Include ID in text output of LM generate (#668)

src/fairseq2/datasets/instruction.py

@@ -294,7 +294,7 @@ def create_reader(
         builder.map(target_encoder, selector="tgt", num_parallel_calls=npc)
 
         def cat_source_and_target(example: Dict[str, Any]) -> Dict[str, Any]:
-            sample_id = example.get("id", None)
+            id_ = example.get("id")
 
             prompt_indices = example["src"]
             target_indices = example["tgt"]
@@ -303,7 +303,7 @@ def cat_source_and_target(example: Dict[str, Any]) -> Dict[str, Any]:
 
             target_mask = torch.arange(len(indices)) >= len(prompt_indices)
 
-            return {"indices": indices, "target_mask": target_mask, "id": sample_id}
+            return {"id": id_, "indices": indices, "target_mask": target_mask}
 
         builder.map(cat_source_and_target, num_parallel_calls=npc)
 
@@ -398,10 +398,13 @@ def create_prompt_reader(
         text_encoder = tokenizer.create_encoder(mode="prompt")
 
         def encode(example: Dict[str, Any]) -> Dict[str, Any]:
-            sample_id = example.get("id", None)
+            id_ = example.get("id")
+
             prompt = example["src"]
 
-            return {"prompt": prompt, "indices": text_encoder(prompt), "id": sample_id}
+            indices = text_encoder(prompt)
+
+            return {"id": id_, "prompt": prompt, "indices": indices}
 
         builder.map(encode, num_parallel_calls=npc)
 

src/fairseq2/recipes/lm/text_generate.py

@@ -403,7 +403,7 @@ def __call__(self, batch: SequenceBatch) -> None:
         except KeyError:
             raise ValueError("`batch.example` must contain a 'prompt' item.")
 
-        sample_ids = batch.example["id"]
+        ids = batch.example["id"]
 
         output = self._generator(batch.seqs, batch.padding_mask)
 
@@ -413,9 +413,7 @@ def __call__(self, batch: SequenceBatch) -> None:
         if not self._text_output_stream and not self._json_output_stream:
             return
 
-        for sample_id, prompt, hypotheses in zip(
-            sample_ids, prompts, output.hypotheses
-        ):
+        for id_, prompt, hypotheses in zip(ids, prompts, output.hypotheses):
             if len(hypotheses) == 0:
                 raise RuntimeError(
                     "The sequence generator returned no hypothesis. Please file a bug report."
@@ -441,6 +439,12 @@ def __call__(self, batch: SequenceBatch) -> None:
 
             # Dump as text.
             if stream := self._text_output_stream:
+                if id_ is not None:
+                    stream.write("<<<<< ID >>>>>")
+                    stream.write("\n")
+                    stream.write(f"{id_}")
+                    stream.write("\n\n")
+
                 stream.write("<<<<< PROMPT >>>>>")
                 stream.write("\n")
                 stream.write(prompt)
@@ -459,22 +463,20 @@ def __call__(self, batch: SequenceBatch) -> None:
                     stream.write("\n\n")
                     stream.write("<<<<< SCORE >>>>>")
                     stream.write("\n")
-
                     stream.write(f"{score:.8f}")
 
                 if step_scores is not None:
                     stream.write("\n\n")
                     stream.write("<<<<< STEP SCORES >>>>>")
                     stream.write("\n")
-
                     stream.write(", ".join(f"{s:.8f}" for s in step_scores))
 
                 stream.write("\n\n\n============================\n\n\n")
 
             # Dump as JSON.
             if stream := self._json_output_stream:
                 json_output = {
-                    "id": sample_id,
+                    "id": id_,
                     "prompt": prompt,
                     "response": response,
                     "token_indices": token_indices,