FP16 not working with NHNet

I am able to run NHNet code with batch size 8 but the accuracy numbers are no way near to what are reported in the paper. So, I thought increasing the batch size might help. But due to GPU limitation, I am not able to do it. So I tried using Mixed Precision to train the model for larger batch. I tried the following 2 things:

Using tf.keras.mixed_precision.experimental.LossScaleOptimizer(opt,"dynamic")
But this gives the following error.
AttributeError: 'LossScaleOptimizer' object has no attribute '_hypers_created'

2.I also tried using:  tf.keras.mixed_precision.experimental.set_policy('mixed_float16')
But that gives this error:
TypeError: Tensors in list passed to 'inputs' of 'Einsum' Op have types [float16, float32] that don't all match.
System information

Used exact same code from NHNet repo
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
TensorFlow installed from (source or binary): tf-nightly==2.4.0.dev20200724
TensorFlow version (use command below): v1.12.1-31004-g203aa8b634 2.2.0-dev20200501
Python version: 3.7.7
CUDA/cuDNN version: 10.1/7
GPU model and memory: TITAN RTX 24GB

Describe the current behavior
As soon as epoch 1 starts the code throws error as mentioned before.
Describe the expected behavior
The training should happen.
Standalone code to reproduce the issue
Exact same code mentioned here: https://github.com/tensorflow/models/blob/master/official/nlp/nhnet/trainer.py
Just add one line after line no 146:
opt = tf.keras.mixed_precision.experimental.LossScaleOptimizer(opt,"dynamic")

You need some adaptation also for the train_step. See:
https://www.tensorflow.org/guide/mixed_precision?hl=en#training_the_model_with_a_custom_training_loop

The code actually uses model.fit and hence I didn't change anything. But I changed it now, but still its not helping.
My code looks like this:
class Trainer(tf.keras.Model):
  """A training only model."""

  def __init__(self, model, params):
    super(Trainer, self).__init__()
    self.model = model
    self.params = params
    self._num_replicas_in_sync = tf.distribute.get_strategy(
    ).num_replicas_in_sync

  def call(self, inputs, mode="train"):
    return self.model(inputs, mode)

  def train_step(self, inputs):
    """The logic for one training step."""
    with tf.GradientTape() as tape:
      logits, _, _ = self(inputs, mode="train", training=True)
      targets = models.remove_sos_from_seq(inputs["target_ids"],
                                           self.params.pad_token_id)
      loss = transformer_metrics.transformer_loss(logits, targets,
                                                  self.params.label_smoothing,
                                                  self.params.vocab_size)
      # Scales the loss, which results in using the average loss across all
      # of the replicas for backprop.
      scaled_loss = self.optimizer.get_scaled_loss(loss) / self._num_replicas_in_sync

    tvars = self.trainable_variables
    grads = self.optimizer.get_unscaled_gradients(tape.gradient(scaled_loss, tvars))
    self.optimizer.apply_gradients(list(zip(grads, tvars)))
    return {
        "training_loss": loss,
        "learning_rate": self.optimizer._decayed_lr(var_dtype=tf.float32)
    }

def train(params, strategy, dataset=None):
  """Runs training."""

  if not dataset:
    dataset = input_pipeline.get_input_dataset(
        FLAGS.train_file_pattern,
        FLAGS.train_batch_size,
        params,
        is_training=True,
        strategy=strategy)

  with strategy.scope():
    model = models.create_model(
        FLAGS.model_type, params, init_checkpoint=FLAGS.init_checkpoint)
    opt = tf.keras.optimizers.Adam(learning_rate=params.learning_rate)
    opt = tf.keras.mixed_precision.experimental.LossScaleOptimizer(opt,"dynamic")
    trainer = Trainer(model, params)
    model.global_step = opt.iterations

    trainer.compile(
        optimizer=opt,
        experimental_steps_per_execution=FLAGS.steps_per_loop)
    summary_dir = os.path.join(FLAGS.model_dir, "summaries")
    summary_callback = tf.keras.callbacks.TensorBoard(
        summary_dir, update_freq=max(100, FLAGS.steps_per_loop))
    checkpoint = tf.train.Checkpoint(model=model, optimizer=opt)
    checkpoint_manager = tf.train.CheckpointManager(
        checkpoint,
        directory=FLAGS.model_dir,
        max_to_keep=10,
        step_counter=model.global_step,
        checkpoint_interval=FLAGS.checkpoint_interval)
    if checkpoint_manager.restore_or_initialize():
      logging.info("Training restored from the checkpoints in: %s",
                   FLAGS.model_dir)
    checkpoint_callback = keras_utils.SimpleCheckpoint(checkpoint_manager)

  # Trains the model.
  steps_per_epoch = min(FLAGS.train_steps, FLAGS.checkpoint_interval)
  epochs = FLAGS.train_steps // steps_per_epoch
  history = trainer.fit(
      x=dataset,
      steps_per_epoch=steps_per_epoch,
      epochs=epochs,
      callbacks=[summary_callback, checkpoint_callback],
      verbose=2)
  train_hist = history.history
  # Gets final loss from training.
  stats = dict(training_loss=float(train_hist["training_loss"][-1]))
  return stats

This still gives the same error:  AttributeError: 'LossScaleOptimizer' object has no attribute '_hypers_created.
If I remove "learning_rate": self.optimizer._decayed_lr(var_dtype=tf.float32) in the return, it throws this error:
Traceback (most recent call last):
  File "trainer.py", line 237, in <module>
    app.run(main)
  File "/home/rishabh/.local/lib/python3.7/site-packages/absl/app.py", line 299, in run
    _run_main(main, args)
  File "/home/rishabh/.local/lib/python3.7/site-packages/absl/app.py", line 250, in _run_main
    sys.exit(main(argv))
  File "trainer.py", line 231, in main
    stats = run()
  File "trainer.py", line 210, in run
    stats = train(params, strategy)
  File "trainer.py", line 176, in train
    verbose=2)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 72, in _method_wrapper
    return method(self, *args, **kwargs)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 907, in fit
    tmp_logs = train_function(iterator)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 766, in __call__
    result = self._call(*args, **kwds)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 809, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 688, in _initialize
    *args, **kwds))
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 2902, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 3232, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 3121, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 981, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 595, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 964, in wrapper
    user_requested=True,
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 585, in converted_call
    return _fall_back_unconverted(f, args, kwargs, options, e)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 393, in _fall_back_unconverted
    return _call_unconverted(f, args, kwargs, options)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 343, in _call_unconverted
    return f(*args, **kwargs)
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 627, in train_function
    for _ in math_ops.range(self._steps_per_execution - 1):
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 552, in __iter__
    self._disallow_iteration()
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 545, in _disallow_iteration
    self._disallow_when_autograph_enabled("iterating over `tf.Tensor`")
  File "/home/rishabh/.conda/envs/condaenvNH/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 523, in _disallow_when_autograph_enabled
    " decorating it directly with @tf.function.".format(task))
tensorflow.python.framework.errors_impl.OperatorNotAllowedInGraphError: iterating over `tf.Tensor` is not allowed: AutoGraph did not convert this function. Try decorating it directly with @tf.function.

