Adding a test to prevent late failure in the Table question answering (#9808)

pipeline.

- If table is empty then the line that contain `answer[0]` will fail.
- This PR add a check to prevent `answer[0]`.
- Also adds an early check for presence of `table` and `query` to
prevent late failure and give better error message.
- Adds a few tests to make sure these errors are correctly raised.

src/transformers/pipelines/table_question_answering.py

@@ -3,7 +3,7 @@ import collections
 import numpy as np
 
 from ..file_utils import add_end_docstrings, is_torch_available, requires_pandas
-from .base import PIPELINE_INIT_ARGS, ArgumentHandler, Pipeline
+from .base import PIPELINE_INIT_ARGS, ArgumentHandler, Pipeline, PipelineException
 
 
 if is_torch_available():
@@ -239,6 +239,10 @@ class TableQuestionAnsweringPipeline(Pipeline):
         batched_answers = []
         for pipeline_input in pipeline_inputs:
             table, query = pipeline_input["table"], pipeline_input["query"]
+            if table.empty:
+                raise ValueError("table is empty")
+            if not query:
+                raise ValueError("query is empty")
             inputs = self.tokenizer(
                 table, query, return_tensors=self.framework, truncation="drop_rows_to_fit", padding=padding
             )
@@ -276,5 +280,7 @@ class TableQuestionAnsweringPipeline(Pipeline):
                     answer["aggregator"] = aggregator
 
                 answers.append(answer)
+            if len(answer) == 0:
+                raise PipelineException("Empty answer")
             batched_answers.append(answers if len(answers) > 1 else answers[0])
         return batched_answers if len(batched_answers) > 1 else batched_answers[0]

tests/test_pipelines_table_question_answering.py

@@ -131,6 +131,49 @@ class TQAPipelineTests(CustomInputPipelineCommonMixin, unittest.TestCase):
         self.assertIsInstance(table_querier.model.config.aggregation_labels, dict)
         self.assertIsInstance(table_querier.model.config.no_aggregation_label_index, int)
 
+        with self.assertRaises(ValueError):
+            table_querier(
+                {
+                    "table": {},
+                    "query": "how many movies has george clooney played in?",
+                }
+            )
+        with self.assertRaises(ValueError):
+            table_querier(
+                {
+                    "query": "how many movies has george clooney played in?",
+                }
+            )
+        with self.assertRaises(ValueError):
+            table_querier(
+                {
+                    "table": {
+                        "Repository": ["Transformers", "Datasets", "Tokenizers"],
+                        "Stars": ["36542", "4512", "3934"],
+                        "Contributors": ["651", "77", "34"],
+                        "Programming language": ["Python", "Python", "Rust, Python and NodeJS"],
+                    },
+                    "query": "",
+                }
+            )
+        with self.assertRaises(ValueError):
+            table_querier(
+                {
+                    "table": {
+                        "Repository": ["Transformers", "Datasets", "Tokenizers"],
+                        "Stars": ["36542", "4512", "3934"],
+                        "Contributors": ["651", "77", "34"],
+                        "Programming language": ["Python", "Python", "Rust, Python and NodeJS"],
+                    },
+                }
+            )
+
+    def test_empty_errors(self):
+        table_querier = pipeline(
+            "table-question-answering",
+            model="lysandre/tiny-tapas-random-wtq",
+            tokenizer="lysandre/tiny-tapas-random-wtq",
+        )
         mono_result = table_querier(self.valid_inputs[0], sequential=True)
         multi_result = table_querier(self.valid_inputs, sequential=True)