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[mlir][docs] Fix typos in documentation for MLIR tensor dialect (#119095)
Fix typos in the tensor dialect documentation: 1. Typos/Copy-paste errors referencing invalid `memref` type for `tensor.dim` op. 2. Miscellaneous typos across other tensor dialect ops.
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mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td

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@@ -213,11 +213,11 @@ def Tensor_DimOp : Tensor_Op<"dim", [
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// Return the dynamic dimension of %A.
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%c1 = arith.constant 1 : index
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%y = tensor.dim %A, %c1 : memref<4x?xf32>
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%y = tensor.dim %A, %c1 : tensor<4x?xf32>
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// Equivalent generic form:
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%x = "tensor.dim"(%A, %c0) : (memref<4x?xf32>, index) -> index
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%y = "tensor.dim"(%A, %c1) : (memref<4x?xf32>, index) -> index
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%x = "tensor.dim"(%A, %c0) : (tensor<4x?xf32>, index) -> index
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%y = "tensor.dim"(%A, %c1) : (tensor<4x?xf32>, index) -> index
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```
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}];
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@@ -673,7 +673,7 @@ def Tensor_GatherOp : Tensor_Op<"gather", [
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At the tensor-level, the index tensor is specified in an AoS form (i.e.
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coordinate tuple is the most minor). It is the responsibility of further
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lowerings and bufferiation to implement various concrete layouts.
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lowerings and bufferization to implement various concrete layouts.
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Note: As currently specified, the operation must lower to an abstraction that
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performs copies to the output tensor. This is because the buffer type system
@@ -710,7 +710,7 @@ def Tensor_GatherOp : Tensor_Op<"gather", [
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let extraClassDeclaration = [{
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// TODO: InferTypeOpInterface once enough confidence is built with
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// tensor<tensor> and its lwoering to memref<memref>.
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// tensor<tensor> and its lowering to memref<memref>.
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static RankedTensorType inferResultType(RankedTensorType sourceType,
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RankedTensorType indicesType,
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ArrayRef<int64_t> gatherDims,
@@ -1673,7 +1673,7 @@ def Tensor_ScatterOp : Tensor_Op<"scatter", [
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source tensor has size `1`.
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I.e. if the dest type is `axbxcxd` and the coordinates are [1, 3], then
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the source type suffix is `ax1xcx1`.
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Sactter also allows rank-reducing semantics where the shape `ax1xcx1` can be
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Scatter also allows rank-reducing semantics where the shape `ax1xcx1` can be
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further simplified to `axc`.
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The elemental type of the indices tensor can be any integer type.
@@ -1693,7 +1693,7 @@ def Tensor_ScatterOp : Tensor_Op<"scatter", [
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At the tensor-level, the index tensor is specified in an AoS form (i.e.
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coordinate tuple is the most minor). It is the responsibility of further
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lowerings and bufferiation to implement various concrete layouts.
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lowerings and bufferization to implement various concrete layouts.
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Note: As currently specified, the operation must lower to an abstraction that
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performs copies to the output tensor. This is because the buffer type system
@@ -2115,7 +2115,7 @@ def Tensor_UnPackOp : Tensor_RelayoutOp<"unpack"> {
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/// Check if this UnPackOp is like a simple unpad operation.
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/// In other words, this operation:
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/// 1. drops useless dimensions (dimension of size 1), and
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/// 2. reduces dimensions in place (i.e., no tranpose.)
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/// 2. reduces dimensions in place (i.e., no transpose.)
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bool isLikeUnPad();
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}];
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