torch.sinh () function provides support for the hyperbolic sine function in PyTorch. Input in radians is expected. Input type — tensor, and if the input contains more than one element, the element-wise hyperbolic sine is calculated.
Syntax : torch.sinh (x, out = None)
x : Input tensor
name (optional): Output tensor
Return type : A tensor with the same type as that of x.
Code # 1:
1.0000 -0.5000 3.4000 -2.1000 0.0000 -6.5000 [torch. FloatTensor of size 6] 1.1752 -0.5211 14.9654 -4.0219 0.0000 -332.5700 [torch.FloatTensor of size 6]
Code # 2: Rendering
# Import PyTorch library
# Importing the NumPy library
numpy as np
# Import matplotlib.pylot
matplotlib.pyplot as plt
# Vector size 15 with values from -5 to 5
# Applying the hyperbolic sine and
# save the result to & # 39; b & # 39;
torch.sinh (torch.FloatTensor (a))
plt. plot (a, b.numpy (), color
-74.2032 -36.3203 -17.7696 -8.6771 -4.2032 -1.9665 -0.7766 0.0000 0.7766 1.9665 4.2032 8.6771 17.7696 36.3203 74.2032 [torch.FloatTensor of size 15]
Scientific progress has increasingly become reliant on large-scale data collection and analysis methodologies. The same is true for the advanced use of computing in business, government, and other are...
I have developed this book to investigate Mesos-based cluster development and integration. I found that data center operating system (DCOS; and it’s command-line interface [CLI]) was a natural progr...
Data is “unreasonably effective”. Nobel laureate Eugene Wigner referred to the unreasonable effectiveness of mathematics in the natural sciences. What is big data? Its sizes are in the order of te...
Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python, 2nd Edition....