class ITensor;
class ITensorInfo;
-/** Basic function to run @ref NEActivationLayerKernel
+/** Basic function to run @ref cpu::kernels::CpuActivationKernel
*
* @note The function simulates an activation layer with the specified activation function.
*/
class ITensor;
class ITensorInfo;
-/** Basic function to run @ref CpuAddKernel */
+/** Basic function to run @ref cpu::kernels::CpuAddKernel */
class NEArithmeticAddition : public IFunction
{
public:
/** Initialise the kernel's inputs vector and output.
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
- * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayerKernel, @ref NEHeightConcatenateLayerKernel and @ref NEDepthConcatenateLayerKernel.
+ * @note Preconditions can be found respectively at @ref cpu::kernels::CpuConcatenateWidthKernel, @ref cpu::kernels::CpuConcatenateHeightKernel,
+ * @ref cpu::kernels::CpuConcatenateDepthKernel and @ref cpu::kernels::CpuConcatenateBatchKernel.
*
* @param[in,out] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[out] output Output tensor. Data types supported: Same as @p input.
/** Static function to check if given info will lead to a valid configuration of @ref NEConcatenateLayer
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
- * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayerKernel, @ref NEHeightConcatenateLayerKernel and @ref NEDepthConcatenateLayerKernel.
+ * @note Preconditions can be found respectively at @ref cpu::kernels::CpuConcatenateWidthKernel, @ref cpu::kernels::CpuConcatenateHeightKernel,
+ * @ref cpu::kernels::CpuConcatenateDepthKernel and @ref cpu::kernels::CpuConcatenateBatchKernel.
*
* @param[in] inputs_vector The vectors containing all the tensors info to concatenate. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] output Output tensor info. Data types supported: Same as @p input.
class ITensor;
class ITensorInfo;
-/** Basic function to run @ref CpuCopyKernel */
+/** Basic function to run @ref cpu::kernels::CpuCopyKernel */
class NECopy : public IFunction
{
public:
{
class ITensor;
-/** Basic function to run @ref CpuFillKernel */
+/** Basic function to run @ref cpu::kernels::CpuFillKernel */
class NEFill : public IFunction
{
public:
class ITensor;
class ITensorInfo;
-/** Basic function to run @ref NEFloorKernel */
+/** Basic function to run @ref cpu::kernels::CpuFloorKernel */
class NEFloor : public IFunction
{
public:
/*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* In both cases:
* -# @ref NEGEMMMatrixAdditionKernel (if c != nullptr and beta != 0.0 and is not reshaped once)
* Else:
- * -# @ref NEArithmeticAdditionKernel (if c != nullptr and is reshaped once and not optimized assembly in place)
+ * -# @ref NEArithmeticAddition (if c != nullptr and is reshaped once and not optimized assembly in place)
*
* -# @ref NEActivationLayer (if activation is specified in GEMMInfo)
*/
/*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* -# @ref NEGEMM (if the data type is BFLOAT16/FP16/FP32)
* -# @ref NEGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8/QASYMM8_SIGNED)
* -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if the data type is QASYMM8/QASYMM8_SIGNED)
- * -# @ref NEArithmeticAdditionKernel (if biases != nullptr and we have a 1x1 convolution with the NHWC data layout)
+ * -# @ref NEArithmeticAddition (if biases != nullptr and we have a 1x1 convolution with the NHWC data layout)
* -# @ref NECol2ImKernel (if NCHW data layout)
*
*/
/** Function to perform MaxUnpooling. This function calls the following NEON kernels:
*
- * -# @ref NEFillKernel
+ * -# @ref NEFill
* -# @ref NEMaxUnpoolingLayerKernel
*/
class NEMaxUnpoolingLayer : public IFunction
class ITensor;
class ITensorInfo;
-/** Basic function to run @ref CpuPermuteKernel */
+/** Basic function to run @ref cpu::kernels::CpuPermuteKernel */
class NEPermute : public IFunction
{
public:
/*
- * Copyright (c) 2020 Arm Limited.
