make fill_random_weights work for MTIA tbe module (pytorch#2286)

Summary:
Pull Request resolved: pytorch#2286

att, just a couple places left over previously when adding MTIA EmbeddingLocation.

Reviewed By: jspark1105

Differential Revision: D53062844

fbshipit-source-id: 051aafc0199cf7cfb99417f5ef39c36fd450fc6a

fbgemm_gpu/fbgemm_gpu/split_table_batched_embeddings_ops_inference.py

@@ -101,7 +101,7 @@ def nbit_construct_split_state(
             offsets.append(host_size)
             host_size += state_size
         elif location == EmbeddingLocation.DEVICE or location == EmbeddingLocation.MTIA:
-            placements.append(EmbeddingLocation.DEVICE)
+            placements.append(location)
             offsets.append(dev_size)
             dev_size += state_size
         else:
@@ -1176,7 +1176,10 @@ def split_embedding_weights_with_scale_bias(
         splits: List[Tuple[Tensor, Optional[Tensor], Optional[Tensor]]] = []
         for t, (_, rows, dim, weight_ty, _) in enumerate(self.embedding_specs):
             placement = self.weights_physical_placements[t]
-            if placement == EmbeddingLocation.DEVICE.value:
+            if (
+                placement == EmbeddingLocation.DEVICE.value
+                or placement == EmbeddingLocation.MTIA.value
+            ):
                 weights = self.weights_dev
             elif placement == EmbeddingLocation.HOST.value:
                 weights = self.weights_host