Get translations inside the components method

I am trying to use translations object inside the methods. I lost more than 1 hour with this and finally came with this solution, but it is really intuitive to me. Is there any shorter way, because I can't find it in documentation.
export default {
    data () {
        return {
            trans: this.$store.state.i18n.translations[this.$store.state.i18n.locale],
            ...
        }
    },
    methods: {
        ...
        setTitle (index, item) {
            console.log('--- TITLE ---');
            console.log(this.trans['services.' + index + '.items.' + item + '.title']);
            return this.trans['services.' + index + '.items.' + item + '.title'];
        }
        ...
    }
}

@tikiatua
I'm using another package to set the page header. I'm trying to use your i18n package for the translation.
I get this.$t is not a function, which makes sense, I guess, but I'm not sure how to correct it.

export default {
  metaInfo: {
    title: this.$t('login')
  }
}

I also tried sticking it in created () but in that instance this is dealing with data, not the component.

Hi @daveo1001,
It is a little tricky to follow your code logic, given only the snippets above. However, this is usually related to the current component and is only available if the component is already initialized.
As a first step: try to use mounted() instead of created(). https://vuejs.org/v2/guide/instance.html#Lifecycle-Diagram
If this does not work, I would recommend to use the functions provided on the vue instance i.e. Vue.i18n.translate(..). see #50 for an example on how to use it with vue router.

nope and nope :/
But I figured it out. The package i'm using for setting title in header had an example.
Thanks for the quick response!

So basically you need to use a computed property?

I don't really get the wizardy portion of vue but turning the metaInfo from an object into a function got things cooking. Oh, and I had to move this.$t() into a lifestyle function instead of being inside data, which makes sense but I wasn't thinking. Here's the final working code.

export default {
  data: () => ({
    title: '' // can't put this.$t() here
  }),
  metaInfo () {
    return {
      title: this.title
    }
  },
  created () {
    this.title = this.$t('login')
  }
}

Thanks again for hanging out with me as I got through this!

hi i need help with my code
`

Hi @daplan128
Thank you for your request. From what I understand, you try to iterature over this.helpTitles to construct a translated object to push onto the this.helpInfo array. However this.helpTitles is set as a string further above. Maybe there is something I do not understand correctly.
    methods: {
        createHelp() {
            this.info = [this.Info1, this.Info2, this.Info3, this.Info4, this.Info5, this.Info6, this.Info7, this.Info8]
            this.question = [this.Question1, this.Question2, this.Question3, this.Question4, this.Question5, this.Question6, this.Question7, this.Question8]
            // this.helpTitles is specified as string value in the data section
            for (let i = 0; i < this.helpTitles.length; i++) {
                this.helpInfo.push({
                    'id': i,
                    // where dou you get the helpTitles, info and question arrays from.
                    // this should probably be this.helpTitles, this.info and this.question
                    'title': this.$t(helpTitles[i]),
                    'answear': this.$t(info[i]),
                    'question': this.$t(question[i])
                })
            }
        }
    },
    mounted() {
        this.createHelp()
    }

@tikiatua This is my original code, it shows the support information of my website, each title has a series of questions and answers saved within a .json file with all the information to be translated, the app opens correctly with it with the browser language but when I change the language with a switch, the data is not rendered, add metaInfo as explained in the comments and try to add $ t in metainfo and in the method but I get an error I don't understand where I should add $ t so that the title is translated with its questions and answers (these are organized through the helpItem component)
<template>

{{ $t("helpage.help") }}

{{ $t("helpage.table") }}

{{help}}

{{ help.title }}:

                <HelpItem :question="help.question" :answear="help.answear" :num="help.id"/>

{{ $t("helpage.ask") }}

{{$t('general.helpInfo.floaterInfo1')}}

{{$t('general.helpInfo.email')}}

{{$t('general.helpInfo.floaterInfo2')}}

{{ $t("helpage.feedback") }}

{{$t('general.helpInfo.feedbackInfo')}}

{{ $t("helpage.table") }}

{{help}}

</template>

Hmm.. Ok. I think, I know the reason for the problem. The $t function returns an object that is not reactive.
This means, that changing the locale on the store will not change values already returned by this.$t(...). So the information that is returned in your data() function will not be automatically updated, if the locale on the store changes. Likewise, the information stored in the this.helpInfo will also not be updated, when you change the locale.
I presume, that it should work, if you return the translations as computed properties instead of putting them on the data object – could you try this out.
If this works, the next step would be to get the integration with the metaInfo() method working.

@daplan128: I created a small example that works as intended. You can save it as html file and open it directly in the browser. The example is not yet done with the metaInfo plugin.
<!DOCTYPE html>

  <meta charset="utf-8">
  <title>vuex-i18n</title>


Missing field "filteredBy.resourceType" parsing Subscription/SubscriptionTopic

Hi everybody,
we think there is a problem with all resource fields named "resourceType".
For Example:
{
	"resourceType": "Subscription",
	"id": "admission",
        ....
        "filterBy": [
		{
			"resourceType": "AuditEvent",
			"searchParamName": "PatientId",
			"value": "Patient/123"
		}
	],
}

In that case, when hapi-fhir parses that resource the field filterBy.resourceType is missing.
We think it's caused by JsonParser.java when checks:
if ("resourceType".equals(nextName))
Is it possible ?
 Did you figured out have to resolve it?
thank you so much

Hi @ebra89 ,
we developed a workaround in the subscription provider, where we patch the resource before persisting it.
bye

  @Create()
  public MethodOutcome createSubscription(@ResourceParam Subscription subscription,
      RequestDetails requestDetails) {

        byte[] oriStream = requestDetails.loadRequestContents();
        try {
          JSONObject oriObject = new JSONObject(new String(oriStream, "UTF-8"));
          if (oriObject.has("filterBy")) {
            JSONArray filterBy = oriObject.getJSONArray("filterBy");
            for (int i = 0; i < filterBy.length(); i++) {
              if (filterBy.getJSONObject(i).has("resourceType")) {
                String resourceType = filterBy.getJSONObject(i).getString("resourceType");
                subscription.getFilterBy().get(i).setResourceType(resourceType);
              }
            }
          }
        } catch (JSONException | UnsupportedEncodingException e) {
          logger.warn(e.getMessage(), e);
        }

Thanks for reply @abozzetto,  we also thought of doing a similar thing, waiting for R5 release which is scheduled for May 2023
thank you


tf.tpu.experimental.initialize_tpu_system fails to work on nightly builds

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Google Colaboratory (Linux)
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): tf-nightly_v2.3.0.dev20200619
Python version: v3.6.9
Bazel version (if compiling from source): N/A
GCC/Compiler version (if compiling from source): N/A
CUDA/cuDNN version: N/A
GPU model and memory: N/A
TPU: Google Colab runtime with TPU accelerator

Describe the current behavior
tf.tpu.experimental.initialize_tpu_system(tpu_cluster_resolver) raises an unexpected error. The stack trace containing this error is provided underneath.
The sample notebook that was being used to train an EfficientNetB0 model with TPUStrategy containing the error message is provided here.
Describe the expected behavior
A ResNet50 model (as EfficientNetB0 is only present in TF-nightly) with similar code is able to run successfully with TPUStrategy and there are no such errors reported while calling tf.tpu.experimental.initialize_tpu_system.  A notebook with the corresponding training code for TFv2.2 can be found here.
Standalone code to reproduce the issue
Just calling tf.tpu.experimental.initialize_tpu_system using the standard mechanism on a Colab runtime with TPU should suffice.
tpu_url = 'grpc://' + os.environ['COLAB_TPU_ADDR']
tpu_cluster_resolver = tf.distribute.cluster_resolver.TPUClusterResolver(tpu=tpu_url)

tf.config.experimental_connect_to_cluster(tpu_cluster_resolver)
tf.tpu.experimental.initialize_tpu_system(tpu_cluster_resolver)

strategy = tf.distribute.experimental.TPUStrategy(tpu_cluster_resolver)

Other info / logs
Running on TPU  ['<IP_ADDRESS>:8470']
INFO:tensorflow:Initializing the TPU system: grpc://<IP_ADDRESS>:8470

INFO:tensorflow:Initializing the TPU system: grpc://<IP_ADDRESS>:8470

INFO:tensorflow:Clearing out eager caches

INFO:tensorflow:Clearing out eager caches

---------------------------------------------------------------------------

InvalidArgumentError                      Traceback (most recent call last)

<ipython-input-4-a42f01f7e70e> in <module>()
      6
      7 tf.config.experimental_connect_to_cluster(tpu)
----> 8 tf.tpu.experimental.initialize_tpu_system(tpu)
      9 tpu_strategy = tf.distribute.experimental.TPUStrategy(tpu)

3 frames

/usr/local/lib/python3.6/dist-packages/tensorflow/python/tpu/tpu_strategy_util.py in initialize_tpu_system(cluster_resolver)
    101     context.context()._clear_caches()  # pylint: disable=protected-access
    102
--> 103     serialized_topology = output.numpy()
    104
    105     # TODO(b/134094971): Remove this when lazy tensor copy in multi-device

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in numpy(self)
   1061     """
   1062     # TODO(slebedev): Consider avoiding a copy for non-CPU or remote tensors.
-> 1063     maybe_arr = self._numpy()  # pylint: disable=protected-access
   1064     return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
   1065

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _numpy(self)
   1029       return self._numpy_internal()
   1030     except core._NotOkStatusException as e:  # pylint: disable=protected-access
-> 1031       six.raise_from(core._status_to_exception(e.code, e.message), None)  # pylint: disable=protected-access
   1032
   1033   @property

/usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, from_value)

InvalidArgumentError: NodeDef expected inputs 'string' do not match 0 inputs specified; Op<name=_Send; signature=tensor:T -> ; attr=T:type; attr=tensor_name:string; attr=send_device:string; attr=send_device_incarnation:int; attr=recv_device:string; attr=client_terminated:bool,default=false; is_stateful=true>; NodeDef: {{node _Send}}

Typically, this bug is prevalent only on nightly builds (master branch) and not on TF v2.2 release.
/cc: @tanzhenyu

I have seen this issue on TF 2.2.0. I think there is something lingering on the TPU cores that initialize_tpu_system is unable to clear out.

I have tried in colab with TF version 2.2 and i am not seeing any issue.However i am seeing this issue with nightly versions(`2.3.0-dev20200621').Please, find the gist here.Thanks!

Yes @ravikyram, thanks for acknowledging.

