Hi HuggingFace Team
We are at the beginning of a new DL project. In this project, we work with transformers in TF2.
Before we start this we’d love to know what are your plans about creating a training framework for TF2.
In our search for answers, we came across a GitHub issue that mentioned that TFtrainer will be changed/removed.
  

      github.com/huggingface/transformers
  

  
    
  
	  
  

  
    
      evaluation in TFTrainer does not run on GPU 1
    

    
      
        opened 
        
          
        
        May 5, 2021
      
      


      
        
          
          rohanshingade
        
      
    

    
    
  


  
    ## Environment info
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     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.5.1
- Platform: ubuntu 18.04
- Python version: 3.6.9
- PyTorch version (GPU?):
- Tensorflow version (GPU?): tensorflow-gpu==2.4.1
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help
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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @Rocketknight1

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

Model hub:

- for issues with a model report at https://discuss.huggingface.co/ and tag the model's creator.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

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@patil-suraj @Rocketknight1

## Information

I'm using TFT5ForConditionalGeneration for masked language modelling task. During training GPU utilisation is above 95% but as soon as evaluation starts it goes to 0%. Evaluation is slow. Even though [evaluate function is in strategy.scope()](https://github.com/huggingface/transformers/blob/c065025c4720a87783ca504a9018454893d00649/src/transformers/trainer_tf.py#L580). it does not use gpu.

The problem arises when using:
* [ ] the official example scripts: (give details below)

I'm using the official example script of TFTrainer and modified `run_tf_glue.py` a bit for custom data input.

The tasks I am working on is:
* [ ] my own task or dataset: (give details below)

Final train_dataset and eval_dataset (input to TFTrainer) have the form `({"input_ids": , "attention_mask": ,"decoder_attention_mask": }, labels)`

## To reproduce

Steps to reproduce the behavior:

I tried reproducing the error using run_tf_squad.py and run_tf_glue.py but both the scripts gave error as the inputs to the trainer were not compatible. Only MRPC task worked, but it had only 400 examples in evaluation so hard to determine. Rest of them simply didn't work, there was an error.

If possible I would like to contribute to TFTrainer in terms of running evaluation on GPU and processing squad and glue dataset to match dimensions to TFTrainer inputs. Guidance is really appreciated. 

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## Expected behavior
  

  

  
    
    
  

  


We were hoping you could shed more light on your plans for the integration of the transformers library with TF2. More concretely -
Do you intend to release a TF Trainer?
Will it be using Keras?
Any date expectations?
Thanks,