Move flake8-related packages deps to reqs-dev.txt

My vim which is integrated with flake8 wouldn't match the output from
travis and would often miss things related to the flake8 plugins
installed using Tox.
By moving this to requirements-dev.txt, we can expect developers would
have the proper configuration locally and get matching results with
Travis when running flake8 or in their IDEs if its integrated with
flake8.

Codecov Report

Merging #5460 into master will increase coverage by 10.77%.
The diff coverage is n/a.

@@             Coverage Diff             @@
##           master    #5460       +/-   ##
===========================================
+ Coverage   48.34%   59.12%   +10.77%
===========================================
  Files         328      372       +44
  Lines       14762    23762     +9000
  Branches     2758     2758
===========================================
+ Hits         7137    14049     +6912
- Misses       7610     9698     +2088
  Partials       15       15

Impacted Files
Coverage Δ

superset/views/base.py
67.56% <0%> (ø)

superset/views/annotations.py
67.64% <0%> (ø)

superset/dict_import_export_util.py
28.57% <0%> (ø)

superset/views/utils.py
93.93% <0%> (ø)

superset/connectors/sqla/views.py
70.47% <0%> (ø)

superset/utils.py
89.01% <0%> (ø)

superset/models/__init__.py
100% <0%> (ø)

superset/connectors/druid/models.py
82.42% <0%> (ø)

superset/models/core.py
85.98% <0%> (ø)

superset/import_util.py
100% <0%> (ø)

... and 34 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 7fcc2af...015d279. Read the comment docs.


Completion abruptly stopped - RuntimeError: CUDA error: an illegal memory access was encountered

The following is sometimes happening while completion is ongoing for large context sizes.

My context size was: 3,262
The max_new_tokens set: 4,096

Traceback (most recent call last):
  File "/home/username/text-generation-webui/modules/callbacks.py", line 56, in gentask
    ret = self.mfunc(callback=_callback, *args, **self.kwargs)
  File "/home/username/text-generation-webui/modules/text_generation.py", line 321, in generate_with_callback
    shared.model.generate(**kwargs)
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/transformers/generation/utils.py", line 1642, in generate
    return self.sample(
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/transformers/generation/utils.py", line 2724, in sample
    outputs = self(
  File "/home/username/text-generation-webui/modules/exllama_hf.py", line 87, in __call__
    logits = self.ex_model.forward(torch.tensor([seq[-1:]], dtype=torch.long), ex_cache, lora=self.lora).to(input_ids.device)
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/exllama/model.py", line 967, in forward
    r = self._forward(input_ids[:, chunk_begin : chunk_end],
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/exllama/model.py", line 1053, in _forward
    hidden_states = decoder_layer.forward(hidden_states, cache, buffers[device], lora)
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/exllama/model.py", line 530, in forward
    self.self_attn.fused(hidden_states, cache, buffer, self.input_layernorm, lora)
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/site-packages/exllama/model.py", line 376, in fused
    key_states = cache.key_states[self.index].narrow(2, 0, past_len + q_len).narrow(0, 0, bsz)
RuntimeError: start (0) + length (4097) exceeds dimension size (4096).
Exception in thread Thread-172 (gentask):
Traceback (most recent call last):
  File "/home/username/miniconda3/envs/textgen/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
Traceback (most recent call last):
  File "/home/username/text-generation-webui/modules/text_generation.py", line 328, in generate_reply_HF
    yield get_reply_from_output_ids(output, input_ids, original_question, state, is_chat=is_chat)
  File "/home/username/text-generation-webui/modules/text_generation.py", line 206, in get_reply_from_output_ids
    if shared.tokenizer.convert_ids_to_tokens(int(output_ids[-new_tokens])).startswith('▁'):
RuntimeError: CUDA error: an illegal memory access was encountered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.

According to the error message, it's attempting to generate at position 4097, so it's exceeding the sequence length you've set. I have to assume this is an issue in text-generation-webui. (?)


rest client double encodes uri parameters

Hi
I think I came across a problem whereby path uri params are being double encoded in the rest client.  My call via the cli was similar to the following (via cygwin):
java -jar mojito-cli-0.67.jar pull -r MyRepository -s T:/workspace/myproject/src/main/resources/i18n

Which  resulted in an error message:
Asset with path [abc\def\Example.properties] was not found in repo [MyRepository]

I tracked down the problem and came up with a potential fix here: https://github.com/garyhodgson/mojito/commit/f477396a81eaf421c016f5ee6bd31236f57f29d3
In short the getForObject method uses getURIForResource which encodes the parameters as a URI String, but then the restTemplate encodes it again later on.  E.g. "/api/assets?path=abc%5Cdef" is actually sent as "/api/assets?path=abc%255Cdef" which mojito can then not find.  I attempted a crude unit test which shows the problem: https://github.com/garyhodgson/mojito/commit/f477396a81eaf421c016f5ee6bd31236f57f29d3#diff-c8652fa74e390a8c272cab005f7ba9f9R79
My initial attempt at a fix was to use the alternative getForObject method which accepts uriVariables - but this didn't work for some reason.  Perhaps someone with a better understanding of Spring Rest could get it to work as it's a probably the better solution.  My fix is simply to pass an instance of a URI as the parameter, which the rest template recognises and does not try and encode again.
Hope this helps.  I can create a Pull request if you wish.

@garyhodgson Thanks for catching this bug.  I like how you wrote unit test to demonstrate the problem and the fix.  Your unit test helped me to quickly see what the problem is.  :1st_place_medal: for test driven development!
Yes, please send pull request so everyone can have your fix.

@garyhodgson Thanks!
@jeeyi I'm gonna refactor that class a little bit. The way some function create URIs with query params  is a little misleading and buggy.


Split dask_yarn

WIP: testing splitting tests up too
Docs need updating before merging.
Should dask_yarn and knit have separate locations on readthedocs?

OK, I did as you asked, @jcrist , please see if my solution is reasonable.
We also need to decide what to do about the docs - there is only one landing page, and it is for knit - and whether dask_yarn now needs its own __version__.

Further actions here:

[ ] update doc with explicit page for dask-yarn
[ ] new release of knit on conda
[ ] new package for dask-yarn on conda forge, which contains nothing except a dependence on knit.


Ask a question related to Ibex

My Environment

EDA tool and version:

Quartus, modelsim, Segger Emdeded studio
Operating system:

Version of the Ibex source code:

Hi ,
I have some question and finde some bug when using Ibex:
1.What for   0x80 in code: PC_BOOT: fetch_addr_n = { boot_addr_i[31:8], 8'h80 }; ?
I set 0x80 to 0x00 in boot address  as this cause error at initialization  copying constan variable from ROM to RAM with Segger Embeded studio.
2.For compiling in Quartus Prime I was replase all generate block to this coding style
generate
genvar k;
// bit reverse operand_a for left shifts and bit counting
for (k = 0; k < 32; k++) begin : gen_rev_operand_a
assign operand_a_rev[k] = operand_a_i[31-k];
end
endgenerate

Fix bug After interrupt innstruction jump to wrong exeption address:
in file ibex_cs_registers.sv
CSR_MTVEC: mtvec_d =  {csr_wdata_int[31:8], 6'b0, 2'b01}; replace to CSR_MTVEC: mtvec_d =  csr_wdata_int;
in file ibex_if_stage.sv
EXC_PC_IRQ:     exc_pc = { csr_mtvec_i[31:8], 1'b0, irq_id[4:0], 2'b00 }; replace to EXC_PC_IRQ:     exc_pc = csr_mtvec_i;

Thank you,
Dmitry

I will try to answer these questions below:

We define the reset vector to be the trap base + 0x80 (effectively the top of the vector table). I suppose boot_addr_i is a slightly misleading name since it is specifying the trap base address.
This was discussed in this issue. The conclusion: we won't change the rtl to work around old / unsupported EDA tools.
Ibex always uses vectored interrupt handling (see the mtvec section of the RISCV privileged spec). This is why bit[0] is is set, and the irq id is used to form the trap address.

@diakovd I think your questions should be answered. If you have follow-up questions, please re-open this issue. Otherwise open a new one. Thanks for your interest in Ibex!

@diakovd I think your questions should be answered. If you have follow-up questions, please re-open this issue. Otherwise open a new one. Thanks for your interest in Ibex!


