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Updated 3 years ago
Putting some torch -light on Pytorch tensors
Pytorch is an open source machine learning library based on the Torch library.Here I am going to explain 5 differnt functions related to Pytorch tensors.
- torch.randn
- torch.add
- torch.asin
- torch.deg2rad
- torch.fmod
Before we begin, let's install and import PyTorch
# Uncomment and run the appropriate command for your operating system, if required
# Linux / Binder
#
# !pip install numpy torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
# Windows
# !pip install numpy torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
# MacOS
# !pip install numpy torch torchvision torchaudio
# Import torch and other required modules
import torch
Function 1 - torch.randn
torch.randn(*size, *, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor
Returns a tensor filled with random numbers from a normal distribution with mean 0 and variance 1 (also called the standard normal distribution).
The shape of the tensor is defined by the variable argument size.
size (int...) – a sequence of integers defining the shape of the output tensor. Can be a variable number of arguments or a collection like a list or tuple.
# Example 1 - working
torch.randn(4)
tensor([ 0.4389, 0.4387, 0.0225, -0.5833])