🐛 [Bug] Error encountered when compiling component module of GPT2

[gs-olive]

Bug Description

When compiling an MLP submodule of the HuggingFace GPT2 model from TorchScript to Torch-TRT, the following error is encountered:

GRAPH: [Torch-TensorRT - Debug Build] - Input to node: %self.c_fc.weight.1 : Float(768, 3072, strides=[3072, 1], requires_grad=0, device=cuda:0) = prim::Constant[value=<Tensor>]()
GRAPH: [Torch-TensorRT - Debug Build] - Input outputs a Tensor
GRAPH: [Torch-TensorRT - Debug Build] - Input is a constant
Traceback (most recent call last):
  File "case_dict.py", line 278, in <module>
    main2()
  File "case_dict.py", line 268, in main2
    comp = torchtrt.compile(traced, inputs=inp, enabled_precisions={torch.float}, truncate_long_and_double=True)
  File "~/TensorRT/py/torch_tensorrt/_compile.py", line 125, in compile
    return torch_tensorrt.ts.compile(
  File "~/TensorRT/py/torch_tensorrt/ts/_compiler.py", line 136, in compile
    compiled_cpp_mod = _C.compile_graph(module._c, _parse_compile_spec(spec))
RuntimeError: required keyword attribute 'upscale_factor' is undefined

To Reproduce

Steps to reproduce the behavior:

1. Instantiate GPT2 model from pretrained source:

from transformers import GPT2Model
model = GPT2Model.from_pretrained("gpt2", use_cache=False, torchscript=True).eval().cuda()

2. Select a small portion of the model: model_portion = model.h[0].mlp
3. Generate hidden state data: hidden_state = torch.rand((1, 768)).cuda()
4. Trace model traced = torch.jit.trace(model_portion, inp).cuda().eval()
5. Compile model:

trt_model = torchtrt.compile(traced, inputs=hidden_state, enabled_precisions={torch.float}, truncate_long_and_double=True)

Expected behavior

Module should compile via the TorchScript path

Environment

• Transformers: 4.27.2
• Torch-TensorRT Version (e.g. 1.0.0): 038520d
• PyTorch Version (e.g. 1.0): 2.1.0.dev20230317+cu117
• CPU Architecture: Intel Xeon CPU
• OS: Ubuntu 20.04
• How you installed PyTorch: pip
• Build command you used: python setup.py develop
• Are you using local sources or building from archives: local
• Python version: 3.8.13
• CUDA version: 11.7

Additional Considerations

The full GPT2 model is functional - see #1455. Each of its component modules should be able to compile successfully as a result.

[gs-olive]

Fixed by using Torch 2.0.0.dev20230219+cu117