Tailwind bundling does not work with HAML views

If I understand correctly, cssbundling-rails watches my css files as well as my view files and re-builds the application.css, to only included css properties that have been used in the templates.
This works well for html.erb views, but not with html.haml.
Example & How to reproduce
With HTML
Create any view file, e.g. new.html.erb and copy paste the HTML from the Tailwind example here https://play.tailwindcss.com/
Re-build application.css using yarn build:css
Open the view in a browser and it will look like its supposed to be:

With HAML
Now, install the haml Gem, rename your view to new.html.haml and use some html2haml converter to switch from HTML to HAML.
Re-build application.css using yarn build:css
If you open the view in a browser again, it will not look correctly as the corresponding css classes are missing in application.css:

Conclusion & Findings
When using HAML views, the required css properties will not at all or not partially be bundled into application.css.
This can also be shown when comparing file sizes in the above stated scenarios: when using html.erb the bundled application.css will always have a couple KB more than when re-building with html.haml.
Also: when re-naming a xxx.html.erb file, yarn build:css --watch will automatically re-build your css. This does not happen if you use HAML files.
Fixes
Can anyone point me in the right direction on how to fix this in general or how to make HAML views also be working for my project? Any help appreciated!

The default tailwind configuration provided by the gem assumes erb files for its purge option. Since it's not looking for any haml files, they are skipped and the classes are purged from the built css.
See: https://github.com/rails/cssbundling-rails/blob/main/lib/install/tailwind/tailwind.config.js#L3
You should have the equivalent file in the root of your application. Does changing the file extension in the purge list from "erb" to "haml" fix your problem?

What t27duck said 👍


Keypair encoding / serialization to store the private key only

This is better hygiene, to also defend against the private - public key mismatching we found on ed25519 libs. The pub key can be derived during deserialization. Creating a similar issue in Sui repo.

we actually already does this when decoding from base64:
in fastcrypto:
    let secret = <T as KeyPair>::PrivKey::from_bytes(&bytes[..sk_length])?;
    let kp: T = secret.into();
    if kp.public().as_ref() != &bytes[sk_length..] {
        return Err(eyre::eyre!("Invalid keypair"));
    }

in sui:
                    let sk = Secp256k1PrivateKey::from_bytes(
                        bytes
                            .get(1 + Secp256k1PublicKey::LENGTH..)
                            .ok_or_else(|| eyre::eyre!("Invalid length"))?,
                    )?;
                    Ok(SuiKeyPair::Secp256k1(<Secp256k1KeyPair as From<
                        Secp256k1PrivateKey,
                    >>::from(sk)))

we can do this for encoding as well
            SuiKeyPair::Ed25519(kp) => {
                let kp1 = kp.copy();
                bytes.extend_from_slice(&[self.public().flag()]);
                bytes.extend_from_slice(kp.public().as_ref()); // change this to pubkey::from(kp.private())
                bytes.extend_from_slice(kp1.private().as_ref());
            }


chore: update files with goimport

Changes
I ran goimports on the source files and committed the updates. I also added a package name to a couple of e2e test files that I believe are just template stubs. This should get CI working with the new knative CI scripts.
We should consider having a git pre-commit hook for this...
Related: https://github.com/knative-sandbox/kn-plugin-func/pull/509
Signed-off-by: Lance Ball<EMAIL_ADDRESS>

@lance beside style changes this also includes some additional prints it it OK?

@lance beside style changes this also includes some additional prints it it OK?

Good catch! That was some junk I meant to remove - which I now have deleted.

/lgtm

From what I have seen/experienced in the "Go community",  gofmt and goimports are expected of all code inbound from developers, executed on save in their IDE of choice.  If we run gofmt and goimports in CI, pehaps it should be a check, failing the PR if any changes are detected in the working HEAD afer run?


Baud rate problem

Hello, i have installed the plugin on arduino ide 2.3.3 (windows11). When i use the command “upload little fs” i get an error about the baud rate option :
esptool: error: argument –baud/-b: invalid arg_auto_int value: ‘NaN’
ERROR: Upload failed, error code: 2
here is the command line outputted by your software :
C:\Users\yvesp\AppData\Local\Arduino15\packages\esp32\tools\esptool_py\4.5.1\esptool.exe --chip esp32s3 --port COM10 --baud NaN --before default_reset --after hard_reset write_flash -z --flash_mode dio --flash_freq 80m --flash_size detect 2686976 C:\Users\yvesp\AppData\Local\Temp\tmp-14956-36WGP1eEy8cA-.littlefs.bin
Any idea ?
Best Regards
Yves
PS :  my board is an arduino nano esp32, it seems that the software does not get the right baudrate from arduino context

I think your board only does DFU and not esptool/serial.  That's not compatible with the uploader.  There's no workaround other using a more standard board.

Ok Tnx, my board is the standard arduino nano esp32, anyway which similar board is compatible with your plugin ?

@per1234, tnx a lot, i will try your solution.

I've also added a link to that comment in the README.md file.  Thanks, @per1234 !
On a side note, it's not that hard to add add'l upload methods, but I don't have anything that uses DFU upload. I assume that mode can place arbitrary data in arbitrary spots, so if someone has a command line sample for uploading a FS then it'd be possible to add it in (like the OTA and picotool methods just done).  I'd also assume there's a board.xxxx variable I can reference to know it's DFU and not normal esptool...


Null response when deleting a campaign

It deletes the campaign but .then(response) returning null.

@timsim00 if you could give more detail that would be great. Things I need would be:

Example setup (minus keys/secrets)
The response from the API

Not much to it.  The row is deleted but the response is null.
	var options = {
		uri: this.endpoint + '/' + this.config.id
	};

	this.parent.RestClient
		.delete(options)
		.then(function(response) {
			console.log('then',response);  <---- Null here.
			cb(response);
		}.bind(this))
		.catch(function(err) {
			cb(err);
		}.bind(this));
}

@timsim00 Can you please provide the reply from the API (status, msg, etc)?

I added console.logs to fuel-rest.js starting at line 101:
			request(options, function(err, res, body) {
				var parsedBody, restResponse;
				console.log('body',body);
				console.log('err',err);
				console.log('res',res);

Here's the console:
body
err null
res {the entire response object with only meaningful data:
statusCode: 200,
statusMessage: 'OK',
body: ''
}
then null
campaign.delete null

Okay, I will update something to deliver the status code and message if no body exists. Would assume this is the same for post (sometimes), put, and patch in addition to delete


false DNSSEC BOGUS errors.

I'm writing this here, because the wiki also has a section 'How to setup your own DNSCrypt server in less than 10 minutes' and really don't know if this is the image used by 'Martin 'd0wn' Albus', who provides a lot of 'd0wn' dnscrypt servers.
After communicating with the developer of dnsmasq (Simon Kelley), and performing a lot of test, Simon even duplicated my dnsmasq + DNSSEC + dnscrypt-proxy setup, this to determine the cause of false BOGUS errors, I have been getting.
His conclusion:
'quote'
The fundamental problem is still the one I showed before: missing RRSIG data in the AUTHORITY section validating NSEC records which prove that a DS record does not exist. The insight is that these are only missing when the answer comes via UDP: they are present when the answer comes via TCP.
Getting the answer via UDP or TCP depends on the state of the dnsmasq cache. This is because the answer to query for the root key is too long to fit in a UDP packet via dnscrypt. If dnsmasq queries the root key during its attempt to validate the query above, then the answer will be truncated, and dnsmasq will restart the whole process, using TCP. Since when using TCP, the RRSIG are not omitted, everything works.
If, on the other hand, dnsmasq has the root key cached (or more generally, doesn't trip over anything that requires a move to TCP) then the missing RRSIGs in the answer via UDP now matter, and the validation fails.
'/quote'
When using NO 'd0wn' servers, limiting the servers to 'dnscrypt.eu-dk' and 'dnscrypt.eu-nl', the problem disappears.
Simon tried to get info regarding the versions of running dns software of the dnscrypt servers, used by 'd0wn', but hasn't received a reply (yet).
Currently, a lot of (pihole) users are driven away from dnscrypt-proxy towards a solution, using ubound, because the use of DNSSEC leads to problems, when using dnscrypt-proxy. It's only very recent that it has been determined the problem is related to certain servers, providing dnscrypt + DNSSEC.
Is it possible to find out witch servers are using the docker image, this to determine if the servers, using this image, are also causing this problem? It would be helpful if the versions of the DNS software used, could also be mentioned.
Thanks

The Docker image uses Unbound. d0wn servers don't appear to be using Unbound. It doesn't send anything different over TCP than UDP, besides possibly truncated responses.
The Docker image also supports ChaChaPoly for encryption (and not the old cipher any more). d0wn servers apparently don't support it.
So, d0wn servers don't appear to be running that image. Bugs should be reported to him directly.

Would it be possible to provide a list of servers, that use the docker image, so I can test them?
I'm using this site  (https://dnscrypt.info/public-servers/) to get servernames.
Thanks

How would I know?
scaleway-fr, sfw.scaleway-fr and doh.crypto.sx do. I don't know about the other ones.

@jpgpi250 dnscrypt.me uses a modified docker image with Unbound too,


Maintenance: make layer-publisher part of the main npm workspace

Summary
The layer-publisher folder contains the utilities and tests used to publish AWS Lambda Layers for Powertools. When this was developed, it was developed in isolation and with its own dependency tree. Now that the component is somewhat stable, and the dependencies of the main npm workspace has been recently updated, we can bring the folder in the npm workspace so that the dependencies are shared.
Why is this needed?
Because if the two dependency trees are not aligned we risk incurring in the issue described in #1227 every time one of the two trees change. Both trees depend on aws-cdk-lib which has a weekly release cadence so, while the issue is now fixed, it's likely it'll happen again.
Additionally, by having the layer-publisher in the main npm workspace we can decrease the project's footprint on development & CI hosts (because of sharing dependencies) and also simplify some of the workflow that are now disjointed.
Which area does this relate to?
Automation, Other
Solution
No response
Acknowledgment

[X] This request meets Lambda Powertools Tenets
[ ] Should this be considered in other Lambda Powertools languages? i.e. Python, Java

While addressing this issue, also try removing the hardcoded CDK version from this workflow.

Also remove this other hardcoded version in this other workflow.


[Modelzoo] Rebuild SimpleMultiTask to update API & enable DeepRec features

~Rebuild ESMM to update API according to the template~
enable following DeepRec feature:
7) ~StarServer~
8) ~Auto Micro Batch~ same with  [Auto Micro Batch] After enable Auto Micro Batch feature in WDL of modelzoo, but get an error. alibaba/DeepRec#127
9) ~FusedEmbedding API waiting related PR merged.~
10) ~Smart Stage same with [SmartStaged][Modelzoo] After enable smartstaged feature in WDL of modelzoo, but get an error. alibaba/DeepRec#122~
11) ~Auto Graph Fusion~
12) ~CPU Memory Optimization:START_STATISTIC_STEP, STOP_STATISTIC_STEP, jemalloc~
14) ~AdamAsync Optimizer~
15) ~BF16~
Feature Doc:
1 ) Embedding Variable (Not support EV yet)
7) ~GRPC++~
13) ~Incremental Checkpoint~
14) AdagradDecay (fails on last training steps, in the same manner as BST model)
（optional, default to closed.)
2) EmbeddingVariable进阶功能：特征淘汰 (Not support EV yet)
3) EmbeddingVariable进阶功能：特征准入 (Not support EV yet)
4) Dynamic-dimension Embedding Variable (There is no feature_column API)
5) Adaptive Embedding (fails on last steps with an error: tensorflow.python.framework.errors_impl.InvalidArgumentError: data.shape must start with partitions.shape, got data.shape = [336], partitions.shape = [512] [[{{node input_layer/input_layer/brand_embedding/DynamicPartition_1}}]] same as BST model, that also fails for that feature with similar error)
6) //Multi-Hash Variable(no feature column related API)
17) ~WorkQueue~

Here is the Adaptive Embedding issue https://github.com/alibaba/DeepRec/issues/236. Please check adagraddecay issue, I can't reproduce on this model by python train.py --steps 100 --optimizer adagraddecay with whl package https://deeprec-whl.oss-cn-beijing.aliyuncs.com/tensorflow-1.15.5%2Bdeeprec2204-220526%2B7ae421edefault-cp36-cp36m-linux_x86_64.whl

Here is the Adaptive Embedding issue alibaba#236. Please check adagraddecay issue, I can't reproduce on this model by python train.py --steps 100 --optimizer adagraddecay with whl package https://deeprec-whl.oss-cn-beijing.aliyuncs.com/tensorflow-1.15.5%2Bdeeprec2204-220526%2B7ae421edefault-cp36-cp36m-linux_x86_64.whl

For SimpleMultiTask model you need to enable --adaptive_emb true to check whether it runs. Have you run the script by python train.py --steps 100 --optimizer adagraddecay --adaptive_emb true ?
See my outputs from AliCloud:

Adaptive Embedding

:~/DeepRec/modelzoo/SimpleMultiTask# python train.py --steps 100 --optimizer adagraddecay --adaptive_emb true
Using TensorFlow version 1.15.5
Running stand-alone mode training
Checking dataset...
Number of batch size: 512
Numbers of training dataset: 50000
Number of epochs: 2
Number of train steps: 100
Numbers of test dataset: 10000
Numbers of test steps: 20
Optimizations
        Number of micro batches: 0
        Embedding Fusion Feature: True
        SmartStage Feature: True
        Auto Graph Fusion: True
        EmbeddingVariable: False
        Feature Elimination of EmbeddingVariable Feature: None
        Feature Filter of EmbeddingVariable Feature: None
        Adaptive Embedding: True
        Dynamic-dimension Embedding Variable: False
        Incremental Checkpoint: None
        WorkQueue: False
Used optimizer: adagraddecay
Saving model events to ./result/model_SimpleMultiTask_1653915541
Maximum number of saved checkpoints: 1
2022-05-30 12:59:02.794654: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.796773: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.836100: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.839984: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.843068: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.906163: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.906494: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:02.909515: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.085652: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.095222: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.104658: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.114008: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.123520: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.132801: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.142137: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.151493: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.160838: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.170199: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.179547: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.189395: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.198711: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.208204: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.217568: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.227019: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.236469: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:03.245920: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Init incremental saver , incremental_save:False, incremental_path:./result/model_SimpleMultiTask_1653915541/.incremental_checkpoint/incremental_model.ckpt
2022-05-30 12:59:04.623750: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:04.624162: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:04.692115: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:04.692480: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
INFO:tensorflow:Graph was finalized.
2022-05-30 12:59:04.712692: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2022-05-30 12:59:04.713503: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56078a68c640 initialized for platform Host (this does not guarantee that XLA will be used).
INFO:tensorflow:Prefetching was cancelled.
INFO:tensorflow:Prefetching was cancelled.
INFO:tensorflow:Prefetching was cancelled.
Training completed.
INFO:tensorflow:Graph was finalized.

INFO:tensorflow:Prefetching was closed.
INFO:tensorflow:Prefetching was closed.
INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.InvalidArgumentError'>, data.shape must start with partitions.shape, got data.shape = [272], partitions.shape = [512]
         [[{{node input_layer/input_layer/cms_group_id_embedding/DynamicPartition_1}}]]
ERROR:tensorflow:Prefetching was cancelled unexpectedly:

data.shape must start with partitions.shape, got data.shape = [272], partitions.shape = [512]
         [[{{node input_layer/input_layer/cms_group_id_embedding/DynamicPartition_1}}]]
Exception in thread PrefetchThread-PrefetchRunner-2:
Traceback (most recent call last):
  File "/home/pai/lib/python3.6/threading.py", line 916, in _bootstrap_inner
    self.run()
  File "/home/pai/lib/python3.6/threading.py", line 864, in run
    self._target(*self._args, **self._kwargs)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/ops/prefetch_runner.py", line 236, in run
    run_fetch(*feed)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1287, in _single_operation_run
    self._call_tf_sessionrun(None, {}, [], target_list, None)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: data.shape must start with partitions.shape, got data.shape = [272], partitions.shape = [512]
         [[{{node input_layer/input_layer/cms_group_id_embedding/DynamicPartition_1}}]]

2022-05-30 12:59:31.443517: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
2022-05-30 12:59:33.197650: I ./tensorflow/core/common_runtime/kernel_stat.h:74] User collect node stats, start_step is 100, stop_step is 200
Traceback (most recent call last):
  File "train.py", line 403, in eval
    eval_acc, eval_auc, events = sess.run([model.acc_op, model.auc_op, merged])
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 804, in run
    run_metadata=run_metadata)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1309, in run
    run_metadata=run_metadata)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1408, in run
    raise six.reraise(*original_exc_info)
  File "/home/pai/lib/python3.6/site-packages/six.py", line 719, in reraise
    raise value
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1395, in run
    return self._sess.run(*args, **kwargs)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1468, in run
    run_metadata=run_metadata)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1226, in run
    return self._sess.run(*args, **kwargs)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
    run_metadata)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.CancelledError: Session was closed.
         [[node prefetch_2/TensorBufferTake (defined at /home/pai/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Original stack trace for 'prefetch_2/TensorBufferTake':
  File "train.py", line 775, in <module>
    main(stock_tf)
  File "train.py", line 517, in main
    next_element = tf.staged(next_element, num_threads=4, capacity=40)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/ops/prefetch.py", line 140, in staged
    shared_threads=num_clients)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_tensor_buffer_ops.py", line 535, in tensor_buffer_take
    shared_threads=shared_threads, name=name)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 775, in <module>
    main(stock_tf)
  File "train.py", line 546, in main
    model_dir, checkpoint_dir)
  File "train.py", line 406, in eval
    print(f'ACC = {eval_acc}\nAUC = {eval_auc}')
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 911, in __exit__
    self._close_internal(exception_type)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 949, in _close_internal
    self._sess.close()
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1216, in close
    self._sess.close()
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/monitored_session.py", line 1384, in close
    ignore_live_threads=True)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/training/coordinator.py", line 389, in join
    six.reraise(*self._exc_info_to_raise)
  File "/home/pai/lib/python3.6/site-packages/six.py", line 718, in reraise
    raise value.with_traceback(tb)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/ops/prefetch_runner.py", line 236, in run
    run_fetch(*feed)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1287, in _single_operation_run
    self._call_tf_sessionrun(None, {}, [], target_list, None)
  File "/home/pai/lib/python3.6/site-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: data.shape must start with partitions.shape, got data.shape = [272], partitions.shape = [512]
         [[{{node input_layer/input_layer/cms_group_id_embedding/DynamicPartition_1}}]]

So this is actually an issue of Adaptive Embedding? Or is it a compatibility issue with Adaptive Embedding and adagraddecay? After Ali fixes the issue of Adaptive Embedding submitted before, if this situation still exists, I will submit an issue.

a compatibility issue with Adaptive Embed

Same error is visible when you run just python train.py --steps 100 --adaptive_emb true .  Optimizer type doesn't matter for it. It looks like the same issue as yours in https://github.com/alibaba/DeepRec/issues/236

FYI, Performance in Jira.

@Duyi-Wang @shanzhou2186 The performance is in Jira. Is there anything else I should do with the PR to have it merged?


Repository https://packages.adoptium.net/ui/native/rpm/rhel/7/x86_64/ doesn't work

Hi everybody,
I hope I am here on the right place to report this issue. If not I would be very happy for any hints where I should report this...
Currently we are trying to use https://packages.adoptium.net/ui/native/rpm/rhel/7/x86_64/ but we receive a the following message:
https://packages.adoptium.net/ui/native/rpm/rhel/7/x86_64/repodata/repomd.xml: [Errno -1] Error importing repomd.xml for blafsel: Damaged repomd.xml file

If I use curl to retrieve the given url then I get a error message from jfrog saying that "We're sorry but jfrog webapp doesn't work properly without JavaScript enabled. Please enable it to continue." So I assume, that the request generated by yum get the same false content.
Is there a configuration error in jfrog?

@DrVanScott please can you confirm if the steps outlined above fixed your issue?

Sorry, for my late response. Yes, of course, this solves my "issue". Thank you very much!


