PrioGraph::clear

Problem

We have top-level allocations for our nodes, locks, and main queue
Everytime we create a new prio_graph, these allocations start off with a capacity of 0
Re-sizing these top-level containers can be expensive

Solution

Allow the prio_graph to be re-usable by adding a clear method
Update benchmark to use insert, make_natural_batches, clear approach

Comparing against #71 @ 6a91ce9.
In most cases the time was significantly reduced.
There are a few outliers where performance regressed up to 15%.
I think overall the change makes sense - re-use our allocations as much as possible.

Benchmark Results
no_conflict_100_2       time:   [4.2075 µs 4.2262 µs 4.2436 µs]
                        change: [-45.139% -44.931% -44.726%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
  10 (10.00%) high mild

no_conflict_100_16      time:   [16.424 µs 16.435 µs 16.449 µs]
                        change: [-53.456% -52.873% -52.295%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
  1 (1.00%) low mild
  4 (4.00%) high mild
  3 (3.00%) high severe

no_conflict_100_32      time:   [31.091 µs 31.126 µs 31.167 µs]
                        change: [-52.664% -52.034% -51.412%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  1 (1.00%) low severe
  5 (5.00%) high mild
  6 (6.00%) high severe

no_conflict_100_64      time:   [60.311 µs 60.585 µs 60.951 µs]
                        change: [-52.788% -51.808% -50.747%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high mild

no_conflict_100_128     time:   [115.63 µs 115.70 µs 115.76 µs]
                        change: [-63.100% -62.910% -62.733%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
  2 (2.00%) high mild
  3 (3.00%) high severe

no_conflict_100_256     time:   [236.83 µs 236.93 µs 237.06 µs]
                        change: [-63.524% -63.178% -62.841%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 18 outliers among 100 measurements (18.00%)
  8 (8.00%) low severe
  1 (1.00%) low mild
  2 (2.00%) high mild
  7 (7.00%) high severe

no_conflict_1000_2      time:   [47.378 µs 47.407 µs 47.444 µs]
                        change: [-55.727% -55.454% -55.201%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  5 (5.00%) high mild
  7 (7.00%) high severe

no_conflict_1000_16     time:   [179.88 µs 183.25 µs 186.28 µs]
                        change: [-70.795% -70.396% -70.002%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 20 outliers among 100 measurements (20.00%)
  1 (1.00%) high mild
  19 (19.00%) high severe

no_conflict_1000_32     time:   [335.85 µs 336.61 µs 337.53 µs]
                        change: [-70.469% -70.203% -69.965%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
  6 (6.00%) high mild
  5 (5.00%) high severe

no_conflict_1000_64     time:   [661.19 µs 663.23 µs 665.41 µs]
                        change: [-66.079% -65.826% -65.586%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
  5 (5.00%) high mild
  3 (3.00%) high severe

no_conflict_1000_128    time:   [1.7057 ms 1.7325 ms 1.7642 ms]
                        change: [-53.721% -53.119% -52.548%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 15 outliers among 100 measurements (15.00%)
  8 (8.00%) high mild
  7 (7.00%) high severe

no_conflict_1000_256    time:   [4.0275 ms 4.0529 ms 4.0799 ms]
                        change: [-57.450% -57.104% -56.740%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
  2 (2.00%) high mild

no_conflict_10000_2     time:   [667.64 µs 669.39 µs 671.66 µs]
                        change: [-42.861% -42.184% -41.458%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
  2 (2.00%) high mild
  7 (7.00%) high severe

no_conflict_10000_16    time:   [2.7641 ms 2.7737 ms 2.7845 ms]
                        change: [-44.435% -44.149% -43.849%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  1 (1.00%) high mild
  5 (5.00%) high severe

no_conflict_10000_32    time:   [5.8236 ms 5.8644 ms 5.9090 ms]
                        change: [-49.101% -48.703% -48.260%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
  2 (2.00%) high mild
  1 (1.00%) high severe

no_conflict_10000_64    time:   [17.571 ms 17.706 ms 17.863 ms]
                        change: [-32.929% -32.317% -31.674%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  1 (1.00%) low mild
  2 (2.00%) high mild
  3 (3.00%) high severe

no_conflict_10000_128   time:   [38.686 ms 38.814 ms 38.988 ms]
                        change: [-34.164% -33.850% -33.500%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  2 (2.00%) high mild
  4 (4.00%) high severe

no_conflict_10000_256   time:   [84.018 ms 84.987 ms 86.062 ms]
                        change: [-35.330% -34.373% -33.373%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 15 outliers among 100 measurements (15.00%)
  7 (7.00%) high mild
  8 (8.00%) high severe

all_conflict_100_2      time:   [13.971 µs 14.000 µs 14.034 µs]
                        change: [-8.5437% -8.1532% -7.7779%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
  6 (6.00%) high mild
  5 (5.00%) high severe

all_conflict_100_16     time:   [48.768 µs 48.973 µs 49.175 µs]
                        change: [-1.2657% -0.8557% -0.4217%] (p = 0.00 < 0.05)
                        Change within noise threshold.
Found 7 outliers among 100 measurements (7.00%)
  6 (6.00%) high mild
  1 (1.00%) high severe

all_conflict_100_32     time:   [88.211 µs 88.461 µs 88.722 µs]
                        change: [+0.3351% +0.6378% +0.9814%] (p = 0.00 < 0.05)
                        Change within noise threshold.
Found 13 outliers among 100 measurements (13.00%)
  9 (9.00%) high mild
  4 (4.00%) high severe

all_conflict_100_64     time:   [170.71 µs 171.09 µs 171.55 µs]
                        change: [+4.1684% +4.4411% +4.7111%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 10 outliers among 100 measurements (10.00%)
  4 (4.00%) high mild
  6 (6.00%) high severe

all_conflict_100_128    time:   [333.38 µs 334.56 µs 335.91 µs]
                        change: [+4.5143% +4.8641% +5.1848%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 3 outliers among 100 measurements (3.00%)
  3 (3.00%) high mild

all_conflict_100_256    time:   [646.07 µs 650.33 µs 655.90 µs]
                        change: [+8.3938% +10.034% +11.904%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high severe

all_conflict_1000_2     time:   [131.15 µs 131.30 µs 131.46 µs]
                        change: [-10.113% -9.7546% -9.3775%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high mild

all_conflict_1000_16    time:   [478.89 µs 480.48 µs 482.19 µs]
                        change: [-0.3434% +0.0921% +0.4840%] (p = 0.67 > 0.05)
                        No change in performance detected.
Found 5 outliers among 100 measurements (5.00%)
  3 (3.00%) high mild
  2 (2.00%) high severe

all_conflict_1000_32    time:   [868.44 µs 869.25 µs 870.13 µs]
                        change: [+0.8347% +1.1074% +1.3915%] (p = 0.00 < 0.05)
                        Change within noise threshold.
Found 7 outliers among 100 measurements (7.00%)
  4 (4.00%) high mild
  3 (3.00%) high severe

all_conflict_1000_64    time:   [1.6525 ms 1.6539 ms 1.6552 ms]
                        change: [+1.8926% +2.2196% +2.5159%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 4 outliers among 100 measurements (4.00%)
  1 (1.00%) high mild
  3 (3.00%) high severe

all_conflict_1000_128   time:   [3.5728 ms 3.6045 ms 3.6344 ms]
                        change: [+13.392% +14.386% +15.313%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 19 outliers among 100 measurements (19.00%)
  15 (15.00%) low severe
  4 (4.00%) low mild

all_conflict_1000_256   time:   [6.3360 ms 6.3634 ms 6.3963 ms]
                        change: [+3.4764% +3.9628% +4.4702%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 5 outliers among 100 measurements (5.00%)
  2 (2.00%) high mild
  3 (3.00%) high severe

all_conflict_10000_2    time:   [1.3373 ms 1.3420 ms 1.3469 ms]
                        change: [-13.524% -13.075% -12.574%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
  1 (1.00%) low mild
  5 (5.00%) high mild
  8 (8.00%) high severe

all_conflict_10000_16   time:   [4.8152 ms 4.8244 ms 4.8342 ms]
                        change: [-1.3816% -1.0788% -0.7725%] (p = 0.00 < 0.05)
                        Change within noise threshold.
Found 4 outliers among 100 measurements (4.00%)
  4 (4.00%) high mild

all_conflict_10000_32   time:   [8.7728 ms 8.7954 ms 8.8203 ms]
                        change: [+0.9330% +1.2252% +1.5443%] (p = 0.00 < 0.05)
                        Change within noise threshold.
Found 17 outliers among 100 measurements (17.00%)
  4 (4.00%) low mild
  3 (3.00%) high mild
  10 (10.00%) high severe

all_conflict_10000_64   time:   [16.718 ms 16.744 ms 16.773 ms]
                        change: [+3.3660% +3.6064% +3.8340%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 9 outliers among 100 measurements (9.00%)
  1 (1.00%) high mild
  8 (8.00%) high severe

all_conflict_10000_128  time:   [33.295 ms 33.331 ms 33.367 ms]
                        change: [+4.5857% +4.7951% +4.9942%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 12 outliers among 100 measurements (12.00%)
  4 (4.00%) low mild
  7 (7.00%) high mild
  1 (1.00%) high severe

all_conflict_10000_256  time:   [64.496 ms 64.684 ms 64.903 ms]
                        change: [+4.6279% +4.9755% +5.3577%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 17 outliers among 100 measurements (17.00%)
  7 (7.00%) low mild
  3 (3.00%) high mild
  7 (7.00%) high severe

tree_100_4_16           time:   [48.282 µs 48.379 µs 48.523 µs]
                        change: [-3.9253% -3.6630% -3.4082%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
  3 (3.00%) high mild
  2 (2.00%) high severe

tree_100_8_16           time:   [46.746 µs 46.815 µs 46.898 µs]
                        change: [-8.1814% -7.9272% -7.6788%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
  6 (6.00%) high mild
  7 (7.00%) high severe

tree_100_4_64           time:   [163.96 µs 164.23 µs 164.50 µs]
                        change: [+0.0610% +0.3218% +0.6105%] (p = 0.01 < 0.05)
                        Change within noise threshold.
Found 5 outliers among 100 measurements (5.00%)
  3 (3.00%) high mild
  2 (2.00%) high severe

tree_100_8_64           time:   [188.94 µs 196.16 µs 203.86 µs]
                        change: [+15.684% +18.045% +20.377%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 18 outliers among 100 measurements (18.00%)
  15 (15.00%) low severe
  1 (1.00%) low mild
  1 (1.00%) high mild
  1 (1.00%) high severe

tree_100_4_128          time:   [323.39 µs 323.58 µs 323.80 µs]
                        change: [+1.2920% +1.5190% +1.7601%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 15 outliers among 100 measurements (15.00%)
  1 (1.00%) low mild
  6 (6.00%) high mild
  8 (8.00%) high severe

tree_100_8_128          time:   [333.59 µs 337.75 µs 341.09 µs]
                        change: [-6.6083% -5.4244% -3.9899%] (p = 0.00 < 0.05)
                        Performance has improved.

