Aluode/PerceptionLabPortable

1# coding=utf-82# Copyright 2020 The HuggingFace Inc. team.3# Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.4#5# Licensed under the Apache License, Version 2.0 (the "License");6# you may not use this file except in compliance with the License.7# You may obtain a copy of the License at8#9#     http://www.apache.org/licenses/LICENSE-2.010#11# Unless required by applicable law or agreed to in writing, software12# distributed under the License is distributed on an "AS IS" BASIS,13# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.14# See the License for the specific language governing permissions and15# limitations under the License.16 17 18from ...configuration_utils import PretrainedConfig19from ...utils import logging20from ..auto import AutoConfig21 22 23logger = logging.get_logger(__name__)24 25 26class EncoderDecoderConfig(PretrainedConfig):27    r"""28    [`EncoderDecoderConfig`] is the configuration class to store the configuration of a [`EncoderDecoderModel`]. It is29    used to instantiate an Encoder Decoder model according to the specified arguments, defining the encoder and decoder30    configs.31 32    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the33    documentation from [`PretrainedConfig`] for more information.34 35    Args:36        kwargs (*optional*):37            Dictionary of keyword arguments. Notably:38 39                - **encoder** ([`PretrainedConfig`], *optional*) -- An instance of a configuration object that defines40                  the encoder config.41                - **decoder** ([`PretrainedConfig`], *optional*) -- An instance of a configuration object that defines42                  the decoder config.43 44    Examples:45 46    ```python47    >>> from transformers import BertConfig, EncoderDecoderConfig, EncoderDecoderModel48 49    >>> # Initializing a BERT google-bert/bert-base-uncased style configuration50    >>> config_encoder = BertConfig()51    >>> config_decoder = BertConfig()52 53    >>> config = EncoderDecoderConfig.from_encoder_decoder_configs(config_encoder, config_decoder)54 55    >>> # Initializing a Bert2Bert model (with random weights) from the google-bert/bert-base-uncased style configurations56    >>> model = EncoderDecoderModel(config=config)57 58    >>> # Accessing the model configuration59    >>> config_encoder = model.config.encoder60    >>> config_decoder = model.config.decoder61    >>> # set decoder config to causal lm62    >>> config_decoder.is_decoder = True63    >>> config_decoder.add_cross_attention = True64 65    >>> # Saving the model, including its configuration66    >>> model.save_pretrained("my-model")67 68    >>> # loading model and config from pretrained folder69    >>> encoder_decoder_config = EncoderDecoderConfig.from_pretrained("my-model")70    >>> model = EncoderDecoderModel.from_pretrained("my-model", config=encoder_decoder_config)71    ```"""72 73    model_type = "encoder-decoder"74    sub_configs = {"encoder": AutoConfig, "decoder": AutoConfig}75    has_no_defaults_at_init = True76 77    def __init__(self, **kwargs):78        super().__init__(**kwargs)79        if "encoder" not in kwargs or "decoder" not in kwargs:80            raise ValueError(81                f"A configuration of type {self.model_type} cannot be instantiated because "82                f"both `encoder` and `decoder` sub-configurations were not passed, only {kwargs}"83            )84        encoder_config = kwargs.pop("encoder")85        encoder_model_type = encoder_config.pop("model_type")86        decoder_config = kwargs.pop("decoder")87        decoder_model_type = decoder_config.pop("model_type")88 89        self.encoder = AutoConfig.for_model(encoder_model_type, **encoder_config)90        self.decoder = AutoConfig.for_model(decoder_model_type, **decoder_config)91        self.is_encoder_decoder = True92 93    @classmethod94    def from_encoder_decoder_configs(95        cls, encoder_config: PretrainedConfig, decoder_config: PretrainedConfig, **kwargs96    ) -> PretrainedConfig:97        r"""98        Instantiate a [`EncoderDecoderConfig`] (or a derived class) from a pre-trained encoder model configuration and99        decoder model configuration.100 101        Returns:102            [`EncoderDecoderConfig`]: An instance of a configuration object103        """104        logger.info("Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config")105        decoder_config.is_decoder = True106        decoder_config.add_cross_attention = True107 108        return cls(encoder=encoder_config.to_dict(), decoder=decoder_config.to_dict(), **kwargs)109 110 111__all__ = ["EncoderDecoderConfig"]112