Keras RNAdam
use of nesterov accelerated geadient instead of momentum in rectified-adam
Install
pip install keras_rnadam
Usage
import keras
import numpy as np
from keras_rnadam import RNAdam
# Build toy model with RNAdam optimizer
model = keras.models.Sequential()
model.add(keras.layers.Dense(input_shape=(17,), units=3))
model.compile(RNAdam(), loss='mse')
# Generate toy data
x = np.random.standard_normal((4096 * 30, 17))
w = np.random.standard_normal((17, 3))
y = np.dot(x, w)
# Fit
model.fit(x, y, epochs=5)
Use Warmup
from keras_nradam import RNAdam
RNAdam(total_step=10000, warmup_proportion=0.1, min_lr=1e-5)
Metadata
Release files for keras-rnadam 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| keras_rnadam-0.2.0.tar.gz | 3.5 kB | Without provenance | Details for keras_rnadam-0.2.0.tar.gz |
Release files / keras_rnadam-0.2.0.tar.gz
| Download URL | keras_rnadam-0.2.0.tar.gz |
|---|---|
| Size | 3.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7436f9d1a7b9bc36251993f53f04db91f7bc1b6576bfa7cddd0dc2f05c433cd3
|
|
BLAKE2b-256 checksum How to use checksums |
0ad91f0fccf4fd7252a5cdf913f02273c4cbebe8b61f4251d438e7040011b8fd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/2.7.15+
|
Security for keras-rnadam 0.2.0
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.