Example and test updates.

Summary: This commit performs pulsar example and test refinements. The examples are fully adjusted to adhere to PEP style guide and additional comments are added.

Reviewed By: nikhilaravi

Differential Revision: D24723391

fbshipit-source-id: 6d289006f080140159731e7f3a8c98b582164f1a

docs/examples/pulsar_basic.py

@@ -7,49 +7,65 @@ Output: basic.png.
 """
 import math
 from os import path
+import logging
 
 import imageio
 import torch
 from pytorch3d.renderer.points.pulsar import Renderer
 
 
-torch.manual_seed(1)
+LOGGER = logging.getLogger(__name__)
 
-n_points = 10
-width = 1_000
-height = 1_000
-device = torch.device("cuda")
-# The PyTorch3D system is right handed; in pulsar you can choose the handedness.
-# For easy reproducibility we use a right handed coordinate system here.
-renderer = Renderer(width, height, n_points, right_handed_system=True).to(device)
-# Generate sample data.
-vert_pos = torch.rand(n_points, 3, dtype=torch.float32, device=device) * 10.0
-vert_pos[:, 2] += 25.0
-vert_pos[:, :2] -= 5.0
-vert_col = torch.rand(n_points, 3, dtype=torch.float32, device=device)
-vert_rad = torch.rand(n_points, dtype=torch.float32, device=device)
-cam_params = torch.tensor(
-    [
-        0.0,
-        0.0,
-        0.0,  # Position 0, 0, 0 (x, y, z).
-        0.0,
-        math.pi,  # Because of the right handed system, the camera must look 'back'.
-        0.0,  # Rotation 0, 0, 0 (in axis-angle format).
-        5.0,  # Focal length in world size.
-        2.0,  # Sensor size in world size.
-    ],
-    dtype=torch.float32,
-    device=device,
-)
-# Render.
-image = renderer(
-    vert_pos,
-    vert_col,
-    vert_rad,
-    cam_params,
-    1.0e-1,  # Renderer blending parameter gamma, in [1., 1e-5].
-    45.0,  # Maximum depth.
-)
-print("Writing image to `%s`." % (path.abspath("basic.png")))
-imageio.imsave("basic.png", (image.cpu().detach() * 255.0).to(torch.uint8).numpy())
+
+def cli():
+    """
+    Basic example for the pulsar sphere renderer.
+
+    Writes to `basic.png`.
+    """
+    LOGGER.info("Rendering on GPU...")
+    torch.manual_seed(1)
+    n_points = 10
+    width = 1_000
+    height = 1_000
+    device = torch.device("cuda")
+    # The PyTorch3D system is right handed; in pulsar you can choose the handedness.
+    # For easy reproducibility we use a right handed coordinate system here.
+    renderer = Renderer(width, height, n_points, right_handed_system=True).to(device)
+    # Generate sample data.
+    vert_pos = torch.rand(n_points, 3, dtype=torch.float32, device=device) * 10.0
+    vert_pos[:, 2] += 25.0
+    vert_pos[:, :2] -= 5.0
+    vert_col = torch.rand(n_points, 3, dtype=torch.float32, device=device)
+    vert_rad = torch.rand(n_points, dtype=torch.float32, device=device)
+    cam_params = torch.tensor(
+        [
+            0.0,
+            0.0,
+            0.0,  # Position 0, 0, 0 (x, y, z).
+            0.0,
+            math.pi,  # Because of the right handed system, the camera must look 'back'.
+            0.0,  # Rotation 0, 0, 0 (in axis-angle format).
+            5.0,  # Focal length in world size.
+            2.0,  # Sensor size in world size.
+        ],
+        dtype=torch.float32,
+        device=device,
+    )
+    # Render.
+    image = renderer(
+        vert_pos,
+        vert_col,
+        vert_rad,
+        cam_params,
+        1.0e-1,  # Renderer blending parameter gamma, in [1., 1e-5].
+        45.0,  # Maximum depth.
+    )
+    LOGGER.info("Writing image to `%s`.", path.abspath("basic.png"))
+    imageio.imsave("basic.png", (image.cpu().detach() * 255.0).to(torch.uint8).numpy())
+    LOGGER.info("Done.")
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    cli()