original_docstring: r"""This is the slowpath function for Eager mode.
    This is for function stateless_while
    
docstring: r"""This is the slowpath function for Eager mode.
  This is for function stateless_while
docstring_tokens: r " " " This is the slowpath function for Eager mode . This is for function stateless_while
code: def stateless_while_eager_fallback(input, cond, body, name=None, ctx=None):
    r"""This is the slowpath function for Eager mode.
    This is for function stateless_while
    """
    _ctx = ctx if ctx else _context.context()
    _attr_T, input = _execute.convert_to_mixed_eager_tensors(input, _ctx)
    _inputs_flat = list(input)
    _attrs = ("T", _attr_T, "cond", cond, "body", body)
    _result = _execute.execute(b"StatelessWhile", len(input),
                               inputs=_inputs_flat, attrs=_attrs, ctx=_ctx,
                               name=name)
    _execute.record_gradient(
        "StatelessWhile", _inputs_flat, _attrs, _result, name)
    return _result
code_tokens: def stateless_while_eager_fallback ( input , cond , body , name = None , ctx = None ) : _ctx = ctx if ctx else _context . context ( ) _attr_T , input = _execute . convert_to_mixed_eager_tensors ( input , _ctx ) _inputs_flat = list ( input ) _attrs = ( "T" , _attr_T , "cond" , cond , "body" , body ) _result = _execute . execute ( b"StatelessWhile" , len ( input ) , inputs = _inputs_flat , attrs = _attrs , ctx = _ctx , name = name ) _execute . record_gradient ( "StatelessWhile" , _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 stateless_while
    """