Deprecate and remove 'fromEd25519SK' method from KeyPair

KeyPair shouldn't be responsible for bytes format: it could be base64, base58, base123, zip, or whatever. KeyPair already accepts Uint8Array in fromBytes and that's enough.
However, the name fromEd25519SK is very appealing so I think it's best to remove it ASAP to avoid more and more people depending on it.

I think this naming scheme could be confusing. fromBytes does not indicate that these bytes are going to be used as ed25519 secret key. We should either rename fromBytes to something like fromEd25519SKbytes or introduce a field which describes the type of the key used (atm only ed25519 is supported). In the second case the methods will look like the following:
static async fromBytes(type: KeyType, arr: Uint8Array): Promise<KeyPair> {
// ...
}

static async random(type: KeyType): Promise<KeyPair> {
// ...
}

toPrivateKey(): Uint8Array {
// ...
}

getKeyType(): KeyType {
// ...
}


Upgrade dependencies

I really love this project and I want to use it but it cause some problems with dependencies because of chacha20poly1305 crate that needs an old version of zeroize.
The developer published a pre-release (0.10.0-pre) so I'll appreciate if you can publish a -pre release too with some upgraded dependencies.
Thanks

@shurizzle Hey! Instead of pulling all versions, could you try with just one change and then test on your project?
chacha20poly1305 = { version = "0", default-features = false }

@shurizzle Also, the version is gonna be just 0.3.1
version = "0.3.1"

Okay, done. Thanks. v0.3.1 published.

@shurizzle 0.3.2 has been published with the latest chacha and zeroize, resolving the conflicts


This node takes over the complete ui

HI
I have the strange effect that as soon as i integrate this node into a flow the rest of my configured ui disapears.
I use W10 and no matter what browser, just this one element is on screen in ui.
Deactivate is not enough, I have to restart node-red afterwards to get the rest of my ui back.
THX in advance

Would you mind sharing a screenshot?

How should I do this? I'm in a highly protected environment. Eventually teams for bussinesBest regards Mike EitelHuegelweg 7 8224 LoehningenSwitzerland +41 79 416 50 @.*** Ursprüngliche Nachricht --------Von: Alexandre Alapetite @.>Datum: Fr., 6.
—You are receiving this because you authored the thread.Reply to this email directly, view it on GitHub, or unsubscribe.Triage notifications on the go with GitHub Mobile for iOS or Android.

You can copy-paste a screenshot here on GitHub

By the way
The Node-Red is running on a Windows 19 SRV.
This working pc is a W10.

I DO NOT KNOW WHY,
but after redoing the complete directory     node-modules    everything works like a charm.
SORRY for the inconvinience,
but I struggled, naturally with breaks ;-), before writing this issue.
Best regards and thx for your very fast reaction !!!

I get back the same effect when i start Node-red as a service in srv19.    Reproducable!
I use the following description:
\Node-RED as a service according to
\https://gist.github.com/dceejay/576b4847f0a17dc066db
\mkdir c:\temp
\nssm install Node-RED "c:\Users\"%USERNAME%"\AppData\Roaming\npm\node-red.cmd"
\nssm set Node-RED AppDirectory "c:\Users\"%USERNAME%".node-red"
\nssm set Node-RED AppParameters "-u c:\Users\"%USERNAME%".node-red > c:\temp\node-red.log"
\ This is on a system that must and can not connect to internet. The only way is the generation of an node-red infrastructure one a www connected pc and tranfer the "USER" directory en block via file zipped transfer. The result is f.x. in:
\ C:\Users\Administrator\node_modules.bin\node-red.cmd
cd C:\Users\Administrator\node_modules.bin
.\nssm install Node-RED C:\Users\Administrator\node_modules.bin\node-red.cmd
.\nssm set Node-RED AppDirectory "c:\Users\Administrator.node-red"
.\nssm set Node-RED AppParameters "-u c:\Users\Administrator.node-red > c:\temp\node-red.log"
.\nssm set Node-RED Description "A wiring tool for the Internet of Things"

If you are still around, attempt of fix in https://github.com/alexandrainst/node-red-contrib-ui-upload/pull/13
Tests welcome

Sorry, but I m in the meantime retired and have no more access to this very big enterprise cloud platform.
But Big thanks that you followed up. Super service


Investigate the appDomain: denied requirement

See https://github.com/Microsoft/vs-extension-testing/pull/1#discussion_r203421340.
If appDomain: denied is a requirement, it should be documented in the usage notes for the repository. Otherwise, the current use of this property should be removed in favor of the xUnit.net default.

This requirement was removed by c9faf5cfbb4281070ca435b058482cc116d435d4


[Enhancement] print more log and stack for audit and paimon table

Fixes #issue
What type of PR is this:

[ ] BugFix
[ ] Feature
[x] Enhancement
[ ] Refactor
[ ] UT
[ ] Doc
[ ] Tool

Does this PR entail a change in behavior?

[ ] Yes, this PR will result in a change in behavior.
[x] No, this PR will not result in a change in behavior.

If yes, please specify the type of change:

[ ] Interface/UI changes: syntax, type conversion, expression evaluation, display information
[ ] Parameter changes: default values, similar parameters but with different default values
[ ] Policy changes: use new policy to replace old one, functionality automatically enabled
[ ] Feature removed
[ ] Miscellaneous: upgrade & downgrade compatibility, etc.

Checklist:

[x] I have added test cases for my bug fix or my new feature
[ ] This pr needs user documentation (for new or modified features or behaviors)

[ ] I have added documentation for my new feature or new function

Bugfix cherry-pick branch check:

[x] I have checked the version labels which the pr will be auto-backported to the target branch

[x] 3.2
[ ] 3.1
[ ] 3.0
[ ] 2.5

[BE Incremental Coverage Report]
:heart_eyes: pass : 0 / 0 (0%)

[BE Incremental Coverage Report]
:heart_eyes: pass : 0 / 0 (0%)

[BE Incremental Coverage Report]
:heart_eyes: pass : 0 / 0 (0%)

[FE Incremental Coverage Report]
:disappointed: fail : 0 / 5 (00.00%)
file detail

path
covered_line
new_line
coverage
not_covered_line_detail

:large_blue_circle:
com/starrocks/qe/AuditLogBuilder.java
0
1
00.00%
[150]

:large_blue_circle:
com/starrocks/connector/paimon/PaimonMetadata.java
0
1
00.00%
[161]

:large_blue_circle:
com/starrocks/qe/AuditEventProcessor.java
0
3
00.00%
[76, 99, 110]

@Mergifyio backport branch-3.2


@conda-forge-admin, please add user @timkpaine

Additional comment:
No response

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I added user @timkpaine in conda-forge/polygon-api-client-feedstock#7.


unable to reproduce hindsight experience replay(HER) results

I am trying to reproduce HER results, here is my setting:
mpirun -version mpirun (Open MPI) 1.10.2
mujoco_py.__version__ '<IP_ADDRESS>'
gym.__version__  '0.10.5'
mujoco 150
tensorflow both 1.4.0 and 1.8.0 tried
successfully bind-to core
tested envs: FetchPickAndPlace, HandManipulateBlock, FetchPush
code version: both c5d6f2996c5504a2e46112464b9b7ee2618d3118 and b71152eea0470ac2629c33e0fc66a54fe494949f tried
Results: never successfully learned a policy, test success rate is very bad. E.g. on FetchPush, after 50 epochs, the test success rate is 0.2.
I observed some strange things:

different process has different epoch during the course of training
success rate often go down to zero
all process are saving logs, instead of the rank=0 process
@pzhokhov @matthiasplappert  Could you please confirm?

Could you provide a Docker image to reproduce the results? Or plz list some versions info.

My guess is the change of Mujoco, cause I have already tried all kinds of possible packages combinations, and even with or without Docker, local machine and AWS machine. @pzhokhov @machinaut  Could you please try the HER code in your internal machine to see if it is reproducible? Thanks a lot.

Hi @Andrewtor ! In terms of fully reproducing of the HER results, I am afraid only @machinaut and @matthiasplappert may have the full context. However, I tried the suggested in the README, and it does seem to work... Below is the output that I am getting (note that I was running it on my laptop, and I had to modify mpi call to add --oversubscribe flag; otherwise, mpi was complaining about running 19 processes on a 4-core CPU):
$ OPENAI_LOGDIR=/tmp/her/test python -m baselines.her.experiment.train --num_cpu 19
Logging to /tmp/her/test
--------------------------------------------------------------------------
A request was made to bind a process, but at least one node does NOT
support binding processes to cpus.

Node: peterz-macbook

Open MPI uses the "hwloc" library to perform process and memory
binding. This error message means that hwloc has indicated that
processor binding support is not available on this machine.

On OS X, processor and memory binding is not available at all (i.e.,
the OS does not expose this functionality).

On Linux, lack of the functionality can mean that you are on a
platform where processor and memory affinity is not supported in Linux
itself, or that hwloc was built without NUMA and/or processor affinity
support. When building hwloc (which, depending on your Open MPI
installation, may be embedded in Open MPI itself), it is important to
have the libnuma header and library files available. Different linux
distributions package these files under different names; look for
packages with the word "numa" in them. You may also need a developer
version of the package (e.g., with "dev" or "devel" in the name) to
obtain the relevant header files.

