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	Simplify _xy_grid computation in raysampling
Summary: Remove the need of tuple and reversed in the raysampling xy_grid computation Reviewed By: bottler Differential Revision: D45269342 fbshipit-source-id: d0e4c0923b9a2cca674b35e8d64862043a0eab3b
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				@ -109,17 +109,11 @@ class MultinomialRaysampler(torch.nn.Module):
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        self._stratified_sampling = stratified_sampling
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        # get the initial grid of image xy coords
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        _xy_grid = torch.stack(
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            tuple(
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                reversed(
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                    meshgrid_ij(
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                        torch.linspace(min_y, max_y, image_height, dtype=torch.float32),
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                        torch.linspace(min_x, max_x, image_width, dtype=torch.float32),
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                    )
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                )
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            ),
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            dim=-1,
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        y, x = meshgrid_ij(
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            torch.linspace(min_y, max_y, image_height, dtype=torch.float32),
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            torch.linspace(min_x, max_x, image_width, dtype=torch.float32),
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        )
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        _xy_grid = torch.stack([x, y], dim=-1)
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        self.register_buffer("_xy_grid", _xy_grid, persistent=False)
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