Add C# specific syntax highlighting

I love this theme but felt that it could be improved a bit for C# use. I changed some colors so it's easier to for example differentiate fields from functions. I also added a C# code example.
Old:

New:

Also please add yourself to the contributors section in package.json & README.md 🙏

I have updated the colors so "this" is consistent with the other purple elements. Thanks for pointing that out.
(Excuse the fat fingers)

:tada: This PR is included in version 1.5.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Table row Iterator trait pattern should be a macro

There's a good bit of code duplication implementing Iterator for all the Table/TableRef row types.
This implementation code should just be a macro: the types backing the iterators are only accessed by their Iterator behavior.

Can deal with this after #148?


Network Deduplication Missing LLCs with LLCs as Agents

This should be a direct LLC <> LLC linkage, but is missed because it's deduplicating on agent names. (See Beacon Communities properties Mandela Homes on Washington and Hammond).
Need an intervening step in run() where corporations listed as agents are flagged and identified in corps (probably just text match on 'LLC').

Workable implementation on 261d39b - also dealt with attorneys, who are often listed agents.


WIP: Jude/ Add Filepond file/image uploader to Post form

[x] replace text editor with draft-js
[x] add post images to schema
[x] added toolbar
[ ] add image uploader to post form
[ ] display post images

To be returned to later after fixing core feature bugs


v2.6 fails a debug session if no Local ServiceConfiguration is present

We had an issue where after we migrated to 2.6 from 2.5 we were getting:
2>unable to get setting value
2>Parameter name: profileNameError: Cancelled
When starting a debug session. Our continuous deployment pipeline where we package through MSBuild with /t:Publish and deploy with PowerShell was working fine.
This was because we don't have neither a Local or Cloud profile in the project. We use a profile per solution configuration that matches the name of the solution configuration. So our "Local" profile is named "Debug".
We use the "TargetProfile" element for each configuration to specify the right service configuration.
Once a local profile was created from a copy of the Debug profile, everything worked fine.

@djfr please open a new issue if the problem still exists/repros.


grpc qdrant client caused error with ordering parameter

I have successfully upserted a vector to the qdrant server with the https protocol. However, upserting using the grpc protocol with an ordering parameter, either "weak", "medium", or "strong", would cause TypeError: Message must be initialized with a dict: qdrant.UpsertPoints.
Current Behavior
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[1], line 17
----> 1 grpc_client.upsert(collection_name=collection_name, points=Batch(ids=ids, payloads=payloads, vectors=vectors), ordering='strong')

File ~/miniconda3/envs/qdrant/lib/python3.8/site-packages/qdrant_client/qdrant_client.py:987, in QdrantClient.upsert(self, collection_name, points, wait, ordering, shard_key_selector, **kwargs)
    959 """
    960 Update or insert a new point into the collection.
    961
   (...)
    983     Operation Result(UpdateResult)
    984 """
    985 assert len(kwargs) == 0, f"Unknown arguments: {list(kwargs.keys())}"
--> 987 return self._client.upsert(
    988     collection_name=collection_name,
    989     points=points,
    990     wait=wait,
    991     ordering=ordering,
    992     shard_key_selector=shard_key_selector,
    993     **kwargs,
    994 )

File ~/miniconda3/envs/qdrant/lib/python3.8/site-packages/qdrant_client/qdrant_remote.py:1274, in QdrantRemote.upsert(self, collection_name, points, wait, ordering, shard_key_selector, **kwargs)
   1270 if isinstance(shard_key_selector, get_args_subscribed(models.ShardKeySelector)):
   1271     shard_key_selector = RestToGrpc.convert_shard_key_selector(shard_key_selector)
   1273 grpc_result = self.grpc_points.Upsert(
-> 1274     grpc.UpsertPoints(
   1275         collection_name=collection_name,
   1276         wait=wait,
   1277         points=points,
   1278         ordering=ordering,
   1279         shard_key_selector=shard_key_selector,
   1280     ),
   1281     timeout=self._timeout,
   1282 ).result
   1284 assert grpc_result is not None, "Upsert returned None result"
   1285 return GrpcToRest.convert_update_result(grpc_result)

TypeError: Message must be initialized with a dict: qdrant.UpsertPoints

Steps to Reproduce
from qdrant_client import QdrantClient
from qdrant_client.models import Batch
import time

grpc_client = QdrantClient("xxx", grpc_port="xxx", prefer_grpc=True, timeout=30.0)

ids = ["xxx"]
payloads = [{
    "extra_info": {
        "name":"hello"
    },
    "created_at": int(time.time())
}]
collection_name = "xxx"
vectors = [[0.1 for i in range(512)]]

grpc_client.upsert(collection_name=collection_name, points=Batch(ids=ids, payloads=payloads, vectors=vectors), ordering='strong')

Expected Behavior
UpdateResult(operation_id=6, status=<UpdateStatus.COMPLETED: 'completed'>)

Possible Solution
When I removed ordering or set it as None, the code worked fine.
grpc_client.upsert(collection_name=collection_name, points=Batch(ids=ids, payloads=payloads, vectors=vectors))

Context (Environment)
I am using python 3.8 with qdrant-client 1.7.0

I assume this is fixed now. Feel free to open this again if that isn't the case.


Add option to disable code frame.

This might sound weird, since code frame is a great feature of babel-eslint.
My use case:
I want to display eslint reports in go.cd, for that I need to generate an HTML report, which is usually easy with eslint HTML formatter, and it results in something like this:

However with babel-eslint, due to the code frame feature the same report looks like this:

This PR adds an option to parserOptions to disable the code highlight feature, and when enabled, it simply returns the regular exepected output to eslint, so... when .eslintrc looks something like this:
{
  "parser": "babel-eslint",
  "parserOptions": {
    "codeFrame": false
  },
  "extends": "eslint:recommended"
}

the generated HTML will look similar to this:

I hope this PR is good enough to merge, however if anything is needed, please just say so :)

Sounds good, cc @kaicataldo on where to put this option, sounds like it has to be in parserOptions

I think keeping it in parserOptions is good

Can we add a test somewhere for this - that it prints/doesn't print those characters? Maybe can just write a syntax error and regex/search for a char?

I've just added some basic tests as suggested. However I'm not sure of their correct place inside the test files. If they are not in right place, please just say so. :)

maybe it could go in it's own file but this is good!

Thanks @Couto, and can you add this to the readme?

btw added you as collab for the eslint team in babel if that's cool


Upgrading from 0.30.0 to 0.31.0 breaks webpack

We've encountered that upgrading to the latest release causes problems downstream in our React/Webpack setup.
Creating an optimized production build...
Failed to compile.

Module not found: Error: Default condition should be last one

This looks related to PR #221
Downgrading back to 0.30.0 makes everything work again.

Can confirm.
Also the only difference between the files built with 0.31.0 as opposed to 0.30.0 seems to be related to the changes made in #221 (only exports in package.json are different).

Can confirm, the output of different versions to the package.json:
0.31.0 & 0.32.0:
"exports": {
  ".": {
    "import": {
      "default": "./esm/index.js",
      "types": "./types/index.d.ts"
    }
  }
},

0.30.0:
  "exports": {
    ".": {
      "import": "./esm/index.js",
      "types": "./types/index.d.ts"
    }
  },

Webpack expects that the default property is always the last one inside of an exports object. (The Nodejs documentation for the exports field mentions that the order is important: look for "key order is signficant" in https://nodejs.org/api/packages.html. Here's an example of another project running into this issue and fixing it by reordering the properties: https://github.com/transitive-bullshit/chatgpt-api/pull/25.)
If you edit the exports to reorder the properties like this, then it works fine with Webpack:
"exports": {
  ".": {
    "import": {
      "types": "./types/index.d.ts",
      "default": "./esm/index.js"
    }
  }
},

Yeah that’s a bug. Types should come first. TypeScript works the same way (sorry, I didn’t know the order mattered until recently)

Fixed in 0.32.1 (thanks @Macil!). Sorry for the delay on this. It was actually wrong before in 0.30.0 too.


Floating point exception in mxnet.ndarray.op.SequenceReverse

Description
(A clear and concise description of what the bug is.)
mxnet.ndarray.op.SequenceReverse has floating point exception when given data has 0 in its shape. Please see the provided code for example.
Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable DMLC_LOG_STACK_TRACE_DEPTH=10 before running your script.)

Floating point exception (core dumped)

To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
import mxnet
import numpy as np
data = mxnet.nd.array(np.random.rand(0,1,1))
mxnet.ndarray.op.SequenceReverse(data)

Steps to reproduce
(Paste the commands you ran that produced the error.)

run the provided code in python interpreter or as a script

What have you tried to solve it?

Environment
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python

# paste outputs here

Got 404 when trying to get the script.
Some environment information:

OS: ubuntu 18.04
Python: 3.7.6
pip: 20.0.2
numpy: 1.18.5
mxnet: 1.6.0

So here's the problem:
% DMLC_LOG_STACK_TRACE_DEPTH=150 MXNET_ENGINE_TYPE=NaiveEngine lldb python3.7 -- test_18940.py
(lldb) target create "python3.7"
Current executable set to 'python3.7' (x86_64).
(lldb) settings set -- target.run-args  "test_18940.py"
(lldb) run
Process 78879 launched: '/usr/local/bin/python3.7' (x86_64)
Process 78879 stopped
* thread #2, stop reason = exec
    frame #0: 0x0000000100006000 dyld`_dyld_start
dyld`_dyld_start:
->  0x100006000 <+0>: popq   %rdi
    0x100006001 <+1>: pushq  $0x0
    0x100006003 <+3>: movq   %rsp, %rbp
    0x100006006 <+6>: andq   $-0x10, %rsp
(lldb) cont
Process 78879 resuming
[23:52:34] ../src/engine/engine.cc:55: MXNet start using engine: NaiveEngine
Process 78879 stopped
* thread #2, queue = 'com.apple.main-thread', stop reason = EXC_ARITHMETIC (code=EXC_I386_DIV, subcode=0x0)
    frame #0: 0x0000000115861a13 libmxnet.dylib`mxnet::op::SequenceReverseOp<mshadow::cpu, float, float>::Forward(this=0x0000000123da0db0, ctx=0x00007ffeefbfc2b0, in_data=0x0000000127b7a2f8, req=0x00007ffeefbfc310, out_data=0x0000000127b7a340, aux_args=0x0000000127b7a328) at sequence_reverse-inl.h:139
   136 	    auto max_seq_len = in_data[seq_reverse::kData].size(0);
   137 	    auto n = in_data[seq_reverse::kData].size(1);
   138 	    auto total_size = in_data[seq_reverse::kData].Size();
-> 139 	    auto rest_dim = static_cast<int>(total_size / n / max_seq_len);
   140
   141 	    Shape<3> s3 = Shape3(max_seq_len, n, rest_dim);
   142 	    Tensor<xpu, 3, DType> data =

https://github.com/apache/incubator-mxnet/blob/9bdd4d6347c284770ee5bfe5ae98f1dabc283829/src/operator/sequence_reverse-inl.h#L139
The code needs to guard against zero-size array for right operand of /, and we should add a smoke test to guard against such problem in this op, similar to https://github.com/apache/incubator-mxnet/pull/18972/files

Could I get this assigned??

Hello,
I see a PR merged for this issue.
Is this still open?

It seems like there is an arithmetic error in the code where the right operand of the division operator is zero, causing an EXC_ARITHMETIC exception. One way to guard against this error is to add a conditional statement that checks if the right operand is zero before executing the division operation.
can i work on it if it's still open?


