Add a model config generator (#1511)

Model config generator takes a PyTorch model as input and generates a JSON file with model layers and other propperties that define sharding on a particular hardware.

apps/language_models/src/model_wrappers/vicuna_model.py

@@ -237,3 +237,25 @@ class SecondVicuna(torch.nn.Module):
             return_vals.append(item[0])
             return_vals.append(item[1])
         return tuple(return_vals)
+
+
+class CombinedModel(torch.nn.Module):
+    def __init__(
+        self,
+        first_vicuna_model_path="TheBloke/vicuna-7B-1.1-HF",
+        second_vicuna_model_path="TheBloke/vicuna-7B-1.1-HF",
+    ):
+        super().__init__()
+        self.first_vicuna = FirstVicuna(first_vicuna_model_path)
+        self.second_vicuna = SecondVicuna(second_vicuna_model_path)
+
+    def forward(self, input_ids):
+        first_output = self.first_vicuna(input_ids=input_ids, use_cache=True)
+        logits = first_output[0]
+        pkv = first_output[1:]
+
+        token = torch.argmax(torch.tensor(logits)[:, -1, :], dim=1)
+        token = token.to(torch.int64).reshape([1, 1])
+        secondVicunaInput = (token,) + tuple(pkv)
+        second_output = self.second_vicuna(secondVicunaInput)
+        return second_output