converted mlperf gpt3 ckpt starts with a worse loss

Hello,
We converted the paxml checkpoint and resumed training with following config:
base_config: "base.yml"
tokenizer_path: "/dockerx/vocab/c4_en_301_5Mexp2_spm.model"
dataset_type: "tfds"
dataset_path: "/ckpts/c4_mlperf_dataset"
dataset_name: "en:3.0.4"
eval_dataset_name: "en:3.0.5"
split: "train2"
tokenize_eval_data: False
eval_data_column: "ids"
add_bos: False
add_eos: False
eval_split: "validation_tokenized_5662seqs"
eval_interval: 10  # the specific number of train step between eval_step
target_eval_loss: 2.69  # early stop once reaching target eval_loss

enable_checkpointing: True
save_interval_steps: 5

# Args coming from the NVIDIA spreadsheet http://shortn/_W9CzVbtQde and
# third_party/py/maxtext/configs/a3/llama_2_7b.
hardware: "gpu"
steps: 10
model_name: "gpt3-175b" # this model config is unchanged
attention: "cudnn_flash_te"

gradient_accumulation_steps: 1

dcn_data_parallelism: 1
dcn_fsdp_parallelism: -1
dcn_pipeline_parallelism: 1
dcn_tensor_parallelism: 1
dcn_sequence_parallelism: 1
ici_fsdp_parallelism: 8
ici_data_parallelism: 1
ici_sequence_parallelism: 1
ici_tensor_parallelism: 1
ici_pipeline_parallelism: 1
per_device_batch_size: 5
max_target_length: 2048

remat_policy: "full"
use_iota_embed: True
scan_layers: False
async_checkpointing: False
logits_dot_in_fp32: False
megablox: False

dtype: "bfloat16"
quantization: ""
quantize_kvcache: False
kv_quant_axis: "heads_and_dkv"
kv_quant_dtype: "int8"
weight_dtype: bfloat16
checkpoint_is_quantized: False # Set to True if reading from a saved aqt quantized checkpoint

skip_first_n_steps_for_profiler: 3

mesh_axes: ['data', 'stage', 'fsdp', 'fsdp_transpose', 'sequence', 'tensor', 'autoregressive']
logical_axis_rules: [
                      ['activation_batch', ['data', 'fsdp', 'fsdp_transpose',]],
                       # For pipeline parallelism the pre and post decoder layer tensors' batch dimension is sharded by stages.
                       # Microbatches are sharded by stage, so moving out of and into this sharding should be a local reshape.
                       # The "stage" needs to be listed first since the microbatch dimension is first before the reshape.
                      ['activation_embed_and_logits_batch', ['stage', 'data', 'fsdp', 'fsdp_transpose']],
                      ['activation_heads', ['tensor','sequence']],
                      ['activation_kv_heads', ['tensor','sequence']],
                      ['activation_length', 'sequence'],
                      ['activation_embed', 'tensor'],
                      ['activation_mlp', 'tensor'],
                      ['activation_kv', 'tensor'],
                      ['activation_kv_batch', ['data', 'fsdp', 'fsdp_transpose',]],
                      ['activation_kv_head_dim', 'tensor'],
                      ['activation_vocab', ['tensor', 'sequence']],
                      ['activation_vocab', 'tensor'],
                      ['activation_vocab', 'sequence'],
                      ['activation_stage','stage'],
                      ['mlp', ['fsdp_transpose', 'tensor', 'autoregressive']],
                      ['vocab', ['tensor', 'autoregressive']],
                      ['embed', ['fsdp', 'fsdp_transpose', 'sequence']],
                      ['embed', ['fsdp', 'sequence']],
                      ['norm', 'fsdp'],
                      ['heads', ['tensor', 'autoregressive']],
                      ['layers', 'stage'],
                      ['kv', []],
                      ['kv_heads', ['tensor', 'autoregressive']],
                      ['kv_head_dim', []],
                      ['cache_batch', []],
                      ['cache_heads', ['autoregressive', 'tensor']],
                      ['cache_kv', []],
                      ['cache_sequence', []],
                    ]

# Axes used for DCN must be earlier in this list than ICI, see (b/339009148) for details
data_sharding: [['data', 'stage', 'fsdp', 'fsdp_transpose', 'sequence', 'tensor', 'autoregressive']]

The tokenizer and data splits (3.0.4, 3.0.5) were downloaded from mlperf2 bucket. I have also tried using the c4_mlperf dataset_type like this:
base_config: "base.yml"
tokenizer_path: "/dockerx/vocab/c4_en_301_5Mexp2_spm.model"
dataset_type: "c4_mlperf"
dataset_path: "/ckpts/c4_mlperf_dataset"
dataset_name: "en:3.0.4"
eval_dataset_name: "en:3.0.5"
split: "train2"
eval_split: "validation_tokenized_5662seqs"

python maxtext/MaxText/train.py /dockerx/maxtext/MaxText/configs/gpt3_175b_gpu.yml base_output_directory=/ckpts/paxml/gpt3-conversion run_name=gpt3-conversion steps=4010 scan_layers=true

