[TransOp fusion]: Fuse `tt.trans` with `tt.load` to expoit 2D block read operations

[etiotto]

Consider a loop containing a tt.dot operation that consume the result of a transposition operation:

    %13:3 = scf.for %arg3 = %c0_i32 to %c1024_i32 step %c32_i32 iter_args(%arg4 = %cst, %arg5 = %c0_i32, %arg6 = %10) -> (tensor<256x256xf32, #mma>, i32, !tt.ptr<tensor<256x32xbf16, #linear>>) : i32 {
      %17 = tt.advance %9, [%11, %arg5] : <tensor<256x32xbf16, #ttg.dot_op<{opIdx = 0, parent = #mma, kWidth = 1}>>>
      %18 = tt.load %17 {boundaryCheck = array<i32: 0, 1>, ttig.block_io = "row_major"} : !tt.ptr<tensor<256x32xbf16, #ttg.dot_op<{opIdx = 0, parent = #mma, kWidth = 1}>>>
      %19 = tt.advance %arg6, [%12, %arg5] : <tensor<256x32xbf16, #linear>>
      %20 = tt.load %19 {boundaryCheck = array<i32: 0, 1>, ttig.block_io = "column_major"} : !tt.ptr<tensor<256x32xbf16, #linear>>
      %21 = tt.trans %20 {order = array<i32: 1, 0>} : tensor<256x32xbf16, #linear> -> tensor<32x256xbf16, #ttg.dot_op<{opIdx = 1, parent = #mma, kWidth = 2}>>
      %22 = tt.dot %18, %21, %arg4, inputPrecision = tf32 : tensor<256x32xbf16, #ttg.dot_op<{opIdx = 0, parent = #mma, kWidth = 1}>> * tensor<32x256xbf16, #ttg.dot_op<{opIdx = 1, parent = #mma, kWidth = 2}>> -> tensor<256x256xf32, #mma>
      %23 = arith.addi %arg5, %c32_i32 : i32
      scf.yield %22, %23, %19 : tensor<256x256xf32, #mma>, i32, !tt.ptr<tensor<256x32xbf16, #linear>>
    }

Here the load for operand "B" of the tt.dot operation lacks the dot layout and therefore it is not lowered to efficient 2D block read HW primitives. In order to improve performance the Triton BE can implement a new transformation aimed at fusing a tt.load operation with a tt.transpose into a new load operation (for a transposed tensor) with block_io layout "row_major".