COMPMID-2819: Throw error if exclude_padding is false for NHWC quantized types in PoolingLayer

Change-Id: I30af78f0d727389f81a8eb291020a1b6b305adf8
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2747
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>

4 files changed, 14 insertions, 2 deletions

diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
index 1d9aa33171..2017bbf986 100644
--- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
@@ -62,6 +62,9 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(input->data_type()) && pool_info.pool_type == PoolingType::L2),
                                     "Unsupported combination of parameters!");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized(input->data_type()) && !pool_info.exclude_padding && (pool_info.pool_type == PoolingType::AVG) && pool_info.pad_stride_info.has_padding()
+                                    && (input->data_layout() == DataLayout::NHWC),
+                                    "exclude_padding equal false is not supported for AVG Pooling with padding on quantized types");
 
     // Checks performed when output is configured
     if(output->total_size() != 0)
diff --git a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
index 326bc77fcd..d6a3fadd33 100644
--- a/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEPoolingLayerKernel.cpp
@@ -136,6 +136,9 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
     ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON(pool_type == PoolingType::L2 && is_data_type_quantized(input->data_type()));
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized(input->data_type()) && !pool_info.exclude_padding && (pool_info.pool_type == PoolingType::AVG) && pool_info.pad_stride_info.has_padding()
+                                    && (input->data_layout() == DataLayout::NHWC),
+                                    "exclude_padding equal false is not supported for AVG Pooling with padding on quantized types");
 
     if(output->total_size() != 0)
     {
diff --git a/tests/validation/CL/PoolingLayer.cpp b/tests/validation/CL/PoolingLayer.cpp
index e9d756d9a2..611c01b37a 100644
--- a/tests/validation/CL/PoolingLayer.cpp
+++ b/tests/validation/CL/PoolingLayer.cpp
@@ -94,6 +94,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Invalid parameters
                                                        TensorInfo(TensorShape(15U, 13U, 5U), 1, DataType::F32),     // Non-rectangular Global Pooling
                                                        TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32),     // Invalid output Global Pooling
+                                                       TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::QASYMM8), // Invalid exclude_padding = false with quantized type, no actual padding and NHWC
                                                        TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32),
                                                      }),
                framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
@@ -103,6 +104,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8),
                                                        TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(2U, 2U, 5U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(12U, 12U, 5U), 1, DataType::QASYMM8),
                                                        TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
                                                      })),
                framework::dataset::make("PoolInfo",  { PoolingLayerInfo(PoolingType::AVG, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
@@ -112,9 +114,10 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                                        PoolingLayerInfo(PoolingType::L2, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
                                                        PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
                                                        PoolingLayerInfo(PoolingType::MAX, DataLayout::NCHW),
+                                                       PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NHWC, PadStrideInfo(), false),
                                                        PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
                                                       })),
-               framework::dataset::make("Expected", { false, false, false, false, false, true, false, true })),
+               framework::dataset::make("Expected", { false, false, false, false, false, true, false, false, true })),
                input_info, output_info, pool_info, expected)
 {
     ARM_COMPUTE_EXPECT(bool(CLPoolingLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pool_info)) == expected, framework::LogLevel::ERRORS);
diff --git a/tests/validation/NEON/PoolingLayer.cpp b/tests/validation/NEON/PoolingLayer.cpp
index 75c619a635..1012320b0d 100644
--- a/tests/validation/NEON/PoolingLayer.cpp
+++ b/tests/validation/NEON/PoolingLayer.cpp
@@ -81,6 +81,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                             TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),     // Invalid pad/size combination
                                             TensorInfo(TensorShape(15U, 13U, 5U), 1, DataType::F32),     // Non-rectangular Global Pooling
                                             TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32),     // Invalid output Global Pooling
+                                            TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::QASYMM8), // Invalid exclude_padding = false with quantized type, no actual padding and NHWC
                                             TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32),
                                           }),
     framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
@@ -89,6 +90,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                             TensorInfo(TensorShape(25U, 16U, 2U), 1, DataType::F32),
                                             TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
                                             TensorInfo(TensorShape(2U, 2U, 5U), 1, DataType::F32),
+                                            TensorInfo(TensorShape(12U, 12U, 5U), 1, DataType::QASYMM8),
                                             TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32),
                                           })),
     framework::dataset::make("PoolInfo",  { PoolingLayerInfo(PoolingType::AVG, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
@@ -97,9 +99,10 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
                                             PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 2)),
                                             PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
                                             PoolingLayerInfo(PoolingType::MAX, DataLayout::NCHW),
+                                            PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NHWC, PadStrideInfo(), false),
                                             PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
                                            })),
-    framework::dataset::make("Expected", { false, false, false, false, true, false, false, true })),
+    framework::dataset::make("Expected", { false, false, false, false, true, false, false, false, true })),
     input_info, output_info, pool_info, expected)
 {
     bool is_valid = bool(NEPoolingLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pool_info));