Also beyond this, I don't think FP16 will work directly as the NHNet model has many custom layers which are not getting converted. When I run the code I get following warnings:
W0917 14:16:15.056954<PHONE_NUMBER>65920 ag_logging.py:146] AutoGraph could not transform <bound method TransformerDecoder.call of <official.nlp.nhnet.decoder.TransformerDecoder object at 0x7f573c702350>> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: module 'gast' has no attribute 'Constant'
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
WARNING:tensorflow:AutoGraph could not transform <bound method TransformerDecoderLayer.call of <official.nlp.modeling.layers.transformer.TransformerDecoderLayer object at 0x7f573c67f750>> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: module 'gast' has no attribute 'Constant'
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
W0917 14:16:15.077228<PHONE_NUMBER>65920 ag_logging.py:146] AutoGraph could not transform <bound method TransformerDecoderLayer.call of <official.nlp.modeling.layers.transformer.TransformerDecoderLayer object at 0x7f573c67f750>> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: module 'gast' has no attribute 'Constant'
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
WARNING:tensorflow:AutoGraph could not transform <bound method CachedAttention.call of <official.nlp.modeling.layers.attention.CachedAttention object at 0x7f573c63ead0>> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: 'arguments' object has no attribute 'posonlyargs'
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
W0917 14:16:15.085375<PHONE_NUMBER>65920 ag_logging.py:146] AutoGraph could not transform <bound method CachedAttention.call of <official.nlp.modeling.layers.attention.CachedAttention object at 0x7f573c63ead0>> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: 'arguments' object has no attribute 'posonlyargs'
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
WARNING:tensorflow:AutoGraph could not transform <bound method MultiChannelAttention.call of <official.nlp.modeling.layers.multi_channel_attention.MultiChannelAttention object at 0x7f573c60af90>> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: 'arguments' object has no attribute 'posonlyargs'
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
W0917 14:16:15.138240<PHONE_NUMBER>65920 ag_logging.py:146] AutoGraph could not transform <bound method MultiChannelAttention.call of <official.nlp.modeling.layers.multi_channel_attention.MultiChannelAttention object at 0x7f573c60af90>> and will run it as-is.

@nlp-sudo
i see few issues with similar error, could you please refer to them if they are helpful.
#37144 #35101 link

I will handle the warning part later, that's not a big deal. It would be really helpful if you can help me out to solve the error:
AttributeError: 'LossScaleOptimizer' object has no attribute '_hypers_created.
I checked the optimizer code of keras too, it does have _hypers_created but I don't know why the error is occurring. And as I said, if I ignore the decaying of learning rate, the other error is coming. Solution to anyone of it would be really helpful.

Can you share a very, very minimal but complete runnable example or Colab (better) to reproduce this?

Also I see some explicit float32 in the model definition at https://github.com/tensorflow/models/blob/master/official/nlp/nhnet/models.py.
So probably it is better that you open a ticket directly in https://github.com/tensorflow/models/  repository

I thought the issue was related to FP16 in Keras and hence opened it here. No issues, I will open a issue in that repo. Thanks for help.

@nlp-sudo
PLease move the issue to closed status, once open in mentioned repo.

Opened an issue here: https://github.com/tensorflow/models/issues/9262
Closing this one.


added after column to borrel reservations

closes #346

probably you want a 'before' column too, because you might not always get what you reserved


[qtpositioning] devendor poly2tri

Devendor poly2tri from qtpositioning.

The patch is fairly large simply due to removal of files, and this part will be sensitive to souce changes. I would suggest to trim the patch and to do file removal as needed with cmake commands.

The patch is fairly large simply due to removal of files, and this part will be sensitive to souce changes. I would suggest to trim the patch and to do file removal as needed with cmake commands.

Good point. How could this be done?
The download happens in qt_install_submodule in the qtbase port.

Patch qt_install_submodule (already done for qttools / qtwebengine)
Reimplement qt_install_submodule in qtpositioning
Implement some sort of callback mechanism or a SRC_DIRECTORIES_TO_REMOVE param


Fixed build

(hopefully, at least)
closes #81

(I'll merge just to fix this, feel free to review either way)

Thanks @caarlos0!


WayPoint - Import A Google Font

Challenge http://www.freecodecamp.com/challenges/waypoint-import-a-google-font has an issue. Please describe how to reproduce it, and include links to screen shots if possible.
Allows you to pass the challenge if you input "Lobster" on the font-family attribute for h2 without making a call to google and inserting the link to the font.
Purr jump eat the grass rip the couch scratched sunbathe, shed everywhere rip the couch sleep in the sink fluffy fur catnip scratched.
![screen shot 2015-05-28 at 10 47 00 pm](https://cloud.githubusercontent.com/assets/6963932/7877184/7be8e778-058b-11e5-9513-7ca833935f97.png)

Thank you for pointing this out. I've hardened the test suite on this one.


ccx: Initialize LPUART2

Initialize LPUART2 on ccx board as per schematics.
Related to issue #54

LPUART2 needs to be enabled in menuconfig.


Prepare for dynamic solving in featureprofiles binding

Updates Ondatra to v0.5.3
Add new dynamic field to the binding proto
Add placeholder function for dynamic solving

Pull Request Functional Test Report for #2754 / 8f7de9ab08d50cd0ac454f7d08c82970d4c95bec
No tests identified for validation.
Help

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

1 of 6 (16.67%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.07%) to 53.035%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

topologies/binding/binding.go
1
6
16.67%

Totals

Change from base Build<PHONE_NUMBER>:
-0.07%

Covered Lines:
1730

Relevant Lines:
3262

💛  - Coveralls


Can't use external libraries in the code: "unable to find source related to xxxx"

I am trying to use Yaegi to run Golang code that contains 3rd party library called:
github.com/tidwall/pretty
You wrote here https://github.com/containous/yaegi/issues/469 that it is possible:

It's also possible to re-build an interpreter containing a pre-compiled library and its wrapper (generated by goexports), so the package can be imported without the overhead of interpretation, as it is done for the standard library packages in yaegi.

But I didn't understand how can I re-build the interpreter with a pre-compiled library?
Ho can I do it?
The following program sample.go triggers a panic:
package main

import (
	"github.com/containous/yaegi/interp"
	"github.com/containous/yaegi/stdlib"
)

const payload = `
package main

import (
	"fmt"
	"github.com/tidwall/pretty"
)

func main(){
	var example2 = "{\"name\": \"hello\"}"
	result := pretty.Pretty([]byte(example2))
	fmt.Println(string(result))
}
`

func main(){

	i := interp.New(interp.Options{})
	i.Use(stdlib.Symbols)

	_, err := i.Eval(payload)
	if err != nil {
		panic(err)
	}
}

Expected result:
{
  "name": "hello"
}

Got:
panic: 6:2: import "github.com/tidwall/pretty" error: unable to find source related to: "github.com/tidwall/pretty"

goroutine 1 [running]:
main.main()
	C:/Users/myuser/go/src/myGoProject/cmd/yaegi_check/check.go:42 +0xbf

I tried to add the external library like your wrote:
_ "github.com/tidwall/pretty"

To:
https://github.com/containous/yaegi/blob/5d56bac8d0183baa5dcf2565605a72680dc652e8/interp/run.go#L5-L9
But I received the same error.

I tried to add the external library as you wrote:
_ "github.com/tidwall/pretty"

To:
https://github.com/containous/yaegi/blob/5d56bac8d0183baa5dcf2565605a72680dc652e8/interp/run.go#L5-L9
But I received the same error.

I am trying to use Yaegi to run Golang code that contains 3rd party library called:
github.com/tidwall/pretty
You wrote here #469 that it is possible:

It's also possible to re-build an interpreter containing a pre-compiled library and its wrapper (generated by goexports), so the package can be imported without the overhead of interpretation, as it is done for the standard library packages in yaegi.

But I didn't understand how can I re-build the interpreter with a pre-compiled library?
Ho can I do it?

The tooling for pre-compiling only works for shipping the standard library for now, and not for third-party libraries yet. Support for third-party libraries is on the roadmap in the short to mid term.

