apply black 20.8b1 formatting update

Summary:
allow-large-files

black_any_style

Reviewed By: zertosh

Differential Revision: D24325133

fbshipit-source-id: b4afe80d1e8b2bc993f4b8e3822c02964df47462

pytorch3d/ops/perspective_n_points.py

@@ -53,7 +53,7 @@ def _compute_alphas(x, c_world):
 
 
 def _build_M(y, alphas, weight):
-    """ Returns the matrix defining the reprojection equations.
+    """Returns the matrix defining the reprojection equations.
     Args:
         y: projected points in camera coordinates of size B x N x 2
         alphas: barycentric coordinates of size B x N x 4
@@ -90,7 +90,7 @@ def _build_M(y, alphas, weight):
 
 
 def _null_space(m, kernel_dim):
-    """ Finds the null space (kernel) basis of the matrix
+    """Finds the null space (kernel) basis of the matrix
     Args:
         m: the batch of input matrices, B x N x 12
         kernel_dim: number of dimensions to approximate the kernel
@@ -106,7 +106,7 @@ def _null_space(m, kernel_dim):
 
 
 def _reproj_error(y_hat, y, weight, eps=1e-9):
-    """ Projects estimated 3D points and computes the reprojection error
+    """Projects estimated 3D points and computes the reprojection error
     Args:
         y_hat: a batch of predicted 2D points in homogeneous coordinates
         y: a batch of ground-truth 2D points
@@ -121,7 +121,7 @@ def _reproj_error(y_hat, y, weight, eps=1e-9):
 
 
 def _algebraic_error(x_w_rotated, x_cam, weight):
-    """ Computes the residual of Umeyama in 3D.
+    """Computes the residual of Umeyama in 3D.
     Args:
         x_w_rotated: The given 3D points rotated with the predicted camera.
         x_cam: the lifted 2D points y
@@ -135,7 +135,7 @@ def _algebraic_error(x_w_rotated, x_cam, weight):
 
 
 def _compute_norm_sign_scaling_factor(c_cam, alphas, x_world, y, weight, eps=1e-9):
-    """ Given a solution, adjusts the scale and flip
+    """Given a solution, adjusts the scale and flip
     Args:
         c_cam: control points in camera coordinates
         alphas: barycentric coordinates of the points
@@ -167,7 +167,7 @@ def _compute_norm_sign_scaling_factor(c_cam, alphas, x_world, y, weight, eps=1e-
 
 
 def _gen_pairs(input, dim=-2, reducer=lambda a, b: ((a - b) ** 2).sum(dim=-1)):
-    """ Generates all pairs of different rows and then applies the reducer
+    """Generates all pairs of different rows and then applies the reducer
     Args:
         input: a tensor
         dim: a dimension to generate pairs across
@@ -184,7 +184,7 @@ def _gen_pairs(input, dim=-2, reducer=lambda a, b: ((a - b) ** 2).sum(dim=-1)):
 
 
 def _kernel_vec_distances(v):
-    """ Computes the coefficients for linearisation of the quadratic system
+    """Computes the coefficients for linearisation of the quadratic system
         to match all pairwise distances between 4 control points (dim=1).
         The last dimension corresponds to the coefficients for quadratic terms
         Bij = Bi * Bj, where Bi and Bj correspond to kernel vectors.
@@ -208,7 +208,7 @@ def _kernel_vec_distances(v):
 
 
 def _solve_lstsq_subcols(rhs, lhs, lhs_col_idx):
-    """ Solves an over-determined linear system for selected LHS columns.
+    """Solves an over-determined linear system for selected LHS columns.
         A batched version of `torch.lstsq`.
     Args:
         rhs: right-hand side vectors
@@ -226,7 +226,7 @@ def _binary_sign(t):
 
 
 def _find_null_space_coords_1(kernel_dsts, cw_dst, eps=1e-9):
-    """ Solves case 1 from the paper [1]; solve for 4 coefficients:
+    """Solves case 1 from the paper [1]; solve for 4 coefficients:
        [B11 B22 B33 B44 B12 B13 B14 B23 B24 B34]
          ^               ^   ^   ^
     Args:
@@ -246,7 +246,7 @@ def _find_null_space_coords_1(kernel_dsts, cw_dst, eps=1e-9):
 
 
 def _find_null_space_coords_2(kernel_dsts, cw_dst):
-    """ Solves case 2 from the paper; solve for 3 coefficients:
+    """Solves case 2 from the paper; solve for 3 coefficients:
         [B11 B22 B33 B44 B12 B13 B14 B23 B24 B34]
           ^   ^           ^
     Args:
@@ -270,7 +270,7 @@ def _find_null_space_coords_2(kernel_dsts, cw_dst):
 
 
 def _find_null_space_coords_3(kernel_dsts, cw_dst, eps=1e-9):
-    """ Solves case 3 from the paper; solve for 5 coefficients:
+    """Solves case 3 from the paper; solve for 5 coefficients:
         [B11 B22 B33 B44 B12 B13 B14 B23 B24 B34]
           ^   ^           ^   ^       ^
     Args:

pytorch3d/ops/utils.py

@@ -94,7 +94,7 @@ def convert_pointclouds_to_tensor(pcl: Union[torch.Tensor, "Pointclouds"]):
 
 
 def is_pointclouds(pcl: Union[torch.Tensor, "Pointclouds"]):
-    """ Checks whether the input `pcl` is an instance of `Pointclouds`
+    """Checks whether the input `pcl` is an instance of `Pointclouds`
     by checking the existence of `points_padded` and `num_points_per_cloud`
     functions.
     """

pytorch3d/renderer/mesh/shader.py

@@ -346,7 +346,7 @@ class SoftSilhouetteShader(nn.Module):
         self.blend_params = blend_params if blend_params is not None else BlendParams()
 
     def forward(self, fragments, meshes, **kwargs) -> torch.Tensor:
-        """"
+        """ "
         Only want to render the silhouette so RGB values can be ones.
         There is no need for lighting or texturing
         """

pytorch3d/renderer/mesh/utils.py

@@ -111,9 +111,9 @@ def _try_place_rectangle(
          |                       |3   |
          |                       |    |
          +-----------------------+----+------X
-y    |1                                  |
-^    |     --->x                         |
-|    +-----------------------------------+
+    y    |1                                  |
+    ^    |     --->x                         |
+    |    +-----------------------------------+
 
          We want to place this rectangle.