How to use callbacks.py

Hi, I am unable to get output from callbacks.py. I modified callbacks.py and run depthai_demo.py. Demo is running but I am getting no output/prints I placed in callbacks.py . Please provide an use case. This is how my callbacks.py looks like
def onNewFrame(frame, source):
    print("-------------on new frame----------")

def onShowFrame(frame, source):
    print("-------------onShowFrame----------")

def onNn(nn_packet):
    print("-------------onNn----------")

def onReport(report):
    print("-------------onReport----------")

def onSetup(*args, **kwargs):
    print("-------------onSetup----------")

def onTeardown(*args, **kwargs):
    print("-------------onTeardown----------")

def onIter(*args, **kwargs):
    print("-------------oniter----------")

Hello @iam-shanmukha, I tried running python3 depthai_demo.py -cb callbacks.py after editing the callbacks.py file and it started printing to the terminal. Are you specifying the callback file?
Thanks, Erik

Hi @Erol444. Yeah I am specifying callbacks.py. Below is the output
python3 depthai_demo.py -cb callbacks.py
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Using depthai module from:  /home/nvidia/.local/lib/python3.6/site-packages/depthai.cpython-36m-aarch64-linux-gnu.so
Depthai version installed:  <IP_ADDRESS>
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Setting up demo...
Available devices:
[0] <IP_ADDRESS> [X_LINK_BOOTLOADER]
Enabling low-bandwidth mode due to connection mode... (protocol: XLinkProtocol.X_LINK_TCP_IP)
Setting PoE video quality to 50 to reduce latency...
qt.qpa.xcb: QXcbConnection: XCB error: 148 (Unknown), sequence: 186, resource id: 0, major code: 140 (Unknown), minor code: 20

Debug output
DEPTHAI_LEVEL=debug python3 depthai_demo.py -cb callbacks.py
[2022-05-31 08:45:50.846] [debug] Python bindings - version: <IP_ADDRESS> from 2022-03-30 20:42:40 +0300 build: 2022-03-30 19:08:03 +0000
[2022-05-31 08:45:50.846] [debug] Library information - version: 2.15.2, commit: ec14f9a98670f685a2ff21f4c33eb1bc18ce836f from 2022-03-30 20:37:33 +0300, build: 2022-03-30 19:03:00 +0000
[2022-05-31 08:45:50.848] [debug] Initialize - finished
[2022-05-31 08:45:51.036] [debug] Resources - Archive 'depthai-bootloader-fwp-0.0.17.tar.xz' open: 5ms, archive read: 184ms
[2022-05-31 08:45:51.909] [debug] Resources - Archive 'depthai-device-fwp-afe8d00c868344c73ee897e26278f80a444b9763.tar.xz' open: 5ms, archive read: 1057ms
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Using depthai module from:  /home/nvidia/.local/lib/python3.6/site-packages/depthai.cpython-36m-aarch64-linux-gnu.so
Depthai version installed:  <IP_ADDRESS>
[2022-05-31 08:45:54.355] [debug] Python bindings - version: <IP_ADDRESS> from 2022-03-30 20:42:40 +0300 build: 2022-03-30 19:08:03 +0000
[2022-05-31 08:45:54.355] [debug] Library information - version: 2.15.2, commit: ec14f9a98670f685a2ff21f4c33eb1bc18ce836f from 2022-03-30 20:37:33 +0300, build: 2022-03-30 19:03:00 +0000
[2022-05-31 08:45:54.357] [debug] Initialize - finished
[2022-05-31 08:45:54.563] [debug] Resources - Archive 'depthai-bootloader-fwp-0.0.17.tar.xz' open: 5ms, archive read: 201ms
[2022-05-31 08:45:55.364] [debug] Resources - Archive 'depthai-device-fwp-afe8d00c868344c73ee897e26278f80a444b9763.tar.xz' open: 5ms, archive read: 1002ms
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Setting up demo...
Available devices:
[0] <IP_ADDRESS> [X_LINK_BOOTLOADER]
[2022-05-31 08:45:58.098] [debug] Device - OpenVINO version: 2021.4
[2022-05-31 08:45:58.098] [debug] Device - BoardConfig: {"gpio":[],"uart":[],"usb":{"flashBootedPid":63037,"flashBootedVid":999,"maxSpeed":4,"pid":63035,"vid":999},"watchdogInitialDelayMs":null,"watchdogTimeoutMs":null}
libnop:
0000: b9 05 b9 05 81 e7 03 81 3b f6 81 e7 03 81 3d f6 04 be be bb 00 bb 00
[2022-05-31 08:45:59.623] [debug] Booting FW with Bootloader. Version 0.0.16, Time taken: 1017ms
[2022-05-31 08:45:59.623] [debug] DeviceBootloader about to be closed...
[2022-05-31 08:45:59.624] [debug] XLinkResetRemote of linkId: (0)
[2022-05-31 08:46:00.216] [debug] DeviceBootloader closed, 592
[<IP_ADDRESS>] [30.155] [system] [info] Memory Usage - DDR: 0.12 / 339.99 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 24.84 / 78.28 MiB, LeonRT Heap: 2.88 / 41.54 MiB
[<IP_ADDRESS>] [30.155] [system] [info] Temperatures - Average: 44.81 °C, CSS: 45.55 °C, MSS 44.41 °C, UPA: 44.87 °C, DSS: 44.41 °C
[<IP_ADDRESS>] [30.155] [system] [info] Cpu Usage - LeonOS 6.10%, LeonRT: 0.57%
Enabling low-bandwidth mode due to connection mode... (protocol: XLinkProtocol.X_LINK_TCP_IP)
Setting PoE video quality to 50 to reduce latency...
[<IP_ADDRESS>] [31.157] [system] [info] Memory Usage - DDR: 0.12 / 339.99 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 24.84 / 78.28 MiB, LeonRT Heap: 2.88 / 41.54 MiB
[<IP_ADDRESS>] [31.157] [system] [info] Temperatures - Average: 44.75 °C, CSS: 45.77 °C, MSS 44.41 °C, UPA: 44.64 °C, DSS: 44.18 °C
[<IP_ADDRESS>] [31.157] [system] [info] Cpu Usage - LeonOS 1.59%, LeonRT: 0.06%
[2022-05-31 08:46:05.427] [debug] Schema dump: 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[2022-05-31 08:46:05.427] [debug] Asset map dump: {"map":{"/node/10/__blob":{"alignment":64,"offset":0,"size":14499200}}}
[<IP_ADDRESS>] [32.159] [system] [info] Memory Usage - DDR: 13.95 / 339.99 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 29.84 / 78.28 MiB, LeonRT Heap: 2.89 / 41.54 MiB
[<IP_ADDRESS>] [32.159] [system] [info] Temperatures - Average: 46.06 °C, CSS: 47.58 °C, MSS 45.09 °C, UPA: 45.32 °C, DSS: 46.23 °C
[<IP_ADDRESS>] [32.159] [system] [info] Cpu Usage - LeonOS 39.85%, LeonRT: 1.66%
[<IP_ADDRESS>] [32.939] [MonoCamera(2)] [info] Using board socket: 2, id: 2
[<IP_ADDRESS>] [32.939] [MonoCamera(0)] [info] Using board socket: 1, id: 1
[<IP_ADDRESS>] [32.942] [system] [info] ImageManip internal buffer size '203904'B, shave buffer size '37888'B
[<IP_ADDRESS>] [32.942] [system] [info] SpatialLocationCalculator shave buffer size '29696'B
[<IP_ADDRESS>] [32.943] [system] [info] SIPP (Signal Image Processing Pipeline) internal buffer size '16384'B

Hi @iam-shanmukha , I also noticed that depthai demo won't run callback if it's in cv mode (which is what you use), but only in QT GUI mode. By default it will use cv gui type on RPi/Jetson, could you try running python3 depthai_demo.py -cb callbacks.py -gt qt?
Thanks, Erik

