Skip to content

Commit

Permalink
apacheGH-38090: [C++][Emscripten] tensor: Suppress shorten-64-to-32 w…
Browse files Browse the repository at this point in the history
…arnings

We need explicit cast to use `int64_t` for `size_t` on Emscripten.

Explicit casts.
  • Loading branch information
kou committed Oct 7, 2023
1 parent 3697bcd commit 8885e41
Show file tree
Hide file tree
Showing 4 changed files with 52 additions and 44 deletions.
27 changes: 15 additions & 12 deletions cpp/src/arrow/sparse_tensor.cc
Original file line number Diff line number Diff line change
Expand Up @@ -151,27 +151,30 @@ void GetCOOIndexTensorRow(const std::shared_ptr<Tensor>& coords, const int64_t r
DCHECK(0 <= row && row < non_zero_length);

const int64_t ndim = shape[1];
out_index->resize(ndim);
out_index->resize(static_cast<size_t>(ndim));

switch (indices_elsize) {
case 1: // Int8, UInt8
for (int64_t i = 0; i < ndim; ++i) {
(*out_index)[i] = static_cast<int64_t>(coords->Value<UInt8Type>({row, i}));
(*out_index)[static_cast<size_t>(i)] =
static_cast<int64_t>(coords->Value<UInt8Type>({row, i}));
}
break;
case 2: // Int16, UInt16
for (int64_t i = 0; i < ndim; ++i) {
(*out_index)[i] = static_cast<int64_t>(coords->Value<UInt16Type>({row, i}));
(*out_index)[static_cast<size_t>(i)] =
static_cast<int64_t>(coords->Value<UInt16Type>({row, i}));
}
break;
case 4: // Int32, UInt32
for (int64_t i = 0; i < ndim; ++i) {
(*out_index)[i] = static_cast<int64_t>(coords->Value<UInt32Type>({row, i}));
(*out_index)[static_cast<size_t>(i)] =
static_cast<int64_t>(coords->Value<UInt32Type>({row, i}));
}
break;
case 8: // Int64
for (int64_t i = 0; i < ndim; ++i) {
(*out_index)[i] = coords->Value<Int64Type>({row, i});
(*out_index)[static_cast<size_t>(i)] = coords->Value<Int64Type>({row, i});
}
break;
default:
Expand All @@ -187,12 +190,12 @@ bool DetectSparseCOOIndexCanonicality(const std::shared_ptr<Tensor>& coords) {
const int64_t non_zero_length = shape[0];
if (non_zero_length <= 1) return true;

const int64_t ndim = shape[1];
const auto ndim = static_cast<size_t>(shape[1]);
std::vector<int64_t> last_index, index;
GetCOOIndexTensorRow(coords, 0, &last_index);
for (int64_t i = 1; i < non_zero_length; ++i) {
GetCOOIndexTensorRow(coords, i, &index);
int64_t j = 0;
size_t j = 0;
while (j < ndim) {
if (last_index[j] > index[j]) {
// last_index > index, so we can detect non-canonical here
Expand Down Expand Up @@ -367,14 +370,14 @@ Result<std::shared_ptr<SparseCSFIndex>> SparseCSFIndex::Make(
const std::vector<int64_t>& indices_shapes, const std::vector<int64_t>& axis_order,
const std::vector<std::shared_ptr<Buffer>>& indptr_data,
const std::vector<std::shared_ptr<Buffer>>& indices_data) {
int64_t ndim = axis_order.size();
auto ndim = axis_order.size();
std::vector<std::shared_ptr<Tensor>> indptr(ndim - 1);
std::vector<std::shared_ptr<Tensor>> indices(ndim);

for (int64_t i = 0; i < ndim - 1; ++i)
for (size_t i = 0; i < ndim - 1; ++i)
indptr[i] = std::make_shared<Tensor>(indptr_type, indptr_data[i],
std::vector<int64_t>({indices_shapes[i] + 1}));
for (int64_t i = 0; i < ndim; ++i)
for (size_t i = 0; i < ndim; ++i)
indices[i] = std::make_shared<Tensor>(indices_type, indices_data[i],
std::vector<int64_t>({indices_shapes[i]}));

Expand Down Expand Up @@ -405,10 +408,10 @@ SparseCSFIndex::SparseCSFIndex(const std::vector<std::shared_ptr<Tensor>>& indpt
std::string SparseCSFIndex::ToString() const { return std::string("SparseCSFIndex"); }

