[mlir][linalg] Introduce transpose semantic to 'linalg.matmul' ops. (#104783)

The main goal of this patch is to extend the semantic of 'linalg.matmul'
named op to include per operand transpose semantic while also laying out
a way to move ops definition from OpDSL to tablegen. Hence, it is
implemented in tablegen. Transpose semantic is as follows.

By default 'linalg.matmul' behavior will remain as is. Transpose
semantics can be appiled on per input operand by specifying the optional
permutation attributes (namely 'permutationA' for 1st input and
'permutationB' for 2nd input) for each operand explicitly as needed. By
default, no transpose is mandated for any of the input operand.

    Example:
    ```
%val = linalg.matmul ins(%arg0, %arg1 : memref<5x3xf32>,
memref<5x7xf32>)
              outs(%arg2: memref<3x7xf32>)
              permutationA = [1, 0]
              permutationB = [0, 1]
    ```

Author: shahidact

mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py

@@ -383,23 +383,6 @@ def select(
     O[None] = TernaryFn.select(cond[None], lhs[None], rhs[None])
 
 
-@linalg_structured_op
-def matmul(
-    A=TensorDef(T1, S.M, S.K),
-    B=TensorDef(T2, S.K, S.N),
-    C=TensorDef(U, S.M, S.N, output=True),
-    cast=TypeFnAttrDef(default=TypeFn.cast_signed),
-):
-    """Performs a matrix multiplication of two 2D inputs.
-
-    Numeric casting is performed on the operands to the inner multiply, promoting
-    them to the same data type as the accumulator/output.
-    """
-    domain(D.m, D.n, D.k)
-    implements(ContractionOpInterface)
-    C[D.m, D.n] += cast(U, A[D.m, D.k]) * cast(U, B[D.k, D.n])
-
-
 @linalg_structured_op
 def quantized_matmul(
     A=TensorDef(T1, S.M, S.K),