2.2 KiB
Audio separatio tools
Some random tools used during development.
They are intended to be invoked from the root of the nodes.
ONNX to safetensors converter
File: onnx2safetensors.py
Used to convert MDX-Net models in ONNX format to safetensors. Might work for other ONNX files using the same operands. But you'll need a PyTorch class for its architecture that creates the layers in the same order as the ONNX file.
Demucs to safetensors
File: demucs2safetensors.py
From a YAML file and the PyTorch components it creates safetensors version of the Demucs file. All metadata and models are contained in the new file.
Batch converter
File: batch_convert.py
Used to convert all the MDX-Net files in one run
Demix
File: demix.py
Used to run the inference on audio files performing the demixing process
Download Model
File: download_model.py
Downloads a model listed in the DB
Show Data Base
File: show_db.py
Prints the content of the models data base.
This is useful to adjust details in the DB, but you need to modify the code (apply_process)
Show ONNX
File: show_onnx.py
Displays the ONNX input, output and layers. Is a text representation, not as nice as Netron, but you can extract a lot of information from it.
It can also show details of what onnx2pytorch interprets from it.
And can do an inferece run using random data. We used it to determine some details of the onnx2pytorch details.
Show Class
File: show_class.py
Used to display our PyTorch class, also the state_dict keys. It can optionally export the class structure as an ONNX file that can be loaded by Netron, but contains too much extra names.
Show Metadata
File: show_metadata.py
Used to display our safetensors metadata. It can decode structures in JSON format we use for Demucs.
Style Fixer
File: style_fixer.py
Fixes various common style errors found in Gemini 2.5 Pro code. The script was created by Gemini ... can create the script, but can't stop making the same errors over and over.
UVR Hash
File: uvr_hash.py
Computes the hash used by UVR to identify a model. We use the same hash, as many tools do.
This is the key value for aur model database.