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# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. + Abstract Engine. All rights reserved.
#
# 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.
from transformers import PretrainedConfig, CLIPVisionConfig, SiglipTextConfig
class MitsuaJapaneseCLIPConfig(PretrainedConfig):
model_type = "mitsua_japanese_clip"
def __init__(
self,
text_config=None, vision_config=None,
projection_dim=512,
logit_scale_init_value=2.6592,
**kwargs,
):
super().__init__(**kwargs)
if text_config is None:
text_config = {}
if vision_config is None:
vision_config = {}
self.vision_config = CLIPVisionConfig(**vision_config)
self.text_config = SiglipTextConfig(**text_config)
self.projection_dim = projection_dim
self.logit_scale_init_value = logit_scale_init_value
self.initializer_factor = 1.0
@classmethod
def from_vision_text_configs(
cls, vision_config: PretrainedConfig, text_config: PretrainedConfig, **kwargs
):
r"""
Instantiate a [`VisionTextDualEncoderConfig`] (or a derived class) from text model configuration and vision
model configuration.
Returns:
[`VisionTextDualEncoderConfig`]: An instance of a configuration object
"""
return cls(
vision_config=vision_config.to_dict(),
text_config=text_config.to_dict(),
**kwargs,
) |