+ * Copyright (c) 2020-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* This function calls the following NEON functions/kernels:
*
* -# @ref NEActivationLayer Activation functions (tanh and logistic)
- * -# @ref NEArithmeticAddition Elementwise addition
+ * -# @ref NEArithmeticAddition Elementwise addition
* -# @ref NEArithmeticSubtractionKernel Elementwise subtraction
- * -# @ref NECopyKernel Copy kernel for copying output_state_out to output
+ * -# @ref NECopy Copy kernel for copying output_state_out to output
* -# @ref NEGEMMLowpMatrixMultiplyCore Quantized matrix multiplication core. Accumulators are 32-bit integers
* -# @ref NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint Convert 32-bit integers into QSYMM16
* -# @ref NEGEMMLowpMatrixAReductionKernel For precomputing effective biases to use
- * -# @ref NEPixelWiseMultiplication Elementwise multiplication
+ * -# @ref NEPixelWiseMultiplication Elementwise multiplication
* -# @ref NETranspose Transpose function for reshaping the weights
* */
class NEQLSTMLayer : public IFunction
// Forward declarations
class ITensor;
-/** Basic function to run @ref NEReshapeLayerKernel */
+/** Basic function to run @ref cpu::kernels::CpuReshapeKernel */
class NEReshapeLayer : public IFunction
{
public:
/** Basic function to spatial divide a tensor. This function calls the following NEON kernels/functions:
*
- * -# @ref NEMemsetKernel
+ * -# @ref NEFill
* -# @ref NESpaceToBatchLayerKernel
*/
class NESpaceToBatchLayer : public IFunction
This is planned to be resolved in 21.02 release.
- Added new data type QASYMM8_SIGNED support for @ref NEROIAlignLayer.
- Added new data type S32 support for:
- - @ref NEArithmeticSubtraction
- - @ref NEArithmeticSubtractionKernel
+ - NEArithmeticSubtraction
+ - NEArithmeticSubtractionKernel
- @ref NEPixelWiseMultiplication
- @ref NEPixelWiseMultiplicationKernel
- @ref NEElementwiseDivision
- More robust script for running benchmarks
- Removed padding from:
- @ref NEPixelWiseMultiplicationKernel
- - @ref NEHeightConcatenateLayerKernel
+ - NEHeightConcatenateLayerKernel
- @ref NEThresholdKernel
- - @ref NEBatchConcatenateLayerKernel
+ - NEBatchConcatenateLayerKernel
- @ref NETransposeKernel
- @ref NEBatchNormalizationLayerKernel
- - @ref NEArithmeticSubtractionKernel
+ - NEArithmeticSubtractionKernel
- @ref NEBoundingBoxTransformKernel
- @ref NELogits1DMaxKernel
- @ref NELogits1DSoftmaxKernel
- NEYOLOLayerKernel
- NEUpsampleLayerKernel
- NEFloorKernel
- - @ref NEWidthConcatenateLayerKernel
- - @ref NEDepthConcatenateLayerKernel
+ - NEWidthConcatenateLayerKernel
+ - NEDepthConcatenateLayerKernel
- @ref NENormalizationLayerKernel
- @ref NEL2NormalizeLayerKernel
- @ref NEFillArrayKernel
- @ref NEQLSTMLayerNormalizationKernel
- Added HARD_SWISH support in:
- @ref CLActivationLayerKernel
- - @ref NEActivationLayerKernel
+ - NEActivationLayerKernel
- Deprecated OpenCL kernels / functions:
- CLGEMMLowpQuantizeDownInt32ToUint8Scale
- CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloat
- @ref NENegLayer
- @ref NEPReluLayer
- @ref NESinLayer
- - @ref NEBatchConcatenateLayerKernel
+ - NEBatchConcatenateLayerKernel
- @ref NEDepthToSpaceLayerKernel / @ref NEDepthToSpaceLayer
- @ref NEDepthwiseConvolutionLayerNativeKernel
- @ref NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel
- @ref NEFFTRadixStageKernel
- @ref NEFFTScaleKernel
- @ref NEGEMMLowpOffsetContributionOutputStageKernel
- - @ref NEHeightConcatenateLayerKernel
+ - NEHeightConcatenateLayerKernel
- @ref NESpaceToBatchLayerKernel / @ref NESpaceToBatchLayer
- @ref NEFFT1D
- @ref NEFFT2D
- @ref CLROIAlignLayer
- @ref CLGenerateProposalsLayer
- Added QASYMM8 support to the following kernels:
- - @ref NEArithmeticAdditionKernel
+ - NEArithmeticAdditionKernel
- @ref NEScale
- Added new tests and improved validation and benchmarking suites.
