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
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
