Poor results of PointRCNN on 3-class KITTI Dataset

Hi,
I'm trying to reproduce PointRCNN. I downloaded the KITTI Dataset and pertained weights from README.md in configs/point_rcnn (point_rcnn_2x8_kitti-3d-3classes_20211208_151344.pth).  In point_rcnn_2x8_kitti-3d-3classes.py, I also modified the '../base/datasets/kitti-3d-car.py' in base list to '../base/datasets/kitti-3d-3class.py'.
Then, I ran: ./tools/dist_test.sh configs/point_rcnn/point_rcnn_2x8_kitti-3d-3classes.py ./checkpoints/point_rcnn_2x8_kitti-3d-3classes_20211208_151344.pth 3 --out results/kitti/point_rcnn.pkl --eval mAP
But the results were quite poor:

Results on AP40 and AP11 were both bad. I think KITTI Dataset is fine since I had reproduced SECOND before and the results turned out to be satisfying. Does anyone has any ideas?
Thanks!

Hi, I met the same problem while reproducing the PointRCNN in the Colab.
I didn't modify anything and just ran the code below:
! python tools/train.py configs/point_rcnn/point_rcnn_2x8_kitti-3d-3classes.py
Things went wrong from the first epoch:
2022-06-28 15:14:08,951 - mmdet - INFO - Epoch [1][1050/3712]	lr: 1.002e-03, eta: 2 days, 7:46:02, time: 0.669, data_time: 0.005, memory: 4663, bbox_loss: 1.0378, semantic_loss: 0.0967, loss_cls: 0.6035, loss_bbox: 0.4432, loss_corner: 48.2661, loss: 50.4473, grad_norm: 8794.3477
2022-06-28 15:14:29,015 - mmdet - INFO - Epoch [1][1080/3712]	lr: 1.002e-03, eta: 2 days, 7:44:22, time: 0.669, data_time: 0.005, memory: 4663, bbox_loss: 1.0433, semantic_loss: 0.0974, loss_cls: 0.5860, loss_bbox: 0.4866, loss_corner: 0.3205, loss: 2.5337, grad_norm: 24.1995
2022-06-28 15:14:48,951 - mmdet - INFO - Epoch [1][1110/3712]	lr: 1.002e-03, eta: 2 days, 7:42:13, time: 0.665, data_time: 0.006, memory: 4663, bbox_loss: 1.0416, semantic_loss: 0.0996, loss_cls: 0.5907, loss_bbox: 0.4486, loss_corner: 0.1719, loss: 2.3524, grad_norm: 7.4220
2022-06-28 15:15:09,090 - mmdet - INFO - Epoch [1][1140/3712]	lr: 1.002e-03, eta: 2 days, 7:41:02, time: 0.671, data_time: 0.006, memory: 4663, bbox_loss: 1.0228, semantic_loss: 0.0953, loss_cls: 0.6039, loss_bbox: 0.4427, loss_corner: 0.1228, loss: 2.2876, grad_norm: 4.2769
2022-06-28 15:15:29,125 - mmdet - INFO - Epoch [1][1170/3712]	lr: 1.002e-03, eta: 2 days, 7:39:27, time: 0.668, data_time: 0.005, memory: 4663, bbox_loss: 1.0216, semantic_loss: 0.0890, loss_cls: 0.6066, loss_bbox: 0.3920, loss_corner: 0.1147, loss: 2.2239, grad_norm: 4.1757
2022-06-28 15:15:49,093 - mmdet - INFO - Epoch [1][1200/3712]	lr: 1.002e-03, eta: 2 days, 7:37:39, time: 0.666, data_time: 0.006, memory: 4663, bbox_loss: 1.0113, semantic_loss: 0.0917, loss_cls: 0.5958, loss_bbox: 0.3984, loss_corner: 0.1307, loss: 2.2279, grad_norm: 7.4968
2022-06-28 15:16:09,144 - mmdet - INFO - Epoch [1][1230/3712]	lr: 1.002e-03, eta: 2 days, 7:36:16, time: 0.668, data_time: 0.006, memory: 4663, bbox_loss: 0.9994, semantic_loss: 0.0906, loss_cls: 0.5769, loss_bbox: 0.4106, loss_corner: 0.1459, loss: 2.2234, grad_norm: 7.5141
2022-06-28 15:16:29,177 - mmdet - INFO - Epoch [1][1260/3712]	lr: 1.002e-03, eta: 2 days, 7:34:51, time: 0.668, data_time: 0.006, memory: 4663, bbox_loss: 0.9867, semantic_loss: 0.0893, loss_cls: 0.5831, loss_bbox: 0.4195, loss_corner: 0.1365, loss: 2.2151, grad_norm: 4.6261
2022-06-28 15:16:49,112 - mmdet - INFO - Epoch [1][1290/3712]	lr: 1.003e-03, eta: 2 days, 7:33:07, time: 0.664, data_time: 0.005, memory: 4663, bbox_loss: 0.9738, semantic_loss: 0.0985, loss_cls: 0.5870, loss_bbox: 0.3961, loss_corner: 0.1182, loss: 2.1736, grad_norm: 5.0624
2022-06-28 15:17:09,152 - mmdet - INFO - Epoch [1][1320/3712]	lr: 1.003e-03, eta: 2 days, 7:31:51, time: 0.668, data_time: 0.005, memory: 4663, bbox_loss: 0.9502, semantic_loss: 0.0872, loss_cls: 0.5810, loss_bbox: 0.3719, loss_corner: 0.1062, loss: 2.0965, grad_norm: 3.5973
2022-06-28 15:17:29,244 - mmdet - INFO - Epoch [1][1350/3712]	lr: 1.003e-03, eta: 2 days, 7:30:48, time: 0.670, data_time: 0.006, memory: 4663, bbox_loss: 1.0032, semantic_loss: 0.0911, loss_cls: 0.5945, loss_bbox: 0.4862, loss_corner: 0.3848, loss: 2.5597, grad_norm: 37.2284
2022-06-28 15:17:49,210 - mmdet - INFO - Epoch [1][1380/3712]	lr: 1.003e-03, eta: 2 days, 7:29:20, time: 0.666, data_time: 0.005, memory: 4663, bbox_loss: 0.9699, semantic_loss: 0.0915, loss_cls: 0.5889, loss_bbox: 0.5508, loss_corner: 0.2513, loss: 2.4524, grad_norm: 5.0381
2022-06-28 15:18:09,228 - mmdet - INFO - Epoch [1][1410/3712]	lr: 1.003e-03, eta: 2 days, 7:28:06, time: 0.667, data_time: 0.005, memory: 4663, bbox_loss: 0.9153, semantic_loss: 0.0883, loss_cls: 0.5952, loss_bbox: 0.4015, loss_corner: 1.9026, loss: 3.9028, grad_norm: 303.6886
2022-06-28 15:18:29,284 - mmdet - INFO - Epoch [1][1440/3712]	lr: 1.003e-03, eta: 2 days, 7:27:02, time: 0.669, data_time: 0.005, memory: 4663, bbox_loss: 0.9129, semantic_loss: 0.0866, loss_cls: 0.5911, loss_bbox: 0.4803, loss_corner: 0.3135, loss: 2.3845, grad_norm: 4.1048
2022-06-28 15:18:49,610 - mmdet - INFO - Epoch [1][1470/3712]	lr: 1.003e-03, eta: 2 days, 7:26:54, time: 0.678, data_time: 0.005, memory: 4663, bbox_loss: 0.9838, semantic_loss: 0.1008, loss_cls: 0.5897, loss_bbox: 0.5671, loss_corner: 1.8919, loss: 4.1333, grad_norm: 274.4772
2022-06-28 15:19:09,654 - mmdet - INFO - Epoch [1][1500/3712]	lr: 1.004e-03, eta: 2 days, 7:25:49, time: 0.668, data_time: 0.005, memory: 4663, bbox_loss: 0.9194, semantic_loss: 0.0920, loss_cls: 0.5920, loss_bbox: 0.4762, loss_corner: 0.2451, loss: 2.3248, grad_norm: 4.3487
2022-06-28 15:19:29,633 - mmdet - INFO - Epoch [1][1530/3712]	lr: 1.004e-03, eta: 2 days, 7:24:35, time: 0.666, data_time: 0.005, memory: 4663, bbox_loss: 0.9465, semantic_loss: 0.0933, loss_cls: 0.5815, loss_bbox: 0.5254, loss_corner: 3.8213, loss: 5.9681, grad_norm: 607.2803
2022-06-28 15:19:49,613 - mmdet - INFO - Epoch [1][1560/3712]	lr: 1.004e-03, eta: 2 days, 7:23:22, time: 0.666, data_time: 0.005, memory: 4663, bbox_loss: 0.9480, semantic_loss: 0.0864, loss_cls: 0.5980, loss_bbox: 0.7677, loss_corner: 0.5075, loss: 2.9076, grad_norm: 20.0053
2022-06-28 15:20:09,703 - mmdet - INFO - Epoch [1][1590/3712]	lr: 1.004e-03, eta: 2 days, 7:22:32, time: 0.670, data_time: 0.005, memory: 4663, bbox_loss: 0.9628, semantic_loss: 0.0895, loss_cls: 0.5946, loss_bbox: 0.5274, loss_corner: 0.2568, loss: 2.4310, grad_norm: 5.4769
2022-06-28 15:20:29,791 - mmdet - INFO - Epoch [1][1620/3712]	lr: 1.004e-03, eta: 2 days, 7:21:43, time: 0.670, data_time: 0.006, memory: 4663, bbox_loss: 0.8967, semantic_loss: 0.0884, loss_cls: 0.6082, loss_bbox: 0.4854, loss_corner: 0.1772, loss: 2.2559, grad_norm: 5.4091
2022-06-28 15:20:49,756 - mmdet - INFO - Epoch [1][1650/3712]	lr: 1.004e-03, eta: 2 days, 7:20:32, time: 0.666, data_time: 0.005, memory: 4663, bbox_loss: 0.8880, semantic_loss: 0.0917, loss_cls: 0.5982, loss_bbox: 0.3574, loss_corner: 0.1468, loss: 2.0820, grad_norm: 4.4186
2022-06-28 15:21:09,783 - mmdet - INFO - Epoch [1][1680/3712]	lr: 1.004e-03, eta: 2 days, 7:19:34, time: 0.668, data_time: 0.006, memory: 4663, bbox_loss: 0.8899, semantic_loss: 0.0883, loss_cls: 0.6022, loss_bbox: 0.3625, loss_corner: 0.1396, loss: 2.0824, grad_norm: 5.1678
2022-06-28 15:21:29,968 - mmdet - INFO - Epoch [1][1710/3712]	lr: 1.005e-03, eta: 2 days, 7:19:05, time: 0.673, data_time: 0.005, memory: 4663, bbox_loss: 0.8365, semantic_loss: 0.0827, loss_cls: 0.5890, loss_bbox: 0.3544, loss_corner: 0.1348, loss: 1.9974, grad_norm: 5.3038
2022-06-28 15:21:49,943 - mmdet - INFO - Epoch [1][1740/3712]	lr: 1.005e-03, eta: 2 days, 7:18:01, time: 0.666, data_time: 0.005, memory: 4663, bbox_loss: 0.9046, semantic_loss: 0.0959, loss_cls: 0.5877, loss_bbox: 0.3839, loss_corner: 0.1077, loss: 2.0799, grad_norm: 3.7638
2022-06-28 15:22:09,919 - mmdet - INFO - Epoch [1][1770/3712]	lr: 1.005e-03, eta: 2 days, 7:16:58, time: 0.666, data_time: 0.006, memory: 4663, bbox_loss: 0.8711, semantic_loss: 0.0870, loss_cls: 0.5767, loss_bbox: 0.3923, loss_corner: 0.1168, loss: 2.0439, grad_norm: 3.9317
2022-06-28 15:22:29,910 - mmdet - INFO - Epoch [1][1800/3712]	lr: 1.005e-03, eta: 2 days, 7:16:00, time: 0.666, data_time: 0.006, memory: 4663, bbox_loss: 0.9079, semantic_loss: 0.0878, loss_cls: 0.5746, loss_bbox: 0.4181, loss_corner: 0.1683, loss: 2.1567, grad_norm: 8.0817
2022-06-28 15:22:49,938 - mmdet - INFO - Epoch [1][1830/3712]	lr: 1.005e-03, eta: 2 days, 7:15:08, time: 0.668, data_time: 0.006, memory: 4663, bbox_loss: 0.8222, semantic_loss: 0.0821, loss_cls: 0.5829, loss_bbox: 0.3561, loss_corner: 0.1353, loss: 1.9786, grad_norm: 3.6453
2022-06-28 15:23:10,090 - mmdet - INFO - Epoch [1][1860/3712]	lr: 1.005e-03, eta: 2 days, 7:14:37, time: 0.672, data_time: 0.005, memory: 4663, bbox_loss: 0.8381, semantic_loss: 0.0876, loss_cls: 0.5922, loss_bbox: 0.3448, loss_corner: 0.1079, loss: 1.9705, grad_norm: 3.3135
2022-06-28 15:23:30,243 - mmdet - INFO - Epoch [1][1890/3712]	lr: 1.006e-03, eta: 2 days, 7:14:07, time: 0.672, data_time: 0.005, memory: 4663, bbox_loss: 0.9006, semantic_loss: 0.0910, loss_cls: 0.5944, loss_bbox: 0.4726, loss_corner: 0.7132, loss: 2.7719, grad_norm: 56.3988
2022-06-28 15:23:50,287 - mmdet - INFO - Epoch [1][1920/3712]	lr: 1.006e-03, eta: 2 days, 7:13:20, time: 0.668, data_time: 0.006, memory: 4663, bbox_loss: 0.8617, semantic_loss: 0.0785, loss_cls: 0.5841, loss_bbox: 0.3942, loss_corner: 0.1423, loss: 2.0607, grad_norm: 3.2757
2022-06-28 15:24:10,443 - mmdet - INFO - Epoch [1][1950/3712]	lr: 1.006e-03, eta: 2 days, 7:12:51, time: 0.672, data_time: 0.005, memory: 4663, bbox_loss: 0.8751, semantic_loss: 0.0855, loss_cls: 0.5897, loss_bbox: 0.4299, loss_corner: 0.1885, loss: 2.1686, grad_norm: 12.4038
2022-06-28 15:24:30,529 - mmdet - INFO - Epoch [1][1980/3712]	lr: 1.006e-03, eta: 2 days, 7:12:12, time: 0.670, data_time: 0.005, memory: 4663, bbox_loss: 0.8527, semantic_loss: 0.0799, loss_cls: 0.5875, loss_bbox: 0.4615, loss_corner: 0.5622, loss: 2.5439, grad_norm: 65.5213
2022-06-28 15:24:50,538 - mmdet - INFO - Epoch [1][2010/3712]	lr: 1.006e-03, eta: 2 days, 7:11:22, time: 0.667, data_time: 0.006, memory: 4663, bbox_loss: 0.8740, semantic_loss: 0.0825, loss_cls: 0.5889, loss_bbox: 0.4086, loss_corner: 0.1248, loss: 2.0787, grad_norm: 3.4692
2022-06-28 15:25:10,416 - mmdet - INFO - Epoch [1][2040/3712]	lr: 1.007e-03, eta: 2 days, 7:10:14, time: 0.663, data_time: 0.005, memory: 4663, bbox_loss: 0.8211, semantic_loss: 0.0819, loss_cls: 0.5990, loss_bbox: 0.4611, loss_corner: 229.7156, loss: 231.6788, grad_norm: 30899.2806