It is due to a version mismatch between your client and TPU worker. Did you use nightly on both instances?

Hi @rxsang, not sure if it's an error regarding the TPU version mismatch between the worker and the client. I had encountered the error on Colab. (Colab TPU runtimes do not provide for choice of versions for the TPU workers) I might need to try the same on Compute Engine Cloud TPUs for checking operability amongst different TPU worker versions.
AFAIK client and worker versions are interoperable as previously I had used TPU workers running TFv1.15 with TFv2.x, so I think.
Thanks.

@swghosh Yeah, Colab always defaults to the latest stable version of TPUs because of technical limitations. The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

@frankchn Thanks for the clarification. Much help.

@swghosh Yeah, Colab always defaults to the latest stable version of TPUs because of technical limitations. The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

@frankchn
I found that tf 2.3 has been released, is there an update plan for the tf version on colab?

The Colab roll out process lags the TensorFlow one by a few days, but it is being rolled out right now and TF 2.3 will be usable by the end of this week. When that happens, TF 2.2 will not be usable any more because of the same incompatibility between versions.

Ok, thanks frank.

still got following error with tf 2.3.0  tpu on colab.
tensorflow.python.framework.errors_impl.InternalError: RET_CHECK failure (learning/brain/google/xla/distributed_tpu_rewrite_pass.cc:1413) arg_shape.handle_type != DT_INVALID
2020-08-06 01:47:30.383712: W ./tensorflow/core/distributed_runtime/eager/destroy_tensor_handle_node.h:57] Ignoring an error encountered when deleting remote tensors handles: Invalid argument: Unable to find the relevant tensor remote_handle: Op ID: 36311, Output num: 0
Additional GRPC error information from remote target /job:worker/replica:0/task:0:
:{"created":"@1596678450.383612323","description":"Error received from peer ipv4:<IP_ADDRESS>:8470","file":"external/com_github_grpc_grpc/src/core/lib/surface/call.cc","file_line":1056,"grpc_message":"Unable to find the relevant tensor remote_handle: Op ID: 36311, Output num: 0","grpc_status":3}

Please, find the gist here.Thanks!

From the trace, it seems you enabled tf summary inside TPU computation. Can you try calling tf.config.set_soft_device_placement(True) at the beginning, so outside compilation can be enabled?

Now, it seems to initialize well with 2.3.0 and nightly with Colab. However, whenever I run gcloud ai-platform training scripts it always produce the same error whatever version of tf I use.. It is really frustrating. There is any single clue for solution anywhere even in Tensorflow official document.

I'm not familiar with the gcloud ai-platform scripts, which TF and TPU version do that script use? @gagika Gigik, anyone from Cloud TPU team could help with that?

For choosing matching Tensorflow version on TPU in colab and kaggle you can use the code below (see here)
!pip install cloud-tpu-client

import tensorflow as tf
from cloud_tpu_client import Client
print(tf.__version__)

Client().configure_tpu_version(tf.__version__, restart_type='ifNeeded')

For using training on TPUs on ai platform you can follow the steps here. At the moment AI supports TF versions 1.13, 1.14, 1.15, 2.1, and 2.2 .

@swghosh Yeah, Colab always defaults to the latest stable version of TPUs because of technical limitations. The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

You don't really understand how frustrating it's becoming using some Tensorflow packages. I practice on Colab and do more work in Kaggle. In Kaggle the line from tensorflow.keras.preprocessing import image_dataset_from_directory only works in tf==2.3, while it works in default 2.2 in Colab.
Also in Kaggle initiating TPU fails in tf 2.3, but works in 2.2....  The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

You don't really understand how frustrating it's becoming using some Tensorflow packages. I practice on Colab and do more work in Kaggle. In Kaggle the line from tensorflow.keras.preprocessing import image_dataset_from_directory only works in tf==2.3, while it works in default 2.2 in Colab.
Also in Kaggle initiating TPU fails in tf 2.3, but works in 2.2....  The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

You don't really understand how frustrating it's becoming using some Tensorflow packages. I practice on Colab and do more work in Kaggle. In Kaggle the line from tensorflow.keras.preprocessing import image_dataset_from_directory only works in tf==2.3, while it works in default 2.2 in Colab.
Also in Kaggle initiating TPU fails in tf 2.3, but works in 2.2....

Right now Kaggle is using tf 2.3 and Colab tf 2.4, so the issue should be resolved on both.
Please let me know if it still there.

@swghosh Yeah, Colab always defaults to the latest stable version of TPUs because of technical limitations. The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

You don't really understand how frustrating it's becoming using some Tensorflow packages. I practice on Colab and do more work in Kaggle. In Kaggle the line from tensorflow.keras.preprocessing import image_dataset_from_directory only works in tf==2.3, while it works in default 2.2 in Colab.
Also in Kaggle initiating TPU fails in tf 2.3, but works in 2.2....

Right now Kaggle is using tf 2.3 and Colab tf 2.4, so the issue should be resolved on both.
Please let me know if it still there.

Now, it seems to initialize well with 2.3.0 and nightly with Colab. However, whenever I run gcloud ai-platform training scripts, it always produces the same error whatever version of tf I use.. It is really frustrating. If it is all about the version mismatch, I can't find any single clue for solution anywhere.

gcloud ai-platform now supports TF 2.3, so the issue should be resolved.

Now, it seems to initialize well with 2.3.0 and nightly with Colab. However, whenever I run gcloud ai-platform training scripts, it always produces the same error whatever version of tf I use.. It is really frustrating. If it is all about the version mismatch, I can't find any single clue for solution anywhere.

gcloud ai-platform now supports TF 2.3, so the issue should be resolved.

@swghosh Yeah, Colab always defaults to the latest stable version of TPUs because of technical limitations. The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

You don't really understand how frustrating it's becoming using some Tensorflow packages. I practice on Colab and do more work in Kaggle. In Kaggle the line from tensorflow.keras.preprocessing import image_dataset_from_directory only works in tf==2.3, while it works in default 2.2 in Colab.
Also in Kaggle initiating TPU fails in tf 2.3, but works in 2.2....

Right now Kaggle is using tf 2.3 and Colab tf 2.4, so the issue should be resolved on both.
Please let me know if it still there.

Same trouble on Kaggle,
Can't install or upgrade to TensorFlow 2.4
See details
Installing tensorflow==2.4...
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
osmnx 0.15.1 requires geopandas>=0.7, but you have geopandas 0.6.3 which is incompatible.
kubernetes 10.1.0 requires pyyaml~=3.12, but you have pyyaml 5.3.1 which is incompatible.
kmeans-smote 0.1.2 requires imbalanced-learn<0.5,>=0.4.0, but you have imbalanced-learn 0.7.0 which is incompatible.
kmeans-smote 0.1.2 requires numpy<1.16,>=1.13, but you have numpy 1.19.5 which is incompatible.
kmeans-smote 0.1.2 requires scikit-learn<0.21,>=0.19.0, but you have scikit-learn 0.23.1 which is incompatible.
jupyterlab-git 0.10.0 requires nbdime<2.0.0,>=1.1.0, but you have nbdime 2.0.0 which is incompatible.
hypertools 0.6.2 requires scikit-learn<0.22,>=0.19.1, but you have scikit-learn 0.23.1 which is incompatible.
google-cloud-pubsub 1.4.3 requires google-api-core[grpc]<1.17.0,>=1.14.0, but you have google-api-core 1.17.0 which is incompatible.
bokeh 2.1.1 requires tornado>=5.1, but you have tornado 5.0.2 which is incompatible.
astroid 2.3.3 requires wrapt==1.11.*, but you have wrapt 1.12.1 which is incompatible.

@swghosh Yeah, Colab always defaults to the latest stable version of TPUs because of technical limitations. The current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.
In general, we only support TPUs when the same version is used on both the user TF and on the TPUs. In practice, there is some scope for different versions working together if there are no changes in terms of protocol or op definitions (e.g. no new ops, ops didn't change signature, etc...) but it is not supported.

You don't really understand how frustrating it's becoming using some Tensorflow packages. I practice on Colab and do more work in Kaggle. In Kaggle the line from tensorflow.keras.preprocessing import image_dataset_from_directory only works in tf==2.3, while it works in default 2.2 in Colab.
Also in Kaggle initiating TPU fails in tf 2.3, but works in 2.2....

Right now Kaggle is using tf 2.3 and Colab tf 2.4, so the issue should be resolved on both.
Please let me know if it still there.

Same trouble on Kaggle,
Can't install or upgrade to TensorFlow 2.4
See details
Installing tensorflow==2.4...
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
osmnx 0.15.1 requires geopandas>=0.7, but you have geopandas 0.6.3 which is incompatible.
kubernetes 10.1.0 requires pyyaml~=3.12, but you have pyyaml 5.3.1 which is incompatible.
kmeans-smote 0.1.2 requires imbalanced-learn<0.5,>=0.4.0, but you have imbalanced-learn 0.7.0 which is incompatible.
kmeans-smote 0.1.2 requires numpy<1.16,>=1.13, but you have numpy 1.19.5 which is incompatible.
kmeans-smote 0.1.2 requires scikit-learn<0.21,>=0.19.0, but you have scikit-learn 0.23.1 which is incompatible.
jupyterlab-git 0.10.0 requires nbdime<2.0.0,>=1.1.0, but you have nbdime 2.0.0 which is incompatible.
hypertools 0.6.2 requires scikit-learn<0.22,>=0.19.1, but you have scikit-learn 0.23.1 which is incompatible.
google-cloud-pubsub 1.4.3 requires google-api-core[grpc]<1.17.0,>=1.14.0, but you have google-api-core 1.17.0 which is incompatible.
bokeh 2.1.1 requires tornado>=5.1, but you have tornado 5.0.2 which is incompatible.
astroid 2.3.3 requires wrapt==1.11.*, but you have wrapt 1.12.1 which is incompatible.

