Dependency React Swipeable Views Appears to have Changed Directory Structure

A reproduction can be found here in the example that was never merged into the README.
https://codesandbox.io/s/mystifying-varahamihira-dphsr?fontsize=14
It appears that react-swipeable-views may have changed the directory structure in version 13.4, that causes material-auto-rotating-carousel to not compile.
I believe the issue sits within the SwipableCarouselView.js file between lines 2-4.
https://github.com/TeamWertarbyte/material-auto-rotating-carousel/blob/master/src/SwipableCarouselView.js#L2-L4
Downgrading to version 13.3 seemed to fix the issue.
The full error is:
[ error ] ./node_modules/material-auto-rotating-carousel/lib/SwipableCarouselView.js
Module not found: Can't resolve 'react-swipeable-views-utils/lib/autoPlay' in '/Users/asciant/Projects/crimson/node_modules/material-auto-rotating-carousel/lib'
{ Error: Cannot find module 'react-swipeable-views-utils/lib/autoPlay'
    at Function.Module._resolveFilename (internal/modules/cjs/loader.js:636:15)
    at Function.Module._load (internal/modules/cjs/loader.js:562:25)
    at Module.require (internal/modules/cjs/loader.js:692:17)
    at require (internal/modules/cjs/helpers.js:25:18)
    at Object.<anonymous> (/Users/asciant/Projects/crimson/node_modules/material-auto-rotating-carousel/lib/SwipableCarouselView.js:15:17)
    at Module._compile (internal/modules/cjs/loader.js:778:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:789:10)
    at Module.load (internal/modules/cjs/loader.js:653:32)
    at tryModuleLoad (internal/modules/cjs/loader.js:593:12)
    at Function.Module._load (internal/modules/cjs/loader.js:585:3)
    at Module.require (internal/modules/cjs/loader.js:692:17)
    at require (internal/modules/cjs/helpers.js:25:18)
    at Object.<anonymous> (/Users/asciant/Projects/crimson/node_modules/material-auto-rotating-carousel/lib/AutoRotatingCarousel.js:67:29)
    at Module._compile (internal/modules/cjs/loader.js:778:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:789:10)
    at Module.load (internal/modules/cjs/loader.js:653:32)
    at tryModuleLoad (internal/modules/cjs/loader.js:593:12)
    at Function.Module._load (internal/modules/cjs/loader.js:585:3)
    at Module.require (internal/modules/cjs/loader.js:692:17)
    at require (internal/modules/cjs/helpers.js:25:18)
    at Object.<anonymous> (/Users/asciant/Projects/crimson/node_modules/material-auto-rotating-carousel/lib/index.js:7:29)
    at Module._compile (internal/modules/cjs/loader.js:778:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:789:10)
    at Module.load (internal/modules/cjs/loader.js:653:32)
    at tryModuleLoad (internal/modules/cjs/loader.js:593:12)
    at Function.Module._load (internal/modules/cjs/loader.js:585:3)
    at Module.require (internal/modules/cjs/loader.js:692:17)
    at require (internal/modules/cjs/helpers.js:25:18)
    at Object.material-auto-rotating-carousel (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:10997:18)
    at __webpack_require__ (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:29:31)
    at Module../components/Detail/Carousel.jsx (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:2785:89)
    at __webpack_require__ (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:29:31)
    at Module../components/Detail/Images.jsx (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:3606:67)
    at __webpack_require__ (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:29:31)
    at Module../components/Detail/index.jsx (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:4448:65)
    at __webpack_require__ (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:29:31)
    at Module../pages/detail.jsx (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:10057:76)
    at __webpack_require__ (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:29:31)
    at Object.3 (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:10138:18)
    at __webpack_require__ (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:29:31)
    at /Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:124:18
    at Object.<anonymous> (/Users/asciant/Projects/crimson/.next/server/static/development/pages/detail.js:127:10)
    at Module._compile (internal/modules/cjs/loader.js:778:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:789:10)
    at Module.load (internal/modules/cjs/loader.js:653:32)
    at tryModuleLoad (internal/modules/cjs/loader.js:593:12)
    at Function.Module._load (internal/modules/cjs/loader.js:585:3)
    at Module.require (internal/modules/cjs/loader.js:692:17)
    at require (internal/modules/cjs/helpers.js:25:18)
    at Object.requirePage (/Users/asciant/Projects/crimson/node_modules/next/dist/next-server/server/require.js:47:12) code: 'MODULE_NOT_FOUND' }

I can't reproduce this with react-swipeable-views 0.13.4 or 0.13.9.


Add quick note about Astro.resolve

Added a small/temporary note in the API reference page with a link to the Astro.resolve() anchor tag in the migration guide.

Yay! 🥳


gen2-gaze-estimation crashes/failures (after working once)

After working thrice, interspersed with some random failures, now the demo does not work.
$ python3 main.py  -cam
Upgraded DepthAI SDK to:  depthai-<IP_ADDRESS>-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Python 3.8.10 (default, Nov 14 2022, 12:59:47)  [GCC 9.4.0] on linux
Ubuntu 20.04.5 LTS
Result 1:
Creating pipeline...
Creating Color Camera...
Creating Face Detection Neural Network...
Creating Landmarks Detection Neural Network...
Creating Head Pose Neural Network...
Creating Gaze Estimation Neural Network...
Traceback (most recent call last):
  File "main.py", line 385, in <module>
    with depthai.Device(create_pipeline()) as device:
depthai.XLinkWriteError: Couldn't write data to stream: '__rpc_main' (X_LINK_ERROR)

Result 2:
Creating pipeline...
Creating Color Camera...
Creating Face Detection Neural Network...
Creating Landmarks Detection Neural Network...
Creating Head Pose Neural Network...
Creating Gaze Estimation Neural Network...
terminate called without an active exception
Stack trace (most recent call last):
#29   Object "[0xffffffffffffffff]", at 0xffffffffffffffff, in
#28   Object "python3", at 0x5faa2d, in _start
#27   Object "/lib/x86_64-linux-gnu/libc.so.6", at 0x7f4b23db4082, in __libc_start_main
#26   Object "python3", at 0x6b840c, in Py_BytesMain
#25   Object "python3", at 0x6b8081, in Py_RunMain
#24   Object "python3", at 0x67fbf6, in PyRun_SimpleFileExFlags
#23   Object "python3", at 0x67dad0, in
#22   Object "python3", at 0x67da2e, in
#21   Object "python3", at 0x67d9b0, in
#20   Object "python3", at 0x68e266, in PyEval_EvalCode
#19   Object "python3", at 0x569d89, in _PyEval_EvalCodeWithName
#18   Object "python3", at 0x571142, in _PyEval_EvalFrameDefault
#17   Object "python3", at 0x5f6705, in _PyObject_MakeTpCall
#16   Object "/home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7f4b0071e728, in
#15   Object "python3", at 0x5a6ca6, in
#14   Object "python3", at 0x59c543, in
#13   Object "python3", at 0x5f52b1, in PyObject_Call
#12   Object "python3", at 0x50ba57, in
#11   Object "python3", at 0x5f6705, in _PyObject_MakeTpCall
#10   Object "python3", at 0x5f5b38, in PyCFunction_Call
#9    Object "/home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7f4b0071f02a, in
#8    Object "/home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7f4b0075a1b1, in
#7    Object "/home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7f4b00929aad, in dai::Device::Device(dai::Pipeline const&, dai::DeviceInfo const&)
#6    Object "/home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7f4b00935a31, in dai::DeviceBase::tryStartPipeline(dai::Pipeline const&)
#5    Object "/home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7f4b0093fde5, in dai::DeviceBase::startPipelineImpl(dai::Pipeline const&)
#4    Object "/lib/x86_64-linux-gnu/libstdc++.so.6", at 0x7f4b226723f6, in std::terminate()
#3    Object "/lib/x86_64-linux-gnu/libstdc++.so.6", at 0x7f4b2267238b, in
#2    Object "/lib/x86_64-linux-gnu/libstdc++.so.6", at 0x7f4b22666910, in
#1    Object "/lib/x86_64-linux-gnu/libc.so.6", at 0x7f4b23db2858, in abort
#0    Object "/lib/x86_64-linux-gnu/libc.so.6", at 0x7f4b23dd300b, in gsignal
Aborted (Signal sent by tkill() 51192 1000)
Aborted (core dumped)

Looks like an exception thrown at startPipelineImpl
(gdb) bt
#0  __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50
#1  0x00007ffff7dd5859 in __GI_abort () at abort.c:79
#2  0x00007ffff6689911 in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6
#3  0x00007ffff669538c in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6
#4  0x00007ffff66953f7 in std::terminate() ()
   from /lib/x86_64-linux-gnu/libstdc++.so.6
#5  0x00007fffd495ebd6 in dai::DeviceBase::startPipelineImpl(dai::Pipeline const&) ()
   from /home/mon/.local/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so
#6  0x00007fffd4954822 in dai::DeviceBase::tryStartPipeline(dai::Pipeline const&) ()

