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stratified_sampling argument: set default to None (#1324)
Summary: The self._stratified_sampling attribute is always overridden unless stratified_sampling is explicitly set to None. However, the desired default behavior is that the value of self._stratified_sampling is used unless the argument stratified_sampling is set to True/False. Changing the default to None achieves this Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/1324 Reviewed By: bottler Differential Revision: D39259775 Pulled By: davnov134 fbshipit-source-id: e01bb747ac80c812eb27bf22e67f5e14f29acadd
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@ -124,7 +124,7 @@ class MultinomialRaysampler(torch.nn.Module):
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max_depth: Optional[float] = None,
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n_rays_per_image: Optional[int] = None,
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n_pts_per_ray: Optional[int] = None,
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stratified_sampling: bool = False,
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stratified_sampling: Optional[bool] = None,
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**kwargs,
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) -> RayBundle:
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"""
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@ -313,7 +313,11 @@ class MonteCarloRaysampler(torch.nn.Module):
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self._stratified_sampling = stratified_sampling
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def forward(
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self, cameras: CamerasBase, *, stratified_sampling: bool = False, **kwargs
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self,
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cameras: CamerasBase,
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*,
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stratified_sampling: Optional[bool] = None,
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**kwargs,
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) -> RayBundle:
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"""
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Args:
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