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| 1 | +# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. |
| 2 | + |
| 3 | +import unittest |
| 4 | + |
| 5 | +import torch |
| 6 | +import torch.nn as nn |
| 7 | +from common_testing import TestCaseMixin, get_random_cuda_device |
| 8 | +from pytorch3d.renderer import ( |
| 9 | + BlendParams, |
| 10 | + HardGouraudShader, |
| 11 | + Materials, |
| 12 | + MeshRasterizer, |
| 13 | + MeshRenderer, |
| 14 | + PointLights, |
| 15 | + RasterizationSettings, |
| 16 | + SoftPhongShader, |
| 17 | + TexturesVertex, |
| 18 | +) |
| 19 | +from pytorch3d.renderer.cameras import FoVPerspectiveCameras, look_at_view_transform |
| 20 | +from pytorch3d.structures.meshes import Meshes |
| 21 | +from pytorch3d.utils.ico_sphere import ico_sphere |
| 22 | + |
| 23 | + |
| 24 | +# Set the number of GPUS you want to test with |
| 25 | +NUM_GPUS = 3 |
| 26 | +GPU_LIST = list({get_random_cuda_device() for _ in range(NUM_GPUS)}) |
| 27 | +print("GPUs: %s" % ", ".join(GPU_LIST)) |
| 28 | + |
| 29 | + |
| 30 | +class TestRenderMultiGPU(TestCaseMixin, unittest.TestCase): |
| 31 | + def _check_mesh_renderer_props_on_device(self, renderer, device): |
| 32 | + """ |
| 33 | + Helper function to check that all the properties of the mesh |
| 34 | + renderer have been moved to the correct device. |
| 35 | + """ |
| 36 | + # Cameras |
| 37 | + self.assertEqual(renderer.rasterizer.cameras.device, device) |
| 38 | + self.assertEqual(renderer.rasterizer.cameras.R.device, device) |
| 39 | + self.assertEqual(renderer.rasterizer.cameras.T.device, device) |
| 40 | + self.assertEqual(renderer.shader.cameras.device, device) |
| 41 | + self.assertEqual(renderer.shader.cameras.R.device, device) |
| 42 | + self.assertEqual(renderer.shader.cameras.T.device, device) |
| 43 | + |
| 44 | + # Lights and Materials |
| 45 | + self.assertEqual(renderer.shader.lights.device, device) |
| 46 | + self.assertEqual(renderer.shader.lights.ambient_color.device, device) |
| 47 | + self.assertEqual(renderer.shader.materials.device, device) |
| 48 | + self.assertEqual(renderer.shader.materials.ambient_color.device, device) |
| 49 | + |
| 50 | + def test_mesh_renderer_to(self): |
| 51 | + """ |
| 52 | + Test moving all the tensors in the mesh renderer to a new device. |
| 53 | + """ |
| 54 | + |
| 55 | + device1 = torch.device("cpu") |
| 56 | + |
| 57 | + R, T = look_at_view_transform(1500, 0.0, 0.0) |
| 58 | + |
| 59 | + # Init shader settings |
| 60 | + materials = Materials(device=device1) |
| 61 | + lights = PointLights(device=device1) |
| 62 | + lights.location = torch.tensor([0.0, 0.0, +1000.0], device=device1)[None] |
| 63 | + |
| 64 | + raster_settings = RasterizationSettings( |
| 65 | + image_size=256, blur_radius=0.0, faces_per_pixel=1 |
| 66 | + ) |
| 67 | + cameras = FoVPerspectiveCameras( |
| 68 | + device=device1, R=R, T=T, aspect_ratio=1.0, fov=60.0, zfar=100 |
| 69 | + ) |
| 70 | + rasterizer = MeshRasterizer(cameras=cameras, raster_settings=raster_settings) |
| 71 | + |
| 72 | + blend_params = BlendParams( |
| 73 | + 1e-4, |
| 74 | + 1e-4, |
| 75 | + background_color=torch.zeros(3, dtype=torch.float32, device=device1), |
| 76 | + ) |
| 77 | + |
| 78 | + shader = SoftPhongShader( |
| 79 | + lights=lights, |
