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Practical: Tensors in PyTorch

A link to a short colab notebook demonstrating tensors in PyTorch

A screenshot of a Colab notebook discussing tensors in PyTorch

© The University of Nottingham

Tensors are the data type used to transmit data through deep learning networks.

In the linked Colab notebook we look at:

how to make tensors in PyTorch
arithmetical operations with tensors: add, subtract, multiply, divide
performing other mathematical functions on tensors: e.g. exponential and trigonometric functions
how to make tensors of a given size and shape, including random tensors
how to access elements within tensors or parts of tensors using indexing and slicing
how to reshape tensors using flatten, squeeze and unsqueeze.

Follow the link below and work through the Colab notebook as before.

Tensors in PyTorch

You may wish to open the link in a new browser tab so you can refer back here quickly.

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This content is taken from The University of Nottingham online course

Deep Learning for Bioscientists

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