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/*
* Copyright (c) 2018-2021 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_CLFUSEBATCHNORMALIZATION_H
#define ARM_COMPUTE_CLFUSEBATCHNORMALIZATION_H
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/IFunction.h"
#include <memory>
namespace arm_compute
{
// Forward declarations
class CLCompileContext;
class CLFuseBatchNormalizationKernel;
class ICLTensor;
class ITensorInfo;
/** Basic function to fuse the batch normalization node to a preceding convolution node */
class CLFuseBatchNormalization : public IFunction
{
public:
/** Default constructor */
CLFuseBatchNormalization();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLFuseBatchNormalization(const CLFuseBatchNormalization &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLFuseBatchNormalization &operator=(const CLFuseBatchNormalization &) = delete;
/** Allow instances of this class to be moved */
CLFuseBatchNormalization(CLFuseBatchNormalization &&) = default;
/** Allow instances of this class to be moved */
CLFuseBatchNormalization &operator=(CLFuseBatchNormalization &&) = default;
/** Default destructor */
~CLFuseBatchNormalization();
/** Set the input and output tensors.
*
* Valid data layouts:
* - NHWC
* - NCHW
*
* Valid data type configurations:
* |src |dst |
* |:--------------|:--------------|
* |F32 |F32 |
* |F16 |F16 |
*
* @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 Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights
* @param[out] fused_bias 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 ICLTensor *input_weights,
const ICLTensor *bn_mean,
const ICLTensor *bn_var,
ICLTensor *fused_weights,
ICLTensor *fused_bias,
const ICLTensor *input_bias = nullptr,
const ICLTensor *bn_beta = nullptr,
const ICLTensor *bn_gamma = nullptr,
float epsilon = 0.001f,
FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION);
/** Set the input and output tensors.
*
* @param[in] compile_context The compile context to be used.
* @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 Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights
* @param[out] fused_bias 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 CLCompileContext &compile_context,
const ICLTensor *input_weights,
const ICLTensor *bn_mean,
const ICLTensor *bn_var,
ICLTensor *fused_weights,
ICLTensor *fused_bias,
const ICLTensor *input_bias = nullptr,
const ICLTensor *bn_beta = nullptr,
const ICLTensor *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 CLFuseBatchNormalization
*
* @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 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 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() override;
private:
std::unique_ptr<CLFuseBatchNormalizationKernel> _fuse_bn_kernel;
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_CLFUSEBATCHNORMALIZATION_H */
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