Now, setting DEPTHAI_LEVEL=debug has started working again 10 or so times until I've had it crash again. x-D
python3 main.py -cam -laz
[2023-02-08 16:46:43.261] [debug] Python bindings - version: <IP_ADDRESS> from 2021-12-01 03:26:17 +0200 build: 2021-12-01 03:15:55 +0000
[2023-02-08 16:46:43.262] [debug] Library information - version: 2.13.3, commit: 0cc6284767ae21e8747d26562cb058d181e0ca34 from 2021-12-01 03:23:55 +0200, build: 2021-12-01 03:08:42 +0000
[2023-02-08 16:46:43.273] [debug] Initialize - finished
Creating pipeline...
Creating Color Camera...
Creating Face Detection Neural Network...
Creating Landmarks Detection Neural Network...
Creating Head Pose Neural Network...
Creating Gaze Estimation Neural Network...
[2023-02-08 16:46:43.351] [debug] Resources - Archive 'depthai-bootloader-fwp-0.0.15.tar.xz' open: 3ms, archive read: 76ms
^[[A[2023-02-08 16:46:43.618] [debug] Resources - Archive 'depthai-device-fwp-48fca4a443d841221c94c70d5c05e7e946168636.tar.xz' open: 2ms, archive read: 353ms
[2023-02-08 16:46:43.954] [debug] Device - OpenVINO version: 2021.4
[1844301071567C0F00] [5.434] [system] [info] Memory Usage - DDR: 0.12 / 358.55 MiB, CMX: 2.05 / 2.50 MiB, LeonOS Heap: 6.72 / 78.59 MiB, LeonRT Heap: 2.88 / 23.84 MiB
[1844301071567C0F00] [5.434] [system] [info] Temperatures - Average: 33.39 °C, CSS: 34.16 °C, MSS 32.97 °C, UPA: 32.73 °C, DSS: 33.69 °C
[1844301071567C0F00] [5.434] [system] [info] Cpu Usage - LeonOS 6.82%, LeonRT: 1.61%
[2023-02-08 16:46:46.542] [debug] Schema dump: {"connections":[{"node1Id":10,"node1Output":"out","node2Id":12,"node2Input":"in"},{"node1Id":11,"node1Output":"out","node2Id":10,"node2Input":"in"},{"node1Id":7,"node1Output":"out","node2Id":9,"node2Input":"in"},{"node1Id":8,"node1Output":"out","node2Id":7,"node2Input":"in"},{"node1Id":4,"node1Output":"out","node2Id":6,"node2Input":"in"},{"node1Id":5,"node1Output":"out","node2Id":4,"node2Input":"in"},{"node1Id":2,"node1Output":"out","node2Id":3,"node2Input":"in"},{"node1Id":0,"node1Output":"preview","node2Id":2,"node2Input":"in"},{"node1Id":0,"node1Output":"preview","node2Id":1,"node2Input":"in"}],"globalProperties":{"calibData":null,"cameraTuningBlobSize":null,"cameraTuningBlobUri":"","leonCssFrequencyHz":700000000.0,"leonMssFrequencyHz":700000000.0,"pipelineName":null,"pipelineVersion":null,"xlinkChunkSize":-1},"nodes":[[0,{"id":0,"ioInfo":{"inputConfig":{"blocking":false,"name":"inputConfig","queueSize":8,"type":3},"inputControl":{"blocking":true,"name":"inputControl","queueSize":8,"type":3},"isp":{"blocking":false,"name":"isp","queueSize":8,"type":0},"preview":{"blocking":false,"name":"preview","queueSize":8,"type":0},"raw":{"blocking":false,"name":"raw","queueSize":8,"type":0},"still":{"blocking":false,"name":"still","queueSize":8,"type":0},"video":{"blocking":false,"name":"video","queueSize":8,"type":0}},"name":"ColorCamera","properties":{"boardSocket":0,"colorOrder":0,"fp16":false,"fps":30.0,"imageOrientation":-1,"initialControl":{"aeLockMode":false,"aeRegion":{"height":0,"priority":0,"width":0,"x":0,"y":0},"afRegion":{"height":0,"priority":0,"width":0,"x":0,"y":0},"antiBandingMode":0,"autoFocusMode":3,"awbLockMode":false,"awbMode":0,"brightness":0,"chromaDenoise":0,"cmdMask":0,"contrast":0,"effectMode":0,"expCompensation":0,"expManual":{"exposureTimeUs":0,"frameDurationUs":0,"sensitivityIso":0},"lensPosition":0,"lumaDenoise":0,"saturation":0,"sceneMode":0,"sharpness":0,"wbColorTemp":0},"inputConfigSync":false,"interleaved":false,"ispScale":{"horizDenominator":0,"horizNumerator":0,"vertDenominator":0,"vertNumerator":0},"previewHeight":300,"previewKeepAspectRatio":true,"previewWidth":300,"resolution":0,"sensorCropX":-1.0,"sensorCropY":-1.0,"stillHeight":-1,"stillWidth":-1,"videoHeight":-1,"videoWidth":-1}}],[1,{"id":1,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":8,"type":3}},"name":"XLinkOut","properties":{"maxFpsLimit":-1.0,"metadataOnly":false,"streamName":"cam_out"}}],[2,{"id":2,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":5,"type":3},"out":{"blocking":false,"name":"out","queueSize":8,"type":0},"passthrough":{"blocking":false,"name":"passthrough","queueSize":8,"type":0}},"name":"NeuralNetwork","properties":{"blobSize":1344256,"blobUri":"asset:__blob","numFrames":8,"numNCEPerThread":0,"numThreads":0}}],[3,{"id":3,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":8,"type":3}},"name":"XLinkOut","properties":{"maxFpsLimit":-1.0,"metadataOnly":false,"streamName":"face_nn"}}],[4,{"id":4,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":5,"type":3},"out":{"blocking":false,"name":"out","queueSize":8,"type":0},"passthrough":{"blocking":false,"name":"passthrough","queueSize":8,"type":0}},"name":"NeuralNetwork","properties":{"blobSize":532736,"blobUri":"asset:__blob","numFrames":8,"numNCEPerThread":0,"numThreads":0}}],[5,{"id":5,"ioInfo":{"out":{"blocking":false,"name":"out","queueSize":8,"type":0}},"name":"XLinkIn","properties":{"maxDataSize":5242880,"numFrames":8,"streamName":"landmark_in"}}],[6,{"id":6,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":8,"type":3}},"name":"XLinkOut","properties":{"maxFpsLimit":-1.0,"metadataOnly":false,"streamName":"landmark_nn"}}],[7,{"id":7,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":5,"type":3},"out":{"blocking":false,"name":"out","queueSize":8,"type":0},"passthrough":{"blocking":false,"name":"passthrough","queueSize":8,"type":0}},"name":"NeuralNetwork","properties":{"blobSize":3839808,"blobUri":"asset:__blob","numFrames":8,"numNCEPerThread":0,"numThreads":0}}],[8,{"id":8,"ioInfo":{"out":{"blocking":false,"name":"out","queueSize":8,"type":0}},"name":"XLinkIn","properties":{"maxDataSize":5242880,"numFrames":8,"streamName":"pose_in"}}],[9,{"id":9,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":8,"type":3}},"name":"XLinkOut","properties":{"maxFpsLimit":-1.0,"metadataOnly":false,"streamName":"pose_nn"}}],[10,{"id":10,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":5,"type":3},"out":{"blocking":false,"name":"out","queueSize":8,"type":0},"passthrough":{"blocking":false,"name":"passthrough","queueSize":8,"type":0}},"name":"NeuralNetwork","properties":{"blobSize":3784320,"blobUri":"asset:__blob","numFrames":8,"numNCEPerThread":0,"numThreads":0}}],[11,{"id":11,"ioInfo":{"out":{"blocking":false,"name":"out","queueSize":8,"type":0}},"name":"XLinkIn","properties":{"maxDataSize":5242880,"numFrames":8,"streamName":"gaze_in"}}],[12,{"id":12,"ioInfo":{"in":{"blocking":true,"name":"in","queueSize":8,"type":3}},"name":"XLinkOut","properties":{"maxFpsLimit":-1.0,"metadataOnly":false,"streamName":"gaze_nn"}}]]}
[2023-02-08 16:46:46.542] [debug] Asset map dump: {"map":{"/node/10/__blob":{"alignment":64,"offset":0,"size":3784320},"/node/2/__blob":{"alignment":64,"offset":8156864,"size":1344256},"/node/4/__blob":{"alignment":64,"offset":7624128,"size":532736},"/node/7/__blob":{"alignment":64,"offset":3784320,"size":3839808}}}
terminate called without an active exception
Stack trace (most recent call last):
[2023-02-08 16:46:48.081] [debug] Log thread exception caught: Couldn't read data from stream: '__log' (X_LINK_ERROR)
[2023-02-08 16:46:48.081] [debug] Timesync thread exception caught: Couldn't read data from stream: '__timesync' (X_LINK_ERROR)
#29   Object "[0xffffffffffffffff]", at 0xffffffffffffffff, in
#28   Object "python3", at 0x5faa2d, in _start
#27   Object "/lib/x86_64-linux-gnu/libc.so.6", at 0x7fdee8eef082, in __libc_start_main
#26   Object "python3", at 0x6b840c, in Py_BytesMain
#25   Object "python3", at 0x6b8081, in Py_RunMain
#24   Object "python3", at 0x67fbf6, in PyRun_SimpleFileExFlags
#23   Object "python3", at 0x67dad0, in
#22   Object "python3", at 0x67da2e, in
#21   Object "python3", at 0x67d9b0, in
#20   Object "python3", at 0x68e266, in PyEval_EvalCode
#19   Object "python3", at 0x569d89, in _PyEval_EvalCodeWithName
#18   Object "python3", at 0x571142, in _PyEval_EvalFrameDefault
#17   Object "python3", at 0x5f6705, in _PyObject_MakeTpCall
#16   Object "/home/mon/Luxonis/venv/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7fdec72c8ff8, in
#15   Object "python3", at 0x5a6ca6, in
#14   Object "python3", at 0x59c543, in
#13   Object "python3", at 0x5f52b1, in PyObject_Call
#12   Object "python3", at 0x50ba57, in
#11   Object "python3", at 0x5f6705, in _PyObject_MakeTpCall
#10   Object "python3", at 0x5f5b38, in PyCFunction_Call
#9    Object "/home/mon/Luxonis/venv/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7fdec72ca6b6, in
#8    Object "/home/mon/Luxonis/venv/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7fdec72ecb94, in
#7    Object "/home/mon/Luxonis/venv/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7fdec742c14a, in dai::Device::Device(dai::Pipeline const&, dai::DeviceInfo const&)
#6    Object "/home/mon/Luxonis/venv/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7fdec7435d71, in dai::DeviceBase::tryStartPipeline(dai::Pipeline const&)
#5    Object "/home/mon/Luxonis/venv/lib/python3.8/site-packages/depthai.cpython-38-x86_64-linux-gnu.so", at 0x7fdec743af83, in dai::DeviceBase::startPipelineImpl(dai::Pipeline const&)
#4    Object "/lib/x86_64-linux-gnu/libstdc++.so.6", at 0x7fdec90313f6, in std::terminate()
#3    Object "/lib/x86_64-linux-gnu/libstdc++.so.6", at 0x7fdec903138b, in
#2    Object "/lib/x86_64-linux-gnu/libstdc++.so.6", at 0x7fdec9025910, in
#1    Object "/lib/x86_64-linux-gnu/libc.so.6", at 0x7fdee8eed858, in abort
#0    Object "/lib/x86_64-linux-gnu/libc.so.6", at 0x7fdee8f0e00b, in gsignal
Aborted (Signal sent by tkill() 14741 1000)
Aborted (core dumped)


Provides setter methods

I don't understand.
Can you cite an example?

Allows the user to modify the content of the IData.
For example: setInt("key", 9).

Nice idea, thanks. I will consider to do that

Just call the update method of IData is enough.
For example, data.update({key: 9})

Yeah, but this won't work with long path.
"path.to[0].deep"

Closing issue since this functionality was implemented by ZenUtils mod.


[RESOLVED] Interface eth0(): High error rate (>2 for 5m)

Problem started at 10:00:32 on 2023.05.29
Problem name: Interface eth0(): High error rate (>2 for 5m)
Host: S100-Primario
Severity: Warning
Operational data: errors in: 1, errors out: 0
Original problem ID: 22893
Event details in Zabbix: http://<IP_ADDRESS>/tr_events.php?triggerid=23483&eventid=22893

Problem has been resolved in 2m 57s at 10:03:29 on 2023.05.29
Problem name: Interface eth0(): High error rate (>2 for 5m)
Host: S100-Primario
Severity: Warning
Original problem ID: 22893


no power issues

So i built 2 of these and using all the build materials for the list. When i power it with ac the wemo does not power on. If i plug in usb to wemo it powers up but no screen  ( no 5v as expected).
I have 120v to power supply lugs and 5v to the 5v lugs but not to wemo 5v or 3v.

Can you post pictures?  Are you using the PCB or protoboard?  In general, I'd advise tracing the path of 5V and see where it stops working.  If you have 5V at the PSU, do you also have 5V at the 5V pin to the WeMos?  If not, can you do a continuity test and see why that is?

im using the pcb board hasp  from the link. have continuity from 5v power supply to both pins wemo and the pin to the right on pcb.  It seems its a ground issue but i no nothing about this power supply form ac to 12v.

