我正在尝试进行逻辑回归,我的训练数据集来自一个numpy float64数组.我的代码看起来像,

import tensorflow as tf

graph = tf.Graph()

with graph.as_default():

examples =tf.constant(mat6) # mat6 is a numpy float64 array

t_labels = tf.constant(labels) # labels is an a numpy float64 array

W = tf.Variable(tf.truncated_normal([115713, 2]))

b = tf.Variable(tf.zeros([2]))

logits = tf.matmul(examples, W)+b

这引发了一个例外

TypeError: Input 'b' of 'MatMul' Op has type float32 that does not match type float64 of argument 'a'.

这可能是因为W和b是float32而不是float64.有没有办法转换W和b或创建它作为float64