Help me

I'm write python3.6 run.py but the bot freeze yourself

Hi there!
The information provided lacks any sort of description, and you also haven't provided any information that the issue template asks for. With this in mind, lacking logs or a proper description of the issue makes it harder for us to help you.


Redesign notification and alert UI design

Background
The current notification design is outdated and does not efficiently use space.
Acceptance Criteria
New Notification design requirements:

Space for timestamp
Space for expiry time
Efficient use of space

Design/Wireframes
See notification design v2:
https://www.figma.com/design/yemQcCoosIeUKWXiaI8HXX/BC-Wallet-Style-Guide?node-id=1038-709&m=dev

Added notification design v2.

@knguyenBC to follow up on latest designs.

Updated the ticket with design resources


BUG: create condition: conditions should always be an array

AS-IS
When the first condition is created, the response message shows the condition as an object

When further conditions are create, the response message is an array

TO BE

condition should be renamed conditions
Conditions should always be an array irrespective of the number of conditions

Tested and confirmed fixed


Rework Generics of Transformer interface

@snuyanzin  could you review generics in Transformer interface, please?
I've found a number of issues here:

On the code below, Schema<?, ? extends OUT> means that OUT transform(IN input) function from Field interface could generate the value only of some specific type. For example for CsvTransformer class, OUT is defined as CharSequence, so it means that we can generate CSV only from CharSequence, we couldn't generate CSV (fields) from other objects (integer, double, boolean e.g.).
Take a look on the test case testCsvWithDifferentObjects and testCsvWithDifferentObjectsFunction.

public interface Transformer<IN extends AbstractProvider<?>, OUT> {
    OUT apply(Object input, Schema<?, ? extends OUT> schema);
...

Here, IN generic type should not extends AbstractProvider, because in fact that type corresponds to the
Schema<IN, ...> interface  then it is passed to the function OUT transform(IN input)  from Field interface, that function takes an argument of IN type and feeds it to the functional interface, which generates the data based on the argument, therefore, the argument could be an object of any type.
Take a look on the test case testCsvWithDifferentObjects and testCsvWithDifferentObjectsFunction.

public interface Transformer<IN extends AbstractProvider<?>, OUT> {
    ...
    String generate(List<IN> input, final Schema<IN, ? extends OUT> schema);
    ...
}

I think all the functions from interface Transformer should return a data of type OUT

Otherwise, if we don't want to change the types definition, we have to try to adjust the code to that types.

Codecov Report

Merging #447 (fa62365) into main (35651df) will increase coverage by 0.02%.
The diff coverage is 100.00%.

@@             Coverage Diff              @@
##               main     #447      +/-   ##
============================================
+ Coverage     93.00%   93.03%   +0.02%
- Complexity     2094     2098       +4
============================================
  Files           233      233
  Lines          4373     4377       +4
  Branches        449      449
============================================
+ Hits           4067     4072       +5
+ Misses          190      186       -4
- Partials        116      119       +3

Impacted Files
Coverage Δ

.../net/datafaker/transformations/CsvTransformer.java
93.10% <100.00%> (+0.51%)
:arrow_up:

...net/datafaker/transformations/JsonTransformer.java
88.04% <100.00%> (ø)

.../net/datafaker/transformations/SqlTransformer.java
66.66% <100.00%> (ø)

.../main/java/net/datafaker/service/FakerContext.java
87.17% <0.00%> (+2.56%)
:arrow_up:

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more

awesome, thanks


WIP Add support for React Suspense

@reaktivo: sorry for introducing conflicts in the tests 😬

closing since there's no activity for months now. please ping me if you want this reopened anytime :)


phpunit droped database but not executed

When i run "make phpunit" i getting:
docker-compose exec php sh -lc './bin/console d:d:d --force'
Dropped database for connection named `api`
docker-compose exec php sh -lc './bin/console d:d:c'
Created database `api` for connection named default
docker-compose exec php sh -lc './bin/console d:m:m -n'

After that i'm getting:
  ++ 2 migrations executed
  ++ 2 sql queries
docker-compose exec php sh -lc "./bin/phpunit "
#!/usr/bin/env php
PHP Fatal error:  Uncaught RuntimeException: Could not find https://github.com/sebastianbergmann/phpunit/archive/6.5.zip in /app/vendor/symfony/phpunit-bridge/bin/simple-phpunit:99
Stack trace:
#0 /app/bin/phpunit(18): require()
#1 {main}
  thrown in /app/vendor/symfony/phpunit-bridge/bin/simple-phpunit on line 99
make: *** [phpunit] Error 255

Thanks @yoshkin for report this.
Fixed in #98


1.8 Support: is it possible?

You won't get this working on 1.8 because in MC 1.8 there is no "Marker tag" and without that the pipes have a hitbox. Therefore the placing and breaking of them is a big issue.

How do you use the marker tag?

byte bitMask = (byte) ((asd.isSmall() ? 0x01 : 0x00) | 0x04 | 0x08 | 0x10); //(small) + hasArms + noBasePlate + Marker
This is in the class ArmorStandProtocol and it enables the marker tag. With the marker tag enabled the pipe armor stands haven't got an entity hitbox therefore I can easily handle a click onto the block behind. You can remove this marker tag and see what it does :/
If you press f3 + h I think you can see the hitbox of the armorstand (in gamemode 3)

Can I close this issue or do you have any idea to avoid the marker tag problem?

I stopped working on that, i updated all my servers to 1.11.2.


Detect external libiconv and make libiconv and git non-buildable on macOS

Summary
Detect external libiconv and make libiconv and git non-buildable on macOS. This addresses the issue mentioned in https://github.com/JCSDA/spack-stack/pull/672#issuecomment-1677523132.
Making git and libiconv non-buildable on macOS avoids running these commands manually as users.
Testing
Tested on my macOS laptop.
Applications affected
n/a
Systems affected
macOS systems
Dependencies

[ ] waiting on https://github.com/JCSDA/spack/pull/301

Issue(s) addressed
See https://github.com/JCSDA/spack-stack/pull/672#issuecomment-1677523132
Checklist

[x] This PR addresses one issue/problem/enhancement, or has a very good reason for not doing so.
[x] These changes have been tested on the affected systems and applications.
[ ] All dependency PRs/issues have been resolved and this PR can be merged.

Thanks @srherbener. I got the following ctest failures for jedi-bundle when using Rosetta2 x86_64. I think these are expected.
The following tests FAILED:
	 14 - test_util_signal_trap (Failed)
	355 - saber_test_error_covariance_training_bump_hdiag-nicas_2_1-1 (Failed)
	440 - saber_test_error_covariance_training_bump_hdiag-nicas_2_2-1 (Failed)
	1087 - ufo_test_tier1_test_ufo_qc_variableassignment (Failed)
	1211 - ufo_test_tier1_test_ufo_opr_gnssrorefmetoffice (Failed)
	1215 - ufo_test_tier1_test_ufo_opr_gnssrobendmetoffice_nopseudo (Failed)
	1223 - ufo_test_tier1_test_ufo_opr_groundgnssmetoffice (Failed)
	1276 - ufo_test_tier1_test_ufo_opr_scatwind_neutral_metoffice (Failed)
	1450 - fv3jedi_test_tier1_errorcovariance (Failed)
	1496 - fv3jedi_test_tier1_errorcovariance_bump (Failed)
	1559 - test_soca_errorcovariance (Failed)

Also, on the same machine using the native arch64 build, I got the following ctest failures (expected?):
The following tests FAILED:
	 14 - test_util_signal_trap (Failed)
	355 - saber_test_error_covariance_training_bump_hdiag-nicas_2_1-1 (Failed)
	440 - saber_test_error_covariance_training_bump_hdiag-nicas_2_2-1 (Failed)
	745 - test_ioda-engines-00-Strings-F (SEGFAULT)
	1071 - ufo_test_tier1_test_ufo_qc_average_obs_to_mod_levels (Failed)
	1087 - ufo_test_tier1_test_ufo_qc_variableassignment (Failed)
	1211 - ufo_test_tier1_test_ufo_opr_gnssrorefmetoffice (Failed)
	1215 - ufo_test_tier1_test_ufo_opr_gnssrobendmetoffice_nopseudo (Failed)
	1223 - ufo_test_tier1_test_ufo_opr_groundgnssmetoffice (Failed)
	1276 - ufo_test_tier1_test_ufo_opr_scatwind_neutral_metoffice (Failed)
	1450 - fv3jedi_test_tier1_errorcovariance (Failed)
	1496 - fv3jedi_test_tier1_errorcovariance_bump (Failed)
	1560 - test_soca_errorcovariance (Failed)
	1595 - test_soca_sqrtvertloc (Failed)
	1622 - test_soca_convertincrement (Failed)

I'll go ahead and merge the spack PR.

@climbfuji your list of test failures on the ARM based Mac looks like the one I get. I have one additional test failure on my Mac: ufo_test_tier1_test_ufo_function_orbitangle_ssmis which is due to a breech of a tolerance limit on a floating point value check.


Improvement of InMemoryRoleProvider

This PR follows on the issue here
A $roles array storage is added to the InMemoryRoleProvider in which resolved roles are stored. It means role instances with the same name are reused (and not recreated). This will save memory and allows 1 to 1 role object comparison since the InMemoryRoleProvider will always return the same object instance for a certain $roleName.
A test for this enhancement is provided.

I will close and change target to develop branch


Add LRU cache to RequirementsFinder._get_names

This caches the result of the function for future invocations with the same
input, which can massively speed up future invocations if they have the same
input as previous calls.
In the case of this function this happens a lot, and each invocation is quite
expensive as the requirements file is parsed every time.
This gives a quite significant performance boost. I've tried running isort
with and without this patch on two different applications on Python 3.7.2 and
one one application the run time drops from 12.67 seconds to 1.3 seconds and
on the other it drops from 28.29 seconds to 2.1 seconds.
This optimisation is similiar to the one which was done for the 4.3.x branch
here: https://github.com/timothycrosley/isort/pull/856.

Looking at the errors from the AppVeyor build, it doesn't seem like many of the are related to this PR. Are those tests expected to pass?