^ scan_layers set to true in line with how we converted the ckpt
completed step: 4000, seconds: 91.772, TFLOP/s/device: 24.021, Tokens/s/device: 22.316, total_weights: 65504, loss: 7.644, perplexity: 2088.295
To see full metrics 'tensorboard --logdir=/ckpts/paxml/gpt3-conversion/gpt3-conversion/tensorboard/'
completed step: 4001, seconds: 12.945, TFLOP/s/device: 170.297, Tokens/s/device: 158.213, total_weights: 65504, loss: 7.687, perplexity: 2179.917
completed step: 4002, seconds: 11.886, TFLOP/s/device: 185.471, Tokens/s/device: 172.310, total_weights: 65504, loss: 7.739, perplexity: 2297.215
completed step: 4003, seconds: 11.885, TFLOP/s/device: 185.479, Tokens/s/device: 172.318, total_weights: 65504, loss: 7.597, perplexity: 1992.680
completed step: 4004, seconds: 11.931, TFLOP/s/device: 184.759, Tokens/s/device: 171.649, total_weights: 65504, loss: 7.680, perplexity: 2165.097
completed step: 4005, seconds: 11.913, TFLOP/s/device: 185.043, Tokens/s/device: 171.912, total_weights: 65504, loss: 7.663, perplexity: 2128.778
completed step: 4006, seconds: 11.945, TFLOP/s/device: 184.546, Tokens/s/device: 171.451, total_weights: 65504, loss: 7.582, perplexity: 1963.248
completed step: 4007, seconds: 11.913, TFLOP/s/device: 185.048, Tokens/s/device: 171.918, total_weights: 65504, loss: 7.648, perplexity: 2096.574
completed step: 4008, seconds: 12.013, TFLOP/s/device: 183.498, Tokens/s/device: 170.478, total_weights: 65504, loss: 7.524, perplexity: 1851.645
completed step: 4009, seconds: 11.920, TFLOP/s/device: 184.929, Tokens/s/device: 171.807, total_weights: 65504, loss: 7.618, perplexity: 2034.629

^ starts with a very high loss and we expected something closer to 2.77
We have ensured that the training loads the right checkpoint, the correct data splits and also the tokenizer from the logs

@ZhiyuLi-goog thanks again for your help with other issues. Do you see any problems with the config or know why the loss is much higher?

I have never tried on GPU.
To narrow down the root cause, could you try with normal attention?
attention: "dot_product"

with attention: "dot_product" :
completed step: 4000, seconds: 91.772, TFLOP/s/device: 24.021, Tokens/s/device: 22.316, total_weights: 65504, loss: 7.644, perplexity: 2088.295
To see full metrics 'tensorboard --logdir=/ckpts/paxml/gpt3-conversion/gpt3-conversion/tensorboard/'
completed step: 4001, seconds: 39.677, TFLOP/s/device: 277.795, Tokens/s/device: 258.083, total_weights: 327520, loss: 7.638, perplexity: 2076.376
completed step: 4002, seconds: 39.883, TFLOP/s/device: 276.359, Tokens/s/device: 256.749, total_weights: 327520, loss: 7.646, perplexity: 2092.290
I get similar loss as before

I saw scan_layers: False is that as expected?

I tested these out. First running
python3 MaxText/train.py MaxText/configs/base.yml run_name="${RUNNAME}" model_name=gpt3-175b

and then also adding the other relevant flags you posted one by one and all of them start with the bad loss (7.6x). So its not flash attn, tokenizer (as validation is pretokenized and evaluated loss is also bad), config args (as i tried the flags you have suggested)
Its probably something to do with the model weights

I can take a look at full logs if you have.
We should have final effective configs in that log.

maxtext_gpt3_logs.txt
Thanks. Here are the logs

Checked the log.
All updated parameters matched and I didn't find anything suspicious.

Thanks for checking
yeah its strange that its starting with a bad loss. I also tried testing the tokenizer and it also seems fine

The only one I found looks weird is

Config param weight_dtype: float32

Config param weight_dtype: bfloat16

Could you try using weight_dtype as float32 instead of bfloat16?

im wondering if we can send you our converted ckpt for you to load and verify its an ckpt problem?

I can take a try in TPU side
By the way, would it be useful to you to print the mean average of each param state after conversion?

im not sure if it will be useful.
We also loaded the pax ckpt directly in pax and the ckpt starts at the right loss. So at this point, we suspect something is going wrong during conversion

It would be easiest if you have some converted ckpt, I can directly compare your converted ckpt against ours.
If you have some output log in conversion script, I can take a look as well.
We didn't try that in gpu, I guess there might be something differently.

great
we will share the converted ckpt and the conversion logs. Do you have a gcloud bucket that i could push it to? or do you recommend some other way?

we will share the converted ckpt and the conversion logs. Do you have a gcloud bucket that i could push it to? or do you recommend some other way?

Great if you can share with us some open gcloud bucket.
By the way, which conversion script are you using? Is the one in mlperf 4.0 submission or the one in maxtext main branch?

ok, let me do that
We tried both versions and with both, we are getting the same problem

We tried both versions and with both, we are getting the same problem

Gotcha, thank you for the info!

We have created the bucket and will share the access with you soon (I got your google email from one of your commits)

Hello again,
You should finally have access to the bucket containing all the ckpts

We have shared three ckpts:
1.gpt3-conversion-forked/ is ckpt created with mlperf fork
2. gpt3-conversion-noscan-cache/
3.gpt3-conversion/
The second and third are both the latest branch - the second was scan_layers=false, and the third is scan_layers=true

Thank you @gramesh-amd
I will test with your ckpt.

