NFS issues caused by recent Docker change

It looks like this commit is causing some issues for us NFS users. I'm not entirely sure how we can get around it, but it may be possible with some NFS options. I can't really comment more on it than that.
The issue occurs when you're mounting a volume from the host, and the host-side doesn't exist. For example, if you have a directory you're going to mount a volume to, and you expect the Docker container to produce a bunch of files in there when it starts instead of starting with a bunch of files (e.g. first-time run of a container).
When this happens, here is the error:
$ docker-compose up
Starting <container_name>

ERROR: for <compose_name>  Cannot start service <compose_name>: error while creating mount source path '<host-side mount point>': <host-side mount point>: operation not permitted
ERROR: Encountered errors while bringing up the project.

If you then just run $ docker-compose up again straight away, it will work (as you can see from the above commit, it only tries to chown after making the folder, and only if it doesn't exist. So, on the second run it has already created it and continues fine from there.
Right now it's only a bit of a minor annoyance, but it would be great to see this issue resolved.
   15 minutes ago      Up 15 minutes       <IP_ADDRESS>:80->80/tcp, <IP_ADDRESS>:443->443/tcp, 19322/tcp, <IP_ADDRESS>:19322->19322/udp   dinghy_http_proxy

Running on OS X 10.11.6.

Hm yeah that's unfortunate but the change makes sense from their end. We haven't run into this yet because in all our docker-compose apps any host-mounted volumes are pre-created and committed to the git repos, you could do that as a workaround to avoid these errors on first startup.
This is related to the other chown/chmod issues that have come up in the past due to the way we're remapping the VM volume to your user on the host MacOS machine, see this FAQ entry: https://github.com/codekitchen/dinghy/blob/master/FAQ.md#im-running-into-file-permissions-issues-on-the-nfs-mounted-volumes
As outlined in the FAQ, I'm not aware of any easy solution -- we'd have to do something like modify the unfs3 daemon to ignore chown/chmod commands. I keep hoping that docker's user namespacing support will eventually solve the issue but it's still not in a state where it helps us here.

Yeah, I suppose that's a decent enough workaround for now in this case. I really hope Docker for Mac catches up with Docker Machine in terms of stability and performance soon. I tried Docker for Mac very recently but kept getting a bunch of issues with following logs crashing Docker Compose... strange.
To be honest though, if that modified unfs3 daemon could work, and it was pulled off well enough - that would be an amazing solution. I just have to worry what other problems it could then cause instead! That's the problem with this sort of thing I guess - as you said in the FAQ, there really is no one-size-fits-all solution without departing to Linux (or using a remote Linux development environment I guess).

I'm going to close this, as I'm not sure there's anything we can take action on here.


Add dcos checks [WIP]

High Level Description
Add a new pkgpanda package dcos-checks. The dcos-checks provides node and cluster checks implementation.

[ ] Add dcos-checks skeleton.
[ ] Add basic systemd units check.
[ ] Add integration test

Related Issues

DCOS-14989 Create dcos-checks package

Checklist for all PR's

[ ] Included a test which will fail if code is reverted but test is not. If there is no test please explain here:

[X] Read the DC/OS contributing guidelines

[X] Followed relevant code rules Rules for Packages and Systemd

Checklist for component/package updates:
If you are changing components or packages in DC/OS (e.g. you are bumping the sha or ref of anything underneath packages), then in addition to the above please also include:

[ ] Change log from the last version integrated (this should be a link to commits for easy verification and review): N/A
[ ] Test Results: N/A
[ ] Code Coverage (if available): N/A

PLEASE FILL IN THE TEMPLATE ABOVE / DO NOT REMOVE ANY SECTIONS ABOVE THIS LINE
Instructions and Review Process
What is the review process and when will my changes land?
All PRs require 2 approvals using github's pull request reviews.
Reviewers should be:

Developers who understand the code being modified.
Developers responsible for code that interacts with or depends on the code being modified.

It is best to proactively ask for 2 reviews by @mentioning the candidate reviewers in the PR comments area. The responsibility is on the developer submitting the PR to follow-up with reviewers and make sure a PR is reviewed in a timely manner. Once a PR has 2 ship-it's, no red reviews, and all tests are green it will be included in the next train.

@mesosphere-mergebot label Work In Progress

@mesosphere-mergebot bump-ee

@mesosphere-mergebot bump-ee

@mesosphere-mergebot label Ready for review

@mesosphere-mergebot label ship-it

Sorry that we are bit late in here. But, I raised some concerns with inclusion of this in dcos/dcos https://github.com/dcos/dcos/pull/1535#issuecomment-300853858
In general, I like mono-repo and prefer the code in single-place. However, the unittests should be the same place too and those needs to be run before the changes get merged.
All Checks have Passed above in this PR has very limited exercise on the 464 files that are being introduced in this PR.
Is my statement correct?
So, if there are unittests can be exercised for this changed and those are run for every change to this package, in the dcos/dcos repo, that will be better way to introduce the codebase.
That will bring an additional dependency to factor in the testing infrastructure requirements for dcos/dcos.
Let us please address these concerns before moving ahead with this.
/cc @BenWhitehead , @mellenburg , @spahl

464 files seems like a lot but in reality its the vendor folder which are dependencies. Thats how go does dependencies.
In reality the files introduced are the skeleton for adding a new check and one new check (~10 files). The check calls 3dt health and it has a unit test and integration test to verify it.
In its current state it does not interact with the current dcos installation process which is by design, the next few pr's will add more checks with unit tests.
There will be a pr for a "runner" in 3dt that will be used to run these checks which the integration test will use.
Following the runner the installer will call the runner as part of the install process which will verify these checks on every install.

Scheduled a meeting, will update pr with discussion results

@mesosphere-mergebot label ship-it
This is moved into its own repo, should be good to go

@mesosphere-mergebot label ship-it

This PR is getting kicked from the train again. There needs to be a bump-ee PR for this. More specifically, the integration test added here fails downstream, so if it needs to be excluded there, then there must a PR to do exactly that vs change.
Also, shouldnt this be coordinated with https://github.com/mesosphere/dcos-enterprise/pull/808 anyway?

@mesosphere-mergebot bump-ee

@mesosphere-mergebot bump-ee

@mesosphere-mergebot bump-ee

@mesosphere-mergebot label ship it


Update keybase to 1.0.18-20170208165022,dc66461

After making all changes to the cask:

[x] brew cask audit --download {{cask_file}} is error-free.
[x] brew cask style --fix {{cask_file}} left no offenses.
[x] The commit message includes the cask’s name and version.

Closing in favour of https://github.com/caskroom/homebrew-cask/pull/29956.


Load a GeoPackage dataset

I have a problem loading a GeoPackage dataset (https://drive.google.com/file/d/16--kcGrC56zayrK04-Brmfo3ImOwtQ5k/view?usp=sharing). The dataset can be loaded using ArchGDAL.
import ArchGDAL as AG
using DataFrames
stations = @chain "stations.gpkg" begin
    AG.read()
    AG.getlayer(0)
    DataFrame()
end

However, I can not load it using GeoTables.
using GeoTables
@time stations = GeoTables.load("stations.gpkg")

The previous code does not finish to be executed. I am using the latest version of GeoTables.jl.

@ErickChacon I can reproduce the issue. Nailed it down to a specific function call.
First we load the GDAL geometries:
using GeoTables

# auxiliary packages
import ArchGDAL as AG
import Tables

# load layer as a Tables.jl table
data  = AG.read("stations.gpkg")
table = AG.getlayer(data, 0)

# get the column with geometries
cols  = Tables.columns(table)
geoms = Tables.getcolumn(cols, :geom)
2-element Vector{ArchGDAL.IGeometry{ArchGDAL.wkbPoint}}:
 Geometry: POINT (-77.55011 -11.06068)
 Geometry: POINT (-77.36839 -11.36014)

Second we try to convert to Meshes.jl geometries:
# convert GDAL geometries to Meshes.jl geometries
items = GeoTables.geom2meshes.(geoms)

but the function GeoTables.geom2meshes hangs now.
It used to work, but the GeoInterface.jl is a never ending effort to convert geometry types, so our function may be broken now. Can you please check if our implementation is up-to-date and is the most efficient?
Feel free to submit a PR if you discover what is causing the function call to hang now.

Hi @juliohm. Thank for the explanation. This is something that I need so I will take a look to geom2meshes and GeoInterface.jl. I will come back when I find the issue.

Thank you @ErickChacon , this issue must be specific to GDAL because the same function works with Shapefile.jl and GeoJSON.jl geometries.

HI @juliohm. Yes, this is specific of GDAL but is not clear for me why it does not work. Continuing with your example. We can easily conver the first point with:
using Meshes
GI.coordinates(geoms[1]) |> Point

However a simple function like the following does not work (it hangs):
function topoint(geom)
    coords = GI.coordinates(geom)
    Point(coords)
end
topoint(geoms[1])

If I splat the coordinates vector, it works without problem.
function topoint2(geom)
    coords = GI.coordinates(geom)
    Point(coords...)
end
topoint2(geoms[1])

I have tried other options like using the GeoInterface.convert approach, but the same problem occurs when trying to create the Point from the coordinates vector. To isolate the problem I do not load Geotables at all. Let me know if yout have any thought about how to proceed.