Any chance of a soldering issue on the 5V or GND pins on the WeMos?  Can you check your joints on the Wemos pin headers and also on the HASP board?
The Wemos has a 5V to 3.3V regulator on board.  5V from the USB or from that 5V pin both go to that regulator which then powers the board.  So, if it works from USB, that means that the regulator is working and the board is working.  This leaves getting 5V to that regulator, which must be your problem.

definitely could be a sodering issues i did my best non are touching but it ant pritty LOL

Visually I don't see anything overtly wrong, but the solder joints here aren't great and it's very possible that they aren't making contact where you'd hope they would.  I'd suggest some solder braid + flux to clean things up a bit.  Also, check continuity from +5V on the top of the Wemos board to +5V on the PSU.  Also check GND to GND, and also confirm there is no continuity between +5V and GND.

No continuity from gnd to gnd. 5v to 5v is fine

I have ground from psu to the header pins on the right but no ground at the wemo pin

That leaves GND at Wemos to it's header pins (on top) or the GND from wemos header pin to the PCB itself on the bottom.  If you have solder flux (not plumbing flux, stuff for electronics), soak those joints and hit it with some heat.

no joy. will it hurt anything if i conect the  2 gnds with a jumper and leave it

Funny i have 2 boards that are doing this

A jumper from PSU GND to Wemos GND is OK.

soldered  a jumper No fire no smoke all good booting up.
thx for your help,


restler grammar should support fuzzable elements for format: date-span and uri

For the following Swagger defined properties:
          "timeSpan": {
              "type": "string",
              "description": "A string which is interpreted as a TimeSpan",
              "format": "date-span",
              "nullable": true
            }

          "targetUrl": {
            "type": "string",
            "format": "uri",
            "nullable": true
          }

Currently, these are compiled to restler_fuzzable_string.
It should instead be restler_fuzzable_date_span and restler_fuzzable_uri.

Hello @mbuki,
restler_fuzzable_datetime can be used in the dictionary.  Are you saying that in the grammar.py these are restler_fuzzable_string?  If yes, this looks like a bug - could you please copy/paste the grammar.py snippet you get for the above schema?
As a workaround, you can use restler_custom_payload, but values need to be specified separately for each of the parameters.  So, in the above:
restler_custom_payload {
  "to": ["2021-03-09T16:01:13Z", "2021-03-10T16:01:13Z"],
  "from": ["2021-03-08T16:01:13Z", "2021-03-11T16:01:13Z"]
}

Another less precise/verbose workaround would be to enter these values into the list of restler_fuzzable_string values.   This will cause more parameter combinations to be tried, but eventually RESTler should plug in those values into the query parameter.

Yes, in the grammar.py these are restler_fuzzable_string.
primitives.restler_static_string("from="),
primitives.restler_fuzzable_string("fuzzstring", quoted=False),
primitives.restler_static_string("&"),
primitives.restler_static_string("to="),
primitives.restler_fuzzable_string("fuzzstring", quoted=False),
primitives.restler_static_string("&"),

There are some additional notes here, so I am explaining from the beginning.
When I run the following command from the root directory of my project where the YAML file is:
Restler compile --api_spec openapi.yaml
I get a new folder called `Compile' with all the default grammar, dict, etc. files.
Looking into that generated dict.json, I also see that the datetime property is not in the right format, i.e.,
"restler_fuzzable_datetime": [
   "6/25/2019 12:00:00 AM"
 ]

This is while the server only accepts ISO timestamps. e.g. "2021-02-09T16:54:13Z".
This is my openapi:
        - in: query
          name: from
          description: runtime after this time.
          schema:
            type: string
            format: datetime
        - in: query
          name: to
          description: runtime before this time.
          schema:
            type: string
            format: datetime

So I think issues are two here. One is datetime from schema to produce correct ISO format in dict.json and the second is to have this format create a correct datetime in grammar.py.
As a workaround, you can use restler_custom_payload, but values need to be specified separately for each of the parameters. So, in the above:
Even if I use:
restler_custom_payload {
  "to": ["2021-03-09T16:01:13Z", "2021-03-10T16:01:13Z"],
  "from": ["2021-03-08T16:01:13Z", "2021-03-11T16:01:13Z"]
}

The former issue persists, i.e., not ISO compliant.
Above all, note that our server does not need quotes around strings, which I see the quoted flag in grammar.py is set to False. So this should be fine as long as the problem from the above matters could be resolved, thanks.

Thanks for these details, this is very helpful.
Could you please clarify, when you change the dictionary (e.g. to add a restler_custom_payload section), are you re-compiling with
Restler compile config.json
where the config.json points to your new, updated dictionary?
Whenever you add new properties in the dictionary, you need to recompile because RESTler may need to update the grammar.  Specifically, when you use restler_custom_payload, RESTler will replaced the fuzzable string grammar elements with restler_custom_payload("to") and use the values in the restler_custom_payload part of the dictionary.
We will update the docs to make this more clear.

I will open a separate bug for these:

One is datetime from schema to produce correct ISO format in dict.json and the second is to have this format create a correct datetime in grammar.py.

Hi @marina-p,
Yes, that's correct. When I change dict.json in Compile folder I do the following. I go to the Compile folder and run:
Restler compile config.json
That generates a new grammar.py based on changes in dict.json. My config.json looks like this:
{
  "SwaggerSpecFilePath": [
    "/root/openapi.yaml"
  ],
  "GrammarOutputDirectoryPath": "/root/Compile",
  "GrammarInputFilePath": "/root/Compile/grammar.json",
  "CustomDictionaryFilePath": "/root/Compile/dict.json",
  "EngineSettingsFilePath":  "/root/Compile/restler_user_settings.json",
  "IncludeOptionalParameters": true,
  "UseBodyExamples": true,
  "UseQueryExamples": true,
  "DiscoverExamples": true,
  "ExamplesDirectory": "/root/Compile/Example",
  "DataFuzzing": true,
  "ReadOnlyFuzz": false,
  "ResolveQueryDependencies": true,
  "ResolveBodyDependencies": true,
  "UseRefreshableToken": true,
  "AllowGetProducers": false
}

My dict.json looks like this:
{
  "restler_fuzzable_string": [
    "fuzzstring"
  ],
  "restler_fuzzable_string_unquoted": [],
  "restler_fuzzable_datetime": [
    "6/25/2019 12:00:00 AM"
  ],
  "restler_fuzzable_datetime_unquoted": [],
  "restler_fuzzable_uuid4": [
    "903bcc44-30cf-4ea7-968a-d9d0da7c072f"
  ],
  "restler_fuzzable_uuid4_unquoted": [],
  "restler_fuzzable_int": [
    "0",
    "1"
  ],
  "restler_fuzzable_number": [
    "0.1",
    "1.2"
  ],
  "restler_fuzzable_bool": [
    "true"
  ],
  "restler_fuzzable_object": [
    "{}"
  ],
  "restler_custom_payload": {
  "to": ["2021-03-09T16:01:13Z", "2021-03-10T16:01:13Z"],
  "from": ["2021-03-08T16:01:13Z", "2021-03-11T16:01:13Z"]
  },
  "restler_custom_payload_unquoted": {},
  "restler_custom_payload_uuid4_suffix": {}
}

And so when I run the compile command stated above with the settings described, I still get the following:
    ....
    primitives.restler_static_string("&"),
    primitives.restler_static_string("from="),
    primitives.restler_fuzzable_string("fuzzstring", quoted=False),
    primitives.restler_static_string("&"),
    primitives.restler_static_string("to="),
    primitives.restler_fuzzable_string("fuzzstring", quoted=False),
    primitives.restler_static_string("&"),
    primitives.restler_static_string("sort="),
    primitives.restler_static_string("["),
    primitives.restler_fuzzable_string("fuzzstring", quoted=True),
    primitives.restler_static_string("]"),
    primitives.restler_static_string("&"),
    ....

I see 4 issues here:

The compiler does not create ISO format for datetime properties seen in the openapi. see the "restler_fuzzable_datetime" field above.
The compiler does not take "restler_fuzzable_datetime" values for constructing datetime formats in the grammar.py.
The compiler does not pick the custom payload for datetime and keeps seeing datetime by its type which is a string and so places fuzzstrings in grammar.py for it. This results in 400 error responses by the server.
Wherever we have

       style: form
       explode: false

in the open api for object properties, we have to create a list without brackets, and quotations. See Query Parameters table, second row, in https://swagger.io/docs/specification/serialization/.

I found this today, and it seems the compiler only supports the date-time format for strings, of the ones stated in the swagger specification. For me, this caused issues with 'date'. I'm on 7.4, but from the code this seems to still be a problem in 8. I just added 'date' to the 'date-time' case in the swaggervisitor in my local source tree, but presumably this is not the fully correct solution (and mainly works because I know how the API I'm testing works).

Hello @larsivi, thanks for bringing this up.  We have added 'date' recently, it's included in 8.1.0 (yep, adding it is a bit more involved at this point than just adding the case to the code... we're looking into to improve the implementation to avoid having to extend the engine for every type of format, see issue #369.  If you read the description in that issue, let us know if you have feedback.)
Thanks!
Marina


Function that takes array of Timestamp cannot be called?

Perhaps I am calling this wrong but it seems like a function with an array of timestamps cannot be called as it is unclear if this should map to a text array or an array of timestamps.
Minimal example:
CREATE OR REPLACE FUNCTION ts_non_array(
  _timestamp TIMESTAMP
) RETURNS TEXT
AS $$
BEGIN
  RETURN 'Hello World';
END
$$ LANGUAGE PLPGSQL VOLATILE;

select ts_non_array('"2013-10-21T13:28:06.419Z"');

CREATE OR REPLACE FUNCTION ts_array(
  _timestamp TIMESTAMP[]
) RETURNS TEXT
AS $$
BEGIN
  RETURN 'Hello World';
END
$$ LANGUAGE PLPGSQL VOLATILE;

select ts_array('{"2013-10-21T13:28:06.419Z","2013-10-21T13:28:06.419Z"}');

Outputs "Hello World in both cases
Calling them from graphql

mutation {tsNonArray (input: {
  _timestamp: "2013-10-21T13:28:06.419Z"
}) {string}
}
RETURNS
{
  "data": {
    "tsNonArray": {
      "string": "Hello World"
    }
  }
}

Calling the one with the array however
mutation {tsArray (input: {
  _timestamp: ["2013-10-21T13:28:06.419Z"]
}) {string}
}

RETURNS
...
errors": [
    {
      "message": "function public.ts_array(text[]) does not exist",
...

Interesting; could you turn on debugging with export DEBUG="postgraphql:*" and tell us what SQL statements are executed?

It gives some output, but not too much see below:
graphql-server_1         | Thu, 19 Jan 2017 23:17:55 GMT postgraphql:request GraphQL query request has begun.
graphql-server_1         | Thu, 19 Jan 2017 23:17:55 GMT postgraphql:request GraphQL query is parsed.
graphql-server_1         | Thu, 19 Jan 2017 23:17:55 GMT postgraphql:request GraphQL query request finished.
graphql-server_1         | 1 error(s) in 6.92ms :: mutation { tsArray(input: {_timestamp: ["2013-10-21T13:28:06.419Z"]}) { string } }

@angelosarto it looks like the Postgres query information is missing from the logs. Perhaps try just DEBUG="postgraphql:postgres"?
I think the fix we need to implement is add Postgres type information to the queries we send to the database. So:
select to_json("public"."ts_array"(array[$1, $2, $3]));

Would become:
select to_json("public"."ts_array"(array[$1::timestamp, $2::timestamp, $3::timestamp]));

…or we may be able to get away with:
select to_json("public"."ts_array"(array[$1::timestamp, $2, $3]));

To hint the type to Postgres.

