Python TypeError:未能将类型为的对象转换为张量

我使用tensorflow 1.8编写机器学习框架。有两个文件包含的数据格式分别为index.csv和wordvecs.csv，如下所示

1
4
2,5
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0,4
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3,0,5

及

我使用这两块代码将所有内容加载到内存中

# loading indices
indices = []
with open('../data/indices.csv', 'r', newline='') as f:
    content = csv.reader(f)
    indices = [list(map(int, row)) for row in content]
print('Finish loading indices.csv\n')

# loading wordvecs
wordvecs = []
with open('../data/wordvecs.csv', 'r', newline='') as f:
    content = csv.reader(f)
    wordvecs = [list(map(float, row)) for row in content]
print('Finish loading wordvecs.csv\n')

然后，我定义了计算图

最后，我定义了一个部分来执行该图。但是，在到达该部分之前，我在第十行ten_wordvecs=tf.stack[tf.reduce_meanstf.gatherten_变量，十个索引中的索引]中得到了以下错误

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我的代码有什么问题？

您可能错过了一个

尝试：

而不是

tf.stack([tf.reduce_mean(tf.gather(ten_variables, index) for index in ten_indices)])

将这些复杂的行拆分为单个指令并逐个调试通常是有帮助的

print('Defining graph')
ten_variables = tf.Variable(wordvecs, name='my_variable') # create variable with initial values from wordvecs
ten_indices = [tf.constant(e) for e in indices] # convert indices into tf.constant
ten_wordvecs = tf.stack([tf.reduce_mean(tf.gather(ten_variables, index) for index in ten_indices)]) # reduce the data inside ten_variables and stack it

TypeError: Failed to convert object of type <class 'generator'> to Tensor. Contents: <generator object <genexpr> at 0x00000149E2C414C0>. Consider casting elements to a supported type.

tf.stack([tf.reduce_mean(tf.gather(ten_variables, index)) for index in ten_indices])

tf.stack([tf.reduce_mean(tf.gather(ten_variables, index) for index in ten_indices)])