Thank you @ErickChacon for investigating this further. Can you confirm that the other geometry types from GeoJSON.jl and Shapefile.jl work fine with your topoint function?
Our constructors for Point are defined here: https://github.com/JuliaGeometry/Meshes.jl/blob/master/src/points.jl

I also noticed that this behavior only happens inside a function and that doing it manually with GDAL types on the REPL works. It must be one of the GDAL pointer idiosyncrasies...

Exactly, it only happens inside the function. Shapefile.jl works without problems for both functions I presented before.

Worth checking with the maintainers of GDAL.jl and ArchGDAL.jl if there is a better method with GeoInterface.jl to make these conversions. I am not following these developments myself.

The return value of GI.coordinates is just a Vector{Float64} like it always has been?
julia> using ArchGDAL

julia> mypoint = ArchGDAL.createpoint(1.0, 5.0)
Geometry: POINT (1 5)

julia> GeoInterface.coordinates(mypoint)
2-element Vector{Float64}:
 1.0
 5.0

GeoInterface.coordinates is a pretty stable interface, and not at all part of our ongoing comparability efforts. So this is probably a Meshes.jl problem.
We usually use GeoInterface.getpoint in an iteration to do these conversions efficiently these days, and they work pretty nicely for everything else, although of course `ArchGDAL.jl will be slower due to the API overheads.

If you read our comments above you will see that the issue is specific to
GDAL. Whenever we call GI.coordinates from inside a function.
Em qui., 27 de abr. de 2023 11:43, Rafael Schouten @.***>
escreveu:

The return value of GI.coordinates is just a Vector{Float64} like it
always has been?
julia> using ArchGDAL
julia> mypoint = ArchGDAL.createpoint(1.0, 5.0)
Geometry: POINT (1 5)
julia> GeoInterface.coordinates(mypoint)2-element Vector{Float64}:
1.0
5.0
GeoInterface.coordinates is a pretty stable interface, and not at all
part of our ongoing comparability efforts. So this is probably a Meshes.jl
problem.
We usually use GeoInterface.getpoint in an iteration to do these
conversions efficiently these days, and they work pretty nicely for
everything else, although of course `ArchGDAL.jl will be slower due to the
API overheads.
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julia> f(geom) = GeoInterface.coordinates(geom)
f (generic function with 1 method)

julia> f(mypoint)
2-element Vector{Float64}:
 1.0
 5.0

?

Can you please read the previous comments? The REPL works fine.
Em qui., 27 de abr. de 2023 11:47, Rafael Schouten @.***>
escreveu:

julia> f(geom) = GeoInterface.coordinates(geom)
f (generic function with 1 method)
julia> f(mypoint)2-element Vector{Float64}:
1.0
5.0
?
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You are receiving this because you were mentioned.Message ID:
@.***>

Or you are saying that this is hanging somewhere else down in the
Meshes.Point constructors?
Em qui., 27 de abr. de 2023 11:50, Júlio Hoffimann <
@.***> escreveu:

Can you please read the previous comments? The REPL works fine.
Em qui., 27 de abr. de 2023 11:47, Rafael Schouten <
@.***> escreveu:

julia> f(geom) = GeoInterface.coordinates(geom)
f (generic function with 1 method)
julia> f(mypoint)2-element Vector{Float64}:
1.0
5.0
?
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I mean it has to be right? Or at least some combination?
Because this works fine everywhere else.

I think it might be a combination of both Meshes.jl and ArchGDAL.jl that does not work. For example, other Meshes constructors for Point work with ArchGDAL.jl like the following:
mypoint = AG.createpoint(1.0, 5.0)
function topoint(geom)
    coords = GI.coordinates(geom)
    Meshes.Point(coords...)
end
topoint(mypoint)

Shapefile.jl will be the same as ArchGDAL.jl.
julia> GeoInterface.coordinates(Shapefile.Point(1.0, 5.0))
2-element Vector{Float64}:
 1.0
 5.0

It cant be the return values causing this unless you are testing with another floating point type in the other packages and thats not triggering the bug.
So how are you imagining that Meshes.jl would cause a low-level GDAL error that we don't get without GDAL?
What is the mechanism? memory use? For this one point that shouldn't be an issue.

Not sure where because the lack of error trace. I also tried using Debugger.jl, the wierd thing is that it it does not hang when calling with @enter topoint(mypoint)

But which constructor is hanging? Is it a Julia issue or a low-level issue in GDAL?

In particular I am exploring the following contructors https://github.com/JuliaGeometry/Meshes.jl/blob/a0487c6824d6ee9d7389edc25ae937f1e4cf26fd/src/points.jl#L53-L55.
The constructor that uses Meshes.Vec does not work with ArchGDAL defined in topoint3:
import ArchGDAL as AG
import GeoInterface as GI
using Meshes

mypoint = AG.createpoint(1.0, 5.0)

function topoint1(geom)
    coords = GI.coordinates(geom)
    Meshes.Point(coords...)
end

function topoint2(geom)
    coords = GI.coordinates(geom)
    Meshes.Point{2,Float64}(coords)
end

function topoint3(geom)
    coords = GI.coordinates(geom)
    Meshes.Point(Meshes.Vec(coords))
end

topoint1(mypoint)
topoint2(mypoint)
topoint3(mypoint)

Thanks for investigating this further @ErickChacon , can you explain why do you think the call to length could be problematic? Isn't the coordinates vector returned by GI.coordinates a simple Julia Vector?

For now, the only reason is because the only intermediate step between Vec(coords) and Vec{2,Float64}(coords) is the use of length, but I am not sure.

@eliascarv can you please double check this?

My ArchGDAL PR may also reduce the weight from the GDAL side, currently getting points has too much overhead:
https://github.com/yeesian/ArchGDAL.jl/pull/369
It may interact with the poor design of Vec here to cause this problem.

Investigating a bit further, I could see that it hangs in the following line https://github.com/JuliaGeometry/Meshes.jl/blob/cb556d34900c64b6f40ac827360039c0fb3549f3/src/vectors.jl#L60, but only when interacting with ArchGDAL. It hangs when calling NTuple{Dim,T}(coords).

Did you make that change?
Also try my ArchGDAL PR for better point performance.
But ultimately using coordinates is not the way to do this. You are losing the compile-time known 2d/3e length and getting it back again at runtime from the lowest point level in a geometry. Its terrible for performance no matter what you do.
Iterating over GI.getgeom(geom) with GI.x and GI.y, and GI.is3d to get the D parameter is the way to do it fast.

It would help if this "preferred new way" of doing things with GI was implemented somewhere for reference. We could just copy/paste the code that is supposedly fast and more aligned with the latest version of the interface.

Did you make that change?

When I say that it hangs when calling NTuple{Dim,T}(coords), I mean without any change in Meshes.jl. But I agree with you that the main issue is by using length in the constructor make it non typestable. If I follow your suggestion, it works as long as length is not used inside the definiction of Vec. The question there would be how to generalize this constructor for higher dimensions?

Also try my ArchGDAL PR for better point performance.
But ultimately using coordinates is not the way to do this. You are losing the compile-time known 2d/3d length and getting it back again at runtime from the lowest point level in a geometry. Its terrible for performance no matter what you do.
Iterating over GI.getgeom(geom) with GI.x and GI.y, and GI.is3d to get the D parameter is the way to do it fast.

Happy to follow that approach. As @juliohm mentioned, which package would you suggest to check for the geointerface implementation? GeometryBasics.jl?

I can confirm that using the following constructor solves the problem and passes all test. @juliohm would you like a pull request on Meshes.jl?
function Vec(coords::AbstractVector{T}) where {T}
    n = length(coords)
    if n == 1
        Vec{1,T}(coords)
    elseif n == 2
        Vec{2,T}(coords)
    elseif n == 3
        Vec{3,T}(coords)
    else
        throw(ErrorException("not implemented"))
    end
end

Of course, it would still be great to update the geointerface for Meshes.jl depending of the package @rafaqz suggest to look at.

@ErickChacon a PR request would be very welcome. The code you shared seems fine, I think we can assume that Meshes.jl only supports up to 3 dimensions currently.

Maybe LibGEOS.jl is the best to compare to?
https://github.com/JuliaGeo/LibGEOS.jl/blob/master/src/geo_interface.jl
You may also notice that it accepts all GeoInterface.jl objects in all functions without explicit conversions by users.
That could also work in Meshes.jl

It may be eaaiest to follpw this PR:
https://github.com/JuliaGeo/LibGEOS.jl/pull/156

This has to do with the fact that GI returns a Union{Vector{T}, Vector{Union{T,Nothing}} etc as the resulting type. This is a MWE where Julia apparently has a bug:
test(v::AbstractVector{T}) where {T} = NTuple{length(v),T}(v)

test([1,2,3]) # works

test([1,2,nothing]) # hangs

Thanks @eliascarv for finding this MWE.

That's interesting, does seem like some kind of compiler bug.
But that return type sucks, we should track down where that comes from.

