Add missing configuration/features to Smithy build plugin

The number and complexity of CLI arguments are getting out of hand. We already have an alternate interface into the code generation logic as a Smithy build plugin, which supports configuration via a smithy-build.json. It also supports standard Smithy features such as projections because it hooks into the full Smithy model building pipeline.
This task is to add the missing necessary configuration knobs to our smithy-build.json configuration handler so that we can migrate off the CLI.

Note the scope of this issue is only for CLI options that are relevant in --aws-sdk mode, since we only have the dafny-client-plugin plugin so far. Some options will only be needed for the dafny-library-plugin we have yet to create: https://github.com/smithy-lang/smithy-dafny/issues/153

Here is some more detail on the scope of this task vs. future ones.
One key difference between the CLI and the Smithy build plugin is how they use input and output. The CLI has options like --library-root pointing to the source code directory, and options like --output-java that allow it to write code anywhere on disk. The Smithy CLI/Gradle plugin only gives Smithy build plugins parsed/resolved/validated Smithy models as input, and expects output to only be written to a build directory like build/sources/dafny-client-plugin.
I believe the best way to bridge this gap is with an additional shared Gradle plugin that can be executed after invoking the smithy-gradle-plugin task to build a model. This plugin would provide the connection between the contents of a directory that the Smithy build plugin outputs like <project-root>/build/sources/dafny-client-plugin/runtimes/java/smithy-generated and where that code is checked in, i.e. <project-root>/runtimes/java/smithy-generated. The --patch-files-dir and --update-patch-files features of the CLI would also move to this plugin.
The plugin would have three different tasks (or at least modes of a single task):

assert-same - apply patch files, then assert that the two locations have the same content
update - apply patch files, then copy from the build directory on top of the checked-in directory
update-patch-files - don't apply patch file, update them to match the difference between the build directory and the checked-in copy

It looks like this is the only missing "feature" to make this work. For the record here is the analysis I did of the current set of CLI options:
CLI options that need new smithy-build.json equivalents

--patch-files-dir/--update-patch-files

Should be handled by post-processing

CLI options that already have smithy-build.json equivalents

--model

Maps to sources

--namespace

Maps roughly to service: the Smithy build plugin tells the code generation logic to generate for all shapes in the namespace of the identified service

--library-root

Always the plugin artifacts output directory (i.e. build/sources/dafny-client-codegen)

--dafny-version

Maps to plugins.dafny-client-codegen.dafnyVersion

--include-dafny

Maps to plugins.dafny-client-codegen.includeDafnyFile

--properties-file

Always set to <output directory>/project.properties

--output-dafny/java/dotnet/...

Target languages are selected via a plugins.dafny-client-codegen.targetLanguages list instead
Output locations are fixed for the Smithy build plugin, see above about post-processing

--aws-sdk

Implicitly always true for dafny-client-plugin

--java-aws-sdk-version

Intentionally not supported: defaults to V2, V1 not used

CLI options not yet relevant (because they will apply to dafny-library-codegen instead)

--dependent-model
--local-service-test


float window is not close when leave buffer

when you click buffers to switch them, the float window is not close.
https://user-images.githubusercontent.com/39482599/221352877-89b47e89-983c-49bc-913f-d3770ed96217.mov
Originally posted by @NavePnow in https://github.com/glepnir/lspsaga.nvim/issues/917#issuecomment-1445053312

use ++unfocus or use buffer  jump command bnext bprev . i don't use mouse.


drivers: wifi: uwp: Support del_sta and get_sta

New delete station command added for softap.
And new get_station command added for sta.
Signed-off-by: Bub Wei<EMAIL_ADDRESS>

Waiting for CP to debug del_sta command.


multiple galleries on one page - keyboard events allways for the first gallery

Hi,
i have for example 2 galleries on one page. The settings for fullscreen, overlay text and so on can i configure for every gallery and it works fine. But when i use the keyboard to show the image right or left, this event allways works for the first gallery. Have please someone an idea, how i can do this for all gallery on the same page?
thanks and kind regards,
andy

Hi, have you found any solution on this problem??

No progress as I see :\

Is there any solution?

Would be nice if there is any solution, even a temporary one. It should be based on the active gallery, not just the first one.

I am facing the same issue does any one knows a solution?


rename PriorityUpdate to PriorityUpdated

name all events in the same fashion

Thanks! :sparkles: :cake: :sparkles:


Unknown plugin "transform-runtime"

Module build failed: ReferenceError: Unknown plugin "transform-runtime" specified in "/node_modules/vue-simple-upload/.babelrc"
Does this need to be installed?

Issue resolved with version 0.1.6


Add ResultSelector

Is your feature request related to a problem? Please describe.
As described here, we already have the inputPath, ResultPath and OutputPath. We're missing the ResultSelector.
Describe the solution you'd like
A new function here that will process the parameters

@jefer590 can you assign me this issue?


unit(dm): add Kill func for unit

What problem does this PR solve?
Issue Number: close #3737
Root case of #3737

when dm-master node offline, dm-worker will lost the keepalive with master
dm-worker will use stopWorker to stop running tasks
if current running unit is syncer, syncer will try continue syncing until current trasaction end https://github.com/pingcap/tiflow/blob/abefe57c154efb28f91cf1a15702988e1a7249e7/dm/syncer/syncer.go#L1411
at the same time master online again or another master node beacme leader will try scheduler task to another running worker
so there are two workers syncning from same source ,and we may meet duplicate key error

What is changed and how it works?

kill running subtasks when worker lost the keep-alive with dm-master (both for master offline or worker offline )

add Kill interface func to unit

impleament kill in syncer unit

change worker.Close to worker.Stop(graceful bool),  when ungraceful stop, worker will call killAllSubTasks to force stop and this will cancel syncer.Run immediately

only when worker lost keepalive unit should call Kill

Check List
Tests

Unit test
Integration test

Code changes

Has exported function/method change
Has exported variable/fields change
Has interface methods change

Side effects

Possible performance regression
Increased code complexity

Related changes

Need to cherry-pick to the release branch
Need to update the documentation
Need to update key monitor metrics in both TiCDC document and official document

Release note
`fix a bug that multiple worker write for same upstream`.

Codecov Report

Merging #4035 (273cdbb) into master (3873d39) will decrease coverage by 1.9151%.
The diff coverage is 69.6271%.

Flag
Coverage Δ

cdc
58.6714% <69.6271%> (+0.4348%)
:arrow_up:

dm
52.1998% <ø> (-3.8348%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.
@@               Coverage Diff                @@
##             master      #4035        +/-   ##
================================================
- Coverage   57.0741%   55.1590%   -1.9152%
================================================
  Files           478        484         +6
  Lines         56551      59885      +3334
================================================
+ Hits          32276      33032       +756
- Misses        20978      23490      +2512
- Partials       3297       3363        +66

/run-dm-integration-tests

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/unhold

ok i will add new interface func to unit called HardStop

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

please paste the root cause of this bug, else it's hard to reason whether this PR fix it.

please paste the root cause of this bug, else it's hard to reason whether this PR fix it.

root cause is updated in PR description, and mean changes to reproduce this bug can found in this commit, ptal

we may still met write conflict even if connection between worker1 and downstream is slow enough, as DMLWorker will wait for 30 * time.Second before notice of kill
also please take a look at #3698

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

/hold wait more ctx refine
/run-dm-integration-tests
just trigger a it test

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

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/run-dm-integration-tests

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/run-dm-integration-tests

/run-dm-integration-tests

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/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

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/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

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/run-dm-integration-tests

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/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

/unhold

/unhold

Should we ungraceful exit the pipeline  in syncer? e.g.
https://github.com/pingcap/tiflow/blob/f710abba6417971370e0d0711d9cd8ca3fa784c4/dm/syncer/compactor.go#L73
https://github.com/pingcap/tiflow/blob/f710abba6417971370e0d0711d9cd8ca3fa784c4/dm/syncer/causality.go#L69
Can you add an ungraceful mock test base on current isolate test?

/run-dm-integration-tests

/run-dm-integration-tests

rest LGTM

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

/run-dm-integration-tests

/merge

FAIL: server_test.go:2144: testMaster.TestGRPCLongResponse
/run-leak-test
/run-verify


Support for WASM generated by GHC

GHC has recently introduced support for the WASM backend.
Unfortunately, w2c2 will throw the following error when trying to generate C code:
$./w2c2 hi.wasm hi.c
w2c2: failed to read module: invalid code section local declarations

I have absolutely no knowledge of wasm, but as far as I understand it's about supporting WASM or WASI standards?

It's pretty likely that this because the GHC WebAssembly backend uses several extensions to the WebAssembly 1.0 spec ("post-MVP features").
Some of those are supported by w2c2 already, see https://github.com/turbolent/w2c2#features.
Several are still missing:

128-bit packed SIMD
Import/Export mutable globals
Multi-value
Reference Types


render is undefined

code fragment below is copy from mustache , but I can't get argument render in Lambdas. The console told me argument render is undefined. Is there something that i misunderstand?
Template:
{{#wrapped}}
{{name}} is awesome.
{{/wrapped}}
Hash:
{
"name": "Willy",
"wrapped": function() {
return function(text, render) {  //actually param render cannot get a argument
return "" + render(text) + ""
}
}
}

@Rouberg Lambdas in Hogan.js is broken. Please try that.
{
  "wrapped": function() {
    return function(text) {
      Hogan.compile(text).render(this);
    }
  }
}

See #199

The 'render' argument isn't in the mustache spec.

