picodl.

A tiny deep learning library built from scratch in Python - autograd engine, layers, losses, optimizers, and a training loop, all on top of plain numpy. No PyTorch, no TensorFlow, no hidden framework underneath.

Documentation

Installation

Install picodl with pip

  pip install picodl-nn

Demo

A sample model

from picodl.nn import NeuralNet
from picodl.layers import Linear, GELU
from picodl.loss import CrossEntropyLoss
from picodl.optim import AdamW
from picodl.train import train

net = NeuralNet([
    Linear(784, 128),
    GELU(),
    Linear(128, 10),
])

train(net, x_train, y_train,
      num_epochs=10,
      loss=CrossEntropyLoss(),
      optimizer=AdamW(lr=0.001, weight_decay=0.01))

net.save("model.picodl")

Authors

@alight659

License

MIT

Metadata

Release files for picodl-nn 0.1.1

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Source distribution for picodl-nn 0.1.1
File	Size	Uploaded	Provenance
picodl_nn-0.1.1.tar.gz	9.1 kB	Sep 18, 2026	Without provenance	Details

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Table of built distributions (wheels) for picodl-nn 0.1.1
File	Interpreter	ABI	Platform	Reset
picodl_nn-0.1.1-py3-none-any.whl 10.3 kB Sep 18, 2026 Without provenance	Python 3	none	any	Details

Total release size: 19.4 kB

Release files / picodl_nn-0.1.1.tar.gz

Download URL	picodl_nn-0.1.1.tar.gz
Size	9.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`32584e23c68cd0b360846a9941095d62dc7f681b0f76160f1ed7ee4f748d35f0`
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Upload date	Sep 18, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.5`

Release files / picodl_nn-0.1.1-py3-none-any.whl

Download URL	picodl_nn-0.1.1-py3-none-any.whl
Size	10.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`6f2be57079f20806608ce9f347d4555e22c52155dc03bb509c3e017ece849705`
BLAKE2b-256 checksum How to use checksums	`2abc9a1e77a1c5d78687e1755c1b44c08d8c61f3ec2944e49f507869f7214885`
Upload date	Sep 18, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.5`

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