@ErickChacon you mentioned that we could fix the issue here by avoiding that constructor, right? Can you prepare a PR here as well to use the splatting operator as you suggested? It would be great if you could create a test set with GDAL geometries making sure that our geom2meshes function is working as expected with all of them.

@juliohm, yes. I am checking https://github.com/JuliaGeo/LibGEOS.jl/blob/master/src/geo_interface.jl to make the interface similar to it. We will just use GI.x, GI.y, and GI.z as used in LibGEOS.jl. They use the following function.
function GI.convert(::Type{Point}, ::PointTrait, geom; context=get_global_context())
    if GI.is3d(geom)
        return Point(GI.x(geom), GI.y(geom), GI.z(geom), context)
    else
        return Point(GI.x(geom), GI.y(geom), context)
    end
end

I am still checking other details to have an interface aligned with @rafaqz suggestions. I will start a pull request soon.

FYI context is purely an annoying libgeos thing ;)
But otherwise that should be generic

FYI context is purely an annoying libgeos thing ;)
But otherwise that should be generic.
Also note Meshes.jl will need a Meshes.geointerface_geomtype method to implement package level conversions.
Probably all this code should be in extensions in Meshes.jl anyway at some point, the dependencies on GeoJSON.jl and Shapefile.jl are obsolete now, they have Tables.jl interfaces.

We don't have plans to add dependencies related to GeoInterface.jl in Meshes.jl, it is not aligned with our philosophy and we don't want to promote use cases where users are fiddling with different geometry types all over the place. We are providing these conversion methods here in GeoTables.jl so that people can do IO, proceed with geometric processing constrained to a single set of geometries in Meshes.jl, and then export the results back to disk. That is the only place where GeoInterface.jl is envisioned in our stack.

Sure thing, love the strict, clean philosophy!
But mostly the idea is that theres no fiddling to be done, interop will be seemless ;)

But mostly the idea is that theres no fiddling to be done, interop will be seemless ;)

Perhaps you are too optimistic about the co-existence of different geometry types in advanced geometric processing pipelines. At some point you will hit function calls that are not implemented in terms of the GeoInterface.jl and the application will just crash. It is as simple as that in my mind, but I would be happy to be proven wrong. Looking forward to the seamless experience!

Its actually pretty easy to add methods for all functions in a package to accept GeoInterface types. See e.g. my LinGEOS PR. There is very little code used on that interop.

Thank you @ErickChacon for fixing this ❤


Support TOML and YAML

Currently we only support JSON. We should also support TOML and YAML files.

I'll take on this one :)


Upgraded cluster from 2.3.5 does not have the default values for maxUnavailable worker and control

What kind of request is this (question/bug/enhancement/feature request): bug
Steps to reproduce (least amount of steps as possible):

Deploy a cluster in 2.3.5
Upgrade to master
Edit on the cluster.
The default values for maxUnavailable_worker and Drain is not seen

maxUnavailable_control is not available in Edit as YAML.

Expected Result:
Default values for the maxUnavailable_worker and Drain should be seen. maxUnavailable_control should be available in Edit as YAML
Environment information

Rancher version (rancher/rancher/rancher/server image tag or shown bottom left in the UI): master-head - commit id: 570461823
Installation option (single install/HA): single

Cluster information

Cluster type (Hosted/Infrastructure Provider/Custom/Imported): rke DO
Kubernetes version (use kubectl version):

1.15

I don't see how we can set these values without user doing a cluster edit action. But it must be operating and doing cluster upgrades with the expected default values right? @sowmyav27

@mrajashree How is this a UI only issue? We have had plenty of other enhancements where we've added in new fields and the default is set during upgrade.

@deniseschannon From offline discussion with @codyrancher since the default values for these fields are present in /v3/schemas/nodeUpgradeStrategy on the upgraded setup, they should be populated from that in the UI

Giving a value for "Maximum Worker Nodes Unavailable" now in UI on master-2450-head (Rancher version 73f603f9f) gives error: invalid value for IntOrString: invalid value "": strconv.Atoi: parsing "": invalid syntax. This worked last week.
There is no workaround that I can tell right now so it blocks us from upgrading kubernetes versions on a cluster.

Rancher version: 2.4 master-head (03/17/2020) commit id: ddda7cb8d
Validated the default value after upgrading from v2.3.5 is 10 percentage:

maxUnavailable in the API shows 10 too.
Drain default value in UI is No.
Drain default value in the API is false.
Editing the cluster and saving the settings also works.


Bug Report:

Please check for duplicates, similar issues or closed issues with the same problem, as well performing simple troubleshooting steps (such as deleting the export folder if it's an issue with compiling, reinstalling Kade Engine) before submitting an issue.
If you are playing a downloaded version of the game, what operating system are you using?
Windows (x86), Windows (x86_64), Linux, or macOS? Specify below.
Windows x64
What version of the game are you using? Look in the bottom left corner of the main menu.
kade engine 1.8
Have you identified any steps to reproduce the bug? If so, please describe them below. Use images if possible.
ive tried to uninstall hscript and re install it but it didn't work
Please describe your issue. Provide extensive detail and images if possible.
when i try to build the game it says this C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:71: characters 52-56 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:74: characters 87-91 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:357: characters 17-18 : hscript.Error has no field e
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:373: characters 70-74 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:379: characters 70-74 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:384: characters 70-74 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:388: characters 69-73 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:392: characters 69-73 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodScriptClass.hx:396: characters 69-73 : hscript.Error has no field line
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodInterpEx.hx:134: characters 9-15 : hscript.Interp has no field setVar
C:/HaxeToolkit/haxe/lib/polymod/git/polymod/hscript/PolymodInterpEx.hx:115: characters 20-26 : Field setVar is declared 'override' but doesn't override any field

I figured it out in TitleState.hx i deleted 		#if polymod
polymod.Polymod.init({modRoot: "mods", dirs: ['introMod']});
#end


Auto-adjusting height

Is there a way to have the swiper height automatically adjust to the slide content (height)?

Note: I had it working using onLayout on slide container views, changing the swiper height accordingly once the slide view is rendered. But onLayout is not ideal because it doesn't update on animations.

+1

+1
Temporary i had set the maximum height out of all view inside the swiper.
We can get height of view using onLayout

Ideally it would be nice if it just worked with Flexbox.
For example:
() => (
  <View>
    <View style={{ height: 100 }} />
    <Swiper>
      <View style={{ flex: 1, backgroundColor: 'tomato' }} />
    </Swiper>
  </View>
)

The Swiper component should have height 557 (if we assume the device height to be 667) but it doesn't (it has height 667), so you can't see the pagination dots.

see #343

Anyone figure anything out for this issue?
Without setting the swiper height it seems to default to the screen's height.
I tried out the onLayout technique for finding height of content and then setting the height of the swiper but that doesn't account for different pages in the swiper with different content heights and also didn't work on Android for me.

I made this work using height="100%" for the Swiper

I made this work using height="100%" for the Swiper

on documentation:
height | - | number | If no specify default fullscreen mode by flex: 1


Update some GAX V4 dependencies.

Some of these need to be updated together, or the target framework updated. Renovate does not know to do that.

DLP should fail until PubSub GAX V4 is released, which is happening right now.


Error importing tensorflow.  Unless you are using bazel, you should not try to import tensorflow from its source directory

These are the sequence of steps i followed to install the distributed version of TF

git clone --recurse-submodules https://github.com/tensorflow/tensorflow
./configure (default with GPU)
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu (at this point saw the expected output and GPU being used)
bazel build -c opt --config=cuda --define=use_fast_cpp_protos=true //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
sudo pip install /tmp/tensorflow_pkg/tensorflow-0.7.1-py2-none-any.whl
Processing /tmp/tensorflow_pkg/tensorflow-0.7.1-py2-none-any.whl
Installing collected packages: tensorflow
pip show tensorflow
Metadata-Version: 2.0
Name: tensorflow
Version: 0.7.1
Summary: TensorFlow helps the tensors flow
Home-page: http://tensorflow.org/
Author: Google Inc.
Author-email<EMAIL_ADDRESS>License: Apache 2.0
Location: /usr/local/lib/python2.7/dist-packages
Requires: six, protobuf, wheel, numpy
Classifiers:
Development Status :: 4 - Beta
Intended Audience :: Developers
Intended Audience :: Education
Intended Audience :: Science/Research
License :: OSI Approved :: Apache Software License
Programming Language :: Python :: 2.7
Topic :: Scientific/Engineering :: Mathematics
Topic :: Software Development :: Libraries :: Python Modules
Topic :: Software Development :: Libraries
Entry-points:
[console_scripts]
tensorboard = tensorflow.tensorboard.tensorboard:main

Now for the error

python
Python 2.7.9 (default, Apr  2 2015, 15:33:21)
[GCC 4.9.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python2.7/dist-packages/tensorflow/init.py", line 23, in
from tensorflow.python import *
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/init.py", line 41, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/init.py", line 35, in
from tensorflow.core.framework.graph_pb2 import *
File "/usr/local/lib/python2.7/dist-packages/tensorflow/core/framework/graph_pb2.py", line 6, in
from google.protobuf import descriptor as _descriptor
ImportError: No module named protobuf

Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.
Can someone help me understand what might cause this? Thank you.

