如何计算TensorFlow中张量的加权和？

2 回答

• 3

  这是内在产品的定义 . 使用numpy.dot：

  data=[[0.2, 0.5, 0.3], [0.4, 0.1, 0.5]]
  np.dot(data,range(len(data)+1))
  array([ 1.1,  1.1])
  

  回复于 2024-05-15T17:45:16+08:00
• 1

  以下代码应该有效：

  import tensorflow as tf
  import numpy as np
  
  
  a = np.array([[0.2, 0.5, 0.3], [0.4, 0.1, 0.5]])
  
  x = tf.placeholder(tf.float64, [2, 3])
  
  # weighted_sum_op = tf.reduce_sum(x * np.arange(0, a.shape[1]), 1,)
  
  # or if you want to have the range in the TensorFlow graph:
  weighted_sum_op = tf.reduce_sum(x * tf.range(0., tf.cast(tf.shape(x)[1], tf.float64)), 1, )
  
  # You ccould also make use of tf.py_func
  # weighted_sum_op = tf.py_func(lambda y: np.dot(y, np.arange(0, y.shape[1])), [x], tf.float64)
  
  with tf.Session() as sess:
      print(sess.run(weighted_sum_op, {x: a}))
  

  回复于 2024-05-15T17:45:16+08:00