Compute Library
 21.02
NEWinogradConvolutionLayer.h
Go to the documentation of this file.
1 /*
2  * Copyright (c) 2017-2021 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
9  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
24 #ifndef ARM_COMPUTE_NEWINOGRADCONVOLUTIONLAYER_H
25 #define ARM_COMPUTE_NEWINOGRADCONVOLUTIONLAYER_H
26 
28 
29 #include "arm_compute/core/Types.h"
34 
36 
37 #include <memory>
38 
39 namespace arm_compute
40 {
41 // Forward declarations
42 class ITensor;
43 class ICPPKernel;
44 
45 /** Basic function to simulate a convolution layer. This function calls the following Neon kernels:
46  * -# @ref NEWinogradLayerTransformWeightsKernel (executed only once in the first call to the run() method )
47  * -# @ref NEWinogradLayerTransformInputKernel
48  * -# @ref NEWinogradLayerTransformOutputKernel
49  * -# @ref NEGEMMAssemblyDispatch
50  * -# @ref CPPPermute (three times: weights, input and output)
51  *
52  * @note Some Winograd configurations (i.e. F(2x2, 5x5), F(4x4, 5x5)) are supported only with enable_fast_math = true
53  */
55 {
56 public:
57  /** Constructor */
58  NEWinogradConvolutionLayer(const std::shared_ptr<IMemoryManager> &memory_manager = nullptr);
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 */
64  ~NEWinogradConvolutionLayer() = default;
65 
66  /** Set the input and output tensors.
67  *
68  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
69  * while every optional dimension from 4 and above represent a batch of inputs.
70  * Data types supported: F16/F32.
71  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
72  * Currently only 3x3 and 5x5 kernels are supported.
73  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
74  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
75  * Data types supported: Same as @p input.
76  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. Currently only unit strides are supported.
77  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
78  * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
79  * available which may introduce a drop of accuracy as well. Default is false
80  */
81  void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo(),
82  bool enable_fast_math = false);
83 
84  // Inherited methods overridden:
85  void run() override;
86  void prepare() override;
87 
88  /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer
89  *
90  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
91  * while every optional dimension from 4 and above represent a batch of inputs.
92  * Data types supported: F16/F32.
93  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
94  * Currently only 3x3 and 5x5 kernels are supported.
95  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
96  * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
97  * Data types supported: Same as @p input.
98  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. Currently only unit strides are supported.
99  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
100  * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
101  * available which may introduce a drop of accuracy as well. Default is false
102  *
103  * @return a status
104  */
105  static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
106  const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
107 
108  /** Prevent instances of this class from being copied (As this class contains pointers) */
110  /** Prevent instances of this class from being copied (As this class contains pointers) */
112 
113 private:
114  MemoryGroup _memory_group;
115  NEGEMM _gemm_function;
116  std::unique_ptr<ICPPKernel> _transform_input_kernel;
117  std::unique_ptr<ICPPKernel> _transform_output_kernel;
118  std::unique_ptr<ICPPKernel> _transform_weights_kernel;
119  NEActivationLayer _activationlayer_function;
120 
121  CPPPermute _permute_input;
122  CPPPermute _permute_weights;
123  CPPPermute _permute_output;
124  Tensor _input_transformed;
125  Tensor _output_transformed;
126  Tensor _input_workspace;
127  Tensor _output_workspace;
128  Tensor _kernel_storage;
129  Tensor _input_nhwc;
130  Tensor _output_nhwc;
131  Tensor _weights_hwio;
132  const ITensor *_input;
133  const ITensor *_weights;
134  ITensor *_output;
135  bool _is_prepared;
136  bool _is_activationlayer_enabled;
137 };
138 } // namespace arm_compute
139 #endif /* ARM_COMPUTE_NEWINOGRADCONVOLUTIONLAYER_H */
Base class for all functions.
Definition: IFunction.h:30
NEWinogradConvolutionLayer & operator=(NEWinogradConvolutionLayer &&)=delete
Prevent instances of this class from being moved (As this class contains non movable objects) ...
Basic function to execute GEMM on Neon.
Definition: NEGEMM.h:62
NEWinogradConvolutionLayer(const std::shared_ptr< IMemoryManager > &memory_manager=nullptr)
Constructor.
Basic function to run CPPPermuteKernel.
Definition: CPPPermute.h:36
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false)
Set the input and output tensors.
Activation Layer Information class.
Definition: Types.h:1550
Interface for Neon tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
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 NEGEMMConvolutionLayer.
~NEWinogradConvolutionLayer()=default
Default destructor.
Basic function to simulate a convolution layer.
Basic implementation of the tensor interface.
Definition: Tensor.h:37
Padding and stride information class.
Definition: Types.h:722
void prepare() override
Prepare the function for executing.
Basic function to run cpu::kernels::CpuActivationKernel.
void run() override
Run the kernels contained in the function.