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Attempt to fix windows MDX ONNX loading tempfile bug in onnx2torch #63

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merged 2 commits into from
Apr 26, 2024
Merged

Attempt to fix windows MDX ONNX loading tempfile bug in onnx2torch #63

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3ad9e61
Attempt to fix windows MDX ONNX loading tempfile bug in onnx2torch
beveradb Apr 25, 2024
a150c3e
Bumped version with onnx2torch windows fix
beveradb Apr 26, 2024
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9 changes: 8 additions & 1 deletion audio_separator/separator/architectures/mdx_separator.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,9 @@
"""Module for separating audio sources using MDX architecture models."""

import os
import platform
import torch
import onnx
import onnxruntime as ort
import numpy as np
import onnx2torch
Expand Down Expand Up @@ -121,7 +123,12 @@ def load_model(self):
self.model_run = lambda spek: ort_inference_session.run(None, {"input": spek.cpu().numpy()})[0]
self.logger.debug("Model loaded successfully using ONNXruntime inferencing session.")
else:
self.model_run = onnx2torch.convert(self.model_path)
if platform.system() == 'Windows':
onnx_model = onnx.load(self.model_path)
self.model_run = onnx2torch.convert(onnx_model)
else:
self.model_run = onnx2torch.convert(self.model_path)

self.model_run.to(self.torch_device).eval()
self.logger.warning("Model converted from onnx to pytorch due to segment size not matching dim_t, processing may be slower.")

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