Python tensorflow.IndexedSlices.shape屬性用法及代碼示例

TensorFlow是Google設計的開源Python庫，用於開發機器學習模型和深度學習神經網絡。

shape用於獲取張量流。TensorShape表示密集張量的形狀。

Syntax: tensorflow.IndexedSlices.shape

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

範例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)

輸出：


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

範例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)

輸出：


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

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注：本文由純淨天空篩選整理自aman neekhara大神的英文原創作品 Python – tensorflow.IndexedSlices.shape Attribute。非經特殊聲明，原始代碼版權歸原作者所有，本譯文未經允許或授權，請勿轉載或複製。