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rasterization header comment fixes
Summary: Fix some missing or misplaced argument descriptions. Reviewed By: nikhilaravi Differential Revision: D31305132 fbshipit-source-id: af4fcee9766682b2b7f7f16327e839090e377be2
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@ -75,6 +75,11 @@ RasterizeMeshesNaiveCuda(
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// coordinates for each pixel; if this is False then
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// this function instead returns screen-space
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// barycentric coordinates for each pixel.
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// clip_barycentric_coords: Whether, after any perspective correction
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// is applied but before the depth is calculated (e.g. for
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// z clipping), to "correct" a location outside the face (i.e. with
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// a negative barycentric coordinate) to a position on the edge of the
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// face.
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// cull_backfaces: Bool, Whether to only rasterize mesh faces which are
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// visible to the camera. This assumes that vertices of
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// front-facing triangles are ordered in an anti-clockwise
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@ -191,6 +196,11 @@ torch::Tensor RasterizeMeshesBackwardCuda(
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// coordinates for each pixel; if this is False then
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// this function instead returns screen-space
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// barycentric coordinates for each pixel.
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// clip_barycentric_coords: Whether, after any perspective correction
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// is applied but before the depth is calculated (e.g. for
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// z clipping), to "correct" a location outside the face (i.e. with
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// a negative barycentric coordinate) to a position on the edge of the
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// face.
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//
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// Returns:
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// grad_face_verts: float32 Tensor of shape (F, 3, 3) giving downstream
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@ -352,6 +362,11 @@ RasterizeMeshesFineCuda(
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// coordinates for each pixel; if this is False then
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// this function instead returns screen-space
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// barycentric coordinates for each pixel.
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// clip_barycentric_coords: Whether, after any perspective correction
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// is applied but before the depth is calculated (e.g. for
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// z clipping), to "correct" a location outside the face (i.e. with
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// a negative barycentric coordinate) to a position on the edge of the
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// face.
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// cull_backfaces: Bool, Whether to only rasterize mesh faces which are
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// visible to the camera. This assumes that vertices of
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// front-facing triangles are ordered in an anti-clockwise
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@ -441,6 +456,7 @@ RasterizeMeshesFine(
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// blur_radius: float distance in NDC coordinates uses to expand the face
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// bounding boxes for the rasterization. Set to 0.0 if no blur
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// is required.
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// faces_per_pixel: the number of closeset faces to rasterize per pixel.
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// bin_size: Bin size (in pixels) for coarse-to-fine rasterization. Setting
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// bin_size=0 uses naive rasterization instead.
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// max_faces_per_bin: The maximum number of faces allowed to fall into each
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@ -451,6 +467,11 @@ RasterizeMeshesFine(
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// coordinates for each pixel; if this is False then
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// this function instead returns screen-space
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// barycentric coordinates for each pixel.
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// clip_barycentric_coords: Whether, after any perspective correction
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// is applied but before the depth is calculated (e.g. for
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// z clipping), to "correct" a location outside the face (i.e. with
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// a negative barycentric coordinate) to a position on the edge of the
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// face.
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// cull_backfaces: Bool, Whether to only rasterize mesh faces which are
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// visible to the camera. This assumes that vertices of
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// front-facing triangles are ordered in an anti-clockwise
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@ -48,10 +48,10 @@ RasterizePointsNaiveCuda(
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// in the batch where N is the batch size.
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// num_points_per_cloud: LongTensor of shape (N) giving the number of points
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// for each pointcloud in the batch.
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// radius: FloatTensor of shape (P) giving the radius (in NDC units) of
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// each point in points.
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// image_size: Tuple (H, W) giving the size in pixels of the output
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// image to be rasterized.
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// radius: FloatTensor of shape (P) giving the radius (in NDC units) of
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// each point in points.
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// points_per_pixel: (K) The number closest of points to return for each pixel
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//
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// Returns:
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@ -126,11 +126,13 @@ torch::Tensor RasterizePointsCoarseCpu(
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// in the batch where N is the batch size.
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// num_points_per_cloud: LongTensor of shape (N) giving the number of points
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// for each pointcloud in the batch.
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// radius: FloatTensor of shape (P) giving the radius (in NDC units) of
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// each point in points.
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// image_size: Tuple (H, W) giving the size in pixels of the output
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// image to be rasterized.
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// radius: FloatTensor of shape (P) giving the radius (in NDC units) of
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// each point in points.
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// bin_size: Size of each bin within the image (in pixels)
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// max_points_per_bin: The maximum number of points allowed to fall into each
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// bin when using coarse-to-fine rasterization.
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//
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// Returns:
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// points_per_bin: Tensor of shape (N, num_bins, num_bins) giving the number
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@ -303,10 +305,10 @@ torch::Tensor RasterizePointsBackward(
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// in the batch where N is the batch size.
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// num_points_per_cloud: LongTensor of shape (N) giving the number of points
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// for each pointcloud in the batch.
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// radius: FloatTensor of shape (P) giving the radius (in NDC units) of
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// each point in points.
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// image_size: Tuple (H, W) giving the size in pixels of the output
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// image to be rasterized.
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// radius: FloatTensor of shape (P) giving the radius (in NDC units) of
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// each point in points.
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// points_per_pixel: (K) The number of points to return for each pixel
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// bin_size: Bin size (in pixels) for coarse-to-fine rasterization. Setting
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// bin_size=0 uses naive rasterization instead.
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@ -71,7 +71,7 @@ def rasterize_meshes(
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bin_size=0 uses naive rasterization; setting bin_size=None attempts to
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set it heuristically based on the shape of the input. This should not
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affect the output, but can affect the speed of the forward pass.
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faces_per_bin: Only applicable when using coarse-to-fine rasterization
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max_faces_per_bin: Only applicable when using coarse-to-fine rasterization
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(bin_size > 0); this is the maximum number of faces allowed within each
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bin. This should not affect the output values, but can affect
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the memory usage in the forward pass.
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@ -62,7 +62,7 @@ def rasterize_points(
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bin_size=0 uses naive rasterization; setting bin_size=None attempts to
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set it heuristically based on the shape of the input. This should not
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affect the output, but can affect the speed of the forward pass.
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points_per_bin: Only applicable when using coarse-to-fine rasterization
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max_points_per_bin: Only applicable when using coarse-to-fine rasterization
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(bin_size > 0); this is the maximum number of points allowed within each
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bin. This should not affect the output values, but can affect
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the memory usage in the forward pass.
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