add CITATION.cff file

Add a CITATION.cff file with

title
authors
affiliations

so that the Zenodo archive contains the same metadata as the JOSS paper #68 .

Potentially helpful information when I did this recently

https://github.com/alchemistry/alchemlyb/issues/394
https://github.com/alchemistry/alchemlyb/pull/395

Closed by #68


Some fixes and additions

remove fann BR, deprecated in favor of torch
add gd support
remove gmime BR, it's unused
add libcurl, enables the use of UCL URL includes
add openblas support for enhanced regex performance
switch to pcre2 for enhanced regex performance
drop some unused defines in the cmake call

Some background:

Since Rspamd 1.7, libfann module is deprecated in honor of Lua Torch.

https://rspamd.com/doc/modules/neural.html
but that looks like it's going to change with the next release again: https://github.com/rspamd/rspamd/issues/2942

this is awesome, thank you very much!


Error in the rename script

Hi thank you for your excellent work, I am porting all your code to tf2 and cleaning it up a little bit. when running rename model I find the following error
in line 12
netG = NetInfo('netG')
is missing a df argument in NetInfo
thank you

Hi can you please share the files you have for this project. The maintainer @nothinglo is not updating the links and all of them are broken.
Thanks @MrRobot2211

Hi,
When I run the TF.py in the "[Online_Demo_Models]_Deep-Photo-Enhancer/LPGAN_exp_G3_736" file, I face this error:
Shapes (2, 1, 32, 32, 128) and () are incompatible
in line: netG_test_output1 = model(netG, test_df.input1, False, netG_act_o, is_first=True)
Would you mind helping me with it? Thank you in advance.


Fetch provisioners list from stake contract only if the list is updated

fixes #1479

Codecov Report
Base: 40.18% // Head: 40.15% // Decreases project coverage by -0.02% :warning:

Coverage data is based on head (2235b70) compared to base (57c6bbd).
Patch coverage: 21.32% of modified lines in pull request are covered.

Additional details and impacted files
@@            Coverage Diff             @@
##           master    #1480      +/-   ##
==========================================
- Coverage   40.18%   40.15%   -0.03%
==========================================
  Files         147      147
  Lines        9651     9724      +73
==========================================
+ Hits         3878     3905      +27
- Misses       5144     5194      +50
+ Partials      629      625       -4

Impacted Files
Coverage Δ

pkg/config/genesis/config.go
0.00% <ø> (ø)

pkg/config/genesis/presets.go
69.23% <ø> (ø)

...nsensus/blockgenerator/candidate/blockgenerator.go
0.00% <0.00%> (ø)

...core/consensus/blockgenerator/candidate/genesis.go
0.00% <0.00%> (ø)

...kg/core/consensus/blockgenerator/candidate/mock.go
0.00% <0.00%> (ø)

pkg/core/data/ipc/transactions/fixtures.go
13.76% <0.00%> (-0.21%)
:arrow_down:

pkg/core/data/ipc/transactions/provider.go
0.00% <0.00%> (ø)

pkg/gql/query/blocks.go
63.22% <0.00%> (ø)

pkg/gql/query/mempool.go
30.00% <0.00%> (ø)

pkg/gql/query/types.go
13.79% <ø> (ø)

... and 12 more

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report at Codecov.
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Scaling of parent entity not effecting child collider

Hello! Just wanted to say I think this repository is really cool but I have found a bug.
Basically, colliders are not effected by the scale transformation of a parent object, even though meshes and everything else are.
Here is a minimal, but still long, example
Cargo.toml:
[package]
name = "bevy_xpbd_scaling_bug"
version = "0.1.0"
edition = "2021"

[dependencies]
bevy = "0.12.1"
bevy_xpbd_3d = "0.3.2"

src/main.rs:
use bevy::prelude::*;
use bevy_xpbd_3d::prelude::*;

fn spawn_objects(
    mut commands: Commands,
    mut materials: ResMut<Assets<StandardMaterial>>,
    mut meshes: ResMut<Assets<Mesh>>,
    mut animations: ResMut<Assets<AnimationClip>>,
) {
    // Spawn camera looking at origin
    commands.spawn((Camera3dBundle {
        transform: Transform::from_xyz(10., 3., 5.).looking_at(Vec3::ZERO, Vec3::Y),
        ..default()
    },));

    // Spawn static 2 by 2 plane collider with 2 by 2 mesh
    let collider = commands
        .spawn((
            Collider::cuboid(2.0, 0.1, 2.0),
            RigidBody::Static,
            PbrBundle {
                mesh: meshes.add(shape::Plane {size: 2.0, subdivisions: 5}.into()),
                material: materials.add(StandardMaterial {
                    emissive: Color::rgb(1., 1., 0.),
                    ..default()
                }),..default()})).id();

    // Spawn empty object and add collider as child
    // Also insert animation that scales it
    let name = Name::new("name");
    commands
        .spawn(SpatialBundle::default())
        .insert(name.clone())
        .add_child(collider)
        .insert({
            let mut player = AnimationPlayer::default();
            let mut animation = AnimationClip::default();
            animation.add_curve_to_path(
                EntityPath {parts: vec![name.clone()]},
                VariableCurve {
                    keyframe_timestamps: vec![0.0, 5.0, 10.0, 100000.0],
                    keyframes: Keyframes::Scale(vec![
                        Vec3::new(1.0, 1.0, 1.0),
                        Vec3::new(5.0, 5.0, 5.0),
                        Vec3::new(2.0, 2.0, 2.0),
                        Vec3::new(2.0, 2.0, 2.0),
                    ]),
                },
            );
            player.play(animations.add(animation));
            player
        });
}

fn main() {
    App::new()
        .add_plugins((DefaultPlugins, PhysicsPlugins::default(), PhysicsDebugPlugin::default()))
        .add_systems(Startup, spawn_objects)
        .run();
}

If you run the example, there is a plane in the middle of the screen that initially starts with a mesh and a collider having the same size. The empty parent of this plane then does a scale animation. The mesh of the child changes in size, but the collider of the child does not.
Photo of the debug render:

I originally experienced this when I had a box with an open top made of 5 colliders that were children of an empty entity. When I scaled the parent, the positions of the colliders changed so that they were still in line with the walls, but their size did not grow to fill the edges.
I'm willing to submit a pull request to fix this but if someone could give me some guidance on where to look that would be nice. Or if someone knows how to fix it already.

It's probably linked to #288
If you add a RigidBody to the entity, the collider is scaling with the entity, otherwise all transforms on the entity won't be applied to the collider.
It's not only scale, but position and rotation as well.
A workaround for me was to add a static RigidBody to the entity.

Hmmm this does not fix the issue for me. I added RigidBody::Static to the parent element and it still did not scale appropriately. However the example does work if I change Keyframes::Scale to Keyframes::Translation, whether a RigidBody is present on the parent or not. So this seems to only affect scale and it does not depend on the RigidBody of the parent. So due to this experimentation, I don't think the issues are linked.

