5),
+                                                      })),
+               framework::dataset::make("Expected", { true, true, true, true, true, false })),
+               input_info, output_info, norm_info, expected)
+{
+    ARM_COMPUTE_EXPECT(bool(CLNormalizationLayer::validate(&input_info, &output_info, norm_info)) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 template <typename T>
 using CLNormalizationLayerFixture = NormalizationValidationFixture<CLTensor, CLAccessor, CLNormalizationLayer, T>;
 
diff --git a/tests/validation/CL/SoftmaxLayer.cpp b/tests/validation/CL/SoftmaxLayer.cpp
index a06aa7b..b935ef5 100644
--- a/tests/validation/CL/SoftmaxLayer.cpp
+++ b/tests/validation/CL/SoftmaxLayer.cpp
@@ -110,6 +110,37 @@
     validate(dst.info()->padding(), padding_dst);
 }
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
+               framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),    // Mismatching shapes
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8, // Invalid output quantization info
+                                                                  QuantizationInfo(1.f/256, 12)),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8,
+                                                                  QuantizationInfo(1.f/256, 12)),
+                                                      }),
+               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
+                                                       TensorInfo(TensorShape(27U, 11U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8,
+                                                                  QuantizationInfo(1.f/256, 12)),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8,
+                                                                  QuantizationInfo(1.f/256, 0)),
+                                                     })),
+               framework::dataset::make("Expected", { true, true, true, true, false, false, false })),
+               input_info, output_info, expected)
+{
+    ARM_COMPUTE_EXPECT(bool(CLSoftmaxLayer::validate(&input_info, &output_info)) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 template <typename T>
 using CLSoftmaxLayerFixture = SoftmaxValidationFixture<CLTensor, CLAccessor, CLSoftmaxLayer, T>;