creyone-model 1.0.3

PyTorch layer building tools for CREYONE

creyone_model

PyTorch layer-building utilities for the CREYONE framework.

Overview

creyone_model provides a config-first API for assembling CNN building blocks. All layer hyper-parameters live in a single CNNBlockCfg dataclass, making it easy to swap layer types (convolution, normalisation, activation, pooling) without changing model code.

Installation

pip install creyone_model

Requires Python ≥ 3.10 and PyTorch ≥ 2.0.

Quick start

from creyone_model import CNNBlockCfg

cfg = CNNBlockCfg(tensor_dims=2, act_name='silu')
block = cfg.block_module(in_dim=3, out_dim=64, kernel_size=3)

import torch
y = block(torch.randn(1, 3, 224, 224))  # (1, 64, 224, 224)

Documentation

Full documentation (API reference + getting started guide) is hosted at https://creyone-model.readthedocs.io/.