Can confirm that the reported workaround does not work for me either

I'm having a somewhat similar issue, except that my entity is top level (I guess)
screencast of the issue
https://github.com/user-attachments/assets/24eff079-700b-4c95-97c8-d13f91e3d937
code:
use crate::dev_tools::editor::{inverse_transform, Polyline, Vertex};
use avian2d::prelude::{Collider, ColliderTransform, IntoCollider};
use bevy::prelude::*;

// scale is messing things up here a little, looks like when collider is recreated it is not scaled until transform is changed

// update polyline vertices according to control positions
pub fn sync_polyline_control_vertices(
    mut commands: Commands,
    mut polylines: Query<(&mut Polyline, &Transform)>,
    controls: Query<(&Vertex, &Parent, &Transform), Changed<Transform>>,
) {
    for (vertex, parent, transform) in controls.iter() {
        let Ok((mut polyline, polyline_transform)) = polylines.get_mut(parent.get()) else {
            continue;
        };

        let Some(local_coords) = polyline.vertices.get_mut(vertex.0 as usize) else {
            continue;
        };

        *local_coords = transform.translation.truncate();
    }
}

// recreate collider when the polyline is changed
pub fn sync_polyline_colliders(
    mut commands: Commands,
    mut polylines: Query<(&Polyline, Entity, &Transform), Changed<Polyline>>,
) {
    for (polyline, entity, p_transform) in polylines.iter_mut() {
        // todo: file an issue, to avian
        if polyline.len() > 1 {
            let mut collider = polyline.collider();

            commands.entity(entity).insert(polyline.collider());
        }
    }
}

every time the new collider is created it's not scaled until the entity's transform is changed. I tried setting collider.set_scale(p_transform.scale.truncate()), but that didn't help.

Ah, forget it, I'm dumb. In case you wondering:
            let mut collider = polyline.collider();

            commands.entity(entity).insert(polyline.collider());

should be:
            let mut collider = polyline.collider();
            collider.set_scale(p_transform.scale.xy(), 10);

            // todo: try set_shape instead of insert
            commands.entity(entity).insert(collider);

But I believe the right approach would be to use Collider::set_shape, It would not require commands for example.

@Jondolf I'm pretty sure you fixed this a while ago, sans the case for negative scales, but those have an own issue.


Add CentOS7 py34 case as allow_failures.

As a temporary workflow.
Related to https://github.com/junaruga/rpm-py-installer/issues/199 .

https://travis-ci.org/junaruga/rpm-py-installer/jobs/570989137#L833
Weird. CentOS7 python 34 case is okay now. python34-devel was installed successfully.

Current master branch's CI was succeeded after rebuilding. I close this PR.
https://travis-ci.org/junaruga/rpm-py-installer/builds/570575968


Review all Codeplex links/mentions and update where needed

Review all Codeplex links/mentions and update where needed #3579
Running PR to port all references to CodePlex to Github/wherever they live now

@isaac2004,
Thanks for having already signed the Contribution License Agreement. Your agreement was validated by .NET Foundation. We will now review your pull request.
Thanks,
.NET Foundation Pull Request Bot

This page references Database Publishing Services which is not on GitHub
https://docs.microsoft.com/en-us/aspnet/web-forms/overview/older-versions-getting-started/deploying-web-site-projects/deploying-a-database-cs

Tailspin project not on GitHub
https://docs.microsoft.com/en-us/aspnet/web-forms/overview/older-versions-getting-started/tailspin-spyworks/index

Also references to Issues in CodePlex, how should they be handled?
https://docs.microsoft.com/en-us/aspnet/web-pages/overview/getting-started/introducing-razor-syntax-c
Link above "Variables" section

Http.sys Manager does not exist on GitHub
http://httpsysmanager.codeplex.com/

@Rick-Anderson @scottaddie I have commited all references to CodePlex that I can easily do, here are some metrics of remaining references

157 References in 40 files to CodePlex

Here are details on references

38 References in 11 files to Work Items in CodePlex (mostly WebStack)
7 References in 5 files to Release info in CodePlex (Katana as AspNet)
97 References in 22 files to Source Controle in Codeplex (readme files, code snippets, etc)

These are references that only exist in CodePlex, let me know next steps.

Also references to Issues in CodePlex, how should they be handled?

Link above Variables
Razor has limitations on nested blocks of C#. For more information see Named C# Variables and Nested Blocks Generate Broken Code
Leave those for now.

This page references Database Publishing Services which is not on GitHub

Even better, if your web host provider supports Microsoft s Database Publishing Services  you can have the script generated by the Database Publishing Wizard automatically executed on the database server on your behalf.
Leave that for now. CodePlex won't go away, it's just read-only.

Http.sys Manager does not exist on GitHub

http://httpsysmanager.codeplex.com/
Can't use use the RO codeplex link?

@Rick-Anderson I won't touch the issues references, what about Release Info and Code Snippets?

@isaac2004   these?

7 References in 5 files to Release info in CodePlex (Katana as AspNet)
97 References in 22 files to Source Controle in Codeplex (readme files, code snippets, etc)

Can you provide links to specific examples? Are there references in An Overview of Project Katana that need to be fixed?

@Rick-Anderson
Examples of Release References

Halfway down page
NuGet 2.8.1 Section

Examples of Source Code References

All Samples here
Multiple Code Samples Here

I think it is probably safe to leave these here as they are just references to code, as long as the code never gets removed from CodePlex

@isaac2004  awesome work. Thanks for doing this.


Conversions May Be Inaccurate

Need to write minimum checks for every converter implementation like:

BaseUnit -> EveryUnit and
EveryUnit -> BaseUnit

For instance:
        [TestMethod()]
        public void kg_lb() {
            converter = new MassConverter("kg", "lbs");
            double valL = 1;
            double valR = 2.20462;

            Assert.AreEqual(valR, converter.LeftToRight(valL, 5));
            Assert.AreEqual(valL, converter.RightToLeft(valR));
        }

All existing Converters are now tested as much as required.
#4 covers any future improvements to these tests.


Feature Request: Batch rendering for autocomplete for large set of data

If the list has more than about 500 entries the rendering hangs (It will eventual show up, but a bit laggy). Large drop downs often happen when dealing with lists of people. Is it possible to render in groups. Like only showing the first hundred then more will be rendered if the user scrolls down near bottom.

Not sure to totally understand the request here, the 500+ entries is before or after the 'filtering' part of the auto-completion ?
If you have 500+ results on an 'autocomplete search', does implementing a 'infinite scrolling' logic to handle very big matching results is really worthy when, I think, most of the users will type other letters into the search text field to narrow down the possibility, and probably very few will start scrolling into the 500+ list.
Couldn't that situation may be handled into the fetch attribute to limit the numbers of results to a pre-determined acceptable numbers for your use case and trim off the rest of the results ?
Maybe setting up the minLength attribute to an higher value may help as well.

Yeah. The max out probably makes sense. Thanks.


Stubbed implementation of GetLightClientBootstrap

PR Description
This PR is a base implementation of GetLightClientBootstrap with return 501;. It is intended to validate the interface.
Fixed Issue(s)
fixes #6287

Documentation

[x] I thought about documentation and added the doc-change-required label to this PR if updates are required.

Changelog

[x] I thought about adding a changelog entry, and added one if I deemed necessary.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

@rolfyone @ajsutton Addressed comments & outstanding todos, do you mind taking another look?
The acceptance test failure is new. Unable to replicate locally, taking another look.

Oh I think that acceptance test failure is likely related to the config backwards compatibility issue as well. It's running the latest version of the validator client (with these changes) against an old release of the beacon node and it's failing to start, likely because of the incorrect config.
To run locally you'll likely need to run ./gradlew distDocker to build the docker images from the latest code including your changes (otherwise it likely winds up running the latest version from master without your changes).  Then you can run the acceptance test in IntelliJ like a normal test.
./gradlew acceptanceTest should automatically build the docker image but it runs all the tests so takes a fair while which is less useful for debugging stuff.

@ajsutton Recreated locally & pushed up a fix.


Protos for RBAC support.

Added protos to support Role Based Access Control in Envoy.
Also removed existing auth.proto because the new RBAC proto is a replacement of it.
Ealier discussions at
https://github.com/envoyproxy/data-plane-api/pull/586.
Signed-off-by: Limin Wang<EMAIL_ADDRESS>

@rodaine @mattklein123 @danielhochman @htuch @lizan @yangminzhu @JimmyCYJ @wora @wenchenglu

@htuch @wora this is pretty much ready to go from my perspective with a bit more clarification. Can you take a look?

