54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
# Copyright 2024 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import shutil
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import tempfile
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import unittest
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from transformers import AutoProcessor, Llama4Processor, PreTrainedTokenizerFast
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from transformers.testing_utils import require_vision
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from transformers.utils import is_vision_available
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from ...test_processing_common import ProcessorTesterMixin
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if is_vision_available():
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from transformers import Llama4ImageProcessorFast
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@require_vision
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class Llama4ProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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processor_class = Llama4Processor
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@classmethod
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def setUpClass(cls):
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cls.tmpdirname = tempfile.mkdtemp()
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image_processor = Llama4ImageProcessorFast(max_patches=1, size={"height": 20, "width": 20})
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tokenizer = PreTrainedTokenizerFast.from_pretrained("unsloth/Llama-3.2-11B-Vision-Instruct-unsloth-bnb-4bit")
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processor_kwargs = cls.prepare_processor_dict()
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processor = Llama4Processor(image_processor, tokenizer, **processor_kwargs)
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processor.save_pretrained(cls.tmpdirname)
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cls.image_token = processor.image_token
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def get_tokenizer(self, **kwargs):
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return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer
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def get_image_processor(self, **kwargs):
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return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).image_processor
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@classmethod
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def tearDownClass(cls):
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shutil.rmtree(cls.tmpdirname)
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