Shashank Nigam

Will Start working with MobileNetV2, InceptionNetV3

For the models conversion do we also nee to train model on SINGA after conversion from onnx, and have a comparison matrix? For example super_resolution via subpixel convolution layer was...

Hi, Can anyone verify if for SuperResolutionNet, attached notebook would be sufficient? Thanks and Regards, Shashank Nigam [SuperResolution.zip](https://github.com/apache/singa/files/4695603/SuperResolution.zip)

Hi, Shufflenetv2 for average pooling layer the conversion from onnx fails on below error: ValueError: Not implemented yet for count_include_pad or ceil_mode with below stack trace ValueError Traceback (most recent...

> @Shashankwer I got the same error too, there is a "not implemented error" too when I try to run ShufflenetV1 > > I got a floating point exception: 8...

Hi @joddiy, For Shufflenetv2 the model conversion is failing due to use of ceil_mode. Although the value is set to false in onnx model (0) its still failing at a...

> > @joddiy Hi, can I ask, for the other models that is not in ONNX, how do we find the reliable reference for it? I look at the papers,...

Hi @joddiy, For The Type I operator floor is not present in autograd.py can we implement the same in autograd.py on taking the implementation of Ceil as the reference. Also...