Tried with DEBUG="postgraphql:postgres"
got this output:
graphql-server_1         | Fri, 20 Jan 2017 23:29:50 GMT postgraphql:postgres begin
graphql-server_1         | Fri, 20 Jan 2017 23:29:50 GMT postgraphql:postgres select to_json(__local_0__) as value from "public"."ts_array2"(array[$1]) as __local_0__
graphql-server_1         | Fri, 20 Jan 2017 23:29:50 GMT postgraphql:postgres error: function public.ts_array2(text[]) does not exist
graphql-server_1         |     at Connection.parseE (/usr/local/lib/node_modules/postgraphql/node_modules/pg/lib/connection.js:554:11)
graphql-server_1         |     at Connection.parseMessage (/usr/local/lib/node_modules/postgraphql/node_modules/pg/lib/connection.js:381:17)
graphql-server_1         |     at Socket.<anonymous> (/usr/local/lib/node_modules/postgraphql/node_modules/pg/lib/connection.js:117:22)
graphql-server_1         |     at emitOne (events.js:96:13)
graphql-server_1         |     at Socket.emit (events.js:188:7)
graphql-server_1         |     at readableAddChunk (_stream_readable.js:176:18)
graphql-server_1         |     at Socket.Readable.push (_stream_readable.js:134:10)
graphql-server_1         |     at TCP.onread (net.js:551:20)
graphql-server_1         | Fri, 20 Jan 2017 23:29:50 GMT postgraphql:postgres commit
graphql-server_1         | 1 error(s) in 10.41ms :: mutation { tsArray2(input: {_timestamp: ["2013-10-21T13:28:06.419Z"]}) { datetimes } }

I also tried with a couple of other types - with INTEGER[] and TEXT[] it works, but I also found it doesn't work with NUMERIC[] as it tries to coerce them all to ints. So we may need to cast each item see below:
SQL (ignore that the field is named _timestamp, got lazy on that copypasta :)
CREATE OR REPLACE FUNCTION numeric_array(
  _timestamp NUMERIC[]
) RETURNS TEXT
AS $$
BEGIN
  RETURN 'Hello World';
END
$$ LANGUAGE PLPGSQL VOLATILE;

graphql mutation query (wouldn't actually have to be a mutation, but hey)
mutation{ numericArray (input: {
  _timestamp: [123.1, 456]
}){string}}

graphiql output
{
  "data": {
    "numericArray": null
  },
  "errors": [
    {
      "message": "invalid input syntax for integer: \"123.1\"",
      "locations": [
        {
          "line": 64,
          "column": 11
        }
      ],
      "path": [
        "numericArray"
      ]
    }
  ]
}

DEBUG Output
graphql-server_1         | Fri, 20 Jan 2017 23:37:14 GMT postgraphql:postgres begin
graphql-server_1         | Fri, 20 Jan 2017 23:37:14 GMT postgraphql:postgres select to_json("public"."numeric_array"(array[($1 + 0), ($2 + 0)])) as value
graphql-server_1         | Fri, 20 Jan 2017 23:37:14 GMT postgraphql:postgres error: invalid input syntax for integer: "123.1"
graphql-server_1         |     at Connection.parseE (/usr/local/lib/node_modules/postgraphql/node_modules/pg/lib/connection.js:554:11)
graphql-server_1         |     at Connection.parseMessage (/usr/local/lib/node_modules/postgraphql/node_modules/pg/lib/connection.js:381:17)
graphql-server_1         |     at Socket.<anonymous> (/usr/local/lib/node_modules/postgraphql/node_modules/pg/lib/connection.js:117:22)
graphql-server_1         |     at emitOne (events.js:96:13)
graphql-server_1         |     at Socket.emit (events.js:188:7)
graphql-server_1         |     at readableAddChunk (_stream_readable.js:176:18)
graphql-server_1         |     at Socket.Readable.push (_stream_readable.js:134:10)
graphql-server_1         |     at TCP.onread (net.js:551:20)
graphql-server_1         | Fri, 20 Jan 2017 23:37:14 GMT postgraphql:postgres commit
graphql-server_1         | 1 error(s) in 20.94ms :: mutation { numericArray(input: {_timestamp: [123.1, 456]}) { string } }

Oh, and a quick post as a workaround in case someone needs one:
If you need an array that is not an int or  text - declare your function to accept TEXT arrays instead and unnest and cast like this:
CREATE OR REPLACE FUNCTION your_function_that_needs_arrays(
  these_are_normal INTEGER[],
  this_is_also_fine TEXT[],
  these_are_really_timestamp TEXT[],
  these_are_really_numeric TEXT[]
) RETURNS something
AS $$

-- Outside of this select you can get new_values._normals, _fines, _timestamps, _numerics as a table  You could also could use aggregate to bring the rows back to arrays...
       SELECT
         t._normals,
         t._fines,
         t._timestamps:: TIMESTAMP,
         t._numerics::NUMERIC
       FROM unnest(these_are_normal, this_is_also_fine, these_are_really_timestamp, these_are_really_numeric)
         AS t(_ _normals, _fines, _timestamps, _numerics)
     ) as new_values

$$ LANGUAGE SQL VOLATILE;

Ok cool. It looks like my proposed solution should fix this case then. I’d be happy to merge a PR which explicitly casts inputs 😊

Thanks for the great test case @angelosarto; can confirm this is fixed in v4 👍


NIFI-10711 Make script runners more debuggable.

Summary
NIFI-00000
Tracking
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[ ] Apache NiFi Jira issue created

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[ ] Pull Request title starts with Apache NiFi Jira issue number, such as NIFI-00000
[ ] Pull Request commit message starts with Apache NiFi Jira issue number, as such NIFI-00000

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[ ] Pull Request based on current revision of the main branch
[ ] Pull Request refers to a feature branch with one commit containing changes

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[ ] Build completed using mvn clean install -P contrib-check

[ ] JDK 8
[ ] JDK 11
[ ] JDK 17

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[ ] New dependencies are compatible with the Apache License 2.0 according to the License Policy
[ ] New dependencies are documented in applicable LICENSE and NOTICE files

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[ ] Documentation formatting appears as expected in rendered files

@mattyb149 can you take a look?

Thanks @mattyb149


CUDA error: invalid configuration argument

Thank you for your work. Your work is excellent.
I was able to train normally and get satisfactory results, but during the verification process, the following error occurs:
Global seed set to 42
Using 16bit None Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
`Trainer(limit_train_batches=1.0)` was configured so 100% of the batches per epoch will be used..
`Trainer(limit_val_batches=1.0)` was configured so 100% of the batches will be used..
[rank: 0] Global seed set to 42
Initializing distributed: GLOBAL_RANK: 0, MEMBER: 1/1
----------------------------------------------------------------------------------------------------
distributed_backend=nccl
All distributed processes registered. Starting with 1 processes
----------------------------------------------------------------------------------------------------

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
fatal: 不是一个 git 仓库（或者直至挂载点 / 的任何父目录）
停止在文件系统边界（未设置 GIT_DISCOVERY_ACROSS_FILESYSTEM）。
/home/zsy/instant-nsr-pl-main/utils/callbacks.py:76: UserWarning: Code snapshot is not saved. Please make sure you have git installed and are in a git repository.
  rank_zero_warn("Code snapshot is not saved. Please make sure you have git installed and are in a git repository.")

  | Name  | Type      | Params
------------------------------------
0 | model | NeRFModel | 12.6 M
------------------------------------
12.6 M    Trainable params
0         Non-trainable params
12.6 M    Total params
25.220    Total estimated model params size (MB)
Epoch 0: : 600it [00:28, 21.05it/s, loss=0.00194, train/num_rays=8192.0]/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/logger_connector/result.py:539: PossibleUserWarning: It is recommended to use `self.log('val/psnr', ..., sync_dist=True)` when logging on epoch level in distributed setting to accumulate the metric across devices.
  warning_cache.warn(
Epoch 0: : 3517it [02:17, 25.67it/s, loss=0.000735, train/num_rays=8192.0, val/psnr=31.60]Traceback (most recent call last):
  File "launch.py", line 128, in <module>██████                                                                                | 17/100 [00:02<00:13,  6.36it/s]
    main()
  File "launch.py", line 117, in main
    trainer.fit(system, datamodule=dm)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 608, in fit
    call._call_and_handle_interrupt(
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 36, in _call_and_handle_interrupt
    return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 88, in launch
    return function(*args, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _fit_impl
    self._run(model, ckpt_path=self.ckpt_path)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1112, in _run
    results = self._run_stage()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1191, in _run_stage
    self._run_train()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1214, in _run_train
    self.fit_loop.run()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
    self.advance(*args, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/fit_loop.py", line 267, in advance
    self._outputs = self.epoch_loop.run(self._data_fetcher)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
    self.on_advance_end()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 250, in on_advance_end
    self._run_validation()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 308, in _run_validation
    self.val_loop.run()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
    self.advance(*args, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 152, in advance
    dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
    self.advance(*args, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 137, in advance
    output = self._evaluation_step(**kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 234, in _evaluation_step
    output = self.trainer._call_strategy_hook(hook_name, *kwargs.values())
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1494, in _call_strategy_hook
    output = fn(*args, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/strategies/ddp.py", line 359, in validation_step
    return self.model(*args, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 886, in forward
    output = self.module(*inputs[0], **kwargs[0])
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/pytorch_lightning/overrides/base.py", line 110, in forward
    return self._forward_module.validation_step(*inputs, **kwargs)
  File "/home/zsy/instant-nsr-pl-main/systems/nerf.py", line 137, in validation_step
    out = self(batch)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zsy/instant-nsr-pl-main/systems/nerf.py", line 31, in forward
    return self.model(batch['rays'])
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zsy/instant-nsr-pl-main/models/nerf.py", line 133, in forward
    out = chunk_batch(self.forward_, self.config.ray_chunk, True, rays)
  File "/home/zsy/instant-nsr-pl-main/models/utils.py", line 22, in chunk_batch
    out_chunk = func(*[arg[i:i+chunk_size] if isinstance(arg, torch.Tensor) else arg for arg in args], **kwargs)
  File "/home/zsy/instant-nsr-pl-main/models/nerf.py", line 103, in forward_
    rgb = self.texture(feature, t_dirs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zsy/instant-nsr-pl-main/models/texture.py", line 27, in forward
    color = self.network(network_inp).view(*features.shape[:-1], self.n_output_dims).float()
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zsy/anaconda3/envs/djx_pytorch/lib/python3.8/site-packages/tinycudann-1.7-py3.8-linux-x86_64.egg/tinycudann/modules.py", line 180, in forward
    self.params.to(_torch_precision(self.native_tcnn_module.param_precision())).contiguous(),
RuntimeError: CUDA error: invalid configuration argument
Epoch 0: : 3517it [02:17, 25.59it/s, loss=0.000735, train/num_rays=8192.0, val/psnr=31.60]

My GPU is a single 3090, in training and testing phase, video memory is normal.

