Address black + isort fbsource linter warnings

Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8

pytorch3d/renderer/points/__init__.py

@@ -5,4 +5,5 @@ from .rasterize_points import rasterize_points
 from .rasterizer import PointsRasterizationSettings, PointsRasterizer
 from .renderer import PointsRenderer
 
+
 __all__ = [k for k in globals().keys() if not k.startswith("_")]

pytorch3d/renderer/points/compositor.py

@@ -5,6 +5,7 @@ import torch.nn as nn
 
 from ..compositing import CompositeParams, alpha_composite, norm_weighted_sum
 
+
 # A compositor should take as input 3D points and some corresponding information.
 # Given this information, the compositor can:
 #     - blend colors across the top K vertices at a pixel
@@ -19,15 +20,11 @@ class AlphaCompositor(nn.Module):
         super().__init__()
 
         self.composite_params = (
-            composite_params
-            if composite_params is not None
-            else CompositeParams()
+            composite_params if composite_params is not None else CompositeParams()
         )
 
     def forward(self, fragments, alphas, ptclds, **kwargs) -> torch.Tensor:
-        images = alpha_composite(
-            fragments, alphas, ptclds, self.composite_params
-        )
+        images = alpha_composite(fragments, alphas, ptclds, self.composite_params)
         return images
 
 
@@ -39,13 +36,9 @@ class NormWeightedCompositor(nn.Module):
     def __init__(self, composite_params=None):
         super().__init__()
         self.composite_params = (
-            composite_params
-            if composite_params is not None
-            else CompositeParams()
+            composite_params if composite_params is not None else CompositeParams()
         )
 
     def forward(self, fragments, alphas, ptclds, **kwargs) -> torch.Tensor:
-        images = norm_weighted_sum(
-            fragments, alphas, ptclds, self.composite_params
-        )
+        images = norm_weighted_sum(fragments, alphas, ptclds, self.composite_params)
         return images

pytorch3d/renderer/points/rasterize_points.py

@@ -1,8 +1,8 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
 
 from typing import Optional
-import torch
 
+import torch
 from pytorch3d import _C
 from pytorch3d.renderer.mesh.rasterize_meshes import pix_to_ndc
 
@@ -155,10 +155,7 @@ class _RasterizePoints(torch.autograd.Function):
 
 
 def rasterize_points_python(
-    pointclouds,
-    image_size: int = 256,
-    radius: float = 0.01,
-    points_per_pixel: int = 8,
+    pointclouds, image_size: int = 256, radius: float = 0.01, points_per_pixel: int = 8
 ):
     """
     Naive pure PyTorch implementation of pointcloud rasterization.
@@ -177,9 +174,7 @@ def rasterize_points_python(
     point_idxs = torch.full(
         (N, S, S, K), fill_value=-1, dtype=torch.int32, device=device
     )
-    zbuf = torch.full(
-        (N, S, S, K), fill_value=-1, dtype=torch.float32, device=device
-    )
+    zbuf = torch.full((N, S, S, K), fill_value=-1, dtype=torch.float32, device=device)
     pix_dists = torch.full(
         (N, S, S, K), fill_value=-1, dtype=torch.float32, device=device
     )

pytorch3d/renderer/points/rasterizer.py

@@ -3,6 +3,7 @@
 
 
 from typing import NamedTuple, Optional
+
 import torch
 import torch.nn as nn
 

pytorch3d/renderer/points/renderer.py

@@ -5,6 +5,7 @@
 import torch
 import torch.nn as nn
 
+
 # A renderer class should be initialized with a
 # function for rasterization and a function for compositing.
 # The rasterizer should: