Too much lock contention?

Trying to investigate this at the JuliaCon hackathon. Opening for discussion.
$ julia -t4

julia> function foo(url, n; downloader=()->Downloads.Downloader(;grace=0))
       Threads.@threads for _ in 1:n
           Downloads.download(url; downloader=downloader())
       end
       end
foo (generic function with 3 methods)

julia> @time foo("https://julialang-s3.julialang.org/bin/mac/aarch64/1.10/julia-1.10.4-macaarch64.dmg", 4, downloader=Returns(nothing))
 28.483014 seconds (916.99 k allocations: 659.244 MiB, 0.70% gc time, 22905 lock conflicts, 1.15% compilation time)

julia> @time foo("https://julialang-s3.julialang.org/bin/mac/aarch64/1.10/julia-1.10.4-macaarch64.dmg", 4)
 26.974909 seconds (1.23 M allocations: 675.870 MiB, 0.82% gc time, 1801 lock conflicts, 1.32% compilation time)

Note 1801 lock conflicts even on the task local Downloader version

I've been trying to get verbose LibCURL output but failing.
https://github.com/JuliaLang/Downloads.jl/compare/master...ib/speed_investigation
Based on https://github.com/invenia/FTPClient.jl/blob/f1d3d975b4ac8b302a90548ccdd6912ed204437f/src/conn_context.jl#L274C1-L314C4

Can you figure out which locks have contention?

I suspect it's not the download start lock but probably the IO locks.

This is the most common lock from @profile
https://github.com/JuliaLang/Downloads.jl/blob/971840a9da72ba3743b837e1217c697db7bab298/src/Curl/Multi.jl#L197-L201
I've also moved to hosting a file locally on a http server and downloading from tha, to test theoretical limit because the conference and hotel wifi isn't great, and with that I see a lot fewer locks.
one download per thread
julia> @time foo("http://localhost:8000/julia-1.10.4-macaarch64.dmg", 6, downloader=Returns(nothing))
  0.958359 seconds (493.32 k allocations: 945.356 MiB, 7.87% gc time, 2380 lock conflicts)

julia> @time foo("http://localhost:8000/julia-1.10.4-macaarch64.dmg", 6)
  0.949370 seconds (460.36 k allocations: 790.393 MiB, 11.77% gc time, 31 lock conflicts)

many downloads per thread
julia> @time foo("http://localhost:8000/julia-1.10.4-macaarch64.dmg", 60, downloader=Returns(nothing))
 21.439162 seconds (4.94 M allocations: 9.233 GiB, 4.32% gc time, 24624 lock conflicts)

julia> @time foo("http://localhost:8000/julia-1.10.4-macaarch64.dmg", 60)
 12.926270 seconds (5.43 M allocations: 9.108 GiB, 3.51% gc time, 567 lock conflicts)

I'm not sure whether a locally http server is a fair test of this.. but the speed is a lot faster.
And if I set https://curl.se/libcurl/c/CURLOPT_BUFFERSIZE.html
setopt(easy, CURLOPT_BUFFERSIZE, 10_000_000)

we get a good speed up
julia> @time foo("http://localhost:8000/julia-1.10.4-macaarch64.dmg", 6)
  0.568647 seconds (709.51 k allocations: 956.762 MiB, 30.29% gc time, 19 lock conflicts, 102.74% compilation time: <1% of which was recompilation)

julia> @time foo("http://localhost:8000/julia-1.10.4-macaarch64.dmg", 60)
  3.849536 seconds (4.77 M allocations: 9.075 GiB, 21.38% gc time, 14 lock conflicts, 0.53% compilation time)

Apparently the default buffersize is 16kB and the default max is 10MB

Take all the numbers here with a pinch of salt, I just tried default settings again and saw similar speeds to the latter results..
But the fastest above via Julia is about 500 MB/s.
Note that the buffersize is increased in this example https://github.com/curl/curl/blob/3765d75ce47b66289f946382b649d0e99389dc77/docs/examples/http2-download.c#L168-L169
and curl itself uses 100kB https://github.com/curl/curl/blob/3765d75ce47b66289f946382b649d0e99389dc77/src/tool_operate.c#L271
Some comparisons:
curl cli - 1 GB/s
% url=http://localhost:8000/julia-1.10.4-macaarch64.dmg
% curl -O -s -w "%{speed_download}" "$url" | awk '{printf "Download speed: %.2f GB/s\n", $1/1024/1024/1024}'
Download speed: 1.02 GB/s
...
Download speed: 1.17 GB/s
Download speed: 1.10 GB/s
Download speed: 1.04 GB/s

wget cli - 2.6 GB/s
And wget gives 2.6 GB/s
% wget --output-document=/dev/null http://localhost:8000/julia-1.10.4-macaarch64.dmg
--2024-07-13 23:33:14--  http://localhost:8000/julia-1.10.4-macaarch64.dmg
Resolving localhost (localhost)... ::1, <IP_ADDRESS>
Connecting to localhost (localhost)|::1|:8000... connected.
HTTP request sent, awaiting response... 200 OK
Length: 163644235 (156M) [application/x-apple-diskimage]
Saving to: '/dev/null'

/dev/null                                     100%[==============================================================================================>] 156.06M  --.-KB/s    in 0.06s

2024-07-13 23:33:15 (2.50 GB/s) - '/dev/null' saved [163644235/163644235]
...
2024-07-13 23:41:44 (2.72 GB/s) - ‘/dev/null’ saved [163644235/163644235]
2024-07-13 23:41:45 (2.67 GB/s) - ‘/dev/null’ saved [163644235/163644235]
2024-07-13 23:41:46 (2.82 GB/s) - ‘/dev/null’ saved [163644235/163644235]

Thanks to @giordano for pointing some of this out.

Using https://github.com/JuliaLang/julia/pull/55120 it turns out the lock with contention is https://github.com/JuliaLang/Downloads.jl/blob/d363a02bac50ddff422e14a5aa89464dc7fdad0b/src/Curl/Multi.jl#L144

I think a few things we might want to consider doing are:

By default setting setopt(easy, CURLOPT_BUFFERSIZE, 10_000_000) - increase from the default of 16 kB to 10 MB
Increase CONNECT_SEMAPHORE https://github.com/JuliaLang/Downloads.jl/blob/d363a02bac50ddff422e14a5aa89464dc7fdad0b/src/Curl/Easy.jl#L56
Document that when using concurrent tasks it's best to use a task-local Downloader

I'll benchmark the parameter space when on a strong internet connection.
I've spun up 4 local http servers on different ports from a ramdisk, and accessing them individually from each task, but I'm not sure it's a fair test.
This is 4 sequential downloads on each of 4 concurrent tasks, 10 times
julia> foo(4, 4, 10)
1532.902446759521 MB/s
2447.040027683379 MB/s
1884.3813202392432 MB/s
2017.8544918394593 MB/s
1973.309438735145 MB/s
1632.805491498009 MB/s
2153.163424235369 MB/s
1935.19328559164 MB/s
1728.2429605092427 MB/s
1970.3497493574216 MB/s

I think I'm reaching a conclusion here.

The current defaults for buffersize & CONNECT_SEMAPHORE are actually optimal already.

Based on local server testing no configuration of them notably beats the current defaults, and lower values are slower
Based on CI benchmarks (where Windows CI machines have the fastest network connection it seems) the current defaults actually perform best

Lock contention numbers are high but don't seem to slow things down. Could callbacks be orchestrated to avoid lock contention? A channel? Not sure but either way I'm not sure it's going to speed things up helpful
However using the global Downloader from different threads does seem to hit enough lock contention to slow things down. I'll add a note in the docs to highlight that.

I'll close.

I'd really like for the defaults to be fast and not require jumping through any hoops. We've put so much work into making this concurrent under the hood with a simple blocking API, seems lame to not make it actually fast. So I'd like to actually fix this and make the warning unnecessary.
I have a few paths I'd like to explore. There's an option for multithreaded libcurl usage—there might be a way to make that work and avoid needing a lock. Another option would be to create a Downloader object per thread. The only way to observe that is the easy hook stuff which is an unofficial and not great API anyway, so we could reasonably do that. The other approach would be something with channels or other ways to avoid locks.


Update EventListener.php

why?

why?