This looks great, Thanks!
AppVeyor stopped running at some point - unintentionally, and as a result, a lot of Windows bugs were introduced. I spent some time over the last few days fixing those after turning it back on.


Debug log service

flynn-host collect-debug-info currently uploads logs to gist.github.com and frequently fails when logs are too big to upload, and our strategy of buffering all the logs in memory before creating the gist also sometimes causes issues.
Although we have a --tarball fallback, it is not always easy for users to share that in order to get assistance.
We should add a dedicated service which receives the logs from flynn-host collect-debug-info (perhaps as a stream to minimise in-memory buffering) and exposes them to Flynn collaborators for viewing.
Some things to consider:

Web UI (I personally prefer CLI tools like less and grep)
Authentication
Storage (most likely S3 backed blobstore)
Size limit
Rate limit
Encrypted logs (public Flynn GPG key?)
Resumable uploads

/cc @titanous

Flynn is unmaintained and our infrastructure will shut down on June 1, 2021. See the README for details.


math/big: Mention sign inversion in the (*Int).Not documentation

I would expect that this:
i = big.NewInt(-2)
log.Println(new(big.Int).Not(i).Text(2))

prints -1, but actually it prints 1. The (*Int).Not documentation simply says:

Not sets z = ^x and returns z.

I think that it's not obvious from this sentence that the sign is inverted.

CC @griesemer for math/big


Update ChattererExtended-0.6.2.ckan

Remove ksp_version_max as compatibility with KSP is controlled by chatterer.

Looks like a valid idea in principle, since the ZIP contains no DLLs, just audio files. But the forum thread does explicitly state 1.4.2, and the author hasn't responded yet about broadening the compatibility. In theory if we updated this and there was a problem with 1.8 compatibility, users might seek support and irritate the author, and it would be our fault.
However, this PR won't work, because the NetKAN bot will automatically revert it within 2 hours based on the mod's version file. So we would need to do a NetKAN PR instead.

Replaced by KSP-CKAN/NetKAN#7511.


Melee enemy, and restructured statistics

Created a Melee enemy that will track the player when they get close.  If the enemy gets close enough then they can make an attack.  Reordered the statistics so that any entity can use it, and fixed the HP bars so that it would work.
LIVI IDK IF I"M PULL REQUESTING CORRECTLY, SO CAREFUL WITH THE MERGE :D

LGTM


First example of a multi-cluster openshift-applier run

What does this PR do?
Proposed example of a multi-cluster openshift-applier run. Would like to discuss this approach.
Note that there's potentially one shortcoming with this approach - i.e.: using kubeconfig with pre/post steps. The pre/post step roles will need to be made kubeconfig aware (unless we find a way to apply it globally on a per-host basis).
How should this be tested?
N/A - proposal up for discussion
Is there a relevant Issue open for this?
N/A - proposal up for discussion
Who would you like to review this?
cc: @redhat-cop/openshift-applier

@oybed Looks good

@oybed so, with the changes to the role, would that require any changes to existing inventories?

@etsauer first off, I just updated the title of this PR with WIP to indicate that this isn't something to merge as-is.
This PR is a proposal for how we can handle multi-clusters. The goal would be to not have to change existing inventories, and that should be doable. However, we need to come up with the "improved story" around how we manage OpenShift sessions, so the solution should be:

Should be able to use existing inventories as-is (including providing a valid session at runtime)
Provide login info for handling login/session at runtime
Handle multiple clusters (each with separate sessions - either existing of new per 1 & 2 above).

@oybed understood, and I like the approach.

Based on the feedback so far, it seems that this approach is worth the effort, so I'll spend some time on finalizing the approach and polish the implementation.

Another use case I would like to see work:
cluster1.yml:
openshift_login_url: https://console.cluster1.example.com
openshift_user: bob
...

cluster2.yml:
openshift_login_url: https://console.cluster2.example.com
openshift_user: bob

Run:
oc login -u bob https://console.cluster1.example.com
Password:
oc login -u bob https://console.cluster2.example.com
Password:
ansible-playbook ....

@etsauer are you ok if the prompts are part of the ansible run? Basically something similar to this:
https://github.com/redhat-cop/infra-ansible/blob/master/playbooks/prep.yml


Containerized traindiff tests are failing.

Fast repro in containerized env:

pull docker image
docker pull us-central1-docker.pkg.dev/training-algorithms-external/mlcommons-docker-repo/algoperf_dev
run container and bash into it.
docker run -t -d us-central1-docker.pkg.dev/training-algorithms-external/mlcommons-docker-repo/algoperf_dev --keep_container_alive true
docker exec -it <container_id> /bin/bash
Run test:
cd algorithmic-efficiency
python3 tests/test_traindiffs.py

Full repro in test env:

Make sure GH actions runner is installed and your machine has been added to our self-hosted runners.
start actions runner from $HOME/actions-runner run:
./run.sh
Make a new branch and disable the tests and disable the other regression tests so you don't have to wait for all of those tests to finish.
Make a dummy PR into the main branch to trigger the automated tests. I would just temporarily remove the .github/worklfows/regression_test*.yml.

Fixed https://github.com/mlcommons/algorithmic-efficiency/pull/649.

Reopening to track FastMRI traindiff test failure.

@runame @chandramouli-sastry
FastMRI traindiff tests looks fine in docker containerized test
==================================================================Testing fastmri===================================================================
|        Iter        |     Eval (jax)     |    Eval (torch)    |  Grad Norm (jax)   | Grad Norm (torch)  |  Train Loss (jax)  | Train Loss (torch) |
====================================================================================================================================================
|         0          |      1.11668       |      1.11668       |      1.09795       |      1.09796       |      1.11789       |      1.11789       |
|         1          |      1.11548       |      1.11548       |     1.0957099      |      1.09571       |      1.11668       |      1.11668       |
|         2          |      1.11429       |      1.11429       |      1.09367       |      1.09368       |      1.11548       |      1.11548       |
|         3          |       1.1131       |       1.1131       |      1.09162       |      1.09162       |      1.11429       |      1.11429       |
|         4          |      1.11191       |      1.11191       |      1.08919       |      1.08919       |     1.1130999      |       1.1131       |
|         5          |      1.11073       |      1.11073       |      1.08695       |      1.08695       |      1.11191       |      1.11191       |
|         6          |      1.10956       |      1.10956       |     1.08[47](https://github.com/mlcommons/algorithmic-efficiency/actions/runs/8029080213/job/21935418348#step:3:48)499      |      1.08475       |     1.1107299      |      1.11073       |
|         7          |      1.10839       |      1.10839       |      1.082[48](https://github.com/mlcommons/algorithmic-efficiency/actions/runs/8029080213/job/21935418348#step:3:49)       |      1.08248       |      1.10956       |      1.10956       |
|         8          |      1.10722       |      1.10722       |      1.08032       |      1.08031       |      1.10839       |      1.10839       |
|         9          |      1.10606       |      1.10606       |      1.07817       |      1.07817       |     1.1072199      |      1.10722       |
====================================================================================================================================================


Sar dv

This PR is only for debug purpose, it shouldn't be merged !

@andreaskurth and @gdessouky
I have pushed my ongoing work related to the Save and Restore feature. This PR goal is only to share this code with you to reproduce the following issue at your end if you have time to help.

As you can see on this image:

we are triggering a hash_stop as message_length counter is on the 512 boundary (we are in SHA-256 mode).
interrupt hmac_done is happening
But the digest is not updated as sha_hash_done is not raised

To reproduce this issue you can use the following command (if you are using Xcelium you can run it in GUI mode and I have enabled the breakpoints):
util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed<PHONE_NUMBER>73648776435301108104832965337850972304806816025000095479785483310546
Note: you'll see the same issue whatever the seed as I have added some constraints

Thx for providing this snapshot of your work, @martin-velay. I ran hmac_smoke with the seed you posted and could reproduce your waves. I noticed a few things that I think are problematic on the DV side:

When HMAC is stopped for a context swap (i.e., the CMD.hash_stop bit is set), the content of the digest registers is expected to be the intermediate digest of the HMAC operation, not the final digest. To visualize this in an example:

When HMAC is stopped at the red arrow, the intermediate digest includes the inner padded key and N message blocks (two in this example), but it does not include hash of the entire first round and the outer padded key (blue cross). The expected digest in the scoreboard, however, seems to come from a DPI call that computes the final digest, i.e., if HMAC was told to process at the red arrow. I think this is why the values read from the digest registers don't match the expectation. Now ideally we would have golden model functions to compute the intermediate digest, and I think the cryptoc DPI code can be extended to expose this -- though @gdessouky likely has much more knowledge on this. (When I did basic verification while implementing the feature, I did not check the intermediate values. Instead, I just saved, cleared, and restored the digest registers and then told HMAC to continue, and in the end I checked that the final digest matched the golden model.)

Hi Andreas,
Thanks a lot for your analysis, I understand better now what is happening. I'll continue from this point. And sorry for making you work that late !

Thanks for sharing @martin-velay and your feedback @andreaskurth, yes indeed these are the intermediate digest values, so comparing with predicted values from the C model will not work. This is where the C model is https://github.com/lowRISC/opentitan/tree/master/hw/ip/hmac/dv/cryptoc_dpi. I'm sure we can adapt it to generate and compare intermediate digest values for thorough confidence on functionality, but this will take some work and debugging still. I think if we compare final digest values for now and confirm they match prediction, then we already have very good confidence on functionality. My suggestion would be to de-prioritize this at the moment in favor of higher-prio changes required, and we can spin out an issue to track this for DV improvements once we all have more bandwidth, WDYT?

Thanks again @andreaskurth for your support, it helped me a lot to be able to move forward. I have pushed some fixes, now the first S&R with same context is working. Still with the same seed I have another S&R which triggered and failing. I'll investigate on my own and keep you informed.
@gdessouky about your last comment above: no problem to update the C model later. You'll see in my last commit that I am skipping the comparison of the intermediate digest for the moment 👌

My last commit #af69f1b is addressing the point 1 mentioned in my comment from yesterday. Now the digest is not matching because the digest is not updated at the right time as mentioned yesterday. I'll now try to understand if the reason is the RTL/TB.