You can see that in some iterations the total loss and grad_norm diverge dramatically, but it is still fine since the model still 'learns'. However, at the second epoch, the model collapsed:
2022-06-28 16:15:03,978 - mmdet - INFO - Epoch [2][2790/3712]	lr: 1.066e-03, eta: 2 days, 6:00:26, time: 0.664, data_time: 0.005, memory: 4663, bbox_loss: 0.5772, semantic_loss: 0.0599, loss_cls: 0.5440, loss_bbox: 0.2615, loss_corner: 0.0466, loss: 1.4892, grad_norm: 1.6312
2022-06-28 16:15:23,742 - mmdet - INFO - Epoch [2][2820/3712]	lr: 1.067e-03, eta: 2 days, 5:59:52, time: 0.659, data_time: 0.005, memory: 4663, bbox_loss: 0.5919, semantic_loss: 0.0578, loss_cls: 0.5427, loss_bbox: 0.2527, loss_corner: 0.0451, loss: 1.4902, grad_norm: 1.7961
2022-06-28 16:15:43,625 - mmdet - INFO - Epoch [2][2850/3712]	lr: 1.068e-03, eta: 2 days, 5:59:23, time: 0.663, data_time: 0.005, memory: 4663, bbox_loss: 0.6300, semantic_loss: 0.0649, loss_cls: 0.5430, loss_bbox: 0.3059, loss_corner: 19426.1580, loss: 19427.7019, grad_norm: 9655975.2565
2022-06-28 16:16:03,481 - mmdet - INFO - Epoch [2][2880/3712]	lr: 1.068e-03, eta: 2 days, 5:58:53, time: 0.662, data_time: 0.005, memory: 4663, bbox_loss: 0.5737, semantic_loss: 0.0629, loss_cls: 0.5389, loss_bbox: 0.3841, loss_corner: inf, loss: inf, grad_norm: 2.7262
/usr/local/lib/python3.7/dist-packages/mmcv/runner/hooks/optimizer.py:50: FutureWarning: Non-finite norm encountered in torch.nn.utils.clip_grad_norm_; continuing anyway. Note that the default behavior will change in a future release to error out if a non-finite total norm is encountered. At that point, setting error_if_nonfinite=false will be required to retain the old behavior.
  return clip_grad.clip_grad_norm_(params, **self.grad_clip)
2022-06-28 16:16:23,290 - mmdet - INFO - Epoch [2][2910/3712]	lr: 1.069e-03, eta: 2 days, 5:58:21, time: 0.660, data_time: 0.005, memory: 4663, bbox_loss: 0.5935, semantic_loss: 0.0629, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:16:43,035 - mmdet - INFO - Epoch [2][2940/3712]	lr: 1.069e-03, eta: 2 days, 5:57:47, time: 0.658, data_time: 0.006, memory: 4663, bbox_loss: 0.6095, semantic_loss: 0.0667, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:17:02,797 - mmdet - INFO - Epoch [2][2970/3712]	lr: 1.070e-03, eta: 2 days, 5:57:13, time: 0.659, data_time: 0.005, memory: 4663, bbox_loss: 0.5640, semantic_loss: 0.0624, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:17:22,623 - mmdet - INFO - Epoch [2][3000/3712]	lr: 1.071e-03, eta: 2 days, 5:56:42, time: 0.661, data_time: 0.005, memory: 4663, bbox_loss: 0.5915, semantic_loss: 0.0607, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:17:42,526 - mmdet - INFO - Epoch [2][3030/3712]	lr: 1.071e-03, eta: 2 days, 5:56:15, time: 0.663, data_time: 0.006, memory: 4663, bbox_loss: 0.5859, semantic_loss: 0.0609, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:18:02,451 - mmdet - INFO - Epoch [2][3060/3712]	lr: 1.072e-03, eta: 2 days, 5:55:48, time: 0.664, data_time: 0.005, memory: 4663, bbox_loss: 0.5654, semantic_loss: 0.0612, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:18:22,237 - mmdet - INFO - Epoch [2][3090/3712]	lr: 1.073e-03, eta: 2 days, 5:55:16, time: 0.660, data_time: 0.005, memory: 4663, bbox_loss: 0.5443, semantic_loss: 0.0628, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:18:41,980 - mmdet - INFO - Epoch [2][3120/3712]	lr: 1.073e-03, eta: 2 days, 5:54:42, time: 0.658, data_time: 0.005, memory: 4663, bbox_loss: 0.5704, semantic_loss: 0.0585, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan
2022-06-28 16:19:01,851 - mmdet - INFO - Epoch [2][3150/3712]	lr: 1.074e-03, eta: 2 days, 5:54:14, time: 0.662, data_time: 0.005, memory: 4663, bbox_loss: 0.5856, semantic_loss: 0.0604, loss_cls: nan, loss_bbox: nan, loss_corner: nan, loss: nan, grad_norm: nan

The losses of second stage becomes nan after this message:
/usr/local/lib/python3.7/dist-packages/mmcv/runner/hooks/optimizer.py:50: FutureWarning: Non-finite norm encountered in torch.nn.utils.clip_grad_norm_; continuing anyway. Note that the default behavior will change in a future release to error out if a non-finite total norm is encountered. At that point, setting error_if_nonfinite=false will be required to retain the old behavior.
Is it a bug or is there something need to be modified but I missed?

Hi, I met the same problem while reproducing the SECOND, the results were quite poor. Have you solved it?
----------- AP11 Results ------------
Car<EMAIL_ADDRESS>0.70, 0.70:
bbox AP11:9.9299, 10.3669, 10.6121
bev  AP11:0.0433, 0.1324, 0.1343
3d   AP11:0.0366, 0.0930, 0.0924
aos  AP11:3.23, 4.70, 4.81
Car<EMAIL_ADDRESS>0.50, 0.50:
bbox AP11:9.9299, 10.3669, 10.6121
bev  AP11:0.1352, 0.3300, 0.3601
3d   AP11:0.1266, 0.3040, 0.2868
aos  AP11:3.23, 4.70, 4.81
----------- AP40 Results ------------
Car<EMAIL_ADDRESS>0.70, 0.70:
bbox AP40:1.3368, 1.9814, 2.3379
bev  AP40:0.0119, 0.0364, 0.0369
3d   AP40:0.0101, 0.0256, 0.0254
aos  AP40:0.51, 0.75, 0.90
Car<EMAIL_ADDRESS>0.50, 0.50:
bbox AP40:1.3368, 1.9814, 2.3379
bev  AP40:0.0743, 0.2669, 0.2871
3d   AP40:0.0680, 0.2434, 0.1577
aos  AP40:0.51, 0.75, 0.90

Hi, I have to fix it in https://github.com/open-mmlab/mmdetection3d/pull/1874. And I will update PointRCNN checkpoints in the model zoo later.

I think the nan issue with PointRCNN is still there. I am using rc5 and after a few iterations, the nan appears.

point-rcnn的demo结果都不正确

the demo of point-rcnn is also error result

I think the nan issue with PointRCNN is still there. I am using rc5 and after a few iterations, the nan appears.

Could you provide your env? I will recheck PointRCNN.

the demo of point-rcnn is also error result

I will update the model zoo checkpoint later.

Hello, VVsssssk! Are there any updates on this issue? I have the same problem and it seems to be that weights haven't been updated yet.
This issue still can be reproduced on the main branch. Is it the newest URL for the weights?
https://download.openmmlab.com/mmdetection3d/v1.0.0_models/point_rcnn/point_rcnn_2x8_kitti-3d-3classes_20211208_151344.pth


master is now named main

Renaming master branch  to main was done on 04/11  https://github.com/containerd/nerdctl/issues/1444
this PR introduce changes comes with this switch.
Plz do not forget to update your local branch and remotes

master in GHA yamls can be dropped too now
https://github.com/containerd/nerdctl/blob/b71443b2a3abc6288944c72229a2e21a1ae7ec6e/.github/workflows/test.yml#L6

master in GHA yamls can be dropped too now
https://github.com/containerd/nerdctl/blob/b71443b2a3abc6288944c72229a2e21a1ae7ec6e/.github/workflows/test.yml#L6

thanks, fixed


Missing allocations

What I'm trying to achieve
It's hard to diagnose what the problem might be, but for example:
we have 100 orders placed, which means there should be 100 allocations. But once in a while, there is missing one or two allocation.
I can't really find what can be a problem, I wrote command to fix it (for loop for each order line and fix stock allocation quantity).
My first thought was there is problem with canceling order or creating draft, as in the past - but that works fine. It looks like 1 in XX orders is placed without allocating stock quantity
Steps to reproduce the problem
As mentioned above, hard to reproduce, placing XXX orders on production env and comparing with script result (counting Order Lines quantity for unfulfilled orders might help)
What I expected to happen
Screenshots

System information
Operating system:
Aws EC2

Hmm, maybe there is some race condition when two users are modifying an order/product at the same time, either in the dashboard or in the storefront? Maybe we're missing some select_for_update somewhere. @patrys I think you were once debugging a similar issue.

