From c6aa49b6709edada24b1ab3bc1308e0974f9e057 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Tue, 7 Aug 2018 11:53:30 +0100 Subject: COMPMID-1344 Add grouping support to CLWeightsReshapeKernel Change-Id: Idde333308db71087ec234b3fd1eb4e36a44db46c Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/143049 Reviewed-by: Gian Marco Iodice Tested-by: Jenkins --- .../core/CL/kernels/CLWeightsReshapeKernel.h | 32 ++++++++++++---------- 1 file changed, 18 insertions(+), 14 deletions(-) (limited to 'arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h') diff --git a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h index 664fc3c216..6c93c23cec 100644 --- a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h +++ b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h @@ -68,26 +68,30 @@ public: ~CLWeightsReshapeKernel() = default; /** Set the input and output of the kernel. * - * @param[in] input The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, - * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QASYMM8/F16/F32 - * @param[in] biases The shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with - * dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input - * @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types. - * @param[out] output The output tensor. Should be a 2D Tensor. Data types supported: Same as @p input + * @param[in] input The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, + * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QASYMM8/F16/F32 + * @param[in] biases The shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with + * dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input + * @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types. + * @param[out] output The output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise. + * Data types supported: Same as @p input + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution */ - void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output); + void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, const unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLWeightsReshapeKernel * - * @param[in] input The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, - * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QASYMM8/F16/F32 - * @param[in] biases The shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with - * dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input - * @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types. - * @param[in] output The output tensor. Should be a 2D Tensor. Data types supported: Same as @p input + * @param[in] input The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared, + * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QASYMM8/F16/F32 + * @param[in] biases The shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with + * dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input + * @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types. + * @param[in] output The output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise. + * Data types supported: Same as @p input + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output); + static Status validate(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, const unsigned int num_groups = 1); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; -- cgit v1.2.1