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系統信息ValueError異常：嘗試重用RNNCell - 在tensorflow while循環
Linux Ubuntu 16.04
tensorflow-gpu==1.1.0
我在一個相當複雜的圖形收到此錯誤，但我可以用低於最小（但希望代表）例如重現：
import tensorflow as tf
import numpy as np
class Controller(object):
def __init__(self, batch_size, input_size):
self.batch_size = batch_size
self.input_size = input_size
with tf.name_scope("controller"):
self.network_vars()
self.nn_output_size = None
with tf.variable_scope("shape_inference"):
self.nn_output_size = self.get_nn_output_size()
def network_vars(self):
self.lstm_cell = tf.contrib.rnn.BasicLSTMCell(256)
self.state = self.lstm_cell.zero_state(self.batch_size, tf.float32)
def network_op(self, x, state):
x = tf.convert_to_tensor(x)
return self.lstm_cell(x, state)
def get_state(self):
return self.state
def update_state(self, new_state):
return tf.no_op()
def process_input(self, x, state=None):
nn_output, nn_state = self.network_op(x, state)
return nn_output, nn_state
def get_nn_output_size(self):
input_tensor = np.zeros([self.batch_size, self.input_size], dtype=np.float32)
output_vector, _ = self.network_op(input_tensor, self.get_state())
shape = output_vector.get_shape().as_list()
if len(shape) > 2:
raise ValueError("Expected the neural network to output a 1D vector")
else:
return shape[1]
class DNC(object):
def __init__(self, controller, batch_size, input_size):
self.controller = controller
self.batch_size = batch_size
self.input_size = input_size
self.build_graph()
def _step_op(self, x, controller_state=None):
_, nn_state = self.controller.process_input(x, controller_state)
return [nn_state[0], nn_state[1]]
def _loop_body(self, t, controller_state):
x = np.random.random_sample((self.batch_size, self.input_size)).astype(np.float32)
output_list = self._step_op(x, controller_state)
new_controller_state = tf.contrib.rnn.LSTMStateTuple(output_list[0], output_list[1])
return t+1, new_controller_state
def build_graph(self):
controller_state = self.controller.get_state()
if not isinstance(controller_state, tf.contrib.rnn.LSTMStateTuple):
controller_state = tf.contrib.rnn.LSTMStateTuple(controller_state[0], controller_state[1])
with tf.variable_scope("sequence_loop") as scope:
time = tf.constant(0, dtype=tf.int32)
final_results = tf.while_loop(
cond=lambda time, *_: time < 50,
body=self._loop_body,
loop_vars=(time, controller_state),
parallel_iterations=32,
swap_memory=True
)
if __name__ == "__main__":
batch_size = 32
input_size = 10
rnn_controller = Controller(batch_size, input_size)
dnc = DNC(rnn_controller, batch_size, input_size)
問題的回溯是：
[email protected]:~$ python controller.py
Traceback (most recent call last):
File "controller.py", line 84, in <module>
dnc = DNC(rnn_controller, batch_size, input_size)
File "controller.py", line 52, in __init__
self.build_graph()
File "controller.py", line 77, in build_graph
swap_memory=True
File "/home/francescoferroni/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2623, in while_loop
result = context.BuildLoop(cond, body, loop_vars, shape_invariants)
File "/home/francescoferroni/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2456, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "/home/francescoferroni/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2406, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "controller.py", line 60, in _loop_body
output_list = self._step_op(x, controller_state)
File "controller.py", line 55, in _step_op
_, nn_state = self.controller.process_input(x, controller_state)
File "controller.py", line 33, in process_input
nn_output, nn_state = self.network_op(x, state)
File "controller.py", line 24, in network_op
return self.lstm_cell(x, state)
File "/home/francescoferroni/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 235, in __call__
with _checked_scope(self, scope or "basic_lstm_cell", reuse=self._reuse):
File "/home/francescoferroni/anaconda3/lib/python3.6/contextlib.py", line 82, in __enter__
return next(self.gen)
File "/home/francescoferroni/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 77, in _checked_scope
type(cell).__name__))
ValueError: Attempt to reuse RNNCell <tensorflow.contrib.rnn.python.ops.core_rnn_cell_impl.BasicLSTMCell object at 0x7fcaeca99518> with a different variable scope than its first use. First use of cell was with scope 'shape_inference/basic_lstm_cell', this attempt is with scope 'sequence_loop/basic_lstm_cell'. Please create a new instance of the cell if you would like it to use a different set of weights. If before you were using: MultiRNNCell([BasicLSTMCell(...)] * num_layers), change to: MultiRNNCell([BasicLSTMCell(...) for _ in range(num_layers)]). If before you were using the same cell instance as both the forward and reverse cell of a bidirectional RNN, simply create two instances (one for forward, one for reverse). In May 2017, we will start transitioning this cell's behavior to use existing stored weights, if any, when it is called with scope=None (which can lead to silent model degradation, so this error will remain until then.)
如果我使用tensorflow 1.0拉澤r比1.1更不會引起任何問題。
[email protected]:~$ source Repositories/tfr10/bin/activate
(tfr10) [email protected]:~$ python controller.py
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally
(tfr10) [email protected]:~$
對於新tensorflow版本，我已經嘗試添加重用= true標誌，定義LSTM細胞時，但後來我得到另一個錯誤：
ValueError: Variable shape_inference/basic_lstm_cell/weights does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope?
我也試着刪除範圍在控制器定義中。
ValueError: Variable basic_lstm_cell/weights does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope?
我懷疑它是與build_graph（）中的while循環有關。我嘗試了下面的其他答案，但無法在循環情況下使用這個tensorflow。任何幫助將不勝感激。
任何Tensorflow嚮導都知道答案？
弗朗西斯