You should start your python outside tensorflow directory. Because python will import tensorflow from current directory.

I had the same errors as you did. I solved this by reinstall protobuf, by pip install -U protobuf==3.0.0b2

@shiyemin yes of course I started the interpreter outside the tensorflow directory
@raingo I tried that but in python interpreter I still get same error. Do you have to do a bazel build for tensorflow by pass in this protobuf library into the build command?

Yes. I built from source, but I didn't do anything special for bazel. I
needed to upgrade protobuf manually because I install the wheel by
pip install wheel --no-deps -U
Sent from a mobile device
On Mar 6, 2016 3:45 PM, "ushnish"<EMAIL_ADDRESS>wrote:

@shiyemin https://github.com/shiyemin yes of course I started the
interpreter outside the tensorflow directory
@raingo https://github.com/raingo I tried that but in python
interpreter I still get same error. Do you have to do a bazel build for
tensorflow by pass in this protobuf library into the build command?
—
Reply to this email directly or view it on GitHub
https://github.com/tensorflow/tensorflow/issues/1402#issuecomment-192984806
.

@raingo did you do git clone --recurse-submodules https://github.com/tensorflow/tensorflow or clone without the submodules since you are installing protobuf separately

Uninstall protobuf before building (or dl whl), everything works fine after that. Had the same issue.
sudo pip uninstall protobuf

@Dringite do you mean git clone with the --recurse-submodules options and then uninstall protobuf? But that'll cause the bazel build to fail?

Problem solved @Dringite you were right, there was no need to have protobuf installed at all. The steps are

git clone --recurse-submodules https://github.com/tensorflow/tensorflow
sudo pip uninstall protobuf
cd tensorflow/
./configure
bazel build -c opt --config=cuda --define=use_fast_cpp_protos=true //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tenso
rflow_pkg
sudo pip install /tmp/tensorflow_pkg/tensorflow-0.7.1-py2-none-any.whl

Notice that i added --define=use_fast_cpp_protos=true in the build command so it might have actually helped.

@ushnish I have followed your way to install tensorflow-0.7.1. In the future if I want to upgrade the version of tensorflow, is it necessary for me to follow your way to install new version? Or is there any other convenient ways?

Tensorflow 0.9.0 also suffers from the same issue.   The answer from @Dringite can solve the issue.  (i.e., pip uninstall protobuf and tensorflow, then pip install tensorflow)

Tensorflow 0.10.0 also suffers from the same issue. The answer from @raingo can solve the issue. (i.e., pip uninstall protobuf, then pip install wheel --no-deps -U)

According to the above method Still not solve
ubuntu 64
tensorflow-0.12.0rc0-cp27-cp27mu-manylinux1_x86_64.whl
`Python 2.7.3 (default, Jun 22 2015, 19:33:41)
[GCC 4.6.3] on linux2
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf
Traceback (most recent call last):
File "", line 1, in
File "/root/tg2env/local/lib/python2.7/site-packages/tensorflow/init.py", line 24, in
from tensorflow.python import *
File "/root/tg2env/local/lib/python2.7/site-packages/tensorflow/python/init.py", line 60, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/root/tg2env/local/lib/python2.7/site-packages/tensorflow/python/init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "/root/tg2env/local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 28, in
_pywrap_tensorflow = swig_import_helper()
File "/root/tg2env/local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
ImportError: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.16' not found (required by /root/tg2env/local/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so)

Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.
`

I'm running Ubuntu 14.04.5 LTS with tensorflow==0.12.0rc0 (most recent in PyPy) and keras==1.1.0.
A quick hack to get you by:
sudo vim /usr/local/lib/python2.7/dist-packages/tensorflow/python/__init__.py

and replace from tensorflow.python import pywrap_tensorflow with import pywrap_tensorflow around line 49 in the try portion of the try/catch.

I got a similar error. It was solved when I run python from the parent directory of tensorflow. But I'm curious if I can import tensorflow from another directory? Because when I do, it shows this error.
"Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there."

@baregawi Is this a new behavior in 0.12?
@NewRem how did you install TensorFlow?
@yifeif It obviously looks fine in our CI, any idea?

Looks like it is related to this line when running tensorflow from source dir, https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/init.py#L49
This should be resolved by not running from the source dir.
@NewRem also curious how you installed tensorflow. You should be able to import tensorflow from a non-repo-source directory.

Thank you all, I solved the problem by upgrading the ubuntu

@martinwicke @yifeif I used pip installation. To be exact, I used these three commands:
$ sudo easy_install pip
$ sudo easy_install --upgrade six
#the CPU version of the binaries to Pypi
$ sudo pip install --ignore-installed tensorflow

@martinwicke I just pip install -U tensorflow after not having updated since September. But I remember having to do a similar hack in September: https://github.com/tensorflow/tensorflow/issues/4616

@baregawi #4616 is different, we are removing spurious symbols from our packages, so a lot of these direct imports will stop working.
This issue is different, and in the past, this has pointed to tensorflow now being properly installed. It's hard to debug remotely though. @ushnish how many pythons do you have installed and which one is tensorflow installed in?
Can you install tensorflow in a virtualenv? If that works, then there's some problem with conflicting versions, either python/ipython or more than one tensorflow installation.

@martinwicke I installed tensorflow_gpu-0.12rc1-py2-none-any.whl step by step via the instruction of official site.
execute this command: sudo pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.0rc1-py2-none-any.whl
Collecting tensorflow-gpu==0.12.0rc1 from https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.0rc1-py2-none-any.whl
  Downloading https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.0rc1-py2-none-any.whl (83.6MB)
    100% |████████████████████████████████| 83.6MB 7.5kB/s
Collecting mock>=2.0.0 (from tensorflow-gpu==0.12.0rc1)
  Downloading mock-2.0.0-py2.py3-none-any.whl (56kB)
    100% |████████████████████████████████| 61kB 33kB/s
Collecting numpy>=1.11.0 (from tensorflow-gpu==0.12.0rc1)
  Downloading numpy-1.11.2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (3.9MB)
    100% |████████████████████████████████| 3.9MB 16kB/s
Collecting protobuf==3.1.0 (from tensorflow-gpu==0.12.0rc1)
  Downloading protobuf-3.1.0-py2.py3-none-any.whl (339kB)
    100% |████████████████████████████████| 348kB 16kB/s
Collecting wheel (from tensorflow-gpu==0.12.0rc1)
  Downloading wheel-0.29.0-py2.py3-none-any.whl (66kB)
    100% |████████████████████████████████| 71kB 19kB/s
Collecting six>=1.10.0 (from tensorflow-gpu==0.12.0rc1)
  Downloading six-1.10.0-py2.py3-none-any.whl
Collecting funcsigs>=1; python_version < "3.3" (from mock>=2.0.0->tensorflow-gpu==0.12.0rc1)
  Downloading funcsigs-1.0.2-py2.py3-none-any.whl
Collecting pbr>=0.11 (from mock>=2.0.0->tensorflow-gpu==0.12.0rc1)
  Downloading pbr-1.10.0-py2.py3-none-any.whl (96kB)
    100% |████████████████████████████████| 102kB 28kB/s
Collecting setuptools (from protobuf==3.1.0->tensorflow-gpu==0.12.0rc1)
  Downloading setuptools-32.0.0-py2.py3-none-any.whl (477kB)
    100% |████████████████████████████████| 481kB 30kB/s
Installing collected packages: six, funcsigs, pbr, mock, numpy, setuptools, protobuf, wheel, tensorflow-gpu
Successfully installed funcsigs-1.0.2 mock-2.0.0 numpy-1.11.2 pbr-1.10.0 protobuf-3.1.0 setuptools-32.0.0 six-1.10.0 tensorflow-gpu-0.12.0rc1 wheel-0.29.0

But unfortunately, I got the same error as following output:
>>> import tensorflow
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Library/Python/2.7/site-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "/Library/Python/2.7/site-packages/tensorflow/python/__init__.py", line 60, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "/Library/Python/2.7/site-packages/tensorflow/python/__init__.py", line 49, in <module>
    from tensorflow.python import pywrap_tensorflow
  File "/Library/Python/2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 28, in <module>
    _pywrap_tensorflow = swig_import_helper()
  File "/Library/Python/2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
ImportError: dlopen(/Library/Python/2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so, 10): no suitable image found.  Did find:
	/Library/Python/2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so: mach-o, but wrong architecture

Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.
>>> exit()

The version of mac system: OS X EI Captain
And I had try each ways above this issues list, but nothing change.
Thank u 4 any response.

@R0rs12ach:
The hint is in this line:
Did find: /Library/Python/2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so: mach-o, but wrong architecture
Are you installing this on PPC? If so, you'll have to install from source, our binary packages only support x86_64.