tree_1000_4_16          time:   [494.49 µs 495.65 µs 496.89 µs]
                        change: [-2.2273% -1.9373% -1.6610%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high mild

tree_1000_8_16          time:   [490.12 µs 490.80 µs 491.62 µs]
                        change: [-3.9438% -3.5361% -3.0780%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 16 outliers among 100 measurements (16.00%)
  5 (5.00%) high mild
  11 (11.00%) high severe

tree_1000_4_64          time:   [1.6695 ms 1.6730 ms 1.6767 ms]
                        change: [-0.6876% -0.3604% -0.0062%] (p = 0.04 < 0.05)
                        Change within noise threshold.
Found 10 outliers among 100 measurements (10.00%)
  3 (3.00%) high mild
  7 (7.00%) high severe

tree_1000_8_64          time:   [1.8437 ms 1.8693 ms 1.8943 ms]
                        change: [+10.013% +11.619% +13.191%] (p = 0.00 < 0.05)
                        Performance has regressed.

tree_1000_4_128         time:   [3.3615 ms 3.3721 ms 3.3840 ms]
                        change: [+3.1254% +3.5111% +3.9389%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 19 outliers among 100 measurements (19.00%)
  6 (6.00%) high mild
  13 (13.00%) high severe

tree_1000_8_128         time:   [3.3183 ms 3.3227 ms 3.3277 ms]
                        change: [+2.8934% +3.0590% +3.2350%] (p = 0.00 < 0.05)
                        Performance has regressed.
Found 13 outliers among 100 measurements (13.00%)
  10 (10.00%) high mild
  3 (3.00%) high severe

random_access_100_2_2   time:   [14.982 µs 15.039 µs 15.093 µs]
                        change: [-5.0659% -4.2588% -3.4368%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high mild

random_access_100_100_2 time:   [12.604 µs 12.623 µs 12.643 µs]
                        change: [-11.589% -11.322% -11.067%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
  1 (1.00%) low severe
  5 (5.00%) high mild
  2 (2.00%) high severe

random_access_100_100_16
                        time:   [85.931 µs 86.051 µs 86.191 µs]
                        change: [-4.9047% -4.4878% -4.0850%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
  4 (4.00%) low mild
  5 (5.00%) high mild
  5 (5.00%) high severe

random_access_100_100_32
                        time:   [121.36 µs 121.49 µs 121.64 µs]
                        change: [-7.2392% -7.0152% -6.7805%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
  1 (1.00%) high mild
  1 (1.00%) high severe

random_access_100_100_64
                        time:   [200.50 µs 200.69 µs 200.92 µs]
                        change: [+0.8265% +1.1292% +1.4004%] (p = 0.00 < 0.05)
                        Change within noise threshold.
Found 11 outliers among 100 measurements (11.00%)
  1 (1.00%) high mild
  10 (10.00%) high severe

random_access_100_1000_2
                        time:   [5.8438 µs 5.8574 µs 5.8736 µs]
                        change: [-38.520% -38.328% -38.131%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  3 (3.00%) low mild
  7 (7.00%) high mild
  2 (2.00%) high severe

random_access_100_1000_16
                        time:   [54.511 µs 54.610 µs 54.709 µs]
                        change: [-18.925% -18.720% -18.472%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
  3 (3.00%) high mild
  2 (2.00%) high severe

random_access_100_1000_32
                        time:   [127.16 µs 127.48 µs 127.85 µs]
                        change: [-16.596% -15.779% -15.073%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
  6 (6.00%) high mild
  3 (3.00%) high severe

random_access_100_1000_64
                        time:   [280.96 µs 288.41 µs 297.45 µs]
                        change: [+6.1290% +8.8936% +11.284%] (p = 0.00 < 0.05)
                        Performance has regressed.

random_access_100_1000_128
                        time:   [429.10 µs 429.24 µs 429.42 µs]
                        change: [-6.6527% -6.2971% -5.9427%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
  4 (4.00%) low mild
  1 (1.00%) high mild
  8 (8.00%) high severe

random_access_100_1000_256
                        time:   [770.96 µs 774.24 µs 777.93 µs]
                        change: [-2.9851% -2.5112% -1.9935%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
  2 (2.00%) high mild
  11 (11.00%) high severe

random_access_100_10000_2
                        time:   [4.3391 µs 4.3615 µs 4.3833 µs]
                        change: [-45.789% -45.625% -45.438%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 23 outliers among 100 measurements (23.00%)
  8 (8.00%) high mild
  15 (15.00%) high severe

random_access_100_10000_16
                        time:   [23.803 µs 23.826 µs 23.853 µs]
                        change: [-55.258% -53.965% -52.566%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
  4 (4.00%) high mild
  9 (9.00%) high severe

random_access_100_10000_32
                        time:   [54.311 µs 54.452 µs 54.633 µs]
                        change: [-51.014% -50.698% -50.396%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 15 outliers among 100 measurements (15.00%)
  3 (3.00%) low mild
  6 (6.00%) high mild
  6 (6.00%) high severe

random_access_100_10000_64
                        time:   [139.40 µs 139.56 µs 139.72 µs]
                        change: [-43.063% -42.756% -42.478%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
  1 (1.00%) high mild
  3 (3.00%) high severe

random_access_100_10000_128
                        time:   [367.75 µs 368.22 µs 368.77 µs]
                        change: [-41.312% -40.625% -39.854%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  5 (5.00%) high mild
  7 (7.00%) high severe

random_access_100_10000_256
                        time:   [782.06 µs 782.82 µs 783.64 µs]
                        change: [-22.880% -22.111% -21.313%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
  1 (1.00%) low mild
  7 (7.00%) high mild
  6 (6.00%) high severe

random_access_1000_2_2  time:   [132.51 µs 133.17 µs 133.76 µs]
                        change: [-12.787% -12.223% -11.676%] (p = 0.00 < 0.05)
                        Performance has improved.

random_access_1000_100_2
                        time:   [159.21 µs 159.54 µs 159.93 µs]
                        change: [-10.732% -10.436% -10.117%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 29 outliers among 100 measurements (29.00%)
  22 (22.00%) low mild
  3 (3.00%) high mild
  4 (4.00%) high severe

random_access_1000_100_16
                        time:   [898.93 µs 899.69 µs 900.45 µs]
                        change: [-8.2894% -7.8964% -7.5945%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
  4 (4.00%) high mild
  3 (3.00%) high severe

random_access_1000_100_32
                        time:   [1.2328 ms 1.2356 ms 1.2388 ms]
                        change: [-10.850% -10.607% -10.373%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
  3 (3.00%) high mild
  4 (4.00%) high severe

random_access_1000_100_64
                        time:   [1.8798 ms 1.8814 ms 1.8831 ms]
                        change: [-9.8333% -9.5731% -9.3192%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
  5 (5.00%) high mild
  2 (2.00%) high severe

random_access_1000_1000_2
                        time:   [132.61 µs 132.83 µs 133.09 µs]
                        change: [-18.019% -17.473% -17.006%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
  8 (8.00%) high mild

random_access_1000_1000_16
                        time:   [780.73 µs 781.88 µs 783.11 µs]
                        change: [-11.402% -11.014% -10.617%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
  1 (1.00%) high mild
  3 (3.00%) high severe

random_access_1000_1000_32
                        time:   [1.5226 ms 1.5249 ms 1.5273 ms]
                        change: [-7.4767% -7.1829% -6.8503%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
  4 (4.00%) high mild
  6 (6.00%) high severe

random_access_1000_1000_64
                        time:   [2.9351 ms 2.9387 ms 2.9428 ms]
                        change: [-6.6150% -6.4771% -6.3182%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  2 (2.00%) low mild
  3 (3.00%) high mild
  7 (7.00%) high severe

random_access_1000_1000_128
                        time:   [4.4555 ms 4.4628 ms 4.4711 ms]
                        change: [-9.3080% -9.1333% -8.9381%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  2 (2.00%) high mild
  10 (10.00%) high severe

random_access_1000_1000_256
                        time:   [7.4753 ms 7.4806 ms 7.4866 ms]
                        change: [-11.127% -10.989% -10.853%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
  6 (6.00%) high mild
  2 (2.00%) high severe

random_access_1000_10000_2
                        time:   [64.192 µs 64.229 µs 64.273 µs]
                        change: [-57.094% -56.856% -56.624%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  2 (2.00%) high mild
  4 (4.00%) high severe

random_access_1000_10000_16
                        time:   [614.85 µs 615.49 µs 616.26 µs]
                        change: [-22.062% -21.231% -20.423%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  2 (2.00%) high mild
  4 (4.00%) high severe

random_access_1000_10000_32
                        time:   [1.3060 ms 1.3084 ms 1.3107 ms]
                        change: [-16.518% -16.168% -15.821%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
  2 (2.00%) high mild
  3 (3.00%) high severe

random_access_1000_10000_64
                        time:   [2.6505 ms 2.6549 ms 2.6603 ms]
                        change: [-8.2887% -8.0388% -7.7842%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  3 (3.00%) high mild
  3 (3.00%) high severe

random_access_1000_10000_128
                        time:   [5.6220 ms 5.6302 ms 5.6397 ms]
                        change: [-8.0551% -7.7778% -7.4791%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  2 (2.00%) high mild
  4 (4.00%) high severe

random_access_1000_10000_256
                        time:   [10.536 ms 10.565 ms 10.604 ms]
                        change: [-7.1500% -6.8285% -6.4562%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
  1 (1.00%) high mild
  6 (6.00%) high severe

random_access_10000_2_2 time:   [1.3377 ms 1.3438 ms 1.3503 ms]
                        change: [-9.8763% -9.3310% -8.7473%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
  6 (6.00%) high mild
  2 (2.00%) high severe

random_access_10000_100_2
                        time:   [1.8859 ms 1.8933 ms 1.9005 ms]
                        change: [-9.6828% -9.3539% -9.0274%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 1 outliers among 100 measurements (1.00%)
  1 (1.00%) high mild

random_access_10000_100_16
                        time:   [9.5406 ms 9.5624 ms 9.5853 ms]
                        change: [-3.9866% -3.7256% -3.4781%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
  4 (4.00%) high mild

random_access_10000_100_32
                        time:   [12.810 ms 12.824 ms 12.840 ms]
                        change: [-8.2901% -8.1081% -7.9161%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
  2 (2.00%) high mild
  9 (9.00%) high severe

random_access_10000_100_64
                        time:   [18.867 ms 18.885 ms 18.905 ms]
                        change: [-8.9137% -8.6887% -8.4673%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
  2 (2.00%) high mild
  1 (1.00%) high severe

random_access_10000_1000_2
                        time:   [2.0669 ms 2.0775 ms 2.0890 ms]
                        change: [-5.9828% -5.4146% -4.8339%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
  1 (1.00%) high mild
  1 (1.00%) high severe

random_access_10000_1000_16
                        time:   [8.8544 ms 8.8822 ms 8.9116 ms]
                        change: [-4.2277% -3.8978% -3.5707%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
  13 (13.00%) high mild
  1 (1.00%) high severe

random_access_10000_1000_32
                        time:   [16.469 ms 16.500 ms 16.537 ms]
                        change: [-5.4373% -5.2534% -5.0260%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
  2 (2.00%) high mild
  8 (8.00%) high severe

random_access_10000_1000_64
                        time:   [31.007 ms 31.147 ms 31.310 ms]
                        change: [-4.1520% -3.6894% -3.2145%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
  3 (3.00%) high mild
  8 (8.00%) high severe

random_access_10000_1000_128
                        time:   [46.194 ms 46.277 ms 46.374 ms]
                        change: [-7.7444% -7.5188% -7.2712%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
  3 (3.00%) high mild
  6 (6.00%) high severe

random_access_10000_1000_256
                        time:   [76.280 ms 76.354 ms 76.452 ms]
                        change: [-9.4061% -9.2227% -9.0371%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
  3 (3.00%) high severe

random_access_10000_10000_2
                        time:   [1.8028 ms 1.8047 ms 1.8068 ms]
                        change: [-14.048% -13.592% -13.167%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 15 outliers among 100 measurements (15.00%)
  1 (1.00%) low mild
  5 (5.00%) high mild
  9 (9.00%) high severe

random_access_10000_10000_16
                        time:   [9.5437 ms 9.5576 ms 9.5748 ms]
                        change: [-3.9349% -3.5408% -3.1392%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
  4 (4.00%) high mild
  5 (5.00%) high severe

random_access_10000_10000_32
                        time:   [17.466 ms 17.506 ms 17.560 ms]
                        change: [-0.6959% -0.4031% -0.0553%] (p = 0.01 < 0.05)
                        Change within noise threshold.
Found 5 outliers among 100 measurements (5.00%)
  1 (1.00%) high mild
  4 (4.00%) high severe

random_access_10000_10000_64
                        time:   [31.399 ms 31.453 ms 31.520 ms]
                        change: [-2.0534% -1.6579% -1.2863%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 6 outliers among 100 measurements (6.00%)
  1 (1.00%) low mild
  5 (5.00%) high severe

random_access_10000_10000_128
                        time:   [62.817 ms 62.919 ms 63.045 ms]
                        change: [-3.6779% -3.4703% -3.2080%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
  2 (2.00%) high mild
  3 (3.00%) high severe

random_access_10000_10000_256
                        time:   [113.43 ms 113.55 ms 113.69 ms]
                        change: [-5.0405% -4.8542% -4.6687%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 15 outliers among 100 measurements (15.00%)
  8 (8.00%) low mild
  1 (1.00%) high mild
  6 (6.00%) high severe


Doesn't work with raw Ember.RSVP.Promise

The code seems to rely on setting of the isFulfilled property to determine if the promise is complete. Trouble is, this isn't a property of Ember.RSVP.Promise itself, but rather Ember.PromiseProxyMixin.
Ember-Data models use this mixin, so this addon works great for that use-case, but for raw promises (e.g. things returned by Ember-Ajax, in my case), fulfillment is never detected and the loader template is displayed forever.

The limitation you point out is correct. A workaround is the following:
promiseObject: Ember.computed(function() {
  return Ember.Object.extend(Ember.PromiseProxyMixin).create({
    promise: this.get('ajax').request(...)
  });
}),
promiseValue: Ember.computed.reads('promiseObject.content')

You can pass promiseObject as the parameter for promise-block and then promiseValue will contain the value returned by the promise once it resolves.
Does this solve your use case?


Use @compileError to catch error at comptime

In old version @panic cause program to compile fine just to crash the moment plot function is called.

Thank you, good catch!


build,win: remove unneeded condition from GYP file

The file itself contains include guards, so don't compile it
conditionally.
R=@piscisaureus, @bnoordhuis

I don't think this change is correct.  The idea is to compile in the snprintf() shim when building with VS 2013 or older.  You're changing that to always compile in the shim, even with VS 2015, which does have a functioning snprintf().

The snprintf.c file already does nothing if compiled with MSVC 2015: https://github.com/libuv/libuv/blob/v1.x/src/win/snprintf.c#L22
Since we need the file also for tests and benchmarks, we'd need to add the conditional to both targets. I noticed we didn't add them here and it looks cleaner without.
Thoughts?

Oh, hadn't seen that.  LGTM in that case.
Just curious, do you get a warning about an empty compilation unit with VS 2015?

Oh, hadn't seen that. LGTM in that case.

Kewl!

Just curious, do you get a warning about an empty compilation unit with VS 2015?

Nope. (I was also surprised because GCC complains about empty translation units if compiled with -pedantic, IIRC)


Optimization settings in Scala 2.12 need to be tweaked

2.12 introduced a new inliner and the previous -opt:l:project flag has been deprecated. See:
[warn] -opt:l:project is deprecated, use -opt:l:inline and -opt-inline-from

On an aside, I'm curious, what is the original motivation to enable the optimizer? It is important to be careful with it because -optimize can break binary compatibility. It is best enabled in the leaf projects (applications) rather than libraries.

This deprecated flag was specific for just optimizing libraries which actually made it really convenient (see release notes for http://www.scala-lang.org/news/2.12.0/#new-optimizer). I actually asked in scalac and reddit what an equivalent new flag would be and I never got an answer.
I am actually not entirely sure what I should be using as a replacement?

@lrytz?

You can get the same behavior with -opt-inline-from:<sources>
$ scalac -opt-inline-from:help
...
  <sources>      Classes defined in source files compiled in the current compilation, either
                 passed explicitly to the compiler or picked up from the `-sourcepath`
...

And, using that option is safe with respect to binary compatibility.

@lrytz Which are the options that can affect bincompat? I was registered to a ticket that discussed it, but cannot find it.

@jvican The -opt:l:classpath (if it still exists) can effect binary compatibility since it uses all files from the class path (hence why its only recommended for applications/fatjars and not libraries)

Ah, alright, it was l:classpath. There's a wip bincompat guide that will be merged into the official website, so I'll suggest the author to elaborate on how the optimizer affects bincompat. /cc @jatcwang

@jvican I have done this in master, feel free to merge into your branch if you want to do so

Sure, will do.


When memory out service is killed.

{ Error: spawn ENOMEM
    at ChildProcess.spawn (internal/child_process.js:358:11)
    at spawn (child_process.js:533:9)
    at Child_Process.spawn (/src/node_modules/duplex-child-process/index.js:58:19)
    at Function.Child_Process.spawn (/src/node_modules/duplex-child-process/index.js:15:30)
    at Object.<anonymous> (/src/dist/transform/index.js:34:43)
    at Generator.next (<anonymous>)
    at fulfilled (/src/dist/transform/index.js:4:58)
    at process._tickCallback (internal/process/next_tick.js:68:7) errno: 'ENOMEM', code: 'ENOMEM', syscall: 'spawn' }
events.js:167
      throw er; // Unhandled 'error' event
      ^

Error: Command failed:
    at ChildProcess.onExit (/src/node_modules/duplex-child-process/index.js:116:12)
    at Object.onceWrapper (events.js:273:13)
    at ChildProcess.emit (events.js:182:13)
    at ChildProcess.EventEmitter.emit (domain.js:442:20)
    at maybeClose (internal/child_process.js:962:16)
    at Socket.stream.socket.on (internal/child_process.js:381:11)
    at Socket.emit (events.js:182:13)
    at Socket.EventEmitter.emit (domain.js:442:20)
    at Pipe._handle.close (net.js:606:12)
Emitted 'error' event at:
    at ChildProcess.onExit (/src/node_modules/duplex-child-process/index.js:120:12)
    at Object.onceWrapper (events.js:273:13)
    [... lines matching original stack trace ...]
    at Pipe._handle.close (net.js:606:12)

haven't seen this any more

can we make sure restart is done better when all cluster instances dies?

You mean the node-clusters? Does the entire process die and therefore the container? I would assume starting docker with restart: always would handle the restart?

yes, it's like all child processes was down but the main thread was running and responding with 499 errors in our nginx container.

Oh okay so the main process does not exit. Is there a way to handle the event when a child pocess dies?

Oh okay so the main process does not exit. Is there a way to handle the event when a child pocess dies?

this is how we do it now, maybe it isn't working:
https://github.com/spacechop/spacechop/blob/master/src/index.ts#L29-L35

I don't think this have to be related to memory, but I keep getting this error after a couple weeks or so. Maybe all errors are not caught correctly.

Oh wait, the combined logs have been rotated and when that happens an error is thrown and the worker dies, maybe the restart of the worker is not effective.

A simple restart of the service resolves the issue.

This should be resolved in latest release-1.0.0-beta9

This seams to work better in the latest version release-1.0.0-beta10, I'm not getting nearly as many 5xx errors from the service. I'll report here if I notice any more issues like this.


Add Banano Node Mainnet

deploy Banano node on Mainnet on Akash.
SDL file + Readme (example post to check nodes via rpc)

how to add signedBy ? :(

how to add signedBy ? :(

Look for signedBy string in other deployment manifest files to see how it is done there.
Please update the top-level README.md file too.