| 80 | + cameras=cameras, |
| 81 | + materials=materials, |
| 82 | + blend_params=blend_params, |
| 83 | + ) |
| 84 | + renderer = MeshRenderer(rasterizer=rasterizer, shader=shader) |
| 85 | + |
| 86 | + mesh = ico_sphere(2, device1) |
| 87 | + verts_padded = mesh.verts_padded() |
| 88 | + textures = TexturesVertex( |
| 89 | + verts_features=torch.ones_like(verts_padded, device=device1) |
| 90 | + ) |
| 91 | + mesh.textures = textures |
| 92 | + self._check_mesh_renderer_props_on_device(renderer, device1) |
| 93 | + |
| 94 | + # Test rendering on cpu |
| 95 | + output_images = renderer(mesh) |
| 96 | + self.assertEqual(output_images.device, device1) |
| 97 | + |
| 98 | + # Move renderer and mesh to another device and re render |
| 99 | + # This also tests that background_color is correctly moved to |
| 100 | + # the new device |
| 101 | + device2 = torch.device("cuda:0") |
| 102 | + renderer.to(device2) |
| 103 | + mesh = mesh.to(device2) |
| 104 | + self._check_mesh_renderer_props_on_device(renderer, device2) |
| 105 | + output_images = renderer(mesh) |
| 106 | + self.assertEqual(output_images.device, device2) |
| 107 | + |
| 108 | + def test_render_meshes(self): |
| 109 | + test = self |
| 110 | + |
| 111 | + class Model(nn.Module): |
| 112 | + def __init__(self): |
| 113 | + super(Model, self).__init__() |
| 114 | + mesh = ico_sphere(3) |
| 115 | + self.register_buffer("faces", mesh.faces_padded()) |
| 116 | + self.renderer = self.init_render() |
| 117 | + |
| 118 | + def init_render(self): |
| 119 | + |
| 120 | + cameras = FoVPerspectiveCameras() |
| 121 | + raster_settings = RasterizationSettings( |
| 122 | + image_size=128, blur_radius=0.0, faces_per_pixel=1 |
| 123 | + ) |
| 124 | + lights = PointLights( |
| 125 | + ambient_color=((1.0, 1.0, 1.0),), |
| 126 | + diffuse_color=((0, 0.0, 0),), |
| 127 | + specular_color=((0.0, 0, 0),), |
| 128 | + location=((0.0, 0.0, 1e5),), |
| 129 | + ) |
| 130 | + renderer = MeshRenderer( |
| 131 | + rasterizer=MeshRasterizer( |
| 132 | + cameras=cameras, raster_settings=raster_settings |
| 133 | + ), |
| 134 | + shader=HardGouraudShader(cameras=cameras, lights=lights), |
| 135 | + ) |
| 136 | + return renderer |
| 137 | + |
| 138 | + def forward(self, verts, texs): |
| 139 | + batch_size = verts.size(0) |
| 140 | + self.renderer.to(verts.device) |
| 141 | + tex = TexturesVertex(verts_features=texs) |
| 142 | + faces = self.faces.expand(batch_size, -1, -1).to(verts.device) |
| 143 | + mesh = Meshes(verts, faces, tex).to(verts.device) |
| 144 | + |
| 145 | + test._check_mesh_renderer_props_on_device(self.renderer, verts.device) |
| 146 | + img_render = self.renderer(mesh) |
| 147 | + return img_render[:, :, :, :3] |
| 148 | + |
| 149 | + # DataParallel requires every input tensor be provided |
| 150 | + # on the first device in its device_ids list. |
| 151 | + verts = ico_sphere(3).verts_padded() |
| 152 | + texs = verts.new_ones(verts.shape) |
| 153 | + model = Model() |
| 154 | + model = nn.DataParallel(model, device_ids=GPU_LIST) |
| 155 | + model.to(f"cuda:{model.device_ids[0]}") |
| 156 | + |
| 157 | + # Test a few iterations |
| 158 | + for _ in range(100): |
| 159 | + model(verts, texs) |
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