| from typing import List | |
| from transformers import PretrainedConfig | |
| """ | |
| The configuration of a model is an object that | |
| will contain all the necessary information to build the model. | |
| The three important things to remember when writing you own configuration are the following: | |
| - you have to inherit from PretrainedConfig, | |
| - the __init__ of your PretrainedConfig must accept any kwargs, | |
| - those kwargs need to be passed to the superclass __init__. | |
| """ | |
| class DPTDepthConfig(PretrainedConfig): | |
| """ | |
| Defining a model_type for your configuration is not mandatory, | |
| unless you want to register your model with the auto classes.""" | |
| model_type = "dptdepth" | |
| def __init__(self, **kwargs): | |
| super().__init__(**kwargs) | |