@R0rs12ach: i had the same problem using mac OS X Yosemite.
i have tried everything written here but it didn't help.
At last i went back to the homepage of tensor flow and tried other installation methods. After that i have followed 'Anaconda installation' -> 'Using conda' i finally could run it properly. Not sure which action i have taken helped.
So far i have tried:
$ sudo easy_install pip
$ sudo easy_install --upgrade six

$ sudo pip install --upgrade $TF_BINARY_URL

pip uninstall protobuf
pip install wheel --no-deps -U)

git clone --recurse-submodules https://github.com/tensorflow/tensorflow
sudo pip uninstall protobuf
cd tensorflow/
./configure
bazel build -c opt --config=cuda --define=use_fast_cpp_protos=true //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tenso
rflow_pkg
sudo pip install /tmp/tensorflow_pkg/tensorflow-0.7.1-py2-none-any.whl

and as said, instead of install with pip i have made it with Anaconda installation from trensorflow homepage: https://www.tensorflow.org/get_started/os_setup#anaconda_installation
Hope it will help you.

@martinwicke I think my computer's arch is :
Darwin MacBook-Pro.local 15.6.0 Darwin Kernel Version 15.6.0: Thu Jun 23 18:25:34 PDT 2016; root:xnu-3248.60.10~1/RELEASE_X86_64 x86_64

the fact is that my computer just x86_64
@MeilingShi : Thank u 4 ur advice, I will try it and paste the result

@MeilingShi I have tried what you said above, but nothing change. In fact, the cuda sdk do not support intel graphic 4000. So, i give up to install tensorflow_gpu_version on my mac which bought at 2013.

@R0rs12ach yes, CUDA only works with NVIDIA graphics cards.
It's still confusing me that it would complain about the library architecture.
Others, I would like to understand this issue, but this thread has become too noisy. Whoever still has this problem, can you open a new issue with your system config according to the template?

I follow the official pip windows installation and get same error as others.
I also tried uninstalling protobuf etc beforehand to no avail. I'm running python 3.5.2 and Anaconda.
Is everyone having this problem on Windows?
`C:\Users\Rafie>python
Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul  5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:119] Couldn't open CUDA library cublas64_80.dll
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_blas.cc:2294] Unable to load cuBLAS DSO.
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:119] Couldn't open CUDA library cudnn64_5.dll
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_dnn.cc:3459] Unable to load cuDNN DSO
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:119] Couldn't open CUDA library cufft64_80.dll
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_fft.cc:344] Unable to load cuFFT DSO.
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:119] Couldn't open CUDA library nvcuda.dll
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_diagnostics.cc:165] hostname: °9l├
Traceback (most recent call last):
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Program Files\Anaconda3\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: A dynamic link library (DLL) initialization routine failed.

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\Program Files\Anaconda3\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import *
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 60, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Program Files\Anaconda3\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: A dynamic link library (DLL) initialization routine failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\Program Files\Anaconda3\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.`

Same issue as @NuovoVesuvio

my environment:
centos6.5 x86_64
python 2.7
I use pip install tensorflow version1.2 succuessfully. However I enter python and import tensorflow, I met the error like above. I try above solution, but it still failed.
ImportError: /lib64/libc.so.6: version `GLIBC_2.16' not found (required by /data/apps/anaconda/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow.so)
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
Anyone has ideas for it? Thanks very much!

The binaries we provide do not work on CentOS 6.5, because the system libraries are too old. You will have to build from source.

I really have the same error. but when i update my tensorflow, it's resolved.
sudo yum install python-pip python-dev
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp27-none-linux_x86_64.whl
sudo pip install --upgrade $TF_BINARY_URL

I have the same problem on fedora 25. I tried all the proposed solution. It works for tensorflow, but not for tensorflow-gpu

Same problem: "Error importing tensorflow. Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter"
Tried building from source, installing through pip. All the same. I will just move to theano

@rodrigomfw can you paste the error before that message? For some people on this thread it's that they have very old systems (CentOS 6.x) which don't support the pre-built binaries. For you it's probably something else since it only affects GPU.
@vrv, I think we should rephrase this error. Most of the time (100% of the time in this thread), this is a failure to import unrelated to the working directory.

Yup, something changed and we now raise ImportError much more often, so the error message is unhelpful.

I just uninstalled tensorflow and tensorflow-gpu both and then I just installed tensorflow-gpu... works perfectly fine for me

Facing this error when installing tensorflow on windows 8 with python 3.5 and importing it from IDLE. I think it is the same issue.

import tensorflow
Traceback (most recent call last):
File "C:\python_35_2_64\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\python_35_2_64\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: A dynamic link library (DLL) initialization routine failed.

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\python_35_2_64\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\python_35_2_64\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\python_35_2_64\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\python_35_2_64\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<pyshell#0>", line 1, in
import tensorflow
File "C:\python_35_2_64\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import *
File "C:\python_35_2_64\lib\site-packages\tensorflow\python_init_.py", line 60, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\python_35_2_64\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\python_35_2_64\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: A dynamic link library (DLL) initialization routine failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\python_35_2_64\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\python_35_2_64\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\python_35_2_64\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\python_35_2_64\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.

pip install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/protobuf-3.1.0-cp27-none-macosx_10_11_x86_64.whl

I did everything above but I always get this:

Using TensorFlow backend.
RuntimeError: module compiled against API version 0xa but this version of numpy is 0x9
Traceback (most recent call last):
File "run.py", line 1, in
import lstm
File "/Users/jjj/Documents/dev/LSTM/lstm.py", line 5, in
from keras.layers.core import Dense, Activation, Dropout
File "/Library/Python/2.7/site-packages/Keras-1.2.0-py2.7.egg/keras/init.py", line 2, in
from . import backend
File "/Library/Python/2.7/site-packages/Keras-1.2.0-py2.7.egg/keras/backend/init.py", line 67, in
from .tensorflow_backend import *
File "/Library/Python/2.7/site-packages/Keras-1.2.0-py2.7.egg/keras/backend/tensorflow_backend.py", line 1, in
import tensorflow as tf
File "/Library/Python/2.7/site-packages/tensorflow/init.py", line 24, in
from tensorflow.python import *
File "/Library/Python/2.7/site-packages/tensorflow/python/init.py", line 60, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/Library/Python/2.7/site-packages/tensorflow/python/init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "/Library/Python/2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 28, in
_pywrap_tensorflow = swig_import_helper()
File "/Library/Python/2.7/site-packages/tensorflow/python/pywrap_tensorflow.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
ImportError: numpy.core.multiarray failed to import
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.

@gistya https://www.tensorflow.org/get_started/os_setup

I got over the problem by reinstalling cuda 8.0 and cudnn 5.1

Maybe this can help you when you got this "Error importing tensorflow. Unless you are using bazel, you should not try to import tensorflow from its source directory"  https://github.com/tensorflow/tensorflow/issues/559

try this one
https://github.com/tensorflow/tensorflow/issues/559
from author se7en007 commented on 4 Jan 2016
import numpy as np
np.path
['/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy']
exit()
sudo rm -rf /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy
...

If anyone had the same problem as mine, i managed to fix it. My error was
ImportError: numpy.core.multiarray failed to import
Error importing tensorflow. Unless yo......
Because i am running on a Mac, there are 2 sets of numpy thats running at the same time, as the Mac came with Python installed, so even if you are updating the numpy, it wasnt updating the one thats needed for Tensorflow. I believe i ran sudo pip install numpy -U --upgrade or something like that so all versions of numpy would be upgraded within my Mac. Then it worked after that.

What does it mean to be in the "source directory". I am also having the same issue however, I have no idea what the source directory is.

seems no solution yet. I am installing gpu version on windows 10. The installation seems ok at least no error or warning. I have
pip install --ignore-installed --upgrade C:\Users\dbsnail\Downloads\tensorflow_gpu-1.0.0rc2-cp35-cp35m-win_amd64.whl

import tensorflow
Traceback (most recent call last):
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Anaconda2\envs\py35\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: The specified module could not be found.

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python_init_.py", line 66, in
from tensorflow.python import pywrap_tensorflow
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\Anaconda2\envs\py35\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import *
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python_init_.py", line 72, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Anaconda2\envs\py35\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: The specified module could not be found.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python_init_.py", line 66, in
from tensorflow.python import pywrap_tensorflow
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Anaconda2\envs\py35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\Anaconda2\envs\py35\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
Failed to load the native TensorFlow runtime.
See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import_error
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

I got the solution, install cuDNN v5.1 for CUDA 8.0
You need to register as a NVIDIA accelerated computing developer program, then from here (https://developer.nvidia.com/rdp/cudnn-download) download and unzip it.
Copy all three subfolders and past it under CUDA folder, in my case is
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
Then , you should be able to load tensorflow without any error
NOTE, I use python 3.5

I first installed wheel, then the tensorflow was installed on my machine(using windows 10).
Now, it is not getting imported here is the error :
Using TensorFlow backend.
Traceback (most recent call last):
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
fp, pathname, description = imp.find_module('_pywrap_tensorflow', [dirname(file)])
File "C:\Users\mzm\Anaconda3\lib\imp.py", line 296, in find_module
raise ImportError(_ERR_MSG.format(name), name=name)
ImportError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 29, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in swig_import_helper
import _pywrap_tensorflow
ModuleNotFoundError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/mzm/PycharmProjects/mzm/FAQ bot/rough.py", line 36, in
from keras.models import Sequential, Model
File "C:\Users\mzm\Anaconda3\lib\site-packages\keras_init_.py", line 3, in
from . import activations
File "C:\Users\mzm\Anaconda3\lib\site-packages\keras\activations.py", line 4, in
from . import backend as K
File "C:\Users\mzm\Anaconda3\lib\site-packages\keras\backend_init_.py", line 73, in
from .tensorflow_backend import *
File "C:\Users\mzm\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 1, in
import tensorflow as tf
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import *
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 60, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
fp, pathname, description = imp.find_module('_pywrap_tensorflow', [dirname(file)])
File "C:\Users\mzm\Anaconda3\lib\imp.py", line 296, in find_module
raise ImportError(_ERR_MSG.format(name), name=name)
ImportError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 29, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Users\mzm\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in swig_import_helper
import _pywrap_tensorflow
ModuleNotFoundError: No module named '_pywrap_tensorflow'
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.
Does any know how to fix it??

