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| author | Sang-Hoon Park <sang-hoon.park@arm.com> | 2020-01-08 16:29:15 +0000 |
|---|---|---|
| committer | Michele Di Giorgio <michele.digiorgio@arm.com> | 2020-01-14 15:31:35 +0000 |
| commit | 70d33bdfd36e1b44b0573189dca67ed7c63dd59e (patch) | |
| tree | 61873b03cdc8eb1cd3544a00d3cef4eefccd5b0f | |
| parent | 4715cf9da26c4e914b9528f736e77d6773285169 (diff) | |
| download | ComputeLibrary-70d33bdfd36e1b44b0573189dca67ed7c63dd59e.tar.gz | |
COMPMID-2755: update CLConvolutionLayer's doxygen and test for QASYMM8_SIGNED
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Change-Id: Ida6ebd2c1ed46d038e13bfbea0306de660dd147b
Reviewed-on: https://review.mlplatform.org/c/2585
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLConvolutionLayer.h | 8 | ||||
| -rw-r--r-- | tests/validation/CL/ConvolutionLayer.cpp | 33 |
2 files changed, 24 insertions, 17 deletions
diff --git a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h index 66dc7af003..b52695463a 100644 --- a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -77,7 +77,7 @@ public: * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. @@ -98,7 +98,7 @@ public: * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as @p input. @@ -121,7 +121,7 @@ public: * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp index 130af572ff..0d8a322694 100644 --- a/tests/validation/CL/ConvolutionLayer.cpp +++ b/tests/validation/CL/ConvolutionLayer.cpp @@ -87,14 +87,15 @@ TEST_SUITE(ConvolutionLayer) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM - TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM - TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), // Select GEMM - TensorInfo(TensorShape(23U, 27U, 31U, 4U), 1, DataType::F32), // Select WINOGRAD - TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32), // Select GEMM - TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32), // Select GEMM - TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32), // Select WINOGRAD - TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32) // Select GEMM + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM + TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM + TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), // Select GEMM + TensorInfo(TensorShape(23U, 27U, 31U, 4U), 1, DataType::F32), // Select WINOGRAD + TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32), // Select GEMM + TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32), // Select GEMM + TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32), // Select WINOGRAD + TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM + TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::QASYMM8_SIGNED), // Select GEMM }), framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32), TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32), @@ -103,7 +104,8 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32), TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16), TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32), - TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32) + TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::QASYMM8_SIGNED), })), framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32), TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32), @@ -112,7 +114,8 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32), TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32), TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32), - TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32) + TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32), + TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::QASYMM8_SIGNED), })), framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1), PadStrideInfo(1, 2, 1, 1), @@ -121,7 +124,8 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z PadStrideInfo(2, 1, 0, 0), PadStrideInfo(3, 2, 1, 0), PadStrideInfo(1, 1, 2, 2), - PadStrideInfo(1, 1, 2, 2) + PadStrideInfo(1, 1, 2, 2), + PadStrideInfo(1, 1, 2, 2), })), framework::dataset::make("GpuTarget", { GPUTarget::BIFROST, GPUTarget::MIDGARD, @@ -130,7 +134,8 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z GPUTarget::MIDGARD, GPUTarget::BIFROST, GPUTarget::BIFROST, - GPUTarget::BIFROST + GPUTarget::BIFROST, + GPUTarget::BIFROST, })), framework::dataset::make("Dilation", { Size2D(1U, 1U), Size2D(1U, 1U), @@ -140,8 +145,9 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z Size2D(1U, 1U), Size2D(1U, 1U), Size2D(2U, 1U), + Size2D(2U, 1U), })), - framework::dataset::make("EnableFastMath", { false, false, false, false, false, false, true, true })), + framework::dataset::make("EnableFastMath", { false, false, false, false, false, false, true, true, true })), framework::dataset::make("Expected",{ ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, @@ -150,6 +156,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, + ConvolutionMethod::GEMM, })), input_info, weights_info, output_info, conv_info, gpu_target, dilation, enable_fast_math, expected) { |