@liminw also, you will need to fix DCO. Please check your sign-off email against the email attached to your account. If you need to rebase/force-push that's fine.


Why is InsessionLatency used for assessment of Monthly activity?

What is the logic behind using InSessionLatency as the defining metric for Monthly workspace activity? What does that metric actually measure?

I see that it does RTT to the client, but what if the cilent is using a PCOIP zero client?

https://github.com/awslabs/workspaces-cost-optimizer/commit/4857119e37b3567f950934751271a8a4cb45ae21#diff-3d526d6575aa9ba2e51771a119f16f5aR87
Comment might explain it

To expand on this, I've just realised that the InSessionLatency metric is only recorded when the user uses the Workspaces client (https://docs.aws.amazon.com/workspaces/latest/adminguide/cloudwatch-metrics.html), so it's not just those who use the PCOIP zero client, it's also those who use the web access - https://clients.amazonworkspaces.com/webclient

We have updated the metric to "UserConnected" for calculation of billable hours. Please deploy the latest version of our solution to get the changes.


no 2.1.0-rc1 or 2.1.0-rc2 in dockerhub only 2.0.0

System information

TensorFlow version: 2.1.0

Describe the problem
Tensorflow/tensorflow does not list 2.1.0-rc1 or rc2 in the list of available tags.
These are available on colab but somehow did not make it to dockerhub.
Provide the exact sequence of commands / steps that you executed before running into the problem
https://hub.docker.com/r/tensorflow/tensorflow/tags/?page=1&name=2.1.0
observe no tags
Any other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

I tried to build the docker from git but get the following error
docker build --build-arg USE_PYTHON_3_NOT_2=true --build-arg TF_PACKAGE_VERSION=2.1.0-rc2  -f ./dockerfiles/gpu.Dockerfile -t tf .
docker run --gpus all -it tf
python3
import tensorflow as tf
2019-12-26 14:45:30.126243: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libnvinfer.so.6
2019-12-26 14:45:30.126620: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvrtc.so.10.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/extras/CUPTI/lib64
2019-12-26 14:45:30.126633: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.

Trying various things to fix the above, but no success so far.

@johngrabner Thanks for your report. #35367 should have fixed this -- it seems like the images were never updated to support CUDA 10.1, which TensorFlow 2.1 requires. Can you try git pull?
I'm waiting on some updates to our internal CI to be able to push the new images. Hopefully, they'll be available before the end of the day.

Looks like image got uploaded
2.1.0rc2-gpu
docker pull tensorflow/tensorflow:2.1.0rc2-gpu
Last updated10 minutes agobytensorflowpackages

Trying it out now

I think it is working, but there is a warning on the second line
2019-12-26 21:53:03.304048: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libnvinfer.so.6
2019-12-26 21:53:03.304418: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvrtc.so.10.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
2019-12-26 21:53:03.304431: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2019-12-26 21:53:08.633799: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-26 21:53:08.656459: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.656893: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 21:53:08.656950: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 21:53:08.657003: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 21:53:08.658244: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 21:53:08.658569: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 21:53:08.659846: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 21:53:08.660518: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 21:53:08.660557: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 21:53:08.660628: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.661080: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.661436: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 21:53:08.661693: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-12-26 21:53:08.682339: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-12-26 21:53:08.682953: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x87addb0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-26 21:53:08.682968: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2019-12-26 21:53:08.760651: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.761034: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x8159cc0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-26 21:53:08.761048: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
2019-12-26 21:53:08.761157: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.761519: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 21:53:08.761548: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 21:53:08.761559: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 21:53:08.761569: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 21:53:08.761579: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 21:53:08.761593: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 21:53:08.761607: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 21:53:08.761642: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 21:53:08.761696: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.762104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.762428: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 21:53:08.762457: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 21:53:08.931909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-26 21:53:08.931936: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102]      0
2019-12-26 21:53:08.931942: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0:   N
2019-12-26 21:53:08.932156: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.932582: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 21:53:08.932950: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8288 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)

It there a standard test you normally run.
The sample code I am using is not happy with rc2
sudo docker exec -it 282c2ff49852 /bin/bash

___  /________________________________  /  /______      __
__  /  _  _ _  __ _  /  __ _  /  /   __  /  __ _ | /| / /
_  /   /  /  / / /(  )/ // /  /   _  __/   _  / / // / |/ |/ /
//    ___/// //// _///    //      //  _/__/|__/
You are running this container as user with ID 1000 and group 1000,
which should map to the ID and group for your user on the Docker host. Great!
tf-docker /tf > python3
Python 3.6.9 (default, Nov  7 2019, 10:44:02)
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf
2019-12-26 22:10:33.702129: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libnvinfer.so.6
2019-12-26 22:10:33.703898: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvrtc.so.10.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
2019-12-26 22:10:33.703956: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
print(tf.version)
2.1.0-rc2
device_lib.list_local_devices()
Traceback (most recent call last):
File "", line 1, in
NameError: name 'device_lib' is not defined
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Traceback (most recent call last):
File "", line 1, in
AttributeError: module 'tensorflow' has no attribute 'Session'
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
2019-12-26 22:14:23.959816: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-12-26 22:14:24.005268: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-12-26 22:14:24.006412: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x596fee0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-26 22:14:24.006426: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2019-12-26 22:14:24.008570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-26 22:14:24.122916: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:14:24.123297: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x59a2520 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-26 22:14:24.123312: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
2019-12-26 22:14:24.123431: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:14:24.123737: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 22:14:24.123767: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 22:14:24.123791: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 22:14:24.141434: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 22:14:24.144722: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 22:14:24.189225: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 22:14:24.196701: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 22:14:24.196859: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 22:14:24.197215: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:14:24.199081: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:14:24.200805: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 22:14:24.201544: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 22:14:24.827415: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-26 22:14:24.827445: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102]      0
2019-12-26 22:14:24.827451: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0:   N
2019-12-26 22:14:24.827988: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:14:24.828372: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:14:24.828708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/device:GPU:0 with 9441 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation:<PHONE_NUMBER>4756662951
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit:<PHONE_NUMBER>4
locality {
}
incarnation:<PHONE_NUMBER>867512922
physical_device_desc: "device: XLA_CPU device"
, name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit:<PHONE_NUMBER>4
locality {
}
incarnation:<PHONE_NUMBER>9365383547
physical_device_desc: "device: XLA_GPU device"
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit:<PHONE_NUMBER>
locality {
bus_id: 1
links {
}
}
incarnation:<PHONE_NUMBER>3523866116
physical_device_desc: "device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5"
]
exit
Use exit() or Ctrl-D (i.e. EOF) to exit
exit()
tf-docker /tf >
tf-docker /tf > cd /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/
tf-docker /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src > python main.py --source=bentham --train
2019-12-26 22:15:29.610690: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libnvinfer.so.6
2019-12-26 22:15:29.610942: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvrtc.so.10.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
2019-12-26 22:15:29.610972: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2019-12-26 22:15:35.159777: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-26 22:15:35.197746: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.198250: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 22:15:35.198296: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 22:15:35.198384: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 22:15:35.199606: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 22:15:35.199860: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 22:15:35.201211: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 22:15:35.201923: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 22:15:35.201963: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 22:15:35.202050: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.202537: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.203006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 22:15:35.203418: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-12-26 22:15:35.229352: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-12-26 22:15:35.229900: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x894c1f0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-26 22:15:35.229913: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2019-12-26 22:15:35.305420: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.305824: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x88bd8d0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-26 22:15:35.305839: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
2019-12-26 22:15:35.306028: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.306367: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 22:15:35.306395: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 22:15:35.306405: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 22:15:35.306417: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 22:15:35.306430: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 22:15:35.306447: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 22:15:35.306484: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 22:15:35.306507: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 22:15:35.306572: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.306891: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.307176: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 22:15:35.307206: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 22:15:35.477274: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-26 22:15:35.477303: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102]      0
2019-12-26 22:15:35.477309: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0:   N
2019-12-26 22:15:35.477490: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.477903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 22:15:35.478271: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9440 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
Model: "model"