Visibility Buffer on MacBookPro13,1 not rendered correctly

VisibilityBuffer example is not rendered correctly on MacBook Pro 13,1 on 10.13.2 (17C88) - Intel SKL graphics.
Changing the parameters does not change much (or makes it even worse). Any clues?
https://imgur.com/mtNkRo1

In the moment we do not test Intel-GPU based devices like MacBook Pro's ... but we let Intel and Apple know about the challenges of supporting Intel-based GPUs and I am hoping they see this message :-) The challenges are driver support for some of the features we use in the Visibility Buffer.
Expect this to be fixed at some point. I can't give you an ETA ... but we are actively working on it. Let's keep this issue up here as a reminder.

I'm sure they will, thanks :)

Hi just got the same problem on a MacBook Pro 15 (early 13) running 10.13.2.  I still get the problem however if I switch from using the default device (Intel) to using my Geforce (changing code around MetalRenderer.mm: 850).
I had a look at the 3 errors that get reported to the console.
Fixed (with no change) the metal compiler warning about signed/unsigned
Fixed (with no change) the problem with ImageFormat::GetBytesPerChannel()  - the assert
I have no idea if  "Execution of the command buffer was aborted due to an error during execution. Invalid Resource (IOAF code 9)" might have an effect.

That should be solved with today's commit.


1.1.7 :  frida is not working

hi,
My device is iphone X 14.6
I used taurine 1.1.7-3 with my device.
jb is ok. but install frida and run script with any apps -> crash & reboot device.
please, fix it. I want frida.
(iphone XS 14.6 same issue)

Hey I have the same issue, it would be great if a developer could look around :)

same problem here with iphone 7 ios 14.6 and taurine 1.1.7 :(

Also cross posted in the frida issues:
https://github.com/frida/frida/issues/2643


Module "type not assignable" error

Hey,
Just read your Medium article and I'm looking forward to using this package! Unfortunately I'm running into an issue creating the direct store.
Below is the main index.ts for my store: store/index.ts
import Vue from 'vue';
import Vuex, { StoreOptions } from 'vuex';
import { createDirectStore } from 'direct-vuex';
import { RootState } from './types';
import profile from './profile';

Vue.use(Vuex);

const { store } = createDirectStore({
  state: {},
  modules: {
    profile,
  },
});

export default new Vuex.Store<RootState>(store);

And here is a module that I am trying to include in the store: store/profile/index.ts
import { Module } from 'vuex';
import getters from './getters';
import actions from './actions';
import mutations from './mutations';
import { ProfileState } from './types';
import { RootState } from '../types';

const state: ProfileState = {
  user: undefined,
  authErrorMessage: '',
  authLoading: false,
};

const profile: Module<ProfileState, RootState> = {
  namespaced: true as true,
  state: {
    user: undefined,
    authErrorMessage: '',
    authLoading: false,
  },
  getters,
  actions,
  mutations,
};

export default profile;

The modules property in store/index.ts (rather the profile property) is causing a type assignability error.
Type '{ profile: Module<ProfileState, RootState>; }' is not assignable to type '{ profile: Module<ProfileState, RootState>; } & ModulesImpl<any>'.
  Type '{ profile: Module<ProfileState, RootState>; }' is not assignable to type 'ModulesImpl<any>'.
    Property 'profile' is incompatible with index signature.
      Type 'Module<ProfileState, RootState>' is not assignable to type 'ModuleOptions<any>'.
        Types of property 'actions' are incompatible.
          Type 'ActionTree<ProfileState, RootState> | undefined' is not assignable to type 'ActionsImpl | undefined'.
            Type 'ActionTree<ProfileState, RootState>' is not assignable to type 'ActionsImpl'.
              Index signatures are incompatible.
                Type 'Action<ProfileState, RootState>' is not assignable to type 'ActionImpl'.
                  Type 'ActionObject<ProfileState, RootState>' is not assignable to type 'ActionImpl'.
                    Type 'ActionObject<ProfileState, RootState>' provides no match for the signature '(context: ActionContext<any, any>, payload: any): any'.ts(2322)
index.ts(11, 3): The expected type comes from property 'modules' which is declared here on type '{ state: {}; modules: { profile: Module<ProfileState, RootState>; }; } & StoreOptions<{}>'

Any help would be great! I am happy to provide more details.
Thanks,

Hi,
Do not use type definitions from Vuex (StoreOptions, Module). These definitions prevent from inferring the details of the store implementation.
I suggest to use createModule:
import { createModule } from "direct-vuex";

const profile = createModule({
  namespaced: true, // 'as true' is not needed when using 'createModule'
  // …
})

See also the documentation.
Additionally, this line can't work:
export default new Vuex.Store<RootState>(store);

Your implementation of store/index.ts must follow the documentation:
// store/index.ts
import Vue from "vue"
import Vuex from "vuex"
import { createDirectStore } from "direct-vuex"
import profile from './profile';

Vue.use(Vuex);

const { store, rootActionContext, moduleActionContext } = createDirectStore({
  modules: {
    profile,
  },
});

// Export the direct-store instead of the classic Vuex store.
export default store;

// The following exports will be used to enable types in the
// implementation of actions.
export { rootActionContext, moduleActionContext };

// The following lines enable types in the injected store '$store'.
export type AppStore = typeof store;
declare module "vuex" {
  interface Store<S> {
    direct: AppStore
  }
}

Notice that your RootState could be inferred:
export type AppState = AppStore["state"];

Ah, that makes sense. Thanks a lot!

How do you avoid cyclic dependencies with regards to the moduleActionContext that is exported from the root store and then imported in a submodule? Since the root store imports the sub module that forms a cycle.
Looking at the documentation the module imports as import { moduleActionContext } from "./store" but the ./store is the file that exports, export { rootActionContext, moduleActionContext }
( I can open a new issue for this question if you would like )

How do you avoid cyclic dependencies

I couldn't avoid them.
export const mod1ActionContext = (context: any) => moduleActionContext(context, mod1)

It works because mod1ActionContext is not executed at the same time it is declared. It is executed when an action is executed, ie. after all the store and modules are already initialized.

A consequence is the store source file must be imported first from the rest of the application. If you import a module first, you can run into this kind of issue.

Make sense, thanks! Everything seems to be working well now


Add support for licenseExpression in paket.template

I wanted to add the license of my project with paket pack in a similar way I am used to with dotnet pack and stumbled across #3710
A while ago Nuget deprecated licenseUrl and this is not yet reflected in paket.template. (https://docs.microsoft.com/de-de/nuget/reference/nuspec#license)
Therefore I tried adding support for the license expression.
I tried to adjust tests a bit and edited documentation. I hope I did everything right.
Thanks for your work! Paket is a really helpful tool :)

sorry for delay. thanks for this PR!


feat(website): update prover endpoints

Combines the following PRs: #15145, #15148, #15155, #15157, #15164, #15166, #15167.
Will close those PRs once this is merged

Thanks for adding my prover to the list. But i can't claim Taiko Contributor 2023 GitPOAP.


run an ad-hoc command using exist service

Is there a way to run an ad-hoc command using exist service, for example run a rake task using rails server service

With the release of Rancher 2.0, development on v1.6 is only limited to critical bug fixes and security patches


Do each of p1 and p2 of fromSlope(p1, p2) mean [y, x]?

Hello, I have a question.
First of all, fromSlope returns results like this:
> angles.fromSlope([0, 0], [1, 0])
0
> angles.fromSlope([0, 0], [1, 1])
45
> angles.fromSlope([0, 0], [0, 1])
90
> angles.fromSlope([0, 0], [-1, 1])
134.99999999999994
> angles.fromSlope([0, 0], [-1, 0])
180

From the above result, I imagine such a figure:
   [1,0]  [1,1]
     |
     |
[0,0]+----[0,1]
     |
     |
   [-1,0] [-1,1]

Finally, p1 indicates the start point and p2 indicates the end point.
Then, each is described as [y, x].
... I thought like this.
Is this understanding correct?
Thanks.

Sorry, I misunderstood.


panic with pod not being found:

panic: pods "hello-cloud-deployment-4100001433-scb8x" not found

goroutine 1 [running]:
panic(0x1275080, 0xc420319880)
	/usr/local/Cellar/go/1.7.5/libexec/src/runtime/panic.go:500 +0x1a1
main.reap(0x1bf08eb000, 0x989680, 0xc4204325c0, 0x2, 0x2, 0x13a7d7b, 0xa, 0x13a598e, 0x8, 0xc42001204a, ...)
	/Users/z001kkm/code/go/src/pod-reaper/main.go:52 +0x319
main.main()
	/Users/z001kkm/code/go/src/pod-reaper/main.go:102 +0x98

Thrown by this line:
err := clientSet.Core().Pods(pod.ObjectMeta.Namespace).Delete(pod.ObjectMeta.Name, nil)

This shouldn't be a panic: if the pod isn't found (might have been deleted by something else/some other event might have happened). If the pod isn't found/the delete fails, we should probably just log it and continue happily.