Avoid coloring the chat to attract more attention (especially useful for casual player ranks)


feat(loader): add yaml

Possibly ask https://github.com/brev/esm-loaders/tree/main/packages/esm-loader-yaml to add theirs?

hello @brev. Can you join us to discuss. Because we nearly furnish same API


Run permission related tests with sudo

This prevents us from running into any permission oddities

@clue @jsor ping

Ping @jsor @clue

This prevents us from running into any permission oddities

Not a big fan of this, but it it helps getting the tests green… ¯_(ツ)_/¯ IMO we should clean up this up once the outstanding issues have been fixed.


Add Open at Login toggle to preferences

Add an Open at Login or Start SpotMenu at Login toggleable item

Seconded!

Added open at login to preferences in version 1.4.2. Latest version can be downloaded here or you can download the source code and build it yourself! Thanks for the feedback.
Feel free to reopen this issue if somethings not working properly

Thanks much, using the new version.


Native Editor - No indicator on icons when action is in progress

Clicking Stop Kernel, Restart Kernel or Export doesn't change the icon to a busy icon nor disable it.
The assumption is I didin't click it correctly and end up clicking more than once..
This results in python file getting exported more than once (4 times for me)
I'd expect the button to be disabled or similar to prevent unnecessary double clicking or provide some UI feedback about something happening...

Minimum would be to disable the icon.


Throttle recovery speed

We're in a process of migration from older hardware under ClickHouse to the newer generation.
Older machines have 12x6T disks, 128GB RAM and 2x10G NICs, newer machines have 12x10T disks, 256GB RAM and 2x25G NICs. Dataset per replica is around 35TiB. Each shard is 3 replicas.
Our process is:

Stop one replica from shard.
Clear it from zookeeper.
Remove it from cluster topology (znode update for remote_servers).
Add new replica to cluster topology.
Start new replica and let it replicate all the data from peers.

The issue we're seeing is that source replicas saturate disks, starving user queries and merges.
It takes ~7h to replicate full dataset, below are the graphs for 12h around that time:

Source peer:

Target peer:

Naturally, source peers are not great at IO in the first place (that's why we're upgrading), but having 7h of degraded service is not great. It'd be nice to be able to set recovery speed, so it doesn't starve  other activities like user queries and merges.
Moreover, max number of parts in partition quickly reaches the max (we set to 1000) on the target replica, where inserts are throttled, which doesn't make things any better. With throttled recovery at lower speed but with higher duration, this will probably be even longer period. Maybe we should split threads that do merges and threads that do replication, it seems like whole pool is busy just replicating.
It is also possible that we're just doing it wrong, then it'd be great to have a guide describing the process.
cc @vavrusa, @dqminh, @bocharov

Limit on number of connections and throttling of recovery speed is actual task.

Related: https://github.com/yandex/ClickHouse/issues/520

+1, running into similar issues when adding/replacing nodes during our tests, any ETA on the fix?

Surprisingly, it affects our hypervisors during deploy of new nodes as well... Would like to see either speed or threads limitation


System.InvalidOperationException: Sequence contains no elements in MultipleClientsFromPathSegmentsOperationNameGenerator when path has no elements

For this Swagger definition:
{
  "paths": {
    "/{id}": {
      "get": {
        "responses": {
          "200": {
            "schema": { "$ref": "#/definitions/touchpoint" },
            "description": "Touch points list"
          },
          "404": { "description": "Touch point not found" }
        },
        "parameters": [
          {
            "in": "path",
            "name": "id",
            "type": "string",
            "required": true
          }
        ],
        "x-auth-type": "Application & Application User",
        "x-throttling-tier": "Unlimited"
      },
      "put": {
        "responses": { "200": { "description": "Created or updated" } },
        "parameters": [
          {
            "in": "path",
            "name": "id",
            "type": "string",
            "required": true
          },
          {
            "schema": { "$ref": "#/definitions/touchpoint" },
            "in": "body",
            "name": "touchpoint",
            "required": true
          }
        ],
        "x-auth-type": "Application & Application User",
        "x-throttling-tier": "Unlimited"
      }
    },
    "/*": {
      "post": {
        "responses": {
          "201": {
            "schema": { "$ref": "#/definitions/touchpoint" },
            "headers": { "Location": { "type": "string" } },
            "description": "Created"
          }
        },
        "parameters": [
          {
            "schema": { "$ref": "#/definitions/touchpoint" },
            "in": "body",
            "name": "touchpoint",
            "required": true
          }
        ],
        "x-auth-type": "Application & Application User",
        "x-throttling-tier": "Unlimited"
      },
      "get": {
        "responses": {
          "200": {
            "schema": {
              "type": "array",
              "items": { "$ref": "#/definitions/touchpoint" }
            },
            "description": "Touch points list"
          }
        },
        "parameters": [
          {
            "in": "query",
            "name": "type",
            "type": "string",
            "required": false
          }
        ],
        "x-auth-type": "Application & Application User",
        "x-throttling-tier": "Unlimited"
      }
    }
  },
  "schemes": [ "https", "http" ],
  "definitions": {
    "touchpoint": {
      "type": "object",
      "properties": {
        "Type": { "type": "string" },
        "Version": { "type": "string" },
        "Model": { "type": "string" },
        "Id": { "type": "string" }
      }
    }
  },
  "swagger": "2.0",
  "info": {
    "description": "Touch Point Management interface",
    "title": "Touch Point Management",
    "version": "1.0.0"
  }
}

I'm getting this error generating the client:
System.InvalidOperationException: Sequence contains no elements
   at System.Linq.Enumerable.First[TSource](IEnumerable`1 source)
   at NSwag.CodeGeneration.OperationNameGenerators.MultipleClientsFromPathSegmentsOperationNameGenerator.GetOperationName(SwaggerDocument document, String path, SwaggerOperationMethod httpMethod, SwaggerOperation operation)
   at NSwag.CodeGeneration.ClientGeneratorBase`3.<>c__DisplayClass12_1.<GetOperations>b__2(<>f__AnonymousType0`3 tuple)
   at System.Linq.Enumerable.WhereSelectEnumerableIterator`2.MoveNext()
   at System.Collections.Generic.List`1..ctor(IEnumerable`1 collection)
   at System.Linq.Enumerable.ToList[TSource](IEnumerable`1 source)
   at NSwag.CodeGeneration.ClientGeneratorBase`3.GetOperations(SwaggerDocument document)
   at NSwag.CodeGeneration.ClientGeneratorBase`3.GenerateFile(SwaggerDocument document, ClientGeneratorOutputType type)
   at NSwag.CodeGeneration.CSharp.SwaggerToCSharpClientGenerator.GenerateFile()
   at Microsoft.VisualStudio.TextTemplating14D6AA0DFDFE7695460927542EC03E29927A9CBB6405D591ED813AACD385AAF3299FE2112D9C621AA83287D3BA8D034559F996A6B5D23B57635ED2D7F8440861.GeneratedTextTransformation.TransformText()	VisionBox.TransactionManager.Services.Clients	C:\Projects\PRODUCTS\TransactionManager\src\VisionBox.Services.Clients\TouchPoint\TouchPointManagement.tt	1

Looks like the problem is the GetOperationName method:
public string GetOperationName(SwaggerDocument document, string path, SwaggerOperationMethod httpMethod, SwaggerOperation operation)
{
    var pathSegments = path.Split('/').Where(p => !p.Contains("{")).Reverse().ToArray();
    return pathSegments.First();
}

Changing to this works fine:
public string GetOperationName(SwaggerDocument document, string path, SwaggerOperationMethod httpMethod, SwaggerOperation operation)
{
    return path.Split('/').Where(p => !p.Contains("{")).Reverse().FirstOrDefault() ?? string.Empty;
}

I would also change GetClientName to:
public string GetClientName(SwaggerDocument document, string path, SwaggerOperationMethod httpMethod, SwaggerOperation operation)
{
    return path.Split('/').Where(p => !p.Contains("{")).Reverse().Skip(1).FirstOrDefault() ?? string.Empty;
}

If you're already paying the LINQ tax, there's no need to pay the array allocation tax.

Don't you have other problems when you just return an empty string?

Well, I get a bunch of methods with the same name, but, for now, I'm using string replacement to solve it.
A MultipleClientsFromPathSegmentsOperationNameGenerator that uses the method will solve them.
But it doesn't crash I can see where it went wrong.