The following program sample.go triggers a panic:
package main

import (
	"github.com/containous/yaegi/interp"
	"github.com/containous/yaegi/stdlib"
)

const payload = `
package main

import (
	"fmt"
	"github.com/tidwall/pretty"

	"log"
	"os/exec"
)

func main(){
	var example2 = "{\"name\": \"hello\"}"
	result := pretty.Pretty([]byte(example2))
	fmt.Println(string(result))
}
`

func main(){

	i := interp.New(interp.Options{})
	i.Use(stdlib.Symbols)

	_, err := i.Eval(payload)
	if err != nil {
		panic(err)
	}
}

Expected result:
{
  "name": "hello"
}

Got:
panic: 6:2: import "github.com/tidwall/pretty" error: unable to find source related to: "github.com/tidwall/pretty"

goroutine 1 [running]:
main.main()
	C:/Users/myuser/go/src/myGoProject/cmd/yaegi_check/check.go:42 +0xbf

You are probably getting that error because yaegi does not support go modules yet. Do you still get the error if you make sure to have "github.com/tidwall/pretty" in your GOPATH (or vendored in) ?

I checked,
My GOATPH is:
GOPATH=C:\Users\user1\go

github.com/tidwall/pretty is inside C:\Users\user1\go \src.
I created a vendor folder and copy & paste the github.com/tidwall/pretty folder to the vendor folder and called it as is: github.com/tidwall/pretty.
But I received the same error:
panic: 6:2: import "github.com/tidwall/pretty" error: unable to find source related to: "github.com/tidwall/pretty"

So currently yaegi doesn't support external libraries?
Is there some workaround for that?

In this link  @mvertes wrote:
It's also possible to re-build an interpreter containing a pre-compiled library and its wrapper (generated by goexports), so the package can be imported without the overhead of interpretation, as it is done for the standard library packages in yaegi.
But I am not sure how to do it.
I run goexports but it failed:
C:\Users\user1\go\src\gosploit>goexports github.com/tidwall/pretty
2020/06/01 18:20:16 failed to format source: 7:10: expected ';', found ':' (and 3 more errors): // Code generated by 'goexports github.com/tidwall/pretty'. DO NOT EDIT.

// +build go1.13,!go1.14

package C:\Users\user1\go\src\myproj1

import (
        "github.com/tidwall/pretty"
        "reflect"
)

func init() {
        Symbols["github.com/tidwall/pretty"] = map[string]reflect.Value{
                // function, constant and variable definitions
                "Color": reflect.ValueOf(pretty.Color),
                        "DefaultOptions": reflect.ValueOf(&pretty.DefaultOptions).Elem(),
                        "Pretty": reflect.ValueOf(pretty.Pretty),
                        "PrettyOptions": reflect.ValueOf(pretty.PrettyOptions),
                        "TerminalStyle": reflect.ValueOf(&pretty.TerminalStyle).Elem(),
                        "Ugly": reflect.ValueOf(pretty.Ugly),
                        "UglyInPlace": reflect.ValueOf(pretty.UglyInPlace),

                // type definitions
                "Options": reflect.ValueOf((*pretty.Options)(nil)),
                "Style": reflect.ValueOf((*pretty.Style)(nil)),

        }
}

?

@g3rzi yaegi is unsupported and untested on windows, so you might be running into a problem just because you're on windows, and we cannot help you debug that.
However, if you retry on another supported platform and you see the same problem, then we might be able to help.

I download the same code to my Ubuntu 16.04.3 LTS:
package main

import (
	"github.com/containous/yaegi/interp"
	"github.com/containous/yaegi/stdlib"
)

const payload = `
package main

import (
	"fmt"
	"github.com/tidwall/pretty"
)

func main(){
	var example2 = "{\"name\": \"hello\"}"
	result := pretty.Pretty([]byte(example2))
	fmt.Println(string(result))
}
`

func main(){

	i := interp.New(interp.Options{})
	i.Use(stdlib.Symbols)

	_, err := i.Eval(payload)
	if err != nil {
		panic(err)
	}
}

I go the following error:
GOROOT=/usr/local/go #gosetup
GOPATH=/home/jiren/go #gosetup
/usr/local/go/bin/go build -o /tmp/___go_build_check_go /home/jiren/go/src/gosploit/cmd/yaegi_check/check.go #gosetup
/tmp/___go_build_check_go #gosetup
panic: 6:2: import "github.com/tidwall/pretty" error: unable to find source related to: "github.com/tidwall/pretty"

goroutine 1 [running]:
main.main()
/home/jiren/go/src/gosploit/cmd/yaegi_check/check.go:68 +0xfe

Process finished with exit code 2

Expected:
GOROOT=/usr/local/go #gosetup
GOPATH=/home/jiren/go #gosetup
/usr/local/go/bin/go build -o /tmp/___go_build_payload1_go__2_ /home/jiren/go/src/gosploit/cmd/payload1/payload1.go #gosetup
/tmp/___go_build_payload1_go__2_ #gosetup
{
"name": "hello"
}

You need to specify the GOPATH through the options of the interpreter:
	i := interp.New(interp.Options{
		GoPath: "/home/jiren/go",
	})

Any update here ? More than a year from the last comment but nothing seems available to fix this !
@mpl

any update? go mod still do not support?

no response after a long time.

go mod init xxx
go get .
go mod vendor
copy package folder (under vendor folder) to $GOPATH/src
yaegi run ./sample.go

it's ok


Confusing error when paths fed to builder are empty

This is thrown
Execution error (NullPointerException) at nextjournal.clerk.builder/build-static-app! (builder.clj:284).
Cannot invoke "clojure.lang.IFn.invoke(Object)" because "report_fn" is null

when calling (builder/build-static-app! {:paths ["foo/**/*.clj"]}) against an empty glob "foo/**/*.clj", also reproducible with (builder/build-static-app! {:paths []}).

Possibly related: if I pass :paths with a single path — if the options map contains only :paths that works more or less fine. But if I also specify :index then I get the same NPE.
As discussed in Clojurians

Can reproduce the problem @aviflat described in :mvn/version "0.12.707". If I understand the code correctly, the problem is that the build-static-app! function, which extracts :keys and then calls process-build-opts which sets the :report-fn.
(let [{:as opts :keys [download-cache-fn upload-cache-fn report-fn compile-css? expanded-paths error]}
        (try (process-build-opts (assoc opts :expand-paths? true))
             (catch Exception e
               {:error e}))

I am not sure how empty paths fix relate to this though.

My previous comment is wrong. I failed to read the let binding correctly. I am still investigating the NPE.

Ok, I got it.
process-build-opts threw an error, never setting report-fn at all.  Root cause was:
`:index` must be string and point to existing file`.

No reason to reopen that, sorry for the noise.


fix: teleport to, improve teleport to popup and fix backpack avatar preview region

Fix #312
addionaly, fix a avatar preview back overflowing when you were in the main menu (the discover button was not 100% clickable)

Codecov Report
Attention: Patch coverage is 0% with 4 lines in your changes are missing coverage. Please review.

Project coverage is 49.10%. Comparing base (028f1f5) to head (d800aa5).

Files
Patch %
Lines

...dot-lib/src/scene_runner/global_get_node_helper.rs
0.00%
3 Missing :warning:

...-godot-lib/src/godot_classes/dcl_confirm_dialog.rs
0.00%
1 Missing :warning:

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #313      +/-   ##
==========================================
+ Coverage   49.05%   49.10%   +0.04%
==========================================
  Files         155      155
  Lines       19042    19042
==========================================
+ Hits         9342     9350       +8
+ Misses       9700     9692       -8

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


vdk-pipelines-control-service: don't include needless service token.

