Example application using trame for exploring MNIST dataset in the context of AI training and XAI thanks to XAITK.
Free software: BSD License
Installing
For the Python layer it is recommended to use conda to properly install the various ML packages.
conda setup on macOS
Go to conda documentation for your OS
brew install miniforge
conda init zshvenv setup 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
# For development when inside repo
pip install -e .
# For testing (no need to clone repo)
pip install trame-mnistRunning the application
conda activate trame-mnist
trame-mnistIf cuda is available, the application will use your GPU, but you can also force the usage of your cpu by adding to your command line the following argument: –cpu
License
trame-mnist is distributed under the OSI-approved BSD 3-clause License.
3 maintainers
Metadata
3 maintainers
Release files for trame-mnist 2.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| trame-mnist-2.0.1.tar.gz | 14.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| trame_mnist-2.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.7 kB
Release files / trame-mnist-2.0.1.tar.gz
| Download URL | trame-mnist-2.0.1.tar.gz |
|---|---|
| Size | 14.7 kB |
| Tags | Source |
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Release files / trame_mnist-2.0.1-py3-none-any.whl
| Download URL | trame_mnist-2.0.1-py3-none-any.whl |
|---|---|
| Size | 17.0 kB |
| Tags | Python 3 |
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twine/4.0.0 CPython/3.9.10
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