Hi @Erol444, thanks but, unable to run with qt. I am attaching the log here
DEPTHAI_LEVEL=debug python3 depthai_demo.py -cb callbacks.py -gt qt
[2022-06-01 15:51:26.831] [debug] Python bindings - version: <IP_ADDRESS> from 2022-05-09 16:11:43 +0300 build: 2022-05-09 13:51:54 +0000
[2022-06-01 15:51:26.831] [debug] Library information - version: 2.15.4, commit: 1503d545d4caad91e0c1a8436c7951ff79b400ef from 2022-05-09 16:09:05 +0300, build: 2022-05-09 13:45:52 +0000
[2022-06-01 15:51:26.833] [debug] Initialize - finished
[2022-06-01 15:51:27.037] [debug] Resources - Archive 'depthai-bootloader-fwp-0.0.18+c555ac2fb184b801291c95f7f73d23bf4dd42cf1.tar.xz' open: 5ms, archive read: 200ms
[2022-06-01 15:51:27.763] [debug] Resources - Archive 'depthai-device-fwp-db9c1703c929df0de6cc99b198d2d149f1735598.tar.xz' open: 5ms, archive read: 926ms
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Using depthai module from:  /home/nvidia/.local/lib/python3.6/site-packages/depthai.cpython-36m-aarch64-linux-gnu.so
Depthai version installed:  <IP_ADDRESS>
[2022-06-01 15:51:30.066] [debug] Python bindings - version: <IP_ADDRESS> from 2022-05-09 16:11:43 +0300 build: 2022-05-09 13:51:54 +0000
[2022-06-01 15:51:30.067] [debug] Library information - version: 2.15.4, commit: 1503d545d4caad91e0c1a8436c7951ff79b400ef from 2022-05-09 16:09:05 +0300, build: 2022-05-09 13:45:52 +0000
[2022-06-01 15:51:30.069] [debug] Initialize - finished
[2022-06-01 15:51:30.267] [debug] Resources - Archive 'depthai-bootloader-fwp-0.0.18+c555ac2fb184b801291c95f7f73d23bf4dd42cf1.tar.xz' open: 4ms, archive read: 194ms
[2022-06-01 15:51:31.085] [debug] Resources - Archive 'depthai-device-fwp-db9c1703c929df0de6cc99b198d2d149f1735598.tar.xz' open: 5ms, archive read: 1012ms
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Setting up demo...
Available devices:
[0] <IP_ADDRESS> [X_LINK_BOOTLOADER]
[2022-06-01 15:51:34.967] [debug] Device - OpenVINO version: 2021.4
[2022-06-01 15:51:34.968] [debug] Device - BoardConfig: {"gpio":[],"network":{"mtu":0,"xlinkTcpNoDelay":true},"pcieInternalClock":null,"sysctl":[],"uart":[],"usb":{"flashBootedPid":63037,"flashBootedVid":999,"maxSpeed":4,"pid":63035,"vid":999},"usb3PhyInternalClock":null,"watchdogInitialDelayMs":null,"watchdogTimeoutMs":null}
libnop:
0000: b9 09 b9 05 81 e7 03 81 3b f6 81 e7 03 81 3d f6 04 b9 02 00 01 ba 00 be be bb 00 bb 00 be be
Traceback (most recent call last):
  File "depthai_demo.py", line 1078, in <module>
    runQt()
  File "depthai_demo.py", line 1062, in runQt
    app.start()
  File "depthai_demo.py", line 791, in start
    exit_code = self.startGui()
  File "/home/nvidia/depthai/gui/main.py", line 373, in startGui
    self.showSetupFrame("Starting demo...")
  File "/home/nvidia/depthai/gui/main.py", line 363, in showSetupFrame
    setupFrame = createBlankFrame(w, h)
  File "/home/nvidia/depthai/depthai_sdk/src/depthai_sdk/utils.py", line 291, in createBlankFrame
    image = np.zeros((height, width, 3), np.uint8)
ValueError: negative dimensions are not allowed
[2022-06-01 15:51:36.057] [debug] Booting FW with Bootloader. Version 0.0.16, Time taken: 925ms
[2022-06-01 15:51:36.058] [debug] DeviceBootloader about to be closed...
[2022-06-01 15:51:36.060] [debug] XLinkResetRemote of linkId: (0)
[2022-06-01 15:51:36.649] [debug] DeviceBootloader closed, 591
[<IP_ADDRESS>] [35.838] [system] [info] Memory Usage - DDR: 0.12 / 341.19 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 24.83 / 78.13 MiB, LeonRT Heap: 2.88 / 41.43 MiB
[<IP_ADDRESS>] [35.838] [system] [info] Temperatures - Average: 38.12 °C, CSS: 39.35 °C, MSS 37.94 °C, UPA: 37.48 °C, DSS: 37.71 °C
[<IP_ADDRESS>] [35.838] [system] [info] Cpu Usage - LeonOS 6.18%, LeonRT: 0.58%
[<IP_ADDRESS>] [36.839] [system] [info] Memory Usage - DDR: 0.12 / 341.19 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 24.83 / 78.13 MiB, LeonRT Heap: 2.88 / 41.43 MiB
[<IP_ADDRESS>] [36.839] [system] [info] Temperatures - Average: 38.59 °C, CSS: 39.11 °C, MSS 38.18 °C, UPA: 38.65 °C, DSS: 38.41 °C
[<IP_ADDRESS>] [36.839] [system] [info] Cpu Usage - LeonOS 1.82%, LeonRT: 0.06%
[<IP_ADDRESS>] [37.840] [system] [info] Memory Usage - DDR: 0.12 / 341.19 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 24.83 / 78.13 MiB, LeonRT Heap: 2.88 / 41.43 MiB
[<IP_ADDRESS>] [37.840] [system] [info] Temperatures - Average: 38.30 °C, CSS: 38.88 °C, MSS 37.94 °C, UPA: 38.41 °C, DSS: 37.94 °C
[<IP_ADDRESS>] [37.840] [system] [info] Cpu Usage - LeonOS 0.85%, LeonRT: 0.04%
[<IP_ADDRESS>] [38.841] [system] [info] Memory Usage - DDR: 0.12 / 341.19 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 24.83 / 78.13 MiB, LeonRT Heap: 2.88 / 41.43 MiB
[<IP_ADDRESS>] [38.841] [system] [info] Temperatures - Average: 38.53 °C, CSS: 39.35 °C, MSS 37.48 °C, UPA: 38.41 °C, DSS: 38.88 °C
[<IP_ADDRESS>] [38.841] [system] [info] Cpu Usage - LeonOS 0.61%, LeonRT: 0.04%
Enabling low-bandwidth mode due to connection mode... (protocol: XLinkProtocol.X_LINK_TCP_IP)
Setting PoE video quality to 50 to reduce latency...
[2022-06-01 15:51:44.612] [debug] Schema dump: 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[2022-06-01 15:51:44.612] [debug] Asset map dump: {"map":{"/node/14/__blob":{"alignment":64,"offset":0,"size":14499200}}}
[<IP_ADDRESS>] [39.848] [system] [info] Memory Usage - DDR: 13.95 / 341.19 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 29.85 / 78.13 MiB, LeonRT Heap: 2.89 / 41.43 MiB
[<IP_ADDRESS>] [39.848] [system] [info] Temperatures - Average: 39.29 °C, CSS: 40.97 °C, MSS 38.65 °C, UPA: 38.18 °C, DSS: 39.35 °C
[<IP_ADDRESS>] [39.848] [system] [info] Cpu Usage - LeonOS 17.55%, LeonRT: 1.97%
[<IP_ADDRESS>] [40.344] [MonoCamera(3)] [info] Using board socket: 2, id: 2
[<IP_ADDRESS>] [40.345] [MonoCamera(0)] [info] Using board socket: 1, id: 1
[<IP_ADDRESS>] [40.348] [system] [info] ImageManip internal buffer size '203904'B, shave buffer size '37888'B
[<IP_ADDRESS>] [40.348] [system] [info] SpatialLocationCalculator shave buffer size '29696'B
Error while running demo script... Command '"/usr/bin/python3" depthai_demo.py -cb callbacks.py --noSupervisor --guiType qt' returned non-zero exit status 1.
Waiting 5s for the device to be discoverable again...
[2022-06-01 15:51:50.924] [debug] Python bindings - version: <IP_ADDRESS> from 2022-05-09 16:11:43 +0300 build: 2022-05-09 13:51:54 +0000
[2022-06-01 15:51:50.924] [debug] Library information - version: 2.15.4, commit: 1503d545d4caad91e0c1a8436c7951ff79b400ef from 2022-05-09 16:09:05 +0300, build: 2022-05-09 13:45:52 +0000
[2022-06-01 15:51:50.926] [debug] Initialize - finished
[2022-06-01 15:51:51.124] [debug] Resources - Archive 'depthai-bootloader-fwp-0.0.18+c555ac2fb184b801291c95f7f73d23bf4dd42cf1.tar.xz' open: 4ms, archive read: 194ms
[2022-06-01 15:51:51.903] [debug] Resources - Archive 'depthai-device-fwp-db9c1703c929df0de6cc99b198d2d149f1735598.tar.xz' open: 5ms, archive read: 973ms
/home/nvidia/.local/lib/python3.6/site-packages/jwcrypto/jwa.py:8: CryptographyDeprecationWarning: Python 3.6 is no longer supported by the Python core team. Therefore, support for it is deprecated in cryptography and will be removed in a future release.
  from cryptography.exceptions import InvalidSignature
Setting up demo...
Traceback (most recent call last):
  File "depthai_demo.py", line 1081, in <module>
    runOpenCv()
  File "depthai_demo.py", line 1071, in runOpenCv
    demo.run_all(confManager)
  File "depthai_demo.py", line 127, in run_all
    self.setup(conf)
  File "depthai_demo.py", line 184, in setup
    self._deviceInfo = getDeviceInfo(self._conf.args.deviceId, args.debug)
  File "/home/nvidia/depthai/depthai_sdk/src/depthai_sdk/utils.py", line 145, in getDeviceInfo
    raise RuntimeError("No DepthAI device found!")
RuntimeError: No DepthAI device found!
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
  File "depthai_demo.py", line 356, in stop
    self._pm.closeDefaultQueues()
AttributeError: 'Demo' object has no attribute '_pm'
Sentry is attempting to send 2 pending error messages
Waiting up to 2 seconds
Press Ctrl-C to quit

