Fix tests imports dpr (#5576)

* fix test imports

* fix max_length

* style

* fix tests

src/transformers/tokenization_dpr.py

@@ -157,13 +157,13 @@ CUSTOM_DPR_READER_DOCSTRING = r"""
             The passages titles to be encoded. This can be a string, a list of strings if there are several passages.
         texts (:obj:`str`, :obj:`List[str]`):
             The passages texts to be encoded. This can be a string, a list of strings if there are several passages.
-        padding (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`True`):
+        padding (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`False`):
             Activate and control padding. Accepts the following values:
 
             * `True` or `'longest'`: pad to the longest sequence in the batch (or no padding if only a single sequence if provided),
             * `'max_length'`: pad to a max length specified in `max_length` or to the max acceptable input length for the model if no length is provided (`max_length=None`)
             * `False` or `'do_not_pad'` (default): No padding (i.e. can output batch with sequences of uneven lengths)
-        truncation (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`True`):
+        truncation (:obj:`Union[bool, str]`, `optional`, defaults to :obj:`False`):
             Activate and control truncation. Accepts the following values:
 
             * `True` or `'only_first'`: truncate to a max length specified in `max_length` or to the max acceptable input length for the model if no length is provided (`max_length=None`).
@@ -203,15 +203,37 @@ class CustomDPRReaderTokenizerMixin:
     def __call__(
         self,
         questions,
-        titles,
-        texts,
-        padding: Union[bool, str] = True,
-        truncation: Union[bool, str] = True,
-        max_length: Optional[int] = 512,
+        titles: Optional[str] = None,
+        texts: Optional[str] = None,
+        padding: Union[bool, str] = False,
+        truncation: Union[bool, str] = False,
+        max_length: Optional[int] = None,
         return_tensors: Optional[Union[str, TensorType]] = None,
         return_attention_mask: Optional[bool] = None,
         **kwargs
     ) -> BatchEncoding:
+        if titles is None and texts is None:
+            return super().__call__(
+                questions,
+                padding=padding,
+                truncation=truncation,
+                max_length=max_length,
+                return_tensors=return_tensors,
+                return_attention_mask=return_attention_mask,
+                **kwargs,
+            )
+        elif titles is None or texts is None:
+            text_pair = titles if texts is None else texts
+            return super().__call__(
+                questions,
+                text_pair,
+                padding=padding,
+                truncation=truncation,
+                max_length=max_length,
+                return_tensors=return_tensors,
+                return_attention_mask=return_attention_mask,
+                **kwargs,
+            )
         titles = titles if not isinstance(titles, str) else [titles]
         texts = texts if not isinstance(texts, str) else [texts]
         n_passages = len(titles)

tests/test_modeling_dpr.py

@@ -17,10 +17,10 @@
 import unittest
 
 from transformers import is_torch_available
+from transformers.testing_utils import require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, ids_tensor
-from .utils import require_torch, slow, torch_device
 
 
 if is_torch_available():

tests/test_tokenization_dpr.py

@@ -14,6 +14,7 @@
 # limitations under the License.
 
 
+from transformers.testing_utils import slow
 from transformers.tokenization_dpr import (
     DPRContextEncoderTokenizer,
     DPRContextEncoderTokenizerFast,
@@ -26,7 +27,6 @@ from transformers.tokenization_dpr import (
 from transformers.tokenization_utils_base import BatchEncoding
 
 from .test_tokenization_bert import BertTokenizationTest
-from .utils import slow
 
 
 class DPRContextEncoderTokenizationTest(BertTokenizationTest):