Compute Library
 21.02
NEDirectConvolutionLayer.h
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1 /*
2  * Copyright (c) 2017-2021 Arm Limited.
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4  * SPDX-License-Identifier: MIT
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24 #ifndef ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H
25 #define ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H
26 
27 #include "arm_compute/core/Types.h"
33 
34 #include <memory>
35 
36 namespace arm_compute
37 {
38 class NEDirectConvolutionLayerOutputStageKernel;
39 class NEDirectConvolutionLayerKernel;
40 class NEFillBorderKernel;
41 
42 /** Function to run the direct convolution.
43  *
44  * This function calls the following Neon kernels:
45  *
46  * -# @ref NEFillBorderKernel for the input
47  * -# @ref NEDirectConvolutionLayerOutputStageKernel
48  * -# @ref NEDirectConvolutionLayerKernel
49  */
51 {
52 public:
53  /** Constructor */
54  NEDirectConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
55  /** Prevent instances of this class from being copied (As this class contains pointers) */
57  /** Prevent instances of this class from being copied (As this class contains pointers) */
59  /** Prevent instances of this class from being moved (As this class contains non movable objects) */
61  /** Prevent instances of this class from being moved (As this class contains non movable objects) */
63  /** Default destructor */
65  /** Set the input, weights, biases and output tensors.
66  *
67  * @note: DirectConvolution only works in the following configurations:
68  * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
69  * 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
70  * 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
71  *
72  * @param[in, out] input Input tensor. Data types supported: F16/F32.
73  * @param[in] weights Set of kernels to convolve the input volume.
74  * Supported sizes: 1x1, 3x3 and 5x5.
75  * The 3rd dimension must be the same as the input's volume 3rd dimension.
76  * Data type supported: Same as @p input.
77  * @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p input.
78  * @param[out] output Output tensor.
79  * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input.
80  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
81  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
82  */
83  void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
84  /** Static function to check if given info will lead to a valid configuration of @ref NEDirectConvolutionLayer
85  *
86  * @note: DirectConvolution only works in the following configurations:
87  * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
88  * 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
89  * 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
90  *
91  * @param[in] input Input tensor. Data types supported: F16/F32.
92  * @param[in] weights Set of kernels to convolve the input volume.
93  * Supported sizes: 1x1, 3x3 and 5x5.
94  * The 3rd dimension must be the same as the input's volume 3rd dimension.
95  * Data type supported: Same as @p input.
96  * @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p input.
97  * @param[in] output Output tensor.
98  * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input.
99  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
100  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
101  *
102  * @return a status
103  */
104  static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &conv_info,
105  const ActivationLayerInfo &act_info = ActivationLayerInfo());
106 
107  // Inherited methods overridden:
108  void run() override;
109 
110 private:
111  MemoryGroup _memory_group;
112  std::unique_ptr<NEDirectConvolutionLayerOutputStageKernel> _output_stage_kernel;
113  std::unique_ptr<NEDirectConvolutionLayerKernel> _conv_kernel;
114  std::unique_ptr<NEFillBorderKernel> _input_border_handler;
115  NEActivationLayer _activationlayer_function;
116  Tensor _accumulator;
117  bool _has_bias;
118  bool _is_activationlayer_enabled;
119  unsigned int _dim_split;
120  bool _is_padding_required;
121 };
122 }
123 #endif /* ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H */
Base class for all functions.
Definition: IFunction.h:30
~NEDirectConvolutionLayer()
Default destructor.
void run() override
Run the kernels contained in the function.
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
Activation Layer Information class.
Definition: Types.h:1550
Interface for Neon tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
NEDirectConvolutionLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
Constructor.
Basic implementation of the tensor interface.
Definition: Tensor.h:37
Padding and stride information class.
Definition: Types.h:722
Basic function to run cpu::kernels::CpuActivationKernel.
void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())
Set the input, weights, biases and output tensors.
Function to run the direct convolution.
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())
Static function to check if given info will lead to a valid configuration of NEDirectConvolutionLayer...
NEDirectConvolutionLayer & operator=(const NEDirectConvolutionLayer &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...