Audio Preprocessing - Jupyter Notebook
Trains is now ClearML
This documentation applies to the legacy Trains versions. For the latest documentation, see ClearML.
The example audio_preprocessing_example.ipynb demonstrates integrating Trains into a Jupyter Notebook which uses PyTorch and preprocesses audio samples. Trains automatically logs spectrogram visualizations reported by calling Matplotlib methods, and audio samples reported by calling TensorBoard methods. In the example, we also demonstrate connecting parameters to a Task and logging them. When the script runs, it creates an experiment named
data pre-processing which is associated with the
Audio Example project.
Trains automatically logs the waveform which the example reports by calling a Matplotlib method. These appear in RESULTS > PLOTS.
Trains automatically logs the audio samples which the example reports by calling TensorBoard methods, and the spectrogram visualizations reported by calling Matplotlib methods. They appear in RESULTS > DEBUG SAMPLES.
You can play the audio samples by double clicking the audio thumbnail.
You can view the spectrogram visualizations in the Trains Web (UI) image viewer.