Enable spelling linter for Markdown, reStructuredText and IPython notebooks

Summary: Enable spelling linter for Markdown, reStructuredText and IPython notebooks under `fbcode/vision/fair`. Apply suggested fixes.

Reviewed By: ppwwyyxx

Differential Revision: D20495298

fbshipit-source-id: 95310c7b51f9fa68ba2aa34ecc39a874da36a75c

docs/tutorials/bundle_adjustment.ipynb

@@ -157,8 +157,8 @@
    },
    "outputs": [],
    "source": [
-    "!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/camera_visualisation.py\n",
-    "from camera_visualisation import plot_camera_scene\n",
+    "!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/camera_visualization.py\n",
+    "from camera_visualization import plot_camera_scene\n",
     "\n",
     "!mkdir data\n",
     "!wget -P data https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/data/camera_graph.pth"
@@ -482,7 +482,7 @@
     "log_R_absolute_init = torch.randn(N, 3).float().cuda()\n",
     "T_absolute_init = torch.randn(N, 3).float().cuda()\n",
     "\n",
-    "# futhermore, we know that the first camera is a trivial one \n",
+    "# furthermore, we know that the first camera is a trivial one \n",
     "#    (see the description above)\n",
     "log_R_absolute_init[0, :] = 0.\n",
     "T_absolute_init[0, :] = 0.\n",

docs/tutorials/camera_position_optimization_with_differentiable_rendering.ipynb

@@ -424,7 +424,7 @@
     "id": "dvTLnrWorQd2"
    },
    "source": [
-    "### Visualise the starting position and the reference position"
+    "### Visualize the starting position and the reference position"
    ]
   },
   {

docs/tutorials/render_textured_meshes.ipynb

@@ -545,7 +545,7 @@
    "source": [
     "## 6. Batched Rendering\n",
     "\n",
-    "One of the core design choices of the PyTorch3D API is to suport **batched inputs for all components**. \n",
+    "One of the core design choices of the PyTorch3D API is to support **batched inputs for all components**. \n",
     "The renderer and associated components can take batched inputs and **render a batch of output images in one forward pass**. We will now use this feature to render the mesh from many different viewpoints.\n"
    ]
   },

docs/tutorials/utils/__init__.py

 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
 
-from .camera_visualisation import (
+from .camera_visualization import (
     get_camera_wireframe,
     plot_camera_scene,
     plot_cameras,

pytorch3d/renderer/mesh/shader.py

@@ -330,7 +330,7 @@ class HardFlatShader(nn.Module):
 class SoftSilhouetteShader(nn.Module):
     """
     Calculate the silhouette by blending the top K faces for each pixel based
-    on the 2d euclidean distance of the centre of the pixel to the mesh face.
+    on the 2d euclidean distance of the center of the pixel to the mesh face.
 
     Use this shader for generating silhouettes similar to SoftRasterizer [0].
 

tests/test_blending.py

@@ -272,7 +272,7 @@ class TestBlending(unittest.TestCase):
         )
 
     def test_softmax_rgb_blend(self):
-        # Create dummy outputs of rasterization simulating a cube in the centre
+        # Create dummy outputs of rasterization simulating a cube in the center
         # of the image with surrounding padded values.
         N, S, K = 1, 8, 2
         device = torch.device("cuda")
@@ -421,7 +421,7 @@ class TestBlending(unittest.TestCase):
         return fn
 
     def test_blend_params(self):
-        """Test colour parameter of BlendParams().
+        """Test color parameter of BlendParams().
             Assert passed value overrides default value.
             """
         bp_default = BlendParams()