# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from common_testing import TestCaseMixin from pytorch3d.renderer.cameras import look_at_view_transform, PerspectiveCameras from pytorch3d.renderer.mesh.rasterizer import Fragments from pytorch3d.renderer.mesh.shader import ( HardFlatShader, HardGouraudShader, HardPhongShader, SoftPhongShader, ) from pytorch3d.structures.meshes import Meshes class TestShader(TestCaseMixin, unittest.TestCase): def test_to(self): cpu_device = torch.device("cpu") cuda_device = torch.device("cuda:0") R, T = look_at_view_transform() shader_classes = [ HardFlatShader, HardGouraudShader, HardPhongShader, SoftPhongShader, ] for shader_class in shader_classes: for cameras_class in (None, PerspectiveCameras): if cameras_class is None: cameras = None else: cameras = PerspectiveCameras(device=cpu_device, R=R, T=T) cpu_shader = shader_class(device=cpu_device, cameras=cameras) if cameras is None: self.assertIsNone(cpu_shader.cameras) else: self.assertEqual(cpu_device, cpu_shader.cameras.device) self.assertEqual(cpu_device, cpu_shader.materials.device) self.assertEqual(cpu_device, cpu_shader.lights.device) cuda_shader = cpu_shader.to(cuda_device) self.assertIs(cpu_shader, cuda_shader) if cameras is None: self.assertIsNone(cuda_shader.cameras) else: self.assertEqual(cuda_device, cuda_shader.cameras.device) self.assertEqual(cuda_device, cuda_shader.materials.device) self.assertEqual(cuda_device, cuda_shader.lights.device) def test_cameras_check(self): verts = torch.tensor( [[-1, -1, 0], [1, -1, 1], [1, 1, 0], [-1, 1, 1]], dtype=torch.float32 ) faces = torch.tensor([[0, 1, 2], [2, 3, 0]], dtype=torch.int64) meshes = Meshes(verts=[verts], faces=[faces]) pix_to_face = torch.tensor([0, 1], dtype=torch.int64).view(1, 1, 1, 2) barycentric_coords = torch.tensor( [[0.1, 0.2, 0.7], [0.3, 0.5, 0.2]], dtype=torch.float32 ).view(1, 1, 1, 2, -1) fragments = Fragments( pix_to_face=pix_to_face, bary_coords=barycentric_coords, zbuf=torch.ones_like(pix_to_face), dists=torch.ones_like(pix_to_face), ) shader_classes = [ HardFlatShader, HardGouraudShader, HardPhongShader, SoftPhongShader, ] for shader_class in shader_classes: shader = shader_class() with self.assertRaises(ValueError): shader(fragments, meshes)