Support embedding from decoder (#1284)

Summary:
Pull Request resolved: #1284

support embedding from decoder

Reviewed By: mwu1993

Differential Revision: D20515702

fbshipit-source-id: 0101c0048c0935eaef641a8bfa92a9e55afc73d3

Author: chenyangyu1988

pytext/torchscript/module.py

@@ -110,9 +110,11 @@ def __init__(
         tensorizer: ScriptTensorizer,
         normalizer: VectorNormalizer,
         index: int = 0,
+        concat_dense: bool = True,
     ):
         super().__init__(model, tensorizer, index)
         self.normalizer = normalizer
+        self.concat_dense = torch.jit.Attribute(concat_dense, bool)
 
     @torch.jit.script_method
     def forward(
@@ -135,5 +137,8 @@ def forward(
         dense_feat = self.normalizer.normalize(dense_feat)
         dense_tensor = torch.tensor(dense_feat, dtype=torch.float)
 
-        encoder_embedding = self.model(input_tensors, dense_tensor)[self.index]
-        return torch.cat([encoder_embedding, dense_tensor], 1)
+        sentence_embedding = self.model(input_tensors, dense_tensor)[self.index]
+        if self.concat_dense:
+            return torch.cat([sentence_embedding, dense_tensor], 1)
+        else:
+            return sentence_embedding