bool SparseCSFIndex::Equals(const SparseCSFIndex& other) const {
for (int64_t i = 0; i < static_cast<int64_t>(indices().size()); ++i) {
for (size_t i = 0; i < indices().size(); ++i) {
if (!indices()[i]->Equals(*other.indices()[i])) return false;
}
for (int64_t i = 0; i < static_cast<int64_t>(indptr().size()); ++i) {
for (size_t i = 0; i < indptr().size(); ++i) {
if (!indptr()[i]->Equals(*other.indptr()[i])) return false;
}
return axis_order() == other.axis_order();
Expand Down
4 changes: 2 additions & 2 deletions cpp/src/arrow/tensor.h
Original file line number Diff line number Diff line change
Expand Up @@ -155,9 +155,9 @@ class ARROW_EXPORT Tensor {
/// Return the offset of the given index on the given strides
static int64_t CalculateValueOffset(const std::vector<int64_t>& strides,
const std::vector<int64_t>& index) {
const int64_t n = static_cast<int64_t>(index.size());
const auto n = index.size();
int64_t offset = 0;
for (int64_t i = 0; i < n; ++i) {
for (size_t i = 0; i < n; ++i) {
offset += index[i] * strides[i];
}
return offset;
Expand Down
28 changes: 14 additions & 14 deletions cpp/src/arrow/tensor/coo_converter.cc
Original file line number Diff line number Diff line change
Expand Up @@ -40,10 +40,10 @@ namespace {
template <typename c_index_type>
inline void IncrementRowMajorIndex(std::vector<c_index_type>& coord,
const std::vector<int64_t>& shape) {
const int64_t ndim = shape.size();
const auto ndim = shape.size();
++coord[ndim - 1];
if (coord[ndim - 1] == shape[ndim - 1]) {
int64_t d = ndim - 1;
auto d = ndim - 1;
while (d > 0 && coord[d] == shape[d]) {
coord[d] = 0;
++coord[d - 1];
Expand Down Expand Up @@ -78,25 +78,25 @@ void ConvertRowMajorTensor(const Tensor& tensor, c_index_type* indices,
template <typename c_index_type, typename c_value_type>
void ConvertColumnMajorTensor(const Tensor& tensor, c_index_type* out_indices,
c_value_type* out_values, const int64_t size) {
const auto ndim = tensor.ndim();
std::vector<c_index_type> indices(ndim * size);
std::vector<c_value_type> values(size);
const auto ndim = static_cast<size_t>(tensor.ndim());
std::vector<c_index_type> indices(static_cast<size_t>(ndim * size));
std::vector<c_value_type> values(static_cast<const size_t>(size));
ConvertRowMajorTensor(tensor, indices.data(), values.data(), size);

// transpose indices
for (int64_t i = 0; i < size; ++i) {
for (int j = 0; j < ndim / 2; ++j) {
for (size_t i = 0; i < static_cast<const size_t>(size); ++i) {
for (size_t j = 0; j < ndim / 2; ++j) {
std::swap(indices[i * ndim + j], indices[i * ndim + ndim - j - 1]);
}
}

// sort indices
std::vector<int64_t> order(size);
std::vector<int64_t> order(static_cast<const size_t>(size));
std::iota(order.begin(), order.end(), 0);
std::sort(order.begin(), order.end(), [&](const int64_t xi, const int64_t yi) {
const int64_t x_offset = xi * ndim;
const int64_t y_offset = yi * ndim;
for (int j = 0; j < ndim; ++j) {
const auto x_offset = static_cast<size_t>(xi * ndim);
const auto y_offset = static_cast<size_t>(yi * ndim);
for (size_t j = 0; j < ndim; ++j) {
const auto x = indices[x_offset + j];
const auto y = indices[y_offset + j];
if (x < y) return true;
Expand All @@ -107,7 +107,7 @@ void ConvertColumnMajorTensor(const Tensor& tensor, c_index_type* out_indices,

// transfer result
const auto* indices_data = indices.data();
for (int64_t i = 0; i < size; ++i) {
for (size_t i = 0; i < size; ++i) {
out_values[i] = values[i];

std::copy_n(indices_data, ndim, out_indices);
Expand All @@ -121,12 +121,12 @@ void ConvertStridedTensor(const Tensor& tensor, c_index_type* indices,
c_value_type* values, const int64_t size) {
using ValueType = typename CTypeTraits<c_value_type>::ArrowType;
const auto& shape = tensor.shape();
const auto ndim = tensor.ndim();
const auto ndim = static_cast<size_t>(tensor.ndim());
std::vector<int64_t> coord(ndim, 0);

constexpr c_value_type zero = 0;
c_value_type x;
int64_t i;
size_t i;
for (int64_t n = tensor.size(); n > 0; --n) {
x = tensor.Value<ValueType>(coord);
if (ARROW_PREDICT_FALSE(x != zero)) {
Expand Down
37 changes: 21 additions & 16 deletions cpp/src/arrow/tensor/csf_converter.cc
Original file line number Diff line number Diff line change
Expand Up @@ -41,14 +41,15 @@ namespace {

