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operations of pytorch

PyTorch :

  • 1.PyTorch is a small part of a computer software which is based on Torch library. It is a Deep Learning framework introduced by Facebook. PyTorch is a Machine Learning Library for Python programming language which is used for applications such as Natural Language Processing.

  • 2.The high-level features which are provided by PyTorch are as follows:

    • With the help of the Graphics Processing Unit (GPU), it gives tensor computing with strong acceleration.
    • It provides Deep Neural Network which is built on a tape-based auto diff system.
  • 3.PyTorch was developed to provide high flexibility and speed during implementing and building the Deep Learning Neural Network.

  • 4.It is quite simple to install, run, and understand. Pytorch is completely pythonic (using widely adopted python idioms rather than writing Java and C++ code) so that it can quickly build a Neural Network Model successfully.

Functions explained in this note book are:

  • torch.acos()
  • torch.abs()
  • torch.complex()
  • torch.bitwise_or()
  • torch.matrix_rank()
# 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: future in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (0.18.2) 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: 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.acos

  • This function computes the inverse cosine of each element in the tensor
  • Syntax : torch.acos(input)
  • Output element of output tensor = inverse cosine of Input element of input tensor.
# Example 1 - working 
torch.acos(torch.randn(1,2,3))
tensor([[[2.0638,    nan, 2.0940],
         [1.5608,    nan, 2.3707]]])