Fix CL DirectConvolutionLayer validate tests

* Add missing activation infos
* Remove faulty test "Shrink window"
* Split the tests based on data layout
* Fix ClDirectConv2dKernel::validate logic
  Fused activation in NCHW is not supported at all

Resolves: COMPMID-5801

Change-Id: I64dfbd24b77bb02fb4a88b73d5ef84676d85b4fd
Signed-off-by: SiCong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8899
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
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, 103 insertions, 35 deletions

diff --git a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp
index b66163c805..5f882e3a28 100644
--- a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp
+++ b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp
@@ -73,7 +73,7 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, co
         ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 1) && std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported for 1x1 convolution.");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 3 || weights->dimension(width_idx) == 5 || weights->dimension(width_idx) == 9) && std::get<0>(conv_info.stride()) > 2,
                                         "Strides larger than 2 not supported for 3x3, 5x5, 9x9 convolution.");
-        ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_data_type_float(src->data_type()) && act_info.enabled(), "Activation supported only for floating point and NHWC.");
+        ARM_COMPUTE_RETURN_ERROR_ON_MSG(act_info.enabled(), "Fused activation is not supported for NCHW layout");
 
         if(is_data_type_quantized(src->data_type()))
         {
@@ -89,6 +89,7 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, co
 
     if(data_layout == DataLayout::NHWC)
     {
+        ARM_COMPUTE_RETURN_ERROR_ON_MSG(act_info.enabled() && !is_data_type_float(src->data_type()), "Fused activation in NHWC is only supported for floating point.");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.m0 <= 0 || desc.m0 > 8, "M0 can only be greater than 0 and less than or equal to 8");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.n0 != 1 && desc.n0 != 2 && desc.n0 != 3 && desc.n0 != 4 && desc.n0 != 8 && desc.n0 != 16,
                                         "N0 can only be: 1, 2, 3, 4, 8, and 16");
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index f026bfe0b0..512c2cab97 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2022 Arm Limited.
+ * Copyright (c) 2017-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -185,52 +185,36 @@ TEST_CASE(NonSquareKernel, framework::DatasetMode::PRECOMMIT)
 // *INDENT-OFF*
 // clang-format off
 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
-               framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type input/weights
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching input feature maps
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported kernel width
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non-rectangular weights dimensions
+               framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching data type input/weights
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching input feature maps
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights dimensions
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid stride
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases size
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases dimensions
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases size
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases dimensions
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid output size
-                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
                                                        TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32),
                                                      }),
                framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16),
                                                         TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(11U, 11U, 2U, 4U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(3U, 3U, 2U, 4U, 3U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32),
                                                      })),
                framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(3U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(4U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(4U), 1, DataType::F32),
                                                      })),
                framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(26U, 11U, 4U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
                                                      })),
                framework::dataset::make("ConvInfo",  { PadStrideInfo(1, 1, 0, 0),
@@ -238,23 +222,27 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
                                                        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),
                                                        PadStrideInfo(1, 1, 0, 0),
                                                       })),
                        framework::dataset::make("ActivationInfo",
 {
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
 })),
-               framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true })),
+               framework::dataset::make("Expected", { false, false, false, false, false, false, true })),
                input_info, weights_info, biases_info, output_info, conv_info, act_info, expected)
 {
     bool is_valid = bool(CLDirectConvolutionLayer::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, act_info));
     ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
 }
+// clang-format on
+// *INDENT-ON*
 
 template <typename T>
 using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
@@ -270,6 +258,46 @@ template <typename T>
 using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
 
