This is an archive of the discontinued LLVM Phabricator instance.

Show First 20 Lines • Show All 155 Lines • ▼ Show 20 Lines	let description = [{
```mlir		```mlir
%1 = sparse_tensor.values %0 : tensor<64x64xf64, #CSR> to memref<?xf64>		%1 = sparse_tensor.values %0 : tensor<64x64xf64, #CSR> to memref<?xf64>
```		```
}];		}];
let assemblyFormat = "$tensor attr-dict `:` type($tensor) `to` type($result)";		let assemblyFormat = "$tensor attr-dict `:` type($tensor) `to` type($result)";
let hasVerifier = 1;		let hasVerifier = 1;
}		}

def SparseTensor_ConcatenateOp : SparseTensor_Op<"concatenate", []>,		def SparseTensor_ConcatenateOp : SparseTensor_Op<"concatenate", [NoSideEffect]>,
Arguments<(ins Variadic<AnyRankedTensor>:$inputs, IndexAttr:$dimension)>,		Arguments<(ins Variadic<AnyRankedTensor>:$inputs, IndexAttr:$dimension)>,
Results<(outs AnyRankedTensor:$result)> {		Results<(outs AnyRankedTensor:$result)> {

let summary = "Concatenates a list of tensors into a single tensor.";		let summary = "Concatenates a list of tensors into a single tensor.";
let description = [{		let description = [{
Concatenates a list input tensors and the output tensor with the same rank.		Concatenates a list input tensors and the output tensor with the same rank.
The concatenation happens on the specified `dimension` (0<= dimension < rank).		The concatenation happens on the specified `dimension` (0<= dimension < rank).
The resulting `dimension` size is the sum of all the input dimension sizes,		The resulting `dimension` size is the sum of all the input dimension sizes,
▲ Show 20 Lines • Show All 549 Lines • Show Last 20 Lines

mlir/test/Dialect/SparseTensor/fold.mlir

	Show All 26 Lines
	// CHECK-NOT: sparse_tensor.values			// CHECK-NOT: sparse_tensor.values
	// CHECK: return			// CHECK: return
	func.func @sparse_dce_getters(%arg0: tensor<64xf32, #SparseVector>) {			func.func @sparse_dce_getters(%arg0: tensor<64xf32, #SparseVector>) {
	%0 = sparse_tensor.pointers %arg0 { dimension = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>			%0 = sparse_tensor.pointers %arg0 { dimension = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>
	%1 = sparse_tensor.indices %arg0 { dimension = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>			%1 = sparse_tensor.indices %arg0 { dimension = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>
	%2 = sparse_tensor.values %arg0 : tensor<64xf32, #SparseVector> to memref<?xf32>			%2 = sparse_tensor.values %arg0 : tensor<64xf32, #SparseVector> to memref<?xf32>
	return			return
	}			}
				// CHECK-LABEL: func @sparse_concat_dce(
				// CHECK-NOT: sparse_tensor.values
				aartbikUnsubmitted Done Reply Inline Actions CHECK-NOT: sparse_tensor.concatenate ;-) aartbik: CHECK-NOT: sparse_tensor.concatenate ;-)
				// CHECK: return
				func.func @sparse_concat_dce(%arg0: tensor<2xf64, #SparseVector>,
				%arg1: tensor<3xf64, #SparseVector>,
				%arg2: tensor<4xf64, #SparseVector>) {
				%0 = sparse_tensor.concatenate %arg0, %arg1, %arg2 {dimension = 0 : index}
				: tensor<2xf64, #SparseVector>,
				tensor<3xf64, #SparseVector>,
				tensor<4xf64, #SparseVector> to tensor<9xf64, #SparseVector>
				return
				}

This is an archive of the discontinued LLVM Phabricator instance.

[mlir][sparse] Mark sparse_tensor.concatenate as NoSideEffectClosedPublic

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mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td

mlir/test/Dialect/SparseTensor/fold.mlir

[mlir][sparse] Mark sparse_tensor.concatenate as NoSideEffect
ClosedPublic