The entire version mismatches surrounding Tensorflow is absolutely
frustrating! Can't te very many Google Engineers synchronise versions and
modules all at once?
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On Fri, Jan 22, 2021 at 2:19 AM Gagik Amirkhanyan<EMAIL_ADDRESS>wrote:

Now, it seems to initialize well with 2.3.0 and nightly with Colab.
However, whenever I run gcloud ai-platform training scripts, it always
produces the same error whatever version of tf I use.. It is really
frustrating. If it is all about the version mismatch, I can't find any
single clue for solution anywhere.
gcloud ai-platform now supports
https://cloud.google.com/ai-platform/training/docs/using-tpus#tpu-runtime-versions
TF 2.3, so the issue should be resolved.
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The entire version mismatches surrounding Tensorflow is absolutely
frustrating! Can't te very many Google Engineers synchronise versions and
modules all at once?
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01/22/21,
01:01:55 PM
On Fri, Jan 22, 2021 at 2:19 AM Gagik Amirkhanyan<EMAIL_ADDRESS>wrote:

Now, it seems to initialize well with 2.3.0 and nightly with Colab.
However, whenever I run gcloud ai-platform training scripts, it always
produces the same error whatever version of tf I use.. It is really
frustrating. If it is all about the version mismatch, I can't find any
single clue for solution anywhere.
gcloud ai-platform now supports
https://cloud.google.com/ai-platform/training/docs/using-tpus#tpu-runtime-versions
TF 2.3, so the issue should be resolved.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/40622#issuecomment-765048728,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AJLJAUGQJWUERTB63FAC5D3S3DHC7ANCNFSM4OC66Z4A
.

@swghoshThe current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.

I've installed 2.2 and I still face the problem, it's super frustrating.

@swghoshThe current version of Colab TPU that runs is version 2.2, so Colab TPUs are only supported with TensorFlow v2.2 by default.

I've installed 2.2 and I still face the problem, it's super frustrating.

not

Not working


DBZ-2821 Support for CHAR VARYING use

https://issues.redhat.com/browse/DBZ-2821
Upstream PR - https://github.com/antlr/grammars-v4/pull/1957

Merged, thx!


feat(source): add new source baozimanhua

aidoku-cli version 0.3.0
Close: #280
Checklist:

[x] Updated source's version for individual source changes
[x] Set appropriate nsfw value
[x] Did not change id even if a source's name or language were changed
[x] Tested the modifications by running it on the simulator or a test device

also run cargo +nightly fmt and cargo +nightly clippy and fix the warnings

I think you need to delete Cargo.lock and recompile, you might be on an old aidoku-rs version

I think you need to delete Cargo.lock and recompile, you might be on an old aidoku-rs version

Done!

run chmod +x build.sh (or equivalent) to make the build script executable for the ci

run chmod +x build.sh (or equivalent) to make the build script executable for the ci

Done!


feat: update smartbear-supported comment

After seeing the comment a number of times being added, I thought it could be updated a little by:

Making it a little shorter
Being less conversational, as this is coming from a bot
Add a bot emoji to additionally highlight that this is a bot
Add a link to Jira to simplify navigation.
No need to explain the processes internal within SmartBear

The original text:

👋 Hi! The 'smartbear-supported' label has just been added to this issue, which will create an internal tracking ticket in PactFlow's Jira (${{steps.create.outputs.issue}}). We will use this to prioritise and assign a team member to this task. All activity will be public on this ticket. For now, sit tight and we'll update this ticket once we have more information on the next steps. See our documentation for more information.

The update text:

🤖 Great news! We've labeled this issue as smartbear-supported and created a tracking ticket in PactFlow's Jira (${{steps.create.outputs.issue}}). We'll keep work public and post updates here. Meanwhile, feel free to check out our docs. Thanks for your patience!

Let me know what you think!

Love it, thanks!


Fix character entity.

Whoops!
There were 1 warnings that will prevent this PR from being merged. Please take a look, and either fix, or provide a justification for why they can't be fixed.
WARNINGS
src/content/en/updates/2019/02/model-viewer.md#L92 - '

:tada: This has been pushed live to https://developers.google.com/web/


Colliders on Bevy meshes don't respect scale on initial tick

Happening on bevy = 0.11 and bevy_rapier3d = 0.22.0
When I load a GLTF Scene that has a scale transform that downscales the scene and spawn Colliders for its meshes, the Colliders don't match the scale until the 2nd frame.
It seems like the Colliders are always double the size of the scaled mesh, no matter what scale I set, so long as it's < 1.0.  For example, I tried spawning a scene with scale 0.005, and the debug rendered colliders are double the mesh sizes (not the original 1.0 scale).
I was able to workaround the issue by simply running the system twice, and on the 2nd iteration, it auto fixes itself: https://github.com/spoorn/mangovillage/blob/3d/client/src/physics/mod.rs#L17
I thought maybe this was due to meshes taking a second to load, but I've tried putting time delays, tick delays (as in waiting 1000 frames before spawning the Colliders), checking if the assets are fully loaded, but the same problem always happens.
I have an MVP here: https://github.com/spoorn/mangovillage/blob/3d/mvp/src/main.rs if needed, clone the repo on branch 3d and run cargo run -p mvp.
Screenshot:

I'll take a look at this soon, thank you for the repro :)


grad-of-grad-of-remat-of-custom_jvp/vjp drops differentiation rules

Adding this test to CustomJVPTest in api_test.py fails:
  def test_remat_higher_order(self):
    @api.custom_jvp
    def f(x):
      return jnp.sin(x)
    def f_jvp(primals, tangents):
      x, = primals
      g, = tangents
      return f(x), 2 * jnp.cos(x) * g
    f.defjvp(f_jvp)

    def g(x):
      return f(f(x))

    ans = api.grad(api.grad(api.remat(g)))(2.)
    expected = api.grad(api.grad(g))(2.)
    self.assertAllClose(ans, expected, check_dtypes=False)

The issue is that there's no JaxprTrace.process_custom_jvp_rule, but remat uses partial evaluation to stage out. I'll fix this in #4008.

This was fixed by #4008 !


Bug report: m365 teams team list -> Error: Request failed with status code 404

Description
Try to list all teams in my tenant with the teams team list command. Throws an error in "regular" mode, but I see the data if I provide the --debug switch.
Steps to reproduce
D:\DEV\PowerShell\Test
λ  m365 teams team list
Error: Request failed with status code 404
Expected result
list of all teams in tenant
Actual result
Error: Request failed with status code 404
Environment
D:\DEV\PowerShell\Test
λ  m365 version
v3.2.0
Win10 preview Build<PHONE_NUMBER>

Hey @thomyg, thanks for reporting. When running the command against a CDX/MOD tenant, with 8 Teams it works just fine. We'd need some more information about what's going wrong exactly. Can you share some more information from the debug mode about the request that's failing to help us reproduce it?

Thx @waldekmastykarz for the quick response!
That is the debug output part I assume to be the problem:
Request error data      : {"error":{"code":"NotFound","message":"Failed to execute Skype backend request GetThreadS2SRequest.","innerError":{"date":"2020-11-13T11:19:33","request-id":"379513b6-099a-4e3a-ad36-c2e1c1bed5cd","client-request-id":"379513b6-099a-4e3a-ad36-c2e1c1bed5cd"}}} headers   : {"cache-control":"private","content-type":"application/json","request-id":"379513b6-099a-4e3a-ad36-c2e1c1bed5cd","client-request-id":"379513b6-099a-4e3a-ad36-c2e1c1bed5cd","x-ms-ags-diagnostic":"{\"ServerInfo\":{\"DataCenter\":\"North Europe\",\"Slice\":\"SliceC\",\"Ring\":\"4\",\"ScaleUnit\":\"001\",\"RoleInstance\":\"AGSFE_IN_16\"}}","strict-transport-security":"max-age=31536000","date":"Fri, 13 Nov 2020 11:19:33 GMT","connection":"close","content-length":"322"} status    : 404 statusText: Not Found
As the debug output has 4029 lines and it seems that all other request before are working and I have around 300 something teams in that tenant, I wouldn't be surprise for that to be something like a "boundary condition" case.
I'll try later today against another tenant, because this user here is in Ring 1.5 on a TAP tenant. Will try on a Ring 4 one for reference and follow up here.

Running against a tenant with 39 teams using version 3.1.0 is working. Will try to get a test tenant with some more teams :D

Thanks for a quick turnaround and the additional info @thomyg. The more data we can gather, the quicker we should be able to fix it 👍

Looks like something is not working on my tenant. Tried "m365 teams team list" against a regular dev tenant with 181 teams and worked without a problem.
I tried walking through the debug output from the tenant that keeps failing. I have 295 teams in that tenant. And I tried to count the teams I get back from the calls. Looks like there are 3 patches made. If I count "displayName" in each of the response data lines, right at the beginning of the output, I count 100+100+95 times "displayName". So, that seems to get everything.
In the response section of the debug output I only count 286 responses, so there is something missing. This led me to have a look in the Teams admin center and I think I found a "suspect"

Keeps in that state also after a couple of refreshes. I guess, if the ootb admin center can't get detailed data for that team, I can't complain about the cli not being able to get the data either. It looks like the name is still retrievable through the API but accessing details throws an error.
Thank you all for your help and tests and let's hope this will be useful to others that might run into similar issues in the future.

That's some decent research. Thanks for the input!

Good find! So the question is how we should handle such cases where you can retrieve some data but not all. Shall we show what we can retrieve, potentially giving you the impression that it's all you've got, or shall we throw an error like we do now, even if we can retrieve some data?

I will use one of my MVP support cases to go deeper on the error. At least I would like to know how I can change that team to make the API work again without the obvious solution of deleting it.
I'm not sure that generating the impression of everything worked fine is the way to go if the API returns a 404. I do like the current behaviour of throwing an error. Without it, or with only a warning, I might not challenge the result and in my case would have not realised, that one of my teams has a potential issue.

Awesome! Appreciate your help @thomyg. Please, let us know if you find anything more about what's wrong with some of the Teams in your tenant.

Hey @thomyg, were you able to find anything more or shall we close this issue for now?

Closing due to lack of response

Closing due to lack of response

Actually just tripped across this same issue here, but in my case the Team that is causing the problem has no issues in my administration console. I can also take the exact same Graph call that fails in the CLI debug log, issue it through Graph Explorer, and it succeeds. We're in a GCC tenant, though, so there might be something different in our environment that's causing it. If I can gather any information that would be helpful, let me know what that would be.

Actually just tripped across this same issue here, but in my case the Team that is causing the problem has no issues in my administration console. I can also take the exact same Graph call that fails in the CLI debug log, issue it through Graph Explorer, and it succeeds. We're in a GCC tenant, though, so there might be something different in our environment that's causing it. If I can gather any information that would be helpful, let me know what that would be.

