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Diffstat (limited to 'arm_compute/core/NEON/kernels/NEFuseBatchNormalizationKernel.h')
| -rw-r--r-- | arm_compute/core/NEON/kernels/NEFuseBatchNormalizationKernel.h | 116 |
1 files changed, 0 insertions, 116 deletions
diff --git a/arm_compute/core/NEON/kernels/NEFuseBatchNormalizationKernel.h b/arm_compute/core/NEON/kernels/NEFuseBatchNormalizationKernel.h deleted file mode 100644 index f598530d1e..0000000000 --- a/arm_compute/core/NEON/kernels/NEFuseBatchNormalizationKernel.h +++ /dev/null @@ -1,116 +0,0 @@ -/* - * Copyright (c) 2018-2019 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#ifndef ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H -#define ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H - -#include "arm_compute/core/NEON/INEKernel.h" - -namespace arm_compute -{ -// Forward declarations -class ITensor; - -/** OpenNE kernel to fuse the batch normalization node to a preceding convolution node */ -class NEFuseBatchNormalizationKernel : public INEKernel -{ -public: - const char *name() const override - { - return "NEFuseBatchNormalizationKernel"; - } - /** Default constructor */ - NEFuseBatchNormalizationKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - NEFuseBatchNormalizationKernel(const NEFuseBatchNormalizationKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - NEFuseBatchNormalizationKernel &operator=(const NEFuseBatchNormalizationKernel &) = delete; - /** Allow instances of this class to be moved */ - NEFuseBatchNormalizationKernel(NEFuseBatchNormalizationKernel &&) = default; - /** Allow instances of this class to be moved */ - NEFuseBatchNormalizationKernel &operator=(NEFuseBatchNormalizationKernel &&) = default; - /** Default destructor */ - ~NEFuseBatchNormalizationKernel() = default; - /** Set the source, destination of the kernel - * - * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC - * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights - * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights - * @param[out] fused_weights (Optional) Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights - * @param[out] fused_bias (Optional) Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights - * @param[in] input_bias (Optional) Input bias tensor for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights - * @param[in] bn_beta (Optional) Batch normalization layer beta tensor. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights - * @note if nullptr, bn_beta is set to 0.0 - * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights - * @note if nullptr, bn_gamma is set to 1.0 - * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. - * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to CONVOLUTION. - */ - void configure(const ITensor *input_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias, - const ITensor *input_bias = nullptr, const ITensor *bn_beta = nullptr, const ITensor *bn_gamma = nullptr, - float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); - /** Static function to check if given info will lead to a valid configuration of @ref NEFuseBatchNormalizationKernel - * - * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC - * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p input_weights - * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p input_weights - * @param[in] fused_weights (Optional) Output fused weights tensor info. It can be a nullptr in case of in-place computation. Same as @p input_weights - * @param[in] fused_bias (Optional) Output fused bias tensor info. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights - * @param[in] input_bias (Optional) Input bias tensor info for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights - * @param[in] bn_beta (Optional) Batch normalization layer beta tensor info. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights - * @note if nullptr, bn_beta is set to 0.0 - * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor info. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights - * @note if nullptr, bn_gamma is set to 1.0 - * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. - * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to CONVOLUTION. - * - * @return a status - */ - static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var, - const ITensorInfo *fused_weights, const ITensorInfo *fused_bias, - const ITensorInfo *input_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr, - float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); - - // Inherited methods overridden: - void run(const Window &window, const ThreadInfo &info) override; - -private: - const ITensor *_input_weights; - const ITensor *_input_bias; - const ITensor *_bn_mean; - const ITensor *_bn_var; - const ITensor *_bn_gamma; - const ITensor *_bn_beta; - ITensor *_fused_weights; - ITensor *_fused_bias; - float _epsilon; - bool _run_in_place_weights; - bool _run_in_place_bias; - - using FuseBatchNormFunction = void(const ITensor *input_weights, const ITensor *input_bias, ITensor *fused_weights, ITensor *fused_bias, - const ITensor *bn_mean, const ITensor *bn_var, const ITensor *bn_beta, const ITensor *bn_gamma, float epsilon, const Window &window); - - FuseBatchNormFunction *_func; -}; -} // namespace arm_compute -#endif /*ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H */ |