Resolved in #5


New version: rhysd.actionlint version 1.6.24

Pull request has been created with Komac v1.4.1 :rocket:
Microsoft Reviewers: Open in CodeFlow

Manual Validation failed with:

2023-04-04 08:51:14.290 [FAIL] Installer failed security check. Url: https://github.com/rhysd/actionlint/releases/download/v1.6.24/actionlint_1.6.24_windows_386.zip Result: 0x80004005

What's that supposed to mean? False positive?

What's that supposed to mean? False positive?

From https://github.com/microsoft/winget-pkgs/pull/101324#issuecomment-1494972091

The "failed security check" is usually defender / smartscreen flagging the URL as an unknown / potentially malicious URL before the download ever completes

But I download from Microsoft Edge is not flagged as malicious.

https://github.com/microsoft/winget-pkgs/pull/102567

https://github.com/microsoft/winget-pkgs/pull/102052#issuecomment-1502066644
https://github.com/microsoft/winget-pkgs/pull/102567


[FEATURE] Add Request and Response Bodies for 4 main Point-in-time endpoints

There are 6 PIT actions that was added to OS 2.4. The following 4 currently do not have Request and Response bodies:

create_pit: POST {index}/_search/point_in_time
get_all_pits: GET _search/point_in_time/_all
delete_all_pits: DELETE _search/point_in_time/_all
delete_pit: DELETE _search/point_in_time

Follow the Developer's Guide doc to fill in the missing info.
You might have to manually make calls to an OS cluster to figure out the shape of the response bodies.
NOTE: Don't work on this issue until https://github.com/opensearch-project/opensearch-api-specification/pull/91 has been merged.

Hello everyone!
We discussed at the meeting with @nhtruong , that @aabeshov and I will do this issue!

Hello everyone!
We have fortunately made this issue and are waiting for your comments about our work!
P.S. We divide it to 2 PR, because we have some problems with counting of job in our CCI program
@aabeshov provided Request and Response Bodies for create_pit and delete_all_pits
I provided Request and Response Bodies for get_all_pits and delete_pit
If its not comfortable for checking or merging, we will definitely discuss this in our conference of CCI and will do it in the future in one pull request

Hello everyone! We have fortunately made this issue and are waiting for your comments about our work!
P.S. We divide it to 2 PR, because we have some problems with counting of job in our CCI program @aabeshov provided Request and Response Bodies for create_pit and delete_all_pits I provided Request and Response Bodies for get_all_pits and delete_pit If its not comfortable for checking or merging, we will definitely discuss this in our conference of CCI and will do it in the future in one pull request. We had no experience in production or open source development before and we are just learning!

Thank you @Tokesh and @aabeshov for contributing! The division into PRs is totally fine. Will review the PRs.

Done in #104 and #105


embulk gem install -l option behavior in 0.8.39 and 0.9.18

Just sharing my knowledge for future support.
I found the difference embulk gem -l behavior in 0.8.39 and 0.9.18
I'll close this in a few days.
0.8.39
% gem install -l embulk-output-bigquery-0.6.0.gem
2019-08-27 22:02:17.523 +0900: Embulk v0.8.39

********************************** INFORMATION **********************************
  Join us! Embulk-announce mailing list is up for IMPORTANT annoucement such as
    compatibility-breaking changes and key feature updates.
  https://groups.google.com/forum/#!forum/embulk-announce
*********************************************************************************

Gem plugin path is: /Users/user/.embulk/jruby/2.3.0

Successfully installed embulk-output-bigquery-0.6.0
1 gem installed

0.9.18
embulk --version
embulk 0.9.18

embulk gem install -l embulk-output-bigquery-0.6.0.gem
Exception in thread "main" java.lang.IllegalArgumentException: Log level embulk-output-bigquery-0.6.0.gem is invalid. Available levels are error, warn, info, debug and trace.
	at org.embulk.cli.CliLogbackConfigurator.chooseLevel(CliLogbackConfigurator.java:150)
	at org.embulk.cli.CliLogbackConfigurator.configureLogger(CliLogbackConfigurator.java:115)
	at org.embulk.cli.CliLogbackConfigurator.configure(CliLogbackConfigurator.java:24)
	at org.embulk.cli.Main.main(Main.java:59)

Workaround
Use long option
embulk gem install --local embulk-output-bigquery-0.6.0.gem

Environment

OS: macOS 10.14.5
Java: 1.8.0_192
Embulk 0.8.39 and 0.9.18

Ah, -l might be consumed by Embulk, not passed to gem. It's considered to be a bug.

Thanks! I'll keep this issue as open.


I can not download Previous episodes in CR

D:\CR-Rip>youtube-dl.exe "http://www.crunchyroll.com/fatekaleid-liner-prisma-ill
ya/episode-1-city-fading-to-silver-715497" -f 720p --all-subs --write-sub --sub-
format ass --embed-subs --verbose -u xxxxxx -p xxxxx
[debug] System config: []
[debug] User config: []
[debug] Command-line args: ['http://www.crunchyroll.com/fatekaleid-liner-prisma-
illya/episode-1-city-fading-to-silver-715497', '-f', '720p', '--all-subs', '--wr
ite-sub', '--sub-format', 'ass', '--embed-subs', '--verbose', '-u', 'PRIVATE', '
-p', 'PRIVATE']
[debug] Encodings: locale cp1252, fs mbcs, out cp850, pref cp1252
[debug] youtube-dl version 2016.08.31
[debug] Python version 3.4.4 - Windows-7-6.1.7601-SP1
[debug] exe versions: ffmpeg N-81154-gfb91143, ffprobe N-81154-gfb91143, rtmpdum
p 2.4
[debug] Proxy map: {}
[Crunchyroll] Logging in
[Crunchyroll] 715497: Downloading webpage
[Crunchyroll] 715497: Downloading media info for 360p
[Crunchyroll] 715497: Downloading m3u8 information
[Crunchyroll] 715497: Downloading media info for 480p
[Crunchyroll] 715497: Downloading m3u8 information
[Crunchyroll] 715497: Downloading media info for 720p
[Crunchyroll] 715497: Downloading m3u8 information
[Crunchyroll] 715497: Downloading media info for 1080p
[Crunchyroll] 715497: Downloading m3u8 information
[Crunchyroll] 715497: Downloading media info
[Crunchyroll] 715497: Downloading subtitles for English (US)
[Crunchyroll] 715497: Downloading subtitles for Español
[Crunchyroll] 715497: Downloading subtitles for Español (España)
[Crunchyroll] 715497: Downloading subtitles for Français (France)
[Crunchyroll] 715497: Downloading subtitles for Português (Brasil)
[Crunchyroll] 715497: Downloading subtitles for Italiano
[Crunchyroll] 715497: Downloading subtitles for Deutsch
ERROR: requested format not available
Traceback (most recent call last):
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp6cf1z6ka\bu
ild\youtube_dl\YoutubeDL.py", line 702, in extract_info
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp6cf1z6ka\bu
ild\youtube_dl\YoutubeDL.py", line 748, in process_ie_result
File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\rg3\tmp6cf1z6ka\bu
ild\youtube_dl\YoutubeDL.py", line 1424, in process_video_result
youtube_dl.utils.ExtractorError: requested format not available
D:\CR-Rip>

ERROR: requested format not available

There is no format 720p exist. -F to list formats.

