dyNET38

What it is and what it does

DyNet38 is a fork of DyNet that provides Python bindings to a C++ neural network library optimized for dynamic computation graphs—networks whose structure changes per training instance. This is particularly valuable in natural language processing, where sentence length, parse trees, and other structural properties vary. The library supports both CPU and GPU execution and includes an auto-batching feature that automatically groups computations for efficiency without requiring manual batching logic.

The package is built on top of cython and numpy, and ships as precompiled wheels for Python 3.8 through 3.12 across Linux, macOS, and Windows. It has been used to build state-of-the-art systems for syntactic parsing, machine translation, and morphological inflection. The aging maintenance status (last release 934 days ago) suggests it is stable but not under active development.

Use it for:

• Build syntactic parsers or dependency parsers where tree structure varies per sentence.
• Implement sequence-to-sequence models for machine translation with dynamic graph construction.
• Train morphological inflection systems where input and output structure depend on linguistic properties.
• Prototype NLP models that benefit from auto-batching without manual minibatch management.
• Run neural network experiments on GPU or CPU with a single codebase.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

DyNet38 is a Python binding for DyNet, a C++ neural network library designed for efficient computation on CPU or GPU with support for dynamic network structures that vary per training instance.

Yes, if you are building NLP models with dynamic structures and prefer a C++-backed library with Python bindings. The permissive Apache 2.0 license and broad platform support (Linux, macOS, Windows) are favorable. However, the aging maintenance status (934 days since last release) and small repository star count (4) suggest limited active development and community; consider your long-term support needs.

Install

dynet38 on PyPI

pip install dynet38

uv add dynet38

poetry add dynet38

Installing dyNET38

Before you install

Medium install friction due to compiled wheels for multiple platforms and Python versions (3.8–3.12). Package is aging—last release was 934 days ago—but the repository remains active with recent commits. Depends on cython and numpy.

License in practice

Licensed under Apache 2.0 (permissive), so you can use it freely in commercial and open-source projects without copyleft obligations.

Quickstart

pip install dynet38

from dynet38 import Model
model = Model()
W = model.add_parameters((10, 5))

Requires a C++ compiler and CMake to build from source; prebuilt wheels are available for Python 3.8–3.12 on Linux, macOS (x86_64 and ARM64), and Windows.

Verify before relying

• Whether prebuilt wheels include GPU support (CUDA/cuDNN) or CPU-only computation.
• Current maintenance status and whether dynet38 is actively maintained separate from the original DyNet project.
• Specific performance characteristics or benchmarks for auto-batching on modern hardware.
• Whether the fork dynet38 maintains API compatibility with the original DyNet.

Package facts

Evidence: dynet38-2.2-cp310-cp310-macosx_10_9_x86_64.whl; dyNET38-2.2-cp310-cp310-macosx_10_9_x86_64.whl; dyNET38-2.2-cp310-cp310-macosx_11_0_arm64.whl; dyNET38-2.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; dyNET38-2.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl; dyNET38-2.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; dyNET38-2.2-cp310-cp310-musllinux_1_1_i686.whl; dyNET38-2.2-cp310-cp310-musllinux_1_1_x86_64.whl; dyNET38-2.2-cp310-cp310-musllinux_1_2_aarch64.whl; dynet38-2.2-cp310-cp310-win_amd64.whl; dynet38-2.2-cp311-cp311-macosx_10_9_x86_64.whl; dyNET38-2.2-cp311-cp311-macosx_10_9_x86_64.whl; dyNET38-2.2-cp311-cp311-macosx_11_0_arm64.whl; dyNET38-2.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; dyNET38-2.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl; dyNET38-2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; dyNET38-2.2-cp311-cp311-musllinux_1_1_i686.whl; dyNET38-2.2-cp311-cp311-musllinux_1_1_x86_64.whl; dyNET38-2.2-cp311-cp311-musllinux_1_2_aarch64.whl; dynet38-2.2-cp311-cp311-win_amd64.whl

Tags

More Artificial Intelligence packages