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https://github.com/huggingface/transformers.git
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f789f960c8
* Avoid build crashes when torch.version.xpu doesn't exist * Trigger tests * Fix image token and skip inappropriate test * Remove ignore_errors=True * Add another skip
72 lines
2.6 KiB
Python
72 lines
2.6 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 typing import Optional
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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 = {}
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processor = Llama4Processor(image_processor, tokenizer, **processor_kwargs)
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processor.save_pretrained(cls.tmpdirname)
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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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# Override as Llama4Processor needs image tokens in prompts
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def prepare_text_inputs(self, batch_size: Optional[int] = None):
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if batch_size is None:
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return "lower newer <|image|>"
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if batch_size < 1:
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raise ValueError("batch_size must be greater than 0")
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if batch_size == 1:
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return ["lower newer <|image|>"]
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return ["lower newer <|image|>", "<|image|> upper older longer string"] + ["<|image|> lower newer"] * (
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batch_size - 2
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)
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@unittest.skip("This test uses return_tensors='np' which is not supported")
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def test_image_chat_template_accepts_processing_kwargs(self):
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pass
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