Hi all,
First off, thanks for the amazing visualization library! I was excited to try it out, but I encountered an infinite recursion error when calling torchlens.log_forward_pass(). I tested this using the AlexNet example from your Colab notebook, both on Colab and my local computer.
Example:
model = torchvision.models.AlexNet()
x = torch.rand(1, 3, 224, 224)
model_history = tl.log_forward_pass(model, x, vis_opt='unrolled')
print(model_history)
Error:
Fatal Python error: Cannot recover from stack overflow.
Python runtime state: initialized
The error trace shows repeated calls to functions in torchlens.helper_funcs.py, particularly:
extend_search_stack_from_item
search_stack_for_vars_of_type
get_vars_of_type_from_obj
log_function_output_tensors_exhaustive
These functions seem to be recursively calling each other indefinitely.
Hi all,
First off, thanks for the amazing visualization library! I was excited to try it out, but I encountered an infinite recursion error when calling torchlens.log_forward_pass(). I tested this using the AlexNet example from your Colab notebook, both on Colab and my local computer.
Example:
model = torchvision.models.AlexNet()
x = torch.rand(1, 3, 224, 224)
model_history = tl.log_forward_pass(model, x, vis_opt='unrolled')
print(model_history)
Error:
Fatal Python error: Cannot recover from stack overflow.
Python runtime state: initialized
The error trace shows repeated calls to functions in torchlens.helper_funcs.py, particularly:
These functions seem to be recursively calling each other indefinitely.