What do the indices mean for the input/output in PyTorch's documentation?
Question:
I was reading the documentation for PyTorch’s Conv2d layer when I encountered this:
What exactly do the indices behind the parameter names in the input/output section mean? padding[0], dilation[0], etc.
Is the reference only applicable when the layer is provided with a tuple? In other words, if a scalar value is provided, does it mean that all references are the same? Can anyone provide some clarification on this matter?
Answers:
padding parameter accepts int, tuple, or str.
- If you use
int as the input, such as padding = 1, then padding[0] = padding[1] = 1.
- If you use the tuple, such as
padding = (1, 2), then padding[0] = 1, padding[1] = 2.
I haven’t tried with str though.
I was reading the documentation for PyTorch’s Conv2d layer when I encountered this:
What exactly do the indices behind the parameter names in the input/output section mean? padding[0], dilation[0], etc.
Is the reference only applicable when the layer is provided with a tuple? In other words, if a scalar value is provided, does it mean that all references are the same? Can anyone provide some clarification on this matter?
padding parameter accepts int, tuple, or str.
- If you use
intas the input, such aspadding = 1, thenpadding[0] = padding[1] = 1. - If you use the tuple, such as
padding = (1, 2), thenpadding[0] = 1, padding[1] = 2.
I haven’t tried with str though.