Hey @pramonoutomo !
Can you add the necessary information so that the merge can be completed?

Old PR and not answered, i propose close @brewsterdrinkwater


IndexError: index 6 is out of bounds for axis 0 with size 6

Hi!
I tried yours naive bayes classifier on
https://archive.ics.uci.edu/ml/machine-learning-databases/glass/glass.data
n_classes = len(self._classes) returns classes like [ 1,2,3,4,5,6 ] unlike in iris [0,1,2]
In loop
for c in self._classes:
X_c = X[y==c]
self._mean[c, :] = X_c.mean(axis=0)
self._var[c, :] = X_c.var(axis=0)
self._priors[c] = X_c.shape[0] / float(n_samples)
I will try to go self._mean[6, ;] which will be out of boundry.
Shouldn't it be
for index, c in enumerate(self._classes):
with index insteed of c in calculations?

Thank yor for reporting this! I think you are correct

I fixed it


Explore how to limit number of cores used in standalone mode

--executor-cores 1 --total-executor-cores 2
may also not work.

They do work. Also, limiting the number of worker cores/number of workers clearly influences the cores used.


Etcher flashing error with clover_v0.20.img

Etcher 1.5.95 + clover_v0.20.img = Checksum error [due to name change?]
Etcher 1.5.95 + clever_v0.18.img = No warning or error

I believe it might be a hardware problem, the image version has nothing with the checksum check.
Please, try to flash your SD card once again.

I had repeatedly flash, re-flash, SD card full format then flash, still, I get the error.

Thanks for the report! We'll definitely investigate this issue more, and maybe even switch to advising Raspberry Pi Imager instead of Etcher.
We tested with Etcher 1.4.4 and had no problems.


[CI] Align indentation

What?
Current format checker doesn't work with indentation for ts and js.
We run these linters within CI.
      - run: npm run lint #  "eslint src --ext ts --max-warnings 0"
      - run: npm run lintjs # "eslint media --ext js --max-warnings 0"
      -...
      - run: bash infra/format # clang-format-8

So we basically use
eslint and clang-format-8 for src(ts) and media(js) directories.
Our eslintrc.json file doens't configure 'indent' and clang-format-8 doesn't seem to care.
For example,
      suite('#getOneccPath()', function() {
        test('returns onecc path as string', function() {
          let toolRunner = new ToolRunner(logger);
          let actual = toolRunner.getOneccPath();  // string or undefined
          // Note. `onecc` path could be changed by user
        assert.isTrue((actual === '/usr/share/one/bin/onecc') ||  //////////////// Unaligned
                      (actual?.endsWith('onecc')));
        });
      });

What
Let's add "indent" to eslint rules.
      "indent": [2, 2, {"SwitchCase": 1}]

Changes
15 problems in media/
92 problems in src/

I will first apply them on media/ directory which is not currently working on.
We are currently working on src/ in hustle, so the changes will be made during next week.

https://github.com/Samsung/ONE-vscode/pull/516#issuecomment-1110638975

Can I ask a question? 😸
Does // cliang-format off work with this change?

@hyunsik-yoon Sorry for the late reply, I think we have talked offline at the time.
eslint enables users to disable formatting for a line or a file FYI
const res = eval('42'); // eslint-disable-line no-eval

The comment will allow eslint to ignore the line.

Formatting Ways

eslint

Our project uses "eslint": "^7.15.0"
Practically not uses (We include eslint in CI but it doens't fixes the code)

# package.json
"lint": "eslint src --ext ts --max-warnings 0"
"lintjs": "eslint media --ext js --max-warnings 0",

vscode (built-in)

If tsc is installed on your pc, vscode allow auto formatting with somewhat common config (format document command)

clang-format-8

Our project currently uses clang-format-8 to force formatting.


chore: storybook improvment

just a simple refactoring for now:

making sure all storybook load
fixing a few types
using storybook v6 beta instead of v5
proof of concept of the new format app/screens/settings-screen/settings-screen.stories.tsx
moving some files around
-- storybook/ --> .storybook
-- using the stories.tsx pattern that is now suggested as best practice from documentation

note: stories.tsx still excludes both from eslint and tsc currently. will slowly fix that.

making sure all storybook load

How are you achieving this?

making sure all storybook load

How are you achieving this?

manual operation for now. had to fix a few things on some screens to make all the stories work,
running this https://storybook.js.org/docs/react/writing-tests/test-runner in CI would be the right solution.
but right now server doesn't work yet, there is some incompatibilities issues to look at.


Fix duplicate node name in graph for tf.concat

This fix tries to address the issue raised in #31137 where
Duplicate node name in graph: 'concat' shown up with the
following:
import tensorflow as tf
from tensorflow.keras import Input

print('Using Tensorflow version {} (git version {})'.format(tf.version.VERSION, tf.version.GIT_VERSION))

i = Input(shape=3)
j = Input(shape=4)
try:
    print(tf.concat([i, j], axis=-1))
except Exception as e:
    print(type(e))
    print(e)
try:
    print(tf.concat([i, j], axis=-1))
except Exception as e:
    print(type(e))
    print(e)
try:
    print(tf.concat([i], axis=-1))
except Exception as e:
    print(type(e))
    print(e)
try:
    print(tf.concat(i, axis=-1))
except Exception as e:
    print(type(e))
    print(e)

The issue was that identity node passed the scope as the name.
This fix fixes the issue.
This fix fixes #31137.
Signed-off-by: Yong Tang<EMAIL_ADDRESS>

Thanks @alextp for the review and suggestion. The PR has been updated. Please take a look.

@alextp @rthadur one kokoro CI test was failing, because of the name change where 'concat:0' =>concat/concat:0. I have updated the PR and fixed the failed test.
Please take a look and sorry for the additional inconvenience.


sea-orm-cli generate entity from sqlite generates String for boolean fields

I haven't gotten to the bottom of diagnosing yet, but I have a table that has a boolean field, in an sqlite database. I'm trying to import the schema from it, but codegen is setting it to a String. Here is what the table looks like:

I debugged the schema from this line, and got this:

And the final output is as follows:
pub struct Model {
    #[sea_orm(primary_key)]
    pub id: i32,
    #[sea_orm(column_type = "Custom(\"BLOB\".to_owned())")]
    pub completed: String,
    pub payload: String,
}

Is this expected output? I haven't tested on Postgres to see if it's different or anything.

Hey @AngelOnFira, could you also attach the SQL of the SQLite table? Thanks!

If the datatype displayed in your screenshot is correct then you've got the wrong type.
It should be a boolean instead of a bool. Sea-schema parses the types here.
bool would then be parsed as a BLOB instead in your case. (Though BLOB has also got the wrong type at the moment, but that is a separate issue)

Nice observations! @Hirtol
Thanks!!

Hey @AngelOnFira, I will close this for now. If you still have problem on this please reopen it :)


Agent's Handbook Equipment Hyperlinks Broken

As title. All hyperlinks for items and equipment for the Agent's Handbook are broken even on the most up-to-date world and system/modules.

Thanks for letting me know, this would be an issue with the premium module rather than the system I think, but I will reach out to them about it and see if we can get it updated to point at the correct place.

I spoke with the designer for the premium Foundry modules for DG, he said he is expecting people to import the compendium item content first:

And specifically to make sure you check off "Keep Document ID's" here:

This does seem to make it work in my test setup:

Perhaps something we can work to make it more intuitive in the future however.

i think if you have what the pf2e modules have and have an adventure importer screen for the handbook that does it for people that would be best.


Don't edit current when changing docks v2

redo of #90816
fixes https://github.com/godotengine/godot/issues/90654

Made the edit(nullptr) in NOTIFICATION_PREDELETE not run when exiting, since it doesn't need to clean up anything if exiting.
The object was apparently freed but not null, causing a crash on some platforms.
Needs testing on Linux and macOS to make sure https://github.com/godotengine/godot/pull/90816#issuecomment-2071069759 doesn't happen.
Edit: made sure it works when there is no EditorNode, like in dotnet glue binding.

Thanks!


CRAN version and GIT commit

Is there a way to tell what GIT commit that the latest CRAN version of XGB corresponds to?  There is no tag of 0.4-4 which is the current CRAN version.

I' m wondering if it is out of date. Cannot find 0.4-4 even in  https://github.com/dmlc/xgboost/commits/master/R-package/DESCRIPTION .


SDL_AMediaCodecJava_dequeueOutputBuffer: Exception

i am getting this error for a video . no visuals only audio is hearable . there is some sort of seek issues are also with that video . what should i do i have searched it but in vain . plz help me out . i am  afraid of thinking about it .

hi lzls i know you are busy . but i got a problem and want your help . please reply me


hooking up publishing to NPM through travis

Coverage remained the same at 100.0% when pulling 374fdeb48af6883efad2f1360470d253c09b975e on dlockhart:npm-publish into a67f9bece0aabb55c4706e6d1575e3898ab1c589 on Brightspace:master.


where is trained model?

Hi, dear contributor,
Where should I download the two models in the picture? Looking forward to your reply.

Please read the paper and documentation first, and follow the process to get it.


[CSM-503] Optimize change addresses evaluation

Tested with outgoing/incoming and a2a transactions

Ok, now it seem to work. Consider it approved :green_apple:


RTSP Supprt

Hi Guillaume, and John,
It looks like support for streaming video once existed, and, if so, I'd like to reinflate it.
My usecase is streaming my garden camera feed to my computer as a screensaver. I want to bring the garden into my office.
This might be slightly different than what was supported before, but I think it could be pretty neat. Could even use the caching feature to save the feed off for timelapsing later. High-res RTSP cameras are quite affordable these days.
Interested in your thoughts.
Ben

Hi @benjaminbrumbaugh !
So not really. The closest thing it had to streaming is playing a http file from beginning to end, but not cache it on disk. Which is "kinda" streaming but not what you are talking about here.
What you want is fairly different conceptually and will run afoul of a lot of the internals of Aerial (which basically plays video randomly based on some rules). Whether it's via RTSP or some basic http, those don't have a beginning or an end, no finite duration, they just stream endlessly. So it will break most playlist concepts.
Now, I still think it would be super cool to add this in some way or another, because it's been requested. My first thought was that when you setup a feed as a "video", you can either set a duration for it, or there's a setting somewhere for how long to stream them (say 5mins). This would solve the playlist integration, you could either only have one and set its duration super high, or have multiple such cameras that will rotate every X minutes. There would be an equally strong case to make that a separate screensaver, and that's up to you.
Also, any form of interaction is currently banned, so don't expect any.
If you are interested in adding this yourself, let me know and I can give you some pointers on how to get started.

