making gpt2 fx traceable

[xuzifei-dmatrix]

What does this PR do?

This PR fixes the issue that gpt2 is no longer fx traceable in the latest version
Below code gives error complaining about control flows not traceable. This PR solves the issue.

from transformers.utils.fx import HFTracer
from transformers import pipeline
import torch
from torch.fx import GraphModule

pipe = pipeline(
    task="text-generation",
    model="openai-community/gpt2",
    device="cuda",
)
x = torch.randint(1, 100, (1, 1024)).to("cuda")
past_key_values = pipe.model(x, use_cache=True).past_key_values
dummy_inputs = dict(input_ids=x, labels=x, past_key_values=past_key_values)

tracer = HFTracer()
gm = GraphModule(pipe.model, tracer.trace(pipe.model, dummy_inputs=dummy_inputs))

Fixes # (issue)

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@ArthurZucker

[ArthurZucker]

Thanks, do you mind running make fix-copies?

[ArthurZucker]

LGTM thanks!

[ArthurZucker]

This indeed fixes the issue of:

TraceError: Proxy object cannot be iterated. This can be attempted when the Proxy is used in a loop or as a *args or **kwargs function argument. See the torch.fx docs on pytorch.org for a more detailed explanation of what types of control flow can be traced, and check out the Proxy docstring for help troubleshooting Proxy iteration errors

[HuggingFaceDocBuilderDev]

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.