Why?
We don't need the token so we shouldn't include it by default
What?
Set the property so the token is not included
How has this been tested?
Integration and unit tests are passing
Signed-off-by: murphp15<EMAIL_ADDRESS>

That is also very useful and it's a security improvement at no cost. (see https://cheatsheetseries.owasp.org/cheatsheets/Kubernetes_Security_Cheat_Sheet.html - "Do not mount the service account credentials in a container if it does not need to access the Kubernetes API.")
So I urge you to finish it and push it. We should do this (preferably separate PR) also for data job started pods.

I have recommended some talks on a conference I was here - relevant one for this PR is https://youtu.be/jRrCi1IS7gk?t=14313 (Hardening against Kubernetes Hacks) You can see how this vulnerability (among others) is being exploited . It's very fun talk and very educative about how Kubernetes works

This property has been added to one of our internal deployments without any issues.


Show Dev Spent column on Treasury Admin report

Hide Dev Spent column on Decentralized and Admin report. Only show on Combined report

https://github.com/chaineco/blockcare/commit/b39d356e7c4e1d8291a561b362fd3f8468db6975


Fix #85: Wrong items alphabetical ordering in server/database view

Fix #85
Does sort when parent node is 'Folder'

@llali can you look at this? I wonder if the right fix is here or in the backend. I also want to make sure that for a large number of objects this scales as expected.

@jeffest thanks for your fix but this bug should be fixed in the service so it can be applied to all objects and all clients.

@llali thanks for letting us know but the credit for this fix must goes to @AlexTroshkin ! :)
I wish I could be able to write it though. Even in the "wrong" place ! :)

As Leila has a separate fix in the tools service, I'm going to close this PR. Thank you for submitting it and please continue to send in PRs when you see issues!


[Test] Update images.yaml for druid

How to categorize this PR?

/area TODO
/kind TODO
What this PR does / why we need it:
Which issue(s) this PR fixes:
Fixes #
Special notes for your reviewer:
Release note:

/retest

Why don't you perform these e2e tests in the etcd-druid repo directly like other "extensions"?

Okay. Will keep it in mind and it won't happen from the next time. Thank you.


Going to a new route directly doesn't update tabbar 'active' tab.

To test, go to peers on your profile. Then go to one of your peers pages by clicking the link. This won't update the tabbar's 'active' tab. I'm working on a pr to fix this.

is this fixed @mike-robertson ?

There is still an issue with tabs if you are linked to a route. SO if you go to peers, click on one of the links, it won't swap the active tab to overview even though it is showing overview and is on the overview route. This is because of a bug in material-ui tabs which I have put a PR in for but haven't gotten any response yet.

if you try to load an overview with no tab name:
https://ui.yasp.co/players/88367253
The overview tab will not be selected.

@mike-robertson I believe this was fixed with #188 and the new routing code.


Gradio/Local Tunnel Error

ERROR:root:Internal Python error in the inspect module.
Below is the traceback from this internal error.
Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/IPython/core/interactiveshell.py", line 3326, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 22, in
get_ipython().run_line_magic('cd', '/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/')
File "/usr/local/lib/python3.9/dist-packages/IPython/core/interactiveshell.py", line 2314, in run_line_magic
result = fn(*args, **kwargs)
File "", line 2, in cd
File "/usr/local/lib/python3.9/dist-packages/IPython/core/magic.py", line 187, in
call = lambda f, *a, **k: f(*a, **k)
File "/usr/local/lib/python3.9/dist-packages/IPython/core/magics/osm.py", line 334, in cd
oldcwd = os.getcwd()
OSError: [Errno 107] Transport endpoint is not connected
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/IPython/core/interactiveshell.py", line 2040, in showtraceback
stb = value.render_traceback()
AttributeError: 'OSError' object has no attribute 'render_traceback'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/IPython/core/ultratb.py", line 1101, in get_records
return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)
File "/usr/local/lib/python3.9/dist-packages/IPython/core/ultratb.py", line 319, in wrapped
return f(*args, **kwargs)
File "/usr/local/lib/python3.9/dist-packages/IPython/core/ultratb.py", line 353, in _fixed_getinnerframes
records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))
File "/usr/lib/python3.9/inspect.py", line 1543, in getinnerframes
frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)
File "/usr/lib/python3.9/inspect.py", line 1501, in getframeinfo
filename = getsourcefile(frame) or getfile(frame)
File "/usr/lib/python3.9/inspect.py", line 709, in getsourcefile
if getattr(getmodule(object, filename), 'loader', None) is not None:
File "/usr/lib/python3.9/inspect.py", line 738, in getmodule
file = getabsfile(object, _filename)
File "/usr/lib/python3.9/inspect.py", line 722, in getabsfile
return os.path.normcase(os.path.abspath(_filename))
File "/usr/lib/python3.9/posixpath.py", line 380, in abspath
cwd = os.getcwd()
OSError: [Errno 107] Transport endpoint is not connected
This is in the UI notebook.

You can use this: https://github.com/jnyfil/sd-webui-localtunnel-client

disconnecting the runtime and reconnecting generally resolves the issue


Implement assert_scalar_eq!

This PR provides an implementation of a assert_scalar_eq! macro which works analogously to assert_matrix_eq! and assert_vector_eq!.
Currently, we have a bunch of tests for scalars that look roughly like this:
let det = lu.det();
let expected_det = 3.0;
let diff = det - expected_det;
assert!(diff.abs() < 1e-6);

This is less than ideal for several reasons. For one, if the test fails, the test does not report what caused it to fail. Moreover, the lack of a standardized procedure means that the requirements are often arbitrary. The macro provided in this PR lets us instead do
assert_scalar_eq!(lu.det(), 3.0, comp = float);

Here we use the float comparator, which provides reasonable defaults, and the tolerance used (ULP and absolute epsilon value) can be tweaked if necessary. Of course, the other comparators (exact, abs and ulp) are also available.
EDIT: This addresses one of the points mentioned in #95.

Looks good to me!
From what I can see this PR does not address areas of the PR where we want to use this new macro. I think we should spin this out as a new issue (tagged easy) and hopefully somebody else picks it up! :)

@AtheMathmo: I agree with the point about documentation. I will change this.

OK, I added some very brief notes on where to find details about floating-point comparison issues and how to resolve them with the assert_matrix/vector/scalar_eq macros. I guess that should do it?

Look good to me. Merging now and will open a new issue for using these macros.


download files to install with docker-compose

instead of using the embeded files, it downloads
the latest docker compose and envoy config files
from github master branch

awesome. feel like updating the gloo docs with some install instructions for docker compose? :laughing:


修正了DMLLoss和DistillationModel中的错误

 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.


Implement mmap

We'll need to implement this in SafePOSIX to get to the goal of a fully userspace implementation. This may be done alongside  #18 but I believe that issue isn't blocking.
There is a Python version of mmap here that should be useful.
Proposed steps

Get memory location in NaCl and check bounds
Pass ptr to Repy, use python mmap to map fd to memory location
We'll need to get the actual fd (not SafePOSIX) using the fileobj
Need to find a way to set memory location with Python's mmap (perhaps using ctypes? )
For now, we'll let flags fall through to the kernel.

About that python mmap implementation, first of all it's in a library which is a no-go for RePy, second of all it seems to be a very thin wrapper around the mmap syscall such that I'm not sure it would add security over just doing it in C. I looked into it a little bit here if you want.

