models/transformer/encode_decode/encoder.py

import torch.nn as nn

from models.transformer.encode_decode.clones import clones
from models.transformer.encode_decode.layer_norm import LayerNorm


class Encoder(nn.Module):
    "Core encoder is a stack of N layers"

    def __init__(self, layer, N):
        super(Encoder, self).__init__()
        self.layers = clones(layer, N)
        self.norm = LayerNorm(layer.size)
        
    def forward(self, x, mask):
        "Pass the input (and mask) through each layer in turn."

        for layer in self.layers:
            x = layer(x, mask)
        return self.norm(x)