Skip to main content

Keras AdaBound

Travis Coverage

AdaBound optimizer in Keras.

Install

pip install keras-adabound

Usage

Use the optimizer

from keras_adabound import AdaBound

model.compile(optimizer=AdaBound(lr=1e-3, final_lr=0.1), loss=model_loss)

Load with custom objects

from keras_adabound import AdaBound

model = keras.models.load_model(model_path, custom_objects={'AdaBound': AdaBound})

About weight decay

The optimizer does not have an argument named weight_decay (as in the official repo) since it can be done by adding L2 regularizers to weights:

import keras

regularizer = keras.regularizers.l2(WEIGHT_DECAY / 2)
for layer in model.layers:
    for attr in ['kernel_regularizer', 'bias_regularizer']:
        if hasattr(layer, attr) and layer.trainable:
            setattr(layer, attr, regularizer)

Metadata

Release files for keras-adabound 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for keras-adabound 0.6.0
File Size Uploaded Provenance Actions
keras-adabound-0.6.0.tar.gz 5.5 kB Without provenance Details for keras-adabound-0.6.0.tar.gz

Release files / keras-adabound-0.6.0.tar.gz

Download URL keras-adabound-0.6.0.tar.gz
Size 5.5 kB
Tags Source
SHA-256 checksum
How to use checksums
d9b62762600c9209765f71a4bd499c0aaea0b6dc3c536329bc947daf5764067e
BLAKE2b-256 checksum
How to use checksums
bf7485de8379eba8e0f819ef9b62ff32d24a3f624758800e12bd9572e3afb546
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.4

Security for keras-adabound 0.6.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page