Compute Library
 22.02
CLDirectDeconvolutionLayer.h
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24 #ifndef ARM_COMPUTE_CLDIRECTDECONVOLUTIONLAYER_H
25 #define ARM_COMPUTE_CLDIRECTDECONVOLUTIONLAYER_H
26 
31 
36 
37 #include <memory>
38 
39 namespace arm_compute
40 {
41 class ICLTensor;
42 /** Function to run the deconvolution layer.
43  *
44  * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perform a 1x1
45  * convolution pass. Input stride defines how many zeroes we should put between each element of the input and pad is the amount of padding.
46  *
47  * The relation between input to output is as follows:
48  * \f[
49  * width\_output = (width\_input - 1) \cdot stride\_x - 2 \cdot padding\_x + kernel\_x
50  * \f]
51  * \f[
52  * height\_output = (height\_input - 1) \cdot stride\_y - 2 \cdot padding\_y + kernel\_y
53  * \f]
54  *
55  * where:
56  * width_input is the size of the first input dimension.
57  * height_input is the size of the second input dimension.
58  * width_output is the size of the first output dimension.
59  * height_output is the size of the second output dimension.
60  * kernel_x and kernel_y are the convolution sizes in x and y.
61  * stride_x and stride_y is the input stride of the first and second dimension.
62  *
63  * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution. Therefore, it will be necessary to use the weights in the
64  * reverse order to perform an actual convolution. This is achieved by using @ref CLReverse.
65  *
66  * This function calls the following OpenCL kernels/functions:
67  *
68  * -# @ref CLDeconvolutionLayerUpsample
69  * -# @ref CLConvolutionLayer
70  *
71  * And the following CPP kernels:
72  * -# @ref CLReverse
73  *
74  */
76 {
77 public:
78  /** Constructor */
79  CLDirectDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
80  /** Prevent instances of this class from being copied (As this class contains pointers) */
82  /** Default move constructor */
84  /** Prevent instances of this class from being copied (As this class contains pointers) */
86  /** Default move assignment operator */
88  /** Set the input, weights, biases and output tensors.
89  *
90  * Valid data layouts:
91  * - NHWC
92  * - NCHW
93  *
94  * Valid data type configurations:
95  * |src0 |src1 |src2 |dst |
96  * |:--------------|:------------------|:------|:--------------|
97  * |F16 |F16 |F16 |F16 |
98  * |F32 |F32 |F32 |F32 |
99  * |QASYMM8 |QASYMM8 |S32 |QASYMM8 |
100  * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
101  * |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 |
102  * |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED |
103  *
104  * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
105  * Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
106  * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
107  * @param[in] bias (Optional) The biases have one dimension.
108  * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
109  * @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
110  * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
111  * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref opencl::kernels::ClWeightsReshapeKernel.
112  *
113  */
114  void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, const WeightsInfo &weights_info = WeightsInfo());
115  /** Set the input, weights, biases and output tensors.
116  *
117  * @param[in] compile_context The compile context to be used.
118  * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
119  * Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
120  * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
121  * @param[in] bias (Optional) The biases have one dimension.
122  * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
123  * @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
124  * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
125  * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref opencl::kernels::ClWeightsReshapeKernel.
126  *
127  */
128  void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info,
130  /** Static function to check if given info will lead to a valid configuration of @ref CLDirectDeconvolutionLayer
131  *
132  * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
133  * Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
134  * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
135  * @param[in] bias (Optional) The biases have one dimension.
136  * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
137  * @param[in] output Output tensor info. The output has the same number of dimensions as the @p input.
138  * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
139  * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref opencl::kernels::ClWeightsReshapeKernel.
140  *
141  * @return a status
142  */
143  static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info,
145 
146  // Inherited methods overridden:
147  void run() override;
148  void prepare() override;
149 
150 private:
151  MemoryGroup _memory_group;
153  CLConvolutionLayer _conv_f;
154  CLReverse _flip_weights;
155 
156  CLTensor _scaled_output;
157  ICLTensor *_original_weights;
158  CLTensor _weights_flipped;
159  CLTensor _flip_axis;
160 
161  bool _is_prepared;
162 };
163 } // namespace arm_compute
164 #endif /* ARM_COMPUTE_CLDECONVOLUTIONLAYER_H */
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info, const WeightsInfo &weights_info=WeightsInfo())
Static function to check if given info will lead to a valid configuration of CLDirectDeconvolutionLay...
Basic function to run CLReverseKernel.
Definition: CLReverse.h:37
Base class for all functions.
Definition: IFunction.h:30
CLDirectDeconvolutionLayer & operator=(const CLDirectDeconvolutionLayer &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
Copyright (c) 2017-2021 Arm Limited.
CLDirectDeconvolutionLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
Constructor.
Convolution Layer Weights Information class.
Definition: Types.h:1728
void run() override
Run the kernels contained in the function.
Function to run the deconvolution layer.
Basic function to execute deconvolution upsample on OpenCL.
Padding and stride information class.
Definition: Types.h:656
void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, const WeightsInfo &weights_info=WeightsInfo())
Set the input, weights, biases and output tensors.
Basic function to compute the convolution layer.
CLCompileContext class.
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
Interface for OpenCL tensor.
Definition: ICLTensor.h:42
void prepare() override
Prepare the function for executing.
Basic implementation of the OpenCL tensor interface.
Definition: CLTensor.h:41