I wrote a script to look at the checkpoint that we generated and compare it to the original data.
What I found (at least in my initial look) is that for each row has the first 1/4 of its data (starting at element 0) populated, and the rest of it was 0.
This is interesting because we used 4 nodes with 8 GPUs, with intra- and inter-node FSDP.
This makes me think that we have data from the first node, and 0's from the other three nodes.
Any suggestions for how we can confirm that this is what happened and debug it?

@gabeweisz
Great finding and thank you for looking into it!
I am just wondering how did you run the script? I do expect to :

have this script running on each device, this is a no-brainer in TPU, and I am wondering if we should do some tweak in GPU
the output_directory should be accessible to each device

key idea
# each process/device will distribute the weight (fsdp) and each device only keep its own shard
result = jax.make_array_from_single_device_arrays(
    shape,
    sharding,
    [jax.device_put(np.array(arr[index]), d) for d, index in sharding.addressable_devices_indices_map(shape).items()],
)
...
...

# distribute saving to a output directory like a gcs bucket which can be accessible by all devices.
if save_checkpoint(checkpoint_manager, converted_state.step, converted_state):
  max_logging.log(f"saved a checkpoint at step {converted_state.step}")
# Upon preemption, exit when and only when all ongoing saves are complete.
if checkpoint_manager.reached_preemption(converted_state.step):
  checkpoint_manager.wait_until_finished()
  sys.exit()

example
I have tried the script yesterday and worked for me.
# checkpoint loading from a fixed folder
RUN_NAME=ckpt
BASE_OUTPUT_DIR=gs://path/to/output

python MaxText/convert_gpt3_ckpt_from_paxml.py \
  --paxml-ckpt-path=gs://mlperf-llm-public2/gpt3_spmd1x64x24_tpuv4-3072_v84_20221101/checkpoints/checkpoint_00004000 \
  --maxtext-model-name=gpt3-175b \
  --run-name=$RUN_NAME \
  --base-output-directory=$BASE_OUTPUT_DIR

Note the output directory is a gcs bucket which can be accessible by all devices.

We ran the script in a way very similar to how you ran it - my colleague Gowtham has shared what we did earlier.
When we ran this, we didn't have a shared NFS big enough for all the nodes and did not have access to a GCS bucket - each node was writing to its own local directory.
I did check, and once the script was finished, only node 0 had a checkpoint - none of the others did.
Do you think this caused the issue? If so, does Orbax have a way to work around this?
Another option is that I can try to modify an on-disk checkpoint using tensorstore as in the documentation - there is no real reason why we need to load the checkpoint onto GPUs to convert it from one format to another.

We just found the place in the documentation where orbax says that all nodes need to write to the same filesystem - that explains what went wrong for us.

When we ran this, we didn't have a shared NFS big enough for all the nodes and did not have access to a GCS bucket - each node was writing to its own local directory.
We just found the place in the documentation where orbax says that all nodes need to write to the same filesystem - that explains what went wrong for us.

Exactly, I think it should be the root cause.

We just found the place in the documentation where orbax says that all nodes need to write to the same filesystem - that explains what went wrong for us.

Hi @gabeweisz, were you able to figure it out? Let me know if you have any further questions. Otherwise, we will close it.

Please go ahead and resolve the ticket

Thank you @gabeweisz !


[enhancement]: Integrate Apple's CoreML optimizations for SD

Is there an existing issue for this?

[X] I have searched the existing issues

Contact Details
No response
What should this feature add?
Apple has announced some tooling for SD optimization on M* Macs. If we can get it integrated quickly (or first...), it could be a huge boon to Invoke's reach.
https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon
https://github.com/apple/ml-stable-diffusion
Still reading, but I wanted to raise the issue with this community.
Alternatives
No response
Aditional Content
No response

just looked a little into this - looks really promising, but some issues as of now:

models have to be converted in order to work. Not a big deal, but worth calling out..
converted models do not seem to be able to accept any other width/height input other than 512x512 (or whatever it was originally trained on. see https://github.com/apple/ml-stable-diffusion/blob/main/python_coreml_stable_diffusion/pipeline.py#L225). That looks like a blocker until they fix it.
The python generation pipeline currently has to load the model from scratch every time (2-3 mins!) and is unable to cache it. Their FAQ describes it in more detail. There's a swift pipeline that can avoid it, but not sure that helps here..

I'd love to see this in action here. Hope my digging helps a bit, and hope their repo advanced quickly to fix these shortcomings.

Please add this!

I've been doing a lot of testing with Apple's repo. Here are the modes that worked best on my M1 Max with 24-core gpu and 32GB:
Using --attention-implementation ORIGINAL with CPU_AND_GPU, I got up to 2.96it/s using ~32W and ~8GB of RAM. This combination should be best for maximum performance on Pro/Max/Ultra.
Using --attention-implementation SPLIT_EINSUM with CPU_AND_NE, I got 1.44its/s using <5W and <1GB of RAM. This combination makes a great high-efficiency mode, and should even get similar performance on an iphone/ipad with an A14 or better.
Using --attention-implementation SPLIT_EINSUM with ALL (cpu, gpu and neural engine), I got 2.46 it/s using ~13W and ~3GB of RAM, and not maxing-out my GPU. This combination makes a good balanced mode, and will likely offer the highest performance on M1/M2 chips, and possible the M1 Pro as well, since it has 2/3 the gpu cores of my M1 Max.
I'll also note that the versions using the neural engine took about 4 minutes to initially load the model, though the Swift implementation was able to do this only on the first run, and load it more quickly after that. Asitop seemed to indicate that the neural engine wasn't running anywhere near maximum generating 512x512 images, but the code in Apple's repo doesn't let you modify that. That combined with the almost nonexistent memory footprint makes me thing this might work really well for generating larger images with hires_fix, or using large tiles with embiggen.
Ideally, Invoke would support these three modes (power, efficiency, and balanced), and let the user choose among them, depending on which processor they have, and how much power they want to use (having my laptop act as a lap warmer in the current weather is kinda nice, but if I was on battery power, I'd definitely want to use the neural engine instead of my GPU.

