New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

Describe the bug
when axis has duplicate value , onnxruntime compute result is all same value ,which is different with expect of tensorflow

Urgency
2020.11.18

System information
Linux Ubuntu 16.04

• ONNX Runtime installed from binary
• ONNX Runtime version:1.4.0
• Python version:3.5

Expected behavior
When there are duplicate values, the duplicate can be removed. j

🐞Describe the bug

Converting Frontend cannot be 100% converted when pytorch model is converted to MLmodel. I get a warning

Trace

`TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other

I am trying to convert a custom pytorch model to tensorflow, I am abe to convert pytorch to onnx but converting onnx to tensorflow gives issue.

The code snippets are as follows-

pytorch to onnx

net = custom pytorch model
net.load_state_dict("pre-trained model")
dummyInput = np.random.uniform(0,1,(1,8,3,256,256))
dummyInput = Variable(torch.FloatTensor(dummyInput))
torch.onnx.export(ne

https://github.com/awslabs/mxnet-model-server/blob/master/plugins/endpoints/src/main/java/software/amazon/ai/mms/plugins/endpoint/ExecutionParameters.java#L26

'max_request_size' seems to refer to bytes, not mb.