[MLIR][Linalg] Introduce Python API for linalg.batch_matmul Ops. (#127614)

As linalg.batch_matmul has been moved into tablegen from OpDSL, its
derived python wrapper no longer exist.This patch adds the required
python wrapper.

Also refactors the BatchmatmulOp printer to make it consistent with its
parser.

Author: shahidact

mlir/python/mlir/dialects/linalg/__init__.py

@@ -149,7 +149,8 @@ def __init__(
 generic = region_op(GenericOp_, terminator=YieldOp)
 
 
-def matmul(
+def create_op(
+    op_type,
     *ins: Union[Operation, OpView, Value],
     outs: Sequence[Union[Operation, OpView, Value]],
     indexing_maps: Optional[Sequence[AffineMapAttr]] = None,
@@ -161,7 +162,7 @@ def matmul(
     init = _get_op_result_or_value(outs[0])
     result_types = [init.type] if isinstance(init.type, RankedTensorType) else []
 
-    op = MatmulOp(
+    op = op_type(
         result_tensors=result_types,
         inputs=ins,
         outputs=[init],
@@ -172,24 +173,32 @@ def matmul(
     return op
 
 
+def matmul(
+    *ins: Union[Operation, OpView, Value],
+    outs: Sequence[Union[Operation, OpView, Value]],
+    indexing_maps: Optional[Sequence[AffineMapAttr]] = None,
+    cast: Optional[Union[TypeFn, Attribute]] = None,
+):
+    return create_op(MatmulOp, *ins, outs=outs, indexing_maps=indexing_maps, cast=cast)
+
+
+def batch_matmul(
+    *ins: Union[Operation, OpView, Value],
+    outs: Sequence[Union[Operation, OpView, Value]],
+    indexing_maps: Optional[Sequence[AffineMapAttr]] = None,
+    cast: Optional[Union[TypeFn, Attribute]] = None,
+):
+    return create_op(
+        BatchMatmulOp, *ins, outs=outs, indexing_maps=indexing_maps, cast=cast
+    )
+
+
 def contract(
     *ins: Union[Operation, OpView, Value],
     outs: Sequence[Union[Operation, OpView, Value]],
     indexing_maps: Sequence[AffineMapAttr],
     cast: Optional[Union[TypeFn, Attribute]] = None,
 ):
-    ins = [_get_op_result_or_value(input) for input in ins]
-    if len(outs) > 1:
-        raise ValueError(f"{outs=} must have length 1.")
-    init = _get_op_result_or_value(outs[0])
-    result_types = [init.type] if isinstance(init.type, RankedTensorType) else []
-
-    op = ContractOp(
-        result_tensors=result_types,
-        inputs=ins,
-        outputs=[init],
-        indexing_maps=indexing_maps,
-        cast=cast,
+    return create_op(
+        ContractOp, *ins, outs=outs, indexing_maps=indexing_maps, cast=cast
     )
-    fill_builtin_region(op.operation)
-    return op