[Mlir-commits] [mlir] 7482cd6 - [mlir][sparse] updated our sparse dialect doc with some recent changes

[Aart Bik]

Author: Aart Bik
Date: 2022-06-07T14:27:57-07:00
New Revision: 7482cd6869317bce29366701a8baa3b0ef125566

URL: https://github.com/llvm/llvm-project/commit/7482cd6869317bce29366701a8baa3b0ef125566
DIFF: https://github.com/llvm/llvm-project/commit/7482cd6869317bce29366701a8baa3b0ef125566.diff

LOG: [mlir][sparse] updated our sparse dialect doc with some recent changes

The `init` and `tensor` ops are renamed (and one moved to another dialect).

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D127169

Added: 
    

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

Removed: 
    


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diff  --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td
index bdc27b57fe10f..fc09a068fe285 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td
@@ -180,9 +180,9 @@ def SparseTensor_LexInsertOp : SparseTensor_Op<"lex_insert", []>,
     Inserts the given value at given indices into the underlying sparse
     storage format of the given tensor with the given indices. This
     operation can only be applied when a tensor materializes unintialized
-    with an `init` operation, the insertions occur in strict lexicographical
-    index order, and the final tensor is constructed with a `tensor`
-    operation that has the `hasInserts` attribute set.
+    with a `bufferization.alloc_tensor` operation, the insertions occur in
+    strict lexicographical index order, and the final tensor is constructed
+    with a `load` operation that has the `hasInserts` attribute set.
 
     Note that this operation is "impure" in the sense that its behavior
     is solely defined by side-effects and not SSA values. The semantics
@@ -309,12 +309,12 @@ def SparseTensor_ReleaseOp : SparseTensor_Op<"release", []>,
   string summary = "Releases underlying sparse storage format of given tensor";
   string description = [{
     Releases the underlying sparse storage format for a tensor that
-    materialized earlier through a `new` operator, `init` operator, or a
-    `convert` operator with an annotated tensor type as destination (unless
-    that convert is folded away since the source and destination types were
-    identical). This operation should only be called once for any materialized
-    tensor.  Also, after this operation, any subsequent `memref` querying
-    operation on the tensor returns undefined results.
+    materialized earlier through a `new` operation, a `convert` operation
+    with annotated destination tensor type (unless the convert is folded
+    away), or a `bufferization.alloc_tensor` operation. The release operation
+    should only be called once for any materialized tensor. After this
+    operation, any subsequent `memref` querying operation on the tensor
+    returns undefined results.
 
     Note that this operation is "impure" in the sense that its behavior
     is solely defined by side-effects and not SSA values. The semantics
@@ -418,7 +418,7 @@ def SparseTensor_BinaryOp : SparseTensor_Op<"binary", [NoSideEffect]>,
           %result = sparse_tensor.binary %a, %b : f64, f64 to f64
             overlap={
               ^bb0(%x: f64, %y: f64):
-                %cmp = arith.cmpi "uge", %column, %row : index
+                %cmp = arith.cmpi "uge", %col, %row : index
                 %upperTriangleResult = arith.addf %x, %y : f64
                 %lowerTriangleResult = arith.subf %x, %y : f64
                 %ret = arith.select %cmp, %upperTriangleResult, %lowerTriangleResult : f64
@@ -427,9 +427,9 @@ def SparseTensor_BinaryOp : SparseTensor_Op<"binary", [NoSideEffect]>,
             left=identity
             right={
               ^bb0(%y: f64):
-                %cmp = arith.cmpi "uge", %column, %row : index
+                %cmp = arith.cmpi "uge", %col, %row : index
                 %lowerTriangleResult = arith.negf %y : f64
-                %ret = arith.select %cmp, %y, %lowerTriangleResult
+                %ret = arith.select %cmp, %y, %lowerTriangleResult : f64
                 sparse_tensor.yield %ret : f64
             }
           linalg.yield %result : f64