Python tensorflow.IndexedSlices.shape属性用法及代码示例

TensorFlow是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。

shape用于获取张量流。TensorShape表示密集张量的形状。

Syntax: tensorflow.IndexedSlices.shape

Returns: It returns tensorflow.TensorShape representing the shape of the dense tensor.

范例1：

Python3

# Importing the library 
import tensorflow as tf 
  
# Initializing the input 
data = tf.constant([[1, 2, 3], [4, 5, 6]]) 
  
# Printing the input 
print('data:', data) 
  
# Calculating result 
res = tf.IndexedSlices(data, [0], tf.constant([1, 2])) 
  
# Finding Shape 
shape = res.shape 
  
# Printing the result 
print('Shape:', shape)

输出：


data: tf.Tensor(
[[1 2 3]
 [4 5 6]], shape=(2, 3), dtype=int32)
Shape: (1, 2)

范例2：

Python3

# Importing the library 
import tensorflow as tf 
  
# Initializing the input 
data = tf.constant([[1, 2, 3], [4, 5, 6]]) 
  
# Printing the input 
print('data:', data) 
  
# Calculating result 
res = tf.IndexedSlices(data, [0], tf.constant([1])) 
  
# Finding Shape 
shape = res.shape 
  
# Printing the result 
print('Shape:', shape)

输出：


data: tf.Tensor(
[[1 2 3]
 [4 5 6]], shape=(2, 3), dtype=int32)
Shape: (1, )

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注：本文由纯净天空筛选整理自aman neekhara大神的英文原创作品 Python – tensorflow.IndexedSlices.shape Attribute。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。