Compute Library
 21.11
CLDepthwiseConvolutionLayerNativeKernel.h
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1 /*
2  * Copyright (c) 2019-2021 Arm Limited.
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24 #ifndef ARM_COMPUTE_CLDEPTHWISECONVOLUTIONLAYERNATIVEKERNEL_H
25 #define ARM_COMPUTE_CLDEPTHWISECONVOLUTIONLAYERNATIVEKERNEL_H
26 
27 #include "src/core/CL/ICLKernel.h"
28 
30 
31 namespace arm_compute
32 {
33 class ICLTensor;
34 
35 /** Interface for the kernel to run a MxN depthwise convolution. M and N are respectively the rows and columns of the filter
36  This kernel assumes that tensor for the weights is NOT reshaped (Native version) */
38 {
39 public:
40  /** Default Constructor */
42  /** Prevent instances of this class from being copied (As this class contains pointers) */
44  /** Prevent instances of this class from being copied (As this class contains pointers) */
46  /** Allow instances of this class to be moved */
48  /** Allow instances of this class to be moved */
50 
51  /** Initialize the function's source, destination and parameters
52  *
53  * @param[in] compile_context The compile context to be used.
54  * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/FP32/FP16. Data layout supported: NHWC
55  * @param[in] weights Weights tensor. A 3D tensor with dimensions [IFM, N, M].
56  * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
57  * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
58  * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
59  * @param[out] output Destination tensor. Pass in nullptr or @p input for in-place operation. Data type supported: Same as @p input.
60  * @param[in] dwc_info Depthwise convolution layer info
61  * @param[in] conv_info Convolution info (padding, stride, dilation, ...)
62  * @param[in] output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
63  * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
64  * @param[in] output_shifts (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
65  * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
66  *
67  * @note: In-place is only supported when
68  * * data layout: NHWC
69  * * filter: 1x1
70  * * @p depth_multiplier: 1
71  * * strides: 1
72  * * dilation: 1
73  * * no padding
74  * * no change of data layout after configure
75  */
76  void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCComputeKernelInfo &dwc_info,
77  const ConvolutionInfo &conv_info, const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
78 
79  /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayerNativeKernel
80  *
81  * Similar to @ref CLDepthwiseConvolutionLayerNativeKernel::configure()
82  */
83  void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCComputeKernelInfo &dwc_info,
84  const ConvolutionInfo &conv_info, const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
85 
86  /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayerNativeKernel
87  *
88  * Similar to @ref CLDepthwiseConvolutionLayerNativeKernel::configure()
89  *
90  * @return a status
91  */
92  static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCComputeKernelInfo &dwc_info,
93  const ConvolutionInfo &conv_info, const ITensorInfo *output_multipliers = nullptr, const ITensorInfo *output_shifts = nullptr);
94 
95  // Inherited methods overridden:
96  void run(const Window &window, cl::CommandQueue &queue) override;
97 
98 private:
99  const ICLTensor *_input {};
100  const ICLTensor *_weights{};
101  const ICLTensor *_biases{};
102  ICLTensor *_output{};
103  unsigned int _depth_multiplier{ 0 };
104  const ICLTensor *_output_multipliers{};
105  const ICLTensor *_output_shifts{};
106  bool _export_to_cl_image { true };
107  bool _is_quantized{ false };
108 };
109 } // namespace arm_compute
110 #endif /*ARM_COMPUTE_CLDEPTHWISECONVOLUTIONLAYERNATIVEKERNEL_H */
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
Store the tensor's metadata.
Definition: ITensorInfo.h:40
void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCComputeKernelInfo &dwc_info, const ConvolutionInfo &conv_info, const ICLTensor *output_multipliers=nullptr, const ICLTensor *output_shifts=nullptr)
Initialize the function's source, destination and parameters.
Status class.
Definition: Error.h:52
Common interface for all the OpenCL kernels.
Definition: ICLKernel.h:68
Copyright (c) 2017-2021 Arm Limited.
void run(const Window &window, cl::CommandQueue &queue) override
Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue...
CLDepthwiseConvolutionLayerNativeKernel & operator=(const CLDepthwiseConvolutionLayerNativeKernel &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
CLCompileContext class.
Compute descriptor used by the depthwise convolution native kernel.
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCComputeKernelInfo &dwc_info, const ConvolutionInfo &conv_info, const ITensorInfo *output_multipliers=nullptr, const ITensorInfo *output_shifts=nullptr)
Static function to check if given info will lead to a valid configuration of CLDepthwiseConvolutionLa...
Describe a multidimensional execution window.
Definition: Window.h:39
Interface for the kernel to run a MxN depthwise convolution.