Version 2.1.0 for 1.16.5 does not work with java 17

log: https://paste.ee/p/02fUO

The error is the same as in #42, so it isn't an issue with Java 17 specifically. I'm not sure why these are popping up now, I've got a potential fix I'll probably release today.

nvm I'm an idiot, i forgot that it needs fabric api. It loads fine with that.
I was trying to isolate it to see if it was an incompatibility with one of my other mods, but I isolated it too much and it crashed for a different reason. It seems to be incompatible with RandomPatches
Log here

I remembered using the two mods together before, so I did some further testing: RandomPatches and FerriteCore are incompatible when using fabric api 0.42.0. Using fabric api 0.41.3 earlier, the two mods work together. Should I report this to the fabric api issues page?

Thanks for narrowing this down! I'm able to reproduce it with those mods, I'll do some debugging and then report it to whatever mod I decide is causing the issue (or fix it if it turns out to be FerriteCore).

https://github.com/TheRandomLabs/RandomPatches/issues/252


Q: What does 'view as admin' in the history panel mean?

This is still an old artifact, just removed it in the refered commit


[Feature] Complete Animations

More Info
Currently, completing a set and drawing cards cause the cards to "teleport", rather than be animated, along with the same operations being undone. These should be animated for a more complete experience.
Proposed Implementation

[x] Create CardAnimationLayer to be overlayed on top of GameView
[x] Give CardAnimationLayer the frames of each card stack as well as draws and completed sets
[x] In GameViewModel create variables for in-progress draw, and in-progress completed sets.
[x] In GameViewModel separate the draw and complete set operations into multiple steps:

[x] First, add the cards to the the in-progress variables and remove them from the GameState if necessary
[x] Second, in a separate function, remove the cards from the in-progress variables and back into the GameState, whether inserting cards into stacks, or adding a completed set.

[x] In CardAnimationLayer, based on the status of the in-progress variables in GameViewModel animate the movement. For example, if the completed set in-progress variable has cards, animate them moving the the completed set frame. Once the cards are removed from the in-progress variable, a completed set should be added to the GameState, taking their place, visually.
[ ] Do the same for undoing and operation

Fixed with #8


xgboost\core.py:1024: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working

xgboost\core.py:1024: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working

https://github.com/dmlc/xgboost/blob/19ee0a357964f4c0a7cef6c00da2e8478e360974/python-package/xgboost/core.py#L1024

@KOLANICH Addressed in  #3909. Thanks!


MatterServer node start optimizations

This PR optimized the start handling in MatterServer. it mainly makes siure that nodes get also started when added to the MatterServer after this one itself was initially started (and so started all previously added nodes). With this it behaves the same for a developer irrelevant when he adds a node

@GermanBluefox FYI ... as discussed today


Range requests don't allow starting from 1

A GET request on a file with Range: bytes=1- fails with a 500 error
2017/03/12 14:15:16 DEBUG : HTTP REQUEST (req 0xc420506900)
2017/03/12 14:15:16 DEBUG : GET /y3mb1k489ZlcjlWn1cOnS3hfMFFVj4oX4N7cLKbNwS7ZqXTSTDBa9gRYYb267j_u6YaKVs40wWBT2tC4t-IulHMaEp9V4Or-mNfXo9xPi29SHbQFRCYfo8hSShagZRlm2IHzkT9UYpazKRGsFBPfVbrfLLXnLLIbCE9u7qZU8dNJ4dKSaDaIAZsNAcklsZHfVXQR7v9WdQ4l3MZ0QPBzmaYvRpmkAMYlII0B0_OuhT_JU4/file1 HTTP/1.1
Host: public.dm2304.livefilestore.com
User-Agent: rclone/v1.35-DEV
Authorization: XXXX
Range: bytes=1-
Referer: https://api.onedrive.com/v1.0/drive/items/71A96798E7B1D253!21440/content

2017/03/12 14:15:17 DEBUG : HTTP RESPONSE (req 0xc420506900)
2017/03/12 14:15:17 DEBUG : HTTP/1.1 500 Internal Server Error
Accept-Ranges: bytes
Date: Sun, 12 Mar 2017 14:15:16 GMT
P3p: CP="BUS CUR CONo FIN IVDo ONL OUR PHY SAMo TELo"
Server: Microsoft-IIS/8.5
Strict-Transport-Security: max-age=31536000; includeSubDomains
X-Asmversion: UNKNOWN; <IP_ADDRESS>
X-Clienterrorcode: GeneralException
X-Msedge-Ref: Ref A: 28387AF187DC4B50A53ECAC5CBB2387B Ref B: LTSSCHEDGE0213 Ref C: Sun Mar 12 07:15:16 2017 PST
X-Msnserver: DM5SCH103162104
X-Qosstats: {"ApiId":0,"ResultType":4,"SourcePropertyId":0,"TargetPropertyId":42}
X-Throwsite: 05d6.85bd
Content-Length: 0

However a A GET request on a file with Range: bytes=2- works fine.
2017/03/12 14:16:25 DEBUG : HTTP REQUEST (req 0xc42029f500)
2017/03/12 14:16:25 DEBUG : GET /y3mCZZmPmP_NgjGqEd7Qt1BJs9HEySNyCXlMGo3b7tgGYc8b0eIIwWK9iM8qYebgiSKx5zpXhejLdSxIrsvrKiD7CLcz_gxUnzE9tpidB7L-sMC55mMgGi9ZdLXHppEqQM_o_A0TVbOZx0S8EwPAzd26qoRJbig_7VTsVXm0Ku-J8b3o5n1Z3BYbSFQ8duWxHbiRjy6oOeESypNzvu3lOQFVc2X4bBoSfH2g-aNP6h1olU/file1 HTTP/1.1
Host: public.dm2304.livefilestore.com
User-Agent: rclone/v1.35-DEV
Authorization: XXXX
Range: bytes=2-
Referer: https://api.onedrive.com/v1.0/drive/items/71A96798E7B1D253!21443/content

2017/03/12 14:16:25 DEBUG : HTTP RESPONSE (req 0xc42029f500)
2017/03/12 14:16:25 DEBUG : HTTP/1.1 206 Partial Content
Content-Length: 8
Accept-Ranges: bytes
Cache-Control: public
Content-Disposition: attachment; filename="file1"
Content-Location: https://public.dm2304.livefilestore.com/y3mR8A3st99FhOtN9ZoeegkZWKmUlD3lisfuf2zEFzotCEP-Dxw8ip0NyEj7aSChaEmwUpeY24EOeADOqT9hXdav-xU6KKDyvhO9ponhtd7y9f6cCePh8EdXSGIPy27FNLLbLRjD5ixYz0HraD3cNfqo_R2tm0Xak3BF1326Inl3RlV9JQNwfgWqKrRzw2LJYLBBqicmpER9kZ57Va-swnG9g
Content-Range: bytes 2-9/10
Content-Type: application/octet-stream
Ctag: aYzo3MUE5Njc5OEU3QjFEMjUzITIxNDQzLjI1Nw
Date: Sun, 12 Mar 2017 14:16:25 GMT
Etag: aNzFBOTY3OThFN0IxRDI1MyEyMTQ0My4x
Expires: Sat, 10 Jun 2017 14:16:25 GMT
Last-Modified: Sun, 12 Mar 2017 14:16:20 GMT
P3p: CP="BUS CUR CONo FIN IVDo ONL OUR PHY SAMo TELo"
Server: Microsoft-IIS/8.5
Strict-Transport-Security: max-age=31536000; includeSubDomains
X-Asmversion: UNKNOWN; <IP_ADDRESS>
X-Content-Type-Options: nosniff
X-Msedge-Ref: Ref A: 5433DD86A7104DA7A8E4A38E0B6D689B Ref B: LTSEDGE0120 Ref C: Sun Mar 12 07:16:25 2017 PST
X-Msnserver: DM5SCH103161906
X-Preauthinfo: rv;poba;
X-Sqldataorigin: S
X-Streamorigin: X

CDEFGHIJ

I can only assume this is a bug in OneDrive.
This was picked up by rclone's unit tests

This is definitely a bug. I believe that if you provide an actual end index you can use that as a work around, but we're fixing the issue as we speak.

This issue should now be resolved!

I can confirm that this fixes the issue - thank you very much :-)
-- Nick


Add support for CPE with or without versions

I also removed some duplicate code from the specs

Hey man, It was a great contribution. Thank you!


token_type_ids not getting padded while finetuning llama2

Environment

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.9 (main, Jan 11 2023, 15:21:40) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.4.0-144-generic-x86_64-with-glibc2.31
Is CUDA available: N/A
CUDA runtime version: 11.7.99
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration:
GPU 0: NVIDIA A100-SXM4-80GB
GPU 1: NVIDIA A100-SXM4-80GB
GPU 2: NVIDIA A100-SXM4-80GB
GPU 3: NVIDIA A100-SXM4-80GB
GPU 4: NVIDIA A100-SXM4-80GB
GPU 5: NVIDIA A100-SXM4-80GB
GPU 6: NVIDIA A100-SXM4-80GB
GPU 7: NVIDIA A100-SXM4-80GB

Nvidia driver version: 470.161.03

transformers: 4.30.2
llm-foundry: 0.2.0
mosaicml: 0.15.1
mosaicml-cli: 0.4.16
mosaicml-streaming: 0.5.1

To reproduce
Yaml config:
max_seq_len: 512
global_seed: 17

# Run Name
run_name: # If left blank, will be read from env var $RUN_NAME

# Model
model:
  name: hf_causal_lm
  pretrained_model_name_or_path: meta-llama/Llama-2-7b-hf
  init_device: cpu
  pretrained: true
  use_auth_token: true

# Tokenizer
tokenizer:
  name: meta-llama/Llama-2-7b-hf
  kwargs:
    model_max_length: ${max_seq_len}

# Local data to load into huggingface datasets
dataset: &hf_dataset
  hf_name: json
  hf_kwargs:
    data_dir: /raid/palash.kamble/LLM/finetune_json_data  # /raid/akshat.patidar/json_data
  preprocessing_fn:

# Dataloaders
train_loader: &train_loader
  name: finetuning
  dataset:
    <<: *hf_dataset
    split: train
    max_seq_len: ${max_seq_len}
    allow_pad_trimming: false
    decoder_only_format: true
    shuffle: true
    # # Use `python llmfoundry/data/packing.py --yaml-path /path/to/this/yaml/ ...`
    # # to profile this run's optimal packing_ratio as it depends on GPU count,
    # # batch size, sequence length
    # packing_ratio:
  drop_last: true
  num_workers: 8
  pin_memory: false
  prefetch_factor: 2
  persistent_workers: true
  timeout: 0

