Improved huggingface batch logic

runtimes/huggingface/mlserver_huggingface/common.py

@@ -3,6 +3,7 @@
 
 from typing import Callable
 from functools import partial
+from mlserver.logging import logger
 from mlserver.settings import ModelSettings
 
 import torch
@@ -59,11 +60,18 @@ def load_pipeline_from_settings(
         framework=hf_settings.framework,
     )
 
-    # If max_batch_size > 0 we need to ensure tokens are padded
-    if settings.max_batch_size:
+    # If max_batch_size > 1 we need to ensure tokens are padded
+    if settings.max_batch_size > 1:
         model = hf_pipeline.model
-        eos_token_id = model.config.eos_token_id  # type: ignore
-        hf_pipeline.tokenizer.pad_token_id = [str(eos_token_id)]  # type: ignore
+        if not hf_pipeline.tokenizer.pad_token_id:
+            eos_token_id = model.config.eos_token_id  # type: ignore
+            if eos_token_id:
+                hf_pipeline.tokenizer.pad_token_id = [str(eos_token_id)]  # type: ignore
+            else:
+                logger.warning(
+                    "Model has neither pad_token or eos_token, setting batch size to 1"
+                )
+                hf_pipeline._batch_size = 1
 
     return hf_pipeline
 

runtimes/huggingface/tests/test_common.py

@@ -102,3 +102,46 @@ def test_pipeline_is_initialised_with_correct_model_param(
     pipeline_call_args = mock_pipeline_factory.return_value.call_args
 
     assert pipeline_call_args.kwargs["model"] == expected
+
+
+@pytest.mark.parametrize(
+    "pretrained_model, task, input_batch_size, expected_batch_size",
+    [
+        (
+            "hf-internal-testing/tiny-bert-for-token-classification",
+            "token-classification",
+            1,
+            1,
+        ),
+        (
+            "hf-internal-testing/tiny-bert-for-token-classification",
+            "token-classification",
+            0,
+            1,
+        ),
+        (
+            "hf-internal-testing/tiny-bert-for-token-classification",
+            "token-classification",
+            10,
+            1,
+        ),  # Neither pad_token nor eos_token defined revert to 1
+    ],
+)
+def test_pipeline_checks_for_eos_and_pad_token(
+    pretrained_model: str,
+    task: Optional[str],
+    input_batch_size: Optional[int],
+    expected_batch_size: Optional[int],
+):
+    hf_settings = HuggingFaceSettings(pretrained_model=pretrained_model, task=task)
+    model_params = ModelParameters()
+    model_settings = ModelSettings(
+        name="foo",
+        implementation=HuggingFaceRuntime,
+        parameters=model_params,
+        max_batch_size=input_batch_size,
+    )
+
+    m = load_pipeline_from_settings(hf_settings, model_settings)
+
+    assert m._batch_size == expected_batch_size