Layer (type)                 Output Shape              Param #
input (InputLayer)           [(None, 1024, 128, 1)]    0

conv2d (Conv2D)              (None, 512, 64, 16)       160

p_re_lu (PReLU)              (None, 512, 64, 16)       16

batch_normalization (BatchNo (None, 512, 64, 16)       112

full_gated_conv2d (FullGated (None, 512, 64, 16)       4640

conv2d_1 (Conv2D)            (None, 512, 64, 32)       4640

p_re_lu_1 (PReLU)            (None, 512, 64, 32)       32

batch_normalization_1 (Batch (None, 512, 64, 32)       224

full_gated_conv2d_1 (FullGat (None, 512, 64, 32)       18496

conv2d_2 (Conv2D)            (None, 256, 16, 40)       10280

p_re_lu_2 (PReLU)            (None, 256, 16, 40)       40

batch_normalization_2 (Batch (None, 256, 16, 40)       280

full_gated_conv2d_2 (FullGat (None, 256, 16, 40)       28880

dropout (Dropout)            (None, 256, 16, 40)       0

conv2d_3 (Conv2D)            (None, 256, 16, 48)       17328

p_re_lu_3 (PReLU)            (None, 256, 16, 48)       48

batch_normalization_3 (Batch (None, 256, 16, 48)       336

full_gated_conv2d_3 (FullGat (None, 256, 16, 48)       41568

dropout_1 (Dropout)          (None, 256, 16, 48)       0

conv2d_4 (Conv2D)            (None, 128, 4, 56)        21560

p_re_lu_4 (PReLU)            (None, 128, 4, 56)        56

batch_normalization_4 (Batch (None, 128, 4, 56)        392

full_gated_conv2d_4 (FullGat (None, 128, 4, 56)        56560

dropout_2 (Dropout)          (None, 128, 4, 56)        0

conv2d_5 (Conv2D)            (None, 128, 4, 64)        32320

p_re_lu_5 (PReLU)            (None, 128, 4, 64)        64

batch_normalization_5 (Batch (None, 128, 4, 64)        448

max_pooling2d (MaxPooling2D) (None, 128, 2, 64)        0

reshape (Reshape)            (None, 128, 128)          0

bidirectional (Bidirectional (None, 128, 256)          198144

time_distributed (TimeDistri (None, 128, 128)          32896

bidirectional_1 (Bidirection (None, 128, 256)          198144

time_distributed_1 (TimeDist (None, 128, 98)           25186
Total params: 692,850
Trainable params: 691,570
Non-trainable params: 1,280

Train for 545 steps, validate for 85 steps
Epoch 1/1000
2019-12-26 22:15:43.691246: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 22:15:44.122500: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 22:15:45.384099: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-12-26 22:15:45.395668: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-12-26 22:15:45.396141: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node model/conv2d/Conv2D}}]]
[[loss/time_distributed_1_loss/Log/_98]]
2019-12-26 22:15:45.396203: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node model/conv2d/Conv2D}}]]
1/545 [..............................] - ETA: 1:01:25WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Early stopping conditioned on metric val_loss which is not available. Available metrics are:
WARNING:tensorflow:Reduce LR on plateau conditioned on metric val_loss which is not available. Available metrics are: lr
1/545 [..............................] - ETA: 1:02:00Traceback (most recent call last):
File "main.py", line 155, in
verbose=1)
File "/home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/network/model.py", line 175, in fit
use_multiprocessing=use_multiprocessing, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training.py", line 819, in fit
use_multiprocessing=use_multiprocessing)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py", line 342, in fit
total_epochs=epochs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py", line 128, in run_one_epoch
batch_outs = execution_function(iterator)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2_utils.py", line 98, in execution_function
distributed_function(input_fn))
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/def_function.py", line 568, in call
result = self._call(*args, **kwds)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/def_function.py", line 632, in _call
return self._stateless_fn(*args, **kwds)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 2363, in call
return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 1611, in _filtered_call
self.captured_inputs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 1692, in _call_flat
ctx, args, cancellation_manager=cancellation_manager))
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 545, in call
ctx=ctx)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/execute.py", line 67, in quick_execute
six.raise_from(core._status_to_exception(e.code, message), None)
File "", line 3, in raise_from
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
(0) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node model/conv2d/Conv2D (defined at /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/network/model.py:175) ]]
[[loss/time_distributed_1_loss/Log/_98]]
(1) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node model/conv2d/Conv2D (defined at /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/network/model.py:175) ]]
0 successful operations.
0 derived errors ignored. [Op:__inference_distributed_function_17754]
Function call stack:
distributed_function -> distributed_function
2019-12-26 22:15:45.548644: W tensorflow/core/kernels/data/generator_dataset_op.cc:103] Error occurred when finalizing GeneratorDataset iterator: Cancelled: Operation was cancelled

is there a way for me to pull down #35434 and see if it fixes the issue?

I don't think that fix is sufficient.
I added the same lines you added but to my dockerfile
FROM tensorflow/tensorflow:2.1.0rc2-gpu-py3-jupyter

# to see if  #35434 fixes the issues
ARG CUDA=10.1
RUN apt-get update && apt-get install -y --no-install-recommends \
        cuda-nvrtc-${CUDA/./-} \
        cuda-nvrtc-dev-${CUDA/./-}

# stuff i need for the app
RUN pip install autopep8==1.4.4
RUN pip install editdistance==0.5.3
RUN pip install flake8==3.7.9
RUN pip install kaldiio==2.15.0
RUN pip install numba==0.46.0
RUN ["apt-get", "install", "-y", "libsm6", "libxext6", "libxrender-dev"]
RUN pip install opencv-python==<IP_ADDRESS>

to make sure docker is clean, rebooted and did
sudo systemctl restart docker
Then cuda errors
sudo docker exec -it 7abde00f1842 /bin/bash

________                               _______________
___  __/__________________________________  ____/__  /________      __
__  /  _  _ \_  __ \_  ___/  __ \_  ___/_  /_   __  /_  __ \_ | /| / /
_  /   /  __/  / / /(__  )/ /_/ /  /   _  __/   _  / / /_/ /_ |/ |/ /
/_/    \___//_/ /_//____/ \____//_/    /_/      /_/  \____/____/|__/

You are running this container as user with ID 1000 and group 1000,
which should map to the ID and group for your user on the Docker host. Great!