 TEST_SUITE(NHWC)
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
+               framework::dataset::make("InputInfo", {
+                                                       TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Arbitrary weight sizes for NHWC are supported
+                                                       TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Non-rectangular weights dimensions for NHWC are supported
+                                                       TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Strides > 2 for any kernel sizes for NHWC are supported
+                                                     }),
+               framework::dataset::make("WeightsInfo",{
+                                                        TensorInfo(TensorShape(2U, 13U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC),
+                                                        TensorInfo(TensorShape(2U, 5U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+                                                        TensorInfo(TensorShape(2U, 3U, 3U, 4U), 1, DataType::F32, DataLayout::NHWC),
+                                                     })),
+               framework::dataset::make("BiasesInfo",{
+                                                       TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+                                                       TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+                                                       TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+                                                     })),
+               framework::dataset::make("OutputInfo",{
+                                                       TensorInfo(TensorShape(4U, 15U, 1U), 1, DataType::F32, DataLayout::NHWC),
+                                                       TensorInfo(TensorShape(4U, 23U, 11U), 1, DataType::F32, DataLayout::NHWC),
+                                                       TensorInfo(TensorShape(4U, 9U, 4U), 1, DataType::F32, DataLayout::NHWC),
+                                                     })),
+               framework::dataset::make("ConvInfo",  {
+                                                       PadStrideInfo(1, 1, 0, 0),
+                                                       PadStrideInfo(1, 1, 0, 0),
+                                                       PadStrideInfo(3, 3, 0, 0),
+                                                      })),
+                       framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+})),
+               framework::dataset::make("Expected", { true, true, true })),
+               input_info, weights_info, biases_info, output_info, conv_info, act_info, expected)
+{
+    bool is_valid = bool(CLDirectConvolutionLayer::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, act_info));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
 TEST_SUITE(FP16)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
                combine(combine(combine(zip(zip(zip(zip(zip(zip(
@@ -479,9 +507,48 @@ TEST_SUITE_END() // QASYMM8_SIGNED
 TEST_SUITE_END() // Quantized
 TEST_SUITE_END() // NHWC
 
+TEST_SUITE(NCHW)
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
+               framework::dataset::make("InputInfo", {
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Unsupported kernel width
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW), // Non-rectangular weights dimensions are unsupported
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, DataLayout::NCHW)  // Unsupported stride
+                                                     }),
+               framework::dataset::make("WeightsInfo",{
+                                                        TensorInfo(TensorShape(11U, 11U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW),
+                                                        TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW),
+                                                        TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, DataLayout::NCHW)
+                                                     })),
+               framework::dataset::make("BiasesInfo",{
+                                                       TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW),
+                                                       TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW),
+                                                       TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NCHW)
+                                                     })),
+               framework::dataset::make("OutputInfo",{
+                                                       TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW),
+                                                       TensorInfo(TensorShape(23U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW),
+                                                       TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32, DataLayout::NCHW)
+                                                     })),
+               framework::dataset::make("ConvInfo",  {
+                                                       PadStrideInfo(1, 1, 0, 0),
+                                                       PadStrideInfo(1, 1, 0, 0),
+                                                       PadStrideInfo(3, 3, 0, 0)
+                                                      })),
+                       framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)
+})),
+               framework::dataset::make("Expected", { false, false, false})),
+               input_info, weights_info, biases_info, output_info, conv_info, act_info, expected)
+{
+    bool is_valid = bool(CLDirectConvolutionLayer::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, act_info));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
 // clang-format on
 // *INDENT-ON*
-TEST_SUITE(NCHW)
+
 TEST_SUITE(Float)
 TEST_SUITE(FP16)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", DataType::F16)),
diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp
index 0f4c6bb279..73c1a5c3e3 100644
--- a/tests/validation/NEON/DirectConvolutionLayer.cpp
+++ b/tests/validation/NEON/DirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2022 Arm Limited.
+ * Copyright (c) 2017-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -220,14 +220,14 @@ DATA_TEST_CASE(KernelSelection, framework::DatasetMode::ALL,
 // *INDENT-OFF*
 // clang-format off
 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
-        framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type input/weights
-                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching input feature maps
+        framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching data type input/weights
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid: Mismatching input feature maps
                                                 TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported kernel width
-                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non-rectangular weights dimensions
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported non-rectangular weights dimensions
                                                 TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights dimensions
-                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid stride
-                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases size
-                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases dimensions
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported stride
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases size
+                                                TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported biases dimensions
                                                 TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid output size
                                               }),
         framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16),