Graph 意外地需要为图形中的不相关占位符提供输入值

在这里，我试图用TFLearn在Tensorflow中实现变分自动编码器

我在

self.training\u model.session

中构建用于训练、编码和生成一个大图的计算。

self.generating\u model

和

self.recognition\u model

与

self.training\u model

共享同一会话

当我运行

generating_model

生成MNIST 2D潜在空间时，一切都很顺利。但是当我运行

self.recognition\u model

对给定的输入数据进行编码时出现了错误，它要求我为属于

self.training\u model

的

self.training\u data

提供输入值

以下是全部错误：

Traceback (most recent call last):
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1039, in _do_call
    return fn(*args)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1021, in _run_fn
    status, run_metadata)
  File "/home/wermarter/anaconda3/lib/python3.5/contextlib.py", line 66, in __exit__
    next(self.gen)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'train_data/X' with dtype float
     [[Node: train_data/X = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/gpu:0"]()]]
     [[Node: add_5/_47 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_8_add_5", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/wermarter/Desktop/vae.py", line 178, in <module>
    main()
  File "/home/wermarter/Desktop/vae.py", line 172, in main
    vae.img_transition(trainX[4], trainX[100])
  File "/home/wermarter/Desktop/vae.py", line 130, in img_transition
    enc_A = self.encode(A)[0]
  File "/home/wermarter/Desktop/vae.py", line 121, in encode
    return self.recognition_model.predict({self.input_data: input_data})
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tflearn/models/dnn.py", line 257, in predict
    return self.predictor.predict(feed_dict)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tflearn/helpers/evaluator.py", line 69, in predict
    return self.session.run(self.tensors[0], feed_dict=feed_dict)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 778, in run
    run_metadata_ptr)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 982, in _run
    feed_dict_string, options, run_metadata)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1032, in _do_run
    target_list, options, run_metadata)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1052, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'train_data/X' with dtype float
     [[Node: train_data/X = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/gpu:0"]()]]
     [[Node: add_5/_47 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_8_add_5", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'train_data/X', defined at:
  File "/home/wermarter/Desktop/vae.py", line 178, in <module>
    main()
  File "/home/wermarter/Desktop/vae.py", line 169, in main
    vae = VAE()
  File "/home/wermarter/Desktop/vae.py", line 28, in __init__
    self._build_training_model()
  File "/home/wermarter/Desktop/vae.py", line 78, in _build_training_model
    self.train_data = tflearn.input_data(shape=[None, *self.img_shape], name='train_data')
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tflearn/layers/core.py", line 81, in input_data
    placeholder = tf.placeholder(shape=shape, dtype=dtype, name="X")
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1507, in placeholder
    name=name)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1997, in _placeholder
    name=name)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'train_data/X' with dtype float
     [[Node: train_data/X = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/gpu:0"]()]]
     [[Node: add_5/_47 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_8_add_5", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

