Wrong behaviour on tensor.roll(0,-1)

[Alexankharin]

My model includes some ooperations with tensors roll Torch model problematic code is

for i in range(10):
     featlist[i]=featuresr*featuresl.roll(i,-1)

and it turnd OK to onnx model. Nevertheless, the shape of output is wrong in case of i equals 0. Netron onnx model exploration shows that operations for roll are slicing and following concatenation. Barracuda looks to wrongly process the slicing of [0:0], that shoud return empty tensor with slicing dimension 0, while it seems to return the tensor with the same shape as input during graph execution (see image)

[Arminasss]

Hello @Alexankharin could you please share the model that you are using so we could have a closer look at the problem?

[Alexankharin]

The model is under NDA, so the minimal reproducable error-causing model is attached it is generated by simple pytorch code

import torch
class MinimalExample(torch.nn.Module):
    def __init__(self):
        super(MinimalExample, self).__init__()
    def forward(self,inpx):
        toret=[]
        for i in range(5):
            toret.append(inpx.roll(i,-1))
        return toret
model=MinimalExample()
inpx=torch.randn(1,3,256,256)
torch.onnx.export(model,              
  inpx,
  "minimalexample.onnx",  
  export_params=True,       
  opset_version=11,          
  do_constant_folding=True, 
  input_names = ['input'], 
  output_names = ['output{}'.format(i) for i in range(5)])

https://drive.google.com/file/d/1O4Z5RLAd1fR6gtq6_zAAHCOIk0bNkkG2/view?usp=sharing

All of the model outputs should have the same shape, barracuda shows the wrong output shape for output0