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from transformers import PretrainedConfig, AutoConfig |
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class CLIPEncoderDecoderConfig(PretrainedConfig): |
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model_type = "clip-encoder-decoder" |
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def __init__( |
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self, |
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**kwargs): |
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super().__init__(**kwargs) |
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self.encoder = AutoConfig.from_pretrained('microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft') |
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self.decoder = AutoConfig.from_pretrained('airesearch/wangchanberta-base-att-spm-uncased') |
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self.is_encoder_decoder = True |
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@classmethod |
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def from_encoder_decoder_configs( |
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cls, encoder_config: PretrainedConfig, decoder_config: PretrainedConfig, **kwargs |
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) -> PretrainedConfig: |
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r""" |
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Instantiate a [`VisionEncoderDecoderConfig`] (or a derived class) from a pre-trained encoder model |
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configuration and decoder model configuration. |
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Returns: |
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[`VisionEncoderDecoderConfig`]: An instance of a configuration object |
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""" |
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decoder_config.is_decoder = True |
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decoder_config.add_cross_attention = True |
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return cls(encoder=encoder_config.to_dict(), decoder=decoder_config.to_dict(), **kwargs) |
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