张量流模型恢复问题



我在Tensorflow中的RNN模型恢复过程中不断发现以下问题。该模型运行良好,但恢复存在问题。下面是我的代码。可能是什么问题。我已经删除并清理了之前的所有会话,但同样的问题仍然存在。

saver = tf.train.import_meta_graph(os.path.join(logs_path, 
'Multi_Layer_RNN_model.ckpt-499999.meta'))
with tf.Session() as sess:
ckpt = tf.train.get_checkpoint_state(logs_path)
saver.restore(sess, tf.train.latest_checkpoint(logs_path))  

错误

InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [105,400] rhs shape= [111,400]
[[Node: save/Assign_11 = Assign[T=DT_FLOAT, _class=["loc:@rnn/lstm_cell/kernel"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](rnn/lstm_cell/kernel/RMSProp_1, save/RestoreV2:11)]]
Caused by op 'save/Assign_11', defined at:
File "C:UsersADMNAppDataLocalcondacondaenvstensorflowlibrunpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:UsersADMNAppDataLocalcondacondaenvstensorflowlibrunpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:UsersADMNAppDataLocalcondacondaenvstensorflowlibsite-packagesipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "C:UsersADMNAppDataLocalcondacondaenvstensorflowlibsite-packagestraitletsconfigapplication.py", line 658, in launch_instance
app.start()
.................

在第一行中,您有理由:

lhs shape= [105,400] rhs shape= [111,400]

似乎神经网络之间的向量/张量维度不同。

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