| import torch | |
| from transformers import PreTrainedModel | |
| from .custom_configuration import CustomConfig, NoSuperInitConfig | |
| class CustomModel(PreTrainedModel): | |
| config_class = CustomConfig | |
| def __init__(self, config): | |
| super().__init__(config) | |
| self.linear = torch.nn.Linear(config.hidden_size, config.hidden_size) | |
| def forward(self, x): | |
| return self.linear(x) | |
| def _init_weights(self, module): | |
| pass | |
| class NoSuperInitModel(PreTrainedModel): | |
| config_class = NoSuperInitConfig | |
| def __init__(self, config): | |
| super().__init__(config) | |
| self.linear = torch.nn.Linear(config.attribute, config.attribute) | |
| def forward(self, x): | |
| return self.linear(x) | |
| def _init_weights(self, module): | |
| pass | |