original_docstring: r"""This is the slowpath function for Eager mode.
    This is for function _while
    
docstring: r"""This is the slowpath function for Eager mode.
  This is for function _while
docstring_tokens: r " " " This is the slowpath function for Eager mode . This is for function _while
code: def _while_eager_fallback(input, cond, body, output_shapes=[], parallel_iterations=10, name=None, ctx=None):
    r"""This is the slowpath function for Eager mode.
    This is for function _while
    """
    _ctx = ctx if ctx else _context.context()
    if output_shapes is None:
      output_shapes = []
    if not isinstance(output_shapes, (list, tuple)):
      raise TypeError(
          "Expected list for 'output_shapes' argument to "
          "'while' Op, not %r." % output_shapes)
    output_shapes = [_execute.make_shape(_s, "output_shapes") for _s in output_shapes]
    if parallel_iterations is None:
      parallel_iterations = 10
    parallel_iterations = _execute.make_int(parallel_iterations, "parallel_iterations")
    _attr_T, input = _execute.convert_to_mixed_eager_tensors(input, _ctx)
    _inputs_flat = list(input)
    _attrs = ("T", _attr_T, "cond", cond, "body", body, "output_shapes",
    output_shapes, "parallel_iterations", parallel_iterations)
    _result = _execute.execute(b"While", len(input), inputs=_inputs_flat,
                               attrs=_attrs, ctx=_ctx, name=name)
    _execute.record_gradient(
        "While", _inputs_flat, _attrs, _result, name)
    return _result
code_tokens: def _while_eager_fallback ( input , cond , body , output_shapes = [ ] , parallel_iterations = 10 , name = None , ctx = None ) : _ctx = ctx if ctx else _context . context ( ) if output_shapes is None : output_shapes = [ ] if not isinstance ( output_shapes , ( list , tuple ) ) : raise TypeError ( "Expected list for 'output_shapes' argument to " "'while' Op, not %r." % output_shapes ) output_shapes = [ _execute . make_shape ( _s , "output_shapes" ) for _s in output_shapes ] if parallel_iterations is None : parallel_iterations = 10 parallel_iterations = _execute . make_int ( parallel_iterations , "parallel_iterations" ) _attr_T , input = _execute . convert_to_mixed_eager_tensors ( input , _ctx ) _inputs_flat = list ( input ) _attrs = ( "T" , _attr_T , "cond" , cond , "body" , body , "output_shapes" , output_shapes , "parallel_iterations" , parallel_iterations ) _result = _execute . execute ( b"While" , len ( input ) , inputs = _inputs_flat , attrs = _attrs , ctx = _ctx , name = name ) _execute . record_gradient ( "While" , _inputs_flat , _attrs , _result , name ) return _result
short_docstring: r"""This is the slowpath function for Eager mode.
short_docstring_tokens: r " " " This is the slowpath function for Eager mode .
comment: r"""This is the slowpath function for Eager mode.
    This is for function _while
    """