Can I debug in nimble?

[ReaperMaKNaE]

Thank you for great work.

I have a simple question, can I use a pdb in the model with nimble?

When I use pdb in the model and do nimble_model.prepare without any debug, it works. but try to call some value during debug, warning message comes out(just call, nothing change):

RuntimeWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won't change the number of iterations executed (and might lead to errors or silently give incorrect results)

and after preparing, massive amount of the error comes out(below log shows a part of the error):

- %1403 : int[] = prim::ListConstruct(%37, %37, %37, %37), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5 ? -- ^ ^ ^ ^ + %1398 : int[] = prim::ListConstruct(%32, %32, %32, %32), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5 ? ++ ^ ^ ^ ^ - %input.38 : Tensor = aten::constant_pad_nd(%input.37, %1403, %39), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5 # /home/rpmk/anaconda3/envs/nimble/lib/python3.7/site-packages/torch/nn/functional.py:3553:0 ? ------- + %input.38 : Tensor = aten::constant_pad_nd(%input.37, %1398, %34), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5 # /home/rpmk/anaconda3/envs/nimble/lib/python3.7/site-packages/torch/nn/functional.py:3553:0 ? +++++++ - %1405 : int[] = prim::ListConstruct(%37, %37), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ + %1400 : int[] = prim::ListConstruct(%32, %32), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ - %1406 : int[] = prim::ListConstruct(%39, %39), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ + %1401 : int[] = prim::ListConstruct(%34, %34), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ - %1407 : int[] = prim::ListConstruct(%37, %37), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ + %1402 : int[] = prim::ListConstruct(%32, %32), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ - %1408 : int[] = prim::ListConstruct(%39, %39), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ + %1403 : int[] = prim::ListConstruct(%34, %34), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 ? ^^^ ^ ^ - %input.39 : Tensor = aten::_convolution(%input.38, %1018, %35, %1405, %1406, %1407, %38, %1408, %37, %38, %38, %38, %40), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 # /home/rpmk/anac onda3/envs/nimble/lib/python3.7/site-packages/torch/nn/modules/conv.py:420:0 - %input.40 : Tensor = aten::batch_norm(%input.39, %1013, %1008, %1003, %998, %38, %33, %34, %38), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.1 # /home/rpmk/anaconda3/envs/nimble/lib/pyt hon3.7/site-packages/torch/nn/functional.py:2058:0 + %input.39 : Tensor = aten::_convolution(%input.38, %1013, %30, %1400, %1401, %1402, %33, %1403, %32, %33, %33, %33, %35), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.0 # /home/rpmk/anac onda3/envs/nimble/lib/python3.7/site-packages/torch/nn/modules/conv.py:420:0 + %input.40 : Tensor = aten::batch_norm(%input.39, %1008, %1003, %998, %993, %33, %28, %29, %33), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.1 # /home/rpmk/anaconda3/envs/nimble/lib/pyth on3.7/site-packages/torch/nn/functional.py:2058:0 - %input.41 : Tensor = aten::hardtanh_(%input.40, %31, %32), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.2 # /home/rpmk/anaconda3/envs/nimble/lib/python3.7/site-packages/torch/nn/function al.py:1186:0 ? ^^ - + %input.41 : Tensor = aten::hardtanh_(%input.40, %26, %27), scope: __module.backbone/__module.backbone.high_level_features/__module.backbone.high_level_features.5/__module.backbone.high_level_features.5.conv/__module.backbone.high_level_features.5.conv.2 # /home/rpmk/anaconda3/envs/nimble/lib/python3.7/site-packages/torch/nn/function al.py:1186:0 ? ^^ +

Can I get any advices?

Thank you.