Update README.md

README.md

@@ -118,10 +118,6 @@ with torch.no_grad():
         input_signal=input_signal.to(device),
         input_signal_length=input_signal_length.to(device)
     ).cpu()
-
-# Check output dimensions
-B, T, C = torch_outputs.shape
-assert C == 2, "Output channels should be 2"
 ```
 
 ### Export to ONNX
@@ -164,9 +160,6 @@ torch.onnx.export(
         "output": {0: "batch_size", 1: "sequence_length"}
     }
 )
-
-# Validate ONNX model
-onnx.checker.check_model(onnx.load(ONNX_EXPORT_PATH))
 ```
 
 ### Inference with ONNX Runtime
@@ -187,11 +180,6 @@ ort_inputs = {
 
 # Run inference
 onnx_outputs = session.run(None, ort_inputs)[0]
-
-# Compare with PyTorch output
-for torch_out, onnx_out in zip(torch_outputs, onnx_outputs):
-    torch.testing.assert_close(torch_out, torch.from_numpy(onnx_out), atol=1e-3, rtol=1e-3)
-print("✅ PyTorch and ONNX Runtime outputs match!")
 ```
 
 ### RTTM Output from Frame-Level Speech Predictions