I have an Express Node.js application, but I also have a machine learning algorithm to use in Python. Is there a way I can call Python functions from my Node.js application
The Boa is good for your needs, see the example which extends Python tensorflow keras.Sequential
class in JavaScript.
const fs = require('fs');
const boa = require('@pipcook/boa');
const { tuple, enumerate } = boa.builtins();
const tf = boa.import('tensorflow');
const tfds = boa.import('tensorflow_datasets');
const { keras } = tf;
const { layers } = keras;
const [
[ train_data, test_data ],
info
] = tfds.load('imdb_reviews/subwords8k', boa.kwargs({
split: tuple([ tfds.Split.TRAIN, tfds.Split.TEST ]),
with_info: true,
as_supervised: true
}));
const encoder = info.features['text'].encoder;
const padded_shapes = tuple([
[ null ], tuple([])
]);
const train_batches = train_data.shuffle(1000)
.padded_batch(10, boa.kwargs({ padded_shapes }));
const test_batches = test_data.shuffle(1000)
.padded_batch(10, boa.kwargs({ padded_shapes }));
const embedding_dim = 16;
const model = keras.Sequential([
layers.Embedding(encoder.vocab_size, embedding_dim),
layers.GlobalAveragePooling1D(),
layers.Dense(16, boa.kwargs({ activation: 'relu' })),
layers.Dense(1, boa.kwargs({ activation: 'sigmoid' }))
]);
model.summary();
model.compile(boa.kwargs({
optimizer: 'adam',
loss: 'binary_crossentropy',
metrics: [ 'accuracy' ]
}));
The complete example is at: https://github.com/alibaba/pipcook/blob/master/example/boa/tf2/word-embedding.js
I used Boa in another project Pipcook, which is to address the machine learning problems for JavaScript developers, we implemented ML/DL models upon the Python ecosystem(tensorflow,keras,pytorch) by the boa library.