class_docstr: Insert a single-dimension in a 1D or higher tensor at each axis in axes.
  
  Parameters
  ----------
  x: tensor<*?, T> (Required)
      * Scalar or tensor.
  axes: const tensor<[K], i32> Required
      * ``K`` is the number of dimensions expanded.
      * Insert single dimension at dimension index at each axes.
      * Negative value to index from the end. ``-d-1 <= axis <= d``
        where ``d`` is the rank of ``x``.
  
  Returns
  -------
  tensor<*(rank(x)+K), T>
      * Same type as the input ``x`` with rank ``rank(x)+K``.
  
  Attributes
  ----------
  T: fp32
code: def __init__(self, **kwargs):
      super(expand_dims, self).__init__(**kwargs)
  
imports: import functools
  import sympy
  from coremltools.converters.mil.mil.types.symbolic import is_symbolic, isscalar, any_symbolic, any_variadic
  from coremltools.converters.mil.mil import get_new_symbol, get_new_variadic_symbol, VALUE, SYMBOL, types
  from ._op_reqs import *
label_desc: Use image node_id 1 to create a new expand_dims object from inherited base classes: Operation with example: obj = expand_dims()