First Batch of P6 Consumes and Items

https://www.wowhead.com/classic/item=233985/the-fumigator
https://www.wowhead.com/classic/item=233995/scroll-wrath-of-the-swarm
https://www.wowhead.com/classic/item=233967/elixir-of-the-honey-badger
https://www.wowhead.com/classic/item=233962/flask-of-madness
https://www.wowhead.com/classic/item=234462/earthstrike
https://www.wowhead.com/classic/item=233627/jom-gabbar
https://www.wowhead.com/classic/item=233966/flask-of-unyielding-sorrow
https://www.wowhead.com/classic/item=233964/flask-of-ancient-knowledge
https://www.wowhead.com/classic/item=233965/flask-of-the-old-gods
https://www.wowhead.com/classic/item=233968/elixir-of-the-mage-lord
https://www.wowhead.com/classic/item=233969/elixir-of-the-ironside
https://www.wowhead.com/classic/item=233986/obsidian-bomb#shared-cooldown

Earthstrike is missing its ranged AP


KeyError:'images' KeyError: Caught KeyError in DataLoader worker process 0.

[NanoDet][04-05 20:27:52]INFO:Setting up data...
creating index...
index created!
creating index...
index created!
[NanoDet][04-05 20:27:53]INFO:Creating model...
INFO:NanoDet:Creating model...
model size is  1.0x
init weights...
=> loading pretrained model https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth
Finish initialize NanoDet-Plus Head.
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
You are using a CUDA device ('NVIDIA GeForce RTX 3060 Laptop GPU') that has Tensor Cores. To properly utilize them, you should set torch.set_float32_matmul_precision('medium' | 'high') which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name      | Type        | Params
0 | model     | NanoDetPlus | 4.2 M
1 | avg_model | NanoDetPlus | 4.2 M
8.5 M     Trainable params
0         Non-trainable params
8.5 M     Total params
33.902    Total estimated model params size (MB)
[NanoDet][04-05 20:27:54]INFO:Weight Averaging is enabled
INFO:NanoDet:Weight Averaging is enabled
Epoch 0:   0%|                                                                                | 0/525 [00:00<?, ?it/s]Traceback (most recent call last):
File "tools/train.py", line 155, in
main(args)
File "tools/train.py", line 150, in main
trainer.fit(task, train_dataloader, val_dataloader, ckpt_path=model_resume_path)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 608, in fit
call._call_and_handle_interrupt(
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 38, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _fit_impl
self._run(model, ckpt_path=self.ckpt_path)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1103, in _run
results = self._run_stage()
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1182, in _run_stage
self._run_train()
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1205, in _run_train
self.fit_loop.run()
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
self.advance(*args, **kwargs)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/loops/fit_loop.py", line 267, in advance
self._outputs = self.epoch_loop.run(self._data_fetcher)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
self.advance(*args, **kwargs)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 187, in advance
batch = next(data_fetcher)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/utilities/fetching.py", line 184, in next
return self.fetching_function()
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/utilities/fetching.py", line 265, in fetching_function
self._fetch_next_batch(self.dataloader_iter)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/utilities/fetching.py", line 280, in _fetch_next_batch
batch = next(iterator)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/supporters.py", line 569, in next
return self.request_next_batch(self.loader_iters)
File "/home/rmsu233/.local/lib/python3.8/site-packages/pytorch_lightning/trainer/supporters.py", line 581, in request_next_batch
return apply_to_collection(loader_iters, Iterator, next)
File "/home/rmsu233/.local/lib/python3.8/site-packages/lightning_utilities/core/apply_func.py", line 51, in apply_to_collection
return function(data, *args, **kwargs)
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 628, in next
data = self._next_data()
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1333, in _next_data
return self._process_data(data)
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1359, in _process_data
data.reraise()
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/_utils.py", line 543, in reraise
raise exception
KeyError: Caught KeyError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
data = fetcher.fetch(index)
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/rmsu233/.local/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/rmsu233/nanodet/nanodet/data/dataset/base.py", line 84, in getitem
data = self.get_train_data(idx)
File "/home/rmsu233/nanodet/nanodet/data/dataset/coco.py", line 147, in get_train_data
meta = self.pipeline(self, meta, input_size)
File "/home/rmsu233/nanodet/nanodet/data/transform/pipeline.py", line 57, in call
meta = self.shape_transform(meta, dst_shape=dst_shape)
File "/home/rmsu233/nanodet/nanodet/data/transform/warp.py", line 308, in call
raw_img = meta_data["images"]
KeyError: 'images'
Epoch 0:   0%|          | 0/525 [00:01<?, ?it/s]

我修改了config/nanodet_custom_xml_dataset.yml文件下的class_name和num_class
以及train&&val: /img_path /ann_path
出现了上述报错


🚀 Feature:

🔖 Feature description
Currently, the copyright year in the footer of the backstage website is hardcoded, requiring manual updates each year. To improve maintainability and ensure the copyright year automatically updates, we should implement a dynamic solution.
🎤 Context
Replace the hardcoded year in the footer with JavaScript's Date object to automatically retrieve the current year.
Utilize JavaScript’s Date object to automatically retrieve the current year.
Update the copyright text to display the dynamic year, ensuring it stays up to date without manual intervention.
✌ Possible Implementation
Identify the section of code in the footer responsible for displaying the copyright year.
Replace the hardcoded year with JavaScript code to fetch and display the current year dynamically.
Test the changes locally to ensure they function as expected.
👀 Have you spent some time to check if this feature request has been raised before?

[X] I checked and didn't find similar issue

🏢 Have you read the Code of Conduct?

[X] I have read the Code of Conduct

Are you willing to submit PR?
Yes I am willing to submit a PR!

https://nexb.com/do-you-really-need-to-update-the-copyright-each-new-year/#:~:text=No%2C but a copyright statement,in their project's copyright notices.

I think we'll close this; we don't really need or want to update the year.


feat(plugins/plugins-tutorials): getting started shouldn't focus on A…

…pache Composer
also fixes rendering bugs e.g. with font zooming
Fixes #1127

oops, really Fixes #1133


Did you try with the latest?  Show us SHA1 hash value of the top commit of your mruby.

I decode base64 and got the script. I could not reproduce the problem on the latest.
FYI, the program can be reformed to
module Rs
  class Rsclass
    def nil.m
      nil.m
    end
    nil.m
  end
end

which causes infinite recursion, and the latest detect the stack overflow.


Harden requirements for taint

This PR raises the number of NACKs required to consider an envoy Pod as failing to 5.  This was problematic when running a single pod setup, where a single failure would cause a revision to get tainted.
The change also has the side effect of making the taint process much slower, due to the fact that we now must wait for 5 failures and there's an exponential backoff mechanism in place when failures occur. To improve this a bit I have reduced the periodic reconcile of EnvoyConfigRevisions to 30 seconds.
/kind bug
/priority important-soon
/assign
/ok-to-test

/lgtm

/approve


team_type update fails with 2.1.9

I reported a similar issue in #444. It looks like the Go library update did not fix the issue completely. The API call now throws a 404 instead of the 400 reported previously.
An execution plan has been generated and is shown below.
Resource actions are indicated with the following symbols:
  ~ update in-place

...

  ~ resource "aiven_account_team_project" "binding" {
        account_id   = "************"
        id           = "********/*********/example-project"
        project_name = "example-project"
        team_id      = "****************"
      ~ team_type    = "developer" -> "operator"
    }

Plan: 0 to add, 1 to change, 0 to destroy.

Do you want to perform these actions?
  Terraform will perform the actions described above.
  Only 'yes' will be accepted to approve.

  Enter a value: yes

...

Error: 404: {"errors":[{"message":"Team does not exist","status":404}],"message":"Team does not exist"} -

Similar to some extend, but it seems to be a different one, the one reported in issue 444 was related to the inability to update the Account Team Project because of a field in the HTTP request that shouldn't be there.
This one is an Aiven API response, saying that team_id belongs to an Account Team which no longer exists. Can you please check if that?

I tested this again and I can verify the team is indeed there. What I do notice is that the change operation does indeed update the team_type.
I guess that leaves two possibilities, the update call partially applies or the returned read call is failing.

That is interesting. Can you please run terraform refresh? This should trigger the read call to validate this assumption?

A straight refresh works.

Without seeing the TF code and knowing actual account details, it is hard to understand what is happening here. As an experiment, can you please try to remove the aiven_account_team_project from the state or actually remove it temporarily and import/recreate it?
If you'll get a similar error after that, please contact our customer support and provide logs and/or terraform code snippet that we can use to get to the bottom of this issue.

Here is the simplest repo case I could get to:
terraform {
  required_providers {
    aiven = {
      source = "aiven/aiven"
    }
  }
}

resource "random_id" "random_postfix" {
  byte_length = 3
}

resource "aiven_account" "account1" {
  name = "test-account-${random_id.random_postfix.hex}"
}

resource "aiven_project" "project" {
  project    = "my-test-project-${random_id.random_postfix.hex}"
  account_id = aiven_account.account1.account_id
}

resource "aiven_account_team" "team" {
  account_id = aiven_account.account1.account_id
  name       = "test-team"
}

resource "aiven_account_team_project" "binding" {
  account_id   = aiven_account.account1.account_id
  team_id      = aiven_account_team.team.team_id
  project_name = aiven_project.project.project
  # team_type    = "developer"
  team_type = "read_only"
}

Once you do the first apply, comment out the read_only team type and un-comment the developer team_type. Re-apply and you should see the issue triggered.
$ terraform apply

An execution plan has been generated and is shown below.
Resource actions are indicated with the following symbols:
  + create

Terraform will perform the following actions:

  # aiven_account.account1 will be created
  + resource "aiven_account" "account1" {
      + account_id    = (known after apply)
      + create_time   = (known after apply)
      + id            = (known after apply)
      + name          = (known after apply)
      + owner_team_id = (known after apply)
      + tenant_id     = (known after apply)
      + update_time   = (known after apply)
    }

  # aiven_account_team.team will be created
  + resource "aiven_account_team" "team" {
      + account_id  = (known after apply)
      + create_time = (known after apply)
      + id          = (known after apply)
      + name        = "test-team"
      + team_id     = (known after apply)
      + update_time = (known after apply)
    }

  # aiven_account_team_project.binding will be created
  + resource "aiven_account_team_project" "binding" {
      + account_id   = (known after apply)
      + id           = (known after apply)
      + project_name = (known after apply)
      + team_id      = (known after apply)
      + team_type    = "developer"
    }

  # aiven_project.project will be created
  + resource "aiven_project" "project" {
      + account_id        = (known after apply)
      + available_credits = (known after apply)
      + ca_cert           = (sensitive value)
      + country           = (known after apply)
      + estimated_balance = (known after apply)
      + id                = (known after apply)
      + payment_method    = (known after apply)
      + project           = (known after apply)
    }

  # random_id.random_postfix will be created
  + resource "random_id" "random_postfix" {
      + b64_std     = (known after apply)
      + b64_url     = (known after apply)
      + byte_length = 3
      + dec         = (known after apply)
      + hex         = (known after apply)
      + id          = (known after apply)
    }

Plan: 5 to add, 0 to change, 0 to destroy.

Do you want to perform these actions?
  Terraform will perform the actions described above.
  Only 'yes' will be accepted to approve.

   Resources: 5 added, 0 changed, 0 destroyed.

$ terraform apply
random_id.random_postfix: Refreshing state... [id=rK61]
aiven_account.account1: Refreshing state... [id=a31d41f49f79]
aiven_account_team.team: Refreshing state... [id=a31d41f49f79/at31d41fedd55]
aiven_project.project: Refreshing state... [id=my-test-project-acaeb5]
aiven_account_team_project.binding: Refreshing state... [id=a31d41f49f79/at31d41fedd55/my-test-project-acaeb5]

An execution plan has been generated and is shown below.
Resource actions are indicated with the following symbols:
  ~ update in-place

Terraform will perform the following actions:

  # aiven_account_team_project.binding will be updated in-place
  ~ resource "aiven_account_team_project" "binding" {
        id           = "a31d41f49f79/at31d41fedd55/my-test-project-acaeb5"
      ~ team_type    = "developer" -> "read_only"
        # (3 unchanged attributes hidden)
    }

Plan: 0 to add, 1 to change, 0 to destroy.

Do you want to perform these actions?
  Terraform will perform the actions described above.
  Only 'yes' will be accepted to approve.

  Enter a value: yes

aiven_account_team_project.binding: Modifying... [id=a31d41f49f79/at31d41fedd55/my-test-project-acaeb5]

Error: 404: {"errors":[{"message":"Team does not exist","status":404}],"message":"Team does not exist"} -

Thanks for this example! I was able to reproduce this issue, and it was as you suggested in the reading logic after the update operation. It was just a typo, and we were using the wrong function for reading.
I will release this ASAP when it is going to be in the master.


GEODE-6571 Remove unneccessary list of region shortcuts

Thank you for submitting a contribution to Apache Geode.
In order to streamline the review of the contribution we ask you
to ensure the following steps have been taken:
For all changes:

[x] Is there a JIRA ticket associated with this PR? Is it referenced in the commit message?

[x] Has your PR been rebased against the latest commit within the target branch (typically develop)?

[x] Is your initial contribution a single, squashed commit?

[x] Does gradlew build run cleanly?

[ ] Have you written or updated unit tests to verify your changes?

[ ] If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?

Note:
Please ensure that once the PR is submitted, check Concourse for build issues and
submit an update to your PR as soon as possible. If you need help, please send an
email to<EMAIL_ADDRESS>

Great work, Mario - you addressed the JIRA ticket exactly as intended.
On review, I found that as a reader, I wanted to see the link to the quick reference table on the content page, not in just the left-hand navigation pane, so I went ahead and reinstated that link.
Thank you for your contribution.

Yes I agree, it is a much better with this link on content page.
Thank you all for approving changes. :)


sorting only specific filters

Is it possible?
Example: the Admin filter would show the cards in the order they are in on the page but the Faculty filter would show the cards in alphabetical order.
Thanks in advance!

Yes this is possible.
Control buttons may have both data-sort and data-filter attributes present.
This is the equivalent of using the 'multimix()' API method.

That's what I thought but adding data-sort to my filter links seems to be breaking it :(
https://md.nova.edu/directory/index.html
Can you have a look and tell me where I'm going wrong please?
Thanks in advance!

Hi, I've taken a look at your page and the problem is caused by your markup structure.
Within your mixitup container, you have a series of cards with the class mix on them. These are your "targets", which is correct.
However, within each card, you have another "panel" element which also has the class mix on it. MixItUp is indexing both sets of elements (the targets, and their children) as targets, and when it iterates through the "panels", it can't find the data-lname attribute, and the error is thrown.
You should be able to just remove the mix class from the inner elements and that will fix it.

so... yeah that was it lol
I did that bc I had an issue with match height script I was using but it's fixed now as well...
thanks so much!


AttributeError: no module named 'open_clip', 'torchsde' and type object 'BasicTransformerBlock' has no attribute 'ATTENTION_MODES'

For the previous month, I used the copy of your fast-stable-diffusion webui (the version of October 16th, 2022) from AUTOMATIC1111 without errors. But after AUTOMATIC1111 updated the webui, there was an error reported: no module named 'open_clip':
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 13, in
from modules import shared, devices, sd_samplers, upscaler, extensions, localization
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py", line 8, in
import k_diffusion.sampling
File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/init.py", line 1, in
from . import augmentation, config, evaluation, external, gns, layers, models, sampling, utils
File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 6, in
from . import sampling, utils
File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/sampling.py", line 7, in
import torchsde
ModuleNotFoundError: No module named 'torchsde'.
(Previously, the error reports "no module named 'open_clip'".)
Then I tried to use the newest version of your WebUI. I found that it copy the stable diffusion file to a new file called "stablediffusion" rather than "stable-diffusion", which is understandable since I found that the stable diffusion file is copied from stability-AI rather than CompVis in the previous version. However, when I tried to start stable diffusion, another error reports:
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 13, in
from modules import shared, devices, sd_samplers, upscaler, extensions, localization
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py", line 11, in
from modules import prompt_parser, devices, processing, images
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 15, in
import modules.sd_hijack
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack.py", line 31, in
ldm.modules.attention.BasicTransformerBlock.ATTENTION_MODES["softmax-xformers"] = ldm.modules.attention.CrossAttention
AttributeError: type object 'BasicTransformerBlock' has no attribute 'ATTENTION_MODES'
Hope that the issue may be solved as soon as possible.

I can confirm seeing the same issue on both fronts, and I note the change in directory name as well... I'm tempted to rename the new directory but there's a LOT of code associated with the folder name and I don't want to break things further.

You need to remove the folder SD in your gdrive and do a clean run.

Hi, I deleted the SD folder and did a clean run but now get
LatentDiffusion: Running in v-prediction mode
DiffusionWrapper has 865.91 M params.
Downloading: 100% 3.94G/3.94G [01:30<00:00, 43.7MB/s]
^C
As someone else reported. I am using paid for Collab. Any ideas much appreciated :-)

set the GPU to standard (to save compute units) and set the VM shape to High-RAM

set the GPU to standard (to save compute units) and set the VM shape to High-RAM

Apologies but Could you advise how/where to do these ?

Sure, in Colab : Runtime-> Change runtime type -> Runtime shape -> High-RAM

You need to remove the folder SD in your gdrive and do a clean run.

Yup, that works! Reminder to readers to copy out your "outputs" directory if you want to save previous results.

Hi, I deleted the previous sd file, having backed up my images, models, hypernets and embeddings, and did a clean run.
Then when I tried to start stable diffusion, regardless of whether the V2 option is checked, there is an error as below:
No module 'xformers'. Proceeding without it.
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
Downloading: 100% 939k/939k [00:01<00:00, 720kB/s]
Downloading: 100% 512k/512k [00:01<00:00, 476kB/s]
Downloading: 100% 389/389 [00:00<00:00, 343kB/s]
Downloading: 100% 905/905 [00:00<00:00, 803kB/s]
Downloading: 100% 4.41k/4.41k [00:00<00:00, 3.65MB/s]
Downloading: 100% 1.59G/1.59G [00:27<00:00, 62.2MB/s]
Loading weights [e3b0c442] from /content/gdrive/MyDrive/Stable-diffusion/model.ckpt
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 216, in
webui()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 156, in webui
initialize()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 86, in initialize
modules.sd_models.load_model()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 261, in load_model
load_model_weights(sd_model, checkpoint_info)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 191, in load_model_weights
sd = read_state_dict(checkpoint_file)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 168, in read_state_dict
pl_sd = torch.load(checkpoint_file, map_location=map_location or shared.weight_load_location)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/safe.py", line 102, in load
return load_with_extra(filename, *args, **kwargs)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/safe.py", line 147, in load_with_extra
return unsafe_torch_load(filename, *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 713, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 920, in _legacy_load
magic_number = pickle_module.load(f, **pickle_load_args)
_pickle.UnpicklingError: invalid load key, '<'.
The first thing deserves to notice is that xformer is not installed in the previous block. The second is the issue "_pickle.UnpicklingError: invalid load key, '<'."

use the latest colab  https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb and do a clean run

I used the latest colab. I found that the file works out when I specify the V2 model. The problem comes out when I try to load a file with quite a few models. I will check whether it is the issue of one or some of my ckpt files.

I tried to load the ckpts individually and all of them worked out successfully, but when I put them into a file and tried to load the whole file the same error was reported.

I did a clear run with the newest colab version. Everything works well except that when I check V2 option and load the folder including both the V2 checkpoint file and other models, the error as below shows up.
No module 'xformers'. Proceeding without it.
LatentDiffusion: Running in v-prediction mode
DiffusionWrapper has 865.91 M params.
Loading weights [ddc6edf2] from /content/gdrive/MyDrive/Stable-diffusion/mdjrny-v4.ckpt
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 216, in
webui()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 156, in webui
initialize()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 86, in initialize
modules.sd_models.load_model()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 261, in load_model
load_model_weights(sd_model, checkpoint_info)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 192, in load_model_weights
model.load_state_dict(sd, strict=False)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1605, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for LatentDiffusion:
size mismatch for model.diffusion_model.input_blocks.1.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.1.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.2.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.2.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.middle_block.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.middle_block.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.6.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.6.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.9.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.9.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.10.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.10.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.11.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.11.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
Since I think that it can be very understandable, I don't think that it is a bug.


Disqus appears to be not working.

Hi.
Like the title says, I can't get disqus to work on my blog.
The site source is here: https://github.com/Skarlso/blogsource
The config is here: https://github.com/Skarlso/blogsource/blob/master/config.toml
I have disqus handle set and there appears to be nothing else required for it to work?
Yet on the site, there is no error, it just simply doesn't get loaded at all.
Cheers.

Hi, @Skarlso
This theme has two templates for contents. For contents under /content/posts folder, the "/layouts/posts" template will be used, it will display date, tags and comments (if your disqusShortname is set in the config). Else will use the default template that comments is disabled by default, but you can add comments: true to the front matter to enable comments.
However, you can add type: posts to the front matter to make any post use the "posts" template.

Hi, @Track3!
Yay, that worked! comments = true in front matter. :))) Thanks!


Mosaic creation broken after the last update

Creating mosaic now returns an error
Hash: 366E0ABBF745B4BE36ADAA04487A519B5D9584BF677ADBC16F9AF7754426F91B
Error code: Failure_Mosaic_Invalid_Name
Deadline: 2018-11-29 14:13:38.615

#100


Use jphp as dependency package?

Hi,
is it possible to use jhp as depency? I am working on a php to groovy transpiler and having a library that executes builtin php functions would be very handy. For instance, I would import your json stuff and magically calling json_encode() works (being executed in Java?).
Or did I get things completely wrong?
Thanks
Daniel

Yes, use maven http://j-php.net/download/ dependencies, for json is jphp-json-ext, for zend std is jphp-zend-ext. jphp-runtime also has basic functions from php.
For instance, the string php functions can be used via this class: https://github.com/jphp-compiler/jphp/blob/master/jphp-zend-ext/src/main/java/org/develnext/jphp/zend/ext/standard/StringFunctions.java


{AKS} Fix unexpected prompt for az aks command

Related command

az aks update
Description

Should check whether assign_identity  is None or not before comparation. Otherwise in most cases assign_identity  is None and will prompt for user's input incorrectly.
Testing Guide

History Notes

[Component Name 1] BREAKING CHANGE: az command a: Make some customer-facing breaking change
[Component Name 2] az command b: Add some customer-facing feature

This checklist is used to make sure that common guidelines for a pull request are followed.

[ ] The PR title and description has followed the guideline in Submitting Pull Requests.

[ ] I adhere to the Command Guidelines.

[ ] I adhere to the Error Handling Guidelines.

AKS

Queued live test pipeline to verify the change.


⚠ Hartman Foundation has degraded performance

In 38bf5fe, Hartman Foundation (https://gordonhartman.com/) experienced degraded performance:

HTTP code: 200
Response time: 2743 ms

Resolved: Hartman Foundation performance has improved in c2543d5.

Resolved: Hartman Foundation performance has improved in c2543d5.


Add Option to round path edges

It would be really cool to round the stroke edges.
Here is an example !

Ufffffff sexy Idea <3

I'm looking forward to see this in the next version !

Thanks for opening the issue, this should be relatively straightforward to do by adding a StrokeCap.round when painting the segments, and exposing an option to users to set it.
I'll try to get it done in the next few days, should have some downtime coming up, meanwhile PRs welcome [but please mention if you're picking it up!]

Wow :O great stuff going on here!

This is now available in version 0.0.3 :tada:
You can pass in an edgeStyle property to your chart and set it to SegmentEdgeStyle.round for the rounded caps.
I've added some documentation it in this section of the readme: https://github.com/xqwzts/flutter_circular_chart#segment-edge-style
Thanks again for bringing up the feature @JulianBissekkou , I might not have the time to work on them immediately, but opening issues is really the best way to bring feature requests and bug reports to my attention.


Update microsoft-azure-storage-explorer to 0.9.2

After making all changes to the cask:

[X] brew cask audit --download {{cask_file}} is error-free.
[X] brew cask style --fix {{cask_file}} reports no offenses.
[X] The commit message includes the cask’s name and version.

Closing in favour of https://github.com/caskroom/homebrew-cask/pull/40284
This should remain as latest and no_check https://github.com/caskroom/homebrew-cask/pull/21886


Support for aws s3 provider

First, great tool and thank you so much for putting it open-source!
I would like to extend VoTT so it can be used with an aws s3 provider. I guess the main thing it would require is to add a definition of a new provider following the example of https://github.com/microsoft/VoTT/blob/master/src/providers/storage/azureBlobStorage.ts.
Am I right? I would gladly help on this even if I'm not really familiar with aws APIs.
Cheers!

Hello! You are correct, if you make an S3 provider using the azure blob provider as an example an open a PR following the contribution guidelines here, we would love to review it and add it to the tool

Any update on this?

Got a busy scheduler and can't look into the development myself, but I'm pretty much interested in having this feature and also helping a bit with the development.
Cheers!

Do you know any image annotator for s3 ?  @Mathijs003  @wilderrodrigues  @PIC123  @pierre-rouanet

Do you know any image annotator for s3 ? @Mathijs003 @wilderrodrigues @PIC123 @pierre-rouanet

You can tray SageMaker groundtruth

Hi! I need this feature as well. I can help with adding this to the tool. Will try to file this as soon as I can.

Hi! I need this feature as well. I can help with adding this to the tool. Will try to file this as soon as I can.

Hi, I also need that, I will be happy to work on this.


README instructs installation from GitHub not Julia Registry

Describe the bug
The README instructs users to install Genie using the GitHub URL, rather than the julia registry. I see that there is a Genie release for the julia registry. When I first read the README, I assumed Genie was still a prototype and that it wasn't registered. Adding instructions for
Pkg.add("Genie")

would give a bit of extra confidence in the solidity of the package.

Hmmm - is Genie registered?! Can you provide more details?
I submitted a PR to the registry a long time ago but it wasn't merged and I didn't follow up anymore. Maybe somebody merged it and I wasn't aware...

Oh, looks like it isn't. I saw your GitHub release and thought it corresponded to a version in the Registry.
The mechanism for all of this changed recently. I stumbled my way through it to get my packages on the new system last week. Using these TagBot and Registrator GitHub bots made it fairly easy.
https://discourse.julialang.org/t/switching-package-registration-systems-soon/22677/20
https://discourse.julialang.org/t/ann-tagbot-creates-tags-and-releases-for-your-julia-packages-when-theyre-registered/23084
There is reasonable documentation, but it is a bit scattered and hard to find. The above community discussions were very helpful.

Thanks - the plan was to register when reaching v1. However, I can't see any downside to registering sooner (now?). If it's that smooth with the new tools, it's definitely worth a try 👍

Done


[SPARK-46538][ML] Fix the ambiguous column reference issue in ALSModel.transform

What changes were proposed in this pull request?
the column references  in ALSModel.transform maybe ambiguous in some case
Why are the changes needed?
to fix a bug
before this fix, the test fails with:
JVM stacktrace:
org.apache.spark.sql.AnalysisException: [MISSING_ATTRIBUTES.RESOLVED_ATTRIBUTE_APPEAR_IN_OPERATION] Resolved attribute(s) "features", "features" missing from "user", "item", "id", "features", "id", "features" in operator !Project [user#60, item#63, UDF(features#50, features#54) AS prediction#94]. Attribute(s) with the same name appear in the operation: "features", "features".
Please check if the right attribute(s) are used. SQLSTATE: XX000;

and

pyspark.errors.exceptions.captured.AnalysisException: Column features#50, features#46 are ambiguous. It's probably because you joined several Datasets together, and some of these Datasets are the same. This column points to one of the Datasets but Spark is unable to figure out which one. Please alias the Datasets with different names via `Dataset.as` before joining them, and specify the column using qualified name, e.g. `df.as("a").join(df.as("b"), $"a.id" > $"b.id")`. You can also set spark.sql.analyzer.failAmbiguousSelfJoin to false to disable this check.

JVM stacktrace:
org.apache.spark.sql.AnalysisException: Column features#50, features#46 are ambiguous. It's probably because you joined several Datasets together, and some of these Datasets are the same. This column points to one of the Datasets but Spark is unable to figure out which one. Please alias the Datasets with different names via `Dataset.as` before joining them, and specify the column using qualified name, e.g. `df.as("a").join(df.as("b"), $"a.id" > $"b.id")`. You can also set spark.sql.analyzer.failAmbiguousSelfJoin to false to disable this check.

Does this PR introduce any user-facing change?
yes, bug fix
How was this patch tested?
added ut
Was this patch authored or co-authored using generative AI tooling?
no

cc @cloud-fan and @WeichenXu123

merged to master


Move exception handling to main.cpp

Actually the best solution we may have at the moment is to catch ALL the exceptions in main.cpp.
@inedostoev Could you please add int main() as an exception (what a pun) to your parser if possible (or, at least, main.cpp)?

Actually I'm starting to think that having C++'s exceptions is not so bad...

I can add file exeptions, for example main.cpp or file with try/catch


Ability to use VSCode to find a type a variable

Please add ability use VSCode to find a type a variable
Slimier to this https://twitter.com/DavidKPiano/status/1403500184290664461

When hover over a variable, we can include the type name as well. Hence this will be consistent with the other constructs

Please consider the following case; it that correctly shows (int|boolen[])? it'll be great.
eg:
import ballerina/io;

public function main() {
    var x = f();
    if !(x is string) {
        io:println(x); // what is the type of x here
    }
}

public function f() returns int|string|boolean[]?{
    return 2;
}

@manuranga @nadeeshaan
import ballerina/module1;

# Description for module variable with init
final isolated configurable int modVar1 = 12;  //hover at modVar1

For the above scenario, What would be the suitable expected hover result? int or Description for module variable with init (which is the result we already suggest)


Github actions are shown at gitea actions when the reposity is a github mirror.

Description
if you mirror a repository from Github to Giteaand you have some Github actions. they yml files and some running history of Github actions are show inside the Gitea actions tab, I think it's weird.
Gitea Version
1.22 dev
Operating System
windows
How are you running Gitea?
local

I don't think we have migrated the history actions tasks log. Maybe it triggered the actions when migrating.

I don't think we have migrated the history actions tasks log. Maybe it triggered the actions when migrating.

I checked again, yes it's triggered, it's not migrated.

this is an example , a mirror repository of cache actions in local gitea casues actions to show up. whie the local repository has disabled actions.

This is weird. I noticed that there are some scheduled workflows in this repository. I guess some of the scheduled workflows might be running after the migration and before disabling Actions.
And I agree that we should disable Actions for mirror repositories by default (#30350)

I have same problem.

You can use the doctor command added in #32424 to disable "Actions" unit for mirrors.

Sorry, I think this hasn't been backported to v1.22.4 @Zettat123

It's ok. ;) I have my python script to patch this. ;)


Get QR code scanner working

[x] Create placeholder design (Complete: https://vax.codes/scan)
[x] Camera/webcam request
[x] Barcode scanning
[x] Signature verifying
[x] Results display
[x] Manual image upload
[x] Manual url entry

Done!


Support another Azure cloud storage authentication using security principal

Is your feature request related to a problem? Please describe.
The current Label Studio Azure Cloud Storage connection only supports one form of authentication using  Shared Key authorization for blobs with AZURE_BLOB_ACCOUNT_NAME and AZURE_BLOB_ACCOUNT_KEY to specify the secret key for the storage account. However Azure has many more authentication methods

see https://learn.microsoft.com/en-us/azure/storage/common/authorize-data-access

Describe the solution you'd like
I'd like to have Microsoft Entra integration for authorizing requests to blob and use Azure role-based access control (Azure RBAC) security principal to access the cloud storage. This will require a few new different  parameters:

AZURE_CLIENT_ID
AZURE_CLIENT_SECRET
instead of AZURE_BLOB_ACCOUNT_KEY

Describe alternatives you've considered
I've tried the existing AZURE_BLOB_ACCOUNT_KEY, but this is not allowed at my current organization

@KonstantinKorotaev  @jombooth  @dredivaris  any thoughts? is this in your roadmap? thank you! :)

not on my roadmap :p

though I should note, I am not a part of HumanSignal and haven't touched this repo for upwards of half a year

@niklub  @robot-ci-heartex any thoughts?

@machov https://github.com/HumanSignal/label-studio/pull/5765 is this something that you are looking for?


Feature/add custom http header

Feature #313

@FelixBoers awesome thanks for the PR :)
I will take a look now!

@FelixBoers this is an awesome PR, thank you very much! Will merge now.

@TomPallister You're welcome. Thanks for sharing your framework!


Cargo.nix generation via cargo2nix is incredibly slow

I've got a 20k lines Cargo.lock and it takes ~1m to generate the corresponding Cargo.nix.
For something that's supposed to be re-generated every time the Cargo.lock is touched that's unacceptably slow.
During that time I can see the cargo2nix process at a high CPU load (~70% on average I think).
This gives me O(n²) vibes, something like, for each dependency we run a cargo API tool that itself does go through the entire Cargo.lock...

Is there such a thing?
Can it be fixed?

Thanks,

It can be fixed.  Open up the cargo source and check the metadata code.  It's output contains all of the necessary information.  Consider the feature logic busted.  It's going to get burned to the ground if a metadata style solution is used.  The template stuff will mostly be intact, but with extra support for platform specific dependencies that happen when deps depend on the target, such as with the Bevy crate.

Thank you for your quick answer. Good to know that it can be fixed.
I'd like to work on this but I'm not sure I understand what you mean.
Is there a comment in the code somewhere that explains the issue and/or what there is to do? Where is "the cargo source's metadata code's output"?
You seem to have plans for a "metadata style solution". Are these documented somewhere?
Thank you. 🙂

Plans are in #301 and possibly other linked issues.
Cargo already outputs the correct information in its metadata command.  Cargo2nix uses the cargo library and basically can access all the same information that the metadata command outputs via serde.  We need nix expressions as the output instead of the JSON.  I'm oversimplifying, but that's the gist.

#301 seems to be a PR about a large change in the nix code, and seems to have no comments on discussion on slowness in the rust code (which it is because of "cargo2nix process at a high CPU load") or plans for using metadata instead.
There is no issue linked to it.
Are you sure that's the right source?

Check issues tagged with high priority.  I'm certain everything you're talking about is somewhere in there.


fix: split file at 00:00:01 && update deps

Checklist

[ ] npm test passes
[ ] tests and/or benchmarks are included
[ ] documentation is changed or added
[ ] commit message follows commit guidelines

Affected core subsystem(s)

Description of change

https://github.com/eggjs/egg/issues/1616

Codecov Report

Merging #15 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master      #15   +/-   ##
=======================================
  Coverage   95.67%   95.67%
=======================================
  Files          12       12
  Lines         185      185
=======================================
  Hits          177      177
  Misses          8        8

Impacted Files
Coverage Δ

app/schedule/rotate_by_file.js
100% <ø> (ø)
:arrow_up:

Continue to review full report at Codecov.

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<EMAIL_ADDRESS>


More Unit Tests

At least every function with a return value needs to be tested.

Implemented & released at 3ccc67c


Optional sort on ask_choice

Hi,
I added a "sort" optional argument to ask_choice to be able to choose if you want to sort the list or not.
This is useful in case the list is already in an order you don't want to modify and that is messed up by any sorting (e.g. to simply keep it in order of insertion). The default value is set to True for backward compatibility.

Thanks for the patch :)


Timezone response

Hi there!
I'm looking how to set a response based on my timezone, like "Hi, we are out of hour, come later"

Thank you for filing this issue. This Github repo is used for issues with the Node.js Dialogflow client library . This issue appears to be a question about your specific implementation rather than a problem with the product or library. Unfortunately this is not a staffed support channel for Dialogflow. Here are some options you can consider: Google Cloud Platform support options are at https://cloud.google.com/support/. Community support is provided at https://stackoverflow.com/questions/tagged/dialogflow-es.
If you believe that part of this issue still needs to be addressed in this client library, then feel free to re-open this issue with more information.


Feature Request: Postgres support

Are there any plans to support additional DBMS for the self hosted version? I'm really in need of something exactly like envkey, but our entire internal infrastructure is built around Postgres. I don't really see myself setting up a dedicated MySQL instance just for envkey, and I'm sure others are in the same spot.
I think you're using knex already, but I don't know the codebase; would it be a lot of work to support other DBMS? Something like sqlite would also very convenient for small or encapsulated deployments.

Hi @Radiergummi, this is possible but it would take some doing as there is some MySQL-specific syntax in a few places and it would also take careful testing to be sure that there are no issues in terms of transactions/isolation/consistency (almost every action in EnvKey is transactional).
We could potentially do this for an enterprise customer, but otherwise I don't see us prioritizing it in the near term. That said, I'd be happy to offer support if a community member wanted to take it on.

@Radiergummi sure thing, I'll move it to a discussion for that purpose.


Why is RoundCodes only compatible with iOS 13.0+?

The README states that RoundCodes is written in Swift 5, requires Xcode 11 and is compatible with iOS 13.0+. Does it not work below iOS 13? Which APIs do you use that are not available on, say, iOS 11?

@mrousavy I think there are no APIs requiring iOS 13. Will add support for iOS 10.


Upgrade to ElasticStack 6.5

As part of a release cycle, upgrade to ELK 6.5 to include real-time log monitoring (console) and Canvas in Kibana for displays.

v3.5 will release with support for ELK 6.6.0


Webpack failing due to UnhandledPromiseRejectionWarning

Describe the bug
Webpack is exiting due to UnhandledPromiseRejectionWarning: TypeError: ManifestPlugin is not a constructor
UnhandledPromiseRejectionWarning: TypeError: ManifestPlugin is not a constructor
     at common (/var/www/project/buildchain/webpack-configs/manifest.config.js:12:13)
     at module.exports (/var/www/project/buildchain/webpack-configs/manifest.config.js:31:20)
     at getModernWebpackConfig (/var/www/project/buildchain/get-webpack-config.js:42:93)
     at names.forEach (/var/www/project/buildchain/get-webpack-config.js:52:52)
     at Array.forEach (<anonymous>)
     at webpackConfigs (/var/www/project/buildchain/get-webpack-config.js:52:11)
     at modernWebpackConfigs (/var/www/project/buildchain/get-webpack-config.js:76:44)
     at Object.<anonymous> (/var/www/project/buildchain/webpack.dev.js:11:18)
     at Module._compile (/var/www/project/buildchain/node_modules/v8-compile-cache/v8-compile-cache.js:192:30)
     at Object.Module._extensions..js (internal/modules/cjs/loader.js:827:10)
 (node:1553) UnhandledPromiseRejectionWarning: Unhandled promise rejection. This error originated either by throwing inside of an async function without a catch block, or by rejecting a promise which was not handled with .catch(). (rejection id: 2)
 (node:1553) [DEP0018] DeprecationWarning: Unhandled promise rejections are deprecated. In the future, promise rejections that are not handled will terminate the Node.js process with a non-zero exit code.

I happened to make this same fix before I noticed that you made this pull request. This fixed it for me too. Seems like it should have worked the original way but not sure why it didn't.

This is really strange... they must have just recently changed this, it worked as-is before. Thx for the PR, will get it merged in!

Fixed in https://github.com/nystudio107/craft/releases/tag/2.4.9

Really strange, when accepting the PR I get the same error @johnnyhawley and @cavellblood got without the PR. For me, it works without the error. Which webpack version are you using?

@iuscare probably you have an older version of the WebpackManifestPlugin installed... delete your package-lock.json and do a npm update


limbo: remove old ee_cert helper, SAN everywhere by default

This removes the old ee_cert helper entirely, replacing it with Builder.leaf_cert.
As part of that, our default generation behavior is now to include SAN(dns="example.com") by default. This should make it easier to integrate the test suite.
Needs a semi-fine-toothed review, since this was mostly machine refactoring.

Oh, the other missing piece to this is that we need to call expected_peer_name on the Builder everywhere. I think the most practical way to do this is to make example.com the default value.
I've pushed 8c9183f to deal with that. The tests run fine with this change. Feel free to revert if you had other ideas.

Oh, the other missing piece to this is that we need to call expected_peer_name on the Builder everywhere. I think the most practical way to do this is to make example.com the default value.

Yeah, that makes sense to me, now that we're setting the SAN to a default of example.com.


Upgrade Kotlin to 1.6.20

Closes #155

Draft until Kotlin 1.6.20 is officially release (currently in preview — 1.6.20-RC).

Duplicate of #162.


Error rather than stack overflow if using template in non-html namespace

Closes #472

@timfish thanks for the PR! Could you please include a unit test covering this change? This way we'll know what the change fixes and we won't regress on the fix when making future changes.

I've added a test, but it doesn't fail if I remove my check!

Well, the test doesn't fail, but the Chrome karma instance stack overflows as that was the behaviour before. Is that suitable?

@timfish Can you share a code sample that would trigger this error?

As per #472, any <template> within an <svg> caused a stackoverflow but with this change should throw a helpful exception instead.


moreblocks glasses losts their "connected" property

Default glass still has it on the server but the moreblocks glasses I tried don't (clean and super_glow).

Fixed https://github.com/MinetestForFun/server-minetestforfun/commit/ea4fc7f70c0b523faaa9f2dec7d6b79ed2aa4270

Need to comment our changes before the next update of this mod.

Fixed https://github.com/MinetestForFun/server-minetestforfun/commit/50170dcaff2c4da904719a53e990f3b0c16b2599


"Send" Button hangs

When I click the send button, it says "Sending..." and is grayed out indefinitely.
I'm just doing direct xrp->xrp trades.

Whoa, wrong project.


Remove cudatoolkit dev

Do we not need to specify script_env here?

Do we not need to specify script_env here?

Got it from your conversation on slack! Please ignore this comment.

@bnemanich - This PR is not created from your fork.


Automatic CI/CD

Following #8, it would be awesome to connect this repo to a CI/CD system so we can run tests for every mergeable pull request and automatically build the plugin package if the build succeeds.
Check GitHub Actions and Azure DevOps.

Done.

Created a azure-pipelines.yml file
Created a "deploy" script in project.json
Setup a pipeline in https://dev.azure.com/codicesoftware/vscode-plasticscm/_build
The pipeline is able to build and pass tests, and publish.

Pass tests for all new commits.
Publish only if the tests pass.
Publish only if a tagged (release) build.
Publish when the build runs on multiple agents (Windows, Linux, etc.)


installation script giving error on python

Hi, when I tried to run the install script provided in Readme, I got this warning first:
WARNING: pip is configured with locations that require TLS/SSL, however the ssl module in Python is not available.
And after 4 retries, I got this error:
Could not fetch URL https://pypi.org/simple/yt-dlp/: There was a problem confirming the ssl certificate: HTTPSConnectionPool(host='pypi.org', port=443): Max retries exceeded with url: /simple/yt-dlp/ (Caused by SSLError("Can't connect to HTTPS URL because the SSL module is not available.")) - skipping
Here is the script I ran:
curl https://raw.githubusercontent.com/Practicalbutterfly5/ytdl/main/installytdl | bash
So I am stuck here.

The error seems to be related to running older version of openssl. I am able to replicate the issue with a fresh install termux.
Simply upgrade your packages
apt update && apt upgrade -y

Indeed, it did tbe trick. It was exactly my situation. I had fresh installation of Termux. Thank you for your help.


Incorrect number of Unread messages

The number of Unread messages is incorrect.
There are 8 messages returned from the backend, but the frontend displays 17.

I can work on that.


Firebase Configuration/Authentication?

Hi Salman,
I am trying to build this project from source to run on my personal Firebase DB.  I have been unable to find references to how your Firebase DB is authenticated. Can you post or contact me with details of how you are authenticating the users?

My Firebase setup isn’t currently working. It’s only in the main repo because I forgot to use a feature branch.
It’s a commented out disaster and there’s no UI for creating an account. In the Firebase connector class there’s a section of commented out code which calls the function “createAccount”. That’ll create an account with an email and password. Currently the Firebase implantation is working from the server, it syncs all the conversations as they come in. I didn’t get around to modifying the android app yet. If you want to do this on your own Firebase instance you can just swap out the config file and watch the real time database.

Awesome, thanks for the help

If you’re familiar with Firebase I’d love some help with efficiency because I’ve literally just started using Firebase (without reading the docs lol) and got it working thanks to good design by google. The goal with using Firebase is that we can have the message database in constant real-time sync and so instead of requesting the whole database every time we fan just get tiny updates. That’ll make the app faster and more reliable and it’ll hopefully let us have SMS and iMessage in the app one day (pipe dream, don’t count on it)

I'm not a Firebase expert, but I'll make a pull request if I make any headway on making a secure connection.  I'm just trying to get it up and running at the moment :)

You’ll also need to uncomment this
https://github.com/shusain93/OSXMessageProxy/blob/master/MessageProxy/ViewController.swift#L45
In order for the Firebase portion to run. Like I said, it’s a commented out disaster :P


About the baseline of the dqn policy.

Could you mind give the baseline result(successful rate...) when used the dqn as the dialogue policy?
because when I run the original code with :
python run.py demo.json onenet_rule_dqn_template train
The final result is
100 episodes, -57.62 return, 1.00% success rate, 20.82 turns
Thus， I would like to know that whether my result is not correct,or I shoud change some parameters to get a better perfomance.
Thanks.

@liusih   please check this issue. https://github.com/ConvLab/ConvLab/issues/33

@liusih please check this issue. #33

Thanks for your replaying!
And by the way, would you mind providing some references you and your group have done to impove the dialogue sucessful rate on the MultiWoz dataset?

Hey
I am having the same issue and cannot seem to get to 30% success, this is using the rule_wdqn recommended setup from thread #33 . Do you have any recommendations on how I can get this to work?

@liusih  Please check https://arxiv.org/abs/2002.04793, and we will release the codebase of convlab-2 soon.

@liusih Please check https://arxiv.org/abs/2002.04793, and we will release the codebase of convlab-2 soon.

Thank you so much!

@jincli Thank you so much!


[HUDI-5514] Add in support for a keyless workflow

Change Logs
Adds a new KeyGenerator that does not require the user to specify any fields to use for the record key and instead deterministically generates a UUID based off a subset of fields in the incoming record.
Impact
No impact to existing users since this is a new KeyGenerator that users will need to opt into.
Risk level (write none, low medium or high below)
Low
Documentation Update
Describe any necessary documentation update if there is any new feature, config, or user-facing change

The config description must be updated if new configs are added or the default value of the configs are changed
Any new feature or user-facing change requires updating the Hudi website. Please create a Jira ticket, attach the
ticket number here and follow the instruction to make
changes to the website.

Contributor's checklist

[ ] Read through contributor's guide
[ ] Change Logs and Impact were stated clearly
[ ] Adequate tests were added if applicable
[ ] CI passed

CI failure due to unrelated flaky test.

will go ahead and land this for now. will get to consensus async.

Hi @the-other-tim-brown I'm interested in this functionality and have some questions, if I understand correctly the UUID will be the same for the same set of values in columns that it's based on?
So this generator can't be used for generating a surrogate key (a standard practice in data warehousing) as key is derived from data? My understanding of keyless model is that record key is a surrogate key that's globally unique.
I'm wondering if there's something that does not allow to create globally unique ids via the key generator interface (maybe virtual keys support)? At the same time in context of this PR, what's the place of UuidKeyGenerator? Could it be used to generate surrogate keys that are globally unique?

Yes it is correct that the keys are not guaranteed to be unique here. The issue with using a random UUID for us was that we were using deltastreamer and if the dag ever retriggered we were seeing data generated with new random UUIDs which could cause the records to be written to different filegroups causing an issue with duplicate/lost data due to some internals of how Hudi works. @nsivabalan had some similar thoughts around other approaches, can you chime in here?

hey @kazdy : we also jammed quite a bit before arriving at this solution. For eg, we did take a stab at generating unique Ids for every record here, but the problem as stated by Tim might not work for 7622. for eg, if we zoom into what happens for a commit in hudi is,
keyGen -> index look up -> upsert partitioner -> write files by executor (merge handle or create handle or append handle) -> may be write to metadata table -> complete commit.
Main crux here is that, in Upsert partitioner, we assign records to diff insert buckets based on record key hash. lets say upsert partitioned determined to add 3 new insert buckets and split 30k records among 3 insert bucket (file groups). This assignment is done using hashing of record key.
Given this, if due to failures, if keyGen stage was retriggered for a subset of spark partitions again, and when it reaches the upsert partitioner, it could get assigned to a diff insert bucket compared to its 1st attempt and so there are chances we will miss some records or add pack more records to one file group that what we intended.
Let me know if this makes sense. happy to jam to see if we can really pull this off by a row Id sort of generating rather than based on record payload.

Thanks for the explanation, so it seems like key generator must be deterministic and there's no way around it.
What I do with hudi datasets where I need a surrogate key is that I just generate a column with UUID using built-in spark uuid() function.  I think it's a valid way to do it :)
I guess using engine-specific uuid() function in keygen would not change anything.


VehicleWheel3D suspension travel 5m (metres)

Godot version
4.0
System information
Any
Issue description
This should be changed to something sensible like 0.5, the tooltip also suggests this in 4.0 thankfully but I think 5 entire metres is a bit of a stretch (ha)
When I was a non-docs-reading noob, this caused me many hours of pain because i put my wheels next to my car expecting them to work but the car would always sink flat into the wheels or too over
Steps to reproduce
Make a car visually ‘accurate’ with nodes, put the wheels in the right spot, don’t change any settings for anything, and then run the project to see your vehicle sink into the floor.
Minimal reproduction project
n/a

Thanks for the report, and sorry for your hours of pain. :rofl:


libgnome-games-support: support cross compilation

Description of changes

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

libgnome-games-support-aarch64-unknown-linux-gnu> valac -C --pkg gtk+-3.0 --target-glib ' 2.40.0' --pkg glib-2.0 --pkg gio-2.0 --pkg gee-0.8 --color=always --directory games/libgnome-games-support-1.so.3.0.4.p --basedir ../games --library gnome-games-support-1 --header games/libgnome-games-support.h --vapi ../libgnome-games-support-1.vapi --abi-stability --target-glib=2.44 ../games/config.vapi ../games/gridframe.vala ../games/scores/category.vala ../games/scores/context.vala ../games/scores/dialog.vala ../games/scores/directory-importer.vala ../games/scores/history-file-importer.vala ../games/scores/importer.vala ../games/scores/score.vala
libgnome-games-support-aarch64-unknown-linux-gnu> error: Package `gee-0.8' not found in specified Vala API directories or GObject-Introspection GIR directories

weird that it only fails when cross-compiling

libgnome-games-support-aarch64-unknown-linux-gnu> valac -C --pkg gtk+-3.0 --target-glib ' 2.40.0' --pkg glib-2.0 --pkg gio-2.0 --pkg gee-0.8 --color=always --directory games/libgnome-games-support-1.so.3.0.4.p --basedir ../games --library gnome-games-support-1 --header games/libgnome-games-support.h --vapi ../libgnome-games-support-1.vapi --abi-stability --target-glib=2.44 ../games/config.vapi ../games/gridframe.vala ../games/scores/category.vala ../games/scores/context.vala ../games/scores/dialog.vala ../games/scores/directory-importer.vala ../games/scores/history-file-importer.vala ../games/scores/importer.vala ../games/scores/score.vala
libgnome-games-support-aarch64-unknown-linux-gnu> error: Package `gee-0.8' not found in specified Vala API directories or GObject-Introspection GIR directories

weird that it only fails when cross-compiling

@Artturin grep nixpkgs for "TODO: the vala setuphook should look for vala filess in targetOffset instead of hostOffset". i never dug into this, but if those comments are true then it might explain this (speculating: native compilation was getting the package via vala, unsupported for cross; this patch causes the package to instead be located via gobject-introspection, which better handles the cross compilation case?).

@Artturin grep nixpkgs for "TODO: the vala setuphook should look for vala filess in targetOffset instead of hostOffset". i never dug into this, but if those comments are true then it might explain this (speculating: native compilation was getting the package via vala, unsupported for cross; this patch causes the package to instead be located via gobject-introspection, which better handles the cross compilation case?).

I see, blame shows that I added those lines and said I was going to do it in a separate PR https://github.com/NixOS/nixpkgs/pull/189397#discussion_r961923690


Is docker image for Apple silicon ARM64 available?

Is docker image for Apple silicon ARM64 available?

the image itself is Linux-64 only, but you can run it in Apple silicon under docker virtualization. Most of the cases run to the end. Some samples failed with 'illegal instructions' or 'segmentation fault', which might probably be fixed in the future version of docker on mac.

Please try using MacOS native docker.

There are already too many compatibility issues between Docker and Arm64 on the Internet. You can replace Docker with Servbay to deploy the development environment. Servbay is more professional on Mac.


tcp support

Add possibility to get Signalk stream over tcp.

Tcp support isn't much code, but I need to first extract the streaming logic (and implement it properly with subscriptions).

#67


LHN - User navigated on Workspaces listing page when tapped on the settings tab in bottom

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Version Number: 1.4.36-0
Reproducible in staging?: Y
Reproducible in production?: N
If this was caught during regression testing, add the test name, ID and link from TestRail:
Email or phone of affected tester (no customers<EMAIL_ADDRESS>Logs: https://stackoverflow.com/c/expensify/questions/4856
Expensify/Expensify Issue URL:
Issue reported by: Applause - Internal Team
Slack conversation:
Action Performed:
Precondition: user should be signed in and

Open app
Tap on settings tab in bottom

Expected Result:
User should be navigated on the Expeinsfy (app) settings page
Actual Result:
User navigated on Workspaces listing page
Workaround:
Unknown
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Android: Native
[ ] Android: mWeb Chrome
[x] iOS: IPAD
[ ] iOS: mWeb Safari
[ ] MacOS: Chrome / Safari
[ ] MacOS: Desktop

Screenshots/Videos
Add any screenshot/video evidence

https://github.com/Expensify/App/assets/78819774/24970b6d-ce86-44a3-a6e6-49265081f05b
View all open jobs on GitHub

Asked about this here: https://expensify.slack.com/archives/C03TQ48KC/p1707124667241939?thread_ts=1706899377.429909&cid=C03TQ48KC
I think it's related to the ideal nav changes

@lanitochka17 @kbecciv Is this ipad specific?

cc @adamgrzybowski

@mountiny In IOS, the settings page opens and then a list of workspaces.
Only IPAD
https://github.com/Expensify/App/assets/78819774/5a257283-7365-4954-85e6-56526af2cb44

PR is up

We need to pay $500 to @situchan for the review and testing here

@situchan Upwork Offer was sent: https://www.upwork.com/nx/wm/offer/101020283

@situchan payment sent and contract ended - thank you! 🎉


interactive bots: Create CommuteBot.

Automated message from Dropbox CLA bot
@540KJ, it looks like you've already signed the Dropbox CLA. Thanks!

Another PR for this was opened at #2738


BCryptDeriveKeyPBKDF2 not included

https://msdn.microsoft.com/en-us/library/windows/desktop/dd433795(v=vs.85).aspx

Sounds related to #365

the BCryptKeyDerivation function is included but not in the tests. BCryptDeriveKeyPBKDF2 implementation isn't included (but still appears in BCrypt.exports.txt).


Added randn operator for symbol API

Description
Missing randn operator for symbol API. Fixes #12755

@ChaiBapchya Can you check the lint failures on CI ?

@ChaiBapchya - Thanks for your contributions. Please add more detailed description from the template.
Why is it not named parameters? Why picking from kwargs? This might not be a good user experience for using the API. Thoughts?

@anirudhacharya - Can you please take a look at this PR?

Also if you are adding this operator in the symbol API, can you implement the operator in C++layer rather than implementing it only in python.

@ChaiBapchya ping!
Could you please take a look into the failing CI?

Closing, will reopen for 2.0


chore(docs): document the error types and variants in the errors module

Tracking issue: https://github.com/near/near-jsonrpc-client-rs/issues/51
Documented the error types and variants in the errors module.

Requested changes addressed ✅

I will merge all the doc PRs as is, and we will address any further issues in separate PRs going forward.


Unified test diff

Please have a look at the individual commit messages for the details.

@oss-review-toolkit/kotlin-devs here's something I wanted to do for a very long time: Make the diff to expected analyzer results more comprehensible and easier to apply without running the test locally. The PipFunTest deliberately breaks, but the diff to the expected result is now in a unified diff format that's compatible with git apply, which means you can simply copy the diff from the log to the clipboard, and then locally run wl-paste | git apply (on Wayland) to apply (but not commit) the patch required to update to new expected results.

You can see some example output at https://github.com/oss-review-toolkit/ort/actions/runs/4892317433/jobs/8733935809?pr=6971#step:6:1882.

PS: The last commit in this PR was already created via the unified diff / git apply.

@oss-review-toolkit/kotlin-devs here's something I wanted to do for a very long time: Make the diff to expected analyzer results more comprehensible and easier to apply without running the test locally. The PipFunTest deliberately breaks, but the diff to the expected result is now in a unified diff format that's compatible with git apply, which means you can simply copy the diff from the log to the clipboard, and then locally run wl-paste | col -bx | git apply (on Linux with Wayland) to apply (but not commit) the patch required to update to new expected results.

This is great! Could you document this somewhere, for example in https://github.com/oss-review-toolkit/ort#testing?

Could you document this somewhere, for example in https://github.com/oss-review-toolkit/ort#testing?

Here you go: https://github.com/oss-review-toolkit/ort/pull/6981


⚠ AsianCinema has degraded performance

In 4ea620e, AsianCinema ($ACM) experienced degraded performance:

HTTP code: 523
Response time: 2302 ms

Resolved: AsianCinema performance has improved in f6a44a3.


Regression in 1.7.0: Slowdown when refreshing window contents.

Open a Mulligan window
Add some elements (seems to be more likely to happen with like 20+ objects to rename)
Change the size of the columns or click the preview steps over and over. (Note you can just click one preview step, you don't have to alternate)
After a few seconds, notice it locks up for a second or two.

This may be the preview Caching, which is on the Editor's Update. I may need to make this async (which might fix #214, or really it might make it worse). But first I want to figure out why it's locking up. Garbage?

My first guess is this might be new Texture on update. We can probably reuse a pool of these instead, grow the pool if we need to.

Should be fixed in develop-1.7.0


Embed osm2streets in map_model

Currently the raw_map layer embeds osm2streets StreetNetwork, just adding A/B Street-specific stuff in addition (buildings, areas, transit routes, and things like crosswalks & modal filters that aren't yet in osm2streets). But then the map_model layer, which is used by the traffic sim and all the apps, has its own representation for roads and intersections, and all the osm2streets stuff is gone. This was OK to start, but it's starting to get a bit tricky:

A/B Street edits lane specs and needs to regenerate geometry and movements, so we have an adapter kind of hack around it now
Rendering code is starting to be duplicated between map_gui and osm2streets. And then again in #1038 for Bevy
There are some osm2streets API concepts like RoadEdge that'd be useful to use over here now, but they're not easy to get at

I'd like to explore options for embedding StreetNetwork inside map_model::Map too. Reasons to be wary of this:

Keeping serialized file size small and loading times quick for large maps is important, potentially at the expense of code readability / API niceness
the API surface of Lane, Road, Intersection is huge and messy
Keeping some indirection / wrapper between osm2streets and here is a good idea for evolving the two codebases at different speeds

Another vague idea is to embed osm2streets::{Road, Intersection} structs inside of A/B Street equivalents, and keep a few extra fields over on this side
CC @BudgieInWA

A quick survey of https://github.com/a-b-street/abstreet/tree/main/map_model/src...

connectivity and pathfind are all about routing. Eventually this code should live in osm2streets (probably a separate crate). #852 is related
edits is all about modifying a map, undo/redo, saving edits so that they survive upstream OSM edits, etc. The relevant parts of this should also eventually live in osm2streets as an add-on crate.
make has some stuff unrelated to roads, but also the code for vehicle and walking turns currently lives here. That's something I want to move to osm2streets (and rewrite way more rigorously) soon


dependency texlive-latex-extra, add to install docs

Needed to resolve:
LaTeX Error: Command \textquotesingle unavailable in encoding T1.
on Ubuntu 16.04
following the discussion at
https://github.com/jgm/pandoc/issues/2439
Adding that package to the install list is the solution.

Thanks very much.
Updated README.rst.
Please see that, and the commit.

Closing as fixed. Thanks very much for the report, and the fix.


classifyarray

Just realized that calcboundaries is just quantile, though a little bit faster:
using StatsBase
a,c = rand(1000, 1000), [0.2, 0.4, 0.7, 0.8, 1]

julia> @btime quantile(vec(a), c)
  98.238 ms (5 allocations: 7.63 MiB)
5-element Vector{Float64}:
 0.20055273960046652
 0.40035575057383455
 0.7008467088240219
 0.8006453000863003
 0.9999981820198582

julia> @btime calcBoundaries(a, c)
  72.043 ms (7 allocations: 7.63 MiB)
5-element Vector{Float64}:
 0.2005524615247647
 0.40035544743228324
 0.7008461304132632
 0.8006452681104108
 0.9999981820198582

Isn't it because quantile is doing some checks internally that calcBoundaries doesn't? I'm more than willing to pay the 20ms penalty on a 10⁶ grid if the result is safer.

Yes totally agree. It was just fun that it took me several readings of the code - and a port PR - to realize that this functionality already exists and has a name :-)

But I just need to check out that quantile behaves as expected in the presences of NaNs

So, if calcboundaries is quantiles, shouldn't it an overload of quantiles instead?

Codecov Report

Merging #10 (bbda1df) into main (642be05) will decrease coverage by 5.47%.
The diff coverage is 0.00%.

@@            Coverage Diff             @@
##             main      #10      +/-   ##
==========================================
- Coverage   37.73%   32.25%   -5.48%
==========================================
  Files           8        9       +1
  Lines          53       62       +9
==========================================
  Hits           20       20
- Misses         33       42       +9

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src/NeutralLandscapes.jl
100.00% <ø> (ø)

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I think this is ready to be reviewed now - though there are neither docs nor tests.
a = rand(DistanceGradient(rand(1:50*50, 10)), 50, 50);
plot(
    heatmap(a),
    heatmap(classifyArray!(copy(a), [0.25, 1, 1, 1, 0.25, 0.5])),
    size = (800, 300)
)
![class](https://user-images.githubusercontent.com/8429802/107883478-75f28800-6eef-11eb-8d66-fe614172c2cc.png)

Honestly I feel like I should just inline those two helper functions? They're not used anywhere else.

Honestly I feel like I should just inline those two helper functions? They're not used anywhere else.

I don't feel strongly about that - I might just rename them to start with _ to give a little hint that they're really not user-facing, but otherwise it doesn't really matter.

Done. How de we feel about the camelCase? I'm almost inclined to just call it classify! though that sounds like something that could clash with other packages.

I like classify! - maybe we don't export it?

Is NeutralLandscapes.classify! nicer than classifyLandscape!? 🤔

Hi @tpoisot I had a number of issues with conflict - I think I resolved them, but I had to rebase and force-push - hope you wont' get into trouble over at #22 which you branched from this.
I renamed to classify! and unexported - if that works let's merge this now.
But actually as you can see in the example, the demolandscape function isn't actually that flexible, so it causes problems here - maybe it's better to go back to the raw code actually?

We could just export classify!. I can't find other uses of it, and people can use import to avoid it if they need to?

OK, I've exported it again (in the ecosystem only MLBase.jl appears to export a function of that name), and inline the two helper functions - and merged.

great, I'll be able to deal with #22 (which doesn't need it yet anyways, but the NN cluster does)

also in favor or not using demolandscape if it causes more issues than it solves


Login page frontend cancel does nothing

From el-proyecte-grande-sprint-1-java-szplkflrn created by IPHUN1989: CodecoolGlobal/el-proyecte-grande-sprint-1-java-szplkflrn#159
null

Problems:

The login page's cancel button does not work
The login page DOM has non unique IDs
Register page has wrong path in router
Register page button css is different compared to login page
The application properties  have uresolevable settings

Acceptance criteria:

The login page's cancel button redirects to the home page
Visiting the login page will not give any console warning
Register page has correct path
Register and login page have the same css style
The application properties settings are not giving warnings

Kamino cloned this issue to IPHUN1989/test_docs


Add aria-label attribute to most components (#399)

This closes #399

Since the test separation PR is merged, please resolve the conflicts ASAP :)


Updated y-axis label display

Changed code to directly use the value of $this->show instead of using a ternary operator.

Oh sorry, GitHub didn't send me a mail for your request. I will test it next week.

Good work, thank you! :+1:
Can you update the "YAxisOptionTest" in your branch please:
$this->assertSame('true', $yAxis['show']);

must be now:
$this->assertSame(true, $yAxis['show']);

Its my first open project in github and I didnt know how to configure the pipelines to run phpstan and the unit tests in merge requests :/


Build and download cts traffic

This pull request introduces changes to the .github/workflows/ebpf.yml workflow file to include a new build job and test tool, cts-traffic. The changes also include the removal of commented-out code related to secnet perf tests. Here's a breakdown of the changes:
Addition of new build job and test tool:

A new build job build_cts_traffic was added to the jobs section. This job uses a reusable workflow from the Alan-Jowett/ctsTraffic repository to build the cts-traffic test tool. The test job now depends on both the build and build_cts_traffic jobs.
The test job was updated to include steps for downloading the cts-traffic artifact, running the cts-traffic test, and uploading the results.
The cleanup steps in the test job were updated to remove the cts-traffic directory if it exists. [1] [2]

Removal of commented-out code:

Commented-out code related to secnet perf tests was removed from the test job.

Super nit: the description says a dependency is added on Alan-Jowett/ctsTraffic but this has actually been merged into the official ctsTraffic repo.


Replace IIdentity with IdentityUser

The Identity tutorial (https://docs.microsoft.com/en-us/aspnet/core/security/authentication/identity-custom-storage-providers?view=aspnetcore-3.1) recommends that your custom user should extend IdentityUser, not IIdentity. I believe Identity's UserManager doesn't utilize IIdentity's fields so why use it? Was this a typo?
https://github.com/dotnet/AspNetCore.Docs/blob/644661bc46c1c5b5e8480fa6d8b66c4b790ced2b/aspnetcore/security/authentication/identity-custom-storage-providers/sample/CustomIdentityProviderSample/CustomProvider/ApplicationUser.cs#L6

Edit by @Rick-Anderson  5.6K PV
PU needs to outline what needs to be updated for 3.1/5.0

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

ID: 54b3ef64-9e17-3aab-0b75-57726d906cb6
Version Independent ID: 8152896e-6969-d992-4877-6d6bbf4772a3
Content: Custom storage providers for ASP.NET Core Identity
Content Source: aspnetcore/security/authentication/identity-custom-storage-providers.md
Product: aspnet-core
Technology: aspnetcore-security
GitHub Login: @ardalis
Microsoft Alias: riande

Next time Can you create an issue from the doc page? That will connect the doc to the issue. Go to the bottom of the page and select This page .

I think the docs are fine, the example here is just demonstrating a custom identity user and showing that you don't have to extend from our base classes.  So in this case I believe its intentional that its showing IIdentity instead.
The canonical case is extending IdentityUser, this example is showing the less common path


Incorrect Content-Type in BlobStorage after Upload with Azure Storage Explorer / AzCopy / Azure Portal

Which version of the AzCopy was used?
10.5.0 in Storage Explorer 1.14.2 (AzCopy command prompt and Azure Portal used version unknown, was done by our IT)
Which platform are you using? (ex: Windows, Mac, Linux)
Windows
What command did you run?
Uploaded folders with files, containing *.html and *.css, to BlobStorage with Azure Storage Explorer.
Then our IT retried the same with AzCopy itself and after that via Azure Portal.
What problem was encountered?
Content-Type for css, htm, html, xml files with 'text/*' has trailing ; appended.
e.g.
for index.html the Content-Type is text/html;
for bundle.css the Content-Type is text/css;
etc.
which leads to Error in Kestrel Webserver because the Content-Type is invalid.
How can we reproduce the problem in the simplest way?
Upload folder with files, containing *.html and *.css, to BlobStorage
Have you found a mitigation/solution?
Change every Content-Type per hand inside the BlobStorage, if you're really bored  🤣
Problem seems to be introduced with #1043

I'm also experiencing this issue. Content-Type used to be set to "text/html; charset=utf-8" previously and with the latest version it's "text/html;". Breaks Cypress tests for us.

Do we have any ETA for the fix or Workaround this issue ?  Any help on this much appreciated.

I can confirm the Content-Type is broken - possibly by a partial fix to this bug - when copying containers.
Usage: Azure DevOps Release Pipeline, Azure PowerShell Task (Task version 4.*, Azure Powershell version 3.1.0), PowerShell script using "azcopy cp".
When copying from one container to another, all files within the destination have a MIME type of "text/plain". This worked correctly in AzCopy version 10.6.0

Fixed with change #1153 in 10.6.1

Still works wrong if upload files with 'az storage copy'

Still works wrong if upload files with 'az storage copy'


$key doesn't support dot property accessors

In my opinion $key should work with both bracket (e.g. foo["bar"]) and dot  (e.g. foo.bar) notations.
Reproduction on Flow/try:
/* @flow */

type Properties = {
  a: string,
  b: string
};

class Foo<Properties: Object> {
  $key: $Keys<Properties>;
  $value: $Values<Properties>;
};

const foo: Foo<Properties> = new Foo();

// ✔ Will work fine:
foo["a"] = "adsasd";

// ✔ Will throw an error because "c" in not in Properties:
foo["c"] = "adsasd";

// ✘ Will throw an error because of the dot notation:
foo.b = "adsasd";

// ✘ Will thrown an error because of deconstruction:
const {a, b} = foo;

(nothing changes when Foo extends Object)

It's now fixed


🐛(courses) hide unpublished objects from list views

Purpose
On the category, program and person list views, unpublished objects are listed on the public site.
Proposal
The template code was a bit too naïve. Exclude unpublished objects (as it was already done for blog posts and organizations) and add tests to secure it.

@jbpenrath @igobranco I had forgotten to add pagination markup at the end of each list view. It is now added.


CI is failing

Currently, the CI is failing due to the generator detecting a mismatch: https://github.com/exercism/raku/runs/5847984377?check_suite_focus=true

#504 and #509 should resolve this.