Guys its simple,
Come out of the tensorflow environment
like -
source deactivate tensorflow
then try your tensor board
Ex:    tensorboard --logdir=/tmp/tboard/output

https://github.com/ravivalluri/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import-error
There is a explain with this problem.

Traceback (most recent call last):
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: %1 is not a valid Win32 application.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:\WorkspaceMaven\A-python\Test.py", line 1, in
import tensorflow as tf
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import *
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python_init_.py", line 60, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: %1 is not a valid Win32 application.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python_init_.py", line 54, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 21, in
_pywrap_tensorflow = swig_import_helper()
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow')
File "C:\Users\SEM\AppData\Local\Programs\Python\Python35\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow'
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.

Hi, I got the same issue:
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.

This was exactly after following the getting started guide and trying a import tensorflow as tf.
Wondering why is this issue closed when so many people still have the issue.
I couldn't find the solution anywhere on this thread or on stackoverflow.
Please help!!

Hi Abhishek,
I am still not resolved with this issue if you find potential fixes than
please let me know.
On Sep 12, 2017 1:50 PM, "Abhishek"<EMAIL_ADDRESS>wrote:

Hi, I got the same issue:
Error importing tensorflow.  Unless you are using bazel,
you should not try to import tensorflow from its source directory;
please exit the tensorflow source tree, and relaunch your python interpreter
from there.
This was exactly after following the getting started guide and trying a
import tensorflow as tf.
Wondering why is this issue closed when so many people still have the
issue.
I couldn't find the solution anywhere on this thread or on stackoverflow.
Please help!!
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/1402#issuecomment-328778159,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ANfiFJR4BmqpKC3Uogd0IgvwdIfrMYv2ks5shj7YgaJpZM4HqPp5
.

Oh,my solution is upgrading the pip to latest version， then use it to reinstall tensorflow

lol, you guys are just naive! It's clearly written that you cant import tensorflow on the terminal itself, C'mon go and create a python file and then compile it silly!

This thread seems somewhat old, but just to share the problem I had and how I solved it.
I first tried to import keras, but I faced the same error on this issue title.
I uninstalled protobuf and updated tensorflow. It worked.
$ pip uninstall protobuf
$ pip install -U tensorflow

1.Download Python 3.5.2 (3.5.2 only!!)
2.In command prompt : pip install tensorflow
(ignore this --Cache entry deserialization failed, entry ignored)
3.:python
4.>>import tensorflow as tf (
if no error then successfully installed
5.>>print(tf.version)
(use double underscore above)

)


add_documents gets called even if add_domains is empty

Try adding an out of scope domain.
in line  https://github.com/honoki/bbrf-client/blob/master/bbrf.py#L246
add_documents gets called with empty add_domain object. Wasted call.

Calls are free, though! :) Thanks for the feedback, but I do not consider this a bug. I believe there are more/other opportunities to improve the performance of the client, one of which would be to move from python to something faster (rust/go).

Calls are free, though! :) Thanks for the feedback, but I do not consider this a bug. I believe there are more/other opportunities to improve the performance of the client, one of which would be to move from python to something faster (rust/go).

I've been revisiting some code, and now understand that you meant an HTTP request rather than a function call! I'm planning to remove this kind of overhead in an upcoming version, by always reducing the number of unnecessary calls to a minimum.
Thanks again for this feedback!

This has been fixed in v1.1.1, along with some other unnecessary calls.


Index-append operation only indexing bulk-size * clients documents

Rally version (get with esrally --version):
Latest from master, 425d8f6e8828f944607807d192aa7a98a45672f3
Invoked command:
./rally --track-path=/home/hinmanm/es/mytrack --target-hosts=<IP_ADDRESS>:9200 --pipeline=benchmark-only

Configuration file (located in ~/.rally/rally.ini)):
[meta]
config.version = 12

[system]
env.name = local

[node]
root.dir = /home/hinmanm/.rally/benchmarks
src.root.dir = /home/hinmanm/es

[source]
remote.repo.url = https://github.com/elastic/elasticsearch.git
elasticsearch.src.subdir = elasticsearch

[build]
gradle.bin = /home/hinmanm/.sdkman/candidates/gradle/current/bin/gradle

[runtime]
java.home = /usr/lib/jvm/java-1.8.0-openjdk-<IP_ADDRESS>-1.b12.fc26.x86_64

[benchmarks]
local.dataset.cache = ${node:root.dir}/data

[reporting]
datastore.type = elasticsearch
datastore.host = localhost
datastore.port = 9900
datastore.secure = False
datastore.user =
datastore.password =

[tracks]
default.url = https://github.com/elastic/rally-tracks

[teams]
default.url = https://github.com/elastic/rally-teams

[defaults]
preserve_benchmark_candidate = False

[distributions]
release.1.url = https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-{{VERSION}}.tar.gz
release.2.url = https://download.elasticsearch.org/elasticsearch/release/org/elasticsearch/distribution/tar/elasticsearch/{{VERSION}}/elasticsearch-{{VERSION}}.tar.gz
release.url = https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-{{VERSION}}.tar.gz
release.cache = true

JVM version:
JDK 8
OS version:
Fedora 26
Description of the problem including expected versus actual behavior:
I have a track with an index-append operation defined inline in the challenge like so:
      "schedule": [
        {
          "operation": {
            "name": "index-append",
            "operation-type": "bulk",
            "bulk-size": {{bulk_size | default(100)}}
          },
          "clients": 4
        },

The documents.json contains 1967 documents, however, only 400 are actually indexed.
Steps to reproduce:

Using a track with many documents, add a challenge schedule with a low bulk-size and multiple clients
Run the track
Observe that only bulk-size x clients documents are indexed, in my case, 100 x 4 = 400 documents actually indexed.

I've noticed that this didn't affect me when the indexing was defined in a separate operation, it only started affecting me when I defined it inline in the challenge.
Provide logs (if relevant):
The data is from a private repo, so I cannot provide it here.

I could reproduce the behavior that you are seeing. It is caused by the fact that you did not specify any iterations or time-periods on the task. If you add "warmup-time-period": 0 to the task definition, then it will index all documents.
The reason for this - admittedly - strange behavior is that you can either have a time-period-based or an iteration-based task. If you do not specify anything, Rally will run the provided operation once without warmup by default and that's what you see here.
While we could argue that it makes no sense to execute a bulk operation only once, Rally does not impose any semantics on the operation on that level. It simply executes what you give it.

Very odd, okay, I wonder if maybe it'd be nice to have a different operation type that will always consume all of the documents from the file? That's the only thing I could think that would help alleviate the weirdness

Yes. I let this ticket open as a reminder for now but I need to think how to make this less trappy in the future.

Another user just hit this in https://discuss.elastic.co/t/bulk-index-operation-for-multiple-indices/120373. Hence, I have changed the milestone now so we do something about this earlier.

Rally 0.9.4 will implement the following behavior in case the user did not specify warmup-time-period, time-period, warmup-iterations or iterations: It will still default to an iteration-based approach (as opposed to a time-based approach). However, instead of defaulting to no warmup iterations and one measurement iteration, it will first check the corresponding parameter source. For bulk operations, the parameter source is able to determine the necessary number of bulks upfront (for all other operations this has never been a problem). Consequently, we will now ingest all data by default.


[Bug] Sidebar on mobile becomes invisible when plugin is enabled

Hi @mirnovov!
Thank you for this great plugin, it works like a charm.
However I have ran into an issue on the mobile Obsidian app (iOS) where when I activate your plugin, the sidebar (file explorer, search, etc.) becomes invisible after a restart of the app.
This happens with the default theme and no other plugins installed.
Marc Julian

I just noticed that the workspace plugin might be the problem since it is not supported for mobile.
I guess I had it installed before and there was still a workspace selected in your plugin (and not a note).
Looks like everything is working now.


Update to Rider 251

Fix LaunchSettingsJsonService instance

@Fantoom @ForNeVeR Hello, folks. Thank you for the fix! But I have to revert it, because for now the plugin must target the 243 release in the main branch. When we are ready, I will reapply your fix.


Is there an endpoint or some request that can be performed to check the FCD height?

We would like to monitor the FCD height and make sure it will never get too behind of the LCD.
The endpoints /blocks/latest, /node_info, /cosmos/base/tendermint/v1beta1/node_info, and /cosmos/base/tendermint/v1beta1/blocks/latest only show the node height, but we're not sure on how to monitor the FCD height (without having to check the logs).

