[mlir][StandardOps] Fix typos in the td file.

[hanchung]

Summary

• Fix arguments name for subview and subtensor.
• Fix a typo in a comment of subtensor's method.

mlir/include/mlir/Dialect/StandardOps/IR/Ops.td

def SubViewOp : BaseOpWithOffsetSizesAndStrides<
   let summary = "memref subview operation";
   let description = [{
     The "subview" operation converts a memref type to another memref type
     which represents a reduced-size view of the original memref as specified by
     the operation's offsets, sizes and strides arguments.
 
     The SubView operation supports the following arguments:
 
-    * semref: the "base" memref on which to create a "view" memref.
+    * source: the "base" memref on which to create a "view" memref.
     * offsets: memref-rank number of offsets into the "base" memref at which to
                create the "view" memref.
     * sizes: memref-rank number of sizes which specify the sizes of the result
              "view" memref type.
     * strides: memref-rank number of strides that compose multiplicatively with
                the base memref strides in each dimension.
 
     The representation based on offsets, sizes and strides support a
def SubTensorOp : BaseOpWithOffsetSizesAndStrides<
     "subtensor", [OffsetSizeAndStrideOpInterface]> {
   let summary = "subtensor operation";
   let description = [{
     The "subtensor" operation extract a tensor from another tensor as
     specified by the operation's offsets, sizes and strides arguments.
 
     The subtensor operation supports the following arguments:
 
-    * tensor: the "base" tensor from which to extract a subtensor.
+    * source: the "base" tensor from which to extract a subtensor.
     * offsets: tensor-rank number of offsets into the "base" tensor from which
                to extract the subtensor.
     * sizes: tensor-rank number of sizes which specify the sizes of the result
              tensor type.
     * strides: tensor-rank number of strides specifying subsampling in each
                dimension.
 
     The representation based on offsets, sizes and strides support a
RankedTensorType getSourceType() {
       return source().getType().cast<RankedTensorType>();
     }
 
     /// The result of a subtensor is always a tensor.
     RankedTensorType getType() {
       return getResult().getType().cast<RankedTensorType>();
     }
 
-    /// A subview result type can be fully inferred from the source type and the
-    /// static representation of offsets, sizes and strides. Special sentinels
-    /// encode the dynamic case.
+    /// A subtensor result type can be fully inferred from the source type and
+    /// the static representation of offsets, sizes and strides. Special
+    /// sentinels encode the dynamic case.
     static Type inferResultType(RankedTensorType sourceRankedTensorType,
                                 ArrayRef<int64_t> staticOffsets,
                                 ArrayRef<int64_t> staticSizes,
                                 ArrayRef<int64_t> staticStrides);
 
     /// Return the expected rank of each of the`static_offsets`, `static_sizes`
     /// and `static_strides` attributes.
     std::array<unsigned, 3> getArrayAttrRanks() {