class_docstr: N-dimensional array.
  
  Examples
  ========
  
  Create an N-dim array of zeros:
  
  >>> from sympy import MutableDenseNDimArray
  >>> a = MutableDenseNDimArray.zeros(2, 3, 4)
  >>> a
  [[[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]]
  
  Create an N-dim array from a list;
  
  >>> a = MutableDenseNDimArray([[2, 3], [4, 5]])
  >>> a
  [[2, 3], [4, 5]]
  
  >>> b = MutableDenseNDimArray([[[1, 2], [3, 4], [5, 6]], [[7, 8], [9, 10], [11, 12]]])
  >>> b
  [[[1, 2], [3, 4], [5, 6]], [[7, 8], [9, 10], [11, 12]]]
  
  Create an N-dim array from a flat list with dimension shape:
  
  >>> a = MutableDenseNDimArray([1, 2, 3, 4, 5, 6], (2, 3))
  >>> a
  [[1, 2, 3], [4, 5, 6]]
  
  Create an N-dim array from a matrix:
  
  >>> from sympy import Matrix
  >>> a = Matrix([[1,2],[3,4]])
  >>> a
  Matrix([
  [1, 2],
  [3, 4]])
  >>> b = MutableDenseNDimArray(a)
  >>> b
  [[1, 2], [3, 4]]
  
  Arithmetic operations on N-dim arrays
  
  >>> a = MutableDenseNDimArray([1, 1, 1, 1], (2, 2))
  >>> b = MutableDenseNDimArray([4, 4, 4, 4], (2, 2))
  >>> c = a + b
  >>> c
  [[5, 5], [5, 5]]
  >>> a - b
  [[-3, -3], [-3, -3]]
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code: def __ne__(self, other):
      return not self == other
  
imports: from sympy.core.basic import Basic
  from sympy.core.containers import Dict, Tuple
  from sympy.core.expr import Expr
  from sympy.core.kind import Kind, NumberKind, UndefinedKind
  from sympy.core.numbers import Integer
  from sympy.core.singleton import S
  from sympy.core.sympify import sympify
  from sympy.external.gmpy import SYMPY_INTS
  from sympy.printing.defaults import Printable
  import itertools
  from collections.abc import Iterable
label_desc: Use image node_id 27 for calling the NDimArray obj's underlying member method code with example usage: obj.__ne__(other) and returns: unknown