Keras.md

Keras notes

Author: Pham Quang Nhat Minh

Convert labels to one-hot encoding

# Convert labels to categorical one-hot encoding
one_hot_labels = keras.utils.to_categorical(labels, num_classes=10)

Using custom metrics in keras

# For custom metrics
import keras.backend as K

def mean_pred(y_true, y_pred):
    return K.mean(y_pred)

model.compile(optimizer='rmsprop',
              loss='binary_crossentropy',
              metrics=['accuracy', mean_pred])

Adding Attention layer on top of RNN layer in keras

• keras-attention-mechanism
• How to Develop an Encoder-Decoder Model with Attention for Sequence-to-Sequence Prediction in Keras
• How to add Attention on top of a Recurrent Layer (Text Classification)
• Position-based Content Attention for Time Series Forecasting with Sequence-to-sequence RNNs
• keras-language-modeling
• Understanding emotions — from Keras to pyTorch
• cbaziotis/Attention.py
• Attention in Long Short-Term Memory Recurrent Neural Networks

Upgrade keras and tensorflow

pip install keras --upgrade

How to use advanced activation layers in Keras?

model = Sequential()
act = keras.layers.advanced_activations.PReLU(init='zero', weights=None)
model.add(Dense(64, input_dim=14, init='uniform'))
model.add(act)

Tham khảo:

https://stackoverflow.com/questions/34717241/how-to-use-advanced-activation-layers-in-keras