watch_torch_model: only first training instance visible

[stocyr]

watch_torch_model() does not work entirely. For all images, I somehow only see the very first training instance the model encountered, though the distributions and also some stuff in the weights still seem to get updated.

Setup:

• Windows 10
• Deepkit Release 2020.1.5
• Deepkit SDK 1.0.1
• Running experiment on anything, from local script run, to local UI start to deployed docker run, eg. on pytorch/pytorch:1.4-cuda10.1-cudnn7-runtime

[marcj]

Yes, this is on purpose. It detects the very first input used and uses this for further debug layer extraction. It wouldn't make much sense to use for every debug extraction a different input as you could not easily compare with previous debug state. However, you can change the input easily, see the documentation. https://deepkit.ai/documentation/python-sdk/model-debugger see "Custom input to visualize"