@whosawhatsis

Using --attention-implementation SPLIT_EINSUM with ALL (cpu, gpu and neural engine), I got 2.46 it/s using ~13W and ~3GB of RAM, and not maxing-out my GPU. This combination makes a good balanced mode, and will likely offer the highest performance on M1/M2 chips, and possible the M1 Pro as well, since it has 2/3 the gpu cores of my M1 Max.

I tried this but I am getting 8gb+ ram usage, I used this command, Am I doing something wrong?
python -m python_coreml_stable_diffusion.pipeline --prompt "a photo of an astronaut riding a horse on mars" -i models/coreml-stable-diffusion-v1-4_split_einsum_packages -o output/ --compute-unit ALL --seed 93

I have this in models folder coreml-stable-diffusion-v1-4_split_einsum_packages

just looked a little into this - looks really promising, but some issues as of now:

models have to be converted in order to work. Not a big deal, but worth calling out..
converted models do not seem to be able to accept any other width/height input other than 512x512 (or whatever it was originally trained on. see https://github.com/apple/ml-stable-diffusion/blob/main/python_coreml_stable_diffusion/pipeline.py#L225). That looks like a blocker until they fix it.
The python generation pipeline currently has to load the model from scratch every time (2-3 mins!) and is unable to cache it. Their FAQ describes it in more detail. There's a swift pipeline that can avoid it, but not sure that helps here..

I'd love to see this in action here. Hope my digging helps a bit, and hope their repo advanced quickly to fix these shortcomings.

Thanks for the link. That led me to the hugging face pipeline. They show a good example there defining a call to allow for flexible height and width:
https://github.com/huggingface/diffusers/blob/4125756e88e82370c197fecf28e9f0b4d7eee6c3/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py#L412
        height: Optional[int] = None,
        width: Optional[int] = None,
        ```

just looked a little into this - looks really promising, but some issues as of now:

models have to be converted in order to work. Not a big deal, but worth calling out..
converted models do not seem to be able to accept any other width/height input other than 512x512 (or whatever it was originally trained on. see https://github.com/apple/ml-stable-diffusion/blob/main/python_coreml_stable_diffusion/pipeline.py#L225). That looks like a blocker until they fix it.
The python generation pipeline currently has to load the model from scratch every time (2-3 mins!) and is unable to cache it. Their FAQ describes it in more detail. There's a swift pipeline that can avoid it, but not sure that helps here..

I'd love to see this in action here. Hope my digging helps a bit, and hope their repo advanced quickly to fix these shortcomings.

Both the 2nd and 3rd points only apply to the SPLIT_EINSUM version of converted models (which uses CPU+ANE). For ORIGINAL version (which uses CPU+GPU) it's possible to change the width/height and model loading is fast.
Apart from the base M1/M2 where ANE outperforms GPU, ORIGINAL version works better for Pro/Max/Ultra. Some more benchmarks can be found on Apple's project page, and in this project here.
Btw Apple recently updated its project to support even ControlNet. MochiDiffusion already added support for it. Yay for competition?
Anyway the future of Stable Diffusion on Apple Silicon looks really promising. Can't wait for SDXL!


Can neither listen to click events of the FAB nor change anything programmatically

None of the following method calls seem to take effect.
FloatingActionButton fabSpeedDialFab = (FloatingActionButton) findViewById(io.github.yavski.fabmenu.R.id.fab);

fabSpeedDialFab.setImageDrawable( ... );
fabSpeedDialFab.setBackgroundTintList( ... );
fabSpeedDialFab.setOnClickListener( ... );

However calling
fabSpeedDialFab.setVisibility( View.GONE );
works and the whole FAB + Speed Dial is invisible.

Calling .setImageDrawable( ... ) after the view was attached to the windows worked.
public void onViewAttachedToWindow(View view) {
                fabSpeedDialFab.setImageDrawable (... );
                fabSpeedDialFab.setBackgroundTintList( ... );
            }


ES6 linting

changed var statements to const/let
added dev dependency on @types/node to remove warnings from index.d.ts
migrated istanbul to nyc coverage
added package lock

What versions of Node.js does this cut off?

@derekcollison This cuts 4 which died a long time ago - 6 is also about to die on 4/30.

Agree, but wondering if we still have users on 4..

if we do, they are on their own on many fronts. Also the release history has versions that accommodate them.

Coverage increased (+0.7%) to 89.205% when pulling 3f70f04553f2f158eb57d3407354cfa5081766ce on es6-lint into 1f558a91157740b0ef2326ceaffea06f2372ec0d on master.

@kozlovic - node-nats tests on travis have a 90% chance of failure always - they require babysitting. Imho most are invalid timeouts.


Get text width

Hello, how can I get the width of the text element? I can get the correct value only after the text is rendered on the page.

Hi @yuraantonov11 , I don't think there's straightforward answer to that. What do you need such information for?

