[mlir][docs] Fix typos in documentation for MLIR tensor dialect #119095
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@llvm/pr-subscribers-mlir-tensor @llvm/pr-subscribers-mlir Author: Giordano Salvador (e3m3) ChangesFix typos in the tensor dialect documentation as referenced in this discourse topic.
Full diff: https://github.com/llvm/llvm-project/pull/119095.diff 1 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td b/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td
index b73da8bb6af59c..812ac209845020 100644
--- a/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td
+++ b/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td
@@ -213,11 +213,11 @@ def Tensor_DimOp : Tensor_Op<"dim", [
// Return the dynamic dimension of %A.
%c1 = arith.constant 1 : index
- %y = tensor.dim %A, %c1 : memref<4x?xf32>
+ %y = tensor.dim %A, %c1 : tensor<4x?xf32>
// Equivalent generic form:
- %x = "tensor.dim"(%A, %c0) : (memref<4x?xf32>, index) -> index
- %y = "tensor.dim"(%A, %c1) : (memref<4x?xf32>, index) -> index
+ %x = "tensor.dim"(%A, %c0) : (tensor<4x?xf32>, index) -> index
+ %y = "tensor.dim"(%A, %c1) : (tensor<4x?xf32>, index) -> index
```
}];
@@ -673,7 +673,7 @@ def Tensor_GatherOp : Tensor_Op<"gather", [
At the tensor-level, the index tensor is specified in an AoS form (i.e.
coordinate tuple is the most minor). It is the responsibility of further
- lowerings and bufferiation to implement various concrete layouts.
+ lowerings and bufferization to implement various concrete layouts.
Note: As currently specified, the operation must lower to an abstraction that
performs copies to the output tensor. This is because the buffer type system
@@ -710,7 +710,7 @@ def Tensor_GatherOp : Tensor_Op<"gather", [
let extraClassDeclaration = [{
// TODO: InferTypeOpInterface once enough confidence is built with
- // tensor<tensor> and its lwoering to memref<memref>.
+ // tensor<tensor> and its lowering to memref<memref>.
static RankedTensorType inferResultType(RankedTensorType sourceType,
RankedTensorType indicesType,
ArrayRef<int64_t> gatherDims,
@@ -1673,7 +1673,7 @@ def Tensor_ScatterOp : Tensor_Op<"scatter", [
source tensor has size `1`.
I.e. if the dest type is `axbxcxd` and the coordinates are [1, 3], then
the source type suffix is `ax1xcx1`.
- Sactter also allows rank-reducing semantics where the shape `ax1xcx1` can be
+ Scatter also allows rank-reducing semantics where the shape `ax1xcx1` can be
further simplified to `axc`.
The elemental type of the indices tensor can be any integer type.
@@ -1693,7 +1693,7 @@ def Tensor_ScatterOp : Tensor_Op<"scatter", [
At the tensor-level, the index tensor is specified in an AoS form (i.e.
coordinate tuple is the most minor). It is the responsibility of further
- lowerings and bufferiation to implement various concrete layouts.
+ lowerings and bufferization to implement various concrete layouts.
Note: As currently specified, the operation must lower to an abstraction that
performs copies to the output tensor. This is because the buffer type system
@@ -2115,7 +2115,7 @@ def Tensor_UnPackOp : Tensor_RelayoutOp<"unpack"> {
/// Check if this UnPackOp is like a simple unpad operation.
/// In other words, this operation:
/// 1. drops useless dimensions (dimension of size 1), and
- /// 2. reduces dimensions in place (i.e., no tranpose.)
+ /// 2. reduces dimensions in place (i.e., no transpose.)
bool isLikeUnPad();
}];
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e3m3
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Thanks for the approval @joker-eph. Apologies for the force push after review; there was a typo in the git commit message "documention" -> "documentation". |
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3 participants
Fix typos in the tensor dialect documentation as referenced in this discourse topic.
memreftype fortensor.dimop.