- Deprecated functions/interfaces
- Added FP16 support to:
- CLDepthwiseConvolutionLayer3x3
- @ref CLDepthwiseConvolutionLayer
- - Added broadcasting support to @ref NEArithmeticAddition / @ref CLArithmeticAddition / @ref CLPixelWiseMultiplication
+ - Added broadcasting support to NEArithmeticAddition / @ref CLArithmeticAddition / @ref CLPixelWiseMultiplication
- Added fused batched normalization and activation to @ref CLBatchNormalizationLayer and @ref NEBatchNormalizationLayer
- Added support for non-square pooling to @ref NEPoolingLayer and @ref CLPoolingLayer
- New OpenCL kernels / functions:
- @ref CPPDetectionWindowNonMaximaSuppressionKernel
- New NEON kernels / functions:
- @ref NEBatchNormalizationLayerKernel / @ref NEBatchNormalizationLayer
- - @ref NEDepthConcatenateLayerKernel / NEDepthConcatenateLayer
+ - NEDepthConcatenateLayerKernel / NEDepthConcatenateLayer
- @ref NEDirectConvolutionLayerKernel / @ref NEDirectConvolutionLayer
- NELocallyConnectedMatrixMultiplyKernel / NELocallyConnectedLayer
- @ref NEWeightsReshapeKernel / @ref NEConvolutionLayerReshapeWeights
- @ref CLNormalizationLayerKernel / @ref CLNormalizationLayer
- @ref CLLaplacianPyramid, @ref CLLaplacianReconstruct
- New NEON kernels / functions:
- - @ref NEActivationLayerKernel / @ref NEActivationLayer
+ - NEActivationLayerKernel / @ref NEActivationLayer
- GEMM refactoring + FP16 support (Requires armv8.2 CPU): @ref NEGEMMInterleave4x4Kernel, @ref NEGEMMTranspose1xWKernel, @ref NEGEMMMatrixMultiplyKernel, @ref NEGEMMMatrixAdditionKernel / @ref NEGEMM
- @ref NEPoolingLayerKernel / @ref NEPoolingLayer
The run will call the function defined in the .cl file.
For the NEON backend case:
-@snippet src/core/NEON/kernels/NEReshapeLayerKernel.cpp NEReshapeLayerKernel Kernel
+@snippet src/core/cpu/kernels/CpuReshapeKernel.cpp NEReshapeLayerKernel Kernel
In the NEON case, there is no need to add an extra file and we implement the kernel in the same NEReshapeLayerKernel.cpp file.
If the tests are already in place, the new kernel can be tested using the existing tests by adding the configure and run of the kernel to the compute_target() in the fixture.
/*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* @param[out] output Destination tensor. Data types supported: opposite of @p input.
*/
void configure(const ITensor *input, ITensor *output);
- /** Static function to check if given info will lead to a valid configuration of @ref NECopyKernel
+ /** Static function to check if given info will lead to a valid configuration of @ref NEConvertQuantizedSignednessKernel
*
* @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED.
* @param[in] output Destination tensor. Data types supported: opposite of @p input.
/*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
*/
void configure(const ITensor *input, ITensor *output, int32_t stride);
- /** Static function to check if given info will lead to a valid configuration of @ref NEReshapeLayerKernel
+ /** Static function to check if given info will lead to a valid configuration of @ref cpu::kernels::CpuReshapeKernel
*
* @param[in] input Source tensor info. Data type supported: All
* @param[in] output Destination tensor info. Data type supported: Same as @p input
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Validate.h"
-using namespace arm_compute;
-
+namespace arm_compute
+{
namespace
{
/** Extends parent shape depending on subtensor's coordinates and shape
return offset;
}
+} // namespace arm_compute
ActivationLayerInfo::ActivationFunction::HARD_SWISH
};
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &activation_info)
+Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &activation_info)
{
- ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8_SIGNED, DataType::QASYMM8, DataType::QSYMM16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8_SIGNED, DataType::QASYMM8, DataType::QSYMM16, DataType::F16, DataType::F32);
- const auto *uk = get_implementation(ActivationSelectorData{ input->data_type() });
+ const auto *uk = get_implementation(ActivationSelectorData{ src->data_type() });
ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
- const DataType data_type = input->data_type();
- const QuantizationInfo &oq_info = (output != nullptr) ? output->quantization_info() : input->quantization_info();
+ const DataType data_type = src->data_type();
+ const QuantizationInfo &oq_info = (dst != nullptr) ? dst->quantization_info() : src->quantization_info();
const ActivationLayerInfo::ActivationFunction f_act = activation_info.activation();
ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized_asymmetric(data_type) && (std::find(std::begin(qasymm8_activations), std::end(qasymm8_activations), f_act) == std::end(qasymm8_activations)),
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 32768.f, 0)));
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 32768.f, 0)));
- // Checks performed when output is configured
- if((output != nullptr) && (output->total_size() != 0))
+ // Checks performed when dst is configured
+ if((dst != nullptr) && (dst->total_size() != 0))
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