If you are getting this message on a non-OS X, non-Linux platform,
then hwloc does not support processor / memory affinity on this
platform. If the OS/platform does actually support processor / memory
affinity, then you should contact the hwloc maintainers:
https://github.com/open-mpi/hwloc.
--------------------------------------------------------------------------
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
2018-09-19 10:29:05.747520: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:05.903942: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.010175: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.085689: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.315689: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.346533: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.488529: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.636835: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.752791: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.773150: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:06.952806: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.069600: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.128797: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.160893: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.175545: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.187744: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.197000: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.228061: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:29:07.631600: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
T: 50
_Q_lr: 0.001
_action_l2: 1.0
_batch_size: 256
_buffer_size: 1000000
_clip_obs: 200.0
_hidden: 256
_layers: 3
_max_u: 1.0
_network_class: baselines.her.actor_critic:ActorCritic
_norm_clip: 5
_norm_eps: 0.01
_pi_lr: 0.001
_polyak: 0.95
_relative_goals: False
_scope: ddpg
ddpg_params: {'buffer_size': 1000000, 'hidden': 256, 'layers': 3, 'network_class': 'baselines.her.actor_critic:ActorCritic', 'polyak': 0.95, 'batch_size': 256, 'Q_lr': 0.001, 'pi_lr': 0.001, 'norm_eps': 0.01, 'norm_clip': 5, 'max_u': 1.0, 'action_l2': 1.0, 'clip_obs': 200.0, 'scope': 'ddpg', 'relative_goals': False}
env_name: FetchReach-v1
gamma: 0.98
make_env: <function prepare_params.<locals>.make_env at 0x1202102f0>
n_batches: 40
n_cycles: 10
n_test_rollouts: 10
noise_eps: 0.2
random_eps: 0.3
replay_k: 4
replay_strategy: future
rollout_batch_size: 2
test_with_polyak: False
Creating a DDPG agent with action space 4 x 1.0...
Training...
--------------------------------------------
| epoch              | 0                   |
| stats_g/mean       | 0.85923815          |
| stats_g/std        | 0.096135505         |
| stats_o/mean       | 0.25883374          |
| stats_o/std        | 0.031376462         |
| test/episode       | 20.0                |
| test/mean_Q        | -0.6188709          |
| test/success_rate  | 0.755263157894737   |
| train/episode      | 20.0                |
| train/success_rate | 0.41578947368421054 |
--------------------------------------------
New best success rate: 0.755263157894737. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_0.pkl ...
-------------------------------------------
| epoch              | 1                  |
| stats_g/mean       | 0.86445            |
| stats_g/std        | 0.08858923         |
| stats_o/mean       | 0.2598202          |
| stats_o/std        | 0.029321056        |
| test/episode       | 40.0               |
| test/mean_Q        | -0.6053122         |
| test/success_rate  | 0.9078947368421053 |
| train/episode      | 40.0               |
| train/success_rate | 0.6342105263157896 |
-------------------------------------------
New best success rate: 0.9078947368421053. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 2                  |
| stats_g/mean       | 0.86439794         |
| stats_g/std        | 0.0857108          |
| stats_o/mean       | 0.2596623          |
| stats_o/std        | 0.028547978        |
| test/episode       | 60.0               |
| test/mean_Q        | -0.65844005        |
| test/success_rate  | 0.8736842105263158 |
| train/episode      | 60.0               |
| train/success_rate | 0.65               |
-------------------------------------------
-------------------------------------------
| epoch              | 3                  |
| stats_g/mean       | 0.8648076          |
| stats_g/std        | 0.08446032         |
| stats_o/mean       | 0.2596404          |
| stats_o/std        | 0.028361032        |
| test/episode       | 80.0               |
| test/mean_Q        | -0.5228803         |
| test/success_rate  | 0.9447368421052633 |
| train/episode      | 80.0               |
| train/success_rate | 0.75               |
-------------------------------------------
New best success rate: 0.9447368421052633. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 4                  |
| stats_g/mean       | 0.86489314         |
| stats_g/std        | 0.08355687         |
| stats_o/mean       | 0.25961322         |
| stats_o/std        | 0.028298117        |
| test/episode       | 100.0              |
| test/mean_Q        | -0.49157524        |
| test/success_rate  | 0.9236842105263158 |
| train/episode      | 100.0              |
| train/success_rate | 0.7052631578947368 |
-------------------------------------------
-------------------------------------------
| epoch              | 5                  |
| stats_g/mean       | 0.8650561          |
| stats_g/std        | 0.08327734         |
| stats_o/mean       | 0.25963134         |
| stats_o/std        | 0.0283915          |
| test/episode       | 120.0              |
| test/mean_Q        | -0.31562403        |
| test/success_rate  | 0.9868421052631579 |
| train/episode      | 120.0              |
| train/success_rate | 0.7105263157894738 |
-------------------------------------------
New best success rate: 0.9868421052631579. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_5.pkl ...
-------------------------------------------
| epoch              | 6                  |
| stats_g/mean       | 0.8652797          |
| stats_g/std        | 0.08305483         |
| stats_o/mean       | 0.2596776          |
| stats_o/std        | 0.028530423        |
| test/episode       | 140.0              |
| test/mean_Q        | -0.28909713        |
| test/success_rate  | 0.9736842105263158 |
| train/episode      | 140.0              |
| train/success_rate | 0.7631578947368421 |
-------------------------------------------
-------------------------------------------
| epoch              | 7                  |
| stats_g/mean       | 0.86517453         |
| stats_g/std        | 0.08301851         |
| stats_o/mean       | 0.2596428          |
| stats_o/std        | 0.02871482         |
| test/episode       | 160.0              |
| test/mean_Q        | -0.14772488        |
| test/success_rate  | 0.994736842105263  |
| train/episode      | 160.0              |
| train/success_rate | 0.7552631578947369 |
-------------------------------------------
New best success rate: 0.994736842105263. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 8                  |
| stats_g/mean       | 0.86503863         |
| stats_g/std        | 0.08310568         |
| stats_o/mean       | 0.2596033          |
| stats_o/std        | 0.028884942        |
| test/episode       | 180.0              |
| test/mean_Q        | -0.19021991        |
| test/success_rate  | 0.994736842105263  |
| train/episode      | 180.0              |
| train/success_rate | 0.7157894736842105 |
-------------------------------------------
New best success rate: 0.994736842105263. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 9                  |
| stats_g/mean       | 0.8657269          |
| stats_g/std        | 0.08322558         |
| stats_o/mean       | 0.2598089          |
| stats_o/std        | 0.029045677        |
| test/episode       | 200.0              |
| test/mean_Q        | -0.14269257        |
| test/success_rate  | 1.0                |
| train/episode      | 200.0              |
| train/success_rate | 0.7447368421052633 |
-------------------------------------------
New best success rate: 1.0. Saving policy to /tmp/her/test/policy_best.pkl ...

As for logging from all ranks - yes, I see that too, although it looks like it is more of a bug than a feature , because the thelog-rank0xx.txt files only have the header (this means that loggers for non-master process are reconfigured after printing the header). This should be easy to fix, although it also looks rather harmless to me.

that was for FetchReach-v0, which is a realtively easy task; here are the results for FetchPush (takes longer, but gets to test success rate of 1.0 after 20 epochs:
python -m baselines.her.experiment.train --num_cpu 19 --env=FetchPush-v1
Logging to /tmp/her/test
--------------------------------------------------------------------------
A request was made to bind a process, but at least one node does NOT
support binding processes to cpus.

Node: peterz-macbook

Open MPI uses the "hwloc" library to perform process and memory
binding. This error message means that hwloc has indicated that
processor binding support is not available on this machine.

On OS X, processor and memory binding is not available at all (i.e.,
the OS does not expose this functionality).

On Linux, lack of the functionality can mean that you are on a
platform where processor and memory affinity is not supported in Linux
itself, or that hwloc was built without NUMA and/or processor affinity
support. When building hwloc (which, depending on your Open MPI
installation, may be embedded in Open MPI itself), it is important to
have the libnuma header and library files available. Different linux
distributions package these files under different names; look for
packages with the word "numa" in them. You may also need a developer
version of the package (e.g., with "dev" or "devel" in the name) to
obtain the relevant header files.