I haven't encountered this problem, but sometimes weird things did happen like this 😂 I suggest you resume from the last checkpoint (ckpts/last.ckpt) and continue training, the problem may be gone.

I also encountered this error, when I run nerf, it is normal when I run neus.


How to get the "standard" logdensity?

Sometimes I am actually bothered by the fact that the base measure of, say, Normal() is not the Lebesgue measure. In case I need the traditional logdensity, what do I do?

This is a great point, and something we definitely need to improve.
I think currently you can do something like

Get the density relative to the base measure you want
Integrate this with respect to the base measure to get the result

It's generally better to do this in log space, so you end up with
julia> ℓ = log𝒹(Normal(), Lebesgue(ℝ))
MeasureTheory.Density{Normal{(), Tuple{}}, Lebesgue{ℝ}, Val{true}}(Normal(), Lebesgue(ℝ), Val{true}())

julia> μ = ∫exp(ℓ, Lebesgue(ℝ))
DensityMeasure ∫(Density{Normal{(), Tuple{}}, Lebesgue{ℝ}, Val{true}}(Normal(), Lebesgue(ℝ), Val{true}()), Lebesgue(ℝ); log = true)

There are obvious problems with this:

It takes more effort than it should
It's very notation-heavy
The result is still a normal distribution, but it's unrecognizable

I think an analogy can help us think about this in the right way. Entirely outside of MeasureTheory, say you want to represent a vector space. There are some things you can do very abstractly, but for others you need to specify a basis. Then

Choice of preferred basis might depend strongly on what kind of operations you want to do
We might want two vector spaces to be == if they have the same span, even if the bases are different

Currently the basemeasure for e.g. a Normal is fixed at 0.398942 * Lebesgue(ℝ), and changing it gives you something that's not a Normal. Maybe this shouldn't be the case?
BTW in case it's not clear, the motivation for our current choice of basemeasure is that of the terms in the logdensity with respect to Lebesgue measure, many of them don't depend on x, the point where we're evaluating the log-density. By removing these terms and changing the base measure accordingly, we can get something more efficient and composable.


IFramePanel implemenation

Q
A

Bug fix?
[ ]

New feature?
[X ]

New sample?
[ ]

Related issues?
fixes #X, partially #Y, mentioned in #Z

What's in this Pull Request?
New Implemenation of an IFramePanel control Similar to the IFrameDialog except renders an IFrame in a Fabric UI Panel. Did not open a discussion for this but I needed to build it anyway. Add it if everyone feels its a good idea.
Has a nice dynamic height if the height is not set. Tested in IE, Chrome, Edge.

HI @spdavid!
Could you please check the error from CircleCI:
[21:47:50] Error - [webpack] 'dist':
./lib/controls/iFramePanel/IFramePanel.js
Module not found: Error: Can't resolve './IframePanelContent' in '/home/circleci/sp-dev-fx-controls-react/lib/controls/iFramePanel'
resolve './IframePanelContent' in '/home/circleci/sp-dev-fx-controls-react/lib/controls/iFramePanel'
  using description file: /home/circleci/sp-dev-fx-controls-react/package.json (relative path: ./lib/controls/iFramePanel)
    Field 'browser' doesn't contain a valid alias configuration
  after using description file: /home/circleci/sp-dev-fx-controls-react/package.json (relative path: ./lib/controls/iFramePanel)
    using description file: /home/circleci/sp-dev-fx-controls-react/package.json (relative path: ./lib/controls/iFramePanel/IframePanelContent)
      no extension
        Field 'browser' doesn't contain a valid alias configuration
        /home/circleci/sp-dev-fx-controls-react/lib/controls/iFramePanel/IframePanelContent doesn't exist
      .js
        Field 'browser' doesn't contain a valid alias configuration
        /home/circleci/sp-dev-fx-controls-react/lib/controls/iFramePanel/IframePanelContent.js doesn't exist
      .json
        Field 'browser' doesn't contain a valid alias configuration
        /home/circleci/sp-dev-fx-controls-react/lib/controls/iFramePanel/IframePanelContent.json doesn't exist
      as directory
        /home/circleci/sp-dev-fx-controls-react/lib/controls/iFramePanel/IframePanelContent doesn't exist

Codecov Report

Merging #226 into dev will not change coverage.
The diff coverage is n/a.

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=======================================
  Coverage   72.71%   72.71%
=======================================
  Files          16       16
  Lines         744      744
  Branches      138      148   +10
=======================================
  Hits          541      541
  Misses        159      159
  Partials       44       44

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@AJIXuMuK All checks now passed.

Thanks @spdavid, I did some code changes to the control for consistency, but also for retrieving the parent element by the className. Control has been merged and will be available in v1.12.0.


build: Update Vulkan-Headers and VUL 1.3.273

CI Vulkan-ExtensionLayer build queued with queue ID 97907.

CI Vulkan-ExtensionLayer build # 813 running.

CI Vulkan-ExtensionLayer build # 813 failed.

CI Vulkan-ExtensionLayer build queued with queue ID 99236.

CI Vulkan-ExtensionLayer build queued with queue ID 99245.

CI Vulkan-ExtensionLayer build # 816 running.


ActivityNet

Can you provide the code of ActivityNet dataset?

ANet branch.

I want to make sure, are you using this?

I use the feature of anet_i3d_feature_25fps/flow(rgb)-resize-step16 and test with your checkpoint_best_auc.pth, but the resuts I get is this.

When I retrain the Anet, it will have this problem after some epochs, maily in the case of evaluation. I don't know why have this problem.  Looking forward your reply!


HTML5 Video player doest not show markers tip on live server. Its working fine on localhost.

I have created a script for interactive video and I got some requirements to show markers in the process bar of video. I worked on that and it works perfectly on localhost but when I put it live, only markers are showing. The text with those markers is not showing. I have searched everywhere on google and lot on videojs guides but I am not able to fix it. Below is my code for creating markers:
<video width="100%" controls id="sgm_2" class="video-js vjs-default-skin" preload="auto">
						<source src="video.mp4" type="video/mp4">
						<source src="video.webm" type="video/webm">

Your browser does not support HTML5 video.

					</video>

var player = videojs('sgm_2');
			player.markers({
				markerTip:{
			        display: true,
			        text: function(marker) {
			        	return marker.text;
			        },
			        time: function(marker) {
				    	return marker.time;
				    }
			    }
			});
			player.markers.reset([
				{
			    	time: 10,
			    	text: "Caption 1"
			    },
			    {
			    	time: 20,
			        text: "Caption 2"
			    },
			    {
			    	time: 30,
			        text: "Caption 3"
			    },
			    {
			    	time: 40,
			        text: "Caption 4"
			    }
			]);`

Can anyone please check what is the thing I am missing or what is wrong with this code? I have also used the funcltion of add instead of reset markers but no luck. I will appreciate any help.
Thank you.

Hey, I"m happy to help.
Could you create a jsbin so I can debug it more closely online? Thanks

same here. markers are not showing after hosting. its working on localhost.
player = videojs('my-video');
player.on('ready', function(){
	$http.get('questions/markers.json').then(function(response){
		makeModalData(response.data);
		player.markers({
		    markers: response.data,
		    onMarkerReached: function (marker, index) {
		    	player.pause();
		    	openModal(marker.id);
		    }
		});
	},function(error){
		debugger;
	});
});

need help.

@karan101292, can you help create an example jsbin so i can repro online and debug?


CI ONLY WiP New analyzer

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Ready for review :)
I haven't done performance tests yet. I'm currently on vacation with only a Windows laptop, unfit for that kind of tests. Maybe I'll have the courage to do some tests over ssh, but most likely it will have to wait until after I'm back on August 16.

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Test PASSed.

Still to-do:

LinkedMember -> Versioned
Try MethodInfoCache in Refiner
Performance measurements

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Updated. I have left the Versioned renaming and the per-method Infos computation in Refiner as separate commits, for easier review, but I think they should be squashed.

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Updated.

Yes, let's wait until I get to do those perf tests. I'll try to do that tomorrow.

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Test PASSed.

Results of the benchmarks: https://gist.github.com/sjrd/5c5c9b9f3f8da398af9a560dd20978bb
Everything is done on the test suite.
warm, compile
the time taken by GenJSCode to compile all of test:compile. The time difference between master and new-analyzer seems to be slightly in favor of new-analyzer, but with such a variance that it's probably non-significant
cold, batch (with checkIR)
testSuite/test:fastOptJS on a cold sbt/JVM, obviously in batch mode. The results here are dominated by the disappearance of the Check Infos subphase, which took a whole second. Timings of individual subphases cannot be compared, because the Check Infos part forced all the files to be loaded in memory, including their Trees and Infos, which means there was much less work for the other subphases to do.
Because the presence of Check Infos completely destroys everything else about the analysis, all the subsequent measurements are done with checkIR disabled.
cold, batch, without checkIR
Here we see that Basic Linking is slightly faster (~200ms) in new-analyzer, despite having to recompute the Infos. This could be caused by not having to construct the in-memory representation of the unused Infos, but somehow I don't buy it. The difference is probably not significant.
The Refiner is significantly slower in new-analyzer in this configuration. But that's also because the Refiner stole some work previously done by the the Optimizer: computing the Infos of optimized methods. And indeed, if we count the improved timings of the Optimizer from master to new-analyzer, it seems to compensate for the longer time in Refiner.
warm, batch, without checkIR
Here, in addition to the JVM being warm, the global IR cache has also already been filled with a lot of things. So even with a clean instance of Linker, some significant I/O work is removed. This explains the huge difference in timings between this set of measurements and the previous one.
Between master and new-analyzer, the timings are inconclusive for Basic Linking. Refiner has similar characteristics as the previous set.
warm, degenerate incremental, without checkIR
Here, we only rm the -fastopt.js file, and re-link. This means that all inputs are unchanged, and the linker is fully up-to-date in its incremental data structures.
Times for Basic Linking are inconclusive again. The Refiner seems to be slower in new-analyzer, which probably means that using the cached Infos in Refiner is somewhat less efficient than directly using those from the Optimizer.
warm, test-suite test-classes re-compiled, no checkIR
In this scenario, we force re-compilation of all files in the test-suite, but otherwise keep a warmed up linker. This forces the Basic Linking step to recompute all the Infos of the test-suite, but not of the standard library.
Here it seems that the Basic Linking step is basically not impacted at all between master and new-analyzer, despite new-analyzer having to recompute all those Infos. The Refiner seems slightly faster, but by a small margin.
warm, change one source, no checkIR
This is supposed to be a "typical" incremental run, where one source file is changed.
The Basic Linking step seems slightly faster in new-analyzer. The Refiner is also faster in new-analyzer, by a somewhat larger margin.
Conclusion
Overall I think these results are good enough. At the very least, they show that we don't have any regression in incremental runs (we even seem to be a bit faster). The batch runs are a bit slower in some configurations, as expected, but by a rather small margin.
@gzm0 Does that satisfy you?

