converting the attached ONNX model with the following script:
from onnxscript import ir
from onnxscript.optimizer import optimize
ir_model = ir.load("input.onnx")
optimized_model = optimize(ir_model)
ir.save(optimized_model, "output.onnx")
generates an ONNX model that does not abide by the ONNX spec.
BatchNormalization layer "/bn1/BatchNormalization" has training_mode=1 set. It has 3 outputs, but the last two are not used. Because they are unused, https://github.com/onnx/ir-py/blob/v0.2.1/src/onnx_ir/passes/common/unused_removal.py#L46-L50 clears the output names and training_mode attribute. While I don't like the notion of unnamed outputs to mean unused, it is an accepted way in ONNX. Later on during optimization, at https://github.com/microsoft/onnxscript/blob/v0.7.0/onnxscript/optimizer/_optimizer.py#L68, new names get reassigned to these outputs, resulting in the following graph snippet:
This graph now has a BatchNormaliztion node, with training_mode=0, with 3 outputs. This is incorrect per spec: "When training_mode=False, extra outputs are invalid." in https://onnx.ai/onnx/operators/onnx__BatchNormalization.html#batchnormalization-15.
I filed this bug with onnxscript, even though the name-clearing happens in onnx-ir.
relevant versions:
onnx 1.21.0
onnx-ir 0.2.1
onnxscript 0.7.1
input.onnx.zip
converting the attached ONNX model with the following script:
generates an ONNX model that does not abide by the ONNX spec.
BatchNormalization layer "/bn1/BatchNormalization" has
training_mode=1set. It has 3 outputs, but the last two are not used. Because they are unused, https://github.com/onnx/ir-py/blob/v0.2.1/src/onnx_ir/passes/common/unused_removal.py#L46-L50 clears the output names and training_mode attribute. While I don't like the notion of unnamed outputs to mean unused, it is an accepted way in ONNX. Later on during optimization, at https://github.com/microsoft/onnxscript/blob/v0.7.0/onnxscript/optimizer/_optimizer.py#L68, new names get reassigned to these outputs, resulting in the following graph snippet:This graph now has a BatchNormaliztion node, with
training_mode=0, with 3 outputs. This is incorrect per spec: "When training_mode=False, extra outputs are invalid." in https://onnx.ai/onnx/operators/onnx__BatchNormalization.html#batchnormalization-15.I filed this bug with onnxscript, even though the name-clearing happens in onnx-ir.
relevant versions:
input.onnx.zip