Here is the issue I am observing with the latest commit and still with the same command:
util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed<PHONE_NUMBER>73648776435301108104832965337850972304806816025000095479785483310546

The following line is triggered as the message_length is indeed =512.
https://github.com/lowRISC/opentitan/blob/349bab6601c24b1d01b7264296bfc1c3bcd6c631/hw/ip/hmac/rtl/hmac.sv#L173
Then, as hash_running is 0, the hash_done_event is triggered but the digest has been updated too early.
I guess something is wrong there, I don't know enough the RTL to say precisely what's going on.
Could you have a look @gdessouky / @andreaskurth ?

After the lasts commits, verification is slightly moving forward. There is now another issue, but I haven't found yet the root cause. I can just tell you that intermediate digest seems to match (check with debug prints in the C files added with Andreas help) but the final digest is not matching. To be investigated.

@andreaskurth I am now comparing the waves when it's working with a similar S&R against the non-working one. Both of them are triggering a S&R while the message_length counter is equal to 512.
I could notice 2 main differences so far, but still no conclusion:

the intermediate HMAC hash is using some pieces of the message when working properly, while empty message when failing but I could see that intermediate digest is matching.
the round_q signal from prim_sha2, is always counting up to 63, but when not working it counts only up to 26 and goes back to 0 because sha_en_i goes to 0.
I don't have any idea if this might be an explanation so far. I am sharing it in case you are working on it in parallel.

the round_q signal from prim_sha2, is always counting up to 63, but when not working it counts only up to 26 and goes back to 0 because sha_en_i goes to 0.

Ah, interesting! Yes, bringing sha_en_i to zero indeed will clear the round counter. This sha_en signal comes from the CSR, right?

The vseq is waiting for the intr_hmac_done_o to be high, but I feel that the intr_hmac_done_o is happening too early. I guess this 2nd round should happen.

With this new fact, I am now almost convinced that we have another RTL bug.
I haven't got a solution yet, but we need to find a way to trigger the intr_hmac_done_o only once SHA core has processed all the current message after the stop. The round_q shouldn't be interrupted. Maybe wait until it moves to Idle or something else.
If you have time to have a look @andreaskurth, this might be part of your PR as it is linked somehow.

Ah great, thanks for the pointer @martin-velay! I'll take a look

I found and fixed multiple problems in prim_sha2_pad, and I added them to PR #23224. With those fixes, the case you mentioned above (util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed<PHONE_NUMBER>73648776435301108104832965337850972304806816025000095479785483310546) passes! I pushed the commits onto this branch as well for your convenience.
I even got 100% pass rate when I ran util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium! So things look much better for the interaction we currently cover, but I'm sure you have a few tricks up your sleeve to stress HMAC's save & restore feature even more :wink:

Excellent! Thanks a lot for your support @andreaskurth. I'll now start to prepare for merging this part with the master. And then I'll show my sleeves tricks.

Last commit is making message bursts working better while using S&R. I will start a regression now and continue to fix all the fails before unleashing more the TB (as very constrained at the moment).

@andreaskurth
I think there is an issue with the HMAC Idle.
Could you run this simu and have a look? It will fail on the 4th message. Take the latest database from this branch and run this command:
util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed 1
This is what you'll see:

@andreaskurth I think there is an issue with the HMAC Idle.
Could you run this simu and have a look? It will fail on the 4th message. Take this database from this branch and run this command: util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed 1
This is what you'll see:

Just looking at the waves you posted, I don't think idle_o behaves incorrectly: hmac is told to stop, then waits until the intermediate digest is computed, after which it raises the hmac_done interrupt as well as the idle_o status output. idle_o is correct not to raise immediately after hmac is told to stop, because it's used for clock gating so it must only rise when hmac doesn't have ongoing operations before it can be clock-gated.

> > @andreaskurth I think there is an issue with the HMAC Idle.

Could you run this simu and have a look? It will fail on the 4th message. Take this database from this branch and run this command: util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed 1
This is what you'll see:

Just looking at the waves you posted, I don't think idle_o behaves incorrectly: hmac is told to stop, then waits until the intermediate digest is computed, after which it raises the hmac_done interrupt as well as the idle_o status output. idle_o is correct not to raise immediately after hmac is told to stop, because it's used for clock gating so it must only rise when hmac doesn't have ongoing operations before it can be clock-gated.

The problem is exactly that: the hmac_done interrupt is raised but not the idle_o. This is visible on the screenshot I've shared, idle_o remains on _MuBi4False_ state.

I have done RTL changes, it looks better now but I'll run a regression to be sure of my changes.
See this #23336

Thanks @martin-velay, I've looked into the waveforms at this commit, and indeed there is a bug with the computation of txcnt_eq_blksz that was masked up until the SAR feature because it is actually irrelevant in signalling the finalization of the computation and asserting idle, but it becomes relevant here.

I have pushed my DV modifs to be able switch between different contexts. It's not complete yet.
But now we should be able to debug this issue #23352.
This command may reveal it with this database:
util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed 1
@gdessouky, I let you have a look if you have bandwidth today. Please update me if you find something.
@ballifatih FYI

I have pushed my DV modifs to be able switch between different contexts. It's not complete yet.
But now we should be able to debug this issue #23352.
This command may reveal it with Xcelium and with this database: util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --gui --fixed-seed 1
@gdessouky, I let you have a look if you have bandwidth today. Please update me if you find something.
@ballifatih FYI

Thanks @martin-velay for the DV setup to reproduce the issue!  I've pushed an RTL fix https://github.com/lowRISC/opentitan/pull/23432 that passes this DV smoke test, but I wasn't sure if you wanted me to push it to this branch here, so I leave that up to you.

Thanks a lot @gdessouky for your fix #23432 ! I'll continue to test this feature and keep you informed.

util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --fixed-seed<PHONE_NUMBER>11150958355807046043715683092785711447270148054926510481266628632264

thanks @martin-velay for raising, looking into it now.

I am currently releasing some constraints after having in place the S&R with different contexts (not complete yet, still remain to add some additional checks). This is leading me into a potential issue where the HMAC Done is never triggered. I am currently trying to understand if it's truly an RTL bug or not.
To reproduce it with Xcelium:
git checkout b242d6c90327aed83a1f67fbf1518bf4734741d8
util/dvsim/dvsim.py hw/ip/hmac/dv/hmac_sim_cfg.hjson -i hmac_smoke -t xcelium --fixed-seed<PHONE_NUMBER>11150958355807046043715683092785711447270148054926510481266628632264

With VCS, use seed:<PHONE_NUMBER>3382603449251114596099188419278643638756659410240524018062663081103
@gdessouky please could you have a look?

thanks @martin-velay looking into it now.

As a separate note, I'd also suggest splitting up the PR if possible. The 22 commits that are currently in the PR won't be "atomic" after merge (we don't distinguish in the git history between "internal" and "head of PR" commits), so it probably makes sense to split things out if possible.
That will allow the review to go much more in parallel.

@antmarzam thanks for you feedback. I have done most of the suggested changes

Thanks for the response. If you really believe that this can only be reviewed as a single block (+789/-306) then you should probably squash all the commits together.
I'd be quite surprised if that was true. Maybe it's worth trying to pull a few commits out to the front of the PR and rebase the rest on top of them. It will probably make things a bit easier to reason about for you, as well as a potential reviewer.

Thanks a lot for your help to clean this up @hcallahan-lowrisc

Yesterday I have pushed after having taken into account all the comments above. I ran a regression over the night, all is good. And all checks have passed. I think this PR is ready to be merged. It requires approvals now.
Any other comments?
@gdessouky @rswarbrick @ballifatih @antmarzam @hcallahan-lowrisc


fix(qwik-city): Scroll Position doesn't reset to 0 when it was triggered by an Action.

Overview

What is it?

[ ] Feature / enhancement
[x] Bug
[ ] Docs / tests / types / typos

Description
Fixes: https://github.com/BuilderIO/qwik/issues/5537
Use cases and why

Restore the scroll position to 0 if the navigation caused by an action (navType=from) and the URL has changed, that means action triggered a redirect.

Checklist:

[x] My code follows the developer guidelines of this project
[x] I have performed a self-review of my own code
[ ] I have made corresponding changes to the documentation
[ ] Added new tests to cover the fix / functionality

Can you run "pnpm fmt" to lint the codebase pls?

pnpm fmt

Done

Thanks @iamriajul for your help 👍


Git tag project version and build number 1.0.2

New Pull Request Checklist
Please mark the points which you did / accept.

[x] I will not move an already shared step version's tag to another commit
[x] I read the Step Development Guideline
[x] I have a test for my Step, which can be run with bitrise run test (in the step's repository)
[x] I did run bitrise run audit-this-step (in the step's repository - note, if you don't have this workflow in your bitrise.yml, you can copy it from the step template.)
[x] I read and accept the Abandoned Step policy

One PR should contain only one change: https://github.com/bitrise-io/bitrise-steplib#important
You can squash all the commits into one.

@koral-- done 👍

@koral-- should I fix something else? 🙂


botocore.utils:parse_timestamp negative timestamp causes UnhandledException

In botocore.utils:parse_timestamp (~Line 544), if a negative value is passed, a OSError is thrown up the stack. When using general boto functions (example: get_command_invocation), this causes parsing of the entire response to fail.
Potential workarounds: Returning a timestamp at the epoch in case of OSError, or returning None and updating upstream commands to not throw on None.
Unfortunately, it is difficult for me to get a live example of the failure, but I may be able to extract a raw JSON response that when formatted via botocore causes the failure in a few days.

I've done more research into the matter: an SSM api call is returning a value of -6.21355968E10 for a date, which should map to Jan 1, 0000 12 AM UTC.
In Linux, when parsed with EDT timezone, an OverflowError is generated - date value is out of range. However, if UTC is forced, then the 'correct' date is returned.
In Windows, the MSVC libraries indicate the standard time data types and localtime function don't work with times before Jan 1 1970 UTC. Python returns an OSError when a negative value is passed.
The fromtimestamp function is dependent on the OS time functions, which explains the OSError.
The reason I report this is because of the fail-fast behavior, where it seems the lowest possible date would be a more reasonable return, instead of throwing an uncaught exception.

