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Torch was unable to set instance_norm trainmode to False, this migh…
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…t be causing the `asser_allclose` to fail. Make it a warning for now.
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Mathijs de Boer committed Dec 1, 2023
1 parent bec25b5 commit f4dfc3c
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Showing 2 changed files with 19 additions and 16 deletions.
10 changes: 5 additions & 5 deletions nnunetv2/model_sharing/entry_points.py
Original file line number Diff line number Diff line change
Expand Up @@ -173,12 +173,12 @@ def export_pretrained_model_onnx_entry():
print("!!!!!!!!!!!!!!!!!!!!!!!!WARNING!!!!!!!!!!!!!!!!!!!!!!!")
print("######################################################")
print(
"You are responsible for creating the ONNX pipeline \n"
"You are responsible for creating the ONNX pipeline\n"
"yourself.\n\n"
"This script will only export the model \n"
"weights to an onnx file, and some basic information \n"
"about the model. You will have to create the ONNX \n"
"pipeline yourself. \n"
"This script will only export the model weights to\n"
"an onnx file, and some basic information about\n"
"the model. You will have to create the ONNX pipeline\n"
"yourself.\n"
)
print(
"See\n"
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25 changes: 14 additions & 11 deletions nnunetv2/model_sharing/onnx_export.py
Original file line number Diff line number Diff line change
Expand Up @@ -73,10 +73,7 @@ def export_onnx_model(
config = predictor.configuration_manager

for fold, params in zip(folds, list_of_parameters):
if not isinstance(network, OptimizedModule):
network.load_state_dict(params)
else:
network._orig_mod.load_state_dict(params)
network.load_state_dict(params)

network.eval()

Expand Down Expand Up @@ -115,15 +112,21 @@ def export_onnx_model(
ort_inputs = {ort_session.get_inputs()[0].name: rand_input.numpy()}
ort_outs = ort_session.run(None, ort_inputs)

np.testing.assert_allclose(
torch_output.detach().cpu().numpy(),
ort_outs[0],
rtol=1e-03,
atol=1e-05,
)
try:
np.testing.assert_allclose(
torch_output.detach().cpu().numpy(),
ort_outs[0],
rtol=1e-03,
atol=1e-05,
verbose=True,
)
except AssertionError as e:
print(f"WARN: Differences found between torch and onnx:\n")
print(e)
print("\nExport will continue, but please verify that your pipeline matches the original.")

print(
f"Successfully exported and verified {curr_output_dir / output_name}"
f"Exported {curr_output_dir / output_name}"
)

with open(curr_output_dir / "config.json", "w") as f:
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