Add `torch >=1.12` requirement for `Tapas` (#24251)

* fix

* fix

* fix

* Update src/transformers/models/tapas/modeling_tapas.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

src/transformers/models/tapas/modeling_tapas.py

@@ -32,6 +32,7 @@ from ...modeling_utils import PreTrainedModel
 from ...pytorch_utils import (
     apply_chunking_to_forward,
     find_pruneable_heads_and_indices,
+    is_torch_greater_or_equal_than_1_12,
     prune_linear_layer,
 )
 from ...utils import (
@@ -46,6 +47,12 @@ from .configuration_tapas import TapasConfig
 
 logger = logging.get_logger(__name__)
 
+if not is_torch_greater_or_equal_than_1_12:
+    logger.warning(
+        f"You are using torch=={torch.__version__}, but torch>=1.12.0 is required to use "
+        "TapasModel. Please upgrade torch."
+    )
+
 _CONFIG_FOR_DOC = "TapasConfig"
 _CHECKPOINT_FOR_DOC = "google/tapas-base"
 

src/transformers/pytorch_utils.py

@@ -29,6 +29,7 @@ logger = logging.get_logger(__name__)
 parsed_torch_version_base = version.parse(version.parse(torch.__version__).base_version)
 
 is_torch_greater_or_equal_than_2_0 = parsed_torch_version_base >= version.parse("2.0")
+is_torch_greater_or_equal_than_1_12 = parsed_torch_version_base >= version.parse("1.12")
 is_torch_greater_or_equal_than_1_10 = parsed_torch_version_base >= version.parse("1.10")
 is_torch_less_than_1_11 = parsed_torch_version_base < version.parse("1.11")
 

tests/models/gpt_bigcode/test_modeling_gpt_bigcode.py

@@ -37,6 +37,9 @@ if is_torch_available():
         GPTBigCodeModel,
     )
     from transformers.models.gpt_bigcode.modeling_gpt_bigcode import GPTBigCodeAttention
+    from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_12
+else:
+    is_torch_greater_or_equal_than_1_12 = False
 
 
 class GPTBigCodeModelTester:
@@ -530,6 +533,10 @@ class GPTBigCodeMHAModelTest(GPTBigCodeModelTest):
     multi_query = False
 
 
+@unittest.skipIf(
+    not is_torch_greater_or_equal_than_1_12,
+    reason="`GPTBigCode` checkpoints use `PytorchGELUTanh` which requires `torch>=1.12.0`.",
+)
 @slow
 @require_torch
 class GPTBigCodeModelLanguageGenerationTest(unittest.TestCase):

tests/models/tapas/test_modeling_tapas.py

@@ -60,6 +60,9 @@ if is_torch_available():
         reduce_mean,
         reduce_sum,
     )
+    from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_12
+else:
+    is_torch_greater_or_equal_than_1_12 = False
 
 
 class TapasModelTester:
@@ -408,6 +411,7 @@ class TapasModelTester:
         return config, inputs_dict
 
 
+@unittest.skipIf(not is_torch_greater_or_equal_than_1_12, reason="Tapas is only available in torch v1.12+")
 @require_torch
 class TapasModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (
@@ -562,6 +566,7 @@ def prepare_tapas_batch_inputs_for_training():
     return table, queries, answer_coordinates, answer_text, float_answer
 
 
+@unittest.skipIf(not is_torch_greater_or_equal_than_1_12, reason="Tapas is only available in torch v1.12+")
 @require_torch
 class TapasModelIntegrationTest(unittest.TestCase):
     @cached_property
@@ -916,6 +921,7 @@ class TapasModelIntegrationTest(unittest.TestCase):
 # Below: tests for Tapas utilities which are defined in modeling_tapas.py.
 # These are based on segmented_tensor_test.py of the original implementation.
 # URL: https://github.com/google-research/tapas/blob/master/tapas/models/segmented_tensor_test.py
+@unittest.skipIf(not is_torch_greater_or_equal_than_1_12, reason="Tapas is only available in torch v1.12+")
 @require_torch
 class TapasUtilitiesTest(unittest.TestCase):
     def _prepare_tables(self):