LGTM Ship It :)


Query the latest network height in vald to start listening to events from

Description/Reasoning
vald seems to retrieve the latest block height of the Axelar node it talks to, instead of the network. This causes it to reprocess events that have already been processed when the node itself is resyncing. As an example, a validator catching up will broadcast old heartbeat events from their vald and cause vald broadcaster queue to be filled.
vald should query the latest block height (or at the least whether the network is in catching up mode) before beginning to process events. Either it can retry every X time units and check if the node is synced before beginning to listen, or it can return an error, and the validator has to manually start it once their node is synced. The former makes it easier for validators to automate and increase their liveness.
Current Behaviour
Expected Behaviour
Steps to reproduce (for bugs)
Relevant Logs or Files

I think the only thing that makes sense is to block if the status of the node is catching up. Starting to query other nodes in the network that are out of sync with the local node is a recipe for disaster


HQ Music for Alexander The Burden of the Father (A4) and The Burden of the Son (A8) does not play in game

Hello, in-game when I enter the raids The Burden of the Father or The Burden of the Son, I do not hear any music, regardless of whether /bgm is turned on.
The relevant generated music file is BGM_EX1_Alex03.scd. This generated file seems to play fine through vgmstream in Foobar2000.
I noticed this music is also used in BGM_ORCH_119.scd, and that file seems to play just fine in-game (Orchestrion "metal").
BGM_EX1_Alex03.scd is about 25mb, while BGM_ORCH_119.scd is about 5mb. I don't know if that's relevant.
The XIVAlexander music import config is here:
https://github.com/Soreepeong/XivAlexander/blob/b78d00f3a9e73fee5bf014eae31574717fa58a6d/StaticData/MusicImportConfig/Heavensward.json#L1009-L1065
Maybe it has something to do with the channel/segments config? I don't really know how that config works.
I've generated all other music files for all expansions using the import config, and so far this is the only time I've encountered this issue. Can anyone else running the upgraded HQ music reproduce this issue in A4 or A8?

A good way to test is just to solo unsynced FYI 😄
I only noticed when I was doing both of those for BLU spells.

I just tested and it works fine for me. Can you try playing the generated scd file with a media player?


Move Template Checkboxes

reconfigure checkboxes on pdf template to fit into boxes

reconfigured text boxes and checkboxes to fit into each space on the final form


Disclose unexpected behavior information

The previous information was not certain, now I made some tests and found the exact behavior.

waiting on @SMJSGaming

Not sure how I missed this for an entire year but ok


db_volume_write() corrupted files

Hi, first of all this package is something that has been very much lacking for R users connecting to Databricks from outside.
I have found that when I try to upload parquet or csv file using db_volume_write() and then create a table from the file or read it back, the file becomes corrupted. Example code below:
arrow::write_parquet(mtcars, "mtcars.parquet")

brickster::db_volume_write(
  path = "Volumes/.../mtcars.parquet",
  file = "mtcars.parquet"
)

brickster::db_volume_read(
  path = "Volumes/.../mtcars.parquet",
  destination = "mtcars_databricks.parquet"
)

arrow::read_parquet("mtcars_databricks.parquet")

And the error I receive:

Error: Invalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.

Could you have a look into this?

Hey @brenktt - thanks for the repro!
Let me look into it, it does seem like db_volume_write is the culprit from my further testing so far.
# write arrow --> read arrow:                                        success
# write arrow --> db_volume_write --> ui download --> read arrow:    error
# write arrow --> db_volume_write --> db_volume_read --> read arrow: error
# write arrow --> ui upload --> db_volume_read --> read arrow:       success

I can see that bytes are getting injected

I've adjusted the code to use different methods in {httr2} and it now should work.
It's currently in the branch volume_fixes.
I'll make a PR once tests pass.

@brenktt if you can test from the branch it would be great to get confirmation it is behaving as expected before I merge!

@zacdav-db I have tested the fixed code and it seems to be working as expected (although the upload/download speed seems to be slower than before), thanks a lot!
Is there a plan to have the package published on CRAN anytime soon?

Thanks @brenktt - I've merged the changes into main branch.
Yes there is a plan but some details are being worked out with other projects at Databricks.
I intend to have brickster on CRAN hopefully in next 4 weeks 🤞.


trial_patient_match - Patient Data Clarification

Hi Ryan,
I'm working on a project to streamline the process of matching cancer patients interested in engaging in clinical trials to suitable clinical trials that are recruiting (generally through ClinicalTrials.gov). It looks like this is the intent of your trial_patient_match models here, and wanted to clarify a few things. To summarize some of what I'm looking to do, I'm looking to make an app where a patient enters their personal information (including age, gender, cancer type, stage etc.) and a list of potential clinical trials that are recruiting is provided. This is made rather difficult given that the Inclusion Criteria of ClinicalTrials.gov API output, which contains most of the finer details of patient-trial matching, is open text and therefore inconsistent. I'm trying to find a way around that barrier.
I played around with the Google Colab notebooks where you train trial_patient_match models on EHR and ClinicalTrials.gov data. It looks like the patient data primarily focuses on previous patient visits and demographic data. I'm not seeing a field for specific cancer type, or time since first diagnosis, cancer stage etc. Is it assumed that those fields are best indicated by the trial data as opposed to the patient data?
It looks to me that the purpose of the trial_patient_match model trains based on matching patients to the trial they have already been accepted into. Is that correct? That makes sense to me, as it would provide a fairly robust list of patient-to-trial-matches, but am toying with the idea of adapting the model to accept survey data.

Hi, Thanks for your interest in pytrial!
The setup in this package refers to the literature in patient trial matching, where they utilized EHR patient sequence and demographic to encode patient records to dense embeddings, then match them to trials.
However, it does mean it is a must to always use this information for matching. The implementation of PatientData contains a field x which could be tabular data represented by pd.DataFrame  so it offers the flexibility to include all kinds of patient properties if they can be organized like tables.
It is also doable to remove the sequence inputs for PatientData but that will need an adaptation of the existing implementations. Unfortunately, we don't have an implementation using only the tabular data for matching. Nonetheless, that will be rather easy to implement cuz all we need to do is disable the sequence inputs from the existing data class. I will suggest you clone the package to your local environment and try to subclass the trial_patient_match.data.PatientData and trial_patient_match.models to adjust the data format and the model inputs.
Zifeng

Hi Zifeng,
Thank you so much! By any chance are there specific papers you are looking at in the patient trial matching literature that you could share here? It would help a great deal reading through the code to know what it is specifically based on.
Thank you for the subclass suggestion! I'll probably make a forked repository for that - it would be easier for me to develop, and ultimately can be pulled back here if you like the additions I make.
Caleb

We have two models implemented in PyTrial: https://pytrial.readthedocs.io/en/latest/pytrial.tasks.trial_patient_match.html

DeepEnroll:  Zhang, Xingyao, et al. “DeepEnroll: patient-trial matching with deep embedding and entailment prediction.” Proceedings of The Web Conference 2020.

COMPOSE: Gao, J., et al. (2020, August). COMPOSE: cross-modal pseudo-siamese network for patient trial matching. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 803-812).

Some other relevant papers:
Dense embeddings

Isabel Segura-Bedmar and Pablo Raez. Cohort selection for clinical trials using deep learning models. Journal of
the American Medical Informatics Association, 26(11):1181– 1188, 2019

Houssein Dhayne, Rima Kilany, Rafiqul Haque, and Yehia Taher. EMR2Vec: Bridging the gap between patient data and clinical trial. Computers & Industrial Engineering, 156: 107236, 2021

Xiong Liu, Cheng Shi, Uday Deore, Yingbo Wang, Myah Tran, Iya Khalil, and Murthy Devarakonda. A scalable ai approach for clinical trial cohort optimization. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages 479–489. Springer, 2021.

Information extraction

Chunhua Weng, Xiaoying Wu, Zhihui Luo, Mary Regina Boland, Dimitri Theodoratos, and Stephen B Johnson. EliXR: an approach to eligibility criteria extraction and representation. Journal of the American Medical Informatics Association, 18(Supplement_1):i116–i124, 2011.

Chi Yuan, Patrick B Ryan, Casey Ta, Yixuan Guo, Ziran Li, Jill Hardin, Rupa Makadia, Peng Jin, Ning Shang, Tian Kang, et al. Criteria2Query: a natural language interface to clinical databases for cohort definition. Journal of the American Medical Informatics Association, 26(4):294–305, 2019.

Tian Kang, Shaodian Zhang, Youlan Tang, Gregory W Hruby,
Alexander Rusanov, Noémie Elhadad, and Chunhua Weng. EliIE: An open-source information extraction system for clinical trial eligibility criteria. Journal of the American Medical Informatics Association, 24(6):1062–1071, 2017.

Ying Xiong, Weihua Peng, Qingcai Chen, Zhengxing Huang, and Buzhou Tang. A unified machine reading comprehension framework for cohort selection. IEEE Journal of Biomedical and Health Informatics, 26(1):379–387, 2021.

Zifeng

Perfect, thank you! I'll close this issue to get it out of your issues feed, but may comment on it in the future with additional questions.

Hi Zifeng,
I have a few follow-up questions. I looked over the papers you provided as well as your demo code for the patient trial matching portion of your program. I don't really have questions about the format for your clinical data - correct me if I'm wrong, but it looks like it was taken straight from ClinicalTrials.gov, where you then applied clinicalBERT to essentially index the inclusion and exclusion criteria to prepare it for matching with patient information.
As for the patient data, I looked at the load_mimic_ehr_sequence function in pytrial.data.demo_data, which you use to create your demo PatientData class in the Colab notebooks. It looks like you return the following values from that function (I describe them for personal note taking here):
load_mimic_ehr_sequence:
	*visit: A list of entries, one for each patient
			> Next Level: List of Visits for that patient
					> Next Level: Each visit consists of a list of 3 integer lists, likely corresponding to 'order' below. What do these integers mean?
	*voc: unknown. Based on 'order' below.
	*order: A hard-coded list ['diag', 'prod', 'med'], likely diagnosis, procedures and medications.
	*mortality: Boolean for each patient. Whether or not they're alive?
	*feature: age, gender, and ethnicity of each patient.
	*n_num_feature: When numeric features end in the features (currently 1 - age alone)
	*cat_cardinalities: Has total number of categories for each categorical feature. 2 and 15 for gender and ethnicity, respectively.

In summary, my questions on this data are the following:

The demo data appears to have been taken from the MIMIC-III dataset, but I think it went through a preprocessing step that is not found in this repository (referring to the data found in 'PyTrial/demo_data/demo_patient_sequence/ehr/'. What was the preprocessing step?
You frequently use the three categories listed in the order list, such as to categorize values in a visit (order list being ['diag', 'prod', 'med']). Are these categories Diagnoses, Procedures and Medications, respectively?
What do the integers found in each visit signify? (Answering question 1 may answer this question. See What do these integers mean? in the above breakdown of the load_mimic_ehr_sequence function output). Are they relatable to the eligibility criteria of a clinical trial?
Can there be no visits recorded for the program to run, or is that a hard requirement?
What is the voc category?
How are you testing this program?
Possibly in relation to question 5, but do you have the ability to obtain patient data for patients that participated in completed or terminated clinical trials (ie, non-demo training data)? I'm reaching out to a few others to possibly obtain this data, but thought I'd ask you too.