@sayrer

Lambdas
When the value is a callable object, such as a function or lambda,
the object will be invoked and passed the block of text.
The text passed is the literal block, unrendered. {{tags}} will not
have been expanded - the lambda should do that on its own.
In this way you can implement filters or caching.
Template:
{{#wrapped}}
  {{name}} is awesome.
{{/wrapped}}

Hash:

{
"name": "Willy",
"wrapped": function() {
return function(text, render) {
return "" + render(text) + ""
}
}
}

**Output:**

```html
<b>Willy is awesome.</b>

You're right, the text only states that the lambda should receive the unrendered chunk of text.
But by looking at the examples, it seems pretty obvious that this is how one could expect hogan.js to behave.
And it would allow to have the same hogan options that Hogan.compile was invoked with instead of having to store them somewhere.

Six years later, still not sure what the right answer is here, but this should get resolved definitively.


Virtual Adapter not supported

The script calls get-netadapter with the switch -Physical which rules out virtual network adapters.
During HLK testing of a virtual network adapter (tap6-windows) this module is used in the test NICSTrictPropertyValidation and results in the test not passing as the virtual adapter is not recognized.

Hello @sdbcs - This test should not be required for virtual adapters. I would request an errata if this is required in your playlist.


Wrong country reported for visitor in analytics tab

Hi, first of all thanks for the fantastic work! So:
What I did
Create a project (and edit it for a while). (Here it is.)
What I expected
In the analytics tab, there's a single visitor (which is me), and I expect the country of this visitor to be properly reported, i.e. I expect the analytics to say this visitor is in Berlin, Germany (or at least Germany)
What actually happened
The analytics tab reports this visitor to be in the US (and I know it's me). The anonymized IP is <IP_ADDRESS>, which belongs to Deutsche Telekom and gets located in Hamburg (my real IP address in this case was <IP_ADDRESS>, which resolves to Berlin).
I saw no errors in the Javascript console.
Here's a screenshot of what I see:

Potential causes
This could be an issue with Piwik which you seem to be using as a backend for analytics, but I haven't encountered this on my own installations of Piwik.

@wehlutyk -- Appreciate you reporting this! We've been working to improve these user analytics and hope to release a new approach by end of this year. Meantime, we'll look into this issue in particular. Thanks!

Great, thanks for the quick reply :)

@wehlutyk Thanks for this bug report! As @lbanner mentioned, we're undertaking an overhaul to the user-facing analytics and anticipate deployment in the coming months. It seems this particular issue will require a fairly time-consuming fix. In the interest of getting the new analytics up and running as quickly as possible, we're going to defer on this issue. The new analytics approach will resolve this issue, but will take a few months to get running. I will make sure we give you a ping when the changes are made.
Thanks for your help!

:-) !


Fix reflecting basePath when no path in handler

Author should do the followings, if applicable

[x] Add tests
[x] Run tests
[x] yarn denoify to generate files for Deno

Hi @sizumita!
Thanks for your contribution.
Could you please address the error causing the CI to fail? And, I'd appreciate if you could add a test for the following pattern:
app.post('/books/:id').get((c) => {
  const foo = c.req.param('id');
  return c.text(foo);
});

Hello, @yusukebe!

Hi @sizumita!
Thanks for your contribution.
Could you please address the error causing the CI to fail? And, I'd appreciate if you could add a test for the following pattern:
app.post('/books/:id').get((c) => {
  const foo = c.req.param('id');
  return c.text(foo);
});

I'm sorry that I missed running test in local.
Since It's caused by missing type and invalid test syntax, I fixed it.
Thank you.

@sizumita
Thanks! One thing. Can you add the test code for this:
app.post('/books/:id').get((c) => {
  const foo = c.req.param('id');
  return c.text(foo);
});

@yusukebe
I'm sorry for missing your order:pray:
I added it and tested in local.

Thanks! Ship it.


UI: Show trace and span IDs

The UI currently only shows the trace ID as part of the URL, and does not show the spans' IDs at all. In order to find related log messages in, for example, Kibana (ELK stack), I'd like to copy-paste the span's ID. However, the UI does not provide this information in a user-friendly way.

Span detail view could show this I guess


Time Tracking plugin displays "patches" text twice for patches

As reported in discord, all patches in addition to saying that they are patches are now also saying that they are patches.

I think this is important to patch before next update.


Keras fails to initiate training with custom BERT layer.

System information

Have I manipulated custom code in attempt to build a Keras layer for BERT. Following this example: https://towardsdatascience.com/bert-in-keras-with-tensorflow-hub-76bcbc9417b
Windows 10:
TensorFlow installed from (source or binary):
TensorFlow version: 1.14
Python version: 3.7
CUDA/cuDNN version: CUDA 10
GPU model and memory:  NVIDIA GTX1080ti

Describe the current behavior
The training data is pre-processed and loaded into memory. The model is compiled and the correct model output is produced with model.summary(). See logs bellow...
On model.fit(), nothing happens... The GPU is at 3% utilization and one CPU core is at 100%.
Describe the expected behavior
I was expecting the keras training logging to be printed post model.fit(). It doesn't appear to be training at all.
Code to reproduce the issue
Custom Code:
import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder
import matplotlib.pyplot as plt
import numpy as np
from tensorflow.keras import backend as K
import sys

from BertLayer import BertLayer
from preprocessing import MyDocs

sess = tf.Session()

def build_model(bert_path, max_seq_length):
    in_id = tf.keras.layers.Input(shape=(max_seq_length,), name="input_ids")
    in_mask = tf.keras.layers.Input(shape=(max_seq_length,), name="input_masks")
    in_segment = tf.keras.layers.Input(shape=(max_seq_length,), name="segment_ids")
    bert_inputs = [in_id, in_mask, in_segment]

    bert_output = BertLayer(n_fine_tune_layers=3, bert_path=bert_path, pooling="first")(bert_inputs)
    dense = tf.keras.layers.Dense(256, activation="relu")(bert_output)
    pred = tf.keras.layers.Dense(5, activation="sigmoid")(dense)  # change this to build classifier

    model = tf.keras.models.Model(inputs=bert_inputs, outputs=pred)
    model.compile(loss="binary_crossentropy", optimizer="adam",  metrics=['binary_accuracy', 'categorical_accuracy'])
    model.summary()

    return model

def initialize_vars(sess):
    sess.run(tf.compat.v1.local_variables_initializer())
    sess.run(tf.compat.v1.global_variables_initializer())
    sess.run(tf.compat.v1.tables_initializer())
    K.set_session(sess)

def main():
    # Params for bert model and tokenization
    bert_path = "https://tfhub.dev/google/bert_uncased_L-12_H-768_A-12/1"
    max_seq_length = 256

    corpus = MyDocs("datasets/bbc/raw", bert_path, max_seq_length)

    ids = []
    masks = []
    segment_ids = []
    for id, mask, segment, label in corpus:
        ids.append(id)
        masks.append(masks)
        segment_ids.append(segment)
    X = [ids, masks, segment_ids]

    labels = corpus.labels
    label_encoder = OneHotEncoder()
    y = label_encoder.fit_transform(np.array(labels).reshape(-1, 1)).todense()
    print('Dimension of labels input is {}.'.format(y.shape))

    print('Building model...')
    model = build_model(bert_path, max_seq_length)

    print('Training model...')
    history = model.fit(X, y,
                        validation_split=0.2,
                        epochs=1,
                        batch_size=1,
                        verbose=2,
                        use_multiprocessing=True)

if __name__ == "__main__":
    main()

BertLayer
import tensorflow as tf
from tensorflow.keras import backend as K
import tensorflow_hub as hub

class BertLayer(tf.keras.layers.Layer):
    def __init__(
        self,
        n_fine_tune_layers=10,
        pooling="mean",
        bert_path="https://tfhub.dev/google/bert_uncased_L-12_H-768_A-12/1",
        **kwargs,
    ):
        self.n_fine_tune_layers = n_fine_tune_layers
        self.trainable = True
        self.output_size = 768
        self.pooling = pooling
        self.bert_path = bert_path

        if self.pooling not in ["first", "mean"]:
            raise NameError(
                f"Undefined pooling type (must be either first or mean, but is {self.pooling}"
                )

        super(BertLayer, self).__init__(**kwargs)

    def build(self, input_shape):
        self.bert = hub.Module(
            self.bert_path, trainable=self.trainable, name=f"{self.name}_module"
        )

        # Remove unused layers
        trainable_vars = self.bert.variables
        if self.pooling == "first":
            trainable_vars = [var for var in trainable_vars if not "/cls/" in var.name]
            trainable_layers = ["pooler/dense"]

        elif self.pooling == "mean":
            trainable_vars = [
                var
                for var in trainable_vars
                if not "/cls/" in var.name and not "/pooler/" in var.name
            ]
            trainable_layers = []
        else:
            raise NameError(
                f"Undefined pooling type (must be either first or mean, but is {self.pooling}"
            )

        # Select how many layers to fine tune
        for i in range(self.n_fine_tune_layers):
            trainable_layers.append(f"encoder/layer_{str(11 - i)}")

        # Update trainable vars to contain only the specified layers
        trainable_vars = [
            var
            for var in trainable_vars
            if any([l in var.name for l in trainable_layers])
        ]

        # Add to trainable weights
        for var in trainable_vars:
            self._trainable_weights.append(var)

        for var in self.bert.variables:
            if var not in self._trainable_weights:
                self._non_trainable_weights.append(var)

        super(BertLayer, self).build(input_shape)

    def call(self, inputs):
        inputs = [K.cast(x, dtype="int32") for x in inputs]
        input_ids, input_mask, segment_ids = inputs
        bert_inputs = dict(
            input_ids=input_ids, input_mask=input_mask, segment_ids=segment_ids
        )
        if self.pooling == "first":
            # pooled output of the entire sequence [batch, hidden_size]
            pooled = self.bert(inputs=bert_inputs, signature="tokens", as_dict=True)["pooled_output"]
        elif self.pooling == "mean":
            # representation of every token in the sequence [batch, max_seq_length, hidden_size]
            result = self.bert(inputs=bert_inputs, signature="tokens", as_dict=True)["sequence_output"]

            mul_mask = lambda x, m: x * tf.expand_dims(m, axis=-1)
            masked_reduce_mean = lambda x, m: tf.reduce_sum(mul_mask(x, m), axis=1) / (
                    tf.reduce_sum(m, axis=1, keepdims=True) + 1e-10)
            input_mask = tf.cast(input_mask, tf.float32)
            pooled = masked_reduce_mean(result, input_mask)
        else:
            raise NameError(f"Undefined pooling type (must be either first or mean, but is {self.pooling}")

        return pooled

    def compute_output_shape(self, input_shape):
        return (input_shape[0], self.output_size)

Other info / logs
model.summary()
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to
==================================================================================================