# eval_loader:
#   <<: *train_loader
#   dataset:
#     <<: *hf_dataset
#     split: validation

# Optimization
scheduler:
  name: linear_decay_with_warmup # linear no warmup is HF default which dolly used
  t_warmup: 0ba
  alpha_f: 0

optimizer:
  # mimic HF defaults to replicate dolly
  name: decoupled_adamw
  lr: 1.0e-5
  betas:
  - 0.9
  - 0.999
  eps: 1.0e-8
  weight_decay: 0

algorithms:
  gradient_clipping:
    clipping_type: norm
    clipping_threshold: 1.0

max_duration: 1ep
eval_interval: 1
eval_first: false
eval_subset_num_batches: -1
global_train_batch_size: 128

# System
seed: ${global_seed}
device_eval_batch_size: 4
device_train_microbatch_size: 4
# device_train_microbatch_size: auto
precision: amp_bf16

# FSDP
fsdp_config:
  sharding_strategy: FULL_SHARD
  mixed_precision: PURE
  activation_checkpointing: false
  activation_checkpointing_reentrant: false
  activation_cpu_offload: false
  limit_all_gathers: true
  verbose: false

# Logging
progress_bar: false
log_to_console: true
console_log_interval: 1ba

callbacks:
  speed_monitor:
    window_size: 10
  lr_monitor: {}
  memory_monitor: {}
  runtime_estimator: {}

# loggers:
#   wandb: {}

# Checkpoint to local filesystem or remote object store
save_interval: 2ba
save_num_checkpoints_to_keep: 1  # Important, this cleans up checkpoints saved to DISK
save_folder: /raid/palash.kamble/LLM/finetune/checkpoints/llama2_7b

Run command
TRAIN_PATH="/raid/palash.kamble/LLM/llm-foundry/scripts/train/train.py"
YAML_PATH="/raid/palash.kamble/LLM/llm-foundry/scripts/train/yamls/finetune/llama2-7b_local_data_sft.yaml"
python3 -m composer -n 8 $TRAIN_PATH $YAML_PATH

Error
ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/raid/palash.kamble/miniconda3/envs/llm_foundry/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 744, in convert_to_tensors
    tensor = as_tensor(value)
ValueError: expected sequence of length 481 at dim 1 (got 477)

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/raid/palash.kamble/miniconda3/envs/llm_foundry/lib/python3.10/site-packages/torch/utils/data/_utils/worker.py", line 308, in _worker_loop
    data = fetcher.fetch(index)
  File "/raid/palash.kamble/miniconda3/envs/llm_foundry/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py", line 54, in fetch
    return self.collate_fn(data)
  File "/raid/palash.kamble/LLM/llm-foundry/llmfoundry/data/finetuning/collator.py", line 116, in __call__
    batch = self._process_and_batch_decoder_only(examples)
  File "/raid/palash.kamble/LLM/llm-foundry/llmfoundry/data/finetuning/collator.py", line 222, in _process_and_batch_decoder_only
    batch = self.tokenizer.pad(
  File "/raid/palash.kamble/miniconda3/envs/llm_foundry/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 3071, in pad
    return BatchEncoding(batch_outputs, tensor_type=return_tensors)
  File "/raid/palash.kamble/miniconda3/envs/llm_foundry/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 211, in __init__
    self.convert_to_tensors(tensor_type=tensor_type, prepend_batch_axis=prepend_batch_axis)
  File "/raid/palash.kamble/miniconda3/envs/llm_foundry/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 760, in convert_to_tensors
    raise ValueError(
ValueError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`token_type_ids` in this case) have excessive nesting
(inputs type `list` where type `int` is expected).

Upon checking input_ids, labels, attention_mask, these are of length equal to seq_len, but only token_type_ids is having variable length.
I did the following temporarily to resolve the issue but don't think it is the right way.
Go to /miniconda3/envs/llm_foundry/lib/python3.10/site-packages/transformers/tokenization_utils_base.py
Added following lines to function convert_to_tensors
seq_len = 512 # taken from yaml
# pad token_type_ids
for k, v in self.items():
    if k == 'token_type_ids':
        for idd in range(len(v)):
            self[k][idd] = [0] * seq_len

I think the custom collate function Seq2SeqFinetuningCollator should take care of padding token_type_ids.
Or is there a way to mention 'padding=True' 'truncation=True'?

The thing that I am confused about is why there are token_type_ids at all. The llama tokenizer doesn't use token_type_ids as far as I know. Do you know where the token_type_ids are coming from?

I tracked this down to a transformers but that was fixed in 4.31.0 (https://github.com/huggingface/transformers/pull/24042/files). If you manually update transformers with pip install --upgrade transformers, it should work. We are also updating our transformers pins, but for now you can workaround with the manual install. Thanks for reporting!

Thanks @dakinggg.


Issue-7

Issue #7
IndexOf extension method is added for ListBuilder

If this PR will be merged (I hope it is :) ), I will try to write wiki documentation about IndexOf method like TheFirst and TheLast

Hi Chris,
I edited the code according to your advice.
IndexOf extension method accepts params int[] indexes.
ArgumentOutOfRangeException is thrown instead of ArgumentException.
Exception message contains list capacity.
Moreover, some checks are added since collection of indexes is supported. In the case of indexes parameter not being able to pass the checks, I also throw an exception.

if indexes parameter is null, I throw ArgumentNullException
if indexes parameter is empty, I throw ArgumentException currently with the message "At least one item should be included".

To prevent mess of commits, I rebased my code. As a result, it is possible that you could not receive notifications.
If you think more changes are required, please do let me know. I will continue editing :)

I need you to do one more thing--change the base branch from master to develop. PR's are not accepted into master as that generates an automatic release.


new BinaryClient('wss://....')

I am trying to create new client like in the title of the topic. But the browser never makes the connection and give the error: ::ERR_NAME_NOT_RESOLVED. Any reason why?

It looks like the package on npm is behind a version. Note the change log on git vs. npm.
Also see the package.json file on npm( "version": "0.2.1") vs git ("version": "0.2.2").
Among the changes ...binaryFeatures.supportsBinaryWebsockets is pulled out. It does a check for WS which was causing the error you (and I) see..... var wstest = new WebSocket('ws://null');
I hope this makes sense.

The problem is solved. Follow this steps:

Generate an HTTPS certificate (eg OPENSSL)
Create HTTPS server instante in node.js
Create BinaryServer
In the [options] of BinaryServer, use the option server. Here use previous HTTPS server

var binaryServer = new BinaryServer({
//port: 9050,
server: serverHTTPS,
//path: "wss://<IP_ADDRESS>:9050"
});

Hi your post is helping me out on my problem. I've done what it has been said by doing the following code:
var https = require('https');
var httpsServer = https.createServer(httpsOptions,function (req, res) {
res.writeHead(200, {'Content-Type': 'text/plain'});
res.end('Not implemented\n');
}).listen(8080);
From the client i start a connection doing :
client = new BinaryClient('wss://<IP_ADDRESS>:8080');
I've dowloaded the following script "https://github.com/capira12/snapdrop/blob/master/app/elements/p2p-network/binaryjs.html" since the url "http://cdn.binaryjs.com/0/binary.js" gives me an error 404.
With chrome it's working fine but when i go on Firefox it says that it couldn't stablish connexion with my wss.
There is a similar issue on this topic :
https://github.com/sitegui/nodejs-websocket/issues/1

Where is the binaryserver invocation?
Em 22/01/2016 15:12, "pglopezamaya"<EMAIL_ADDRESS>escreveu:

Hi your post is helping me out on my problem. I've done what it has been
said by doing the following code:
var https = require('https');
var httpsServer = https.createServer(httpsOptions,function (req, res) {
res.writeHead(200, {'Content-Type': 'text/plain'});
res.end('Not implemented\n');
}).listen(8080);
From the client i start a connection doing :
client = new BinaryClient('wss://<IP_ADDRESS>:8080');
I've dowloaded the following script "
https://github.com/capira12/snapdrop/blob/master/app/elements/p2p-network/binaryjs.html"
since the url "http://cdn.binaryjs.com/0/binary.js" gives me an error 404.
With chrome it's working fine but when i go on Firefox it says that it
couldn't stablish connexion with my wss.
There is a similar issue on this topic :
sitegui/nodejs-websocket#1
https://github.com/sitegui/nodejs-websocket/issues/1
—
Reply to this email directly or view it on GitHub
https://github.com/binaryjs/binaryjs/issues/113#issuecomment-173946123.

I think you forgot the binaryserver invocation. See my previous comment
Em 22/01/2016 15:12, "pglopezamaya"<EMAIL_ADDRESS>escreveu:

Hi your post is helping me out on my problem. I've done what it has been
said by doing the following code:
var https = require('https');
var httpsServer = https.createServer(httpsOptions,function (req, res) {
res.writeHead(200, {'Content-Type': 'text/plain'});
res.end('Not implemented\n');
}).listen(8080);
From the client i start a connection doing :
client = new BinaryClient('wss://<IP_ADDRESS>:8080');
I've dowloaded the following script "
https://github.com/capira12/snapdrop/blob/master/app/elements/p2p-network/binaryjs.html"
since the url "http://cdn.binaryjs.com/0/binary.js" gives me an error 404.
With chrome it's working fine but when i go on Firefox it says that it
couldn't stablish connexion with my wss.
There is a similar issue on this topic :
sitegui/nodejs-websocket#1
https://github.com/sitegui/nodejs-websocket/issues/1
—
Reply to this email directly or view it on GitHub
https://github.com/binaryjs/binaryjs/issues/113#issuecomment-173946123.

Sorry the binary invocation is here :
var server = new binaryServer({ server: httpsServer });

The topic that i attached the link says :
"That error occurred when the browser closed the connection after receiving a self-signed certificate"
Could it be something similar ? And how to fix it on bynaryjs or the node module that it uses "streamws"

Follow this:
http://www.chovy.com/web-development/self-signed-certs-with-secure-websockets-in-node-js/
Will work
2016-01-22 15:53 GMT+00:00 pglopezamaya<EMAIL_ADDRESS>
The topic that i attached the link says :
"That error occurred when the browser closed the connection after
receiving a self-signed certificate"
Could it be something similar ? And how to fix it on bynaryjs or the node
module that it uses "streamws"
—
Reply to this email directly or view it on GitHub
https://github.com/binaryjs/binaryjs/issues/113#issuecomment-173959639.

Hi! Just test it ! It works really good. The problem seems to come from the https module. With express it works good. Thanks!


Markdown output from blocks

In the last block of this:
https://htmlpreview.github.io/?https://github.com/JuliaDiffEq/DiffEqBenchmarks.jl/blob/9f2c1a96db339251e00eaf825ae60c9195070a66/html/NonStiffODE/linear_wpd.html
I just want procedurally-generated appendices. This works, but currently by outputting this string the result looks different from the rest of the outputs. I was hoping to see if I could instead return Markdown and have it be correctly styled.

AFAIK, @mpastell has been quiet for a while now so maybe a potential solution until he comes back (or someone forks this repo) is to edit the HTML post-write and change the CSS class.

Display of markdown objects should work again with the current release.

I reopened as I just realized that Weave doens't convert the markdown output to html or latex. So this should currently work with pandoc, but it doesn't quite work with md2html.
You actually get best appearance (or at least best control) by outputting an object that can be displayed in both html and latex in which case Weave will choose the best option for the output document,

You can now output markdown and it will be rendered in html and latex. e.g.
display("text/markdown",
"""

# Small markdown sample

**Hello** from `code` block.

""")


🌱 [DO NOT MERGE] For testing prow

What this PR does / why we need it:
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #

pull-cluster-api-operator-e2e-main passed when running in old cluster:
https://prow.k8s.io/view/gs/kubernetes-jenkins/pr-logs/pull/kubernetes-sigs_cluster-api-operator/568/pull-cluster-api-operator-e2e-main/1816057440597184512.
PR to move the job to new community cluster was just merged, re-triggering it here to see if it passes 🤞🏼
/test pull-cluster-api-operator-e2e-main

Test passed after moving to new cluster: https://prow.k8s.io/view/gs/kubernetes-jenkins/pr-logs/pull/kubernetes-sigs_cluster-api-operator/568/pull-cluster-api-operator-e2e-main/1816061130288664576 🎉
Re-triggering again just to confirm:
/test pull-cluster-api-operator-e2e-main

Test passed after moving to new cluster: https://prow.k8s.io/view/gs/kubernetes-jenkins/pr-logs/pull/kubernetes-sigs_cluster-api-operator/568/pull-cluster-api-operator-e2e-main/1816061130288664576 🎉
Re-triggering again just to confirm:
/test pull-cluster-api-operator-e2e-main

Passed second time, and confirmed it is working.
/close


Error in function app not connecting to misp server

i get this error trying to get the misp feed to our sentinel. I have followed the guide, and im now clueless to what the mistake might be:
Result: Failure Exception: PyMISPError: Unable to connect to MISP (https://misp-2gcloud.westeurope.cloudapp.azure.com/). Please make sure the API key and the URL are correct (http/https is required): HTTPSConnectionPool(host='misp-2gcloud.westeurope.cloudapp.azure.com', port=443): Max retries exceeded with url: /servers/getVersion (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3102e4deb0>: Failed to establish a new connection: [Errno 110] Connection timed out')) Stack: File "/azure-functions-host/workers/python/3.9/LINUX/X64/azure_functions_worker/dispatcher.py", line 479, in _handle__invocation_request call_result = await self._loop.run_in_executor( File "/usr/local/lib/python3.9/concurrent/futures/thread.py", line 58, in run result = self.fn(*self.args, **self.kwargs) File "/azure-functions-host/workers/python/3.9/LINUX/X64/azure_functions_worker/dispatcher.py", line 752, in _run_sync_func return ExtensionManager.get_sync_invocation_wrapper(context, File "/azure-functions-host/workers/python/3.9/LINUX/X64/azure_functions_worker/extension.py", line 215, in _raw_invocation_wrapper result = function(**args) File "/home/site/wwwroot/MISP2Sentinel/init.py", line 112, in main pmain() File "/home/site/wwwroot/MISP2Sentinel/init.py", line 102, in pmain push_to_sentinel(key, value['id'], value['secret'], value['workspaceid']) File "/home/site/wwwroot/MISP2Sentinel/init.py", line 87, in push_to_sentinel parsed_indicators, total_indicators = _get_misp_events_stix() File "/home/site/wwwroot/MISP2Sentinel/init.py", line 25, in _get_misp_events_stix misp = ExpandedPyMISP(config.misp_domain, config.misp_key, config.misp_verifycert, False) File "/home/site/wwwroot/.python_packages/lib/site-packages/pymisp/api.py", line 212, in init raise PyMISPError(f'Unable to connect to MISP ({self.root_url}). Please make sure the API key and the URL are correct (http/https is required): {e}')

I does not seem to be a problem in the access, its accesseble by public ip, and we can use postman to see it pull data. Some how it still does not seem to work, and gives the same error.

The first lines in the error log indicate that there is a connection issue. Maybe try directly with the IP and check you use a valid API key?

I does not seem to be a problem in the access, its accesseble by public ip

Do you mean publicly be everyone? At least from some locations there seems to be some sort of filtering in place.

Closing pending feedback


Genaralize constriant JSON and MAP impl.

Current impl is more specific to constraint JSON we need to provide generic impl to support both maps and JSON.

Duplicate of https://github.com/ballerinalang/ballerina/issues/4075


How to install?

I am wondering what to do with the ".AppImage" file.

https://itsfoss.com/use-appimage-linux/

Please see above for Linux.


Assignment #2

complete

Good! But you could have left one of the changes you made in the final cut.


Flush message queue?

Among the commands I am sending to my telegram-controlled bot device, there is the /reboot to ask the device to restart. The problem is that as soon as the device returns ready, it will get another /reboot command and so on forever.
Is there a way to "flush" the message queue before rebooting the device (or upon starting)?

75 / 5000
Risultati della traduzione
Hi, check the OTA examples for ESP8266, what you ask you can do like this:
while (!myBot.getUpdates()) {                   Serial.print(".");                   delay(50);                 }                 ESP.restart();

Thanks


Assisted claiming issue & Failed to initialise MQTT Config (MEGH-4159)

Hello Geeks...
Hope all are doing well
I'm playing an amount ESP32S3 chip & rainmaker SDK
I have successfully configured & install ESP32-IDF (v4.4) & Rainmaker SDK
The build also seems good for both SDK
I have flashed switch example on s3 chip & able to send the WiFi hotspot SSID & password via the rainmaker Android app
The S3 is also connecting with the WiFi router & got the IP
After some time during the claiming it's generating the error & claiming got failed
here are the Error logs
E (95615) esp_rmaker_core: Failed to initialise MQTT Config after claiming. Aborting
E (98525) protocomm_nimble: Error setting advertisement data; rc = 30
I have attached the full logs here in the text file
For further debugging, I have logged in with the ESP-Insights dashboard with the same credentials which I was using with the app
And, I got this message on the dashboard
All comments & Suggestions Welcome :)
Thanks
MS

esp_rainmaker_err.txt

FYI: I have made the 1 change in main_app.c as the code was not generating the QR code before
here are the changes
/* Start the Wi-Fi.
 * If the node is provisioned, it will start connection attempts,
 * else, it will start Wi-Fi provisioning. The function will return
 * after a connection has been successfully established
 */
err = app_wifi_start(POP_TYPE_MAC);
if (err != ESP_OK) {
    ESP_LOGE(TAG, "Could not start Wifi. Aborting!!!");
    vTaskDelay(5000/portTICK_PERIOD_MS);
    abort();
}

Hi.. Guys
Here are the furthermore logs by enabling the debug
esp32_rainamekr_err_logs.txt
Thanks

This seems similar to #214

Hi,
Can you revert the code changes you have done and post the log file with the default log level set to "Debug" (using idf.py menuconfig) for investigating why the QR Code was not printing?

Yes, Will do that
Thanks
Mahendra
On Sun, Jan 8, 2023 at 10:23 AM Sanket Wadekar @.***>
wrote:

Hi,
Can you revert the code changes you have done and post the log file with
the default log level set to "Debug" (using idf.py menuconfig) for
investigating why the QR Code was not printing?
—
Reply to this email directly, view it on GitHub
https://github.com/espressif/esp-rainmaker/issues/221#issuecomment-1374708924,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AYXTEPK76CTZNHFCULDH2JTWRJB3XANCNFSM6AAAAAATQYRQT4
.
You are receiving this because you authored the thread.Message ID:
@.***>

From the logs, it looks like the issue is coming from nvs read operations.
Can you try the nvs_rw_value and nvs_rw_blob examples from IDF to confirm the source of this issue?
Also, try with IDF release/v5.0 branch as well.

Yes, that's right
The issue is coming from the NVS read operation, however, from the logs, you can check it has been detected!
Make sure that my board version is: ESP32-S3-DevKitC-1-N32R8V
Yes, will perform the test and update the results over here
Thanks
MS

Hi.. @sanketwadekar
Pl. find the test logs here
I have  used v4.4 IDF version
[nvs_rw_value_logs.txt]
nvs_rw_blob_logs.txt
(https://github.com/espressif/esp-rainmaker/files/10392184/nvs_rw_value_logs.txt)
Thanks
MS

@MahendraDnkTech Can you enable Octal Flash using idf.py menuconfig -> Serial flasher config ->  Enable Octal Flash and retry?

Hi.. @shahpiyushv
here are the logs with enabled octa SPI Flash
nvs_rw_blob_logs.txt
nvs_rw_value_logs.txt
Thanks

Hi.. @shahpiyushv
The switch example of the rainmaker is now working after enabling the Octa spi flash!
Many Thanks


split_v generates tensors of unspecified size for all dimensions, when one dimension is missing at the original one

The new split_v function introduced in 0.12rc0 does not correctly predict the shapes of the resulting tensors when the original tensor has an unknown dimension, resulting on the split dimension being of unknown size. For instance:
tensor = tf.placeholder(tf.float32, [None, 12])
parts = tf.split_v(tensor, [6, 4, 2], split_dim=1)

This results in three tensors, all with shapes [?, ?], instead of the expected [?, 6], [?, 4] and [?, 2]. While at runtime the resulting tensors are of the right size, this makes it more difficult to debug the code during graph definition.
EDIT: This also creates problems when combined with scan. Because scan expects fn to return tensors of the same shape as the initializers, it forces the use of a reshape just to clear the 'unknown' dimension.

Shape inference is done in C++, not python, and at that point everything is a tensor and it is not possible to inspect the contents of tensors during shape inference.  So, in general, it is not possible to provide any better shape information beyond the rank.
That said, we can hack the python interface to check if the size list is a list of integers and not a tensor and then reshape the outputs correctly.  Is that your use case?  Or do you generate the size list dynamically?  Because if it is dynamically generated, there is no way to do the shape inference that you want.

Hello ekelsen, yes that is my case. The list provided to split_v is a list of integers, so the size for this dimension is provided.

This feature should be added before the next release.  Note that this shape inference behavior will be optional as it will add a reshape operation to every output tensor which could be a performance penalty, especially when there are many output tensors (1000+) and the tensors are small.

Thank you in advance. Nevetheless, I'm a little bit confused as to why a reshape for each output tensor is required. I'm not familiar with how tensorflow works internally, but even if the tensor operation itself has no information on the tensor shape other than the rank, shouldn't it be possible to set the output tensors dimension to the provided values (if these are given as integers) without having to add a reshape operator? After all, under these circumstances the output is guaranteed to have this shape for the split dimension, a reshape seems unnecessary to enforce this.

Sorry, yes you're correct that all that's needed here is to set the shape.


add endpoint routing support

#2569
Does this PR introduce a breaking change?
No
Please check if the PR fulfills these requirements

[x] The commit follows our guidelines
[x] Unit Tests for the changes have been added (for bug fixes / features)

Other information:
Add extension methods for adding endpoints to IEndpointRouteBuilder

There's a lot more work to be done to really support EP routing. Will consider for a future version. Thanks though.


missing buffer names

I've recently started using the code and noticed that I cannot retrieve names for uniform buffers in glsl. The name is always a null string. I am however ale to get the names of the buffers members.
I believe this is a bug and would like you guys to fix it asap. Just as a test I opened my compiled spirv code in notepad++ and the actual buffer name was stored in plain text. So it's retrieval seems highly possible.

can you please provide a glsl code so I can reproduce

closing, @madgeniusjm if you do want reopen, please submit an example, preferably something like a Compiler Explorer link (example https://godbolt.org/z/s14W5Mx6M)


update-dashboard bug

Checking environment
AWS CLI version...2.1.28...ok
Fetching AWS Account ID...ok

Config file detected work/xxx/config:
----
export region=us-west-2
export aws_identity_region=us-west-2
export aws_qs_identity_region=us-west-2
export athena_database_name=athenacurcfn_myfirstcur
export athena_cur_table_name=myfirstcur
export user_arn=arn:aws:quicksight:us-west-2:xxx:user/default/Matt
export AWS_DEFAULT_REGION=us-west-2
----
Checking for updates...
Getting latest available source template version...latest available template version is 98
Getting currently deployed source version...latest available template version is None
./shell-script/customer-cudos.sh: line 178: [: None: integer expression expected
./shell-script/customer-cudos.sh: line 181: [: None: integer expression expected
Update available ( None > 98 ), proceeding
...

Running with bash -x:
+ '[' None -eq 98 ']'
./shell-script/customer-cudos.sh: line 178: [: None: integer expression expected
+ '[' None -gt 98 ']'
./shell-script/customer-cudos.sh: line 181: [: None: integer expression expected
+ echo 'Update available ( None > 98 ), proceeding'

No, there is a bug that API for QuickSight in US-EAST-1 returns the value for SourceEntityARN and some other regions don't.

i'm also facing the same issue;
`[cloudshell-user@ip-10-0-49-89 cudos]$ ./shell-script/customer-cudos.sh update-dashboard
Checking environment
AWS CLI version...2.1.28...ok
Fetching AWS Account ID...ok
Config file detected work/199744280866/config:
export region=eu-west-1
export aws_identity_region=us-east-1
export aws_qs_identity_region=us-east-1
export athena_database_name=athenacurcfn_c_u_d_o_sv2
export athena_cur_table_name=cudosv2
export<EMAIL_ADDRESS>export AWS_DEFAULT_REGION=eu-west-1
Checking for updates...
Getting latest available source template version...latest available template version is 103
Getting currently deployed source version...latest available template version is None
./shell-script/customer-cudos.sh: line 178: [: None: integer expression expected
./shell-script/customer-cudos.sh: line 181: [: None: integer expression expected
Update available ( None > 103 ), proceeding
####### Pulling latest changes...
####### Applying latest changes to the deployed Dashboard...
Error: something went wrong, exiting`

Has been fixed, please redeploy the dashboard to make use of the newly populated field SourceEntityArn, update should work as expected after redeploy


[bzip2:x64-windows] build failure

Hi I am sorry I could not install bzip2 package with this updated compiler version. However, with the previous version last year it worked.
would it be possible to have this problem fixed?
Best Regards
Jérôme Garcia
Host Environment

Windows 10
Compiler: version 2020.06.15-nohash

To Reproduce
Steps to reproduce the behavior:
./vcpkg install bzip2:x64-windows
Failure logs
Starting package 1/1: bzip2:x64-windows
Building package bzip2[core]:x64-windows...
Could not locate cached archive: C:\Users\Jérôme\AppData\Local\vcpkg/archives\fd\fdbd36227fe45ab3651e181fb29d360a45311b53.zip
-- Downloading https://github.com/past-due/bzip2-mirror/releases/download/v1.0.6/bzip2-1.0.6.tar.gz...
-- Extracting source E:/alpha/math/C++/librairies/vcpkg-master/downloads/bzip2-1.0.6.tar.gz
-- Applying patch fix-import-export-macros.patch
-- Applying patch fix-windows-include.patch
-- Using source at E:/alpha/math/C++/librairies/vcpkg-master/buildtrees/bzip2/src/1.0.6-8838f21f8e.clean
-- Configuring x64-windows
-- Building x64-windows-dbg
-- Building x64-windows-rel
CMake Error at scripts/cmake/vcpkg_fixup_pkgconfig.cmake:259 (list):
list sub-command FILTER, mode REGEX failed to compile regex
"E:/alpha/math/C++/librairies/vcpkg-master/packages/bzip2_x64-windows/debug/".
Call Stack (most recent call first):
ports/bzip2/portfile.cmake:49 (vcpkg_fixup_pkgconfig)
scripts/ports.cmake:79 (include)
RegularExpression::compile(): Nested *?+.
RegularExpression::compile(): Error in compile.
Error: Building package bzip2:x64-windows failed with: BUILD_FAILED
Please ensure you're using the latest portfiles with .\vcpkg update, then
submit an issue at https://github.com/Microsoft/vcpkg/issues including:
Package: bzip2:x64-windows
Vcpkg version: 2020.06.15-nohash

math/C++/librairies rename to math/Cpp/librairies
There was somewhere a PR fixing it but I was not able to directly find it

Hi @alphaquant2 ,
Can your problem be solved according to @Neumann-A Neumann-A's suggestion? I can install it locally

Hi, indeed in renaming the directory C++ into Cpp, it allowed the compilation to succeed. However as I have other programms working on the same C++ directory in other computers I am doing the move carefully on a test computer to see if the rest will fit. Thanks

the relevant pr is #12964


updating SAT version having security fix

IM:CRAYSAT-1795
Reviewer:Ryan
Summary and Scope
CRAYSAT-1795 Changes to address security vulnerabilities
Hence upgrading the version
Issues and Related PRs
List and characterize relationship to Jira/Github issues and other pull requests. Be sure to list dependencies.

Resolves CRAYSAT-1795

Testing
List the environments in which these changes were tested.
Tested on:

MUG

Test description:
SAT commands have been tested and looks good without any issues
Risks and Mitigations
Low risk
Pull Request Checklist

[x] Version number(s) incremented, if applicable
[x] Copyrights updated
[x] License file intact
[x] Target branch correct
[x] CHANGELOG.md updated
[x] Testing is appropriate and complete, if applicable
[x] HPC Product Announcement prepared, if applicable

It looks like the build of cray-sat:3.21.8 actually failed in the release/3.21 branch of the Jenkins multibranch pipeline here: https://jenkins.algol60.net/job/Cray-HPE/job/sat/job/release%252F3.21/10/console
It may be a transient failure with Snyk scanning. I'm taking a look.

The cray-sat:3.21.8 build failure has been resolved with another rebuild. We're not sure at the moment what went wrong. I'll kick off another build of this branch now.

The build of this branch ran into a couple other intermittent issues. Two rebuilds were required to get it to work. We'll have to look into this if it keeps occurring.

Yaa it was strange for me that such a long time was needed for the new version visibility


New user Feature framework and TrackScheme feature based coloring.

This PR includes the new feature framework, that decouples the feature specifications and the feature storage themselves, as well as its use to generate a feature-based coloring scheme in TrackScheme.
Hi Tobias,
So here is the changes I made to your experiments on the feature framework.
I list here the changes I propose, grouped by category. Most of them relate to providing end-users with information and incremental updates.
Mamut-prefixed classes indicate classes that are specific to the Mastodon-app, that uses ModelGraph with Spots and Links. Other classes are generic and work for Vertex and Edge interfaces.

A. Specify and provide the metadata of features.
1. Feature projection specs can have a multiplicity.
The multiplicity flag aims at addressing the fact that some projections may be defined per source. For instance the mean intensity has one projection per source. But we do not know how many sources we will get. So we flag these projections with a special value of the multiplicity to signal for that.
If a feature projection has a standard multiplicity (e.g. position) you don't have to worry about it. But for instance, here is what you do to define a feature with two series of projections, each per channel:
public static class SpotGaussFilteredIntensityFeatureSpec extends FeatureSpec< SpotGaussFilteredIntensityFeature, Spot >
{
	public SpotGaussFilteredIntensityFeatureSpec()
	{
		super(
				KEY,
				HELP_STRING,
				SpotGaussFilteredIntensityFeature.class,
				Spot.class,
				FeatureProjectionSpec.onSources( MEAN_PROJECTIONS_KEY, Dimension.INTENSITY ,
				FeatureProjectionSpec.onSources( STD_PROJECTIONS_KEY, Dimension.INTENSITY ) );
	}
}

Let's focus on one:
final FeatureProjectionSpec meanProjections = FeatureProjectionSpec.onSources( MEAN_PROJECTIONS_KEY, Dimension.INTENSITY );

(Ignore Dimension for now.)
With this you generate a single projection spec object that signal that there will be one projection per source, all prefixed with MEAN_PROJECTIONS_KEY (in this case Mean).
In the feature computer, when you will need to generate and store the projection of the source number iSource, or when you will need to get the feature projection key for iSource, you will do something like that:
String projectionKey = meanProjections.projectionKey( iSource );

That way you can get and play with projection keys before knowing all the sources you have.
Multiplicity has 3 values, for standard projections, per source projections, and also for source pairs, unused yet.
2. Feature projection specs have a dimenson.
No big deal, I wanted to support units for quantities. Since the feature projection specs know nothing of the model, they cannot have units. But you can defined a dimension for the quantity they represent. Later, actual feature projections will turn this into a unit.
There is a org.mastodon.feature.Dimension enum that stores accepted dimensions, with utility methods.
3. Feature projection have units.
The logical conclusion. FeatureProjection has a units() method that return a String.
There is a method in the Dimension class that can generate the units string automatically from the space and time units:
public String getUnits( final String spaceUnits, final String timeUnits );

... so to do this right we need....
4. The Model stores space and time units.
I hope this will not make you cringe too much. There are two extra string fields into the Model object that stores that.  The two units are serialized with the Model. I stored them into the project.xml file, as two XML elements.
They are determined when the Model is created from the BDV object, reading spatial and time units. Right now, BDV does not support time units, but we are ready to do so.
When a project is loaded, the two strings are retrieved from the project.xml file, and the Model instance created with these. If we fail to load them, they are retrieved from the BDV file. If this still fails ,
by default they are pixel and frame.
This forces us to declare v0.3 for the file format, but it is backward compatible with v0.2.
5. Feature specs provide more information to the user.
A feature spec provide an information text. Put it (e.g. HELP_STRING) in the constructor:
@Plugin( type = FeatureSpec.class )
public static class Spec extends FeatureSpec< LinkDisplacementFeature, Link >
{
	public Spec()
	{
		super(
			KEY,
			HELP_STRING,
			LinkDisplacementFeature.class,
			Link.class,
			FeatureProjectionSpec.standard( KEY, Dimension.LENGTH ) );
	}
}

and the class has a getInfo() method:
public String getInfo();

This is exploited e.g. in the feature projection.
B. Filter feature computer by application.
I drilled a little bit into the FeatureComputerService. I reasoned that FeatureComputerService is the class that manages a collection of FeatureComputers, and is in charge of facilitating feature calculation.
We might have features that are defined only for a specific application, for instance the Mastodon-app which is based on the Model with ModelGraph objects etc... The way we separate FeatureComputers from another application is with FCs that implement a specific interface. In our case that is MamutFeatureComputer, that has nothing special.
So we also have a specific MamutFeatureComputerService for the Mastodon-app, that only discovers MamutFeatureComputers.  It inherits from DefaultFeatureComputerService, which discovers all FCs, and implements the common FeatureComputerService interface.
I think it works well this way. With the FeatureSpecService, all features are discovered. But inside the MamutFeatureComputerService, only those that can be computed by a MamutFeatureComputer are considered and presented to the user.
This also solves a problem I had with "manual" features: Features that are defined for Spots and Links but are not computed by a FC. For instance they might store the quality of a spot detection, or the cost of a link. They will not appear in the feature computation dialog, because a FC will not be found for them. And therefore, they won't be deleted after a feature computation request. But because they will be stored in the FeatureModel, they will appear in whatever uses features, like table, coloring etc.
C. Facilities for feature computers.
Well of course we want to provide incremental updates to features, but first a digression:
1. PropertyChangeListener as dependency for FCs.
The DefaultFeatureComputerService ad inherited classes have a PropertyChangeListener (that does nothing by default). Interested FC can access it via the dependency mechanism, and us it to report computation progresses. For instance, you would put this in your FC code:
@Parameter
private PropertyChangeListener listener;

and then:
Status events.
listener.propertyChange(  new PropertyChangeEvent(
				this,
				"status",
				"",
				"Trolololot" ) );

Progress event.
listener.propertyChange(  new PropertyChangeEvent(
				this,
				"progress",
				0,
				(int) ( 100. * done++ / todo ) ) );

Clear status event.
listener.propertyChange(  new PropertyChangeEvent(
				this,
				"clear",
				"",
				"" ) );

2. Incremental updates for feature computers.
The Mamut features can subscribe to a object that will facilitate implementing incremental updates. That is: only recompute feature values for objects that have been modified since last time a computation was made.
A GraphUpdateStack instance will record graph changes between certain 'commits'.
After features have been computed, a commit is made to the stack by the feature computer service. The commit stores the list of feature keys that have been computed. The stack can store a limited number of commits (10).
When needed, a FeatureComputer can call the changesFor( key ) method, which will return an GraphUpdate object containing all the changes that happened in the graph since the last time the feature was computed. This object can be used to make an incremental computation of the feature.
The GraphUpdate object is produced by concatenating all the GraphUpdates over all commits until the commit with the feature key is found.
If a GraphUpdate object cannot be produced (is null, because e.g. the feature was never computed, or because the last commit with this feature was 'forgotten' by the stack), this signals that a full
computation must be made.
The updates have a certain locality. For instance you can ask for all the vertices that have been modified, and/or for all the edges of the spots that have been modified. There is just two locality vaue now:

SELF: You have been modified.
NEIGHBOR: Your direct neighbor has been modified (edges of a vertex, source and target vertices of an edge).

The SpotGaussFilteredIntensityFeatureComputer uses it.
3. Feature computer service is cancelable and feature computers can be cancelable.
You can cancel the feature computation process. If the current feature computer is cancelable, the cancel event will be forwarded to it.
Again the SpotGaussFilteredIntensityFeatureComputer is cancelable.

D. A settings page to edit color modes.
User-provided information about how to generate colors based on feature values is stored in a FeatureColorMode class, that can be serialized to YAML, and is managed like the BDV RenderSettings and the TrackSchemeStyle.
The mode editing panel resembles this:

Classic case like coloring a vertex by a vertex feature is supported, but it is also possible to color and edge by a vertex feature and vice-versa:

The editor looks like this on Windows platform:

The color maps are represented by a ColorMap class, that can also be serialized to YAML. There is no editor for these colormaps, however it is possible to drop ImageJ LUT files in the ~/.mastodon/luts folder:
tinevez@lilium:~$ ls .mastodon/luts/
Algae.lut   Curl.lut    Dense.lut   Ice.lut     Phase.lut   Tempo.lut
Amp.lut     Deep.lut    Gray.lut    Matter.lut  Solar.lut   Thermal.lut
Balance.lut Delta.lut   Haline.lut  Oxy.lut     Speed.lut   Turbid.lut

tinevez@lilium:~$ cat .mastodon/luts/Algae.lut
Index	Red	Green	Blue
0	17	36	20
1	17	37	20
2	18	37	21
3	18	38	22
4	18	39	22
...

The coloring is based on the feature projections (scalar, double values) of a feature. The editor panel lets the user pick a pair of feature and projection keys:

Finally, the validity of a color mode depends on the feature to be calculated. It is possible and even common to have a color mode pointing to features that are not registered in the feature model. We want to let the user edits such modes, but we warn them that the related features need to be computed before use in a view:

TrackScheme coloring.
The TrackScheme coloring menu now includes feature-based color modes. The color modes that are invalid (depending on feature that are not yet computed) appear disabled in the menu:

It looks like this on Windows platform:

Here is an example:

Another example for a track feature: all the spots of a track have the same feature values, ergo the same color:

Supersede and include

#67
#63

The Travis job fails on Javadoc errors. Shall I fix them all?


Channel Bookmarks

Summary
This PR adds the channel bookmarks to mobile
In order to use it needs a server running https://github.com/mattermost/mattermost/pull/25449
Ticket Link
https://mattermost.atlassian.net/browse/MM-54432
Release Note
Added channel bookmarks

Hey @enahum - please add a link to the Jira ticket in the description. Thanks!

Awesome!! It's working really well, two quick issues I found: @enahum @lindy65

Long bookmark names that wrap have a UI issue in the long press menu:

Deleting doesn't seem to be working. The first try it fails silently (ie you hit delete and then the modal closes but the bookmark is still there), then second try on the same bookmark shows this error:

Will take a look on the delete error.
For the long name, will add ellipsis

@enahum confirming a few things:

Permissions are respected when configured in the system scheme, team scheme or channel moderation pages as per spec: https://mattermost.atlassian.net/wiki/spaces/WD/pages/2505113601/Bookmarks+Permissions
The feature is behind an license check (professional and above)

@enahum confirming a few things:

Permissions are respected when configured in the system scheme, team scheme or channel moderation pages as per spec: https://mattermost.atlassian.net/wiki/spaces/WD/pages/2505113601/Bookmarks+Permissions

The feature is behind an license check (professional and above)

cc// @lindy65 for test cases ^

Yes both things implemwnted by @mgdelacroix

Hi @larkox, requesting help from you to review this as Miguel is now out for baby leave

Hey Elias, some feedback regarding the mobile app.

The text and the image don't look vertically aligned.

The plus button should alawys be fixed on the right with a gradient.

Plus button should have 56% opacity.

No border on the emoji picker.

Images and emojis also clipped off in the picker button.

When a large file is uploading, I can't cancel it, the screen is fixed until the upload is done. I should be able to hit the close button to stop uploading and close the modal.

Is it possible to use the favicon first instead of the open graph image? (We can avoid it if a time consuming change).

@enahum

The image size is fine, the text and the image just needs to be center aligned vertically.
Here's the Figma link as well:
https://www.figma.com/file/1Q0OOa5P7Jz7Y2j7QVObzo/Bookmarks-Bar?type=design&node-id=999-52392&mode=design&t=YUF03jSc0NKMLq8n-11

The deisgn is the same, you can check it out here.
The plus button is just floating, you can move the bookmarks items left and right without any issues, it doesn't effect the position of the plus.
https://www.figma.com/file/1Q0OOa5P7Jz7Y2j7QVObzo/Bookmarks-Bar?type=design&node-id=999-52392&mode=design&t=YUF03jSc0NKMLq8n-11

For the size of the image in the emoji picker button, I think the size you have is fine, it just shouldn't be clipped off.
The size I have on my design is 20px - 20px, the same as the size in the emoji picker in the custom status modal.

Need to update logic as well.

@enahum I'll jump in to take over for @asaadmahmood on this.
For file attachment bookmarks, I'd like to propose some changes if we can. As soon as a file is chosen, it should start uploading and show progress within the attachment card - just like we do for attachments in the post draft Figma. I realize this isn't a great time to propose a change like this, so please let me know what you think is doable and we can negotiate. We should have expressed this uploading flow more clearly in design spec I think - apologies for that.

While uploading, the save button is disabled
progress bar and percentage show in the attachment card
the x button in the top nav bar for the modal cancels any change and stops upload
an x button appears on the attachment as well that will remove the attachment and stop the upload

Once uploaded, the save button is enabled
users can remove the attachment with the x that appears on the attachment card. Removing the attachment then resets to the empty state and shows the 'upload' button
For this reason, I'm proposing we remove the 'edit' button that currently appears under the attachment.

@matthewbirtch I see two problems with this flow

What happens when the file is removed or upload cancelled? Do we open the file selection again or close the screen?
The major problem is this can leave orphan files already uploaded that won't be removed from the server and data storage

@asaadmahmood @matthewbirtch changes made

@asaadmahmood @matthewbirtch changes made

Thanks @enahum I'm having trouble with the local environment so I'll have to trigger a test build.

@matthewbirtch the bar in channel info is exactly the same componennt that appears in the channel, and I definitely want to keep it that way, in terms of how it looks and how it works so take that into consideration for the design and the feedback.
I will be addressing all the feedback in this PR and the server PR on Monday

@matthewbirtch the bar in channel info is exactly the same componennt that appears in the channel, and I definitely want to keep it that way, in terms of how it looks and how it works so take that into consideration for the design and the feedback.
I will be addressing all the feedback in this PR and the server PR on Monday

Cool. That's why I asked. No worries - let's proceed that way and you can ignore the specific ask about showing the + button inline on the info modal

@larkox @matthewbirtch @asaadmahmood changes made. PTAL

@matthewbirtch can you provide repro steps for this

On iPad, the top bar for the 'Add bookmark' modal isn't getting the theme applied correctly.

it seems to be working fine for me

@matthewbirtch can you provide repro steps for this

On iPad, the top bar for the 'Add bookmark' modal isn't getting the theme applied correctly.

it seems to be working fine for me

Here are my repro steps @enahum:

Close the app on iPad
On webapp, change theme to Denim
Re-open the app on iPad
Open the Add a bookmark modal - everything looks fine
Close this modal
Then on webapp, change theme to Onyx
On iPad, open the Add a bookmark modal - notice the top bar is wrongly themed
If I then close the app and reopen it, the top bar in this modal displays properly themed

@matthewbirtch done. Thanks!

@lindy65 are you owning QA review on this PR? Can you help review with priority to unblock merging as I believe all other reviews have been complete. Thanks!
You'll have to point the mobile app to the server spinwick: https://github.com/mattermost/mattermost/pull/25449#issuecomment-1923341668

@esethna yes.. but it should be tested anyway

Hi @enahum, I've done a QA pass according to UX doc and am seeing one issue.
Repro steps:

Create a custom emoji as the sysadmin on the server from browser/desktop app
Go to an existing bookmark you already have in a channel
Long-press on the bookmark and choose Edit
Tap on the default emoji icon to the left of bookmark title
Search for and select the custom emoji you created in step 1) but don't tap on SAVE yet

Observed:
Custom emoji is inserted but default title emoji is also displayed below it

Repro steps continued:
6. Tap on SAVE
Observed:
Both the custom emoji and default emoji are displayed (on Channel Info screen and on the bookmark in the channel)

Repro steps continued:
7. Long-press on the bookmark and select Edit
Observed:
Only the custom emoji is now displayed to the left of the bookmark title.  Both the default bookmark icon and custom emoji are still shown on the bookmark in channel but exiting the channel and re-entering it fixes this and only the custom emoji is shown on the bookmark in channel now.

@lindy65 I made some changes to ensure it does not happen


Currently we use custom ProxySelector ( https://github.com/alphagov/pay-direct-debit-connector/blob/6f423b5dddddf2039aa1f878c4865eefe2e226ae/src/main/java/uk/gov/pay/directdebit/common/proxy/CustomInetSocketAddressProxySelector.java ) which is used as a default proxy selector for any outbound Java requests https://github.com/alphagov/pay-direct-debit-connector/blob/6f423b5dddddf2039aa1f878c4865eefe2e226ae/src/main/java/uk/gov/pay/directdebit/DirectDebitConnectorApp.java#L93
We want to change the configuration and implementation and not to use custom ProxySelector when initialising GoCardless SDK
We should use InetSocketAddress.createUnresolved(configuration.getProxyConfig().getHost(), configuration.getProxyConfig().getPort()) instead of new InetSocketAddress(configuration.getProxyConfig().getHost(), configuration.getProxyConfig().getPort()), because new InetSocketAddress(...) will resolve to IP address straight away and this IP address may be invalid in the future (we should use hostnames for our proxy address).
InetSocketAddress.createUnresolved will not resolve reverse proxy domain name to IP address, hence it will always be valid (even in case when the hostname changes it's IP address)
Removed the ProxySelector.setDefault(customInetSocketAddressProxySelector) call to apply InetSocketAddress.createUnresolved
related PR: https://github.com/alphagov/pay-direct-debit-connector/pull/271

can you give a bit more background about the reasons for doing this?

@heathd I have updated the commit message and PR description with more information.
In a nutshell it's a small improvement not to use ProxySelectors
Thanks

👍


No language support for CGI data

I'd like to see support for CGI strings.
Example:
?page=My%20Page&zip_code=46800&q=hidden

You want to user this as one-line snippets? It can be done if there is "?" mark first, otherwise it may cause many misdetections IMO.

@Sannis are you going to implement it? If not, then there's no point in just keeping an open issue without an implementation.


Support wildcard and superfluous deletes

Currently deletes are per-triple. This means that deleting all triples for a particular subject has to be done by querying that subject's triples, and deleting them all individually. Besides being an annoying way of deleting, it also leads to a duplication of all the data being deleted, and we lose semantic value, as we do not save the fact that we deleted everything related to a particular subject.
I propose we implement wildcard deletes. Wildcard deletes would assert that for a particular subject, predicate, or object, or for a particular subject-predicate or predicate-object pair, all triples have been deleted in a particular layer.
Additionally, it should be possible to insert such a wildcard delete even if there's no previous insert that'd match the wildcard. This would allow us to shortcut many queries searching for data by specifying at a certain layer that this data will not be found no matter how deep the query drills into the layer stack.
I'm not sure if we can implement wildcard deletes with the present structures or if a new set of structures will be needed.

Reasoning from terminusdb, the most interesting wildcard deletes would be subject, object, and subject-predicate.

When deleting a particular document, we always want to insert a wildcard delete for that document id as subject and a wildcard delete for that document id as object.
When replacing a particular document, we want to insert a wildcard delete for that document id, followed by inserts for the whole document. Any existing triples with this document in the object position remain valid however.
When replacing or deleting a particular property of a document, we want to insert a wildcard delete for the subject-predicate pair.

less useful:

wildcard predicate-object deletion has limited use, such as when deleting all objects of a particular type. This may also come in handy when changing the key strategy of a type, requiring all ids of that type to be regenerated. Any queries that need to list all objects of a particular type can then know to look no further than a particular layer.
wildcard deletes on predicates are less useful. We hardly ever query on predicates alone. So even if we delete all triples of a particular property, the wildcard delete would not speed up anything. Furthermore, this is simply not a delete we ever do semantically.

I think this is a really good idea. When looking up change information however, we'll have to look deeper down the layer stack to find the answer, but since this is likely to be a lot less common (and a lot more focused) I think this makes sense. It should speed up both search for documents structure (by allowing us to know for sure that nothing is lower in the stack) and deletion.
For the eventual use of content-addressable-hashing, will we need some encoding for the stars, or do we look up the answer for the delta and use that? I'm thinking that there is no advantage to the later, but maybe I'm missing something.


Fix typo in ISSUE_TEMPLATE.md

Fix a typo in the ISSUE_TEMPLATE.md

I've signed the CLA.

@googlebot ping!

It seems the CLA bot is having some issues with this one. Should I close this and re-create it?

@jgeiger Thanks for noticing and correcting it 👍


Update the viewer

Hey, I have an issue updating the viewer. I use react-router to fast load the components. My problem is that I don't know how to reload the viewer. It only reloads when I refresh the page, and that's not what I want.

Hi, that shouldn't happen, you're right. What version are you on?

I suspect that your're on a version prior to 1.0.0. Because of the anonymous user (which was removed in this commit), we had to use a constant id for the current user (see here and here). If you don't use the same id, Relay does not know, that the user after login should replace the anonymous user object from before.
The new versions from 1.0.0 on are not using the anonymous user anymore but some flags like isLoggedIn on the viewer type. This is a lot cleaner, because you don't need to use the roles anymore on the client and this confusing requirements, that most probably led to your reloading issue, are gone.
Did this help you?

Thanks, i was using an old version.


Issues trying to initialize a ct::core::ControlSimulator

Hello,
I'm struggling to understand how to build a ct::core::ControlSimulator instance. This are my lines of code
const size_t state_dim = ct::core::SecondOrderSystem::STATE_DIM;      // = 2
const size_t control_dim =  ct::core::SecondOrderSystem::CONTROL_DIM;  // = 1

ct::core::StateVector<state_dim> x0;
x0.setZero();

ct::core::Time sim_dt = 0.005;
double w_n = 50;
std::shared_ptr<ct::core::SecondOrderSystem> oscillator(new ct::core::SecondOrderSystem(w_n));

ct::core::ControlSimulator<ct::core::SecondOrderSystem> mpc_sim(sim_dt, sim_dt, x0, oscillator, true);

However, when I try to compile I get the following error.
/usr0/home/rshu/ct_ws/devel/include/ct/core/simulation/ControlSimulator.h:37:54: error: no type named ‘SCALAR’ in ‘class ct::core::tpl::SecondOrderSystem<double>’
     using SCALAR = typename CONTROLLED_SYSTEM::SCALAR;

could you please help understand what I'm doing wrong when initializing a Control Simulator.
Thank you,
Roberto

Dear @rshum19
The bug above is coming from the fact that the system that you pass to the control simulator must define a typedef for the SCALAR type. That means your custom system must provide that typedef.
Please be warned about the following: The control simulator is a legacy class which has not been used for quite a while. I would recommend you to resort to the standard integrator implementation instead (see also masspoint integration example).

Dear @markusgft
Thank you for the advice, if it a legacy class then I will refrain from using and resort to standard integrator implementation.


Updated MeerK40t UI for Linux

Replacing the scene panel allows linux to scroll and pan correctly, but still no visualization of the objects.


Compare mod lists

There should be a requirement of having the same mods. Just check mod IDs and version numbers.

Some other files to maybe get checksums of:
Everything in Maps/ and Data/ matches (probably excluding EngagementDialogue.yaml, ExtraDialogue.yaml, and animationDescriptions.yaml, and other languages?)
Probably want to check the mod manifest for some sort of 'is cosmetic' or otherwise clean tag. For instance, Map Image Exporter wouldn't cause issues.


About HMC-QU dataset processing

https://www.kaggle.com/datasets/aysendegerli/hmcqu-dataset
Dear author, thank you for your excellent work on open source. I have a question for you. I downloaded the dataset HMC-QU from the website kaggle. I found that the resolution of the original image and the segmented mask is not the same. The resolution of the original image is generally 422636 (there are some others), while the resolution of the mask is 224224. May I ask the author how you deal with it?

https://www.kaggle.com/datasets/aysendegerli/hmcqu-dataset
Dear author, thank you for your excellent work on open source. I have a question for you. I downloaded the dataset HMC-QU from the website kaggle. I found that the resolution of the original image and the segmented mask is not the same. The resolution of the original image is generally 422_636 (there are some others), while the resolution of the mask is 224_224. May I ask the author how you deal with it?

After comparison, we resized these data and standardized them to 256 x 256.

That is, directly resize 422636 (or any other resolution) to 224224?

That is, directly resize 422*636 (or any other resolution) to 224*224?

That is, directly resize 422636 (or any other resolution) to 224224?

256×256

Thank you for your explanation, but some detail questions still need you to give answers, the dataset gives gt size of 224224 in mat format, and the given avi size is not 224224, do you mean the adjustment is to resize the avi data directly to 224 or crop it to 224? Because these two operations will form different gt counterparts. Based on the experiment, my guess is avi(non-224)->(crop)->2D image(224)->(resize)->256.Hope I can get your answer!

All our data is directly resized to 256 x 256.


When there is no AK/SK. There is no hint to create AK/SK

What is the Issue?
When there is no AK/SK. There is no hint to create AK/SK.
The table has no data when I click on the Resource page.
How can it be fixed?
The user needs to be prompted to create AK/SK.

Solved by #55


DDI training compared to not DDI training

Hi! I am curious about why you use DDI (data-dependent initialization) here, as not doing DDI won't cause a bug in the program. So how is the performance of not using DDI at the beginning? Does it have a specific use?

Also, where is the source of this method? I found a paper (https://arxiv.org/pdf/1511.06856.pdf) but it not seems to be the implementation used in this repo. Appreciate any discussions!

Hi
Do you have some insights about it?
Do you know if the DDI is necessary?

Hi @cantabile-kwok Do you have some insights about it? Do you know if the DDI is necessary?

Hi, I did not investigate this issue into much detail afterwards, and I started training with DDI every time since then, to prevent potential degradation of performance. I think using DDI is never a bad thing because it lets your model initialized with more reasonable parameters.


Add peek(key)

As a shortcut to getIfPresent(key, false) – mimicking eg. https://www.npmjs.com/package/lru-cache#api
Also: Document getIfPresent(key, false)
And as an added bonus: Ignore yarn.lock

Coverage increased (+0.1%) to 91.85% when pulling fcc8495177d84180238b1c721b519be82b77b1da on voxpelli:peek into 2af3aed38695624ea416f43bed9d39432c447f1b on aholstenson:master.


Exe path

Hi
where can I define the exe path

Please elaborate.
What exe?

after compiling test.cs, a test.exe is created.
where can I define the path of this exe?

The exe is created in the same location where your script is.
This location is not customizable so the exe will need to be copied manually.
With the plugin the idea is that you do not need to know where executable is if you are using Npp to run the scripts and only if you really want to build an exe then you trigger a dedicated workflow that opens the explored at the folder where the executable is.


Extra options

Hello,  great copy from the cordova plugin, we are using it in our migrated capacitor app atm. My only concern for now is the lack of default options. It would be great to offer more options available like the original plugin. It would be a great help to have at least the height and weight properties, but the same would be even better :)

yeah, I will try to copy all features :-), but if you can help me, I'll feel  better

any advices on how to crop and resize the image from your plugin?

in the meantime you add all the extra options, any advices on how to crop and resize the image from your plugin?

CameraPreview.capture(pictureOpts).then((base64PictureData) => {
// We pass width, height, x and y coordinates of our rectangle to crop func
// BEFORE crop function ends, it sends cropped base64 image to a server
this.crop(base64PictureData.value, rectWidth, rectHeight, xCoord, yCoord, (croppedBase64Image) => {
//do stuff with your image
})
crop(base64PictureData, rectWidth, rectHeight, xCoord, yCoord, callback: (param) => void) {
    // image will contain ORIGINAL image
    const image = new window.Image();

    // image will contain CROPPED image
    const canvas = document.createElement('canvas');
    const ctx = canvas.getContext('2d');

    // Load original image into image element
    image.src = 'data:image/png;base64,' + base64PictureData;
    image.onload = () => {

        const scaleHeight = rectHeight / image.height;
        const scaleWidth = rectWidth / image.width;

        let scale;
        let xImgUnits;
        let yImgUnits;
        if (scaleHeight < scaleWidth) {
            scale = scaleWidth;
            xImgUnits = 0;
            yImgUnits = (image.height - (rectHeight / scale)) / 2;
        } else {
            scale = scaleHeight;
            xImgUnits = (image.width - (rectWidth / scale)) / 2;
            yImgUnits = 0;
        }

        const rectWidthImgUnits = rectWidth / scale;
        const rectHeightImageUnits = rectHeight / scale;

        // Set canvas size equivalent to interpolated rectangle size
        canvas.width = rectWidthImgUnits;
        canvas.height = rectHeightImageUnits;

        ctx.drawImage(image,
            xImgUnits, yImgUnits,                       // Start CROPPING from (x_img_units, y_img_units).
            rectWidthImgUnits, rectHeightImageUnits,    // Crop interpolated rectangle
            0, 0,                                           // Place the result at 0, 0 in the canvas,
            rectWidthImgUnits, rectHeightImageUnits);   // Crop interpolated rectangle

        // Get base64 representation of cropped image
        const croppedBase64Image = canvas.toDataURL();

        // Now we are ready to send cropped image TO SERVER
        callback(croppedBase64Image);

        return croppedBase64Image;
    };
}

this draws a box to take the picture from (license plate for example)

the markup is terrible, stupid code plugin

yeah, I will try to copy all features :-), but if you can help me, I'll feel better

hey can you add me as a contributor? Ik have made some changes for the ios implementation on orientation. I can make a pr if you want, thanks

I just added you


WIP: base dask on fsspec

[ ] Tests added / passed
[ ] Passes black dask / flake8 dask

** do not merge **
To do:

many modules now just import things, and can be removed
install required fsspec
this required modifications in fsspec ( https://github.com/intake/filesystem_spec/pull/64 ), not yet merged or released
required very small change in s3fs (because we were previous mangling username/password to key/secret)
some thought should be given to caching of FS instances
probably knock-on effects outside the bytes subpackage.

On the plus side: lots of red in the +/-!

Side thought: You should write about this.  The message might be something like "We (I) have invested a lot of time building out the bytes handling in Dask in a nicely modular way that can be helpful to others.  We found that, surprisingly, it was helpful to others.  This includes Intake, X, Y, and Z (zarr, rapids, ...?).  We've now moved the last bits from Dask so that you too can use these systems without depending on Dask explicitly (though of course it's a very lightweight dependency).

@mrocklin : yep, eventually. I posted the code here more for backup and to show the dev group that this thing really would work.

Merger here requires mergers on other repos and possibly releases; but all tests pass locally now.

OK, so errors are due to two main things:

s3fs not having been released with fsspec
gzipfile et al being seekable with py37, but not giving "operation not supported" earlier

Merger here requires mergers on other repos and possibly releases; but all tests pass locally now.

Woot!

So it would be a good idea to make a decision now on read_* functions with compression. Should blocksize!=None be a straight exception? None of the compression engines support real random access normally (even if some can). Currently, random access is allowed and works on py37, but it is scanning through the file to find the right offset. That could be useful in some scenarios, but terrible in most.
If an early exception, I would probably put it in logical_size, since that's where the first scan would occur, to find the end of the uncompressed data.

Just a single failure on https://travis-ci.org/dask/dask/jobs/557843869#L1002 around compression with chunksize; but quite a few windows path errors I'll need to do some work on.

So it would be a good idea to make a decision now on read_* functions with compression. Should blocksize!=None be a straight exception? None of the compression engines support real random access normally (even if some can). Currently, random access is allowed and works on py37, but it is scanning through the file to find the right offset. That could be useful in some scenarios, but terrible in most.

When you say it like that, erring seems reasonable to me.  I haven't thought about this very deeply though.  cc'ing @jcrist who might have thoughts?

For read_csv we already warn and then switch to using blocksize=None:
https://github.com/dask/dask/blob/3eb2dc89c9a70dcb828e86d043e23b751ab0d0fd/dask/dataframe/io/csv.py#L380-L387
Seems reasonable to me to convert this to an error everywhere.

OK, actually passes Travis for py37 (linting not yet done).
Now back to windows paths...

green on windows, only flake errors on py37 :)

py37: passing (with s3fs from master)
py36: failing s3 only (s3fs from release)
py35: failing s3 (s3fs from release) and something in kwargs to compression

Summary:

I recommend merging this.

Outstanding:

the test failure on appveyor is due to something with partd, which I'm pretty sure is unrelated
the appveyor and py37 tests use master versions, which currently are the same as released versions. This can be reverted, but wanted to be sure that's the consensus.

the test failure on appveyor is due to something with partd, which I'm pretty sure is unrelated

Most likely https://github.com/dask/dask/issues/5104

the appveyor and py37 tests use master versions, which currently are the same as released versions. This can be reverted, but wanted to be sure that's the consensus.

Could they master versions be moved to the nightly upstream build? I've almost got that passing, just one remaining pandas failure that I'll try to fix today.

Could they master versions be moved to the nightly upstream build?

Sure, I'm ok with that - then for this PR, should go back to released versions only in all builds.

PR#4995 now has these changes merged in, and all tests are passing.

Will merge this evening, unless there are objections.

Woo! Thanks for all your work on this @martindurant :)


Add a New Log Storage component

Description
This is a Log Storage component for a Multi Language System，such as Nodejs as GW and Java apply the services and so on. If need a middleware to format and store the info、debug or trace log across the different Language service, it's useful.
Now the component only supports the alicloud SLS. LogHub,LogShipper and ELK storage plat are in plain.
Issues
https://github.com/dapr/docs/issues/2592

Thanks for the contribution @RcXu !
This is not just a new component, but a new building block. Normally, before we can introduce new building blocks, we strongly suggest having a discussion in https://github.com/dapr/dapr/ and review this with other maintainers and especially STC members. Has any discussion taken place already?

A new building block cannot be created without discussion among the steering committee and maintainers.
Additionally the interface for the new building block must first be created in dapr/dapr.
Please rewrite this component as a Binding or State Store. If neither of those approaches work for you then this PR needs to be closed or abandoned.
As is, on behalf of @dapr/maintainers-components-contrib I do not approve.

Thanks for the contribution @RcXu !
This is not just a new component, but a new building block. Normally, before we can introduce new building blocks, we strongly suggest having a discussion in https://github.com/dapr/dapr/ and review this with other maintainers and especially STC members. Has any discussion taken place already?

Thks very much, I get this, I willl choice a  way to rewrite this component .

A new building block cannot be created without discussion among the steering committee and maintainers. Additionally the interface for the new building block must first be created in dapr/dapr.
Please rewrite this component as a Binding or State Store. If neither of those approaches work for you then this PR needs to be closed or abandoned.
As is, on behalf of @dapr/maintainers-components-contrib I do not approve.

Thks very mush,I get it, I will rewrite it.


recursiveSearch is using obj[key] causes TS error

Typescript does not like calling objects like this when the key is not specified to be a string. An expect error was added that needs to be removed.

Resolved in fcf2c0304821157baff69ae3765773dc64c07252


Changed default port

CMS port is now set to 3001 by default instead of 3000

In testing this pull request, I found that unfortunately Windows fails to understand PORT= as setting an environment variable, and instead fails to execute the start command. The default port was changed in the feature/official-cra merge through the use of a .env.development file instead, so this PR is now sadly redundant.


batch的问题

你好 感谢您的工作  当设置batch>1时 输出onnx依然是1x3x640x640请问怎么实现多batch

感谢反馈，将ultralytics/yolo/engine/exporter.py 中第165行注释掉即可

谢谢您的回复 我按照您说的注释后导出的onnx float32[8,3,640,640]  转为trt后在测试中单帧时间是减少的 但是batch=8视频测试感觉速度很慢 尽管显示的推理时间减少 ,请问这是什么原因
batch=1:
[02/09/2023-08:11:13] [I] preprocess time = 1.55475; infer time = 4.24176; postprocess time = 0.207648
[02/09/2023-08:11:13] [I] preprocess time = 1.56528; infer time = 4.70144; postprocess time = 0.446816
[02/09/2023-08:11:13] [I] preprocess time = 1.55267; infer time = 4.42013; postprocess time = 0.532928
[02/09/2023-08:11:13] [I] preprocess time = 1.55062; infer time = 4.35418; postprocess time = 0.318272
[02/09/2023-08:11:13] [I] preprocess time = 1.55472; infer time = 4.92086; postprocess time = 0.352256
[02/09/2023-08:11:13] [I] preprocess time = 1.54694; infer time = 4.4991; postprocess time = 0.202784
[02/09/2023-08:11:13] [I] preprocess time = 1.54602; infer time = 4.53914; postprocess time = 0.19776
[02/09/2023-08:11:13] [I] preprocess time = 1.55939; infer time = 4.22522; postprocess time = 0.19568
batch=8:
[02/09/2023-08:10:27] [I] preprocess time = 0.50718; infer time = 3.5722; postprocess time = 0.502048
[02/09/2023-08:10:28] [I] preprocess time = 0.508036; infer time = 3.58598; postprocess time = 0.509088
[02/09/2023-08:10:28] [I] preprocess time = 0.507736; infer time = 3.26151; postprocess time = 0.504344
[02/09/2023-08:10:28] [I] preprocess time = 0.507856; infer time = 3.25583; postprocess time = 0.505184
[02/09/2023-08:10:29] [I] preprocess time = 0.507544; infer time = 3.26184; postprocess time = 0.504592
[02/09/2023-08:10:29] [I] preprocess time = 0.508048; infer time = 3.25737; postprocess time = 0.502216
[02/09/2023-08:10:29] [I] preprocess time = 0.507568; infer time = 3.25582; postprocess time = 0.508636
[02/09/2023-08:10:30] [I] preprocess time = 0.507796; infer time = 3.24886; postprocess time = 0.5033
[02/09/2023-08:10:30] [I] preprocess time = 0.5073; infer time = 3.25684; postprocess time = 0.502984
[02/09/2023-08:10:30] [I] preprocess time = 0.550244; infer time = 3.49358; postprocess time = 0.506428
[02/09/2023-08:10:31] [I] preprocess time = 0.55456; infer time = 3.47292; postprocess time = 0.529296
[02/09/2023-08:10:31] [I] preprocess time = 0.48488; infer time = 3.0887; postprocess time = 0.504836
[02/09/2023-08:10:32] [I] preprocess time = 0.484532; infer time = 3.08768; postprocess time = 0.504032
[02/09/2023-08:10:32] [I] preprocess time = 0.485148; infer time = 3.09106; postprocess time = 0.50042
[02/09/2023-08:10:32] [I] preprocess time = 0.484668; infer time = 3.07816; postprocess time = 0.500792
[02/09/2023-08:10:33] [I] preprocess time = 0.484952; infer time = 3.08939; postprocess time = 0.499584

单进程中每处理8帧后再一起显示，所以感觉一卡一卡的，如果想要观感流畅，需要至少两个进程，一个进程负责推理，另一个负责显示图像，可参考https://github.com/LSH9832/edgeyolo中的batch_detect.py写一个多进程脚本

单进程中每处理8帧后再一起显示，所以感觉一卡一卡的，如果想要观感流畅，需要至少两个进程，一个进程负责推理，另一个负责显示图像，可参考https://github.com/LSH9832/edgeyolo中的batch_detect.py写一个多进程脚本
好的 感谢！！


Support minimum represented value in generated for known integer sizes

In my cddl: "d" => uint 0..100
Later in the generated types.h: uint32_t d;
Any way to limit the size in the generated structure? It seems wasteful to generate a uint32_t for something we know will not be decoded if it's not within size uint8_t.
I get that the decoder may try and use this memory and the default int type of cbor can use all 32bits. But, wouldn't this be rather easy to handle if the decoding step went to a temporary first and was stored into the smaller type if it met the conditions?

Perhaps even more egrigous in terms of memory usage is this for optional ? values
CDDL:    ?bool_value     :  "b" => bool,
Generated header:
struct header_bstr_bool_value bool_value;       // Structure that defines with a single bool member
uint_fast32_t bool_value_present;               // Bool used elsewhere, but an obvious case for one is uint32?

Hi, this has been changed for _present values. Integers may not be changed, at least not for a while, since it requires more changes to pull off.

Confirmed, there are bools for present. As to the others, I'm not in a hurry, it would just be a nice change to see uint8_t over uint32_t for something that can only store a few options.


[Doc Improvement][Update deep link to apps for mobile]

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Publish this library to jcenter

More info

https://reflectoring.io/bintray-jcenter-maven-central/
https://brightinventions.pl/blog/how-to-publish-a-library-to-a-maven-repository

Steps

Go to bintray https://bintray.com/nazmulidris/maven/color-console and click the button to "Add to JCenter"
In build.gradle replace the following

maven {
  url  "https://dl.bintray.com/nazmulidris/maven"
}

with
jcenter()


Get rid of reference to BufferImpl.EMPTY and dependency on embulk-core

Those classes have been directly accessing embulk-core's internal BufferImpl, but they should not access it as an external library.
Instead of BufferImpl.EMPTY, it implements its own "empty Buffer" by itself.

Thanks!


Error while running the code

C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py:1915: UserWarning: Model.fit_generator is deprecated and will be removed in a future version. Please use Model.fit, which supports generators.
warnings.warn('Model.fit_generator is deprecated and '
Traceback (most recent call last):
File "C:\Users\Ganesh\Desktop\FaceMask\FaceMaskDetector\facemask.py", line 58, in
model_saved=model.fit_generator(
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py", line 1918, in fit_generator
return self.fit(
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py", line 1108, in fit
data_handler = data_adapter.get_data_handler(
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\data_adapter.py", line 1348, in get_data_handler
return DataHandler(*args, **kwargs)
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\data_adapter.py", line 1138, in init
self._adapter = adapter_cls(
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\data_adapter.py", line 916, in init
super(KerasSequenceAdapter, self).init(
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\data_adapter.py", line 793, in init
peek, x = self._peek_and_restore(x)
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\data_adapter.py", line 927, in _peek_and_restore
return x[0], x
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras_preprocessing\image\iterator.py", line 65, in getitem
return self._get_batches_of_transformed_samples(index_array)
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras_preprocessing\image\iterator.py", line 231, in _get_batches_of_transformed_samples
x = img_to_array(img, data_format=self.data_format)
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\keras_preprocessing\image\utils.py", line 309, in img_to_array
x = np.asarray(img, dtype=dtype)
File "C:\Users\Ganesh\AppData\Local\Programs\Python\Python39\lib\site-packages\numpy\core_asarray.py", line 83, in asarray
return array(a, dtype, copy=False, order=order)
TypeError: array() takes 1 positional argument but 2 were given

same error here

Use Model.fit, which supports generators.


black leaves extra whitespace in my rendered documentation

Following:

#1830

See also https://til.simonwillison.net/sphinx/literalinclude-with-markers
https://docs.datasette.io/en/latest/testing_plugins.html#using-datasette-client-in-tests looks like this:

That's because I ran black and it insisted on adding extra whitespace like this:
https://github.com/simonw/datasette/blob/0f63cb83ed31753a9bd9ec5cc71de16906767337/tests/test_docs.py#L106-L141

I can use # fmt: off to tell Black not to format that part of the file.

That fixed it:
https://docs.datasette.io/en/latest/testing_plugins.html#using-datasette-client-in-tests