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# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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.
"""
Image/Text processor class for ALIGN
"""
from ...processing_utils import ProcessingKwargs, ProcessorMixin
class AlignProcessorKwargs(ProcessingKwargs, total=False):
# see processing_utils.ProcessingKwargs documentation for usage.
_defaults = {
"text_kwargs": {
"padding": "max_length",
"max_length": 64,
},
}
class AlignProcessor(ProcessorMixin):
r"""
Constructs an ALIGN processor which wraps [`EfficientNetImageProcessor`] and
[`BertTokenizer`]/[`BertTokenizerFast`] into a single processor that inherits both the image processor and
tokenizer functionalities. See the [`~AlignProcessor.__call__`] and [`~OwlViTProcessor.decode`] for more
information.
The preferred way of passing kwargs is as a dictionary per modality, see usage example below.
```python
from transformers import AlignProcessor
from PIL import Image
model_id = "kakaobrain/align-base"
processor = AlignProcessor.from_pretrained(model_id)
processor(
images=your_pil_image,
text=["What is that?"],
images_kwargs = {"crop_size": {"height": 224, "width": 224}},
text_kwargs = {"padding": "do_not_pad"},
common_kwargs = {"return_tensors": "pt"},
)
```
Args:
image_processor ([`EfficientNetImageProcessor`]):
The image processor is a required input.
tokenizer ([`BertTokenizer`, `BertTokenizerFast`]):
The tokenizer is a required input.
"""
attributes = ["image_processor", "tokenizer"]
image_processor_class = "EfficientNetImageProcessor"
tokenizer_class = ("BertTokenizer", "BertTokenizerFast")
valid_processor_kwargs = AlignProcessorKwargs
def __init__(self, image_processor, tokenizer):
super().__init__(image_processor, tokenizer)
__all__ = ["AlignProcessor"]
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