sess.run（）を実行中にエラーが発生しました

Question

グラフモデルを実行したいが問題がある。コードは次のとおりです。

epoch_x, epoch_y = features, labels 
sess.run(optimizer, feed_dict = {"x:0": epoch_x, "y:0": epoch_y}) 

とエラーがある：

--------------------------------------------------------------------------- KeyError Traceback (most recent call last) D:\AnacondaIDE\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1067 subfeed_t = self.graph.as_graph_element(subfeed, allow_tensor=True, -> 1068 allow_operation=False) 1069 except Exception as e:

D:\AnacondaIDE\lib\site-packages\tensorflow\python\framework\ops.py in as_graph_element(self, obj, allow_tensor, allow_operation) 2707
with self._lock: -> 2708 return self._as_graph_element_locked(obj, allow_tensor, allow_operation) 2709

D:\AnacondaIDE\lib\site-packages\tensorflow\python\framework\ops.py in _as_graph_element_locked(self, obj, allow_tensor, allow_operation) 2749 "exist. The operation, %s, does not exist in the " -> 2750 "graph." % (repr(name), repr(op_name))) 2751 try:

KeyError: "The name 'x:0' refers to a Tensor which does not exist. The operation, 'x', does not exist in the graph."

During handling of the above exception, another exception occurred:

TypeError Traceback (most recent call last) in() 22 # feed_dict = {x: epoch_x, y: epoch_y} 23 ---> 24 sess.run(optimizer, feed_dict = {"x:0": epoch_x, "y:0": epoch_y}) 25 train_loss.append(sess.run(cost, feed_dict = {x: epoch_x, y: epoch_y})) 26 train_accuracy.append(sess.run(accr, feed_dict = {x: epoch_x, y: epoch_y}))

D:\AnacondaIDE\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata) 893 try: 894 result = self._run(None, fetches, feed_dict, options_ptr, --> 895 run_metadata_ptr) 896 if run_metadata: 897 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

D:\AnacondaIDE\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1069 except Exception as e: 1070 raise TypeError('Cannot interpret feed_dict key as Tensor: ' -> 1071 + e.args[0]) 1072 1073 if isinstance(subfeed_val, ops.Tensor):

TypeError: Cannot interpret feed_dict key as Tensor: The name 'x:0' refers to a Tensor which does not exist. The operation, 'x', does not exist in the graph.

私はまた、次のステートメントを試してみました：

sess.run(optimizer, feed_dict = {"x": epoch_x, "y": epoch_y}) 

その後、エラーがある：

--------------------------------------------------------------------------- NameError Traceback (most recent call last) in() 22 # feed_dict = {x: epoch_x, y: epoch_y} 23 ---> 24 sess.run(optimizer, feed_dict = {x: epoch_x, y: epoch_y}) 25 train_loss.append(sess.run(cost, feed_dict = {x: epoch_x, y: epoch_y})) 26 train_accuracy.append(sess.run(accr, feed_dict = {x: epoch_x, y: epoch_y}))

NameError: name 'x' is not defined

print(features.shape)は次のようになります。

(4000, 6000, 3)

私はTensorflow-gpu（1.3.0）を使用しています。

Answer 1

フィードディクテーションには引用符は必要ありませんが、キーはフィードするプレースホルダを指すPython変数である必要があります。例えば

、あなたが

pl_ = tf.placeholder(...., name='placeholder_1') 

のようなものを持っているあなたのプレースホルダを宣言するとき、あなたはこの

sess.run(...., feed_dict={pl_: value}) 

とNOT THIS

sess.run(..., feed_dict={'placeholder_1': value})