reminder :)

Hello @iam-shanmukha , great that you got it working with QT GUI! Regarding working with CV GUI - we are a bit short on engineering resources, but I will add this as a FeatureRequest on this repo. Thanks!


How could I implement a vertically-sliding door?

Not really an issue, but I couldn't find a better place to ask about this. 😅
I'd like to implement a sliding door: in short, it should behave like a static body, but I'd like to be able to animate its position (either vertically or horizontally). Could you share any quick pointers to the right approach with qu3e? I'm evaluating possible candidates for my game physics and I'd like to get a better idea before getting into code.
I love how simple and lightweight qu3e is, great job!

The best way is to make your door a eKinematicBody. Kinematic bodies are like dynamic bodies, but do not react to collisions (they have infinite mass). Then you can set the velocity of your door, and the physics engine will move it for you. Other dynamic bodies that hit the door will be pressed away or squashed appropriately.
Typically your player controller will also be implemented with a kinematic body. Kinematic bodies do not collide with one another -- the idea is you would code in your own custom logic for handling collisions between the player and the world. But, if this is too much work, you can try making your player controller with a dynamic body, and manipulate the dynamic body by applying impulses. In my opinion using a dynamic body here is more difficult to tune, and in the end inferior to using a custom kinematic body solution.


feat: add inference-net as a provider

Title:

Adds inference.net as a provider.

Related Issues: (optional)

#574

There's no full documentation yet, but as per their examples for now added support for chatComplete function only.

Please resolve merge conflicts


Make commiter name/email configurable through automation.xml file

Currently commiter name/email are hardcoded in the Configuration.php
it would be good to make those default values that can be changed in the automation.xml

So far I did not had a single use case for this feature but if anyone would ever need it we can discuss it using https://github.com/aeon-php/automation/discussions


Template network contextualization doesn't work with Open Nebula 6.8.0 and RHEL9

Description
We're trying to instantiate a RHEL 9 template with a static IP. We installed the context packages onto the template according to this: https://github.com/OpenNebula/one-apps/wiki/linux_installation. RHEL 9 uses NetworkManager by default. The hostnames and static IPs show up just fine after instantiating, however, the gateway and DNS servers never get set. I've attached a picture of the template variables, I've tried every combination of params that I can think of in here, including removing NETWORK = "YES" and setting each ETH0 param manually and the DNS servers never get set.
To Reproduce
Instantiate template with static IP

Expected behavior
The given DNS servers should be associated with the network interface.
Details

Affected Component: Sunstone
Hypervisor: KVM
Version: 6.8.0

Additional context
I opened support case 54333 for this issue and it was prematurely closed. The following workaround was given:
In Sunstone:

Go to the Virtual Networks page
Select the network that you want to use (ID 12)
Click on "Update" and navigate to the "Context" tab
Modify the Gateway and DNS parameters and click "Update"

While this does work, manually updating every network object if our DNS servers ever change is not a viable long-term solution. This is also not documented anywhere, including the known issues page, so this issue is needed for visibility in case others experience the same issue.

Progress Status

[ ] Code committed
[ ] Testing - QA
[ ] Documentation (Release notes - resolved issues, compatibility, known issues)

After testing: VM-specific ETH* context parameters can not be set, vnet context is being used. Same issue as in issue#6606
Issue related to issue#6552

After testing: VM-specific ETH* context parameters can not be set, vnet context is being used. Same issue as in issue#6606
Issue related to issue#6552

This issue is different, it seems the parameter set is properly set by ignored by the context packages. I'm moving this issue to one-app repo


Benchmark code

Could you share the code for your benchmark? Which version of DECIMER did you use? I highly suspect that you have evaluated the performance of an outdated version of our tool in your publication.

@Jiacai-Yi?


Add function to calculate ICs

Include variable burn in time; option for dynamic calculation of initial conditions given changing parameter values?

Same as issue #13

Same as issue #13


feat(cmake): add conditional builds for falcoctl and rules paths

There are systems, like Nix derivations where the build process does not have network access in order to enforce reproducibility. This patch allows people building Falco to optionally skip the build of falcoctl with -DADD_FALCOCTL_DEPENDENCY=OFF and point to their own self-backed, or pre-fetched rules files with -DFALCOSECURITY_RULES_FALCO_PATH=<some-path> and -DFALCOSECURITY_RULES_LOCAL_PATH=<some-path>.
For context, I needed to apply these patches while building the project with Nix in https://github.com/tembleking/falco-nix but I think that would be benefitial for the community to have also these options open, and that would also make Falco feasible to be added to the nixpkgs repository at https://github.com/nixos/nixpkgs
/kind feature
/kind release
/area build
- When building Falco, users can now disable the build of `falcoctl` with the engine, by specifying the CMake flag `-DADD_FALCOCTL_DEPENDENCY=OFF`.
- When building Falco, users can now specify the source paths of both the rules files, and the local rules files with the CMake flags `-DFALCOSECURITY_RULES_FALCO_PATH=<some-path>` and `-DFALCOSECURITY_RULES_LOCAL_PATH=<some-path>`.

[APPROVALNOTIFIER] This PR is NOT APPROVED
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Welcome @tembleking! It looks like this is your first PR to falcosecurity/falco 🎉

/milestone 0.39.0
I really like this small patch; it's great to have Falco building in as many env as we can :)

LGTM label has been added.  Git tree hash: a3cfc97834d3b14e1e02854cea7dc9ca1de9cbb7

[APPROVALNOTIFIER] This PR is APPROVED
This pull-request has been approved by: FedeDP, tembleking
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[APPROVALNOTIFIER] This PR is APPROVED
This pull-request has been approved by: Andreagit97, FedeDP, tembleking
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Update no of words in string.c

Fixed a bug where the output wasn't correct. Handled an edge case.

Thanks Rutuj, the changes have been merged to the main branch. I really appreciate your efforts. Keep it up!


[zabbix-community/zabbix] Add cronjob to purge specifics tables

Hi,
Is it possible to add cronjobs to purge the "alerts" table like the cronjob ha_nodes_autoclean with the possibility to enable it or not and set the number of days to keep ?
For more context, we use a notification action who resend alerts every 5 minutes. An entrie are create in the "alerts" table every 5min per alert not resolved.
David

Hi @david-moreau david-moreau!
Thanks for report this feature.
Do you would like to open a Pull Request to implement this? We will appreciate your contribution.
Hi @sa-ChristianAnton!
What you think about this feature? Is possible? I don't know how to implement this.

