Python| PyTorch tan() 方法

PyTorch 是 Facebook 开发的开源机器学习库。它用于深度神经网络和自然语言处理目的。

函数torch.tan()为 PyTorch 中的切线函数提供支持。它期望以弧度形式输入，输出在 [-∞, ∞] 范围内。输入类型是张量，如果输入包含多个元素，则计算元素切线。

Syntax: torch.tan(x, out=None)

Parameters:
x: Input tensor
name (optional): Output tensor

Return type: A tensor with the same type as that of x.

代码#1：

Python3

# Importing the PyTorch library
import torch
  
# A constant tensor of size 6
a = torch.FloatTensor([1.0, -0.5, 3.4, -2.1, 0.0, -6.5])
print(a)
  
# Applying the tan function and
# storing the result in 'b'
b = torch.tan(a)
print(b)

输出：

1.0000
-0.5000
 3.4000
-2.1000
 0.0000
-6.5000
[torch.FloatTensor of size 6]


 1.5574
-0.5463
 0.2643
 1.7098
 0.0000
-0.2203
[torch.FloatTensor of size 6]

代码 #2：可视化

Python3

# Importing the PyTorch library
import torch
  
# Importing the NumPy library
import numpy as np
  
# Importing the matplotlib.pyplot function
import matplotlib.pyplot as plt
  
# A vector of size 15 with values from -1 to 1
a = np.linspace(-1, 1, 15)
  
# Applying the tangent function and
# storing the result in 'b'
b = torch.tan(torch.FloatTensor(a))
  
print(b)
  
# Plotting
plt.plot(a, b.numpy(), color = 'red', marker = "o") 
plt.title("torch.tan") 
plt.xlabel("X") 
plt.ylabel("Y") 
  
plt.show()

输出：

-1.5574
-1.1549
-0.8670
-0.6430
-0.4569
-0.2938
-0.1438
 0.0000
 0.1438
 0.2938
 0.4569
 0.6430
 0.8670
 1.1549
 1.5574
[torch.FloatTensor of size 15]