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# coding=utf-8
# Copyright 2023 Custom LLaVA Neuron Ablation 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.
"""
Processor class for Custom LLaVA with neuron ablation support.
"""
from transformers.models.llava.processing_llava import LlavaProcessor
from transformers.utils import logging
logger = logging.get_logger(__name__)
class CustomLlavaProcessor(LlavaProcessor):
r"""
Constructs a Custom LLaVA processor which wraps a LLaVA image processor and a LLaVA tokenizer into a single processor.
This is identical to the base LlavaProcessor but is provided for consistency with the custom model naming.
[`CustomLlavaProcessor`] offers all the functionalities of [`CLIPImageProcessor`] and [`LlamaTokenizerFast`]. See the
[`~LlavaProcessor.__call__`] and [`~LlavaProcessor.decode`] for more information.
Args:
image_processor ([`CLIPImageProcessor`], *optional*):
The image processor is a required input.
tokenizer ([`LlamaTokenizerFast`], *optional*):
The tokenizer is a required input.
"""
def __init__(self, image_processor=None, tokenizer=None):
super().__init__(image_processor, tokenizer)
logger.info("Initialized CustomLlavaProcessor with neuron ablation support") |