Is this commit fine for you? Please try the change with the latest CI artifacts

It no longer throws.
But while the /{id} path generates IndexAsync method names and string.Format("{0}/{1}", BaseUrl, "{id}") URLs, the / path generates Async method names and string.Format("{0}/{1}", BaseUrl, "").
Was that what you're expecting?

I think in this scenario you shouldn't use this operation name generator. Generally it is only working when you have paths in the form "api/controller/action"


netlify tests fail due Ubuntu version

while doing PR for documentation update PR it was discovered that all tests for Netlify can't be run (and turn to fail state due outdated Ubuntu version).
10:12:45 AM: ---------------------------------------------------------------------
  UNSUPPORTED BUILD IMAGE

  The build image for this site uses Ubuntu 16.04 Xenial Xerus, which is no longer supported.

  To enable builds for this site, select a later build image at the following link:
  https://app.netlify.com/sites/getistio-demo/settings/deploys#build-image-selection

  For more details, visit the build migration guide:
  https://answers.netlify.com/t/please-read-end-of-support-for-xenial-build-image-everything-you-need-to-know/68239
  ---------------------------------------------------------------------

@deva26 / @pmerrison / @MB-Designs / @peterj / @Marc-Morata-Fite / @psbrar99 - I wouldn't mind looking into it but don't have access to Netfly - can one of you help me with getting access?
Thank you!

This is fixed. Should we rebuild?

all fixed - thank you!


Fix tooltips on high dpi displays

Feel free to close this if it's unwelcome :)
I was having some trouble figuring out what all the upgrades were doing, and found myself wishing there were tooltips. Later on while playing, I happened to hover one of the upgrades lower down on the screen, and found a tooltip way off at the top of the screen.
This should fix things up. I tested with a scale_factor of 1.0 as well.

Nah this is welcome, I didn't know this was the cause of the bug. I thought it was just an unexplainable difference between platforms. There's another bug with the scene view bounds because it also uses physical_rect -- I'll fix that in a separate commit.

Thanks!


issue/1888-remove-depracated-OptionVariable

Description
Currently nullable attributes are represented by OptionVariable. They will now be represented by a plain ResultVariable with a nullable type.
closes #1888
Self Check:
Strike through any lines that are not applicable (~~line~~) then check the box

[x] Attached issue to pull request
[x] Changelog entry
[x] Type annotations are present
[x] Code is clear and sufficiently documented
[x] No (preventable) type errors (check using make mypy or make mypy-diff)
[x] Sufficient test cases (reproduces the bug/tests the requested feature)
[x] Correct, in line with design
[ ] End user documentation is included or an issue is created for end-user documentation (add ref to issue here: )

Reviewer Checklist:

[ ] Sufficient test cases (reproduces the bug/tests the requested feature)
[ ] Code is clear and sufficiently documented
[ ] Correct, in line with design

Processing this pull request

Merged into branches master in dcd541dd1f3e0569b53a60b786615122a06eaef5

This branch was not deleted as it seems to still be in use.


IntoParams doesn't work if not in the same file as handler

I have the following handler:
#[utoipa::path(
    context_path = "/api/v1/private/workers/{worker_id}/pipe_transports",
    responses(
        (status = 200, description = "Pipe Transport created"),
    ),
    tag = "pipe_transports"
  )]
#[post("")]
#[tracing::instrument(skip(state))]
pub async fn create(
    req_path: Path<request::CreatePipeTransportRequestPath>,
    state: Data<crate::state::AppStateHandle>,
) -> Result<Json<response::CreatePipeTransportResponse>, AppError> {
    .......
}

with the following struct for the Path in a different file (request::CreatePipeTransportRequestPath)
#[derive(Debug, Deserialize, Serialize, IntoParams)]
pub struct CreatePipeTransportRequestPath {
    pub worker_id: WorkerId,
}

this result in the following error:

the trait bound handlers::workers::pipe_transports::request::CreatePipeTransportRequestPath: utoipa::ParameterIn is not satisfied
the trait utoipa::ParameterIn is not implemented for handlers::workers::pipe_transports::request::CreatePipeTransportRequestPath

but, if I put CreatePipeTransportRequestPath in the same file as my create handler, I don't have any error.

Hi, good finding. This should be fixed with next release and actually with this PR: https://github.com/juhaku/utoipa/pull/156. The ParameterIn trait will  be removed completely so it wont cause any unnecessary issues.

Indeed it works now! Thank you very much 😁

It actually still doesn't work. I do not get the error yes, but nothing is generated

if i put the struct in the same file then it is generated as expected

(I'm using another struct in this screenshot)

Right, now there is a another issue hindering this from functioning. Originally it was not not desingned to support such case where the type would be in another module. I will address this in next PR, but current workaround is to declare the type in same module as the handler is defined.


[Refactor] Use ambient capabilities for the virt-launcher binary

What this PR does / why we need it:
The virt-launcher binary needs the cap_net_bind_service capability to work. Currently, we are using xattr as a part of the bazel build toolchain to add this capability (https://github.com/rmohr/bazeldnf/blob/main/pkg/xattr/xattr.go) to the binary executable file as a file capability. Ambient capabilities are a better solution for this use case. #8967 suggests we use ambient capabilities rather than file capabilities (using xattr). Here we can see the cap_net_bind_service capability added to the virt-launcher binary using xattr.
Ideal solution would be to ask Kubernetes to start virt-launcher-monitor with cap_net_bind_service as an ambient capability, that would then be inherited by virt-launcher without having to setcap any binary file. But Kubernetes doesn't support that just yet (see KEP-2763).
This PR does the next best thing, which is to have virt-launcher-monitor start virt-launcher with the appropriate ambient capabilities so we don't have to setcap the virt-launcher binary file.
This PR uses the kernel.org/pub/linux/libs/security/libcap/cap package for managing capabilities. This package provides the Libcap API bindings for Linux capabilities in go.
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #8967
Special notes for your reviewer:
In order for this to work, cap_setpcap capability has to be added to the virt-launcher-monitor binary. To do that, we need to modify the xattr rule of bazeldnf to add support for cap_setpcap as well.
Release note:

NONE

/ok-to-test

Closing this in favour of #9599

Thanks @xpivarc. I somehow missed it.


Include a minimal example

Hi Alex,
Thanks for putting this up.
I'm a bit out of my depth with this tech. I'm trying to get the same DFRobot capacitive touch screen working and came across similar issues to what a lot of people seem to be encountering - the INT pin not working.
I'm trying to get a minimal polling solution going with platformio, teensy 4.1. Essentially just what you have in the readme.
I get a few errors:
lib/GT911/GT911.cpp:93:19: error: '_min' was not declared in this scope; did you mean 'min'?

and
lib/GT911/GT911.cpp:93:38: error: 'I2C_BUFFER_LENGTH' was not declared in this scope; did you mean 'BUFFER_LENGTH'?

I tried changing to min and added #define I2C_BUFFER_LENGTH 32 but get no printing in the serial monitor.
Would you be able to include a minimal example in the repo?
Thanks.

Those changes you've made should work.
I've not compiled against a Teensy, will try and add in some defines.
If you try adding Serial.println("test"); in setup() after Serial.begin(); does that output?
If you can get that to output you could also try Serial.println(ts.begin()); to see if that prints 1

Yeah so the method doesn't exist (0). Makes me wonder if its referencing the class in the DFRobot_GT911.h file even though it links to your implementation.

Did it print test in the serial monitor?
The DFRobot class shouldn't cause an issue.
Are you able to show your wiring?
Checking Teensy's site it says pins 18 & 19 are the default I2C pins on the 4.1

Thank you! That led me to scrutinising the SDA and SCL, I tried swapping the cables and now I'm getting coordinates 🥲🔫
Thanks a bunch for your patience and help!


Merging branch to Releases/2.x for: static alias resolution didn't work when several aliases started with the same text (#98)

Fixes #98


Could we access IHttpContextAccessor in a custom target via DI?