I didn't find flaws in the logic for the GraphQL API of Checkout, maybe some variants have the flag track_inventory set to False? That could be a possibility.
We are talking about stocks and quantity_allocated, yes? Double checking. Which version/hash of saleor?

I think what could be happening is some race condition where the model that contains the quantity allocated field is read and then subsequently saved for an unrelated reason. Django by default saves all model fields, not just the ones that were assigned to, so if the allocation happens between the read and the write, the write would undo the allocation.

I didn't find flaws in the logic for the GraphQL API of Checkout, maybe some variants have the flag track_inventory set to False? That could be a possibility.
We are talking about stocks and quantity_allocated, yes? Double checking. Which version/hash of saleor?

2.9.0 (first release)
Track_inventory is not the case - this error occurs only to products with enabled tracking inventory.
Yes - it's about quantity_allocated. Usually it's too small.
Some sample:
Stock (1114 Piel Tetra) allocation | 8 -> 10
Stock (1129 S1) allocation | 2 -> 3
Stock (1132 Piel Flanela) allocation | 1 -> 2
Stock (1120 Ciazowy Retro) allocation | 6 -> 7
Stock (1115 Ciazowy Fashion) allocation | 4 -> 6

As you can see that's usually some small numbers / differences, this sample is for products which were almost sold out and fulfilled, but even if we had 200 stock of them, at the end of sale there would be only few allocatons missings.
Although - after further testing, even after we closed the shop this missing allocations appeared. My guess it's somewhere with Fulfillment logic, but still no clue what happens.
I also check quantity, and it's all right - so quantity is reduced properly, but quantity_allocated is not.

We discussed this issue today and we're wondering if it isn't fixed on master after quantity_allocated was moved to the Stock model. This model is now the main source of truth about the stock quantity of a variant and should be saved only when the quantities are changing. I would wait for PR https://github.com/mirumee/saleor-dashboard/pull/390 (should be merged this week) and see how it works once the warehouses/stock UI is fully operational again.

Closing, as with new allocation logic problem is solved


feat(network): don't filter historical ephemeral events

can always filter later, but can't unfilter

If this is approved before 8/6 I will be mega happy bc launch coming up soon <3
But if not that's also ok

reminder to add a changeset describing this change

I wonder if this change is still necessary since it's a change to the v1 network stack that will be removed very soon and the v2 stack already syncs ephemeral table events?

I wonder if this change is still necessary since it's a change to the v1 network stack that will be removed very soon and the v2 stack already syncs ephemeral table events?

Yeah true, I don't need it anymore since I'm on new network stack (should have updated here, ty for reminder)

might be nice to merge for consistency between v1 and v2 though since this'll be the default in v2


machine plenary templates: allow to use the rack fullname

If config option machine_ns_rack_fullname is true (default is false
to maintain backward compatibility, use the rack fullname instead of
the rack name to build the machine namespace in the plenary templates.
When the option is true, also export the rack fullname instead of
the rack name in /hardware/rack/name.

Fixes #105 (GitHub issue https://github.com/quattor/aquilon/issues/105)
Change-Id: I99dd2d0af0091dca588e576d45b18bd833100fbc

lets first finish with 110 PR

Closing without merging as aq cat --machine  is the tool to use and does the right thing.


LIHADOOP-39635

Add new configuration parameters heuristic, which will list the current values for configuration parameters, and also recommended new values. To determine new values, it will check for:

execution memory spill: this will slow down the application, so try to prevent this by increasing partitions, increasing executor memory, or decreasing cores.
long tasks: this will slow down the application, so try to prevent this by increasing the number of partitions.
task skew: this will slow down the application, so add recommendations for making partitions more even.
OOM or GC: increase memory, increase partitions, or decrease cores, to try to avoid the error.
container killed by YARN errors: increase overhead memory.
unused executor memory, if this is much higher than max JVM used memory; either increase cores or decrease memory.
driver configuration parameters (memory and cores).

There are a lot of extra unrelated commits. Replacing this with a new branch, PR in https://github.com/edwinalu/dr-elephant/pull/2.


Remove duplicate enum and macro about numberic_enum_mod

What problem does this PR solve?
Issue Number: close #11297
Problem Summary:
What is changed and how it works?
What's Changed:
Remove duplicated enum and related macros about PerfLevel
Related changes

Need to cherry-pick to the release branch

Check List
Tests

No code

Side effects

Performance regression

Consumes more CPU
Consumes more MEM

Breaking backward compatibility

Release note
 None.

Oh, I forgot this one. You shouldn't delete the enum in engine_trait.
The engine_trait is an abstraction of RocksDB engine, meaning we should be able to plug in different kv engines under the same interface set. That's why we should accept generic configuration (engine_trait::PerfLevel) and convert it to specific configuration (engine_rocks::PerfLevel) when entering specific engine implementation.
Instead, you can delete the engine_rocks::perf_level_serde. That doesn't seem useful anymore.

@tabokie Sorry to miss this, Got it

@tabokie Maybe we should remove duplicated macro numeric_enum_mod and rocksdb_enum_mod either in this issue. For example put the macors in the crate tikv-util

@yuqi1129 That's a good idea. You can try it.

/cc @tabokie

/merge

/merge


Encode settings into shareable links

Gonna need to consider sanitizing all data to ensure there's no tomfoolery.

Maybe just save a list of task ids to display and do a strict compare against the list on site


Add CUDA support for vectorization.

This patch contains a test that relies on a previously committed pull request (#1404).

I certainly can't claim to understand all this code, but I think the organisation of it looks OK.
One thing that would be handy is if there were a small test of CudaKernelBase.forall, because we will be relying on that API. This could just test with a simple kernel like:
@cuda.jit
def cuda_arange(ary, count):
    i = cuda.grid(1)
    if i < count:
        ary[i] = i

and the test would ensure that calling cuda_arange.forall(len(arr))(arr, len(arr)) sets the values in the array such that it is equal to the result of np.arange(len(arr), arr.dtype) (as an example).


No check if the mob is IEntityOwnable and owned

Issue Description:
Players should not be able to make spawners of owned entities.
Entities spawned from a shard made of owned entities are not owned.
Proposed fixes:
no shard creation from owned entities
or
entities spawned from a shard made of owned entities should also be owned by the same owner.
fix #2 may cause issues for some mods.
What happens:
Entities spawned from a shard made of owned entities are not owned.
What you expected to happen:
Entities spawned from a shard made of owned entities are owned or cannot spawn.

Affected Versions (Do not use "latest"):

Soul Shards: SoulShards-TOW-1.10.2-2.6.3-43

What defines an "owned entity"? Do you mean things like dogs and cats vs wolves and ocelots?

Yes, other mods have ownable entities that break balance due to the missing check.
IEntityOwnable (might be old)
http://takahikokawasaki.github.io/minecraft-resources/javadoc/forge/1.7.10-<IP_ADDRESS>1/net/minecraft/entity/IEntityOwnable.html
Example mod: https://github.com/Thutmose/Pokecube
Thutmose:
those mods (soul shards) really should check if the mob is IEntityOwnable and owned...
and then not let them pick up if it is
nothing I can really do about it though on my end

All entities that extend EntityLiving are caught and enabled by default. The config exists just for this reason. If it bothers other devs, I have an IMC API to blacklist entities by class. (In 1.11, I am changing that to registry names)


Update error handling for recent TLS 1.2 problems talking to Apple servers

Help users towards the solution for #6553 by providing better error messaging when Ruby can't make an SSL connection to Apple's servers.
I needed to move the local Faraday error class creation outside of the Commander module in order to have the correct shadowing happen if/when Faraday is later defined.
I knew I was on the right track with that when Ruby complained that the ConnectionFailed class supertypes did not match (I originally started with StandardError, like in the previous code). Looking at the Faraday code, those extra super classes are now also defined locally so that the class hierarchies can match correctly.

This kind of makes an assumption that people are using homebrew :-)
In case anyone else is already using MacPorts, here are the commands to get this working:
sudo port install ruby23
sudo port select --set ruby ruby23
sudo gem install fastlane


Some (memory) optimizations to the normalizer

When trying to (locally) merge PRs #2621, #2645, #2730, and a few minor others, I noticed a pretty huge regression in memory usage.
Some files, in particular those under examples/csl would take several GBs of memory, up to 15 iirc (I will run a detailed comparison soon). The only thing I could think that changed was that some functions deep down in the Meta-F* library were redefined to call others, so the normalizer would now perform more steps. The following program confirmed it:
let rec tau () : Tac unit = tau ()
let _ = assert True by tau ()

While this is a tail-recursive recursive function, it would use an unbounded amount of memory. This even happens for a Tot function. I've noticed a few causes of this:
1- When unfolding an fvar, we were keeping the KAM's environment. This is unneeded: the fvar has no free indices, and similarly for other cases.
2- For the loop above, even in Tot, when we push the () argument to the stack, we save its environment. Then we unfold tau (and drop the current env, due to (1)), and shift the argument on the stack to the new environment. Repeating this process creates a long chain of unit-length environments, that uses an unbounded amount of heap. My naive solution here was to detect some particular closed cases, and discard the environment for the argument if so.
3- In the particular case of Tac, we are accumulating Meta nodes on the KAM's stack, when only the outermost one is actually needed.
With these changes, this loop now runs in constant memory. F* CI returned green.
If this looks sane, I can batch it into my merge for the other PRs. (Or just merge one by one....

Here's a comparison for master with and without this PR (when I add the other PRs mentioned above, some files still use more memory: SteelIntroExists goes up to 8GB).
Before:
Top 20 memory:
 ./tests/micro-benchmarks/_cache/SteelIntroExists.fst.checked    6167.0 MB  ████████
 ./examples/csl/_cache/SL.ExamplesLocks2.fst.checked             2414.5 MB  ███▏
 ./ulib/.cache/Steel.Effect.Atomic.fst.checked                   2244.9 MB  ██▉
 ./examples/csl/_cache/SL.ConcurrentExamples.fst.checked         2236.9 MB  ██▉
 ./examples/csl/_cache/SL.ExamplesLocks.fst.checked              2173.0 MB  ██▊
 ./ulib/.cache/Steel.HigherReference.fst.checked                 1936.1 MB  ██▌
 ./ulib/.cache/Steel.Semantics.Hoare.MST.fst.checked             1848.6 MB  ██▍
 ./ulib/.cache/Steel.ST.HigherArray.fst.checked                  1740.8 MB  ██▎
 ./ulib/.cache/FStar.Math.Fermat.fst.checked                     1503.3 MB  █▉
 ./ulib/.cache/Steel.Effect.fst.checked                          1394.1 MB  █▊
 ./ulib/.cache/Steel.Channel.Simplex.fst.checked                 1305.3 MB  █▋
 ./examples/csl/_cache/SL.ExamplesAuto.fst.checked               1253.8 MB  █▋
 ./examples/csl/_cache/SL.ExamplesPar.fst.checked                1181.8 MB  █▌
 ./ulib/.cache/Steel.ST.Array.Util.fst.checked                   1099.9 MB  █▍
 ./ulib/.cache/Steel.ST.GenElim.Base.fsti.checked                1031.7 MB  █▎
 ./ulib/.cache/Steel.Memory.fst.checked                          1026.7 MB  █▎
 ./ulib/.cache/LowStar.BufferView.fst.checked                    1007.3 MB  █▎
 ./ulib/.cache/LowStar.Monotonic.Buffer.fst.checked              1000.2 MB  █▎
 ./ulib/.cache/Steel.ST.EphemeralHashtbl.fst.checked              974.4 MB  █▎
 ./ulib/.cache/Steel.Array.fsti.checked                           946.7 MB  █▏

After:
 ./tests/micro-benchmarks/_cache/SteelIntroExists.fst.checked    6137.4 MB  ████████
 ./ulib/.cache/Steel.Effect.Atomic.fst.checked                   2206.3 MB  ██▉
 ./ulib/.cache/Steel.HigherReference.fst.checked                 1923.6 MB  ██▌
 ./ulib/.cache/Steel.Semantics.Hoare.MST.fst.checked             1862.6 MB  ██▍
 ./ulib/.cache/Steel.ST.HigherArray.fst.checked                  1724.9 MB  ██▎
 ./ulib/.cache/Steel.Effect.fst.checked                          1392.1 MB  █▊
 ./ulib/.cache/Steel.ST.GenElim.Base.fst.checked                 1142.8 MB  █▍
 ./examples/csl/_cache/SL.ConcurrentExamples.fst.checked         1082.9 MB  █▍
 ./examples/csl/_cache/SL.ExamplesLocks2.fst.checked             1032.8 MB  █▎
 ./ulib/.cache/Steel.ST.GenElim.Base.fsti.checked                1023.9 MB  █▎
 ./ulib/.cache/Steel.ST.Array.fst.checked                        1017.0 MB  █▎
 ./ulib/.cache/LowStar.Monotonic.Buffer.fst.checked               997.0 MB  █▎
 ./ulib/.cache/Steel.ST.EphemeralHashtbl.fst.checked              991.6 MB  █▎
 ./ulib/.cache/Steel.Effect.Atomic.fsti.checked                   980.9 MB  █▎
 ./ulib/.cache/Steel.Reference.fst.checked                        955.8 MB  █▎
 ./examples/csl/_cache/SL.ExamplesLocks.fst.checked               946.0 MB  █▏
 ./ulib/.cache/FStar.UInt.fst.checked                             929.8 MB  █▏
 ./ulib/.cache/Steel.ST.HigherArray.fsti.checked                  913.3 MB  █▏
 ./ulib/.cache/Steel.Effect.Common.fst.checked                    864.4 MB  █▏
 ./ulib/.cache/LowStar.RVector.fst.checked                        827.2 MB  █

Note the reduction for all csl files (some of which drop from the top 20). Most other files stay in the same ballpark.

Guido, it is great to see improvements to memory usage. This reminds me of this discussion on the HACL side: https://github.com/hacl-star/hacl-star/issues/541
If you are looking for more benchmarks to assess memory usage, we have a few files in HACL* that are routinely peaking above 10GB (see issue). I can provide details if you're interested!

Thanks Guido. That specific file is gone but we had quite high memory usage on a few normalizer-heavy files in HACL, so if you're currently doing memory usage improvements, I'm happy to chat about it more with you in case you're looking for test cases. Let me know.

This looks great!  It's especially nice that a few simple localized changes, each with clear justifications, end up producing significant savings.
Can we get those memory profile reports integrated with our Makefiles somehow, so that others can run them easily too. I'd be happy to see another PR with that at some point.
Thanks Guido. Merging.

Can we get those memory profile reports integrated with our Makefiles somehow, so that others can run them easily too. I'd be happy to see another PR with that at some point.

Yes! I'll wrap that up soon.

I ran an everest build overnight (which later failed in mitls, but anyway...) monitoring memory usage on F* and HACL*, here's the top of the list:
Top 25 memory:
 ./hacl-star/obj/EverCrypt_Hash_Incremental.krml                                     4525.1 MB
 ./hacl-star/obj/Vale.AES.X64.GCMencryptOpt.fst.checked                              3619.4 MB
 ./hacl-star/obj/Vale.AES.X64.GCMdecryptOpt.fst.checked                              3545.9 MB
 ./hacl-star/obj/Vale.Wrapper.X64.GCMdecryptOpt.fst.checked                          3225.6 MB
 ./hacl-star/obj/Vale.Wrapper.X64.GCMencryptOpt.fst.checked                          3182.6 MB
 ./hacl-star/obj/Vale.Wrapper.X64.GCMdecryptOpt256.fst.checked                       3165.4 MB
 ./hacl-star/obj/Vale.Wrapper.X64.GCMencryptOpt256.fst.checked                       3139.3 MB
 ./hacl-star/obj/Vale.AES.X64.AESGCM.fst.checked                                     2809.7 MB
 ./hacl-star/obj/Spec.SHA3.Incremental.fst.checked                                   2514.2 MB
 ./hacl-star/obj/Vale.Curve25519.X64.FastHybrid.fst.checked                          2267.9 MB
 ./hacl-star/obj/Vale.Curve25519.X64.FastUtil.fst.checked                            2203.2 MB
 ./hacl-star/obj/Hacl.Test.HMAC_DRBG.fst.checked                                     2161.1 MB
 ./hacl-star/obj/Hacl.Test.ECDSA.fst.checked                                         2152.2 MB
 ./hacl-star/obj/Test.Vectors.fst.checked                                            2142.7 MB
 ./hacl-star/obj/Vale.Poly1305.X64.fst.checked                                       2076.4 MB
 ./hacl-star/obj/Hacl.Impl.SHA2.Core.fst.checked                                     2055.0 MB
 ./hacl-star/obj/Vale.Curve25519.X64.FastSqr.fst.checked                             1997.1 MB
 ./FStar/ulib/.cache/Steel.HigherReference.fst.checked                               1962.2 MB
 ./FStar/ulib/.cache/Steel.Semantics.Hoare.MST.fst.checked                           1842.7 MB
 ./hacl-star/obj/Hacl.Meta.HPKE.fst.checked                                          1800.1 MB
 ./hacl-star/obj/Vale.Transformers.InstructionReorder.fst.checked                    1787.7 MB
 ./hacl-star/obj/Test.krml                                                           1771.0 MB
 ./hacl-star/obj/Hacl.Spec.K256.Field52.Lemmas3.fst.checked                          1767.0 MB
 ./hacl-star/obj/Vale.SHA.PPC64LE.SHA_helpers.fst.checked                            1697.6 MB
 ./hacl-star/obj/Hacl.Impl.HPKE.fst.checked                                          1690.7 MB

(I got this via this change to the HACL* makefile:
diff --git a/Makefile b/Makefile
index ec1803ac05..00dd0387fa 100644
--- a/Makefile
+++ b/Makefile
@@ -215,6 +215,7 @@ SHELL:=$(shell which bash)
 ifeq (,$(NOSHORTLOG))
 run-with-log = \
   @echo "$(subst ",\",$1)" > $3.cmd; \
+ runlim -o<EMAIL_ADDRESS>\
   $(TIME) -o $3.time sh -c "$(subst ",\",$1)" > $3.out 2> >( tee $3.err 1>&2 ); \
   ret=$$?; \
   time=$$(cat $3.time); \

and then used a script to collect results. Hope most invocations go via this rule. The first column in the table above is the name of the rule that triggered the F*, or whatever else, call.)
This is a different way of measuring than the one used by @msprotz in hacl-star/hacl-star#541, but:

It seems consistent, I think, except that I don't see the EverCrypt_Hash_Incremental.krml call appearing there. Maybe that's because of (3), but not sure.

Memory usage seems lower on many files (e.g. Test.Vectors goes from ~4.3GB to ~2.1GB), and not worse on the rest.

Also, runlim is supposed to measure the usage of the whole process tree, so this is including the Z3 invocations. Though I can't say I trust it 100% :-)

Jonathan, if it's easy, can you re-run your measuring script again and see if it's consistent with this? These are my hashes:
F* 20e3eede1fc3aeb4b5828c3661d4991161d2b03d
karamel e8910fa23959ce874b17f0ecc23ee6acf491a565
everparse f4660cce73dbf90590f9a71cea229012dddb273e
hacl-star cd82cb8391f48e819fac229d32c6cacbefd11cc5
mitls-fstar a12125f8ffa63596bc50720853e4d0c0564f45e9

I am observing comparable numbers. Test.Vectors went from 7GB (F* 80abd5984f) down to 2.1GB (F* 20e3eede1f). And the rest is pretty stable.
These are my numbers, which don't take the memory used by z3 into account (top 10 files):
2369448 Hacl.Test.ECDSA.fst
2704932 Spec.SHA3.Incremental.fst
3188952 Vale.AES.X64.AESGCM.fst
3281896 Vale.Wrapper.X64.GCMencryptOpt256.fst
3352760 Vale.Wrapper.X64.GCMencryptOpt.fst
3408116 Vale.Wrapper.X64.GCMdecryptOpt256.fst
3413536 Vale.Wrapper.X64.GCMdecryptOpt.fst
3558760 Vale.AES.X64.GCMencryptOpt.fst
3602964 Vale.AES.X64.GCMdecryptOpt.fst
4618788 EverCrypt.Hash.Incremental.fst

This is quite a dramatic improvement. Thanks Guido! CCing @karthikbhargavan and @polubelova regarding the memory improvements. @pnmadelaine might even be able to allow more parallel jobs on the CI machine

I'm surprised about EverCrypt Hash Incremental, though. This file is just an application of a functor, and doesn't have big calc proofs or anything.  See https://github.com/hacl-star/hacl-star/blob/main/providers/evercrypt/fst/EverCrypt.Hash.Incremental.fst
It also didn't show up in my previous benchmarking in https://github.com/hacl-star/hacl-star/issues/541 -- any thoughts about what might be happening here?

Do you think calls to normalize_term (pow2 64 - 1) get memoized? There are quite a few of these we could pull out into a global definition?

Haven't looked in detail yet, but note that it's the extraction call that is expensive, not its verification. For producing the .checked file I get:
[runlim] time:			29.19 seconds
[runlim] space:			824.1 MB

I'll try to pin it down further soon.


Pub/Sub

Basically make it easier for users to share blocks across graphs.
Roam/inter made tremendous progress here, but still seems like there could be more functionality built and maintainer won't have time to upkeep it long term.
Source: Tony Ennis
Implementation might require a service being built

multiplayer!


is the lib still maintenance?

@timfpark ?

@timfpark @matt-oakes Would be awesome if we could migrate this lib into react-native-community

seem dead

@gran33  @lyseiha this library is great one, but I thing this repo is dead, for me @react-native-community/geolocation is pretty good and has all the functionalities, and if you need some advanced location permission handling use this RN permissions package


ProtocolCodeAction error despite validity of code

This is the error I get. Unfortunately, I cannot get my debugger to catch app code, so this is the information I currently have on hand.
Uncaught TypeError: Class extends value undefined is not a constructor or null
    at Object.<anonymous> (D:\Triage UI\electrontriage\node_modules\vscode-languageclient\lib\common\protocolCodeAction.js:8)
    at Object.<anonymous> (D:\Triage UI\electrontriage\node_modules\vscode-languageclient\lib\common\protocolCodeAction.js:16)
    at Module._compile (internal/modules/cjs/loader.js:1152)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:1173)
    at Module.load (internal/modules/cjs/loader.js:992)
    at Module._load (internal/modules/cjs/loader.js:885)
    at Function.f._load (electron/js2c/asar_bundle.js:5)
    at Module.require (internal/modules/cjs/loader.js:1032)
    at require (internal/modules/cjs/helpers.js:72)
    at Object.<anonymous> (D:\Triage UI\electrontriage\node_modules\vscode-languageclient\lib\common\codeConverter.js:14)

This errors before any of my app code even executes, meaning it is a problem with the library in and of itself, not my code.
I don't have a clear idea what could be causing the issue. I directly imported all the related packages from NPM and modified none of the code on disk. The only package that is used in my stack locally is a compatibility layer module aliased to vscode (as per the expected use, required by monaco-languageclient). You can view it here. However, I doubt this alias has any influence on languageserver-node.

