Created by: qingqing01

The following issue comes from email.

Thank you for your work on Paddle. I think the design is very interesting.

I would like to use pretrained word vectors in an embedding layer. I want the weights to be static, because my training data is small. For clarity, here's how I would implement the desired behaviour with Keras:

    model.add(
        Embedding(
            embeddings.shape[0],
            embeddings.shape[1],
            input_length=shape['max_length'],
            trainable=False,
            weights=[embeddings],
            mask_zero=True
        )
    )

Is there a way to implement this with the Paddle Python bindings? Unfortunately I haven't been able to find this in the documentation or source yet.