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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,
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import unittest

from parameterized import parameterized

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_vision_available

from ...test_processing_common import ProcessorTesterMixin


if is_vision_available():
    from transformers import Glm4vProcessor


@require_vision
@require_torch
class Glm4vProcessorTest(ProcessorTesterMixin, unittest.TestCase):
    processor_class = Glm4vProcessor
    # Use tiny repos to avoid loading the full 151k-vocab tokenizer (~309 MB)
    # Tiny processor created with make_tiny_processor.py from "THUDM/GLM-4.1V-9B-Thinking"
    tiny_model_id = "hf-internal-testing/tiny-processor-glm4v"

    @classmethod
    def _setup_test_attributes(cls, processor):
        cls.image_token = processor.image_token
        # GLM4V uses the same token for images and video, so a video's tokens only count as
        # video inside the begin/end span
        cls.video_token = f"<|begin_of_video|>{processor.video_token}<|end_of_video|>"

    @parameterized.expand([(1, "pt")])
    @unittest.skip("Mode requires metadata to be always passed by users")
    def test_apply_chat_template_decoded_video(self, batch_size: int, return_tensors: str):
        pass

    @property
    def video_sampling_expectations(self):
        return [
            {"num_frames": 3, "fps": None, "expected_dim": 0, "output_length": 4},
            {"num_frames": None, "fps": 3, "expected_dim": 0, "output_length": 4},
            {"do_sample_frames": False, "fps": 10, "expected_dim": 0, "output_length": 24},
            {"do_sample_frames": False, "expected_dim": 0, "output_length": 24},
        ]