[BUG] Attribute aa in ConvNormAct not found

Describe the bug
A cloud mask model I was using required ConvNormAct from timm/layers/conv_bn_act (link). I got this AttributeError: 'ConvNormAct' object has no attribute 'aa' which seems to suggest the line of create_aa() was not executed for some reason.
To Reproduce
Steps to reproduce the behavior:
1.
2.
Expected behavior
The aa object should either be created as a layer, or None, or raise an error if create_aa failed.
Screenshots
File ~/workflow-notebook-v1/Notebooks/../modules/cloud_mask/cloud_mask.py:52, in CloudMask.predict(self, inp, batch_size)
     [50](https://file+.vscode-resource.vscode-cdn.net/home/workflow-notebook-v1/Notebooks/~/workflow-notebook-v1/modules/cloud_mask/cloud_mask.py:50)       outs = 0.0
     [51](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/workflow-notebook-v1/modules/cloud_mask/cloud_mask.py:51)       for model in self.models:
---> [52](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/workflow-notebook-v1/modules/cloud_mask/cloud_mask.py:52)         outs += model(inp[ib:ib+batch_size]) / len(self.models)
     [54](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/workflow-notebook-v1/modules/cloud_mask/cloud_mask.py:54)       preds[ib:ib+batch_size] = F.interpolate(F.softmax(outs, dim=1), size=(H, W), mode='bilinear',
     [55](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/workflow-notebook-v1/modules/cloud_mask/cloud_mask.py:55)                                               align_corners=False)
     [57](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/workflow-notebook-v1/modules/cloud_mask/cloud_mask.py:57) return preds

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1736, in Module._wrapped_call_impl(self, *args, **kwargs)
   [1734](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1734)     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   [1735](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1735) else:
-> [1736](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1736)     return self._call_impl(*args, **kwargs)

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1747, in Module._call_impl(self, *args, **kwargs)
   [1742](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1742) # If we don't have any hooks, we want to skip the rest of the logic in
   [1743](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1743) # this function, and just call forward.
   [1744](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1744) if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   [1745](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1745)         or _global_backward_pre_hooks or _global_backward_hooks
   [1746](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1746)         or _global_forward_hooks or _global_forward_pre_hooks):
-> [1747](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1747)     return forward_call(*args, **kwargs)
   [1749](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1749) result = None
   [1750](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1750) called_always_called_hooks = set()

File ~/anaconda3/lib/python3.11/site-packages/fastai/layers.py:408, in SequentialEx.forward(self, x)
    [406](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/fastai/layers.py:406) for l in self.layers:
    [407](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/fastai/layers.py:407)     res.orig = x
--> [408](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/fastai/layers.py:408)     nres = l(res)
    [409](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/fastai/layers.py:409)     # We have to remove res.orig to avoid hanging refs and therefore memory leaks
    [410](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/fastai/layers.py:410)     res.orig, nres.orig = None, None

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1736, in Module._wrapped_call_impl(self, *args, **kwargs)
   [1734](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1734)     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   [1735](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1735) else:
-> [1736](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1736)     return self._call_impl(*args, **kwargs)

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1747, in Module._call_impl(self, *args, **kwargs)
   [1742](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1742) # If we don't have any hooks, we want to skip the rest of the logic in
   [1743](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1743) # this function, and just call forward.
   [1744](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1744) if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   [1745](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1745)         or _global_backward_pre_hooks or _global_backward_hooks
   [1746](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1746)         or _global_forward_hooks or _global_forward_pre_hooks):
-> [1747](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1747)     return forward_call(*args, **kwargs)
   [1749](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1749) result = None
   [1750](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1750) called_always_called_hooks = set()

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/container.py:250, in Sequential.forward(self, input)
    [248](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/container.py:248) def forward(self, input):
    [249](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/container.py:249)     for module in self:
--> [250](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/container.py:250)         input = module(input)
    [251](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/container.py:251)     return input

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1736, in Module._wrapped_call_impl(self, *args, **kwargs)
   [1734](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1734)     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   [1735](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1735) else:
-> [1736](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1736)     return self._call_impl(*args, **kwargs)

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1844, in Module._call_impl(self, *args, **kwargs)
   [1841](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1841)     return inner()
   [1843](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1843) try:
-> [1844](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1844)     return inner()
   [1845](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1845) except Exception:
   [1846](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1846)     # run always called hooks if they have not already been run
   [1847](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1847)     # For now only forward hooks have the always_call option but perhaps
   [1848](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1848)     # this functionality should be added to full backward hooks as well.
   [1849](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1849)     for hook_id, hook in _global_forward_hooks.items():

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1790, in Module._call_impl.<locals>.inner()
   [1787](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1787)     bw_hook = BackwardHook(self, full_backward_hooks, backward_pre_hooks)
   [1788](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1788)     args = bw_hook.setup_input_hook(args)
-> [1790](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1790) result = forward_call(*args, **kwargs)
   [1791](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1791) if _global_forward_hooks or self._forward_hooks:
   [1792](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1792)     for hook_id, hook in (
   [1793](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1793)         *_global_forward_hooks.items(),
   [1794](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1794)         *self._forward_hooks.items(),
   [1795](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1795)     ):
   [1796](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1796)         # mark that always called hook is run

File ~/anaconda3/lib/python3.11/site-packages/timm/layers/conv_bn_act.py:85, in ConvNormAct.forward(self, x)
     [83](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/timm/layers/conv_bn_act.py:83) x = self.conv(x)
     [84](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/timm/layers/conv_bn_act.py:84) x = self.bn(x)
---> [85](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/timm/layers/conv_bn_act.py:85) if self.aa is not None:
     [86](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/timm/layers/conv_bn_act.py:86)     x = self.aa(x)
     [87](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/timm/layers/conv_bn_act.py:87) return x

File ~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1931, in Module.__getattr__(self, name)
   [1929](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1929)     if name in modules:
   [1930](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1930)         return modules[name]
-> [1931](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1931) raise AttributeError(
   [1932](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1932)     f"'{type(self).__name__}' object has no attribute '{name}'"
   [1933](https://file+.vscode-resource.vscode-cdn.net/home//workflow-notebook-v1/Notebooks/~/anaconda3/lib/python3.11/site-packages/torch/nn/modules/module.py:1933) )

AttributeError: 'ConvNormAct' object has no attribute 'aa'

Desktop (please complete the following information):

OS: Ubuntu 22.04.4 LTS
This repository version [e.g. pip 0.3.1 or commit ref]
PyTorch version w/ CUDA/cuDNN  PyTorch version: 2.5.1+cu124
NumPy version: 1.26.4
Timm version: 1.0.11

Additional context
Add any other context about the problem here.

@DagonArises I'm not at all famililar with the packages being used, but quite likely a model is being restored via ... model = torch.load('checkpoint.pth') instead of model.load_state_dict(torch.load('checkpoint.path'))
checkpoint state dicts typically remain compatible across years of timm versions, but pickling the whole model will only work within a narrow range as adding attributes will cause breaks. I can probably fix this specific case to make it a bit more tolerant if you have a new timm version in the environment and it's trying to unpickle a full model saved with an older one, but no gaurantees

        aa = getattr(self, 'aa', None)
        if aa is not None:
            x = self.aa(x)

that might work around this specific case, though would have to see if it breaks torchscript or other use cases.

@DagonArises I've committed that work around, seems to have no impact but I can't do anything else beyond that if there's another related problem. Have to fix the down stream use or maybe try a fresh environment with updated versions.


feat: add C implementation for math/base/special/maxabs

Resolves #1460 .
Description

What is the purpose of this pull request?

This pull request adds a C implementation for @stdlib/math/base/special/maxabs.
Related Issues

Does this pull request have any related issues?

This pull request:

resolves #1460

Questions

Any questions for reviewers of this pull request?

No.
Other

Any other information relevant to this pull request? This may include screenshots, references, and/or implementation notes.

No.
Checklist

Please ensure the following tasks are completed before submitting this pull request.

[x] Read, understood, and followed the contributing guidelines.

@stdlib-js/reviewers

Thanks for working on this @Shashankss1205. Left a few comments. This PR is blocked until #1459 is merged, given that it is a dependency of this implementation.

I have committed the changes. Please take a look at it and inform if there are any changes that are needed. @kgryte

@Shashankss1205 Now that https://github.com/stdlib-js/stdlib/pull/1459 is merged, would you please either merge in the latest changes from develop or rebase your PR branch so that CI will pass? Otherwise, I only found that a bunch of the C files are still missing trailing newlines. Once resolved, this PR should be ready to merge. Thank you very much!

Now can You please review the PR @Planeshifter . I have made the corresponding changes.

LGTM. Thanks @Shashankss1205 !

Thank You!! Looking forward to working more here.


eigenda flags don't use same syntax as other flags

Should we change the eigenda flags to use . instead of -: eigenda.<FLAG_NAME> instead of eigenda-<FLAG_NAME, like we do for all the other subsystem flags?

closed by https://github.com/Layr-Labs/eigenda-proxy/pull/146


docker exec -it 9a5c836d34f0 -c 'osm2pgrouting -f FORTALEZA.osm -h <IP_ADDRESS> -p 5432 -d routing'           OCI runtime exec failed: exec failed: container_linux.go:345: starting container process caused "exec: "-c": executable file not found in $PATH": unknown

how do i run a command to import data with osm2pgrouting?
I use this command:
docker exec -it 9a5c836d34f0 -c 'osm2pgrouting -f FORTALEZA.osm -h <IP_ADDRESS> -p 5432 -d routing' bash
and I get this error:
docker exec -it 9a5c836d34f0 -c 'osm2pgrouting -f FORTALEZA.osm -h <IP_ADDRESS> -p 5432 -d routing'           OCI runtime exec failed: exec failed: container_linux.go:345: starting container process caused "exec: "-c": executable file not found in $PATH": unknown

not sure what "docker exec -c" would do.
Here are the official docs https://docs.docker.com/engine/reference/commandline/exec/
(hint try to add "bash " before -c or just get a shell in your docker container and go from there.


[Event Request] codeunit 1535 "Approvals Mgmt." - OnAfterFindUserSetupBySalesPurchCode

In codeunit 1535 "Approvals Mgmt." please add the following event:
    local procedure FindUserSetupBySalesPurchCode(var UserSetup: Record "User Setup"; ApprovalEntryArgument: Record "Approval Entry")
    begin
        if ApprovalEntryArgument."Salespers./Purch. Code" <> '' then begin
            UserSetup.SetCurrentKey("Salespers./Purch. Code");
            UserSetup.SetRange("Salespers./Purch. Code", ApprovalEntryArgument."Salespers./Purch. Code");
            if not UserSetup.FindFirst() then
                Error(
                  PurchaserUserNotFoundErr, UserSetup."User ID", UserSetup.FieldCaption("Salespers./Purch. Code"),
                  UserSetup."Salespers./Purch. Code");
            // New event
            OnAfterFindUserSetupBySalesPurchCode(UserSetup, ApprovalEntryArgument);
            // New event
            exit;
        end;
    end;

    [IntegrationEvent(false, false)]
    local procedure OnAfterFindUserSetupBySalesPurchCode(var UserSetup: Record "User Setup"; ApprovalEntryArgument: Record "Approval Entry")
    begin
    end;

Thank you

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.


Instagram Direct integration

Instagram Direct integration
Hello,
I would like to suggest to add Instagram Direct on Franz, an option that it is important for a lot of franz users.
Best regards,
Pablo K.
(Franz is awesome!!)

From https://meetfranz.com/support, you can find this Google Form for service requests.

Hey both @akspablo @closingin did you manage to get the current instagram plugin for Franz to work in V5?

@raynesio I never heard of an Instagram plugin and I wouldn't use it anyway, that's totally unrelated to messaging. And as I said, I think that service requests don't belong here.
If you're looking for an Instagram wrapper you can find one here, but I don't understand why it should be added to Franz imo.

@GevaZeichner There's nothing on Instagram's website that allows you to use the DM feature that exists on their mobile app. So this wouldn't fit.
And anyway, new services have to be requested on the link I sent above.
@haraldox This issue can be closed.

It's not on their website. It's on a 3rd party app: http://igdm.me/
Requested there too.

@GevaZeichner But IG:dm is a software, not a web page (as far as I searched) ? Franz works by loading web pages so that wouldn't be possible.
Even if this software provided a web app, it would require you to install it on your desktop, which would mean the service wouldn't work without it. Bad user experience.

The IG:dm project is open source, is it possible we could ascertain how they were able to get direct messaging working and somehow make that work? I understand that franz basically loads a website, so I would guess someone would have to create a website that hosts the necessary code for instagram dm and such. There is no way to put a web app into a franz recipe directly is there?

I ended up looking around for websites that offer instagram direct messaging. I found postgrain.com which has a free tier. Only caveat is your account has to have 50 followers and 5 media posts. I am not there yet so I can't check their interface. I would surmise it could be integrated with franz.

okay, got it to work, but looks like direct messaging is not part of the free tier

Following up on this - anyone tried to integrate IG:dm project into franz?

Hello @dstanley83 ! IG:dm doesn't provide a web interface (it's an electron application), so it's currently not possible to integrate it in Franz.

Then let's dev a web interface for IG:DM! haha

Since IGDM is an electron app it already is a web interface, we'd just need someone to host it somewhere publicly, which, however, probably is against Instagram's TOS.

Did anyone got this to work in the meantime?

I'd be really interested in this - perhaps someone could work out how to do it and then we can host it our selves for our private use? It's the only messaging service I use that I don't have access to on my Mac.

Hello @zulumbazoid and @realdannys , if you want to discuss about a feature that is related to IG:dm and not Franz, please don't do it in this repository's issues.
If you want IG:dm to work in Franz, you need this software to expose either a web app or a web server that Franz can use (web server because there's a new premium feature in Franz that allows you to add your own custom recipes directly). Otherwise it's not possible, maybe you can ask them or search for an existing issue in their repository.

Hello,
I just found this: https://github.com/alexdevero/franz-instagram-recipe
Seems to work under the recipe/dev folder
I'm new to this. Is this safe to add?

@elvisbrens that’s not Instagram DM, it’s just the Insta web interface.

@realdannys It also has DM. When you add the service and login, look for the DM icon in the top-right corner.

@realdannys It also has DM. When you add the service and login, look for the DM icon in the top-right corner.

Ah yes sorry you're right - it appears to load the mobile view of the website. Not sure it's that much use though as you won't get any of the messaging features of Franz...notifications etc, it's basically just like loading up the mobile version of Insta in your browser. It's something I guess.

Instagram Direct chat already works in web version at url https://www.instagram.com/direct/inbox/ if we use user-agent from any mobile browser, eg Mozilla/5.0 (Linux; Android 4.0.4; Galaxy Nexus Build/IMM76B) AppleWebKit/535.19 (KHTML, like Gecko) Chrome/18.0.1025.133 Mobile Safari/535.19
So we can easily add Instagram Direct chat, if override user-agent string!

Instagram Direct chat already works in web version at url https://www.instagram.com/direct/inbox/ if we use user-agent from any mobile browser, eg Mozilla/5.0 (Linux; Android 4.0.4; Galaxy Nexus Build/IMM76B) AppleWebKit/535.19 (KHTML, like Gecko) Chrome/18.0.1025.133 Mobile Safari/535.19
So we can easily add Instagram Direct chat, if override user-agent string!

Perhaps this is the answer - the plugin above seems to access this menu but also the rest of Instagram and defaults to the homepage - it of course just acts as web browser window so you get no notifications, no symbols it has no interface with the chat - so i'm not sure if someone can build upon the mobile link to actually work with Franz features or not.

@realdannys It also has DM. When you add the service and login, look for the DM icon in the top-right corner.

Ah yes sorry you're right - it appears to load the mobile view of the website. Not sure it's that much use though as you won't get any of the messaging features of Franz...notifications etc, it's basically just like loading up the mobile version of Insta in your browser. It's something I guess.

I just wanted to add that an instagram chat would be nice even without any notification. Just to be able to use keyboards.

You can do it yourself!

add a Custom Website service, and use the normal instagram.com url (add name, logo etc)
open the service and login to instagram
kill Franz
open ~/Library/Application/ Support/Ferdi/recipes/franz-custom-website/index.js with a code editor (On Mac, will be different on Windows)
make it looks like this

"use strict";

module.exports = Franz => class CustomWebsite extends Franz {
  overrideUserAgent() {
    return "Mozilla/5.0 (iPhone; CPU iPhone OS 10_3_1 like Mac OS X) AppleWebKit/603.1.30 (KHTML, like Gecko) Version/10.0 Mobile/14E304 Safari/602.1";
}
  async validateUrl(url) {
     return true
  }
};

open Franz and change the URL of your service to https://www.instagram.com/direct/inbox (you cannot do it before editing the index.js)

close Franz

(optional) replace the validateUrl method in the index.js by this one

  async validateUrl(url) {
    try {
      const resp = await window.fetch(url, {
        method: 'GET',
        headers: {
          'Content-Type': 'application/json'
        }
      });
      return resp.status.toString().startsWith('2') || resp.status.toString().startsWith('3');
    } catch (err) {
      console.error(err);
    }

    return false;
  }

Should work!

Well this is interesting - maybe we can get proper support now?
https://www.macrumors.com/2020/01/14/instagram-dms-coming-to-web/


Updated programming tutorials en document (Hacktoberfest 2021)

Klaudia2432 commented 6 minutes ago
##What does this PR do?
##Add resource(s) | Remove resource(s) | Add info | Improve repo
Added resources
##For resources
##Description
Added English resources to document
##Why is this valuable (or not)?
There are more resources listed in the document
##How do we know it's really free?
I have tested it and it's free, you need to sign in but it's totally free
##For book lists, is it a book? For course lists, is it a course? etc.
Tutorials, courses

TIP :writing_hand:: It's a good practice to fill Pull Request fields. It helps a bit we can understand your contribution better :hugs:. and then, increase maintainers productivity :rocket:

:writing_hand: TIP OF THE DAY: Not is needed open new PR/branch to fix something.
Continue work on same branch and then, on push it to your fork, the corresponding upstream PR will be automatically synchronized :wink:


Pass in testnet param

Fixes
AttributeError: 'Namespace' object has no attribute 'testnet'
Sending request... Error: No validators available

Thank you, @monkeyscanjump, for your effort and collaboration on this PR. While these changes are close to the final solution, additional adjustments were needed and have already been implemented in commit ef273599f2e48a6f38bf013e4e844f065cbc809a, so we’ll be closing this PR. We appreciate your work and encourage any future contributions!

Nice! Tested latest changes! Thanks!


Add deploy checks

This might help with #444 and #440
Please let me know if there's something else missing or unnecessary

@GustavoKatel Great combo!  Thank you very much for your contributions and time.


fix path: ~lsstsw/eups/current/bin/setups.sh

[jbasney@lsst-dev ~]$ source ~lsstsw/eups/bin/setups.sh
-bash: /home/lsstsw/eups/bin/setups.sh: No such file or directory
[jbasney@lsst-dev ~]$ source ~lsstsw/eups/current/bin/setups.sh
[jbasney@lsst-dev ~]$

@jbasney  Sorry I didn't notice the PR until now. What's the status here given @timj's comment? Given that @jdswinbank is taking over maintenance of the shared stack on lsst-dev (afaik) maybe John can validate/update this doc page.

I will indeed be revising this page as part of DM-5435. Expect that to land sometime in the next ~week, and it will obsolete the current text.

It's not quite ready for review, but the documentation regarding the shared stack is now available at https://github.com/lsst-dm/dm_dev_guide/pull/26. Comments, questions & suggestions welcome.

#26 is merged, and the fault text no longer exists. Closing this down.


Update Changelog for exporter

Contributing to the Azure SDK
Please see our CONTRIBUTING.md if you are not familiar with contributing to this repository or have questions.
For specific information about pull request etiquette and best practices, see this section.

closing this. Sorry @vishweshbankwar I was having merge conflicts and git wasn't cooperating. Thanks for getting this started for me.


Custom icons have no badge and cannot be deleted

Bug description:
Deleting custom icons doesn't work and keeps reappearing
Badges wont show up on custom icons

Steps to reproduce:
Add whatsapp, login with phone, change whatsapp icon to business icon from web, save, close ferdi, then attempt to delete it.
It will only delete for current session, if you close and reopen ferdi the custom icon stays and doesnt show any notification badge
Expected behavior
Badges should show up on any icon
Should be able to delete/replace custom icon

Environment:

Operating System: Windows 10
Ferdi Version: Ferdi 5.6.0
Server: Ferdi using with import from Franz

Can confirm this, happens to me too with the latest nightly.


ADBDEV-6756: [6X] Migrate ADBC dependencies to the base image

[6X] Migrate ADBC dependencies to the base image
The ADCC extension's scripts are split in different files due to differences in
dependencies across Linux distributions. This patch adds required dependencies
to the base Ubuntu image.

Move adb-python bin/ directory to a reusable variable.
Add protobuf-compiler to apt packages and protobuf==3.20.0 python module to
base image for Ubuntu.

Allure report https://allure.adsw.io/launch/86562

Allure report https://allure.adsw.io/launch/87020

When I try to run adcc-extension's tests (I removed lines from script with installing protobuf-compiler and protobuf), I get error

Yeah, test/test_in_docker_u22.sh contains the following line, which causes this error:
export PATH=/opt/adb6-python3.9/bin/:$PATH

And /opt/adb6-python3.9/bin/ now has a python executable, which will replace python2 if is in PATH. We already copy all binaries except python to /usr/local/bin/. You can use the script added in the MR of ADCC-4880 on Gitlab to test all docker images for these changes.

Allure report https://allure.adsw.io/launch/87598

Allure report https://allure.adsw.io/launch/87617

docker run --rm -it --privileged --sysctl 'kernel.sem=500 1024000 200 4096' -v $PWD:/home/gpadmin/adcc hub.adsw.io/library/gpdb6_u22:ADBDEV-6756 adcc/adcc-extension/test/test_in_docker_u22.sh

You skipped --sysctl 'net.unix.max_dgram_qlen=4096' in the command. I reran the tests and they worked ok.

Allure report https://allure.adsw.io/launch/87715


execute "az" command will exit with error "Fail to load or parse file /root/.azure/azureProfile.json"

Have you tried trouble shooting?
Trouble shooting doc
Agent Version and Platform
Version of your agent? 2.140.0
OS of the machine running the agent? Linux
VSTS Type and Version
VisualStudio.com
If VisualStudio.com, what is your account name? http://zhqqitest.visualstudio.com
What's not working?
I'm the author of this plugin Azure IoT Edge For VSTS, and recently my customer reported that one of my task failed with the error message "Fail to load or parse file /root/.azure/azureProfile.json". I checked and found that
When executing az cli on build agent for example:
2018-09-10T02:26:53.5131871Z [command]/usr/bin/az login --service-principal -u *** -p *** --tenant ***
2018-09-10T02:27:01.1514627Z Fail to load or parse file /root/.azure/azureProfile.json. It is overridden by default settings.
2018-09-10T02:27:01.1538224Z [
2018-09-10T02:27:01.1554452Z Fail to load or parse file /root/.azure/az.json. It is overridden by default settings.
2018-09-10T02:27:01.1571907Z Fail to load or parse file /root/.azure/az.sess. It is overridden by default settings.
It will show some file is missing and cause the exit code of command set to non-zero. But this never happened before. I gave a work-around to add an Azure CLI task before to generate the missing files and the tasks in my extension can work. But is there a fix from your side? Thank you
Agent and Worker's Diagnostic Logs
Related Repositories

Same exact problem here with a different task. I use Terraforming (by AKC)
Last successful build was on 2.139.1
For me this is a critical issue as all releases are currently blocked for me. Hosted Linux Agent with 2.140.0 on https://imaginedcloud.visualstudio.com
Is there a way to pin the hosted version to an agent still on 2.139.1? I tried putting an Agent.Version demand but it used -gtVersion in the history instead of exact.

@michaeljqzq @johlrich the problem is not caused by the agent, it's a task bug. the updated version Azure CLI in the hosted image produce some STDERR on first launch and the task is not handle it correctly.
https://github.com/Microsoft/vsts-tasks/pull/8279

@TingluoHuang thanks for the detail. I will follow up with the task author and link them to it.
Is there a way to pin the hosted agent's version so I can at least run on the 2.139.1 version until that happens?

@johlrich pin back the agent version won't help, it's the image update that brings in the latest version Az cli cause the problem, and we don't have a way to pin back image update at this point. :(

@TingluoHuang ahhhh thanks for that important detail, I didn't realize that was a first run thing. Adding a task before that one to just call az has at least unblocked me until the task can be fixed.

cool, thanks for sharing the workaround.

i am going to close the issue since it's not an agent issue.


[Event Request]Application “Tests-Bank”, Codeunit  134271 "Payment Recon. E2E Tests Perf."

[Event Request]Application “Tests-Bank”, Codeunit  134271 "Payment Recon. E2E Tests Perf."
Could you please insert the OnTestInitialize Event at the beginning of Initialize procedure:

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. We will update this issue with information about availability.


[Bug] I_like does not copy the device of the LinearOperator it is "like"

🐛 Bug
If I have a linear operator A on GPU and call Ident = cola.ops.I_like(A), then the new identity operator will be placed on CPU.
This is annoying because if combined functions like cola.eig(Ident - A, k=1) will fail because the the tensors are on different devices.
To reproduce
** Code snippet to reproduce **
import torch
import cola

print(f'CUDA Available {torch.cuda.is_available()}')

A = cola.ops.Diagonal(torch.randn((200, 200)))
A = A.to('cuda')

Ident = cola.ops.I_like(A)

print(f'A: {A.device}')
print(f'Ident: {Ident.device}')

** Stack trace/error message **
CUDA Available True
A: cuda:0
Ident: cpu

Expected Behavior
For I_like(A).device == A.device.
System information
Please complete the following information:
CoLA: 0.0.5
Pytorch: 2.3.0+cu121
Python: 3.11.9
Ubunutu 24.04

Thank you for pointing out this bug and thanks for the concise and well though code snippet to reproduce! I've just added a fix on https://github.com/wilson-labs/cola/pull/99. Also the problem of trying to evaluate cola.eig(Ident - A, k=1) was much deeper that what I initially thought, involving a fix not only to I_like but other ops.


Update nohello.js

"在吗？" in Chinese means "You there?", which is more popular in Chinese network than "你好".
"你好" is a formal use, it's not common in online chat.

So it is, I agree with you. This PR should be merged.

Thanks!


ConversationalRetrievalChain with Custom Agent is not returning source documents

System Info
Hi i am using ConversationalRetrievalChain with agent and agent.run function is not returning source documents.
Is this by functionality or is it a missing feature?
def llm_answer(query):
   chat_history = []
   result = qa({"question": query, "chat_history": chat_history})
   print('result is')
   print(result)
   print('-----------------------------')
   print(result['source_documents'][0])
   print('-----------------------------')
   #populateHistory(query, result)
   return result

qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0), db.as_retriever(), return_source_documents=True)

class requestModel(BaseModel):
    question: str

app = FastAPI()
tools = [
    Tool.from_function(
        func=llm_answer,
        name = "Email knowledge base",
        description="useful for when you need to answer questions from emails in knowledge base",
        args_schema=requestModel
        )
#more tools
]

agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)

# Define API endpoint for querying the model
@app.post('/answer')
async def answer(request: requestModel):
    print('request received')
    source_documents = []
    # Get data from request
    print("Query is " + request.question)
    q_answer2 = agent.run(request.question)
    print("answer is ")
    print(q_answer2)
    #construct a json object to return answer and sources to the client
    reply = {'answer' : str(q_answer2), 'sources' : []}
    # for x in q_answer2["source_documents"]:
    #     reply['sources'].append(x.metadata["source"])
    return reply

Who can help?
@hwchase17
Information

[ ] The official example notebooks/scripts
[ ] My own modified scripts

Related Components

[ ] LLMs/Chat Models
[ ] Embedding Models
[ ] Prompts / Prompt Templates / Prompt Selectors
[ ] Output Parsers
[ ] Document Loaders
[ ] Vector Stores / Retrievers
[ ] Memory
[X] Agents / Agent Executors
[ ] Tools / Toolkits
[X] Chains
[ ] Callbacks/Tracing
[ ] Async

Reproduction
use code sample provided
Expected behavior
agent.run should provide with both answers and source_documents

with
`dochistory  = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=vectorstore.as_retriever(search_kwargs={"k": 6}), return_source_documents=True)
...
tools = [
Tool(
    name = "Document Cache",
    func=dochistory.run,
    description="Useful for when you need to answer questions about the aspects asked. Input may be a partial or fully formed question."
    ),

...
llm_chain=LLMChain(llm=llm,prompt=prompt)
agent = ZeroShotAgent(llm_chain=llm_chain, tools=tools, verbose=True,return_source_documents=True,prompt=prompt)
agent_chain = AgentExecutor.from_agent_and_tools(
agent=agent, tools=tools, verbose=True, memory=memory,return_source_documents=True
)
result=agent_chain.run(query)
get error  ValueError:run` not supported when there is not exactly one output key. Got ['result', 'source_documents'].
code runs if I don't ask for source documents but I want them.

with `dochistory = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=vectorstore.as_retriever(search_kwargs={"k": 6}), return_source_documents=True) ... tools = [
Tool(
    name = "Document Cache",
    func=dochistory.run,
    description="Useful for when you need to answer questions about the aspects asked. Input may be a partial or fully formed question."
    ),

... llm_chain=LLMChain(llm=llm,prompt=prompt)
agent = ZeroShotAgent(llm_chain=llm_chain, tools=tools, verbose=True,return_source_documents=True,prompt=prompt)
agent_chain = AgentExecutor.from_agent_and_tools( agent=agent, tools=tools, verbose=True, memory=memory,return_source_documents=True ) result=agent_chain.run(query) ` get error
"ValueError: run not supported when there is not exactly one output key. Got ['result', 'source_documents']" code runs if I don't ask for source documents but I want them.

yes i also need source_documents

@tevslin  So i found  a way where we can extract the source documents
while initializing agent set following to true:
return_intermediate_steps=True, return_source_documents=True
Then invoke agent like below
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,return_intermediate_steps=True,return_source_documents=True)
q_answer2 = agent({request.question})

q_answer2  would return a key "intermediate_steps" that contains source docs and you can extract them as below:

qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0), db.as_retriever(), return_source_documents=True) #condense_question_prompt=prompt

tools = [
#...
]

agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,return_intermediate_steps=True,return_source_documents=True)

# Define API endpoint for querying the model
@app.post('/answer')
async def answer(request: requestModel):
    print('request received')
    # Get data from request
    print("Query is " + request.question)
    q_answer2 = agent({request.question})
    print(q_answer2)
    reply = {'answer' : str(q_answer2["output"]), 'sources' : []}
    intermediate_steps = q_answer2["intermediate_steps"]
    try:
        if(intermediate_steps):
            source_docs = intermediate_steps[0][1]['source_documents']
            print(source_docs)
            for x in source_docs:
                if x.metadata["source"] not in reply['sources']:
                    reply['sources'].append(x.metadata["source"])
    except Exception as err:
        print("Error fetching source documents: {}".format(err))
    return reply

Thank for working on this. I am using an agent executor. If I put return_intermediate_steps=True in the agent definiton, it seems to be ignored. If I put it in AgentExecutor.from_agent_and_tools I get run not supported when there is not exactly one output key. Got ['output', 'intermediate_steps']. "run" refers to the entry point to the search tool I've provided as a retriever. I think I may be overloading the langchain apis by wanting to have a retriever, and agent executor, a chat model, and also get sources - but this is what I'd like to do.

Please refer to this issue: https://github.com/hwchase17/langchain/issues/3523#issuecomment-1540239594

@tevslin So i found a way where we can extract the source documents
while initializing agent set following to true:
return_intermediate_steps=True, return_source_documents=True
Then invoke agent like below
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,return_intermediate_steps=True,return_source_documents=True)
q_answer2 = agent({request.question})

q_answer2 would return a key "intermediate_steps" that contains source docs and you can extract them as below:

qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0), db.as_retriever(), return_source_documents=True) #condense_question_prompt=prompt

tools = [
#...
]

agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,return_intermediate_steps=True,return_source_documents=True)

# Define API endpoint for querying the model
@app.post('/answer')
async def answer(request: requestModel):
    print('request received')
    # Get data from request
    print("Query is " + request.question)
    q_answer2 = agent({request.question})
    print(q_answer2)
    reply = {'answer' : str(q_answer2["output"]), 'sources' : []}
    intermediate_steps = q_answer2["intermediate_steps"]
    try:
        if(intermediate_steps):
            source_docs = intermediate_steps[0][1]['source_documents']
            print(source_docs)
            for x in source_docs:
                if x.metadata["source"] not in reply['sources']:
                    reply['sources'].append(x.metadata["source"])
    except Exception as err:
        print("Error fetching source documents: {}".format(err))
    return reply

This also does not Work

I am using similar logic and it does work.
From: Sadaf-Syeda @.>
Sent: Sunday, May 28, 2023 10:56 AM
To: hwchase17/langchain @.>
Cc: Tom Evslin @.>; Mention @.>
Subject: Re: [hwchase17/langchain] ConversationalRetrievalChain with Custom Agent is not returning source documents (Issue #4562)
@tevslin https://github.com/tevslin  So i found a way where we can extract the source documents
while initializing agent set following to true:
return_intermediate_steps=True, return_source_documents=True
Then invoke agent like below
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,return_intermediate_steps=True,return_source_documents=True)
q_answer2 = agent({request.question})
q_answer2 would return a key "intermediate_steps" that contains source docs and you can extract them as below:
qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0), db.as_retriever(), return_source_documents=True) #condense_question_prompt=prompt
tools = [
#...
]
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,return_intermediate_steps=True,return_source_documents=True)
Define API endpoint for querying the model
@app.post('/answer')
async def answer(request: requestModel):
print('request received')
# Get data from request
print("Query is " + request.question)
q_answer2 = agent({request.question})
print(q_answer2)
reply = {'answer' : str(q_answer2["output"]), 'sources' : []}
intermediate_steps = q_answer2["intermediate_steps"]
try:
if(intermediate_steps):
source_docs = intermediate_steps[0][1]['source_documents']
print(source_docs)
for x in source_docs:
if x.metadata["source"] not in reply['sources']:
reply['sources'].append(x.metadata["source"])
except Exception as err:
print("Error fetching source documents: {}".format(err))
return reply
This also does not Work
—
Reply to this email directly, view it on GitHub https://github.com/hwchase17/langchain/issues/4562#issuecomment-1566165019 , or unsubscribe https://github.com/notifications/unsubscribe-auth/AGLSBBXEV2W26STCIUZQR2LXINRQ3ANCNFSM6AAAAAAX7F4HNU .
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it does not work with me either. I am using the following:
qa_chain = RetrievalQAWithSourcesChain.from_chain_type(
        llm=llm,
        chain_type="stuff",
        retriever=db.as_retriever(),
        chain_type_kwargs=chain_type_kwargs,
        return_source_documents=True,
        verbose=True
        )
    tools = [
    Tool(
        name="QA",
        func=qa_chain,
        description="easy to answer"

    ),
    ]
    agent = initialize_agent(tools, llm, agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION, verbose=True,
    return_intermediate_steps=True,return_source_documents=True)
    #answer = agent_chain.run(input=question)
    answer =  agent({question})

I am getting the following error:
ValueError: A single string input was passed in, but this chain expects multiple inputs ({'chat_history', 'input'}). When a chain expects multiple inputs, please call it by passing in a dictionary, eg `chain({'foo': 1, 'bar': 2})`

even when I changed the answer into:
answer =  agent({"input":question})

I got the following error:
ValueError: Missing some input keys: {'chat_history'}

what should I add for this? I am just using RetrievalQAWithSourcesChain

did anyone resolve this?


[Kusto extension] Updated links

This PR fixes #

Pull Request Test Coverage Report for Build 267571624

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 38.113%

Totals

Change from base Build 267487791:
0.0%

Covered Lines:
19122

Relevant Lines:
45833

💛  - Coveralls

#sign-off


feat: add skeleton helper

Please check if the PR fulfills these requirements

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

const skeletonManager = rootEntity.addComponent(SkeletonManager);
skeletonManager.showSkin(entity);

skeletonManager.clear();

Add this to Readme feature list.


create inspector lands function

Create Function inspector_lands**

Develop a function to retrieve and manage lands assigned to the inspector.

Replace Non-Existent Statuses with "Pending":

Identify and replace all non-existent statuses with "Pending".

Enhance the update_land function to accept a land_status parameter.

I’d love to work on this task.

Hello @fishonamos, I'm Wheval a Frontend and Cairo Developer.
I’d like to help with this.
I would create a Inspector_lands function that retrieves and manages land assigned to each inspector using Map.
I would replace the state of Non-existent with Pending.
I would modify the update_land function to accept a land_status parameter.
I would compile my code to test for build errors.
Please assign. This would be my first contribution to Landver.
Thank you!
ETA is 1day.

Hello, I will like to work on this issue.
I will create the inspector_lands function to retrieve and manage the lands assigned to an inspector, then I will replace all the non-existent statuses to "Pending" and add land_status parameter to the update_land function.
My ETA is 8-10 hours

Is it okay if I tackle this?

I Can Handle this issue
Tackling this issue:

Giving that I understand how the code base works having contributed to this  code before I will easily create a function signature inspector_lands() in an interface.
I will implement the function to follow the above listed specificaation.
I will write test for the function to ensure that it works as intended.

ETA: 10 hours Max

@Cyberking99 @ekumamatthew More issues coming.


Bump gRPC version to 0.13 and get C# version autogenerated

To be able to generate "candidate" packages with 0.13 version.
-- version to 0.13
-- use templates to get C# version automatically
-- simplify C# nugets a little bit

Merged upstream/master to make this mergeable again.


Added what you are seeking quote

First pull and push?

Fork, Pull, Push, glad to have your contribution Faizan! Merging it now :D

Was I able to send the pull request correctly?

Yes you were! You can try it out again and I will be more than happy to approve it, so that you get some practice if you're confused about something 😄


Update how-to-ota.md

Added a piece in the CLI to UI part on ensuring that in the config file the appCenterOTA key is set to true, otherwise the OTA option will not appear in the UI builder

Hi @stmarkidis can I get your opinion on this change please?

@ConnorLand it's a good suggestion

Great. @MartijnBooijAppronto I have manually implemented your doc update myself, so I am closing this PR. If you check the page you'll see your update.
Thank you for contributing to the documentation.


Please remove 'git reset --hard' from the scripts, it's TOO DANGEROUS

I'm submitting a ...
[ ] bug report
[*] feature request
[ ] question about the decisions made in the repository
[ ] question about how to use this project

Summary

Please remove 'git reset --hard' from the scripts in package.json, it's TOO DANGEROUS. People may expect npm run scripts never do anything other than building, testing, at least never anything as dangerous as git reset --hard without warning.
If the task requires a clean work directory, check it instead of doing 'git reset --hard'. Let's just say I learnt this in an expensive way. Please remove it, or at least prompt user (to type something long, like what you need to do when you delete a git repository).

@bingtimren thank you very much for opening this issue, and very sorry you lost work. I fixed this in v2.4.5 – I think the root issue was the misleadingly-named all task, which wasn't clearly used for clean-releases. I removed that task, so only the actual npm run reset (and larger npm run prepare-release) task is potentially destructive.
I think that should avoid most accidents, but it would be nice if perhaps the npm run prepare-release task had a "Press enter to reset the project and begin a release..." prompt. Unfortunately, I don't know how to do that in an adequately-cross-platform way without adding another dependency (which I don't think is worth it for this single case).
If anyone has any ideas about how this can be improved, I'd love to hear them (and/or take a PR).

@bitjson  I've been bitten by this too many times. Here's a suggestion that works under git bash for Windows. It was necessary to run the porcelain test via sh. For some reason, calling test from within the script always induced an error.
"porcelain": "sh -c '[[ -z \"$(git status --porcelain)\" ]]' || (echo Warning - pending changes && exit 1)",
"status": "npm run porcelain && echo Ready for release",
"reset": "npm run porcelain && npm run reset-hard",
"reset-hard": "git clean -dfx && git reset --hard && sleep 2 && npm run setup",


Icon for polls/surveys

Describe the requested icon(s)
Hey, thanks for the great library.
I would like to request an icon for polls/surveys.

References
Something like this:

https://t4.ftcdn.net/jpg/02/48/04/59/360_F_248045991_doOwB0DorOcevRs44cwFvwRHktjVO1Qr.webp
https://static-00.iconduck.com/assets.00/poll-icon-511x512-rsm3y3qi.png
https://www.svgrepo.com/show/347908/poll.svg

Additional context
I need it for my survey app inside a mobile navigation and i think it could be helpful for various other user-centered applications

We have chart-bar and chart-bar-horizontal, these should work as they are very similar to your examples. I'll make sure to improve tagging so they are searchable with poll-related keywords.

Hey, thanks for the reply.
Personally i would love the bars in the speech bubble to indicate that this is a survey.
But thanks for two icons and the improved tagging, this would work as well or in the mean time.

Added ranking.


Enable charmap plugin for unicode symbols in tinymce

Motivation

Some municipalities are using special characters like ← but have to copy them from word to get them as valid unicode characters. We should encourage our user to use this symbols and provide a better integration for them.
Proposed Solution

Activate the inbuilt charmap plugin for tinymce which includes some common unicode symbols.
Additional Context

https://www.tiny.cloud/docs/plugins/opensource/charmap/

the issue has already been processed


refactor cluster_controller class to reduce complex

Refactor the Reconcile() function in https://github.com/cloudnative-pg/cloudnative-pg/blob/main/controllers/cluster_controller.go#L134 to reduce complex

I'm closing this since I don't think it's valid anymore, if you think it's valid @litaocdl please reopen it


Add Mysterious Sword Master Youmu (from LostWord)

New sale https://twitter.com/gift_news/status/1527532221623836672

Thanks, merged with a slight name change


No support to non utf-8 encoding file names

Currently there is no support to file name that does not use UTF-8 encoding.

Will document this, and add protection in file/dir creation.


Fixing gp default optimizer

Pull Request Description
This PR proposes a quick fix for the name of the default optimizer in GP regressor.
What issue does this change request address? (Use "#" before the issue to link it, i.e., #42.)
Closes #1855
What are the significant changes in functionality due to this change request?
Fixes a defect.

For Change Control Board: Change Request Review
The following review must be completed by an authorized member of the Change Control Board.

[x] 1. Review all computer code.
[x] 2. If any changes occur to the input syntax, there must be an accompanying change to the user manual and xsd schema. If the input syntax change deprecates existing input files, a conversion script needs to be added (see Conversion Scripts).
[x] 3. Make sure the Python code and commenting standards are respected (camelBack, etc.) - See on the wiki for details.
[x] 4. Automated Tests should pass, including run_tests, pylint, manual building and xsd tests. If there are changes to Simulation.py or JobHandler.py the qsub tests must pass.
[x] 5. If significant functionality is added, there must  be tests added to check this. Tests should cover all possible options.  Multiple short tests are preferred over one large test. If new development on the internal JobHandler parallel system is performed, a cluster test must be added setting, in  XML block, the node <internalParallel> to True.
[x] 6. If the change modifies or adds a requirement or a requirement based test case, the Change Control Board's Chair or designee also needs to approve the change.  The requirements and the requirements test shall be in sync.
[x] 7. The merge request must reference an issue.  If the issue is closed, the issue close checklist shall be done.
[x] 8. If an analytic test is changed/added is the the analytic documentation updated/added?
[x] 9. If any test used as a basis for documentation examples (currently found in raven/tests/framework/user_guide and raven/docs/workshop) have been changed, the associated documentation must be reviewed and assured the text matches the example.

@Jimmy-INL You need to regold the test.

Job Test Ubuntu 18 PIP on 3f4ec97 : invalidated by @Jimmy-INL

PR is good, but I think you need to regenerate the manual to reflect the changes. @Jimmy-INL

@wangcj05, I think I have fixed the manual issue. But maybe all other ROMs with the new API have it as well. If so, should I try to fix it here? Also, could you please take a look at what I have added in the docGenerator?

Job Mingw Test on 71a21c1 : invalidated by @Jimmy-INL

@Jimmy-INL Do you need this PR for RAVEN workshop?

Yes

From: Congjian Wang - INL @.>
Sent: Thursday, July 21, 2022 3:07:45 PM
To: idaholab/raven @.>
Cc: Mohammad G. Abdo @.>; Mention @.>
Subject: [EXTERNAL] Re: [idaholab/raven] Fixing gp default optimizer (PR #1854)
@Jimmy-INLhttps://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FJimmy-INL&data=05|01|mohammad.abdo%40inl.gov|91dfbd659cd040b6ae7908da6b5d0f2f|4cf464b7869a42368da2a98566485554|0|0|637940344674268563|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=4HKzcNGF6Ij%2FH6WJ9oNJQLguNpDuyO3Lh50f7fhzQuY%3D&reserved=0 Do you need this PR for RAVEN workshop?
—
Reply to this email directly, view it on GitHubhttps://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fidaholab%2Fraven%2Fpull%2F1854%23issuecomment-1191936438&data=05|01|mohammad.abdo%40inl.gov|91dfbd659cd040b6ae7908da6b5d0f2f|4cf464b7869a42368da2a98566485554|0|0|637940344674268563|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=fqj59a%2FqtzmDEj%2B3D2DEy0lVL5hCaoKdGxxlPrtD9Sw%3D&reserved=0, or unsubscribehttps://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FAMP5ECXTHBBGRPCT75JHO53VVG32DANCNFSM5YZFZY7A&data=05|01|mohammad.abdo%40inl.gov|91dfbd659cd040b6ae7908da6b5d0f2f|4cf464b7869a42368da2a98566485554|0|0|637940344674268563|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=4N163AKnaMSyFLZibk4V5r%2Fgxik8T9O8RZGPW2J4s0I%3D&reserved=0.
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Job Mingw Test on 26c9530 : invalidated by @wangcj05

Job Mingw Test on 26c9530 : invalidated by @Jimmy-INL

@Jimmy-INL It seems civet is down. In order to merge your PR, you need to run the tests on your local machine, and report the results here. As well as the compilation of user manual.

These are the test results from my local machine since civit is down.

recent changes just to resolve reviewer's comment, just changes have been validated in local machine since civet test system is under maintenance now. Previous tests for commit "26c9530" is green. As CCB, I approve this PR.

checklist is satisfied. PR can be merged.


issue-931-search-cleared-event

fixing backspace to empty icon change

Works great. Thanks for working through this!


Optimized Traversable<>.unzip(Function, Function)

New unzip() method accepts two functions to avoid extensive Tuple creation under the hood.

This is a PR to address https://github.com/vavr-io/vavr/issues/2503

Codecov Report

Merging #2662 (cd58bbc) into master (a09f8cc) will increase coverage by 0.05%.
The diff coverage is 100.00%.

@@             Coverage Diff              @@
##             master    #2662      +/-   ##
============================================
+ Coverage     92.87%   92.93%   +0.05%
- Complexity     5370     5398      +28
============================================
  Files            89       89
  Lines         12790    12889      +99
  Branches       1620     1627       +7
============================================
+ Hits          11879    11978      +99
  Misses          722      722
  Partials        189      189

Impacted Files
Coverage Δ
Complexity Δ

src/main/java/io/vavr/collection/Set.java
100.00% <ø> (ø)
2.00 <0.00> (ø)

src/main/java/io/vavr/collection/SortedSet.java
100.00% <ø> (ø)
2.00 <0.00> (ø)

src/main/java/io/vavr/collection/Traversable.java
96.87% <ø> (ø)
114.00 <0.00> (ø)

src/main/java/io/vavr/collection/Array.java
99.31% <100.00%> (+0.01%)
244.00 <3.00> (+3.00)

src/main/java/io/vavr/collection/BitSet.java
98.06% <100.00%> (+0.03%)
83.00 <1.00> (+1.00)

src/main/java/io/vavr/collection/CharSeq.java
99.64% <100.00%> (+<0.01%)
351.00 <2.00> (+2.00)

src/main/java/io/vavr/collection/HashSet.java
95.81% <100.00%> (+0.08%)
141.00 <1.00> (+1.00)

src/main/java/io/vavr/collection/Iterator.java
89.78% <100.00%> (+0.07%)
186.00 <4.00> (+4.00)

...rc/main/java/io/vavr/collection/LinkedHashSet.java
96.65% <100.00%> (+0.07%)
146.00 <1.00> (+1.00)

src/main/java/io/vavr/collection/List.java
99.44% <100.00%> (+<0.01%)
267.00 <2.00> (+2.00)

... and 8 more

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Thank you @danieldietrich for detailed explanation! Let me follow-up with the code change.

I've changed the return type of Traversable<>.unzip(Function, Function) to Tuple2<Iterator<T1>, Iterator<T2>, and removed all the unnecessary container-specific code. Once the code looks good, I'll take another step to remove previous implementation of unzip(Function<T, Tuple2<T1,T2>>).

@danieldietrich ,
// ...
final Iterator<T1> iter1 = map(unzipper1);
final Iterator<T2> iter2 = map(unzipper2);
return Tuple.of(iter1, iter2);

—  I do not think Iterator.unzip(Function, Function) implementation would work this way. My reasoning: iterator is mutable, so traversing over, say, first Iterator _1 in the resulting Tuple2 will affect traversing of the iterator in _2.
Can you please share your perspective on this?

There's what I observe under debugger with said Iterator.unzip(Function, Function) implementation:

Please note empty a_2 - my explanation this is because a_1 iterator was already traversed, and there's no more data yielded by a_2.
Do you think this explanation may seem reasonable?

I do not think Iterator.unzip(Function, Function) implementation would work this way

You are absolutely right - it was a fast shot without really thinking about it. If we can't re-use an existing iterator (one of those internals in the Iterator interface), we have to write a new one that is able to feed two iterators. (Something like tee in bash).
Let be think about it, I will come back with a suggestion.

Sadly, there is no chance to do it without allocating memory. This is the easiest way to do it (I did not test the code in an editor):
    @Override
    default <T1, T2> Tuple2<Iterator<T1>, Iterator<T2>> unzip(
            Function<? super T, ? extends T1> unzipper1, Function<? super T, ? extends T2> unzipper2) {
        Objects.requireNonNull(unzipper1, "unzipper1 is null");
        Objects.requireNonNull(unzipper2, "unzipper2 is null");
        if (!hasNext()) {
            return Tuple.of(empty(), empty());
        } else {
            final Stream<T> stream = Stream.ofAll(() -> this);
            final Iterator<? extends T1> iter1 = stream.iterator().map(unzipper1);
            final Iterator<? extends T2> iter2 = stream.iterator().map(unzipper2);
            return Tuple.of(iter1, iter2);
        }
    }

Could you do this for Iterator.unzip und Iterator.unzip3, please?

Will do, thank you @danieldietrich

@danieldietrich , side question: from the Iterator class description, and from code implementation, it's not clear to me — generally speaking, is there a legitimate way to create a copy of an iterator instance? Or, they are inherently non-copyable? (I think copying an iterator instance could help us avoid memory allocation while traversing Tuple's _1, _2).

@danieldietrich , I've updated the code of Tuple2<Iterator<T1>, Iterator<T2>> unzip(Function, Function) according to your recommendations. gradlew check is successful now. Please kindly review and let know if it looks Ok. Once we're there, I will..

...update unzip3(Function<T, Tuple3>) to unzip3(Function<T, T1>, Function<T, T2>, Function<T, T2>) — as you suggested;
...add necessary tests coverage;
...remove old unzip method using Function<T, Tuple> arguments, along with their tests.

Please let know if it looks Ok to you.

@sleepytomcat

side question (...) is there a legitimate way to create a copy of an iterator instance?

Currently there exists not way because Iterator is stateful (other than Vavr collections, which are persistent). However, the idea is tempting. I could imagine that an Iterator could have a copy() aka clone() aka duplicate() method that creates a new Iterator instance by copying the state. This might involve recursively copying wrapped Iterator instances. I will think a bit about it, but it is out of scope for this PR.

@sleepytomcat Thank you, please go on with 1)-3) like you suggested!
Great that you updated the links to the methods in the javadoc at the top of the file! 👍🏼

@danieldietrich , the items (1)-(3) completed, please review the code and share your feedback. Thank you!

I think I messed up with pulling upstream changes. Fixing.

Return type changed to Tuple3<Iterator<T1>, Iterator<T2>, Iterator<T3>> as suggested. Thank you!


I'm having trouble running the distill_llama.py.

I think there's one experiment missing in the experiment config folder: eval_Scrolls.yaml, which calls OurTrainer in the finetune_seq2seq.py in the eval phase, which uses dataset scrolls, but doesn't precede the operation of importing datasets.
 Traceback (most recent call last):   File "/data1/lxw/code/lolcats/distill_llama.py", line 469, in <module>     main()   File "/data1/lxw/code/lolcats/distill_llama.py", line 393, in main     final_metrics = finetune_trainer.evaluate(model, step=-1, max_batches=None, prefix='final')                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^   File "/data1/lxw/code/lolcats/src/trainer/finetune_seq2seq.py", line 68, in evaluate     return self.eval_step(*args, **kwargs)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^   File "/data1/lxw/code/lolcats/src/trainer/finetune_seq2seq.py", line 94, in eval_step     raise ValueError("scrolls_metric is not set in the dataset") ValueError: scrolls_metric is not set in the dataset

hi there! sorry for the late response.
just to double-check, are you getting this error from calling the sample script like  ?
python distill_llama.py --model_config distill_llama3_8b_lk_smd_wtk64_fd64_w01 \
--distill_config distill_alpaca_clean_xent0_mse1000_lr1e-2 \
--finetune_config finetune_lora_qkvo_alpaca_clean \
--eval_config eval_alpaca_clean \
...

and does the error only happen at the end of calling the script?
I'm a bit confused by the error message, but what I think is happening is that the metric is not being loaded here
to debug, are you able to:

import load_metric from huggingface datasets? i.e.,

from datasets import load_metric

Run this function? in dataloaders/utils/setup.py


ValueError: time data does not match format

Out of nowhere I started getting the following error:
Traceback (most recent call last):
File "/usr/local/bin/rsumpwebchart.py", line 25, in
main()
File "/usr/local/bin/rsumpwebchart.py", line 21, in main
webchart.create_chart(homedir)
File "/usr/local/lib/python3.5/dist-packages/raspisump/webchart.py", line 36, in create_chart
todaychart.graph(csv_file, filename, bytes2str)
File "/usr/local/lib/python3.5/dist-packages/raspisump/todaychart.py", line 54, in graph
converters={0: bytes2str}
File "/usr/lib/python3/dist-packages/numpy/lib/npyio.py", line 985, in loadtxt
items = [conv(val) for (conv, val) in zip(converters, vals)]
File "/usr/lib/python3/dist-packages/numpy/lib/npyio.py", line 985, in
items = [conv(val) for (conv, val) in zip(converters, vals)]
File "/usr/local/lib/python3.5/dist-packages/raspisump/todaychart.py", line 45, in bytesconverter
return strconverter(s)
File "/usr/lib/python3/dist-packages/matplotlib/dates.py", line 287, in call
return date2num(datetime.datetime(*time.strptime(s, self.fmt)[:6]))
File "/usr/lib/python3.5/_strptime.py", line 504, in _strptime_time
tt = _strptime(data_string, format)[0]
File "/usr/lib/python3.5/_strptime.py", line 343, in _strptime
(data_string, format))
ValueError: time data '\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0013:58:01' does not match format '%H:%M:%S'
I haven't had the chance to dig in any deeper.  Just curious if anyone may have run into this.

Yes, I have seen that.  If you open up your csv file find the line that has \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0013:58:01'  .    Delete that line and save the file.  This happens on corrupted readings very rarely.   It's happened to me 3 times over the past four years.  After the line is deleted the graph will be able to be created.

That was it.  Thanks!


Fix the upgrade path for 2.8.x traditional and DBless

Description
What did you change and why?

After talking with Michael Martin, he confirmed that in 2.8.x, traditional and DB less can both go directly to 3.2.x. Hybrid still must do the indirect route however.

Include any supporting resources, e.g. link to a Jira ticket, GH issue, FTI, Slack, Aha, etc.
Testing instructions
Netlify link: /gateway/latest/upgrade/
Checklist

[x] Review label added
[x] PR pointed to correct branch (main for immediate publishing, or a release branch: e.g. release/gateway-3.2, release/deck-1.17)

3.2 was rolled back. Can you please open this PR against release/gateway-3.2 instead?


Error while creating a highlighting while selecting a single line with visual line mode

See title.
Selecting a single line in visual line mode and then pressing f<CR> causes the following error:
Error detected while processing function highlighter#Command[22]..<SNR>168_SetHighlight[28]..<SNR>168_GetVisualLine:
line    9:
E951: \% value too large

After the error is dismissed the line is successfully highlighted
Digging around, the error seems to occur at line 264 of autoload/highlighter.vim. One guess is that it is caused by an of-by-one error and indeed changing l:right to l:right-1 does cause the error to go away. I'm not sure what the intended purpose of the function is as the highlighting seems to work even when the error occurs so I'm not sure that this fix preserves the intended functionality of the code.

Thank you for reporting this error 👍
Now there is an update. Would you please try it?

The error seems to be fixed now!

Great, Thanks!


Make swaybar and swaybg shell surfaces

Per discussion in #343

Just realized I used spaces instead of tabs. I'll fix that once I got feedback.

Other than changing space to tabs. Is there anything else you want me to change?


Incremental build support for json-based frontend

Hi!
In this PR we add incremental build support for json-based frontend. All we need is provide a list of changed files in a txt file and feed in through flag --changed-files-index for infer analyzejson command.
Please let us know your thoughts. Thanks!

Hi @xi-liu-ds, sorry for the delay. It looks like this duplicates more code still from InferAnalyze.ml. Would that duplication still be needed if parsing the json was done in a capture phase instead of together with the analysis? It feels to me like doing so would give you incremental analysis for free as well as being more maintainable, as the analysis phase would be just the normal Infer analysis. Also there wouldn't need to be an analyzejson command.
I think capturing json could be done similarly as how we capture clang compilation databases so you could take inspiration from those code paths. We use it like this:
# does capture + analysis
$ infer run --compilation-database file.json
# equivalent to running these two commands:
$ infer capture --compilation-database file.json
$ infer analyze

Similarly we'd have two options --json-cfg and --json-tenv that have to be specified together or not at all:
# does capture + analysis
$ infer run --json-cfg cfg.json --json-tenv tenv.json
# equivalent to running these two commands:
$ infer capture --json-cfg cfg.json --json-tenv tenv.json
$ infer analyze

So we would have a new driver mode JsonSIL set similarly to ClangCompilationDB. Then it's just a matter of separating out the capture phase out of InferAnalyzeJson.ml and into its own module and call it from Driver.ml, then the analysis phase can be deleted from InferAnalyzeJson.ml (and so the rest of the file with it) as it's not a separate thing from the normal infer analysis anymore.
Would that approach work for you and are there any blockers? I'm not sure how much we need to ensure backwards compability or we can just get rid of the analyzejson command altogether if we go down this route, for example.

Hi @xi-liu-ds, sorry for the delay. It looks like this duplicates more code still from InferAnalyze.ml. Would that duplication still be needed if parsing the json was done in a capture phase instead of together with the analysis? It feels to me like doing so would give you incremental analysis for free as well as being more maintainable, as the analysis phase would be just the normal Infer analysis. Also there wouldn't need to be an analyzejson command.
I think capturing json could be done similarly as how we capture clang compilation databases so you could take inspiration from those code paths. We use it like this:
# does capture + analysis
$ infer run --compilation-database file.json
# equivalent to running these two commands:
$ infer capture --compilation-database file.json
$ infer analyze

Similarly we'd have two options --json-cfg and --json-tenv that have to be specified together or not at all:
# does capture + analysis
$ infer run --json-cfg cfg.json --json-tenv tenv.json
# equivalent to running these two commands:
$ infer capture --json-cfg cfg.json --json-tenv tenv.json
$ infer analyze

So we would have a new driver mode JsonSIL set similarly to ClangCompilationDB. Then it's just a matter of separating out the capture phase out of InferAnalyzeJson.ml and into its own module and call it from Driver.ml, then the analysis phase can be deleted from InferAnalyzeJson.ml (and so the rest of the file with it) as it's not a separate thing from the normal infer analysis anymore.
Would that approach work for you and are there any blockers? I'm not sure how much we need to ensure backwards compatibility or we can just get rid of the analyzejson command altogether if we go down this route, for example.

Thanks Jules for the suggestion! We are aware that analyze json has some code duplication from InferAnalyze.ml. We are investigating the solution you provided and see if it can fully replace the current experience from InferAnalyzeJson.ml.

Hi @jvillard So sorry about the delay on this PR. I finally had chance to look deep into it this week.
It turns out that your suggestions are great and helped to remove lots of duplicate code! Thank you so much!
Like you suggested, now we can do infer capture --json-cfg cfg.json --json-tenv tenv.json to run json frontend analysis. And for incremental build, all we need is infer capture --json-cfg cfg.json --json-tenv tenv.json --incremental-analysis --changed-files-index change_file_index.txt
Please take a look when you get a chance. Thanks again!

Thanks for your comments! Now the incremental build support has been improved even more. It can be trigger by using the following commands:
infer capture --cfg-json cfg.json --tenv-json tenv.json
infer analysis --changed-files-index change_file_index.txt -j 1

Or just simply
infer run --cfg-json cfg.json --tenv-json tenv.json --changed-files-index change_file_index.txt -j 1

Fix unit tests since now we merged infer analyzejson into infer run now.

thanks @xi-liu-ds, very happy to have finally merged this! :tada:
I also merged InferAnalyzeJson into CaptureSILJson in e6809d9b5196311d6cc68eb409313645da63ef81


⚠ DDoS-Relay EU-N-hel1-2 has degraded performance

In 7efa2a6, DDoS-Relay EU-N-hel1-2 (http://<IP_ADDRESS>:42069/;csv) experienced degraded performance:

HTTP code: 200
Response time: 231 ms

Resolved: DDoS-Relay EU-N-hel1-2 performance has improved in 0588c5c after 6 minutes.


Is this supported in Grafana 5.3.2 version ?

I exported a dashboard containing echart panel from grafana 5.2.1 version to 5.3.2 version. And I don't see the panels in 5.3.2. I wonder if the echart panel is supported in 5.3.2. Please comment on what would be the problem.

Hi @VinayDanda,
Currently this is super-beta stage, sorry for that 😅 but should be as AFAIK it's not using any specific functionality and I'm developing using a 5.3.2 version to test.
Can you please open borwser's developers tool and see if there's any specific error message in there?
Thanks


[Task]: Create Flex layout component.

Use Flex component provided by WDS.
set default position as relative. Can be over-ridden by props.
If isDropTarget, the subscribe to position observer to track size of the layout.
Pass an appropriate id to the component: layout-${layoutID}.
Use appropriate default values for rowGap, columnGap etc. (Check with Taras).
Use container queries if required. WDS Flex component supports it. add isContainer as prop to enable container queries.

Use case no. 3  (isDropTarget) will be handled in a separate ticket:
#27287


humbug_get_contents() is deprecated

  [Humbug\SelfUpdate\Exception\HttpRequestException]
  humbug_get_contents() is deprecated since 1.1.0 and will be removed in 4.0.0. Use Humbug/get_contents() instead.

4.0.0, not 2.0.0?


Lunar: Add explanation of variables and code structure.

To help those porting, or just reading the original code.

thanks!


Gridsizer not always fully covering frame

Steps to reproduce:
Create a new frame.
Remove sizer_1.
Add a 20x20 GridSizer.
The grid will sometimes not fully cover the window.

This issue doesn't happen all the time. It happens randomly.
My info:
M1 Mac
Mac OS 11.1
wxPython 4.0.6
wxGlade 1.0.1
Python 2.7.14

I can't see this on my installations. I don't have a 4.0.6 on macOS, though.
Are you sure that the screenshot is from a GridSizer, not FlexGridSizer?

I'm pretty sure it was from GridSizer.

I was doing some testing and I found I could reproduce this issue using a Gridbagsizer. So it could be a gridbagsizer. When I create a frame and replace the boxsizer with a gridbagsizer I see this issue. The problem is the Size attribute under the Common tab is checked and set to 585, 525. I feel this should not happen.

The frame was what actually had its Size attribute under the Common tab set to 585, 525, not the gridbagsizer. I am not sure why the gridbagsizer doesn't expand to fill the entire frame like a gridbagsizer would. This problem is also seen with the flexgridsizer.  Attached is a wxg file that demonstrates this issue.
problem.zip

The gridbagsizer is not supposed to fill the available space unless setting a row or col to be growable.
If you use a gridbagsizer with 20x20, this is a clear indication that your overall structure has a problem.
From your bug reports I would guess you are trying to use grid sizers to resemble pixel placement of widgets.
Forget about this. It's a mess and a waste of time.
Please follow the documentation and keep in mind:
http://wxglade.sourceforge.net/docs/wxbasics.html#sizers-layout-managers
Note
For your own projects, always use the simplest available sizers. Usually you will need mainly box sizers and maybe one or two FlexGridSizers.
Use nested sizers to match the hierarchical / logical structure of your project. This will make it easy to re-arrange things to find the best user interface.
Never ever try to use a Grid(Bag)Sizer as main sizer of a window trying to resemble pixel placement or Tkinter’s grid geometry manager. This is a mess to create and maintain. Actually, a GridBagSizer is rarely needed.


Add Pending Activity check

Description
This PR addresses issue occurring while re-scheduling a workflow with same instance id, while previous run was terminated but still an activity left un-finished.
I have tried to enlist the detailed description of issue and thought process behind fix in following comment: https://github.com/dapr/dapr/issues/6454#issuecomment-1670041771
Another workflow with same instance Id is allowed to Run.
That's why the concept of Generation in there. And also, in https://github.com/dapr/dapr/pull/6455#issue-1745212239 , @cgillum specifically talks about it, so that means that it is Allowed.
To keep behavior consistent, I strongly feel that thus any Workflow terminated once, should be allowed to be scheduled with same id again.
It is just that the definition of Complete needs to be defined correctly i.e. Workflow with same ID should not be allowed just because previous Workflow run was Terminated. It should be allowed only if No Activity is remaining to be returned back as Completed or Failed, in addition to Workflow Completed.
So, let's analyze following 2 cases:
Case 1:
Scheduled a workflow W1 with activities A1, A2, A3 and A4. Let's Assume, workflow id is ID1.
In A2, put a sleep of 30 seconds.
After 10 seconds of scheduling workflow, Terminate it.

Here, re-scheduling of this workflow should NOT be allowed as A2 has not yet returned, even though Workflow itself has been Terminated.
Case 2:
Scheduled a workflow W1 with activities A1, A2, A3 and A4. Let's Assume, workflow id is ID1.
In A2, put a sleep of 30 seconds.
After 10 seconds of scheduling workflow, Terminate it.
Wait for 25 more seconds. By this time, A2 has also Completed. A3 and A4 will not be called.
At this time, schedule this workflow again with same id ID1.
Here, re-scheduling of this workflow SHOULD be allowed as A2 has returned, and Workflow itself has been truly Terminated and Completed.
Issue reference

Please reference the issue this PR will close: #6454
Checklist
Please make sure you've  completed the relevant tasks for this PR, out of the following list:

[x] Code compiles correctly
[ ] Created/updated tests
[ ] Unit tests passing
[ ] End-to-end tests passing
[ ] Extended the documentation / Created issue in the https://github.com/dapr/docs/ repo: dapr/docs#[issue number]
[ ] Specification has been updated / Created issue in the https://github.com/dapr/docs/ repo: dapr/docs#[issue number]
[ ] Provided sample for the feature / Created issue in the https://github.com/dapr/docs/ repo: dapr/docs#[issue number]

/ok-to-test

/test-sdk-all


Can't run samples on S5.

When I run samples on S5 I only get a screen with clear color displayed. Nothing gets rendered besides that. Checking logcat it outputs a couple of <core_glEnableVertexAttribArray:193>: GL_INVALID_VALUE
I'm on Android 5.0. G900M.
Here follows logcat output.

Hi @phi-lira ,
I think you can only use the devices that are mentioned in the developer documentation.
Hardware Requirements: Samsung Galaxy Note 4 or Samsung Galaxy S6.
Hope it helps.

The S5 I have has a QualComm GPU.  Is your a Mali device?
And @lokeshguddu if you run on a device other than Note 4 or S6, then it will fall back to the monoscopic renderer.  It will still run, but you will only see one eye, centered in the middle of the screen.

@thomasflynn  Mine is Qualcomm Snapdragon too. Can you send me an apk so I can confirm is not something on my build settings?

There's a limit on the size of attachments we can send over email and even simple-sample is just barely over the limit.  Instead, I created a branch and checked them in :).  Go here:
https://github.com/thomasflynn/GearVRf/tree/s5/GVRf/apks
I have apks for both simple-sample and solar-system.  They both work on my s5.  Let me know if they work for you.

@thomasflynn Thanks for the apks and sorry for the delay to reply this. I got tangled in some issues.
Ok. Both of them are working perfecly here, which means it's definitely something on my environment. Do you make any changes to manifest (like vr-dual or something else) or to project to get this working on S5?

no changes.

Oh boy. I'll try to figure it out what's happening.
I'll close this.

Found out the problem. It does work on S5 when building with lollipop libraries (api 21 and above).
I built with api 19 and it's working now.
I'm not sure if this is a known issue or not. That's why I'm reopening this.

perhaps we need to start comparing configurations?  I changed simple-sample's AndroidManifest.xml from:
<uses-sdk
    android:minSdkVersion="19"
    android:targetSdkVersion="21" />

to
<uses-sdk
    android:minSdkVersion="21"
    android:targetSdkVersion="21" />

and that still works.  Also made sure all my android sdks were up to date.  What else do I need to do?

I was previously building libOVR, VrApi, VrAppFramework and Framework with Library 5.0.1 set on my Android build target. Now that I changed it to 4.4.2 it worked.

I also changed Oculus SDK 0.6.0 to 0.6.1 (but I'm almost certain I tested before changing build path and it didn't work)

ok, set all my projects to 5.0.1, still worked.  still worked.  I've been using Oculus SDK <IP_ADDRESS> since i did the port to it.  maybe there's a difference between building on Linux vs Windows.  i'm about to be sucked into endless meetings most of the rest of the day.  I'll try a build from Windows after I get out.

No. Don't bother. I just reverted back to 5.0.1 and it worked. I guess this is one of those problems that gets fixes by itself and I'm just glad it's working now.
Closing again. Sorry for the mess.


Scene Cut Detect

Apple Feedback Assistant ID: MISSING!
I would love for machine learning to be able to identify each cut and to recommend a cut point. The feature works well in Davinci and is helpful in workflows when you want to reduce how much footage you want to send to a collaborator.

There's a couple of third party tools for this:
https://ulti.media/fcpx-cut-finder/
https://www.digitalrebellion.com/promedia/

Also, if you haven't already, you should definitely file feedback, and edit your original post to include the Feedback ID:
https://feedbackassistant.apple.com


Autocomplete cannot be displayed if ctrl/cmd+space is already bind by something else

Environment

Elixir & Erlang/OTP versions (elixir --version): Elixir 1.14.3 (compiled with Erlang/OTP 25)
Operating system: Linux 5.15.0-58-generic #64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux
How have you started Livebook (mix phx.server, livebook CLI, Docker, etc): mix phx.server
Livebook version (use git rev-parse HEAD if running with mix): 76fec4d1621cf6c1e5b97554faeff26215876cee
Browsers that reproduce this bug (the more the merrier): Chromium
Include what is logged in the browser console: irrelevant
Include what is logged to the server console: irrelevant

Current behavior
Currently, the autocompletion is bonded to ctrl+space on Linux and cmd+space on Mac. However, this hotkey is widely used by launchers such as kupfer and alfred. So, it's impossible to open the autocompletion prompt in LiveBook without closing the launcher.
Expected behavior
Either:

Allow rebinding of the hotkey, either in UI or at least somewhere in the project configuration.
Provide an alternative hotkey.
Automatically show the autocomplete prompt while typing.
Add a button in the UI or a line in the context menu to show the autocomplete prompt.

Automatically show the autocomplete prompt while typing.

Don't we automatically show autocompletion while typing? I guess we don't show it immediately after the . but that's something we can add I believe.


feat: add filter_boxes method

This PR adds a filter_boxes method in the core DetectionPostProcessor which performs the following:

NMS with a high threshold to eliminate boxes included in others. NMS is implemented in Numpy (Fast-RCNN implementation).
Merging for boxes with a consequent IOU, to avoid overlapping of letters which would appears in both words.

For now, only straight bounding boxes are supported, as the computation of NMS/boxes to merge is slightly harder when dealing with rotated boxes. In case of rotated boxes, it will simply return the array of boxes without filtering.
Closes #330
Any feeback is welcome!

Also, this PR modifies the default output behaviour (cf the failed unittest in the API)

Changes:

nms is now implemented in metrics, but not used here.
the filter_boxes method uses box_ioa (which is implemented in metrics) to merge boxes above a threshold. This will remove boxes included in others or merge those who overlap significantly.
a resolve_enclosing_boxarray function is implemented in geometry.
added corresponding tests.


(Feature/Styling) Opportunity Card Updated

Description
Redesign of the job/opportunity card and make it complement the whole website.  Make the card more intutive and easy to see.
Please include a summary of the change and which issue is fixed. List any dependencies that are required for this change.
I have only made changes to files needed for it that were opporutunity card and its styles. Rest are as it is. I have made the card more visible, fixed the image layout, added some classes and button props and make it visually appealing.
Fixed #194
Type of change
Visual Change/ Layout / UI design
Please check options that are relevant to your PR.

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] This change requires a documentation update

Checklist:

[x] I have pulled the latest changes in the repository
[x] I have squashed my commits
[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings

@mohitms007 Looks nice to me can you keep Apply button on the right bottom of card?
CC: @abdus

@mohitms007 Looks nice to me can you keep Apply button on the right bottom of card?
Increase shadow a bit on hover, not much just a little.
Remove top blue bar
CC: @abdus

Sure! Will fix it immediately.

@mohitms007 Looks nice to me can you keep Apply button on the right bottom of card?
Increase shadow a bit on hover, not much just a little.
Remove top blue bar
CC: @abdus

Fixed it.

@mohitms007 Cards are not visible completely in small screens. Please check this thing. Rest seems good.

@mohitms007 Cards are not visible completely in small screens. Please check this thing. Rest seems good.

Fixed it.

@mohitms007 That's the problem with some other screen sizes too. Please check for all screens before you update your PR.
Also, do take latest pull from upstream.

@mohitms007 That's the problem with some other screen sizes too. Please check for all screens before you update your PR.
Also, do take latest pull from upstream. Rest everything seems fine. Please update these changes so that I can merge your PR.

Checked all the screens works fine now


OnEach does not preserve data type

This breaks classical simulation which needs the precise data type to convert between values and bits.
from qualtran import QInt
from qualtran.bloqs.arithmetic.bitwise import BitwiseNot

def test_bitwise_not(inp, expected_result):
    bloq = BitwiseNot(QInt(4))
    (result,) = bloq.call_classically(x=inp)
    assert result == expected_result

test_bitwise_not(0, expected_result=-1)
# ValueError: Too-large classical QInt(4): 15 encountered in BitwiseNot<0>.x

test_bitwise_not(-1, expected_result=0)
# ValueError: Negative classical value encountered in val

Would specifying a dtype for OnEach solve the problem?

Would specifying a dtype for OnEach solve the problem?

Yep I think so, by updating the signature. and passing the dtype to the split in the decomp.
https://github.com/quantumlib/Qualtran/blob/157459ef8c267b18d3a7f79fe4bd5d7653a21636/qualtran/bloqs/basic_gates/on_each.py#L63-L69
But by changing bloq attribute n to dtype, we need to update all call sites, and this may make things more verbose. Especially because a user who wants to apply OnEach usually doesn't care about the dtype.

A somewhat hacky fix would be to add an optional dtype to the constructor and then use that if it's not None, or add a specialized version for typed registers.

Another solution would be a factory method, but this would also require every call site to be changed I think.

I think this was fixed by #1283 but the new parameter is not documented! cc @NoureldinYosri


Release 0.1.3

@rultor release, tag is 0.1.3

@rultor release, tag is 0.1.3

@mkanev OK, I will release it now. Please check the progress here

@rultor release, tag is 0.1.3

@mkanev Done! FYI, the full log is here (took me 3min)