Sometimes we may want to access IHttpContextAccessor.HttpContext.Request in a custom target, is there any way to do this?
I had tried the following way, but I got this error message Failed to create target type: kafka
    [Target("Kafka")]
    public class KafkaTarget : TargetWithLayout
    {
        private readonly IHttpContextAccessor _httpContextAccessor;

        public KafkaTarget(IHttpContextAccessor httpContextAccessor)
        {
            _httpContextAccessor = httpContextAccessor;
        }

        [RequiredParameter]
        public Layout Topic { get; set; }

        protected override void Write(LogEventInfo logEvent)
        {
            var mykey = string.Empty;

            if (_httpContextAccessor.HttpContext.Request.Headers.TryGetValue("mykey", out var val))
            {
                mykey = val.ToString();
            }

            string topic = this.Topic.Render(logEvent);
            string logMessage = this.Layout.Render(logEvent);

            var json = JsonConvert.SerializeObject(new
            {
                dateTime = DateTime.Now.ToString("yyyy-MM-dd HH:mm:ss.fff"),
                level = logEvent.Level.Name,
                message = logMessage,
                special = mykey
            });

            try
            {
                var config = new ProducerConfig
                {
                    BootstrapServers = "locahost:9092"
                };

                using (var producer = new ProducerBuilder<Null, string>(config).Build())
                {
                    var result = producer.ProduceAsync(topic, new Message<Null, string>()
                    {
                        Value = json
                    }).GetAwaiter().GetResult();
                }
            }
            catch (Exception ex)
            {
                InternalLogger.Error(ex, $"kafka published error.");
            }

            base.Write(logEvent);
        }
    }

    <target xsi:type="kafka"
            name="kafka"
            topic="test"
            layout="${message}"
            />

You should really try to avoid accessing thread-context-specific-variables in NLog-targets.
You should instead depend on Layout and LayoutRenderers. Instead you should make a pull-request for this:
https://github.com/NLog/NLog.Web/issues/355 (Create layoutrenderer that inherits from AspNetLayoutMultiValueRendererBase)
And then you could just use ${aspnet-request-headers}.

Thanks for the suggestion!  😄

@catcherwong I guess you can already make use of ${aspnet-request:header=mykey}
So something like this:
    <target xsi:type="kafka"
            name="kafka"
            topic="test"
            layout="${message}"
            specialKey="${aspnet-request:header=mykey}"
            />

And then just do this in KafkaTarget:
string mykey = this.SpecialKey.Render(logEvent);

@snakefoot  Thank you vary much,
I have done this job with a inelegant way. I record them via ${aspnet-request:item=xxx} in layout.
    <target xsi:type ="kafka"
        name="kafka"
        topic="test"
        bootstrapServers = "localhost:9092"
        layout="${aspnet-request:item=traceId}~${aspnet-request:item=requestIp}~${message}"
        />

Maybe separate the special key from layout is more better than I did. I will have a try later.
Thanks again! 😄


instance backup export lifecycle event

Add instance backup export lifecycle event

@masnax needs a tiny fix

Testsuite passed


Cursor disppears hovering over link or buttons on firefox

Using YoloMouse in combination with firefox, cursor always disappears hovering over link, buttons, anything clickable on webpage and we know most pages are filled with these.
I have tried chromium based browser (Brave and Vivaldi) and that seem to work fine.
I'm attaching a small video to show how it looks like.
Possible to filter out programs which YoloMouse could interfere with?
cursor-yolomouse.zip

Try clearing that area with CTRL ALT 0. Note that currently YM isn't really
tested/meant for apps just games.. however since so many folks like it with
regular apps I'm working on a more universal update :)
On Sat, Mar 28, 2020 at 12:30 AM Christoffer Jansson <
<EMAIL_ADDRESS>wrote:

Using YoloMouse in combination with firefox, cursor always disappears
hovering over link, buttons, anything clickable on webpage and we know most
pages are filled with these.
I have tried chromium based browser (Brave and Vivaldi) and that seem to
work fine.
I'm attaching a small video to show how it looks like.
Possible to filter out programs which YoloMouse could interfere with?
cursor-yolomouse.zip
https://github.com/PandaTeemo/YoloMouse/files/4396771/cursor-yolomouse.zip
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
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.


Something wrong when Javascript Games switching to python

Describe the bug
Something wrong when Javascript Games switching to python
Steps to reproduce the behavior
1.Navigate to https://arcade.makecode.com/beta#
2.Javascript Games
3.Click every example
4.Switch to python editor
Expect behavior
The switch is successful and can run normally
Actual behavior
Something wrong when Javascript Games switching to python. There are 3 situations.
1.Switching to python editor failed.(Planet Putt Putt, Darker Duck, Caterpillar, Cube Land, Particle Effects Demo)

2.The switch is successful but simulator is empty. And after switching to JS back, the code missed.(Five Second Games)

3.The switch is successful but code error in python editor.(Ping, Guess the letter, Bouncer Bucket)

Additional context
1.OS: Windows(rs6)
2.arcade version: 0.18.8
3.Microsoft MakeCode version: 6.1.24

No plan to fix this in the near future


OpenVR failed initialization with error code VRInitError_Init_HmdNotFoundPresenceFailed: "Hmd Not Found Presence Failed (126)"?

so basically i have a quest 3, got subnautica on the pc then got the mod, problem, this is the only error it has and it stops me from playing the game, any clue on how to fix it and what it means? cause the game works fine its only the mod thats just not working

How do you play?
If you play with airlink or questlink please read the install guide and add -vrmode openvr to your launch controls and launch the game from within steamvr.


Remove useless into_iter() on Range

Summary
Clippy has started complaining about this on the stable branch, and it's probably correct to do so.

Details and comments

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
8 unchanged lines in 1 file lost coverage.
Overall coverage increased (+0.002%) to 85.378%

Files with Coverage Reduction
New Missed Lines
%

crates/accelerate/src/vf2_layout.rs
8
86.44%

Totals

Change from base Build<PHONE_NUMBER>:
0.002%

Covered Lines:
68110

Relevant Lines:
79775

💛  - Coveralls


Updating reference to 'config.h' to have a proper public header path

👍 Is there a CI system in plans so these breaks can be caught before merging?

We have a gated check-in for our internal VSO builds, but we're having trouble making the packageES VSO build system do a gated build for our GitHub projects.  Haven't dug into cause yet.


Replace fails in file with mixed line endings

Hi,
when I have a file, that generally has LF line endings, but for some reason, there
are also some CRLF line endings, then htmlreplace does not replace anything in the file.

Ugh line endings again... Could you please provide this odd file so i can fix it once and for all?

Sure,
how should I do that? It seems, i cannot attach it here.

Would splitting lines based on \n only (completely ignore \r) be the right approach here? If you do that the \r, if it's present, would just be part of the line. And you can handle any mixture of \n or \r\n lines. I don't think there is any need to actually test for \r\n.

@ghost23 Maybe Dropbox, Google Drive worked pretty well in this comment too: https://github.com/VFK/gulp-html-replace/issues/19#issuecomment-69750870 Any file sharing thing basically. Thank you.
@bmacnaughton It might work, but there may be some weird problems in rare cases. I better look at that file and run some tests before i do anything about it.

That makes sense  :)
https://www.dropbox.com/s/s5sej5grjr1fccv/line_endings-html.html?dl=0

I think it works OK but you do have to make a decision on line 26 about what linefeed sequence to insert.
It wouldn't handle OLD Mac files with a \r line separator, but I don't think that really matters any longer.

@bmacnaughton  I'm using split by \n, this seems to be working ok, thanks for the idea. I think i better modify the code to not do "split" at all, but this is something for the future releases.
@ghost23, @charlescaron i've added your files to the "test" folder. I couldn't ask for a permission, there is no such thing as private messages on github, but if you're not ok with this (maybe those files are from some super-secret project or something) then please open an issue and i'll remove them.

Thanks for the note. I think you're right - no split at all would be better but that's a bigger change. The history of line endings still makes life complicated.


Make concurrency check handle re-entrance

Fixes #7375

@anpete, @ajcvickers Fixed async

Superseded by #17089


Migration to Bootstrap 5

Thanks again for your job with this Select2 Bootstrap 4 theme.
Are you planning to do it again for Bootstrap 5? Currently in beta, BS 5 final release should be available soon.

Yes. I'll create another version once Bootstrap 5 is out. This time I'll wait for the final version first.
They did quite a few changes between the Bootstrap 4 betas and the final release.

That's great news, thanks!

Are you still planning to work on a version for Bootstrap 5?

