Python – tensorflow.dynamic_stitch()
TensorFlow 是由 Google 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单个张量。
Syntax: tensorflow.dynamic_stitch( indices, data, name)
Parameter:
- indices: It is a list of Tensors having minimum 1 tensor and each tensor with dtype int32.
- data : It is list of Tensors having same length as indices.
- name(optional): It defines the name for the operation.
Result:
It returns a Tensor of same dtype as data.
示例 1:
Python3
# 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)
Python3
# 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, 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:
Python3
# 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)