forked from OSchip/llvm-project
[mlir] Add to shape.is_broadcastable description
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@ -188,6 +188,11 @@ def Shape_IsBroadcastableOp : Shape_Op<"is_broadcastable", [Commutative]> {
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they are broadcastable. This broadcastable follows the same logic as what
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shape.broadcast documents.
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Concretely, shape.is_broadcastable returning true implies that
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shape.broadcast will not give an error, and shape.cstr_broadcastable will
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not result in an assertion failure. Similarly, false implies an error or
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assertion failure.
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Example:
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```mlir
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%true = shape.is_broadcastable [2,2], [3,1,2]
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@ -199,7 +204,7 @@ def Shape_IsBroadcastableOp : Shape_Op<"is_broadcastable", [Commutative]> {
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Shape_ShapeOrExtentTensorType:$rhs);
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let results = (outs I1:$result);
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let assemblyFormat = "$lhs `,` $rhs `:` type($lhs) `,` type($rhs) attr-dict";
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let assemblyFormat = "$lhs `,` $rhs attr-dict `:` type($lhs) `,` type($rhs)";
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}
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def Shape_RankOp : Shape_Op<"rank", [NoSideEffect]> {
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