Yes. I plan on doing that in 1 or 2 months when I start my first Bootstrap 5 project.
I'm sorry if you need that urgently.

Sorry to bother you again, but it's just to know if you finally got the opportunity to work on a Bootstrap 5 theme?
This is free open source world, you owe nothing to anyone. :) I'm just asking to know if it can happen one day.
Your work for Bootstrap 4 was awesome, thanks again for that!

Hey, I did some work with Bootstrap 6, I plan on releasing the theme for BS 5, but this will probably happen end of this month or next month. I started updating the styles but there's still more work to do.

The BS5 version will be another repo, I'll name it select2-theme-bootstrap5. There are probably people using wildcard for importing this BS4 theme, I don't want to break their project.
I'll ping you here when I'm ready and have the first version published in npm

@florianlacreuse you can find the current progress here - https://github.com/angel-vladov/select2-theme-bootstrap5
Keep in mind that is still work in progress, and it's not properly tested yet. I haven't updated the README file as well.

You can find the select2 bs5 theme here
Git - https://github.com/angel-vladov/select2-theme-bootstrap5
NPM - https://www.npmjs.com/package/select2-theme-bootstrap5
This is a pre-release version. Please let me know if you find any bugs.

Thank you, that was quick! I'll look into it as soon as possible. I'll create issues or PR if needed.


I just get a new page with only one line: "This is the shortest HTML 5 code".

If you have a problem launching a live-server, please try following steps:

Make sure you use the right hotkeys. After v2.0.0, the keys became ctrl-alt combination.
Try launching live-server from top menu: Package -> live-server -> Start Server to see if it works.


Run server on ephemeral port

Is there a way to run a server on an ephemeral port, with e.g.:
socket = await asyncudp.create_socket(local_addr=('<IP_ADDRESS>', 0))

I haven't seen a way to fetch the port in that case. Would you be open to a PR that would add that? Would you have some advice before I start looking into it? :blush:

socket = await asyncudp.create_socket(local_addr=('<IP_ADDRESS>', 0))
print(socket.getsockname())

Nice catch. I'llupdate


IE11 not honoring responseType: 'json'

I am trying to execute a simple xhr.get call and use the json object in response.body. This works fine in Chrome and Firefox, but in IE11; it does not convert the response.body into an object, but leaves it as a String. Here it only converts the response.body if isJson is set in the options ahead of time. I have no need for that property besides to hack it to work for IE11. Shouldn't isJson be set to true if the responseType is 'json' or the json property exists?
Returns a string in response.body in IE11
xhr.get({
  url: myUrl?parameters,
  responseType: 'json'
}, callback);

My hack to convert response.body to an Object in IE11
xhr.get({
  url: myUrl?parameters,
  responseType: 'json',
  json: true
}, callback);

It looks like Microsoft is aware of it, but no fix coming for IE11.

Related to #114

It has seemed pretty odd to me that you have to specify json: true even when the server is putting Content-Type:application/json headers on the response.

Without the json: true property, when my requests hit getBody(), xhr.responseType is an empty string in IE11. Even with Content-Type:application/json on the response header.

Now consider other browsers that xhr supports like IE8 or IE9.
that's why json field remains the only option. Also, detecting response type and auto-parsing without explicit request would break backward compatibility and forever forbid you from getting a json response as text with intention to parse later or not at all.
I don't think we could introduce a change to fix this issue. Planning to close as wontfix.

Does request/request really ignore the Content-Type header on responses from the server?  I assumed this was a bug.

Personally, an XHR client ignoring the Content-Type header on the response seems like a bug to me, but if request/request doesn't do it and it's "desired functionality" then I don't imagine it's worth breaking backwards compatibility.  Just a bit more impetus to improve the docs.

I confirm the library is ignoring the Content-Type. This issue is breaking the [Keystone.js[(https://github.com/keystonejs/keystone) CMS.

This is a bug in IE11 and the correct response would be to fix it there.
https://github.com/request/request is not sniffing content-types and the aim of xhr is to mimic their API.
All I could do without breaking compatibility with request is setting isJson to true internally if responseType==='json'
It could be a breaking change for existing users, so I can add that to v3
I'm open to opinions about that.

I think the whole point of a library is to abstract and avoid people dealing with browsers issues. A great example is what jQuery does and how it provides the same experience regardless of the browsers and their issues. So, while I appreciate that this is a IE bug, the library should avoid devs to even know about it.

This library has more goals than abstracting away browser issues.
As I said, I have an idea how to introduce a fix for IE11 in v3 without sacrificing other goals - keeping semantic versioning and remaining API compatible with https://github.com/request/request
If you can help me find a way to fix it without breaking any possible applications that use xhr, I'm all ears. We could release the fix very soon, without changing major version.
Also feel free to PR a test that covers this exact case. It always helps with looking for fixes.

on IE don't use xhr.responseType = 'json'; and parse yourself the response var res = JSON.parse(xhr.responseText);
var xhr = new XMLHttpRequest();
    //xhr.responseType = 'json';
    var params = ...
    xhr.open("POST", "/xxx", true);
    xhr.setRequestHeader('Content-type', 'application/x-www-form-urlencoded');
    xhr.onreadystatechange = function() {//Call a function when the state changes.
      if(xhr.readyState == 4 && xhr.status == 200) {
        var res = JSON.parse(xhr.responseText);
      }
    }
    xhr.send(params);


Travis CI builds don't pass with master branch anymore

Curiously, the master branch (updated about two months ago) has had the builds all passed, while the exact same code now apparently cannot pass the builds. The test failures are due to two estimator checks (autoencoder and MLP classifier) not passed. The environments (packages, etc.) should be identical between two months and this week, but maybe there's something we've overlooked.
I came across this while investigating why the builds didn't pass at #101.

any updates on this? would really like to get that tensorflow security PR merged in.
https://github.com/civisanalytics/muffnn/pull/101
--timball

Hey @timball I'll take a look at this issue.

#103 fixed the build, but I think we should leave this open since I fixed it by skipping part of scikit-learn's check_estimator function (see the PR for details). It'd be nice to solve that in a cleaner way eventually.


create a file that handles table creation for you

I created a file tables.php that why you just go to the url it would create a table for you instead of thinking on the fields saves time and effort

ohh, I haven't considered that, tbh i almost gave up on this repo... but this seems interesting, I a going through exams now so i am not active rn... tho i'll merge this, ty :>

Hey, I am done with my exams and finally got to check out ur pull request... Though am facing trouble adapting to it, can u guide me with how am supposed to configure db or new files?


VS code workspace support

Using vscode workspaces would help us silo efforts, so you can work on either WP, Next, or both.
https://code.visualstudio.com/docs/editor/workspaces
It can also keep configurations for extensions, prettier, etc. siloed

Have played with this a bit more -- I think it can be valuable on a project with totally silo'd pieces with different configs (like a data project and a wordpress). But in our case, we're frequently working across folders, so hiding all but one is suboptimal. And prettier config can be shared.


fix(pendo): make injectors public

Issue
na
Description
fix(pendo): make injectors public
Additional context

Gravitee.io Automatic Deployment
A prerelease version of this package has been published! 🚀
To use it in your project run the following lines:
npm install<EMAIL_ADDRESS># or
yarn add<EMAIL_ADDRESS>

:tada: This PR is included in version 3.5.2 :tada:
The release is available on:

npm package (@latest dist-tag)
npm package (@latest dist-tag)
npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


defaulting analytics to on violates user consent

it's unethical of you to not disclose that your application is spyware without advance consent.

I'm going to remove that functionality. It actually hasn't been running for a while now anyway

There's still a setting for it in settings, and it assigned me an ID. Is it still disabled? How do I disable this?


Take a pass through the major command line tools and play monkey input on them

csv-importer
csv-exporter
noms *

Close?

I still think this would be good, at least for one person to do for a half day to generate bugs that'll make the tools feel more solid. If you prefer to close and just let people report bugs as they find them, that's ok too.

Zane, can you take this one? Basically: play qa engineer on all the noms * subcommands, as well as csv-import and csv-export. This will probably generate some easy bugs, which you can then take as well.

sure  thing i'll take a look!

I've gone through the tools and picked up some feature requests, filed/assigned myself the related bugs.  I think it would be safe to close this issue.