}
return Status{};
}
-std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input, ITensorInfo *output)
+std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *src, ITensorInfo *dst)
{
// Configure kernel window
- Window win = calculate_max_window(*input, Steps());
+ Window win = calculate_max_window(*src, Steps());
- if(output != nullptr)
+ if(dst != nullptr)
{
- // Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output, *input->clone());
+ // dst auto inizialitation if not yet initialized
+ auto_init_if_empty(*dst, *src->clone());
Coordinates coord;
- coord.set_num_dimensions(output->num_dimensions());
- output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
+ coord.set_num_dimensions(dst->num_dimensions());
+ dst->set_valid_region(ValidRegion(coord, dst->tensor_shape()));
}
return std::make_pair(Status{}, win);
}
} // namespace
-void CpuActivationKernel::configure(const ITensorInfo *input, ITensorInfo *output, ActivationLayerInfo activation_info)
+void CpuActivationKernel::configure(const ITensorInfo *src, ITensorInfo *dst, ActivationLayerInfo activation_info)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
_act_info = activation_info;
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input, output, activation_info));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, activation_info));
// Configure kernel window
- auto win_config = validate_and_configure_window(input, output);
+ auto win_config = validate_and_configure_window(src, dst);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICPPKernel::configure(win_config.second);
}
-Status CpuActivationKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info)
+Status CpuActivationKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_UNUSED(act_info);
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, act_info));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (output != nullptr) ? output->clone().get() : nullptr).first);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, act_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), (dst != nullptr) ? dst->clone().get() : nullptr).first);
return Status{};
}
* @param[in] activation_info Activation layer information.
*/
void configure(const ITensorInfo *src, ITensorInfo *dst, ActivationLayerInfo activation_info);
- /** Static function to check if given info will lead to a valid configuration of @ref NEActivationLayerKernel
+ /** Static function to check if given info will lead to a valid configuration of @ref CpuActivationKernel
*
* @param[in] src Source tensor info. In case of @p dst tensor info = nullptr, this tensor will store the result
* of the activation function. Data types supported: QASYMM8/QASYMM8_SIGNED/QSYMM16/F16/F32.
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info);
+ static Status validate(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info);
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
void configure(const ITensorInfo *src, ITensorInfo *dst, const PaddingList &padding = PaddingList());
/** Static function to check if given info will lead to a valid configuration of @ref CpuCopyKernel
*
- * @param[in] srd Source tensor. Data types supported: All
+ * @param[in] src Source tensor. Data types supported: All
* @param[in] dst Destination tensor. Data types supported: same as @p src.
* @param[in] padding (Optional) Padding to be applied to the input tensor
*
/** Computes bilinear interpolation using the top-left, top-right, bottom-left, bottom-right pixels and the pixel's distance between
* the real coordinates and the smallest following integer coordinates.
*
- * @param[in] a00 The top-left pixel value.
- * @param[in] a01 The top-right pixel value.
- * @param[in] a10 The bottom-left pixel value.
- * @param[in] a11 The bottom-right pixel value.
- * @param[in] dx Pixel's distance between the X real coordinate and the smallest X following integer
- * @param[in] dy Pixel's distance between the Y real coordinate and the smallest Y following integer
+ * @param[in] a00 The top-left pixel value.
+ * @param[in] a01 The top-right pixel value.
+ * @param[in] a10 The bottom-left pixel value.
+ * @param[in] a11 The bottom-right pixel value.
+ * @param[in] dx_val Pixel's distance between the X real coordinate and the smallest X following integer
+ * @param[in] dy_val Pixel's distance between the Y real coordinate and the smallest Y following integer
*
* @note dx and dy must be in the range [0, 1.0]
*
{
namespace cpu
{
-/** Basic function to run @ref CpuActivationKernel */
+/** Basic function to run @ref kernels::CpuActivationKernel */
class CpuActivation : public ICpuOperator
{
public:
* @param[in] activation_info Activation layer parameters.
*/
void configure(const ITensorInfo *input, ITensorInfo *output, const ActivationLayerInfo &activation_info);
- /** Static function to check if given info will lead to a valid configuration of @ref NEActivationLayer
+ /** Static function to check if given info will lead to a valid configuration of @ref CpuActivation
*
* @param[in] input Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/QSYMM16/F16/F32.
