From 6e1791b1bfabc81f08d3117939f6eb5264ed4edf Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Mon, 2 Dec 2019 19:01:25 +0000 Subject: COMPMID-2764: Add support for QASYMM8_SIGNED in NEConvolutionLayer. Change-Id: I8fbbd2e399f48968337a60147098d04f27c2d1c0 Signed-off-by: Georgios Pinitas Reviewed-on: https://review.mlplatform.org/c/2402 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Comments-Addressed: Arm Jenkins --- arm_compute/runtime/NEON/functions/NECol2Im.h | 6 +-- .../runtime/NEON/functions/NEConvolutionLayer.h | 12 ++--- .../NEON/functions/NEGEMMConvolutionLayer.h | 54 +++++++++++----------- 3 files changed, 36 insertions(+), 36 deletions(-) (limited to 'arm_compute/runtime') diff --git a/arm_compute/runtime/NEON/functions/NECol2Im.h b/arm_compute/runtime/NEON/functions/NECol2Im.h index 64ce9944e2..613507cf6a 100644 --- a/arm_compute/runtime/NEON/functions/NECol2Im.h +++ b/arm_compute/runtime/NEON/functions/NECol2Im.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -39,7 +39,7 @@ class NECol2Im : public INESimpleFunctionNoBorder public: /** Configure the col2im NEON kernel * - * @param[in] input The input tensor to convert. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input The input tensor to convert. Data types supported: Any * @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 * @param[in] convolved_dims Output convolved dimensions. @@ -47,7 +47,7 @@ public: void configure(const ITensor *input, ITensor *output, const Size2D &convolved_dims); /** Static function to check if given info will lead to a valid configuration of @ref NECol2Im * - * @param[in] input The input tensor to convert. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input The input tensor to convert. Data types supported: Any * @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 * @param[in] convolved_dims Output convolved dimensions. diff --git a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h index 4310ab4b41..91fcef5971 100644 --- a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h @@ -80,10 +80,10 @@ public: * * @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. + * Data types supported: QASYMM8/QASYMM8_SIGNED/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. + * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED 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. @@ -101,10 +101,10 @@ public: * * @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. + * Data types supported: QASYMM8/QASYMM8_SIGNED/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. + * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type. * @param[in] 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. @@ -125,7 +125,7 @@ public: * * @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. + * Data types supported: QASYMM8/QASYMM8_SIGNED/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] 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. @@ -149,5 +149,5 @@ private: std::shared_ptr _memory_manager; std::unique_ptr _function; /**< Function to run */ }; -} +} // namespace arm_compute #endif /* __ARM_COMPUTE_NECONVOLUTIONLAYER_H__ */ diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h index 6452fc9249..c513afa790 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h @@ -63,16 +63,16 @@ public: NEConvolutionLayerReshapeWeights &operator=(NEConvolutionLayerReshapeWeights &&) = default; /** 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/QSYMM8_PER_CHANNEL/F16/F32. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/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. */ void configure(const ITensor *weights, const ITensor *biases, ITensor *output); /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayerReshapeWeights * - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QSYMM8_PER_CHANNEL/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 info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. + * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. + * @param[in] output Destination tensor info. Data types supported: Same as @p weights. * * @return an error status */ @@ -135,8 +135,8 @@ private: * * -# @ref NEIm2ColKernel * -# @ref NEGEMM (if the data type is FP32 or FP16) - * -# @ref NEGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8) - * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if the data type is QASYMM8) + * -# @ref NEGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8/QASYMM8_SIGNED) + * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if the data type is QASYMM8/QASYMM8_SIGNED) * -# @ref NEArithmeticAdditionKernel (if biases != nullptr and we have a 1x1 convolution with the NHWC data layout) * -# @ref NECol2ImKernel (if NCHW data layout) * @@ -158,10 +158,10 @@ public: * * @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: QASYMM8/QSYMM8_PER_CHANNEL/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. * @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. + * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED 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. @@ -175,13 +175,13 @@ public: 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], + * @param[in] input Source tensor info. 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: QASYMM8/QSYMM8_PER_CHANNEL/F16/F32. - * @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[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. + * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type. + * @param[in] output Destination tensor info. 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 NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights @@ -202,24 +202,24 @@ public: private: /** Configures the appropriate matrix multiply routine * - * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Data type supported: QASYMM8/QSYMM8_PER_CHANNEL/F16/F32. + * @param[in] input Input tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[in] weights Weights tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. * @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. + * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type. * @param[out] output Output tensor. Data types supported: Same as @p input, - * except for input of QASYMM8 type where output should be of S32 type. + * except for input of QASYMM8/QASYMM8_SIGNED type where output should be of S32 type. * @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] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) */ void configure_mm(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo(), int gemm_3d_depth = 1); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer matrix multiply routines * - * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Data type supported: QASYMM8/QSYMM8_PER_CHANNEL/F16/F32. - * @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[in] output Output tensor. Data types supported: Same as @p input, - * except for input of QASYMM8 type where output should be of S32 type. + * @param[in] input Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[in] weights Weights tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. + * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type. + * @param[in] output Output tensor info. Data types supported: Same as @p input, + * except for input of QASYMM8/QASYMM8_SIGNED type where output should be of S32 type. * @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] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) * @param[in] skip_im2col (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false) @@ -230,8 +230,8 @@ private: int gemm_3d_depth = 1, bool skip_im2col = false); /** Static function to check if GEMM3D is supported in @ref NEGEMM or in @ref NEGEMMLowpMatrixMultiplyCore * - * @param[in] input_info Input tensor info. Data types supported: QASYMM8/F16/F32. - * @param[in] weights_info Weights tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] input_info Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[in] weights_info Weights tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] act_info Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. * @param[in] gemm_3d_depth Depth of GEMM 3D * @param[in] skip_im2col Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout -- cgit v1.2.1