code: def matrix_to_qubit(matrix):
      """Convert from the matrix repr. to a sum of Qubit objects.
  
      Parameters
      ----------
      matrix : Matrix, numpy.matrix, scipy.sparse
          The matrix to build the Qubit representation of. This works with
          SymPy matrices, numpy matrices and scipy.sparse sparse matrices.
  
      Examples
      ========
  
      Represent a state and then go back to its qubit form:
  
          >>> from sympy.physics.quantum.qubit import matrix_to_qubit, Qubit
          >>> from sympy.physics.quantum.represent import represent
          >>> q = Qubit('01')
          >>> matrix_to_qubit(represent(q))
          |01>
      """
      # Determine the format based on the type of the input matrix
      format = "sympy"
      if isinstance(matrix, numpy_ndarray):
          format = "numpy"
      if isinstance(matrix, scipy_sparse_matrix):
          format = "scipy.sparse"
  
      # Make sure it is of correct dimensions for a Qubit-matrix representation.
      # This logic should work with sympy, numpy or scipy.sparse matrices.
      if matrix.shape[0] == 1:
          mlistlen = matrix.shape[1]
          nqubits = log(mlistlen, 2)
          ket = False
          cls = QubitBra
      elif matrix.shape[1] == 1:
          mlistlen = matrix.shape[0]
          nqubits = log(mlistlen, 2)
          ket = True
          cls = Qubit
      else:
          raise QuantumError(
              "Matrix must be a row/column vector, got %r" % matrix
          )
      if not isinstance(nqubits, Integer):
          raise QuantumError(
              "Matrix must be a row/column vector of size "
              "2**nqubits, got: %r" % matrix
          )
      # Go through each item in matrix, if element is non-zero, make it into a
      # Qubit item times the element.
      result = 0
      for i in range(mlistlen):
          if ket:
              element = matrix[i, 0]
          else:
              element = matrix[0, i]
          if format in ("numpy", "scipy.sparse"):
              element = complex(element)
          if element != 0.0:
              # Form Qubit array; 0 in bit-locations where i is 0, 1 in
              # bit-locations where i is 1
              qubit_array = [
                  int(i & (1 << x) != 0) for x in range(nqubits)
              ]
              qubit_array.reverse()
              result = result + element * cls(*qubit_array)
  
      # If SymPy simplified by pulling out a constant coefficient, undo that.
      if isinstance(result, (Mul, Add, Pow)):
          result = result.expand()
  
      return result
  
imports: import math
  from sympy.core.add import Add
  from sympy.core.mul import Mul
  from sympy.core.numbers import Integer
  from sympy.core.power import Pow
  from sympy.core.singleton import S
  from sympy.functions.elementary.complexes import conjugate
  from sympy.functions.elementary.exponential import log
  from sympy.core.basic import _sympify
  from sympy.external.gmpy import SYMPY_INTS
  from sympy.matrices import Matrix, zeros
  from sympy.printing.pretty.stringpict import prettyForm
  from sympy.physics.quantum.hilbert import ComplexSpace
  from sympy.physics.quantum.state import Ket, Bra, State
  from sympy.physics.quantum.qexpr import QuantumError
  from sympy.physics.quantum.represent import represent
  from sympy.physics.quantum.matrixutils import numpy_ndarray, scipy_sparse_matrix
  from mpmath.libmp.libintmath import bitcount
label_desc: Use image node_id 1 for calling a global function with example usage: matrix_to_qubit(matrix) and returns: result