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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_CXX11_TENSOR_TENSOR_IO_H
#define EIGEN_CXX11_TENSOR_TENSOR_IO_H
namespace Eigen {
namespace internal {
// Print the tensor as a 2d matrix
template <typename Tensor, int Rank>
struct TensorPrinter {
static void run (std::ostream& os, const Tensor& tensor) {
typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
typedef typename Tensor::Index Index;
const Index total_size = internal::array_prod(tensor.dimensions());
if (total_size > 0) {
const Index first_dim = Eigen::internal::array_get<0>(tensor.dimensions());
static const int layout = Tensor::Layout;
Map<const Array<Scalar, Dynamic, Dynamic, layout> > matrix(const_cast<Scalar*>(tensor.data()), first_dim, total_size/first_dim);
os << matrix;
}
}
};
// Print the tensor as a vector
template <typename Tensor>
struct TensorPrinter<Tensor, 1> {
static void run (std::ostream& os, const Tensor& tensor) {
typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
typedef typename Tensor::Index Index;
const Index total_size = internal::array_prod(tensor.dimensions());
if (total_size > 0) {
Map<const Array<Scalar, Dynamic, 1> > array(const_cast<Scalar*>(tensor.data()), total_size);
os << array;
}
}
};
// Print the tensor as a scalar
template <typename Tensor>
struct TensorPrinter<Tensor, 0> {
static void run (std::ostream& os, const Tensor& tensor) {
os << tensor.coeff(0);
}
};
}
template <typename T>
std::ostream& operator << (std::ostream& os, const TensorBase<T, ReadOnlyAccessors>& expr) {
typedef TensorEvaluator<const TensorForcedEvalOp<const T>, DefaultDevice> Evaluator;
typedef typename Evaluator::Dimensions Dimensions;
// Evaluate the expression if needed
TensorForcedEvalOp<const T> eval = expr.eval();
Evaluator tensor(eval, DefaultDevice());
tensor.evalSubExprsIfNeeded(NULL);
// Print the result
static const int rank = internal::array_size<Dimensions>::value;
internal::TensorPrinter<Evaluator, rank>::run(os, tensor);
// Cleanup.
tensor.cleanup();
return os;
}
} // end namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_IO_H
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