CBOW word embedding in Keras

cbow_code_sample_keras.py

modelWRD = Sequential()

# 1st layer is a dummy-permutation=identity to specify input shape
modelWRD.add( Permute((1,), input_shape=(n_words,)) )

modelWRD.add( EMBEDDING )

modelWRD.add( Lambda(
                   lambda x : K.sum(x,axis=1), # sum over words
                   output_shape=(embedding_dimension,))
            )

# Dense is a linear map followed by an activation
modelWRD.add( Dense(vocab_size, activation='softmax') )