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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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13
tests/models/levit/test_modeling_levit.py
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@@ -40,7 +40,6 @@ if is_torch_available():
MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,
MODEL_MAPPING_NAMES,
)
from transformers.models.levit.modeling_levit import LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST
if is_vision_available():
@@ -382,9 +381,9 @@ class LevitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
@slow
def test_model_from_pretrained(self):
for model_name in LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = LevitModel.from_pretrained(model_name)
self.assertIsNotNone(model)
model_name = "facebook/levit-128S"
model = LevitModel.from_pretrained(model_name)
self.assertIsNotNone(model)
# We will verify our results on an image of cute cats
@@ -398,13 +397,11 @@ def prepare_img():
class LevitModelIntegrationTest(unittest.TestCase):
@cached_property
def default_image_processor(self):
return LevitImageProcessor.from_pretrained(LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST[0])
return LevitImageProcessor.from_pretrained("facebook/levit-128S")
@slow
def test_inference_image_classification_head(self):
model = LevitForImageClassificationWithTeacher.from_pretrained(LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST[0]).to(
torch_device
)
model = LevitForImageClassificationWithTeacher.from_pretrained("facebook/levit-128S").to(torch_device)
image_processor = self.default_image_processor
image = prepare_img()