[DNM]add metric for size of snap chunk

LGTM

The metrics will become meaningless after we add limitation on snap worker queue. So close it.


feat(java): optimize readVarInt performance for jvm jit

This PR optimizes readVarInt performance by reduce code size of readVarInt for better jvm jit

Before:

After:


Merge algorithm for non-collinear systems

Consider the anisotropic exchange tensor $J_{ij}$ describing the interaction between two magnetic sites with local magnetic moments $\mathbf{m}_i$ and $\mathbf{m}_j$. Let $\hat{\mathbf{u}}_{ij}$ be a unit vector that is normal to both $\mathbf{m}_i$ and $\mathbf{m}_j$. Then, we can only obtain the projection $\hat{\mathbf{u}}^T J_{ij} \hat{\mathbf{u}}$ with a single TB2J calculation. The latter can be written as
$\hat{\mathbf{u}}^T J_{ij} \hat{\mathbf{u}} = \hat{J}_{ij}^{xx} u_x^2 + \hat{J}_{ij}^{yy} u_y^2 + \hat{J}_{ij}^{zz} u_z^2 + 2\hat{J}_{ij}^{xy} u_x u_y + 2\hat{J}_{ij}^{yz} u_y u_z + 2\hat{J}_{ij}^{zx} u_z u_x$,
where we considered $J_{ij}$ to be symmetric.
If we perform six calculations such that $\hat{\mathbf{u}}_{ij}$ lies along six different directions, then we obtain six linear equations which can be solved for the six independent unknown components of $J_{ij}$.
When  $\mathbf{m}_i$ and $\mathbf{m}_j$ are parallel to each other, then we can use the components of $J_{ij}$ along the plane orthogonal to both $\mathbf{m}_i$ and $\mathbf{m}_j$ . Thus, with six different calculations, we could obtain more than six equations for the six components of $J_{ij}$ . In this case, we can obtain the tensor components by a least squares method.

Hello Andres,
@antelmor Thank you!

Could you keep the legacy TB2J_merge.py and put the new script into TB2J_merge2.py, so that when $m_i$ and $m_j$ are parallel, we don't need to redo all the calculations.  Or do you think even in these cases, the six-state method should replace the legacy one?
Could you add a simple tutorial in doc/src/rotate_and_merge.rst?
How do we get the infomation of the magnetic moments, by the user input or by reading the siesta/openmx/abacus output? I don't think the Wannier functions work well with the strong non-collinear case  in the current implementation so perhaps we don't need to worry about how to read from other codes for the moment.
Best wishes,
HeXu

Hello @mailhexu.

This new script is a generalization of the legacy TB2J_merge.py. It also works for the collinear cases in which we only need three configurations. The script doesn't require a specific number of rotated configurations; it always gives the best result considering all the configurations given to the script. If we give too few configurations, the results will have a large error. In the case of a collinear system, we need to provide at least three non-parallel configurations; whereas for a non-collinear system, we need at least six. In the most recent commit, I added a warning message that tells the user when more configurations are required. Furthermore, this script works the same if the configurations are spin-rotated or structure-rotated. This differs from the legacy script, where the user had to tell which rotation type was used.
I will add a tutorial considering both a collinear and a non-collinear system.
The script gets the magnetic moments from the TB2J.pickle of each finished calculation. So far I have only tested the script with Siesta-TB2J calculations. Could this change if we use Wannier-TB2J calculations?

Hello Andres,
Thanks!
Don't worry about the Wannier-TB2J calculation for the non-collinear cases. For now I will add that the Wannier-TB2J interface is dis-encouraged in the documentation if the spin is not almost collinear.
I will check again and merge when the documentation is ready.
Best regard,
HeXu

Hello @mailhexu.
I have modified the script to rotate the structures; it can now generate the structures required for a noncollinear system. Moreover, I have created an additional script for the TB2J-SIESTA calculations, where you can globally rotate the magnetic moments contained in the density matrix file of an SIESTA calculation. This is helpful when a user wants to rotate the spins instead of the structure. Finally, I have updated the rotate_and_merge.rst file with the required documentation for all the scripts.
Best,
Andres.


nothing visible in devices

nothing visible in devices and log no error messages do you know what I'm doing wrong

The plugin starts with an arp request to determin the ipaddresses of all your devices in your network. And then performs an recursive lookup to determin the hostname of your device. For this step you must have setup /etc/hosts on your domoticz server and added the full qualified domain name and ipaddress of your WIZ connected devices, of setup a DNS server (fi on your router). Also the FQDN-names have to start with the Prefix you've configurated in the plugin, default "WIZ_"

Guess this issue is solved and close it. If the issue is niet solved, please deel free to reopen it.


WIP: Add RNNoise, use it in Mumble

Motivation for this change
Vastly improves suppression of background and typing noises.

Things done

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

[x] NixOS
[ ] macOS
[ ] other Linux distributions

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

Notify maintainers
Me as new maintainer.
@chpatrick to test, then we can remove WIP.

CC @clefru because I got RNNoise from your NUR, so you may like this upstreaming.

Works for me!


Wrapper tx replay protection

As noted in https://github.com/anoma/anoma/blob/625bab46c32da6aeb35418869974bfb1ac98cd3e/docs/src/specs/ledger.md: "DKG transactions will include replay protection (this is because we can simply check a counter against the source (i.e. gas payer) of the transaction before the transactions order is committed to by the DKG protocol, which could affect the expected counter order for sources with multiple queued transactions)".
We should add reply protection to the wrapper tx. This can simply be a counter in implicit accounts that is checked and incremented by the wrapper transactions.

The replay protection should probably be implemented in the protocol as it doesn't need to involve any VP. The counter field should then be added to the wrapper tx. For a tx to be valid, it should match the current value of the counter stored for the source implicit account in the ledger. To submit multiple txs from the same account at once, we should allow to set the explicitly set the --counter for any tx. If not specified, the client can read (default to 0, if no counter is set yet) and use the current value from the ledger.

with #676, it should be possible to auto-increment the counter so the user never has to specify it explicitly

So after some discussion, we came to the following idea:

In each the storage addressed to each implicit account, we keep a counter.
Wrapper txs will now include a counter field
During process proposal, we check in the wrapper txs that the counter field is >= than the counter in storage.
During finalize block, in the write ahead log, for each tx, we take the max of the new counter for the associated implicit acount and the tx counter field.


Unquoted strings, inline arrays

Hey!
I needed to make it prettier so I could use it :-)

Error: Module not found: Error: Can't resolve 'json-to-pretty-yaml' in debian environment while running Ut's


MCS-1777 Pipeline Improvements and Bug Fixes for Eval 7

Upgraded our ray version (thanks Phi!)
Changed p2.xlarge to p3.2xlarge
Added a controller timeout
Added an if statement to check for null case that was causing an error
Ensure the ray autoscaler will delete idle workers by deleting all references to finished ray objects.

This PR is ready for review and will be useful for validation and evaluation runs.

This PR is ready for review and will be useful for validation and evaluation runs.

Nice, I'll use this for CORA's run moving forward.


docs(RAB): add @MerlinEgalite as reviewer

My review of Realitio Proxy contracts: https://docs.google.com/document/d/1BoB2G8W3LKe3YZWbNJUp_iYSsbtb_d_6YJOgcvcBtLA/edit?usp=sharing

Can you please update the permissions of the doc? We can't view it.

Should be good now @mtsalenc


Tweaks to SFC compiler: user nodeTransforms

What problem does this feature solve?
I would like to suggest 2 tweaks to the SFC compiler, related to user nodeTransforms.
Tweak 1: run user transforms first
I didn't find documentation for custom nodeTransform but reading the source code I noticed they run after the built-in transforms.
This means that it's too late if you wanted to customize, or leverage, what a built-in transform does.
I'd rather have user transforms run first, or maybe have 2 options: preNodeTransforms and postNodeTransforms (is that even useful?).
Use-case: custom v-if
I'm trying to build a directive that removes elements from DOM (sometimes), i.e. that works like v-if.
The v-if magic is all compile-time so this can't be done with a normal directive at runtime, instead a custom compiler transform to process my v-magic is required.
The thing is: transformIf is not easily re-usable. A large portion of its logic is not exported and wrapped into a function that can't be re-wrapped itself. Copy-pasting here is a bad idea because it could break with any release.
So I thought: easy enough, I'm gonna do a transformMagic that changes the node.props to replace its own v-magic with an equivalent v-if.
In other words: instead of implementing a kind of if transform, I expand my v-magic directive into an equivalent v-if with a condition built by my transform.
This, of course, would only work if the built-in transformIf runs after my user transform, otherwise the v-if expansion would go unnoticed by the compiler.
Tweak 2: Import stuff into the codegen
When emitting custom code, you will quickly want to reuse logic from helpers.
It seems context.helper is hard-coded for a list of internal Vue helpers and I didn't find an API to import arbitrary code, which is quickly limiting when you want to generate your own code.
So I suggest that context has a new API to enable import arbitrary code from arbitrary modules, see Proposed API.
What does the proposed API look like?
For tweak 2, maybe something like:
let hat = context.import("hat", "@/magic.js");

This would ensure that the codegen contains import { hat } from<EMAIL_ADDRESS>A few notes on its behavior:

Context should ensure there is no conflict in imported names. It returns the imported alias and is free to create aliases as it sees fit.
The function should be idempotent: making the same call multiple times should only include the module once and always return the same identifier.
Importing multiple values from the same module should end up concatenated import { hat, wand } from<EMAIL_ADDRESS>

This is... somewhat intended. Opening it up too much essentially allows you to not just extend the Vue template, but create your own dialect. For example a custom v-if is definitely something I do not want to support.
The compiler API serves primarily for Vue internal uses - it is exposed for simple single node transforms. If we have to tweak it to suit more complex use cases, it's increasing the maintenance burden for some very very niche needs, which isn't worthwhile.

I understand the maintenance bit.
It's a bit unfortunate though that removing a node from DOM is something only the compiler can do :(
Here's a use case, let me know if you think of a better way.
I would like to create a directive to easily apply some security policies throughout our application.
Something like v-policy:Admins.
You can easily make it set display: none but there are edge cases where it doesn't totally cut it.
For example if you need to put it on a <template> that encloses several elements.
So if v-if is the single, blessed way to remove something from DOM, we would probably configure a function to be globally available (I think this is possible, right?) and then write v-if="policy('Admins')" instead.
Sure, it works, but at large scale v-policy:Admins feels more convenient and expressive.
RE: creating dialects, this is about creating a directive, it's already possible in the compiler (in a limited way) and I don't feel like it creates more of a dialect than creating a regular runtime directive.


Add test for string rectangle clashing with vector bwtween bonded atoms.

Reference Issue
Fixes #5185
What does this implement/fix? Explain your changes.
Puts an extra test to make sure the annotation doesn't lie on the vector between two bonded atoms.  With a double bond, there isn't a line exactly along that vector.
Any other comments?
Tested on macOs only.

The failure seems to be because I failed to remember to do a non-Freetype version of the test.

I don't think this failure is down to me:
2022-04-11T21:56:12.1737219Z FAIL: testNonUniqueCrash (main.TestCase)
2022-04-11T21:56:12.1738339Z ----------------------------------------------------------------------
2022-04-11T21:56:12.1738885Z Traceback (most recent call last):
2022-04-11T21:56:12.1739348Z   File "/home/vsts/work/1/s/Code/SimDivPickers/Wrap/testPickers.py", line 139, in testNonUniqueCrash
2022-04-11T21:56:12.1739859Z     self.assertTrue(tuple(mm2) != tuple(mm1)) or (tuple(mm3) != tuple(mm1))
2022-04-11T21:56:12.1740278Z AssertionError: False is not true
2022-04-11T21:56:12.1740449Z
2022-04-11T21:56:12.1740984Z ----------------------------------------------------------------------
2022-04-11T21:56:12.1741372Z Ran 11 tests in 0.148s
Both of the failed checks seem to end up in the same place, as far as I can work out.

@DavidACosgrove, yeah, that's one of those intermittent failures that happens in the CI builds.


coub.com - downloaded file is not working

coub.com - downloaded file is not working
youtube-dl.exe Latest (v2019.04.17)

Duplicate:
#13754
(I'll also add a new comment there)


Ashutosh-yadav added to the list

hey, i have added my name in  the list.

@ashu-beckham, I'm quite elated about your PR. I wanna evolve this project to addresses various problems faced by first-time contributors. I'd love to learn about your journey in open source community, the problems, pain points you had etc.
Could you explain how you felt when you went through the tutorial, made a PR and learned that I merged it?


Create CONTRIBUTING.md

Changes

Create a basic CONTRIBUTING.md file with instructions on how to get started

Context

We should have a document that explains how to get started with helping us.
This is beneficial for us too, as we can put things we need to remember while developing in here. 😉
Fixes #220.

It needs more work, but for now this is good enough to start with. 😄


Add DNSSEC support for zones.

Check DNSSEC availability for a zone
Activate DNSSEC for a zone
Deactivate DNSSEC for a zone
Retrieve a zone's DNSSEC DS records

Thanks for this! I'll get it merged here shortly.

Version 0.7 was released with this.


can't embed iframe into table cell?

Need to embed iframe in a table cell.
Tried this:
         # additional_info row
        unless action.additional_info.blank?
          row_2a = Array.new
          row_2a << Caracal::Core::Models::TableCellModel.new do |cell_doc|
            # cell_doc.p action.additional_info # THIS WORKS FINE!
            cell_doc.iframe(data: (PandocRuby.new(action.additional_info, from: 'markdown').to_docx).force_encoding('UTF-8'))
          end
          actions_data << row_2a
        end

while cell_doc.p works cell_doc.iframe throws undefined method for TableCellModel.
thanks in advance!

Looks like https://github.com/urvin-compliance/caracal/blob/562bdc4ceff095d467deca74acdfda5b45c20929/lib/caracal.rb#L34
is missing the include for the IFrames module??


docs(platform): correct a minor typo of "hardware"

Short description of what this resolves:
"hardware" is mistyped "hardward"
Changes proposed in this pull request:

Correct that. That's all.

Ionic Version: 2.x

Thank you!


Using with Intel XDK

Subject of the issue
I Use Intel XDK and this tool has its own bower management
I don't see angular-translate  in the list of i18n packages.
Your environment
T* version of angular-translate:      the last version

version of angular : 1.6.4
which browser and its version: chrome or ie no matter

Steps to reproduce
install intel XDK
create a new project html5
add a bower package
Expected behaviour
The angular-translate should or could be in the i18n package list
Actual behaviour
i am testing intel XDK and i wonder :

why i don't find this very good angular-translate

Sorry, we neither know about nor will take care special support for Intel XDK. We are publishing packages listed in bower and npm, that's enough and is working.
Your toolchain have to support one of both (bower/npm).
In your case: It sounds it does not support bower correctly.


Added Penguins case study notebook

Included a new demo notebook that contains the code for the blog post titled Intelligent Visual Data Discovery with Lux — A Python library by Parul Pandey

This looks great, thank you @parulnith!


Issue with clone example

First check https://github.com/SortableJS/Vue.Draggable/blob/master/CONTRIBUTING.md
Jsfiddle link
https://github.com/SortableJS/vue.draggable.next/blob/master/example/components/clone.vue
Step by step scenario
file:///home/developer/Videos/Kazam_screencast_00002.mp4
Actual Solution
Expected Solution

Hi there @yogeshwar1996 ,
I recently noticed the same issue. In the Vue devtools, I observed that list2 was being updated, but the view wasn't reflecting the changes. In my current project, where I'm using the Composition API, I resolved this by making the lists reactive. Essentially, I did the following:
import { ref } from "vue";
import Draggable from "vuedraggable";

const list1 = ref([
  { name: "John", id: 1 },
  { name: "Joao", id: 2 },
  { name: "Jean", id: 3 },
  { name: "Gerard", id: 4 },
]);

const list2 = ref([
  { name: "Juan", id: 5 },
  { name: "Edgard", id: 6 },
  { name: "Johnson", id: 7 },
]);

Hopefully this will be useful to you or someone else.
Kind regards,
Mladen
p.s. You did not attach your video properly.


In the Event.exception constructor, modify a clone of the args argument instead of args itself

Hotfix for https://github.com/dart-lang/tools/issues/1195 for package:unified_analytics v6.

[x] I’ve reviewed the contributor guide and applied the relevant portions to this PR.

Contribution guidelines:

See our contributor guide for general expectations for PRs.
Larger or significant changes should be discussed in an issue before creating a PR.
Contributions to our repos should follow the Dart style guide and use dart format.
Most changes should add an entry to the changelog and may need to rev the pubspec package version.
Changes to packages require corresponding tests.

Note that many Dart repos have a weekly cadence for reviewing PRs - please allow for some latency before initial review feedback.

@devoncarew
Do you know if updating
https://github.com/dart-lang/tools/blob/e83caeee0d405a74dd1a81d5bacb66db273cf6ce/.github/workflows/publish.yaml#L1-L9
to run against any branch would work for publishing patches to older versions of packages? Assuming that would work, do we want it to (are there branch protections that we have on main that we would then want on all branches)?

Note for @kenzieschmoll, you can ignore the .github/workflows config file changes. This was cherry-picked from main just to get this branch tested on CI.

Hi!

Do you know if updating to run against any branch would work for publishing patches to older versions of packages? Assuming that would work, do we want it to (are there branch protections that we have on main that we would then want on all branches)? I'm happy to track this in a separate issue if we don't want to solve it today.

I think we want to:

create a branch from the tag of unified_analytics that we want to patch (https://github.com/dart-lang/tools/tags)
apply the changes, push it up in a PR for review for merge into that branch
not try to use the publishing automation to publish that new patch, but publish locally from disk

Our publishing automation isn't really set up to handle publishing older patches; that's a rare enough occurrence that I think it's reasonable to handle it by manually publishing from a branch from disk.

SGTM. The first step is already satisfied here, so I will publish this myself once this gets an approval.


Write some tests

I think most everything we have currently is tested and we should build this out naturally as we add more features or come across bugs. The android unit tests are in CI but have problems with timeouts. They can be run via android studio integration test or from hitting the unit test button in the example.
@nakajima whats the status on getting iOS in CI?


Some warnings in cmd - don't know why

Checklist

[x] I have read the FAQ
[ ] I have checked if this issue already exists (both open and closed issues)
[x] I am using the most recent version of pogom from the master branch
[x] If this is an installation issue, I am posting my OS, OS version, python version, pip version
[ ] I'm posting the complete log
[ ] I'm using a descriptive title for this issue

My Issue
I have some warning and i don't know why, and what i doing wrong
I'm using a descriptive title for this issue
maybe everything is ok, but i don't have enough knowledge to judge this

My OS: Windows 8.1
Python: 2.7.12
Pip: 8.1.2

Dupe of #152


Update CLI command parameters

CLI command has changed a lot, it would be great to modify the parameters according to the latest v2 CLI.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: b2646ad4-34b7-fc5e-dcc9-d53a061df394
Version Independent ID: bbff4fda-24e4-2b62-24b9-94cda5f53bed
Content: Work with Azure Functions Core Tools
Content Source: articles/azure-functions/functions-run-local.md
Service: azure-functions
GitHub Login: @ggailey777
Microsoft Alias: glenga

@JohnReeson Thanks for the feedback. Just for reference can you please specify which specific command you are pointing to.

@JohnReeson I have created a PR to update the document. It will be merged soon. We will now proceed to close this thread. If there are further questions regarding this matter, please tag me in your reply. We will gladly continue the discussion and we will reopen the issue.
Thanks for your valuable feedback.


Validation: Only System Operator role is allowed to submit requests concerning tax tariffs

Synopsis
Only tariffs can be marked as tax (tax indicator = true), this is currently enforced by existing validation rules.
The Market Participant role EZ, also known as System Operator, is the only role allowed to submit requests concerning tax tariffs. This story intends to implement validation rule(s) enforcing this.
Tech notes
This must be enforced for both D08 Charge Prices and D18 Charge Information requests. Be aware that TaxIndicator is mandatory in D18 requests, but not in D08. Perhaps this will be an input validation for D18, but a domain validation for D08 (done in Charge.cs)
In DataHub 2 this is VR 508.
D08
Error code: E0I
Error message: "The sender role used is not allowed to submit a price series for charge ID {{DocumentSenderProvidedChargeId}} of type {{ChargeType}} owned by {{ChargeOwner}} as it is marked as a tax"
D18
Error code: E0I
Error message: "The sender role used is not allowed to set tax indicator to {{ChargeTaxIndicator}} for charge ID {{DocumentSenderProvidedChargeId}} of type {{ChargeType}} owned by {{ChargeOwner}}"
Role: EZ = System Operator
Role: DDM = Grid Access Provider
Acceptance criteria:

[ ] 1 The system behaves as described in below scenarios

#
Request type
Sender role
TaxIndicator
Expected result

1
D18 Charge Information
DDM
:heavy_check_mark:
Rejected

2
D08 Charge Prices
DDM
:heavy_check_mark:
Rejected

3
D18 Charge Information
DDM
:x:
Accepted

4
D08 Charge Prices
DDM
:x:
Accepted

5
D18 Charge Information
EZ
:heavy_check_mark:
Accepted

6
D08 Charge Prices
EZ
:heavy_check_mark:
Accepted

7
D18 Charge Information
EZ
:x:
Accepted

8
D08 Charge Prices
EZ
:x:
Accepted

[ ] 2 The new rule(s) have been added to the asynchronous validation rules md file.

Tested in T-001:
AC1:

1	D18 Charge Information	DDM	Tax Rejected:
Rejection:
        <cim:originalTransactionIDReference_MktActivityRecord.mRID>OpId2022-09-16T06:45:19.794Z</cim:originalTransactionIDReference_MktActivityRecord.mRID>
        <cim:Reason>
            <cim:code>E0I</cim:code>
            <cim:text>The sender role used is not allowed to set tax indicator to Tax for charge ID DdmTax0001 of type Tariff owned by<PHONE_NUMBER>016</cim:text>
        </cim:Reason>

2	D08 Charge Prices	DDM	Tax	Rejected:
Using tarif 'TarId051' as test data, as this is actually a tax tariff created by the Grid Access Provider prior to the implementation of this story.

