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58 lines (45 loc) · 1.7 KB
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// tensor/cpu-impl-linear.cc
// 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.
#include "tensor/cpu-impl-linear.h"
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) {
AddProductScalar3CPU<float>(a, b, c);
} else if (c.dtype == kDoubleDtype) {
AddProductScalar3CPU<double>(a, b, c);
} else {
KALDI_ERR << "Data type not supported for this operation";
}
}
} // namespace tensor
} // namespace kaldi