ValueError: Cannot feed value of shape (784,) for Tensor 'Placeholder:0', which has shape '(?, 784)'

这个错误是tensorflow在读取数据进行推理时经常出现的一个错误，这里以mnist数据为例，mnist训练集数据维度为（55000，784），如果读取单个数据的话只有一个数据[0,0,0,1,…,0]其维度为1x784。
但是在推理时，feed_dict需要采用的是[[0,0,0,1,…,0]],这样的话才知道有多少个数据被送进来，所以需要进行扩维度。

batch_xs=mnist.train.images[1]
#一定要扩充维度，否则就会报错
train=np.expand_dims(batch_xs, 0)

这样操作后就不会报错了~~~

完整代码：

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
from tensorflow.python.tools.inspect_checkpoint import  print_tensors_in_checkpoint_filemnist=input_data.read_data_sets("MNIST_data/",one_hot=True)
batch_xs=mnist.train.images[1]
#一定要扩充维度，否则就会报错
train=np.expand_dims(batch_xs, 0)print(train.shape)
saver = tf.train.import_meta_graph("./save/mnist_model.ckpt.meta")
gragh = tf.get_default_graph()# 获取当前图，为了后续训练时恢复变量
# tensor_name_list = [tensor.name for tensor in gragh.as_graph_def().node]# 得到当前图中所有变量的名称
# print(tensor_name_list)with tf.Session() as sess:print_tensors_in_checkpoint_file("./save/mnist_model.ckpt",None,True)saver.restore(sess,"./save/mnist_model.ckpt")X= gragh.get_tensor_by_name('Placeholder:0')z=gragh.get_tensor_by_name('output:0')result=tf.arg_max(z,1)print("result:",sess.run(result,feed_dict={X:train}))

最终输出：

识别出来的数字为: [3]
真实数字为： [0. 0. 0. 1. 0. 0. 0. 0. 0. 0.]

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