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Use of PyTorch tensors for Linear Algebra

An short introduction about PyTorch and about the chosen functions.

  • torch.from_numpy(ndarray)

  • torch.is_tensor(obj)

  • torch.numel(input)

  • torch.std_mean(input, unbiased=True)

  • torch.hstack(tensors,out=None)

Before we begin, let's install and import PyTorch


# 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
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: 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: typing-extensions in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (3.7.4.3) 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
!pip install jovian --upgrade --q
import jovian