If you are getting this message on a non-OS X, non-Linux platform,
then hwloc does not support processor / memory affinity on this
platform. If the OS/platform does actually support processor / memory
affinity, then you should contact the hwloc maintainers:
https://github.com/open-mpi/hwloc.
--------------------------------------------------------------------------
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
Logging to /tmp/her/test
2018-09-19 10:50:16.738578: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:16.955833: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.061770: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.076134: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.088448: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.117264: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.149102: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.222471: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.292475: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.327248: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.459242: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.590884: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.711807: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.775800: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.864287: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:17.908064: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:18.139650: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:18.151192: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-09-19 10:50:18.250176: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
T: 50
_Q_lr: 0.001
_action_l2: 1.0
_batch_size: 256
_buffer_size: 1000000
_clip_obs: 200.0
_hidden: 256
_layers: 3
_max_u: 1.0
_network_class: baselines.her.actor_critic:ActorCritic
_norm_clip: 5
_norm_eps: 0.01
_pi_lr: 0.001
_polyak: 0.95
_relative_goals: False
_scope: ddpg
ddpg_params: {'buffer_size': 1000000, 'hidden': 256, 'layers': 3, 'network_class': 'baselines.her.actor_critic:ActorCritic', 'polyak': 0.95, 'batch_size': 256, 'Q_lr': 0.001, 'pi_lr': 0.001, 'norm_eps': 0.01, 'norm_clip': 5, 'max_u': 1.0, 'action_l2': 1.0, 'clip_obs': 200.0, 'scope': 'ddpg', 'relative_goals': False}
env_name: FetchPush-v1
gamma: 0.98
make_env: <function prepare_params.<locals>.make_env at 0x11f4cb2f0>
n_batches: 40
n_cycles: 50
n_test_rollouts: 10
noise_eps: 0.2
random_eps: 0.3
replay_k: 4
replay_strategy: future
rollout_batch_size: 2
test_with_polyak: False
Creating a DDPG agent with action space 4 x 1.0...
Training...
--------------------------------------------
| epoch              | 0                   |
| stats_g/mean       | 0.8360133           |
| stats_g/std        | 0.070711836         |
| stats_o/mean       | 0.20072728          |
| stats_o/std        | 0.04820741          |
| test/episode       | 20.0                |
| test/mean_Q        | -2.8287208          |
| test/success_rate  | 0.06052631578947369 |
| train/episode      | 100.0               |
| train/success_rate | 0.05789473684210527 |
--------------------------------------------
New best success rate: 0.06052631578947369. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_0.pkl ...
--------------------------------------------
| epoch              | 1                   |
| stats_g/mean       | 0.83661866          |
| stats_g/std        | 0.070463195         |
| stats_o/mean       | 0.20079727          |
| stats_o/std        | 0.046594433         |
| test/episode       | 40.0                |
| test/mean_Q        | -4.7467957          |
| test/success_rate  | 0.05526315789473685 |
| train/episode      | 200.0               |
| train/success_rate | 0.0805263157894737  |
--------------------------------------------
--------------------------------------------
| epoch              | 2                   |
| stats_g/mean       | 0.83717275          |
| stats_g/std        | 0.07052471          |
| stats_o/mean       | 0.20096424          |
| stats_o/std        | 0.046536215         |
| test/episode       | 60.0                |
| test/mean_Q        | -6.798854           |
| test/success_rate  | 0.0368421052631579  |
| train/episode      | 300.0               |
| train/success_rate | 0.06263157894736841 |
--------------------------------------------
--------------------------------------------
| epoch              | 3                   |
| stats_g/mean       | 0.8375681           |
| stats_g/std        | 0.07220657          |
| stats_o/mean       | 0.20106846          |
| stats_o/std        | 0.047893688         |
| test/episode       | 80.0                |
| test/mean_Q        | -8.33555            |
| test/success_rate  | 0.08947368421052632 |
| train/episode      | 400.0               |
| train/success_rate | 0.07315789473684212 |
--------------------------------------------
New best success rate: 0.08947368421052632. Saving policy to /tmp/her/test/policy_best.pkl ...
--------------------------------------------
| epoch              | 4                   |
| stats_g/mean       | 0.8380812           |
| stats_g/std        | 0.074504875         |
| stats_o/mean       | 0.20130211          |
| stats_o/std        | 0.050066657         |
| test/episode       | 100.0               |
| test/mean_Q        | -9.596677           |
| test/success_rate  | 0.12105263157894736 |
| train/episode      | 500.0               |
| train/success_rate | 0.09157894736842105 |
--------------------------------------------
New best success rate: 0.12105263157894736. Saving policy to /tmp/her/test/policy_best.pkl ...
--------------------------------------------
| epoch              | 5                   |
| stats_g/mean       | 0.83841157          |
| stats_g/std        | 0.07488041          |
| stats_o/mean       | 0.2013661           |
| stats_o/std        | 0.051691666         |
| test/episode       | 120.0               |
| test/mean_Q        | -10.214026          |
| test/success_rate  | 0.19473684210526315 |
| train/episode      | 600.0               |
| train/success_rate | 0.1368421052631579  |
--------------------------------------------
New best success rate: 0.19473684210526315. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_5.pkl ...
--------------------------------------------
| epoch              | 6                   |
| stats_g/mean       | 0.838558            |
| stats_g/std        | 0.0755987           |
| stats_o/mean       | 0.20133492          |
| stats_o/std        | 0.054816753         |
| test/episode       | 140.0               |
| test/mean_Q        | -10.3022995         |
| test/success_rate  | 0.32105263157894737 |
| train/episode      | 700.0               |
| train/success_rate | 0.20105263157894737 |
--------------------------------------------
New best success rate: 0.32105263157894737. Saving policy to /tmp/her/test/policy_best.pkl ...
--------------------------------------------
| epoch              | 7                   |
| stats_g/mean       | 0.83899546          |
| stats_g/std        | 0.07556747          |
| stats_o/mean       | 0.20141052          |
| stats_o/std        | 0.05857262          |
| test/episode       | 160.0               |
| test/mean_Q        | -8.998865           |
| test/success_rate  | 0.4921052631578947  |
| train/episode      | 800.0               |
| train/success_rate | 0.33210526315789474 |
--------------------------------------------
New best success rate: 0.4921052631578947. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 8                  |
| stats_g/mean       | 0.83939147         |
| stats_g/std        | 0.075496286        |
| stats_o/mean       | 0.20155519         |
| stats_o/std        | 0.06378212         |
| test/episode       | 180.0              |
| test/mean_Q        | -6.195773          |
| test/success_rate  | 0.6868421052631579 |
| train/episode      | 900.0              |
| train/success_rate | 0.5273684210526316 |
-------------------------------------------
New best success rate: 0.6868421052631579. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 9                  |
| stats_g/mean       | 0.8396733          |
| stats_g/std        | 0.07484583         |
| stats_o/mean       | 0.20158955         |
| stats_o/std        | 0.07016367         |
| test/episode       | 200.0              |
| test/mean_Q        | -3.0124419         |
| test/success_rate  | 0.8947368421052632 |
| train/episode      | 1000.0             |
| train/success_rate | 0.735263157894737  |
-------------------------------------------
New best success rate: 0.8947368421052632. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 10                 |
| stats_g/mean       | 0.8397267          |
| stats_g/std        | 0.07451639         |
| stats_o/mean       | 0.20160568         |
| stats_o/std        | 0.07562807         |
| test/episode       | 220.0              |
| test/mean_Q        | -1.6202121         |
| test/success_rate  | 0.981578947368421  |
| train/episode      | 1100.0             |
| train/success_rate | 0.8794736842105264 |
-------------------------------------------
New best success rate: 0.981578947368421. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_10.pkl ...
-------------------------------------------
| epoch              | 11                 |
| stats_g/mean       | 0.83967227         |
| stats_g/std        | 0.073999055        |
| stats_o/mean       | 0.20169127         |
| stats_o/std        | 0.0800517          |
| test/episode       | 240.0              |
| test/mean_Q        | -1.3142627         |
| test/success_rate  | 0.9868421052631579 |
| train/episode      | 1200.0             |
| train/success_rate | 0.9205263157894737 |
-------------------------------------------
New best success rate: 0.9868421052631579. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 12                 |
| stats_g/mean       | 0.83949757         |
| stats_g/std        | 0.0736674          |
| stats_o/mean       | 0.2017575          |
| stats_o/std        | 0.08310792         |
| test/episode       | 260.0              |
| test/mean_Q        | -1.2539071         |
| test/success_rate  | 0.9973684210526316 |
| train/episode      | 1300.0             |
| train/success_rate | 0.9326315789473684 |
-------------------------------------------
New best success rate: 0.9973684210526316. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 13                 |
| stats_g/mean       | 0.8393596          |
| stats_g/std        | 0.07323617         |
| stats_o/mean       | 0.20179422         |
| stats_o/std        | 0.08519861         |
| test/episode       | 280.0              |
| test/mean_Q        | -1.3014504         |
| test/success_rate  | 0.9921052631578948 |
| train/episode      | 1400.0             |
| train/success_rate | 0.9494736842105262 |
-------------------------------------------
-------------------------------------------
| epoch              | 14                 |
| stats_g/mean       | 0.83927107         |
| stats_g/std        | 0.0729011          |
| stats_o/mean       | 0.20185308         |
| stats_o/std        | 0.08728129         |
| test/episode       | 300.0              |
| test/mean_Q        | -1.1226116         |
| test/success_rate  | 0.9973684210526316 |
| train/episode      | 1500.0             |
| train/success_rate | 0.9410526315789474 |
-------------------------------------------
New best success rate: 0.9973684210526316. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 15                 |
| stats_g/mean       | 0.8392332          |
| stats_g/std        | 0.07264432         |
| stats_o/mean       | 0.20186192         |
| stats_o/std        | 0.08905856         |
| test/episode       | 320.0              |
| test/mean_Q        | -1.110528          |
| test/success_rate  | 1.0                |
| train/episode      | 1600.0             |
| train/success_rate | 0.9347368421052631 |
-------------------------------------------
New best success rate: 1.0. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_15.pkl ...
-------------------------------------------
| epoch              | 16                 |
| stats_g/mean       | 0.8392867          |
| stats_g/std        | 0.07242713         |
| stats_o/mean       | 0.20181471         |
| stats_o/std        | 0.09072706         |
| test/episode       | 340.0              |
| test/mean_Q        | -1.0836452         |
| test/success_rate  | 1.0                |
| train/episode      | 1700.0             |
| train/success_rate | 0.9478947368421051 |
-------------------------------------------
New best success rate: 1.0. Saving policy to /tmp/her/test/policy_best.pkl ...
-------------------------------------------
| epoch              | 17                 |
| stats_g/mean       | 0.8392765          |
| stats_g/std        | 0.072172314        |
| stats_o/mean       | 0.20178589         |
| stats_o/std        | 0.092163086        |
| test/episode       | 360.0              |
| test/mean_Q        | -1.1025819         |
| test/success_rate  | 0.9973684210526316 |
| train/episode      | 1800.0             |
| train/success_rate | 0.946315789473684  |
-------------------------------------------
-------------------------------------------
| epoch              | 18                 |
| stats_g/mean       | 0.8392689          |
| stats_g/std        | 0.07199024         |
| stats_o/mean       | 0.201805           |
| stats_o/std        | 0.09327159         |
| test/episode       | 380.0              |
| test/mean_Q        | -1.2058954         |
| test/success_rate  | 0.994736842105263  |
| train/episode      | 1900.0             |
| train/success_rate | 0.9436842105263158 |
-------------------------------------------
-------------------------------------------
| epoch              | 19                 |
| stats_g/mean       | 0.83924884         |
| stats_g/std        | 0.07176003         |
| stats_o/mean       | 0.20179835         |
| stats_o/std        | 0.09407368         |
| test/episode       | 400.0              |
| test/mean_Q        | -0.95651287        |
| test/success_rate  | 1.0                |
| train/episode      | 2000.0             |
| train/success_rate | 0.9442105263157894 |
-------------------------------------------
New best success rate: 1.0. Saving policy to /tmp/her/test/policy_best.pkl ...
------------------------------------------
| epoch              | 20                |
| stats_g/mean       | 0.8392229         |
| stats_g/std        | 0.07160524        |
| stats_o/mean       | 0.20186374        |
| stats_o/std        | 0.09510062        |
| test/episode       | 420.0             |
| test/mean_Q        | -0.9781728        |
| test/success_rate  | 1.0               |
| train/episode      | 2100.0            |
| train/success_rate | 0.946315789473684 |
------------------------------------------
New best success rate: 1.0. Saving policy to /tmp/her/test/policy_best.pkl ...
Saving periodic policy to /tmp/her/test/policy_20.pkl ...

package versions:
mujoco_py==<IP_ADDRESS>,
gym==0.10.5,
mujoco 150

Hey @pzhokhov
Thank you for respond! What kind of python environment and what version are you using? Say Anaconda installed environment?  Besides, in the starting of your log, it says that you are unable to bind-to core, could you please see mpirun --version? I found only system's openmpi can bind to core which is located in /usr/bin/mpirun.

