Python – tensorflow.dynamic_stitch()
TensorFlow是谷歌设计的开源Python库,用于开发机器学习模型和深度学习神经网络。
dynamic_stitch()用于将多个张量合并为一个张量。
语法: tensorflow.dynamic_stitch( indices, data, name)
参数:
- indices:它是一个张量列表,至少有1个张量,每个张量的dtype为int32。
- data:它是具有相同长度索引的张量列表。
- name(可选):它定义了该操作的名称。
结果:
它返回一个与数据的dtype相同的张量。
示例 1:
# Importing the library
import tensorflow as tf
# Initializing the input
indices = [[0, 1, 5], [2, 4, 3, 6]]
data = [[1, 2, 3], [4, 5, 6, 7]]
# Printing the input
print('indices:', indices)
print('data: ', data)
# Calculating result
x = tf.dynamic_stitch(indices, data)
# Printing the result
print('x: ', x)
输出:
indices: [[0, 1, 5], [2, 4, 3, 6]]
data: [[1, 2, 3], [4, 5, 6, 7]]
x: tf.Tensor([1 2 4 6 5 3 7], shape=(7, ), dtype=int32)
示例 2:
# Importing the library
import tensorflow as tf
# Initializing the input
indices = [[0, 1, 6], [5, 4, 3]]
data = [[1, 2, 3], [4, 5, 6]]
# Printing the input
print('indices:', indices)
print('data: ', data)
# Calculating result
x = tf.dynamic_stitch(indices, data)
# Printing the result
print('x: ', x)
输出:
indices: [[0, 1, 2], [5, 4, 3]]
data: [[1, 2, 3], [4, 5, 6]]
x: tf.Tensor([1 2 3 6 5 4], shape=(6, ), dtype=int32)