tf-docker /tf > cd /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/
tf-docker /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src > python main.py --source=bentham --train
2019-12-26 23:01:13.422419: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libnvinfer.so.6
2019-12-26 23:01:13.446401: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libnvinfer_plugin.so.6
2019-12-26 23:01:19.131157: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-26 23:01:19.163713: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.164228: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 23:01:19.164285: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 23:01:19.164339: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 23:01:19.181939: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 23:01:19.186051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 23:01:19.219655: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 23:01:19.222981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 23:01:19.223009: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 23:01:19.223076: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.223463: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.223765: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 23:01:19.224099: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-12-26 23:01:19.250610: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-12-26 23:01:19.251627: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x8035b20 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-26 23:01:19.251648: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2019-12-26 23:01:19.344922: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.345338: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7e7bd20 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-26 23:01:19.345355: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
2019-12-26 23:01:19.345489: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.345810: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.755GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2019-12-26 23:01:19.345842: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 23:01:19.345857: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 23:01:19.345873: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-26 23:01:19.345888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-26 23:01:19.345903: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-26 23:01:19.345917: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-26 23:01:19.345931: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 23:01:19.345977: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.346316: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.346639: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2019-12-26 23:01:19.347084: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2019-12-26 23:01:19.924373: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-26 23:01:19.924403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102]      0
2019-12-26 23:01:19.924410: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0:   N
2019-12-26 23:01:19.924955: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.925353: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-26 23:01:19.925701: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9581 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
Model: "model"
_________________________________________________________________
Layer (type)                 Output Shape              Param #
=================================================================
input (InputLayer)           [(None, 1024, 128, 1)]    0
_________________________________________________________________
conv2d (Conv2D)              (None, 512, 64, 16)       160
_________________________________________________________________
p_re_lu (PReLU)              (None, 512, 64, 16)       16
_________________________________________________________________
batch_normalization (BatchNo (None, 512, 64, 16)       112
_________________________________________________________________
full_gated_conv2d (FullGated (None, 512, 64, 16)       4640
_________________________________________________________________
conv2d_1 (Conv2D)            (None, 512, 64, 32)       4640
_________________________________________________________________
p_re_lu_1 (PReLU)            (None, 512, 64, 32)       32
_________________________________________________________________
batch_normalization_1 (Batch (None, 512, 64, 32)       224
_________________________________________________________________
full_gated_conv2d_1 (FullGat (None, 512, 64, 32)       18496
_________________________________________________________________
conv2d_2 (Conv2D)            (None, 256, 16, 40)       10280
_________________________________________________________________
p_re_lu_2 (PReLU)            (None, 256, 16, 40)       40
_________________________________________________________________
batch_normalization_2 (Batch (None, 256, 16, 40)       280
_________________________________________________________________
full_gated_conv2d_2 (FullGat (None, 256, 16, 40)       28880
_________________________________________________________________
dropout (Dropout)            (None, 256, 16, 40)       0
_________________________________________________________________
conv2d_3 (Conv2D)            (None, 256, 16, 48)       17328
_________________________________________________________________
p_re_lu_3 (PReLU)            (None, 256, 16, 48)       48
_________________________________________________________________
batch_normalization_3 (Batch (None, 256, 16, 48)       336
_________________________________________________________________
full_gated_conv2d_3 (FullGat (None, 256, 16, 48)       41568
_________________________________________________________________
dropout_1 (Dropout)          (None, 256, 16, 48)       0
_________________________________________________________________
conv2d_4 (Conv2D)            (None, 128, 4, 56)        21560
_________________________________________________________________
p_re_lu_4 (PReLU)            (None, 128, 4, 56)        56
_________________________________________________________________
batch_normalization_4 (Batch (None, 128, 4, 56)        392
_________________________________________________________________
full_gated_conv2d_4 (FullGat (None, 128, 4, 56)        56560
_________________________________________________________________
dropout_2 (Dropout)          (None, 128, 4, 56)        0
_________________________________________________________________
conv2d_5 (Conv2D)            (None, 128, 4, 64)        32320
_________________________________________________________________
p_re_lu_5 (PReLU)            (None, 128, 4, 64)        64
_________________________________________________________________
batch_normalization_5 (Batch (None, 128, 4, 64)        448
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 128, 2, 64)        0
_________________________________________________________________
reshape (Reshape)            (None, 128, 128)          0
_________________________________________________________________
bidirectional (Bidirectional (None, 128, 256)          198144
_________________________________________________________________
time_distributed (TimeDistri (None, 128, 128)          32896
_________________________________________________________________
bidirectional_1 (Bidirection (None, 128, 256)          198144
_________________________________________________________________
time_distributed_1 (TimeDist (None, 128, 98)           25186
=================================================================
Total params: 692,850
Trainable params: 691,570
Non-trainable params: 1,280
_________________________________________________________________
Train for 545 steps, validate for 85 steps
Epoch 1/1000
2019-12-26 23:01:27.960566: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-26 23:01:28.353452: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-26 23:01:29.606042: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-12-26 23:01:29.617482: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-12-26 23:01:29.617918: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node model/conv2d/Conv2D}}]]
	 [[loss/time_distributed_1_loss/scan/while/body/_1/Less/_64]]
2019-12-26 23:01:29.618012: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node model/conv2d/Conv2D}}]]
  1/545 [..............................] - ETA: 59:56WARNING:tensorflow:Can save best model only with val_loss available, skipping.
WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are:
WARNING:tensorflow:Reduce LR on plateau conditioned on metric `val_loss` which is not available. Available metrics are: lr
  1/545 [..............................] - ETA: 1:00:30Traceback (most recent call last):
  File "main.py", line 155, in <module>
    verbose=1)
  File "/home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/network/model.py", line 175, in fit
    use_multiprocessing=use_multiprocessing, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training.py", line 819, in fit
    use_multiprocessing=use_multiprocessing)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py", line 342, in fit
    total_epochs=epochs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py", line 128, in run_one_epoch
    batch_outs = execution_function(iterator)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2_utils.py", line 98, in execution_function
    distributed_function(input_fn))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/def_function.py", line 568, in __call__
    result = self._call(*args, **kwds)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/def_function.py", line 632, in _call
    return self._stateless_fn(*args, **kwds)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 2363, in __call__
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 1611, in _filtered_call
    self.captured_inputs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 1692, in _call_flat
    ctx, args, cancellation_manager=cancellation_manager))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/function.py", line 545, in call
    ctx=ctx)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/eager/execute.py", line 67, in quick_execute
    six.raise_from(core._status_to_exception(e.code, message), None)
  File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
  (0) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node model/conv2d/Conv2D (defined at /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/network/model.py:175) ]]
	 [[loss/time_distributed_1_loss/scan/while/body/_1/Less/_64]]
  (1) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node model/conv2d/Conv2D (defined at /home/john/Documents/GitHub/Offline_Handwriting_Recognition/Solutions/arthurflor23_handwritten-text-recognition/handwritten-text-recognition-master/src/network/model.py:175) ]]
0 successful operations.
0 derived errors ignored. [Op:__inference_distributed_function_17754]

Function call stack:
distributed_function -> distributed_function

2019-12-26 23:01:29.771757: W tensorflow/core/kernels/data/generator_dataset_op.cc:103] Error occurred when finalizing GeneratorDataset iterator: Cancelled: Operation was cancelled

Still crashes
2019-12-27 00:08:54.931864: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-12-27 00:08:54.932313: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node model/conv2d/Conv2D}}]]
	 [[loss/time_distributed_1_loss/GatherNd/_102]]

after adding the following to my dockerfile (ie to match the fixes you shared)
FROM tensorflow/tensorflow:2.1.0rc2-gpu-py3-jupyter

# to see if  #35434 fixes the issues
ARG CUDA=10.1
RUN apt-get update && apt-get install -y --no-install-recommends \
        cuda-nvrtc-${CUDA/./-} \
        cuda-nvrtc-dev-${CUDA/./-} \
        libcublas10=<IP_ADDRESS>-1 \
        libcublas-dev=<IP_ADDRESS>-1

Maybe this code is stressing  cuda differently
I tried a simple 10 line nmist example and it works correctly with gpu, even before the last change and with only the first change.
The code that is causing the above error is sourced from https://github.com/arthurflor23/handwritten-text-recognition.  I am not too familiar with it. Author claims its solid.
Arthur runs this code on colab with 2.1.0-rc1.  I am running this on docker and
it only worked for me with a cpu docker upgraded to 2.1.0.rc1 and not with a gpu docker.
As you can see it fails with the GPU version even with these fixes.
I use the GPU docker all of the time, but with 1.13.1-gpu-py3-jupyter on other code.
Arthur's code that is dying, uses the new 2.0 api.
More Robust Test:
Do you have a more robust test case I can run, my setup is not too special, but
maybe you don't have this at your location.