@g-zachar, I want to get the text width because I need to set the width of the next element after the text.
In this picture, I have a dynamic label length and width.

Well since everything is a texture you can do the following:
// force a texture load this.tag("MyTextLabel").loadTexture(); // get width of the texture const width = this.tag("MyTextLabel").renderWidth;

@yuraantonov11 You should be able to build it using flex layout and not bother manually calculating width.


feat: add support for chemical equations (\ce) by contrib/mhchem.min.js

Thanks for the PR. Can you please fix the format issue and add a test case for this?

Thanks for the PR. I have pushed a new release to crates.io.

Oops, sorry it was night on my side; Thanks for adding the tests; Awesome tool!!


[Feature] - Restore a backup into an Astra DB

Restore a backup (both Astra and database)

astra db restore mydb \
  -d,--dest ./tmp

It would be preferable to have a parameter named --backup-location instead of --dest.
Should we give the option to restore only one keyspace?
Should we add an option that will confirm everything is set for backup restore to succeed? (like checking backup schema vs mydb schema, backup-location exists...)


Add MIDI parsing capabilities to godot.

I know this may be requested, but I need godot to extend their MIDI support to being able to parse MIDI files.
https://www.youtube.com/watch?v=qmZMGb3N0KE
It will help me develop some software for blind musicians, like the girl in this video, who was unable to become a professional pianist because of a lack of braile scores.
My goal is to make some imitone + synthesia kind of hybrid, where I'll take the audio from some microphone and then output the note using some text to speech system to convert the MIDI note into speech instructions over what note or adorment the note has and wait until the player has input said note, similar to synthesia but I'll need to being able to parse the microphone audio in case the blind musician uses other instrument that isn't a MIDI keyboard.

Microphone input is supported.
MIDI playback is not supported (existing feature request issue: #12238).
Unlikely parsing MIDI files without playback capabilities will be added to the engine, but you can parse MIDI files with GDScript or make a gdnative wrapper for third-party MIDI library.
I have simple gdnative add-on for the text-to-speech support here: https://github.com/bruvzg/godot_tts (this implementation won't be ever integrated into the engine, due to licensing issues (depends on LGPL libs)).

We had a Google Summer of Code project by @DanielMatarov for MIDI playback last year, the results of which can be found in https://github.com/DanielMatarov/Google-Summer-of-Code--Module-and-test-projects
I'm not sure what its current state is, but we should look into better integrating it and documenting its usage.
There's also a GDScript MIDI player at https://bitbucket.org/arlez80/godot-midi-player

We had a Google Summer of Code project by @DanielMatarov for MIDI playback last year, the results of which can be found in https://github.com/DanielMatarov/Google-Summer-of-Code--Module-and-test-projects
I'm not sure what its current state is, but we should look into better integrating it and documenting its usage.
There's also a GDScript MIDI player at https://bitbucket.org/arlez80/godot-midi-player

https://www.youtube.com/watch?v=J1jm1qBoVCs
Made some test with such player, is right now kind of buggy and doesn't render properly the files.

Hi,
The project I worked on last year seems to no longer work in the newest
version of Godot. Somebody has filed an issue, and the problem seems to
stem from the mix function.
On Mon, 27 May 2019, 05:29 ca3games<EMAIL_ADDRESS>wrote:

We had a Google Summer of Code project by @DanielMatarov
https://github.com/DanielMatarov for MIDI playback last year, the
results of which can be found in
https://github.com/DanielMatarov/Google-Summer-of-Code--Module-and-test-projects
I'm not sure what its current state is, but we should look into better
integrating it and documenting its usage.
There's also a GDScript MIDI player at
https://bitbucket.org/arlez80/godot-midi-player
https://www.youtube.com/watch?v=J1jm1qBoVCs
Made some test with such player, is right now kind of buggy and doesn't
render properly the files.
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What's the latest version your MIDI code works?

I think 3.0
On Mon, May 27, 2019 at 4:48 PM ca3games<EMAIL_ADDRESS>wrote:

What's the latest version your MIDI code works?
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.

Duplicate of #12238.


Use FQCN in validation error messages

Supercedes #16926

@bot-gradle test this

OK, I've already triggered ReadyForMerge build for you.

@bot-gradle test this

OK, I've already triggered ReadyForMerge build for you.

@bot-gradle test and merge
@wolfs I'm proactively merging since you had said +1 on the PR which had the plugins in addition. Feel free to comment if I need to fix something.

OK, I've already triggered a build for you.

OK, I've already triggered a build for you.


Fix filters for custom attributes

Changes proposed ✍

Create a new field to handle multi-select filter with pre-existent options. Sort options alphabetically
After bulk enrichment, fetch attributes to get the latest attributes and options
For "multi-select" and "special" render the new filter component. For "multi-select" and "special" that do not have available options, do not render as a filter

Screenshots (front-end changes only)

Checklist ✅

[x] Label appropriately with Feature, Enhancement, or Bug.
[ ] Tests are passing.
[ ] New backend functionality has been unit-tested.
[ ] Environment variables have been updated:

[ ] Local frontend configuration: frontend/.env.dist.local, frontend/.env.dist.composed.
[ ] Local backend: backend/.env.dist.local, backend/.env.dist.composed.
[ ] Configuration docs have been updated.
[ ] Team members only: update environment variables in override, staging and production env. files and trigger update config script.

