Explicar um modelo de classificação de imagens com a IA explicável da Agent Platform avaliações

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Jamil J. · Revisado há 3 months

Please fix the setup code as the entire time allotted for the Lab is usually spent trying to fix the tensorflow-hub import error involving pkg_resources. See the steps that worked for me below: Fix: Root Cause The machine has multiple Python environments (/opt/conda/, ~/.local/, plus conda envs for pytorch, tensorflow, jupyterlab). The notebook kernel uses /opt/conda/bin/python, but setuptools was either missing or installed in the wrong version there. The old version of tensorflow_hub in /opt/conda/ depends on pkg_resources, which is part of setuptools — but newer setuptools (70+) broke this by making pkg_resources no longer automatically available. What Was Tried (in order) pip install --user setuptools → already satisfied, but in the wrong environment pip install --user --force-reinstall setuptools → installed to ~/.local/, not where the kernel looks pip install --force-reinstall tensorflow-hub tensorflow-model-remediation → installed correctly but pkg_resources still broken /opt/conda/bin/pip install --force-reinstall tensorflow-hub → put packages in the right place but setuptools was still too new /opt/conda/bin/pip install --force-reinstall setuptools==69.5.1 ✅ → this fixed it Why setuptools==69.5.1 Was the Fix The find command revealed that pkg_resources only existed inside pip's own vendor folder, not as a standalone importable module. This confirmed that setuptools was either missing or too new. Versions 70+ of setuptools changed how pkg_resources is exposed, breaking older packages that import it directly. Pinning to 69.5.1 restored the old behaviour and made pkg_resources importable again. Key Lesson Always install packages using /opt/conda/bin/pip (not pip or pip install --user) when the notebook kernel is /opt/conda/bin/python. The --user flag installs to ~/.local/, which may or may not be on the kernel's path, causing confusing split-environment issues.

OBINNA O. · Revisado há 3 months

Vishwa K. · Revisado há 3 months

very good

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Shivanshi B. · Revisado há 3 months

Has errors

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