From 916d1bcee42051721a82cfb46b52855c2fe56646 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Mon, 13 Aug 2018 11:20:41 +0100 Subject: COMPMID-1498 - Enable grouping in CLGEMMConvolutionLayer Change-Id: I15c7df21773145b03f42b6f78bd7ad2e5b8a5219 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/144126 Tested-by: Jenkins Reviewed-by: Giorgio Arena Reviewed-by: Georgios Pinitas --- arm_compute/core/CL/kernels/CLCol2ImKernel.h | 5 ++-- arm_compute/core/CL/kernels/CLIm2ColKernel.h | 4 ++-- .../core/CL/kernels/CLWeightsReshapeKernel.h | 8 +++---- arm_compute/core/NEON/kernels/NEIm2ColKernel.h | 4 ++-- arm_compute/core/utils/misc/ShapeCalculator.h | 9 +++---- .../runtime/CL/functions/CLConvolutionLayer.h | 9 ++++--- .../runtime/CL/functions/CLGEMMConvolutionLayer.h | 28 ++++++++++++---------- .../GLES_COMPUTE/functions/GCConvolutionLayer.h | 23 ++---------------- .../runtime/NEON/functions/NEConvolutionLayer.h | 9 ++++--- .../NEON/functions/NEGEMMConvolutionLayer.h | 6 +++-- 10 files changed, 49 insertions(+), 56 deletions(-) (limited to 'arm_compute') diff --git a/arm_compute/core/CL/kernels/CLCol2ImKernel.h b/arm_compute/core/CL/kernels/CLCol2ImKernel.h index 5c047ca091..2a18ae08c8 100644 --- a/arm_compute/core/CL/kernels/CLCol2ImKernel.h +++ b/arm_compute/core/CL/kernels/CLCol2ImKernel.h @@ -63,12 +63,11 @@ public: CLCol2ImKernel &operator=(CLCol2ImKernel &&) = default; /** Default destructor */ ~CLCol2ImKernel() = default; - /** Set the input and output of the kernel. * * @param[in] input The input tensor to convert. Data types supported: QASYMM8/F16/F32 * @param[out] output The output tensor. 3 lower dimensions represent a single output [width, height, OFM], - * while the rest represent batch of outputs. Data types supported: Same as @p input + * while the rest represent batch of outputs. Data types supported: Same as @p input. Data layout: NCHW * @param[in] convolved_dims Output convolved dimensions. * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution */ @@ -77,7 +76,7 @@ public: * * @param[in] input The input tensor to convert. Data types supported: QASYMM8/F16/F32 * @param[in] output The output tensor. 3 lower dimensions represent a single output [width, height, OFM], - * while the rest represent batch of outputs. Data types supported: Same as @p input + * while the rest represent batch of outputs. Data types supported: Same as @p input. Data layout: NCHW * @param[in] convolved_dims Output convolved dimensions. * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution * diff --git a/arm_compute/core/CL/kernels/CLIm2ColKernel.h b/arm_compute/core/CL/kernels/CLIm2ColKernel.h index c678f277cb..0647f5dcec 100644 --- a/arm_compute/core/CL/kernels/CLIm2ColKernel.h +++ b/arm_compute/core/CL/kernels/CLIm2ColKernel.h @@ -76,7 +76,7 @@ public: * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. * @param[in] has_bias In case biases are provided expands the matrix with 1. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout */ void configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation = Size2D(1U, 1U), unsigned int num_groups = 1); @@ -90,7 +90,7 @@ public: * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. * @param[in] has_bias In case biases are provided expands the matrix with 1. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout * * @return a status */ diff --git a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h index d3bbbaf470..bdc5792641 100644 --- a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h +++ b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h @@ -75,10 +75,10 @@ public: * @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. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout * Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it. */ - void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, const unsigned int num_groups = 1); + void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, 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, @@ -88,12 +88,12 @@ public: * @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. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout * Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it. * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, const unsigned int num_groups = 1); + static Status validate(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups = 1); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; diff --git a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h index 37145a38c1..38bdff0e98 100644 --- a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h +++ b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h @@ -84,7 +84,7 @@ public: * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. * @param[in] has_bias In case biases are provided expands the matrix with 1. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported * @param[in] is_fully_connected (Optional) Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments * @param[in] is_flatten (Optional) Determines whether this kernel will be called by @ref NEFlattenLayer in order to validate the arguments */ @@ -100,7 +100,7 @@ public: * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. * @param[in] has_bias In case biases are provided expands the matrix with 1. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported * @param[in] is_fully_connected (Optional)Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments * @param[in] is_flatten (Optional) Determines whether this kernel will be called by @ref NEFlattenLayer in order to validate the arguments * diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h index 8a00c22306..c40e7119b2 100644 --- a/arm_compute/core/utils/misc/ShapeCalculator.h +++ b/arm_compute/core/utils/misc/ShapeCalculator.h @@ -55,19 +55,20 @@ inline TensorShape compute_permutation_output_shape(const ITensorInfo &input, co permute(output_shape, perm); return output_shape; } -inline TensorShape compute_weights_reshaped_shape(const ITensorInfo &weights, bool has_bias = false, const unsigned int num_groups = 1) +inline TensorShape compute_weights_reshaped_shape(const ITensorInfo &weights, bool has_bias = false, unsigned int num_groups = 1) { // Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it. - ARM_COMPUTE_ERROR_ON(num_groups == 0); - ARM_COMPUTE_ERROR_ON((weights.dimension(3) % num_groups) != 0); ARM_COMPUTE_ERROR_ON(weights.data_layout() == DataLayout::NHWC && num_groups > 1); + ARM_COMPUTE_ERROR_ON((weights.dimension(3) % num_groups) != 0); // Calculate output shape TensorShape weights_reshaped{ weights.tensor_shape() }; + weights_reshaped.set(3, weights_reshaped[3] / num_groups); + weights_reshaped.collapse(3); const size_t tmp_dim = weights_reshaped[0]; - weights_reshaped.set(0, weights_reshaped[1] / num_groups); + weights_reshaped.set(0, weights_reshaped[1]); weights_reshaped.set(1, tmp_dim + (has_bias ? 