Request:
<?xml version="1.0" encoding="UTF-8"?>
<cim:RequestChangeOfPriceList_MarketDocument xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:cim="urn:ediel.org:structure:requestchangeofpricelist:0:1" xsi:schemaLocation="urn:ediel.org:structure:requestchangeofpricelist:0:1 urn-ediel-org-structure-requestchangeofpricelist-0-1.xsd">
    <cim:mRID>DocId2022-09-16T07:10:38.097Z</cim:mRID>
    <cim:type>D10</cim:type>
    <cim:process.processType>D08</cim:process.processType>
    <cim:businessSector.type>23</cim:businessSector.type>
    <cim:sender_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:sender_MarketParticipant.mRID>
    <cim:sender_MarketParticipant.marketRole.type>DDM</cim:sender_MarketParticipant.marketRole.type>
    <cim:receiver_MarketParticipant.mRID codingScheme="A10">5790001330552</cim:receiver_MarketParticipant.mRID>
    <cim:receiver_MarketParticipant.marketRole.type>DDZ</cim:receiver_MarketParticipant.marketRole.type>
    <cim:createdDateTime>2022-09-16T07:10:38Z</cim:createdDateTime>
    <cim:MktActivityRecord>
        <cim:mRID>OpId2022-09-16T07:10:38.097Z</cim:mRID>
        <cim:ChargeGroup>
            <cim:ChargeType>
                <cim:chargeTypeOwner_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:chargeTypeOwner_MarketParticipant.mRID>
                <cim:type>D03</cim:type>
                <cim:mRID>TarId051</cim:mRID>
                <cim:effectiveDate>2022-09-30T22:00:00Z</cim:effectiveDate>
                <cim:Series_Period>
                    <cim:resolution>PT1H</cim:resolution>
                    <cim:timeInterval>
                        <cim:start>2022-09-30T22:00Z</cim:start>
                        <cim:end>2022-10-01T22:00Z</cim:end>
                    </cim:timeInterval>
                    <cim:Point>
                        <cim:position>1</cim:position>
                        <cim:price.amount>1.112</cim:price.amount>
                    </cim:Point>

Rejection:
        <cim:originalTransactionIDReference_MktActivityRecord.mRID>OpId2022-09-16T07:10:38.097Z</cim:originalTransactionIDReference_MktActivityRecord.mRID>
        <cim:Reason>
            <cim:code>E0I</cim:code>
            <cim:text>The sender role used is not allowed to submit a price series for charge ID TarId051 of type Tariff owned by<PHONE_NUMBER>016 as it is marked as a tax</cim:text>
        </cim:Reason>
    </cim:MktActivityRecord>

3	D18 Charge Information	DDM	NotTax	Accepted:
Request:
<?xml version="1.0" encoding="UTF-8"?>
<cim:RequestChangeOfPriceList_MarketDocument xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:cim="urn:ediel.org:structure:requestchangeofpricelist:0:1" xsi:schemaLocation="urn:ediel.org:structure:requestchangeofpricelist:0:1 urn-ediel-org-structure-requestchangeofpricelist-0-1.xsd">
	<cim:mRID>DocId2022-09-16T06:51:00.639Z</cim:mRID>
	<cim:type>D10</cim:type>
	<cim:process.processType>D18</cim:process.processType>
	<cim:businessSector.type>23</cim:businessSector.type>
	<cim:sender_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:sender_MarketParticipant.mRID>
	<cim:sender_MarketParticipant.marketRole.type>DDM</cim:sender_MarketParticipant.marketRole.type>
	<cim:receiver_MarketParticipant.mRID codingScheme="A10">5790001330552</cim:receiver_MarketParticipant.mRID>
	<cim:receiver_MarketParticipant.marketRole.type>DDZ</cim:receiver_MarketParticipant.marketRole.type>
	<cim:createdDateTime>2022-09-16T06:51:00Z</cim:createdDateTime>
	<cim:MktActivityRecord>
		<cim:mRID>OpId2022-09-16T06:51:00.639Z</cim:mRID>
		<cim:ChargeGroup>
			<cim:ChargeType>
				<cim:chargeTypeOwner_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:chargeTypeOwner_MarketParticipant.mRID>
				<cim:type>D03</cim:type>
				<cim:mRID>TarId054</cim:mRID>
				<cim:name>Charge name</cim:name>
				<cim:description>updated The charge description</cim:description>
				<cim:priceTimeFrame_Period.resolution>PT1H</cim:priceTimeFrame_Period.resolution>
				<cim:effectiveDate>2022-09-30T22:00:00Z</cim:effectiveDate>
				<!--cim:terminationDate>2022-08-10T22:00:00Z</cim:terminationDate-->
				<cim:VATPayer>D01</cim:VATPayer>
				<cim:transparentInvoicing>false</cim:transparentInvoicing>
				<cim:taxIndicator>false</cim:taxIndicator>
			</cim:ChargeType>
		</cim:ChargeGroup>
	</cim:MktActivityRecord>
</cim:RequestChangeOfPriceList_MarketDocument>

Confirmation:
<?xml version="1.0" encoding="utf-8"?>
<cim:ConfirmRequestChangeOfPriceList_MarketDocument xmlns:cim="urn:ediel.org:structure:confirmrequestchangeofpricelist:0:1">
    <cim:mRID>7b73579ba7314d3cae9f33136bce2c55</cim:mRID>
    <cim:type>D11</cim:type>
    <cim:process.processType>D18</cim:process.processType>
    <cim:businessSector.type>23</cim:businessSector.type>
    <cim:sender_MarketParticipant.mRID codingScheme="A10">5790001330552</cim:sender_MarketParticipant.mRID>
    <cim:sender_MarketParticipant.marketRole.type>DDZ</cim:sender_MarketParticipant.marketRole.type>
    <cim:receiver_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:receiver_MarketParticipant.mRID>
    <cim:receiver_MarketParticipant.marketRole.type>DDM</cim:receiver_MarketParticipant.marketRole.type>
    <cim:createdDateTime>2022-09-16T06:51:29Z</cim:createdDateTime>
    <cim:reason.code>A01</cim:reason.code>
    <cim:MktActivityRecord>
        <cim:mRID>136c8348c07f478db2e942bf5d2bdb89</cim:mRID>
        <cim:originalTransactionIDReference_MktActivityRecord.mRID>OpId2022-09-16T06:51:00.639Z</cim:originalTransactionIDReference_MktActivityRecord.mRID>
    </cim:MktActivityRecord>
</cim:ConfirmRequestChangeOfPriceList_MarketDocument>

4	D08 Charge Prices	DDM	NotTax	Accepted:
Using 'TarId054' which is NOT a tax.
Request:
<?xml version="1.0" encoding="UTF-8"?>
<cim:RequestChangeOfPriceList_MarketDocument xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:cim="urn:ediel.org:structure:requestchangeofpricelist:0:1" xsi:schemaLocation="urn:ediel.org:structure:requestchangeofpricelist:0:1 urn-ediel-org-structure-requestchangeofpricelist-0-1.xsd">
    <cim:mRID>DocId2022-09-16T07:15:09.701Z</cim:mRID>
    <cim:type>D10</cim:type>
    <cim:process.processType>D08</cim:process.processType>
    <cim:businessSector.type>23</cim:businessSector.type>
    <cim:sender_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:sender_MarketParticipant.mRID>
    <cim:sender_MarketParticipant.marketRole.type>DDM</cim:sender_MarketParticipant.marketRole.type>
    <cim:receiver_MarketParticipant.mRID codingScheme="A10">5790001330552</cim:receiver_MarketParticipant.mRID>
    <cim:receiver_MarketParticipant.marketRole.type>DDZ</cim:receiver_MarketParticipant.marketRole.type>
    <cim:createdDateTime>2022-09-16T07:15:09Z</cim:createdDateTime>
    <cim:MktActivityRecord>
        <cim:mRID>OpId2022-09-16T07:15:09.701Z</cim:mRID>
        <cim:ChargeGroup>
            <cim:ChargeType>
                <cim:chargeTypeOwner_MarketParticipant.mRID codingScheme="A10">8100000000016</cim:chargeTypeOwner_MarketParticipant.mRID>
                <cim:type>D03</cim:type>
                <cim:mRID>TarId054</cim:mRID>
                <cim:effectiveDate>2022-09-30T22:00:00Z</cim:effectiveDate>
                <cim:Series_Period>
                    <cim:resolution>PT1H</cim:resolution>
                    <cim:timeInterval>
                        <cim:start>2022-09-30T22:00Z</cim:start>
                        <cim:end>2022-10-01T22:00Z</cim:end>
                    </cim:timeInterval>
                    <cim:Point>
                        <cim:position>1</cim:position>
                        <cim:price.amount>1.112</cim:price.amount>
                    </cim:Point>

Confirmation:
    <cim:MktActivityRecord>
        <cim:mRID>e93ff9bb409b4c25ae1fc60bedd1fdbd</cim:mRID>
        <cim:originalTransactionIDReference_MktActivityRecord.mRID>OpId2022-09-16T07:15:09.701Z</cim:originalTransactionIDReference_MktActivityRecord.mRID>
    </cim:MktActivityRecord>
</cim:ConfirmRequestChangeOfPriceList_MarketDocument>

5	D18 Charge Information	EZ	Tax	Accepted
6	D08 Charge Prices	EZ	Tax	Accepted
7	D18 Charge Information	EZ	NotTax	Accepted
8	D08 Charge Prices	EZ	NotTax	Accepted

AC2 :heavy_check_mark:


@conda-forge-admin,please add bot automerge

Additional comment:
No response

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I added bot automerge in conda-forge/hart-protocol-feedstock#3.


main,osbuildprogress: add --progress=text,debug support (COMPOSER-2394)

This adds a new progress flag that makes use of the
osbuild jsonseq progress information to show progress and
hide the low-level details from the user.
Here is what it looks like:
https://asciinema.org/a/cJpB6066UoDDzAylwHVHjEEIN
(c.f. COMPOSER-2394)

Moved back to draft as the "pb.Pool" idea does not work with podman as it does not give us a real pty

I moved this back to draft as the pb.Pool used does not actually work with "podman run" (the integration test found this). podman run does give us alog-driver=passthough" by default (and not passthrough-tty (to avoid TIOCSTI attacks)). So the sensible thing is probably to look into how we can build the progressbar without pb.Pool and without terminal raw mode (which is a bit of a challenge).


Line break between glossary and comma

This is caused by the block marginal interface that's contained inside the span. When it's visible, it breaks the algorithm that keeps commas next to words because it finds a block between them. The only way to fix this is to change how marginals are structured, which would change how they are edited. This one is going to stay open for a while...


Groups to assign administrator roles in Azure AD

Unfortunately the assertion "You can use groups to assign administrator roles in Azure AD" is false. For instance you can't assign the "Global Administrators" role to a Group in Azure AD.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 5e434b86-3ce5-0e90-1ad0-b7f35f4c88df
Version Independent ID: 66d94ffb-9140-4960-ccb2-54e54d1ece86
Content: Users, groups, licensing, and roles overview - Azure AD
Content Source: articles/active-directory/users-groups-roles/directory-overview-user-model.md
Service: active-directory
Sub-service: users-groups-roles
GitHub Login: @curtand
Microsoft Alias: curtand

@fabmas Thanks for your feedback! We will investigate and update as appropriate.

@fabmas thanks for letting us know about this, I'm currently putting this in the doc now please let us know if you have anymore concerns in regards to this, otherwise I will be closing this out end of day today.
The current Section

You can use groups in Azure AD to assign licenses to large numbers of users, or to assign user access to deployed enterprise apps. You can use groups to assign administrator roles in Azure AD, or you can grant access to resources that are external, such as SaaS applications or SharePoint sites.

