Negate ONNX Model and PyTorch script for generating it.

neg.onnx

pytorch1.5:b


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negate.py

import torch

class TwoLayerNet(torch.nn.Module):
    def __init__(self):
        """
        constructor just calls super.
        """
        super(TwoLayerNet, self).__init__()

    def forward(self, x):
        """
        In the forward function we accept a Tensor of input data and we must return
        a Tensor of output data. We can use Modules defined in the constructor as
        well as arbitrary operators on Tensors.
        """
        return x.neg()

model = TwoLayerNet()
inp = torch.tensor([[[[-0.5]*320]]], dtype=torch.float32)
torch.onnx.export(model, inp, 'neg.onnx')