🐛 [Bug] Encountered bug : torch._dynamo.exc.InternalTorchDynamoError: 'NoneType' object is not subscriptable

Bug Description

I met a bug when I use torch-tensorrt to quantize a YOLOv6 model into fp8_e4m3. I use the code in vgg_fp8_code , but I met the bug report as below:

E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Error while creating guard:
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Name: "type(L['self'].neck.Bifusion0.upsample.upsample_transpose).mro[4].forward.defaults[0]"
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Source: local_nn_module
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Create Function: CONSTANT_MATCH
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Guard Types: None
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Code List: None
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Object Weakref: None
E0720 18:37:39.430194 140203970340672 torch/_guards.py:251] [0/0] Guarded Class Weakref: None
Traceback (most recent call last):
File "/mnt/d/LM/YOLOv6/test_tensorrt.py", line 96, in
exp_program = torch.export.export(model, (input_tensor,))
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/export/init.py", line 174, in export
return _export(
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/export/_trace.py", line 635, in wrapper
raise e
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/export/_trace.py", line 618, in wrapper
ep = fn(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/export/exported_program.py", line 83, in wrapper
return fn(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/export/_trace.py", line 860, in _export
gm_torch_level = _export_to_torch_ir(
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/export/_trace.py", line 347, in _export_to_torch_ir
gm_torch_level, _ = torch._dynamo.export(
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 1311, in inner
result_traced = opt_f(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
return fn(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 921, in catch_errors
return callback(frame, cache_entry, hooks, frame_state, skip=1)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 400, in _convert_frame_assert
return _compile(
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/contextlib.py", line 79, in inner
return func(*args, **kwds)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 703, in _compile
raise InternalTorchDynamoError(str(e)).with_traceback(
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 676, in _compile
guarded_code = compile_inner(code, one_graph, hooks, transform)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 262, in time_wrapper
r = func(*args, **kwargs)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 634, in compile_inner
check_fn = CheckFunctionManager(
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/guards.py", line 1048, in init
guard.create(builder)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_guards.py", line 249, in create
return self.create_fn(builder, self)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/guards.py", line 501, in CONSTANT_MATCH
val = self.get(guard.name)
File "/home/cyy/anaconda3/envs/yolo_quantize/lib/python3.10/site-packages/torch/_dynamo/guards.py", line 284, in get
return eval(name, self.scope, CLOSURE_VARS)
File "", line 1, in
torch._dynamo.exc.InternalTorchDynamoError: 'NoneType' object is not subscriptable

I wonder why this bug happened. Are there some unsupported architectures in YOLOv6 for fp8 quantization?

To Reproduce

My code is copied from the examples of VGG-fp8 like this:

`
eval = Evaler(data=data,
batch_size=4,
img_size=640,
conf_thres=0.4,
device=device,
shrink_size=None,
plot_curve=False,
half=False)
model = eval.init_model(None, weights, task)

def eval_func(model):
    model.eval()
    eval2 = Evaler(data=data, 
              batch_size=2,
              img_size=640,
              conf_thres=0.4, 
              device=device, 
              shrink_size=None,
              plot_curve=False,)
    eval2.stride = int(model.stride.max())
    dataloader2 = eval2.init_data(None, task)
    pred_result, vis_outputs, vis_paths = eval2.predict_model(model, dataloader2, task)
    map50, map = eval2.eval_model(pred_result, model, dataloader2, task)
    del eval2
    return map50

quant_cfg = mtq.FP8_DEFAULT_CFG
# PTQ with in-place replacement to quantized modules
mtq.quantize(model, quant_cfg, forward_loop=eval_func)
# model has FP8 qdq nodes at this point

input_img = torch.randn([1, 3, 640, 640])
with torch.no_grad():
    with export_torch_mode():
    # Compile the model with Torch-TensorRT Dynamo backend
        input_tensor = input_img.cuda()
        exp_program = torch.export.export(model, (input_tensor,))
        trt_model = torchtrt.dynamo.compile(
            exp_program,
            inputs=[input_tensor],
            enabled_precisions={torch.float8_e4m3fn},
            min_block_size=1,
            debug=False,
        )

        print(trt_model)`

Environment

Build information about Torch-TensorRT can be found by turning on debug messages

• Torch-TensorRT Version (e.g. 1.0.0): 2.3.0
• PyTorch Version (e.g. 1.0): 2.3.0
• CPU Architecture: x86-64
• OS (e.g., Linux): linux(WSL2)
• How you installed PyTorch (conda, pip, libtorch, source): pip
• Python version: 3.10
• CUDA version: 12.1
• GPU models and configuration: RTX4090

Start with /mnt/d/LM/YOLOv6/test_tensorrt.py and compare its export and compile sequence with examples/dynamo/vgg16_fp8_ptq.py. Reproduce the failure under the stated PyTorch and Torch-TensorRT versions, isolating torch.export from torchtrt.dynamo.compile and the YOLOv6 model. Done means identifying whether the failure is an unsupported architecture or an export/guard regression, with a focused regression case or documented compatibility result.