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Remove static pretrained maps from the library's internals (#29112)

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* [test_all] Remove static pretrained maps from the library's internals

* Deprecate archive maps instead of removing them

* Revert init changes

* [test_all] Deprecate instead of removing

* [test_all] PVT v2 support

* [test_all] Tests should all pass

* [test_all] Style

* Address review comments

* Update src/transformers/models/deprecated/_archive_maps.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/deprecated/_archive_maps.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* [test_all] trigger tests

* [test_all] LLAVA

* [test_all] Bad rebase

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
This commit is contained in:
Lysandre Debut
2024-03-25 10:33:38 +01:00
committed by GitHub
parent 76a33a1092
commit 39114c0383
842 changed files with 4608 additions and 8613 deletions
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7
tests/models/perceiver/test_modeling_perceiver.py
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@@ -56,7 +56,6 @@ if is_torch_available():
MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,
MODEL_MAPPING_NAMES,
)
from transformers.models.perceiver.modeling_perceiver import PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST
if is_vision_available():
@@ -832,9 +831,9 @@ class PerceiverModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
@slow
def test_model_from_pretrained(self):
for model_name in PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = PerceiverModel.from_pretrained(model_name)
self.assertIsNotNone(model)
model_name = "deepmind/language-perceiver"
model = PerceiverModel.from_pretrained(model_name)
self.assertIsNotNone(model)
# We will verify our results on an image of cute cats

4
tests/models/perceiver/test_tokenization_perceiver.py
View File

@@ -270,10 +270,6 @@ class PerceiverTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer = self.perceiver_tokenizer
self.assertEqual(tokenizer.decode([178]), "<EFBFBD>")
# tokenizer can be instantiated without any pretrained files, so no need for pretrained tokenizer list
def test_pretrained_model_lists(self):
pass
# tokenizer does not have vocabulary
def test_get_vocab(self):
pass