SUMIN/HuggingFace_transformer
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🚨 🚨 Setup -> setupclass conversion (#37282)

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* More limited setup -> setupclass conversion

* make fixup

* Trigger tests

* Fixup UDOP

* Missed a spot

* tearDown -> tearDownClass where appropriate

* Couple more class fixes

* Fixups for UDOP and VisionTextDualEncoder

* Ignore errors when removing the tmpdir, in case it already got cleaned up somewhere

* CLIP fixes

* More correct classmethods

* Wav2Vec2Bert fixes

* More methods become static

* More class methods

* More class methods

* Revert changes for integration tests / modeling files

* Use a different tempdir for tests that actually write to it

* Remove addClassCleanup and just use teardownclass

* Remove changes in modeling files

* Cleanup get_processor_dict() for got_ocr2

* Fix regression on Wav2Vec2BERT test that was masked by this before

* Rework tests that modify the tmpdir

* make fix-copies

* revert clvp modeling test changes

* Fix CLIP processor test

* make fix-copies
This commit is contained in:
Matt
2025-04-08 17:15:37 +01:00
committed by GitHub
parent c15a7adb28
commit 4d0de5f73a
49 changed files with 740 additions and 574 deletions
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12
tests/models/llava_next/test_processor_llava_next.py
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@@ -34,14 +34,15 @@ if is_vision_available():
class LlavaNextProcessorTest(ProcessorTesterMixin, unittest.TestCase):
processor_class = LlavaNextProcessor
def setUp(self):
self.tmpdirname = tempfile.mkdtemp()
@classmethod
def setUpClass(cls):
cls.tmpdirname = tempfile.mkdtemp()
image_processor = LlavaNextImageProcessor()
tokenizer = LlamaTokenizerFast.from_pretrained("huggyllama/llama-7b")
processor_kwargs = self.prepare_processor_dict()
processor_kwargs = cls.prepare_processor_dict()
processor = LlavaNextProcessor(image_processor, tokenizer, **processor_kwargs)
processor.save_pretrained(self.tmpdirname)
processor.save_pretrained(cls.tmpdirname)
def get_tokenizer(self, **kwargs):
return LlavaNextProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer
@@ -49,7 +50,8 @@ class LlavaNextProcessorTest(ProcessorTesterMixin, unittest.TestCase):
def get_image_processor(self, **kwargs):
return LlavaNextProcessor.from_pretrained(self.tmpdirname, **kwargs).image_processor
def prepare_processor_dict(self):
@staticmethod
def prepare_processor_dict():
return {
"chat_template": "{% for message in messages %}{% if message['role'] != 'system' %}{{ message['role'].upper() + ': '}}{% endif %}{# Render all images first #}{% for content in message['content'] | selectattr('type', 'equalto', 'image') %}{{ '<image>\n' }}{% endfor %}{# Render all text next #}{% if message['role'] != 'assistant' %}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{{ content['text'] + ' '}}{% endfor %}{% else %}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{% generation %}{{ content['text'] + ' '}}{% endgeneration %}{% endfor %}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ 'ASSISTANT:' }}{% endif %}",
"patch_size": 3,