Updated Section

You can use groups in Azure AD to assign licenses to large numbers of users, or to assign user access to deployed enterprise apps. You can use groups to assign all administrator roles except for Global Administrator in Azure AD, or you can grant access to resources that are external, such as SaaS applications or SharePoint sites.


ffmpeg issue on Mac

I'm getting the following error with the video: { log_file_path: STDERR}  option
Unknown input format: 'x11grab'
This page seems to suggest that avfoundation should be used instead on mac.
https://github.com/Homebrew/legacy-homebrew/issues/17641
Any ideas on how to fix this?

Same issue here using OSX.
I get this on the log file:
avconv version 12, Copyright (c) 2000-2016 the Libav developers
  built on Mar  6 2017 22:35:59 with Apple LLVM version 8.0.0 (clang-8<IP_ADDRESS>)
Unknown input format: 'x11grab'

Hi @leonid-shevtsov, thanks for your work on this tool. Trying to use it to record some RSpec/Capybara tests running on PhantomJS/Selenium, but having the same problem. I can actually reproduce it with the test suite — running rspec spec/integration_spec.rb:19 fails with no specific error message besides the assertion, but if you add a log_file_path and tail it you see the error message. This happens with both avconv and ffmpeg, with latest and older versions of both (going back to libav 9.10 and ffmpeg 2.7.2, which based on their CHANGELOGs still support x11grab, but clearly don't?).
I've noticed that the Travis CI build configured for this repo is still passing. That runs on Linux and I see how it runs sudo apt-get install -y libav-tools, but I'm unclear reading the printout on what actual versions are installed. I wonder if you could throw some light here? I'm also confused because these versions are kind of old, so presumably this hasn't been working for a while? Or I'm missing something, which is quite possible given that I know nothing about ffmpeg or  avconv.

I attempted to use this and specified the path to ffmpeg but headless still complains it can't be found yet i can run ffmpeg from commandline
#<Headless:0x00007ff76052e6d0 @display=99, @xvfb_launch_timeout=10, @autopick_display=true, @reuse_display=true, @dimensions="1280x1024x24", @video_capture_options={:provider_binary_path=>"/usr/local/bin/ffmpeg"}, @destroy_at_exit=true, @pid=18221, @old_display="/private/tmp/com.apple.launchd.7tpGUVqPN2/org.macosforge.xquartz:0", @at_exit_hook_installed=true>
(byebug) continue
Error Message: /usr/local/bin/ffmpeg not found on your system. Install it or change video recorder provider
Stacktrace:

> 698 | headless.video.start_capture

@leonid-shevtsov any ideas? I'm getting the same issue and not sure of how to go about getting headless to work on OSX.


Add "errorCallback" for Ajax requests, and disable buttons to stop double-clicks

Describe the Change
Add a new errorCallback for sendAjaxReq for custom logic after an error is triggered. Also add support for disabling buttons which trigger sendAjaxReq to prevent double clicks.

Also spotted that the docs still referenced Out-PodeWebValidation!


Support of Kotlin 1.4-M1

Hello, did you planned Kotlin 1.4-M1?

I'll wait to M2. Related issue: https://github.com/korlibs/klock/issues/101
I would want to use the both mode that has some flaws on M1 yet: https://blog.jetbrains.com/kotlin/2020/03/kotlin-1-4-m1-released/#both-mode

1.12.0 released against Kotlin 1.4


fix: formatting error

This PR should fix this format problem:

Confirmed that make html in the docs/ directory cleans up the rendered sphinx docs:


ESLint extension missing 'javascript' tag

https://github.com/Microsoft/vscode-docs/issues/1420 noted that ESLint is not displayed in the query of popular JavaScript extensions on the languages/javascript topic.
The Marketplace query is simply searching for "javascript".
Adding a 'javascript' tag to package.json should help users find this JavaScript extension.

@gregvanl where do I add this tag. All I have is a "categories" field?

Looking at the tagging source code in vsce, I think the easiest way is to add "JavaScript" to the extension description.
How about changing the description to: "Integrates the ESLint JavaScript Linter into VS Code"?
You can also add a keyword to package.json but having a better description is probably a good thing.

Changed the description as recommended.


Errors when running tests

On a fresh clone of the repo some of the integration tests in test_accounts.py and test_teams.py raise
socket.gaierror: [Errno -3] Temporary failure in name resolution

Been poking at it for a while and can't quite figure out what is going on

@tonespi thanks for reporting this.  I'm still fleshing out the tests a bit, so I'm not surprised on this.  I'll try to reproduce and fix this over the weekend.

@tonespi take a look at the updated team tests and let me know if that works for you.

I believe this should be resolved in the latest push.  Feel free to reply here if you continue to have issues.

Unfortunately the tests still fail.
I have two small commits fixing some build issues and a fix for patching redis in the integration tests.
They unfortunately don't fix this issue but they do allow a clean build from scratch.


Can't bind to 'ngModel' since it isn't a known property of 'input'. ("

Augury: 1.19.0
Date: Wed, 06 Jun 2018 20:28:12 GMT
OS: Win32
Demo test application:
-- Git repository for demo app showing the issue (optional but very helpful for difficult issues).
-- If a code snippet will completely show the issue, please include it.
Description of issue:
-- Include (clipped) screenshot images if possible.
Angular version (required): ???
Steps to reproduce:

Additional details:

Hey, thanks for the bug report.
Can you tell us what action triggered this error?

Closing due to insufficient information


Log streams for apps not working in 0.30.1

The 0.30.1 update fixed https://github.com/pivotal-cf/pcfdev/issues/365 but there still seems to be some sort of issue with apps log streaming. Commands like cf push or cf logs never display any log output from the app.
Some more details here: https://github.com/pivotal-cf/pcfdev/issues/365#issuecomment-468360804

@kdvolder Appreciate you raising an issue about this and keeping us honest. You're definitely correct that there is a bug in that last release and getting it resolved is a high priority. Expect the fix to come very, very soon.

We've made another patch release for this issue v0.30.2 for PCF1.11.0, which can be retrieved here: https://network.pivotal.io/products/pcfdev#/releases/314093. Please give it a go and do not hesitate to let us know if there are any problems.
We completely apologize as we cannot guarantee the same level of quality in our deprecated offering as we can in the new CF Dev

We completely apologize as we cannot guarantee the same level of quality in our deprecated offering as we can in the new CF Dev

FWIW: I think you are doing a great Job :-) Very grateful for all the feedback and these quick patches. I'll try this out shortly.


Update composer dependences, remove dead code, make minor App Engine fixes

@cpatrick @mgrauer PTAL.

Assuming Travis is happy, lgtm.


upgraded to spyder 4.0 - launching the command prompt errors and slow performance

Issue Report Checklist

[x] Searched the issues page for similar reports
[x] Read the relevant sections of the Spyder Troubleshooting Guide and followed its advice
[x] Reproduced the issue after updating with conda update spyder (or pip, if not using Anaconda)
[x] Could not reproduce inside jupyter qtconsole (if console-related)
[x] Tried basic troubleshooting (if a bug/error)

[x] Restarted Spyder
[ ] Reset preferences with spyder --reset
[ ] Reinstalled the latest version of Anaconda
[ ] Tried the other applicable steps from the Troubleshooting Guide

[x] Completed the Problem Description, Steps to Reproduce and Version sections below

launching the command prompt error:
File "", line 3, in  ImportError: No module named conda
What steps reproduce the problem?
upgrading to spyder 4.0

What is the expected output? What do you see instead?
Paste Traceback/Error Below (if applicable)

File "<stdin>", line 3, in <module> ImportError: No module named conda

Versions

Spyder version: 4.0
Python version: 3.7.5
Qt version: 5.9.6
PyQt version: 5.9.2
Operating System name/version: Pop OS - Ubuntu - 19.10

Dependencies

PASTE DEPENDENCIES HERE
cloudpickle >=0.5.0          :  1.2.2 (OK)
pygments >=2.0               :  2.5.2 (OK)
qtconsole >=4.6.0            :  4.6.0 (OK)
nbconvert >=4.0              :  5.6.1 (OK)
sphinx >=0.6.6               :  2.2.2 (OK)
pylint >=0.25                :  2.4.4 (OK)
psutil >=0.3                 :  5.6.7 (OK)
qtawesome >=0.5.7            :  0.6.0 (OK)
qtpy >=1.5.0                 :  1.9.0 (OK)
pickleshare >=0.4            :  0.7.5 (OK)
zmq >=17                     :  18.1.0 (OK)
chardet >=2.0.0              :  3.0.4 (OK)
numpydoc >=0.6.0             :  0.9.1 (OK)
spyder_kernels >=1.8.1;<2.0.0:  1.8.1 (OK)
qdarkstyle >=2.7             :  2.7 (OK)
atomicwrites >=1.2.0         :  1.3.0 (OK)
diff_match_patch >=20181111  :  20181111 (OK)
intervaltree                 :  None (OK)
watchdog                     :  None (OK)
keyring                      :  None (OK)
pexpect >=4.4.0              :  4.7.0 (OK)
pympler                      :  None (OK)
sympy >=0.7.3                :  1.4 (OK)
cython >=0.21                :  0.29.14 (OK)
IPython >=4.0                :  7.10.1 (OK)
matplotlib >=2.0.0           :  3.1.0 (OK)
pandas >=0.13.1              :  0.25.3 (OK)
numpy >=1.7                  :  1.17.4 (OK)
scipy >=0.17.0               :  1.3.2 (OK)
pyls >=0.31.2;<0.32.0        :  0.31.2 (OK)
xdg >=0.26                   :  0.26 (OK)
rtree >=0.8.3                :  0.8.3 (OK)

The response time when using spyder is extremely slow as well.
Thank you

Please uninstall Anaconda, reinstall it and try again. It looks like your current installation is broken.

Closing due to lack of response.

Thank you and apologies for delay.


Add SVG support.

Is it possible to use SVG image with this lib? When i try to display an SVG image, it dosen't work.

That's not supported by SDWebImage or Glide.
You may want to look into just including svgs with your app directly if possible, or using a dedicated svg package for React Native.

Hi, I am having the same problem. This component is awesome but I am having issues loading SVG images. Can you please try to integrate https://github.com/brentvatne/react-native-svgkit

Turning this into a feature request. It would be nice to have.

Shouldn't this be open since we still don't have any updates regarding having svg files into react-native-fast-image?

Have support now?

svgs still don't work

svg still does not Work?

Why this issue is closed if this library does not support SVG images?

Request to reopen this. This is a feature request. At least the documentation should say prominently that svg does not work.

Please add SVG support; it would be great to have this feature!


Fix repeated command line options handling in distutils.FancyGetopt

Documentation and comments in the code suggest that it should be possible to specify command line options that can be repeated. However, trying to use this facility for options that take arguments results in only the last specified argument to be retained. It works as expected for boolean options. Probably this bug went so far unnoticed because this functionality is used in setuptools or distutils only for the --verbose option which does not take arguments.
Fixes #2482

Thanks for the contrib. Unfortunately, everything under the _distutils name needs to be contributed to pypa/distutils. Also, I'll probably resist accepting non-critical fixes until setuptools is generally using distutils by default, an effort which is blocked on some complicated ecosystem challenges.

Thank you. I didn't see that repo. I thought the distutils standard library module was merged into setuptools. Should I open a ticket and a pull request there or is distutils development effectively halted as you imply?

I don't have a hard and fast rule. I suggest go ahead and submit this PR to that repo. If I don't accept it, I'll probably just leave it to linger until distutils adoption has moved forward.

I don't have a hard and fast rule. I suggest go ahead and submit this PR to that repo. If I don't accept it, I'll probably just leave it to linger until distutils adoption has moved forward.


