How to create a config.json after saving a model

seanbenhur · October 2, 2021, 12:02pm

Hi, I am trying to convert my model to onnx format with the help of this notebook
I got error , since config.json does not exist.
My model is a custom model with extra layers, similar to this,

Now how can I create a config.json file for this?

nielsr · October 4, 2021, 9:18am

Normally, if you save your model using the .save_pretrained() method, it will save both the model weights and a config.json file in the specified directory.

seanbenhur · October 4, 2021, 9:46am

Yes, but this is a custom model that I have saved in pytorch style, since it consists of additional layers, is there anyway to generate confg.json file?

BramVanroy · October 4, 2021, 9:51am

You need to subclass it to have the save_pretrained methods available. So instead of

class Mean_Pooling_Model(nn.Module):

use

from transformers.modeling_utils import PreTrainedModel
class Mean_Pooling_Model(PreTrainedModel):

It will add extra functionality on top of nn.Module.

github.com

huggingface/transformers/blob/bcc3f7b6560c1ed427f051107c7755956a27a9f2/src/transformers/modeling_utils.py#L415

    
      
                      exclude_embeddings (:obj:`bool`, `optional`, defaults to :obj:`True`):
                          Whether or not to count embedding and softmax operations.
          
          
        Returns:
                      :obj:`int`: The number of floating-point operations.
                  """
          
          
        return 6 * self.estimate_tokens(input_dict) * self.num_parameters(exclude_embeddings=exclude_embeddings)
          
          

          
class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMixin):
              r"""
              Base class for all models.
          
          
    :class:`~transformers.PreTrainedModel` takes care of storing the configuration of the models and handles methods
              for loading, downloading and saving models as well as a few methods common to all models to:
          
          
        * resize the input embeddings,
                  * prune heads in the self-attention heads.
          
          
    Class attributes (overridden by derived classes):

seanbenhur · October 4, 2021, 9:55am

Thank you I will try this!

seanbenhur · October 6, 2021, 9:00am

Is it possible to generate the configuration file for already trained model , i.e weights stored in normal pytorch model.bin