Can you share the content of your protocolCodeAction.js file?

This is the error I get. Unfortunately, I cannot get my debugger to catch app code

If you manually add debugger; statements to protocolCodeAction.js, your debugger still will not suspend the process?

The error indicates that the super class of the ProtocolCodeAction can't be found and loaded (it is undefined). The super class is VS Code's CodeAction class. So the problem comes from the compatibility layer very likely not providing a CodeAction class.
I will close the issue since there is nothing the library can do to fix this.


Fonts are not being loaded in web views

This is the case since we’ve switched to WKWebView. I filed the following tickets

[ ] Martsy https://github.com/artsy/microgravity/issues/1078
[ ] Force https://github.com/artsy/force/issues/3506

This is the error from the inspector:
TypeError: undefined is not an object (evaluating 'window['mti_element_cache'].length')

I found two sites discussion this problem. The first suggestion is to add this call before the fonts.net javascript is loaded:
<script type="text/javascript">
window['mti_element_cache'] = []
</script>

The second suggestion is to replace the fonts.net javascript call with something that calls the CSS directly, something like this:
<link type="text/css" rel="stylesheet" rel="nofollow" href="//fast.fonts.net/cssapi/ff111ab-123-456-789.css"/>

There's the potential that the webpages had always been using our app's font cache, which is now not available to them as the web rendered is out of process.
http://stackoverflow.com/questions/25785179/using-custom-fonts-in-wkwebview

@orta Yeah that’s very possible.

Same with iPad/Force btw:

So, this is likely our side, running a vanilla WKWebView app:

I have tried:
1, remove the avante garde font from the app
2, make the wkwebkit action delegate always return YES
3, I tried removing all font references in the info.plist

A guess, the avant garde font is not the same filename as the rtf - it is also a TTF where everything else is an OTF - https://github.com/artsy/Artsy-UIFonts/blob/old_fonts_new_lib/Pod/Classes/UIFont+ArtsyFonts.m#L90-L100

So the font martsy is using has completely different names etc from our Avant Garde, I doubt they're conflicting. I also tried adding our fonts into the example project I made, and got nowhere.
{'fontfamily' : "ITC Avant Garde Gothic W04" ,'fontWeight' : "400" ,'fontStyle' : "Bold" ,contentIds :{EOT: '521186fb-1032-4a81-bff4-a67d052d6e5e',WOFF: '5f1f53ca-f786-466b-979b-2dc11d2d05e9',WOFF2: 'cd6106cf-c21e-4d0b-953e-3905a1b9dece',TTF: 'ac3dc0aa-6281-4d8f-aadb-67c67099ff9c',SVG: '0f98417d-ca43-4d3e-b392-21a473e4917a'} from https://fast.fonts.net/jsapi/f7f47a40-b25b-44ee-9f9c-cfdfc8bb2741.js
vs

Injecting the mti_element_cache beforehand removes the error, but doesn't fix the font issue:
    NSString *jScript = @"window['mti_element_cache'] = []";
    WKUserScript *wkUScript = [[WKUserScript alloc] initWithSource:jScript injectionTime:WKUserScriptInjectionTimeAtDocumentStart forMainFrameOnly:YES];
    WKUserContentController *wkUController = [[WKUserContentController alloc] init];
    [wkUController addUserScript:wkUScript];

    WKWebViewConfiguration *wkWebConfig = [[WKWebViewConfiguration alloc] init];
    wkWebConfig.userContentController = wkUController;

    WKWebView *web = [[WKWebView alloc] initWithFrame:self.view.bounds configuration:wkWebConfig];
    [self.view addSubview:web];

    NSURLRequest *request = [NSURLRequest requestWithURL:[NSURL URLWithString:@"http://m.artsy.net"]];
    [web loadRequest:request];

hah, so I stopped almost all code being ran in the app delegate, then almost gave up and noticed
    [ARDefaults setup];
    [ARRouter setup];

were still being ran. Removing those brings back the fonts.

I'm leaving it at that, I need to work on Emergence.
I gave enough info for someone to finish up. The problem lies in either the defaults or the router. If I had to guess, it might be around our custom browser id.


usage: model_list and some common questions

I want to konw:

support model list (a table includs hardware, backend, model name, dtype, optimization techs. )
does the project support service with concurrency? that is, if many client sent requests at the same time, will the deployment batch them and inference at once time?
can I put precessing & postprocessing in the deployment? instead of client.

I want to konw:

support model list (a table includs hardware, backend, model name, dtype, optimization techs. )
does the project support service with concurrency? that is, if many client sent requests at the same time, will the deployment batch them and inference at once time?
can I put precessing & postprocessing in the deployment? instead of client.

框架是从支持推理后端角度来支持模型推理服务的，当前支持tensorflow、torch、tensorrt、tensorrt-llm、vllm等，模型支持列表就是基于每个框架开发的模型。硬件方面主要用于gpu硬件推理，对于tf、torch框架也可以选择跑在cpu，也都是推理后端决定的。具体推理后端见推理后端，以及单独的grps_trtllm、grps_vllm工程。不同推理后端对应不同的镜像，见镜像列表。
框架本身支持并发请求，也可以限制同一时间并发推理的个数，并且可以选择dynamic batching模式进行动态批处理请求，具体见Batching。
通过自定义工程即可进行服务端的自定义开发，进而进行前后处理。具体见：自定义模型工程。

The framework supports model inference services from the perspective of supporting the inference backend. Currently, it supports frameworks such as TensorFlow, PyTorch, TensorRT, TensorRT-LLM, and VLLM. The model support list is based on models developed for each framework. On the hardware side, it is primarily used for GPU hardware inference, and for TensorFlow and PyTorch frameworks, it is also possible to choose to run on the CPU, which is determined by the inference backend. For specific inference backends, refer to Inference Backend, as well as the individual grps_trtllm and grps_vllm projects. Different inference backends correspond to different images, as listed in the Image List.
The framework itself supports concurrent requests and can limit the number of concurrent inferences at the same time. It also offers the option to use dynamic batching mode for dynamic batch processing of requests. For details, refer to Batching.
Custom server-side development can be carried out through custom projects for further pre- and post-processing. For specifics, refer to Custom Model Project.


clear() throws java.lang.UnsupportedOperationException: remove

Create a map and call .clear():
java.lang.UnsupportedOperationException: remove

	at java.base/java.util.Iterator.remove(Iterator.java:102)
	at java.base/java.util.AbstractCollection.clear(AbstractCollection.java:431)
	at java.base/java.util.AbstractMap.clear(AbstractMap.java:297)

Indeed those optional APIs are not yet implemented. They are on the TODO list. Meanwhile instead of Iterator.remove() it is possible to use an iterator and invoke remove() on relevant key-value mapping. For clear() there is no good alternative. Using close() and building again will release the entire off-heap memory and allocate again.


Select * INTO x from Y

Can we have a statement that allows us to insert into a temp table using the sql standard INTO?
All other statements seem to be available but this, and hand-coding this goes against the use-case for Kata.
cheers,
Jim

No, currently you can use the db.Statement() method, but it's nice to have,
can you provide a full example, on how it should be implemented on multiple dbs?
so you can speed up the process a bit

Hi,
In SQL Server, you can do this
SELECT *         into equipments_backup 	FROM test     where id = 2
Postgres SQL
SELECT * INTO films_recent FROM films WHERE date_prod >= '2002-01-01';
MySQL,SQLLite
'CREATE TABLE equipments_backup
AS SELECT *
FROM test
where id = 2
'
in sqlKata, can do something like
db.Query("Books").WhereTrue("IsPublished").Into("NewTableName")

yes it's a very useful statement, I came here searching about "how to in sqlkata" ... I'll try a different solution for my process


Edit deleted NavBar styles

Describe the bug
A clear and concise description of what the bug is.
I see the navbar styles are altered in an unfitted manner.
I wish to change those and fix it.
To Reproduce
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):

OS: [e.g. iOS]
Browser [e.g. chrome, safari]
Version [e.g. 22]

Smartphone (please complete the following information):

Device: [e.g. iPhone6]
OS: [e.g. iOS8.1]
Browser [e.g. stock browser, safari]
Version [e.g. 22]

Additional context
Add any other context about the problem here.

can you help me? getting error

https://github.com/Counselllor/Counsellor-Web/assets/146661411/fdcfafa6-62f4-4489-a8ba-438413e6221b
Is this okay? Please check

Okay Raise PR !

Some recent push is causing my CSS additions overwrite. I am trying to figure out the issue. Hope it gets solved soon

Should revert back the commits, and then push the changes? it will only change Navbar component folder

When i am going back to that old commit, the navbar is working fine, but pulling new changes causing something, that I am unable to figure out

fork a new project and try to do from scratch , let's try this !
Delete the old ones

Tried it, same issue.

Can you send the whole code here !
let me check from side

Missed deadline IG


Grid rendering is extremely slow

Enabling the background grid tanks performance and often causes inresposiveness especially at higher field of view.
I have exact issue on both Librewolf (Firefox fork) and Ungoogled Chromium.

Can you give an example screen recording?

Can you give an example screen recording?

Sure, I noticed that only 2-3 cpu threads spike during this. I have webgl enabled (it's disabled in Librewolf by default)
https://github.com/ricktu288/ray-optics/assets/84380947/7f528b9e-8657-4a81-8f51-2f7286799703
Here are my webgl related settings in Librewolf:

Now in the new version, the grid will only be redrawn when the user move/resize the view.


Cannot import name import_string

I'm trying to start my application, but keep getting this error:
Unhandled exception in thread started by <function wrapper at 0x1084b9320>
Traceback (most recent call last):
File "/Library/Python/2.7/site-packages/django/utils/autoreload.py", line 93, in wrapper
fn(*args, **kwargs)
File "/Library/Python/2.7/site-packages/django/core/management/commands/runserver.py", line 98, in inner_run
self.validate(display_num_errors=True)
File "/Library/Python/2.7/site-packages/django/core/management/base.py", line 310, in validate
num_errors = get_validation_errors(s, app)
File "/Library/Python/2.7/site-packages/django/core/management/validation.py", line 34, in get_validation_errors
for (app_name, error) in get_app_errors().items():
File "/Library/Python/2.7/site-packages/django/db/models/loading.py", line 196, in get_app_errors
self._populate()
File "/Library/Python/2.7/site-packages/django/db/models/loading.py", line 78, in _populate
self.load_app(app_name)
File "/Library/Python/2.7/site-packages/django/db/models/loading.py", line 99, in load_app
models = import_module('%s.models' % app_name)
File "/Library/Python/2.7/site-packages/django/utils/importlib.py", line 40, in import_module
import(name)
File "/Library/Python/2.7/site-packages/debug_toolbar/models.py", line 5, in
from debug_toolbar import settings as dt_settings
File "/Library/Python/2.7/site-packages/debug_toolbar/settings.py", line 8, in
from django.utils.module_loading import import_string
ImportError: cannot import name import_string
Any ideas?

Are you using compatible versions of Django and of the debug toolbar?

I have django 1.5 and debug_toolbar 1.4

how to solve this i do not using any toolbar i got the same error while i'm installing RatticDB on ubuntu 12.04

have the problem in mac(django==1.5.7)

this function add in Since Django 1.7

use django1.5 with django-debug-toolbar 1.0.1
u can install it with 'pip install django-debug-toolbar==1.0.1'

use django1.5 with django-debug-toolbar 1.3.2

is there a list somewhere of which debug toolbar versions work with which django versions?
I need one that works with Django 1.4 😿

ok it seems I need 1.3.2


Support Kafka

Maybe not possible as a full record manager in the library, because can't control concurrency https://issues.apache.org/jira/browse/KAFKA-2260
However, in situations where there is only one thread per sequence, then it would be possible.

Right, it might be a mean to transport events rather then store.
https://medium.com/serialized-io/apache-kafka-is-not-for-event-sourcing-81735c3cf5c

If you need eventsourcing on Kafka, please add weight for KAFKA-2260.