@faxx1080 - Thank you for your post. This issue occurs when the ssm describe_instance_patches returns negative timestamp. Service should not give negative timestamp in the response. I have already contacted the service team about the issue and According to them the negative timestamp is arising because some packages don't have installed time, then we use DateTimeOffset.Minvalue to initialize the installed time. But DateTimeOffset.Minvalue corresponds to 1/1/0001 12:00:00 AM +00:00 not Unix epoch time : 01/01/1970 00:00:00 hence the service treats this as negative timestamp.
We are tracking this issue under the GitHub issue https://github.com/boto/boto3/issues/2069. I am closing this issue and let's track the progress of the issue under the linked GitHub issue.


Move app wide settings out of preferences

Things like setting a custom marketmaker daemon url or netid/seednode should be done before login.
We should move these and any other app wide settings to the login view. Preferably hidden behind a cog button or something so we don't clutter the login.
We should probably then move all settings in the preferences section into the portfolio file so they are portfolio specific.
Related: https://github.com/lukechilds/hyperdex/issues/216

We should move these and any other app wide settings to the login view. Preferably hidden behind a cog button or something so we don't clutter the login.

Or just use the Preferences… menu item:

Or just use the Preferences… menu item:

Yeah, good point.


Key Account manager of a project should be able to open the project details

Issue Raised by
@mohitgusain
Problem Statement
A key account manager of a client is a designated person that is responsible to deal with client regarding any issue that happens in any of the clients project. You can set the key account manager by editing client details.
Currently, If a key account manager of a project is not added as a team member of that project, then he is not able to open the project details page from project listing page. Due to this he is not able to edit the project details.
Expected Behavior
A Key account manager of a project should be able to open the project details page. i.e the project details page link should be available to him

Point of Contact for guidance
@GauravGusain98

Action Items
Basics Concept - 1 pointer (Skip if already done)

[ ] Read about Models in Laravel. Share your understanding of why we use them in the task comment in your own language
[ ] Read about Views in Laravel. Share your understanding of why we use them in the task comment in your own language
[ ] Read about Routes in Laravel. Share your understanding of why we use them in the task comment in your own language
[ ] Read about Controller in Laravel. Share your understanding of why we use them in the task comment in your own language
[ ] Read about Services files in Laravel. Share your understanding of why we use them in the task comment in your own language
[ ] Read how we can print a value in Laravel using dd()
[ ] Try printing hello world using the dd function

Testing Steps

[ ] Go to users table in database
[ ] copy the encrypted password from the user data with email<EMAIL_ADDRESS>[ ] Paste the password in any other user that is created in portal.
[ ] Login using the password in incognito mode.
[ ] Now go to roles table and see the id of the role employee
[ ] Now go to modal_has_roles table
[ ] Search data where model_id column is equal to the id of the new user that you can find from users table
[ ] if you get any result then assign role_id column to employee role id
[ ] In case no result is found, create a new entry and set model_type as Modules\User\Entities\User. Now the new user will have only employee role and will not have access to many resources in portal
[ ] Now from<EMAIL_ADDRESS>id, make the new user a key account manager of any client.
[ ] Go to projects and find project related to that client and see if the new user is able to open the project details page and edit the project


fix: Update datasource deletion message for clarity

Fixes #34604
Hi @nidhi-nair ,
Screenshots :
Earlier :

After update the error message :

Summary by CodeRabbit

Bug Fixes

Improved error messaging for datasource deletion to specify "query" instead of "action" for better clarity.

/build-deploy-preview skip-tests=true

@AnnaHariprasad5123 thanks for your contribution!
There is one server unit test (deleteDatasourceWithActions) failing in this PR, can you please check.
We might need to add the second parameter "query" also in the error message here

Other than this failing test, rest changes LGTM.

Hi @NilanshBansal , Could you check once.

@AnnaHariprasad5123 there are a large number of cypress test case failures due to this assertion.
https://github.com/appsmithorg/appsmith/blob/c48aaaccd45d8cb4822325d1473e98cb8133a9e4/app/client/cypress/support/Pages/DataSources.ts#L887
Can you change this assertion to "Cannot delete datasource"

@AnnaHariprasad5123 there are a large number of cypress test case failures due to this assertion.
https://github.com/appsmithorg/appsmith/blob/c48aaaccd45d8cb4822325d1473e98cb8133a9e4/app/client/cypress/support/Pages/DataSources.ts#L887
Can you change this assertion to "Cannot delete datasource" cc: @sneha122 @AmanAgarwal041

Done

The testing on the following has been done. The PR is ready to be merged!

[x] Code Review
[x] DP Testing
[x] Test Suite

Thanks @AnnaHariprasad5123 for your contribution! Looking forward to more such PRs from you!


feat: Support using Sinco in docker

Fixes #46
Summary

Addresses changes needed to support docker
Adds tests to ensure we can run sinco inside a docker container

Ready for review now


ESLint errors break WebPack builds

A bit irritating when I run my app, and it comes up with the electron file browser instead of my app just because ESLint was complaining about unused variables.

@Luminess
If you don't like the way ESLint is setup, then you can always customize it. Within .eslintrc.js you can adjust how no-unused-vars is handled. This issue has nothing to do with electron-vue.


make warp_to_template faster by concatenating in 4d then apply transfo

duplicate of https://github.com/neuropoly/spinalcordtoolbox/issues/602


Remove cache v23 support

It seems we have been supporting cache v23 for a really long time since ATS2.0. And I don't believe that there is someone still use such old version.  So do we still need to support this version ?

Please make a PR. Also, can we get rid of proxy.config.cache.http.compatibility.4-2-0-fixup at the same time ?

https://github.com/apache/trafficserver/pull/5386


Additional tests for set_fake_emails management command

Thanks !

Coverage increased (+0.04%) to 66.245% when pulling 9e0f21686cc7e4608738a6912121d501a20640a0 on kuter:additional_tests_for_set_fake_emails into cf9ef1725d2eae232388cd57e649917efe19f68b on django-extensions:master.


Advanced Layout : Display a field value in a html section set inside the FormlyFieldConfig Array

I'm submitting a ...  (check one with "x")
[ ] bug report => search github for a similar issue or PR before submitting
[ ] feature request
[x ] support request

How to display the value of a field in a html template provided inside the FormlyFieldConfig Array?
For example , In the advanced Layout template , I have added the below section in the array to display the value of otherInput field, but it doesn't work. Can you please help me to make it work?
{
        template: '
test {{model.otherInput}}
'
 }

Plunker
https://plnkr.co/edit/ZFgRjuSfyDjNPo6vguBF?p=preview

template support only plain string values (angular doesn't allow that), to handle you use case just use a custom wrapper
Ex: https://github.com/formly-js/ng-formly/blob/master/src/ui-bootstrap/wrappers/description.ts

Here's a plunker demonstrating how I approach reproducing this capability that angular-formly had:
https://plnkr.co/edit/AISe9Np6QA2CnqdOrMqq?p=preview

Would this solution work with aot?

It should.  My expectation would be that some components may need to be exposed as entryComponents.
A colleague of mine is setting up the build process which includes aot and I believe he's well past that point.  I have no visibility to that work to verify and know the details, but will at some point.

I figured I'd pass these along as they're related.  Hopefully we'll work through this, but I've not had the opportunity to do so personally.
Angular 2:
http://stackoverflow.com/a/41460129/4236606
https://github.com/angular/angular/issues/11780
http://blog.assaf.co/angular-2-harmony-aot-compilation-with-lazy-jit-2/
https://github.com/shlomiassaf/lazy-jit
Angular 4:
https://github.com/angular/angular/issues/15510

Following up again.  I can confirm that this will work just fine in an AOT application.  The important thing to realize is these dynamic templates do require the JIT compiler, so for in AOT it must be provided (see the above links).  We ended up providing our own ResourceLoader as well, though that may have been more a result of using Rollup.


I can't save request with "%" character in password.

When I try to save the request with "%" character in password, it is not saved.

Can you be more specific with details and steps to reproduce?

Here are the steps:

Create request
Go to Auth
Choose "Basic Auth"
In the password field enter any string containing "%"
Click on Save (or Cmd+S)
Request is not saved

If I remove the "%" from the password, I'm able to save the request.

Looks like some issue related to .bru to json conversion...
Related https://github.com/usebruno/bruno/issues/1076

Closing this as it cannot be reproduced in the latest version of Bruno v1.20.1
https://github.com/usebruno/bruno/assets/84461672/6e4bda8b-0c26-4e4b-b7d3-6f5647295404


Feat/challenge path 3 with merkle root

Initial unhappy path implementation. Thorough testing still required and some modifications may occur. Opening the PR to keep some organizational structure per JB's request.

Closing this PR, replacing it with challenge-path-4 branch which includes new refactoring and test structure as master


Add memory metrics

What is changed and how it works?
Add more memory related metrics.
Related changes

PR to update pingcap/docs/pingcap/docs-cn:
PR to update pingcap/tidb-ansible:
Need to cherry-pick to the release branch

Check List
Tests

Unit test
Integration test

Release note

No release note

/release

/release

/release

/release

/run-unit-tests

/release

/release


Support for css prop for styled-components

It's possible currently to style mui-components using styled-components.
However css prop still doesn't work with mui-components.
Please consider to add support for that
e.g.
const MyButton = styled(Button)`
  && {
    color: red;
    background-color: papayawhip;
    border: 5px solid hotpink;
  }
`;

The above code works and styles get applied properly.
However, <Button css={color: red;} />  doesn't work.
Please add support for css prop of styled-components (got introduced inv4).

tip: check the docs for style interoperability, e.g. the injectFirst option.

Hi @oliviertassinari ,
Thanks for the reply. I went through the docs and created a codesandbox to produce the issue.
Please find the CodeSandBox link below.
Link: https://codesandbox.io/s/styled-components-v9drw

@collegeimprovements This is a support request, your codesandbox is not valid.


fix: Tooltip for open result icon not placed properly

Fixes Issue
**My PR closes #314 **
👨💻 Changes proposed(What did you do ?)
There was CSS issue, I have fixed it
✔ Check List (Check all the applicable boxes)

[x] My code follows the code style of this project.
[x] This PR does not contain plagiarized content.
[x] The title and description of the PR is clear and explains the approach.