Unfortunately, with your provided version packages, the success rate of FetchPush is still very low, far from your results. Could you please look at my packages, dependencies installed and conda env packages isntalled.
Besides, I am on ubuntu 16.04.

Problem solved, DO NOT USE conda.

I have OpenMPI 3.1.1 on osx... glad to hear that it works! That is still a mystery to me though that conda would not report any errors, but somehow silently lead to bad training... @Andrewtor have you found anything that could shed light on that?

Thanks, I used the system packed OpenMPI 'mpirun (Open MPI) 1.10.2'. I have tested almost all environments without anaconda, namely, I installed packages through pip3 instead of anaconda, works well.
Yes, it is kind of strange. I am also curious about the reason. Maybe there is some conflict between anaconda.


Attempt to fix Xcode 13 for unspecified platform

sigh. Checks won’t run.

I think you'll need npm run prepare as well, or does that happen automatically at deploy-time?
Also, the @types/node bump might conflict with my PR, but so would npm run prepare.


Unexpected Data in Extract for Forsyth Tech

The Forsyth Tech Bulk Upload file has the following issues.
AI Course Crawler Extract link: https://master.ai-course-crawler.development.c66.me/datasets/courses/16
Extract file in Google Sheets with comparison to expected: https://docs.google.com/spreadsheets/d/1z-8mCAYKzjELVCfZEmTBA4AkBDRxLlmwFTveLIWVh-I/edit?usp=sharing
The information below is applicable to the majority of courses with this data set.
ALL ISSUES

Unexpected data that is not on URL provided to Course Crawler, including credentials and personal enrichment programs
Missing Prerequites and Corequisites for course (should be a Condition Profile format)
Credit Type assumed to be Semester Credit (see https://github.com/CredentialEngine/ai-course-crawler/issues/31)
Data download has ANSI UTF-8 text encoding issues with export to Excel
See:

EXPECTED, see highlighted row in the "Comparison to Correct Bulk Upload" tab in this spreadsheet
Rows 2-15 and 25-54 - these are not courses listed on the URL provided

Row 18  "Improving Study Skills"- all course data is extracted correctly; credit unit type is set to SemesterHour when the URL just lists "Credit".
Here is what was listed for this course in the URL provided to the crawler:

Also prerequisites and corequisites are included on URL but not in extract. Could have extracted the following Header Rows:
Condition Profile: Condition Type = Requires
Condition Profile: Name =The following is required before taking this course
Condition Profile: Description = None
Condition Profile: Condition Type = Corequisite
Condition Profile: Name = The following is required to be taken with this course
Condition Profile: Description = None
(This example listed None for requirements and corequisites; other courses had additional data.)

@rsaksida  - For purposes to release something MVP, let's concentrate on the main fields only, and then when we are sure about the rest of the functionality, let's do things like prerequisites, corequisites, credit-type and other additional fields.


Fix codespell and Trivy vulnerability scanner errors

What type of PR is this?
test

What this PR does / why we need it:
Fix codespell and Trivy vulnerability scanner errors
Which issue(s) this PR fixes:

Fixes #
Requirements:

[ ] uses conventional commit messages

[ ] includes documentation
[ ] adds unit tests
[ ] tested upgrade from previous version

Special notes for your reviewer:
Release note:
none

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 1 (0.0%)  changed or added relevant line in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 78.134%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

pkg/azurelustre/azurelustre.go
0
1
0.0%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
854

Relevant Lines:
1093

💛  - Coveralls


Refactor the memory allocation code in System.Private.Inteop

@jkotas @tijoytom @yizhang82 could you please have a look?

LGTM

Thanks @tijoytom
@jkotas I am going to merge it but if you have any more comments, please let me know and we can fix it.


Try pools

Added a pool for allocation of the bundles that tie keys to operation.  Improved the multithreaded performance a bit.  Also made some modifications to the ring buffer to improve performance.
@alexandercampbell-wf @rosshendrickson-wf @ericolson-wf @seanstrickland-wf @matthinrichsen-wf @wesleybalvanz-wf @blakewilson-wf

+1

+1


Does keysubtracter use vector addition subtraction or only simpe addition subtraction ?

Hello. Big Thank you for your codes Friend !!!
Why reult of  key subtracter is diferent when in this, for example https://github.com/MrMaxweII/Secp256k1-Calculator calculator ?
In Yur example in keyhunt:
02d1e9e73f79c1c86eda6096987c13c7547f808f571910c3d50f0dfd94456e21f6 # +<PHONE_NUMBER>32
03a2efa402fd5268400c77c20e574ba86409ededee7c4020e4b9f0edbee53de0d4 # target
First, why pubkey change them prfixe from "02" to "03" ?
And why the I add to pubkey in calculator, I get result:
02a2efa402fd5268400c77c20e574ba86409ededee7c4020e4b9f0edbee53de0d4 +<PHONE_NUMBER>32 = a2efa402fd5268400c77c20e574ba86409ededee7c4020e4b9f12e3345631806 !!!
and if I not remove 02, then:
02a2efa402fd5268400c77c20e574ba86409ededee7c4020e4b9f0edbee53de0d4 +<PHONE_NUMBER>32 =
a2efa402fd5268400c77c20e574ba866949034211daee06d3a4c7119a4f69584 !!!
**So,
03a2efa402fd5268400c77c20e574ba86409ededee7c4020e4b9f0edbee53de0d4 <> a2efa402fd5268400c77c20e574ba86409ededee7c4020e4b9f12e3345631806 <>  a2efa402fd5268400c77c20e574ba866949034211daee06d3a4c7119a4f69584
!**
Albrto, you key substracter is good idea. This method already tested, and worked. But, please, see you code, I think in code is some error, what if You remove error, this will be again Your's  helpfull   supercode ))
Br !!!

keysubtracter use Elliptic curve Addition.
02 y 03 are standar notation in  compress publickey.
Please read the next link almost two times: https://www.oreilly.com/library/view/mastering-bitcoin/9781491902639/ch04.html


chore: Use slices for computing args hash in class registerer

To remove capsule usage without getting 7-minute build times.

This is currently failing to build with:
$ ../../noir/noir-repo/target/release/nargo build --package contract_class_registerer_contract
The application panicked (crashed).
Message:  ICE: should have slice capacity set for value v738 being stored at v726
Location: compiler/noirc_evaluator/src/ssa/opt/flatten_cfg/capacity_tracker.rs:134

This is a bug. We may have already fixed this in newer versions of Nargo so try searching for similar issues at https://github.com/noir-lang/noir/issues/.
If there isn't an open issue for this bug, consider opening one at https://github.com/noir-lang/noir/issues/new?labels=bug&template=bug_report.yml


change ido pool to use PDAs

Updates the old IDO pool code to use the latest anchor features.
Main Updates

Use PDAs everywhere. For the IDO account, redeemable mint account, token accounts

Store key bumps in a struct

Get rid of sysvar clock account and load internally instead
Use all of the fancy new account types

Signer
Program
Account

Close and reclaim rent from PDA token accounts

New features!
auto-redeemable tokens
IDO organisers will be able to redeem tokens on user's behalf after the end of the IDO. This will prevent there from being unclaimed tokens leftover weeks after the IDO finishes.
Time delayed USDC withdrawals
One of the biggest weakness of this launching mechanism is the ability of large whales to skew perception by depositing large amounts of capital and withdrawing at the last second. E.g. Mango IDO where the max value in the IDO pool was $500m and ended up at $70m.
To discourage this behaviour we add a small time-delay to returning USDC after it has been withdrawn from the pool. Participants can still withdraw their USDC at any time up until the end of the IDO. However, this USDC will only be returned to them after a set period of time, for example 1 week. This adds a time cost of money for whales that intend to attempt to manipulate prices and abuse the unlimited deposits option.

@armaniferrante Spent some time today reading over it very carefully. Spotted a few obvious bugs and fixed them, plus cleaned up comments and dead code. It's ready for a review / merge whenever you have the time. Thanks!

@armaniferrante @Henry-E I just wonder:

in the initialize_pool function we use seeds = [ido_name.as_bytes()]
in the exchange_redeemable_for_watermelon function we use: let seeds = &[ido_name.trim_ascii_whitespace(), bump];
are they always the same? As I see, the ido_name has been manipulated before store into IdoAccount account

Yes, they will be the same. The difference you're seeing is just linked to how the stored ido name variable has extra whitespace at the end.
However, I know think a better solution is to force the JavaScript client to use a seed with extra whitespace added. Rather than have the smart contract handle the trimming logic.


Removed the sentence "Run by clicking the RUN button" as there was no…

… RUN button anymore.
(at the start of the examples sections)

Thanks


example program doesn't compile

I ran the example program, core 2.0.2. Got this below compile error:
C:\Users\X\Documents\Arduino\libraries\VEML3328\src\VEML3328.cpp: In member function 'void VEML3328::setConfiguration(uint16_t)':
C:\Users\X\Documents\Arduino\libraries\VEML3328\src\VEML3328.cpp:54:14: error: invalid conversion from 'char*' to 'const uint8_t*' {aka 'const unsigned char*'} [-fpermissive]
   Wire.write(bytes,2);
              ^~~~~
In file included from C:\Users\X\Documents\Arduino\libraries\VEML3328\src\VEML3328.cpp:27:
C:\Users\X\AppData\Local\Arduino15\packages\esp32\hardware\esp32\2.0.2\libraries\Wire\src/Wire.h:107:18: note:   initializing argument 1 of 'virtual size_t TwoWire::write(const uint8_t*, size_t)'
     size_t write(const uint8_t *, size_t);
                  ^~~~~~~~~~~~~~~
exit status 1
Error compiling for board Adafruit ESP32 Feather.