Thanks for the quick response, Guillaume!I wouldn’t mind trying my hand at a PR based on your feedback, but I’m on the hook for another project at the moment. Maybe we could talk through it though.How does it handle a playlist of size one? I’m thinking there is a case to be made for each stream being another playlist object. It seems like with this approach, one can get all of the different combinations one might want—one stream only, multiple streams with duration switching, or integrated into a diverse list of content. It also still feels appropriate and intuitive, at least to me at this point.On Jun 9, 2024, at 6:47 AM, Guillaume Louel @.***> wrote:
Hi @benjaminbrumbaugh !
So not really. The closest thing it had to streaming is playing a http file from beginning to end, but not cache it on disk. Which is "kinda" streaming but not what you are talking about here.
What you want is fairly different conceptually and will run afoul of a lot of the internals of Aerial (which basically plays video randomly based on some rules). Whether it's via RTSP or some basic http, those don't have a beginning or an end, no finite duration, they just stream endlessly. So it will break most playlist concepts.
Now, I still think it would be super cool to add this in some way or another, because it's been requested. My first thought was that when you setup a feed as a "video", you can either set a duration for it, or there's a setting somewhere for how long to stream them (say 5mins). This would solve the playlist integration, you could either only have one and set its duration super high, or have multiple such cameras that will rotate every X minutes. There would be an equally strong case to make that a separate screensaver, and that's up to you.
Also, any form of interaction is currently banned, so don't expect any.
If you are interested in adding this yourself, let me know and I can give you some pointers on how to get started.
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you were mentioned.Message ID: @.***>


➡ Need to take offset into account when calculating draw area

There was a small artifact noticeable when offset wasn't taken into account when calculating the bounds of the rectangle, leading to 1px clipping artifacts.
This would break in cosmic-text where the offset would be used to offset the glyph with a tiny fractional amount, causing incorrect rounding in this routine as a result.
https://github.com/pop-os/cosmic-text/blob/2342bf0eaebe6d41661b1fb49ed30d4021a9807d/src/swash.rs#L33-L35
Current main branch;

With this fix applied;

Notice some instances of the 💩 , 🐭and more subtly the top of the 🤖 emoji.

@dfrg This is a relatively small change leading to much nicer visual representation (and I think it's correct?) Could you double check?

This looks reasonable to me. Thanks!
Also, please feel free to @ me in future PRs. I don’t check this project much and I’m bombarded with GH notifications so I tend to miss things.

@dfrg Thanks! Could you push a new (patch) release?

Certainly! I’ll try to get to it later this evening.


repair partition selection

Remove system property EventHubHeaders.PARTITION_KEY in EventHubMessageConverter
Update PartitionSupplier parameter for EventHubs SDK, get partitionId first, then partitionKey, choose one.
Suuport spring cloud stream partitionKeyExpression configuration.

would u please elaborate the purpose of this PR more


pylyzer: 0.0.67 -> 0.0.68

Things done
Changelog: https://github.com/mtshiba/pylyzer/releases/tag/v0.0.68

Built on platform(s)

[ ] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[ ] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review pr 349970

x86_64-linux

:x: 1 package failed to build:

pylyzer

aarch64-linux

:x: 1 package failed to build:

pylyzer

x86_64-darwin

:x: 1 package failed to build:

pylyzer

aarch64-darwin

:x: 1 package failed to build:

pylyzer

Compilation fails:
error[E0005]: refutable pattern in local binding
   --> crates/py2erg/convert.rs:450:13
    |
450 |         let Ok(py_program) = locator.fold(py_program);
    |             ^^^^^^^^^^^^^^ pattern `Err(_)` not covered
    |
    = note: `let` bindings require an "irrefutable pattern", like a `struct` or an `enum` with only one variant
    = note: for more information, visit https://doc.rust-lang.org/book/ch18-02-refutability.html
    = note: the matched value is of type `Result<ModModule<SourceRange>, Infallible>`
help: you might want to use `let else` to handle the variant that isn't matched
    |
450 |         let Ok(py_program) = locator.fold(py_program) else { todo!() };
    |                                                       ++++++++++++++++

For more information about this error, try `rustc --explain E0005`.
error: could not compile `py2erg` (lib) due to 1 previous error

Maybe it needs rust 1.82.

Maybe it needs rust 1.82.

Indeed, it works on staging-next. Let's wait for it to land on master.

nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review pr 349970

x86_64-linux

:white_check_mark: 1 package built:

pylyzer

aarch64-linux

:white_check_mark: 1 package built:

pylyzer

x86_64-darwin

:white_check_mark: 1 package built:

pylyzer

aarch64-darwin

:white_check_mark: 1 package built:

pylyzer

@ofborg build pylyzer pylyzer.tests


Extract test name from executable

This is used to fill in the xml test report.
Tested on Unix, untested on Win32

Merged. Thanks.


[BUG] After promote node role, existing vmi will be recreated

Describe the bug

To Reproduce
Steps to reproduce the behavior:

up one master A and one node B
create a vm on the node B
join another node C

node B and node C will be promoted to master
vmi on node B will be recreated
Expected behavior

vmi on the node B won't be recreated
Log

Environment:

Harvester ISO version:
Installation Mode: ISO/app-mode
Underlying Infrastructure (e.g. Baremetal with Dell PowerEdge R630):

Additional context
Add any other context about the problem here.

Validated on master-head
Steps:

Add one master A and one node B
Create a VM on the node B
Join another node C

Result:
After node B and C were promoted to master, the VM was not encountered restarting


A brute force fix for powershell alias problems

This is a possible fix for #351. What it does:

Resets common Powershell aliases to their defaults in Scoop's script scope (e.g. ls, gcm). This was already being done with script-scoped functions, but this change does it with script-scoped aliases instead.
Prioritises local functions over user-defined aliases with the same name.
Doesn't require renaming functions to make them more obscure in the hope that they won't collide with user's aliases.
Gives more protection against invasive aliases.

On my machine this adds about 30ms execution time to each scoop command issued.
I'm going to think about this one before committing. Comments welcome.

It's just a quick comment. I did not think of the reset_aliases approach carefully yet.
Is it going to resolve the original problem case of #351? I can see that reset_aliases deals with -scope global. In the problem #351 Invoke-Build defines the aliases not in the global scope. Also Invoke-Build calls may be nested so that aliases may be defined in several scopes.

@nightroman it does solve the simpler test case you provided in #351 with set alias exec Invoke-Exec. It seems that get-alias -scope global matches aliases defined in the parent scope and above—I'm assuming that includes any aliases set by Invoke-Build that leak into Scoop's scope.

This test fails
function test2 {
	Get-Alias test -Scope global
}
function test1 {
	Set-Alias test bar
	test2
}
test1

Set-Alias : This command cannot find a matching alias because an alias with the name 'test' does not exist.

It works if -Scope global is removed.

@nightroman yep, you need to execute a script to see aliases that were defined without -scope global become "global" from the point of view of the script.
"get-alias test -scope global" > test.ps1
set-alias test write-host
./test.ps1

Yes, if you execute this code in the global scope, i.e. from interactive
console or using powershell -File.
If we put these three lines in a new script test2.ps1 and invoke it without
dot sourcing then test is not found.
@'
"get-alias test -scope global" > test.ps1
set-alias test write-host
./test.ps1
'@ > test2.ps1

# works
powershell -file test2.ps1
powershell -command '. .\test2.ps1'

# fails
powershell -command .\test2.ps1

It's because in first two cases the code is invoked in the global scope, so
that the alias test is created in the global scope and get-alias -global
finds it there.
In the 3rd case the code is invoked in a script scope and get-alias -global
cannot find it.
Perhaps I miss something obvious. Please ignore my worries if Invoke-Build case
from #351 works fine with this change. It's my problem to understand how it works.

If you can provide a complete test case for Invoke-Build I'd be happy to run it and see if it works.

Please get the script Invoke-Build.ps1.
It can be used alone without the package.
Create this build script .build.ps1, i.e. a standard PowerShell script with a task:
task update {
    scoop update
}

Invoke it by InvokeBuild in PowerShell
<path1>\InvokeBuild update <path2>\.build.ps1

Or, if InvokeBuild is in the path and .build.ps1 is in the current directory, then simply
InvokeBuild

Thanks. The test did fail, so I've updated this to override all aliases, not just global ones.

@lukesampson @nightroman I'm thinking we merge this in as the solution for now.

@deevus thanks, done.


No Data

Hello! Thank you for putting this together. It's my first foray into Prometheus and Grafana, and it's been fairly painless.
I am stuck on one matter. I have the Grafana dashboard up and running on localhost:3000 and I see metrics are being successfully collected in my terminal and on localhost:9171. But this does not reflect in the dashboard.
The queries are working, as I get this when I Inspect:
{   "request": {     "url": "http://localhost:9090/api/v1/query_range?query=github_repo_stars%7Brepo%3D%22gravitational%09eleport%22%7D&start=1562803200&end=1622851200&step=86400",     "method": "GET",     "hideFromInspector": false   },   "response": {     "status": "success",     "data": {       "resultType": "matrix",       "result": []     }   } }
It looks like the request is successful, but it's not returning any data? Any guidance?

Hello! Thank you for putting this together. It's my first foray into Prometheus and Grafana, and it's been fairly painless.
I am stuck on one matter. I have the Grafana dashboard up and running on localhost:3000 and I see metrics are being successfully collected in my terminal and on localhost:9171. But this does not reflect in the dashboard.
The queries are working, as I get this when I Inspect:
{   "request": {     "url": "http://localhost:9090/api/v1/query_range?query=github_repo_stars%7Brepo%3D%22gravitational%09eleport%22%7D&start=1562803200&end=1622851200&step=86400",     "method": "GET",     "hideFromInspector": false   },   "response": {     "status": "success",     "data": {       "resultType": "matrix",       "result": []     }   } }
It looks like the request is successful, but it's not returning any data? Any guidance?


