| 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) |
|
|