[ ] API documentation has been updated (if necessary) (see docs on API documentation).
[x] Quality standards are met.
[x] All changes have been tested in a staging site.
[x] All changes are working locally running crowd.dev's Docker local environment.

LGTM


getLight() should initialize all fields.

Fixes #4014.

These fields are consumed in evaluatePunctualLights so I think they need to be initialized to something.


Be able to change the default nuxt webpack config

I want to extend the webpack config with the svg-sprite-loader, which looks like:
https://github.com/kisenka/svg-sprite-loader/blob/master/examples/browser-sprite/webpack.config.js
This conflicts with the url loader in Nuxt:
// https://nuxtjs.org/guide/assets/#webpacked
{
  test: /\.(png|jpe?g|gif|svg)$/,
  loader: 'url-loader',
  query: {
    limit: 1000, // 1KO
    name: 'img/[name].[hash:7].[ext]'
  }
}

I get a svg-sprite-loader exception. 2 rules applies to warning and was able to fix it by removing the rule and re-add it with an exclude property:
extend(config, { dev, isClient }) {
  /**
   * Initialise SVG Sprites
   */

  // get and remove file loader
  const rule = config.module.rules.find(r => r.test.toString() === '/\\.(png|jpe?g|gif|svg)$/');
  config.module.rules.splice(config.module.rules.indexOf(rule), 1);

  // add it again, but now without 'assets\/svg'
  config.module.rules.push({
    test: /\.(png|jpe?g|gif|svg)$/,
    loader: 'url-loader',
    exclude: /(assets\/svg)/,
    query: {
      limit: 1000, // 1KO
      name: 'img/[name].[hash:7].[ext]',
    },
  });

  config.module.rules.push({
    test: /\.svg$/,
    include: [
      path.resolve(__dirname, 'assets/svg'),
    ],
    use: 'svg-sprite-loader',
  });
},

This feels like a dirty hack, but it was the only way to get it working.
Could you add some support to be able to change the default nuxt webpack config or tell me how I could have done it otherwise?

Hack worked for me. Thanks! Would rather not be hacking though.
Has there since been a way to do this the proper way?

Any idea how to get it working when using nuxt generate?
This works great when running in dev mode but when I run nuxt generate the svg sprite is missing from the dom.

I did something similar to this hack to send options to the sass-loader (I wanted includePaths to let me pull in some libraries)... I'd be happy to do the work to implement a better approach, but would like guidance on what api would best fit with the nuxt approach.
@alexchopin did you already have thoughts on how you'd like this to look?
Feel free to totally overrule this, but if you didn't already have prior thoughts, one possibility would be to group rule types (images, css, fonts, js, ...) and allow you to explicitly override each of those groups... and then potentially have a "catch all" or "extra" for completely new rules...
so in the example above, your nuxt.config.js would look something like:
build: {
  rules: {
    images: [
     {
        test: /\.(png|jpe?g|gif|svg)$/,
        loader: 'url-loader',
        exclude: /(assets\/svg)/,
        query: {
          limit: 1000, // 1KO
          name: 'img/[name].[hash:7].[ext]',
        },
      },
      {
        test: /\.svg$/,
        include: [
          path.resolve(__dirname, 'assets/svg'),
        ],
        use: 'svg-sprite-loader',
      }
    ]
  }
}

Thanks @vanoorschot for the hack! Nicely done :)
Not sure what has changed since but with the current RC you can do this which results in much shorter code.
build: {
    extend (config, ctx) {
      // Excludes /assets/svg from url-loader
      const urlLoader = config.module.rules.find((rule) => rule.loader === 'url-loader')
      urlLoader.exclude = /(assets\/svg)/

      // Includes /assets/svg for svg-sprite-loader
      config.module.rules.push({
        test: /\.svg$/,
        include: [
          path.resolve(__dirname, 'assets/svg')
        ],
        use: 'svg-sprite-loader'
      })

      // Uncomment line below to view webpack rules
      // console.dir(config.module.rules)
    }
  },
}

You still have to import the svg in your components so that it can be injected into document.body.

Is this still working for you in RC11? I get "ReferenceError: path is not defined" when i try this.


Error: the task 'Ctags Companion: rebuild ctags' neither specifies a command nor a dependsOn property. The task will be ignored. Its definition is:

Hi, when I try to use ctags-companion in SystemVerilog project, found the error below.
My vscode version is 1.52.1 which is released in 2020-12-16. Is the version incompatible？

Error: the task 'Ctags Companion: rebuild ctags' neither specifies a command nor a dependsOn property. The task will be ignored. Its definition is:
{
"type": "shell",
"id": "shell,ctags -R --fields=+nKz -f .vscode/.tags,",
"problemMatcher": [],
"label": "Ctags Companion: rebuild ctags"
}

Many thanks to your help.

Hello, thank you for the bug report. I will look into it.
For now you may try this workaround:

manually run ctags -R --fields=+nKz -f .vscode/.tags from command line
invoke "reindex" command from vscode

@yoe3eyes I downloaded vscode 1.52.1 but I am unable to reproduce the issue.
Which Ctags Companion version do you have installed?

