paramz

library0.9.6pypypiunverified

paramz is a parameterization framework for Python, providing mutable, constrained parameters with optimization capabilities (e.g., scipy-based L-BFGS-B). Current version is 0.9.6; release cadence is irregular with no recent updates since 2020.

ai-ml

pip install paramz

github ↗package ↗

INSTALL

IMPORT

SIG · PARAMZ

paramz

ai-mlpythonv0.9.6

Install

7.6s avg

Import

—

Disk

231MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.9.6 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 231.6MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 7.6s · import 0.000s · 223MB

231MB installed

● package 231MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Param

✓ from paramz import Param

Correct import for the main parameter class; note that paramz is not namespaced.

ParamArray

✓ from paramz import ParamArray

✗ from paramz.core import ParamArray

ParamArray is directly exposed in the top-level package, not in core.

Model

✓ from paramz import Model

✗ from paramz.model import Model

Model is a top-level class, not a submodule.

Create a model with a parameter and display its values.

from paramz import Param, Model import numpy as np class MyModel(Model): def __init__(self): super().__init__() self.param = Param('x', np.array([1.0, 2.0])) m = MyModel() print(m) print(m.param.values)

Debug

Known issues

deprecatedparamz is in maintenance mode; consider switching to GPy's paramz (built-in) or Pyro's parameterization for active development.

fix

Migrate to GPyTorch or Pyro.

affects: all

gotchaParam objects have their values stored as a NumPy array; setting values directly via assignment (e.g., param.values = new_array) may not trigger constraints properly. Use param[:] = new_array instead.

fix

Always assign using slice syntax: param[:] = new_values.

affects: all

gotchaWhen using gradient-based optimization, ensure that the model's log_likelihood() and gradients() methods are implemented; otherwise the optimizer may fail silently.

fix

Define log_likelihood() returning the negative log-likelihood and optionally gradients() for custom gradient computation.

affects: all

Upgrade

Version history

0.9.6latest on PyPI · released Jan 12, 2024

Audit

Dependencies

No dependency data recorded yet.

Agent activity

9 hits · last 30 days

node

Amazon

Resources

githubhttps://github.com/sods/paramz ↗

packagehttps://pypi.org/project/paramz/ ↗