// tensor/cpu-impl-linear.h

// Copyright 2019 Johns Hopkins University (author: Daniel Povey)

// See ../../COPYING for clarification regarding multiple authors

//

// Licensed under the Apache License, Version 2.0 (the "License");

// you may not use this file except in compliance with the License.

// You may obtain a copy of the License at

//

// http://www.apache.org/licenses/LICENSE-2.0

//

// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY

// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED

// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,

// MERCHANTABLITY OR NON-INFRINGEMENT.

// See the Apache 2 License for the specific language governing permissions and

// limitations under the License.

#ifndef KALDI_TENSOR_CPU_IMPL_LINEAR_H_

#define KALDI_TENSOR_CPU_IMPL_LINEAR_H_ 1

#include "tensor/tensor.h"

// This header actually contains implementations of functions that are required

// by tensor-impl-linear.cc. It should not be included by users of this

// library.

namespace kaldi {

namespace tensor {

template <typename Real>

inline static void AddProductScalar3CPU(

float alpha, float beta,

const TensorImpl &a, const TensorImpl &b, const TensorImpl *c) {

Real *a_data = static_cast<Real*>(a->data),

*b_data = static_cast<Real*>(b->data),

*c_data = static_cast<Real*>(c->data);

if (beta != 0.0) {

*c_data = (beta * *c_data) + alpha * (*a_data + *b_data);

} else { // don't propagate NaN

*c_data = alpha * (*a_data + *b_data);

}

}

void AddProductScalar3CPU(

float alpha, float beta,

const TensorImpl &a, const TensorImpl &b, const TensorImpl *c) {

if (c.dtype == kFloatDtype) {

} else {

KALDI_ASSERT(c.dtype == kDoubleDtype &&

"Data type not supported for this operation");

}

}

AddProductScalar3Cpu(alpha, beta, a, b, c);

} // namespace tensor

} // namespace kaldi

#endif // KALDI_TENSOR_CPU_IMPL_LINEAR_H_