pytorch-named-dims

PyTorch tensor dimension names for all nn.Modules.

Extends PyTorch Named Tensors (new in PyTorch 1.4.0, still experimental as of PyTorch 1.5.0). It works in Python 3.6+.

Inspired by:

• Quantum Tensors JS by Piotr Migdał
• Tensor Considered Harmful by Alexander Rush

Installation

Not yet on PyPI. Install:

pip install git+git://github.com/stared/pytorch-named-dims.git

Example

import torch
from torch import nn
from pytorch_named_dims import nm

convs = nn.Sequential(
    nm.Conv2d(3, 5, kernel_size=3, padding=1),
    nn.ReLU(),  # preserves dims on its own
    nm.MaxPool2d(2, 2),
    nm.Conv2d(5, 2, kernel_size=3, padding=1)
)

x_input_1 = torch.rand((4, 3, 2, 2), names=('N', 'C', 'H', 'W'))  # good
x_input_2 = torch.rand((4, 3, 2, 2), names=('N', 'C', 'W', 'H'))  # bad

convs(x_input_1)  # returns ('N', 'C', 'H', 'W')
convs(x_input_2)  # raises:
# Layer Conv2d requires dimensions ['N', 'C', 'H', 'W'] but got ('N', 'C', 'W', 'H') instead.

• TODO: Colab

Funding

Project is supported by Program Operacyjny Inteligentny Rozwój grant for ECC Games for GearShift project.