The format DOES exist, but the format identifiers have now changed to video-specific IDs:
`tomman@m24legacy:~/temp$ youtube-dl --username USER -F http://www.crunchyroll.com/fatekaleid-liner-prisma-illya/episode-5-the-little-lady-attacks-715505
Type account password and press [Return]:
[Crunchyroll] Logging in
[Crunchyroll] 715505: Downloading webpage
[Crunchyroll] 715505: Downloading media info for 360p
[Crunchyroll] 715505: Downloading m3u8 information
[Crunchyroll] 715505: Downloading media info for 480p
[Crunchyroll] 715505: Downloading m3u8 information
[Crunchyroll] 715505: Downloading media info for 720p
[Crunchyroll] 715505: Downloading m3u8 information
[Crunchyroll] 715505: Downloading media info for 1080p
[Crunchyroll] 715505: Downloading m3u8 information
[Crunchyroll] 715505: Downloading media info
[info] Available formats for 715505:
format code  extension  resolution note
hls-meta-0   mp4        multiple   Quality selection URL
hls-meta-1   mp4        multiple   Quality selection URL
hls-meta-2   mp4        multiple   Quality selection URL
hls-meta-3   mp4        multiple   Quality selection URL
hls-535      mp4        640x360     535k , avc1.4d001e, mp4a.40.2
hls-732      mp4        848x480     732k , avc1.4d001e, mp4a.40.2
hls-1114     mp4        1280x720   1114k , avc1.64001f, mp4a.40.2
hls-1898     mp4        1920x1080  1898k , avc1.640028, mp4a.40.2 (best)
youtube-dl --username USER -F http://www.crunchyroll.com/fatekaleid-liner-prisma-illya/episode-6-chilling-hostility-715507
Type account password and press [Return]:
[Crunchyroll] Logging in
[Crunchyroll] 715507: Downloading webpage
[Crunchyroll] 715507: Downloading media info for 360p
[Crunchyroll] 715507: Downloading m3u8 information
[Crunchyroll] 715507: Downloading media info for 480p
[Crunchyroll] 715507: Downloading m3u8 information
[Crunchyroll] 715507: Downloading media info for 720p
[Crunchyroll] 715507: Downloading m3u8 information
[Crunchyroll] 715507: Downloading media info for 1080p
[Crunchyroll] 715507: Downloading m3u8 information
[Crunchyroll] 715507: Downloading media info
[info] Available formats for 715507:
format code  extension  resolution note
hls-meta-0   mp4        multiple   Quality selection URL
hls-meta-1   mp4        multiple   Quality selection URL
hls-meta-2   mp4        multiple   Quality selection URL
hls-meta-3   mp4        multiple   Quality selection URL
hls-541      mp4        640x360     541k , avc1.4d001e, mp4a.40.2
hls-749      mp4        848x480     749k , avc1.4d001e, mp4a.40.2
hls-1154     mp4        1280x720   1154k , avc1.64001f, mp4a.40.2
hls-1976     mp4        1920x1080  1976k , avc1.640028, mp4a.40.2 (best)
`
In my case I'm trying to get the 720p episode, yet one is labeled as "hls-1114" and the other is labeled as "hls-1154". This completely breaks scripting since you can no longer simply specifiy "download whatever video is at 720p".
is there a workaround for this?

you can use -f 'best[height=720]' instead of -f 720p.


Improve documentation

I found many functions lack of proper parameter descriptions, for example in server.js. Especially options  are often completely undocumented.

Also the README should add a "migrate from 3.x" guide, even if there are no breaking issues

@HappyZombies @jorenvandeweyer I have fiddled around with RST but it's a real struggle :see_no_evil:
My proposal would be:

use a markdown template and update all guides to markdown-based
use jsDoc with jsDoc to markdown to auto-generate API docs
use GitHub actions + GitHub pages to auto-publish documentation instead of readthedocs

What do you think?

If you want I can set it up.

@jorenvandeweyer sounds promising! We can try to work on this on a separate branch. Does it support jsDoc?

@jankapunkt No it does not support jsDoc, do we need it?

I think we are good with the current docs for now but in the long run jsDoc is a good way for API docs as the functions are documented in place


Allow alternate core implementation of CCM

Allow hardware platforms with an integrated crypto accelerator capable of CCM to do CCM natively, instead of having to go through the mbedTLS AES primitive block-by-block.

Approved for merge. Note to @gilles-peskine-arm - needs an update in the ChangeLog, but you can do that during the merge, as it doesn't touch code.

CI status: there were failures but these are known problems (timing self-test and compat.sh slow start) that are unrelated to this PR. So CI ok for merging purposes.


Confirm event after firing a sensory event, closes #41

Codecov Report

Merging #52 into master will increase coverage by <.01%.
The diff coverage is 87.5%.

@@            Coverage Diff             @@
##           master      #52      +/-   ##
==========================================
+ Coverage   81.44%   81.44%   +<.01%
==========================================
  Files          92       92
  Lines        1940     1951      +11
  Branches      110      107       -3
==========================================
+ Hits         1580     1589       +9
- Misses        360      362       +2

Impacted Files
Coverage Δ

.../baker/runtime/actor/ProcessInstanceProtocol.scala
62.5% <ø> (ø)
:arrow_up:

.../com/ing/baker/runtime/actor/ProcessInstance.scala
95.95% <100%> (ø)
:arrow_up:

...uage/src/main/scala/com/ing/baker/il/package.scala
85.71% <100%> (+0.42%)
:arrow_up:

.../main/scala/com/ing/baker/runtime/core/Baker.scala
80.58% <84.61%> (-0.07%)
:arrow_down:

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 7cb78d3...e95a15e. Read the comment docs.


How can i mask a decimal value?

I'm trying to mask a decimal value, but i can't did this.
Something like a repetition pattern would work too.
ex: [0-9]-[0-9]*
Any idea?
Tks

I usually do something like: "999-999"

Sorry for the time, I was lost in another galaxy.
I don't understand the problem, can you tell me more details?
You want your value shows as 9-9?

Hi, did you look at money mask?

Maybe I can use money mask setting unit to blank...

Yep,
For now, I will close this issue. Feel free to reopen if needed =).

@benhurott , how can i add more than two decimal cases to money type?


memory leak in train loop?

I've noticed memory use grows with time in a coach learning process.  This matters because RL training can take a long time and lower memory usage can reduce learning costs.
I instrumented the agent train loop with tracemalloc and looked at the top memory allocators:
[<StatisticDiff traceback=<Traceback (<Frame filename='.../lib/python3.6/tracemalloc.py' lineno=123>,)> size=10454240 (+5227308) count=130690 (+65355)>,
 <StatisticDiff traceback=<Traceback (<Frame filename='.../lib/python3.6/tracemalloc.py' lineno=462>,)> size=6771608 (+3628608) count=141067 (+75596)>,
 <StatisticDiff traceback=<Traceback (<Frame filename='.../coach/rl_coach/core_types.py' lineno=250>,)> size=8879952 (+2959984) count=29997 (+9999)>,
 <StatisticDiff traceback=<Traceback (<Frame filename='.../lib/python3.6/site-packages/tensorflow/python/client/session.py' lineno=346>,)> size=7193760 (+2397864) count=59932 (+19977)>,
 <StatisticDiff traceback=<Traceback (<Frame filename='.../lib/python3.6/copy.py' lineno=161>,)> size=5522440 (+1840120) count=90051 (+30005)>,
 <StatisticDiff traceback=<Traceback (<Frame filename='.../lib/python3.6/site-packages/tensorflow/python/framework/ops.py' lineno=5228>,)> size=5080408 (+1680000) count=30365 (+10000)>,
 <StatisticDiff traceback=<Traceback (<Frame filename='.../lib/python3.6/site-packages/tensorflow/python/client/session.py' lineno=296>,)> size=4311216 (+1436904) count=59878 (+19957)>,

Ignoring the tracemalloc ones we see the top allocator is in Transition.add_info, traceback
  File ".../coach/rl_coach/core_types.py", line 250
    self.info.update(new_info)
  File ".../coach/rl_coach/agents/agent.py", line 870
    transition.add_info(self.last_action_info.__dict__)
  File ".../coach/rl_coach/level_manager.py", line 219
    done = acting_agent.observe(env_response)
  File ".../coach/rl_coach/graph_managers/graph_manager.py", line 443
    result = self.top_level_manager.step(None)
  File ".../coach/rl_coach/graph_managers/graph_manager.py", line 476
    self.act(EnvironmentSteps(1))

This seems like a leak, since transition objects should be free for gc?
Any advice here?  I can't reason what might be keeping a reference to the transition.