I've tried the "reindex" command manually under x64 and Linux, both of them can't find the command.
But, under x64 which I installed the newest version of all the tools, the “rebuild ctags” works fine and I can use the Go to Defintion now. Thank you for the work~
I think it might be my Linux environment is separated from the internet which I can only use FTP to upload extension.If it is so, is there any thing I can do to use the extension without internet？

Hi, the problem seems have been solved when I update the universal-ctags to the newest. I can use "Go to Defintion" now after rebuild. (Or it could be I organized filelist in a right way, I'm not sure which action made it work).
And the question mentioned above seem not fix yet. I can still see the error report.
Anyway, Its very helpful. Thank you for your reply~


Bump the memory limits for metrics and queue workers

It has been seen when running in containers that the reported memory usage is a little higher than RSS which is a little higher than PSS.
This means that if we are on the edge on an appliance the same usage will be over the limit on pods.

Test failure unrelated, https://github.com/ManageIQ/manageiq/pull/20384 should fix it

Jansa backport details:
$ git log -1
commit a3aaa1549fbc850038c5511ae585b0d8b43cf773
Author: Joe Rafaniello<EMAIL_ADDRESS>Date:   Thu Jul 23 16:35:08 2020 -0400

    Merge pull request #20383 from agrare/bump_memory_thresholds

    Bump the memory limits for metrics and queue workers

    (cherry picked from commit cca2bd8e9c8839deff16ff62a2be49558885f8f4)


Frontend: Feature/product page

Description
this PR is about product page where you can choose color, quantity, size and see the similar product of same category.
ADD TO CART and EXPLORE THIS CATEGORY and ADD product in favorite, these are the functionality implement later in another issue.
Fixes #65
How to test?
please run command ->npm run dev and goto http://localhost:3000/product/8
Checklist

[x] I have performed a self-review of my own code
[x] I have followed the name conventions for CSS Classnames and filenames, Components names and filenames, Style filenames, if you are in doubt check the the project README.MD and here https://github.com/HackYourFuture-CPH/curriculum/blob/master/review/review-checklist.md
[x] I have commented my code, particularly in hard-to-understand areas, if you code was simple enough mark the box anyway
[x] I have made corresponding changes to the documentation, if you code was simple enough mark the box anyway
[ ] This PR is ready to be merged and not breaking any other functionality

@zkwsk @Jul-S @simonreddy2001  Thanks to all for review comments :-)

Thanks to all for review and comments :-)


Security Warning  (Insecure Content-Security-Policy)

A security warning is shown in the console log running Dat Desktop in development mode:
/home/daniel/Work/Dotloom/dat-desktop/node_modules/electron/dist/resources/electron.asar/renderer/security-warnings.js:184 Electron Security Warning (Insecure Content-Security-Policy) This renderer process has either no Content Security
      Policy set or a policy with "unsafe-eval" enabled. This exposes users of
      this app to unnecessary security risks.

For more information and help, consult
https://electronjs.org/docs/tutorial/security.
 This warning will not show up
once the app is packaged.

Cleanup this warn.

Content-Security-Policy set to script-src 'self' 'unsafe-inline'


Fix disappearence of go_containerregistry 0.1.4

Updating it to <IP_ADDRESS> to fix build issues like
ERROR: /home/rmohr/.cache/bazel/_bazel_rmohr/d8c39dc5bdaf4508a5ddf82e95ab388c/external/io_bazel_rules_docker/container/go/pkg/oci/BUILD:18:11: @io_bazel_rules_docker//container/go/pkg/oci:go_default_library depends on @com_github_google_go_containerregistry//pkg/v1/layout:go_default_library in repository @com_github_google_go_containerregistry which failed to fetch. no such package '@com_github_google_go_containerregistry//pkg/v1/layout': java.io.IOException: Error downloading [https://api.github.com/repos/google/go-containerregistry/tarball/8a2841911ffee4f6892ca0083e89752fb46c48dd] to /home/rmohr/.cache/bazel/_bazel_rmohr/d8c39dc5bdaf4508a5ddf82e95ab388c/external/com_github_google_go_containerregistry/temp3242427000601878860/8a2841911ffee4f6892ca0083e89752fb46c48dd.tar.gz: Checksum was cadb09cb5bcbe00688c73d716d1c9e774d6e4959abec4c425a1b995faf33e964 but wanted 60b9a600affa5667bd444019a4e218b7752d8500cfa923c1ac54ce2f88f773e2

Signed-off-by: Roman Mohr<EMAIL_ADDRESS>
What this PR does / why we need it:
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #
Special notes for your reviewer:
Release note:

NONE

/retest

Force merging to restore builds on master.


Appstudio update test-component-pac-fbby

Pipelines as Code configuration proposal
To start the PipelineRun, add a new comment with content /ok-to-test
For more detailed information about running a PipelineRun, please refer to Pipelines as Code documentation Running the PipelineRun
To customize the proposed PipelineRuns after merge, please refer to Build Pipeline customization

Pipelines as Code CI/test-component-pac-fbby-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
7 seconds
init

✅ Succeeded
15 seconds
clone-repository

✅ Succeeded
26 seconds
build-container

✅ Succeeded
20 seconds
inspect-image

✅ Succeeded
21 seconds
deprecated-base-image-check

✅ Succeeded
4 minutes
clair-scan

✅ Succeeded
40 seconds
clamav-scan

✅ Succeeded
15 seconds
sbom-json-check

✅ Succeeded
9 seconds
label-check

✅ Succeeded
7 seconds
show-sbom

✅ Succeeded
8 seconds
show-summary


[WIP] KEP 4818: PodLifecycleSleepActionAllowZero

Description
Docs for KEP 4818: Allow zero value for Sleep Action of PreStop Hook.
Related PRs

Enhancements PR: https://github.com/kubernetes/enhancements/pull/4855
Code PR: https://github.com/kubernetes/kubernetes/pull/127094

Issue

Closes: nil, part of https://github.com/kubernetes/enhancements/issues/4818

Placeholder PR for the KEP, will come back to this next week.

