TENSOR OPERATIONS ASSIGNMENT

Pytorch is a library consisting of different neural networks.The following functions below are some of the insightful functions I observed in the given documentation.

torch.as_tensor()
torch.where()
torch.argmax()
torch.prod()
torch.split()

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

Looking in links: https://download.pytorch.org/whl/torch_stable.html
Requirement already satisfied: numpy in /opt/conda/lib/python3.8/site-packages (1.19.2)
Requirement already satisfied: torch==1.7.0+cpu in /opt/conda/lib/python3.8/site-packages (1.7.0+cpu)
Requirement already satisfied: torchvision==0.8.1+cpu in /opt/conda/lib/python3.8/site-packages (0.8.1+cpu)
Requirement already satisfied: torchaudio==0.7.0 in /opt/conda/lib/python3.8/site-packages (0.7.0)
Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (3.7.4.3)
Requirement already satisfied: dataclasses in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (0.6)
Requirement already satisfied: future in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (0.18.2)
Requirement already satisfied: pillow>=4.1.1 in /opt/conda/lib/python3.8/site-packages (from torchvision==0.8.1+cpu) (8.0.0)

# Import torch and other required modules
import torch

Function 1 - torch.as_tensor

This function converts any type of representation of data(lists, tuples, numpy arrays etc.) into a tensor quantity.

# Example 1 - Converting the list of numbers into a tensor.
ab = torch.as_tensor([1, 2, 3, 4])
print(ab)
ab.dtype

tensor([1, 2, 3, 4])

torch.int64