Concatenating observations that include image, pose and sensor readings

[edowson (Elvis Dowson)]

On a related note, this post by @ptrblck talks about concatenating a layer output with additional input data. I need to think and read a bit more, for what I need to do though.

Concatenate layer output with additional input data

Here is a small example for your use case: class MyModel(nn.Module): def __init__(self): super(MyModel, self).__init__() self.cnn = models.inception_v3(pretrained=False, aux_logits=False) self.cnn.fc = nn.Linear( self.cnn.fc.in_features, 20) self.fc1 = nn.Linear(20 + 10, 60) self.fc2 = nn.Linear(60, 5) def forward(self, image, data): x1 = self.cnn(image) x2 = data x = torch.cat((x1, x2…