I changed:
void VEML3328::setConfiguration(uint16_t configuration) {
  char bytes[2];
  bytes[0]= (configuration >> 0) & 255;
  bytes[1]= (configuration >> 8) & 255;
  Wire.beginTransmission(VEML3328_I2C_ADDRESS);
  Wire.write(COMMAND_CODE_CONF);
  Wire.write(bytes,2);
  Wire.write(0);
  Wire.endTransmission();
  lastConfiguration = configuration;
}

to:
void VEML3328::setConfiguration(uint16_t configuration) {
  char bytes[2];
  bytes[0]= (configuration >> 0) & 255;
  bytes[1]= (configuration >> 8) & 255;
  Wire.beginTransmission(VEML3328_I2C_ADDRESS);
  Wire.write(COMMAND_CODE_CONF);
  Wire.write(bytes[0]);
  Wire.write(bytes[1]);
  Wire.write(0);
  Wire.endTransmission();
  lastConfiguration = configuration;
}

...and the error went away.
The sensor still isn't giving me data, but it's a custom board and I haven't finished debugging. Maybe I have a hardware mistake. Will report back when resolved

Hello, I ran it on an Arduino Nano board and haven't tested it on an ESP yet. It seems like a problem with the wire library of the ESP. Can you try it on an Arduino board and let me know if it works?
The hardware is fairly simple, but you can check if it is probably connected by running the I2C scanner example that comes in the Wire library.
Please keep me updated.

Just finished my latest PCB, but it's still not working on my ESP32. I do not own an Arduino.
This code:
void color_sensor_setup2(void)
  {
  if(!RGBCIR.begin())
    Serial.println("ERROR: couldn't detect the sensor");

  else
    {
    Serial.println("Vishay VEML3328 RGBCIR color sensor auto mode enabled.");
    RGBCIR.Enable();                    //enable the sensor channels
    RGBCIR.setGain(4);                  //set the amplification gain to 4 (0.5,1,2,4 can also be selected)
    RGBCIR.setSensitivity(high_sens);   //set the sensitivity mode (low_sens, high_sens can also be selected)
    RGBCIR.setDG(4);                    //set the digital gain (1,2,4 can also be selected)
    RGBCIR.setIntegrationTime(IT_50MS); //set the sensor's integration time or the time it takes to take one measurement (IT_50MS, IT_100MS, IT_200MS, IT_400MS can also be selected)

    delay(1000);
    }
  }

Outputs Vishay VEML3328 RGBCIR color sensor auto mode enabled regardless of whether the sensor is connected or not.
Serial.println(RGBCIR.getGreen()); just returns 0's. No errors returned.

Solved. I had used the Huzzah Feather board variant during compile, which incorrectly defaults to pins 22/23 for SDA/SCL. I changed the board to ESP32 WROVER which uses the correct hardware pins 21/22. Ugh!


VSCode + Remote Containers not working

Do you have any idea how to fix this issue, with this error message:
"unable to prepare context: path "d:foobar.devcontainer" not found"
Somebody posted this question to your article, and then answered it themselves, but didn't quite clarify how. They just said "the files, which should be opened inside the devcontainer must already lie in WSL space". What files? What space?
Thank you.

Nvm, I've figured it out. He meant that the folder you want to open in a container in VS Code has to reside in the Linux filesystem (/home), not in the Windows filesystem (/mnt). Once I set my project's location to a directory in the Linux filesystem (eg /home/user/my_project), and not in the Windows filesystem (eg /mnt/d/my_project), opening project files in container worked for me too. Thx.

Glad you figured it out! Thanks for posting this.


middleware: add errors middleware host header config

What does this PR do?
Adds a new configuration called Host to the errors middleware. The value set for this configuration is used as the host header when proxying requests to the error service.
If no config value is set, or if it's set to an empty string, then the original request's host header will be used.
Motivation
fixes #8267
More

[x] Added/updated tests
[x] Added/updated documentation

Additional Notes
I'm curious to know if any other changes are necessary when updating the Kubernetes CRDs. It seems to me like the config is dynamically read in, so there's no need to bump the CRD version here, but I could be wrong!

Hello @aaronraff,
To fix the issue https://github.com/traefik/traefik/issues/8267 a new option is not necessary as the PassHostHeader option could be leveraged to forward the configured error service URL Host instead of <IP_ADDRESS>.
After looking deeper at the Errors middleware code, we also thought that it is better to forward the client request Host header to the configured error service instead of <IP_ADDRESS> and we opened a PR for that https://github.com/traefik/traefik/pull/8460.
As this PR introduces a new option and according to what we said before we will close it.
Thanks again for your contribution!


Add a way pick combos from a menu.

Combo collections can be quite big, and one can easily forget combo keyword. A good way to help the user would be to have a global shortcut that would pop a menu where the user can navigate groups and combos.

This would be very important, yes. I would've made a similar entry if this weren't there, it's a must-have for those with lots of similar related text replacements --a popup is a crucial addition !

The feature as been implemented, but not as a menu, see issue #166 for details and test build.


Generate packages for publishing

[x] Google Play Store

The package generation for Microsoft Store, Apple Store and Meta Quest will be on hold for now due to an incomplete Developer account for the platforms.

Generated Android packages using Bubblewrap


Migration history is not migrationPath-aware

Migration history table stores only version and apply_time.
But there's a problem when we need to migrate down - we need to specify exact migrationPath for migrations we want to revert!

The current implementation assumes that migrations are all located in one place. this will be solved when we support multiple paths. duplicate of #384.

Just for others who will meet the same problem.
I've used different migrationPath for installing CMS extensions migrations.
I have information on migrationPath and extension ID.
Therefore solution was to separate all extensions migrations to separate table - one table for one migration.
The better solution is expected from solving #384

https://github.com/deesoft/yii2-console
Support multiple path and compatible with current migration table.


Upgrade to Angular 16

Hello,
Thanks for the great project! I noticed the project is using Angular 13 as per package.json. Any plans to upgrade it to Angular 16?
Best,
Daniel

Hello Daniel!
Thank you for the feedback! Yes, I plan to upgrade it, but don't know when exactly yet.


Feature/vitisbuild

Thanks for the PR! Could you change the target branch to feature/vitisbuild? We are gathering there at the moment all the fixes needed to run VitisBuild correctly.


Bar chart - allow null values in data series.

First, xchart is great so thanks for all the great work.
Say that we have series 1 and series 2.
Series 1 contains values for A and B  and series 2 contain values for B and C (A, B and C are the x axis labels).
This kind of bar chart is impossible to present using xchart since I can't pass null values for C in series 1 and A in series 2.
Also, if you do decide to add this feature I think that the null values should not create blank spaces of missing bars. In my opinion, the bars should be one next to the other without blank spaces.
This is a very common use case and I would really appreciate it if you consider adding this feature to xchart.

Done. See latest snapshot jar or code.

I'm getting "X-Axis data must be of type Number or Date for X-Y chart types!!!" when I create a series with null values and then add that series to the bar chart.
Can you please send me an example? (How can I add a series with null values?)


refactor/change response documentation format

docs(README.md): change folder "demo" to "docs"
chore(npm): upgrade dependencies
refactor(src/lib/buildRequest): change response example format
test(src/lib/buildRequest): make all test pass

closes #30

Very good work, thank you! I think I will have to release a minor version after this since it's a breaking change.
Before I merge this, can you please fix the linting issues? Your prettier config must have gotten rid of some semicolons :P It should have warned you about this when you made the PR, but I made a mistake in the Github Actions workflow and it only runs on push.

Done, I don't use semicolons on a normal day!
:grin: :grin: :grin:


Improved contributing_to_vhive.md: More detailed rationale and technique for Rebase & Merge

Summary
Improved the descriptions in the "Rebasing on the Main Branch" and "Maintaining a Clean Main Branch & Avoiding Merge Commits" sections.
Implementation Notes :hammer_and_pick:

Provided an example of the consequence of a messy merge without rebasing
Included git checkout your-branch in the instructions on how to rebase on main
Included clearer motivations behind maintaining a clean main branch and avoiding merge commits

External Dependencies :four_leaf_clover:

N/A

Breaking API Changes :warning:

N/A

Simply specify none (N/A) if not applicable.

@googlercolin Please, sign your commit and update the branch.

Please sign the commit.
BTW, do we mention the requirement to sign commits in the doc?

@ustiugov, I have signed the commit and pushed it here. The spellcheck linter is a bit weird because "linearizes" is an actual word in the Oxford dictionary. "Upstream's" was also flagged out. I've changed them nonetheless.
For the part on signing commits, I think I will make another PR to include it in the doc as it is not there at the moment.


Freezing the GUI

During the processing of one big file, after processing about 400 scans (256 points window), the GUI is freezed.

Was it because the GUI used to much ram? I noticed that every time I pressed Next scan the ram usage goes up.
The GUI itself does not keep anything after pressing Next scan so if the problem is really the ram usage then the your library is probably the culprit.


Implementing a generational copying GC on top of page allocator (#2706)

(copied from live edits here: https://hackmd.io/s/SJrB4eSKK)
Original Author:  Ömer Sinan Ağacan (@osa1)
Here I describe just one way of implementing a copying generational GC, using
page allocator implemented in #2706.
Key concepts
Reference: The GC Handbook.
Descriptions below are in my words. When confused, please refer to The GC
Handbook.

Age of an object: How many times the object survived GC.

Generation/generational: Generational means we split heap into regions.
These regions are called "generations". Generations are numbered
incrementally, starting with 0. When we do a GC, instead of collecting the
whole heap, we decide how many generations to collect. If we want collect N
generations, then we collect generations [0,N).
The algorithm described here doesn't allow collecting all subsets of
generations. We always collect generations [0,N) for some N > 0.