I made a comment suggesting how we could approach this


Add "Accept"-header on NSQ lookup

Hi there! First of all, thank you for the project and all the work and time you put into it to get in all the features.
I stumbled across an old NSQ implementation laying around, and trying to connect to it's nsqlookupd received a deserialization error for the LookupResponse. Investigating, it turned out, it was a pre-1.0 response, which had a different format. And, looking into the python implementation, I found they set an additional header (https://github.com/nsqio/pynsq/blob/master/nsq/reader.py#L599) to ensure they receive the data in the expected format.
To be more backward compatible and prevent receiving newer, unexpected changes in the future, I propose to add the following header:
Accept: application/vnd.nsq; version=1.0
to this request:
https://github.com/harporoeder/tokio-nsq/blob/1613556e61fe4a6b22291ae2f947cc7d5b5bfef5/src/consumer.rs#L223
If you want, I can take a shot at a PR?
Have a nice day!
Christoph

Hello @girstenbrei Pardon the late response.
I added the header where you indicated and will get a new release up.

See release '0.13.1'.

Hi there! Don't worry about doing things when they fit in.
Works like a charm, thank you a lot for your effort! I tested connecting to the same nsqlookupd version (is v0.3.8) and everything works out of the box!
Closing this now as solved by 0.13.1.


Issues supplying APNs SSL certificate and private key to createPlatformApplication

To get Apple Push Notifications working with the AWS SNS system you need to setup a platform application. The platform application creation requires an SSL certificate and a private key that Apple provides. You supply them as follows
        var attributes : [String : String] = [
            "PlatformCredential" : privateKey,
            "PlatformPrincipal" : SSLCertificate
            ]

        let createApplicationInput = SNS.CreatePlatformApplicationInput(attributes:attributes, name:applicationName, platform:"APNS_SANDBOX")
        let createApplicationResponse = try sns.createPlatformApplication(createApplicationInput)

I am providing them in the form
-----BEGIN CERTIFICATE-----
MIIEKJHKhkjjsndfmnisudf...
-----END CERTIFICATE-----

and
-----BEGIN PRIVATE KEY-----
MIIEkjjgusdfdfjjnemn/sdfhkjsdf
-----END PRIVATE KEY-----

The call fails though with the following error
AWSResponseError(errorCode: "MalformedInput", message: Optional("Value found where not expected"))

Had a little investigation here. Your body is as follows
Action=CreatePlatformApplication
&Name=myapp
&Platform=APNS_SANDBOX
&Attributes.PlatformCredential=<ssl certificate>
&Attributes.PlatformPrincipal=<private key>
&Version=2010-03-31

AWS is expecting it in the following form
Action=CreatePlatformApplication
&Name=myapp
&Platform=APNS_SANDBOX
&Attributes.entry.1.key=PlatformCredential
&Attributes.entry.1.value=<ssl certificate>
&Attributes.entry.2.key=PlatformPrincipal
&Attributes.entry.2.value=<private key>
&Version=2010-03-31

It appears to be serializeToFlatDictionary() that is returning the "malformed" dictionary.

I fixed the code to output the correct dictionary format in JSONSerializer.serializeToFlatDictionary(). See code changes below
    func serializeToFlatDictionary(_ data: Data) throws -> [String: Any] {
        func flatten(dictionary: [String: Any]) -> [String: Any] {
            var flatted: [String: Any] = [:]

            func destructiveFlatten(dictionary: [String: Any]) {
                for (key, value) in dictionary {
                    switch value {
                    case let value as [String: Any]:
                        for iterator in flatten(dictionary: value).enumerated() {
                            switch iterator.element.value {
                            case let value2 as [String: Any]:
                                destructiveFlatten(dictionary: value2)

                            case let values as [Any]: // TODO: values<Element> might be dictionary...
                                for iterator in values.enumerated() {
                                    flatted["\(key).member.\(iterator.offset+1)"] = iterator.element
                                }

                            default:
                                flatted["\(key).entry.\(iterator.offset+1).key"] = iterator.element.key
                                flatted["\(key).entry.\(iterator.offset+1).value"] = iterator.element.value
                            }
                        }

                    case let values as [Any]: // TODO: values<Element> might be dictionary...
                        for iterator in values.enumerated() {
                            flatted["\(key).member.\(iterator.offset+1)"] = iterator.element
                        }

                    default:
                        flatted[key] = value
                    }
                }
            }
            destructiveFlatten(dictionary: dictionary)
            return flatted
        }

CreatePlatformApplication is still failing though. It is now returning the error "PlatformPrincipal not valid". I have tested the certificate and key using the CLI and web interface and they both work fine.

Closing this issue in favour of splitting it into two #106 and #107


Where can I find supplementary material?

Hi,
Thank you for sharing your research.
I would like to know the formulation for statistical foreground probability and statistical boundary probability, but the paper says to refer to the supplementary material. Where can I find the supplementary material?

https://zju3dv.github.io/deep_ac/videos/DeepAC_sup.pdf

Thank you for responding quickly.


Refactor play_media function to improve readability and maintainability

Breaking change
Proposed change
Sonarcloud flagged this method as having a high cognitive complexity which means that it will be hard to maintain. After looking at the method i identified logic that would be more suited to be placed in it's own function. By doing this the method will decrease in LOC and it will become easier to read and maintain.
Type of change

[ ] Dependency upgrade
[ ] Bugfix (non-breaking change which fixes an issue)
[ ] New integration (thank you!)
[ ] New feature (which adds functionality to an existing integration)
[ ] Deprecation (breaking change to happen in the future)
[ ] Breaking change (fix/feature causing existing functionality to break)
[x] Code quality improvements to existing code or addition of tests

Additional information

This PR fixes or closes issue: fixes #
This PR is related to issue:
Link to documentation pull request:

Checklist

[x] The code change is tested and works locally.
[x] Local tests pass. Your PR cannot be merged unless tests pass
[x] There is no commented out code in this PR.
[x] I have followed the development checklist
[x] I have followed the perfect PR recommendations
[x] The code has been formatted using Ruff (ruff format homeassistant tests)
[ ] Tests have been added to verify that the new code works.

If user exposed functionality or configuration variables are added/changed:

[ ] Documentation added/updated for www.home-assistant.io

If the code communicates with devices, web services, or third-party tools:

[ ] The manifest file has all fields filled out correctly.
Updated and included derived files by running: python3 -m script.hassfest.
[ ] New or updated dependencies have been added to requirements_all.txt.
Updated by running python3 -m script.gen_requirements_all.
[ ] For the updated dependencies - a link to the changelog, or at minimum a diff between library versions is added to the PR description.

To help with the load of incoming pull requests:

[ ] I have reviewed two other open pull requests in this repository.

Tests were run by following the documentation and executing : Tasks: Run Task -> Pytest
Source: https://developers.home-assistant.io/docs/development_environment/

The improvement proposed in this PR is limited:

The new function is not so readable.
Moreover, the new function's name is not representative since it handles BangOlufsen-only media.


Wh smp 107 logout link fix

Once a user logs out, the cannot access site by pushing the back button.

Hasn't passed build check

There are conflicts


cleanup: remove trailing whitespace

note that this does not remove the trailing whitespace from the generated code as I reported in #96

This change is now part of create-react-native-module.


Determine admin better

I need to check cases like a Resource of ['*'] by fixing https://github.com/duo-labs/cloudmapper/blob/07c29f09d966605e04eda37a38a0adf85717a8c5/commands/find_admins.py#L62 to use something like:
def is_resource_any(resource):
    if resource == '*':
        return True
    if isinstance(resource, list) and len(resource) == 1 and resource[0] == '*':
        return True

    return False

Really, I need to use Zelkova or something smarter for all this.

To add on this issue , the current find_admins, figures out admin roles and admin users.
But however , it would be great if the find_admins command can go one step further and find the instances to which these roles are tagged back.  This would help in determining the privelege escalation path for a normal user according to IAM but having access to an instance would result in him / her having admin level access. This could be possibly given as an info as the tool could not determine who actually has access inside the concerned instance using aws apis.
But it would be a good information for the user of cloudmapper using the tool to dig the path deeper.

I was reading an article of Cyberark , I am sure you might have gone through it. They have published a set of ways by which they find shadow_admins in AWS. The article is at :-
https://www.cyberark.com/threat-research-blog/cloud-shadow-admin-threat-10-permissions-protect/
There opensource tool for finding shadow admins is  at : https://github.com/cyberark/SkyArk/tree/master/AWStealth
Some of them that are not presently part of cloudmapper checks are :-

iam:CreateLoginProfile

iam:UpdateLoginProfile

iam: PutUserPolicy, iam:PutGroupPolicy or iam:PutRolePolicy

iam: CreatePolicy

iam:UpdateAssumeRolePolicy

iam:CreatePolicyVersion, iam:SetDefaultPolicyVersion

iam:PassRole with iam:CreateInstanceProfile/ iam:AddRoleToInstanceProfile

I understand determining admins in such indirect ways would not be always accurate and might have lot of false positives. But however this information if given as an info with some confidence level value of cloudmapper , an auditor can atleast manually start digging in that direction further.
Over a period of time as and when any new privelege esclation technique is found , those could be added to the module making it more mature.

Also, what about the ability to switch role?  Could this allow a person to login one way, then assume an Admin role?  Also, they could assume an Admin role in another account?  I would like to know who has this ability because we have Cross Account Roles that have a one-way trust coming from the Credential account.
    "Action": "sts:AssumeRole",
    "Resource": "*"

@etendards Identifying role switching to admin roles is going to be outside of the scope of this issue for now as it involves a fair bit of extra effort beyond my original goals for this issue.  Initially I want to do a better job of identifying what principals are admins by viewing their privileges in isolation.  A later feature may identify who is an admin based on the roles they can assume into.


fix: process global session after timeout should refresh global session status

ref: https://github.com/cectc/dbpack/issues/
Ⅰ. Describe what this PR did
Ⅱ. Does this pull request fix one issue?
Ⅲ. Why don't you add test cases (unit test/integration test)?
Ⅳ. Describe how to verify it
Ⅴ. Special notes for reviews

LGTM

LGTM

LGTM


Clippy warning for same_name_method on generated file

Clippy warns on same_name_method because the generated code has two methods with the same name: one from a trait, another not from trait (get()/iter()).
I made a simple example to reproduce the issue: https://github.com/Zacho2/rustembed-clippy. This is basically the same as rust-embed/examples/basic.rs.
Example output from clippy:
$ cargo clippy -- -W clippy::same_name_method
    Checking rustembed-clippy v0.1.0 (/home/Documents/src/rustembed-clippy)
warning: method's name is the same as an existing method in a trait
 --> src/main.rs:3:10
  |
3 | #[derive(RustEmbed)]
  |          ^^^^^^^^^
  |
note: existing `get` defined here
 --> src/main.rs:3:10
  |
3 | #[derive(RustEmbed)]
  |          ^^^^^^^^^
  = help: for further information visit https://rust-lang.github.io/rust-clippy/master/index.html#same_name_method
  = note: requested on the command line with `-W clippy::same-name-method`
  = note: this warning originates in the derive macro `RustEmbed` (in Nightly builds, run with -Z macro-backtrace for more info)

warning: `rustembed-clippy` (bin "rustembed-clippy") generated 1 warning
    Finished dev [unoptimized + debuginfo] target(s) in 0.17s

It seems like one option is to add #[allow(clippy::same_name_method)] to the generated code. Maybe there's another option where we can fold the generated code into one get/iter method.

Unless we make a breaking change / major version, we can't remove the non-trait methods. I'd accept a PR that adds the allow attribute to the generated code.

Alright, I plan to submit a PR for the allow attribute shortly.


Week4

changes into mine repository

This needs to be done on your own fork, not on the upstream repository.