input_ids (InputLayer)          [(None, 256)]        0
__________________________________________________________________________________________________
input_masks (InputLayer)        [(None, 256)]        0
__________________________________________________________________________________________________
segment_ids (InputLayer)        [(None, 256)]        0
__________________________________________________________________________________________________
bert_layer (BertLayer)          (None,<PHONE_NUMBER>90   input_ids[0][0]
                                                                 input_masks[0][0]
                                                                 segment_ids[0][0]
__________________________________________________________________________________________________
dense (Dense)                   (None, 256)          196864      bert_layer[0][0]
__________________________________________________________________________________________________
dense_1 (Dense)                 (None, 5)            1285        dense[0][0]
==================================================================================================
Total params: 110,303,039
Trainable params: 22,052,357
Non-trainable params: 88,250,682
__________________________________________________________________________________________________

Other logs:
WARNING: Logging before flag parsing goes to stderr.
W0722 16:38:28.879759 14352 deprecation_wrapper.py:119] From C:\Users\jorda\OneDrive\Documents\Programs\aria_projects\document_classifier\BERT\venv\preprocessing.py:7: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

2019-07-22 16:38:28.917117: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library nvcuda.dll
2019-07-22 16:38:29.034609: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6325
pciBusID: 0000:08:00.0
2019-07-22 16:38:29.034810: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-07-22 16:38:29.035881: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-07-22 16:38:29.041192: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2019-07-22 16:38:29.044644: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6325
pciBusID: 0000:08:00.0
2019-07-22 16:38:29.044900: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-07-22 16:38:29.045354: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-07-22 16:38:30.462499: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-07-22 16:38:30.462613: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0
2019-07-22 16:38:30.462745: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N
2019-07-22 16:38:30.464681: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8788 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:08:00.0, compute capability: 6.1)
2019-07-22 16:38:30.470977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6325
pciBusID: 0000:08:00.0
2019-07-22 16:38:30.471127: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
Building docs...
2019-07-22 16:38:30.471801: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-07-22 16:38:30.471966: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-07-22 16:38:30.472067: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0
2019-07-22 16:38:30.472126: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N
2019-07-22 16:38:30.472605: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8788 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:08:00.0, compute capability: 6.1)
W0722 16:38:34.138283 14352 deprecation_wrapper.py:119] From C:\Users\jorda\OneDrive\Documents\Programs\aria_projects\document_classifier\BERT\venv\bert\tokenization.py:125: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.

Dimension of labels input is (2225, 5).
Building model...
W0722 16:39:05.050155 14352 deprecation.py:506] From C:\Program Files\Python37\lib\site-packages\tensorflow\python\ops\init_ops.py:1251: calling VarianceScaling.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
W0722 16:39:05.109156 14352 deprecation.py:323] From C:\Program Files\Python37\lib\site-packages\tensorflow\python\ops\nn_impl.py:180: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
Model: "model"

How long did you wait for?
In the background (it is not printed to console) the weights for the TF Hub module will have to be downloaded (500MB for BERTBASE, 1GB for BERTLARGE), and then the BERT layer instantiated. This does take a fair amount of time for the download, and then to build the graph.
I don't like the example in the medium post. They made a few mistakes e.g. the way they implemented fine_tune_layers is completely wrong.
I have a much improved version in this Colab notebook:
https://colab.research.google.com/github/NVAITC/examples/blob/master/keras_bert_amp.ipynb
You are free to take this and use it.

How long did you wait for?

I waited for about 48 hours...

I have a much improved version in this Colab notebook:

I will have a look and implement this version and post back my findings.

You are free to take this and use it.

You rock! Thanks.

@tlkh

In the background (it is not printed to console) the weights for the TF Hub module will have to be downloaded (500MB for BERTBASE, 1GB for BERTLARGE), and then the BERT layer instantiated. This does take a fair amount of time for the download, and then to build the graph.

I have taken the BERT class from your script and adjusted my code to fit; however, I am still getting the same issue. Training fails to start. I waited 6 hours. Network i/o was not evidencing any download either.
** main.py **
def build_model(bert_path, max_seq_length, tune_cells):
    in_id = tf.keras.layers.Input(shape=(max_seq_length,), name="input_ids")
    in_mask = tf.keras.layers.Input(shape=(max_seq_length,), name="input_masks")
    in_segment = tf.keras.layers.Input(shape=(max_seq_length,), name="segment_ids")
    bert_inputs = [in_id, in_mask, in_segment]

    bert_output = BERT(finetune_cells=tune_cells, bert_path=bert_path)(bert_inputs)
    pooled = tf.keras.layers.GlobalMaxPooling1D()(bert_output)
    dense = tf.keras.layers.Dense(256, activation="relu")(pooled)
    pred = tf.keras.layers.Dense(5, activation="sigmoid")(dense)

    model = tf.keras.models.Model(inputs=bert_inputs, outputs=pred)
    model.compile(loss="binary_crossentropy", optimizer="adam",  metrics=['binary_accuracy', 'categorical_accuracy'])
    model.summary()

    return model

def set_session(USE_XLA=True, MIXED_PRECISION=True):
    """
    Set the session config to optimise GPU computations.
    - Automatic Mixed Precision is available for server grade GPUs.
    """
    config = tf.ConfigProto()
    if USE_XLA:
        opt_level = tf.OptimizerOptions.ON_1
        tf.enable_resource_variables()
    else:
        opt_level = tf.OptimizerOptions.OFF

    config.graph_options.optimizer_options.global_jit_level = opt_level

    config.graph_options.rewrite_options.auto_mixed_precision = MIXED_PRECISION

    sess = tf.Session(config=config)
    tf.keras.backend.set_session(sess)

    return tf.keras.backend.get_session()

def initialize_sess(sess):
    sess.run(tf.local_variables_initializer())
    sess.run(tf.global_variables_initializer())
    sess.run(tf.tables_initializer())
    tf.keras.backend.set_session(sess)

    K.set_session(sess)

def plot_loss(history):
    for metric in ['loss', 'binary_accuracy', 'categorical_accuracy']:
        train = history.history[metric]
        val = history.history['val_' + metric]
        plt.plot(train, label='train')
        plt.plot(val, label='val')
        plt.legend()
        plt.show()

def main():
    """
    0. Set Global Variables
    """
    sess = set_session()
    bert_path = "https://tfhub.dev/google/bert_uncased_L-12_H-768_A-12/1"
    max_seq_length = 256
    tune_layers = 1
    epochs = 2
    batch_size = 64

    """
    1. Build Data Set
    """
    corpus = MyDocs("datasets/bbc/raw", sess, bert_path, max_seq_length)

    ids = []
    masks = []
    segment_ids = []
    for id, mask, segment, label in corpus:
        ids.append(id)
        masks.append(masks)
        segment_ids.append(segment)
    X = [ids, masks, segment_ids]

    labels = corpus.labels
    label_encoder = OneHotEncoder()
    y = label_encoder.fit_transform(np.array(labels).reshape(-1, 1)).todense()
    print('Dimension of labels input is {}.'.format(y.shape))

    """
    2. Build Model and Train
    """
    print('Building model...')
    model = build_model(bert_path, max_seq_length, tune_layers)

    # Instantiate variables
    initialize_sess(sess)

    print('Training model...')
    history = model.fit(X, y,
                        validation_split=0.2,
                        epochs=epochs,
                        batch_size=batch_size,
                        verbose=2,
                        use_multiprocessing=True)
    plot_loss(history)

@jordanparker6 Thanks for the bug! verbose=2 will only print 1 line per epoch. Could it be that your Model is taking a huge amount of time to run through an epoch? Try verbose=1, which outputs on every batch. Please let me know if you still don't see any output

@omalleyt12 No change in the output post changing the verbose level. I let it run for 4 days...

The only thing that stand out to me is that model.fit(..., use_multiprocessing=True) should be False here, as True is only relevant to keras.Sequence or generator objects. Could you try that and let me know if it starts training?

Sorry for the late reply. I will try it tonight and get back to you.

@omalleyt12 that didn't work either...

@omalleyt12 is the fact that i am using a GTX1080ti with 11gb of GPU RAM an issue?

@jordanparker6
Is this still an issue

@Saduf2019 no many other libraries have provided a work around. See huggingfaces transformer library or fastbert.

@jordanparker6
IN that case please confirm if we may move this to closed status.


Add coverage

This adds coverage reports to the project, including an integration with codecov.

[Current coverage][cc-pull] is 99.03%

No coverage report found for master at 6a3fa03.

Powered by Codecov. Last updated by [6a3fa03...0c1d3d2][cc-compare]
[cc-base-branch]: https://codecov.io/gh/actano/yourchoice/branch/master?src=pr
[cc-compare]: https://codecov.io/gh/actano/yourchoice/compare/6a3fa03f21b3f33a0fc6f9475d817671ec6ad7f4...0c1d3d28da5bea47eff3f4568697e66516933c93?src=pr
[cc-pull]: https://codecov.io/gh/actano/yourchoice/pull/22?src=pr


Use node:* import protocol for safer module resolution

This PR uses node:* imports for fs and path modules.
Note that using node:* imports requires us to whitelist node:fs and node:path in the import/core-modules eslint setting. If we do not whitelist it then our linter fails because it can not identify node:fs as a node module.
Closes 3664

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

@chainoperator
you made the commit as @johnomarkid  so that account must sign the CLA too

@wemeetagain good catch! That's my work account :) I amended the commit to use the correct account.
Looks like the workflows need approval again since I switched accounts. Sorry about that.

My pleasure!
Just curious, what's the process for getting PRs merged after they have been approved?

We usually take care of it from there, thanks for the contribution @chainoperator!


(PUP-11216) Add support for multiple facter impl

Add support for multiple facter implementations and
provide default FacterImpl that is used to delegate
all methods to Facter.
Any client can register its own Facter implementation:
Puppet.initialize_settings([], true, true, facter: facter_impl)

Did some testing and it LGTM
± % bundle exec irb
2.7.3 :001 > require 'puppet'
 => true
2.7.3 :002 > class MyFacterImpl
2.7.3 :003 >   def initialize
2.7.3 :004 >   end
2.7.3 :005 >
2.7.3 :006 >   def value(fact_name)
2.7.3 :007 >     "CustomValue"+fact_name.to_s
