import tensorflow as tf
a = tf.random.normal([3, 3])
a
# 为True元素，即>0的元素的索引
indices = tf.where(mask)
indices
# 取回>0的值
tf.gather_nd(a, indices)
A = tf.ones([3, 3])
B = tf.zeros([3, 3])
# True的元素会从A中选值，False的元素会从B中选值
tf.where(mask, A, B)
indices = tf.constant([[4], [3], [1], [7]])
updates = tf.constant([9, 10, 11, 12])
shape = tf.constant([8])
# 把updates按照indices的索引放在底板shape上
tf.scatter_nd(indices, updates, shape)
indices = tf.constant([[0], [2]])
updates = tf.constant([
[[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]],
[[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]],
])
updates.shape
shape = tf.constant([4, 4, 4])
tf.scatter_nd(indices, updates, shape)
import numpy as np
points = []
for y in np.linspace(-2, 2, 5):
for x in np.linspace(-2, 2, 5):
points.append([x, y])
np.array(points)
y = tf.linspace(-2., 2, 5)
y
x = tf.linspace(-2., 2, 5)
x
points_x, points_y = tf.meshgrid(x, y)
points_x.shape
points = tf.stack([points_x, points_y], axis=2)
points
