pon*_*dto 16 python numpy tensorflow
我试图在tensorflow中定义一个自定义op,其中我需要构造一个矩阵(z),它将包含两个矩阵(x和y)的行对的所有组合的总和.一般情况下,行数x和y有动力.
在numpy中它很简单:
import numpy as np
from itertools import product
rows_x = 4
rows_y = 2
dim = 2
x = np.arange(dim*rows_x).reshape(rows_x, dim)
y = np.arange(dim*rows_y).reshape(rows_y, dim)
print('x:\n{},\ny:\n{}\n'.format(x, y))
z = np.zeros((rows_x*rows_y, dim))
print('for loop:')
for i, (x_id, y_id) in enumerate(product(range(rows_x), range(rows_y))):
print('row {}: {} + {}'.format(i, x[x_id, ], y[y_id, ]))
z[i, ] = x[x_id, ] + y[y_id, ]
print('\nz:\n{}'.format(z))
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收益:
x:
[[0 1]
[2 3]
[4 5]
[6 7]],
y:
[[0 1]
[2 3]]
for loop:
row 0: [0 1] + [0 1]
row 1: [0 1] + [2 3]
row 2: [2 3] + [0 1]
row 3: [2 3] + [2 3]
row 4: [4 5] + [0 1]
row 5: [4 5] + [2 3]
row 6: [6 7] + [0 1]
row 7: [6 7] + [2 3]
z:
[[ 0. 2.]
[ 2. 4.]
[ 2. 4.]
[ 4. 6.]
[ 4. 6.]
[ 6. 8.]
[ 6. 8.]
[ 8. 10.]]
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但是,我还没有弄清楚如何在tensorflow中实现类似的任何东西.
我主要是通过SO和tensorflow API来寻找能够产生两个张量元素组合的函数,或者是一个能够给出张量元素排列的函数,但无济于事.
任何建议都是最受欢迎的.
P-G*_*-Gn 16
你可以简单地使用张量流的广播能力.
import tensorflow as tf
x = tf.constant([[0, 1],[2, 3],[4, 5],[6, 7]], dtype=tf.float32)
y = tf.constant([[0, 1],[2, 3]], dtype=tf.float32)
x_ = tf.expand_dims(x, 0)
y_ = tf.expand_dims(y, 1)
z = tf.reshape(tf.add(x_, y_), [-1, 2])
# or more succinctly
z = tf.reshape(x[None] + y[:, None], [-1, 2])
sess = tf.Session()
sess.run(z)
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