Installation
The MLdebugger Python SDK is a framework for collecting internal features and metadata from models built and trained in Python, enabling evaluation and debugging.
System Requirements
- Python: 3.7 - 3.12
- ML Framework: PyTorch (1.7.1-2.10.0) or TensorFlow/Keras (2.1.0-2.18.0)
About Python 3.6
Python 3.6 is not supported. Core dependencies (cryptography, SQLAlchemy 2.x, pandas 1.3+) require Python 3.7+.
Prerequisites
This SDK assumes that inference can be executed using models implemented in PyTorch or TensorFlow. Please run the following commands in a Python environment where one of these ML frameworks is installed and the model can be executed.
Installation Methods
Standard Installation
Install directly using the Dropbox shared link.
pip install "https://dl.dropboxusercontent.com/s/hw78mfecqq3qyy8630d15/ml_debugger-0.3.3-py3-none-any.whl?rlkey=00o6520zstd9syaosw2rxypz9"
Installation URL
The installation URL may change. Contact the Adansons team for the latest URL.
Installation Without Dependencies
If you want to avoid dependency conflicts with your existing environment, use the --no-deps option.
pip install --no-deps "https://dl.dropboxusercontent.com/s/hw78mfecqq3qyy8630d15/ml_debugger-0.3.3-py3-none-any.whl?rlkey=00o6520zstd9syaosw2rxypz9"
In this case, you need to install the following main dependencies separately:
| Package | Minimum Version | Purpose |
|---|---|---|
| numpy | 1.19.0 | Numerical computation |
| pandas | 1.3.0 | Data manipulation |
| sqlalchemy | 1.4.0 | Database operations |
| sqlmodel | 0.0.8 | ORM models |
| requests | 2.25.0 | API communication |
| pyyaml | 6.0 | Configuration files |
Update Method
To update an existing installation to the latest version, use the --upgrade option.
pip install --upgrade "https://dl.dropboxusercontent.com/s/hw78mfecqq3qyy8630d15/ml_debugger-0.3.3-py3-none-any.whl?rlkey=00o6520zstd9syaosw2rxypz9"
Installation Verification
To verify that the installation was successful, run the following command.
python -c "from importlib.metadata import version; print(version('ml-debugger'))"
If it runs without errors and displays the version number, the installation is successful.
0.3.3
Next Steps
After installation is complete, proceed to Getting Started to learn the basic usage of the SDK.