GeForce RTX 2080 Ti/PCIe/SSE2
Intel® Core™ i7-8700K CPU @ 3.70GHz
Ubuntu 18.04.3 LTS

Any how, let me know how I can help.

still broken

The original issue of missing docker images is now resolved. For other build problems, please file a new issue.

A workaround for second issue was made available by https://github.com/tensorflow/tensorflow/issues/25446.
Looks like tf 2.0 stresses cuda more.
https://www.tensorflow.org/guide/gpu#limiting_gpu_memory_growth
So any psudo complex tf using rtx video cards will need this as the first few lines of code.
gpus = tf.config.experimental.list_physical_devices('GPU')
if gpus:
  try:
    # Currently, memory growth needs to be the same across GPUs
    for gpu in gpus:
      tf.config.experimental.set_memory_growth(gpu, True)
    logical_gpus = tf.config.experimental.list_logical_devices('GPU')
    print(len(gpus), "Physical GPUs,", len(logical_gpus), "Logical GPUs")
  except RuntimeError as e:
    # Memory growth must be set before GPUs have been initialized
    print(e)


"ModuleNotFoundError: No module named 'transformers.pytorch_utils' when using llm2vec with transformers 4.40.1"

Is the module transformers.pytorch_utils expected to exist in transformers version 4.40.1?
Are there any known compatibility issues with transformers 4.40.1 and llm2vec or peft that I should be aware of?

Which version of llm2vec are you using? The latest version of llm2vec is compatible with transformers 4.40.1. Can you share the exact command that resulted in the error?

Closing as it is stale. Feel free to re-open if you have any more questions regarding this issue.


Investigate database state and integration test configuration

Reset database before each test?  Reset database once before all tests?
Will this not be an issue when we can make new projects?  Existing project names?
Don't want:

Reset database on test server start -- then have to restart server all the time
Test only endpoints to clear database

Ideas:

Flyway clean mvn plugin
Custom script

Attempting to use h2 database for spring test profile that should be easier to erase on demand.
Thinking about making a controller that is profile blocked to has erase database capabilities.

Given up on using an embedded database for e2e tests.  Migrations won't work for each DB type.
Now trying to make and use test endpoints, to clear the database and insert default test data.


Where should I place my extend code of mongoid in my rails project?

I want to change the logic of mongoid's to_json by following code:
module Mongoid
  module Document
    def as_json(options={})
      attrs = super(options)
      attrs["id"] = self.persisted? ? self._id : nil
      attrs
    end
  end
end

where should I place it? So far I place it in application.rb and it can be loaded when starting rails. However, I want to move it to other place, where should I move to?

That's really up to you. In Rails projects a common place to put these is in /lib.


Use of promises in survey build

Just a little thing I spotted while have a poke through the repo:
https://github.com/techforbetter/connect5/blob/3f1b403bf375b1ac4893460425f1734f052a7211/server/database/surveyBuild.js#L18-L24
then takes a function as an argument. On line 21, you are invoking Model.insertMany, then passing its return value to then. The return value is a promise, not a function.
This means that deleteMany and insertMany are executed at the same time, not sequentially. A simple analogous example is:
Promise.resolve(2).then(1).then(console.log);

This logs 2, not 1, because non-function values passed to then or catch are ignored.

Thank you @eliascodes for a good spot. :+1:
we will fix that :)

@RamyAlshurafa has this been resolved?

@arrested-developer, Now yes :)


skip-dirs does not seem to work when specified in GHA workflow, or via environment variable

Steps to replicate:
Specify a step in a workflow as follows:
      - name: Run Trivy vulnerability scanner in IaC mode
        uses: aquasecurity/trivy-action@master
        with:
          scan-type: 'config'
          hide-progress: false
          format: 'table'
          exit-code: '1'
          ignore-unfixed: true
          severity: 'CRITICAL,HIGH'
          skip-dirs: "foo,bar"

Expected result:
Directories specified in skip-dirs are not scanned for vulnerabilities
Actual result:
Directories are scanned without exclusion taking effect.
Notes:
Supplying a comma separated string of directories using an environment variable as suggested in the cli documentation with TRIVY_SKIP_DIRS does not have the desired effect either.

Some clarity on how to specify the list would be useful. As the config file is YAML, should it be a comma separated string, or should it be a YAML list?


Adding Animation

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Your website already looks amazing but incorporating animation on all the images used on all the pages can make it even more appealing
Describe the solution you'd like
A clear and concise description of what you want to happen.
I want to add floating animations on all the pages
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.

Right Now , We are not looking for this area !
You can work on another major problem
Thanks you !


Update date format string for locales as per internationalization Standards.

Story
Description

As a <consumer/designer/user of graphs> I would like to update the date format(date month) for locales like Swedish (SV), French (fr), or Dutch (NL) to meet internationalization standards.
Motivation

So that date format on the axis will be displayed as per internationalized standatards.
Definition of Done

We'll know we're done when we are able to display the correct date format on the axis for locales like Swedish (SV), French (fr) or Dutch (NL).

Closing this as we're tracking this internally.


[DO NOT MERGE] rebase changes

Hi @pavankjadda . Do you know why the plugin does not work on CLion?

Using v4.0. Plugin is working well for PyCharm/PHPStorm


Clicking on any Contributor name in sharing tab asks for Save/Discard

Steps

Go to Sharing tab of any project.
Click on any contributor name.

 Expected
 Should be redirected to Profile page.
 Actual
Confirmation modal is displayed along with Save & Discard changes option on the page.
![screen shot 2015-02-27 at 1 22 24 pm](https://cloud.githubusercontent.com/assets/8779995/6418532/c3e020d6-be83-11e4-8636-92891ac69532.png)

@kushG This is on Production?

Yes it is !

OK

@steve, is the fix merged? I can still replicate this in production

@kushG The fix is currently on staging only.

Got you.....I thought hotfix goes directly into production !

@kushG It usually does, yes, but since this one is easy to test, I wanted it to be verified on staging first.
Anyway, this is on production now. =)


Trouble with installation

Hello, I have problem with build vrouter
I started from:
$: repo init -u git@github.com:Juniper/contrail-vnc -m vrouter-manifest.xml
$: repo sync
//And build:
$ scons vrouter

But this return me followed error:
File "/..../SConstruct", line 16, in <module>
IOError: [Errno 2] No such file or directory: '/..../controller/src/base/version.info':

So the issue is that I didn't have in file contrail-controller?
I downloaded it and put as a folder into vrouter dir (with changed name controller), so my project tree looks as followed:
/vrouter/.
/vrouter/build
/vrouter/config.log
/vrouter/controller [externally downloaded as a ZIP and unpacked here]
/vrouter/SConstruct
/vrouter/tools
/vrouter/vrouter

Then when I trying to build
$ scons vrouter

It give me next error:
NameError: name 'sys' is not defined:
  File "/.../vrouter/SConstruct", line 16:
    SConscript(dirs=['controller', 'vrouter', 'tools/sandesh'])
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 609:
    return method(*args, **kw)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 546:
    return _SConscript(self.fs, *files, **subst_kw)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 260:
    exec _file_ in call_stack[-1].globals
  File "/home/hjacker/git/vrouter/controller/SConscript", line 5:
    SConscript(dirs=['lib', 'src'])
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 609:
    return method(*args, **kw)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 546:
    return _SConscript(self.fs, *files, **subst_kw)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 260:
    exec _file_ in call_stack[-1].globals
  File "/home/hjacker/git/vrouter/controller/lib/SConscript", line 43:
    SConscript(dirs = dir, variant_dir = '#/build/third_party/' + dir)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 609:
    return method(*args, **kw)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 546:
    return _SConscript(self.fs, *files, **subst_kw)
  File "/usr/lib/scons/SCons/Script/SConscript.py", line 260:
    exec _file_ in call_stack[-1].globals
  File "/.../vrouter/build/third_party/rapidjson/SConscript", line 19:
    sys.exit(1)

So it looked like rapidjson/SConscript didn't import sys
I added to rapidjson/SConscript
import sys

and finally I got:
scons: Reading SConscript files ...
/.../vrouter/third_party/rapidjson not present

I think that I messed out with this, can You help me with this installation?
I had Ubuntu with default Python 2.7.6
repo version v1.12.20
and SCons by Steven Knight et al.:
script: v2.3.0, 2013/03/03 09:48:35, by garyo on reepicheep
engine: v2.3.0, 2013/03/03 09:48:35, by garyo on reepicheep
engine path: ['/usr/lib/scons/SCons']

The problem was with .repo/manifest.xml
After
repo init -u git@github.com:Juniper/contrail-vnc -m vrouter-manifest.xml

in manifest.xml are whole projects and it looks as followed:
$: cat .repo/manifest.xml
<manifest>
<remote name="github" fetch=".."/>

<default revision="R2.1" remote="github"/>

<project name="contrail-build" remote="github" path="tools/build">
  <copyfile src="SConstruct" dest="SConstruct"/>
</project>
<project name="contrail-controller" remote="github" path="controller"/>
<project name="contrail-vrouter" remote="github" path="vrouter"/>
<project name="contrail-third-party" remote="github" path="third_party"/>
<project name="contrail-generateDS" remote="github" path="tools/generateds"/>
<project name="contrail-sandesh" remote="github" path="tools/sandesh"/>
<project name="contrail-packages" remote="github" path="tools/packages">
  <copyfile src="packages.make" dest="packages.make"/>
</project>
<project name="contrail-nova-vif-driver" remote="github" path="openstack/nova_contrail_vif"/>
<project name="contrail-neutron-plugin" remote="github" path="openstack/neutron_plugin"/>
<project name="contrail-web-controller" remote="github"/>
<project name="contrail-web-core" remote="github"/>
<project name="contrail-webui-third-party" remote="github" path="contrail-webui-third-party"/>

</manifest>

but it require only: vrouter, sandesh and contrail-build
so it must be replaced with followed(from wiki):
<manifest>
<remote name="github" fetch=".."/>
<default revision="R2.1" remote="github"/>
<project name="contrail-build" remote="github" path="tools/build">
<copyfile src="SConstruct" dest="SConstruct"/>
</project>
<project name="contrail-vrouter" remote="github" path="vrouter"/>
<project name="contrail-sandesh" remote="github" path="tools/sandesh"/>
</manifest>

For me it was not obvious at first glance.
Question about sys dependencies in python scripts:
-is ok that python didn't see sys package? Or it is my miss configuration?

Pedro asked me to get back to you about this a few days back, just getting to it now, sorry.
The first error you saw:
File "/..../SConstruct", line 16, in <module>
IOError: [Errno 2] No such file or directory: '/..../controller/src/base/version.info':

Expecting controller to be present is a bad assumption on the part of our build infra. I have submitted a review to fix that. Once it goes through CI, it will make things easier. If you wanted to cherry-pick that diff into your workspace and test it in your setup, I'd appreciate it.
Your experiment of adding controller was a good attempt on your part, but even after fixing the issue in rapidjson/SConstruct, controller has its own large set of dependencies, as you discovered when the build complained about a missing third-party package.
Answering your last question, that's definitely an error in rapidjson/SConstruct to not have the import sys. Nothing wrong with your Python etc configuration. I've submitted a controller review to add the missing import.
Finally, the manifest issue. The .repo/manifest.xml should be a symlink into .repo/manifests, pointing to the actual manifest you specified with -m flag you passed to repo init. For example, in my workspace:
[klash@ubuntu-build02] ls -l .repo/manifest.xml
lrwxrwxrwx 1 klash ft 30 Apr  9 15:52 .repo/manifest.xml -> manifests/vrouter-manifest.xml

I suspect that a repo command you ran changed that symlink. So first check the symlink and let me know please.
One last thing, did you provide the full repo init command you passed? I'm noticing revision="R2.1" in the XML output. I would have expected to see a -b or --manifest-branch argument. Are you really trying to work with R2.1, or was there some type of glitch?

Thank You for answer. I started with empty folder and again create repo for begin
$: repo init -u git@github.com:Juniper/contrail-vnc -m vrouter-manifest.xml
$: repo sync
$ scons vrouter

And I got "scons: done building targets." so the path work
About revision, I wanted the latest rev, but when the master didn't work for me it is my habit to switch into older revision/tag to see if it give me the same issues.
I don't know if You want to merge this fix into github but I can close my github-issue if You want

My two fixes have been merged into github, so I think that closing this github-issue is the right thing.


Can this module be made to work with gRPC to access Google Drive?

I'm not sure I understand the question. JSON-RPC and gRPC are completly different protocols, and Google Cloud does not support JSON-RPC syntax. Can you elaborate please?

I'm sorry for my misunderstanding. I was looking for an existing Raku module that is close to a possible solution for access to Google Drive. Their docs mention gRPC--hence my query.

Closing as not related to this module. Proper gRPC support in Raku is on a wishlist for a long time: https://perl-foundation-outreach.github.io/gsoc-2021-ideas/raku/gRPC.html


chore: release 1.0.1

:robot: I have created a release *beep* *boop*
1.0.1 (2019-06-15)
Bug Fixes

docs: move to new client docs URL (#339) (c9f8d13)

This PR was generated with Release Please.

Release is at https://github.com/googleapis/nodejs-logging-winston/releases/tag/v1.0.1

The release build has started, the log can be viewed here. :sunflower:

:egg: You hatched a release! The release build finished successfully! :purple_heart:


Ability to save multiple templates for an action.

A user should be able to add multiple templates for an action. These actions:

[ ] Confirm/reject actions round
[ ] Round action for job and internship can be different
[ ] No show

I think we do have this functionality in portal. We would like to revamp the email templating a bit, I will create a separate ticket for that, hence closing this issue.


Hookup Mentor Notifications

Is your feature request related to a problem? Please describe.
The notifications on the frontend are currently just a shell. The UI is setup but the component is not hooked up to the backend.
Describe the solution you'd like
The backend has the email notifications currently working. We will need to connect the component, so that when the user toggles them on, they will get the corresponding email.
Additional context
Currently we will not have sms messaging for testing, so we will need to comment out that code for now.
┆Issue is synchronized with this Trello card by Unito

@nzeager just getting this on your radar.


Spider-Man wont boot on SPCH-1001 but boots on SPCH-101

tonyhax version:  1.4.3
Installation method: ps2 ulaunchelf
Entry point game: cool boarders 4
Console model: SPCH 1001 will not run disc but SPCH 101 will run same disk
Integrity check: yes for both
BIOS version: SPCH 101 bios = v4.5
Target game:  SLUS-00875 | SPIDER-MAN
Bug explanation: SLUS-00875, SPIDER-MAN will not run on my SPCH 1001, it gets stuck on starting. However, my SPC-101 will run the same spider man disc.  SPCH 1001 has successfully run other games via tonyhax 1.4.3 and cool boarders 4

Have you tried with other games? To rule out a dying laser drive. Old units AFAIK are notorious for having the drives made with plastic that fail after some time due to heat from the PSU.

Have you tried with other games? To rule out a dying laser drive. Old units AFAIK are notorious for having the drives made with plastic that fail after some time due to heat from the PSU.

