diff options
Diffstat (limited to 'arm_compute/runtime')
5 files changed, 34 insertions, 41 deletions
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; |