5、数学运算

1 a = tf.fill([2,2],2) #创建的是 dtype=int32
2 print(a)
3 
4 b = tf.ones([2,2]) #创建的是dtype=float32
5 print(b)
6 
7 print(a+b)

cannot compute AddV2 as input #1(zero-based) was expected to be a int32 tensor but is a float tensor [Op:AddV2] name: add/

a = tf.fill([2,2],2.)
print("a:\n",a)

b = tf.ones([2,2])
print("b: \n",b)

print("a+b:\n",a+b)
print("a-b:\n",a-b)
print("a*b:\n",a*b)
print("a/b:\n",a/b)

a:
 tf.Tensor(
[[2. 2.]
 [2. 2.]], shape=(2, 2), dtype=float32)
b: 
 tf.Tensor(
[[1. 1.]
 [1. 1.]], shape=(2, 2), dtype=float32)
a+b:
 tf.Tensor(
[[3. 3.]
 [3. 3.]], shape=(2, 2), dtype=float32)
a-b:
 tf.Tensor(
[[1. 1.]
 [1. 1.]], shape=(2, 2), dtype=float32)
a*b:
 tf.Tensor(
[[2. 2.]
 [2. 2.]], shape=(2, 2), dtype=float32)
a/b:
 tf.Tensor(
[[2. 2.]
 [2. 2.]], shape=(2, 2), dtype=float32)

1 a = tf.ones([2,2])
2 # b1 = tf.log(a) # AttributeError: module ‘tensorflow‘ has no attribute ‘log‘
3 b1 = tf.math.log(a) 
4 print(b1)
5 
6 b2 = tf.exp(a)  #e的a次方
7 print(b2)

tf.Tensor(
[[0. 0.]
 [0. 0.]], shape=(2, 2), dtype=float32)

tf.Tensor(
[[2.7182817 2.7182817]
 [2.7182817 2.7182817]], shape=(2, 2), dtype=float32)

 1 b = tf.fill([2,2],2.) #如果不设成浮点型，计算sqrt的时候会出现问题
 2 print(b)
 3 
 4 b1 = tf.pow(b,3)  # b的3次方
 5 print(b1)
 6 
 7 b2 = b**3  # b的三次方
 8 print(b2)
 9 
10 b3 = tf.sqrt(b) #b的开方，即b的0.5次方
11 print(b3)

tf.Tensor(
[[2. 2.]
 [2. 2.]], shape=(2, 2), dtype=float32)

tf.Tensor(
[[8. 8.]
 [8. 8.]], shape=(2, 2), dtype=float32)

tf.Tensor(
[[8. 8.]
 [8. 8.]], shape=(2, 2), dtype=float32)

tf.Tensor(
[[1.4142135 1.4142135]
 [1.4142135 1.4142135]], shape=(2, 2), dtype=float32)