出现Variable embedding_attention_seq2seq/rnn/embedding_wrapper/embedding already exists, disallowed. Did you mean to set reuse=True in VarScope?

[c0derm4n]

ValueError Traceback (most recent call last)
in ()
140 with tf.Session() as sess:
141 sample_encoder_inputs, sample_decoder_inputs ,sample_target_weights= get_samples() #被投喂的数据
--> 142 encoder_inputs, decoder_inputs, target_weights, outputs, loss = get_model() #申请placeholder，前馈得到outputs
143
144 input_feed = {} #投喂数据的键值对，将真实数据投喂到placeholder构成的list--encoder_inputs中，同理对decoder_inputs

in get_model()
131 embedding_size=size,
132 feed_previous=False,
--> 133 dtype=tf.float32)
134
135 #计算交叉熵损失

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py in embedding_attention_seq2seq(encoder_inputs, decoder_inputs, cell, num_encoder_symbols, num_decoder_symbols, embedding_size, num_heads, output_projection, feed_previous, dtype, scope, initial_state_attention)
852 embedding_size=embedding_size)
853 encoder_outputs, encoder_state = rnn.static_rnn(
--> 854 encoder_cell, encoder_inputs, dtype=dtype)
855
856 # First calculate a concatenation of encoder outputs to put attention on.

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\rnn.py in static_rnn(cell, inputs, initial_state, dtype, sequence_length, scope)
1210 state_size=cell.state_size)
1211 else:
-> 1212 (output, state) = call_cell()
1213
1214 outputs.append(output)

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\rnn.py in ()
1197 varscope.reuse_variables()
1198 # pylint: disable=cell-var-from-loop
-> 1199 call_cell = lambda: cell(input_, state)
1200 # pylint: enable=cell-var-from-loop
1201 if sequence_length is not None:

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py in call(self, inputs, state, scope)
178 with vs.variable_scope(vs.get_variable_scope(),
179 custom_getter=self._rnn_get_variable):
--> 180 return super(RNNCell, self).call(inputs, state)
181
182 def _rnn_get_variable(self, getter, *args, **kwargs):

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\layers\base.py in call(self, inputs, *args, **kwargs)
439 # Check input assumptions set after layer building, e.g. input shape.
440 self._assert_input_compatibility(inputs)
--> 441 outputs = self.call(inputs, *args, **kwargs)
442
443 # Apply activity regularization.

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\contrib\rnn\python\ops\core_rnn_cell.py in call(self, inputs, state)
112 "embedding", [self._embedding_classes, self._embedding_size],
113 initializer=initializer,
--> 114 dtype=data_type)
115 embedded = embedding_ops.embedding_lookup(embedding,
116 array_ops.reshape(inputs, [-1]))

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\variable_scope.py in get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter)
1063 collections=collections, caching_device=caching_device,
1064 partitioner=partitioner, validate_shape=validate_shape,
-> 1065 use_resource=use_resource, custom_getter=custom_getter)
1066 get_variable_or_local_docstring = (
1067 """%s

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\variable_scope.py in get_variable(self, var_store, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter)
960 collections=collections, caching_device=caching_device,
961 partitioner=partitioner, validate_shape=validate_shape,
--> 962 use_resource=use_resource, custom_getter=custom_getter)
963
964 def _get_partitioned_variable(self,

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\variable_scope.py in get_variable(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter)
358 reuse=reuse, trainable=trainable, collections=collections,
359 caching_device=caching_device, partitioner=partitioner,
--> 360 validate_shape=validate_shape, use_resource=use_resource)
361 else:
362 return _true_getter(

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py in _rnn_get_variable(self, getter, *args, **kwargs)
181
182 def _rnn_get_variable(self, getter, *args, **kwargs):
--> 183 variable = getter(*args, **kwargs)
184 trainable = (variable in tf_variables.trainable_variables() or
185 (isinstance(variable, tf_variables.PartitionedVariable) and

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\variable_scope.py in _true_getter(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource)
350 trainable=trainable, collections=collections,
351 caching_device=caching_device, validate_shape=validate_shape,
--> 352 use_resource=use_resource)
353
354 if custom_getter is not None:

C:\Users\lenovo\Anaconda3\envs\py35\lib\site-packages\tensorflow\python\ops\variable_scope.py in _get_single_variable(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape, use_resource)
662 " Did you mean to set reuse=True in VarScope? "
663 "Originally defined at:\n\n%s" % (
--> 664 name, "".join(traceback.format_list(tb))))
665 found_var = self._vars[name]
666 if not shape.is_compatible_with(found_var.get_shape()):