Update QA to new inputs and datamodule

.gitignore

@@ -170,6 +170,7 @@ __MACOSX
 *-v2.0.json
 cifar-10*
 mini-imagenet*
+squad_tiny*
 
 docs/source/_static/images/course_UvA-DL
 docs/source/_static/images/lightning_examples

docs/source/api/text.rst

@@ -39,15 +39,13 @@ __________________
     ~question_answering.model.QuestionAnsweringTask
     ~question_answering.data.QuestionAnsweringData
 
-    question_answering.data.QuestionAnsweringBackboneState
-    question_answering.data.QuestionAnsweringCSVInput
-    question_answering.data.QuestionAnsweringInput
-    question_answering.data.QuestionAnsweringDictionaryInput
-    question_answering.data.QuestionAnsweringFileInput
-    question_answering.data.QuestionAnsweringJSONInput
-    question_answering.data.QuestionAnsweringOutputTransform
-    question_answering.data.QuestionAnsweringInputTransform
-    question_answering.data.SQuADInput
+    question_answering.input.QuestionAnsweringInputBase
+    question_answering.input.QuestionAnsweringCSVInput
+    question_answering.input.QuestionAnsweringJSONInput
+    question_answering.input.QuestionAnsweringSQuADInput
+    question_answering.input.QuestionAnsweringDictionaryInput
+    question_answering.input_transform.QuestionAnsweringInputTransform
+    question_answering.output_transform.QuestionAnsweringOutputTransform
 
 Summarization
 _____________

flash/core/integrations/transformers/transforms.py

@@ -17,15 +17,18 @@
 import torch
 
 from flash.core.data.input_transform import InputTransform
-
-
-def to_tensor(sample: Dict[str, Any]) -> Dict[str, Any]:
-    for key in sample:
-        sample[key] = torch.as_tensor(sample[key])
-    return sample
+from flash.core.data.io.input import DataKeys
 
 
 @dataclass
 class TransformersInputTransform(InputTransform):
+    @staticmethod
+    def to_tensor(sample: Dict[str, Any]) -> Dict[str, Any]:
+        for key in sample:
+            if key is DataKeys.METADATA:
+                continue
+            sample[key] = torch.as_tensor(sample[key])
+        return sample
+
     def per_sample_transform(self) -> Callable:
-        return to_tensor
+        return self.to_tensor

flash/text/question_answering/cli.py

@@ -11,7 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
 from flash.core.data.utils import download_data
 from flash.core.utilities.flash_cli import FlashCLI
 from flash.text import QuestionAnsweringData, QuestionAnsweringTask
@@ -20,21 +19,17 @@
 
 
 def from_squad(
-    backbone: str = "distilbert-base-uncased",
     batch_size: int = 4,
-    num_workers: int = 0,
-    **input_transform_kwargs,
+    **data_module_kwargs,
 ) -> QuestionAnsweringData:
     """Downloads and loads a tiny subset of the squad V2 data set."""
     download_data("https://pl-flash-data.s3.amazonaws.com/squad_tiny.zip", "./data/")
 
     return QuestionAnsweringData.from_squad_v2(
         train_file="./data/squad_tiny/train.json",
         val_file="./data/squad_tiny/val.json",
-        backbone=backbone,
         batch_size=batch_size,
-        num_workers=num_workers,
-        **input_transform_kwargs,
+        **data_module_kwargs,
     )
 
 
@@ -48,7 +43,6 @@ def question_answering():
             "trainer.max_epochs": 3,
             "model.backbone": "distilbert-base-uncased",
         },
-        legacy=True,
     )
 
     cli.trainer.save_checkpoint("question_answering_model.pt")