Compute Library
 22.05
CLWinogradConvolutionLayer.h
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24 #ifndef ARM_COMPUTE_CLWINOGRADCONVOLUTIONLAYER_H
25 #define ARM_COMPUTE_CLWINOGRADCONVOLUTIONLAYER_H
26 
27 #include "arm_compute/core/Types.h"
30 
31 #include <memory>
32 
33 namespace arm_compute
34 {
35 class CLCompileContext;
36 class ICLTensor;
37 class ITensorInfo;
38 
39 /** Basic function to execute Winograd-based convolution on OpenCL. This function calls the following OpenCL functions/kernels:
40  *
41  * -# @ref opencl::ClWinogradConv2d
42  *
43  */
45 {
46 public:
47  /** Default Constructor */
48  CLWinogradConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
49  /** Default Destructor */
51  /** Prevent instances of this class from being copied (As this class contains pointers) */
53  /** Default move constructor */
55  /** Prevent instances of this class from being copied (As this class contains pointers) */
57  /** Default move assignment operator */
59  /** Set the input and output tensors.
60  *
61  * Valid data layouts:
62  * - NHWC
63  * - NCHW
64  *
65  * Valid data type configurations:
66  * |src0 |src1 |src2 |dst |
67  * |:--------------|:--------------|:------|:--------------|
68  * |F16 |F16 |F16 |F16 |
69  * |F32 |F32 |F32 |F32 |
70  *
71  * @note: This function only works with 3x3,3x1,1x3,5x5,5x1,1x5,7x1 and 1x7 kernels along with unit strides for both NCHW and NHWC data layout
72  * @note Some Winograd configurations (i.e. F(4x4, 5x5)) are supported only with enable_fast_math = true
73  *
74  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
75  * while every optional dimension from 4 and above represent a batch of inputs.
76  * Data types supported: F16/F32.
77  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
78  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
79  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
80  * Data types supported: Same as @p input.
81  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
82  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
83  * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
84  * available which may introduce a drop of accuracy as well. Default is false
85  */
86  void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
87  const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
88  /** Set the input and output tensors.
89  *
90  * @note: This function only works with 3x3,3x1,1x3,5x5,5x1,1x5,7x1 and 1x7 kernels along with unit strides for both NCHW and NHWC data layout
91  * @note Some Winograd configurations (i.e. F(4x4, 5x5)) are supported only with enable_fast_math = true
92  *
93  * @param[in] compile_context The compile context to be used.
94  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
95  * while every optional dimension from 4 and above represent a batch of inputs.
96  * Data types supported: F16/F32.
97  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
98  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
99  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
100  * Data types supported: Same as @p input.
101  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
102  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
103  * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
104  * available which may introduce a drop of accuracy as well. Default is false
105  */
106  void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
107  const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
108  /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradConvolutionLayer
109  *
110  * @note: This function only works with 3x3,3x1,1x3,5x5,5x1 and 1x5 kernels along with unit strides for both NCHW and NHWC data layout
111  * @note Some Winograd configurations (i.e. F(4x4, 5x5)) are supported only with enable_fast_math = true
112  *
113  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
114  * while every optional dimension from 4 and above represent a batch of inputs.
115  * Data types supported: F16/F32.
116  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
117  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
118  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
119  * Data types supported: Same as @p input.
120  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
121  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
122  * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
123  * available which may introduce a drop of accuracy as well. Default is false
124  *
125  * @return a status
126  */
127  static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
128  const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
129 
130  // Inherited methods overridden:
131  void run() override;
132  void prepare() override;
133 
134 private:
135  struct Impl;
136  std::unique_ptr<Impl> _impl;
137 };
138 } // namespace arm_compute
139 #endif /* ARM_COMPUTE_CLWINOGRADCONVOLUTIONLAYER_H */
Base class for all functions.
Definition: IFunction.h:30
CLWinogradConvolutionLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
Default Constructor.
void run() override
Run the kernels contained in the function.
void prepare() override
Prepare the function for executing.
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
Activation Layer Information class.
Definition: Types.h:1625
Copyright (c) 2017-2022 Arm Limited.
Padding and stride information class.
Definition: Types.h:669
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false)
Static function to check if given info will lead to a valid configuration of CLWinogradConvolutionLay...
~CLWinogradConvolutionLayer()
Default Destructor.
CLCompileContext class.
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false)
Set the input and output tensors.
CLWinogradConvolutionLayer & operator=(const CLWinogradConvolutionLayer &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
Basic function to execute Winograd-based convolution on OpenCL.