def _run_paddle_cond(pred, true_fn, false_fn, true_args, false_args,
return_vars):
return_var_ids = [id(var) for var in return_vars]
# NOTE 1: Returned vars of Paddle op `control_flow.cond` must be Paddle Tensors
# NOTE 2: Here uses id(var) not var, because `if var in return_var` use operator `==`,
# which will call `fluid.layers.equal` and causes error when var in return_vars is not initialized.
true_args = [
to_static_variable(var) if id(var) in return_var_ids else var
for var in true_args
]
false_args = [
to_static_variable(var) if id(var) in return_var_ids else var
for var in false_args
]
pred = cast_bool_if_necessary(pred)
return control_flow.cond(pred, lambda: true_fn(*true_args),
lambda: false_fn(*false_args))
def _run_paddle_while_loop(cond, body, loop_vars):
# NOTE: loop_vars of Paddle op `control_flow.while_loop` must be Paddle Tensors.
loop_vars = [to_static_variable(var) for var in loop_vars]
loop_vars = control_flow.while_loop(cond, body, loop_vars)
return loop_vars