Admin View Model for #29 Phase 2

The following JSPs were not included:
error.jsp
home.jsp
index.jsp
login.jsp
because they are static pages.
@nowucca -- your feedback is appreciated.
Thank you!!

Thank you so much @tippyweb for these changes.

Good morning @nowucca
This is wonderful.  Thank you so much again for your kind assistance, @nowucca !!
From this weekend, I'm taking SANS course "Defending Web Applications Security Essentials".  I hope to be able to do more volunteer work for you real soon again!!
Have a great week, @nowucca !!!


Docs outline and tensorflow + aws

Provides docs structure and partial docs coverage, more coming soon!

Will squash & merge because this is a lot of commits


first steps.

There's no benefit to having this first PR grow and grow.
Now that we have some definitions of modules and types in place, I think it makes sense to merge this and start a fresh PR for the next steps:

[ ] adapt cases from parser.mly in moc source into corresponding cases in parser.lalrpop here
[ ] write basic pretty printer, in format module (to help us see and test the parsed ASTs in a manageable way).  The formatter need not do actual formatting.  No context-sensitive whitespace choices needed.  It's just to see the parsed ASTs for very small programs.
[ ] test parses for basic expressions, trying to cover the language syntax.
[ ] test formatter and parser together: that each example program "round-trips" in the parser-formatter-parser combined flow.


Fixes #2

Fixes #2
This separates the existing unit tests out from some performance regression tests. I'd like to set up the repo so that the perf tests are optional for merging PRs, but we at least get a signal if something regresses (or significantly improves).

Codecov Report

Merging #9 (622055d) into main (a8d0bc3) will not change coverage.
The diff coverage is n/a.

:exclamation: Current head 622055d differs from pull request most recent head 1dc8680. Consider uploading reports for the commit 1dc8680 to get more accurate results

@@            Coverage Diff            @@
##              main        #9   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files            1         1
  Lines           23        23
=========================================
  Hits            23        23

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Add instructions or Helm chart for deploying on Knative

We wish to offer the option to deploy the project as a Cron Job Source in Knative, so we need to create instructions or a Helm chart to do so.

#11 closed, so closing issue.


Plugin reverts last changes on other states

Let's imagine we have 2 states: A and B
interface TestModel {
  conter: number;
}

@State<TestModel>({
  name: 'a',
  defaults: {
    counter: 0,
  },
})
export class AState {}

@State<TestModel>({
  name: 'b',
  defaults: {
    counter: 0,
  },
})
export class BState {}

The app is configured to save the BState changes via HTTP on the backend
    NgxsAsyncStoragePluginModule.forRoot(
      MyEngine,
      {
        key: 'b',
      }
    ),

Let's imagine it takes 1 second to pull data from the backend.
After the initialization we have next state tree:
{
  a: {
    counter: 0
  },
  b: {
    counter: 0
  }
}

Then we start pulling the B state which has the counter value 1 on the backend.
While B state is pulling we have updated several times the state A:
{
  a: {
    counter: 3
  },
  b: {
    counter: 0
  }
}

Then B state data received and plugin updates the state. And it reverts our changes from state A:
{
  a: {
    counter: 0
  },
  b: {
    counter: 1
  }
}

That is because of:
https://github.com/ngxs-labs/async-storage-plugin/blob/39fb6ecb0720a6be05b86e4a360f3bc88d4e4dda/src/lib/async-storage.plugin.ts#L71
where 'previousState' is the state that was at the moment of pulling, not the latest one.
The expected behavior is to update the B state only:
{
  a: {
    counter: 3
  },
  b: {
    counter: 1
  }
}

I currently work around this issue by waiting for the init action to be fired (as this plugin hijacks the init action). This kind of makes sense as I first want to load in the, in my case indexeddb, data before I start to execute a bunch of selects/actions.
I created a Store wrapper that handles this, it does not implement selectOnce and selectSnapshot but you can figure that out if you need it:
import {Type} from '@angular/core';
import {Actions, InitState, ofActionCompleted, Store} from '@ngxs/store';
import {NEVER, Observable} from 'rxjs';
import {shareReplay, startWith, switchMap} from 'rxjs/operators';

export class AsyncStore {
  initCompleted$ =
      this._actions$.pipe(ofActionCompleted(InitState), startWith(false), shareReplay(1));

  constructor(private _store: Store, private _actions$: Actions) {}

  dispatch(event: any|any[]): Observable<any> {
    const observable = this.initCompleted$.pipe(switchMap(ready => {
      if (ready) {
        return this._store.dispatch(event);
      } else {
        return NEVER;
      }
    }));
    observable.subscribe();
    return observable;
  }

  select<T>(selector: (state: any, ...states: any[]) => T): Observable<T>;
  // tslint:disable-next-line: unified-signatures
  select<T = any>(selector: string|Type<any>): Observable<T>;
  select(selector: any): Observable<any> {
    return this.initCompleted$.pipe(switchMap(ready => {
      if (ready) {
        return this._store.select(selector);
      } else {
        return NEVER;
      }
    }));
  }
}

Hello, I deal with memory limit of localStorage using sync storage-plugin.  I  tried to replace the default storage plugin with this async storage plugin and related indexedDb behind. Unoftunatelly did not pass the "regretion tests". I  run in couple of issues  probably caused by this bug.
I have a scenario where I fetch/hydrate multiple related entity subsets from Rest Api and use loaded status mark for each entity. After all are fetched (loaded = true for all) I prepare component view with that data.
When I use persitency per key NgxsAsyncStoragePluginModule.forRoot( { key: ['ProductPrices', 'ProductData"...]} I never get all loading status = true. Seem that subsequent fetch erases previously fetched entity from STATE.
When I use global @@STATE persistency the behaviour is different.  By first page load all entity are correctly fetched from Rest API and set to loaded=true in stores. But when I reload the page, some entity are reused from indexedDB, and some are forced to fetch via Rest again..
Do You think it is a simple fix of mentioned nextState = setValue(previousState, key, val);  implementation? Or could be conceptual problem connected to async execution where the order of getItems, setItems, select execution is not guranteed. So it can break the store consistency based on funtional paradigm and sequential application of reducers. Is that possible?
I see the workaround, maybe it could help in case we have only one time data hydration from rest api. But in case I fetch related entity subsets based on user query dynamically multiple times during the store lifecycle?
BTW: Is there any simple way how to use IndexedDb with ngsx. Even with sync performance penalty? The same speed as localStorage, just to circumvent its memory limitation?  Anybody tried async - await implementaion of storage interface which assures seguential storage manipulation?

In our situation, we are seeing @@INIT fire after the application has loaded. This has the unfortunate side-effect of wiping our data.


Add support for rendering doubles using Grisu 2

Moving this from icicle to here so we can call it from Haskell.
Also, we finally have a roundtrip test for the double parsing / rendering!
! @amosr @tranma

👍


[documentation] includeHtml not mentioned in any of the examples

the parameter is listed but not shown what method it is for. Together with the new packaging that eliminated intellisense, it's a big guessing game for new users

It's documented at least in the source code. Will add it later to the examples.


Speedup Parsers.validID

It turned up in profiling sessions. Previously, it used parser combinators
which are somewhat slow especially when the JVM is still cold.
The grammar for ID is simple enough to afford this handwritten parser.

Could we write a property-based that tests that this new impl == matches(ID, s)?

Nice, thanks for adding the test @dwijnand. I wonder if it ever finds an example that would actually return true for either sides of the equality, though...

@jrudolph good intuition! you were right.. expanded the tests and fixed a bug in your re-impl: https://github.com/sbt/sbt/pull/3955.


⚠ Bofrost.lu has degraded performance

In ac095f0, Bofrost.lu (https://www.bofrost.lu) experienced degraded performance:

HTTP code: 200
Response time: 1023 ms

Resolved: Bofrost.lu performance has improved in 88b8ab6 after 6 minutes.


fix winforms backgroundWorker samples

Per https://mseng.visualstudio.com/TechnicalContent/_queries/edit/1409990/?triage=true.
@rpetrusha suggested improvements to the samples.

@rpetrusha - Here are the fixes for the backgroundWorker samples for https://mseng.visualstudio.com/TechnicalContent/_queries/edit/1409990/?triage=true. Thanks for your help.


cleos undelegatebw with oversized bandwidth brings down nodeos

Passing a value to cleos undelegatebw larger than the available staked bandwidth brings down nodeos. Here is the cleos command:
cleos -u http://localhost:8002 --wallet-url http://localhost:6666 system undelegatebw testa5555543 testa5555543 "1000000000.0000 SYS" "1000000000.0000 SYS" -p testa5555543
2524986ms thread-0   main.cpp:419                  create_action        ] result: {"binargs":"304829a51493b1ca304829a51493b1ca00a0724e18090000045359530000000000a0724e180900000453595300000000"} arg: {"code":"eosio","action":"undelegatebw","args":{"from":"testa5555543","receiver":"testa5555543","unstake_net_quantity":"1000000000.0000 SYS","unstake_cpu_quantity":"1000000000.0000 SYS"}}
2524995ms thread-0   main.cpp:2493                 main                 ] Failed with error: Bad Cast (7)
Invalid cast from type 'null_type' to Object

Here is the output from nodeos:
2243507ms thread-0   producer_plugin.cpp:215       on_incoming_block    ] Received block 000015964dfc3d06... #5526 @ 2018-05-22T15:37:23.500 signed by testxx555554 [trxs: 0, lib: 5190, confirmed: 0]
2243979ms thread-0   wasm_interface.cpp:909        eosio_assert         ] message: insufficient staked net bandwidth
2243980ms thread-0   net_plugin.cpp:2954           plugin_shutdown      ] shutdown..
2243980ms thread-0   net_plugin.cpp:2957           plugin_shutdown      ] close acceptor
2243980ms thread-0   net_plugin.cpp:2960           plugin_shutdown      ] close 30 connections
2243982ms thread-0   net_plugin.cpp:2968           plugin_shutdown      ] exit shutdown
2243987ms thread-0   fork_database.cpp:94          close                ] states.size(): 570
2243989ms thread-0   controller.cpp:261            ~controller_impl     ] db.revision(): 5526 head->block_num: 5526 blog.read_head()->block_num(): 4957
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243995ms thread-0   net_plugin.cpp:706            ~connection          ] released connection from client
2243996ms thread-0   main.cpp:101                  main                 ] bad alloc

The original staking for the account was:
../../build/programs/cleos/cleos --wallet-url http://localhost:6666 --url http://localhost:8000 system newaccount eosio --transfer testa5555543 EOS8XNhhdcfzSJeBYgV9SxuW3PaUerKRwPzxYFb4fBnhVU793hW3j --stake-net "75367526.4854 SYS" --stake-cpu "75367526.4854 SYS"

Commit bbcd65187f3f09ff4ff5eea91c6e562d5784892c should have resolved this.


