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Fix warnings about shadowing definitions.

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This commit is contained in:
Rasmus Munk Larsen 2021-11-23 14:34:47 -08:00
parent 5e89573e2a
commit cfdb3ce3f0
1 changed files with 17 additions and 17 deletions
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34
unsupported/Eigen/CXX11/src/Tensor/TensorIO.h
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@ -58,10 +58,10 @@ struct TensorIOFormat {
}
for (std::size_t k = 1; k < prefix.size(); k++) {
int i = int(prefix[k].length()) - 1;
while (i >= 0 && prefix[k][i] != '\n') {
int j = int(prefix[k].length()) - 1;
while (j >= 0 && prefix[k][j] != '\n') {
spacer[k] += ' ';
i--;
j--;
}
}
}
@ -137,10 +137,10 @@ class TensorWithFormat<T, ColMajor, rank> {
friend std::ostream& operator<<(std::ostream& os, const TensorWithFormat<T, ColMajor, rank>& wf) {
// Switch to RowMajor storage and print afterwards
typedef typename T::Index Index;
std::array<Index, rank> shuffle;
std::array<Index, rank> id;
std::iota(id.begin(), id.end(), Index(0));
typedef typename T::Index IndexType;
std::array<IndexType, rank> shuffle;
std::array<IndexType, rank> id;
std::iota(id.begin(), id.end(), IndexType(0));
std::copy(id.begin(), id.end(), shuffle.rbegin());
auto tensor_row_major = wf.t_tensor.swap_layout().shuffle(shuffle);
@ -187,14 +187,14 @@ template <typename Tensor, std::size_t rank>
struct TensorPrinter {
static void run(std::ostream& s, const Tensor& _t, const TensorIOFormat& fmt) {
typedef typename internal::remove_const<typename Tensor::Scalar>::type Scalar;
typedef typename Tensor::Index Index;
typedef typename Tensor::Index IndexType;
static const int layout = Tensor::Layout;
// backwards compatibility case: print tensor after reshaping to matrix of size dim(0) x
// (dim(1)*dim(2)*...*dim(rank-1)).
if (fmt.legacy_bit) {
const Index total_size = internal::array_prod(_t.dimensions());
const IndexType total_size = internal::array_prod(_t.dimensions());
if (total_size > 0) {
const Index first_dim = Eigen::internal::array_get<0>(_t.dimensions());
const IndexType first_dim = Eigen::internal::array_get<0>(_t.dimensions());
Map<const Array<Scalar, Dynamic, Dynamic, layout> > matrix(_t.data(), first_dim,
total_size / first_dim);
s << matrix;
@ -212,7 +212,7 @@ struct TensorPrinter {
is_same<Scalar, std::complex<numext::uint8_t> >::value,
std::complex<int>, const Scalar&>::type>::type PrintType;
const Index total_size = array_prod(_t.dimensions());
const IndexType total_size = array_prod(_t.dimensions());
std::streamsize explicit_precision;
if (fmt.precision == StreamPrecision) {
@ -230,30 +230,30 @@ struct TensorPrinter {
std::streamsize old_precision = 0;
if (explicit_precision) old_precision = s.precision(explicit_precision);
Index width = 0;
IndexType width = 0;
bool align_cols = !(fmt.flags & DontAlignCols);
if (align_cols) {
// compute the largest width
for (Index i = 0; i < total_size; i++) {
for (IndexType i = 0; i < total_size; i++) {
std::stringstream sstr;
sstr.copyfmt(s);
sstr << static_cast<PrintType>(_t.data()[i]);
width = std::max<Index>(width, Index(sstr.str().length()));
width = std::max<IndexType>(width, IndexType(sstr.str().length()));
}
}
std::streamsize old_width = s.width();
char old_fill_character = s.fill();
s << fmt.tenPrefix;
for (Index i = 0; i < total_size; i++) {
for (IndexType i = 0; i < total_size; i++) {
std::array<bool, rank> is_at_end{};
std::array<bool, rank> is_at_begin{};
// is the ith element the end of an coeff (always true), of a row, of a matrix, ...?
for (std::size_t k = 0; k < rank; k++) {
if ((i + 1) % (std::accumulate(_t.dimensions().rbegin(), _t.dimensions().rbegin() + k, 1,
std::multiplies<Index>())) ==
std::multiplies<IndexType>())) ==
0) {
is_at_end[k] = true;
}
@ -262,7 +262,7 @@ struct TensorPrinter {
// is the ith element the begin of an coeff (always true), of a row, of a matrix, ...?
for (std::size_t k = 0; k < rank; k++) {
if (i % (std::accumulate(_t.dimensions().rbegin(), _t.dimensions().rbegin() + k, 1,
std::multiplies<Index>())) ==
std::multiplies<IndexType>())) ==
0) {
is_at_begin[k] = true;
}