Pytorch functions for Machine learning
PyTORCH is a library to process tensors.
Hence it becomes incresingly important to understands its fuction that can help you with your machine learning tasks.
This artcile will help you to explore 5 of the pytorch functions
- torch.linespace
- torch.eye
- torch.full
- torch.take
- torch.unbind
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.linspace
This function is used to create equally spaced 1D tensors
torch.linspace(start, end, steps, *, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False)
-
start (float) – the starting value for the set of points
-
end (float) – the ending value for the set of points
-
steps (int) – size of the constructed tensor
-
out (Tensor, optional) – the output tensor.
-
dtype (torch.dtype, optional) – the desired data type of returned tensor. Default: if None, uses a global default (see torch.set_default_tensor_type()).
-
layout (torch.layout, optional) – the desired layout of returned Tensor. Default: torch.strided.
-
device (torch.device, optional) – the desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see torch.set_default_tensor_type()). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.
-
requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default: False.
# Example 1
torch.linspace(1, 10)
tensor([ 1.0000, 1.0909, 1.1818, 1.2727, 1.3636, 1.4545, 1.5455, 1.6364,
1.7273, 1.8182, 1.9091, 2.0000, 2.0909, 2.1818, 2.2727, 2.3636,
2.4545, 2.5455, 2.6364, 2.7273, 2.8182, 2.9091, 3.0000, 3.0909,
3.1818, 3.2727, 3.3636, 3.4545, 3.5455, 3.6364, 3.7273, 3.8182,
3.9091, 4.0000, 4.0909, 4.1818, 4.2727, 4.3636, 4.4545, 4.5455,
4.6364, 4.7273, 4.8182, 4.9091, 5.0000, 5.0909, 5.1818, 5.2727,
5.3636, 5.4545, 5.5455, 5.6364, 5.7273, 5.8182, 5.9091, 6.0000,
6.0909, 6.1818, 6.2727, 6.3636, 6.4545, 6.5455, 6.6364, 6.7273,
6.8182, 6.9091, 7.0000, 7.0909, 7.1818, 7.2727, 7.3636, 7.4545,
7.5455, 7.6364, 7.7273, 7.8182, 7.9091, 8.0000, 8.0909, 8.1818,
8.2727, 8.3636, 8.4545, 8.5455, 8.6364, 8.7273, 8.8182, 8.9091,
9.0000, 9.0909, 9.1818, 9.2727, 9.3636, 9.4545, 9.5455, 9.6364,
9.7273, 9.8182, 9.9091, 10.0000])