回溯（最近一次呼叫最后一次）：
文件“/home/wermarter/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py”，第1039行，在调用中
返回fn（*args）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/client/session.py”，第1021行，在
状态，运行（元数据）
文件“/home/wermarter/anaconda3/lib/python3.5/contextlib.py”，第66行，在__
下一个（self.gen）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/framework/errors\u impl.py”，第466行，处于引发异常状态
pywrap_tensorflow.TF_GetCode（状态））
tensorflow.python.framework.errors\u impl.InvalidArgumentError：必须为带有数据类型float的占位符tensor“train\u data/X”提供一个值
[[Node:train_data/X=Placeholder[dtype=DT_FLOAT，shape=[]，[u device=“/job:localhost/replica:0/task:0/gpu:0”]（）]
[[Node:add_5/_47=_Recv[client_terminated=false，Recv_device=“/job:localhost/replica:0/task:0/cpu:0”，send_device=“/job:localhost/replica:0/task:0/gpu:0”，send_device_化身=1，tensor_name=“edge_8_add_5”，tensor_type=DT_FLOAT，_device=“/job:localhost/replica:0/task:0/cpu:0”（]）]
在处理上述异常期间，发生了另一个异常：
回溯（最近一次呼叫最后一次）：
文件“/home/wermarter/Desktop/vae.py”，第178行，在
main（）
文件“/home/wermarter/Desktop/vae.py”，主文件第172行
vae.img_转换（列车X[4]，列车X[100]）
文件“/home/wermarter/Desktop/vae.py”，第130行，在img_转换中
enc_A=自编码（A）[0]
文件“/home/wermarter/Desktop/vae.py”，第121行，编码
返回self.recognition\u model.predict（{self.input\u data:input\u data}）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tflearn/models/dnn.py”，第257行，在predict中
返回self.predictor.predict（提要）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tflearn/helpers/evaluator.py”，第69行，在predict中
返回self.session.run（self.tensors[0]，feed\u dict=feed\u dict）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/client/session.py”，第778行，正在运行
运行_元数据_ptr）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/client/session.py”，第982行，正在运行
提要（dict字符串、选项、运行元数据）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/client/session.py”，第1032行，运行
目标\u列表、选项、运行\u元数据）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/client/session.py”，第1052行，在
提升类型（e）（节点定义、操作、消息）
tensorflow.python.framework.errors\u impl.InvalidArgumentError：必须为带有数据类型float的占位符tensor“train\u data/X”提供一个值
[[Node:train_data/X=Placeholder[dtype=DT_FLOAT，shape=[]，[u device=“/job:localhost/replica:0/task:0/gpu:0”]（）]
[[Node:add_5/_47=_Recv[client_terminated=false，Recv_device=“/job:localhost/replica:0/task:0/cpu:0”，send_device=“/job:localhost/replica:0/task:0/gpu:0”，send_device_化身=1，tensor_name=“edge_8_add_5”，tensor_type=DT_FLOAT，_device=“/job:localhost/replica:0/task:0/cpu:0”（]）]
由op“列车数据/X”引起，定义于：
文件“/home/wermarter/Desktop/vae.py”，第178行，在
main（）
文件“/home/wermarter/Desktop/vae.py”，主文件第169行
vae=vae（）
文件“/home/wermarter/Desktop/vae.py”，第28行，初始__
自我.(构建)培训(模型)
文件“/home/wermarter/Desktop/vae.py”，第78行，在构建培训模型中
self.train\u data=tflearn.input\u data（shape=[None，*self.img\u shape]，name='train\u data'）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tflearn/layers/core.py”，第81行，输入数据
占位符=tf.占位符（shape=shape，dtype=dtype，name=“X”）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/ops/array_ops.py”，第1507行，在占位符中
名称=名称）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/ops/gen_array_ops.py”，第1997行，在占位符中
名称=名称）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/framework/op_def_library.py”，第768行，在apply_op
op_def=op_def）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/framework/ops.py”，第2336行，在create_op中
初始值=自身值。\默认值\初始值，初始值=初始值）
文件“/home/wermarter/anaconda3/lib/python3.5/site packages/tensorflow/python/framework/ops.py”，第1228行，在__
self.\u traceback=\u extract\u stack（）
InvalidArgumentError（回溯见上文）：必须为带有数据类型float的占位符张量“train_data/X”输入一个值
[[Node:train_data/X=Placeholder[dtype=DT_FLOAT，shape=[]，[u device=“/job:localhost/replica:0/task:0/gpu:0”]（）]
[[Node:add_5/_47=_Recv[client_terminated=false，Recv_device=“/job:localhost/replica:0/task:0/cpu:0”，send_device=“/job:localhost/replica:0/task:0/gpu:0”，send_device_化身=1，tensor_name=“edge_8_add_5”，tensor_type=DT_FLOAT，_device=“/job:localhost/replica:0/task:0/cpu:0”（]）]

这是一个特定于代码的错误。我的

自我识别