Print ASCII diagrams of your Keras models to visualize the layers and their shapes.
InputLayer (None, 50, 300)
Reshape (None, 1, 50, 300)
Convolution2D (None, 250, 48, 1)
Relu (None, 250, 48, 1)
MaxPooling2D (None, 250, 1, 1)
Flatten (None, 250)
Dropout (None, 250)
Dense (None, 7)
Softmax (None, 7)
A more complex model from babi_rnn.py:
InputLayer (None, 5)
Embedding (None, 5, 50)
InputLayer (None, 552) Dropout (None, 5, 50)
Embedding (None, 552, 50) LSTM (None, 50)
Dropout (None, 552, 50) RepeatVector (None, 552, 50)
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Merge (None, 552, 50)
LSTM (None, 50)
Dropout (None, 50)
Dense (None, 36)
pip install keras_diagram
Note for Conda installation (Python 3.5): pip install pypandoc
from keras_diagram import ascii
model = Sequential()
model.add(...)
print(ascii(model))
./test.py # run tests via docker
./publish.py # build distributions and publish to pypi
./shell.py # run bash above docker container with current folder mounted