From b60ec2754313b013a29aa068bea7a55ebe00453c Mon Sep 17 00:00:00 2001
From: Marcin Chrzanowski <m@m-chrzan.xyz>
Date: Tue, 25 May 2021 17:37:20 +0200
Subject: Implement encoder layer

---
 model/encoder_layer.py | 35 +++++++++++++++++++++++------------
 1 file changed, 23 insertions(+), 12 deletions(-)

diff --git a/model/encoder_layer.py b/model/encoder_layer.py
index 56a3a0c..71a7d8f 100644
--- a/model/encoder_layer.py
+++ b/model/encoder_layer.py
@@ -1,15 +1,26 @@
 from torch import nn
 
+from model.attention import Attention
+from model.forward import FeedForward
+
 class EncoderLayer(nn.Module):
-  def __init__(self, hidden_dim, d_ff, num_heads, use_attention=True,
-               use_feedforward=True):
-    super(EncoderLayer, self).__init__()
-    # TODO: implement a single encoder layer, using Attention and FeedForward.
-    pass
-
-  def forward(self, x):
-    # x shape: (seqlen, batch, hiddendim)
-    # TODO: implement a single encoder layer, using Attention and FeedForward.
-    result, att_weights = x, None # placeholder
-    pass
-    return result, att_weights
+    def __init__(self, hidden_dim, d_ff, num_heads, use_attention=True,
+                   use_feedforward=True):
+        super(EncoderLayer, self).__init__()
+        self._use_attention = use_attention
+        self._use_feedforward = use_feedforward
+        if use_attention:
+            self.attention = Attention(hidden_dim, num_heads)
+        if use_feedforward:
+            self.feedforward = FeedForward(hidden_dim, d_ff)
+
+    def forward(self, x):
+        weights = None
+        if self._use_attention:
+            y, weights = self.attention(x)
+            x = x + y
+        if self._use_feedforward:
+            y = self.feedforward(x)
+            x = x + y
+
+        return x, weights
-- 
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