We may add an API to Repy for Lind that takes a filelikeobject from Repy,
the relevant flags, etc. and does mmap.  This will either need to call
native code from your C routine or use the Python mmap library.
The reason to move this all to repy is that it simplifies the file
descriptor tracking, etc. immensely...
On Tue, Sep 10, 2019 at 10:19 AM jesings<EMAIL_ADDRESS>wrote:

About that python mmap implementation, first of all it's in a library
which is a no-go for RePy, second of all it seems to be a very thin wrapper
around the mmap syscall such that I'm not sure it would add security over
just doing it in C. I looked into it a little bit here
https://github.com/python/cpython/blob/master/Modules/mmapmodule.c if
you want.
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per Slack discussion, @jesings is going to examine how this works with Repy and I will hook in the NaCl side.

I would just like to clarify that this will not require any of the security concerns of the rest of safeposix, rather it will just potentially check that the arguments are of correct form and call the python mmap. Is this correct?

In addition do you have any input on how to call mmap from within repy if direct importation of libraries is not an option?

I think that this repyportability file was used to port outside libraries? But I'm not exactly sure, perhaps @JustinCappos can shed some light here.

This is used to let Repy code (like a repy library) being called from
Python.  It's probably not that relevant for Lind.
On Tue, Sep 17, 2019 at 12:44 PM Nicholas Renner<EMAIL_ADDRESS>wrote:

I think that this repyportability file
https://github.com/Lind-Project/nacl_repy/blob/master/portability/repyportability.py
was used to port outside libraries? But I'm not exactly sure, perhaps
@JustinCappos https://github.com/JustinCappos can shed some light here.
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@jesings you can either quickly monkeypatch mmap in here which should be good to start. The more accepted way to interface is here if you want to try that out.

From my research into how to implement this, I understand now how to get a C pointer from the python mmap object (although how that will interface with NaCl I'm not sure. The problem is use of this pointer renders the mmap object unusable and unclosable (without errors), even if the pointer is deleted. This stackoverflow post lays it out. In addition, I'm not sure whether or not we need to store a reference to mmap to save it from the garbage collector and/or to recover from the invalid state we set it to by using the c pointer? If so, I was thinking that it could be metadata on that file descriptor, and have a custom destructor if we needed it.

My reading of the issue and thinking about why Python would do this leads
me to believe that they don't want data structures that are needed by the
garbage collector to be mmaped away.  Since we're only mapping memory that
will not contain Python objects (it is in the guest cages), this shouldn't
be a problem for us.
On Thu, Dec 19, 2019 at 12:27 PM jesings<EMAIL_ADDRESS>wrote:

From my research into how to implement this, I understand now how to get a
C pointer from the python mmap object (although how that will interface
with NaCl I'm not sure. The problem is use of this pointer renders the mmap
object unusable and unclosable (without errors), even if the pointer is
deleted. This stackoverflow post
https://stackoverflow.com/questions/53339931/properly-discarding-ctypes-pointers-to-mmap-memory-in-python
lays it out. In addition, I'm not sure whether or not we need to store a
reference to mmap to save it from the garbage collector and/or to recover
from the invalid state we set it to by using the c pointer? If so, I was
thinking that it could be metadata on that file descriptor, and have a
custom destructor if we needed it.
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Something I'm also noticing is that we're going to need to specify a starting address to mmap (the parameter void *addr from the manpage). The plan is to get a safe starting address from NaCl and send it to SafePOSIX to map there.
It seems though you can specify this starting address for the system call, the Python implementation hides that ability from us? We may need to hack into that.

If the python interface isn't quite what you need, there is always more directly making calls to the OS interface with ctypes.  We use that a fair amount in the repy sandbox already...

Nice, this ones finally done!


TypeError: Cannot read property 'OAuth2' of undefined

I am following this tutorial: https://developers.google.com/sheets/api/quickstart/nodejs
I copied and pasted the sample code with no changes but am getting this error when I run it:
const OAuth2Client = google.auth.OAuth2();
^
TypeError: Cannot read property 'OAuth2' of undefined
at Object. (/Users/pebbles/Documents/GitHub/KnockoutTutorial/quickstart.js:4:34)
at Module._compile (module.js:652:30)
at Object.Module._extensions..js (module.js:663:10)
at Module.load (module.js:565:32)
at tryModuleLoad (module.js:505:12)
at Function.Module._load (module.js:497:3)
at Function.Module.runMain (module.js:693:10)
at startup (bootstrap_node.js:188:16)
at bootstrap_node.js:609:3
I am very new and have no idea what I'm doing; I'm just doing my best to follow instructions and learn as I go.  I'm filing this issue based on @JustinBeckwith's comments here because I think I'm having the same problem as AkshayaSaravanann and don't see that any new issue was filed: https://github.com/google/google-auth-library-nodejs/issues/251

Instead of this line:
const OAuth2Client = google.auth.OAuth2();
I tried using the following:
const { OAuth2Client } = require('google-auth-library');
(I got this from nagyzsolthun's comment on Issue #251)
It successfully gave me the url to get the code to enter.  When I entered the code, I got these warnings:
(node:2477) UnhandledPromiseRejectionWarning: TypeError: google.sheets is not a function
at listMajors (/Users/pebbles/Documents/GitHub/KnockoutTutorial/quickstart.js:90:25)
at oAuth2Client.getToken (/Users/pebbles/Documents/GitHub/KnockoutTutorial/quickstart.js:72:23)
at /Users/pebbles/Documents/GitHub/KnockoutTutorial/node_modules/google-auth-library/build/src/auth/oauth2client.js:148:46
at
at process._tickCallback (internal/process/next_tick.js:188:7)
(node:2477) UnhandledPromiseRejectionWarning: Unhandled promise rejection. This error originated either by throwing inside of an async function without a catch block, or by rejecting a promise which was not handled with .catch(). (rejection id: 1)
(node:2477) [DEP0018] DeprecationWarning: Unhandled promise rejections are deprecated. In the future, promise rejections that are not handled will terminate the Node.js process with a non-zero exit code.

I added brackets and now it works!
const { google } = require('googleapis');
instead of
const google = require('googleapis');
I got the idea from this thread:
https://stackoverflow.com/questions/48816324/gmail-api-quickstart-failing-at-google-gmailv1
Now to research what those brackets did and why it fixed things!

Greetings!  And apologies for the trouble.  That doc looks to still be out of date.  In v25, we made a breaking change that switched the syntax of the import statement from this:
const google = require('googleapis');

To this....
const {google} = require('googleapis');

This is what's called a destructuring assignment.  It's functionally equivalent to saying:
const google = require('googleapis').google;

We made this change as we moved towards es module style syntax, which made it A LOT easier for us to support TypeScript.
Again - I apologize that our doc wasn't up to date.  Hopefully this explains a little about the differences, and why we made the change :)

this is what helped me:
const OAuth2Client = google.google.auth.OAuth2;


fluentd out_file created  time is not the same  with system time

fluentd or td-agent version: 3.2.0
Environment information: centos 6.7
cat /etc/td-agent/td-agent.conf
<source>
  @type forward
  port 24224
  bind <IP_ADDRESS>
</source>

<match accessLog-1100000221>
  @type file
  path /mnt/1100000221/30000/adms-service-access-%Y-%m-%d-%H-%M
  append true
  <format>
    @type single_value
  </format>
  <buffer time>
    @type file
    flush_mode interval
    flush_interval 5s
    timekey 1m
  </buffer>
</match>

The problem:

The  time out file created does not  match the system time of server.

yes. in_forward respects the original time like this. this means if there is time parameter in message in_forward receives, in_forward uses it and the value is sure to be diffirent from system time.
BTW, please follow the contribution guide next time. https://github.com/fluent/fluentd/blob/master/CONTRIBUTING.md#got-a-question-or-problem


article headline not in sync with article preview

this popped up with the recent update, 2.23.1
in a vertical 3-pane layout, the headline in the center column may not display the correct preview in the right-side column
in the screen-cap, the headline that is focused (black background) is displaying the text from the headline above - also the title and other metadata is missing
for every article headline clicked below the point where the problem starts to occur, the text in the preview pane never changes
reference: Naval Inspector General Complaint about UFOs/UAPs/Aliens and Much More – January 2020
feed address: https://www.theblackvault.com/documentarchive/feed/

downgrading the add-on to 2.0.33 doesn't fix this issue

I can't reproduce this, does the issue persist after restarting the browser?

yes

Hi, I'm having the same issue since last update with a different feed: ArsTechnica
Seems that enabling Open media preview automatically: triggers this issue.


chore: update LICENSE

Description
Just updates LICENSE file.
Additional context

What is the purpose of this pull request?

