Replace dummies by requires_backends

src/transformers/models/layoutlmv2/__init__.py

@@ -18,7 +18,7 @@
 
 from typing import TYPE_CHECKING
 
-from ...file_utils import _LazyModule, is_detectron2_available, is_tokenizers_available
+from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
 
 
 _import_structure = {
@@ -29,7 +29,7 @@
 if is_tokenizers_available():
     _import_structure["tokenization_layoutlmv2_fast"] = ["LayoutLMv2TokenizerFast"]
 
-if is_detectron2_available():
+if is_torch_available():
     _import_structure["modeling_layoutlmv2"] = [
         "LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST",
         "LayoutLMv2ForQuestionAnswering",
@@ -47,7 +47,7 @@
     if is_tokenizers_available():
         from .tokenization_layoutlmv2_fast import LayoutLMv2TokenizerFast
 
-    if is_detectron2_available():
+    if is_torch_available():
         from .modeling_layoutlmv2 import (
             LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
             LayoutLMv2ForQuestionAnswering,

src/transformers/models/layoutlmv2/modeling_layoutlmv2.py

@@ -28,6 +28,7 @@
     add_start_docstrings_to_model_forward,
     is_detectron2_available,
     replace_return_docstrings,
+    requires_backends,
 )
 from ...modeling_outputs import (
     BaseModelOutput,
@@ -41,6 +42,7 @@
 from .configuration_layoutlmv2 import LayoutLMv2Config
 
 
+# soft dependency
 if is_detectron2_available():
     import detectron2
     from detectron2.modeling import META_ARCH_REGISTRY
@@ -683,7 +685,8 @@ def forward(self, hidden_states):
 )
 class LayoutLMv2Model(LayoutLMv2PreTrainedModel):
     def __init__(self, config):
-        super(LayoutLMv2Model, self).__init__(config)
+        requires_backends(self, "detectron2")
+        super().__init__(config)
         self.config = config
         self.has_visual_segment_embedding = config.has_visual_segment_embedding
         self.embeddings = LayoutLMv2Embeddings(config)

src/transformers/testing_utils.py

@@ -31,6 +31,7 @@
 from .deepspeed import is_deepspeed_available
 from .file_utils import (
     is_datasets_available,
+    is_detectron2_available,
     is_faiss_available,
     is_flax_available,
     is_keras2onnx_available,
@@ -456,6 +457,14 @@ def require_datasets(test_case):
         return test_case
 
 
+def require_detectron2(test_case):
+    """Decorator marking a test that requires detectron2."""
+    if not is_detectron2_available():
+        return unittest.skip("test requires `detectron2`")(test_case)
+    else:
+        return test_case
+
+
 def require_faiss(test_case):
     """Decorator marking a test that requires faiss."""
     if not is_faiss_available():

tests/test_modeling_layoutlmv2.py

@@ -18,7 +18,7 @@
 import unittest
 
 from transformers.file_utils import is_detectron2_available, is_torch_available
-from transformers.testing_utils import require_torch, slow, torch_device
+from transformers.testing_utils import require_detectron2, require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
@@ -36,7 +36,6 @@
     )
     from transformers.models.layoutlmv2.modeling_layoutlmv2 import LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST
 
-
 if is_detectron2_available():
     from detectron2.structures.image_list import ImageList
 
@@ -247,6 +246,7 @@ def prepare_config_and_inputs_for_common(self):
 
 
 @require_torch
+@require_detectron2
 class LayoutLMv2ModelTest(ModelTesterMixin, unittest.TestCase):
 
     test_pruning = False