Remove licensing from Response Caching Middleware sample

Remove licensing from Response Caching Middleware sample

Hi @GuardRex, I'm your friendly neighborhood .NET Foundation Pull Request Bot (You can call me DNFBOT). Thanks for your contribution!
You've already signed the contribution license agreement. Thanks!
The agreement was validated by .NET Foundation and real humans are currently evaluating your PR.
TTYL, DNFBOT;


fix(package): upgrade jsdom to 11.12.0

This is the last version to support the "old API".

It's only used by the test suite, so it should be fine. I tested all version up to this point.


'tf.random_normal' broken on Ubuntu 16.04

'tf.random_normal' broken on Ubuntu 16.04/NVIDIA

runs ok, but puts zeros for everything

Would be important to learn whether NVidia or Ubuntu are to blame, because NVidia have been accused of deliberately leaving their OpenCL drivers in a buggy/bad/slow state.
I ought to have a new AMD GPU later today, will try to test this out.
It would be interesting to consider a "software" fallback, though; e.g. an OpenCL kernel that, seeded by system entropy from /dev/urandom, could generated ~CSPRNG output without relying on hardware entropy sources on the card. I wouldn't use it for crypto, but it would be fine for seeding random distributions? Some key-streams are very minimal and might be easy to implement, although most generate random ints, rather than floats. I'm not sure how irritating it is to type-cast from within OpenCL kernels.

By default, if we choose not to register a GPU kernel, it will use a CPU kernel in its place.
I'd be very interested to know if this is Ubutnu specific or NVIDIA specific.  This is key information for deciding the future of this issue.

Just booted into my AMDGPU-pro driver environment for the AMD R9 390, Ubuntu 16.04, Intel i5, and ran tests:
cathal@thinkum:~/tf-coriander$ py.test
================================================================= test session starts =================================================================
platform linux -- Python 3.5.2, pytest-3.1.0, py-1.4.33, pluggy-0.4.0
rootdir: /home/cathal/tf-coriander, inifile: pytest.ini
plugins: pep8-1.0.6
collected 99 items

tensorflow/stream_executor/cl/test/conftest.py .
tensorflow/stream_executor/cl/test/measure_binary_ops_perf.py .
tensorflow/stream_executor/cl/test/measure_reduction_ops_perf_bybatchsize.py .
tensorflow/stream_executor/cl/test/measure_reductions_perf.py .
tensorflow/stream_executor/cl/test/measure_unary_ops_perf.py .
tensorflow/stream_executor/cl/test/measure_unary_ops_perf_bybatchsize.py .
tensorflow/stream_executor/cl/test/run_unary_op.py .
tensorflow/stream_executor/cl/test/test_binary_ops.py .xx................
tensorflow/stream_executor/cl/test/test_blas.py ..
tensorflow/stream_executor/cl/test/test_common.py .
tensorflow/stream_executor/cl/test/test_gradients.py ..
tensorflow/stream_executor/cl/test/test_loss.py ..
tensorflow/stream_executor/cl/test/test_misc.py .........s
tensorflow/stream_executor/cl/test/test_nn.py ..
tensorflow/stream_executor/cl/test/test_random.py .FF..
tensorflow/stream_executor/cl/test/test_reductions.py ...........................
tensorflow/stream_executor/cl/test/test_simple.py ..
tensorflow/stream_executor/cl/test/test_softmax.py ....
tensorflow/stream_executor/cl/test/test_unary_ops.py ................

------------------------------------- generated xml file: /home/cathal/tf-coriander/test/junit-pytest-report.xml --------------------------------------
=============================================================== short test summary info ===============================================================
FAIL tensorflow/stream_executor/cl/test/test_random.py::test_random_normal[shape0]
FAIL tensorflow/stream_executor/cl/test/test_random.py::test_random_normal[shape1]
SKIP [1] tensorflow/stream_executor/cl/test/test_misc.py:158: Need to fix passing float** to kernel for this to work
XFAIL tensorflow/stream_executor/cl/test/test_binary_ops.py::test[uint8-div-a / b]
XFAIL tensorflow/stream_executor/cl/test/test_binary_ops.py::test[uint8-mul-a * b]
====================================================================== FAILURES =======================================================================
_____________________________________________________________ test_random_normal[shape0] ______________________________________________________________

shape = (3, 4)

    @pytest.mark.parametrize(
        'shape',
        shapes)
    def test_random_normal(shape):
        with tf.Graph().as_default():
            with tf.device('/gpu:0'):
                W_t = tf.Variable(tf.random_normal(shape))
                mu_t = tf.reduce_mean(W_t)
                var_t = tf.reduce_mean(W_t * W_t)

                with tf.Session(config=tf.ConfigProto(log_device_placement=False)) as sess:
                    sess.run(tf.initialize_all_variables())
                    W, mu, var = sess.run((W_t, mu_t, var_t))
                if np.prod(W.shape) < 20:
                    print('W', W)
                else:
                    print('W.reshape(-1)[:20]', W.reshape(-1)[:20])
                print('mu', mu, 'var', var)
                assert abs(mu) < 1.0
>               assert var > 0.05
E               assert 0.0 > 0.05

tensorflow/stream_executor/cl/test/test_random.py:34: AssertionError
---------------------------------------------------------------- Captured stdout call -----------------------------------------------------------------
W [[ 0.  0.  0.  0.]
 [ 0.  0.  0.  0.]
 [ 0.  0.  0.  0.]]
mu 0.0 var 0.0
---------------------------------------------------------------- Captured stderr call -----------------------------------------------------------------
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1083] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Hawaii, pci bus id: 0000.0000)
_____________________________________________________________ test_random_normal[shape1] ______________________________________________________________

shape = (50, 70, 12)

    @pytest.mark.parametrize(
        'shape',
        shapes)
    def test_random_normal(shape):
        with tf.Graph().as_default():
            with tf.device('/gpu:0'):
                W_t = tf.Variable(tf.random_normal(shape))
                mu_t = tf.reduce_mean(W_t)
                var_t = tf.reduce_mean(W_t * W_t)

                with tf.Session(config=tf.ConfigProto(log_device_placement=False)) as sess:
                    sess.run(tf.initialize_all_variables())
                    W, mu, var = sess.run((W_t, mu_t, var_t))
                if np.prod(W.shape) < 20:
                    print('W', W)
                else:
                    print('W.reshape(-1)[:20]', W.reshape(-1)[:20])
                print('mu', mu, 'var', var)
                assert abs(mu) < 1.0
>               assert var > 0.05
E               assert 0.0 > 0.05

tensorflow/stream_executor/cl/test/test_random.py:34: AssertionError
---------------------------------------------------------------- Captured stdout call -----------------------------------------------------------------
W.reshape(-1)[:20] [ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.
  0.  0.]
mu 0.0 var 0.0
---------------------------------------------------------------- Captured stderr call -----------------------------------------------------------------
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1083] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Hawaii, pci bus id: 0000.0000)
============================================== 2 failed, 94 passed, 1 skipped, 2 xfailed in 5.64 seconds ==============================================
Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: Hawaii, pci bus id: 0000.0000
c: /job:localhost/replica:0/task:0/gpu:0
b: /job:localhost/replica:0/task:0/gpu:0
a: /job:localhost/replica:0/task:0/gpu:0
Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: Hawaii, pci bus id: 0000.0000
c: /job:localhost/replica:0/task:0/gpu:0
b: /job:localhost/replica:0/task:0/gpu:0
a: /job:localhost/replica:0/task:0/gpu:0

Consider this the same output for #13 and #34 also; no segfaults when I manually ran the MNIST example, and the tests didn't all segfault either. :)
So aside from the RNG, things are looking very good for the most recent release! How much is the RNG relied-upon for the other tests, though? If the RNG is always returning 0, then how do the other tests pass? Is it simply not used for seeding the weights of networks, generally?

PS, I'll shortly be wiping and switching to the ROCm driver on a different card, so I don't know if I can continue providing useful test output for the AMDGPU-pro driver + R9 390, at least for a while (until I can afford another MoBo to plug it in! :) ).

Well, the nets will be poorly initialized, but they will still learn, slowly
On 30 May 2017 10:26:20 BST, Cathal Garvey<EMAIL_ADDRESS>wrote:

Just booted into my AMDGPU-pro driver environment for the AMD R9 390,
Ubuntu 16.04, Intel i5, and ran tests:
cathal@thinkum:~/tf-coriander$ py.test
================================================================= test
session starts
=================================================================
platform linux -- Python 3.5.2, pytest-3.1.0, py-1.4.33, pluggy-0.4.0
rootdir: /home/cathal/tf-coriander, inifile: pytest.ini
plugins: pep8-1.0.6
collected 99 items

tensorflow/stream_executor/cl/test/conftest.py .
tensorflow/stream_executor/cl/test/measure_binary_ops_perf.py .
tensorflow/stream_executor/cl/test/measure_reduction_ops_perf_bybatchsize.py
.
tensorflow/stream_executor/cl/test/measure_reductions_perf.py .
tensorflow/stream_executor/cl/test/measure_unary_ops_perf.py .
tensorflow/stream_executor/cl/test/measure_unary_ops_perf_bybatchsize.py
.
tensorflow/stream_executor/cl/test/run_unary_op.py .
tensorflow/stream_executor/cl/test/test_binary_ops.py
.xx................
tensorflow/stream_executor/cl/test/test_blas.py ..
tensorflow/stream_executor/cl/test/test_common.py .
tensorflow/stream_executor/cl/test/test_gradients.py ..
tensorflow/stream_executor/cl/test/test_loss.py ..
tensorflow/stream_executor/cl/test/test_misc.py .........s
tensorflow/stream_executor/cl/test/test_nn.py ..
tensorflow/stream_executor/cl/test/test_random.py .FF..
tensorflow/stream_executor/cl/test/test_reductions.py
...........................
tensorflow/stream_executor/cl/test/test_simple.py ..
tensorflow/stream_executor/cl/test/test_softmax.py ....
tensorflow/stream_executor/cl/test/test_unary_ops.py ................

