問題說明：

對於image_batch進行feed_dict，結果一直報錯：

TypeError: The value of a feed cannot be a tf.Tensor object. Acceptable feed values include Python scalars, strings, lists, numpy ndarrays, or TensorHandles.For reference, the tensor object was Tensor("shuffle_batch_1:1", shape=(3, 5), dtype=int32) which was passed to the feed with key Tensor("y-input_1:0", shape=(?, 5), dtype=float32).

問題分析：

feed_dict不能喂入tf張量，可以喂入陣列，字串，列表等

而喂入的image_batch經過了tf.reshape，變成了tf張量。

解決方法：

將tf.Tensor變成陣列即可。

陣列與張量的互相轉換：

import tensorflow as tf

sess=tf.Session()

sess.run(tf.global_variables_initializer())

#轉化為numpy陣列

img_numpy=img.eval(session=sess)

print("out2=",type(img_numpy))

#轉化為tensor

img_tensor= tf.convert_to_tensor(img_numpy)

print("out2=",type(img_tensor))