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import unittest |
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import torch |
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from mmengine import DefaultScope |
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from mmdet3d.registry import MODELS |
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from mmdet3d.testing import (create_detector_inputs, get_detector_cfg, |
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setup_seed) |
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class TestCenterPoint(unittest.TestCase): |
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def test_center_point(self): |
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import mmdet3d.models |
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assert hasattr(mmdet3d.models, 'CenterPoint') |
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setup_seed(0) |
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DefaultScope.get_instance('test_center_point', scope_name='mmdet3d') |
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centerpoint_net_cfg = get_detector_cfg( |
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'centerpoint/centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py' |
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) |
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model = MODELS.build(centerpoint_net_cfg) |
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num_gt_instance = 50 |
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packed_inputs = create_detector_inputs( |
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with_img=True, num_gt_instance=num_gt_instance, points_feat_dim=5) |
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for sample_id in range(len(packed_inputs['data_samples'])): |
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det_sample = packed_inputs['data_samples'][sample_id] |
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num_instances = len(det_sample.gt_instances_3d.bboxes_3d) |
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bbox_3d_class = det_sample.gt_instances_3d.bboxes_3d.__class__ |
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det_sample.gt_instances_3d.bboxes_3d = bbox_3d_class( |
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torch.rand(num_instances, 9), box_dim=9) |
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if torch.cuda.is_available(): |
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model = model.cuda() |
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data = model.data_preprocessor(packed_inputs, True) |
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with torch.no_grad(): |
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torch.cuda.empty_cache() |
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losses = model.forward(**data, mode='loss') |
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assert losses['task0.loss_heatmap'] >= 0 |
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assert losses['task0.loss_bbox'] >= 0 |
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assert losses['task1.loss_heatmap'] >= 0 |
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assert losses['task1.loss_bbox'] >= 0 |
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assert losses['task2.loss_heatmap'] >= 0 |
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assert losses['task2.loss_bbox'] >= 0 |
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assert losses['task3.loss_heatmap'] >= 0 |
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assert losses['task3.loss_bbox'] >= 0 |
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assert losses['task3.loss_bbox'] >= 0 |
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assert losses['task4.loss_bbox'] >= 0 |
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assert losses['task5.loss_heatmap'] >= 0 |
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assert losses['task5.loss_bbox'] >= 0 |
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with torch.no_grad(): |
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results = model.forward(**data, mode='predict') |
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self.assertEqual(len(results), 1) |
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self.assertIn('bboxes_3d', results[0].pred_instances_3d) |
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self.assertIn('scores_3d', results[0].pred_instances_3d) |
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self.assertIn('labels_3d', results[0].pred_instances_3d) |
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