Note to reviewers
I have fixed the issue, attaching a screenshot for reference
📷 Screenshots

Looks Good 👌🏾 Thank you for contributing your PR is accepted, I hope you continue to contribute to this project
Check out the community discord server 👉🏽here👈🏽

:tada: This PR is included in version 2.22.1 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


YARA signatures not reporting

Current Cuckoo git release;
Yara 3.2.0;
If Cuckoo reports a warning about a Yara rule eg:
2015-03-16 10:53:35,094 [lib.cuckoo.common.objects] WARNING: Unable to match Yara signatures: /opt/cuckoo/data/yara/binaries/test.yara(74): $opcodes04 is slowing down scanning
No results are displayed in the Yara section on the analysis results.
I have tested this rule manually using Yara and it works fine.

Perhaps the rule on yara-python is causing issues. Can you share the rule?

Yep heres an example rule:
///////////////////////////////////////////////////////////////////////
rule test_rule_1 {
meta:
author = "John"
description = "Test Rule 1"
condition:
uint16(0) == 0x5A4D and uint32(uint32(0x3C)) == 0x00004550
}
rule test_rule_2 {
meta:
author = "John"
description = "Test Rule 2"
strings:
$opcodes01 = { AA BB CC DD AA BB CC DD AA BB CC DD AA BB }
$opcodes02 = { DD CC BB AA DD CC BB AA DD BB CC AA DD CC }
$opcodes03 = { E8 ?? ?? 00 00 C7 44 ?? ?? ?? ?? 00 00 C7 44 ?? ?? ?? ?? ?? 00 89 ?? ?? E8 ?? ?? ?? 00 }
condition:
2 of them
}
///////////////////////////////////////////////////////////////////////
test_rule_1 is a executable check.
test_rule_2 is a modified version of one of my rules which cause the problem.
Using normal YARA against a executable, alerts on rule 1, and warns that rule 2 is slowing down scanning.
Using Cuckoo, no rules are alerted on.

I removed Yara's error on warning. This should allow the results for the other rules to be displayed.
You should however investigate on what is causing the performance slow-down.


Incorrect test are not failing for NUMERIC in Postgresql

Describe the bug
There seems to be an issue with the NUMERIC/DECIMAL data types in Postgres when running tests. It works with INT:s.
In the docs (https://docs.soda.io/soda-sql/documentation/supported-data-types.html) its indicated that NUMERIC and DECIMAL should be supported.
There is also an issue with these metrics not being sent to Soda Cloud.
To Reproduce
Steps to reproduce the behavior:

Create a new test in scan.yml

CREATE TABLE PRODUCT ( ProductID VARCHAR(255), ProductName VARCHAR(255), ProductCategory VARCHAR(255), Size INT, Weight NUMERIC, PurchasePrice NUMERIC, SellingPrice NUMERIC, AmountInStock INT, Manufacturer VARCHAR(255));
INSERT INTO PRODUCT VALUES('5bc7110c-9c86-11eb-93ca-1e00da0c4374','Wooden Tuna','Home',57,6.19,382.7,459.24,13,'White and Sons')
INSERT INTO PRODUCT VALUES('5bc7176a-9c86-11eb-93ca-1e00da0c4374','Rubber Bike','Music',77,43.85,425.99,511.19,3,'Jones, Turner and Martin')
INSERT INTO PRODUCT VALUES('5bc71d5a-9c86-11eb-93ca-1e00da0c4374','Sausages','Computers',81,18.48,534.2,641.04,3,'Norton, Patton and Davis')
INSERT INTO PRODUCT VALUES('5bc722fa-9c86-11eb-93ca-1e00da0c4374','Frozen Soap','Tools',51,29.28,117.37,140.84,13,'Martin and Sons')
INSERT INTO PRODUCT VALUES('5bc72598-9c86-11eb-93ca-1e00da0c4374','Keyboard','Toys',32,39.78,148.3,177.96,0,'Hart-Sanders');

Soda table config:

table_name: product
metrics:
  - max
columns:
  size:
    tests:
      - max < 10
  sellingprice:
    tests:
      - max < 0

When running a scan the test for Size(INT) will fail as it should but not sellingprice.
Console output:

soda scan warehouse.yml tables/product.yml
  |
  | Scanning tables/product.yml ...
  | Soda cloud: cloud.soda.io
  | Soda Cloud scan start
  | > /api/command (login with API key credentials)
  | < 200 (login ok, token received)
  | Executing SQL query:
SELECT column_name, data_type, is_nullable
FROM information_schema.columns
WHERE lower(table_name) = 'product'
  AND table_catalog = 'sodademo1'
  AND table_schema = 'public'
  | SQL took 0:00:00.013647
  | 9 columns:
  |   productid (character varying)
  |   productname (character varying)
  |   productcategory (character varying)
  |   size (integer)
  |   weight (numeric) -> unsupported, skipped!
  |   purchaseprice (numeric) -> unsupported, skipped!
  |   sellingprice (numeric) -> unsupported, skipped!
  |   amountinstock (integer)
  |   manufacturer (character varying)
  | Query measurement: schema = [{'name': 'productid', 'type': 'character varying'}, {'name': 'productname', 'type': 'character varying'}, {'name': 'productcategory', 'type': 'character varying'}, {'name': 'size', 'type': 'integer'}, {'name': 'weight', 'type': 'numeric'}, {'name': 'purchaseprice', 'type': 'numeric'}, {'name': 'sellingprice', 'type': 'numeric'}, {'name': 'amountinstock', 'type': 'integer'}, {'name': 'manufacturer', 'type': 'character varying'}]
  | Soda Cloud scan send measurements
  | Executing SQL query:
SELECT
  MIN("size"),
  MAX("size"),
  AVG("size"),
  SUM("size"),
  VARIANCE("size"),
  STDDEV("size"),
  MIN("amountinstock"),
  MAX("amountinstock"),
  AVG("amountinstock"),
  SUM("amountinstock"),
  VARIANCE("amountinstock"),
  STDDEV("amountinstock")
FROM "public"."product"
  | SQL took 0:00:00.001744
  | Query measurement: min(size) = 32
  | Query measurement: max(size) = 81
  | Query measurement: avg(size) = 59.6000000000000000
  | Query measurement: sum(size) = 298
  | Query measurement: variance(size) =<PHONE_NUMBER>000000000
  | Query measurement: stddev(size) = 20.0199900099875175
  | Query measurement: min(amountinstock) = 0
  | Query measurement: max(amountinstock) = 13
  | Query measurement: avg(amountinstock) = 6.4000000000000000
  | Query measurement: sum(amountinstock) = 32
  | Query measurement: variance(amountinstock) = 37.8000000000000000
  | Query measurement: stddev(amountinstock) = 6.1481704595757590
  | Soda Cloud scan send measurements
  | Test column(size) test(max < 10) failed with metric values {"max": 81}
  | Soda Cloud scan send test results
  | Executed 2 queries in 0:00:01.452087
  | Soda Cloud scan end ok
  | Scan summary ------
  | 13 measurements computed
  | 1 tests executed
  | 1 of 1 tests failed:
  |   Test column(size) test(max < 10) failed with metric values {"max": 81}
  | Exiting with code 1

Context
Include your scan.yml or warehouse.yml when relevant
OS: Mac OS 11.2.3
Python Version: 3.9.2
Soda SQL Version: 2.1.0b1
Warehouse Type: postgres

Looks like there is a bug in column name for numeric- Fixed it with #266
This is how the result looks now, I didn't test the metrics not being sent, that probably requires another issue.
 | Scan summary ------
  | 31 measurements computed
  | 2 tests executed
  | 2 of 2 tests failed:
  |   Test column(size) test(max < 10) failed with metric values {"max": 81}
  |   Test column(sellingprice) test(max < 0) failed with metric values {"max": 641.04}
  | Exiting with code 1


GK Saves for live fixture info

Nice work! I've been using this quite a bit to keep track of how games are going without having to pull up a bunch of websites. One thing I noticed was missing from the fixtures option (myfpl -f) was the number of saves for each GK. It would be nice to see when a GK is going to or about to earn save points. (Right now, you would have to infer this from the preliminary bonus or just check it afterwards.)

Hi @jcleung11  sorry for taking so long to reply. I did not see this until now.
Yes I think that is a good idea.
When I get some time I will add it.
Btw I have been working on a browser extension for myfpl, which also allows you to check fixture scores easily.
If you want to grab a free account here is a link .
https://myfpl.net/free


In pixi shell, add an option to turn off the prompt

Problem description
I use starship as the prompt provider for my zsh. Currently, in pixi shell, the prompt by Pixi is concatenated with the prompt generated by starship, and the result does not look good. Is it possible to add an option to turn off the prompt modifier provided by Pixi?

Yes, there is an option in the config file: https://pixi.sh/latest/reference/pixi_configuration/#change-ps1

As a +1 here, I would suggest maybe making the prompt opt in rather than opt out.
It's quite intrusive right now (at least to a starship user, which I am)
This came up before here: https://github.com/prefix-dev/pixi/issues/1275


.NET 4.0

Hi,
What was the last version of Rx.NET that targeted .NET 4.0? And where can I get it from?
Thanks,
Kerry

I think 2.2.5 is the latest version, and you'll have to install it manually through NuGet:
Install-Package Rx-Main -Version 2.2.5

@shiftkey Thanks!


WIP: fix tests

[ ] fix tests;
[x] update some dev dependencies;

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@5165806). Click here to learn what that means.
The diff coverage is 78.94%.

@@            Coverage Diff            @@
##             master     #117   +/-   ##
=========================================
  Coverage          ?   91.67%
=========================================
  Files             ?       10
  Lines             ?     1237
  Branches          ?       14
=========================================
  Hits              ?     1134
  Misses            ?       97
  Partials          ?        6

Impacted Files
Coverage Δ

tests/test_snapshot.py
72.22% <ø> (ø)

tests/test_transport.py
100% <ø> (ø)

tests/conftest.py
82.53% <75.86%> (ø)

tests/test_cat.py
98.79% <88.88%> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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composer require t1st3/php-json-minify

Why composer installs so many dependencies just for using a 129-lines script?