Right now, we don't support GCC High as it requires issuing different requests. We have a possible solution but we can't test it ourselves because we don't have access to a GCC tenant. If you'd be so kind, would you mind giving it a try? You can find more information about how to test at #1931

Right now, we don't support GCC High as it requires issuing different requests. We have a possible solution but we can't test it ourselves because we don't have access to a GCC tenant. If you'd be so kind, would you mind giving it a try? You can find more information about how to test at #1931

Right now, we don't support GCC High as it requires issuing different requests. We have a possible solution but we can't test it ourselves because we don't have access to a GCC tenant. If you'd be so kind, would you mind giving it a try? You can find more information about how to test at #1931

Oh, actually we're on GCC, not GCC High. Is this fix still relevant to our environment? I'm happy to try it anyway.

Right now, we don't support GCC High as it requires issuing different requests. We have a possible solution but we can't test it ourselves because we don't have access to a GCC tenant. If you'd be so kind, would you mind giving it a try? You can find more information about how to test at #1931

Oh, actually we're on GCC, not GCC High. Is this fix still relevant to our environment? I'm happy to try it anyway.

Yes, I believe it would be. Thank you so much for willing to give it a try 👏

Yes, I believe it would be. Thank you so much for willing to give it a try 👏

Well, my experimenting was halted, the GCC High version didn't seem to want to do much with my GCC tenant; I had trouble even logging in and getting credentials to the shell. A lot of the commands didn't work, but again we're not in a GCC High environment, just good old GCC.
I can live with the 404 for now and use PowerShell to list all Teams. :-)
Thanks for the help, though!

Well, my experimenting was halted, the GCC High version didn't seem to want to do much with my GCC tenant; I had trouble even logging in and getting credentials to the shell. A lot of the commands didn't work, but again we're not in a GCC High environment, just good old GCC.
I can live with the 404 for now and use PowerShell to list all Teams. :-)
Thanks for the help, though!

You mean you couldn't use the version from the issue I referenced at all? If so, then we'd need to investigate what's wrong because it's meant to work on all clouds rather than just GCC High

You mean you couldn't use the version from the issue I referenced at all? If so, then we'd need to investigate what's wrong because it's meant to work on all clouds rather than just GCC High

You mean you couldn't use the version from the issue I referenced at all? If so, then we'd need to investigate what's wrong because it's meant to work on all clouds rather than just GCC High

I may have done something silly on my side, I was incredibly busy and trying to multitask when I tested it. I'll give it another go and let you know. Don't worry yet. :-)

You mean you couldn't use the version from the issue I referenced at all? If so, then we'd need to investigate what's wrong because it's meant to work on all clouds rather than just GCC High

I may have done something silly on my side, I was incredibly busy and trying to multitask when I tested it. I'll give it another go and let you know. Don't worry yet. :-)

Thank you for giving it another try, much appreciated!

Thank you for giving it another try, much appreciated!


Investigate possible perf degredation using rawkernel

We believe this has been fixed with a change unrelated to raw kernel. Closing.


npm install failure

After downloading react-slingshot and calling "npm install" I get this error:
313437 info install<EMAIL_ADDRESS>313438 info postinstall<EMAIL_ADDRESS>313439 info prepublish<EMAIL_ADDRESS>313440 verbose validateInstall loading C:\Users\znowden\Desktop\react-slingshot\package.json for validation
313441 verbose stack Error: The package<EMAIL_ADDRESS>does not satisfy its siblings' peerDependencies requirements!
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\lib\install.js:125:32
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\lib\install.js:268:7
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\node_modules\read-installed\read-installed.js:142:5
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\node_modules\read-installed\read-installed.js:263:14
313441 verbose stack     at cb (C:\Program Files\nodejs\node_modules\npm\node_modules\slide\lib\async-map.js:47:24)
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\node_modules\read-installed\read-installed.js:263:14
313441 verbose stack     at cb (C:\Program Files\nodejs\node_modules\npm\node_modules\slide\lib\async-map.js:47:24)
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\node_modules\read-installed\read-installed.js:263:14
313441 verbose stack     at cb (C:\Program Files\nodejs\node_modules\npm\node_modules\slide\lib\async-map.js:47:24)
313441 verbose stack     at C:\Program Files\nodejs\node_modules\npm\node_modules\read-installed\read-installed.js:263:14
313442 verbose cwd C:\Users\znowden\Desktop\react-slingshot
313443 error Windows_NT 10.0.10586
313444 error argv "C:\\Program Files\\nodejs\\node.exe" "C:\\Program Files\\nodejs\\node_modules\\npm\\bin\\npm-cli.js" "install"
313445 error node v4.4.3
313446 error npm  v2.15.1
313447 error code EPEERINVALID
313448 error peerinvalid The package<EMAIL_ADDRESS>does not satisfy its siblings' peerDependencies requirements!
313448 error peerinvalid Peer<EMAIL_ADDRESS>wants<EMAIL_ADDRESS>313448 error peerinvalid Peer<EMAIL_ADDRESS>wants<EMAIL_ADDRESS>313448 error peerinvalid Peer<EMAIL_ADDRESS>wants<EMAIL_ADDRESS>313448 error peerinvalid Peer<EMAIL_ADDRESS>wants<EMAIL_ADDRESS>|| 0.14.x || 15.* || ^15.0.0-rc
313449 verbose exit [ 1, true ]

Then when calling "npm start" I get this error from tools\testSetup.js:26:1 :
Error: Cannot find module 'babel-register'

VC++ components and Python 2.7 are installed as instructed.

About that second issue I'm convinced that you got this error after calling npm test (npm start should not even try to load testSetup). I had the same problem. Try solving it by running:
npm install babel-register --save-dev

I've just submitted a PR that fixes it https://github.com/coryhouse/react-slingshot/pull/117 .

Fixed! Thanks for the PR!

The PR did not fix the issue and I did not run npm test. I cloned the repo, entered "npm install" then "npm start". Let me know if you need more details, this is a fresh clone on a reasonably clean machine so would expect to see more reports of this in the near future.

Odd, about to head out to dinner. I'll give this a look tonight.

@znowden It's installing from scratch just fine on my Windows machine. Did you complete the setup steps listed in the docs?
Can you provide the following?

Windows version
What command line you're using on Windows
npm version
node version

Under dependencies update react-redux 4.4.0 in the package.json to 4.4.1
http://stackoverflow.com/questions/35890730/react-15-not-compatible-with-react-redux

Thanks, upgrading react-redux to 4.4.1 worked.

Great to hear! Dependencies updated.


https://github.com/ibm-messaging/message-hub-samples/tree/master/java/message-hub-kafka-ssl docs unclear

Trying to understand how to populate ssl.truststore.locationias is a major painpoint for me.
It would be nice to see an example of what this filepath would actually look like on a mac and pc. Some more elaboration on this point in the youtube tutorial would also be helpful.

Additionally, I would be far less likely to churn if this sample was generated for me from within the bluemix microservice, with the config prepopulated according to my credentials. Long time to value

Hi @brresnic
To use Message Hub you don't have to set any truststore properties. Java will use the default truststore that contains the needed certificates.
We are in the process of revamping the samples, hopefully the next update sometime next week should make this clearer

We've removed mentions of "ssl.truststore.location" as this configuration is not required for the samples to work -> closing


Hard-coded branding size constrains

Currently, in the core styles, there are hard-coded size constrains for the branding: max-width: 20%; max-height: 100%;.
This could become problematic for certain scenarios, for example, produce accidental text wrapping or downscaling for long images. Applying arbitrary browser scaling for logos often results in a blurry or rough-edged output.
I would suggest to not constrain the developer-provided content whenever possible. Sure any size exceeds and overlaps are problematic, but in case if they are not shown, it is even harder to notice and fix that. The height constrain makes more sense for the navbar content, but the width constrain — looks like it could be removed altogether.
Another idea to consider is to have the navbar height: auto;, so that the height is automatically determined from the content. This guarantees to not produce any height overlaps (since the height would be increased instead), and we would have less magic numbers to maintain.
Related issue: the branding image used in the demo does not have a size defined. With the built-in constrains removed, the image is so big, it exceeds the navbar height and overlaps the content. Suggestion: specify width and height attributes on the image with a suitable size in the demo. It is a generally good practice for the developers to follow.

Good observations, and I agree.
The Lumo and Material themes probably want to have a fixed height for the navbar, and then having the max-height of the branding content limited sounds reasonable. But for the core styles, maybe it would be best to let the navbar just grow with the content.


Identify all model types statically

We would like to add more static validation around model types, making sure they use Property types correctly etc. One obstacle to this is to be able to statically identify all model types to be validated.
Static validation (vs runtime validation) is important because we would like to let plugin developers know as early as possible about problems, instead of delaying reports of problems until runtime, when we can only tell the user, who might not be able to do much about them.
Other potential benefits of being able to statically identify all model types would be to generate extension methods for easier use in Kotlin DSL, or to auto-generate documentation for the plugin.
We can already discover implementors of Task, TransformParameter and TransformAction statically. We can also discover @Nested types their properties refer to, and even try to discover any subclasses of those types. However, for extension types we have no such discovery method.
The only way we can precisely identify extension types today is during runtime, when such an object is passed to ExtensionContainer.create() and friends, but no static option exists.
We should introduce some sort of static identification for extension types. Primarily there are two approaches:

use an annotation like @Extension (@Model and use it on Task etc.)
use a tagging interface like Extension (and maybe even introduce a super-interface Model and make Task etc. extend it)

The advantages of an interface are:

it's easier to identify the whole hierarchy
we can require the presence of the interface in the APIs (e.g. only allow registering extensions that implement Extension)

The downside is that plugins wanting to support both old and new versions would be hard to compile, as the Extension type would not be available for earlier Gradle versions.
With the annotation approach we lose the benefits of stronger typing, but plugins compiled against later Gradle versions can still be used by earlier Gradle versions.

One way we could introduce the super-interface approach without causing problems for older Gradle versions is to introduce it over a longer period of time. We could introduce Extension and Model in, say, Gradle 8.7, and make sure we fail for any Gradle type being used as an extension that is without it. This way we can ensure that all Gradle types are annotated well.
Then we leave things be for a while, and say, in Gradle 10 we start nagging for user types as well, and then make it an error in Gradle 11, and let the APIs only accept Extension subtypes.
This gives users a wide range of Gradle versions they can support without much effort at any point in the process. And they can still support older versions after Gradle 11 enforces the presence of Extension by using multi-Gradle-version plugins, though that approach requires some extra work on their part.
The obvious downside is that we drag out the process over a long period of time.

A downside of an interface is one can't unimplement it.
For instance, if user wants exclude a subtype from verification (e.g. the subtype will never be passed to extensions.create), they will have troubles.
Interfaces require an instance to get data out of overridable methods, so interfaces in Java can't convey static metadata. Annotations can have static attributes defined by the user.
For extensions, it might be important to declare the target at the declaration side. In other words, "this is an extension to Task", "this is an extension to Project" or "this is an extension to a user-defined type Foo" (Foo being an extension to something else).
It would be challenging to convey such information with interfaces.

it's easier to identify the whole hierarchy

With seperate compilation in place, one can't reliably predict if a class would have an interface or not.
Imagine class Base (in base.jar), class Derived extends Base (in derived.jar).
No interfaces so far. Later, Base is recompiled as Base implements Extension. Now Derived magically receives an interface without recompilation.

For instance, if user wants exclude a subtype from verification (e.g. the subtype will never be passed to extensions.create), they will have troubles.

Why would you extend an extension type and then not use it as an extension? Mind you, I think if we went with the annotation approach, we'd have it inherit as well.

Why would you extend an extension type and then not use it as an extension?

For example, use it as an abstract class to inherit actual extensions


Wide table is inaccessible

Look at this:
http://tc39.github.io/ecmascript_simd/#deserialize-int
In Chrome, I don't get a horizontal scrollbar, and the table is simply inaccessible. Smells like a stylesheet issue.

Hmm, I agree with stylesheet issue (I'll theorize further that its due to improper usage of the overflow property somewhere). But that said, this table seems simply too wide. In the old days it would not fly as it's too wide to fit on a page. We care less about this today but requiring horizontal scrollbars and horizontal scrolling seems unfortunate... Possible to split the columns into two separate tables maybe?

Thanks! Yeah maybe it should be done some other way, maybe transposed or with shorter heading text or something. Two tables would seem unfortunate unless there's a clear semantic way of breaking it up that doesn't come to mind immediately to me.

I can't think of something obvious :(


Deep sync improvement

Deep sync state will be true until we are completely synced. With this change, the deep sync state will be set to false as soon as syncing gets close to being synced.

prnet cleaned-up successfully


fix flask ExtDeprecationWarning

Hi @timofurrer
this is my first pull request ever and it is a small one.. But when starting the minion-server I get this error
/home/rob/.env/mci/lib/python3.4/site-packages/flask/exthook.py:71: ExtDeprecationWarning: Importing flask.ext.mongoengine is deprecated, use flask_mongoengine instead. format(x=modname), ExtDeprecationWarning
I used this as a reference for the solution: https://github.com/MongoEngine/flask-mongoengine/issues/222
Hope to hear from you!

Welcome to GitHub and Open Source!
It's always great to have people contributing their first time to OSS!
I appreciate the time you spent to have a look at this!
Awesome!
:beers:

Awesome! Thanks! Within a few minutes I will have open a pull request for #5
:D


All CI failing with FATAL: org.acegisecurity.providers.UsernamePasswordAuthenticationToken cannot be cast to org.jenkinsci.plugins.GithubAuthenticationToken

Archiving artifacts
FATAL: org.acegisecurity.providers.UsernamePasswordAuthenticationToken cannot be cast to org.jenkinsci.plugins.GithubAuthenticationToken
java.lang.ClassCastException: org.acegisecurity.providers.UsernamePasswordAuthenticationToken cannot be cast to org.jenkinsci.plugins.GithubAuthenticationToken

@apjanke not sure what to do about this one but seems to be failing all builds at the moment.

This one wasn't Andrew's issue. It appears the Jenkins security update applied today causes authentication exclusively on the archiving stage to fail, intermittently. It started earlier, then went away for a while, and now seems to be back.
Doesn't seem to have a direct impact on the builds themselves, both upstream and downstream builds pass okay, just the archiving stage falls on its face. Still looking into the root cause.

@DomT4 I know, I just figured Andrew would be awake ;)

You'd be right, by the looks of it 😉. I'm going to try a couple of things but there's not a lot we can do if they don't work; the alternative is downgrading onto a release with 7 known vulnerabilities. One day we can kill off Jenkins and life will be a happy happy place.

Apparently temporarily fixed by just restarting the darn thing ¯\_(ツ)_/¯.

Nice. Who says UNIX cannot be more like Windows?

😆 I laughed far too much at that. I'm hoping that if it can be consistently resolved by effectively restarting it every time it's a Jenkins bug and not some configuration nightmare.

Looks like it's back http://bot.brew.sh/job/Homebrew Core Pull Requests/1799/version=el_capitan/console

Maybe worth filing an issue upstream about this?

Someone already did.

Looks like a downgrade is in order.

Looks like there's a preliminary fix for this: https://github.com/jenkinsci/ghprb-plugin/pull/336
So perhaps we should try that patch even though it's not in a final form.

Apparently this may be a workaround:

Christopher Orr added a comment - 18 minutes ago

This is related to the fix for SECURITY-243 mentioned here:
https://wiki.jenkins-ci.org/display/SECURITY/Jenkins+Security+Advisory+2016-05-11

Enabling the system property mentioned in that part of the security advisory should temporarily work around this problem.

We'd already enabled that to resolve other plugin issues but this one proved sticky.

Did whitelist all parameters listed?
 If using the standard ${sha1} branch spec, builds will fail with "Couldn't find any revision to build".
Pull requests remain in the "pending" state as the plugin fails to update the PR with the build outcome
OpenParameter names used
ghprbActualCommit,ghprbActualCommitAuthor,ghprbActualCommitAuthorEmail,ghprbAuthorRepoGitUrl,
ghprbCommentBody,ghprbCredentialsId,ghprbGhRepository,ghprbPullAuthorEmail,ghprbPullAuthorLogin,
ghprbPullAuthorLoginMention,ghprbPullDescription,ghprbPullId,ghprbPullLink,
ghprbPullLongDescription,ghprbPullTitle,ghprbSourceBranch,ghprbTargetBranch,ghprbTriggerAuthor,
ghprbTriggerAuthorEmail,ghprbTriggerAuthorLogin,ghprbTriggerAuthorLoginMention,GIT_BRANCH,sha1

We whitelisted literally everything 😄.

Then it sounds like it's time for a downgrade or the experimental PR https://github.com/jenkinsci/ghprb-plugin/pull/336

Check the team chat.


Error while trying to create a ec2 instance using Auto scaling group

Hi,
I have created a Launch configuration using the below cloud formation template and created Autoscaling group using AWS Console. I am getting the below error while launching Ec2 instance using Auto scaling group.Please find the screen shots.
Error:
Launching a new EC2 instance. Status Reason: The parameter groupName cannot be used with the parameter subnet. Launching EC2 instance failed.
Cause:CauseAt 2020-04-29T07:46:29Z an instance was started in response to a difference between desired and actual capacity, increasing the capacity from 0 to 1.
Script:
ASG Error.docx
{
"AWSTemplateFormatVersion": "2010-09-09",
"Description": "Exercise-1: Launch configuation",
"Parameters": {
"keyvaluepair": {
"Description": "Key value pair",
"Type": "AWS::EC2::KeyPair::KeyName"
},
"securitygroup": {
"Description": "Security group name",
"Type": "AWS::EC2::SecurityGroup::GroupName"
}
},
"Resources": {
"myLaunchConfig": {
"Type": "AWS::AutoScaling::LaunchConfiguration",
"Properties": {
"KeyName": {
"Ref": "keyvaluepair"
},
"SecurityGroups": [
{
"Ref": "securitygroup"
}
],
"ImageId": "ami-071ef7270bf52835d",
"InstanceType": "t2.micro"
}
}
}
}

if it is aws challenge please try to resolve the error by yourself  do not post those challenges over here because it is a challenge so try to find the solution with your own in case if you are not find the solution then wait for the next challenge and ask over here then i will post the solution here.
please try to find the solutions for challenges with your own.
if you have any classroom doubts please ask over here.


How to fix the resourceid with constant value

Hello,
I have a question about the using of a constant name for resourceid.
The resource id is changed every time, when a new session is set. Is there a possibility to stop generating of new resourceid and fix it to constant value?
How I can fix a constant value for resourceid in cracklord source?
Thanks in advance!
Best regards,

So the Resource ID is a UUID set by the queue when you connect a new one.
What is the use case you are looking for to have a constant one?
On Jul 22, 2016 4:50 AM, "ytronics"<EMAIL_ADDRESS>wrote:

Hello,
I have a question about the using of a constant name for resourceid.
The resource id is changed every time, when a new session is set. Is there
a possibility to stop generating of new resourceid and fix it to constant
value?
How I can fix a constant value for resourceid in cracklord source?
Thanks in advance!
Best regards,
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/jmmcatee/cracklord/issues/120, or mute the thread
https://github.com/notifications/unsubscribe-auth/AAoUHGY3ibic4uttRJQ6vnuYMiU5sDLVks5qYK6PgaJpZM4JSsBO
.

Hello,
A simple description of my use case:
I want to fix resource id to constant value, because I have only one HW resource in my resource server. Therefore, I expect the resource server to have constant value for resource id when I connect to it.
I see that the resource id is changed every time, when I add my HW resource in the system.
Can I fix resource id with constant value in the queue?
Best regards,

So there is not a way to change the Resource ID to be constant. The queue
has to have a unique ID each time. I'm still not sure why you would even
need to know the Resource ID. Are you calling the API from a script? If so
you can pull the Resource ID from the API programmatically as well.
On Jul 22, 2016 7:38 AM, "ytronics"<EMAIL_ADDRESS>wrote:

Hello,
A simple description of my use case:
I want to fix resource id to constant value, because I have only one HW
resource in my resource server. Therefore, I expect the resource server to
have constant value for resource id when I connect to it.
I see that the resource id is changed every time, when I add my HW
resource in the system.
Can I fix resource id with constant value in the queue?
Best regards,
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/jmmcatee/cracklord/issues/120#issuecomment-234561523,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAoUHO5KQtXnTnH6uTE91jfVTHABQnp3ks5qYNXXgaJpZM4JSsBO
.

Closing, but let me know if you have more information or questions here.


should has(jld,name) work?

Consider
jld = jldopen("test.jld","w")
jld["a"]=1
has(jld,"a") # ERROR: MethodError: `has` has no method ...
has(jld.plain,"a")

Is there a reason this doesn't work?

You're looking for haskey, not has. But yes, it would be nice if this worked, so that jld behaved like an associative structure.

Is there a reason this doesn't work?

No good reason.

I first looked for haskey. But I posted about has because that works for the plain HDF5File. I'm happy to try to add this.
It seems like JLDFile (and HDF5File) should are kind of emulating an associative like Dict, but with many deviations. . What would you think about doing the following for both JLDFile and HDF5File (in HDF5.jl of course):

Add haskey
Add keys methods that do the same thing as names(jld)

It's worth thinking a bit more about how exactly JLDFile is similar to a Dict and when it isn't.

Probably a lot of the deviations are due to the fact that these packages date from the julia 0.2 days.
In general I'd say it would be best if it emulated the Dict interface wherever it makes sense. At the moment, I'm failing to think of a way in which it shouldn't act like a Dict.


Other Works by Artist Update

From @briansw on July 6, 2016 18:30
Launch as Lab feature first for review

We'd like to break up the "Other Works by [Artist]" Module into two modules:

[Medium] by Artist – Medium chosen should match the medium of the artwork user is currently viewing, display 10 inquireable works
Other Works by [Artist] – Ideally, this excludes the works found in the medium module, display 10 inquireable works

Don't break into two modules when:

The work the user is viewing is the only instance of that medium by the artist
Artist has 10 or fewer inquireable works
All of the artist's works are the same medium

Copied from original issue: artsy/force-private#5326

This is done.

@alloy this hasn't been worked on yet. This ticket is about displaying a module of works in the same medium as the one the user is currently looking at. We currently only display an array of available works by the artist without taking medium into account.

@briansw Thanks for being sharp! 🙌

@tayapage6 @alloy since this is something that remains to be done should I wait for it to be prioritized or just pick it up when I'm ready for a new ticket?

@xtina-starr Do you have a feeling for the scope of the required work?

@alloy not entirely. I believe majority of the work would be metaphysics.

Let’s wait for it to become prioritised then.


List all services in spreadsheet format with production URLs

Sometimes we need to plan maintenance work over a large number of services at once, and it is useful to be able to produce a spreadsheet of services with their production URLs. This commit adds a new command to do that.
Usage:
❯ dalmatian config services-to-tsv -h
List all services in spreadsheet format with URLs
Format: <infra><tab><service><tab><comma-separated-prod-domains><newline>
e.g. dalmatian config services-to-tsv
Usage: services-to-tsv <infrastructure name [OPTIONAL]>
  -i                     - infrastructure name (optional)
  -h                     - help

and the output looks like this:
❯ dalmatian config services-to-tsv -i infra1
==> Assuming role to provide access to infra1 infrastructure account ...
infra1    service1   blogs.example.com
infra1    service2   web.example.com
infra1    service3   intranet.example.com

If it's listing production URLs it should probably also take into account subdirectory installs?

Minor observation for a potential opportunity to make https://github.com/dxw/dalmatian-tools/blob/main/bin/config/list-infrastructures a function that can be re-used then referenced in your file? Not a blocker for this PR


feat: init

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  Partials        ?         0

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The diff coverage is n/a.

@@           Coverage Diff            @@
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  Coverage        ?   100.00%
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  Misses          ?         0
  Partials        ?         0

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Character encoding issue in Scala 3 REPL

Related to the Scala 3 REPL
Juha: UTF-8 ("äö") surprisingly did not work for me in the REPL until I adjusted VM options — I don’t recall having had to do that on Windows before, but I could be mistaken (Anyway, this was in a non-A+-courses project. I guess it should work for students.)

By default it doesn't work in Scala 2 REPL either

Adding -Dfile.encoding=UTF-8 to VM options seems to solve the problem, both in Scala 2 and 3. This could be added to the course configuration file.

Adding the aforementioned option solves the problem


path to generated files missing

a small thing !!
suggest add some propertysheets that handles general paths for generated files folder
When making a fresh clone and then starting the Logging example project, then it can not build -- due to missing paths
Suggestion:
Just add paths in propertysheet files for the Logging project, thereby no change in the actual code

I tried it and it then builds

Can you provide more specific information about what paths need to be added? Maybe create a pull request?


Cloudinary upgrade

Hi,
Any plan to upgrade the cloudinary dependency ?
Thanks,
Julien

Hi,
what dependencies are you referring to ?

Hi,
what dependencies are you referring to ?

Hi,
Thanks for the quick reply.
The package.json dependency : "cloudinary/cloudinary_php": "^1.1"
They are on 1.20 now (https://packagist.org/packages/cloudinary/cloudinary_php) , maybe we could benefit from some few fix/improvements.

Hi,
Thanks for the quick reply.
The package.json dependency : "cloudinary/cloudinary_php": "^1.1"
They are on 1.20 now (https://packagist.org/packages/cloudinary/cloudinary_php) , maybe we could benefit from some few fix/improvements.

That is the minimum required. You can use any version that satisfy the ^1.1 constraint. This includes 1.20.
See https://getcomposer.org/doc/articles/versions.md#caret-version-range- for more information.
There will be a new version once cloudinary/cloudinary_php version 2.0 will be released.

That is the minimum required. You can use any version that satisfy the ^1.1 constraint. This includes 1.20.
See https://getcomposer.org/doc/articles/versions.md#caret-version-range- for more information.
There will be a new version once cloudinary/cloudinary_php version 2.0 will be released.

alright, got it !
Thanks !

alright, got it !
Thanks !


Slow image preview if large number of multiple uploads

It's better if preview generated during upload process (eg upload starts).

You can make the ngf-src="uploadProcessStarted && file" that way it would generate the preview after the upload is started


VS Code can't generate debug files for C# projects.

Type: Bug
Issue Description
Steps to Reproduce
Expected Behavior
Actual Behavior
Logs

C# log
Post the output from Output-->C# here
C# LSP Trace Logs
Post the output from Output-->C# LSP Trace Logs here.  Requires `dotnet.server.trace` to be set to `Trace`
Environment information
VSCode version: 1.86.0-insider
C# Extension: 2.14.8
Using OmniSharp: false
Dotnet Information
.NET SDK:
 Version:           8.0.100
 Commit:            57efcf1350
 Workload version:  8.0.100-manifests.6c33ef20
Runtime Environment:
OS Name:     ubuntu
OS Version:  23.10
OS Platform: Linux
RID:         linux-x64
Base Path:   /snap/dotnet-sdk/228/sdk/8.0.100/
.NET workloads installed:
Workload version: 8.0.100-manifests.6c33ef20
There are no installed workloads to display.
 I keep getting the same error:
"Could not locate .NET Core Project in 'Working folder'
Assets were not generated.
The "dotnet build" command works fine from the console and from the VS Code UI, the program runs fine as long as you type "dotnet run" in your console, I just can't figure it out how to make the debugger work!
I have tried manually creating the project from the console, tried creating the project from the VS Code UI, trough the C# extension, still not able to generate files for debugging.
The latest available .NET SDK is installed 8.0.100, also NuGet is installed which I don't believe I actually need.
I have tried reinstalling VS Code and all the extensions and deleting all the folders in the system, still can't generate debug files!**
Extension version: 2.14.8
VS Code version: Code - Insiders 1.86.0-insider (9621add46007f7a1ab37d1fce9bcdcecca62aeb0, 2023-12-20T05:36:34.875Z)
OS version: Linux x64 6.5.0-14-generic
Modes:

System Info

Item
Value

CPUs
12th Gen Intel(R) Core(TM) i7-1260P (16 x 1039)

GPU Status
2d_canvas: enabledcanvas_oop_rasterization: disabled_offdirect_rendering_display_compositor: disabled_off_okgpu_compositing: enabledmultiple_raster_threads: enabled_onopengl: enabled_onrasterization: enabledraw_draw: disabled_off_okskia_graphite: disabled_offvideo_decode: enabledvideo_encode: disabled_softwarevulkan: disabled_offwebgl: enabledwebgl2: enabledwebgpu: disabled_off

Load (avg)
2, 1, 1

Memory (System)
15.31GB (12.61GB free)

Process Argv
--unity-launch --crash-reporter-id 228f420d-f7e5-41c2-9bb2-941c0513b33d

Screen Reader
no

VM
0%

DESKTOP_SESSION
plasma

XDG_CURRENT_DESKTOP
KDE

XDG_SESSION_DESKTOP
KDE

XDG_SESSION_TYPE
x11

A/B Experiments
vsliv695:30137379
vsins829:30139715
vsliv368cf:30146710
vsreu685:30147344
vspor879:30202332
vspor708:30202333
vspor363:30204092
vslsvsres303:30308271
vshan820:30294714
vscod805cf:30301675
bridge0708:30335490
bridge0723:30353136
vsaa593cf:30376535
py29gd2263:30784851
vsclangdf:30492506
c4g48928:30535728
dsvsc012:30540252
showlangstatbar:30737417
fixshowwlkth:30771523
showindicator:30805243
pythongtdpath:30726887
i26e3531:30792625
welcomedialog:30812478
pythonidxpt:30768918
pythonnoceb:30776497
asynctok:30898717
dsvsc013:30777762
dsvsc014:30777825
pythonmpsinfo:30901776
dsvsc015:30821418
pythontestfixt:30866404
pythonregdiag2:30926734
pyreplss1:30879911
pythonmypyd1:30859725
pythoncet0:30859736
pythontbext0:30879054
accentitlementst:30870582
dsvsc016:30879898
dsvsc017:30880771
dsvsc018:30880772
aa_t_chat:30882232
cp7184t:30925682

Did you ever figure this out or give up and close it? I'm dealing with the exact same issue and am running out of solutions to try.

No I didn't. I've just stopped using Debian operating systems like Ubuntu and Kubuntu and moved on with Fedora KDE. That problem doesn't exist there.
There probably is a solution but I just couldn't find anything useful on the internet and I'm satisfied with Fedora.
Best regards!

From: gpzeke @.>
Sent: Wednesday, May 15, 2024 7:52:24 PM
To: dotnet/vscode-csharp @.>
Cc: El1nsky @.>; State change @.>
Subject: Re: [dotnet/vscode-csharp] VS Code can't generate debug files for C# projects. (Issue #6775)
Did you ever figure this out or give up and close it? I'm dealing with the exact same issue and am running out of solutions to try.
—
Reply to this email directly, view it on GitHubhttps://github.com/dotnet/vscode-csharp/issues/6775#issuecomment-2113023914, or unsubscribehttps://github.com/notifications/unsubscribe-auth/BAEJA2S3EYBOYKPBUGMOI2TZCOHD5AVCNFSM6AAAAABBGGJE2SVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCMJTGAZDGOJRGQ.
You are receiving this because you modified the open/close state.Message ID: @.***>


Fix installation command using binaries

Currently the command to install Plansys2 using binaries is using an underscore:
sudo apt install ros-<distro>-plansys2_*

It should use a hyphen to install all packages correctly:
sudo apt install ros-<distro>-plansys2-*

Good catch!!
Thanks @DaniGarciaLopez


Fix typo

Fixed in https://github.com/reactjs/react.dev/pull/7182, sorry I saw that first.