Use Hamcrest assertions instead of JUnit in  examples/microprofile/openapi-basics - backport 2.x (#1749)

Part of #1749
I've already signed OCA. It's an automation problem.
Original PR

/oca-checked

/trigger


Pass factory method parameters to contructor

Given the following code:
itemsDelegate.onSelect = { (item) in
            let controller = self.assembly.itemController()
            controller.stockItem = stockItem
            self.navigationController!.pushViewController(controller, animated: true)
        }

And the DI factory
public class ApplicationAssembly: DependencyFactory {

    func itemController() -> CartController {
        return scoped(CartController(nibName: "ItemView", client: warehouseClient(), assembly: self)) {
            (controller) in
            controller.title = "Ascii Warehouse"
        }
    }
}

It would be nice if it was possible to write it as follows:

```swift
let controller = self.assembly.itemController(stockItem)
self.navigationController!.pushViewController(controller, animated: true)

Where the factory method passes the stockItem param into the init method. Is this possible?

Tested - it works fine. Don't know why I thought it wouldn't.

While you technically can do this I have run into the case where another place needs access to the same object during the same request, but doesn't know which parameter to pass in. Since it will get a cached instance it doesn't really matter, but it is a bit awkward.
I don't really know how other DI systems handle this (I'm actually a DI newbie still). My gut feeling though is that DI factory methods must never take parameters as all places that call that method may not have access to the parameter.

It is a common case that you want to instantiate a class with some static dependencies wired up, along with something known only at runtime. Eg, in the example above we have a CartController with a client wired in, and then a StockItem instance known at runtime.
We can easily create a factory class that emits the instance we want.

class CartControllerFactory {

    private(set) var NetworkClient
    init (networkClient: NetworkClient) {
        self.networkClient = networkClient
    }

    func controllerWithStockItem(stockItem: StockItem) {
        return CartController(stockItem: stockItem, networkClient: networkClient)
    }
}

In Typhoon (heavier DI framework that uses the Objective-C runtime) we thought it would be nice to just use the DI assembly as such a factory, for top-level classes, to get the lower-level dependencies injected in.
Its still possible to run into the problem you described with circular dependencies - such as a controller with a custom view, and the custom view's delegate is the controller. Typhoon, for better or worse, detects and handles this.
https://github.com/appsquickly/Typhoon/wiki/Propagating-runtime-arguments#propagating-run-time-arguments-through-to-dependencies

Added a link to this lib from Typhon : https://github.com/appsquickly/Typhoon

Thank you for the vote of confidence.

Thanks for the nice lib - had fun using it.


persistence: include bundle-prefix for whitelisted classes

I tested this manually in karaf, in three ways:

started brooklyn-latest karaf, deployed an app, stopped and restarted (confirming that rebind worked)
started an older brooklyn karaf (approx 0.10.0), deployed an app, stooped and restarted brooklyn-latest
started an older brooklyn non-karaf (approx 0.10.0), deployed an app, stooped and  restarted brooklyn-latest karaf

The rebind worked fine in each case.
For (3), I also tested this with customer-specific jars (with catalog items and apps referencing those classes). On restarting the latest brooklyn, I added these jars as bundles in the catalog "libraries" section. This required a few more steps to get the upgrade working, but it confirmed that the part covered by this PR worked as expected.

LGTM. The white-list has precendece over the bundle prefixes. Serializing them in all cases is a no-op for white listed bundles. But very useful for rebind when the white-list changes.
There's a failing test:
OsgiClassPrefixerTest.testGetPrefixWithWhitelistedBundle:73->assertAbsent:104 val=Optional.of(org.apache.brooklyn.my-bundle:) expected [false] but found [true]
Good to merge after fixing the test.

Thanks @neykov - merging now.


chore: fix changelog and release v0.31.0

Codecov Report
Patch coverage has no change and project coverage change: -25.65 :warning:

Comparison is base (2a48818) 59.70% compared to head (1684795) 34.05%.

Additional details and impacted files
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##             main     #684       +/-   ##
===========================================
- Coverage   59.70%   34.05%   -25.65%
===========================================
  Files          43       43
  Lines        3474     3474
===========================================
- Hits         2074     1183      -891
- Misses       1131     2117      +986
+ Partials      269      174       -95

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Maximum function nesting level of '512' reached, aborting!

I set up the event-projector in my local environment - just for one model for testing purposes. When i create a new entry in tinker everything works fine. However - if i try it in my application i get this error:
Maximum function nesting level of '512' reached, aborting!

Any clues?

I really don't know why it's not working on my side...
My Model:
<?php

namespace Portal\Models;

use Illuminate\Database\Eloquent\Model;
use Portal\Events\AbsenceCreated;
use Portal\Events\AbsenceDeleted;
use Ramsey\Uuid\Uuid;

class Absence extends Model
{
    protected $table = 'absences';
    protected $guarded = [];
    protected $dates = ['date_start','date_end','date_of_absence'];
    /*protected $casts = [
        'date_of_absence' => 'date:Y-m-d',
    ];*/

    public static function createWithAttributes(array $attributes): Absence
    {
        /*
         * Let's generate a uuid.
         */
        //dd($attributes);
        $attributes['uuid'] = (string) Uuid::uuid4();

        /*
         * The account will be created inside this event using the generated uuid.
         */
        event(new AbsenceCreated($attributes));

        /*
         * The uuid will be used the retrieve the created account.
         */
        return static::uuid($attributes['uuid']);
    }

    public function remove()
    {
        event(new AbsenceDeleted($this->uuid));
    }

    public static function uuid(string $uuid): ?Absence
    {
        return static::where('uuid', $uuid)->first();
    }
}

The Projector:

class AbsenceProjector implements Projector
{
    use ProjectsEvents;

    /*
     * Here you can specify which event should trigger which method.
     */
    protected $handlesEvents = [
        AbsenceCreated::class => 'onAbsenceCreated',
        AbsenceDeleted::class => 'onAbsenceDeleted',
    ];

    public function onAbsenceCreated(AbsenceCreated $event)
    {
        Absence::create($event->absenceAttributes);
    }

    public function onAbsenceDeleted(AbsenceDeleted $event)
    {
        Absence::uuid($event->absenceUuid)->delete();
    }
}

The Event:

class AbsenceCreated implements ShouldBeStored
{
    /** @var array */
    public $absenceAttributes;

    public function __construct(array $absenceAttributes)
    {
        $this->absenceAttributes = $absenceAttributes;
    }
}

In MY Controller:
```
$date_start = Carbon::createFromFormat('Y-m-d',$request->get('date_start'));
$date_end = Carbon::createFromFormat('Y-m-d',$request->get('date_end'));
    $date_start2 = clone $date_start;
    //parse through days of month
    $dates = [];
    while ($date_start->lte($date_end)) {
        $dates[] = $date_start->copy();
        $date_start->addDay();
    }

foreach ($dates as $date) {
..... some other logic....
if (Absence::createWithAttributes([
'user_id'           => $request->get('user_id'),
'date_of_absence'   => $date,  // it work's with $date->format('Y-m-d')
'date_start'        => $date_start2->format('Y-m-d'),
'date_end'          => $date_end->format('Y-m-d'),
'absence_type'      => $request->get('absence_type'),
'comment'           => $request->get('comment'),
'state'             => $approved,
'approver'          => $approver
])) $ok = true;
}

Hi jetwes, did you solve the problem?
I'm running in a similar problem with dates columns...

I'd be happy to take a look at it if either one of you could set up a demo repo.

Unfortunately i hadn't the time in the last weeks to investiagte further - so i stopped using the package for the moment...

I'd be happy to take a look at it if either one of you could set up a demo repo.

I guess the problem is in the serialization/deserialization. I opened another issue here: https://github.com/spatie/laravel-event-projector/issues/126
but I guess it's all the same story


[Doc] add "Expect:100-continue" to stream load

Signed-off-by: amber-create<EMAIL_ADDRESS>Fixes #issue

@mergify backport branch-2.3 branch-2.4 branch-2.5 branch-3.0


feat: fix changes to bottom countries, remove zoom on world map

Cool, should I go ahead and merge it?


fix: scaling pdfs with action max/min

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


browser: Send a more truthful User-Agent header

This one I'm not too sure about. I think it might actually make sense to just mimic the Firefox ESR UA string (for privacy reasons) unless the browser ends up supporting features that don't exist in the other big browsers, or if it's missing support for big features the other ones have.

Yeah, I agree that this is worse for fingerprint-privacy, even if Hastur's probably pretty fingerprintable right now anyway due to the few headers we send and things like what we don't load and the lack of TCP-pipelining.
Let's hold off on merging something like this for now and make the UA-header settable from e.g. a .hasturrc and/or the GUI in the future.


STYLE: Improve ivar printing in itk::ProcessObject PrintSelf method

Improve ivar printing in itk::ProcessObject PrintSelf method:

Print the member variable names verbatim to conform to the ITK SW Guide.
Avoid printing data other than ivars (e.g. values obtained through Get methods).

PR Checklist

[X] No API changes were made (or the changes have been approved)
[X] No major design changes were made (or the changes have been approved)

By no means this PR intends to be comprehensive; I just identified these cases while investigating the error in https://github.com/InsightSoftwareConsortium/ITK/pull/3908#issuecomment-2207685811.

/azp run ITK.Windows


ScheduledTask: Get-ScheduledTask function name clash with Carbon module

Details of the scenario you tried and the problem that is occurring
We're using DSC resources from both ComputerManagementDsc and Carbon modules.
Carbon implements Get-ScheduledTask function, which is missing the -TaskPath parameter. Functions from ScheduledTask DSC resource call Get-ScheduledTask without importing ScheduledTasks modules, or calling the function using the module name (i.e. ScheduledTasks\Get-ScheduledTask)
This makes it impossible to use or even have installed both modules on the same machine.
Suggested solution to the issue
While this issue might be better addressed in Carbon, it doesn't really hurt making ScheduledTask code more specific about which Get-ScheduledTask function it's using.
We could either make the code explicitly import the ScheduledTasks module, or use the "long" form to call overlapping functions (I think it's just `Get-ScheduledTask, but I can review)
I'd be happy to submit a patch.
The DSC configuration that is used to reproduce the issue (as detailed as possible)
# insert configuration here

The operating system the target node is running

OsName               : Microsoft Windows Server 2016 Standard
OsOperatingSystemSKU : StandardServerEdition
OsArchitecture       : 64-bit
WindowsBuildLabEx    : 14393.3024.amd64fre.rs1_release.190530-2002
OsLanguage           : en-US
OsMuiLanguages       : {en-US}

Version and build of PowerShell the target node is running

Name                           Value
----                           -----
PSVersion                      5.1.14393.2969
PSEdition                      Desktop
PSCompatibleVersions           {1.0, 2.0, 3.0, 4.0...}
BuildVersion                   10.0.14393.2969
CLRVersion                     4.0.30319.42000
WSManStackVersion              3.0
PSRemotingProtocolVersion      2.3
SerializationVersion           <IP_ADDRESS>

Version of the DSC module that was used ('dev' if using current dev branch)
<IP_ADDRESS>

Hi @bozho - thanks for raising this. Would be happy to accept a PR with the change of adding the module name to the function name call (e.g. ScheduledTasks\Get-ScheduledTask).


attach snapshot feature & dynamic vmdk file

use latest vmdk file rather than 000001.vmdk file
it can clone live snapshot

Looks really nice, thank you!


Update create-trigger.md

closes #14762

There still is no Triggers tab as stated in the doc on the page: Zaraz > Tools Configuration. See attached screenshot.


