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[pulsar] Removing LOGGER.debug statements for performance gain.

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We identified that these logging statements can deteriorate performance in certain cases. I propose removing them from the regular renderer implementation and letting individuals re-insert debug logging wherever needed on a case-by-case basis.
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Christoph Lassner 2022-07-25 09:08:58 -07:00 committed by GitHub
parent cb49550486
commit e7c1f026ea
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1 changed files with 0 additions and 42 deletions
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pytorch3d/renderer/points/pulsar/renderer.py
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@ -474,12 +474,6 @@ class Renderer(torch.nn.Module):
rot_mat = axis_angle_to_matrix(rot_vec)
if first_R_then_T:
pos_vec = torch.matmul(rot_mat, pos_vec[..., None])[:, :, 0]
LOGGER.debug(
"Camera position: %s, rotation: %s. Focal length: %s.",
str(pos_vec),
str(rot_vec),
str(focal_length),
)
sensor_dir_x = torch.matmul(
rot_mat,
torch.tensor(
@ -500,56 +494,20 @@ class Renderer(torch.nn.Module):
)[:, :, 0]
if right_handed:
sensor_dir_z *= -1
LOGGER.debug(
"Sensor direction vectors: %s, %s, %s.",
str(sensor_dir_x),
str(sensor_dir_y),
str(sensor_dir_z),
)
if orthogonal:
sensor_center = pos_vec
else:
sensor_center = pos_vec + focal_length * sensor_dir_z
LOGGER.debug("Sensor center: %s.", str(sensor_center))
sensor_luc = ( # Sensor left upper corner.
sensor_center
- sensor_dir_x * (sensor_size_x / 2.0)
- sensor_dir_y * (sensor_size_y / 2.0)
)
LOGGER.debug("Sensor luc: %s.", str(sensor_luc))
pixel_size_x = sensor_size_x / float(width)
pixel_size_y = sensor_size_y / float(height)
LOGGER.debug(
"Pixel sizes (x): %s, (y) %s.", str(pixel_size_x), str(pixel_size_y)
)
pixel_vec_x: torch.Tensor = sensor_dir_x * pixel_size_x
pixel_vec_y: torch.Tensor = sensor_dir_y * pixel_size_y
pixel_0_0_center = sensor_luc + 0.5 * pixel_vec_x + 0.5 * pixel_vec_y
LOGGER.debug(
"Pixel 0 centers: %s, vec x: %s, vec y: %s.",
str(pixel_0_0_center),
str(pixel_vec_x),
str(pixel_vec_y),
)
if not orthogonal:
LOGGER.debug(
"Camera horizontal fovs: %s deg.",
str(
2.0
* torch.atan(0.5 * sensor_size_x / focal_length)
/ math.pi
* 180.0
),
)
LOGGER.debug(
"Camera vertical fovs: %s deg.",
str(
2.0
* torch.atan(0.5 * sensor_size_y / focal_length)
/ math.pi
* 180.0
),
)
# Reduce dimension.
focal_length: torch.Tensor = focal_length[:, 0]
if batch_processing: