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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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11
tests/models/cvt/test_modeling_cvt.py
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@@ -31,7 +31,6 @@ if is_torch_available():
import torch
from transformers import CvtForImageClassification, CvtModel
from transformers.models.cvt.modeling_cvt import CVT_PRETRAINED_MODEL_ARCHIVE_LIST
if is_vision_available():
@@ -236,9 +235,9 @@ class CvtModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
@slow
def test_model_from_pretrained(self):
for model_name in CVT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = CvtModel.from_pretrained(model_name)
self.assertIsNotNone(model)
model_name = "microsoft/cvt-13"
model = CvtModel.from_pretrained(model_name)
self.assertIsNotNone(model)
# We will verify our results on an image of cute cats
@@ -252,11 +251,11 @@ def prepare_img():
class CvtModelIntegrationTest(unittest.TestCase):
@cached_property
def default_image_processor(self):
return AutoImageProcessor.from_pretrained(CVT_PRETRAINED_MODEL_ARCHIVE_LIST[0])
return AutoImageProcessor.from_pretrained("microsoft/cvt-13")
@slow
def test_inference_image_classification_head(self):
model = CvtForImageClassification.from_pretrained(CVT_PRETRAINED_MODEL_ARCHIVE_LIST[0]).to(torch_device)
model = CvtForImageClassification.from_pretrained("microsoft/cvt-13").to(torch_device)
image_processor = self.default_image_processor
image = prepare_img()

11
tests/models/cvt/test_modeling_tf_cvt.py
View File

@@ -23,7 +23,6 @@ if is_tf_available():
from transformers import TFCvtForImageClassification, TFCvtModel
from transformers.modeling_tf_utils import keras
from transformers.models.cvt.modeling_tf_cvt import TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST
if is_vision_available():
@@ -251,9 +250,9 @@ class TFCvtModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
@slow
def test_model_from_pretrained(self):
for model_name in TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = TFCvtModel.from_pretrained(model_name)
self.assertIsNotNone(model)
model_name = "microsoft/cvt-13"
model = TFCvtModel.from_pretrained(model_name)
self.assertIsNotNone(model)
# We will verify our results on an image of cute cats
@@ -267,11 +266,11 @@ def prepare_img():
class TFCvtModelIntegrationTest(unittest.TestCase):
@cached_property
def default_image_processor(self):
return AutoImageProcessor.from_pretrained(TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST[0])
return AutoImageProcessor.from_pretrained("microsoft/cvt-13")
@slow
def test_inference_image_classification_head(self):
model = TFCvtForImageClassification.from_pretrained(TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST[0])
model = TFCvtForImageClassification.from_pretrained("microsoft/cvt-13")
image_processor = self.default_image_processor
image = prepare_img()