################
*MNIST models in Keras (Guild AI)*
Models
######
acgan
=====
*Auxiliary Classifier Generative Adversarial Network (ACGAN) for MNIST in
Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (100)*
**beta-1**
*Beta 1 (0.5)*
**epochs**
*Number of epochs to train (100)*
**learning-rate**
*Learning rate (0.0002)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_acgan.py
- https://arxiv.org/abs/1511.06434
cnn
===
*Convolutional neural network (CNN) classifier for MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (128)*
**epochs**
*Number of epochs to train (12)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_cnn.py
denoising-autoencoder
=====================
*Denoising autoencoder for MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (128)*
**epochs**
*Number of epochs to train (30)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_denoising_autoencoder.py
hierarchical-rnn
================
*Hierarchical RNN (HRNN) classifier for MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (32)*
**epochs**
*Number of epochs to train (5)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_hierarchical_rnn.py
- https://arxiv.org/abs/1506.01057
- http://ieeexplore.ieee.org/document/7298714/
irnn
====
*Implementation of 'A Simple Way to Initialize Recurrent Networks of Rectified
Linear Units' with MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (32)*
**epochs**
*Number of epochs to train (200)*
**learning-rate**
*Learning rate (1e-06)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_irnn.py
- http://arxiv.org/pdf/1504.00941v2.pdf
mlp
===
*Multilayer perceptron (MLP) classifier for MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (128)*
**epochs**
*Number of epochs to train (20)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_mlp.py
net2net
=======
*Implementation of 'Net2Net: Accelerating Learning via Knowledge Transfer'
with MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (32)*
**epochs**
*Number of epochs to train (3)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_net2net.py
- http://arxiv.org/abs/1511.05641
siamese
=======
*Siamese MLP classifier for MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (128)*
**epochs**
*Number of epochs to train (20)*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_siamese.py
- http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf
swwae
=====
*Stacked what-where autoencoder for MNIST in Keras*
Operations
^^^^^^^^^^
train
-----
*Train the model*
Flags
`````
**batch-size**
*Training batch size (128)*
**epochs**
*Number of epochs to train (5)*
**pool-size**
*kernel size used for the MaxPooling2D (2)
Choices:
2
3
*
References
^^^^^^^^^^
- https://github.com/keras-team/keras/blob/master/examples/mnist_swwae.py
- https://arxiv.org/abs/1311.2901v3
- https://arxiv.org/abs/1506.02351v8
Metadata
Release files for gpkg.keras.mnist 0.5.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| gpkg.keras.mnist-0.5.1-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details for gpkg.keras.mnist-0.5.1-py2.py3-none-any.whl |
Release files / gpkg.keras.mnist-0.5.1-py2.py3-none-any.whl
| Download URL | gpkg.keras.mnist-0.5.1-py2.py3-none-any.whl |
|---|---|
| Size | 6.1 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
e2f40f61865b689927de1dd2c59e025ea51bfc7fb7d130a5b3c1ed86eb75c449
|
|
BLAKE2b-256 checksum How to use checksums |
ef7e37cfea2fdf8952cc01797b6d646d247ea181bffb3d5a4bdbca788cae61ab
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.9.1 pkginfo/1.4.2 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.19.6 CPython/2.7.12
|
Security for gpkg.keras.mnist 0.5.1
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.