张量

"""将Numpy数组转换为张量"""
a = np.arange(0,5)
print("数组a:",a)
b = tf.convert_to_tensor(a,dtype=tf.int64)
print("张量b：",b)

"""创建全为0的张量"""
zero_Tensor = tf.zeros([2,3])
print(zero_Tensor)

"""创建全为1的张量"""
one_Tensor = tf.ones(4)
print(one_Tensor)

"""创建全为指定值的张量"""
direct_Tensor = tf.fill([2,2],9)
print(direct_Tensor)

"""生成正态分布的随机数，默认均值为0，方差为1"""
print(tf.random.normal([2,2],mean=0,stddev=1))

"""生成截断式生态分布的随机数"""
print(tf.random.truncated_normal([2,2],0.5,1))

"""生成均匀分布随机数"""
print(tf.random.uniform([2,2],minval=0,maxval=1))

"""强制将张量转换为指定数据类型"""
x1 = tf.constant([1., 2., 3.], dtype=tf.float64)
print("x1:", x1)
x2 = tf.cast(x1, tf.int32)
print("x2", x2)

"""计算张量维度上最大值、最小值"""
print("minimum of x2：", tf.reduce_min(x2))
print("maxmum of x2:", tf.reduce_max(x2))