huggingface--transformers
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39 行
1.5 KiB
Python
39 行
1.5 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 unittest
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from transformers import Llama4Processor
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from transformers.testing_utils import require_vision
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from ...test_processing_common import ProcessorTesterMixin
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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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# Tiny processor created with make_tiny_processor.py from "meta-llama/Llama-4-Scout-17B-16E-Instruct"
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tiny_model_id = "hf-internal-testing/tiny-processor-llama4"
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@classmethod
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def _setup_image_processor(cls):
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# max_patches=1 ensures each image produces exactly 1 tile, so len(pixel_values)==batch_size.
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# Small size (20×20) keeps tensor allocations minimal.
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image_processor_class = cls._get_component_class_from_processor("image_processor")
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return image_processor_class(max_patches=1, size={"height": 20, "width": 20})
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@classmethod
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def _setup_test_attributes(cls, processor):
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cls.image_token = processor.image_token
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