Hi @aeciopires
I will try to make a pull request but it will take me some time.
To implement this feature, we can use the same structure like cronjob-hanodes-autoclean and launch this sql request found on this repo
DELETE FROM alerts WHERE (UNIX_TIMESTAMP(NOW()) - clock) > (@history_interval * 24 * 60 * 60);
I don't know if we need to add another table purge like 'events' or 'acknowledges'
David

Hi! I have thought about this and actually don't believe this should be a feature of this Helm chart. The reason: Zabbix server writing into the alerts table is totally normal behavior and purging the table is more a workaround for a very specific usecase rather than something usually ever being necessary even in big productive environments.
What I would love to see instead as a pull request is a more generalistic approach: in values.yaml, a data structure "extraCronJobs" could be added which may contain a "pluggable" way to add this kind of things. I would even like the idea of supplying an example values.yaml containing exactly this implementation described for your specific use case.
What do you think, is this a good approach?

Little additional information regarding the alerts table: it should really not be necessary to clean it using a cron job:
The alerts table has constraints to the events table entries. Meaning that if an entry from events table that have been making the alert happen (events table contains "problems", alerts table contains "notifications sent" and "scripts executed"), the corresponding alerts table entries will also be deleted.
zabbix=# \d alerts
                                 Table "public.alerts"
    Column     |          Type           | Collation | Nullable |        Default
---------------+-------------------------+-----------+----------+-----------------------
 alertid       | bigint                  |           | not null |
 actionid      | bigint                  |           | not null |
 eventid       | bigint                  |           | not null |
 userid        | bigint                  |           |          |
 clock         | integer                 |           | not null | 0
 mediatypeid   | bigint                  |           |          |
 sendto        | character varying(1024) |           | not null | ''::character varying
 subject       | character varying(255)  |           | not null | ''::character varying
 message       | text                    |           | not null | ''::text
 status        | integer                 |           | not null | 0
 retries       | integer                 |           | not null | 0
 error         | character varying(2048) |           | not null | ''::character varying
 esc_step      | integer                 |           | not null | 0
 alerttype     | integer                 |           | not null | 0
 p_eventid     | bigint                  |           |          |
 acknowledgeid | bigint                  |           |          |
 parameters    | text                    |           | not null | '{}'::text
Indexes:
    "alerts_pkey" PRIMARY KEY, btree (alertid)
    "alerts_1" btree (actionid)
    "alerts_2" btree (clock)
    "alerts_3" btree (eventid)
    "alerts_4" btree (status)
    "alerts_5" btree (mediatypeid)
    "alerts_6" btree (userid)
    "alerts_7" btree (p_eventid)
    "alerts_8" btree (acknowledgeid)
Foreign-key constraints:
    "c_alerts_1" FOREIGN KEY (actionid) REFERENCES actions(actionid) ON DELETE CASCADE
    "c_alerts_2" FOREIGN KEY (eventid) REFERENCES events(eventid) ON DELETE CASCADE
    "c_alerts_3" FOREIGN KEY (userid) REFERENCES users(userid) ON DELETE CASCADE
    "c_alerts_4" FOREIGN KEY (mediatypeid) REFERENCES media_type(mediatypeid) ON DELETE CASCADE
    "c_alerts_5" FOREIGN KEY (p_eventid) REFERENCES events(eventid) ON DELETE CASCADE
    "c_alerts_6" FOREIGN KEY (acknowledgeid) REFERENCES acknowledges(acknowledgeid) ON DELETE CASCADE

Events table cleanup is part of housekeeper and possible to set up in Administration->General->Housekeeping (default: 365 days).
Just checked that in a live installation using Postgres.

Hi @sa-ChristianAnton ,
You are right it's clearly a workaround and add extraCronJobs is a better idea.
I know the dependence between event table and alerts table. Currently I have to keep the events for several months but the repush of alerts every 5 minutes causes an alarming increase of the alerts table.
David

closing issue as "not planned". Looking forward for pull requests.


bst show expands '*' to artifact refs

See original issue on GitLab
In GitLab by [Gitlab user @aevri] on Mar 13, 2019, 18:26
Summary
If you try bst show '*', then you will be presented with an error like:
Cannot perform this operation with artifact refs:

    running-commands/hello/8276376b077eda104c812e6ec2f488c7c9eea211ce572c83d734c10bf241209f
    running-commands/hello/5c4ed6545bfab8fde4a19fe01e8b1d5534ad3f5419f3c17eb558109c86432cea

If you try instead with bst show '*.bst' then you get what you might expect:
      cached d23ade23cf21ef256f1b1c6c7e25af5d0a69346cacb38a411d1eeed279f548da alpine.bst
      cached eaa9ad447253da4a89215c783b73d68de8e62212174d81d04ccc7e6dcc088dde base.bst
      cached 8276376b077eda104c812e6ec2f488c7c9eea211ce572c83d734c10bf241209f hello.bst

The artifact refs are invalid input for bst show, as such we should not have the CLI expand wildcards to existing artifact refs for this command.

In GitLab by [Gitlab user @aevri] on Mar 13, 2019, 18:29
mentioned in merge request !1223

In GitLab by [Gitlab user @tristanvb] on Mar 14, 2019, 06:42

If you try bst show '*', then you will be presented with an error like:

How is bst show finding artifact refspecs ?
As I understand it, bst show should only accept .bst files, while bst artifact show would expect refspecs.

If you try instead with bst show '*.bst' then you get what you might expect:

Hmmm, this looks like it might only happen in the unlikely case that you are in a subdirectory which has bst files, instead of invoking it from the regular place (the project directory).
This seems like an integration bug to me:

Passing a wildcard to bash will automatically cause filename expansions
Elements passed to BuildStream are not filenames, they are targets

I would rather expect that * means "All targets", which should not be limited to elements which are in the current directory, or elements which are in the toplevel elements directory only.

In GitLab by [Gitlab user @aevri] on Mar 14, 2019, 08:47
Oh! I thought this was a deliberate design choice :)
Note that bash plays no part here - the asterisk is single-quoted.
It happens because of this:
https://gitlab.com/BuildStream/buildstream/blob/6a1e74619e0009ca5611bba025b8dcf08bec353e/buildstream/_stream.py#L1439
Stream._load() now does _classify_artifacts on all target strings. If the target string ends with .bst, e.g. *.bst then it's an element target, otherwise it's an artifact target.
This means that all commands that accept targets now also accept artifact targets, and tell you off for using them :) (except for artifact log of course, that actually wants them).

In GitLab by [Gitlab user @aevri] on Mar 20, 2019, 16:37
[Gitlab user @tristanvb] - I'm thinking the behaviour of bst show '*' can be considered 'broken', as it does something surprising to most of us and leaves the user mostly in the dark as to why it happened. These 'artifact refs' are largely undocumented.
Do you agree? If so I can work up some proposals for how to fix it :)

In GitLab by [Gitlab user @tristanvb] on Mar 24, 2019, 09:12

Do you agree? If so I can work up some proposals for how to fix it :)

I certainly agree, I don't think bst show is supposed to accept refspecs anyway; I would expect different behaviors for bst show and bst artifact show.
I expect formats and options to bst artifact show to be different as well, since there are different things you can show about an artifact and an element (like the size of the artifact, build date, etc).
The difference is that we did decide to accept the opposite thing as a matter of convenience, i.e. one should be able to do bst artifact show <element.bst>.
Right now there is no bst artifact show command, but I do believe there should be one which behaves similarly to bst show; regardless of this, I do believe that we had decided that bst artifact commands could accept element names, and those would be expanded to the artifact ref spec which would be valid for that element in the current project state (so it would require loading the bst files in order to resolve the cache key for those parameters).
The opposite of this (accepting artifacts as element names in other commands), of course doesnt seem to make sense.

In GitLab by [Gitlab user @tmewett] on Aug 12, 2019, 10:18
I'm not entirely sure what the correct behaviour for wildcard usage in commands is -- I can't find any documentation for it.
Edit: it is documented here, but as was said, the wildcard expansion is done on many more commands https://buildstream.gitlab.io/buildstream/using_commands.html#bst-artifact-log

In GitLab by [Gitlab user @tmewett] on Aug 22, 2019, 16:36
Some relevant implementation info:

Target names given on the command line are glob-expanded and differentiated as either element paths or artifact refs by Stream._classify_artifacts
The actual glob expansion occurs in Stream._classify_artifacts for elements and in BaseCache._list_refs_mtimes (called by ArtifactCache.list_artifacts) for artifacts
Stream._classify_artifacts is called by Stream._load, so any function loading elements will perform this glob expansion whether it wants to or not
Disallowing artifacts is done with the load_refs boolean argument to _load which raises an error when _classify_artifacts gives any artifacts. However it does not prevent artifact glob expansion from occuring. (This is the root cause of this issue)

In my opinion, the glob expansion is too deep and far away from the CLI entry point, meaning individual commands have little control over what types of target can be expanded. Maybe it should be stripped out of internal functions and done in _frontend/cli.py by the top-level commands themselves.