Evacuation: Same as in current copying GC, but an object may be evacuated
to a different generation than its current generation. See below for details.

Promotion: When an object in generation N is evacuated to generation
N+1, it's called promotion.

Eager promotion: In some cases we want to evacuate an object in
generation N to generation M, where M > N + 1. This is called eager
promotion.

Major GC: Collecting all of the generations.

Minor GC: Not collecting one or more of the generations.

Remembered set: In a GC algorithm where only some of the heap is
collected, we need to keep track of objects in collected regions that are
pointed by uncollected regions, and keep those objects alive.
Remembered sets are one way to maintain such pointers. A generation other
than the youngest will have a remembered set. When an object is mutated (i.e.
a field is updated with a pointer value), the mutated object is added to the
remembered set of its generation.
In a GC, remembered sets of uncollected generations are treated as roots.

Write barrier: Code that runs before or after a heap mutation (i.e.
inserting a value to an object field, or an array).
https://github.com/dfinity/motoko/pull/2702 tries to find all the places in
the compiler and the runtime system where we do heap mutation.

Aging: If we want to keep new allocations in generation 0 for more than
one GC, that's called "aging". Aging = N means new allocations stay in
generation 0 for N collections.

Memory manager concepts
These are also summarized in https://github.com/dfinity/motoko/pull/2706.
Discussion below is slightly simplified and ignores large objects.

Large object: An object that is too large to copy. Ideally we want to
avoid copying these objects and implement some kind of mark-sweep style
collection.

Page: A memory region, a few words smaller than 64 KiB. Each page has a
few words metadata at the beginning. The rest is used by spaces for
allocation.

Space: A memory region that supports allocation. Internally a Space is
a list of pages, with a "heap pointer" pointing at next free space in the
current page.
Initially a space has one page. It allocates new pages as we allocate into
the space and fill the current page.

Space and Page types have various methods to support copying and
mark-compact collections.
A special Space called ALLOCATION_SPACE is used directly by the mutator
(Motoko code) to allocate new objects.
Implementing a generational GC using Space and Page types
Each generation will be a Space.
Space type will be extended with a new field for the "remembered set" for the
generation. For ALLOCATION_SPACE this field won't be used as (1) it can't
point to a younger generation (2) it will be collected always.
After an update message we decide how many generations to collect (0 or more, 0
meaning no GC). I don't know how to decide on this. We will probably need to
start with a conservative algorithm, then improve it based on benchmarks and
experimentation, as we did for the current scheduler.
After deciding how many generations to collect, we run the standard copying GC
algorithm, with these differences:

Each collected generation will have a new Space, called "to space". Old
Space for these generations will be called "from space".

Uncollected generations do not need new spaces. Existing spaces will be used
to copy new objects to these generations.

Remembered sets of uncollected generations will be treated as roots.

Maintaining remembered sets: To add an object or field address to the
remembered sets we use write barriers. Whenever an object is mutated, the write
barrier (mutation code) adds the object to its generation's remembered set.

evac (the evacuation function) will copy an object in generation N to the
generation N+1. When N is the oldest generation it will copy it to the to
space for the current generation.
When the object is in an uncollected generation, evac returns early and
does not copy the object.

(No changed needed in scav)

After a GC, from spaces of collected generations will be freed. No changes
needed in Space::free.

That's it! Shouldn't be too difficult once the page allocator is stable.
(optional) Eager promotion
According to generational hypothesis, new allocations die young, but if an
object survived a few GCs, than it will likely survive many more GCs.
So if a new allocation is pointed by an old object, it makes sense to evacuate
the new allocation to the old generation with the old object, as old object
will keep it alive for many GCs.
Eager promotion can be easily implemented by passing an extra argument for
"target generation" to evac. When scavenging a remembered set, pass the
generation number (or reference, pointer) to the generation of the remembered
set. evac then copies the current object to the target generation.
Example: if we have 3 generations (ALLOCATION_SPACE or 0, 1, 2) and we see an
object in ALLOCATION_SPACE when scavenging the remembered set of generation
2, we evacuate the object to generation 2 instead of 1.
I'm not sure how beneficial eager promotion is. In generational copying GCs I
worked on before this was already implemented, so I didn't have the chance to
measure its effectiveness.
(optional) Aging
According to generational hypothesis, new allocations die young, but maybe not
in exactly one GC. So in some cases it makes sense to collect new allocations
always for a few GCs before promoting to an older generation.
There's an easy way to implement this: just have multiple generations that are
collected always. For example, if we want to collect an object always until it
survives N generations, implement N generations that are collected always. This
is how GHC implements aging.
Alternatively we could store ages in object headers. We current have a few bits
available for this, and aging parameter will be very small (most likely just
2).
Similar to eager promotion, I'm not sure about effectiveness of this idea.
(optional) Using different collection algorithms
There is an easy way to use an arbitrary collection algorithm for the oldest
generation:

Treat oldest generation remembered set as root. DO NOT collect the oldest
generation yet.

When collecting rest of the generations, evacuate live objects to the oldest
generation.

Now any objects that are potentially live will be in the oldest generation.
Collect oldest generation with whatever algorithm you want. (e.g.
mark-compact)

This is used in GHC's concurrent collector.
In general, when collecting a region of the memory using a moving GC algorithm
(e.g. copying, mark-compact), any pointers to the collect region need to be
updated. That means younger objects will have to be evacuated first to the
generation being collected differently.
However, if we collect the oldest generation using a non-moving algorithm (e.g.
mark-sweep), then we don't need to evacuate all live younger objects to the
oldest generation, as pointers from young to old won't need to be updated. When
we see an object in the oldest generation during evacuation we simply mark it.

Thanks! This is not yet incremental, right, and eventually we need a full, major GC?
Are there designs for incremental GC as well?


Fix CI

Details
Reduce size of video grains generated by hypothesis in tests. This addresses an issue where hypothesis now restricts the size of test data which it generates. Large sizes never actually worked correctly.
Pivotal Story
Story URL:
Related PRs
Where appropriate. Indicate order to be merged.
Links to external test runs/working deployment
Where appropriate, if separate to default CI run
Submitter PR Checks
(tick as appropriate)

[ ] PR completes task/fixes bug
[ ] Tests exercise code appropriately
[ ] New features and API breaks are flagged in commit messages using magic strings
[ ] Documentation updated (README, Confluence, Docstrings, API spec, Engineering Guide, etc.)
[ ] Downstream repos have been checked for potential breaks & fixed as needed
[ ] APIs/UIs/CLIs updated as required
[ ] PR added to Pivotal story
[ ] Follow-up stories added to Pivotal
[ ] Any temporary code/configuration removed (e.g. test deployment environment, temporary commontooling branch)
[ ] Any pins against pre-releases have been removed

Reviewer PR Checks
(tick as appropriate)

[ ] PR completes task/fixes bug
[ ] Tests exercise code appropriately
[ ] Design makes sense, and fits with our current code base
[ ] Code is easy to follow
[ ] PR size is sensible
[ ] Commit history is sensible and tidy

Info on Cloudfit PRs

The checks above are guidelines. They don't all have to be ticked, but they should all have been considered.
For more details on how to asses PRs, see: https://github.com/bbc/rd-apmm-docs-ways-of-working/blob/master/workflow/PRChecklist.md

Oh, it was changed to draft as I reviewed it :-)

Fixes made anyway :)


Update FunctionNaming to support factory funcs

FunctionNaming does not report factory functions when the function name
is identical to the type of the result.
These factory functions can have the same name as the class being
created.
This closes #1639

Codecov Report

Merging #1668 into master will increase coverage by 2.52%.
The diff coverage is 50%.

@@             Coverage Diff              @@
##             master    #1668      +/-   ##
============================================
+ Coverage     75.86%   78.39%   +2.52%
+ Complexity     1836     1635     -201
============================================
  Files           326      249      -77
  Lines          5507     4703     -804
  Branches       1002      884     -118
============================================
- Hits           4178     3687     -491
+ Misses          795      543     -252
+ Partials        534      473      -61

Impacted Files
Coverage Δ
Complexity Δ

...b/arturbosch/detekt/rules/naming/FunctionNaming.kt
94.73% <50%> (-5.27%)
9 <0> (+1)

...tekt/formatting/wrappers/SpacingAroundOperators.kt

...h/detekt/formatting/wrappers/SpacingAroundComma.kt

...arturbosch/detekt/formatting/FormattingProvider.kt

...bosch/detekt/formatting/wrappers/ImportOrdering.kt

...tlin/io/gitlab/arturbosch/detekt/api/YamlConfig.kt

...in/io/gitlab/arturbosch/detekt/api/SplitPattern.kt

...n/io/gitlab/arturbosch/detekt/api/ConsoleReport.kt

...ekt/sample/extensions/rules/TooManyFunctionsTwo.kt

...turbosch/detekt/formatting/wrappers/PackageName.kt

... and 68 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 9855f84...cc133aa. Read the comment docs.


[test_propagate_nan]: Fails to run correctly on PVC

The end-to-end core test test_propagate_nan fails to run correctly on a PVC GPU. We need to investigate the cause of the functional problem(s).

For tl.PropagateNan.NONE and tl.PropagateNan.ALL, we use LLVM::MinNumOp and LLVM::MinimumOp for tl.minimum. But they are all converted to  OpExtInst %float %1 fmin %30 %31 because OpenCL.std does not support the IEEE 754-2008 definition for minNum

See this link.
tl.maximum is also this case.


running error

Excuse me! When I was debugging main.py, the 'primitive_ation' of the output 'nonlocal_variable' in line 503 was none, but the display was' grab '. Did you encounter this situation?

Excuse me! When I was debugging main.py, the 'primitive_ation' of the output 'nonlocal_variable' in line 503 was none, but the display was' grab '. Did you encounter this situation?


Routing not working

I implemented routing as described in https://nuxt-swiftsearch.netlify.app/routing.
However when I select any refinement the Url becomes /category?INDEX=[object+Object] and the refinement is not selected. What am I missing here?

