input: Write a function to optimize a Python program that processes a 2d array and stores the transpose output in a new array. If the input array is empty, return an empty array. The function should be efficient in terms of both time and space complexity.
  
  def transpose(A):
   if not A:
   return []
   n = len(A)
   m = len(A[0])
   B = [[0 for x in range(n)] for x in range(m)]
   for i in range(n):
   for j in range(m):
   B[j][i] = A[i][j]
   return B
  
  assert transpose([[1, 2, 3], [4, 5, 6]]) == [[1, 4], [2, 5], [3, 6]]
  assert transpose([[1, 2], [3, 4], [5, 6]]) == [[1, 3, 5], [2, 4, 6]]
  assert transpose([[]]) == [[]]
  assert transpose([]) == []
output: def transpose(A):
      if not A:
          return []
      n = len(A)
      m = len(A[0])
      B = [[0 for x in range(n)] for x in range(m)]
      for i in range(n):
          for j in range(m):
              B[j][i] = A[i][j]
      return B