------------------------------------- generated xml file:
/home/cathal/tf-coriander/test/junit-pytest-report.xml
--------------------------------------
=============================================================== short
test summary info
===============================================================
FAIL
tensorflow/stream_executor/cl/test/test_random.py::test_random_normal[shape0]
FAIL
tensorflow/stream_executor/cl/test/test_random.py::test_random_normal[shape1]
SKIP [1] tensorflow/stream_executor/cl/test/test_misc.py:158: Need to
fix passing float** to kernel for this to work
XFAIL
tensorflow/stream_executor/cl/test/test_binary_ops.py::test[uint8-div-a
/ b]
XFAIL
tensorflow/stream_executor/cl/test/test_binary_ops.py::test[uint8-mul-a
* b]
======================================================================
FAILURES
=======================================================================
_____________________________________________________________
test_random_normal[shape0]
______________________________________________________________

shape = (3, 4)

   @pytest.mark.parametrize(
       'shape',
       shapes)
   def test_random_normal(shape):
       with tf.Graph().as_default():
           with tf.device('/gpu:0'):
               W_t = tf.Variable(tf.random_normal(shape))
               mu_t = tf.reduce_mean(W_t)
               var_t = tf.reduce_mean(W_t * W_t)

with tf.Session(config=tf.ConfigProto(log_device_placement=False)) as
sess:
                   sess.run(tf.initialize_all_variables())
                   W, mu, var = sess.run((W_t, mu_t, var_t))
               if np.prod(W.shape) < 20:
                   print('W', W)
               else:
                   print('W.reshape(-1)[:20]', W.reshape(-1)[:20])
               print('mu', mu, 'var', var)
               assert abs(mu) < 1.0
>               assert var > 0.05
E               assert 0.0 > 0.05

tensorflow/stream_executor/cl/test/test_random.py:34: AssertionError
----------------------------------------------------------------
Captured stdout call
-----------------------------------------------------------------
W [[ 0.  0.  0.  0.]
[ 0.  0.  0.  0.]
[ 0.  0.  0.  0.]]
mu 0.0 var 0.0
----------------------------------------------------------------
Captured stderr call
-----------------------------------------------------------------
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1083] Creating
TensorFlow device (/gpu:0) -> (device: 0, name: Hawaii, pci bus id:
0000.0000)
_____________________________________________________________
test_random_normal[shape1]
______________________________________________________________

shape = (50, 70, 12)

   @pytest.mark.parametrize(
       'shape',
       shapes)
   def test_random_normal(shape):
       with tf.Graph().as_default():
           with tf.device('/gpu:0'):
               W_t = tf.Variable(tf.random_normal(shape))
               mu_t = tf.reduce_mean(W_t)
               var_t = tf.reduce_mean(W_t * W_t)

with tf.Session(config=tf.ConfigProto(log_device_placement=False)) as
sess:
                   sess.run(tf.initialize_all_variables())
                   W, mu, var = sess.run((W_t, mu_t, var_t))
               if np.prod(W.shape) < 20:
                   print('W', W)
               else:
                   print('W.reshape(-1)[:20]', W.reshape(-1)[:20])
               print('mu', mu, 'var', var)
               assert abs(mu) < 1.0
>               assert var > 0.05
E               assert 0.0 > 0.05

tensorflow/stream_executor/cl/test/test_random.py:34: AssertionError
----------------------------------------------------------------
Captured stdout call
-----------------------------------------------------------------
W.reshape(-1)[:20] [ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.
0.  0.  0.  0.  0.
 0.  0.]
mu 0.0 var 0.0
----------------------------------------------------------------
Captured stderr call
-----------------------------------------------------------------
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1083] Creating
TensorFlow device (/gpu:0) -> (device: 0, name: Hawaii, pci bus id:
0000.0000)
============================================== 2 failed, 94 passed, 1
skipped, 2 xfailed in 5.64 seconds
==============================================
Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: Hawaii, pci
bus id: 0000.0000
c: /job:localhost/replica:0/task:0/gpu:0
b: /job:localhost/replica:0/task:0/gpu:0
a: /job:localhost/replica:0/task:0/gpu:0
Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: Hawaii, pci
bus id: 0000.0000
c: /job:localhost/replica:0/task:0/gpu:0
b: /job:localhost/replica:0/task:0/gpu:0
a: /job:localhost/replica:0/task:0/gpu:0

Consider this the same output for #13 and #34 also; no segfaults when I
manually ran the MNIST example, and the tests didn't all segfault
either. :)
So aside from the RNG, things are looking very good for the most recent
release! How much is the RNG relied-upon for the other tests, though?
If the RNG is always returning 0, then how do the other tests pass? Is
it simply not used for seeding the weights of networks, generally?
--
You are receiving this because you authored the thread.
Reply to this email directly or view it on GitHub:
https://github.com/hughperkins/tf-coriander/issues/35#issuecomment-304823492

--
Sent from my Android device with K-9 Mail. Please excuse my brevity.

Created simple cpu-side, easy-to-run, easy-to-introspect philoxrandom script at https://github.com/hughperkins/pub-prototyping/blob/master/cpp/testphilox.cpp , which calls into a copied/modified version of the tensorflow PhiloxRandom generator at https://github.com/hughperkins/pub-prototyping/blob/master/cpp/from_tf/philox_random.h
This then gives the same outputs as calling tf.random_uniform, with seed 123:
tensroflow output:
W_cpu [[ 0.04080963  0.20842123  0.09180295  0.70220065]
 [ 0.7073133   0.39646494  0.06650937  0.29188633]
 [ 0.02963269  0.95492315  0.00610673  0.3169049 ]]

test script output:
0:<PHONE_NUMBER> 0.0408096
1:<PHONE_NUMBER> 0.208421
2:<PHONE_NUMBER> 0.091803
3: 257548726 0.702201
4: 727353662 0.707313
5:<PHONE_NUMBER> 0.396465
6:<PHONE_NUMBER> 0.0665094
7:<PHONE_NUMBER> 0.291886
8:<PHONE_NUMBER> 0.0296327
9:<PHONE_NUMBER> 0.954923
10:<PHONE_NUMBER> 0.00610673
11:<PHONE_NUMBER> 0.316905

I'm then going to work my way through the opencl kernel, comparing the values in the kernel, with those on the cpu, and finding where they start to differ. I'm going to use COCL_DUMP_CL, COCL_LOAD_CL, and COCL_DUMP_CONFIG to inject values I'm interested in, into an output buffer, and inspect them.  https://github.com/hughperkins/coriander/blob/master/doc/advanced_usage.md#runtime-options

Sounds really promising! Can't wait to see this one fixed, I have a feeling a lot of the test cases are "passing", but aren't really behaving as intended, because of poor initialisation. In the meantime I was planning to just monkey-patch this with the numpy-derived random hack, above, and see how that improves things. :P

The test cases dont need initialization: they test specific operations.  Please check them, and let me know any test cases you feel are weak, and how we can improve them.

I mean, when you do py.test -v, those test specific operations.  The end-to-end tests are the scripts we are using from Aymeric Damien's Tensorflow-Examples.

But yeah, monkey-patching will work, as long as you dont use AdamOptimizer, which initializes itself from tf.random. It'll initialize itself really poorly currenlty, and learning will suck. If you use SGD optimizer, it should work ok-ish.

Sorry, I meant the Tensorflow-Examples repo, yes. :) When I was running those previously I noticed that some of the examples weren't learning at any appreciable rate, which was probably down to the randn initialisation being poor. Or worse, if things were being set to 0, then perhaps a lot of neurons were simply dead. I'm running it all again after monkey-patching Numpy's randn in, and they seem to be learning again.
Good to know about Adam! Possibly the monkey-patch would have to be applied further up the chain to work on Adam, then.. This is all running in a virtualenv, so I don't mind doing radical surgery on the Random lib if it lets me use TF. :P

...I'm perusing the code for AdamOptimizer, but I don't actually see any calls to tf.random in it or its superclass. Is this instead happening somewhere else, like in tf.initialize_all_valirables?

Hmmm, just noticed my earlier reply failed to send:

Sorry, I meant the Tensorflow-Examples repo, yes. :) When I was running those previously I noticed that some of the examples weren't learning at any appreciable rate, which was probably down to the randn initialisation being poor

Yes thats true. You are right.

Possibly the monkey-patch would have to be applied further up the chain to work on Adam, then.

Possibly, but sounds a lot of work.
And thence onto new reply :-)

...I'm perusing the code for AdamOptimizer, but I don't actually see any calls to tf.random in it or its superclass. Is this instead happening somewhere else, like in tf.initialize_all_valirables?

So, what I would do would probably be in first instance to view the graph on the tensorboard. tensorboard rocks :-) .  https://www.tensorflow.org/get_started/graph_viz

Great advice, thanks!

Update: tf.random_uniform enhanced tests works on Mac now :-) . Means, tf.random_uniform gives same results as cpu now, not like before. Fixed in https://github.com/hughperkins/tf-coriander/commit/4c1c54473926b3f8a9365bbbcd653041bb1108e2 , but specifically in https://github.com/hughperkins/coriander/commit/6452be7c5b7b426d88b3fb4c9e7f1d679b5ced6d
I'm hoping that the experience in PhiloxRandom for Mac will help me to fix the Ubuntu version.

(well... that's odd... the opencl generated on Mac is different than on Ubuntu. Thats quite unexpected ... since the opencl generation is my own code, therefore invariant, and it's based on the compilation using llvm-4.0, which is also invariant. Oh .... different standard libraries. Maybe for that)
Mac sample:
struct class_tensorflow__random__Array {
    int f0[4];
};
struct class_tensorflow__random__Array_0 {
    int f0[2];
};
struct class_tensorflow__random__NormalDistribution {
    char f0;
};
struct class_tensorflow__random__PhiloxRandom {
    struct class_tensorflow__random__Array f0;
    struct class_tensorflow__random__Array_0 f1;
};

Ubuntu sample:
struct class_tensorflow__random__Array {
    int f0[4];
};
struct class_tensorflow__random__Array_0 {
    int f0[2];
};
struct class_tensorflow__random__NormalDistribution {
    char f0;
};
struct class_tensorflow__random__Array_1 {
    float f0[4];
};
struct class_tensorflow__random__PhiloxRandom {
    struct class_tensorflow__random__Array f0;
    struct class_tensorflow__random__Array_0 f1;
};

An entire extra struct. Exact same kernel being compiled...
Oh, I just found out (as I'm writing this) why random_normal is broken I reckon. There is a shim for sincosf,but the mangled names are different, so on Mac it is correctly shimmed, but not on Ubuntu. That should be easy to fix...
End of OpenCL on Mac:
        /* int v119 = phi v304 */
        v119 = v304;
        goto v3;
    } else {
        goto v10;
    }
v10:;
    goto v11;
v11:;
    return;
}

End of OpenCL on Ubuntu:
        goto v3;
    } else {
        goto v10;
    }
v10:;
    goto v11;
v11:;
    return;
}
void _Z7sincosffPfS_(float v1, float* v2, float* v3, local int *scratch) {

}

That sincos bit has a different mangled name than on Mac, and wasnt detected, but it's easy to tell Coriander the Ubuntu name, and thus detect it.

Oh... I've found the difference... in Tensorflow, in the random distributions code, they have the following:
#if defined(__linux__)
  sincosf(v1, f0, f1);
#else
  *f0 = sinf(v1);
  *f1 = cosf(v1);
#endif

Different code, depending on linux or not :-O

Urgh, so this is an upstream issue, it assumes that Linux's version of available libs (CUDA?) have an extra function defined? Is that something fixable within the coriander framework, just by delegating to sin/cos?

It's easy to fix, in Coriander, by writing an appropriate shim.  There are some shims already https://github.com/hughperkins/coriander/blob/master/src/shims.cpp
Well...  easy - ish, since it will be the first shim that needs to handle pointers, and pointers in opencl need address spaces statically declared. That means, I'll need a shim for every combination of address spaces used by the code. ie, in opencl:
float angle = 0.1f;
global float *globala;
global float *globalb;
float *a;
float *b;

sincos(angle, a, b); // both are private
sincos(angle, globala, globalb); // both are global
sincos(angle, a, globalb); // one private, one global...

local float localb[30];
sincos(angle, a, loclalb); // one private, a shared...

Since OpenCL 1.2 is C99, you can only use the name sincos once, for one pair of address spaces, so there'll need to be a unique function name, for every pair of address spaces used, like eg sincos_p_p, sincos_g_g, ...  So I'll need to write code to handle that.  It's ok, I have various ideas on how to handle this, not a challenging issue, but might take a few man-hours or so.

Fixed in https://github.com/hughperkins/tf-coriander/commit/7d2deb9869194b046d82834d77d1d358dd674532 :-) . Turned out didnt need any shims, or address space stuff. Yay :-)

This is great! So, aside from Splitting, this is almost fully-functioning Tensorflow on CL now? :o Congratulations!

split and conv. but yeah :-) Thanks! :-)

(well, "fully-functioning". more like "has enough functionality to run some basic conv nets".  It'd still be nice to have eg batchnormalization, and some other things, ideally.
)

Question: what model(s) do you need to run in priority?  I cant do everything at once, so if I know which model(s) you are trageting in priority, I can look at those first.