2.7.3 :008 >   end
2.7.3 :009 >
2.7.3 :010 >   def add(name, &block)
2.7.3 :011 >     "Custom_add"+name.to_s
2.7.3 :012 >   end
2.7.3 :013 > end
 => :add
2.7.3 :014 > Puppet.runtime[:facter].value(:operatingsystem)
 => "Darwin"
2.7.3 :015 > Puppet.runtime[:facter]
 => #<Puppet::FacterImpl:0x00007fe625bbd2b8>
2.7.3 :016 > custom_facter_impl = MyFacterImpl.new
 => #<MyFacterImpl:0x00007fe626bd74f0>
2.7.3 :017 > Puppet.initialize_settings([], true, true, facter: custom_facter_impl)
 => {:facter=>#<MyFacterImpl:0x00007fe626bd74f0>}
2.7.3 :018 > Puppet.runtime[:facter].value(:operatingsystem)
 => "CustomValueoperatingsystem"
2.7.3 :019 > Puppet.runtime[:facter]
 => #<MyFacterImpl:0x00007fe626bd74f0>

jenkins please test this with servertests


Memory access error due to 'memcmp'

I tried to use rapidjson on the large json, and valgrind/memcheck finds errors,
see below. The offending line is this:

if (name[member->name.data_.s.length] == '\0' &&
memcmp(member->name.data_.s.str, name, member->name.data_.s.length *
sizeof(Ch)) == 0)

This happens during map value lookup. 'memcmp' can't be used in this place,
because some keys can be longer than the supplied value, and it is illegal to
read a string past its terminating zero character.

In fact, this bug can cause segmentation fault if the end of the string
supplied by the caller would happen to align with the end of the memory segment.

---error log---
==81117== Invalid read of size 1
==81117==    at 0x110A543: memcmp (mc_replace_strmem.c:1001)
==81117==    by 0x49F01C: rapidjson::GenericValue<rapidjson::UTF8<char>,
rapidjson::MemoryPoolAllocator<rapidjson::CrtAllocator> >::FindMember(char
const*) (document.h:271)
==81117==    by 0x49EECC: rapidjson::GenericValue<rapidjson::UTF8<char>,
rapidjson::MemoryPoolAllocator<rapidjson::CrtAllocator> >::operator[](char
const*) (document.h:239)
==81117==    by 0x49EE9C: rapidjson::GenericValue<rapidjson::UTF8<char>,
rapidjson::MemoryPoolAllocator<rapidjson::CrtAllocator> >::operator[](char
const*) const (document.h:247)

Original issue reported on code.google.com by<EMAIL_ADDRESS>on 28 Apr 2014 at 11:42

Merged into: #108

You may have seen #108 [1], which is about the same issue and has a link to a
patch in the comments.

hth,
Philipp

[1] http://code.google.com/p/rapidjson/issues/detail?id=108

Original comment by<EMAIL_ADDRESS>on 29 Apr 2014 at 4:00

[deleted comment]

[deleted comment]

Original comment by<EMAIL_ADDRESS>on 20 Jun 2014 at 11:17

Changed state: Duplicate


[Ubuntu] Publish Profile and other Azure related activites fail; no sign in allowance or token collection provided

Describe the bug
Upgraded to latest nightly electron build, running from WSL2 (Ubuntu) on my machine.  Working through creating a publish profile for my bot, I get to the page where I start defining which directory; however it doesn't see me as signed in; there's no sign-in or sign-out button, and I'm not asked for my tokens.
Version
Version:  2.0.0-nightly.242920.45439b5
Electron: 8.2.4
Chrome: 80.0.3987.165
NodeJS: 12.13.0
V8: 8.0.426.27-electron.0
Browser

[X] Electron distribution
[ ] Chrome
[ ] Safari
[ ] Firefox
[ ] Edge

OS

[ ] macOS
[ ] Windows
[X] Ubuntu

To Reproduce
Steps to reproduce the behavior:

Create a composer bot
Start creating a publish profile
Get to the stage where it lets you choose directory
Experienced: Dropdown is empty, and has error (or not), but no directory is chosen, and there's no login UI

Expected behavior
To be able to be effectively signed to Azure to complete the task
Screenshots

Additional context

@tonyanziano is this because there is no native oneauth library?

Correct. Linux is not supported by OneAuth. Currently they only have libraries for Mac, Windows 32-bit and 64-bit.
@carlosscastro and I spoke offline and he said he would reach out in the future to the OneAuth team to see what their roadmap is for Linux.


Compilation of example program on OS X

I am following the basis getting starting guide and am currently trying to compile the Susan program. Unfortunately, compilation fails on OS X (Darwin-14.4.0-x86_64-i386-64bit):
cnugteren$ ck compile program:cbench-automotive-susan --speed
***************************************************************************************
Current directory: /Users/cnugteren/CK/ctuning-programs/program/cbench-automotive-susan/tmp
***************************************************************************************
Resolving dependencies ...
***************************************************************************************
Compiler vars:
  XOPENME=
***************************************************************************************
Executing prepared batch file tmp-PzV7hE.sh ...
CK_CC  CK_OPT_SPEED CK_FLAGS_CREATE_OBJ CK_COMPILER_FLAGS_OBLIGATORY CK_FLAGS_DYNAMIC_BIN {CK_FLAG_PREFIX_INCLUDE}../ {CK_FLAG_PREFIX_VAR}XOPENME {CK_FLAG_PREFIX_INCLUDE}/Users/cnugteren/CK-TOOLS/lib-rtl-xopenme-0.3-gcc-local-macos-64/include  ../susan.c  {CK_FLAGS_OUTPUT}susan.o
./tmp-PzV7hE.sh: line 8: CK_CC: command not found
***************************************************************************************
Compilation time: 0.013 sec.; Object size: 0; MD5:
Warning: compilation failed!

It seems that several variables starting with CK_ are not properly substituted, perhaps there is a missing $-sign? Or did I forget to do something, perhaps loading some environmental variables? Setting $CK_CC to for example Clang doesn't seem to help.

Sorry for those issues - I did not test CK on Mac OS and I assumed that the conventions/commands are the same as in Linux. However, seems like there are differences. I think the problem is in exporting variables:
before compiling programs, I check for CK environments with compilers. So for MacOS, by default, I added entry "env:compiler-gcc-local-macos-h64-t64" (part of my fix yesterday). You can find this entry via:

ck find env:compiler-gcc-local-macos-h64-t64
There you will see file "env.sh" - it is executed just before compilation and it's the one that sets
up CK_CC, etc.

It uses bash and relies on two things:
#! /bin/bash
if [ "$1" != "1" ]; then if [ "$CK_ENV_COMPILER_GCC_SET" == "1" ]; then return; fi; fi
Above line checks if the script was already called to avoid calling it again (unless forced by CK) -
maybe there is an issue there and it doesn't go further.
Otherwise, I also use:
export CK_AR=ar
export CK_ASM_EXT=.s
export CK_CC=gcc
export CK_COMPILER_FLAGS_OBLIGATORY=
Maybe export doesn't properly on MacOS and something else is needed?..
Can you please just try to run it like that:
. ./env.sh ; echo $CK_CC
If it doesn't work, then the problem is in exports or first line ...
Thanks!

Setting the environment works fine:
compiler-gcc-local-macos-h64-t64$ . ./env.sh ; echo $CK_CC
gcc
compiler-gcc-local-macos-h64-t64$ $CK_CC --version
Apple LLVM version 6.1.0 (clang-602.0.53) (based on LLVM 3.6.0svn)

(note that running gcc or g++ actually runs Clang on OS X)
I believe that the problem is that the other script doesn't actually substitute CK_CC with $CK_CC (and so on): somehow the dollar signs are removed.

Strange. May I ask you to compile program with the following flag:

ck compile program:cbench-automotive-susan --speed --skip_clean_after

It should keep all temporary files. You can find them in tmp directory of the entry:

ck find program:cbench-automotive-susan

There should be one or more files tmp-XYZ.sh
Can you please print them here (or at least one where there is CK_CC)?
Thanks!

Oh, I fixed that - stupid mistake - I just did not add environment var description to MasOS entry in CK.
I just fixed that. You can update CK is usual with:

ck pull all

Can you please try to compile program again (I am now concerned about GCC -> LLVM substitution - hope there will be no new problems with calling conventions) ...

Thanks! Looks like compilation goes fine, but now there are linker warnings:
Executing prepared batch file tmp-XLctMv.sh ...
gcc  -O3 -c   -I../ -DXOPENME -I/Users/cnugteren/CK-TOOLS/lib-rtl-xopenme-0.3-gcc-local-macos-64/include  ../susan.c  -o susan.o
../susan.c:688:9: warning: implicit conversion from 'double' to 'TOTAL_TYPE' (aka 'int') changes value from 0.1 to 0 [-Wliteral-conversion]
  total=0.1; /* test for total's type */
       ~^~~
1 warning generated.
gcc    susan.o  -o a.out    -L/Users/cnugteren/CK-TOOLS/lib-rtl-xopenme-0.3-gcc-local-macos-64/lib -lrtlxopenme -lm
ld: warning: directory not found for option '-LCK_ENV_LIB_RTL_XOPENME_LIB'
ld: warning: directory not found for option '-LLIBRARY_PATH'
./tmp-XLctMv.sh: line 15: objdump: command not found
./tmp-XLctMv.sh: line 17: md5sum: command not found
***************************************************************************************
Compilation time: 1.139 sec.; Object size: 0; MD5:
Warning: compilation failed!

The issues with objdump and md5sum can probably be solved by installing the software packages (e.g. using home-brew). Alternatively for maximum compatibility, md5sum can be replaced by the system's md5 -r and objdump can be replaced by otool -tV <executable> (to disassemble). Let me know if you need more information.
I am not sure if this is relevant, but OS X uses $DYLD_LIBRARY_PATH instead of $LD_LIBRARY_PATH.

I think I fixed all above issues:
As usual, do not forget to do

ck pull all

problem with -L... is because you install XOPENME library while there was still a problem with $ on MACOS. So you need to reinstall it. The easiest way is probably to find a given entry in CK:

ck show env  --tags=xopenme

Then find related ENV UID (on the left) - normally you should have only 1 entry ...
And then remove this CK environment entry:

ck rm env:

for example: ck rm env:593df795f48cfbb5
Now you can reinstall xopenme and hopefully it should now have $ ...

I fixed objdump as you suggested. It is in the env.sh of the following GCC desriptions:

ck find env:-macos-

I also fixed md5sum as you suggested - I moved it to the OS description (key "md5sum"):

ck load os:macos-64

Please, tell me if it will work! Thanks!!!
By the way, note that my idea of CK was to make it extensible by the community aka research Wikipedia, i.e. users can add/unify descriptions/modules just like we do above.
So, if we will manage to add support for MAC OS without breaking the whole framework,
it  should support such agile approach ;) ...

Works as advertised, thanks!

Great! By the way, before closing this ticket, do you mind to remove again the env of the XOPENME as describe above and then try to install it automatically, i.e. when you compile program?
I am curious if above fixes fixed the autoinstall problem too?..
Thanks again!

No, that doesn't solve it:
WARNING: environment was not found using tags="lib,xopenme" and setup={"target_os_bits": "64", "host_os_uoa": "macos-64", "target_os_uoa": "macos-64"}
  Would you like to search and install package with these tags automatically (Y/n)? Y
CK error: environment was not found using tags="lib,xopenme" and setup={"target_os_bits": "64", "host_os_uoa": "macos-64", "target_os_uoa": "macos-64"}!

Is there a way to get it more verbose?

Sure. I need to check first what happens. Will try to reproduce this on my machine. Will tell you if I manage to sort it out ...

I will close this ticket and will check it in ticket #24 ...


Support local test execution in the client

We mostly support this now. We have "local-only" jobs that must be run on the local worker. We'll add more specialty job spec options for local-only jobs as we need them.


fix xo_format.5 typo

fix incorrect example output, JSON output will contain the value 65, not 6

Merged into develop


Support Kubernetes v1.26

close: https://github.com/cybozu-go/moco/issues/492

note: https://twitter.com/superbrothers/status/1611544104089026562

📝
https://github.com/kubernetes/kubernetes/releases/tag/v1.26.1