All of endpoints you mentioned are not implemented in FCD project, but LCD (Lite Client Daemon) of Cosmos SDK. I recommend you to use /cosmos/base/tendermint/v1beta1/blocks/latest of LCD.


OpenLayers.Protocol.HTTP.callback is not never called

See http://stackoverflow.com/questions/7655191/fixed-strategy-can-it-handle-protocol-errors/
The protocol.callback function in never called

note: not ready to review yet !

Thanks fredj,
http://stackoverflow.com/questions/7655191/fixed-strategy-can-it-handle-protocol-errors/8326458#8326458

I just say that the callback property is not part of the API

see #85


Temporarily disable failed external tests for openj9

To enable sanity.external pipeline, temporarily disable failed external tests

Signed-off-by: Longyu Zhang<EMAIL_ADDRESS>

Test links:
sanity.external: https://ci.adoptopenjdk.net/view/Test_grinder/job/Grinder/1533/


⚠ Bofrost.fr has degraded performance

In f0ec10c, Bofrost.fr (https://www.bofrost.fr) experienced degraded performance:

HTTP code: 200
Response time: 825 ms

Resolved: Bofrost.fr performance has improved in 8c74865 after 6 hours, 26 minutes.


Add baselineIops to disk

This is required by https://github.com/aptible/dashboard.aptible.com/pull/612; uses https://github.com/aptible/api.aptible.com/pull/362
cc @gib @sandersonet

:+1:


docs: add Mian Jing to showcase

Motivation
(Write your motivation here.)
Have you read the Contributing Guidelines on pull requests?
(Write your answer here.)
Test Plan
(Write your test plan here. If you changed any code, please provide us with clear instructions on how you verified your changes work. Bonus points for screenshots and videos!)
Related PRs
(If this PR adds or changes functionality, please take some time to update the docs at https://github.com/facebook/docusaurus, and link to your PR here.)

Thanks

Please sign the CLA so I can merge
It's better to give an English-translated title & description on our main site, even something like "Mian Jing", "Compilation of front-end interview questions", etc.
The source URL doesn't actually point to your source. Do you have the source code to share?

Closing until PR is updated


Use Client defined in dex instead of go-oidc for storing clients

We still use oidc.ClientMetadata and oidc.ClientCredentials but now we can easily add dex-specific stuff to the Client object. Will be very useful for the cross client stuff I'm about to do.

small nit https://github.com/coreos/dex/pull/411#discussion_r60486786
other than that lgtm

fixed your nit - gonna squash now


Array types are illegal for response

I'm not able to provide return type of byte array for a response
<response code="200"><see cref="T:byte[]"/></response>

@VasylSulakov .Net documentation doesn't provide a cleaner way to document arrays and compiler also doesn't compile the /// comments with array into a fully qualified type name. So you will need to document the array type like below

I will be closing this please reopen if you have more questions.


sources: Add explicitSource

Motivation for this change
Edit: PR description slightly outdated, please see the commit message for the current one (which has feedback addressed).
This has the intention to address various issues with the existing
builtins.filterSource and surrounding library functions:

The library functions existing so far are not straightforward to use correctly and are hard to remember. Consequently only few people use them.

Most existing functions are about excluding unwanted files, making various hardcodes (such as .o and .so in cleanSourceFilter) that typically still forget some other unwanted files. The added approach is more about explicitly listing wanted files,
thus being more reliable.

This very frequently results in non-reproducible builds when working from project working trees (as opposed to nixpkgs pkgs builds, which always operate from clean checkouts), with "build", "gen" or similar directories being accidentally included as sources.
It is also a common sources of the dreaded
warning: dumping very large path (> 256 MiB); this may run out of memory
message (and as indicated, bad for performance).

The most common antipattern regarding the above is src = ./..
To prevent it, we need to provide functionality that's straightforward to understand and convenient.

builtins.filterSource f ./. can result in build impurities depending on the basename of the parent directory (see https://github.com/NixOS/nix/issues/1305).
A solution to that is builtins.path. The added function makes its use very convenient.

The existing functions make it difficult to debug what files are included and why.
The added function provides an argument debugEnableTracing, that makes debugging easy.
Output looks like:
trace: myproject: include regular   /home/user/myproject/Setup.hs
trace: myproject: skip    regular   /home/user/myproject/myproject.nix
trace: myproject: skip    directory /home/user/myproject/dist
trace: myproject: include directory /home/user/myproject/images
trace: myproject: include regular   /home/user/myproject/images/image.svg
trace: myproject: include directory /home/user/myproject/src
trace: myproject: include directory /home/user/myproject/src/MyDir
trace: myproject: include regular   /home/user/myproject/src/MyDir/File1.hs
trace: myproject: include regular   /home/user/myproject/src/MyDir/File2.hs

After spending tens of hours of tracking down irreproducible builds resulting from bad src = assignments in various projects, I hope that this function will put an end to it.
Things done

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

[ ] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Assured whether relevant documentation is up to date
[x] Fits CONTRIBUTING.md.
[x] Manual testing of the added functions

Examples:

lib.explicitFilterSource "lib" ./lib { srcDirs = [ ./lib ]; pathComponentExcludes = ["tests"]; }

TODO

[x] Get general feedback on the idea.
[ ] Update nixpkgs manual, adding a section on using nix packages in project working trees, explaining how build files are often accidentally included, and recommending explicitFilterSource as a solution.
[ ] Update nix manual, mentioning in the sections about builtins.filterSource and builtins.path's filter that nixpkgs has convenience functions to handle common situations.

Thanks to @Infinisil @tilpner @srhb @toonn @Myrl for helping with various parts of it.

Very cool! One request from my side would be to ensure the doc comments are formatted in the loose convention understood by nixdoc. This means using multi-line comments for "public" functions (those which should be included in the docs), having a Type: line and putting examples at the end following an Example: line. See #49383 for examples.
We don't include sources.nix in the manual generation yet, but we should and this would help 🙂

wow!
any progress in the last 1.5 months?

any progress in the last 1.5 months?

Not yet, currently bisecting some kernel issues :D

I subscribed to this issue because I ran into confusion with the currently available methods so I'd definitely still like to see progress.

I really want to see something like this to succeed, the missing best practices around filterSource are a giant problem.
A composable design with mostly straightforward semantics would be amazing to have, yet for some reason it seems like it’s very hard to create.

for some reason it seems like it’s very hard to create.

Appearances can be deceiving. I'm thinking a combination of learned helplessness and lack of urgency.
cleanSourceWith is about three years old. Took another 21 months for another contributor to make name settable and then another 6 months for yet another contributor to improve on that and solve the name problem by default. Meanwhile, I suspect everyone assumes that this is "core nixpkgs" or something and infer incorrectly from there. Nixpkgs itself only uses cleanSourceWith indirectly and only in 8 places.

@roberth Splitting the function into reusable components sounds good, but it's a bigger task than I have time to tackle currently.
Would you mind giving a shot at implementing your proposed ideas?

@roberth Splitting the function into reusable components sounds good, but it's a bigger task than I have time to tackle currently.
Would you mind giving a shot at implementing your proposed ideas?

I'm currently prioritizing reviews and maintenance over code contributions for the same reason.

I recently developed a more composable, safer and easier-to-use abstraction for source filtering in a draft PR to Nixpkgs, please take a look, try it out, and give feedback! https://discourse.nixos.org/t/easy-source-filtering-with-file-sets/29117

I will close this as abandoned. You are free to reopen.


Manifest Permissions

Please check all of the platforms you are having the issue on (if platform is not listed, it is not supported)

[] iOS
[X] Android
[] tvOS
[] macOS
[X] .NET Standard
UWP IS NOT SUPPORTED DURING THE BETA PERIOD - ONLY PRs ARE WELCOME FOR NOW

Version of OS(s) listed above with issue
Android version 8.0
Version of Library
6.2.0
Expected Behaviour
After calling:
                var scanner = CrossBleAdapter.Current.Scan().Subscribe(result =>
                {