Honestly, not sure at this stage. I'll probably be working mostly with text-based models, RNNs/LSTMs etcetera, for the moment. I'd love to start playing with convnets but I'm not at that yet. :)
So for me, even being able to correctly initialise nets is :balloon: :tada:

Cool :-)

created new v0.17.3 wheel. Dont suppose... do you mind double-checking that tf.random_normal is working ok for you now?  Also, maybe run all the unit tests too, ie py.test -v?

Already on it! :)

:-) . By the way, I'm not sure if the RPATH stuff is correct on ubuntu. If it still fails, it might be because it's using the libcocl.so in /usr/local/lib. So, if it doesnt work after installign the wheel:

let me know, and show the output
and then, after doing that, you might try just downloading the latest coriander, building and installing that, and see if that changes anything

Looking good for the py.test output. :)
I'm sorry to say I don't know what you're referring to re: "RPATH". Happy to help test, if you give me context and/or suggested shell commands to interrogate this.
Going to start running a few TensorFlow-Examples scripts now, also.
test_results.txt

I'm sorry to say I don't know what you're referring to re: "RPATH". Happy to help test, if you give me context and/or suggested shell commands to interrogate this.

As long as the py.test -v is passing, it's all good.  Good news that that is passing now :-)

So far, all examples I've tried from TensorFlow-Examples have worked perfectly, after I shim out the GPU specifying context managers. I'm training convolutional_network.py now and it's learing.. I don't know how well it's learning, but the loss generally is going down, and the accuracy is generally going up, so I'll mark that down as "success" for now. :)
Thanks again!

Cool! :-)


[AT-1210] document picture update

Description
JDBC Document pictures update
Related Issue
https://bitquill.atlassian.net/browse/AT-1210
Additional Reviewers
@affonsoBQ
@alexey-temnikov
@alinaliBQ
@andiem-bq
@birschick-bq
@mitchell-elholm
@RoyZhang2022

closing this PR as relating AWS PRs are posted and merged.


vscode fauxpilot

always install fauxpilot extension
enable/disable fauxpilot as the user wants
default: disabled

Thank's @amine-bs ! I think it would make more sense to handle the installation of fauxpilot directly in the Dockerfile as we do for other vscode extensions. @fcomte ?

yes we should not do that at runtime


[zh-cn]sync service.md kube-scheduler.md

[zh-cn]sync service.md kube-scheduler.md

Thanks for the prompt sync.
/lgtm
/approve


BUG: docs on asset is confusing

What browser are you using?
Chrome
Describe the bug
The docs on "asset - custom storage" displaying irreproducible code because of wrong snippet provided.
// ...
<StudioEditor
  options={{
    // ...
    assets: {
      storageType: 'self',

      // `onUpload` ...

      onLoad: async ({ editor }) => {
        // TODO: implement myDownloadFilesLogic to fetch urls and metadata for each asset file
        const results: FileMetadataAndUrl[] = await myDownloadFilesLogic({ files });

        // return an array with the loaded assets
        return results.map(({ file, url }) => ({
          id: url,
          src: url,
          name: file.name,
          mimeType: file.type,
          size: file.size
        }));
      },

      // `onDelete` ...

The function myDownloadFilesLogic is supposed to get { files } as input but the onLoad function only provide editor. Where can we get the files ?
How to reproduce the bug?
See docs: https://app.grapesjs.com/docs-sdk/configuration/assets
What is the expected behavior?
It should provide from where we can get the files
What is the current behavior?
It doesn't provide files
If is necessary to execute some code in order to reproduce the bug, paste it here below:

Code of Conduct

[X] I agree to follow this project's Code of Conduct

Thanks @jordiyapz you're right, the example is wrong there.
It should be more like:
const results = await myDownloadFilesLogic();

The myDownloadFilesLogic() should be all up to you how to fetch the list of assets for specific project that's why you don't have files there.
We'll update it 🙇♂


Ingest all of Opset 16

Closes #1201
ScatterElements adds a DefaultStrAttribute (therefor it doesn't need the introduction of a new versioned op)
RoiAlign adds a DefaultStrAttribute (which is defaulted to the old behaviour)
And finally GridSample ingestion was added. It still needs a shape inference implementation. I test was deleted that checked that the parsing of gridSample failed. It could be deleted because GridSample is now ingestible

@chentong319 Thanks for the review.
I've updated the PR with your suggestions. Please let me know if you would any other changes

@chentong319,
The following test in test/mlir/onnx/onnx_decompose.mlir already tests this rule
https://github.com/onnx/onnx-mlir/blob/35b424c84d12e9196da0ec9d3194e67e6a76c18e/test/mlir/onnx/onnx_decompose.mlir#L403-L414
I'm not exactly sure what another test for ScatterND would add in terms of coverage

Oh, I forgot that you just updated the rule, not add a new one.

Jenkins Linux ppc64le Build #6936 [push] Ingest all of Opset 16  ... started at 21:12

Jenkins Linux amd64 Build #7872 [push] Ingest all of Opset 16  ... started at 20:09

Jenkins Linux s390x Build #7889 [push] Ingest all of Opset 16  ... started at 21:09

Thanks for the review! Much appreciated

Jenkins Linux amd64 Build #7872 [push] Ingest all of Opset 16  ... passed after 1 hr 16 min

Jenkins Linux ppc64le Build #6936 [push] Ingest all of Opset 16  ... passed after 1 hr 42 min

Jenkins Linux s390x Build #7889 [push] Ingest all of Opset 16  ... passed after 1 hr 58 min


HAP-NodeJS it's not working on iOS 11.

I make the light to open automatically via HAP-NODEJS but HomeKit can't find device. I using same wifi to connect raspberry pi and my iPhone. I think I write everthings correct.

I changed uuid values of my services.
Now it working for me.


chore: use BlockHashAndNumber from SN_API

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Edge of sprite artifact

No idea why this is closed, i used the Msaa workaround from here:
https://github.com/bevyengine/bevy/issues/4748


Display 'distance' instead of 'ref' for highway milestones

Description
Please, display the distance value instead of ref to better identify highway milestones on the editor.

If you have more than one on screen, it's hard to distinguish which is which since all of them will display the same ref number if they all belong to the same highway route.

Moreover, displaying the distance can be an aid so that you don't get lost while mapping long stretches of road with few reference points.
Thank you.
Igor

Here’s where the label is getting populated with ref:
https://github.com/openstreetmap/iD/blob/6239cc0ccc8e056759d4f8cf683fd2c671dfcda6/modules/util/util.js#L200-L202
As you can see from the code immediately following it, there is an opportunity to vary the labeling based on the feature’s primary tags.

Can you assign this issue to me? I am confident that I will be able to solve it.


[WIP] Out of tree

As discussed on Slack with @prashanth26 and @AxiomSamarth
This is not properly tested. At this point, we just want to know that we are in the right direction, and what obvious mistakes we are making or things we are missing.
Note about commits: this was very messy to get the commits right. It now is down to 3 commits:

Copy over the sample
Run make rename
Add the Equinix Metal provider

/assign @prashanth26 @AxiomSamarth

I am sorry, I had actually begun to review it thoroughly and suddenly remembered that you wanted us to go through and let you know if you are in the right direction. So, you can ignore the comments.

Haha, no worries at all.

@prashanth26 @AxiomSamarth I think this can go through a proper first review. I am going to start trying to deploy devices with it, so I expect to find issues, but it can have a proper review to start.

I would also like to recommend using the status codes at errors (which are mostly missing) and consume github.com/gardener/machine-controller-manager/pkg/util/provider/machinecodes/codes/codes.go for the same.

I see the error codes in https://pkg.go.dev/github.com/gardener/machine-controller-manager/pkg/util/provider/machinecodes/codes#Code , but how do I use those? Those are uint32 and these functions all return error 🤷♂

Please import "github.com/gardener/machine-controller-manager/pkg/util/provider/machinecodes/status" and return the errors as status.Error(codes.Internal, err.Error())

@prashanth26 and @AxiomSamarth I think I covered all of the issues you raise. Kindly confirm, and I can get started properly putting this thing through its paces.

@prashanth26 and @AxiomSamarth I think I covered all of the issues you raise. Kindly confirm, and I can get started properly putting this thing through its paces.

@deitch Thank you so much. I will review it and provide my feedback comments if any by end of Monday :)

Sounds good. As your first draft were good, I will start testing.

I managed to run tests creating and deleting devices - both via Machine and via MachineDeployment - on Equinix Metal. I had to make some changes (already updated and pushed to this PR), so all works well now.
Going to try to create some sane unit tests (not quite so easy as unit tests shouldn't deploy real infrastructure), but other than that, fully ready for review.

I restructured it to use your SPI interface, so we can plug in alternate provider interfaces for tests, and am playing around a bit to figure out how your target testing structure works.

@deitch Greetings Avi,
Sorry for the delay. I went through the changes and the test framework. The changes look good to me. There is an extremely minor change needed as mentioned in the comment Otherwise, everything looks good to me. :)
cc: @prashanth26

I will finish adding those tests, run another round against live EM, and then comment here.

Tests for 3 of the 6 core functions in place. Almost there...

All 6 in place. Ready for review.

All 6 in place. Ready for review.

I went through the tests. Everything looks good to me. I also see a coverage of ~80% which is nice 👍 Thanks for the PR @deitch

Made all of the updates you recommended @AxiomSamarth .
I am going to do one more run of live-testing against Equinix Metal right away, and will comment here when done.

Live testing all looks good. Ready to go.


Fritz!Box SystemLogs >> DynDNS error

Fritz!Box trys to resolve dns name from service address.
dynDNS error: the specified domain name cannot be resolved despite a successful update
55 error messages at one day.

try to take the servers name instead of the ip address, readme.md adjusted


Make it possible to remove headers

Right now you can only add and overwrite headers using header / Key Value.
What if I want to remove a header? Can we add something that will remove header e.g. -header / Server so I can remove headers that are being sent by server or application?
Line in question would probably be: https://github.com/mholt/caddy/blob/master/middleware/headers/headers.go#L25
Function in question would probably be: http://golang.org/pkg/net/http/#Header.Del
I could do it myself but I have no experience in Go and would probably not write it very pretty.

I agree we need this feature. We can't change the directive name (well, we could allow "-header" but I'm not fond of changing the parser for that) - so what about something like header -Server or header Server -? (The first won't allow us to set header fields starting with - and the second won't allow us to set header fields with a value of -.) - do you have a preference either way?

I'll go with header -Server

header -{key} sounds perfect to me.

As another option, what about using ~Server? The ~ seems to be used to negate (bitwise operations).

Okey, I will implement this feature this evening. I already tested on local and it works for me. Just need to do some more tests and make a pull requests.

@stanislavromanov Thanks! That's looking good.
@cbess You're right, to us programmers, the ~ is a natural 'negation' operator. However, Caddy's audience is also for non-programmers. I'm still not sure this syntax is perfect, but it is concise, and I think a minus is a little more intuitive than a tilde.

@mholt Understood. I guess I see it as for dev it will have a double meaning and thereby (hopefully) easier to remember. For non-programmers, its still a single char, they won't know the difference. Either way great job with the server.

We can change - to ~ very easily. Just need to make up our minds, merge and then we can update documentation on the next release.

Awesome. :)