Server panic after signal SIGTERM

version: latest
When sending a sigterm to the runner with sudo docker kill woodpecker --signal=SIGTERM, the runner gracefully shutsdown, but the server panics
panic: Write called after Handler finished

goroutine 29210 [running]:
net/http.(*http2responseWriter).write(0xc000012828, 0x18, 0x0, 0x0, 0x0, 0x11009c2, 0x18, 0x1045f60, 0x7f359512c401, 0x7f359512c460)
        /usr/local/go/src/net/http/h2_bundle.go:6256 +0x1f7
net/http.(*http2responseWriter).WriteString(0xc000012828, 0x11009c2, 0x18, 0x7f359512c460, 0xc000012828, 0x7f359512c401)
        /usr/local/go/src/net/http/h2_bundle.go:6249 +0x55
io.WriteString(0x7f359512c440, 0xc000012828, 0x11009c2, 0x18, 0xc000012828, 0x7f3595967101, 0x7f359512c420)
        /usr/local/go/src/io/io.go:309 +0x74
github.com/gin-gonic/gin.(*responseWriter).WriteString(0xc0002f9500, 0x11009c2, 0x18, 0x7f359512c420, 0xc0002f9500, 0xc001807e01)
        /drone/src/github.com/woodpecker-ci/woodpecker/vendor/github.com/gin-gonic/gin/response_writer.go:85 +0x7a
io.WriteString(0x7f3595967170, 0xc0002f9500, 0x11009c2, 0x18, 0xc0002f9500, 0xc0000797c0, 0x0)
        /usr/local/go/src/io/io.go:309 +0x74
github.com/woodpecker-ci/woodpecker/server/api.LogStreamSSE.func2(0x12dfdd0, 0xc0003b8180, 0xc0015dbad0, 0xc000edee40, 0x12e9e58, 0xc0002f9500, 0xc0016111b0)
        /drone/src/github.com/woodpecker-ci/woodpecker/server/api/stream.go:207 +0x168
created by github.com/woodpecker-ci/woodpecker/server/api.LogStreamSSE
        /drone/src/github.com/woodpecker-ci/woodpecker/server/api/stream.go:191 +0x699

not a problem anymore ... - i guess #514 did the job

Thanks @6543

@isuruf if you see it out in the wild again - please reopen a new issue :)
keep clam and report bugs :bug: :+1:


trying to use Facebook and FacebookWeb but getting a crash

Im getting this error  reason: '*** -[__NSPlaceholderDictionary initWithObjects:forKeys:count:]: attempt to insert nil object from objects[0]
im passing in my app_id but still not working

+1


Reports Not Showing for Teams Communications Admin

This article states that a "Teams Communications Admin" should be able to see Reports. We have a user with this role, but is unable to see reports. I'm assuming that's because the article is providing data that once was true, but is no longer.

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

ID: 78ade1a4-092c-1132-44df-ee2c683fdd33
Version Independent ID: 396b1aee-2f40-9895-9b00-07e38d11d31b
Content: Microsoft Teams analytics and reporting - Microsoft Teams
Content Source: Teams/teams-analytics-and-reports/teams-reporting-reference.md
Service: msteams
GitHub Login: @LanaChin
Microsoft Alias: v-lanac

@geektbee  Thank you for submitting feedback and contributing to the docs. We are currently investigating this.

@geektbee - thanks so much for your feedback and helping us to improve our docs. These articles have been updated to clarify which reporting access for admin roles:

https://docs.microsoft.com/microsoftteams/teams-analytics-and-reports/teams-reporting-reference
https://docs.microsoft.com/MicrosoftTeams/using-admin-roles


{{ 'foo' if false }} shortcut not usable with StrictUndefined

Using the shortcut version of the ternary operator with no else implies else <undefined>. This is fine when using the normal Undefined but makes this shortcut basically useless with StrictUndefined (and to some extent LoggingUndefined).
>>> from jinja2 import StrictUndefined, Environment
>>> env = Environment(undefined=StrictUndefined)
>>> env.from_string('{{ "foo" if false }}').render()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/adrian/.python-env/lib/python2.7/site-packages/jinja2/environment.py", line 989, in render
    return self.environment.handle_exception(exc_info, True)
  File "/home/adrian/.python-env/lib/python2.7/site-packages/jinja2/environment.py", line 754, in handle_exception
    reraise(exc_type, exc_value, tb)
  File "<template>", line 1, in top-level template code
jinja2.exceptions.UndefinedError: the inline if-expression on line 1 evaluated to false and no else section was defined.

I'd change the default from <undefined> to '' - like this the behavior of existing templates will not change (empty output) but it would work fine with the stricter Undefined variants.
The only breakage I could imagine is someone using it in a function/macro call with an explicit is defined check later on. But I think that's rather unlikely and if necessary a new policy option could be added to make it default to <undefined> again.

Any update on this issue


Correct name for the blade's label (Replicate data globally)

@andresnava,
Thanks for having already signed the Contribution License Agreement. Your agreement was validated by Microsoft. We will now review your pull request.
Thanks,
Microsoft Pull Request Bot

@mimig1 Hi Mimi. Please review these proposed changes. Thanks.

#sign-off @andresnav - Thank you for the fix!


Enable gloangcilint: unconvert

Signed-off-by: Artem Yarmoluk<EMAIL_ADDRESS>
Enable unconvert linter
Checklist

[x] Commits are signed with Developer Certificate of Origin (DCO)
[ ] Tests have been added
[ ] A PR is opened to update the documentation on https://github.com/kedacore/keda-docs
[ ] Changelog has been updated

Fixes #1158

Please resolve the conflict

Done!

Thanks @gordonbondon


Update news/website easily

Make it easier for users (researchers in Donal's group) to update news and add content.

Today the web site is pure html, which means if you want something on the website you have to clone the code and push your changes to git. When master is updated docker image will be built, when the image is ready the site can be deployed.
To make it possible to update content online on the site we need to replace the "pure html site" with some kind of CMS.

CMS typically requires vigilant maintenance and updates for security reasons due to the popularity as hacking targets.


Add support for Buffer values

Fixes #86
The solution is a bit more complex because I don't have access to the Buffer type. If I try to access the type, I get the following error:
Cannot find name 'Buffer'. Do you need to install type definitions for node? Try `npm i --save-dev @types/node`.ts(2580)

This PR implements a Buffer check that does not rely on @types/node to be installed, even though, I would much prefer that solution. The mysql package is built on top of mariadb which is a nodejs-specific implementation. However, I wasn't sure about the platform-specificity of this repo.
@tim-smart any objections against pulling in @types/node? If the packages should be platform-agnostic, I think there's some extra work to do to achieve that for the mysql package, at least.

I would like to avoid @types/node if possible, as the sqlite package targets browsers.
Will take a look at this in a couple hours :)


Crash trying to create a more complex layout (UICollectionReusableView with a UICollectionView inside)

Hey there,
Thanks for creating this and making this open source.
I've got a UICollectionView with this flow layout, and it works fine.
However, now when I try to make the "CSStickyHeaderParallaxHeader" supplementary view be a UICollectionReusableView but with a UICollectionView inside it, it crashes for me when I scroll up.
The design I'm trying to implement is for browsing profiles. I want the CSStickyHeaderParallaxHeader supplementary view to show a list of images the user can swipe left/right. As soon as the user swipes up/down, the supplementary view should stay and not move (like your Spotify example).
However because I'm using a UICollectionReusableView with a UICollectionView inside, it seems to crash as soon as I swipe up. It gives me this error in the console:
2016-01-05 21:31:58.048 App[22890:3720901] the behavior of the UICollectionViewFlowLayout is not defined because:
2016-01-05 21:31:58.049 App[22890:3720901] the item height must be less than the height of the UICollectionView minus the section insets top and bottom values, minus the content insets top and bottom values.
2016-01-05 21:31:58.049 App[22890:3720901] The relevant UICollectionViewFlowLayout instance is <CoverflowFlowLayout: 0x7fa7db5d3610>, and it is attached to <UICollectionView: 0x7fa7dc063400; frame = (0 0; 375 168); clipsToBounds = YES; autoresize = RM+BM; gestureRecognizers = <NSArray: 0x7fa7db5d1e70>; layer = <CALayer: 0x7fa7db5cee70>; contentOffset: {0, 0}; contentSize: {1503.3404761904762, 190}> collection view layout: <CoverflowFlowLayout: 0x7fa7db5d3610>.
2016-01-05 21:31:58.049 App[22890:3720901] Make a symbolic breakpoint at UICollectionViewFlowLayoutBreakForInvalidSizes to catch this in the debugger.

I can bypass this crash if I set the "parallaxHeaderMinimumReferenceSize" of your flow layout to be the same as the "parallaxHeaderReferenceSize". However now I don't get the parallax effect. The supplementary view moves up as well. It's not "sticky" in the background, if that makes sense. I want to have an "overlay" effect (again something similar to the Spotify example).
Do you have any ideas what might be causing this issue? Let me know if you need more info or if you want me to record a short video demonstrating my problem, I can send it to you via email.
Thanks

Yes , i got the same issue ..... but i want parallax effect , did you find any solution ?


Start use lates version of rebar3_edoc_extensions

There is already a work in progress in another branch to improve the documentation based on the new features in rebar3_edoc_extensions. I'm going to close this pull request in favor of the other one with the doc improvements, sorry for that.
Thank you for your help though!


openeo GRASS driver: support actinia processes

add generic translation of actinia processes from openeo pg to actinia pg
waiting for https://github.com/mundialis/actinia-gdi/pull/44

(https://github.com/mundialis/actinia-gdi/pull/44 has been merged)


Import failed in ComfyUI

Hi, I tried to install it on ComfyUI but looks like something is wrong. It says the import failed without other information, could you help me to figure it out?

There should be more information on the comfyui startup log, most likely missing some requirement from the requirement.txt

I just learned today that if another node has a smaller minimum requirement, the ComfyUI manager considers the dependency fulfilled, even if another node has higher minimum requirement set. This is why if you have diffusers 0.25, it won't be updated to 0.26.2 if it's set as minimum, if there's another custom node that sets minimum to be lower than 0.25, ie. Marigold.
Thus, for now, I've set this repo to have exact requirement of 0.26.2. I probably should make install.py instead, will look into that.

is there a fix for this currently? I noticed that some of the files were updated last week but I Just installed and tried running in comfy and got the same error as above. I am nowhere near an expert in code. Any help would be appreciated


Interface of binary injector depends on whether we will have a single of two fields for trace context

Current implementation of binary context inject/extract expects that entire SpanContext can be encoded in a single field:
https://github.com/bogdandrutu/openconsensus/blob/42f90bf8196cc1e3913510160cdfdc3995a7119d/api/src/main/java/openconsensus/context/propagation/BinaryFormat.java#L26-L33
However current proposal lists traceparent and tracestate as separate headers. See https://github.com/w3c/trace-context-binary/issues/7 with the proposal to change it

I am in favor of a single binary blob for trace context in w3c

I'm in favor of a single binary blob as well.

@carlosalberto please comment on issue in W3C on benefits of a single blob over two blobs.


SHALLOW CLONE support for Delta tables with deletion vectors

