423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2025-08-02 20:02:49 +08:00
Code Issues Packages Projects Releases Wiki Activity

Avoid plain division involving integers

Browse Source 
Summary: To avoid pytorch warnings and future behaviour changes, stop using torch.div and / with tensors of integers.

Reviewed By: gkioxari, mruberry

Differential Revision: D21857955

fbshipit-source-id: fb9f3000f3d953352cdc721d2a5f73d3a4bbf4b7
This commit is contained in:
Jeremy Reizenstein 2020-06-03 11:29:57 -07:00 committed by Facebook GitHub Bot
parent 40b068e4bc
commit 5444c53cee
3 changed files with 6 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
pytorch3d/ops/cubify.py
View File

@ -18,9 +18,9 @@ def unravel_index(idx, dims) -> torch.Tensor:
if len(dims) != 4: if len(dims) != 4:
raise ValueError("Expects a 4-element list.") raise ValueError("Expects a 4-element list.")
N, H, W, D = dims N, H, W, D = dims
n = torch.div(idx, H * W * D) n = idx // (H * W * D)
h = torch.div(idx - n * H * W * D, W * D) h = (idx - n * H * W * D) // (W * D)
w = torch.div(idx - n * H * W * D - h * W * D, D) w = (idx - n * H * W * D - h * W * D) // D
d = idx - n * H * W * D - h * W * D - w * D d = idx - n * H * W * D - h * W * D - w * D
return torch.stack((n, h, w, d), dim=1) return torch.stack((n, h, w, d), dim=1)

2
pytorch3d/structures/meshes.py
View File

@ -1031,7 +1031,7 @@ class Meshes(object):
unique_mask[1:] = sorted_hash[1:] != sorted_hash[:-1] unique_mask[1:] = sorted_hash[1:] != sorted_hash[:-1]
unique_idx = sort_idx[unique_mask] unique_idx = sort_idx[unique_mask]
self._edges_packed = torch.stack([u / V, u % V], dim=1) self._edges_packed = torch.stack([u // V, u % V], dim=1)
self._edges_packed_to_mesh_idx = edge_to_mesh[unique_idx] self._edges_packed_to_mesh_idx = edge_to_mesh[unique_idx]
face_to_edge = torch.arange(3 * F).view(3, F).t() face_to_edge = torch.arange(3 * F).view(3, F).t()

7
tests/test_rasterizer.py
View File

@ -24,11 +24,8 @@ DEBUG = False # Set DEBUG to true to save outputs from the tests.
def convert_image_to_binary_mask(filename): def convert_image_to_binary_mask(filename):
with Image.open(filename) as raw_image: with Image.open(filename) as raw_image:
image = torch.from_numpy(np.array(raw_image)) image = torch.from_numpy(np.array(raw_image))
min = image.min() mx = image.max()
max = image.max() image_norm = (image == mx).to(torch.int64)
image_norm = (image - min) / (max - min)
image_norm[image_norm > 0] == 1.0
image_norm = image_norm.to(torch.int64)
return image_norm return image_norm