Spaces:
Running
Running
| # 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 pytorch3d.renderer.materials import Materials | |
| from .common_testing import TestCaseMixin | |
| class TestMaterials(TestCaseMixin, unittest.TestCase): | |
| def test_init(self): | |
| """ | |
| Initialize Materials class with the default values. | |
| """ | |
| device = torch.device("cuda:0") | |
| mat = Materials(device=device) | |
| self.assertTrue(torch.is_tensor(mat.ambient_color)) | |
| self.assertTrue(torch.is_tensor(mat.diffuse_color)) | |
| self.assertTrue(torch.is_tensor(mat.specular_color)) | |
| self.assertTrue(torch.is_tensor(mat.shininess)) | |
| self.assertTrue(mat.ambient_color.device == device) | |
| self.assertTrue(mat.diffuse_color.device == device) | |
| self.assertTrue(mat.specular_color.device == device) | |
| self.assertTrue(mat.shininess.device == device) | |
| self.assertTrue(mat.ambient_color.shape == (1, 3)) | |
| self.assertTrue(mat.diffuse_color.shape == (1, 3)) | |
| self.assertTrue(mat.specular_color.shape == (1, 3)) | |
| self.assertTrue(mat.shininess.shape == (1,)) | |
| def test_materials_clone_to(self): | |
| device = torch.device("cuda:0") | |
| cpu = torch.device("cpu") | |
| mat = Materials() | |
| new_mat = mat.clone().to(device) | |
| self.assertTrue(mat.ambient_color.device == cpu) | |
| self.assertTrue(mat.diffuse_color.device == cpu) | |
| self.assertTrue(mat.specular_color.device == cpu) | |
| self.assertTrue(mat.shininess.device == cpu) | |
| self.assertTrue(new_mat.ambient_color.device == device) | |
| self.assertTrue(new_mat.diffuse_color.device == device) | |
| self.assertTrue(new_mat.specular_color.device == device) | |
| self.assertTrue(new_mat.shininess.device == device) | |
| self.assertSeparate(new_mat.ambient_color, mat.ambient_color) | |
| self.assertSeparate(new_mat.diffuse_color, mat.diffuse_color) | |
| self.assertSeparate(new_mat.specular_color, mat.specular_color) | |
| self.assertSeparate(new_mat.shininess, mat.shininess) | |
| def test_initialize_materials_broadcast(self): | |
| materials = Materials( | |
| ambient_color=torch.randn(10, 3), | |
| diffuse_color=torch.randn(1, 3), | |
| specular_color=torch.randn(1, 3), | |
| shininess=torch.randn(1), | |
| ) | |
| self.assertTrue(materials.ambient_color.shape == (10, 3)) | |
| self.assertTrue(materials.diffuse_color.shape == (10, 3)) | |
| self.assertTrue(materials.specular_color.shape == (10, 3)) | |
| self.assertTrue(materials.shininess.shape == (10,)) | |
| def test_initialize_materials_broadcast_fail(self): | |
| """ | |
| Batch dims have to be the same or 1. | |
| """ | |
| with self.assertRaises(ValueError): | |
| Materials( | |
| ambient_color=torch.randn(10, 3), diffuse_color=torch.randn(15, 3) | |
| ) | |
| def test_initialize_materials_dimensions_fail(self): | |
| """ | |
| Color should have shape (N, 3) or (1, 3), Shininess should have shape | |
| (1), (1, 1), (N) or (N, 1) | |
| """ | |
| with self.assertRaises(ValueError): | |
| Materials(ambient_color=torch.randn(10, 4)) | |
| with self.assertRaises(ValueError): | |
| Materials(shininess=torch.randn(10, 2)) | |
| def test_initialize_materials_mixed_inputs(self): | |
| mat = Materials(ambient_color=torch.randn(1, 3), diffuse_color=((1, 1, 1),)) | |
| self.assertTrue(mat.ambient_color.shape == (1, 3)) | |
| self.assertTrue(mat.diffuse_color.shape == (1, 3)) | |
| def test_initialize_materials_mixed_inputs_broadcast(self): | |
| mat = Materials(ambient_color=torch.randn(10, 3), diffuse_color=((1, 1, 1),)) | |
| self.assertTrue(mat.ambient_color.shape == (10, 3)) | |
| self.assertTrue(mat.diffuse_color.shape == (10, 3)) | |
| self.assertTrue(mat.specular_color.shape == (10, 3)) | |
| self.assertTrue(mat.shininess.shape == (10,)) | |