[ ] Bug fix
[ ] New Feature
[ ] Documentation update
[x] Other

Before submitting the PR, please make sure you do the following

[x] Read the Contributing Guidelines.
[x] Read the Pull Request Guidelines and follow the Commit Convention.
[x] Check that there isn't already a PR that solves the problem the same way to avoid creating a duplicate.
[x] Provide a description in this PR that addresses what the PR is solving, or reference the issue that it solves (e.g. fixes #123).
[ ] Ideally, include relevant tests that fail without this PR but pass with it.

Closing as other PRs updated the LICENSE file.


check for accounting column when throwing "Number of rows" error in r…

The remove_rows method in transition.py checks if the rows to remove greater than current number of rows, and throws an error if this test fails. When using accounting columns, the parameter nrows does not represent the number of rows to remove, but difference in value in the accounting column. Therefore the test must first check if accounting column exists, and if it does check if if nrows > data[accounting_column].sum()

Coverage decreased (-0.04%) to 94.296% when pulling 26e08b8a87507f27d572cf9f7c717cdfeb11058d on apdjustino:fix-accounting-column into 24970393b117cbf2464eeb336f425cbfb641fa1b on UDST:master.

Thanks @apdjustino!   See my comment above about unit_check already taking into account the different things nrows could represent.  Am I missing something?

Hi @janowicz, it looks like I was using a slightly older version of UrbanSim when I posted this pull request. You are right, it is already accounted for.


Issue for PR 4304 to fix some doc paths

A few urls to Platforms.md and CodeSigning.md are missing the master/fastlane/docs fastlane bit.  PR #4304

Thanks @jschoolcraft! We really appreciate you working to help us 👍 Hope you have a great weekend!


Valve settings with values less than zero are considered invalid

The following lines of code appear to prevent any valve from having a setting value that is less than 0.0. https://github.com/OpenWaterAnalytics/EPANET/blob/9707075a5a8ad661c2880e108d69551a725aafcf/src/epanet.c#L3888-L3889
Pressures in Epanet appear to all be gauge pressures because a tank with 2 metres of water inside it is evaluated to have 2 m of pressure at the node. In the standalone version of Epanet, valves can have negative settings without issue and I have used PRVs to model a process that brings the pressure bellow atmospheric (i.e. less than 0 metres of pressure).
There doesn't appear to be a field for inputting what atmospheric pressure is in the standalone Epanet either but shouldn't the actual lower bound for pressure related valves be vacuum (approx. -10 m)? Standalone Epanet also only seems to complain about negative pressures if they are on a demand node and seemingly allows pressures that are bellow a vacuum.
This is causing issues for me when interfacing with Epanet through the Epanet-Matlab-Toolkit because the .inp file will have PRVs with settings less than 0. Hydraulic analysis will execute without issue. An error will only be thrown if the original valve setting is attempted to be reapplied (this is necessary if the valve is opened or closed and needs to be reactivated).

I submitted a PR that will allow one to specify a negative pressure setting for a PRV using the Toolkit, so that it maintains consistency with the way an input file is processed. I can't say how soon this update will make it into the Matlab library. In the meantime would it be possible to lower the elevation of the PRV node by the amount of the negative setting so that a setting of 0 could be used instead?


Suggest a physics engine that can replace the old CollisionSystem

:bulb: Idea:
We would like to replace the old CollisionSystem, that is no longer used for interacting with nodes, with a physics engine for motion and collision detection.
:wrench: Tasks:

Suggest a physics engine for Android (an overview of different physics engines will be great too).
Propose a way to add it to Sceneview as an optional plugin (adding as little code as possible to the main sceneview module and creating a new sceneview-physics module or repository that implements synchronization of nodes state between Sceneview and the physics engine).
Write your findings in this issue! :rocket:

A quick search on Google brought me to Bullet Physics. Seem to be very popular since many years. The 3D-Engine libgdx has a JNI Wrapper for the 3D-Physics part of Bullet (https://libgdx.com/wiki/extensions/physics/bullet/bullet-physics).


Reflection: prevent address truncation on ELF64

Ensure that we use the address type as specified by ELF rather than
truncate to a 32-bit value.

Replace this paragraph with a description of your changes and rationale. Provide links to external references/discussions if appropriate.

Resolves SR-NNNN.

CC: @drodriguez @dcci

@swift-ci please test and merge


fix: make page wrapper take full height

Motivation
Fixes #7018, broken as result changes in https://github.com/facebook/docusaurus/pull/6925/files#diff-efc286976b85125e3056044ed1ef259e5794477ab266e4c6207a68d795f76b4a
Note: this bug will be noticeable if the content area column on the right is smaller by height than the sidebar.
I had to add back the docs-wrapper class as it was before, since I guess that's the only available way to make things work.
Have you read the Contributing Guidelines on pull requests?
Yes
Test Plan
Create empty Markdown page or via dev tools try to empty content area on any existent page -- the sidebar should be stretched to the footer.
Related PRs

I agree with you, it's even more strange to see the class containing of "wrapper" added to the root element of a page. Such classes have no place in the html element, and so they should be removed from there later. For now, I have changed the original fix to keep better consistent with #6925.

Thanks, I think we can move forward from here


spec: remove lingering "fulfills" reference

h/t to @cdaylward for pointing this out
Missed in https://github.com/appc/spec/pull/143/files

LGTM


Build a fully contained static binary

This reduces the container image from around 60-70mb to just under 10mb.
The image is also "distroless" meaning it has no binaries or utilities other than what is needed. Currently this is tzdata, ca-certificates, user/group files, and the dims binary.

6.77MB arm64 compressed image
https://hub.docker.com/layers/beetlebugorg/go-dims/edge/images/sha256-acaae13e8718077b37158c6a2ed515e15b0525653989d9f8142f1f9bdcbb7cf7?context=explore


engine: start streaming pod log at tthe tilt start time. fixes issue #2263

Hello @jazzdan,
Please review the following commits I made in branch nicks/issue2263:
d2399277ea96dbf89abfc608abd168c36ee9235c (2019-10-01 14:47:01 -0400)
engine: start streaming pod log at tthe tilt start time. fixes issue #2263

using this in practice, i'm not sure this is what we want. it's just kind of mysterious might need some way to log "attached to existing pod, here are the last N log lines"


Remove deprecated queue depth code

The UI was ported from queue depth to job load, so we can remove this code now.

Closed due to being merged into master


Does angrop support PE files?

Question:
Does this framework work on PE binaries as well?

It does!

When trying to execute the func_call function on a PE executable I get the following error:
@ltfish
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/the-sage/.local/lib/python2.7/site-packages/angrop/chain_builder.py", line 444, in func_call
    if address in self.project.loader.main_object.plt:
AttributeError: 'PE' object has no attribute 'plt'

Help?