I think what was happening was that some code I added to the fetch list was allocating variables and this was causing growth in memory.   I haven;t worked out why the tracemalloc output is misleading yet :/


Kptfile pipelines should support mount and network flags

Describe your problem
I'm trying to use kpt pipeline with render-helm-chart function as mutator.
In order to use local or remote chart we need to pass one of the following flags to docker which the Kptfile doesn't support:

mount
network

(In some cases the as-current-user flag is required as well.)
Current mitigation is to use exec mutator and run a script with the required flags, for example:
snippet from kptfile
pipeline:
  mutators:
    - exec: ./render_command.sh
  validators:
    - image: gcr.io/kpt-fn/kubeval:v0.1

render_command.sh
#!/bin/bash
kpt  fn eval  \
  --image gcr.io/kpt-fn/render-helm-chart:unstable \
  --mount type=bind,src=$(pwd),dst=/tmp/charts \
  --as-current-user \
  --truncate-output=false \
  --results-dir /tmp/result \
  -- name=spanner-chart releaseName=test

It would be useful if we can pass these flags in the Kptfile like that:
pipeline:
  mutators:
    - image: gcr.io/kpt-fn/render-helm-chart:unstable
      mount:
         type: bind
         src: .
         dst: /tmp/charts
      as-current-user: true
      configMap:
         name: spanner-chart
         releaseName: test

Thanks for sharing the use-case details. I must say that's a very clever use of exec mode.
Typically, we think of fn render as an operation that will be performed whenever there are changes to package manifests. It's expected that package manifests will be generated on demand (first time with default values.yaml or when helm chart's version changes) instead frequently. So on-demand generation, it is recommended to use fn eval that supports network and storage.
Regarding the enhancements requests, we are open to support network access in fn render and it has been in our backlog for some time. However, there are concerns related to portability of a package in supporting storage in fn render.

An alternative take on rendering Helm charts in declarative pipelines can be found here: https://github.com/michaelvl/krm-functions/blob/main/docs/render-helm-chart.md

@michaelvl thanks, that declarative version is much better, it's inline with some of what I was discussion in #3847
@tliron FYI with regard to the Nephio Helm support discussion.

@droot @johnbelamaric are there any further plans here? I think that a solution to this would probably solve the problem of being able to fetch values dynamically from any remote data source as well.


Too many options for "GitHub add-ons" in Code Review section

There are 13 options listed for "GitHub Add ons" in the Code Review section.
This is too many. Could we limit the selection to things we have experience with and that work well?

Sure, just delete all of them! I did a survey last spring, but didn't try any because Lars B. didn't want to. So I put the results in the guide, hoping that whoever would do a code review next would try one and update the chapter. I guess no one did, and now that list is probably hopelessly outdated.
Also, Github now has code review functionality built in, so that should probably be the first choice unless it turns out to be deficient somehow. Shall I just remove the whole thing and suggest people use  Github?

Good plan! I think GitHub should cover all of our Code Review needs for now, since "keep it simple" is our current Code Review Motto :-)


Upgrade Jest to v25

Resolves https://github.com/FormidableLabs/enzyme-matchers/issues/334.
Reopens https://github.com/FormidableLabs/enzyme-matchers/pull/335.

Can the version pin for jest-environment-jsdom be more open? It looks like it's only used in one place and a more loose version pin would allow jest-enzyme to be compatible with more versions of jest. As it currently stands, the dependecy on jest-environment-jsdom ends up pulling in pretty much the full jest dependency tree, which is not good if the consuming package is not on the same major version of jest. I just tried setting up jest-enzyme in a package running jest 26 and ended up with a bunch of jest 24 packages. I'm now getting typescript errors for things like jest not being defined, which I assume is caused by incompatible versions of jest being installed.

@GreenGremlin Yeah, agreed, I made https://github.com/FormidableLabs/enzyme-matchers/pull/343 to address this, but it looks the maintainers are missing in action.

@blainekasten seems like this needs to be published


Make note of important Marathon breaking changes (DCOS_OSS-4243)

Doc change. DCOS_OSS-4243

@mesosphere-mergebot label Ready for Review

@mesosphere-mergebot label work in progress

This was advertised via another channel. Closing.


Only support single GPU validation?

