code: def batch_matmul_rocblas(
      cfg,
      x,
      y,
      out_shape=None,
      out_dtype=None,
      transpose_a=False,
      transpose_b=True,
  ):
      """Computes matrix multiplication of `x` and `y` via rocblas when
      `x` and `y` are batched matrices.
  
      Parameters
      ----------
      cfg : ConfigSpace
          Autotvm tuning space config file
      x : tvm.te.Tensor
          3-D with shape [batch, M, K]
      y : tvm.te.Tensor
          3-D with shape [batch, N, K]
      Returns
      -------
      output : tvm.te.Tensor
          3-D with shape [batch, M, N]
      """
      del out_dtype
      batch, M, K = get_const_tuple(x.shape)
      _, N, _ = get_const_tuple(y.shape)
      if out_shape is not None:
          assert (
              out_shape[0] == batch
          ), "Input and output batch sizes must match"
          assert (
              out_shape[1] == M and out_shape[2] == N
          ), "Invalid output shape"
      result = rocblas.batch_matmul(x, y, transpose_a, transpose_b)
      cfg.add_flop(batch * M * N * K * 2)
      return result
  
imports: from tvm import autotvm
  from tvm.contrib import rocblas
  from ..None import generic
  from ..utils import get_const_tuple
label_desc: Use image node_id 1 for calling a global function with example usage: batch_matmul_rocblas(cfg, x, y, out_shape, out_dtype, transpose_a, transpose_b) and returns: result