class_docstr: Reverses variable length slices for specified axes / dimensions of the input
  tensor. This op first slice input tensor along the ``batch_axis`` dimension, then
  partially reverse the elements along the ``seq_axis`` for the first ``lengths[i]``
  elements.
  
  Parameters
  ----------
  x: tensor<*?, T> (Required)
      * Input tensor.
  lengths: const<L, i32> (Required)
      * 1-dimensional tensor of length ``x.shape[batch_axis]`` specifying the length
        of the sequence to reverse.
      * Values must be in range ``[0, x.shape[seq_axis]]``.
  seq_axis: const<i32> (Optional)
      * The dimension to reverse.
      * Defaults to ``0``.
  batch_axis: const<i32> (Optional)
      * Dimension for slicing.
      * Defaults to ``0``.
  
  Returns
  -------
  tensor<*?, T>
      * same type and shape as the input tensor.
  
  Attributes
  ----------
  T: fp32
code: def __init__(self, **kwargs):
      super(reverse_sequence, 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 reverse_sequence object from inherited base classes: Operation with example: obj = reverse_sequence()