code: def vstack(blocks, format=None, dtype=None):
      """
      Stack sparse matrices vertically (row wise)
  
      Parameters
      ----------
      blocks
          sequence of sparse matrices with compatible shapes
      format : str, optional
          sparse format of the result (e.g., "csr")
          by default an appropriate sparse matrix format is returned.
          This choice is subject to change.
      dtype : dtype, optional
          The data-type of the output matrix. If not given, the dtype is
          determined from that of `blocks`.
  
      See Also
      --------
      hstack : stack sparse matrices horizontally (column wise)
  
      Examples
      --------
      >>> from scipy.sparse import coo_matrix, vstack
      >>> A = coo_matrix([[1, 2], [3, 4]])
      >>> B = coo_matrix([[5, 6]])
      >>> vstack([A, B]).toarray()
      array([[1, 2],
             [3, 4],
             [5, 6]])
  
      """
      return bmat([[b] for b in blocks], format=format, dtype=dtype)
  
imports: import numbers
  from functools import partial
  import numpy
  from scipy._lib._util import check_random_state, rng_integers
  from .sputils import upcast, get_index_dtype, isscalarlike
  from .csr import csr_matrix
  from .csc import csc_matrix
  from .bsr import bsr_matrix
  from .coo import coo_matrix
  from .dia import dia_matrix
  from .base import issparse
label_desc: Use image node_id 9 for calling a global function with example usage: vstack(blocks, format, dtype) and returns: bmat