As a final point, one of the primary changes I needed to make to run your demo code was to specify an mps device for BERT, as I have an M1 Mac and cannot seem to get cuda running appropriately. I forked the repository to investigate and implement this change, but haven't generalized the code to check for cuda first, then mps, then cpu. That may be an appropriate change in the future.
Best,
Caleb

Hi Caleb,

the preprocessing code is not provided in pytrial. I used the code from SafeDrug https://github.com/ycq091044/SafeDrug with some edits.

yes.

it indicates the index of event belonging to 'diag', 'prod', 'med'. It should be available in the vocabular provided in the demo data.

I think visits are required to run the code. Otherwise, we need to modify the model to disable the inputs and processing for visit data, with if/else logics.

Pls see the point 3.

We do not have a structured unit test yet. The testing process is made by writing an example for each model, e.g., like the ones in https://colab.research.google.com/drive/12JK9DCyHvMZuylgWZ6cDDLx8JC6sMait?usp=sharing

some data  is available in project data sphere (https://www.projectdatasphere.org/). But it is still challenging to get their properties that decide if they are eligible or just partially eligible to the corresponding trials.

Zifeng


Add C# logo

Add logo for C# which is similar to C and C++.

<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 48 48" width="240" height="240"><path fill="#37474f" fill-rule="evenodd" d="M22.903,3.286c0.679-0.381,1.515-0.381,2.193,0 c3.355,1.883,13.451,7.551,16.807,9.434C42.582,13.1,43,13.804,43,14.566c0,3.766,0,15.101,0,18.867 c0,0.762-0.418,1.466-1.097,1.847c-3.355,1.883-13.451,7.551-16.807,9.434c-0.679,0.381-1.515,0.381-2.193,0 c-3.355-1.883-13.451-7.551-16.807-9.434C5.418,34.899,5,34.196,5,33.434c0-3.766,0-15.101,0-18.867 c0-0.762,0.418-1.466,1.097-1.847C9.451,10.837,19.549,5.169,22.903,3.286z" clip-rule="evenodd"/><path fill="#546e7a" fill-rule="evenodd" d="M5.304,34.404C5.038,34.048,5,33.71,5,33.255 c0-3.744,0-15.014,0-18.759c0-0.758,0.417-1.458,1.094-1.836c3.343-1.872,13.405-7.507,16.748-9.38 c0.677-0.379,1.594-0.371,2.271,0.008c3.343,1.872,13.371,7.459,16.714,9.331c0.27,0.152,0.476,0.335,0.66,0.576L5.304,34.404z" clip-rule="evenodd"/><path fill="#fff" fill-rule="evenodd" d="M24,10c7.727,0,14,6.273,14,14s-6.273,14-14,14 s-14-6.273-14-14S16.273,10,24,10z M24,17c3.863,0,7,3.136,7,7c0,3.863-3.137,7-7,7s-7-3.137-7-7C17,20.136,20.136,17,24,17z" clip-rule="evenodd"/><path fill="#455a64" fill-rule="evenodd" d="M42.485,13.205c0.516,0.483,0.506,1.211,0.506,1.784 c0,3.795-0.032,14.589,0.009,18.384c0.004,0.396-0.127,0.813-0.323,1.127L23.593,24L42.485,13.205z" clip-rule="evenodd"/><path fill="#fff" fill-rule="evenodd" d="M34 20H35V28H34zM37 20H38V28H37z" clip-rule="evenodd"/><path fill="#fff" fill-rule="evenodd" d="M32 25H40V26H32zM32 22H40V23H32z" clip-rule="evenodd"/></svg>

Hey,
Wikipedia doesn't think this is C# logo.
Do you have any references pointing out the "official" use for this one?

I referred to this https://github.com/exercism/meta/issues/27#issuecomment-320491569, thought we can have it as we have similar logos for C and C++. No concrete references citing the official use of this one.

Any plans on adding this logo or should I close the issue?

Added in a339cabb020a1fc0d9f9df7cf55dd7d5802a55d9
Thanks


Form and export script field updates

These are a collection of fields to update in the webapp and the export script:

[x] Add all the options in Access DB for the following fields:

Behaviour

Direction of travel

[ ] Make the following fields as decimal (max 5 decimal points): (this limit will be added to all other fields that allow decimal numbers in https://github.com/BMMRO-tech/BMMRO/issues/118) -- check each field in ms access

Water depth (max 7 decimal places in ms access)

Water Temp

Distance

Surface bout (it seems in ms access limit is 2 decimal place)

[ ] Add "Not Noted" as one of the options for all drop downs in both forms

[ ] If in the webapp, none of the options are selected from the dropdown, while exporting make them into "Not Noted".

[ ] Add :ss to all time fields but make it optional to add ss in the validation. If no ss are entered default them to 00.

[ ] When 6+ is selected as an option for Wave height, update the export script to convert 6+ to 99

[ ] Add Photographer Frame Number to the export script (if it doesn't break the import)

[x] Make the group composition box as big as 'Visual Identifications' box in encounter form (text area instead of text field) - changed to text area but did not change the max length (currently max length in group composition is 255 but visual id's has a limit of 200)

[ ] Create a new field called 'End Date' - validation is cannot be before start date and cannot be after 72hrs (3 days), default value is same as start date. This field is used for calculating Elapsed time when the the researchers stay overnight on the boat. Update elapsed time validation to reflect the 72hrs. Round the :ss to the nearest minute when calculating elapsed time. End date field does not need to be exported to csv.

[ ] Add high tide, low tide, entered by and needs to be checked to the export script. We currently save "needs to be checked" as a boolean, but in ms access this is a yes/no field. We need to confirm that true/false is correctly mapped to yes/no.

Questions:

bottom substrate dropdown is not ordered alphabetically, should it be? Added 'not noted' at the bottom of the list
tide stade dropdown is not ordered alphabetically, should it be? Added 'not noted' at the bottom of the list
does it make sense to add "not noted" to the project dropdown?


Update salt to 2016.3.3

Motivation for this change
2016.3.3 is the latest version.
Salt no longer depends on SaltTesting, but I updated that as well for good measure.
Things done

[ ] Tested using sandboxing
(nix.useSandbox on NixOS,
or option build-use-sandbox in nix.conf
on non-NixOS)
Built on platform(s)

[ ] NixOS
[ ] OS X
[x] Linux

[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

So I just saw that these are referenced via python-packages.nix. That's wrong. python-packages.nix should only contain packages that are primarily used as libraries. If these two are applications, then the callPackage should be in all-packages.nix.

Salt is an application and I will make a PR to move it to all-packages.nix, I did not know about the distinction. SaltTesting is a Python library that Salt used to depend on, so I believe it is safe to leave in python-packages.nix.

yes, that one can stay but it will need to use buildPythonPackage instead of buildPythonApplication


[Feature][Connector-V2][HTTP] Use json-path parsing

close #3500

Purpose of this pull request

Check list

[ ] Code changed are covered with tests, or it does not need tests for reason:
[ ] If any new Jar binary package adding in your PR, please add License Notice according
New License Guide
[ ] If necessary, please update the documentation to describe the new feature. https://github.com/apache/incubator-seatunnel/tree/dev/docs
[ ] If you are contributing the connector code, please check that the following files are updated:

Update change log that in connector document. For more details you can refer to connector-v2
Update plugin-mapping.properties and add new connector information in it
Update the pom file of seatunnel-dist

@hailin0 @Hisoka-X PTAL

By the way, this is a good feature.

We have an issue discuss about this https://github.com/apache/incubator-seatunnel/issues/3573. Can we wait for the discussion to finish before processing this pr?

Please pending this pull request. Waiting for #3573 finished and decied this pull request is or not merged. cc @Hisoka-X @EricJoy2048 @liugddx

Please pending this pull request. Waiting for #3573 finished and decied this pull request is or not merged. cc @Hisoka-X @EricJoy2048 @liugddx

Hi, we have communicated about this issue. If you have other good suggestions, you can also put forward them. @Hisoka-X @EricJoy2048 @TaoZex

Please pending this pull request. Waiting for #3573 finished and decied this pull request is or not merged. cc @Hisoka-X @EricJoy2048 @liugddx

Hi, we have communicated about this issue. If you have other good suggestions, you can also put forward them. @Hisoka-X @EricJoy2048 @TaoZex

@TyrantLucifer


Video and audio mute showing.

Hi ,
I am using flutter app.I am connecting from mobile and desktop web browser.Having problem since few days,Video and audio mute showing .Actually the video and audio is on by the user.

Mobile video not displaying in browser but browser video showing in mobile.
please tell the solution

Will update the jitsi meet SDK version in the next release. This will probably fix the issue.

I close this issue for now. Please test if this issue still appears with the newest release.


Event Entities for changes

I just installed the latest version with the new notify settings.
This is a great idea - i used to parse json to detect room changes for example.
However, I would like to suggest to use the new event entities (introdoced in HA 2023.8), for a more versatile usage.
For example, I would like to show a conditional card on my dashboard instead of getting a notification.
Events could be used to trigger an automation, which could send a notification, but also to change the state of a helper entity etc.
Does the integration trigger events already, which could be used in an automation?

I worked on the notify feature for several months; as a result, the event entity wasn't available at this time.
I will put this on my to-do list.


Cannot create Subscription rule when DPI > 100%

This was not fixed. Windows 7 DPI scaling 125% or 135% does not show action buttons. But shows on 100%

Hi @baltuonis I don't have the possibility to install and test SBE on Window 7, sorry about that :(

I was able to reproduce this on Windows 7 at 125% and 135%. On Windows 7 125% is the default where as Windows 10 100% is the default.
I'll provide screenshots on Monday. I don't have access to my Windows 7 machine until I get to work.

Closing this as it has been verified on Windows 10.


Add support for component coap

https://github.com/apache/camel/blob/master/components/camel-coap/src/main/docs/coap-component.adoc

Found 0 matching posts for subject:coap in Camel - Users within 700 days


Mobile layout

In mobile layout it be good to use responsive like bloks.io site
Desktop view

Mobile view

merged!


Separate ollama instance for titles

Is your feature request related to a problem? Please describe.
Auto-generated titles cause serious performance problems. They trash KV cache in llama.cpp, so the whole prompt and the first response have to be processed again after followup question, which is slow on CPU. Titles also take time to generate, sometimes a lot of time if the model gets stuck in a loop. If separate model is used for titles, time is wasted loading it and then reloading the main model.
Describe the solution you'd like
Make it possible to configure second ollama instance dedicated to titles. Query this second instance concurrently, so that user can continue chatting.
Things get a bit messy with models, especially custom ones. A lazy way to do this is to offer only models available in the second ollama instance. A more complete solution is to add a new settings tab for title generation, which would allow model download and customization (prompt, max tokens).
Describe alternatives you've considered
Llama.cpp supports multiple concurrent sessions (or "slots"), which would fix the KV cache trashing, but ollama does not support it yet. Neither llama.cpp nor ollama have support for loading and running multiple models concurrently.

Duplicate #278


Remove unnecessary nonzero requirements in some fields of NoSQL config struct

What changed?
Remove unnecessary nonzero fields in NoSQL config struct

Why?