In GitLab by [Gitlab user @tristanvb] on Nov 6, 2020, 06:58
changed title from {-Element ref spec might be confusing-} to {+bst show expands '*' to artifact refs+}

In GitLab by [Gitlab user @tristanvb] on Nov 6, 2020, 06:58
changed the description

In GitLab by [Gitlab user @tristanvb] on Nov 10, 2020, 08:00
I seem to have completely overlooked [Gitlab user @tmewett]'s investigation here, diving right into the empty pool, I smashed my face directly into Stream._classify_artifacts() as well.
[Gitlab user @tmewett]'s assessment is correct, this logic is burried too deep and applied much too widely, this needs to be split up such that either the element globbing needs to be done in the frontend (as [Gitlab user @tmewett] suggests), or at least the intentions stemming from each command is passed down via some arguments to Stream so that Stream can do the appropriate thing.

In GitLab by [Gitlab user @tristanvb] on Nov 11, 2020, 07:27
While looking into this, I can see that for some reason fnmatch is being used for the glob filtering, I think this is also wrong.
Firstly, it does not match what one would expect from normal shell globbing, bst show '*.bst' mistakenly yields elements like vm/config/ostree.bst, which should only be reachable by way of */*/*.bst, or with globstar **.bst (or simply **).
More importantly, the behavior is not an exact match to what one should expect when using BuildStream, it would make more sense to handle all globbing with utils.glob() and as such, have the same behavior when handling glob patterns in split rules as we do when matching existing artifacts or elements.

In GitLab by [Gitlab user @tristanvb] on Nov 11, 2020, 10:23
mentioned in commit 3e8c7205d7eaf82aa38d8ece0fb701694327bb52

In GitLab by [Gitlab user @tristanvb] on Nov 11, 2020, 11:19
mentioned in commit 6df8570a4136ab8753ea14dac9b58af91e497840

In GitLab by [Gitlab user @tristanvb] on Nov 13, 2020, 09:27
mentioned in commit c1c65249d220bdee8bebba23a1092af1fa916478

In GitLab by [Gitlab user @tristanvb] on Nov 17, 2020, 05:04
mentioned in commit d7f637943470ec655b1e1f485db72427f93b8c0c

In GitLab by [Gitlab user @tristanvb] on Nov 19, 2020, 06:54
mentioned in commit 6fd3b0b9467c9baa83aa959237ce8c8acc7c0d6a

In GitLab by [Gitlab user @tristanvb] on Nov 20, 2020, 08:04
mentioned in commit 9eee3353a9342ff697e0260ffa58700b857b6288


Adding an apache2 license file

Don't know how we forgot this, haha

cursed DCO.... always ruining my commits


Remove Gramine dependencies that are not needed at runtime

Remove Gramine packages that are not needed at runtime. These packages are needed in build time and not needed in run time.

This change is

Looks like @amathew3  pushed more changes not realizing that @dimakuv had already fixed the new issue. The branch is in a mess now I think. He is working on reverting the changes.


Mockup server

Pull Request Test Coverage Report for Build 479

1 of 19 (5.26%)  changed or added relevant lines in 2 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.9%) to 92.897%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

bddrest/mockupserver/init.py
0
18
0.0%

Totals

Change from base Build 473:
-0.9%

Covered Lines:
1674

Relevant Lines:
1802

💛  - Coveralls


Documentation on how to extend the crawler ecosystem

Description
This agentless crawler ecosystem looks very interesting.  I would like to contribute to it but I'm new to both this project and to Python.  Can someone familiar with this project add some information around how the plugin architecture works such as prerequisites and class interface contracts.  How this project is structure.  If it is structured like a standard Python app, maybe a link to some source of truth on what this looks like.  And if there are any Python specific tools/concepts/libs that this project depends or focuses around, that would be good to detail out as well.

See Section 3.1.5 here: http://www.cs.toronto.edu/~sahil/suneja-mw17-2-TR.pdf


Minor documentation error

There is a minor error on this page of the v4 documentation.
The data-target="#exampleModal" is supposed to refer to id="myModal"
So in order for the modal to work, the id has to be identical. I expect the second id should be changed to exampleModal to avoid confusion from the other modals.

fixed ages ago https://github.com/twbs/bootstrap/pull/21671

Hmm.. I see that it was supposed to be fixed ages ago, but the live documentation still contains the wrong code?

the live docs are for the alpha 6 release. the repo has moved beyond that. once beta 1 is released the fixed docs will go up

Ok. Thanks :)


Test CI

Seeing some Windows failures over in https://github.com/dask/dask/pull/9731 that I think are unrelated...

Windows builds have fixed themselves (woo). See https://github.com/dask/dask/issues/9734 for more details.


Content Block Media is missing an autoid attribute for optional CTA

In V1.5.0, in the Content Block Media Pattern, there is an optional content group CTA:

However there is no data-autoid attribute for this Group CTA, so our ingestion logic cannot make this markup optionally renderable.  Can you please fix it by adding an auto-id attribute to this element?

Defect review meeting:  This feature request (they would debate whether this is a feature request or not) is needed in MVP.  This missing data-autoid affects the analytics.  Drupal can go into Production without this fix, but that will create technical debt on both their team and the Analytics teams.  Requesting that we reconsider and include this fix in a patch.  Delivery date of the patch would be Friday, April 3.


Generate cadl-location.yaml in Java sdk automation pipeline

please hold on this work because I will confirm with Wes whether we must use the common script.

Confirmed in chat, @raych1 will have a script to automate this, we will wait for the script to be ready and integrate with it.


soapProxy + "https://" in WSDL's endpoint address does not work

Fix: Route to internal proxy and from there use SSL


Add remote client log to file

Logging messages from the dependency libraries should not log onto the
screen when using the remote client.  This patch writes logging to
~/.config/containers/podman-remote.log
Fixes #3299
Signed-off-by: Jhon Honce<EMAIL_ADDRESS>

I think this needs to be documented in the man page.

LGTM

/lgtm


Diffusion model generating identical images after DDPO fine-tuning

System Info
System Info

transformers version: 4.44.2
Platform: Linux-5.15.0-1068-aws-x86_64-with-glibc2.31
Python version: 3.9.19
Huggingface_hub version: 0.24.7
Safetensors version: 0.4.5
Accelerate version: 0.34.2
Accelerate config:    not found
PyTorch version (GPU?): 2.4.1+cu121 (False)
Tensorflow version (GPU?): not installed (NA)
Flax version (CPU?/GPU?/TPU?): not installed (NA)
Jax version: not installed
JaxLib version: not installed
Using distributed or parallel set-up in script?: Yes, trying in a multiGPU node

Information

[ ] The official example scripts
[X] My own modified scripts

Tasks

[ ] An officially supported task in the examples folder
[X] My own task or dataset (give details below)

Reproduction
I fine-tuned a SD model using the DDPO model following the script https://github.com/huggingface/trl/blob/main/examples/scripts/ddpo.py. I have a custom reward model and a prompt dataset. I fine-tuned on a small prompt set (30 prompts) to check if the model is overfitting on the rewards. The rewards are increasing over steps.
For inference I used the following script to generate images for some sample prompts:
import torch
from trl import DefaultDDPOStableDiffusionPipeline

torch.manual_seed(42)
### Pre-trained model inference
pipeline = DefaultDDPOStableDiffusionPipeline(
        "runwayml/stable-diffusion-v1-5"
    )

device = torch.device("cuda")
pipeline.vae.to(device)
pipeline.text_encoder.to(device)
pipeline.unet.to(device)

prompts = ["Tom Cruise in a yellow suit and a pink tie",
           "A red elephant next to a brown dog",
           "A blue building next to a red elephant"]
results = pipeline(prompts)

for prompt, image in zip(prompts, results.images):
    image.save(f"./example_images/{prompt}_pretrained.png")

#### Fine-tuned model inference

prompts = ["Tom Cruise in a yellow suit and a pink tie",
           "A red elephant next to a brown dog",
           "A blue building next to a red elephant"]

pipeline = DefaultDDPOStableDiffusionPipeline(
        "runwayml/stable-diffusion-v1-5"
    )
#pipeline.sd_pipeline.load_lora_weights("/checkpoints/shashankgupta/ddpo_test2")

device = torch.device("cuda")

pipeline.vae.to(device)
pipeline.text_encoder.to(device)
pipeline.unet.to(device)

results = pipeline(prompts)

for prompt, image in zip(prompts, results.images):
    image.save(f"./example_images/{prompt}_ft.png")

Model was generating different images until I realised that I didn't use manual_seed when loading the fine-tuned model. When I apply manual_seed the second time, the fine-tuned model generates almost identical images.
Expected behavior
After RL fine-tuning, the diffusion model should generate different images for the same prompt.

