diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h')
| -rw-r--r-- | arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h | 51 |
1 files changed, 38 insertions, 13 deletions
diff --git a/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h b/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h index a441fb44b3..1367f378f7 100644 --- a/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h +++ b/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h @@ -25,13 +25,15 @@ #define __ARM_COMPUTE_NEDEPTHWISECONVOLUTIONKERNEL3x3_H__ #include "arm_compute/core/NEON/INEKernel.h" +#include "arm_compute/core/NEON/kernels/convolution/depthwise/depthwise.hpp" + +#include <memory> namespace arm_compute { class ITensor; -/** Interface for the kernel to run a 3x3 depthwise convolution on a tensor. - */ +/** Interface for the kernel to run a 3x3 depthwise convolution on a tensor. */ class NEDepthwiseConvolutionLayer3x3Kernel : public INEKernel { public: @@ -51,24 +53,47 @@ public: NEDepthwiseConvolutionLayer3x3Kernel &operator=(NEDepthwiseConvolutionLayer3x3Kernel &&) = default; /** Initialize the function's source, destination, conv and border_size. * - * @param[in] input Source tensor. DataType supported: QASYMM8, F32. - * @param[in] weights Weights tensor. This is a 3D tensor with dimensions [3, 3, IFM]. Data type supported: Same as @p input. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] input Source tensor. DataType supported: QASYMM8, F32. + * @param[in] weights Weights tensor. This is a 3D tensor with dimensions [3, 3, IFM]. Data type supported: Same as @p input. + * @param[out] output Destination tensor. Data type supported: Same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] data_layout (Optional) Data layout of the input and weights tensor */ - void configure(const ITensor *input, const ITensor *weights, ITensor *output, const PadStrideInfo &conv_info); + void configure(const ITensor *input, const ITensor *weights, ITensor *output, const PadStrideInfo &conv_info, DataLayout data_layout = DataLayout::NCHW); + /** Static method that checks if optimized execution is supported for the given parameters + * + * @param[in] input_shape Input shape + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] dt Data type of the input and weights + * @param[in] data_layout (Optional) Data layout of the input and weights tensor + * + * @return True if the optimized kernels can be executed else false + */ + static bool is_optimized_execution_possible(TensorShape input_shape, PadStrideInfo conv_info, DataType dt, DataLayout data_layout = DataLayout::NCHW); + /** Generates the convolver object */ + void generate_convolver(); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; BorderSize border_size() const override; private: - BorderSize _border_size; - const ITensor *_input; - ITensor *_output; - const ITensor *_weights; - PadStrideInfo _conv_info; - unsigned int _num_elems_written_per_iteration; + void configure_generic(); + void configure_optimized(); + void run_generic(const Window &window, const ThreadInfo &info); + void run_optimized(const Window &window, const ThreadInfo &info); + std::unique_ptr<depthwise::IDepthwiseConvolution> create_convolver_object(TensorShape shape, PadStrideInfo conv_info, + const uint8_t *w_ptr, uint8_t *in_ptr, uint8_t *out_ptr); + +private: + BorderSize _border_size; + const ITensor *_input; + ITensor *_output; + const ITensor *_weights; + PadStrideInfo _conv_info; + std::unique_ptr<depthwise::IDepthwiseConvolution> _convolver; + unsigned int _num_elems_written_per_iteration; + bool _run_optimized; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTIONKERNEL3x3_H__ */ |