PR #46723: Adjust types of loop counters

Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/46723

Reduces some warnings about comparison of integers of different signs.
Copybara import of the project:

--
311f436f77b334f5462127d8cf179cce067969ca by Marius Brehler <marius.brehler@iml.fraunhofer.de>:

Adjust types of loop counters

Reduces some warnings about comparison of integers of different signs.

PiperOrigin-RevId: 360912203
This commit is contained in:
Marius Brehler 2021-03-04 07:35:15 -08:00 committed by TensorFlow MLIR Team
parent 57e9941d5d
commit 29f70cb892
2 changed files with 3 additions and 3 deletions

View File

@ -226,7 +226,7 @@ struct GatherSlice : public OpRewritePattern<GatherOp> {
llvm::SmallVector<int64_t, 8> slice_stride(slice_end.size(), 1); llvm::SmallVector<int64_t, 8> slice_stride(slice_end.size(), 1);
llvm::SmallVector<int64_t, 8> slice_shape(slice_end.size()); llvm::SmallVector<int64_t, 8> slice_shape(slice_end.size());
for (int64_t i = 0; i < slice_end.size(); ++i) { for (size_t i = 0; i < slice_end.size(); ++i) {
slice_shape[i] = slice_end[i] - slice_start[i]; slice_shape[i] = slice_end[i] - slice_start[i];
} }
Type element_type = gather.getType().cast<TensorType>().getElementType(); Type element_type = gather.getType().cast<TensorType>().getElementType();
@ -242,7 +242,7 @@ struct GatherSlice : public OpRewritePattern<GatherOp> {
dnums.collapsed_slice_dims().getIntValues(), dnums.collapsed_slice_dims().getIntValues(),
[](const llvm::APInt& i) { return i.getSExtValue(); })); [](const llvm::APInt& i) { return i.getSExtValue(); }));
llvm::SmallVector<int64_t, 8> reshape_shape; llvm::SmallVector<int64_t, 8> reshape_shape;
for (int64_t i = 0; i < slice_shape.size(); ++i) { for (size_t i = 0; i < slice_shape.size(); ++i) {
if (llvm::count(collapsed_slice_dims, i) == 0) { if (llvm::count(collapsed_slice_dims, i) == 0) {
reshape_shape.push_back(slice_shape[i]); reshape_shape.push_back(slice_shape[i]);
} }

View File

@ -437,7 +437,7 @@ class BroadcastConverter
unsigned num_prepended_dims = llvm::size(broadcast_op.broadcast_sizes()); unsigned num_prepended_dims = llvm::size(broadcast_op.broadcast_sizes());
SmallVector<AffineExpr, 4> input_dim_exprs; SmallVector<AffineExpr, 4> input_dim_exprs;
input_dim_exprs.reserve(input_rank); input_dim_exprs.reserve(input_rank);
for (int i = 0; i < input_rank; ++i) { for (unsigned i = 0; i < input_rank; ++i) {
input_dim_exprs.push_back(b->getAffineDimExpr(num_prepended_dims + i)); input_dim_exprs.push_back(b->getAffineDimExpr(num_prepended_dims + i));
} }