Fixing GPU for token-classification in a better way. (#13856)

Co-authored-by:  Pierre Snell <pierre.snell@botpress.com>

Co-authored-by: Pierre Snell <pierre.snell@botpress.com>

src/transformers/pipelines/base.py

@@ -791,7 +791,7 @@ class Pipeline(_ScikitCompat):
         elif isinstance(inputs, tuple):
             return tuple([self._ensure_tensor_on_device(item, device) for item in inputs])
         elif isinstance(inputs, torch.Tensor):
-            return inputs.to(self.device)
+            return inputs.to(device)
         else:
             return inputs
 

src/transformers/pipelines/token_classification.py

@@ -204,9 +204,10 @@ class TokenClassificationPipeline(Pipeline):
         offset_mapping = model_inputs.pop("offset_mapping", None)
         sentence = model_inputs.pop("sentence")
         if self.framework == "tf":
-            outputs = self.model(model_inputs.data)[0][0].numpy()
+            outputs = self.model(model_inputs.data)[0][0]
         else:
-            outputs = self.model(**model_inputs)[0][0].numpy()
+            outputs = self.model(**model_inputs)[0][0]
+
         return {
             "outputs": outputs,
             "special_tokens_mask": special_tokens_mask,
@@ -216,7 +217,7 @@ class TokenClassificationPipeline(Pipeline):
         }
 
     def postprocess(self, model_outputs, aggregation_strategy=AggregationStrategy.NONE):
-        outputs = model_outputs["outputs"]
+        outputs = model_outputs["outputs"].numpy()
         sentence = model_outputs["sentence"]
         input_ids = model_outputs["input_ids"][0]
         offset_mapping = model_outputs["offset_mapping"][0] if model_outputs["offset_mapping"] is not None else None

tests/test_pipelines_token_classification.py

@@ -25,7 +25,14 @@ from transformers import (
     pipeline,
 )
 from transformers.pipelines import AggregationStrategy, TokenClassificationArgumentHandler
-from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
+from transformers.testing_utils import (
+    is_pipeline_test,
+    nested_simplify,
+    require_tf,
+    require_torch,
+    require_torch_gpu,
+    slow,
+)
 
 from .test_pipelines_common import ANY, PipelineTestCaseMeta
 
@@ -246,6 +253,19 @@ class TokenClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTest
             ],
         )
 
+    @require_torch_gpu
+    @slow
+    def test_gpu(self):
+        sentence = "This is dummy sentence"
+        ner = pipeline(
+            "token-classification",
+            device=0,
+            aggregation_strategy=AggregationStrategy.SIMPLE,
+        )
+
+        output = ner(sentence)
+        self.assertEqual(nested_simplify(output), [])
+
     @require_torch
     @slow
     def test_dbmdz_english(self):