Excellent news, this is not a software issue. My SCPH-1001 using the latest Tonyhax v1.4.4 Boot CD via CD Player Swap Trick boots Spider-Man as expected.
I think the issue this indivisual was having is an iffy CD drive. Just because one game works ok on your console, does not mean every game will work as expected if the CD drive is having trouble reading discs.
CD-Rs are less reflective then pressed CD-ROM discs. The earliest consoles not only shipped with an inferior drive mechanism made of warpable plastic on the sled rails, they also have a CD servo that is much more intolerant of read errors/slight miscalculations in seeking due to worn down lubrication, see: https://alex-free.github.io/unofficial-ps1-cd-drive-service-manual/ for more on that.
Anyways, Spider-Man immediately starts playing an FMV after booting, which will for sure cause issues if your CD drive is not working as well as it should be. I believe this person is simply encountering a disc read error when the game tries to start playing the opening FMV.


Impact model - [closed]

In GitLab by @nmansard on Jan 21, 2019, 21:59
Merges topic/impact -> topic/refact
I introduce a new action model for handling the impact. The derivatives are correct, also it is possible to make more clever computation.
I worked on this model tonight as it was not possible to merge other MR. The top-priority MR is the one of @cmastalli that should be merged asap.

In GitLab by @cmastalli on Jan 21, 2019, 23:35
Please note that we can merge !51. After that, let's move all impact classes to crocoddyl/impact.py

In GitLab by @nmansard on Jan 22, 2019, 08:58
mentioned in merge request !54

In GitLab by @proyan on Jan 22, 2019, 09:29
This is just such a curious thing to do. Why exactly are you doing this?

In GitLab by @proyan on Jan 22, 2019, 09:35
This looks to be okay to me. @cmastalli If I merge this, could you please take care of the organization of the impact class?

In GitLab by @cmastalli on Jan 22, 2019, 09:42
I think it's better to re-organize first, do you agree?
I can take care of this task, @nmansard should a put this in my list priority or the unit-test?
In any case there are conflicts in this PR due to changes in the topic/refact branch.

In GitLab by @proyan on Jan 22, 2019, 09:49
Go ahead. I'll let you deal with this PR then.

In GitLab by @cmastalli on Jan 22, 2019, 11:12
mentioned in merge request !56

In GitLab by @cmastalli on Jan 22, 2019, 11:13
I'll close this PR, and rebased version is made in the following PR !56.

In GitLab by @cmastalli on Jan 22, 2019, 11:13
closed


[PE-D][Tester C] Symbols in user input

Wouldn't it make more sense that symbols like "s/o" be accepted as specifically for TA's it might be necessary for the student's full legal name to be input?

Labels: severity.Medium type.FunctionalityBug
original: jiayr99/ped#9

Update UG/DG: Names do not Allow Special Characters (except , & Spaces)


DrawerLayoutAndroid.ios.js missing from npm package

The npm package for 0.11.3 (http://registry.npmjs.org/react-native/-/react-native-0.11.3.tgz) does not have DrawerLayoutAndroid.ios.js included (
https://github.com/facebook/react-native/blob/master/Libraries/Components/DrawerAndroid/DrawerLayoutAndroid.ios.js) which causes builds to fail on ios

@chrisnojima do you have a temporary solution for this?

just doing an npm install https://github.com/facebook/react-native.git (you can pass in the tag/commit if you want)

Cool!

I believe your issue is related to this one: https://github.com/facebook/react-native/issues/3094

Yup fixed in 11.4 tnx!


Upgrade CQT and fix some lint errors

Description

Additional context

Issue reference

Before submitting the PR, please make sure you do the following

[ ] Read the Contributing Guidelines.
[ ] Follow the PR Title/Commit Message Convention.
[ ] Provide a description in this PR that addresses what the PR is solving, or reference the issue that it solves (e.g. fixes #123).
[ ] Ideally, include relevant tests that fail without this PR but pass with it.

This is now blocked and partially solved by https://github.com/lmc-eu/spirit-design-system/pull/1188


Incompatible with version 0.17.x

This mod is incompatible with the latest 0.17.x version of Factorio

Just released a version for 0.17 :)


Decommission Jenkins Windows workers

there is no further need for https://scala-ci.typesafe.com/computer/jenkins-worker-publish/ , now that https://github.com/scala/scala/pull/9496 has landed and https://github.com/scala/scala/pull/9591 is about to land
I have already disabled https://scala-ci.typesafe.com/job/scala-2.12.x-integrate-windows/ and https://scala-ci.typesafe.com/job/scala-2.13.x-integrate-windows/
@lrytz I've never touched the EC2 side of the Jenkins stuff. is this something you could handle...? (I'm not even certain there is anything that needs to be done. if Jenkins no longer ever wakes up the instance, perhaps the cost drops to $0.00 and that's the end of it? no clue.)

I can remove the instances eventually. There's a tiny cost for keeping the EBS volume around, but overall costs are dominated by compute time.

@lrytz maybe time to pull the trigger on this? I worry about security when old stuff just hangs around indefinitely

The only thing I could possibly imagine is if we would need another 2.11 release. But maybe restoring that ability would probably be just as hard as backporting the current release infra from 2.12/2.13 to 2.11?

At present I’m only proposing decommissioning the Windows worker; 2.11 releases were done by the Ubuntu worker.

I think (not sure though) the windows machine was used for building the msi (https://scala-ci.typesafe.com/view/scala-2.11.x/job/scala-2.11.x-release-package-windows/)

Ah, I stand corrected (or perhaps-corrected).
If we had to do another 2.11 release but just leave out the MSI, that wouldn't exactly be the end of the world.
But perhaps it's better to just leave this alone, then. Shall I close the ticket?

I think we can leave things in place as they are for now, until the moment when we actually have a reason to change them (maybe when we get rid of our jenkins). The Windows machines are never actually running, so I don't see a big risk.


fix: use the tag/commit as the aro version and copy image to the integration

Which issue this PR addresses:
Fixes https://msazure.visualstudio.com/AzureRedHatOpenShift/_workitems/edit/13493157
What this PR does / why we need it:
ARO uses both tags and commits as its version.
The commits are used for the development scenario, tags are used when building and deploying to production.
Adds the pipeline step to copy the resulted image to the integration registry.
Test plan for issue:
N/A
Is there any documentation that needs to be updated for this PR?
Part of the pipeline documentation.

@bryanro92 I'm going to merge as it is will be much easier to test pipelines. If you find any issues while looking into it - please ping @petrkotas about them.


New harmonyhubjs-client but nevertheless MAX_CLIENTS=6 ERROR

Hi,
I downloaded the harmonyhubjs-client and replace the old from homebridge-harmonyhub, but the MAX_CLIENTS=6 ERROR come again.
I see here on git this example for the settings, but i can`t fing the default settings... Can anyone help me? Where is the location from the default settings, that i can change the ip.

duplicate of #34


RefreshIndicator should stay visible while scrolling during refresh()

Steps to Reproduce
Trigger a refresh() of the RefreshIndicator and then scroll down (drag your finger up). The refresh indicator goes away even though the Future from refresh() has not complete. The indicator should stay visible: https://material-design.storage.googleapis.com/publish/material_v_8/material_ext_publish/0B1PhAWhtrRTrUlM4NHN1ei1DS2s/patterns-swipetorefresh-behavior_do_xhdpi_009.webm

/cc @HansMuller

I have a fix for this. It should be available later today.


Re-enable MultipleContextTest

I want to see if this test works now

I've added this commit: https://github.com/hibernate/hibernate-reactive/pull/1034/commits/c8349a0b5bb078633efa2c8e63c7b6fd604a1461
It's a proof of concept about what we need to change.