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@@ -28,7 +28,7 @@ try:
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except ImportError:
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TENSORBOARD_FOUND = False
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-def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoint_iterations, checkpoint):
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+def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoint_iterations, checkpoint, debug_from):
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first_iter = 0
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tb_writer = prepare_output_and_logger(dataset)
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gaussians = GaussianModel(dataset.sh_degree)
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@@ -78,6 +78,8 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
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viewpoint_cam = viewpoint_stack.pop(randint(0, len(viewpoint_stack)-1))
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# Render
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+ if (iteration - 1) == debug_from:
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+ pipe.debug = True
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render_pkg = render(viewpoint_cam, gaussians, pipe, background)
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image, viewspace_point_tensor, visibility_filter, radii = render_pkg["render"], render_pkg["viewspace_points"], render_pkg["visibility_filter"], render_pkg["radii"]
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@@ -193,6 +195,7 @@ if __name__ == "__main__":
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pp = PipelineParams(parser)
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parser.add_argument('--ip', type=str, default="127.0.0.1")
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parser.add_argument('--port', type=int, default=6009)
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+ parser.add_argument('--debug_from', type=int, default=-1)
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parser.add_argument('--detect_anomaly', action='store_true', default=False)
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parser.add_argument("--test_iterations", nargs="+", type=int, default=[7_000, 30_000])
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parser.add_argument("--save_iterations", nargs="+", type=int, default=[7_000, 30_000])
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@@ -210,7 +213,7 @@ if __name__ == "__main__":
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# Start GUI server, configure and run training
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network_gui.init(args.ip, args.port)
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torch.autograd.set_detect_anomaly(args.detect_anomaly)
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- training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint)
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+ training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint, args.debug_from)
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# All done
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print("\nTraining complete.")
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bkerbl