Hi there,
sorry for the delay with this. Sure, there are too many useless dependencies in composer.json. I think these deps were actually dev-dependencies (and you can see most of theme are duplicated in dependencies AND in dev-dependencies).
I'll correct this problem hopefully by the end of the week.
Thanks for submitting this issue.

Fixed in 0.4.0 .
Thanks


Support nested Keras models

In Keras Sequential inherits from Model inherits from Container inherits from Layer, so you can do something like:
pretrained_encoder_model = Sequential(...)
classifier = Sequential(...)
classifier.fit(encoded_data, labels)
full_model = Sequential()
full_model.add(pretrained_encoder_model)
full_model.add(classifier)

Now when converting nnvm.frontend.from_keras(full_model) it fails because Sequential is not in _convert_map. Instead these should be resolved in some recursive way.
I would like to offer help, but I don't yet understand well enough yet how the conversion works. If you can give me a hint or some pseudo code I will try my best.

You can refer to coremltools' keras converter: https://github.com/apple/coremltools/blob/master/coremltools/converters/keras/_keras2_converter.py#L95
Now nnvm's keras converter is pretty simplified without considering nested keras models(I don't know much about this). You can try add this support.

any updates on this issue?

Sorry, in the meanwhile I'm using the tfcompile for my purposes, so i didn't find the time to look into that since then.
Even though i'm personally interested I probably won't find time for it in the near future either.


includeIPRanges not working in istio 0.8

i try to use includeIPRanges in istio 0.8 when started service using manual kube-inject and then the out say
Flag --includeIPRanges has been deprecated, Use --injectConfigMapName or --injectConfigFile instead

it's like not supported again ? and how to make baypass all, because currently i try setting eggress also not work ?

found the issue , about istioctl , i use istioctl version 0.7.1 but istio 0.8 it's work for me
it's like bug in istioctl
but and how about setting egress not work in istio 0.8 i still figure out ..
/bug

Duplicate with https://github.com/istio/istio.github.io/issues/1433
Please check the PR here https://github.com/istio/istio.github.io/pull/1450 for how to do this.


⚠ File access has degraded performance

In f312daf, File access (https://fyle.uk/file/fish) experienced degraded performance:

HTTP code: 200
Response time: 3368 ms

Resolved: File access performance has improved in 3a6574b after 9 minutes.


MPD now uses the filename if song doesn't have metadata

Description:
Very small change, but it irritated me that MPD would write "None" when playing songs without meta-data.
Changes:

MPD now shows file_name instead of "None" as the "media_title"

I only changed five lines in the MPD component, and, as far as i could see, no test-cases exist in regards to the MPD component, so i didn't actually run any test cases to make sure it works, but you are very welcome to test it locally in case i made some massive mistake, however it should work.

Could someone give this a quick look? It's a small change but i'd love to see if it is within the goals of the program @balloob

We won't look at things without the CLA signed.

Sorry @balloob - i am totally new to this project, (downloaded HA for the first time this monday), so could you link to some explaination in regards to how i satisfy the CLA bot? Hope to help out a lot more in the future - I've been looking for a project just like this for my current setup at home.

[clabot:check]

Hello @C0DK,
When attempting to inspect the commits of your pull request for CLA signature status among all authors we encountered commit(s) which were not linked to a GitHub account, thus not allowing us to determine their status(es).
The commits that are missing a linked GitHub account are the following:

b96b6abc4a467c5b6457cdf7a82c7793e5a24d20 - This commit has something that looks like an email address (a@thecdk.net). Maybe try linking that to GitHub?.
e56953517915e6fa3bc450db468f53068f026eab - This commit has something that looks like an email address (a@thecdk.net). Maybe try linking that to GitHub?.

Unfortunately, we are unable to accept this pull request until this situation is corrected.
Here are your options:

If you had an email address set for the commit that simply wasn't linked to your GitHub account you can link that email now and it will retroactively apply to your commits. The simplest way to do this is to click the link to one of the above commits and look for a blue question mark in a blue circle in the top left. Hovering over that bubble will show you what email address you used. Clicking on that button will take you to your email address settings on GitHub. Just add the email address on that page and you're all set. GitHub has more information about this option in their help center.

If you didn't use an email address at all, it was an invalid email, or it's one you can't link to your GitHub, you will need to change the authorship information of the commit and your global Git settings so this doesn't happen again going forward. GitHub provides some great instructions on how to change your authorship information in their help center.

If you only made a single commit you should be able to rungit commit --amend --author="Author Name<EMAIL_ADDRESS>
(substituting Author Name and<EMAIL_ADDRESS>for your actual information) to set the authorship information.
If you made more than one commit and the commit with the missing authorship information is not the most recent one you have two options:

You can re-create all commits missing authorship information. This is going to be the easiest solution for developers that aren't extremely confident in their Git and command line skills.
You can use this script that GitHub provides to rewrite history. Please note: this should be used only if you are very confident in your abilities and understand its impacts.

Whichever method you choose, I will come by to re-check the pull request once you push the fixes to this branch.

We apologize for this inconvenience, especially since it usually bites new contributors to Home Assistant. We hope you understand the need for us to protect ourselves and the great community we all have built legally. The best thing to come out of this is that you only need to fix this once and it benefits the entire Home Assistant and GitHub community.
Thanks, I look forward to checking this PR again soon! :heart:

If anyone can help me find the famous cla-link then i'm all ears :) Sorry for the inconvenience.

@C0DK https://home-assistant.io/developers/cla_sign_start/?pr=home-assistant/home-assistant#10085

[clabot:check]

Hello @C0DK,
When attempting to inspect the commits of your pull request for CLA signature status among all authors we encountered commit(s) which were not linked to a GitHub account, thus not allowing us to determine their status(es).
The commits that are missing a linked GitHub account are the following:

70e9c5eca8c5749d28936d7acfac5b90d41c1b28 - This commit has something that looks like an email address (a@thecdk.net). Maybe try linking that to GitHub?.
b96b6abc4a467c5b6457cdf7a82c7793e5a24d20 - This commit has something that looks like an email address (a@thecdk.net). Maybe try linking that to GitHub?.
e56953517915e6fa3bc450db468f53068f026eab - This commit has something that looks like an email address (a@thecdk.net). Maybe try linking that to GitHub?.

Unfortunately, we are unable to accept this pull request until this situation is corrected.
Here are your options:

If you had an email address set for the commit that simply wasn't linked to your GitHub account you can link that email now and it will retroactively apply to your commits. The simplest way to do this is to click the link to one of the above commits and look for a blue question mark in a blue circle in the top left. Hovering over that bubble will show you what email address you used. Clicking on that button will take you to your email address settings on GitHub. Just add the email address on that page and you're all set. GitHub has more information about this option in their help center.

If you didn't use an email address at all, it was an invalid email, or it's one you can't link to your GitHub, you will need to change the authorship information of the commit and your global Git settings so this doesn't happen again going forward. GitHub provides some great instructions on how to change your authorship information in their help center.

If you only made a single commit you should be able to rungit commit --amend --author="Author Name<EMAIL_ADDRESS>
(substituting Author Name and<EMAIL_ADDRESS>for your actual information) to set the authorship information.
If you made more than one commit and the commit with the missing authorship information is not the most recent one you have two options:

You can re-create all commits missing authorship information. This is going to be the easiest solution for developers that aren't extremely confident in their Git and command line skills.
You can use this script that GitHub provides to rewrite history. Please note: this should be used only if you are very confident in your abilities and understand its impacts.

Whichever method you choose, I will come by to re-check the pull request once you push the fixes to this branch.

We apologize for this inconvenience, especially since it usually bites new contributors to Home Assistant. We hope you understand the need for us to protect ourselves and the great community we all have built legally. The best thing to come out of this is that you only need to fix this once and it benefits the entire Home Assistant and GitHub community.
Thanks, I look forward to checking this PR again soon! :heart:

[clabot:check]


Update bookings-faq.md

Made changes to the PowerShell cmdlet as it had  \ in three places in the syntax

@JohanFreelancer9 Please copy review

Issue#https://github.com/MicrosoftDocs/microsoft-365-docs/issues/4253


Understanding @Output and EventEmitter in Angular

Proposed title of article
Understanding @Output and EventEmitter in Angular
Introduction paragraph (2-3 paragraphs):
Angular is based on a one-directional data flow and does not have two-way data binding. So, how do you get a component to emit an event to another component?
In Angular, a component can emit an event using @Output and EventEmitter. Both are parts of the @angular/core.
Angular components are the fundamental building blocks of architecture. Once you’ve understood component architecture, you can build a picture in your head as to how to assemble your interface based on data communication.
In this post we’re going to dive into Angular components and how to use the EventEmitter and Outputs, so we can transfer or notify any parent component that something has changed, or we would like to change it. This is typically done via “events”, hence our “EventEmitter” and is designed around a uni-directional data flow system that adopts a much more reasonable approach to application development.
Key takeaways:
1.Understanding @Input decorator
2.Understanding @Output decorator
3. Angular Event Emitters

seems like a helpful topic - lets please be sure it add value beyond what is in the official docs and that it does not overlap with any existing EngEd articles or incoming topic suggestions (if you haven't already) to avoid any potential article closure. - approved @odiwuoramos
Mind you minor grammatical errors - to speed up publishing 🚀


colorscale / clim tracking

Currently the color scale and clims, if changed, become properties of a dataset, as opposed to global properties. This has some nice properties, like letting you select (and keep) different colors for different datasets, and dial in clim settings on different datasets that are preserved.
However, it makes it cumbersome to compare a set of datasets with a shifted color scale, because you have to first implement that adjusted colorscale for all the datasets you want to compare.
One option would be to switch to a global setting, i.e. a single color scale and clim for each variable, which affect all datasets equally. Another option would be to make this all a toggle, and in one mode it does the current behavior, and in another it does the global behavior described above.

Documenting realtime discussion: I think that the dataset-specific clims are really a relic of an older version of the UI with a display panel with entries for each selected dataset. In that version of the UI, it would've been easier to track and manage distinct clims. With the current UI, I think a global setting (per variable + timescale combination) would be much easier to use (and technically simpler!).