Roll Flutter Engine from 828e4dbf6693 to a18ee3c7f57a (7 revisions)

https://github.com/flutter/engine/compare/828e4dbf6693...a18ee3c7f57a
2023-11-12<EMAIL_ADDRESS>Reverts Dart SDK to 3.3.0-120.0.dev (flutter/engine#47959)
2023-11-12<EMAIL_ADDRESS>Roll Fuchsia Linux SDK from ikCrJNCuuApNeuH-6... to K3jvECt7y1_-zBVw3... (flutter/engine#47958)
2023-11-11<EMAIL_ADDRESS>Roll Dart SDK from 6415489ae51b to 1a1b9cbc838a (1 revision) (flutter/engine#47952)
2023-11-11<EMAIL_ADDRESS>Roll Fuchsia Linux SDK from 8sk2n2-NXJ-ceyc7T... to ikCrJNCuuApNeuH-6... (flutter/engine#47950)
2023-11-11<EMAIL_ADDRESS>Roll Dart SDK from a03a7b62eb4e to 6415489ae51b (1 revision) (flutter/engine#47949)
2023-11-11<EMAIL_ADDRESS>Roll Skia from 290962a9d913 to 1e9711980c61 (1 revision) (flutter/engine#47940)
2023-11-11<EMAIL_ADDRESS>Roll Dart SDK from 370145bbbd4f to a03a7b62eb4e (1 revision) (flutter/engine#47945)
Also rolling transitive DEPS:
fuchsia/sdk/core/linux-amd64 from 8sk2n2-NXJ-c to K3jvECt7y1_-
If this roll has caused a breakage, revert this CL and stop the roller
using the controls here:
https://autoroll.skia.org/r/flutter-engine-flutter-autoroll
Please CC bdero@google.com,rmistry<EMAIL_ADDRESS>on the revert to ensure that a human
is aware of the problem.
To file a bug in Flutter: https://github.com/flutter/flutter/issues/new/choose
To report a problem with the AutoRoller itself, please file a bug:
https://issues.skia.org/issues/new?component=1389291&template=1850622
Documentation for the AutoRoller is here:
https://skia.googlesource.com/buildbot/+doc/main/autoroll/README.md

Commit queue failed; closing this roll.


New Greek translation

I'm in the process of re-writing how the language files are implemented so at this time I won't merge this commit with the master repository; however I'll use the translated strings and credit you where necessary when the time comes.


pypi links don't resolve

on line 47.

@gvoysey it's fine now. it seems like the host was not available at that time


natal repl fails sometimes

It happens from time to time and it usually works after a couple tries.
➜  hello-project  rlwrap natal repl
Starting REPL

[1] HelloProject on iPhone (felipes-mbp-vexwifi-com-br)

Connecting to HelloProject on iPhone (felipes-mbp-vexwifi-com-br) ...

fs.js:892
  return binding.stat(pathModule._makeLong(path));
                 ^

Error: ENOENT: no such file or directory, stat '/Volumes/Ambly-81C53995/watch.log'
  at Error (native)
  at Object.fs.statSync (fs.js:892:18)
  at new Tail (/usr/local/lib/node_modules/natal/node_modules/tail/tail.js:67:16)
  at Socket.onLeinOut (/usr/local/lib/node_modules/natal/natal.coffee:440:20)
  at emitOne (events.js:82:20)
  at Socket.emit (events.js:169:7)
  at readableAddChunk (_stream_readable.js:146:16)
  at Socket.Readable.push (_stream_readable.js:110:10)
  at Pipe.onread (net.js:523:20)

➜  hello-project  rlwrap natal repl
Starting REPL

[1] HelloProject on iPhone (felipes-mbp-vexwifi-com-br)

Connecting to HelloProject on iPhone (felipes-mbp-vexwifi-com-br) ...

Watch compilation log available at: /Volumes/Ambly-81C53995/watch.log
Building ...
To quit, type: :cljs/quit
cljs.user=> ... done. Elapsed 0.442214224 seconds
cljs.user=>
Watching paths: /Users/felipe/devel/playground/natal/hello-project/src
cljs.user=>

Oh, sorry. It's duplicated #36

Have you seen this happen with 0.1.12?

No, I upgraded to 0.1.12 after I saw the other issue and it's working fine now. :)


Incorrect dependency reporting for iPython in 3.0.0b1

I've got iPython 3.0.0 installed, and it says that 3.0 is the minimum required, but it's flagged as a problem in the screengrab..

This is a duplicate of issue #2612.
@goanpeca you introduced this bug when you changed the way we detect package versions in utils/programs.py to check for Spyder updates.


Fix /ping endpoint Content-type

Broken since v1.4.0
Prefer this over converting to JSON by adding double quotes since it is more
backward compatible.
Fixes MARATHON-7322

Should be cherry picked to the 1.4 branch

Thanks @pierrecdn!
    .  o ..
     o . o o.o
          ...oo
            __[]__          Shippin'
         __|_o_o_o\__         it!
         \""""""""""/
          \. ..  . /
     ^^^^^^^^^^^^^^^^^^^^


[Blog] [Japanese] Localized three blogs into Japanese

Hi,
Please merge these localized three blog posts.
Also, I added the "hasCJKLanguage property" to the config.toml because of the summary page (https://jp.gethue.com/posts/) is not displayed well.
https://gohugo.io/getting-started/configuration/
Best Regards,
Tatsuo

Indeed, thanks as usual!
It is live now: https://jp.gethue.com//posts/


Adding hello world contract

This PR is adding the bases of a hello world contract for learning purposes. Solves #19.

When I run snforge test it throws this:
error[E0002]: Method `write` could not be called on type `core::starknet::storage::storage_base::StorageBase::<core::byte_array::ByteArray>`.
Candidate `StoragePointerWriteAccess::write` inference failed with: Trait has no implementation in context: core::starknet::storage::StoragePointerWriteAccess::<core::starknet::storage::storage_base::StorageBase::<core::byte_array::ByteArray>>.
 --> /root/stark-cairo-nodes/cairo/scripts/hello_world/src/hello_world.cairo:18:30
            self.stored_data.write("Hello world!")

The test is failing. And I dont know why.

Try using felt252 to handle the string instead of a ByteArray

Still throwing the same error. Weird asf.

Hmm ok I'll get your branch into my machine and check, for the moment I suggest researching in other repos how the thread bytearrays it seems that maybe we are missing an import or something like that

[FAIL] hello_world_integrationtest::test_contract::test_get_hello_world

Failure data:
    "Failed to get contract artifact for name = Hello."

Running 0 test(s) from src/
Tests: 0 passed, 1 failed, 0 skipped, 0 ignored, 0 filtered out

Failures:
    hello_world_integrationtest::test_contract::test_get_hello_world

@Gerson2102 can you add screenshots of the scarb build and snforge test result commands?

scarb build

snforge test

Another weird thing that is happening, is the branches. If I go to scripts I'm in hello-world-contract if i go to hello_world I'm in main.

@Gerson2102 this happens because if you used scarb init to start the development this creates a new git repository, to solve this go to hello-world-contract and run rm -r .git

Got it. Fixed it.


drawchart event for finish loading?

i need to notify the user that the chart is loading and when finished, how can i do that?

Thanks for your question! I think this is what you want
/****************************delegate method***************************************/
@protocol AAChartViewDidFinishLoadDelegate<NSObject>
-(void)AAChartViewDidFinishLoad;//the delegate method of finish loading
@end
/****************************delegate method***************************************/

@interface AAChartView : AAWebView<AAWebViewDelegate>

@property(nonatomic,weak)id<AAChartViewDidFinishLoadDelegate>delegate;

@property(nonatomic,assign)CGFloat contentWidth;//content width of AAChartView
@property(nonatomic,assign)CGFloat contentHeight;//content height of AAChartView

-(void)aa_drawChartWithChartModel:(AAChartModel *)chartModel;//function of drawing chart view
-(void)aa_refreshChartWithChartModel:(AAChartModel *)chartModel;//function of refreshing chart view
@end

NOTE:If you want to use this function ,you need to update the project of AAChartView to the latest code,Please !


