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Example application using trame for exploring MNIST dataset in the context of AI training and XAI thanks to XAITK.

Installing

For the Python layer it is recommended to use conda to properly install the various ML packages.

macOS conda setup

brew install miniforge
conda init zsh

venv creation for AI

# Needed in order to get py3.9 with lzma
# PYTHON_CONFIGURE_OPTS="--enable-framework" pyenv install 3.9.9

conda create --name trame-mnist python=3.9
conda activate trame-mnist
conda install "pytorch==1.9.1" "torchvision==0.10.1" -c pytorch
conda install scipy "scikit-learn==0.24.2" "scikit-image==0.18.3" -c conda-forge
pip install -e .

Run the application

conda activate trame-mnist
trame-mnist

Metadata

Release files for trame-mnist 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for trame-mnist 1.0.0
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Built distribution (wheel)

Table of built distributions (wheels) for trame-mnist 1.0.0
File Interpreter ABI Platform
trame_mnist-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 26.8 kB

Release files / trame-mnist-1.0.0.tar.gz

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Release files / trame_mnist-1.0.0-py3-none-any.whl

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Uploaded via twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.7

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2.1.0

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2.0.1

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2.0.0

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1.1.0

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1.0.1

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This release

1.0.0 This release

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