Dear csjliang
When I use Distributed Training by README
2021-07-25 20:04:34,446 INFO: [LPTN_..][epoch: 16, iter:  19,800, lr:(1.000e-04,)] [eta: 2 days, 18:43:45, time (data): 0.178 (0.001)] l_g_pix: 3.1238e+01 l_g_gan: 8.7738e+01 l_d_real: 7.0186e+01 out_d_real: -7.0186e+01 l_d_fake: -8.7537e+01 out_d_fake: -8.7537e+01
2021-07-25 20:06:00,337 INFO: [LPTN_..][epoch: 17, iter:  19,900, lr:(1.000e-04,)] [eta: 2 days, 18:42:21, time (data): 0.504 (0.001)] l_g_pix: 2.0734e+01 l_g_gan: 9.3872e+01 l_d_real: 6.7697e+01 out_d_real: -6.7697e+01 l_d_fake: -9.4580e+01 out_d_fake: -9.4580e+01
2021-07-25 20:07:30,459 INFO: [LPTN_..][epoch: 17, iter:  20,000, lr:(1.000e-04,)] [eta: 2 days, 18:41:57, time (data): 0.202 (0.001)] l_g_pix: 3.0153e+01 l_g_gan: 9.9768e+01 l_d_real: 7.4591e+01 out_d_real: -7.4591e+01 l_d_fake: -9.9862e+01 out_d_fake: -9.9862e+01
2021-07-25 20:07:30,460 INFO: Saving models and training states.
0%|                                                                                | 0/998 [00:00<?, ?image/s]2021-07-25 20:07:30,515 INFO: Only support single GPU validation.
0%|                                                                                | 0/998 [00:00<?, ?image/s]Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 226, in main
model.validation(val_loader, current_iter, tb_logger,
File "/home/delight-gpu/project/LPTN/codes/models/base_model.py", line 45, in validation
self.dist_validation(dataloader, current_iter, tb_logger, save_img)
File "/home/delight-gpu/project/LPTN/codes/models/lptn_model.py", line 169, in dist_validation
self.nondist_validation(dataloader, current_iter, tb_logger, save_img)
File "/home/delight-gpu/project/LPTN/codes/models/lptn_model.py", line 225, in nondist_validation
metric_module, metric_type)(result_img, gt_img, **opt_)
UnboundLocalError: local variable 'gt_img' referenced before assignment
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 226, in main
model.validation(val_loader, current_iter, tb_logger,
File "/home/delight-gpu/project/LPTN/codes/models/base_model.py", line 45, in validation
self.dist_validation(dataloader, current_iter, tb_logger, save_img)
File "/home/delight-gpu/project/LPTN/codes/models/lptn_model.py", line 169, in dist_validation
self.nondist_validation(dataloader, current_iter, tb_logger, save_img)
File "/home/delight-gpu/project/LPTN/codes/models/lptn_model.py", line 225, in nondist_validation
metric_module, metric_type)(result_img, gt_img, **opt_)
UnboundLocalError: local variable 'gt_img' referenced before assignment
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 226, in main
model.validation(val_loader, current_iter, tb_logger,
File "/home/delight-gpu/project/LPTN/codes/models/base_model.py", line 45, in validation
self.dist_validation(dataloader, current_iter, tb_logger, save_img)
File "/home/delight-gpu/project/LPTN/codes/models/lptn_model.py", line 169, in dist_validation
self.nondist_validation(dataloader, current_iter, tb_logger, save_img)
File "/home/delight-gpu/project/LPTN/codes/models/lptn_model.py", line 225, in nondist_validation
metric_module, metric_type)(result_img, gt_img, **opt_)
UnboundLocalError: local variable 'gt_img' referenced before assignment
0%|                                                                                | 0/998 [00:02<?, ?image/s]
0%|                                                                                | 0/998 [00:02<?, ?image/s]
0%|                                                                                | 0/998 [00:03<?, ?image/s]
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 11662) of binary: /home/delight-gpu/anaconda3/envs/lptn/bin/python
ERROR:torch.distributed.elastic.agent.server.local_elastic_agent:[default] Worker group failed
INFO:torch.distributed.elastic.agent.server.api:[default] Worker group FAILED. 3/3 attempts left; will restart worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Stopping worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous'ing worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous complete for workers. Result:
restart_count=1
master_addr=<IP_ADDRESS>
master_port=4321
group_rank=0
group_world_size=1
local_ranks=[0, 1, 2]
role_ranks=[0, 1, 2]
global_ranks=[0, 1, 2]
role_world_sizes=[3, 3, 3]
global_world_sizes=[3, 3, 3]
INFO:torch.distributed.elastic.agent.server.api:[default] Starting worker group
INFO:torch.distributed.elastic.multiprocessing:Setting worker0 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_1/0/error.json
INFO:torch.distributed.elastic.multiprocessing:Setting worker1 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_1/1/error.json
INFO:torch.distributed.elastic.multiprocessing:Setting worker2 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_1/2/error.json
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 128, in main
Traceback (most recent call last):
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
File "codes/train.py", line 249, in
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
_init_dist_pytorch(backend, **kwargs)
_init_dist_pytorch(backend, **kwargs)  File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
dist.init_process_group(backend=backend, **kwargs)
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
_store_based_barrier(rank, store, timeout)_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
raise RuntimeError(
RuntimeError: Timed out initializing process group in store based barrier on rank: 0, for key: store_based_barrier_key:1 (world_size=3, worker_count=6, timeout=0:30:00)
raise RuntimeError(raise RuntimeError(
RuntimeErrorRuntimeError: : Timed out initializing process group in store based barrier on rank: 1, for key: store_based_barrier_key:1 (world_size=3, worker_count=6, timeout=0:30:00)Timed out initializing process group in store based barrier on rank: 2, for key: store_based_barrier_key:1 (world_size=3, worker_count=6, timeout=0:30:00)
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 28662) of binary: /home/delight-gpu/anaconda3/envs/lptn/bin/python
ERROR:torch.distributed.elastic.agent.server.local_elastic_agent:[default] Worker group failed
INFO:torch.distributed.elastic.agent.server.api:[default] Worker group FAILED. 2/3 attempts left; will restart worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Stopping worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous'ing worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous complete for workers. Result:
restart_count=2
master_addr=<IP_ADDRESS>
master_port=4321
group_rank=0
group_world_size=1
local_ranks=[0, 1, 2]
role_ranks=[0, 1, 2]
global_ranks=[0, 1, 2]
role_world_sizes=[3, 3, 3]
global_world_sizes=[3, 3, 3]
INFO:torch.distributed.elastic.agent.server.api:[default] Starting worker group
INFO:torch.distributed.elastic.multiprocessing:Setting worker0 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_2/0/error.json
INFO:torch.distributed.elastic.multiprocessing:Setting worker1 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_2/1/error.json
INFO:torch.distributed.elastic.multiprocessing:Setting worker2 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_2/2/error.json
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
raise RuntimeError(
RuntimeError: Timed out initializing process group in store based barrier on rank: 2, for key: store_based_barrier_key:1 (world_size=3, worker_count=9, timeout=0:30:00)
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
Traceback (most recent call last):
init_dist(args.launcher)
File "codes/train.py", line 249, in
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
raise RuntimeError(
RuntimeError: Timed out initializing process group in store based barrier on rank: 0, for key: store_based_barrier_key:1 (world_size=3, worker_count=9, timeout=0:30:00)
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
raise RuntimeError(
RuntimeError: Timed out initializing process group in store based barrier on rank: 1, for key: store_based_barrier_key:1 (world_size=3, worker_count=9, timeout=0:30:00)
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 30527) of binary: /home/delight-gpu/anaconda3/envs/lptn/bin/python
ERROR:torch.distributed.elastic.agent.server.local_elastic_agent:[default] Worker group failed
INFO:torch.distributed.elastic.agent.server.api:[default] Worker group FAILED. 1/3 attempts left; will restart worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Stopping worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous'ing worker group
INFO:torch.distributed.elastic.agent.server.api:[default] Rendezvous complete for workers. Result:
restart_count=3
master_addr=<IP_ADDRESS>
master_port=4321
group_rank=0
group_world_size=1
local_ranks=[0, 1, 2]
role_ranks=[0, 1, 2]
global_ranks=[0, 1, 2]
role_world_sizes=[3, 3, 3]
global_world_sizes=[3, 3, 3]
INFO:torch.distributed.elastic.agent.server.api:[default] Starting worker group
INFO:torch.distributed.elastic.multiprocessing:Setting worker0 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_3/0/error.json
INFO:torch.distributed.elastic.multiprocessing:Setting worker1 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_3/1/error.json
INFO:torch.distributed.elastic.multiprocessing:Setting worker2 reply file to: /tmp/torchelastic_l8eumjpm/none_twj5_557/attempt_3/2/error.json
Traceback (most recent call last):
File "codes/train.py", line 249, in
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)main()
File "codes/train.py", line 43, in parse_options
File "codes/train.py", line 128, in main
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
_store_based_barrier(rank, store, timeout)raise RuntimeError(
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
RuntimeError: Timed out initializing process group in store based barrier on rank: 1, for key: store_based_barrier_key:1 (world_size=3, worker_count=12, timeout=0:30:00)
raise RuntimeError(
RuntimeError: Timed out initializing process group in store based barrier on rank: 0, for key: store_based_barrier_key:1 (world_size=3, worker_count=12, timeout=0:30:00)
Traceback (most recent call last):
File "codes/train.py", line 249, in
main()
File "codes/train.py", line 128, in main
opt = parse_options(is_train=True)
File "codes/train.py", line 43, in parse_options
init_dist(args.launcher)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 14, in init_dist
_init_dist_pytorch(backend, **kwargs)
File "/home/delight-gpu/project/LPTN/codes/utils/dist_util.py", line 25, in _init_dist_pytorch
dist.init_process_group(backend=backend, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 547, in init_process_group
_store_based_barrier(rank, store, timeout)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/distributed_c10d.py", line 219, in _store_based_barrier
raise RuntimeError(
RuntimeError: Timed out initializing process group in store based barrier on rank: 2, for key: store_based_barrier_key:1 (world_size=3, worker_count=12, timeout=0:30:00)
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 32378) of binary: /home/delight-gpu/anaconda3/envs/lptn/bin/python
ERROR:torch.distributed.elastic.agent.server.local_elastic_agent:[default] Worker group failed
INFO:torch.distributed.elastic.agent.server.api:Local worker group finished (FAILED). Waiting 300 seconds for other agents to finish
/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/elastic/utils/store.py:70: FutureWarning: This is an experimental API and will be changed in future.
warnings.warn(
INFO:torch.distributed.elastic.agent.server.api:Done waiting for other agents. Elapsed: 0.0010943412780761719 seconds
{"name": "torchelastic.worker.status.FAILED", "source": "WORKER", "timestamp": 0, "metadata": {"run_id": "none", "global_rank": 0, "group_rank": 0, "worker_id": "32378", "role": "default", "hostname": "LIGHT-24B.PC.CS.CMU.EDU", "state": "FAILED", "total_run_time": 22569, "rdzv_backend": "static", "raw_error": "{"message": ""}", "metadata": "{"group_world_size": 1, "entry_point": "python", "local_rank": [0], "role_rank": [0], "role_world_size": [3]}", "agent_restarts": 3}}
{"name": "torchelastic.worker.status.FAILED", "source": "WORKER", "timestamp": 0, "metadata": {"run_id": "none", "global_rank": 1, "group_rank": 0, "worker_id": "32379", "role": "default", "hostname": "LIGHT-24B.PC.CS.CMU.EDU", "state": "FAILED", "total_run_time": 22569, "rdzv_backend": "static", "raw_error": "{"message": ""}", "metadata": "{"group_world_size": 1, "entry_point": "python", "local_rank": [1], "role_rank": [1], "role_world_size": [3]}", "agent_restarts": 3}}
{"name": "torchelastic.worker.status.FAILED", "source": "WORKER", "timestamp": 0, "metadata": {"run_id": "none", "global_rank": 2, "group_rank": 0, "worker_id": "32380", "role": "default", "hostname": "LIGHT-24B.PC.CS.CMU.EDU", "state": "FAILED", "total_run_time": 22569, "rdzv_backend": "static", "raw_error": "{"message": ""}", "metadata": "{"group_world_size": 1, "entry_point": "python", "local_rank": [2], "role_rank": [2], "role_world_size": [3]}", "agent_restarts": 3}}
{"name": "torchelastic.worker.status.SUCCEEDED", "source": "AGENT", "timestamp": 0, "metadata": {"run_id": "none", "global_rank": null, "group_rank": 0, "worker_id": null, "role": "default", "hostname": "LIGHT-24B.PC.CS.CMU.EDU", "state": "SUCCEEDED", "total_run_time": 22569, "rdzv_backend": "static", "raw_error": null, "metadata": "{"group_world_size": 1, "entry_point": "python"}", "agent_restarts": 3}}
/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py:354: UserWarning:

           CHILD PROCESS FAILED WITH NO ERROR_FILE

CHILD PROCESS FAILED WITH NO ERROR_FILE
Child process 32378 (local_rank 0) FAILED (exitcode 1)
Error msg: Process failed with exitcode 1
Without writing an error file to <N/A>.
While this DOES NOT affect the correctness of your application,
no trace information about the error will be available for inspection.
Consider decorating your top level entrypoint function with
torch.distributed.elastic.multiprocessing.errors.record. Example:
from torch.distributed.elastic.multiprocessing.errors import record
@record
def trainer_main(args):
# do train

warnings.warn(_no_error_file_warning_msg(rank, failure))
Traceback (most recent call last):
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/launch.py", line 173, in
main()
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/launch.py", line 169, in main
run(args)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/run.py", line 621, in run
elastic_launch(
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 116, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 348, in wrapper
return f(*args, **kwargs)
File "/home/delight-gpu/anaconda3/envs/lptn/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 245, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:

     codes/train.py FAILED

=======================================
Root Cause:
[0]:
time: 2021-07-25_21:37:41
rank: 0 (local_rank: 0)
exitcode: 1 (pid: 32378)
error_file: <N/A>
msg: "Process failed with exitcode 1"
Other Failures:
[1]:
time: 2021-07-25_21:37:41
rank: 1 (local_rank: 1)
exitcode: 1 (pid: 32379)
error_file: <N/A>
msg: "Process failed with exitcode 1"
[2]:
time: 2021-07-25_21:37:41
rank: 2 (local_rank: 2)
exitcode: 1 (pid: 32380)
error_file: <N/A>
msg: "Process failed with exitcode 1"

Hi,
Actually, the error in your case is "local variable 'gt_img' referenced before assignment".