Fixed in #7182, sorry I saw that first.

That's a 2nd one!


vscode-extensions.discloud.discloud: init 2.21.2

Description of changes
Adding a new vscode extension: https://marketplace.visualstudio.com/items?itemName=discloud.discloud

Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

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

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

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

Please squash commits for extension. Ideally, a single VSCode extension should be a single commit.

Thank you for the review and feedback @superherointj !
I've rebased and squashed my previous commits into a single commit as requested.
I apologize for any confusion...
Please let me know if I need to change anything else.
Thank you for your time.

The code that adds yourself as a maintainer (globally) should be a separate commit.
The vscode extension code should be a single commit.
This matters when managing the maintainer lifecycle.
By keeping it separate, it's possible to revert the commit that added yourself as maintainer later.

That makes more sense...
Thank you very much for your explanation.


KAFKA-2640: Add tests for ZK authentication

I've added a couple of initial tests to verify the functionality. I've tested that the JAAS config file loads properly and SASL with DIGEST-MD5 works with ZooKeeper.

In ZkSecurityMigrator, do we need to set the acl for "/" so that only clients with permission can delete paths under "/"?

Thanks for the patch. Just a minor comment above. Otherwise, LGTM.

@junrao I've pushed a fix for your last comment. Thanks for reviewing it.


Upload folder and delete folder

Can you add this funtions in web browser when load <IP_ADDRESS>:8080 :

Upload folder

Delete folder

Thank you and sorry for my bad english!

You can checkout the folder_upload branch but I didn't merge it to master yet

Pushed 3c6fa09 to master


Remove gulp, implement use of new es6 class syntax

Hi, would you consider to remove gulp and use just plain npm scripts to lighten the project development too?
And what do you think about using the new class syntax for this module?

Please, don't use ES6. There are still plenty of old browsers out there that don't support it, and the benefits of it over ES5 are superficial.

@NxtChg I just saw that in the readme he wrote that he's already using pure es6 js (of course, otherwise a package big just 1kb wouldn't be possible)
But now that you let me think about it, typescript could be used to transpile to ES5/ES6

@giacomocerquone: of course, otherwise a package big just 1kb wouldn't be possible

It's not 1kb because of the ES6. Even in most cases transpiled es5 code is bigger than it can be, exactly because es6 transpilation process.

Using es6 class not make any sense here. Don't force people to hop on that train when it's absolutely not needed.

And third, it seems that he more like gulp for his flow, not modernish Webpack shitty shits. But Yea, here i can agree that npm scripts is mostly enough and when you need transpile can use Rollup, because it is from where everything of Tree Shaking started. Webpack does many things in wrong way - it's ACE is code splitting.

Who talked about webpack and most importantly, why are you talking about webpack?
It's because of ES6 too! There are no arrow function (which he use) in ES5, there are no constants definition (that can lead to lighter source)
For classes I agree with you, it was just an idea to consider

Just mention it, because most may assume that when someone suggest to ditch gulp :d
Yes, but both const and let are transpiled to same thing, so same bytes, no matter what you use in es6. As about that ES6 makes code more readable, i'm agree. But just my point is that ES6 dont leads to smaller es5.

For me, es6 is only good because the modules, currently, until we stop transpile for prod.

@giacomocerquone Thanks for the feedback, but I'm not sure if classes will provide any tangible benefit here. Also gulp is used for more fine-tuned control on dist file generation, and displaying stuff in the console after a build, like the package bundle size. I agree gulp is becoming an obsolete thing, but I don't think it needs to be removed just yet.


Scans are not staggered

Thanks for this great software!
I noticed today that during startup (and also with click on "rescan all") SyncTrayzor scans all folders simultaneously. A plain Syncthing (same version) installation scans one folder at a time while the rest has status "waiting to scan"
Why is this different?

SyncTrayzor does not get involved in the scans at all. When you press Rescan All I'm Syncthing's web interface, SyncTrayzor is not even aware that you've pressed it. Whatever the difference you're seeing is, it's not related to SyncTrayzor I'm afraid.

Ok, thanks for commenting, I thought so too. I will compare several config.xml and report back


Issue #4: It should be possible not to use the visibility handler/visibility settings.

Context
See related issue #4
The Uniform bucket-level access doesn't accept the predefinedAcl option to be set when performing actions on objects. I tried all default acl options, even null, and it ends up with following error: Cannot insert legacy ACL for an object when uniform bucket-level access is enabled
Proposed solution
In order to ensure backward compatibility, it should be nice to have a new constant to bypass this settings.

Can we finally merge this? This issue has being alive for almost 3 months.

thanks @mmachatschek, issue & PR have been moved to thephpleague/flysystem
=> https://github.com/thephpleague/flysystem/pull/1357


build a commons chunk

https://webpack.github.io/docs/list-of-plugins.html#2-explicit-vendor-chunk

duplicate of #681


React does not recognize the nodeId prop on a DOM element

Getting this warning as an error in the browser for using TreeView from @material-ui/lab:
Warning: React does not recognize the nodeId prop on a DOM element. If you intentionally want it to appear in the DOM as a custom attribute, spell it as lowercase nodeid instead. If you accidentally passed it from a parent component, remove it from the DOM element.
This is how I use it:
return (
    <TreeView
      nodeId="0"
      defaultCollapseIcon={<ExpandMoreIcon />}
      defaultExpandIcon={<ChevronRightIcon />}
      defaultExpanded={['1']}
      onNodeSelect={handleNodeClick}
    >
      <TreeItem nodeId="1" label="A">
        <TreeItem nodeId="2" label="AA" />
        <TreeItem nodeId="3" label="AB" />
        <TreeItem nodeId="4" label="AC" />
        <TreeItem nodeId="5" label="AD" />
        <TreeItem nodeId="6" label="AE" />
        <TreeItem nodeId="7" label="AF" />
        <TreeItem nodeId="8" label="AG" />
        <TreeItem nodeId="9" label="AH" />
      </TreeItem>
      <TreeItem nodeId="10" label="B" />
      <TreeItem nodeId="11" label="C" />
      <TreeItem nodeId="12" label="D" />
      <TreeItem nodeId="13" label="E" />
    </TreeView>
  );

Thanks for the report.
nodeId is not supported on TreeView. Only TreeItem needs a nodeId. What lead you to pass a nodeId to TreeView?

Thank you very much @eps1lon.
Oh, my bad.. I really don't know how I managed to use nodeId on the TreeView component.


Update palladium_megaverse.html

More spelling fixes.

Submission Checklist
Required

[x] The pull request title clearly contains the name of the sheet I am editing.
[x] The pull request title clearly states the type of change I am submitting (New Sheet/New Feature/Bugfix/etc.).
[x] The pull request makes changes to files in only one sub-folder.
[x] The pull request does not contain changes to any json files in the translations folder (translation.json is permitted)

Changes / Description

Additional spelling fixes.

Character Sheet Info Roll20 Internal Use only.


Avoid reformatting data set name in TestResult output

The formatting that occurs in TestResult::makeDescription() applies to the test name to turn snake_case or camelCase test names into more readable strings with whitespace.
This is nice; however, it also applies the formatting to the data set name. Because it is just an array key, the data set name may not be in the predictable format of snake or camel case like a test method.
This reformatting obscures the actual data set name, adds double spaces, and removes underscores where they may be important. It also causes different data sets with names differing only in case or underscores to be identical, therefore collapsing them into a single row in the output.
I have modified the makeDescription() method to apply formatting only to the base test name, and then append the unmodified data set name (or index).
Before:
 ✓ it calculates the points for a letter with data set " " // underscore removed, collapsed with space data set
 ✓ it calculates the points for a letter with data set " a" // upper case removed, unnecessary space added
 ...
 ✓ it calculates the points for a card with data set " queen of  hearts" // double space
 ✓ it implements the interface with data set " app\ contracts\ playing card" // class name broken

After:
 ✓ it calculates the points for a letter with data set " " // space is a different data set
 ✓ it calculates the points for a letter with data set "_" // underscore is a different dataset
 ✓ it calculates the points for a letter with data set "A"
 ...
 ✓ it calculates the points for a card with data set "Queen of Hearts"
 ✓ it implements the interface with data set "App\Contracts\PlayingCard"

Hope this is useful!

Thanks!


Prerender true in README?

It's necessary to have a index.html in your build/public (output_location) folder before you can deploy. In order to do that it's necessary to have a export const prerender = true; in your index.svelte.
I don't know if this is a normal thing for SvelteKit, because I'm still a little bit new in SvelteKit. But is it an idea to put this in the README in order to help others in the future?
It took me a while to figure that out. Couldn't figure out why my project didn't have a index.html in the build folder. Now I do. 🙂
I didn't have any other problems with configuring the adapter, btw. Took a while to figure some things out, but it was more project specific. Was looking for this adapter for a while, so thank you! 🙌🏼

It makes sense that an index.html is necessary for a static website. There wouldn't be any starter point for the app if it wasn't there.
Maybe it's an Oryx thing, because that is what Azure Static Web Apps uses to build static applications.
This was the log, btw:
---End of Oryx build logs---
Finished building app with Oryx
Failed to find a default file in the app artifacts folder (build/static). Valid default files: index.html,Index.html.
If your application contains purely static content, please verify that the variable 'app_location' in your workflow file points to the root of your application.
If your application requires build steps, please validate that a default file exists in the build output directory.

<EMAIL_ADDRESS>no longer requires index.svelte to be prerendered.


Parallel deserialization not supported?

I have a huge number of files with a lot of JSON. In order to improve the loading of these I tried to run multiple threads working in different subsets of the files. This should in theory improve performance approx by the number of cores available, given that the disk access is not the bottleneck.
To my surprise I got no performance gain at all. To eliminate the potential bottleneck of the disk I first loaded all files into memory streams, and then want ahead with multiple tasks. No improvement.
I then started measuring the actual time each deserialization took. When using only one thread each deserialization took around 1ms (most files have the same size). When using multiple threads I got everything from 1 to 30ms per deserialization.
This is obviously just a guess, but to me this looks like there is some synchronization going in which t will only let one single object be deserialized at the time. If that is the case, what can I do to improve this?

I'm also having difficulty finding documentation or guidance about multi-threaded usage. Are you using the same serializer instance across all threads or is each thread creating it's own?

Parallel deserialization is definitely supported. WebAPI uses it and IIS has a separate thread per request.


Eager load $article->isFavorited()

Detailed description
Hi there!
When i check if article is favorited by auth user
$article->isFavorited()
the debugbar gives me
Model: App\Models\Article => Relation: ChristianKuri\LaravelFavorite\Models\Favorite - You should add with(ChristianKuri\LaravelFavorite\Models\Favorite) to eager-load this relation.
wire controller
/**
   * The read function.
   * @return array
   */
  public function read(): array
  {
    return [
      'articles' => Article::search($this->search)
        ->with('user')
        ->where('status', true)
        ->latest()
        ->paginate($this->perPage),
    ];
  }

  public function render()
  {
    return view('livewire.front.article-wire', $this->read())->layout('layouts.app');
  }

In Article model i tried
protected $with = ['favorites'];

but it didn't work
How could I eager load that?
Thanks!

Laravel 9
Livewire

don't think this is possible to eager load that query.


Supports custom derived path feature

Describe the task
Supports custom derived path feature

Will resolve in https://github.com/Koniverse/SubWallet-Extension/issues/3556


Vendors glog dependency for the api branch.

Signed-off-by: Mrunal Patel<EMAIL_ADDRESS>(github: mrunalp)

LGTM


changes to script to reflect NATIVE type build.

resolves #229

Is this script still used?  I suppose it may still have some utility, but I've switched to just running the installer every time I want to test a new build.

@tst-lsavoie -yes I used it a couple times.

Already an approval, so merging

This script is very useful for testing when you modify C++ modules.
And two more scripts when you modify Python code in server/wsgi stuff
update_wsgi.sh


Error: Cannot find module './dist/shared.cjs.prod.js'

I am not sure if it is related to pnpm or not because it's also crash on React project. I tried to search the issue but I can't find similar issues or I didn't know the correct keyword to use.
internal/modules/cjs/loader.js:937
  throw err;
  ^

Error: Cannot find module './dist/shared.cjs.prod.js'
Require stack:
-<EMAIL_ADDRESS>- /Users/pontakornth/.vscode/extensions/johnsoncodehk.volar-0.31.1/node_modules/vscode-vue-languageservice/out/services/semanticTokens.js
- /Users/pontakornth/.vscode/extensions/johnsoncodehk.volar-0.31.1/node_modules/vscode-vue-languageservice/out/index.js
-<EMAIL_ADDRESS>-<EMAIL_ADDRESS>-<EMAIL_ADDRESS>    at Function.Module._resolveFilename (internal/modules/cjs/loader.js:934:15)
    at Module._load (internal/modules/cjs/loader.js:779:27)
    at Function.f._load (electron/js2c/asar_bundle.js:5:12913)
    at Module.require (internal/modules/cjs/loader.js:1006:19)
    at require (internal/modules/cjs/helpers.js:88:18)
    at Object.<anonymous> (/Users/pontakornth/.vscode/extensions/johnsoncodehk.volar-0.31.1/node_modules/@vue/shared/index.js:4:20)
    at Module._compile (internal/modules/cjs/loader.js:1125:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:1155:10)
    at Module.load (internal/modules/cjs/loader.js:982:32)
    at Module._load (internal/modules/cjs/loader.js:823:14) {
  code: 'MODULE_NOT_FOUND',
  requireStack: [
<EMAIL_ADDRESS>    '/Users/pontakornth/.vscode/extensions/johnsoncodehk.volar-0.31.1/node_modules/vscode-vue-languageservice/out/services/semanticTokens.js',
    '/Users/pontakornth/.vscode/extensions/johnsoncodehk.volar-0.31.1/node_modules/vscode-vue-languageservice/out/index.js',
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>  ]
}

This is the output from VSCode. HTML, document and API output similar errors.
System Information
Volar: 0.31.1
NPM: 8.1.2
PNPM: 6.23.6
Node: 16.0.0

@johnsoncodehk
It occurs randomly so I don't know how to reproduce it. Do you have any suggestion?
BTW I tried to restart the language server. It said "command 'volar.action.restartServer' not found". I think it might be related.

Although I don't know how this problem happen, I just fixed it in https://github.com/johnsoncodehk/volar/commit/3dcdb27742c7238acb62d6edf4e096093d8300bb, even it make the install package bigger.


chore: init java package

Initialize Java package
Description

Add a java project in pkg folder
Add global Makefile entries for Java language
Add Java code generation from antlr files

References
#138
Review Checklist

[x] I have clicked on "allow edits by maintainers".
[ ] I have added documentation for new/changed functionality in this PR or in a PR to openfga.dev [Provide a link to any relevant PRs in the references section above]
[x] The correct base branch is being used, if not main
[ ] I have added tests to validate that the change in functionality is working as expected

This first commit just add the java project that "receives" the generated code (there is no other code/test for now).
I tried to keep the same tooling than the java-sdk project.

@rhamzeh I added the tests stack to run all the "dsltojson", "jsontodsl" and "dslvalidator" tests based on what was written in the go and js packages. All tests are failing for now as nothing is implemented yet ^^

I also imported the code I worked on a couple months ago, 98 over 263 tests pass (especially conditions and mixed operators are not implemented at all).

Overall, it looks really good! Thanks @le-yams!
I'm still going over the code, but I see no problems with it so far. It's unfortunate Java is so verbose, but we have to live with that.
Will ask the rest of the folks to give it a look too!

can you add a workflow file for Java

I've just push it (I'm not very used to gradle and github workflows so it probably need some tweaking ^^).

@le-yams - just jumping in to say I love your progress on this and am very excited to see it when ready!

Thanks @rhamzeh :)
I'm close to getting all tests green. I currently am strugling with two final tests that stays red.
The two tests seems to be about the same thing (first for the dsl to json transformation, second for the dsl validation).
Here is a test output:
Expecting message to be:
  "3 errors occurred:
	* syntax error at line=1, column=0: extraneous input 'type' expecting {WHITESPACE, '#', 'model', NEWLINE}
	* syntax error at line=1, column=5: extraneous input 'user' expecting {'#', 'model', NEWLINE}
	* syntax error at line=2, column=0: mismatched input '<EOF>' expecting {'#', 'model'}

"
but was:
  "2 errors occurred:
	* syntax error at line=1, column=0: extraneous input 'type' expecting {WHITESPACE, '#', 'model', NEWLINE}
	* syntax error at line=1, column=5: mismatched input 'user' expecting {'#', 'model', NEWLINE}

"

Could it be related to the following comment present in the go dsltojson_test.go file?
_, err := transformer.TransformDSLToJSON(testCase.DSL)

errorsCount := len(testCase.ExpectedErrors)
if errorsCount == 0 {
  require.NoError(t, err)
} else {
  require.Error(t, err)

  // unfortunately antlr is throwing different error messages in Go and JS - considering that at the moment
  //  we care that it errors for syntax errors more than we care about the error messages matching,
  //  esp. in Go as we are not building a language server on top of the returned errors yet
  //  actual matching error strings is safe to ignore for now
  // require.EqualErrorf(t, err, testCase.GetErrorString(), "")
}

Because if I comment the size and messages related assertions (only keeping the error/no error check) it goes green.

Also - FYI we're working on modular models in this branch https://github.com/openfga/language/tree/feat/148-support-modular-models, which implements the ideas documented in the Modular Models RFC and in the language epic related to that.

Hey @rhamzeh :)

Also, I checked and it seemed the antlr files have not been regenerated, based on the latest antlr grammar in this branch (it might also be worth merging main and regenerating based of that)

Yes, I haven't worked on this branch in a while, it definitively needs a rebase and the grammar to be regenerated.

Finally, I may be doing something wrong but the tests keep failing for me locally

Not sure if it's the tests your talking about, there indeed was remaining failing tests and I was asking in my previous comment about it ^^.
I'll apply the differents suggestions you made and start to work on rebasing the branch :)

Unfortunately CI is still failing, looking into it.

Not sure if it's the tests your talking about, there indeed was remaining failing tests and I was asking in my previous comment about it

I don't think that's it, in my test run there were 203 tests failing 😕

@rhamzeh it seems that the CI has the same result as me and only 2 tests are failing 😃.
So should I make the assertion less precise to make them pass? (cf this comment)

Yep, let's! Then we can get it merged 🎉

@rhamzeh I did the same as in the go tests, I commented the assertions and added the same explaining comment

Super excited to have this finally in! Thank you @le-yams!


Steam Deck support?

I was wondering if I could run chimera os on my steam deck??

nvm its not bootable, but if anyone finds a bootable version of this image could you please post a link in the issue??

tried it, device /dev/disk/by-label/CHIMERAOS_202402 times out

I tend to have the time out error on my PC, depending on what port I plug the drive in. Either way, I just installed ChimeraOS stable 45-1 using Apr 1st ISO on my LCDeck without an issue. I'm using Valve's own docking station, btw.

I tend to have the time out error on my PC, depending on what port I plug the drive in. Either way, I just installed ChimeraOS stable 45-1 using Apr 1st ISO on my LCDeck without an issue. I'm using Valve's own docking station, btw.

I've trying using a usb-c to usb-a adapter directly into the SD and a genaric usb-c hub, but no dice.

I tend to have the time out error on my PC, depending on what port I plug the drive in. Either way, I just installed ChimeraOS stable 45-1 using Apr 1st ISO on my LCDeck without an issue. I'm using Valve's own docking station, btw.

I've trying using a usb-c to usb-a adapter directly into the SD and a genaric usb-c hub, but no dice.

Go into the UEFI (hold vol +) there’s a setting I. There relating to usb mode, it will be on drv (I think) change it to xhci and then you should be able to boot.
Was mentioned somewhere for bazzite but it also got the chimera installer booting for me

I tend to have the time out error on my PC, depending on what port I plug the drive in. Either way, I just installed ChimeraOS stable 45-1 using Apr 1st ISO on my LCDeck without an issue. I'm using Valve's own docking station, btw.

I've trying using a usb-c to usb-a adapter directly into the SD and a genaric usb-c hub, but no dice.

Go into the UEFI (hold vol +) there’s a setting I. There relating to usb mode, it will be on drv (I think) change it to xhci and then you should be able to boot.
Was mentioned somewhere for bazzite but it also got the chimera installer booting for me
posting from mobile

I may try that when I get homr