Update: I trained with LoRA fine-tuning, which was resulting in similar models. Fine-tuned the entire model, it generates different images.

Update: I trained with LoRA fine-tuning, which was resulting in similar models. Fine-tuned the entire model, it generates different images.


set up hosting for Stockpile App

The app is hosted on Firebase: https://phonegap-stockpile-app.firebaseapp.com/

Closed with #19


"sortBy" is not controlable

sortBy prop only initializes the table's sort but does not change it.
Also valid for sortAscending

Fixed.


Ability to Reorder Courses

Changes

[x] Moved Semester and Course to global types
[x] Make Planner.tsx rely on derived types
[x] Make @dnd-kit IDs generate in a useMemo instead of in callbacks
[x] Add sortable semester tiles
[ ] Make course sortable when dragging onto new semester tile

Abandoning this for now because it's hella laggy to implement sortable courses.


Ansible: Fix linter errors

Checklist

[ ] commit message has one of the standard prefixes
[ ] faq.md updated if appropriate
[ ] other documentation is changed or added (if applicable)
[ ] playbook changes run through VPC or QPC (if you have access)
[ ] VPC/QPC not applicable for this PR
[ ] for inventory.yml changes, bastillion/nagios/jenkins updated accordingly

Closing this as not required, as the fix needs more investigation.


DCOS-9891: Renaming Tasks to Instances in pods

This PR addresses task naming issues:

On the collection view Tasks are now called Instances on the pods (I don't have a large enough screen to get a screenshot of this)
On the pod instance detail view, the filter header shows Showing X of X Instances instead of tasks.

Ok, so apparently all 'Tasks' should be named 'Instances', if that's correct and we are in hurry we can merge this, however this means that all variable names must be changed to instanceXXX from taskXXX

Is this correct?

@wavesoft @MatApple Nope. We should only change "Task" to "Instance" in the overview and service detail views, but shouldn't touch the task detail and node page. I'll update the branch respectively.

The following labels/names have changed:

/cc @leemunroe @pyronicide @marcomonaco

LGTM 🚢

good 🚢

👍


Githubaction

resolve #32

so far the action running at https://github.com/SamYuan1990/GM-interoperability/actions and passed


Not inline screenshot when using image compression -z

Hi guys, I just wonder to use image compression (-z) to reduce my report file size, but after implement this, screenshot not shown in CI report attachment. But I can't also use 2 BlockArguments in same time (-i and -z). Can I still reduce image size and inline it too? Thankyou.

Would be nice to allow those two arguments ... I will add the "Feature" label.

Could the images be resized before the HTML is built? Seems like resizing before inlining would make the resulting file smaller.

This should be fixed by #253 -z and -i may be run simultaneously. This also implicitly converts the heic encoding to jpeg, since Chrome does not natively support heic/heif..


Shopify's Playbook for Scaling Machine Learning /  Solmaz Shahalizadeh @ Shopify Engineering Blog

URL: https://shopify.engineering/shopify-playbook-scaling-machine-learning
Review (1-2 sentences):  If you're at the start of building ML infrastructure and launching models it's worth reading. Good structured points about what to focus on in each period of maturity.

Published in Digest #24.


error in parsing numbers need to look

for( i in 0...200 ){
    var d: Doudecimal = i;
    trace( i + ' = ' + d );
}

have re-implemented int->doudecimal.  It may not be reliable over 0xFFFFFF due to target platform limitations


Made an NPM Package-able version of amp-url-creator.js

Hello,
I went ahead and followed the process of: https://github.com/ampproject/amphtml/tree/master/extensions/amp-viewer-integration/0.1/messaging to create an npm package for amp-url-creator.js. This is needed by amp-recaptcha-input for generating subdomains when embedding the recaptcha bootstrap iframe.
This is similar to (the incomplete) amp-cache-url generator from AMP Toolbox Cache Url. However, this amp-url-creator supports the SHA 256 fallback that is also present in the viewer, and the Cache Library.
Lastly, this does some other small project maintenance, to fix the test suite on local devices, and update references to amp-url-creator.js in other files.
Also, the README links to a npm package URL I hope to upload the package to once this passes review. 😄
Passing Tests

@torch2424 why do we need to create a second package for this? Would it make more sense to integrate this into https://github.com/ampproject/amp-toolbox/tree/master/cache-url and keep this as the default implementation?

Closing this...
If we decide to go another route, this can always be re-opened :)

Perfect - thanks a lot!


Extend message endpoint with parameters for producer, subscription and consumer

User story

As a frontend-dev
I need parameters in the message endpoint
So that I can show the messages for producers, subscriptions and consumers in the UI

Acceptance criteria

when the producer parameter is set, only {number} messages for this producer are returned
when the subscription parameter is set, only {number} messages for this subscription are returned
when the consumer parameter is set, only {number} messages for this consumer are returned
=> for the consumer only the acknowledge messages should be considered (you can use the getUnackedMessages() method)

Definition of done (DoD)

Feature is done when the acceptance criteria are fullfiled
Feature is done when there are test where it is necessary and they pass
Feature is done when the linter passes
Feature is done when it is merged onto our main branch (after the code has been reviewed by at least one other person)
Feature is done when the code has been documentend or commented properly

DoD general criteria

Feature has been fully implemented
Feature has been merged into the mainline
All acceptance criteria were met
Product owner approved features
All tests are passing
Developers agreed to release

Producers and Subscriptions are a good idea but i don´t see any chance to geht the messages bei consumer :/

This is how we thought about this:
If it is possible to retrieve the subscriptions of the topic, then it should also be possible to retrieve the consumers for each subscription (using getConsumers() on the subscriptionStats).
This would mean, that it is possible to map consumers to subscriptions.
If the previously mentioned mapping is established it would be possible to iterate over the mapped subscriptions (for the consumer from the parameter) and retrieve the messages the same way as it would be done when querying for subscriptions directly.
The messages of the so identified subscriptions would then have to be ordered in a single logical queue (by timestamp or sqn) and could then be traversed and retrieved.
The only part that we fought might be a problem, is to identify where the beginning of messages that have not yet been acknowledged is.
We hope that the getUnackedMessages() method of the consumerStats is usable to move back in the queue and start at the acknowledged "slot".
If there are any issues you noticed, or things we did not think about, please let us know!

Your thoughts are great but in the solution you described every consumer has the same messages like its subscription. This is in some cases right but not in all. If you have a failover subscription your solution is not working i think. https://pulsar.apache.org/docs/3.0.x/concepts-messaging/#failover--partitioned-topics

Okay, you are absolutely right. If not all consumers receive the same messages then the proposed approach does not work.
Therefore we will remove the functionality to retrieve the messages for the consumers.
Thank you for your help! 😄


Bump to 0.11.0

@bors: r+

:pushpin: Commit 1f889f7 has been approved by alexcrichton

r? @wycats
(rust_highfive has picked a reviewer for you, use r? to override)

:hourglass: Testing commit 1f889f7 with merge 59238e8...

:sunny: Test successful - cargo-cross-linux, cargo-linux-32, cargo-linux-64, cargo-mac-32, cargo-mac-64, cargo-win-gnu-32, cargo-win-gnu-64, cargo-win-msvc-32, cargo-win-msvc-64


⚠ Bofrost.at has degraded performance

In 3a95bd7, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1702 ms

Resolved: Bofrost.at performance has improved in 55c9cf8.