PluginName requirement will break existing users
Keyspace will not be generically applicable for all NoSQL DBs

How did you test it?
N/A

Potential risks
No

Release notes

Documentation Changes

Pull Request Test Coverage Report for Build 6b77ca95-68bd-4afe-960f-76fdfc638a86

0 of 0   changed or added relevant lines in 0 files are covered.
24 unchanged lines in 3 files lost coverage.
Overall coverage increased (+0.06%) to 60.204%

Files with Coverage Reduction
New Missed Lines
%

common/types/mapper/thrift/shared.go
2
70.54%

service/matching/taskListManager.go
2
74.72%

common/persistence/cassandra/cassandraPersistence.go
20
50.82%

Totals

Change from base Build 7b19fe40-f6f2-42c2-bf9d-c74beecead23:
0.06%

Covered Lines:
89971

Relevant Lines:
149444

💛  - Coveralls

was this actually necessary? with #4284 , the cassandra config is correctly ported into the new structure.
or more generally: is it a problem if someone doesn't define a plugin name? I'm not sure what that'd result in elsewhere.

was this actually necessary? with #4284 , the cassandra config is correctly ported into the new structure.
or more generally: is it a problem if someone doesn't define a plugin name? I'm not sure what that'd result in elsewhere.

I think the zero value error happens when creating the config struct using yaml library which happens before the logic in #4284.

Ah, yes, good point.  It'd still be necessary in that case.


tone categories

In the raw data (https://github.com/lexibank/hsiuhmongmien/blob/master/raw/HM_official.tsv), there are some tones with /1, /2...etc. Are these the labels for tone categories?

@LinguList, this has to do indeed with tone categories (also whether they are voiced or voiceless). is there a plan to do something with this (I'm asking in the context of the lexibank 2.0 release)? right now the cliff conversion does not include this.

@LinguList brief reminder so we can have this issue resolved for the lexibank 2.0 release.

@MuffinLinwist fixed now.


!include command not functionnal

Hi!
your package is working like a charm but I've encountered a problem :
after many attempts of any syntax available I have not been able to include a file in a markdown.
both files are in the same directory.
main.md that needs to display a  .puml inside
puml_file.puml
here is the syntax used :
main.md   (articially added space between the ` to trump markdown)
# random title 1
text
## subtitle
text
` ` `plantuml
@startuml

[[!include puml_file.puml]]

@enduml
` ` `

puml_file.puml contains a minimal working example that works fine when mput directly inside of main.md
@startuml
a->b
@enduml

I see a couple of things that may be causing your issue:

The include works using absolute paths. By using [[!include puml_file.puml]], the lib will fetch something like http://localhost:3000/puml_file (or whatever host where it may be running). So it will expect the file top be at the root path. If that's your issue, you may be facing a 404 when fetching puml_file.puml. Try replacing the include by an absolute path from your root to the puml_file.puml

After applying the include, your plantuml will result in something like this
 @startuml
 @startuml
 a->b
 @enduml
 @enduml

which also may be causing a compilation issue. Try to remove the @startuml and @enduml either from your include file or from the code markup.
Hope that this can help you!


Building docker image fails with "addgroup: gid '123' in use" error

Description
When using the command:
docker-compose build --build-arg uid=$(id -u) --build-arg gid=$(id -g)
it fails with:
addgroup: gid '123' in use
Underneath it invokes:
ARG ruby_version

FROM ruby:$ruby_version-alpine3.16 AS builder

ARG uid
ARG gid

RUN apk add --no-cache --update \
      build-base \
      curl \
      git \
      less \
      libcurl \
      linux-headers \
      postgresql-client \
      postgresql-dev \
      tzdata \
      wget \
      zsh \
      nodejs \
      yarn \
      gcompat \
      npm

RUN ( ( getent passwd $uid && deluser $(getent passwd $uid | cut -d: -f1)) || true) && \
    ( ( getent group $gid && delgroup $(getent group $gid | cut -d: -f1)) || true) && \
    addgroup -g $gid -S app && \
    adduser -u $uid -S -G app -h /home/app -D app

It is passing fine on ubuntu 20.04.
Platforms affected

[ ] Azure DevOps
[X] GitHub Actions - Standard Runners
[ ] GitHub Actions - Larger Runners

Runner images affected

[ ] Ubuntu 18.04
[ ] Ubuntu 20.04
[X] Ubuntu 22.04
[ ] macOS 10.15
[ ] macOS 11
[ ] macOS 12
[ ] Windows Server 2019
[ ] Windows Server 2022

Image version and build link
Image: ubuntu-22.04
Version: 20221119.2
Is it regression?
ubuntu 20.04
Expected behavior
docker image builds without error
Actual behavior
Fails:
delgroup: 'ntp' still has 'ntp' as their primary group!
addgroup: gid '123' in use
The command '/bin/sh -c ( ( getent passwd $uid && deluser $(getent passwd $uid | cut -d: -f1)) || true) &&     ( ( getent group $gid && delgroup $(getent group $gid | cut -d: -f1)) || true) &&     addgroup -g $gid -S app &&     adduser -u $uid -S -G app -h /home/app -D app' returned a non-zero code: 1

Repro steps
provided in description

Hi @morgoth , thanks, we will investigate.

Can you provide minimal repro steps?

@igorboskovic3 It will be rather hard for me to create minimal script, as there are a lot of layers -> alpine, docker, docker-compose, etc.

Hello @morgoth!
We do not really control what happens in docker containers, and your error is caused by the Dockerfile itself, not the runner image it is running on.

@mikhailkoliada But you can control the default group (and by so the gid) of default user on your runs-on: ubuntu-latest setup and why did you use gid=123 for default group for default user instead of 1000. Such config is very probable to be conflicting.

Agree with @sebastianpiskorski.
I discovered this change because of a pipeline unexpectedly failed on one of my projects.
It's quite common to wanting to create a user within an image matching the host - meaning that lots of dockerfile setups will not work when using ubuntu-latest because the NTP user already exists on some images with uid 123 (namely alpine)
Is there any plans to reconsider this change?

My workaround (ubuntu/alpine) - does not delete existing users/groups within container, but rather reuses them:

# ...

ARG MY_USER='foo'
ARG MY_GROUP='foo'
ARG MY_UID=6789
ARG MY_GID=6789
ARG MY_HOME=/home/${MY_USER}

ENV MY_USER=$MY_USER \
    MY_GROUP=$MY_GROUP \
    MY_UID=$MY_UID \
    MY_GID=$MY_GID \
    MY_HOME=$MY_HOME \

RUN getent group "$MY_GID" > /dev/null && export MY_GROUP=$(getent group "$MY_GID" | cut -d: -f1); \
    getent passwd "$MY_UID" > /dev/null && export MY_USER=$(getent passwd "$MY_UID" | cut -d: -f1 ); \
    if [ -f /etc/alpine-release ]; then \
      ( getent group "$MY_GID" > /dev/null || addgroup -g "$MY_GID" "$MY_GROUP" ) && \
      ( getent passwd "$MY_UID" > /dev/null || adduser -h "$MY_HOME" -G "$MY_GROUP" -u "$MY_UID" -D "$MY_USER" ); \
    else \
      ( getent group "$MY_GID" > /dev/null || groupadd -g $MY_GID $MY_GROUP ) && \
      ( getent passwd "$MY_UID" > /dev/null || useradd -m -d $MY_HOME -g $MY_GID --uid $MY_UID $MY_USER ); \
    fi;

# ...


Cannot read property 'reuseTiles' of undefined

Hi Team, I am testing leaflet in Salesforce Lightning Components and getting this issue: Cannot read property 'reuseTiles' of undefined when trying to relocate the MAP using "panTo" function.
I am debugin and the parameters are well and with values ( map.panTo([account.Location__Latitude__s, account.Location__Longitude__s]) but  I am not able to find the issue. Any of you have been facing this issue before in any situation ?  Best Regards,

Sorry, but this bugtracker is for the Leaflet core only. If your problem cannot be reproduced standalone, without using salesforce components, we won't be able to help.

@enriquediazmorales, sorry posting reply too late.. if your issue is not yet addressed, i recommend you to install Leaflet latest version and run your code again. this will fix this issue.


How to use PaginatableList with Google Places?

Google Places is using a different type of pagination mechanism. Instead of using page size, and page number directly, it gives a response that includes the data array and a next page token.  The next page token needs to be appended as an extra param in the next query. How does PaginatableList handle this case?

Please check this tutorial. https://medium.com/ttt-studios/how-to-use-react-native-paginationlist-f9f32f4109f3


The keys are out of order when destroy volume.

What happened:
juicefs version is 1.0.0-beta2
ref:  https://github.com/juicedata/juicefs/runs/6331647124?check_suite_focus=true
2022/05/07 02:44:53.111556 juicefs[12502] <INFO>: Meta address: redis://<IP_ADDRESS>/1 [interface.go:383]
2022/05/07 02:44:53.112957 juicefs[12502] <WARNING>: AOF is not enabled, you may lose data if Redis is not shutdown properly. [info.go:84]
2022/05/07 02:44:53.113194 juicefs[12502] <INFO>: Ping redis: 159.512µs [redis.go:2497]
UUID is 5d943c4e-9665-453e-94a2-61dc9a429111
2022/05/07 02:44:53.169229 juicefs[12511] <INFO>: Meta address: redis://<IP_ADDRESS>/1 [interface.go:383]
2022/05/07 02:44:53.170631 juicefs[12511] <WARNING>: AOF is not enabled, you may lose data if Redis is not shutdown properly. [info.go:84]
2022/05/07 02:44:53.170896 juicefs[12511] <INFO>: Ping redis: 132.01µs [redis.go:2497]
2022/05/07 02:44:53.175824 juicefs[12511] <FATAL>: The keys are out of order: marker "chunks/0/0/2_0_10240", last "chunks/0/0/2_0_10240" current "chunks/" [sync.go:128]

What you expected to happen:
should not crash when destroy.
How to reproduce it (as minimally and precisely as possible):
Anything else we need to know?
Environment:

JuiceFS version (use juicefs --version) or Hadoop Java SDK version:
Cloud provider or hardware configuration running JuiceFS:
OS (e.g cat /etc/os-release):
Kernel (e.g. uname -a):
Object storage (cloud provider and region, or self maintained):
Metadata engine info (version, cloud provider managed or self maintained):
Network connectivity (JuiceFS to metadata engine, JuiceFS to object storage):
Others:

It is most likely a bug of minio and cannot be reproduced.

I am getting the same error
$ juicefs destroy sqlite3:///home/kisiel/data/juicefs/sqlite3/001.db 9a69ec6a-9788-4da9-bf80-2a22b32c7714
2022/11/26 22:17:45.724895 juicefs[792266] <INFO>: Meta address: sqlite3:///home/kisiel/data/juicefs/sqlite3/001.db [interface.go:402]
 volume name: 001
 volume UUID: 9a69ec6a-9788-4da9-bf80-2a22b32c7714
data storage: s3://data/001/
  used bytes: 0
 used inodes: 0
WARNING: The target volume will be permanently destroyed, including:
WARNING: 1. ALL objects in the data storage: s3://data/001/
WARNING: 2. ALL entries in the metadata engine: sqlite3:///home/kisiel/data/juicefs/sqlite3/001.db
Proceed anyway? [y/N]: y
2022/11/26 22:17:49.066357 juicefs[792266] <ERROR>: The keys are out of order: marker "", last "meta/dump-2022-11-26-213402.json.gz" current "meta/dump-2022-11-26-183248.json.gz" [sync.go:132]
Deleted objects count: 4

juicefs version 1.0.2+2022-10-13.514ef03


docs: fix bundle

Current dependencies on/for this PR:

main

PR #2523   👈

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