1 : 0)); if(weights.num_dimensions() < 5) { diff --git a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h index c9a74f2a4c..8270e9723e 100644 --- a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h @@ -60,10 +60,11 @@ public: * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation - * available which may introduce a drop of accuracy as well. Default is false + * available which may introduce a drop of accuracy as well. Default is false + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout */ void configure(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(), bool enable_fast_math = false); + const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayer * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], @@ -79,11 +80,13 @@ public: * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation * available which may introduce a drop of accuracy as well. Default is false + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout * * @return a status */ 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(), bool enable_fast_math = false); + const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, + unsigned int num_groups = 1); /** Static function to check if given info will return the convolution called by @ref CLConvolutionLayer * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h index 8538d83c2b..c6ae535713 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h @@ -59,22 +59,24 @@ public: CLConvolutionLayerReshapeWeights(); /** Set the input and output tensors. * - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: QASYMM8/F16/F32. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. - * @param[out] output Destination tensor. Data types supported: Same as @p weights. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. + * Data type supported: QASYMM8/F16/F32. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. + * @param[out] output Destination tensor. Data types supported: Same as @p weights. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout */ - void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output); + void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayerReshapeWeights * - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: QASYMM8/F16/F32. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. - * @param[in] output Destination tensor. Data types supported: Same as @p weights. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. + * Data type supported: QASYMM8/F16/F32. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. + * @param[in] output Destination tensor. Data types supported: Same as @p weights. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout * * @return a status */ - static Status validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output); + static Status validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups = 1); // Inherited methods overridden: void run() override; @@ -122,9 +124,10 @@ public: * tensor has also been transposed with CLGEMMTranspose1xWKernel. Data type supported: Same as @p input. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout */ 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()); + const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer. * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], @@ -140,11 +143,12 @@ public: * tensor has also been transposed with CLGEMMTranspose1xWKernel. Data type supported: Same as @p input. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout * * @return a status */ 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()); + const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); // Inherited methods overridden: void run() override; diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h index 421150e18e..4fac95e72f 100644 --- a/arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h +++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h @@ -101,29 +101,10 @@ public: * tensor has also been transposed with GCGEMMTranspose1xWKernel. Data type supported: Same as @p input. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported */ void configure(const IGCTensor *input, const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo()); - /** Static function to check if given info will lead to a valid configuration of @ref GCConvolutionLayer. - * - * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], - * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. - * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. - * Data types supported: Same as @p input. - * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. - * @param[in] weights_info Specifies if the weights tensor has been reshaped with GCWeightsReshapeKernel. If this is not part of the fully connected layer the weights - * tensor has also been transposed with GCGEMMTranspose1xWKernel. Data type supported: Same as @p input. - * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - * - * @return a status - */ - 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()); + const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); // Inherited methods overridden: void run() override; diff --git a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h index c4226cbc5d..5b53aec9e6 100644 --- a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h @@ -64,10 +64,11 @@ public: * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation - * available which may introduce a drop of accuracy as well. Default is false + * available which may introduce a drop of accuracy as well. Default is false + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported */ void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(), - const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); + const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayer * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], @@ -85,11 +86,13 @@ public: * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation * available which may introduce a drop of accuracy as well. Default is false + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported * * @return a status */ 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(), bool enable_fast_math = false); + const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, + unsigned int num_groups = 1); /** Static function to check if given info will return the convolution called by @ref NEConvolutionLayer * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h index e587cb4e6f..dc00b17efc 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h @@ -116,9 +116,10 @@ public: * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported */ void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(), - const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo()); + const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], @@ -134,11 +135,12 @@ public: * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. + * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported * * @return a status */ 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()); + const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); // Inherited methods overridden: void run() override; -- cgit v1.2.1