This PR is part of the feature: Support Delta tables with deletion vectors (more details at https://github.com/delta-io/delta/issues/1485)
This PR adds support for SHALLOW CLONEing a Delta table with deletion vectors. The main change is to convert the relative path of DV file in AddFile to absolute path when cloning the table.
Added tests

@larsk-db @xupefei Please review the PR.


Add version command

Add a version command to Lula
lula version
Pull version from config.CLIVersion in order to have this established at build time.

addressed with #164


How to setup angular-Material change for bootstrap?

Thank so much

any description why not @angular/material

:) in turkish we say "içinde içinde"
That means Solution is in it....
There is a few questions about that, you can check...
For your need steps may be (I did with this way)
1- read
https://github.com/angular/material2/blob/master/guides/getting-started.md
2- Start with small target, so skip themes ext.
3- Be carefull about
webpack configurations
Client\styles vendor.css    / You need to add here Material Icons and Roboto Fonts
.angular-cli.json               / in docs they say styles and scripts section to use but not effective for thi s project
And last my app.component.ts looks like this. I am not sure best but working
@Component({
selector: 'appc-root',
templateUrl: './app.component.html',
styleUrls: [
'./app.component.scss'
,'./primengtheme.scss'
,'./primengbase.scss'
],
encapsulation: ViewEncapsulation.None
})

@kanpinar have you experienced some discrepancies with the original MS SPA Angular template for ASP.NET Core 2.0(https://github.com/aspnet/JavaScriptServices/tree/dev/templates/Microsoft.DotNet.Web.Spa.ProjectTemplates/angular)?
Long story short, I have a "working" solution supporting Angular Material 2 (no JS warning when running and the controls are all running fine). However, I am facing one single issue that bothers me a bit when webpack is doing its job file changes, seems the rendering is duplicated on the go, if I reload the page, it's fine but I loose the i-don't-need-to-refresh-my-page-to-see-observe-changes feature: https://github.com/aspnet/JavaScriptServices/issues/1231
I am wondering if it's due to the fact that I had to change the tag for the server pre-rendering asp-prerender-module: https://github.com/aspnet/JavaScriptServices/blob/04fe1204a95ee09c9c0bf14c81e680c6f38f37dc/templates/Microsoft.DotNet.Web.Spa.ProjectTemplates/angular/Views/Home/Index.cshtml#L5
Which on my side has had to be replaced by asp-ng2-prerender-module in order to support Angular Material 2:
https://github.com/ehouarn-perret/EhouarnPerret.CSharp.AngularMaterial2/blob/92151f65e683b3a193b4d4985428ad244dae0ae8/EhouarnPerret.CSharp.AngularMaterial2/Views/Home/Index.cshtml#L5

@ehouarn-perret Have you managed to find a solution to this issue? I'm getting exactly the same issues with HMR (like you, I've had to change the tag for server pre-rendering).


[REVIEW] tool.umap: Support random_state in rapids umap

This is a very simple change to propagate the random_state argument from tool.umap into the RAPIDS UMAP estimator.

Ping. This is a needed in the https://github.com/clara-parabricks/rapids-single-cell-examples so that we can make our notebooks reproducible. It's a trivial addition to propagate the random_state argument to the RAPIDS UMAP estimator. Any chance this can be considered for review?

Looks good to me.

Thanks @gokceneraslan!


first/1 and --stream

There seems to be something wrong with gojq's "streaming parser" when it is used with first/1, or vice versa.
The table below shows some performance metrics comparing jq and gojq when running a query
against a "real-world" JSON data set available at:
https://data.montgomerycountymd.gov/api/views/4mse-ku6q/rows.json
Its size is: 1,459,336,880 bytes, and it is archived at
https://web.archive.org/web/20230112063656/https://data.montgomerycountymd.gov/api/views/4mse-ku6q/rows.json
I suspect you could reproduce the problem quite easily with other large datasets in which the query result is obtained quickly by jq running a command similar to $CMD, where:
CMD='first(inputs|select(length==2 and .[1]==["meta","view","createdAt"]))|.[1]'

Here are the performance numbers obtained using $CMD against the traffics violation dataset:

u+s
mrss (MB)
command

221.4s
2.0
jq -n --stream "$CMD"

697.8s
8051
gojq -n --stream "$CMD"

Since gojq does print the correct value relatively promptly,
it seems clear that the main problem is that gojq is not exiting early:
this would account for both the greater u+s time and the much greater memory consumption.

I see there might be something wrong with memory management but it does not look like a bug of first/1. The command gojq -n --stream 'first(inputs | select(length == 2 and .[1] >= 1000))' <(seq -f "%.0f"<PHONE_NUMBER>0) exits quickly and works well, but when I change the query to .[1] >= 100000000, the memory consumption grows too much unlike jq. Maybe unused json values are not garbage collected, but I'm not sure what's the root cause. Well, time performance is not bad; gojq emits [[],100000000] in 1:22, while jq in 1:34. Needs more time for me to look into and any investigation is welcome.

Got curious and did a mem profile of gojq -n 'first(range(1000000000) | select(. >= 100000000))' here is the biggest for the  "inuse space" set:

@itchyny - The tell-tale sign that first and streaming are not working properly together is that in the example I gave, the answer is emitted almost immediately, but then processing continues.  Evidently, first is not effectively able to signal to gojq to STOP NOW in the way it does when streaming is not involved.

If my command is not enough, please create reliable way to reproduce the issue. Your reported JSON is too large for my network to fetch correctly.

@itchyny - It's only 1.5 GB.  Using wget it takes about 2.5 minutes to download:
wget https://data.montgomerycountymd.gov/api/views/4mse-ku6q/rows.json

If wget is not working for you, could you try wget2 or curl?

Well, I actually tried 5 times with all failures, maybe the server has timeout around 8 minutes. Their server always respond with Internal error.
 % wget https://data.montgomerycountymd.gov/api/views/4mse-ku6q/rows.json
--2023-01-13 08:39:18--  https://data.montgomerycountymd.gov/api/views/4mse-ku6q/rows.json
Resolving data.montgomerycountymd.gov (data.montgomerycountymd.gov)... <IP_ADDRESS>, <IP_ADDRESS>, <IP_ADDRESS>
Connecting to data.montgomerycountymd.gov (data.montgomerycountymd.gov)|<IP_ADDRESS>|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: unspecified [application/json]
Saving to: ‘rows.json’

rows.json                               [                                                    <=>            ] 246.82M   545KB/s    in 8m 21s

2023-01-13 08:47:40 (504 KB/s) - ‘rows.json’ saved [258809927]

 % tail -c 100 rows.json
 Automobile", "2007", "TOYT",{
  "error" : true,
  "message" : "Internal error",
  "status" : 500
}

 % ping data.montgomerycountymd.gov
PING ext-lb-pool-1.aws.us-east-1-f-prod.socrata.net (<IP_ADDRESS>): 56 data bytes
64 bytes from <IP_ADDRESS>: icmp_seq=0 ttl=42 time=191.831 ms
64 bytes from <IP_ADDRESS>: icmp_seq=1 ttl=42 time=191.800 ms
64 bytes from <IP_ADDRESS>: icmp_seq=2 ttl=42 time=192.203 ms
64 bytes from <IP_ADDRESS>: icmp_seq=3 ttl=42 time=193.013 ms
64 bytes from <IP_ADDRESS>: icmp_seq=4 ttl=42 time=192.023 ms
^C
--- ext-lb-pool-1.aws.us-east-1-f-prod.socrata.net ping statistics ---
5 packets transmitted, 5 packets received, 0.0% packet loss
round-trip min/avg/max/stddev = 191.800/192.174/193.013/0.444 ms

 % traceroute data.montgomerycountymd.gov
traceroute: Warning: data.montgomerycountymd.gov has multiple addresses; using <IP_ADDRESS>
traceroute to ext-lb-pool-1.aws.us-east-1-f-prod.socrata.net (<IP_ADDRESS>), 64 hops max, 52 byte packets
 1  <IP_ADDRESS> (<IP_ADDRESS>)  3.572 ms  3.069 ms  4.550 ms
 2  * * *
 3  * * *
 4  * * *
 5  * * *
 6  osk004bb00.iij.net (<IP_ADDRESS>)  8.691 ms
    osk004bb01.iij.net (<IP_ADDRESS>)  10.145 ms
    osk011bb01.iij.net (<IP_ADDRESS>)  9.473 ms
 7  lax002bb12.iij.net (<IP_ADDRESS>)  122.045 ms
    lax002bb13.iij.net (<IP_ADDRESS>)  111.835 ms
    lax002bb12.iij.net (<IP_ADDRESS>)  116.853 ms
 8  abn001bb10.iij.net (<IP_ADDRESS>)  187.658 ms  187.170 ms
    abn001bb10.iij.net (<IP_ADDRESS>)  182.308 ms
 9  equinix02-iad2.amazon.com (<IP_ADDRESS>)  204.752 ms
    equinix01-iad2.amazon.com (<IP_ADDRESS>)  175.488 ms  176.742 ms
10  * * *
11  * * *
12  * * *

@itchyny -
I compressed the file (using bz2) and made it available on resilio:
The file: 139786726 Jan 11 4mse-rows.json.bz2
If you open the following link in a browser, it will guide you through the process:
https://link.resilio.com/#f=4mse-rows.json.bz2&t=6&i=BHGCKLIIEKL2E2Y7Y3B6NAOO5EMJW2AGI&e=1674183157&v=2.7

@itchyny - You're right - my mis-report was based on a typo.  My apologies.  Would you mind if I simply deleted this entire issue (if that is possible?)


Extremely Large Network Outputs

After training the model with the 24GB training dataset, I loaded it into a client on CARLA, just to realize that it outputs extremely large values (i.e. in the thousands) as opposed to values limited by 1. Is there a normalization step that needs to be applied?

Hi Chris,
It happened to me too sometimes that the values for the outputs didn't match the distribution of the data.
Some things that might work:

try different hyper-parameters (e.g. lambda_steer, lambda_throttle etc.). In your case, only speed might be learned correctly, but throttle, brake, and steer might be barely taken into account.
restart the training (due to a different initialization it might not converge correctly)

I also described these points here.
https://medium.com/merantix/journey-from-academic-paper-to-industry-usage-cf57fe598f31
We also had to adjust the controller (https://github.com/carla-simulator/imitation-learning/blob/master/agents/imitation/imitation_learning.py) a bit, due  to the throttle unit, but since you get also too big values for steer and brake, this is less likely.

Hi Markus,
Thanks for the response. I realized that after 90000 iterations, the model started to have these values explode. Before, the car did follow the path mostly well.
I was wondering if you know how we would be able to augment the existing training set's h5 files? We would like to go around the map and collect new training data to add to the learning process.
Thanks,
Chris

I realized that after 90000 iterations, the model started to have these values explode

I experienced the same behavior (this is very obvious to see in Tensorboard). Every time I train and if this happens, it happens at a different amount of steps. I didn't debug this so far, it would be good to find out why.

how we would be able to augment the existing training set's h5 files?

This is done on the fly just before training already: see https://github.com/merantix/imitation-learning/blob/master/imitation/input_fn.py#L196

We would like to go around the map and collect new training data to add to the learning process.

To collect data, refer to https://github.com/carla-simulator/imitation-learning/ and the associated paper

Hi Markus,
Sorry if I was unclear. I meant more in terms of how to record images taken from the CARLA simulator and convert them to the h5 files in the same format as the ones in Codevilla's training dataset. I don't think he shared the code for this, but I was wondering if there are any samples I can look at since I am relatively new to using the CARLA/H5 API.

We didn't add additional training images/sequences so I would have to research to find out myself


Feature/api specs proposal

As a reminder from #280 we need to keep specs markdowns here

[ ] index.html.md
[ ] includes/*.md - without the leading numbers in names

Closes #266
I'm happy with the resulted API redefinition.