[Event Request] Table 36 "Sales Header" - OnBeforeSynchronizeForReservations

We are migrating our code from NAV 2018 to BC16.4. In the Table 36 "Sales Header", in the procedure SynchronizeForReservations, we need to add our code at specific places. To do so, we need a IsHandled flag and an event publisher, like this :

With this integration event :

Do you think it could be possible ?
Thank you for your work.

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. We will update this issue with information about availability.


Multi and Auto Compressor

Link #3390

[ ] pruner & quantizer: if we need API to recover the wrapper from a file? for simulation next time.
[ ] multi-compressor:

[ ] naming
[ ] if we need support schedule pruner? (support one-shot now)

[ ] auto-compressor

[ ] API naming
[ ] mode (use one compressor or multi-compressor)
[ ] default search space (it is like a tuner, support grid search now)


Review findings for Notifications

What will this achieve?
To complete readiness for release:

[x] Change the component name to NotificationsPanel.
[x] Change setOpen to be a simple event call onClickOutside.
[x] Change xxxLabel to xxxText when they are bits of text to assemble, and make them functions whenever there are numbers etc to be substituted in.
[x] See if you can use a copy of carbon ClickListener instead of useClickOutside.js.
[x] Add a settingsIconDescription, viewAllLabel (as func), dismissSingleNotificationIconDescription, to ensure translateability.
[x] Ensure that a passed ref is assigned into notificationsPanelRef.
[x] Double-check the notification bottom padding 1.125rem why it's not a carbon token, and change the divider line width from calc(100% - 2rem) to calc(100% - 2 * $spacing-05)
[x] Ensure tests achieve 100% coverage, and add a test for labels and text functions, and add a test for the onHandlers.
[x] Update storybook doc to remove/suppress the empty state (just show it as code), and add some text to tell the user to look in the header bar at the top of the page. Also kind of nice if the dismiss actions work in the story.

https://github.com/carbon-design-system/ibm-cloud-cognitive/pull/584

This is now complete, as NotificationsPanel has been released


Make the dataset BIDS compatible

Currently, the naming with "_mean" suffix is not BIDS compatible. I think there are ways to describe processing applied to a time series.

What about this?
data_leipzig_rest
├── dataset_description.json
├── derivatives
│   ├── labels
│   │   └── sub-leipzigR01
│   │       └── func
│   │           └── sub-leipzigR01_task-rest_desc-mocomeanseg.nii.gz  <---- Manual spinal cord segmentation
│   └── moco
│       └── sub-leipzigR01
│           └── func
│               ├── sub-leipzigR01_task-rest_desc-moco_bold.nii.gz     <---- 20 motion-corrected EPI volumes
│               └── sub-leipzigR01_task-rest_desc-mocomean_bold.nii.gz <---- Mean of motion-corrected volumes
├── participants.json
├── participants.tsv
└── task-rest_bold.json

Looks like a good start! To be closer to the official examples, I would do:

labels -->  label
sub-leipzigR01_task-rest_desc-mocomeanseg.nii.gz --> sub-leipzigR01_task-rest_desc-spinalcord_mask.nii.gz

Okay, perfect, thank you- I will change it and reupload the data!

Dear all,
As you know our dataset is consisting of derivatives only. Therefore, OpenNeuro as it is in its current form would not accept it but they are updating their platform and this is the reply I got from them:

Thanks for reaching out. This is quite timely, as we've been working on a validator for derivatives that would allow us to host derivatives-only datasets. The current plan is to roll it out as an option that can be enabled on a per-dataset basis by an admin, and we hope to do that within the next month or so. If you'd like, I can get back in touch when we're ready and we can get it set up for your dataset; this would help us test out our processes for non-admin users.
What I would recommend for the data organization would be to treat it as one coherent dataset, and not two parallel datasets:

data_leipzig_rest
├── dataset_description.json
├── sub-leipzigR01
│   └── func
│       ├── sub-leipzigR01_task-rest_desc-moco_bold.json       <---- sidecar json file containing imaging parameters
│       ├── sub-leipzigR01_task-rest_desc-moco_bold.nii.gz     <---- 20 motion-corrected EPI volumes
│       ├── sub-leipzigR01_task-rest_desc-mocomean_bold.nii.gz <---- Mean of motion-corrected volumes
│       └── sub-leipzigR01_task-rest_desc-spinalcord_mask.nii.gz  <---- Manual spinal cord segmentation
├── participants.json
├── participants.tsv
└── task-rest_bold.json

In the meantime, you can test out the new validator by using the version published to https://deno.land/x/bids_validator:
deno run --allow-read --allow-env https://deno.land/x/bids_validator/bids-validator.ts path/to/dataset
We'd be happy to hear any issues you run into. You can open them here: https://github.com/bids-standard/bids-validator/issues
Best,
Chris

What do you think?

this is the reply I got from them:

could you please cross-ref the GH conversation

As you know our dataset is consisting of derivatives only.

maybe we should consider having the images NOT in the derivatives, but in the common location?

@rohanbanerjee pls help with https://github.com/sct-pipeline/fmri-segmentation/issues/1#issuecomment-1670116219

As you know our dataset is consisting of derivatives only.

maybe we should consider having the images NOT in the derivatives, but in the common location?

I think we can use the 20 volumes as source data and then mask and mean as derivatives! We would need to change the naming of the data sub-leipzigR01_task-rest_desc-moco_bold.nii.gz a bit to make it compatible to be source data!
alternatively, we can think about sharing data here: https://data.mendeley.com/

I think we can use the 20 volumes as source data and then mask and mean as derivatives!

can we consider using the mean in the source data (even though I know this is not really a source...)

alternatively, we can think about sharing data here: https://data.mendeley.com/

no, let's stick with OpenNeuro

Good questions! I mean technically we can, because I had one volume EPI data

I think we can use the 20 volumes as source data and then mask and mean as derivatives!

can we consider using the mean in the source data (even though I know this is not really a source...)

Technically, we can! I had shared one-volume EPI data as the source data (as we just acquired one volume for that specific acquisition). Would you want me to ask these questions to OpenNeuro developers and get back to you?

alternatively, we can think about sharing data here: https://data.mendeley.com/

no, let's stick with OpenNeuro

sure, I also think that would be better!

Would you want me to ask these questions to OpenNeuro developers and get back to you?

yes, ask the question, but instead of getting back to me, please cross-ref the conversation here-- again, GH is a public comm platform and we should all be able to see and participate in the discussion thread with openneuro-- if this is unclear @rohanbanerjee please chat with @MerveKaptan to clarify

Sure, we will open an issue on OpenNeuro GH and post the link here.

Sure, we will open an issue on OpenNeuro GH and post the link here.

Thank you both for clarifying! I was not using GH previously, but their ticket system : https://openneuro.freshdesk.com/support/tickets/1525
Now we will move it to GitHub as Rohan suggested!

Thank you both for clarifying! I was not using GH previously, but their ticket system : https://openneuro.freshdesk.com/support/tickets/1525
Now we will move it to GitHub as Rohan suggested!

no-- if they have a ticket system, then you should use their ticket system, or whatever they ask users to use. I was suggesting GH bc i thought they were using GH issues as their user-facing ticket system. On the other hand, I am not able to see your ticket, which is not great... communication alternatives are neurostars.org (or maybe GH issue if they also have that).
Anyhow, at this point it is rather up to us to decide what to do with this dataset and how to convert it to BIDS, right?

Hi @jcohenadad,
I think both are fine. As your suggestion, I have moved this to GitHub.
Actually, talking to Chris from the OpenNeuro team helped a lot and I finally have an idea how we can organize the data!
What we need to do is to have a source dataset which will be 20 volume time-series and we could basically organize the derivatives however we would like to!

Hi @jcohenadad,
What do you think? Once we decide on an organization, I can re-organize the data as we want to.
I can move the 20 motion-corrected volumes to source data and keep the derivatives as they are.
Alternatively, I can also move both derivatives into one folder (instead of separating them for moco mean and spinal segmentation).
Please do let me know!

the original motivation for having the moco dataset in source is because of https://github.com/sct-pipeline/fmri-segmentation/issues/1#issuecomment-1670041420-- now, if https://github.com/sct-pipeline/fmri-segmentation/issues/1#issuecomment-1670041420 is fixed, then we can put everything under derivatives/ if it is not, then you split between source (moco data) and derivatives (mean and seg)

Thank you, @jcohenadad ! I missed this reply for some reason. Okay, I will ask the OpenNeuro team again and act accordingly.

