Compute Library
 22.05
CLGEMMConvolutionLayer.h
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24 #ifndef ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H
25 #define ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H
26 
33 
34 #include <memory>
35 
36 namespace arm_compute
37 {
38 // Forward declarations
39 class CLCompileContext;
40 class ICLTensor;
41 class ITensorInfo;
42 
43 /** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
44  *
45  * -# @ref opencl::ClGemmConv2d
46  */
48 {
49 public:
50  /** Constructor
51  *
52  * @param[in] memory_manager (Optional) Memory manager.
53  * @param[in] weights_manager (Optional) Weights manager.
54  */
55  CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr);
56  /** Prevent instances of this class from being copied (As this class contains pointers) */
58  /** Default move constructor */
60  /** Prevent instances of this class from being copied (As this class contains pointers) */
62  /** Default move assignment operator */
64  /**Default destructor */
66  /** Set the input and output tensors.
67  *
68  * Valid data layouts:
69  * - NHWC
70  * - NCHW
71  *
72  * Valid data type configurations:
73  * |src0 |src1 |src2 |dst |
74  * |:--------------|:------------------|:--------|:--------------|
75  * |F16 |F16 |F16 |F16 |
76  * |F32 |F32 |F32 |F32 |
77  * |QASYMM8 |QASYMM8 |S32 |QASYMM8 |
78  * |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 |
79  * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
80  * |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED |
81  *
82  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
83  * while every optional dimension from 4 and above represent a batch of inputs.
84  * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
85  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
86  * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
87  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
88  * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
89  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
90  * Data types supported: Same as @p input.
91  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
92  * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
93  * tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
94  * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
95  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
96  * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
97  * @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
98  */
99  void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(),
100  const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1,
102  /** Set the input and output tensors.
103  *
104  * @param[in] compile_context The compile context to be used.
105  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
106  * while every optional dimension from 4 and above represent a batch of inputs.
107  * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
108  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
109  * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
110  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
111  * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
112  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
113  * Data types supported: Same as @p input.
114  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
115  * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
116  * tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
117  * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
118  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
119  * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
120  * @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
121  */
122  void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
124  const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1,
126  /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer.
127  *
128  * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
129  * while every optional dimension from 4 and above represent a batch of inputs.
130  * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
131  * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
132  * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
133  * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
134  * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type.
135  * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
136  * Data types supported: Same as @p input.
137  * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
138  * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
139  * tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input.
140  * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
141  * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
142  * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
143  * @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
144  *
145  * @return a status
146  */
147  static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
148  const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1,
150 
151  // Inherited methods overridden:
152  void run() override;
153  void prepare() override;
154 
155 private:
156  struct Impl;
157  std::unique_ptr<Impl> _impl;
158 };
159 } // namespace arm_compute
160 #endif /* ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H */
CLGEMMConvolutionLayer & operator=(const CLGEMMConvolutionLayer &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
experimental::PostOpList< ITensorInfo * > post_ops
Base class for all functions.
Definition: IFunction.h:30
Basic function to compute the convolution layer.
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.
Convolution Layer Weights Information class.
Definition: Types.h:1844
CLGEMMConvolutionLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr, IWeightsManager *weights_manager=nullptr)
Constructor.
const unsigned int num_groups
Definition: Im2Col.cpp:153
Padding and stride information class.
Definition: Types.h:669
void run() override
Run the kernels contained in the function.
Weights manager interface to handle weights transformations.
CLCompileContext class.
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info=WeightsInfo(), const Size2D &dilation=Size2D(1U, 1U), const ActivationLayerInfo &act_info=ActivationLayerInfo(), unsigned int num_groups=1, const experimental::PostOpList< ITensorInfo *> &post_ops=experimental::PostOpList< ITensorInfo *> {})
Static function to check if given info will lead to a valid configuration of CLGEMMConvolutionLayer.
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
Class for specifying the size of an image or rectangle.
Definition: Size2D.h:34
void prepare() override
Prepare the function for executing.
void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info=WeightsInfo(), const Size2D &dilation=Size2D(1U, 1U), const ActivationLayerInfo &act_info=ActivationLayerInfo(), unsigned int num_groups=1, const experimental::PostOpList< ICLTensor *> &post_ops=experimental::PostOpList< ICLTensor *> {})
Set the input and output tensors.
A sequence of PostOps that can be appended to the end of other operators.
Definition: IPostOp.h:119
~CLGEMMConvolutionLayer()
Default destructor.