Get following error when compiling

Cannot compile. Get the following error...
nvcc -g -std=c++11 -Ipython -c "import tensorflow; print(tensorflow.sysconfig.get_include())" -I"/usr/local/cuda-9.0/include" -DGOOGLE_CUDA=1 -D_MWAITXINTRIN_H_INCLUDED -D_FORCE_INLINES -D__STRICT_ANSI__ -D_GLIBCXX_USE_CXX11_ABI=0 -c -gencode=arch=compute_30,code=sm_30 FlowNet2_src/ops/preprocessing/kernels/data_augmentation.cu.cc -x cu -Xcompiler -fPIC  -o FlowNet2_src/ops/build/data_augmentation.o
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1255): warning: calling a constexpr host function("real") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1255): warning: calling a constexpr host function("imag") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1255): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1255): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1260): warning: calling a constexpr host function("real") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1260): warning: calling a constexpr host function("imag") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1260): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1260): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1285): warning: calling a constexpr host function("real") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1286): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1287): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1285): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1286): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1287): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1288): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1293): warning: calling a constexpr host function("real") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1294): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1295): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1293): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1294): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1295): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1296): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(74): warning: calling a constexpr host function("real") from a host device function("bfloat16") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(74): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(77): warning: calling a constexpr host function("real") from a host device function("bfloat16") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(77): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(166): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(170): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/absl/strings/string_view.h(496): error: constexpr function return is non-constant
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/google/protobuf/arena_impl.h(55): warning: integer conversion resulted in a change of sign
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/google/protobuf/arena_impl.h(309): warning: integer conversion resulted in a change of sign
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/google/protobuf/arena_impl.h(310): warning: integer conversion resulted in a change of sign
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(523): error: calling a constexpr host function("real") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(524): error: calling a constexpr host function("imag") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(530): error: calling a constexpr host function("real") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(531): error: calling a constexpr host function("imag") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(651): warning: missing return statement at end of non-void function "Eigen::internal::igammac_cf_impl<Scalar, mode>::run [with Scalar=float, mode=Eigen::internal::VALUE]"
detected during:
instantiation of "Scalar Eigen::internal::igammac_cf_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::VALUE]"
(855): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::VALUE]"
(2096): here
instantiation of "Eigen::internal::igamma_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma(const Scalar &, const Scalar &) [with Scalar=float]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h(34): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(712): warning: missing return statement at end of non-void function "Eigen::internal::igamma_series_impl<Scalar, mode>::run [with Scalar=float, mode=Eigen::internal::VALUE]"
detected during:
instantiation of "Scalar Eigen::internal::igamma_series_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::VALUE]"
(863): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::VALUE]"
(2096): here
instantiation of "Eigen::internal::igamma_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma(const Scalar &, const Scalar &) [with Scalar=float]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h(34): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(651): warning: missing return statement at end of non-void function "Eigen::internal::igammac_cf_impl<Scalar, mode>::run [with Scalar=float, mode=Eigen::internal::DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igammac_cf_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::DERIVATIVE]"
(855): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::DERIVATIVE]"
(2102): here
instantiation of "Eigen::internal::igamma_der_a_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma_der_a(const Scalar &, const Scalar &) [with Scalar=float]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h(38): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(712): warning: missing return statement at end of non-void function "Eigen::internal::igamma_series_impl<Scalar, mode>::run [with Scalar=float, mode=Eigen::internal::DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igamma_series_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::DERIVATIVE]"
(863): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::DERIVATIVE]"
(2102): here
instantiation of "Eigen::internal::igamma_der_a_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma_der_a(const Scalar &, const Scalar &) [with Scalar=float]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h(38): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(651): warning: missing return statement at end of non-void function "Eigen::internal::igammac_cf_impl<Scalar, mode>::run [with Scalar=float, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igammac_cf_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(855): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(2108): here
instantiation of "Eigen::internal::gamma_sample_der_alpha_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::gamma_sample_der_alpha(const Scalar &, const Scalar &) [with Scalar=float]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h(42): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(712): warning: missing return statement at end of non-void function "Eigen::internal::igamma_series_impl<Scalar, mode>::run [with Scalar=float, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igamma_series_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(863): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=float, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(2108): here
instantiation of "Eigen::internal::gamma_sample_der_alpha_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::gamma_sample_der_alpha(const Scalar &, const Scalar &) [with Scalar=float]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h(42): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(651): warning: missing return statement at end of non-void function "Eigen::internal::igammac_cf_impl<Scalar, mode>::run [with Scalar=double, mode=Eigen::internal::VALUE]"
detected during:
instantiation of "Scalar Eigen::internal::igammac_cf_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::VALUE]"
(855): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::VALUE]"
(2096): here
instantiation of "Eigen::internal::igamma_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma(const Scalar &, const Scalar &) [with Scalar=double]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h(120): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(712): warning: missing return statement at end of non-void function "Eigen::internal::igamma_series_impl<Scalar, mode>::run [with Scalar=double, mode=Eigen::internal::VALUE]"
detected during:
instantiation of "Scalar Eigen::internal::igamma_series_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::VALUE]"
(863): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::VALUE]"
(2096): here
instantiation of "Eigen::internal::igamma_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma(const Scalar &, const Scalar &) [with Scalar=double]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h(120): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(651): warning: missing return statement at end of non-void function "Eigen::internal::igammac_cf_impl<Scalar, mode>::run [with Scalar=double, mode=Eigen::internal::DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igammac_cf_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::DERIVATIVE]"
(855): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::DERIVATIVE]"
(2102): here
instantiation of "Eigen::internal::igamma_der_a_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma_der_a(const Scalar &, const Scalar &) [with Scalar=double]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h(135): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(712): warning: missing return statement at end of non-void function "Eigen::internal::igamma_series_impl<Scalar, mode>::run [with Scalar=double, mode=Eigen::internal::DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igamma_series_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::DERIVATIVE]"
(863): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::DERIVATIVE]"
(2102): here
instantiation of "Eigen::internal::igamma_der_a_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::igamma_der_a(const Scalar &, const Scalar &) [with Scalar=double]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h(135): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(651): warning: missing return statement at end of non-void function "Eigen::internal::igammac_cf_impl<Scalar, mode>::run [with Scalar=double, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igammac_cf_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(855): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(2108): here
instantiation of "Eigen::internal::gamma_sample_der_alpha_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::gamma_sample_der_alpha(const Scalar &, const Scalar &) [with Scalar=double]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h(154): here
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h(712): warning: missing return statement at end of non-void function "Eigen::internal::igamma_series_impl<Scalar, mode>::run [with Scalar=double, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
detected during:
instantiation of "Scalar Eigen::internal::igamma_series_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(863): here
instantiation of "Scalar Eigen::internal::igamma_generic_impl<Scalar, mode>::run(Scalar, Scalar) [with Scalar=double, mode=Eigen::internal::SAMPLE_DERIVATIVE]"
(2108): here
instantiation of "Eigen::internal::gamma_sample_der_alpha_retval<Eigen::internal::global_math_functions_filtering_base<Scalar, void>::type>::type Eigen::numext::gamma_sample_der_alpha(const Scalar &, const Scalar &) [with Scalar=double]"
/home/adhara/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/CUDA/CudaSpecialFunctions.h(154): here
5 errors detected in the compilation of "/tmp/tmpxft_000011ac_00000000-6_data_augmentation.cu.cpp1.ii".
Makefile:62: recipe for target 'preprocessing' failed
make: *** [preprocessing] Error 1

Try this
https://github.com/sampepose/flownet2-tf/issues/74#issuecomment-452579028

I am having the same error even after trying the given solution.