Fish lied to you, it does not support PE. This is only a hiccup though
since almost all of angr is totally platform and architecture agnostic so
you just need to tweak the parts that access Linux-specific features (such
as the PLT) to not do that on windows, and it should be fine.
There’s also the problem that there’s a lot of built in logic to do things
like perform Linux syscalls, but as long as you don’t use those features
you’ll be fine.
On Wed, Jun 27, 2018 at 10:36 PM mbhatt1<EMAIL_ADDRESS>wrote:

When trying to execute the func_call function on a PE executable I get the
following error:
@ltfish https://github.com/ltfish
Traceback (most recent call last):
File "", line 1, in
File "/home/the-sage/.local/lib/python2.7/site-packages/angrop/chain_builder.py", line 444, in func_call
if address in self.project.loader.main_object.plt:
AttributeError: 'PE' object has no attribute 'plt'
Help?
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You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
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.

Right - it does not support PE, but it's not because there is anything fundamentally different between PE and ELF. We just never developed or tested angrop on PE files. You can tweak things and change code so that it will work on PEs.

pants on fire then? :'(

Do yall know of a ROP generator that works for PE yet? I need to do sth quickly

I will push the fix that make angrop work on windows if you acknowledge how tasteless that comment was
(I have not tested these changes extensively but the write_to_mem command seems to be producing sane results)

I acknowledge that I have a weird sense of humor yes. Also that angr and angrop both are awesome sauce! Lol

:roll_eyes:
open source isn't a candy shop. we have lives and obligations and can't fix all your problems and CERTAINLY can't be your technical advisors. If you had spent about 10 seconds looking into this problem yourself you would have figured out you could work around it by passing in an address instead of a symbol name. Enjoy your fix, and perhaps be a little more less flippant toward the people you're apparently depending on in the future.

I didn't mean to. Sorry. I am new to ROP and this seemed the easiest way of doing something quickly. Heartfelt apologies. :)

Thank you so much


Odp changes gc

@rmstar @tivv @itsankit-google Please review

Why are SAP plugin related tests added in google-cloud repo?


Pass values to date-input when using default items

At the moment there is no way to pass values (or field-level error states/CSS classes) to the date-input when using the default item set. This means you have to redefine the items param, including CSS classes for widths, whenever the date-input is used. This encourages repeated code and is arguably more prone to error.
Is it worth having a values param and an errors param on date-input? This could fall back to values/errors passed via the items param for backward compatibility, but favouring the new items/errors props.
e.g.
{{ govukDateInput({
  id: "dob",
  namePrefix: "dob",
  values: {
    day: 4,
    month: 5,
    year: 20t19
  },
  errorMessage: 'Please enter a valid year',
  errors: {
    year: true
  }
}) }}

I don't have an immediate need for this but it's something I noticed and thought worth suggesting in case others agree.

I just faced this issue too (when using the Prototyping Kit). It's a requirement when implementing the "Check your answers" pattern, as that allows people to go back and edit their dates, so you need to be able to set the values from their previous answer.

Just faced this issue as well. Would be great if there were an easier way of setting default value - though I appreciate this may be tricky.
In the short term I wonder if the default example / most examples should include the items array - nearly all services will have to have it to be able to let users change existing answers / do validation.


[Bug] Episodes won't load because of the episode name.

Device information

Tachiyomi version: <IP_ADDRESS>-mi-3686
Android version: 10
Device: Xiaomi redmi note 7 pro

Steps to reproduce

Go to 4anime.to extension and search re:zero
Select the first season and open it.

Expected behavior
Since all the episodes are available on the website, the episodes should appear on Aniyomi.
Actual behavior
The episodes doesn't appear and give the error : For input string:"01A".
Other details
The first and second episodes of the show in the website is named as 01A and 01B  respectively.

Closing cause 4anime is deprecated


Update Docker Builds to PHP 8.3

Docker is currently set to use PHP 8.2 as there is an upstream issue (Imagick/imagick#640) causing our builds to fail when attempting to install imagick with PHP 8.3.
Hopefully the fix (Imagick/imagick#641) will be merged soon - opening this issue to track the progress.
Once released I will bump PHP in Docker to 8.3.

Hopefully the fix (Imagick/imagick#641) will be merged soon - opening this issue to track the progress.

A single line change submitted to the repo 3 weeks ago with no update from the maintainers. They haven't even approved of the workflow runs. That's not looking promising, lol

A single line change submitted to the repo 3 weeks ago with no update from the maintainers. They haven't even approved of the workflow runs. That's not looking promising, lol

It is unfortunate, especially considering this is the official PHP imagick extension repo.
Though, I'd rather not work around it if avoidable as it just puts more work on us (albeit minimal) and PHP 8.2 is above our minimum spec at the moment. That said, if it starts to impact on us in any way I'll use the workaround.

Looks like we're just waiting on a new release for this to be fixed, which should hopefully occur soon  🤞.

Looks like we're just waiting on a new release for this to be fixed, which should hopefully occur soon 🤞.

There haven't been any commits in 9 months.. good luck 🤷♀

Given we only recommend the imagick extension because of DomPDF, I've gone ahead and asked them to clarify if there's any actual benefit to having both it and the gd extension. https://github.com/dompdf/dompdf/discussions/3376.
Hopefully there isn't so we can simply drop it altogether rather than twiddling out thumbs and waiting indefinitely for the compilation issues to maybe be fixed.

I've gone ahead and asked them to clarify if there's any actual benefit to having both it and the gd extension. dompdf/dompdf#3376.

Given the reply over there and how minimally we use it I'd say it can be dropped.

Given the reply over there and how minimally we use it I'd say it can be dropped.

Agreed, given that this still hasn't been resolved, reliance on imagick as a requirement should best be avoided. I'll get a PR up dropping it from the docker image.
Somewhat related - @BelleNottelling it looks like both GD and imagick are only recommended requirements, is this still correct? I would guess that with both missing, the related PDF functionality would be broken.

Somewhat related - @BelleNottelling it looks like both GD and imagick are only recommended requirements, is this still correct? I would guess that with both missing, the related PDF functionality would be broken.

Hmm, indeed GD is only listed as a suggestion and not as a requirement. That replicates the DomPDF docs, but since our template includes an image by default it probably should be required

what about building in the docker file magick from source like here?
https://orkhan.dev/2024/02/07/using-imagick-with-php-83-on-docker/


Delete liburing and the old experiment referencing it.

Are we still interested in pursuing this at some point?

Maybe someday but no immediate plans.


Rerender

See https://github.com/conda-forge/basemap-feedstock/pull/9

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.


[Bug]: Remove unused networks

Description
When deleting a resource/project in coolify the underlaying docker network won't get deleted.
Minimal Reproduction (if possible, example repository)

Create a project using docker-compose
Define some custom networks
Delete the project
run "docker network ls" or docker network prune

Exception or Error
No response
Version
v4.0.0-beta.306

I noticed that it is not possible to remove the networks by hand because docker tells me that the network still has active endpoints which i guess only can be coolify itself.

You have to remove this networks in coolify. Go to Servers > choose server > Destinations > Scan Destinations.
There you should see all networks. You can click on every single network so it gets added to the section „Available for using:“ above. There you can click and delete every single network.


Types.elm -> Protocol.elm

Having Types.* encourages careless accumulation of types inside it.
If we have Protocol.MsgFromServer Protocol.MsgFromClient instead, we can hope one might double take on Protocol.Customer being canonical and consider if it's really rooted under Protocol or should perhaps Customer be its own module.

