# DeepModels
Implementations of various deep learning models using Keras.
## Requirements
An existing installation of either Tensorflow or Theano.
## Installation
```
pip install deep-models
```
## Usage
The models are implemented using Keras and instantiation returns a Keras Model object unless otherwise noted.
### Wide Residual Network
```python3
from deep_models import wide_residual_network as wrn
# Load your data
trainX = ...
trainY = ...
img_shape = (32, 32, 3)
# Create the model
# k is the width, 6 * n + 4 is the depth
model = wrn.build_model(img_shape, classes=10, n=4, k=10, dropout=0.3)
# Train the model
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["acc"])
model.fit(
trainX, trainY,
batch_size=128,
epochs=100,
validation_split=0.2)
```
## Examples
Some working examples are available in the notebooks directory.
## License
See LICENSE file
Implementations of various deep learning models using Keras.
## Requirements
An existing installation of either Tensorflow or Theano.
## Installation
```
pip install deep-models
```
## Usage
The models are implemented using Keras and instantiation returns a Keras Model object unless otherwise noted.
### Wide Residual Network
```python3
from deep_models import wide_residual_network as wrn
# Load your data
trainX = ...
trainY = ...
img_shape = (32, 32, 3)
# Create the model
# k is the width, 6 * n + 4 is the depth
model = wrn.build_model(img_shape, classes=10, n=4, k=10, dropout=0.3)
# Train the model
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["acc"])
model.fit(
trainX, trainY,
batch_size=128,
epochs=100,
validation_split=0.2)
```
## Examples
Some working examples are available in the notebooks directory.
## License
See LICENSE file
Metadata
Release files for Deep-Models 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Deep-Models-0.1.5.tar.gz | 2.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Deep_Models-0.1.5-py3.6.egg | Legacy Egg format | - | - | Details |
Total release size: 7.5 kB
Release files / Deep-Models-0.1.5.tar.gz
| Download URL | Deep-Models-0.1.5.tar.gz |
|---|---|
| Size | 2.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
cc2ecf467255994fd18815003bdd4e6082a00acc2d549f9866486b61fe3888ac
|
|
BLAKE2b-256 checksum How to use checksums |
89de75eca9c01fec53ab53aa0af946a303746d8fd3b6ebce77a55428f8814435
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / Deep_Models-0.1.5-py3.6.egg
| Download URL | Deep_Models-0.1.5-py3.6.egg |
|---|---|
| Size | 4.9 kB |
| Tags | Egg |
|
SHA-256 checksum How to use checksums |
d35e1d289fa1830f79bccf34ca95d4a164844fa29344d64a54549df3b5f72cd2
|
|
BLAKE2b-256 checksum How to use checksums |
1e27b6fe16680fb214a61b5d1ef499af4d92cb244d03aa34cb386be535d10227
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |