Overhaul TF serving signatures + dummy inputs (#23234)

* Let's try autodetecting serving sigs

* Don't clobber existing sigs

* Change shapes for multiplechoice models

* Make default dummy inputs smarter too

* Fix missing f-string

* Let's YOLO a serving output too

* Read __class__.__name__ properly

* Don't just pass naked lists in there and expect it to be okay

* Code cleanup

* Update default serving sig

* Clearer error messages

* Further updates to the default serving output

* make fixup

* Update the serving output a bit more

* Cleanups and renames, raise errors appropriately when we can't infer inputs

* More renames

* we're building in a functional context again, yolo

* import DUMMY_INPUTS from the right place

* import DUMMY_INPUTS from the right place

* Support cross-attention in the dummies

* Support cross-attention in the dummies

* Complete removal of dummy/serving overrides in BERT

* Complete removal of dummy/serving overrides in RoBERTa

* Obliterate lots and lots of serving sig and dummy overrides

* merge type hint changes

* Fix for token_type_ids with vocab_size 1

* Add missing property decorator

* Fix T5 and hopefully some models that take conv inputs

* More signature pruning

* Fix T5's signature

* Fix Wav2Vec2 signature

* Fix LongformerForMultipleChoice input signature

* Fix BLIP and LED

* Better default serving output error handling

* Fix BART dummies

* Fix dummies for cross-attention, esp encoder-decoder models

* Fix visionencoderdecoder signature

* Fix BLIP serving output

* Small tweak to BART dummies

* Cleanup the ugly parameter inspection line that I used in a few places

* committed a breakpoint again

* Move the text_dims check

* Remove blip_text serving_output

* Add decoder_input_ids to the default input sig

* Remove all the manual overrides for encoder-decoder model signatures

* Tweak longformer/led input sigs

* Tweak default serving output

* output.keys() -> output

* make fixup

tests/test_modeling_tf_common.py

@@ -1677,7 +1677,10 @@ class TFModelTesterMixin:
 
             # After testing that the model accepts all int inputs, confirm that its dummies are int32
             for key, tensor in model.dummy_inputs.items():
-                self.assertTrue(isinstance(tensor, tf.Tensor), "Dummy inputs should be tf.Tensor!")
+                self.assertTrue(
+                    isinstance(tensor, tf.Tensor) or tf.keras.backend.is_keras_tensor(tensor),
+                    "Dummy inputs should be tf.Tensor!",
+                )
                 if tensor.dtype.is_integer:
                     self.assertTrue(tensor.dtype == tf.int32, "Integer dummy inputs should be tf.int32!")