SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

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

Browse Source 
* [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
Download Patch File Download Diff File Expand all files Collapse all files

13
tests/models/bit/test_modeling_bit.py
View File

@@ -32,7 +32,6 @@ if is_torch_available():
from torch import nn
from transformers import BitBackbone, BitForImageClassification, BitImageProcessor, BitModel
from transformers.models.bit.modeling_bit import BIT_PRETRAINED_MODEL_ARCHIVE_LIST
if is_vision_available():
@@ -269,9 +268,9 @@ class BitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
@slow
def test_model_from_pretrained(self):
for model_name in BIT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = BitModel.from_pretrained(model_name)
self.assertIsNotNone(model)
model_name = "google/bit-50"
model = BitModel.from_pretrained(model_name)
self.assertIsNotNone(model)
# We will verify our results on an image of cute cats
@@ -285,13 +284,11 @@ def prepare_img():
class BitModelIntegrationTest(unittest.TestCase):
@cached_property
def default_image_processor(self):
return (
BitImageProcessor.from_pretrained(BIT_PRETRAINED_MODEL_ARCHIVE_LIST[0]) if is_vision_available() else None
)
return BitImageProcessor.from_pretrained("google/bit-50") if is_vision_available() else None
@slow
def test_inference_image_classification_head(self):
model = BitForImageClassification.from_pretrained(BIT_PRETRAINED_MODEL_ARCHIVE_LIST[0]).to(torch_device)
model = BitForImageClassification.from_pretrained("google/bit-50").to(torch_device)
image_processor = self.default_image_processor
image = prepare_img()