[Mlir-commits] [mlir] [mlir][tensor] Add a tensor.concat operation (PR #72779)

[llvmlistbot at llvm.org]

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@@ -121,6 +121,66 @@ def Tensor_CastOp : Tensor_Op<"cast", [
   let hasCanonicalizer = 1;
 }
 
+//===----------------------------------------------------------------------===//
+// ConcatOp
+//===----------------------------------------------------------------------===//
+
+def Tensor_ConcatOp : Tensor_Op<"concat",
+    [Pure,
+     DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>,
+     DeclareOpInterfaceMethods<ReifyRankedShapedTypeOpInterface>]> {
+  let summary = "tensor concatenation operation";
+  let description = [{
+    The "concat" operation constructs a tensor out of a variadic list of input
+    tensors, concatenated along a static dimension. All inputs and the result
+    type must share the same rank.
+
+    `dim` specifies the dimension along which to concatenate. The size of the
+    concatenated dimension in the result must be equal to the sum of the sizes
+    of the inputs along that dimension. All other dimensions in both the inputs
+    and result must be the same size.
+
+    Example:
+
+    ```mlir
+    %0 = tensor.concat dim(0) %0, %1, %2 :
----------------
MaheshRavishankar wrote:

I dont think `memref.concat` makes sense. The norm is that `memref` operations dont have copy semantics, so `memref.concat` might not be expressible as that (without introducing some pointer arithmetic stuff). I think at `memref` level `memref.subviews` + `memref.copy` are better representation of concat, with something else converting the `tensor.concat` into as much as in-place update as possible. Given that I think not having DPS for `concat` might be fine... 

https://github.com/llvm/llvm-project/pull/72779