Hi,
Actually, the error in your case is "local variable 'gt_img' referenced before assignment".

Dear csjliang
I am not  change your code. I just use your code to train my data set by multi-GPU.

The code has been validated. Please make sure to follow our instructions in ReadMe. Thanks.


Scientists want cellxgene to support data modalities that help define cell types and states

Background
The central dogma of molecular biology describes the flow of molecular information between genetic systems. Each of these stages and processes can be assayed to generate count data. In brief:
Input    Output               Process                            Multiplicity
DNA      poised polymerase    transcription initiation           1:N
pp.      preRNA               transcription                      1:1
preRNA   mRNA                 splicing,                          1:N
mRNA     protein              translation,                       1:1
protein  active protein       phosphorylation, ubiquitinlyation, 1:N
                              cleavage, other, )

There are common assays that generate biological data on molecules (not exhaustive):
Molecule  Assays
DNA       ATAC-seq, DNAse-seq
pp.       Polymerase ChIP
preRNA    end-localized RNAseq: 10x 3', 10x 5', Drop-seq, InDrops, Full length RNAseq: SS2
mRNA      end-localized RNAseq: 10x 3', 10x 5', Drop-seq, InDrops, Full length RNAseq: SS2
protein   CITE-seq, MIBI, CyTOF,

There are also assays or algorithms that measure or infer processes (not exhaustive):
Process      Assay
splicing     RNA-velocity
translation  ribosome profiling

Important notes:

Later stages of genetic information transfer can be translated, usually with a loss of information, to earlier states. For example, there is a 1:1 correspondence between active protein > mRNA > preRNA > DNA. The converse is not true.
"molecules per gene", the most common measurement from 10x genomics, records information that corresponds to "pre-RNA".
Most RNA-seq assays can provide information on transcripts. They elect not to because the data have low accuracy; they don't record enough of the gene to identify all the splicing events and therefore often cannot uniquely identify an mRNA molecule from the set of possible molecules.

The types of assays that users have requested are listed as child tickets of this epic.

chanzuckerberg/cellxgene#1673 contains a potential implementation for multiple symbol types, which could be relevant to datasets with multiple modalities that map to the same feature types. e.g. PTPRC (gene) vs CD45R0 (messenger, protein)

chanzuckerberg/cellxgene#1673 contains a potential implementation for multiple symbol types, which could be relevant to datasets with multiple modalities that map to the same feature types. e.g. PTPRC (gene) vs CD45R0 (messenger, protein)


Add URN field to Contact model

@rudigiesler ready for review

I feel like there should be more to this ticket but I'm not sure what else to add.

:+1:

@rowanseymour Our addition of the URNs field to Contacts for you to look at


[Logger] Don't panic if unsupported char

Hello,
Currently, when we print a char in the screen if it is unsupported on noto-sans-mono-bitmap it panics.
Now the noto-sans-mono-bitmap supports the '■' char, we can use it instead of panicking.
Changes included in this PR:
- Update noto-sans-mono-bitmap (Cargo.toml)
- Don't panic if an unsupported char is found (src/binary/logger.rs)
Thanks!

I opened https://github.com/rust-osdev/bootloader/pull/267 to bump the noto-sans-mono-bitmap to 0.2.0 (unreleased yet). This will make this PR obsolete.

Closing this in favor of #267.


InterOP: enable test report generation for tests

Signed-off-by: anandrkskd<EMAIL_ADDRESS>What type of PR is this:
/kind tests
What does this PR do / why we need it:
As we are want to start InterOP testing for v3, we need to start test reports generation.
Which issue(s) this PR fixes:
Fixes #
PR acceptance criteria:

[ ] Unit test

[ ] Integration test

[ ] Documentation

How to test changes / Special notes to the reviewer:

/test v4.11-integration-e2e

    Deleting dir: C:\Users\Administrator.ANSIBLE-TEST-VS\AppData\Local\Temp\2777555636
    Unable to delete C:\Users\Administrator.ANSIBLE-TEST-VS\AppData\Local\Temp\2777555636 on attempt #4, trying again...
    [odo] I1116 04:58:59.493023    2412 delete.go:80] failed to delete resource "binding-zdpp" (binding.operators.coreos.com.v1alpha1.servicebindings): timeout while waiting for "binding-zdpp" resource to be deleted
    [odo] Failed to delete the "Deployment" resource: mynode-app
    [odo] Failed to delete the "ServiceBinding" resource: binding-zdpp
    Deleting dir: C:\Users\Administrator.ANSIBLE-TEST-VS\AppData\Local\Temp\2777555636
    Successfully deleted C:\Users\Administrator.ANSIBLE-TEST-VS\AppData\Local\Temp\2777555636 after #5 attempts
    Deleting dir: C:\Users\Administrator.ANSIBLE-TEST-VS\AppData\Local\Temp\1672953641
  << End Captured GinkgoWriter Output

  Timed out after 180.003s.
  Expected process to exit.  It did not.
  In [BeforeEach] at: C:/Users/Administrator.ANSIBLE-TEST-VS/2486/tests/helper/helper_dev.go:187
------------------------------
+++++++
------------------------------
+ [SLOW TEST] [121.536 seconds]
odo dev command tests when a hotReload capable project is used with odo dev should execute the run command
C:/Users/Administrator.ANSIBLE-TEST-VS/2486/tests/integration/cmd_dev_test.go:2464
------------------------------

Summarizing 1 Failure:
  [FAIL] odo add binding command tests when the component is bootstrapped when adding a binding (current namespace) when odo dev is run when odo dev command is stopped [BeforeEach] should have successfully delete the binding
  C:/Users/Administrator.ANSIBLE-TEST-VS/2486/tests/helper/helper_dev.go:187

Ran 325 of 399 Specs in 902.445 seconds
FAIL! -- 324 Passed | 1 Failed | 0 Pending | 74 Skipped

Retriggering the tests...

/override ci/prow/v4.11-integration-e2e
Tests passing on IBM Cloud.


Home app no longer finds the bridge

All devices went non-responsive. Found homebridge to be running fine with no errors. Stopped and restarted it anyway and no luck. Deleted the homebridge from the Home app and tried to re-add it and it won't find it. Changed the username, pin, and both -- still no luck.
Again, Homebridge starts up and runs fine. Home app isn't seeing it.

I'm having the same issue

I am experiencing the same problem. Homebridge is running, I see the changes but the Home app losses connection after a while. Running the latest version 0.4.29 and 1 plugin (homebridge-hue) installed.

I have the same problem! First time config its ok but if I shut down or restart Homebridge Home app don't work.

Here's some output from syslog:
EventedHTTPServer [::ffff:<IP_ADDRESS>] New connection from client
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP server listening on port 42175
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP request: /pair-verify
HAPServer [CC:22:3D:E3:CE:30] HAP Request: POST /pair-verify
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP Response is finished
EventedHTTPServer [::ffff:<IP_ADDRESS>] New connection from client
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP server listening on port 35249
EventedHTTPServer [::ffff:<IP_ADDRESS>] Client connection closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP connection was closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP server was closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP request: /pair-verify
HAPServer [CC:22:3D:E3:CE:30] HAP Request: POST /pair-verify
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP Response is finished
EventedHTTPServer [::ffff:<IP_ADDRESS>] Client connection closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP connection was closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP server was closed

Also me. Same symptoms and after deleting accessories and persist folders, changing username and ping. Homebridge working but not detected by Home app in two different devices with two different Apple accounts :(

Probably related: https://github.com/nfarina/homebridge/issues/1528
I noticed this on multiple occasions (with both homebridge and my other HAP-NodeJS installation, which homebridge is based on). Deleting the persist folder usually fixes it, but it's annoying as I have to rebuilt my configuration in the Home app.
syslog messages are the same as @ronaldvans - leading me to believe the initial verification/encryption/handshake data is corrupted somehow.

