From 5b74a2cc2735d432daea67627ea56ac90245da73 Mon Sep 17 00:00:00 2001
From: Krzysztof Chalupka <chalupka@fb.com>
Date: Wed, 1 Jun 2022 08:47:26 -0700
Subject: [PATCH] Remove use of torch.tile to fix CI

Summary: Our tests fail (https://fburl.com/jmoqo9bz) because test_splatter_blend uses torch.tile, which is not supported in earlier torch versions. Replace it with tensor.extend.

Reviewed By: bottler

Differential Revision: D36796098

fbshipit-source-id: 38d5b40667f98f3163b33f44e53e96b858cfeba2
---
 tests/test_splatter_blend.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/tests/test_splatter_blend.py b/tests/test_splatter_blend.py
index caaa5d5f..e90bc152 100644
--- a/tests/test_splatter_blend.py
+++ b/tests/test_splatter_blend.py
@@ -7,7 +7,7 @@
 import unittest
 
 import torch
-from common_testing import TestCaseMixin
+from pytorch3d.common.compat import meshgrid_ij
 from pytorch3d.renderer.cameras import FoVPerspectiveCameras
 from pytorch3d.renderer.splatter_blend import (
     _compute_occlusion_layers,
@@ -20,6 +20,8 @@ from pytorch3d.renderer.splatter_blend import (
     _prepare_pixels_and_colors,
 )
 
+from .common_testing import TestCaseMixin
+
 offsets = torch.tensor(
     [
         [-1, -1],
@@ -248,15 +250,13 @@ class TestComputeSplattingColorsAndWeights(TestCaseMixin, unittest.TestCase):
     def setUp(self):
         self.N, self.H, self.W, self.K = 2, 3, 4, 5
         self.pixel_coords_screen = (
-            torch.tile(
-                torch.stack(
-                    torch.meshgrid(
-                        torch.arange(self.H), torch.arange(self.W), indexing="ij"
-                    ),
-                    dim=-1,
-                ).reshape(1, self.H, self.W, 1, 2),
-                (self.N, 1, 1, self.K, 1),
-            ).float()
+            torch.stack(
+                meshgrid_ij(torch.arange(self.H), torch.arange(self.W)),
+                dim=-1,
+            )
+            .reshape(1, self.H, self.W, 1, 2)
+            .expand(self.N, self.H, self.W, self.K, 2)
+            .float()
             + 0.5
         )
         self.colors = torch.ones((self.N, self.H, self.W, self.K, 4))