Implemented in 90821870c82cb0fb63ccbf158d9a0f96418176dc


Scalar metrics 17 1

A simple update for desispec 0.17.1 in scalar_metrics.py.
It was tested for my installation, but it needs to be tested in the online version.
The requirements or extras should be modified in order to install a scipy version >=0.19.0 due to a desispec module.

@felipeaoli this PR uses an old version of QLF can you merge branch master into it and test again?

Merge solved


tools: Set a+x on rpm_spec_vendor2provides

New script is missing the executable bit.

This actually has the same problem as before. How are you using it? What I'm trying to do is:
go mod edit -replace github.com/osbuild/images=../osbuild-images
which changes the go.mod file, adding:
replace github.com/osbuild/images => ../osbuild-images
But that won't have an effect until you run ./tools/prepare-source.sh to update the vendor directory with the changes.
This copies the new files into the replaced package, and updates vendor/modules.txt which is where the problem is:
# github.com/osbuild/images v0.0.0-20230710155525-7045e8251769 => ../osbuild-images
Since I'm using a local path, not a URL and version, there is no version component, so the regex tries to select it for the Provides but fails with:
[bcl@derek osbuild-composer]$ make scratch                                      (main-test-generator *$%)
mkdir -p /home/bcl/Red_Hat/projs/osbuild-composer/rpmbuild/SPECS
git show HEAD:osbuild-composer.spec > rpmbuild/SPECS/osbuild-composer.spec
./tools/rpm_spec_add_provides_bundle.sh rpmbuild/SPECS/osbuild-composer.spec
Traceback (most recent call last):
File "/home/bcl/Red_Hat/projs/osbuild-composer/./tools/rpm_spec_vendor2provides", line 56, in
main()
File "/home/bcl/Red_Hat/projs/osbuild-composer/./tools/rpm_spec_vendor2provides", line 52, in main
process(file)
File "/home/bcl/Red_Hat/projs/osbuild-composer/./tools/rpm_spec_vendor2provides", line 33, in process
ipath, version = replace_regex.sub("", dep[2:]).split(" ")[:2]
^^^^^^^^^^^^^^
ValueError: not enough values to unpack (expected 2, got 1)
How are you testing this?
I've added a patch here that fixes things for me, using a fake version when using filesystem paths in the replace line.

Oh, my bad.  Thanks!


[MM-28225] Private Cloud sales card

Summary
Sales card on the Subscriptions screen to upsell Mattermost Private Cloud.
Ticket Link
https://mattermost.atlassian.net/browse/MM-28225

@devinbinnie I don't see the subscription page, or the billing & account section altogether in the system console

@devinbinnie I don't see the subscription page, or the billing & account section altogether in the system console

@matthewbirtch Flipped the switch, it's on now.


add some notes about JIT compilation issues

Wasm is of course designed such that reasonably optimized machine code can be generated in n log n time. And it can be generated with a simpler compiler than usual.  So I don't think it's too much of a stretch for high-performance clients to provide at least a minimal compiler.  Wasm's design also makes high-speed interpreters possible in system-level languages like C and Rust, so compilers aren't the only option.


After re-importing local cluster with addLocal=auto, Default and System projects are not associated with the correct namespaces

rancher/rancher:v2.1.2-rc12
After re-importing local cluster with addLocal=auto, Default and System projects are not associated with the correct namespaces, causing local cluster's workloads and namespaces to not be displayed correctly.
Test case:

Fresh install w/ addLocal=auto
Deploy some workloads to local cluster
Upgrade to same version w/ addLocal=false
View workloads still running through kubectl but the local cluster is not present in UI & agents are not running
Upgrade to same version with addLocal=auto
Deployed workloads should show in the local cluster properly

To reproduce:

Fresh install of 2.1.2-rc12 w/ addLocal=auto
Local cluster is shown in the UI
Deployed workload w/ ingress into local cluster's Default project.
--
Upgraded to 2.1.2-rc12 w/ addLocal=false
Local cluster is removed from UI
Pod from deployed workload is still running in default namespace, and the ingress is still functioning
--
Upgraded to 2.1.2-rc12 w/ addLocal=auto
Local cluster is added back to the UI

Expected:
The workload and ingress are present in the UI under the local cluster's Default project, and the System project contains correct namespaces and workloads.
Actual:
The deployed workload and ingress are not present in the UI under the local cluster's Default project, and the local cluster's System project is empty.
Additional info:
Namespaces after initial install:
kubectl get ns
NAME            STATUS    AGE
c-j6bcm         Active    5m
cattle-system   Active    8m
default         Active    10m
ingress-nginx   Active    9m
kube-public     Active    10m
kube-system     Active    10m
local           Active    8m
p-fdvjr         Active    8m
p-fpmbk         Active    8m
p-qntdk         Active    5m
p-v6q87         Active    5m
user-n56bc      Active    7m

Namespaces after re-importing local cluster:
kubectl get ns
NAME            STATUS    AGE
c-j6bcm         Active    23m
cattle-system   Active    25m
default         Active    27m
ingress-nginx   Active    26m
kube-public     Active    27m
kube-system     Active    27m
local           Active    13m
p-n4h44         Active    13m
p-qntdk         Active    23m
p-sszxg         Active    13m
p-v6q87         Active    23m
user-n56bc      Active    24m

The default namespace where the workload was deployed has the annotation:
field.cattle.io/projectId=local:p-fdvjr, which no longer exists
The project ID for the local cluster's Default project is now: local:p-n4h44
The kube-system namespace has the annotation:
field.cattle.io/projectId=local:p-fpmbk, which no longer exists
The project ID for the local cluster's System project is now: local:p-sszxg

rancher/rancher:master
HA setup w/ helm installation
All test cases detailed in #16523 passed.


AddFunds: Auto complete for selecting the source of money

The form that a host can use to add funds to a collective asks you to provide the source of the money or create one (context: the host can receive money on behalf of a collective directly on their bank account, in which case they have to manually allocate those funds to the balance of the right collective).
Right now, the dropdown menu is populated by fetching all the members across all collectives hosted by the host. That list is massive for the open source collective and makes the interface almost unusable.

It would be a much better UX to have an auto complete field to automatically search for a previously used sources https://github.com/opencollective/frontend/blob/master/src/components/AddFundsSourcePicker.js
It looks like Downshift by @kentcdodds would be a good candidate for doing this. See this example with Apollo: https://codesandbox.io/s/m5zrvqj85p
Related to #1234

As a quick mitigation, we could only show the list of previous sources of money.
This query returns this:
SELECT c.slug
FROM "Collectives" c INNER JOIN "Transactions" t ON t."FromCollectiveId" = c.id
WHERE t."PaymentMethodId" = :HostPaymentMethodId
  AND t.type='CREDIT'
  AND t."deletedAt" IS NULL
GROUP BY c.slug

What happens with new organizations that we are using as source for the first time?

same as today: you'll have to select "other" and then specify its name / url / email to create one on the fly.

This would be the dropdown with this query for the open source collective:

@xdamman why is threadless not showing up?

It is showing up but as a user. Not sure why it was created that way. You may want to convert it.


Fix RabbitMQ not able to start in Balanced Mode

start node agent workflow after starting messaging transport to avoid null agent exception, when rabbit mq is used in balanced mode

Solves:
https://github.com/JasperFx/wolverine/issues/818
https://github.com/JasperFx/wolverine/issues/788


delete existing files when uploading folder to s3

A little late, but resolution to our most infamous bug. I was going to include this in a different branch but figured let's just get this merged.
Would we prefer any sort of safety measures? Or actually checking if a folder exists? Or just this - clean out the prefix in s3 before uploading anything

noting that we used delete() locally and it doesn't throw an error or warning when the folder doesn't exist, so no extra safety measures needed