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#pragma once
#include <torch/csrc/jit/api/module.h>
namespace torch::jit {
/** \brief Fold Conv2d-BatchNorm2d into Conv2d in all methods of this
* module and all its submodules, forward is included by default.
*
* The weight and bias of the Conv2d are correspondingly updated. Should only be
* used on modules in eval mode.
*/
TORCH_API Module FoldConvBatchNorm(const Module& module);
struct TORCH_API ConvBNParameters {
at::Tensor conv_w;
at::Tensor conv_b;
at::Tensor bn_rm;
at::Tensor bn_rv;
double bn_eps = 0.0;
at::Tensor bn_w;
at::Tensor bn_b;
};
/**
* Given the current weight and bias tensors of a Conv module and parameters
* of the BatchNorm module we're folding with, compute the updated values
* for the weight and bias.
*
* The function is basically copied from torch/nn/utils/fusion.py
*/
TORCH_API std::tuple<at::Tensor, at::Tensor> computeUpdatedConvWeightAndBias(
const ConvBNParameters& p);
} // namespace torch::jit
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