I'm having the same issue, has anyone been able to find a fix?

This did it for me:

Stop Homebridge in Terminal and Exit
Delete the persist folder
Kill the home app
Restart Homebridge and check the Home App
If this does not fix it, repeat steps 1-3 and then:
Change any character in the username and pin section to the config.json.
Restart Homebridge and check the Home App
If this does not fix it, repeat steps 1-2 and then:
Delete Homebridge out of the Home App (Warning. You're starting over in the Home App. Room names and pictures remain, but assignments and automations are all gone.)
Kill the Home app.
Restart Homebridge and check the Home App.

I had to go to through all of these steps. In the past, sometimes 1-4 worked for me. It has been up for two or three days now.

I did this process several times but didn’t work. Finally, I remove everything from the Home App, kill the app and reset all settings in my homebridge. I wait several hours before trying again and it worked! Just remove it, and be patient before adding it again :) It should be an iCloud issue.

On 3 Nov 2017, at 01:56, jack-hub<EMAIL_ADDRESS>wrote:
This did it for me:
Stop Homebridge in Terminal and Exit
Delete the persist folder
Kill the home app
Restart Homebridge and check the Home App
If this does not fix it, repeat steps 1-3 and then:
Change any character in the username and pin section to the config.json.
Restart Homebridge and check the Home App
If this does not fix it, repeat steps 1-2 and then:
Delete Homebridge out of the Home App (Warning. You're starting over in the Home App. Room names and pictures remain, but assignments and automations are all gone.)
Kill the Home app.
Restart Homebridge and check the Home App.
I had to go to through all of these steps. In the past, sometimes 1-4 worked for me. It has been up for two or three days now.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub https://github.com/nfarina/homebridge/issues/1581#issuecomment-341600262, or mute the thread https://github.com/notifications/unsubscribe-auth/ALZREBzLRbonrMiGdLYtnesvljPX8hCFks5symS7gaJpZM4QKaB7.

Hello All, I had this same issue and I solved it today. homebridge was found but all accesoires where 'Not Responding'
I thought it was because of an IOS 11 update first but after completely removing / reinstalling my PI3 with homebridge the issue was still there. I googled a lot and in my case my router (Netgear Orbi) had this multicast feature set to disabled:
Disable IGMP Proxying. IGMP proxying allows a computer on the local area network (LAN) to receive the multicast traffic it is interested in from the Internet.
After enabling this multicast feature and rebooting the router it was completely running fine again!
It's unknown to me why this setting was disabled but now it is working like a charm again :-)
Keep up the good work nfarina! I love homebridge!

same issue here. re-added and it worked for a day or so. now iOS doesn't find home bridge anymore.
My router has no way of turning disabling IGMP.

OK so new update here from me after disabling IGMP it worked for a 1,5 day and got the problem again. So the status now is that Siri works and automation in the iOS home app also works. But most of the accessoires are not responding again.
I am completely surprised and do not know what exactly the problem is and how to resolve it. I have tried with downgrading and upgrading my router and IGMP settings but it does not impact the result. So again Siri commands seem to work but the Home app accessoires cannot (most of them) be controlled. Homebridge on my raspberry pi is working fine without errors in the logs.
any suggestions?

I deleted the persist folder and re-added homebridge on my iPhone
better than here. For me it worked only about 30 min...
logs of homebridge look fine, gets the updates from home-assistant just no mention of any iOS device...

I somehow suspect the appletv to be part of the problem... not sure if and why. But I will try with the appletv disconnected. Do you have appleTV?

@DiMarcello77 I got the same issue,How did you connect pi3 to the router? I use wifi. Homebridge on my raspberry pi3 got the error in /var/log/homebridge.err like this:
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP Response is finished
EventedHTTPServer [::ffff:<IP_ADDRESS>] Client connection closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP connection was closed
EventedHTTPServer [::ffff:<IP_ADDRESS>] HTTP server was closed

Hi, I use LAN cable but also tested with Wifi. I have also experienced the above messages!

I do not have the apple TV but using my ipad air 2 as home hub. I tried with disable and enable this but did not solve any problem.

Update from my side. Without the appleTV (I unplugged them) I have had no problems fro the last 3 days. I will keep it running for a few more days and then plug the appleTV back in and see what happens...

When I use LAN cable,the problem seemed to be sloved. I hope this method works

seems like homebridge is not a dependable source
On Tue, Nov 28, 2017 at 7:27 AM, ilovehotmilk<EMAIL_ADDRESS>wrote:

When I use LAN cable,the problem seemed to be sloved. I hope this method
works
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/nfarina/homebridge/issues/1581#issuecomment-347507891,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AfsCoh-k2tYfkrh03V5fWdLH_seHCTVtks5s6_wkgaJpZM4QKaB7
.


Transaction not showing

Hello i had sent 0.1395 bitcoin to this address 1KqatWZt2Zwzp4DQTVv9ddFVCawZ14LNdP via my unocoin wallet address on 2016-11-28 13:29:46 and hash code d2bb8740f9e1c4f421d3c1c3f19bf090bb46a3e2c0369b29c9d3e01c815c356c but i still not received bitcoin to other address please solve this problem

я оплатила 0,00557 ВТС на адрес 19zmqFok8qLF4xtz6VdUs6pGr4PgcUT6rJ 23.02.2017, транзакция
c93428466a3df7404de27e8dc10899659badd4a6b8961a9f5dcd8be112cc186c, но биткоины так и не получила на мой адрес 34hiPe3MuVjBga1GayyhQ1qgxmoBHdp6RF. Помогите решить эту проблему

Hello, there was a payment bd7AsLDEmjf16i7Z58fFLUBd2udi4g0ft8QWTuBg Mining-Dutch - (payment not confirmed)
10,680,92032240 digibyte to the address DFZqTpmPe9kjs5eLbuW1BV7qq58sRFZk5A, and until now it has not been confirmed, please sort it out


Added a Czech translation for base

Base was missing Czech translation

Great! Thank you @genesiscz , it's been merged into master and it'll be available later today, after I bundle it with a few more non-breaking changes.
Cheers! Thanks for taking the time to put this together.


Support ParameterFilter and RequestBodyFilter on OpenApiOperation from metadata

@marcominerva reported an issue in https://github.com/dotnet/aspnetcore/issues/45307 wherein parameter filters are not applied to parameters in OpenApiOperations sourced from metadata.
I believe this happens for ParameterFilters (and like RequestBodyFilters) because these filter types are invoked closer to the creation of those generators where as DocumentFilters and OperationFilters run after the OpenApiOperation has been plucked from metadata.
Is there a strategy we can use to run these filter types across both scenarios without much duplication?

Any progress here?

Still having this problem on .NET 8.0.1

It's supported with #3059


[Event Hubs Client] Enhance ReadMe

Update the client library ReadMe to adapt to the guidelines  for format and content where reasonable to do so.
While the ideal goal is conform to the template, the goal is not 100% compliance.  Some content should be left as it was written in the standalone repository in order to keep to the scope of work of adopting the client library source into the central repository, as opposed to moving all Service Bus-related artifacts.

Work is believe to be complete; to be included as part of the work for [Event Hubs] Migrate Client Code into Central Repository


Able to trigger delivery with incorrect/non-existing service name

When triggering a sequence e.g. keptn trigger delivery --project my-project --service my-misspelled-service ... keptn validates the existence of project my-project but is not checking whether service my-misspelled-service was created.
To Reproduce
Trigger a sequence (e.g. delivery) with a service name for which no service was created.
Expected behavior
The sequence is not launched.
The user is presented with an error message like it is the case for non-existing projects.
Current behavior
The sequence is launched but fails later on, e.g. when the helm service wants to deploy the artifact for the service.

Does the same problem happen also when triggering evaluation?

@warber is the problem present only when using CLI or via API as well ?


one line htaccess setup option

if your htaccess already has RewriteEngine on, you only need a one-liner for configuring Bridgy Fed for discovery and following. also pruned some spaces in the 3-liner code for Apache. no need for a br right before a pre tag

Thanks for the contribution! I may revise this to DRY it, but great idea.


Update XmlFileErrorLog.cs

Add Application name on xml file log

@atifaziz Same comment as in the other pull request 😄