COMPMID-1026 - Add support for 4x4 output tile in CLWinogradConvolutionLayer
The performance achieved can be found at the following confluence page:
https://confluence.arm.com/display/MLENG/GEMM-based+convolution+vs+Winograd-based+convolution+on+OpenCL
Change-Id: I4b690cfdd4eb4ff0cd17b14fdd49ccaa1d1dc85c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/127729
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/tests/validation/CL/Winograd.cpp b/tests/validation/CL/Winograd.cpp
index 4bfe4c8..6e673a5 100644
--- a/tests/validation/CL/Winograd.cpp
+++ b/tests/validation/CL/Winograd.cpp
@@ -236,7 +236,9 @@
TensorInfo(TensorShape(512U, 49U, 16U, 5U), 1, DataType::F32), // Valid
TensorInfo(TensorShape(13U, 108U, 16U, 4U), 1, DataType::F32), // Padding needed
TensorInfo(TensorShape(7U, 20U, 16U, 7U), 1, DataType::F32), // Valid
- TensorInfo(TensorShape(7U, 20U, 16U, 7U), 1, DataType::F32) // Wrong WinogradInfo
+ TensorInfo(TensorShape(7U, 20U, 16U, 7U), 1, DataType::F32), // Wrong WinogradInfo
+ TensorInfo(TensorShape(7U, 256U, 36U, 3U), 1, DataType::F32), // Valid
+ TensorInfo(TensorShape(7U, 256U, 16U, 3U), 1, DataType::F32) // Wrong number of batches
}),
framework::dataset::make("BiasInfo", {
TensorInfo(TensorShape(512U), 1, DataType::F16),
@@ -245,6 +247,8 @@
TensorInfo(TensorShape(512U), 1, DataType::F32),
TensorInfo(TensorShape(13U), 1, DataType::F32),
TensorInfo(TensorShape(7U), 1, DataType::F32),
+ TensorInfo(TensorShape(7U), 1, DataType::F32),
+ TensorInfo(TensorShape(7U), 1, DataType::F32),
TensorInfo(TensorShape(7U), 1, DataType::F32)
})),
framework::dataset::make("OutputInfo", {
@@ -254,7 +258,9 @@
TensorInfo(TensorShape(14U, 14U, 512U, 5U), 1, DataType::F32),
TensorInfo(TensorShape(17U, 23U, 13U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(8U, 10U, 7U, 7U), 1, DataType::F32),
- TensorInfo(TensorShape(7U, 9U, 7U, 7U), 1, DataType::F32)
+ TensorInfo(TensorShape(7U, 9U, 7U, 7U), 1, DataType::F32),
+ TensorInfo(TensorShape(64U, 64U, 7U, 3U), 1, DataType::F32),
+ TensorInfo(TensorShape(64U, 64U, 7U, 3U), 1, DataType::F32)
})),
framework::dataset::make("WinogradInfo", {
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(14U, 14U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
@@ -264,8 +270,10 @@
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(17U, 23U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(8U, 10U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
WinogradInfo(Size2D(2U, 3U), Size2D(3U, 3U), Size2D(8U, 10U), PadStrideInfo(1, 1, 0, 0), DataLayout::NCHW),
+ WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(64U, 64U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW),
+ WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(64U, 64U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW)
})),
- framework::dataset::make("Expected", { false, false, false, true, false, true, false })),
+ framework::dataset::make("Expected", { false, false, false, true, false, true, false, true, false })),
input_info, bias_info, output_info, winograd_info, expected)
{
ARM_COMPUTE_EXPECT(bool(CLWinogradOutputTransformKernel::validate(&input_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), winograd_info)) == expected, framework::LogLevel::ERRORS);