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authorGian Marco Iodice <gianmarco.iodice@arm.com>2018-05-14 14:21:39 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:52:35 +0000
commita8aef2916379402e241d9f2c5e0faf3f99c860f7 (patch)
treeaccf1f74bb836766260dbdb90aad7b6048c675d2 /tests
parentcb0010b02281245c66d5c996fa9ef8b22f036a2d (diff)
downloadComputeLibrary-a8aef2916379402e241d9f2c5e0faf3f99c860f7.tar.gz
COMPMID-792 - Re-enabled Winograd on NEON in all graph examples.
Since now the input transform can be multi-threaded, I re-ebaled Winograd in all graph examples Change-Id: I39ef78243bb47fdae135e18dcae2102af0675b3b Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/131048 Reviewed-by: Anthony Barbier <anthony.barbier@arm.com> Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests')
-rw-r--r--tests/validation/CL/ConvolutionLayer.cpp14
-rw-r--r--tests/validation/CL/DilatedConvolutionLayer.cpp4
-rw-r--r--tests/validation/NEON/ConvolutionLayer.cpp6
3 files changed, 15 insertions, 9 deletions
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 935a6ebefa..0c40953524 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -77,22 +77,25 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(23U, 27U, 31U, 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),
- TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32, 0),
TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0)
}),
framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 31U, 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),
- TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32, 0),
TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0)
})),
framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0),
TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0),
TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0),
TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, 0),
@@ -101,6 +104,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1),
PadStrideInfo(1, 2, 1, 1),
PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(2, 1, 0, 0),
PadStrideInfo(3, 2, 1, 0),
PadStrideInfo(1, 1, 2, 2),
@@ -109,6 +113,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
framework::dataset::make("GpuTarget", { GPUTarget::BIFROST,
GPUTarget::MIDGARD,
GPUTarget::G71,
+ GPUTarget::G71,
GPUTarget::MIDGARD,
GPUTarget::BIFROST,
GPUTarget::BIFROST,
@@ -122,12 +127,13 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
Size2D(1U, 1U),
Size2D(1U, 1U),
Size2D(1U, 1U),
+ Size2D(1U, 1U),
Size2D(2U, 1U),
})),
-framework::dataset::make("EnableFastMath", { false, false, false, false, false, true, true })),
+framework::dataset::make("EnableFastMath", { false, false, false, false, false, false, true, true })),
framework::dataset::make("Expected",
{
- ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM,
+ ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM,
})),
input_info, weights_info, output_info, conv_info, gpu_target, dilation, enable_fast_math, expected)
{
diff --git a/tests/validation/CL/DilatedConvolutionLayer.cpp b/tests/validation/CL/DilatedConvolutionLayer.cpp
index 9da7c32d7c..25931c0f4c 100644
--- a/tests/validation/CL/DilatedConvolutionLayer.cpp
+++ b/tests/validation/CL/DilatedConvolutionLayer.cpp
@@ -66,13 +66,13 @@ TEST_SUITE(DilatedConvolutionLayer)
DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(23U, 27U, 23U, 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(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 23U, 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)
})),
diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp
index 4f59345f6c..330480e4d8 100644
--- a/tests/validation/NEON/ConvolutionLayer.cpp
+++ b/tests/validation/NEON/ConvolutionLayer.cpp
@@ -78,12 +78,12 @@ TEST_SUITE(NEON)
TEST_SUITE(ConvolutionLayer)
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(23U, 27U, 32U, 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, 32U, 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)
})),
@@ -97,7 +97,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z
PadStrideInfo(2, 1, 0, 0),
PadStrideInfo(3, 2, 1, 0)
})),
- framework::dataset::make("Expected", { ConvolutionMethod::WINOGRAD, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })),
+ framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })),
input_info, weights_info, output_info, conv_info, expected)
{
ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false),
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-16 19:42:41 +0000