Removing hacky layer norm

ml-agents/mlagents/trainers/torch/networks.py

                 encoder(x) for encoder, x in zip(self.var_len_encoders, var_len_inputs)
             ]
             qkv = self.entities_embeddings(encoded_self, encoded_var_len)
-            mu_qkv = torch.mean(qkv, dim=2, keepdim=True)
-            qkv = (qkv - mu_qkv) / (
-                torch.sqrt(torch.mean((qkv - mu_qkv) ** 2, dim=2, keepdim=True))
-                + 0.0001
-            )
             attention_embedding = self.rsa(qkv, masks)
             encoded_self = torch.cat([encoded_self, attention_embedding], dim=1)