* @param[in] output Destination tensor info. Data type supported: same as @p src
{
namespace cpu
{
-/** Basic function to run @ref CpuAddKernel */
+/** Basic function to run @ref kernels::CpuAddKernel */
class CpuAdd : public ICpuOperator
{
public:
*
*/
void configure(const ITensorInfo *src0, const ITensorInfo *src1, ITensorInfo *dst, ConvertPolicy policy, const ActivationLayerInfo &act_info = ActivationLayerInfo());
- /** Static function to check if given info will lead to a valid configuration of @ref CpuAddKernel
+ /** Static function to check if given info will lead to a valid configuration of @ref CpuAdd
*
* @param[in] src0 First input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32
* @param[in] src1 Second input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/S32/F32
{
/** Basic function to execute concatenate tensors along a given axis. This function calls the following kernels:
*
- * -# @ref CpuConcatenateWidthKernel (if underlying concatenation axis is 0).
- * -# @ref CpuConcatenateHeightKernel (if underlying concatenation axis is 1).
- * -# @ref CpuConcatenateDepthKernel (if underlying concatenation axis is 2).
- * -# @ref CpuConcatenateBatchKernel (if underlying concatenation axis is 3).
+ * -# @ref kernels::CpuConcatenateWidthKernel (if underlying concatenation axis is 0).
+ * -# @ref kernels::CpuConcatenateHeightKernel (if underlying concatenation axis is 1).
+ * -# @ref kernels::CpuConcatenateDepthKernel (if underlying concatenation axis is 2).
+ * -# @ref kernels::CpuConcatenateBatchKernel (if underlying concatenation axis is 3).
*/
class CpuConcatenate : public ICpuOperator
{
/** Configure operator for a given list of arguments
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
- * @note Preconditions can be found respectively at @ref CpuConcatenateWidthKernel, @ref CpuConcatenateHeightKernel, @ref CpuConcatenateDepthKernel and @ref CpuConcatenateBatchKernel.
+ * @note Preconditions can be found respectively at @ref kernels::CpuConcatenateWidthKernel, @ref kernels::CpuConcatenateHeightKernel,
+ * @ref kernels::CpuConcatenateDepthKernel and @ref kernels::CpuConcatenateBatchKernel.
*
* @param[in,out] srcs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[out] dst Output tensor. Data types supported: Same as @p srcs_vector.
/** Static function to check if given info will lead to a valid configuration of @ref NEConcatenateLayer
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
- * @note Preconditions can be found respectively at @ref CpuConcatenateWidthKernel, @ref CpuConcatenateHeightKernel, @ref CpuConcatenateDepthKernel and @ref CpuConcatenateBatchKernel.
+ * @note Preconditions can be found respectively at @ref kernels::CpuConcatenateWidthKernel, @ref kernels::CpuConcatenateHeightKernel,
+ * @ref kernels::CpuConcatenateDepthKernel and @ref kernels::CpuConcatenateBatchKernel.
*
* @param[in] srcs_vector The vectors containing all the tensors info to concatenate. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] dst Output tensor info. Data types supported: Same as @p srcs_vector.
{
namespace cpu
{
-/** Basic function to run @ref CpuCopyKernel */
+/** Basic function to run @ref kernels::CpuCopyKernel */
class CpuCopy : public ICpuOperator
{
public:
{
namespace cpu
{
-/** Basic function to run @ref CpuFillKernel */
+/** Basic function to run @ref kernels::CpuFillKernel */
class CpuFill : public ICpuOperator
{
public:
{
namespace cpu
{
-/** Basic function to run @ref CpuFloorKernel */
+/** Basic function to run @ref kernels::CpuFloorKernel */
class CpuFloor : public ICpuOperator
{
public:
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output);
+ static Status validate(const ITensorInfo *src, const ITensorInfo *dst);
};
} // namespace cpu
} // namespace arm_compute
{
namespace cpu
{
-/** Basic function to run @ref CpuPermuteKernel */
+/** Basic function to run @ref kernels::CpuPermuteKernel */
class CpuPermute : public ICpuOperator
{
public:
{
namespace cpu
{
-/** Basic function to run @ref CpuReshapeKernel */
+/** Basic function to run @ref kernels::CpuReshapeKernel */
class CpuReshape : public ICpuOperator
{
public:
projects / platform / upstream / armcl.git / commitdiff