arm_compute v18.11
diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp
index 0fd7ed4..0b9ada7 100644
--- a/tests/validation/CL/DeconvolutionLayer.cpp
+++ b/tests/validation/CL/DeconvolutionLayer.cpp
@@ -23,6 +23,7 @@
*/
#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h"
@@ -45,17 +46,22 @@
{
constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */
RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.2)); /**< Tolerance value for comparing reference's for DataType::F16 */
+constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
constexpr float tolerance_num = 0.07f; /**< Tolerance number */
-const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 3)
+const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 5) * framework::dataset::make("StrideY", 1, 5) * framework::dataset::make("PadX", 0, 3)
* framework::dataset::make("PadY", 0, 3) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2)
* framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
+const auto data3x3_precommit = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 2) * framework::dataset::make("StrideY", 1, 2) * framework::dataset::make("PadX", 0, 2)
+ * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 3 });
+
const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1)
* framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
+const auto data_layouts_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
} // namespace
TEST_SUITE(CL)
@@ -70,8 +76,8 @@
const unsigned int num_kernels = 1;
const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels);
const TensorShape bias_shape(num_kernels);
- auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 0, 0, 1, 1);
- TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape);
+ auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 1, 1);
+ TensorShape output_shape = compute_deconvolution_output_shape(out_dim, TensorInfo(input_shape, 1, data_type), TensorInfo(weights_shape, 1, data_type));
// Create tensors
CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1);
@@ -105,28 +111,25 @@
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights shape
- TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Non supported data type
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid bias shape
TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32), // Window shrink
TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32),
}),
framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32),
})),
framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(1U), 1, DataType::F16),
TensorInfo(TensorShape(1U), 1, DataType::F32),
- TensorInfo(TensorShape(1U), 1, DataType::F32),
TensorInfo(TensorShape(25U, 11U), 1, DataType::F32),
TensorInfo(TensorShape(1U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::F32),
+ TensorInfo(TensorShape(4U), 1, DataType::S32),
})),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
@@ -134,25 +137,22 @@
framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
- PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 1, 1),
PadStrideInfo(1, 1, 0, 0),
})),
framework::dataset::make("ax", { 1U,
1U,
1U,
- 1U,
0U,
0U,
})),
framework::dataset::make("ay", { 1U,
1U,
1U,
- 1U,
0U,
0U,
})),
- framework::dataset::make("Expected", { false, false, false, false, false, true })),
+ framework::dataset::make("Expected", { false, false, false, false, true })),
input_info, weights_info, bias_info, output_info, pad_info, ax, ay, expected)
{
bool is_valid = bool(CLDeconvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pad_info, ax, ay));
@@ -174,62 +174,134 @@
TEST_SUITE(FP32)
TEST_SUITE(W4x4)
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture4x4<float>, framework::DatasetMode::ALL, combine(data4x4, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture4x4<float>, framework::DatasetMode::NIGHTLY, combine(combine(data4x4, framework::dataset::make("DataType", DataType::F32)),
+ data_layouts_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_fp32);
}
-TEST_SUITE_END()
+TEST_SUITE_END() // W4x4
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::ALL, combine(data3x3, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::PRECOMMIT, combine(combine(data3x3_precommit, framework::dataset::make("DataType", DataType::F32)),
+ data_layouts_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_fp32);
}
-TEST_SUITE_END()
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(combine(data3x3, framework::dataset::make("DataType", DataType::F32)),
+ data_layouts_dataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_fp32);
+}
+TEST_SUITE_END() // W3x3
TEST_SUITE(W1x1)
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<float>, framework::DatasetMode::ALL, combine(data1x1, framework::dataset::make("DataType", DataType::F32)))
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<float>, framework::DatasetMode::NIGHTLY, combine(combine(data1x1, framework::dataset::make("DataType", DataType::F32)),
+ data_layouts_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_fp32);
}
-TEST_SUITE_END()
+TEST_SUITE_END() // W1x1
-TEST_SUITE_END()
+TEST_SUITE_END() // FP32
TEST_SUITE(FP16)
TEST_SUITE(W4x4)
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture4x4<half>, framework::DatasetMode::ALL, combine(data4x4, framework::dataset::make("DataType", DataType::F16)))
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture4x4<half>, framework::DatasetMode::NIGHTLY, combine(combine(data4x4, framework::dataset::make("DataType", DataType::F16)), data_layouts_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
}
-TEST_SUITE_END()
+TEST_SUITE_END() // W4x4
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::ALL, combine(data3x3, framework::dataset::make("DataType", DataType::F16)))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::PRECOMMIT, combine(combine(data3x3_precommit, framework::dataset::make("DataType", DataType::F16)),
+ data_layouts_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
}
-TEST_SUITE_END()
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerFixture3x3<half>, framework::DatasetMode::NIGHTLY, combine(combine(data3x3, framework::dataset::make("DataType", DataType::F16)),
+ data_layouts_dataset))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+TEST_SUITE_END() // W3x3
TEST_SUITE(W1x1)
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<half>, framework::DatasetMode::ALL, combine(data1x1, framework::dataset::make("DataType", DataType::F16)))
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<half>, framework::DatasetMode::NIGHTLY, combine(combine(data1x1, framework::dataset::make("DataType", DataType::F16)), data_layouts_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
}
-TEST_SUITE_END()
+TEST_SUITE_END() // W1x1
-TEST_SUITE_END()
-TEST_SUITE_END()
+TEST_SUITE_END() // FP16
+TEST_SUITE_END() // Float
-TEST_SUITE_END()
-TEST_SUITE_END()
+template <typename T>
+using CLDeconvolutionLayerQuantizedFixture4x4 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 4, 4>;
+
+template <typename T>
+using CLDeconvolutionLayerQuantizedFixture3x3 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 3, 3>;
+
+template <typename T>
+using CLDeconvolutionLayerQuantizedFixture1x1 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 1, 1>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+
+TEST_SUITE(W4x4)
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture4x4<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data4x4, framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ data_layouts_dataset),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0))))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W4x4
+
+TEST_SUITE(W3x3)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data3x3_precommit, framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ data_layouts_dataset),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0))))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDeconvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data3x3, framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ data_layouts_dataset),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0))))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W3x3
+
+TEST_SUITE(W1x1)
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture1x1<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data1x1, framework::dataset::make("DataType",
+ DataType::QASYMM8)),
+ data_layouts_dataset),
+ framework::dataset::make("QuantizationInfo", QuantizationInfo(2.f / 255.f, 0))))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W1x1
+
+TEST_SUITE_END() // QASYMM8
+TEST_SUITE_END() // Quantized
+
+TEST_SUITE_END() // DeconvolutionLayer
+TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute