tensorflow张量

 # 张量

    
 import tensorflow as tf
    
 """
    
 1. 定义: 
    
   6.     tensorflow想象成一个n维 数组, 类型 tf.tensor, tensor里面有两个重要概念:
    
     
    
     a. 类型: 
    
         
    
         dtype: 定义类型:
    
         
    
         tf.placeholder(dtype = tf.float)
    
     
    
     b. shape
    
     
    
 2. 转换:
    
   18.         a. 类型转换:
    
         
    
         tf.case(转换张量, 转换的类型)
    
         
    
     b. 形状转换: shape 
    
      
    
         i.动态转换
    
             reshape: 
    
         
    
         ii.静态转换
    
             set_shape:
    
 """
    
  
    
  
    
 def shape():
    
     """
    
     show 张量的形状
    
     :return: 
    
     """
    
  
    
     a = tf.constant(10) # 标量  shape=()
    
  
    
     b = tf.constant([1, 2, 3, 4])  # 向量  shape=(4,)
    
  
    
     c = tf.constant([[1, 2, 3], [4, 5, 6]])   # shape=(2, 3)
    
  
    
     print(a)
    
     print(b)
    
     print(c)
    
     return None
    
  
    
  
    
 def create():
    
  
    
     """
    
     创建张量
    
     :return: 
    
     """
    
  
    
     # 创建一个全部都是0的张量
    
     zero = tf.zeros(dtype=tf.float32, shape=[2,3])
    
  
    
     # 创建一个全部都是1的张量
    
     one = tf.ones(dtype=tf.int32, shape=[4,4])
    
  
    
     # 创建固定张量
    
     constant = tf.constant([[1,2,3],[2,2,2],[3,3,3]])
    
  
    
     # 创建随机张量
    
     random = tf.random_normal(dtype=tf.float32, shape=[2,3])
    
     # 访问内部的值,开启会话
    
     with tf.Session() as sess:
    
     print("zero :", sess.run(zero))
    
     print("one :", sess.run(one))
    
     print("constant :", sess.run(constant))
    
     print("random :", sess.run(random))
    
  
    
     return None
    
  
    
  
    
 def change():
    
  
    
     """
    
     tensorflow类型转化
    
     :return: 
    
     """
    
  
    
     tensor = tf.ones(dtype=tf.int32, shape=[2, 3])
    
     print(tensor)
    
  
    
     a = tf.cast(tensor, tf.float32)
    
     # Tensor("ones:0", shape=(2, 3), dtype=int32)
    
     # Tensor("Cast:0", shape=(2, 3), dtype=float32)
    
  
    
     print(a)
    
  
    
  
    
  
    
 def change_shape():
    
  
    
     """
    
     形状转换 
    
     :return: 
    
     """
    
  
    
     a = tf.constant([1, 2, 3, 4])   # shape(4,)
    
     ph = tf.placeholder(dtype=tf.float32, shape=[None, 4])
    
  
    
  
    
     # 动态转换
    
     # a1 = tf.reshape(a, [3, 2])
    
  
    
     # 静态转换: 静态转换是不能够跨阶转换的
    
     # a.set_shape([2, 2]) Shapes (4,) and (2, 2) are not compatible
    
  
    
     # 塑形只能有塑形一次
    
     ph.set_shape([5, 4])
    
     # ph.set_shape([3, 4])
    
  
    
  
    
     print(ph)
    
     with tf.Session() as sess:
    
   
    
     print("a1 :", sess.run(a))
    
  
    
 change_shape()
    
    
    
    
    python
    
    
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