PyTorch is an open-source machine learning library developed by Facebook. It is used for deep neural network and natural language processing purposes.
The function torch.cos() provides support for the cosine function in PyTorch. It expects the input in radian form and the output is in the range [-1, 1]. The input type is tensor and if the input contains more than one element, element-wise cosine is computed.
Syntax: torch.cos(x, out=None)
Parameters:
x: Input tensor
name (optional): Output tensor
Return type: A tensor with the same type as that of x.
Code #1:
Python3
# Importing the PyTorch libraryimport torch# A constant tensor of size 6a = torch.FloatTensor([1.0, -0.5, 3.4, -2.1, 0.0, -6.5])print(a)# Applying the cos function and# storing the result in 'b'b = torch.cos(a)print(b) |
Output:
1.0000 -0.5000 3.4000 -2.1000 0.0000 -6.5000 [torch.FloatTensor of size 6] 0.5403 0.8776 -0.9668 -0.5048 1.0000 0.9766 [torch.FloatTensor of size 6]
Code #2: Visualization
Python3
# Importing the PyTorch libraryimport torch# Importing the NumPy libraryimport numpy as np# Importing the matplotlib.pyplot functionimport matplotlib.pyplot as plt# A vector of size 15 with values from -5 to 5a = np.linspace(-5, 5, 15)# Applying the cosine function and# storing the result in 'b'b = torch.cos(torch.FloatTensor(a))print(b)# Plottingplt.plot(a, b.numpy(), color = 'red', marker = "o") plt.title("torch.cos") plt.xlabel("X") plt.ylabel("Y") plt.show() |
Output:
0.2837 -0.4138 -0.9090 -0.9598 -0.5414 0.1417 0.7556 1.0000 0.7556 0.1417 -0.5414 -0.9598 -0.9090 -0.4138 0.2837 [torch.FloatTensor of size 15]
