为什么我不能使用TensorArray.gather（）在@tf.function?

Question

从TensorArray读取：

def __init__(self, size):
    self.obs_buf = tf.TensorArray(tf.float32, size=size, clear_after_read=False)
    self.obs2_buf = tf.TensorArray(tf.float32, size=size, clear_after_read=False)
    self.act_buf = tf.TensorArray(tf.float32, size=size, clear_after_read=False)
    self.rew_buf = tf.TensorArray(tf.float32, size=size, clear_after_read=False)
    self.done_buf = tf.TensorArray(tf.float32, size=size, clear_after_read=False)

def get_sample(self, batch_size):
        idxs = tf.random.uniform(shape=[batch_size], maxval=self.size, dtype=tf.int32)
        tf.print(idxs)
        return self.obs_buf.gather(indices=idxs),     \     # HERE IS THE ISSUE
               self.act_buf.gather(indices=idxs),     \
               self.rew_buf.gather(indices=idxs),     \
               self.obs2_buf.gather(indices=idxs),    \
               self.done_buf.gather(indices=idxs)

使用：

@tf.function
def train(self, rpm, batch_size, gradient_steps):
    for gradient_step in tf.range(1, gradient_steps + 1):
        obs, act, rew, next_obs, done = rpm.get_sample(batch_size)

        with tf.GradientTape() as tape:
        ...

问题:

回溯（最近一次调用last）：RLU培训中第130行的文件“\main.py”。train（）文件“C:\Users\user\Documents\Projects\rl toolkit\rl_training.py”，第129行，在train self中_rpm，赛尔夫。批量大小，自行确定。梯度步数，记录步数b=self。在call result=self中记录文件“C:\Users\user\AppData\Local\Programs\Python\36\lib\site packages\tensorflow\Python\eager\def\u function.py”，第828行_调用（*args，**kwds）文件“C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site packages\tensorflow\Python\eager\def_function.py”，第871行，在调用self中_初始化（args，kwds，add_initializers_to=initializers）文件“C:\Users\user\AppData\Local\Programs\Python36\lib\site packages\tensorflow\Python\eager\def\function.py”，第726行，在_initialize*args，**kwds）文件“C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site packages\tensorflow\Python\eager\function.py”，第2969行，在"获取"具体"函数"内部"垃圾"收集图"函数中,"自我"_可能定义函数（args，kwargs）文件“C:\Users\user\AppData\Local\Programs\Python36\lib\site packages\tensorflow\Python\eager\function.py”，第3361行，在可能定义函数图\u function=self中_创建图函数（args，kwargs）文件“C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site packages\tensorflow\Python\eager\function.py”，第3206行，在创建图函数捕获中，按值=self_按值捕获），文件“C:\Users\user\AppData\Local\Programs\Python\36\lib\site packages\tensorflow\Python\framework\func\graph.py”，第990行，func-graph\u-from\u-py-func-func\u-outputs=Python\u-func（*-func参数，**func\u-kwargs）文件“C:\Users\user\AppData\Local\Programs\Python\Python\Python36\lib\site packages\site-function\tensorflow\Python\Python\def\def\func\func\fu，第634行，in-wrapped_fn out=弱_wrapped_fn（）。wrapped（*args，**kwds）文件“C:\Users\user\AppData\Local\Programs\Python36\lib\site packages\tensorflow\Python\eager\function.py”，第3887行，在绑定方法包装返回wrapped\u fn（*args，**kwargs）文件“C:\Users\user\AppData\Local\Programs\Python36\lib\site packages\tensorflow\Python\framework\func\graph.py”，第977行，在包装器中生成e.ag\u错误\u元数据。例外情况（e）tensorflow。python框架错误。OperatorNotAllowedInGraphError:在用户代码中：

C:\Users\user\Documents\Projects\rl-toolkit\policy\sac\sac.py:183 update  *
    obs, act, rew, next_obs, done = rpm.get_sample(batch_size)
C:\Users\user\Documents\Projects\rl-toolkit\utils\replay_buffer.py:39 __call__  *
    return self.obs_buf.gather(indices=idxs),                    self.act_buf.gather(indices=idxs),                    self.rew_buf.gather(indices=idxs),                    self.obs2_buf.gather(indices=idxs),                   self.done_buf.gather(indices=idxs)
C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\tensor_array_ops.py:1190 gather  **
    return self._implementation.gather(indices, name=name)
C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\tensor_array_ops.py:861 gather
    return array_ops.stack([self._maybe_zero(i) for i in indices])
C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py:505 __iter__
    self._disallow_iteration()
C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py:498 _disallow_iteration
    self._disallow_when_autograph_enabled("iterating over `tf.Tensor`")
C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py:476 _disallow_when_autograph_enabled
    " indicate you are trying to use an unsupported feature.".format(task))

OperatorNotAllowedInGraphError: iterating over `tf.Tensor` is not allowed: AutoGraph did convert this function. This might indicate you are trying to use an unsupported feature.

为什么我不能在这种情况下使用Tensorary？我还有什么选择？

Answer 1

在这里解决了。必须使用tf。变量而不是tf。TensorArray.