Not working with virtualbox 5.2 (latest in ubuntu package)

Hey,
we receive an update of Virtualbox on ubuntu package VirtualBox Version 5.2.18_Ubuntu r123745. But it seems this plugin doesn't work with VirtualBox 5.2. Here is the error:
There was an error while executing VBoxManage, a CLI used by Vagrant
for controlling VirtualBox. The command and stderr is shown below.
Command: ["clonemedium", "/*****/VirtualBox VMs"/*****/ubuntu-xenial-16.04-cloudimg.vmdk", "/*****/VirtualBox VMs/*****/ubuntu-xenial-16.04-cloudimg.vdi", "--format", "VDI"]

Stderr: VBoxManage: error: UUID {b85d6f69-494b-484a-8ae3-e88f9767d605} of the medium '/*****/VirtualBox VMs/*****/ubuntu-xenial-16.04-cloudimg.vmdk' does not match the value {8b6ab839-6848-4f96-8309-4ad89b452485} stored in the media registry ('/*****/.config/VirtualBox/VirtualBox.xml')
VBoxManage: error: Details: code NS_ERROR_FAILURE (0x80004005), component MediumWrap, interface IMedium, callee nsISupports
VBoxManage: error: Context: "CloneTo(pDstMedium, ComSafeArrayAsInParam(l_variants), NULL, pProgress.asOutParam())" at line 987 of file VBoxManageDisk.cpp

Any idea on this ?

I have uninstall Virtualbox from package and install it from the website .deb (https://www.virtualbox.org/wiki/Downloads). -> Version 5.2.22 r126460.
I also uninstall vagrant-disksize plugin and reinstall it.
Seems to work now, no error when resize disk.
Note: Vagrant 2.2.1

I will close this and hope if someone has the same issue can use my workaround/solution.
Cheers!


Minor Fixes

[x] Make some of the fields have a drop down instead of text field in Add staff. So we don't have weird entries in db

[x] Fetching data for the chart in dashboard

[ ] In edit entries, approve disapprove page put the links in anchor tag so they can click and view their uploads

[x] Infinite post requests firing in dashboard

[x] make changes to the upload function so the files are renamed appropriately

[x] Profile picture being either a jpg or png not both in dashboard (taken up by @programmingMohit )

Profile picture fix has been dealt in a different manner in #66


Added deprecated decorator

Sending deprecation warnings to frontend
Implemented deprecation in documentation
Added manual to CONTRIBUTING.md

Requires https://github.com/equinor/webviz-core-components/pull/114 to be taken in.


add haxsite repo into ubiquity

This can allow building and distribution with stackblitz + github account so you can create new sites without installing anything and it's kept in version control!

needs to be run through twig tho  or will lack some defaults so its not a normal ubiquity call

not needed


Update version: KeeWeb.KeeWeb version 1.18.7

Pull request has been created with WinGet Automation :rocket:
Microsoft Reviewers: codeflow:open?pullrequest=https://github.com/microsoft/winget-pkgs/pull/115051&drop=dogfoodAlpha

@wingetbot run


docs: Add webhook batching and update retry

@EnriqueL8 It looks like there is a broken link in the docs which the linter is complaining about:
For the Links > Internal check, the following failures were found:

* At ./_site/reference/types/subscription.html:623:

  internally linking to #SubscriptionOptions; the file exists, but the hash 'SubscriptionOptions' does not

Closing this PR due to inactivity. Please feel free to re-open if this work is still ongoing.


Setup js pipeline with compressor

At a minimum I'd like to be able to use ES6 features in the source, so that will require a transpiler in addition to minification.
It might be overkill, but TypeScript could be nice too.
It looks like this plugin actually handles both the scss and ES6 js together, which could be a nice drop-in solution going forward.

this is technically a blocker for #66 since I don't really wanna start writing JS in earnest without a good setup. gonna take a crack at implementing django-compressor-toolkit linked above.

@thatbudakguy Do let me know when you've configured this. There look like a lot of new npm dependencies which will need to be mirrored onto QA and PROD (and tested to make sure they're there correctly).

@bwhicks the way I'm implementing this is just including a package.json and lockfile so that you can install all the js dependencies in one step with npm install. compressor will look for the dependencies in node_modules local to the project folder (or, if it's easier, we could configure it to look anywhere else on the system in prod only). does that sound OK?

@thatbudakguy This may complicate things. I'll need to check the SELinux configs since we've never managed our own node_modules before. It seems like the most practical way to handle things though (npm dependencies had been managed globally but this looks like it would work better as part of the build cycle). Go ahead and configure that way, and let me sort out the sanest path for deploys. Thanks!


SQLITE_TOOBIG since upgrad to java 21 and <IP_ADDRESS>

Hi everyone,
in our project we have struggles since we've upgraded our versions.
We've upgraded the sqlite-jdbc from 3.28.0 to <IP_ADDRESS> and the Java Version from 1.8 to 21.
Since this upgrade we are getting the following errors:
Cause: org.sqlite.SQLiteException: [SQLITE_TOOBIG] String or BLOB exceeds size limit (statement too long)
With the versions 3.28.0 and 1.8 the same sql statement is working. May someone know why this is not working anymore?
Thanks!
Best
Andreas

Sorry my fault, I meant version <IP_ADDRESS> :)
Ok thanks for the fast answer! We will have a look on the limits.
Best Andreas


Error building minified bundle in react app

I received an error after updating to query-string: v6.0.0
I'm using it in a frontend app, based on create-react-app (react v16+ not ejected, chrome)
$ react-scripts build
Creating an optimized production build...
Failed to compile.

Failed to minify the code from this file:

 	./node_modules/query-string/index.js:8

Read more here: http://bit.ly/2tRViJ9

https://github.com/sindresorhus/query-string/releases/tag/v6.0.0

Have to revert back to 5.1.0 to make bundling with work

@sindresorhus would you be open to a PR that uses Babel to compile index.js to ES5 before packaging and submitting to NPM?
This change breaks our use of query-string in a browser environment unless we change our webpack config to compile all node_modules JS files, which would slow down our build times dramatically. Having a babel-compiled version that is used in the NPM bundle would solve this issue for us, while allowing you to keep using the new features like const and arrow functions in the source file.

I am not. Just stay on version 5 if you need it. This module is mature and stable and will probably not change much.


Mentee API - Edit mentee application

Is your feature request related to a problem? Please describe.
We need a mentee endpoint to edit mentee application
Describe the solution you'd like
Documentation: https://documenter.getpostman.com/view/8545501/T1LLFTrx?version=latest#dec99bfb-5ed0-46fe-a961-35a24a783b20
Describe alternatives you've considered
N/A
Additional context
N/A

I'm working on this

Passed on the work to @YohanAvishke


Includes Testing Script and Connection Fixes

Thanks Bala. This is great feedback - I'll go ahead and merge this in and make the changes in the next PR.


Potential window calculation bug in 0.11.0

Bevy version
0.11.0
[Optional] Relevant system information
AdapterInfo { name: "NVIDIA GeForce RTX 4090", ven
dor: 4318, device: 9860, device_type: DiscreteGpu, driver: "NVIDIA", driver_info: "536.67", backend: Vulkan }

What you did
Working on asteroid clone.  When spawning the asteroids I notice that they were not spawning inside the primary window dimensions but instead inside the monitors dimensions
What went wrong
Expectation

Spawn 4 asteroids inside the primary window

Actual

Spawned 4 asteroids inside the monitor's space

Additional information
spawn function
fn spawn_enemies(
    mut commands: Commands,
    window_query: Query<&Window, With<PrimaryWindow>>,
    asset_server: Res<AssetServer>
) {
    let window = window_query.get_single().unwrap();

    for i in 0..INIT_ENEMY_COUNT {
        println!("random: {}", random::<f32>());
        let random_x = random::<f32>() * window.width();
        let random_y = random::<f32>() * window.height();

        println!("asteroid {} x {} < {}", i, random_x, window.width());
        println!("asteroid {} y {} < {}", i, random_y, window.height());

        commands.spawn(
        (
                SpriteBundle {
                    transform: Transform::from_xyz(random_x, random_y, 0.0),
                    texture: asset_server.load("sprites/astroid/astroid_1.png"),
                    ..default()
                },
                Asteroid {
                    direction: Vec2::new(random::<f32>(), random::<f32>()).normalize()
                }
            )
        );
    }
}

Logs
random: 0.6633456
asteroid 0 x 1127.3723 < 1280
asteroid 0 y 677.8708 < 720
random: 0.21800572
asteroid 1 x 1112.581 < 1280
asteroid 1 y 310.15686 < 720
random: 0.43018222
asteroid 2 x 684.5423 < 1280
asteroid 2 y 597.50165 < 720
random: 0.89251626
asteroid 3 x 478.23364 < 1280
asteroid 3 y 611.35547 < 720

Window size at startup

Full monitor view

I guess I'm not following.  When I read window I assume the actual display window.  In the case above is 720x1280 and all the random values I'm generating are with in those values but when working they are spawned based on the monitor resolution not the window resolution

Let's take your example and change INIT_ENEMY_COUNT to 10000.

You're spawning enemies in the range of 0..1280, 0..720 which is a rectangle the size of the window, but the camera is showing -640..640,-360..360 because the origin is at 0.0, 0.0.
You can make this small change to your code to spawn the enemies in the right area.
let random_x = random::<f32>() * window.width() - window.width() / 2.;
let random_y = random::<f32>() * window.height() - window.height() / 2.;

Oh I got you now.   Thank you for taking the time.  I'm just getting into this stuff and want to understand what's going on over just blunt forcing my way through it.  Thank you again for taking the time

Happy to help!


leViT problem？

Describe the bug
def get_attention_biases(self, , device: torch.device) -> torch.Tensor:
if self.training:
return self.attention_biases[:, self.attention_bias_idxs]
after self.attention_biases[:, self.attention_bias_idxs], the result that the size in each head is same as self.attention_bias_idxs is all zero instead of the content of self.attention_bias_idxs.
Expected behavior
I think return self.attention_biases[:, self.attention_bias_idxs] + self.attention_bias_idxs can make each head have relative distance which is same as the content of self.attention_bias_idxs.

not sure what your issue is, the attention biases are learned parameters and the indices are used to gather them into the shape matching attention, I'd recommend asking the authors in the original github if you have further questions


My first revup bar

Topic: bar

Reviews in this chain:
└https://github.com/josh-dewitt-skydio/revup/pull/2 My first revup bar

#
head
base
diff
date
summary

0
09da14ca
aadd1ceb
diff
Aug 2 11:35 AM
1 file changed, 1 insertion(+)


Diplay:None

Hi, I'm trying to use the plugin with a music player in a iframe. There is a method to make the content remains visible once you close the menu (without using display: none).

Please paste your code.


Axis labels in plots generated by ssm vignette have excessively large fonts

When I knit the ssm tutorial many plots have axis labels fonts that are so large they obscure each other and/or mess up the plot dimensions.

utilities.Rmd is also affected


Guietta :ValueError: Could not determine the Gui instance identifier

Python version used : 3.7
kindly help to resolve this issue.
script :
from guietta import _, Gui, Quit
gui = Gui(
[ 'Enter numbers:', 'a' , '+' , 'b', ['Calculate'] ],
[ 'Result: -->' , 'result' , _ , _ , _ ],
[ _ , _ , _ , _ , Quit ]
)
with gui.Calculate:
gui.result = gui.a + gui.b
gui.run()
Error:
C:\Users\labuser\Downloads\temp>python cguietta.py
Traceback (most recent call last):
File "cguietta.py", line 11, in
gui.result = gui.a + gui.b
File "C:\Users\labuser\AppData\Local\Programs\Python\Python37\lib\site-packages\guietta\guietta.py", line 159, in exit
raise ValueError('Could not determine the Gui instance identifier')
ValueError: Could not determine the Gui instance identifier
C:\Users\labuser\Downloads\temp>

Hello, this bug should be fixed in version 0.3.8. Please try to upgrade to that version and see if it works

Wow !! That was a quick Fix . .  Really Appreciate it  ..
Thank you ..

also, i was looking for documentation. i wanted to set the title for gui window.
if you can let me know , where i can find documentation for guietta, it would be helpful

The documentation is at https://guietta.readthedocs.io/en/stable/index.html
You can set the title, but it's a bit hidden in the documentation :) Have a look at the Gui class definition here: https://guietta.readthedocs.io/en/stable/reference.html#gui-class-reference  you can add a title='mytitle' keyword argument.

got the "title" working . . Thanks for your help and Guidance . .