Crash with version <IP_ADDRESS> for 1.12.2, previous one working fine

Mod Version: DynamicSurroundings-1.12.2-<IP_ADDRESS>.jar
Forge Version: <IP_ADDRESS>24
Optifine Version: 1.12.2_HD_U_C9
Link to crash log: https://hastebin.com/ponokiceha.go
Description: This is my personal, private 1.12.2 pack, currently in development. I've been using build <IP_ADDRESS> until today, then tested with <IP_ADDRESS>. The pack itself loads fine, but the game crashes upon loading the singleplayer test world. I reverted back to <IP_ADDRESS> and the problem went away. Did not try with freshly generated world yet.

Does it always crash?

I retried and it did not crash. Now I'm wondering what may have caused that.

Yeah.  Given what I know of these types of errors and how this particular collection is used, it appears there is a thread running "client" side that is not the client thread and it is doing an entity update of some sort.  Unfortunately when we get a Minecraft crash report we do not have visibility into the call stacks of the other threads to see what is going on.  Upshot is:

There is a bug somewhere.  I don't think it is DS.
It appears timing related so the chances of it happening may be uncommon.
We don't know what the other threads are doing.  I need to dig into things to see if I can manage to capture that data somehow.

Let me know if I can help. If I find a mod conflicting with yours, that mod will drop out of my pack until it's fixed.

I may make a debug one-off build for you to try.  It will have additional diagnostics to ensure the update is occuring on the client thread.

Find a test JAR here.  It's the same as <IP_ADDRESS>, but with an additional check to ensure the living update is coming in on the client thread.  If for some reason it is not an exception will be generated and your client will crash with the info which hopefully will point a finger at the offender.

For future test builds, I recommend marking it as such both in filename and mod description.
I ran it with the test build, no crashes. Let me know if you have use for any other logs. I'd also be happy to run further tests if you need me to. It would be helpful to identify the bad apple here, since I am running a number of not-so-great mods for testing and could use pointers on which ones to drop out of the pack.

The version thing is on my list of things to do.  I may have to make code changes to support parsing out the version string properly.

Assume Bug with Optifine 1.12.2 U C9 I think this is the issue
https://www.youtube.com/watch?v=QUI7iRR9FD8

I haven't looked into the OptiFine JAR that much, so it could be.  However, I suspect what is demonstrated in the video has something to do with OptiFine client side chunk caching.  If that cache gets screwed up somehow weird rendering things can happen.

The issue has not resurfaced so far. I am keeping an eye on it and will share further crash logs, if any.

Thanks for keeping me up to date.

Got it to crash the same way again. Happened after I added a few mods and updated others. Again, game started fine, but crashed on loading the worldsave. Unfortunately, I have not been running your modified DS version at the time. Here is the log anyway: https://hastebin.com/uwegulitoy.bash

Unfortunately it doesn't show anything new.

@Curunir I assume the crash hasn't happened yet?  It wouldn't surprise me if it didn't.  These types of crashes sometimes require the moons to align.

@Curunir Have you come across this problem again?  I am reading a new release and I am going to activate this check so if anyone else comes across it I can hopefully get a good trace.

It hasn't occurred again. I did see your note in the changelog for <IP_ADDRESS>. Good luck getting proper data on it.

@Curunir Have you checked out <IP_ADDRESS> RE: this issue?  In that particular version I changed the method of how DS traverses the map object.   I haven't heard anyone encountering the concurrency issue since then.

I will check once I get back to building a pack for 1.12.2. Due to the rapid updates, I took a break and went back to building a stay-behind 1.7.10 Pack.

@Curunir Following up.  I was wondering if you had further updates?

Closing due to inactivity.  If the issue does come back up feel free to re-open.


[Macros] Add API for expanding a macro defined in terms of another macro

Introduce APIs to help with expanding a macro that is defined in terms of another macro, e.g.,
macro f(a: Int) = #g(a: a, b: "something")

There are effectively two new APIs:

MacroDeclSyntax.checkDefinition() checks that the definition of a macro is well-formed, producing a semantic representation suitable for expansion when it is, or produces error diagnostics when it isn't.
MacroDeclSyntax.expand which takes that semantic representation and a (well-formed) argument list or syntax node and performs the actual expansion.

@swift-ci please test

@swift-ci please test

@swift-ci please test

@swift-ci please test Windows

I'm holding off on merging this until I have the compiler side of it implemented, to make sure we have the right API here.


[build issue] version GLIBCXX_3.4.26 not found when building from source

Hi, I tried to follow the installation cmds in the doc, for building triton from source.
But Afterwards, I met this error:
/home/dli/.triton/llvm/llvm-4017f04e-ubuntu-x64/bin/mlir-tblgen: /lib64/libstdc++.so.6: version 'GLIBCXX_3.4.26' not found (required by /home/dli/.triton/llvm/llvm-4017f04e-ubuntu-x64/bin/mlir-tblgen)

Looks like triton downloads a LLVM static library which is built with GLIBCXX_3.4.26, but my local libstdc++.so.6 only supports to maximum GLIBCXX_3.4.25. (And in fact my OS is Rocky, not ubuntu)
A limitation in my side is I don't have permissions to upgrade system libstdc++ in my machine, then what should I do? e.g.,

How to choose another alternative LLVM static library with a correct SHA?
How to build the LLVM library from source required by triton, instead of downloading a built static one?

Any comments, links, or guidances are welcome! Thanks!

@peterbell10

The fix used in pytorch (pytorch/pytorch#121556) was to use conda install sysroot_linux-64=2.17 libstdcxx-ng=12.3.0 which gives particular versions of GLIBC and GLIBCXX.

I tried this way provided by Peter, but didn't work for me in local/native hosts.
I will retry to build it in docker to make env configuration easier.

I think it can be solved by Peter's suggestion.


Example not working on XCode 8

Version

react-native-router-flux v3.36.0
react-native v0.33.0

Actual behaviour
Example fails to compile giving an RCT Websocket error.

I think you have to remove some compiler flags from RCTWebsocket.

Would you know which compiler flags @dragfire? I haven't encountered this error before and I'm relatively new to the mobile stack.
Thanks!

https://github.com/facebook/react-native/issues/8584#issuecomment-236366222

Hopefully that should fix it.

That did the trick! Thanks @dragfire.


Check if process is defined

This PR checks if process is defined before reading it. I ran into this when trying to use XState with Cloudflare Durable Objects.
Fixes #787

How have you tried to consume XState in this environment? Have you used any of the templates mentioned here?

How have you tried to consume XState in this environment? Have you used any of the templates mentioned here?

Yes, I used the TS template.  I think it's a good idea to not assume that process is defined everywhere XState can run; this problem has come up in the past quite a few times.
I fixed it by using the Rollup replace plugin, but developers shouldn't need to do that. This problem also occurs when trying to use XState in the browser (e.g., via unpkg) without using xstate.web.js.

I just find it a little bit ironic in general that the ecosystem has converged on using a tool that was designed to work with node (npm registry and CLIs interacting with it) and then started to complain about code distributes there to use node-specific conventions :shrug:
I understand the overall frustration with this but I'm a little bit torned between various goals here. Somewhat luckily we now have better ways of distributing code for various target environments, or when using different conditions (like development/production). Not that long time ago there was no standard for doing this - and even today most people probably won't be able to configure tooling correctly to pick up correct things. This is very nuanced and that's why I believe that using higher-level tooling that configured stuff on our behalf is very important.
We need to decide what are our defaults and priorities though, some of the goals include:

good DX (in a form of additional warnings/errors, only available in the development)
bundlesize (thanks to the former being hidden behind a development flag this one gets optimized)
0-config consumption

The problem with the current solution is that it violates first two. With the shape of this PR we regress on the second goal.
Take a look at what happens with a simple test:
// input
const IS_PRODUCTION =
  typeof process !== 'undefined'
    ? process.env.NODE_ENV === 'production'
    : false;

export default function () {
  if (IS_PRODUCTION) {
    console.log('prod');
  } else {
    console.log('dev');
  }
}

// terser output
const o="undefined"!=typeof process&&"production"===process.env.NODE_ENV;export default function(){o?console.log("prod"):console.log("dev")}

As we might see - the dev-only code has stayed untouched and is still present in the output. This is of no surprise, if we consider the type of IS_PRODUCTION it's a boolean here. A static tool can't evaluate the condition because it doesn't have access to the runtime information.
We might think that  at least this will get fixed when one is using a "replacement" plugin. Take a look at such a situation then:
// input
const IS_PRODUCTION =
  typeof process !== 'undefined' ? 'production' === 'production' : false;

export default function () {
  if (IS_PRODUCTION) {
    console.log('prod');
  } else {
    console.log('dev');
  }
}

// output
const o="undefined"!=typeof process;export default function(){o?console.log("prod"):console.log("dev")}

Unfortunately, not much of a change here - the dev-only code is still here. Why is that? Well, the type of the IS_PRODUCTION didn't change here - it's still a boolean.
We can try to flip the situation and assume that we default to the production code (the previous version uses false as the default for IS_PRODUCTION):
// input
const IS_PRODUCTION =
  typeof process !== 'undefined' ? 'production' === 'production' : true;

export default function () {
  if (IS_PRODUCTION) {
    console.log('prod');
  } else {
    console.log('dev');
  }
}

// output
export default function(){console.log("prod")}

Ka-ching 💰 ! We have it! Well... do we? If we consult this with our overall goals then we might see that we've fixed the bundlesize problem but we've regressed on the DX part (by default, it can be gained back when using a bundler). It really is a Fast Good Cheap situation that we are having here.
Don't take me wrong - I'm open for adjusting this but I would like to make sure that we are making a well-informed decision here, taking all of that into consideration.
Nowadays we could remove process.env.NODE_ENV stuff from the distributes files entirely, thanks to package.json#exports. Unfortunately, in v4 we kinda allow accessing stuff from xstate/lib and xstate/es and this becomes more tricky than it should be and I'm somewhat afraid of making such changes in v4. And even with that in place - the webpack's recommendation is to default to the production code and make dev code opt-in. If we apply that we end up with the last situation that I've depicted - no improved DX by default. Fortunately, I think that most of modern, popular, bundling "wrappers" (like Vite, Snowpack, webpack 5, etc) know how to pick development/production code based on package.json#exports. So I guess that those who are hand-crafting their configs would just need to know how to opt into the development code on their own.

