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()):