Document the generation of wazuh-dashboard packages

Description
We need to document how to generate wazuh-dashboard packages as an official documentation page.

The dockerfile is almost finished to create an image that facilitates the process of building all the packages and the generation of the base package with everything integrated in tar format, according to the specified branches of each repository.
After creating the base package(s) to generate the unified base they can be extracted from the container with the command docker cp <container name>:</home/node/packages/. or /home/node/wzd/dev-tools/build-packages/base/output/.> <path where you want to copy them>.
with the unified package if you wish you can create the deb and rpm packages by running their respective scripts.
It remains to update the pr documentation to the documentation repository with this new information and polish a little more if necessary the dockerfile.

Pull request closed, please check https://github.com/wazuh/wazuh-documentation/pull/7328#issuecomment-2141833100


Code for validation on the nuscenes dataset

Thank you very much for your work. I was wondering if you have plans to release the code for validation on the nuscenes dataset?

Our submission on nuScenes is based on the mmdetection3d, which is not very compatible with this OpenPCDet. Our performance on nuScenes is also not very good, so we will not release the code.

Received, thanks for your response

@crinoiddream Hi, I have considered the same question as you, and after carefully reading the original paper, I have found that the entire network is named VirConvNet, and the new operation name is VirConv, so the convolution operation of VirConv was likely used here.

Is there any plan to open source the code for virtualization processing of nuscenes data sets?


default timeout when sending only one frame

Expected Behavior
nemesis should quit after the last frame has been sent and not wait for -i  or the default of 1 second.
Actual Behavior
nemesis waits for -i  after the last frame has been sent.
Steps to Reproduce the Problem
send a frame ;)
Specifications

Version:  1.6
Platform: Ubuntu bionic

Solution
For me, it seem line 344 of nemesis-functions.c isn't working as it should.
344                 if (count != 0 && interval >= 0)
345                         usleep(interval);

If count would be 0, it should not sleep. So I think there's an issue with the counter (off by one?)

Ah, good catch!  Haven't looked at it in detail, but maybe count isn't decremented as it should?

I think I've got it.
in the do { } while() loop of the nemesis_send_frame() function, count can never be 0. The while condition prevents that. That means the usleep() has to be skipped on the last packet which is count==1, not count==0.
changing 344 to: if (count != 1 && interval >= 0)
that should solve it.

There, should work better now. Thanks for reporting this :-)


get Table Data by sub id

This is  a feature request.

Prerequisites

[x] Are you running the latest version?
[x] Are you reporting to the correct repository?
(enso is made of many specialized packages: https://github.com/laravel-enso)
[x] Did you check the documentation?
[x] Did you perform a cursory search?

Description
i like use laravel-enso in my site.
but i need get tables data by sub id
Example
add vue-table  in profile  isadmin
isAdmin get table data : route = /api/users/2/project/getTableData
2 is profile.id
cant in /Table/template/users/project.json add user_id parameter

You can achieve what you need by using /api/users/project/getTableData and using  the params prop for the front-end component
<vue-table
    ...
    :params="{ user_id: 2 }"/>

and then read the params in your ProjectTable builder
$params = json_decode($this->request()->get('params'));
and use $params->user_id in your query
Even better, you can use the filters prop.
You can find all the examples here. Click the Show Code button below the table...
Adding params to the getTableData route form the json template is not something that we are interested adding.

Can I close this?

Closing due to inactivity


Invoke command "The member "Handlecount" is not present."

"Get-Process" fails but not "ls"
PS C:\Users\niroy> Invoke-Command -ComputerName <IP_ADDRESS> -Credential $Credential -Authentication Basic -ScriptBloc
k { Get-Process }

Handles  NPM(K)    PM(K)      WS(K) VM(M)   CPU(s)     Id  SI ProcessName                  PSComputerName
-------  ------    -----      ----- -----   ------     --  -- -----------                  --------------
              0        0          0     0              96   0 acpi_thermal_pm              <IP_ADDRESS>
The member "Handlecount" is not present.
    + CategoryInfo          : NotSpecified: (:) [Get-Process], ExtendedTypeSystemException
    + FullyQualifiedErrorId : AliasLookupMemberNotPresent,Microsoft.PowerShell.Commands.GetProcessCommand
    + PSComputerName        : <IP_ADDRESS>

PS C:\Users\niroy> Invoke-Command -ComputerName <IP_ADDRESS> -Credential $Credential -Authentication Basic -ScriptBloc
k { ls }

    Directory: /home/powershell

Mode                LastWriteTime         Length Name                                PSComputerName
----                -------------         ------ ----                                --------------
d-----        1/21/2016   3:54 PM                PowerShell-Linux                    <IP_ADDRESS>
d-----       12/23/2015   1:42 PM                jdk                                 <IP_ADDRESS>
d-----       12/23/2015   2:07 PM                indicationlog                       <IP_ADDRESS>
d-----         2/1/2016   5:53 PM                workspace                           <IP_ADDRESS>
------       12/23/2015   1:42 PM      153530841 jdk.sh                              <IP_ADDRESS>
------         2/3/2016   2:51 PM            689 pester-tests.xml                    <IP_ADDRESS>
------       12/21/2015  11:36 AM            717 README.md                           <IP_ADDRESS>
------        1/21/2016   3:41 PM         506256 slave.jar                           <IP_ADDRESS>

Got a recent customer report of this issue.  Don't see a PR linked to this.  Note that it seems the customer was using SSH remoting, so it's likely due to de-serialization complaining as we explicitly removed that member from PSCore6.

The HandleCount property is brought back in .NET Core 2.0, and I have verified that Get-Process works fine in both 'PSCore 6.0 -> Windows PowerShell' and 'Windows PowerShell -> PSCore 6.0'.
PSCore 6.0 -> Windows PowerShell
PS:9> Invoke-Command -ComputerName . -ScriptBlock { get-process powershell }

 NPM(K)    PM(M)      WS(M)     CPU(s)     Id  SI ProcessName                           PSComputerName
 ------    -----      -----     ------     --  -- -----------                           --------------
     66    49.13      76.32       2.27 ...044   1 powershell                            localhost
     64    45.30      89.88       6.20 ...000   1 powershell                            localhost
     64    49.38      97.81       3.67 ...720   1 powershell                            localhost
     72    59.50      92.86       2.81 ...504   1 powershell                            localhost
     37    87.11     105.33       1.95 ...208   1 powershell                            localhost

[E:\pscore]
PS:10> Invoke-Command -ComputerName . -ScriptBlock { $PSVersionTable }

Name                           Value
----                           -----
CLRVersion                     4.0.30319.42000
PSVersion                      5.1.15063.483
WSManStackVersion              3.0
PSCompatibleVersions           {1.0, 2.0, 3.0, 4.0...}
SerializationVersion           <IP_ADDRESS>
BuildVersion                   10.0.15063.483
PSRemotingProtocolVersion      2.3
PSEdition                      Desktop

Windows PowerShell -> PSCore 6.0
PS:7> Invoke-Command -ComputerName . -ConfigurationName powershell.6.0.0-beta.3 -ScriptBlock { Get-Process powershell }

Handles  NPM(K)    PM(K)      WS(K)     CPU(s)     Id  SI ProcessName                    PSComputerName
-------  ------    -----      -----     ------     --  -- -----------                    --------------
    659      66    50304      78172       2.27 ...044   1 powershell                     localhost
    862      64    46428      92088       6.20 ...000   1 powershell                     localhost
    861      63    50500     100124       3.67 ...720   1 powershell                     localhost
    836      69    60832      97632       2.94 ...504   1 powershell                     localhost
    753      39    90920     109528       2.13 ...208   1 powershell                     localhost

Given that, I will close this issue as resolved.

It duplicate #1812 - there you made a great review of the Issue.

@iSazonov Thanks. BTW, the synthesized HandleCount has been removed since we moved to .NET Core 2.0.


Image onLoad never fires in iOS

 onLoad={} callback never fires in iOs, but it does in Android.
Environment
Using expo.io sdk 25, which means RN version 0.52.0.
Steps to Reproduce
<Image source={this.props.source} onLoad={()=> console.log('I loaded')}>
You'll never see this log message in iOs, but you'll see it in Android.
We wanted to use this callback to change the state to hide the spinner (ActitvityIndicator), but i never fires in iOS.
Expected Behavior
The callback to fire when the image loaded.
Actual Behavior
Never fires.

It's still reproduced on v0.56.0


US485727: Use jre11 base image

CI Build Link:
http://sou-jenkins2.swinfra.net:8080/job/CAFapi/job/CAFapi~opensuse-opensearch1-image~US485727~CI


Which service for clients?

Taking the example Kubernetes template in the README, is the idea that clients can now just connect to the one zookeeper service, e.g. zookeeper:2181, or do they still need to target all cluster members as usual, e.g. zookeeper-1:2181,zookeeper-2:2181,zookeeper-3:2181? To ask in a more concrete way, if one were to use your docker-kafka project alongside this one, which is the appropriate setting for ZOOKEEPER_SERVERS? I tried this and Kafka starts fine just pointing at the former, but I'm not certain if that's going to ultimately be problematic under load.

You point the clients to the zookeeper:2181 service.  The client's don't care which Zookeeper instance they talk to.  The instance specific services are there for use by Zookeeper, as each instance needs to connect to all other instances concurrently to form a quorum.

@eliaslevy Thanks!


Polymorphic Encryption

Hello, great library you got here!
How could I go about extending this library to polymorphic encryption? Are there any plans to do so, and if not, what would be a good angle of attack?
Thank you

Hello ! Not sure what you mean by polymorphic encryption :/
Does it mean homomorphic encryption ? If so, you can look at https://github.com/tf-encrypted/tf-seal

Tf-seal looks very interesting! Thank you.
Section 1.2 of this document gives a simple overview of polymorphic encryption.
https://eprint.iacr.org/2016/411.pdf
What I am looking for is an open source project that provides the ability to use homomorphic encryption with multiple private keys, without duplicating the encrypted data through the use of a "transcryptor".