Dear @jcohenadad & @rohanbanerjee,
FYI, I have been testing out a few things, and I believe, it will be easier and quicker to go with the following solution:  "split between source (moco data) and derivatives (mean and seg)". I will reorganize the data and start uploading.
That being said, for some sites, we would still need the sidecar .json files as mentioned here .
Thank you!
Merve

Hi @jcohenadad & @rohanbanerjee,
Another question about the BIDS organization. Currently, the latest BIDS version does not have an option for multisite data, please see here.
We can either treat each data set separately or combine all the subjects in one dataset and add a site column to participants.tsv file as suggested in the link above.
I believe the second option will be more neat as it is one project. Would you agree?
Thank you,
Merve

Currently, the latest BIDS version does not have an option for multisite data, please see here.

it does, see here and an example for the spine-generic project.

I believe the second option will be more neat as it is one project. Would you agree?

👍

The dataset is BIDS compliant now and has been uploaded to Openneuro. Closing the issue.


Error after run ./console phpci:run-builds

Hi,
i have installed th elatest version today. Now i have configured the application an the connect to github will done. After i setup my project and then i running the command for builds, i retrive the follow error.
What can i do?
I have testet with:
php5.4
php5.5
php5.6
Installed on a parallels-machine (PLESK) with latest centos.
Script was running with a user with permission for write-access.
<......> is the path to my vhosts....
[2015-02-21 17:06:53] RunCommand.INFO: Finding builds to process [] [] [2015-02-21 17:06:53] RunCommand.INFO: Found 1 builds [] [] [2015-02-21 17:06:57] RunCommand.INFO: Initialized empty Git repository in /var/www/vhosts/<......>/PHPCI/build/19/.git/ {"buildID":"19"} [] PHP Fatal error:  Call to undefined method DirectoryIterator::getExtension() in /var/www/vhosts/<......>/PHPCI/Model/Build.php on line 153 [2015-02-21 17:06:57] _.ERROR: ErrorException: 1: Call to undefined method DirectoryIterator::getExtension() in /var/www/vhosts/<......>/PHPCI/Model/Build.php line 153 (uncaught exception) at /var/www/vhosts/<......>/PHPCI/Model/Build.php line 153 {"exception":"[object] (ErrorException: 1: Call to undefined method DirectoryIterator::getExtension() in /var/www/vhosts/<......>/PHPCI/Model/Build.php line 153 at /var/www/vhosts/<......>/PHPCI/Model/Build.php:153)"} []

Oh sorry, i see my php-cli isn't correct. Please close this issue.
Thanks


[Feature][UI Next] Add alarm instance manage

Purpose of the pull request
close #7894

Brief change log

[x] Alarm Instance Manage

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Codecov Report

Merging #8208 (dff18e2) into dev (7945a2f) will decrease coverage by 0.04%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##                dev    #8208      +/-   ##
============================================
- Coverage     41.44%   41.40%   -0.05%
+ Complexity     3804     3801       -3
============================================
  Files           658      658
  Lines         27657    27657
  Branches       3131     3131
============================================
- Hits          11462    11450      -12
- Misses        15096    15107      +11
- Partials       1099     1100       +1

Impacted Files
Coverage Δ

...r/plugin/registry/zookeeper/ZookeeperRegistry.java
48.21% <0.00%> (-8.04%)
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...er/master/dispatch/host/assign/RandomSelector.java
77.77% <0.00%> (-5.56%)
:arrow_down:

...inscheduler/common/task/sqoop/SqoopParameters.java
74.00% <0.00%> (-2.00%)
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...dolphinscheduler/remote/future/ResponseFuture.java
81.96% <0.00%> (-1.64%)
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Migrate to gradle

./gradlew install will do a build and publish it to your local maven repo.
Set environment var dev to true to build snapshot builds of LavalinkClient for local development usage.

Confirmed that jitpack builds working.
Teamcity CI has been configured, will just need a switch after the merge to dev (disable maven build step, enable the gradle one).

Goodbye 512 lines of XML


Issues with Storing and Searching Notes

While running the sample eLLMental project, when "search" is run after storing notes, it only retrieves the IDs of the Pinecone vectors instead of the actual notes.
Furthermore, there is a problem in the search functionality itself. For instance, regardless of the content of the search (e.g., "test" or "hello"), it always retrieves 2 vectors.

This has been solved in #35


Adding code coverage

Coverage is helpful to understand what part of the codes are not tested yet, and to give a rough measure on stability of the code. We can more or less copy the way it has been done in rascaline. I will try to do the Python coverage, someone else needs to do the coverage for the C-API

[ ] Python coverage that can simply added with pytest-cov
[ ] C-API

Reference how it was done in rascaline
https://github.com/Luthaf/rascaline/pull/126
https://github.com/Luthaf/rascaline/pull/200

Updating the issue: we now have code coverage for Python, but are still missing it for the Rust and C++ code.


the result is bad that I train the fcos3d with nuscenes v1.0-mini

Hello mmdetection3d team,
I want to train fcos3d with nuscenes dataset, while the whole datasets is really huge, sometimes it is hard for me to download all the data. Therefore, I train the fcos3d with nuscenes v1.0-mini data. The following is the steps:
mmdetection3d version: release v0.17.1

I downloaded the data from nuscenes website:

unzip the v1.0-mini.tgz

modify the v1.0-mini inside v1.0-mini to v1.0-trainval

symbolic link the datasets: ln -s v1.0-mini mmdetection3d/data

modify tools/create_data.py
elif args.dataset == 'nuscenes' and args.version != 'v1.0-mini':
train_version = f'{args.version}-trainval'
nuscenes_data_prep(
root_path=args.root_path,
info_prefix=args.extra_tag,
version=train_version,
dataset_name='NuScenesDataset',
out_dir=args.out_dir,
max_sweeps=args.max_sweeps)
#test_version = f'{args.version}-test'
#nuscenes_data_prep(
#    root_path=args.root_path,
#    info_prefix=args.extra_tag,
#    version=test_version,
#    dataset_name='NuScenesDataset',
#    out_dir=args.out_dir,
#    max_sweeps=args.max_sweeps)

Create the date with: python tools/create_data.py nuscenes --root-path ./data/nuscenes --out-dir ./data/nuscenes --extra-tag nuscenes --workers 20

the created folder as follow:

the trained model:

test the model: python demo/mono_det_demo.py demo/data/nuscenes/n015-2018-07-24-11-22-45+0800__CAM_BACK__1532402927637525.jpg demo/data/nuscenes/n015-2018-07-24-11-22-45+0800__CAM_BACK__1532402927637525_mono3d.coco.json configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune.py work_dirs/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d/latest.pth
The result shows as below:

Compare with the result of the demo, this result is really bad.

I'm wondering if the bad result is caused by the training datasets?

There is only one minor problem in your implementation: you can set --version to v1.0-mini to generate infos only for that mini-data version, but I guess this point won't affect your results.
I did not try to train the model with the mini version, but I guess it is possible that the limited data results in such bad performance. Someone has tried with 1/10 full dataset before and there was also a serious performance degradation. If you are interested in training models with a small dataset, you can try with KITTI, and the PRs #964 and #1014 for FCOS3D++ are ready to be merged into v1.0.0.dev0.

Close due to inactivity.


Gf/stop loss confirmation screen

Stop Loss Order Confirmation Screen
Changes 👷♀

Added a screen in the auto buy / auto sell flow for confirmation before confirming an order.

How to test 🧪

Go through the add auto buy set up process
You will see an additional screen in the flow

Closing old PR (cleaning up PR tab).


card-network removal from filters and calendly link removal

Temporary fix for the issue : https://github.com/juspay/hyperswitch-cloud/issues/7206

Also removed calendly link from dashboard


ci: add parser validation script and workflow

Adds a GitHub Actions workflow that will check each TOML parser to see if it validates against the
provided parser schema (only when the #:schema directive is at the top of the file). Validation error
messages can be seen in the GitHub Actions logs at https://github.com/globaldothealth/isaric/actions.

Yes, this will be really useful!.
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