Thank you, @Rigo-m ! It seems the issue resolved on its own, seems to work fine now :-)

Maybe you just had to reload the application after adding router.options.ts :)
Also: be mindful of a problem handling query strings with nuxt 3.11, which is either not present in 3.10 or will be resolved in 3.12


!destroy cmd with radius

Should add an option as a radius to destroy all units into a given radius, for the !destroy command for units

Possibility to have this for scenery as well? To remove trees for example

Implemented in #31
Crifort's suggestion is still to do


Define stackoverflow tag

We should probably define a stackoverflow tag so that users can post questions and we can easily find them. It looks like 'monocle' has already been defined, so maybe 'scala-monocle'.
Once a decision has been made, we should add it to the readme.

I have enough reputation to add tags, but I couldn't find any questions on Stack Overflow specifically about Monocle.
Could you point me to a question, so that I can edit to add the 'scala-monocle' tag?

I found a few references to Monocle in answers but no specific question. So it probably doesn't make sense to create a tag at the moment.
Thanks @flicken , if it changes I will ask for your help :)

not required


Fix project without .git files

Screenshots

Checklist
Please ensure all of the following are completed before submitting the PR:

[x] Code has been tested and verified.
[x] Documentation has been updated to reflect the changes.
[x] All tests pass successfully.
[x] Code follows the project's coding guidelines and style.
[x] The branch is up-to-date with the latest changes from the main branch.
[x] Reviewed by at least one other contributor.

Thanks for submitting a pull request!
We will review it as soon as possible.

@aurora-care-bear please approve this PR.

Hey @Angelk90,
Thanks for your contribution.
Your PR has been merged!
Your name will appear on https://auroraeditor.com/#contributors in a few moments, if you have contributed to the editor.
Thanks again for your contribution!
Kind Regards,
Aurora Editor Team.


i'm too dumb to install go packages

i do git clone https://github.com/ericchiang/pup/ then cd into the directory and type go get github.com/ericchiang/pup/
it doesn't print anything
i type pup and it says Command 'pup' not found, but there are 16 similar ones.
tell me how i actually do it cause i cant find any place that is willing to show me how to install it

The Install section of the README is woefully out of date, but it'll likely never be fixed, as @ericchiang seems to have abandoned this project.
To install with Go:
go install github.com/ericchiang/pup@latest

Also, don't bother installing with Homebrew, as we've already deprecated it anyway.


Newsletter Timeline: Drop Date 9/28/16

9/1 - Open Call for Topics to Community (Tweet on 9/1, Google Group 9/1, DevCall 9/6)
9/7 - Last Call for idea submissions
9/8 - Close Call for Topics
9/15 - Ana to create draft + find headliner image (request design help if needed)
9/19 - Send email requesting feedback to Medium editors (BG, CW, FP, JW, MB)
9/22 - Send email reminder to editors - last chance to respond on 9/23
9/23 - Close feedback process for editors, prepare for final draft
9/28 - Publish on Medium

Update from 9/12 - closed call for topics for 9/28. Initial draft due 9/15.

@Ruv7 Did you get enough topics?

@willingc - No.

How many do you need? I could likely find something at PyData. One of the JupyterDays Atlanta presenters will be presenting something on birds songs and data analysis.

One technical article. I have two other non technical topics I'd like to write about.

Thanks @willingc  for the initial review. I sent out the draft to the newsletter editing team. Feedback closes 9/23.

@Ruv7 You may want to @-mention any folks that haven't responded by 9/22 EOD

Yes, thanks for the reminder.

In case you didn't see the email from yesterday, here is a quick flag for @ellisonbg @fperez @Carreau @JamiesHQ  @willingc  - the draft of the next newsletter is available on Medium. Please let me know if you have any overarching feedback otherwise you can make your edits to the document directly making to sure to click "close" and "save for later" on the bottom right when you're done with your work. Feedback due by Friday the 23rd.

ps. I didn't give you as much time to respond as I would have liked. I updated the next newsletter's timeline to increase this review time.

FYR: I just added images for Featured Contributors and a banner image...

Newsletter dropped as planned on 9/28. Thanks to all who contributed! Let me know if you guys see anything that we can do better next time. Comment on the issue for the [10/20 newsletter].(https://github.com/jupyter/newsletter/issues/50)

Thanks @Ruv7  👍


Heat recovery agent

Added heat recovery agent to the EnergyEfficencies list of agents.  Modified Economizer to fix some issues that were found with it.

@rlutes bump...can we merge this?  Was there anything else?


Add Markdown (md) support

There is a proposal to use "text/markdown" but it is still a draft
(https://datatracker.ietf.org/doc/draft-ietf-appsawg-text-markdown/)
in RFC editor queue so it seems wise to use "text/x-markdown" as long
as it is not official (see http://stackoverflow.com/a/25812177 for a
discussion on Markdown's mime type on Stack overflow).

Thanks for the references, and good work!


feat:fix:  added Gaurav-Verma07 and fixed a minor bug in index.js

Hii,
I've added my project cardgame.
and also fixed a minor bug in index.js line 62 to open the project tab upon click.
Please review and merge accordingly.
Thanks.

Hii, I've added my project cardgame. and also fixed a minor bug in index.js line 62 to open the project tab upon click. Please review and merge accordingly. Thanks.

good catch! gaurav


themeToVars don't export other object from createTheme

What package has an issue
@mantine/vanilla-extract
Describe the bug
I have no access to the other object in vanilla-extract. Is this intentional or a bug?
I resolved the issue with a direct theme import into my css file and load it directly from there. If this the correct way can someone told me how to create a interface for the other object?
Thanks for the help!
What version of @mantine/* page do you have in package.json? (Note that all @mantine/* packages must have the same version in order to work correctly)
7.0.0-beta.2
If possible, please include a link to a codesandbox with the reproduced problem
No response
Do you know how to fix the issue
None
Are you willing to participate in fixing this issue and create a pull request with the fix
None
Possible fix
No response

There is no way to resolve these variables. If you need to access these values, import theme object directly.

@rtivital thanks you for the quick answer. Any idea how to type the other object in v7? Because the v6 way is not working.


fix the number on ImageNet classification validation error

According to the three paper, Inception(https://arxiv.org/pdf/1409.4842v1.pdf), Inception V2(https://arxiv.org/pdf/1502.03167v3.pdf), Inception V3(https://arxiv.org/pdf/1512.00567v3.pdf).
Their ImageNet Classification Validation Error should be 6.67%, 4.9%, 3.46%。

Can one of the admins verify this patch?

@vrv


Added: "Install with Sketch Runner"

Hey there Andrew,
I just added that it is now possible to install and update Sketch Palettes through Sketch Runner. Hope that's ok. ✌

Hey, thanks for contributing!
I think I want to hold off adding that though. Sketch Runner is a badass plugin, but I'm hesitant to encourage installing Sketch Palettes that way. There was a tool called Sketch Toolbox previously that allowed you to search and install Sketch plugins also, which was nice. But I was getting a lot of bug reports for the plugin and it turned out that installing via Sketch Toolbox was the culprit. I think Sketch Runner is a super useful plugin, and probably much more stable and supported than Sketch Toolbox was, but I'd like to avoid that scenario in the future. Anyway, I really appreciate your input, and your interest improving the plugin.


getAllPosts

getAllPosts > 10 post , please tutorial ?

please reference the wordpress docs on returning more posts from the API:
https://developer.wordpress.org/rest-api/reference/posts/


Next page without progress logic

works towards fixing #674

currently having an issue where the redirect takes me back much further than intended, also the isDevelopment tag doesn't work as expected but i could again try an early return statement for dev=true

asides always seeing the locks flash, (should be solved in the other PR) there are some times it delays for 1.5-2s before moving )again tried reproducing but couldn't.


Improve accuracy of ProjectsIdentifiedProgressDetails events for builds loaded from configuration cache

Fixes #?
Context

Use build file rather than build directory for Project.getBuildFile()
Do not fire this event for builds whose projects were not loaded.

Contributor Checklist

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[ ] Check "Allow edit from maintainers" option in pull request so that additional changes can be pushed by Gradle team
[ ] Provide integration tests (under <subproject>/src/integTest) to verify changes from a user perspective
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[ ] Ensure that tests pass sanity check: ./gradlew sanityCheck
[ ] Ensure that tests pass locally: ./gradlew <changed-subproject>:quickTest

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[ ] Verify design and implementation
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@bot-gradle test and merge

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fix build error in  the sample project. Let the sample project be suc…

Let the sample project be successfully built in xcode11.

Thank you for your contribution, but I haven't found any similar problems with Xcode11.


Fsspec is inconsistant when doing fs.ls

What does this PR do?
FSSpec, which we use for doing IO which may or may not be local, has some inconsistancies in how it lists files. On local and some remote systems fs.ls(path) gives a list of strings and others (hdfs for example) it gives a list of dictionaries with the paths and meta data.
Switching to fs.listdir(path) seems to give consistent behavior on the platforms I tested. Despite fsspec listing that ls is an alias for listdir in their documentation.
Fixes # (issue)
Before submitting

[ ] Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
[X] Did you read the contributor guideline, Pull Request section?
[X] Did you make sure your PR does only one thing, instead of bundling different changes together? Otherwise, we ask you to create a separate PR for every change.
[ ] Did you make sure to update the documentation with your changes?
[ ] Did you write any new necessary tests?
[X] Did you verify new and existing tests pass locally with your changes?
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Anyone in the community is free to review the PR once the tests have passed.
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The failing tests seem to be an nvidia mirror issue?
E: Failed to fetch https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/Packages.gz  File has unexpected size (47871 != 49498). Mirror sync in progress? [IP: <IP_ADDRESS> 443]

Good catch! Did you file an issue for fsspec to fix their HDFS implementation?

Can we get a test for this fix?

