TF - Fix interchangeable past/past_key_values and revert output variable name in GPT2 (#16332)

* revert tf gpt2

* add test for unpack_inputs and fix test case

* add changes to vision encoder decoder

tests/test_modeling_tf_common.py

@@ -27,6 +27,7 @@ from typing import List, Tuple
 from huggingface_hub import delete_repo, login
 from requests.exceptions import HTTPError
 from transformers import is_tf_available
+from transformers.configuration_utils import PretrainedConfig
 from transformers.models.auto import get_values
 from transformers.testing_utils import tooslow  # noqa: F401
 from transformers.testing_utils import (
@@ -80,6 +81,7 @@ if is_tf_available():
         TFSampleDecoderOnlyOutput,
         TFSampleEncoderDecoderOutput,
     )
+    from transformers.modeling_tf_utils import unpack_inputs
 
     if _tf_gpu_memory_limit is not None:
         gpus = tf.config.list_physical_devices("GPU")
@@ -1553,6 +1555,68 @@ class UtilsFunctionsTest(unittest.TestCase):
         tf.debugging.assert_near(non_inf_output, non_inf_expected_output, rtol=1e-12)
         tf.debugging.assert_equal(non_inf_idx, non_inf_expected_idx)
 
+    # tests whether the unpack_inputs function behaves as expected
+    def test_unpack_inputs(self):
+        class DummyModel:
+            def __init__(self):
+                config_kwargs = {"output_attentions": False, "output_hidden_states": False, "return_dict": False}
+                self.config = PretrainedConfig(**config_kwargs)
+
+            @unpack_inputs
+            def call(
+                self, input_ids=None, past=None, output_attentions=None, output_hidden_states=None, return_dict=None
+            ):
+                return input_ids, past, output_attentions, output_hidden_states, return_dict
+
+        dummy_model = DummyModel()
+        input_ids = tf.constant([0, 1, 2, 3])
+        past = tf.constant([4, 5, 6, 7])
+
+        # test case 1: Pass inputs as keyword arguments; Booleans are inherited from the config.
+        output = dummy_model.call(input_ids=input_ids, past=past)
+        tf.debugging.assert_equal(output[0], input_ids)
+        tf.debugging.assert_equal(output[1], past)
+        self.assertFalse(output[2])
+        self.assertFalse(output[3])
+        self.assertFalse(output[4])
+
+        # test case 2: Same as above, but with positional arguments.
+        output = dummy_model.call(input_ids, past)
+        tf.debugging.assert_equal(output[0], input_ids)
+        tf.debugging.assert_equal(output[1], past)
+        self.assertFalse(output[2])
+        self.assertFalse(output[3])
+        self.assertFalse(output[4])
+
+        # test case 3: We can also pack everything in the first input.
+        output = dummy_model.call(input_ids={"input_ids": input_ids, "past": past})
+        tf.debugging.assert_equal(output[0], input_ids)
+        tf.debugging.assert_equal(output[1], past)
+        self.assertFalse(output[2])
+        self.assertFalse(output[3])
+        self.assertFalse(output[4])
+
+        # test case 4: Explicit boolean arguments should override the config.
+        output = dummy_model.call(input_ids=input_ids, past=past, output_attentions=False, return_dict=True)
+        tf.debugging.assert_equal(output[0], input_ids)
+        tf.debugging.assert_equal(output[1], past)
+        self.assertFalse(output[2])
+        self.assertFalse(output[3])
+        self.assertTrue(output[4])
+
+        # test case 5: Unexpected arguments should raise an exception.
+        with self.assertRaises(ValueError):
+            output = dummy_model.call(input_ids=input_ids, past=past, foo="bar")
+
+        # test case 6: Despite the above, `past_key_values` should be interchangeable with `past`
+        # (the decorator moves it to `past`, or vice-versa, depending on the signature).
+        output = dummy_model.call(input_ids=input_ids, past_key_values=past)
+        tf.debugging.assert_equal(output[0], input_ids)
+        tf.debugging.assert_equal(output[1], past)
+        self.assertFalse(output[2])
+        self.assertFalse(output[3])
+        self.assertFalse(output[4])
+
 
 @require_tf
 @is_staging_test