Compute Library
 22.11
CpuDirectConv2d.h
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24 #ifndef ARM_COMPUTE_CPU_DIRECTCONV2D_H
25 #define ARM_COMPUTE_CPU_DIRECTCONV2D_H
26 
28 #include "arm_compute/core/Types.h"
35 #include "src/cpu/ICpuKernel.h"
36 #include "src/cpu/ICpuOperator.h"
40 
41 #include <memory>
42 
43 namespace arm_compute
44 {
45 namespace cpu
46 {
47 /** Function to run the direct convolution.
48  *
49  * This function calls the following kernels:
50  *
51  * -# @ref NEFillBorderKernel for the input
52  * -# @ref kernels::CpuDirectConv2dOutputStageKernel
53  * -# @ref kernels::CpuDirectConv2dKernel
54  */
56 {
57 public:
58  CpuDirectConv2d(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
60  /** Set the input, weights, biases and output tensors.
61  *
62  * @note: DirectConvolution only works in the following configurations:
63  * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
64  * 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
65  * 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
66  *
67  * @param[in, out] src Input tensor info. Data types supported: F16/F32.
68  * @param[in] weights Set of kernels to convolve the input volume.
69  * Supported sizes: 1x1, 3x3 and 5x5.
70  * The 3rd dimension must be the same as the input's volume 3rd dimension.
71  * Data type supported: Same as @p src.
72  * @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p src.
73  * @param[out] dst Output tensor info.
74  * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input.
75  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
76  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
77  */
79  /** Static function to check if given info will lead to a valid configuration
80  *
81  * Similar to CpuDirectConv2d::configure()
82  *
83  * @return a status
84  */
85  static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *dst, const PadStrideInfo &conv_info,
86  const ActivationLayerInfo &act_info = ActivationLayerInfo());
87 
88  // Inherited methods overridden:
89  void run(ITensorPack &tensors) override;
90 
91 private:
92  MemoryGroup _memory_group;
93  std::unique_ptr<kernels::CpuDirectConv2dOutputStageKernel> _output_stage_kernel;
94  std::unique_ptr<kernels::CpuDirectConv2dKernel> _conv_kernel;
95  std::unique_ptr<NEFillBorderKernel> _input_border_handler;
96  std::unique_ptr<CpuActivation> _activationlayer_function;
97  Tensor _accumulator;
98  bool _has_bias{ false };
99  bool _is_activationlayer_enabled{ false };
100  unsigned int _dim_split{ 0 };
101  bool _is_padding_required{ false };
102 };
103 } // namespace cpu
104 } // namespace arm_compute
105 #endif /* ARM_COMPUTE_CPU_DIRECTCONV2D_H */
CpuDirectConv2d(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *dst, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())
Static function to check if given info will lead to a valid configuration.
Basic interface for functions which have a single async CPU kernel.
Definition: INEOperator.h:43
void configure(ITensorInfo *src, ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *dst, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())
Set the input, weights, biases and output tensors.
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
Activation Layer Information class.
Definition: Types.h:1639
SimpleTensor< float > src
Definition: DFT.cpp:155
Copyright (c) 2017-2022 Arm Limited.
Function to run the direct convolution.
Basic implementation of the tensor interface.
Definition: Tensor.h:37
Padding and stride information class.
Definition: Types.h:669
Tensor packing service.
Definition: ITensorPack.h:39
void run(ITensorPack &tensors) override
Run the kernels contained in the function.
const int32_t * bias