                });

app should start scanning and detect devices.
Actual Behavior
project fails with this error in output (in Bold):
08-29 13:27:16.421 D/OpenGLRenderer(18475): HWUI GL Pipeline
08-29 13:27:16.446 D/Mono    (18475): Assembly Ref addref ReactiveBLE[0x79a5091e00] -> Plugin.BluetoothLE[0x79a5091d00]: 2
Resolved pending breakpoint at 'ReactBLE.cs:16,1' to void ReactiveBLE.ReactBLE.<>c.b__0_0 (Plugin.BluetoothLE.IScanResult result) [0x00001].
08-29 13:27:16.486 D/Mono    (18475): Assembly Ref addref ReactiveBLE[0x79a5091e00] -> System.Reactive[0x79a5091f00]: 2
Resolved pending breakpoint at 'ReactBLE.cs:14,1' to void ReactiveBLE.ReactBLE.ScanForDevices () [0x00002].
Resolved pending breakpoint at 'ReactBLE.cs:20,1' to void ReactiveBLE.ReactBLE.ScanForDevices () [0x00036].
08-29 13:31:39.431 D/Mono    (18475): Assembly Ref addref Plugin.BluetoothLE[0x79a5091d00] -> System.Reactive[0x79a5091f00]: 3
08-29 13:31:39.439 D/Mono    (18475): Assembly Ref addref Plugin.BluetoothLE[0x79a5091d00] -> System.Core[0x79a4f32780]: 7
08-29 13:31:39.455 D/BluetoothManager(18475): getDevicesMatchingConnectionStates
08-29 13:31:39.476 D/Mono    (18475): DllImport searching in: '__Internal' ('(null)').
08-29 13:31:39.476 D/Mono    (18475): Searching for 'java_interop_jnienv_call_boolean_method'.
08-29 13:31:39.476 D/Mono    (18475): Probing 'java_interop_jnienv_call_boolean_method'.
08-29 13:31:39.477 D/Mono    (18475): Found as 'java_interop_jnienv_call_boolean_method'.
Thread started:  #3
08-29 13:31:39.654 D/BluetoothAdapter(18475): isLeEnabled(): ON
08-29 13:31:39.659 D/BluetoothLeScanner(18475): onScannerRegistered() - status=0 scannerId=12 mScannerId=0
08-29 13:31:39.665 W/Binder  (18475): Caught a RuntimeException from the binder stub implementation.
08-29 13:31:39.665 W/Binder  (18475): java.lang.SecurityException: Need ACCESS_COARSE_LOCATION or ACCESS_FINE_LOCATION permission to get scan results
08-29 13:31:39.665 W/Binder  (18475): 	at android.os.Parcel.readException(Parcel.java:1942)
08-29 13:31:39.665 W/Binder  (18475): 	at android.os.Parcel.readException(Parcel.java:1888)
08-29 13:31:39.665 W/Binder  (18475): 	at android.bluetooth.IBluetoothGatt$Stub$Proxy.startScan(IBluetoothGatt.java:918)
08-29 13:31:39.665 W/Binder  (18475): 	at android.bluetooth.le.BluetoothLeScanner$BleScanCallbackWrapper.onScannerRegistered(BluetoothLeScanner.java:431)
08-29 13:31:39.665 W/Binder  (18475): 	at android.bluetooth.le.IScannerCallback$Stub.onTransact(IScannerCallback.java:56)
08-29 13:31:39.665 W/Binder  (18475): 	at android.os.Binder.execTransact(Binder.java:674)
08-29 13:31:41.715 I/Adreno  (18475): QUALCOMM build                   : 7142022, Ib5823dd10c
08-29 13:31:41.715 I/Adreno  (18475): Build Date                       : 06/23/17
08-29 13:31:41.715 I/Adreno  (18475): OpenGL ES Shader Compiler Version: EV<IP_ADDRESS>
08-29 13:31:41.715 I/Adreno  (18475): Local Branch                     : O11A
08-29 13:31:41.715 I/Adreno  (18475): Remote Branch                    :
08-29 13:31:41.715 I/Adreno  (18475): Remote Branch                    :
08-29 13:31:41.715 I/Adreno  (18475): Reconstruct Branch               :
08-29 13:31:41.715 I/vndksupport(18475): sphal namespace is not configured for this process. Loading /vendor/lib64/hw/gralloc.msm8994.so from the current namespace instead.
08-29 13:31:41.741 I/Adreno  (18475): PFP: 0x00000000, ME: 0x00000000
08-29 13:31:41.758 I/OpenGLRenderer(18475): Initialized EGL, version 1.4
08-29 13:31:41.758 D/OpenGLRenderer(18475): Swap behavior 2
08-29 13:31:41.808 D/Mono    (18475): DllImport searching in: '__Internal' ('(null)').
08-29 13:31:41.808 D/Mono    (18475): Searching for 'java_interop_jnienv_call_nonvirtual_float_method_a'.
08-29 13:31:41.808 D/Mono    (18475): Probing 'java_interop_jnienv_call_nonvirtual_float_method_a'.
08-29 13:31:41.808 D/Mono    (18475): Found as 'java_interop_jnienv_call_nonvirtual_float_method_a'.
08-29 13:31:41.836 I/vndksupport(18475): sphal namespace is not configured for this process. Loading /vendor/lib64/hw/gralloc.msm8994.so from the current namespace instead.
Here is my Manifest:
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android" android:versionCode="1" android:versionName="1.0" package="com.companyname.ReactiveBLE" android:installLocation="auto">
	<uses-sdk android:minSdkVersion="19" android:targetSdkVersion="26" />
	<uses-permission android:name="android.permission.BLUETOOTH" />
	<uses-permission android:name="android.permission.BLUETOOTH_ADMIN" />
	<uses-permission android:name="android.permission.ACCESS_COARSE_LOCATION" />
	<uses-permission android:name="android.permission.ACCESS_FINE_LOCATION" />
	<application android:label="ReactiveBLE.Android"></application>
</manifest>

I h
I am following the usage guide on this page:
https://github.com/aritchie/bluetoothle
This is with a new project with Xamarin.Forms referenced.
Thank you for your support.

You still need to request permission to use the location services which is external to this library.  You can use something like permission plugin

I think I'm having the same issue here. Why would I need to request permission for location just to to get bluetooth to work?
In the "SETUP" guid it says "" regarding the permission.
I'm not interested in either the name or the address. Is there any way to do this without the user having to allow the location permission first?
Also, please make this more clear to understand in the SETUP guide. This should be part of the documentation imho

No - this is simply the way android permissions about Bluetooth work due privacy reasons.
As for docs, if you don't like them, please send a PR.  I'm not trying to "sell" this library.  If it adds value to you, great, if it doesn't, great.  I do docs when I feel like it which is rarely since it isn't exactly fun for me.


add comment for CodeGuru Review

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I made mistake, Sorry for that.


download.sh - detect gtar if macOS, add timestamp

macOS tar does not have the same functionality of GNU tar, so I've had to install the latter seprately using Homebrew, which provides gtar.  Our bash script needs to detect if it is being run on a macOS platform and then call gtar instead of tar.
the tarball provided by VirusSeq contains a date and time stamp that needs to be extracted and applied to our output filenames, i.e., instead of writing virusseq.fasta.xz we should be writing virusseq.2022-04-11T20_03_59.fasta.xz

Ran into following error running on Ubuntu 18.04:
tar: Pattern matching characters used in file names
tar: Use --wildcards to enable pattern matching, or --no-wildcards to suppress this warning
tar: files-archive-592f95e0-6a4f-4ad6-bbe9-ab19da5cc663.tsv[0]: Not found in archive
tar: Exiting with failure status due to previous errors

Here is the bash cmd lines but I can t get the form $filenames[0] to make what it is supposed to make on my bash
#get the good tar command depending of bash or macos
tarcmd=$(case "$(uname -s)" in Darwin)  echo 'gtar';;  Linux) echo 'tar';; esac)
#get the timestamp for file name
datestamp=$(date --utc +%Y-%m-%dT%H_%M_%S)
# scan tarball for filenames
filenames=$($tarcmd -ztf virusseq.tar.gz)
# stream FASTA data into xz-compressed file
$tarcmd -axf virusseq.tar.gz -O $filenames[0] | xz > virusseq.$datestamp.fasta.xz
# stream metadata into gz-compressed file
$tarcmd -axf virusseq.tar.gz -O $filenames[1] | gzip > virusseq.$datestamp.metadata.tsv.gz
# delete tarball
rm virusseq.tar.gz

I think the script is ok now, I did made the change on a branch and pull the branch in dev, could you test it on mac OS ?

If anybody can test this on a mac we could close the issue I guess

art@Wernstrom data_needed % bash download.sh
download.sh: line 2: syntax error near unexpected token `;;'
download.sh: line 2: `tarcmd=$(case "$(uname -s)" in Darwin)  echo 'gtar';;  Linux) echo 'tar';; esac)'

I did change the case statement by an if statement  and I don t find back this version on download.sh

Resolved


fog doesnt render

fabric 0.14.21 hold that chunk v2.0.1 1.20.1

Does the fog render if you start the game with all the same mods except for Hold That Chunk?

yes by itself it doesnt render the fog

This mod doesn't touch rendering at all, so this doesn't make sense to me.
What setting do you have for Ignore Server Render Distance? And how high is your Render Distance? What other client mods are you using?

sorry this was a month ago and i dont know how to reproduce it anymore because it looks fine

I doubt it was caused by Hold That Chunk to begin with.


Add overlord monitor for monitoring leadership status.

This ask is that a Monitor be put in place on the overlord (and probably coordinator) that reports the leadership status of that part of the service.

That should be there already.
/leader
On Mon, Jan 9, 2017 at 4:34 PM, Charles Allen<EMAIL_ADDRESS>wrote:

This ask is that a Monitor be put in place on the overlord (and probably
coordinator) that reports the leadership status of that part of the service.
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@drcrallen do you mean a separate monitor vs an http endpoint? what's the use case?

I mean a com.metamx.metrics.Monitor that emits information about if the node is currently leader. We're seeing some leadership issues when the zk connection has problems. And having information about if a node thinks it is leader would have been helpful.