inline void IncrementIndex(std::vector<int64_t>& coord, const std::vector<int64_t>& shape,
const std::vector<int64_t>& axis_order) {
const int64_t ndim = shape.size();
const int64_t last_axis = axis_order[ndim - 1];
const auto ndim = shape.size();
const auto last_axis = static_cast<size_t>(axis_order[ndim - 1]);
++coord[last_axis];
if (coord[last_axis] == shape[last_axis]) {
int64_t d = ndim - 1;
while (d > 0 && coord[axis_order[d]] == shape[axis_order[d]]) {
coord[axis_order[d]] = 0;
++coord[axis_order[d - 1]];
auto d = ndim - 1;
while (d > 0 && coord[static_cast<size_t>(axis_order[d])] ==
shape[static_cast<size_t>(axis_order[d])]) {
coord[static_cast<size_t>(axis_order[d])] = 0;
++coord[static_cast<size_t>(axis_order[d - 1])];
--d;
}
}
Expand All @@ -74,7 +75,7 @@ class SparseCSFTensorConverter : private SparseTensorConverterMixin {
const int index_elsize = index_value_type_->byte_width();
const int value_elsize = tensor_.type()->byte_width();

const int64_t ndim = tensor_.ndim();
const auto ndim = static_cast<size_t>(tensor_.ndim());
// Axis order as ascending order of dimension size is a good heuristic but is not
// necessarily optimal.
std::vector<int64_t> axis_order = internal::ArgSort(tensor_.shape());
Expand Down Expand Up @@ -107,8 +108,8 @@ class SparseCSFTensorConverter : private SparseTensorConverterMixin {
std::copy_n(xp, value_elsize, values);
values += value_elsize;

for (int64_t i = 0; i < ndim; ++i) {
int64_t dimension = axis_order[i];
for (size_t i = 0; i < ndim; ++i) {
auto dimension = static_cast<size_t>(axis_order[i]);

tree_split = tree_split || (coord[dimension] != previous_coord[dimension]);
if (tree_split) {
Expand All @@ -133,7 +134,7 @@ class SparseCSFTensorConverter : private SparseTensorConverterMixin {
}
}

for (int64_t column = 0; column < ndim - 1; ++column) {
for (size_t column = 0; column < ndim - 1; ++column) {
AssignIndex(index_buffer, counts[column + 1], index_elsize);
RETURN_NOT_OK(indptr_buffer_builders[column].Append(index_buffer, index_elsize));
}
Expand All @@ -146,11 +147,11 @@ class SparseCSFTensorConverter : private SparseTensorConverterMixin {
std::vector<int64_t> indptr_shapes(counts.begin(), counts.end() - 1);
std::vector<int64_t> indices_shapes = counts;

for (int64_t column = 0; column < ndim; ++column) {
for (size_t column = 0; column < ndim; ++column) {
RETURN_NOT_OK(
indices_buffer_builders[column].Finish(&indices_buffers[column], true));
}
for (int64_t column = 0; column < ndim - 1; ++column) {
for (size_t column = 0; column < ndim - 1; ++column) {
RETURN_NOT_OK(indptr_buffer_builders[column].Finish(&indptr_buffers[column], true));
}

Expand Down Expand Up @@ -228,29 +229,33 @@ class TensorBuilderFromSparseCSFTensor : private SparseTensorConverterMixin {

void ExpandValues(const int64_t dim, const int64_t dim_offset, const int64_t start,
const int64_t stop) {
const auto& cur_indices = indices_[dim];
const auto& cur_indices = indices_[static_cast<size_t>(dim)];
const int indices_elsize = ElementSize(cur_indices);
const auto* indices_data = cur_indices->raw_data() + start * indices_elsize;

if (dim == ndim_ - 1) {
for (auto i = start; i < stop; ++i) {
const int64_t index =
SparseTensorConverterMixin::GetIndexValue(indices_data, indices_elsize);
const int64_t offset = dim_offset + index * strides_[axis_order_[dim]];
const int64_t offset =
dim_offset +
index * strides_[static_cast<size_t>(axis_order_[static_cast<size_t>(dim)])];

std::copy_n(raw_data_ + i * value_elsize_, value_elsize_, values_ + offset);

indices_data += indices_elsize;
}
} else {
const auto& cur_indptr = indptr_[dim];
const auto& cur_indptr = indptr_[static_cast<size_t>(dim)];
const int indptr_elsize = ElementSize(cur_indptr);
const auto* indptr_data = cur_indptr->raw_data() + start * indptr_elsize;

for (int64_t i = start; i < stop; ++i) {
const int64_t index =
SparseTensorConverterMixin::GetIndexValue(indices_data, indices_elsize);
const int64_t offset = dim_offset + index * strides_[axis_order_[dim]];
const int64_t offset =
dim_offset +
index * strides_[static_cast<size_t>(axis_order_[static_cast<size_t>(dim)])];
const int64_t next_start = GetIndexValue(indptr_data, indptr_elsize);
const int64_t next_stop =
GetIndexValue(indptr_data + indptr_elsize, indptr_elsize);
Expand Down

0 comments on commit 8885e41

Please sign in to comment.