[MODEL EVALUATION REQUEST] ibm-granite/granite-3.0-1b-a400m-base

Model ID
ibm-granite/granite-3.0-1b-a400m-base
Model type
Decoder model (e.g., GPT)
Model languages

[X] Danish
[X] Swedish
[X] Norwegian (Bokmål or Nynorsk)
[X] Icelandic
[X] Faroese
[X] German
[X] Dutch
[X] English

Merged model
Not a merged model

Bug! #562

Results are live now 🎉


💄Minor formatting style

This PR contains following minor nits:

Sort imports
Fix yarn commands
Use caret (^) in package.

Is there a TSLint rule to do that automatically?

There might be one, I will check and add the rule in following PR.


[Bug]: Cookies are not saved when using localhost:3000

Expected Behavior
Persist the cookie between request on odoo.
Actual Behavior
The cookie is not saved on browser, losting the state of navigation.
Possible Solution
Save the cookie with domain localhost
Steps to reproduce

Run app
enter localhost:3000
add item to cart
add another item
check wrong cart.

What version of odoo integration are you using?
15
What version of Node.js are you using?
14
What browser (and version) are you using?
crome
What operating system (and version) are you using?
Ubuntu 22
Relevant log output
No response
Code of Conduct

[X] I agree to follow this project's Code of Conduct

Fixed in
https://github.com/vuestorefront-community/template-odoo/commit/e5713a292fdb22000a6efe9a10efde6428e12e86
Set https://docs.vuestorefront.io/v2/security/api-url.html make it work


Renaming connectivity resource groups

Community Note

Please vote on this issue by adding a 👍 reaction to the original issue to help the community and maintainers prioritize this request
Please do not leave "+1" or "me too" comments, they generate extra noise for issue followers and do not help prioritize the request
If you are interested in working on this issue or have submitted a pull request, please leave a comment

Description
I'm trying to provide a custom resource group name for the connectivity resources, since the default one doesn't follow the naming standards I'm using. I've managed to do it for DNS RG after looking at #292 , but I'm struggling to figure out how to change it for hub_networks. Is there any guidance for that?
For this specific environment resource group naming is a hard requirement, the other resources can be handled with resource_prefix in advanced block. I've tried to work my way through the logic here, but I'm not getting anywhere.
This is my advanced block so far:
advanced = {       custom_settings_by_resource_type = {         azurerm_resource_group = {           dns = {             (var.connectivity_resources_location) = {               name = "rg-dns"             }           }         }       }     }
Is your feature request related to a problem?
Following best practice naming standards

Describe the solution you'd like

Additional context
I know the advanced block isn't really documented, maybe not even supported? But it would be great to have some more details on the usage.

Geez, why does it always succeed right after asking for help :-)
The ONE combination I hadn't tried.. This works:
advanced = {
      resource_prefix = ""
      custom_settings_by_resource_type = {
        azurerm_resource_group = {
          dns = {
            (var.connectivity_resources_location) = {
              name = "rg-dns"
            }
          }
          connectivity = {
            (var.connectivity_resources_location) = {
              name = "rg-connectivity-westeurope"
            }
          }
        }
      }
    }


Create PLAYBACK_SEEK event

resolve #1162 creating a new event PLAYBACK_SEEK
Also, fixes a test for HLS playback spec.

Coverage decreased (-0.1%) to 76.431% when pulling cbb2f2546207bec6c8a968355a345dabaf0888c2 on joaopaulovieira:master into 796d76092da9e40f99c5a7fb1aec8223d9a775d3 on clappr:master.

Can you try to add a test case for this event? Here's a similar spec.

Yeah! I was looking for some similar test, but in the events_spec.js :sweat_smile:


NETOBSERV-252 Topology: Owners / Namespaces as nodes

This PR allow scope selection:

Node
Namespace
Owner
Resource

As a first release, I suggest to avoid fancy animations. You can either change scope in the options or click on a topology node and expand it

It will set filters to the selected node and move one scope deeper.

In the Options side panel in Topology, something causes the drop-down for Groups to stop working, meaning when you click it, nothing happens.  I encountered this several times.  I'm not sure if it is related to this change, but I am using this pull request code.

In the Options side panel in Topology, something causes the drop-down for Groups to stop working, meaning when you click it, nothing happens.

Strange. I disabled the groups for node / namespace scope but it works for other cases.
The code is ready to review, please tell me if you get that issue again

It seems to work but it is not very clear to me what the "expand" icon does:

It seems to work but it is not very clear to me what the "expand" icon does:

Here are the actions when you click on expand icon:

move scope one step deeper (Node -> Namespace -> Owner -> Resource)
add filter from current item
run the new query and display results (a fancy animation will help in the future)

So in your example, you will move to Resource scope (since you are currently showing Owner scope) and filter on prometheus-k8s StatefulSet
I'm open to any suggestions :angel:
Feel free to take a look to that conversation: https://coreos.slack.com/archives/C02939DP5L5/p1650980052628909

Spotted an issue with the "Owner" scope (discussed on slack as well) :

The metrics are still grouped by Node [PS: I write Node with first-letter cap to refer to k8s Node as opposed to "graph node"], hence resulting in several graph nodes displayed on screen for a single Owner (e.g.  flowlogs-pipeline in the screenshot above).
I guess there's two ways to fix that:

either change the logql query to not group by Node when querying for aggregation scopes that are orthogonal to Nodes, like "owner" and maybe also "namespaces". The advantage of this approach is that the resulting metrics will be computed exactly for the aggregation we're looking for; But cons: we loose the hostIP information, hence we can't show it in stats / info panel for these scopes.
merge similar graph nodes after query. It preserves hostIP information, however the metrics associated to the graph node will (I guess) be more tricky to process, we'll end up with no just 1 but N sets of metrics, one per Node.

I just deployed but I don't see the new "step into" icon, there's only the three other icons

I just deployed but I don't see the new "step into" icon, there's only the three other icons
The owners are now correctly deduplicated white_check_mark

Oops sorry I missed a renaming. Let me correct that :+1:

BTW, we can now see a clear architectural picture, this is really nice:

I think one of the next improvement we could do, is to find a way to group a service and its related workload, for an even more synthetic view. I'm not sure exactly how to do that, there's several possibilities, I created a spike task: https://issues.redhat.com/browse/NETOBSERV-340

/retest

/lgtm

/retest


Was there an issue with AMP_unset, or was there an issue with Identify.set being over-called?

Summary
In the following version, the error Amplitude Logger [Error]: Failed to save events bease the queue length exceeded 1000' appears
I experienced an error that shut down the web. When I looked up a little more, it seemed like an error that Amplitude was unable to handle too many events after accumulating a lot of events in the AMP_unset-something part of the localStorage, was there an issue with the specific version?
It doesn't happen when you downgrade to @amplitude/analytics-client-common@npm:^2.1.0, and it's good for the latest version.
The code I used is simple. I think there is an error in identify.
This error caused a fatal error on our web, so it would be good if you could quickly inform us of the related issue
The only PR I've found is the modifications below, but I don't know if this is what caused it
https://github.com/amplitude/Amplitude-TypeScript/pull/689
  const indentifyObj = new Identify();
  const sampledTarget = user.sample;

  indentifyObj.set('sampledTarget', sampledTarget);
  indentifyObj.set('sampleRate', AMPLITUDE_SAMPLE_RATE.toString());

ref version
@amplitude/analytics-client-common@npm:^2.1.1":
  version: 2.1.1

"@amplitude/analytics-core@npm:^2.1.0, @amplitude/analytics-core@npm:^2.2.2":
  version: 2.2.2
  resolution: "@amplitude/analytics-core@npm:2.2.2"

@leeyun1533 - there was a bug in version 2.5.3 which was introduced by the PR you referenced. It was reverted and 2.6.0 was published. Can you please check if you're running into the issue with 2.6.0 as well?

Thank you. It seems to have been fixed in the latest version. Could you give me a link to Revert PR?
More than 4 million users use it in our service, and the issue of excessive memory has had a bad effect on the user experience.
I think it's a critical issue and I'm trying to get a closer look at it.

Here's the PR that reverts the issue: https://github.com/amplitude/Amplitude-TypeScript/pull/687
And here's the PR for fix forward: https://github.com/amplitude/Amplitude-TypeScript/pull/689
The issue specifically happens when the server returns a bad request (for example the user id length was less than 5 characters or for other reasons). There was a bug in how we handled 4xx result codes.


Mac Wallet does not Start after Update to 2.9.3

Actual behavior:
Using a intel Mac Book Pro 2015, loaded the Wallet Update to 2.9.3, after the Update the Program didn't start again.
After less than a second the Error message: "DeFI Wallet wurde unerwartet beendet" occurred - in english: "DeFI Wallet was unexpected terminated" (more or less)
Also making a clear install after deleting all Files (including Data and Wallet Files) dit not fix this error
Expected behavior:
Program should start
How to reproduce it (as minimally and precisely as possible):

What are your environment parameters?

DeFiCh/app Version:  2.9.3
Operating System (OS):  MacOS Mojave 2.14.5
– RAM (GB):   8Gbyte
– CPU (Intel Core i5/i7/etc.):  2,9 GHz Intel Core i5
Current free storage capacity: > 25 GByte free

Anything else we need to know?
Downgrading to 2.9.2 made no change, downgrading to 2.9.1 worked

I have the same issue, late 2012 intel-mac.... also in TG channels more reports of the same issue with intel macs

Same issue - still reported at #1160

Are there any suggestions for a fix?
i have the same issue..
macOS 12.3
2 GHz Quad-Core Intel Core i5 from 2020
Sync to peer is not possible

Hi @neuriGH @Mark76DefiChain @stergios-gaidatzis , regarding the issue #1160 , we can further discuss the issue there. Kindly copy and paste your comment there, also please save your app log & node log; and attach them together with your comment, so the team can investigate. We would like to keep same issues in one thread. Thank you!

Hi, please find attached the crash report and the logs...
I closed 2.9.1. and than installed 2.9.3
2022-03-30-mark76-wallet293.zip

HI @Mark76DefiChain, this is a preview build of the upcoming app release (with the new node). Can you try if this version is opening on your end? - https://github.com/DeFiCh/app/releases/tag/v2.10.0-alpha.1
Take note it's a dev build so only run it but don't do any transactions yet