# Copyright 2022 HuggingFace Inc.
#
# 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
# limitations under the License.
import unittest
from transformers import DonutProcessor
from ...test_processing_common import ProcessorTesterMixin
class DonutProcessorTest(ProcessorTesterMixin, unittest.TestCase):
# Tiny processor created with make_tiny_processor.py from "naver-clova-ix/donut-base"
tiny_model_id = "hf-internal-testing/tiny-processor-donut"
processor_class = DonutProcessor
@classmethod
def _setup_image_processor(cls):
image_processor_class = cls._get_component_class_from_processor("image_processor")
# Default size=2560×1920 is the document-scanning resolution (~59 MB per image as float32).
# Use 64×64 for tests — no assertions check spatial dimensions.
return image_processor_class.from_pretrained(cls.tiny_model_id, size={"height": 64, "width": 64})
def test_token2json(self):
expected_json = {
"name": "John Doe",
"age": "99",
"city": "Atlanta",
"state": "GA",
"zip": "30301",
"phone": "123-4567",
"nicknames": [{"nickname": "Johnny"}, {"nickname": "JD"}],
"multiline": "text\nwith\nnewlines",
"empty": "",
}
sequence = (
"John Doe99Atlanta"
"GA30301123-4567"
"Johnny"
"JD"
"text\nwith\nnewlines"
""
)
processor = self.get_processor()
actual_json = processor.token2json(sequence)
self.assertDictEqual(actual_json, expected_json)