Cannot trace_module on models using model's generate function
## Environment info
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     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.3.1
- Platform: Linux-5.8.14_1-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no

### Who can help
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@patrickvonplaten, @sshleifer
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@patrickvonplaten, @sshleifer

## Information

Model I am using BART

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

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [*] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. load any model that uses the generate function
2. try to trace it using trace_module

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Can be easily reproduced with the following snippet:

```
import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = 'sshleifer/bart-tiny-random'
tokenizer = AutoTokenizer.from_pretrained(model)
sqgen_model = AutoModelForSeq2SeqLM.from_pretrained(model, torchscript=True)
sqgen_model.eval()
dummy_input = ' '.join('dummy' for dummy in range(512))
batch = tokenizer(
    [dummy_input], return_tensors='pt', truncation=True, padding='longest',
)
with torch.no_grad():
    traced_model = torch.jit.trace_module(  # type: ignore
        sqgen_model,
        {
            'forward': (batch.input_ids, batch.attention_mask),
            'generate': (batch.input_ids, batch.attention_mask),
        },
    )

```

It throws an error:

```
  File "/home/void/.miniconda3/envs/lexml/src/transformers/src/transformers/generation_utils.py", line 288, in generate
    assert isinstance(max_length, int) and max_length > 0, "`max_length` should be a strictly positive integer."
AssertionError: `max_length` should be a strictly positive integer.
```

obviously because the generate function's second argument is supposed to be max_length and not attention_mask

## Expected behavior
Should be able to trace models that use the generate function.

<!-- A clear and concise description of what you would expect to happen. -->

`generate` currently does not support `torch.jit.trace`. This is sadly also not on the short-term roadmap.<|||||>@patrickvonplaten, thanks for the response. In that case is there no way to trace the inference process of generative models provided here ? So any kind of inference of the form text -> text (for eg: summarization) cannot be exported to torchscript ? <|||||>Yes, if you want to make it faster, reduce `num_beams`.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
<|||||>Hi, are summarization kinds of models still not traceable ??

I am trying to deploy this onto AWS inferentia, whose prerequisite is that the model should be traceable !!

for example this sshleifer/distilbart-cnn-12-6

@sshleifer, @patrickvonplaten can you guys please help ??<|||||>Hey @DevBey,

Could you maybe open a new issue that states exactly what doesn't work in your case? This issue is quite old now and it would be nice to have a reproducible code snippet with the current `transformers` version.