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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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import shutil
import tempfile
import unittest

from transformers import AutoProcessor, Llama4Processor, PreTrainedTokenizerFast
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available

from ...test_processing_common import ProcessorTesterMixin


if is_vision_available():
    from transformers import Llama4ImageProcessorFast


@require_vision
class Llama4ProcessorTest(ProcessorTesterMixin, unittest.TestCase):
    processor_class = Llama4Processor

    @classmethod
    def setUpClass(cls):
        cls.tmpdirname = tempfile.mkdtemp()

        image_processor = Llama4ImageProcessorFast(max_patches=1, size={"height": 20, "width": 20})
        tokenizer = PreTrainedTokenizerFast.from_pretrained("unsloth/Llama-3.2-11B-Vision-Instruct-unsloth-bnb-4bit")
        processor_kwargs = cls.prepare_processor_dict()
        processor = Llama4Processor(image_processor, tokenizer, **processor_kwargs)
        processor.save_pretrained(cls.tmpdirname)
        cls.image_token = processor.image_token

    def get_tokenizer(self, **kwargs):
        return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer

    def get_image_processor(self, **kwargs):
        return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).image_processor

    @classmethod
    def tearDownClass(cls):
        shutil.rmtree(cls.tmpdirname)