Can we get a test for this fix?


ctr: drop labels from ctr containers subcommand list

The labels can be very long (e.g. cri-containerd stores a large JSON metadata
blob as io.cri-containerd.container.metadata) which renders the output
useless due to all the line wrapping etc.
The information is still available in ctr containers info «name».
Signed-off-by: Ian Campbell<EMAIL_ADDRESS>

[... many pages...]

Codecov Report

Merging #1456 into master will not change coverage.
The diff coverage is n/a.

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##           master   #1456   +/-   ##
======================================
  Coverage    40.8%   40.8%
======================================
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  Lines        2924    2924
======================================
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  Misses       1453    1453
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@ijc Sorry for the long label. :p That's our checkpoint now. Will use Extension when it's merged. https://github.com/containerd/containerd/pull/1378

@Random-Liu I think it's reasonable to have either long labels or many labels so I don't think it is your fault at all (and yours are ong, but they aren't really all that long). IMHO this PR is worthwhile even if you happen to migrate away and solve the case which is actually hitting me.

How about printing the number of the labels instead?

That doesn't seem terribly useful to me, perhaps a simple "has" / "has-not" indicator for labels would be useful, but TBH I'm not even convinced by that.
I did initially try making labels options (ctr containers --labels) but it was cluttering the code a bit and since the information is in ctr containers info foo it didn't seem worth pursuing.

Obviously we have downplayed the ctr tool as a dependable interface in general, so I'm fine with this PR from that angle. However, demo-ing at conferences to show simple label interactions is kind of a nice feature and if they disappear totally that's not as great.
Given the string is being assembled in the current code, seems simple enough to just trim to {some reasonable # of chars} and add an ellipsis in the ctr default output. Add to that some clear docs that you can view all labels via the info output.

If you remove this, there is no way to view labels on a container.
Seems like #1378 is the right fix for this and move all of this into the extensions field.

@estesp/ @stevvooe  Labels are visible for a container in the ctr c info output:
$ sudo ./bin/ctr c info aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa | head -n3
{
    "ID": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "Labels": null,

So they don't disappear completely (whether that is good enough for stage demo purposes I don't know). Sorry for the degenerate example but:
$ sudo ./bin/ctr c label aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa foo=bar
ctr: container.Image field is immutable: invalid argument

Maybe I'm driving it wrong (this also isn't the latest version, so maybe it is already fixed)
Perhaps having ctr c label list the labels for all (or the named) containers when no other argument is given is a nice enough compromise to keep the default ctr c list readable.
Truncating is an interesting idea, although in the case I was seeing the container id and the image name were both quite long too, so truncating to 80 or even 120 chars wouldn't leave much useful in the labels.
@stevvooe I agree that the right fix for this case is to move the label content to the extensions, but the issue would still remain with any other heavy (meaning more than a couple of dozen or so characters) use of labels which would hit issues with wrapping too.

LGTM
Lets remove them from the default output on list to clean it up.  Right now they can be seen via info so that should work.


Added the functionality from RollOver Daily Todos plugin

Added pass_over_todos (potentially rename to roll_over_daily_todos?) option which allows moving any incompleted todo from yesterday onto today's daily note.

This is exactly what I been looking for. Thanks, I hope it gets merged soon

I manually added the changes to my config and is not working :(
I can read the changes and it looks good to me, it searches for the empty checkboxes from the day before and updates the content of the new note, but I am just learning lua and for now I can not pin point the issue, I will try to debug it

ok, figure it out, the only thing missing was to add the option to the daily notes section to pass_over_todos = true
This works great

@Trap101 @jacostag thanks for this, I meant to review a while ago but it fell off my radar. @Trap101 if you're still around could you fix the typo and merge conflicts? Then I'll give it a proper review.

Sorry for taking so long, conflict has been resolved and just tested, the functionality should be working. I am not the best at naming so change the settings / variable names as they should be

@epwalsh @Trap101, If all checks have passed can we get this into obsidian pls. This is a really nice feature to have. However, it has been open for a while now. The manual rolling over todo's from previous day, is really a pain.


Curl download continuation is broken

The curl download continuation functionality is not working because the downloaded binary is named to a random hash when downloading to the tmp folder. At the point of download, we should rely on a hash, based on candidate+vendor+version to make it deterministic when attempting to redownload a binary.

Make hash generation deterministic
The sdkman_curl_continue flag needs to be added to selfupdate.sh and install.sh in the hooks project too.

 Fix sdkman_curl_continue configuration


about some updates

Clear and concise description of the problem
the project needs a more colorful site, it should work more on marketing, there are also users who have problems with connecting some wallets and have private key problems, also the project should not hide itself, it should be more transparent with its investors and team to the community
Suggested solution
Connection problems with the site should not be resolved and all kinds of security measures should be increased.
Alternative
wallet numbers, meaningless letters and numbers and the phrase ibx at the beginning may be more distinguished
Additional context
No response
Validations

[X] Read the docs.
[X] Check that there isn't already an issue that request the same feature to avoid creating a duplicate.

Thank you for your suggestion, we totally agree with you, can you provide us with a more detailed print screen? That way our product manager can see it. Thank you again for your kind support.


Interface localisation

Has this project an ability to add interface i18n?
I can localise it.

This was also requested in #17, so I'm closing this issue as a duplicate. Short answer: no, this project does not currently allow for localization, but there are plans to change that.


Che tides controller and controller test

In this PR, we add an endpoint /api/tides/get that can be used to get information
about the height of tides at a particular time.
link: http://team01-mczimmermann-dev.dokku-07.cs.ucsb.edu
closes #13

LGTM


20161122152339_new_plan_template_structure.rb removes answers

Please complete the following fields as applicable:
What version of the DMPRoadmap code are you running? (e.g. v2.2.0)
branch dmponline4_upgrade_step2
Expected behaviour:
Keep as many answers in new table new_answers
Actual behaviour:
In my installation there are 119011 records in table answers,
but only 77736 in table new_answers.
Steps to reproduce:

fill database with data from a DMPonline_v4 instance
git checkout dmponline4_upgrade_step2
bundle exec rake db:migrate

I see here that an old answer is only copied to a NewAnswer in order to attach notes (which were comments) to it. Not?

Hi @nicolasfranck
That behavior is intentional.  in dmponline4, multiple answers were stored for each question, but only the latest was accessible via the frontend.  When we re-modeled the DB for DMPRoadmap, we decided that there would be exactly one answer for each combination of question and plan.  This meant that the final set of answers may be smaller than your original set.
I've pulled out the relevant lines from your link:
old_ans = Answer.where(question_id: new_question.question_id, plan_id: old_plan.id).order("created_at DESC").first
comments = Comment.where(question_id: new_question.question_id, plan_id: old_plan.id)
unless old_ans.nil? && comments.length < 1
    new_ans = initNewAnswer(old_ans, new_plan, new_question)
    new_ans.save!
end

Effectively we take old_ans the most recently created answer, and create a new_ans if this is present.
Also part of the above DB remodel was attaching Notes(formerly comments as you surmise) directly to an answer, rather than to a combination of plan and question.  Because of this change, we also need to generate a (blank) answer to attach the Notes to.
Let me know if that makes sense:)

Right, I remember fixing that in my instance of dmponline..
If I run a group-query like this
select plan_id,question_id,count(*) from answers group by plan_id,question_id

it returns 77843 records. so a difference of 107 records with the expected 77736,
but those can probably be explained differently.
Thanks for your response!

That double negation unless old_ans.nil? && comments.length < 1 is a bit hard to understand, so I was curious why there were any answers left after that run ;-)


Modern package manager

As an operator,
I want to use the latest package managers available,
so that I can install packages using Chef Infra Client
Work to be Done
We need to update the package manager support in Chef Infra Client to support the latest and greatest package managers on platforms we support. On Ubuntu the snap package manager is becoming popular and on Windows Microsoft has released the Windows Package Manager. Infra Client needs to support both of these.
Acceptance criteria
We have Test Kitchen integration tests to install packages in CI for both of these package managers.

Closing in favor of https://chefio.atlassian.net/browse/INFC-81


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20 seconds ago
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Feat/new options

Coverage decreased (-0.08%) to 86.415% when pulling 502ca536d560e2b0b5e32d7f7daca81b67e60157 on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage decreased (-0.08%) to 86.415% when pulling 7dd8b3730d9e9895655f3cb112826aa4cf00ec01 on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage decreased (-0.08%) to 86.415% when pulling 7dd8b3730d9e9895655f3cb112826aa4cf00ec01 on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.1%) to 86.614% when pulling 632d39a663d129cc2d172aa521d938d52fa6beee on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.1%) to 86.624% when pulling dd030620daedf962fe9d355bb640649210aea855 on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.3%) to 86.775% when pulling 10d25019b44d04489afb594621e2139f07d82b80 on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.08%) to 86.569% when pulling ba39c1fda83e2b9b5304b7b2a47421eaf28839cb on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.005%) to 86.499% when pulling<PHONE_NUMBER>003771c9d290f597b716af5f8158ea on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.005%) to 86.499% when pulling<PHONE_NUMBER>003771c9d290f597b716af5f8158ea on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.

Coverage increased (+0.08%) to 86.574% when pulling<PHONE_NUMBER>003771c9d290f597b716af5f8158ea on feat/new-options into 36016ee532feeaf87adea94b1573c8a76d98db93 on master.


Return relative URLs for blob upload locations.

Return relative URLs for blob upload locations.
Signed-off-by: Richard Scothern<EMAIL_ADDRESS>

Current coverage is 53.44%

Merging #1491 into master will decrease coverage by -7.39% as of 877456d

@@            master   #1491   diff @@
======================================
  Files          124     124
  Stmts        10462   10454     -8
  Branches       845     741   -104
  Methods          0       0
======================================
- Hit           6365    5587   -778
+ Partial        845     741   -104
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Review entire Coverage Diff as of 877456d

Uncovered Suggestions

+0.19% via .../driver/s3-aws/s3.go#240...259
+0.17% via ...ge/driver/gcs/gcs.go#471...488
+0.16% via ...ge/driver/oss/oss.go#150...166
See 7 more...

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LGTM

LGTM

LGTM