nvcc -g -std=c++11 -Ipython -c "import tensorflow; print(tensorflow.sysconfig.get_include())" -I"/usr/local/cuda-10.1/include" -DGOOGLE_CUDA=1 -DNDEBUG -D_MWAITXINTRIN_H_INCLUDED -D_FORCE_INLINES -D__STRICT_ANSI__ -D_GLIBCXX_USE_CXX11_ABI=0 -c -gencode=arch=compute_75,code=sm_75 FlowNet2_src/ops/preprocessing/kernels/data_augmentation.cu.cc -x cu -Xcompiler -fPIC  -o FlowNet2_src/ops/build/data_augmentation.o
In file included from /home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/util/ConfigureVectorization.h:384:0,
from /home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/Core:22,
from /home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/Tensor:14,
from /home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/third_party/eigen3/unsupported/Eigen/CXX11/Tensor:1,
from /home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/framework/tensor_types.h:19,
from FlowNet2_src/ops/preprocessing/kernels/augmentation_base.h:4,
from FlowNet2_src/ops/preprocessing/kernels/data_augmentation.cu.cc:5:
/usr/local/cuda-10.1/include/host_defines.h:54:2: warning: #warning "host_defines.h is an internal header file and must not be used directly.  This file will be removed in a future CUDA release.  Please use cuda_runtime_api.h or cuda_runtime.h instead." [-Wcpp]
#warning "host_defines.h is an internal header file and must not be used direct
^
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1288): warning: calling a constexpr host function("real") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1288): warning: calling a constexpr host function("imag") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1288): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1288): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1293): warning: calling a constexpr host function("real") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1293): warning: calling a constexpr host function("imag") from a host device function("abs") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1293): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1293): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1317): warning: calling a constexpr host function("real") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1318): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1319): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1317): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1318): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1319): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1320): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1325): warning: calling a constexpr host function("real") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1326): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1327): warning: calling a constexpr host function("imag") from a host device function("exp") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1325): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1326): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1327): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/../../../Eigen/src/Core/MathFunctions.h(1328): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(133): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(138): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(208): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/unsupported/Eigen/CXX11/src/Tensor/TensorRandom.h(213): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(74): warning: calling a constexpr host function("real") from a host device function("bfloat16") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(74): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(77): warning: calling a constexpr host function("real") from a host device function("bfloat16") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(77): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(166): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/lib/bfloat16/bfloat16.h(170): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/absl/strings/string_view.h(496): warning: expression has no effect
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(55): warning: integer conversion resulted in a change of sign
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(309): warning: integer conversion resulted in a change of sign
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/google/protobuf/arena_impl.h(310): warning: integer conversion resulted in a change of sign
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(364): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(374): warning: calling a constexpr host function from a host device function is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(523): error: calling a constexpr host function("real") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(524): error: calling a constexpr host function("imag") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(530): error: calling a constexpr host function("real") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
/home/ivlab/anaconda2/envs/tuto/lib/python3.7/site-packages/tensorflow/include/tensorflow/core/util/cuda_device_functions.h(531): error: calling a constexpr host function("imag") from a device function("CudaAtomicAdd") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.
4 errors detected in the compilation of "/tmp/tmpxft_0000685c_00000000-6_data_augmentation.cu.cpp1.ii".
Makefile:62: recipe for target 'preprocessing' failed
make: *** [preprocessing] Error 1

@Zhangsy0603 the solution you provided did not work.

@adhara123007 did you fix your problem? could you please help me out if you did?


[improve][broker] Include runtime dependencies in server distribution

Motivation
The server distribution assembly does not currently include artifact runtime dependencies, pulling only the compile dependencies instead. While this has not impacted the customers, a class loading issue can always crop up. This is what happened while importing OpenTelemetry dependencies related to PIP-320. OpenTelemetry itself marks its many dependencies as runtime (see, for instance, https://mvnrepository.com/artifact/io.opentelemetry/opentelemetry-exporter-otlp/1.34.1). Including each of them manually in our POM is both tedious and error-prone.
Modifications

Reverts the dependency scope for the server assembly to the default value, runtime.
Manually excludes some of the libraries that would be needlessly pulled.
Allows org.roaringbitmap-shims-0.9.44.jar to be included in the assembly.
Removes assembly exclusion for lombok as it is not needed anymore.

Verifying this change

[ ] Make sure that the change passes the CI checks.

This change is already covered by existing integration tests.
Does this pull request potentially affect one of the following parts:

If the box was checked, please highlight the changes

[x] Dependencies (add or upgrade a dependency)
[ ] The public API
[ ] The schema
[ ] The default values of configurations
[ ] The threading model
[ ] The binary protocol
[ ] The REST endpoints
[ ] The admin CLI options
[ ] The metrics
[ ] Anything that affects deployment

Documentation

[ ] doc
[ ] doc-required
[x] doc-not-needed
[ ] doc-complete

Matching PR in forked repository
PR in forked repository: https://github.com/dragosvictor/pulsar/pull/9

Perhaps we should double-check by making a diff between the included JARs in the before and after versions?

This is actually done by the license checked script :) The list there needs to match the jars included


Make c2d and methods samples single threaded

This PR is for two of the samples (hub_c2d and hub_methods), which used MQTT_setCallbacks and were asynchronous.  This change makes these samples single threaded by using MQTTClient_recieve.
This PR does NOT include the hub_twin sample.  While this sample also needs to be made single-threaded, to do so requires work in another task: removing user command prompt.  MQTTClient_receive for hub_twin sample will naturally be incorporated into that task.
I intentionally did not go through and refactor other methods, nor update all the printfs to LOG_ERROR, etc.  This is because I wanted to keep this PR focused on the threading change required.  Consistency cleanup for all samples will happen in a separate task.

Rewriting sections to receive up to 5 messages.


Make compilation of stdlib components more resilient to cache corruption

Our stdlib components generate index which includes IR cache, suggestions and bindings.
In case there is some data corruption, the compilation appears to go south and generate spurious failures, rather than attempting to catch up and generate broken modules on the fly.
To illustrate the problem:

Build local distribution

sbt> buildEngineDistribution

Remove some caches

> built-distribution/enso-engine-0.0.0-dev-linux-amd64/enso-0.0.0-dev/lib/Standard/Table/0.0.0-dev/.enso/cache/ir/0.0.0-dev/Standard/Table/Internal

Experience the wrath of the compiler

> built-distribution/enso-engine-0.0.0-dev-linux-amd64/enso-0.0.0-dev/bin/enso --ir-caches --run test/Table_Tests
...
In module Standard.Table.Internal.Java_Problems:
Compiler encountered errors:
Java_Problems.enso[24:15-24:33]: The name `Invalid_Aggregation` could not be found.
Java_Problems.enso[24:60-24:65]: The name `Vector` could not be found.
Java_Problems.enso[25:9-25:13]: The name `Error` could not be found.
...

Follow up on https://github.com/enso-org/enso/issues/6092

Circular dependencies may introduce confusing errors as explained in https://github.com/enso-org/enso/pull/6655#issuecomment-1547530674.
To repro:
-- a/distribution/lib/Standard/Table/0.0.0-dev/src/Data/Type/Value_Type.enso
+++ b/distribution/lib/Standard/Table/0.0.0-dev/src/Data/Type/Value_Type.enso
@@ -1,5 +1,6 @@
 from Standard.Base import all
 import Standard.Base.Errors.Illegal_Argument.Illegal_Argument
+import Standard.Database.Data.SQL_Type.SQL_Type

 import project.Data.Type.Value_Type_Helpers
 from project.Errors import Invalid_Value_Type
@@ -132,7 +133,7 @@ type Value_Type

        Fallback provided to allow describing types that are not supported by
        Enso at this time.
-    Unsupported_Data_Type type_name:(Text|Nothing)=Nothing (underlying_type:Any|Nothing=Nothing)
+    Unsupported_Data_Type type_name:(Text|Nothing)=Nothing (underlying_type:SQL_Type|Nothing=Nothing)

and run enso on test/Benchmarks. It will complain with
In module Standard.Database.Connection.Database:
Compiler encountered errors:
Database.enso[23:11-23:28]: The name `Connection_Details` could not be found.
Database.enso[23:33-23:50]: The name `Connection_Options` could not be found.
Database.enso[23:55-23:64]: The name `Connection` could not be found.
Database.enso[23:68-23:76]: The name `SQL_Error` could not be found.
Database.enso[24:25-24:42]: The name `Connection_Options` could not be found.
Database.enso[28:29-28:41]: The name `Single_Choice` could not be found.
Database.enso[30:28-30:33]: The name `Vector` could not be found.
Database.enso[31:63-31:67]: The name `False` could not be found.
Database.enso[35:9-35:14]: The name `Option` could not be found.
Database.enso[36:5-36:17]: The name `Single_Choice` could not be found.
Database.enso[36:27-36:33]: The name `Display` could not be found.
Aborting due to 11 errors and 0 warnings.
Execution finished with an error: Compilation aborted due to errors.

It'd be great if we reported a sane error when there are cyclic reference:

#6679

Closing as no longer an issue.