You could try torchtyping pip install torchtyping
Or jaxtyping that also support torch and numpy.
a simple example is given below from the github readme
Turn this
def batch_outer_product(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
# x has shape (batch, x_channels)
# y has shape (batch, y_channels)
# return has shape (batch, x_channels, y_channels)
return x.unsqueeze(-1) * y.unsqueeze(-2)
To this
def batch_outer_product(x: TensorType["batch", "x_channels"],
y: TensorType["batch", "y_channels"]
) -> TensorType["batch", "x_channels", "y_channels"]:
return x.unsqueeze(-1) * y.unsqueeze(-2)