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authorAndrew Mundy <andrew.mundy@arm.com>2018-03-15 16:47:03 +0000
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:49:16 +0000
commit4d9379a9d3ada794f532ce8acdc8607f4faa2b21 (patch)
tree14ba02ebcdaf6cb927e9422e45cbab6456c9a097 /tests
parent3f217ec4ff11e20fe686beb9a28d0bbd80a56cd6 (diff)
downloadComputeLibrary-4d9379a9d3ada794f532ce8acdc8607f4faa2b21.tar.gz
COMPMID-1040: Added support for nullptr bias tensor in NEWinogradLayer
Change-Id: Ie624ee17c63dede711d913a82819e128954a57c9 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/124861 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests')
-rw-r--r--tests/validation/NEON/ConvolutionLayer.cpp43
-rw-r--r--tests/validation/NEON/DilatedConvolutionLayer.cpp30
-rw-r--r--tests/validation/fixtures/WinogradLayerFixture.h13
3 files changed, 47 insertions, 39 deletions
diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp
index 27216af6d1..3a365253cb 100644
--- a/tests/validation/NEON/ConvolutionLayer.cpp
+++ b/tests/validation/NEON/ConvolutionLayer.cpp
@@ -76,22 +76,17 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo
TEST_SUITE(NEON)
TEST_SUITE(ConvolutionLayer)
-DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0)
- }),
- framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0)
- })),
- framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(1U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(16U), 1, DataType::F32, 0)
- })),
+DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0)
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0)
+ })),
framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32, 0),
TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
@@ -103,11 +98,10 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
PadStrideInfo(3, 2, 1, 0)
})),
framework::dataset::make("Expected", { ConvolutionMethod::WINOGRAD, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })),
- input_info, weights_info, biases_info, output_info, conv_info, expected)
+ input_info, weights_info, output_info, conv_info, expected)
{
ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&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);
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
@@ -117,6 +111,9 @@ TEST_SUITE(WinogradLayer)
template <typename T>
using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradLayer, T>;
+template <typename T>
+using NEWinogradConvolutionLayerNoBiasFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradLayer, T, false>;
+
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
combine(combine(framework::dataset::concat(datasets::SmallWinogradConvolutionLayer3x3Dataset(),
@@ -128,6 +125,16 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, frame
validate(Accessor(_target), _reference, tolerance_f32);
}
+FIXTURE_DATA_TEST_CASE(RunSmallNoBias, NEWinogradConvolutionLayerNoBiasFixture<float>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(framework::dataset::concat(datasets::SmallWinogradConvolutionLayer3x3Dataset(),
+ datasets::SmallWinogradConvolutionLayer5x5Dataset()),
+ framework::dataset::make("DataType", { DataType::F32 })),
+ ActivationFunctionsDataset))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_f32);
+}
+
TEST_SUITE_END()
TEST_SUITE_END()
diff --git a/tests/validation/NEON/DilatedConvolutionLayer.cpp b/tests/validation/NEON/DilatedConvolutionLayer.cpp
index 1e8c19fc5e..358cec3d6f 100644
--- a/tests/validation/NEON/DilatedConvolutionLayer.cpp
+++ b/tests/validation/NEON/DilatedConvolutionLayer.cpp
@@ -66,22 +66,17 @@ const auto CNNDataTypes = framework::dataset::make("DataType",
TEST_SUITE(NEON)
TEST_SUITE(DilatedConvolutionLayer)
-DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0)
- }),
- framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0)
- })),
- framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(1U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(21U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(16U), 1, DataType::F32, 0)
- })),
+DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0)
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0)
+ })),
framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32, 0),
TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
@@ -98,11 +93,10 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
Size2D(3U, 3U)
})),
framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })),
- input_info, weights_info, biases_info, output_info, conv_info, dilation, expected)
+ input_info, weights_info, output_info, conv_info, dilation, expected)
{
ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&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, WeightsInfo(), dilation);
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
diff --git a/tests/validation/fixtures/WinogradLayerFixture.h b/tests/validation/fixtures/WinogradLayerFixture.h
index 5210cbf720..481eb93e80 100644
--- a/tests/validation/fixtures/WinogradLayerFixture.h
+++ b/tests/validation/fixtures/WinogradLayerFixture.h
@@ -48,7 +48,7 @@ namespace validation
{
using namespace arm_compute::misc::shape_calculator;
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool use_bias = true>
class WinogradConvolutionLayerValidationFixture : public framework::Fixture
{
public:
@@ -93,7 +93,7 @@ protected:
// Create and configure function
FunctionType conv;
- conv.configure(&src, &weights, &bias, &dst, info, act_info);
+ conv.configure(&src, &weights, (use_bias) ? &bias : nullptr, &dst, info, act_info);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -133,7 +133,14 @@ protected:
// Fill reference
fill(src, 0, -1.f, 1.f);
fill(weights, 1, -1.f, 1.f);
- fill(bias, 2, -1.f, 1.f);
+ if(use_bias)
+ {
+ fill(bias, 2, -1.f, 1.f);
+ }
+ else
+ {
+ fill(bias, 2, 0.f, 0.f);
+ }
return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info), act_info) : reference::convolution_layer<T>(src, weights, bias,
output_shape, info);
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-13 05:04:49 +0000