@Andarist Should we close this or go with your solution (which I committed)?

superseded by https://github.com/statelyai/xstate/pull/4016


The panic log is recovered, how can it be hooked

1. What version of Go and system type/arch are you using?
go version go1.20.3 windows/amd64
2. What version of GoFrame are you using?
GoFrame CLI Tool v2.4.3, https://goframe.org
GoFrame Version: v2.3.3 in current go.mod
3. Can this issue be re-produced with the latest release?
yes
4. What did you do?
I want to hook panic logs like https://goframe.org/pages/viewpage.action?pageId=1114336
5. What did you expect to see?
send notifications to me
6. What did you see instead?
exception recovered

As shown in the doc, you can implement a writer , eg.
type MyWriter struct {
	logger *glog.Logger
}

func (w *MyWriter) Write(p []byte) (n int, err error) {
        defer func() {
                if errx := recover(); errx !=nil {
                        // notify somewhere
                }
        }
	var (
		s   = string(p)
		ctx = context.Background()
	)
	if gregex.IsMatchString(`PANI|FATA`, s) {
		fmt.Println("SERIOUS ISSUE OCCURRED!! I'd better tell monitor in first time!")
		g.Client().PostContent(ctx, "http://monitor.mydomain.com", s)
	}

       // trigger some panic
	return w.logger.Write(p)
}

As shown in the doc, you can implement a writer , eg.
type MyWriter struct {
	logger *glog.Logger
}

func (w *MyWriter) Write(p []byte) (n int, err error) {
        defer func() {
                if errx := recover(); errx !=nil {
                        // notify somewhere
                }
        }
	var (
		s   = string(p)
		ctx = context.Background()
	)
	if gregex.IsMatchString(`PANI|FATA`, s) {
		fmt.Println("SERIOUS ISSUE OCCURRED!! I'd better tell monitor in first time!")
		g.Client().PostContent(ctx, "http://monitor.mydomain.com", s)
	}

       // trigger some panic
	return w.logger.Write(p)
}

I tried, but couldn't trigger this Writer

@zcyc You need set the writer for the logger you are using. For example, glog.SetWriter or g.Log().SetWriter.


Log Sonic Pi GUI messages when operating in headless mode

When sonic-pi is launched in headless mode (e.g. ubuntu-16.04-gce-launch) there is no GUI in which to view error messages.  The sonic-jam binary should start an OSC server on port 4558 and log all messages.

Started branch https://github.com/josephburnett/sonic-jam/tree/logui for this.  Got the server working (with a fork of osc which removes '*' from the invalid address characters *?) but it isn't quite working yet.


Bad ?arg=value requests still give data

For example, see the fetch_mmm_point_data() function in  taspr.py. The script checks for a ?summarize=mmm argument via if request.args.get("summarize") == "mmm": condition. However any typo in this argument (or any argument at all for that matter) will default this condition to return 'None' in which case the script moves to the else: condition and continues to execute.
For example, the endpoints below with bad arguments all return data, but should probably return an error instead to avoid confusion:
http://<IP_ADDRESS>:5001/temperature/65.0628/-146.1627/1940/2060?summarize=max
http://<IP_ADDRESS>:5001/temperature/65.0628/-146.1627/1940/2060?summarize=mmmm
http://<IP_ADDRESS>:5001/temperature/65.0628/-146.1627/1940/2060?summary=mmm
http://<IP_ADDRESS>:5001/temperature/65.0628/-146.1627/1940/2060?foo=bar
Consider using a zero-length argument dictionary check first, eg:
if len(request.args) == 0:        return "default endpoint"
then check for arguments explicitly, eg:
elif: "summarize" in request.args:           if request.args.get("summarize") == "mmm":                    summarize the data           else: throw an error

This issue was addressed in  #341 but only for the permafrost.py route. Consider explicit argument validation: either route-specific (as done in permafrost.py or as new API-wide function (see #339 ).

https://marshmallow.readthedocs.io/en/stable/

Affected endpoints:
https://earthmaps.io/degree_days/
https://earthmaps.io/hydrology/
https://earthmaps.io/snow/
https://earthmaps.io/taspr/


Added Merge sort(C++) and Bubble Sort(python)

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Fixes #{ISSUE_NUMBER}
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#147

@ubamba98 is this issue assigned to you?

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There was no issue related to the topics could you create one and assign it to me? Would really like to contribute to the project


i3lock-color: 2.7-2016-09-17 -> 2.8; Closes #24450

Motivation for this change
Update Closes: #24450
Things done

[x] Tested using sandboxing
(nix.useSandbox on NixOS,
or option build-use-sandbox in nix.conf
on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] Linux

[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

Crap didn't think about that will fix tomorrow
Sent from my iphone
On Mar 30, 2017, 9:10 PM -0500, Tim Steinbach<EMAIL_ADDRESS>wrote:

@NeQuissimus requested changes on this pull request.
In pkgs/applications/window-managers/i3/lock-color.nix (https://github.com/NixOS/nixpkgs/pull/24493#discussion_r109075795):

name = "i3lock-color-${version}"; - src = fetchFromGitHub {

Does this not turn this whole thing into a different piece of software?
Now you pull i3lock without the colour extensions from i3lock-color.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub (https://github.com/NixOS/nixpkgs/pull/24493#pullrequestreview-30154133), or mute the thread (https://github.com/notifications/unsubscribe-auth/AAHL7yCvQIVB79TkFa2arLDM1mjMLJ8vks5rrGB8gaJpZM4MvCOs).

@NeQuissimus done

AFAICT, there's no 2.8 release of i3lock-color. Better name it 2.7-2017-04-01 I suppose. Does it still compile with the updated deps?

It compiled just forgot to change version
Sent from my iphone
On Apr 1, 2017, 7:36 AM -0500, Yorick<EMAIL_ADDRESS>wrote:

AFAICT, there's no 2.8 release of i3lock-color. Better name it 2.7-2017-04-01 I suppose. Does it still compile with the updated deps?
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Fixed version; Sorry been half sleep lately from work


Pop out player outside of the app (new window)

We discussed this with the community on Discord at one point and it was brought up again as a feature request by a user. The idea would be that you can pop out the pop-out player to a new window. This would be useful in a multi-monitor setup or to make sure that the player is not interfering with app usage.

The player had a Picture-in-picture popout option that basically meets your requirements (you can still right click->pip), but it was removed from the player UI.
We could restore the PiP button but style and position it separately from the other UI elements if needed.
Regarding performance profiling though, the player users a webworker for decoding, and the remaining usage goes towards the UI (updating the DOM for the trackbar, current timestamp, etc).
I think just adding back a button for PiP would be the simplest, easiest option here.

The player had a Picture-in-picture popout option that basically meets your requirements (you can still right click->pip), but it was removed from the player UI.
We could restore the PiP button but style and position it separately from the other UI elements if needed.
Regarding performance profiling though, the player users a webworker for decoding, and the remaining usage goes towards the UI (updating the DOM for the trackbar, current timestamp, etc).
I think just adding back a button for PiP would be the simplest, easiest option here.

This feature was intended for the desktop app and having a popout as a new window of the electron application.

This feature was intended for the desktop app and having a popout as a new window of the electron application.

Is it possible in Electron to use a video overlay like in chromium with the built-in PiP functionality ?


Update stable version in repo from 0.3.0 to 0.4.0

Think about update stable version to 0.4.0
Version: stable=0.3.0 (60 days old) => latest=0.4.0 (30 days old)
Installs: stable=129 (55.84%), latest=55 (23.81%), total=231
Click to edit

This issue seems to be outdated.
This issue suggests to update the stable version of this adapter to 0.4.0 but the current stable version is already 0.4.0.
So this issue should be closed.


✨ Add our naming standards for workflow files to the README.md

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (4d428d5) 98.51% compared to head (77734ff) 98.51%.

Additional details and impacted files
@@           Coverage Diff           @@
##             main    #3995   +/-   ##
=======================================
  Coverage   98.51%   98.51%
=======================================
  Files          43       43
  Lines        4035     4035
=======================================
  Hits         3975     3975
  Misses         60       60

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:loudspeaker: Have feedback on the report? Share it here.


Fix case of no zero crossings for QBO metric computation

This fixes a special case in which there are no zero crossings for U(30hPa) ie there are no oscillations between positive and negative values for a given model in less than 12 months for wind speed around tropics.

@alistairsellar this special case does not change any of our previously reviewed results, but it has crept up only now in the example recipe since for MPI-ESM-LR there are no zero crossings when subsetting the QBO computation between the tropics (previously, before the review from July, there was no tropics subsettting, so the example recipe was completing fine) :beer:

Please fix the conflicts.
@alistairsellar can you please test it / give feedback?


Error with latest commit

Seems like you changed a bit to much when converting from CamelCase.
Some "logging.Functions" were also renamed...
Quick patch to fix it:
--- duallog.py  2020-03-03 21:19:26.102004804 +0100
+++ /usr/local/lib/python3.7/dist-packages/duallog/duallog.py   2020-03-03 19:55:26.844999139 +0100
@@ -68,15 +68,15 @@
     file_name = os.path.join(dir, file_name)

     # Set up logging to the logfile.
-    file_handler = logging.handlers.Rotatingfile_handler(
-        file_name=file_name, max_bytes=max_bytes, backup_count=backup_count)
+    file_handler = logging.handlers.RotatingFileHandler(
+        filename=file_name, maxBytes=max_bytes, backupCount=backup_count)
     file_handler.setLevel(logging.DEBUG)
     file_formatter = logging.Formatter(file_msg_format)
     file_handler.setFormatter(file_formatter)
     logger.addHandler(file_handler)

     # Set up logging to the console.
-    stream_handler = logging.stream_handler()
+    stream_handler = logging.StreamHandler()
     stream_handler.setLevel(minLevel)
     stream_formatter = logging.Formatter(console_msg_format)
     stream_handler.setFormatter(stream_formatter)

This fixes it for me.


Started on: making Loki plan trafo (pipeline) aware

Corresponding CLOUDSC branch: nams-cloudsc-loki-plan (necessary since CLOUDSC wasn't using loki_transform_target yet).

more or less just copied/utilised the infrastructure and mechanism for (dispatching) transformations and duplicated for planning
the only trafo that uses this for now is the FileWriteTransformation

consequently write_cmake_plan is not renaming the modules/routines anymore

Next step:

create new item (and/or delete existing item)

I've added cloudsc_init.F90  in the above CLOUDSC branch as well as a DuplicateKernel and RemoveKernel trafo to test that (obviously not working yet)

Out-dated and superseded due to/by #453.