arm_compute v18.05
diff --git a/tests/validation/CL/DepthwiseConvolutionLayer.cpp b/tests/validation/CL/DepthwiseConvolutionLayer.cpp
index 8ac882c..093d342 100644
--- a/tests/validation/CL/DepthwiseConvolutionLayer.cpp
+++ b/tests/validation/CL/DepthwiseConvolutionLayer.cpp
@@ -45,60 +45,262 @@
RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.001)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
constexpr RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QASYMM8 */
+constexpr float tolerance_num = 0.05f; /**< Tolerance number */
+
+const auto depth_multipliers = framework::dataset::make("DepthMultiplier", { 1, 2, 3 });
} // namespace
TEST_SUITE(CL)
TEST_SUITE(DepthwiseConvolutionLayer)
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate3x3, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights
+ TensorInfo(TensorShape(32U, 18U, 3U), 1, DataType::F32, 0), // Mismatching input feature maps
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Unsupported weights dimensions
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::QASYMM8, 0), // Unsupported activation
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Mismatching depth multiplier
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid stride
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid biases size
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid biases dimensions
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid output size
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Window shrink
+ TensorInfo(TensorShape(32U, 18U, 8U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(50U, 32U, 8U), 1, DataType::QASYMM8, 0),
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(5U, 5U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::QASYMM8, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 16U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 24U), 1, DataType::QASYMM8, 0),
+ })),
+ framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::S32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(16U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, 0),
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::QASYMM8, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(30U, 16U, 16U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(48U, 30U, 24U), 1, DataType::QASYMM8, 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(4, 1, 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),
+ PadStrideInfo(1, 1, 0, 0),
+ })),
+ framework::dataset::make("DepthMultiplier", { 1,
+ 1,
+ 1,
+ 1,
+ 3,
+ 1,
+ 1,
+ 1,
+ 1,
+ 1,
+ 2,
+ 3,
+ })),
+ framework::dataset::make("ActivationInfo", { ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true, true })),
+ input_info, weights_info, biases_info, output_info, conv_info, depth_multiplier, act_info, expected)
+{
+ bool is_valid = bool(CLDepthwiseConvolutionLayer3x3::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, depth_multiplier, act_info));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+
+DATA_TEST_CASE(ValidateGeneric, framework::DatasetMode::ALL, zip(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, 3U), 1, DataType::F32, 0), // Mismatching input feature maps
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching depth multiplier
+ 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, 8U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(32U, 13U, 8U), 1, DataType::QASYMM8, 0),
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F16, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 16U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 24U), 1, DataType::QASYMM8, 0),
+ })),
+ framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(16U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, 0),
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(25U, 11U, 16U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(32U, 11U, 24U), 1, DataType::QASYMM8, 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(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 1, 0),
+ })),
+ framework::dataset::make("DepthMultiplier", { 1,
+ 1,
+ 3,
+ 1,
+ 1,
+ 1,
+ 2,
+ 3,
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, true, true })),
+ input_info, weights_info, biases_info, output_info, conv_info, depth_multiplier, expected)
+{
+ bool is_valid = bool(CLDepthwiseConvolutionLayer::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, depth_multiplier));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
template <typename T>
using CLDepthwiseConvolutionLayerFixture = DepthwiseConvolutionLayerValidationFixture<CLTensor, CLAccessor, CLDepthwiseConvolutionLayer, T>;
-TEST_SUITE(Generic)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionLayerDataset(), framework::dataset::make("DataType",
- DataType::F32)))
-{
- validate(CLAccessor(_target), _reference, tolerance_f32);
-}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
- framework::dataset::make("DataType",
- DataType::F32)))
-{
- validate(CLAccessor(_target), _reference, tolerance_f32);
-}
-TEST_SUITE_END()
-
template <typename T>
using CLDepthwiseConvolutionLayerFixture3x3 = DepthwiseConvolutionLayerValidationFixture<CLTensor, CLAccessor, CLDepthwiseConvolutionLayer3x3, T>;
TEST_SUITE(Float)
-TEST_SUITE(F16)
+TEST_SUITE(FP16)
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture3x3<half>, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
- framework::dataset::make("DataType",
- DataType::F16)))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture3x3<half>, framework::DatasetMode::ALL,
+ combine(combine(combine(framework::dataset::concat(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
+ datasets::SmallDepthwiseConvolutionLayerDataset3x3NCHW()),
+ depth_multipliers),
+ framework::dataset::make("DataType",
+ DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
{
validate(CLAccessor(_target), _reference, tolerance_f16);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture3x3<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture3x3<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+ depth_multipliers),
framework::dataset::make("DataType",
- DataType::F16)))
+ DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
{
validate(CLAccessor(_target), _reference, tolerance_f16);
}
TEST_SUITE_END()
+
+TEST_SUITE(Generic)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(), depth_multipliers),
+ framework::dataset::make("DataType",
+ DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType",
+ DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+TEST_SUITE_END()
TEST_SUITE_END()
TEST_SUITE(FP32)
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
- framework::dataset::make("DataType",
- DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(framework::dataset::concat(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
+ datasets::SmallDepthwiseConvolutionLayerDataset3x3NCHW()),
+ depth_multipliers),
+ framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
{
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+ depth_multipliers),
framework::dataset::make("DataType",
- DataType::F32)))
+ DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END()
+
+TEST_SUITE(Generic)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(), depth_multipliers),
+ framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
{
validate(CLAccessor(_target), _reference, tolerance_f32);
}
@@ -114,29 +316,41 @@
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
TEST_SUITE(Generic)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(),
- framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
{
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
- framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })),
+ framework::dataset::make("DataLayout", DataLayout::NCHW)))
{
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
TEST_SUITE_END()
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
- framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
+ framework::dataset::make("DepthMultiplier", 1)), // COMPMID-1071 Add depth multiplier support for NHWC
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
{
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
- framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+ framework::dataset::make("DepthMultiplier", 1)), // COMPMID-1071 Add depth multiplier support for NHWC
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
{
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}