I think this needs to target dev-1.32.

@kannon92 Ah I missed that, thanks for pointing it out Kevin!

I messed up the git history after rebasing, I'll fix it later today!
CC: @sftim

Hi @sreeram-venkitesh 👋,
A quick reminder to get your PR ready for review before the deadline, Thursday Oct 24 at 18:00 PDT. For additional information, refer to: Documenting for a release - PR Ready for Review.
Thank you!

/remove-area blog localization release-eng web-development
/remove-language bn de es fr hi id it ja ko pl pt ru uk vi zh
/remove-sig release

/remove-area blog localization release-eng web-development
/remove-language bn de es fr hi id it ja ko pl pt ru uk vi zh
/remove-sig release

/remove-language de es id ja ko pt ru zh

This PR is now ready for review! 🎉
CC: @chanieljdan

/approve

Hi @sreeram-venkitesh looking good on this one, do you know if we could get a technical review from someone in sig-node? Once they give their LGTM then this can get merged. Thanks!

LGTM from sig-node side.

Thanks @kannon92!

Technical LGTM provided above, as well as sig-docs approval
/lgtm


Coinbase is not authenticating, at least in sandbox

Trying to get authenticated by Coinbase Advanced API Sandbox.
var exchange = await ExchangeAPI.GetExchangeAPIAsync(ExchangeName.Coinbase);
exchange.LoadAPIKeysUnsecure(ConsumerKey, ConsumerSecret, ConsumerPassword);
exchange.BaseUrlWebSocket = "wss://ws-feed-public.sandbox.exchange.coinbase.com";
exchange.BaseUrl = "https://api-public.sandbox.exchange.coinbase.com";

Getting Invalid passphrase exception when executing some simple request, e.g. get ticker info.
exchange.GetTickerAsync("BTC-USD")

Keys were generated here.
https://public.sandbox.exchange.coinbase.com/apikeys
Considering recent changes in Coinbase, is this initialization still valid or I need to generate signature myself using CryptoUtility and somehow include it as a bearer token in every request?

@artemiusgreat, are you using Coinbase Exchange (for businesses) or Coinbase Advanced (for individuals)?


[model_to_estimator] estimator not evaluate all outputs defined in keras model but only one

Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):  Linux Ubuntu 16.04
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 1.13.1
Python version: 3.5.2
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version: CUDA 10.0
GPU model and memory:

Describe the current behavior
When using keras model with multiple outputs, and convert it to estimator by model_to_estimator, it only evaluate one output by estimator.evaluate or tf.estimator.train_and_evaluate.
And don't know which output it evaluate (it doesn't display output name but only metrics name).
Describe the expected behavior
It should only evaluate all outputs defined in keras model, not only pick one.
Code to reproduce the issue
A example here:
    ...

    model = tf.keras.Model(inputs=input_layer, outputs=[output_layer1, output_layer2])

    model.compile(optimizer=optimizer_builder.build(config.optimizer),
                  loss={
                      'output_layer1': 'sparse_categorical_crossentropy',
                      'output_layer2': 'sparse_categorical_crossentropy'},
                  metrics={
                      'output_layer1': 'accuracy',
                      'output_layer2': 'accuracy'})

    estimator = tf.keras.estimator.model_to_estimator(
        keras_model=model,
        config=run_config,
    )
    train_spec = tf.estimator.TrainSpec(
        input_fn=lambda: train_input_fn(config))
    eval_spec = tf.estimator.EvalSpec(
        input_fn=lambda: eval_input_fn(config))
    tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)

    # Only evaluate one output and don't know which output it evaluate

Other info / logs
tf log here, except two outputs log, but only get one:
# Training is OK
INFO:tensorflow:global_step/sec: 1.02106
INFO:tensorflow:loss = 0.16959098, step = 33600 (97.938 sec)
INFO:tensorflow:global_step/sec: 0.943188
INFO:tensorflow:loss = 0.17629223, step = 33700 (106.023 sec)
INFO:tensorflow:global_step/sec: 0.848641
INFO:tensorflow:loss = 0.1101246, step = 33800 (117.835 sec)
INFO:tensorflow:global_step/sec: 0.852682
INFO:tensorflow:loss = 0.104427785, step = 33900 (117.277 sec)
INFO:tensorflow:Saving checkpoints for 34000 into /summary/model.ckpt.
...

# Evaluating only evaluate one output
INFO:tensorflow:Running local_init_op.
INFO:tensorflow:Done running local_init_op.
INFO:tensorflow:Evaluation [150/1500]
INFO:tensorflow:Finished evaluation at 2019-09-17-14:14:45
INFO:tensorflow:Saving dict for global step 34000: accuracy = 0.6914724, sparse_categorical_crossentropy = 1.0857606, global_step = 34000, loss = 1.1107497

TensorBoard except two outputs scalar, but only get one:

@Jasonnor, Thanks for reporting the issue.
Will it be possible to provide the standalone code to reproduce the reported issue. Thanks!

@gadagashwini Sure! Here is a test code:
https://colab.research.google.com/drive/1qU5uhOfCy1MFtvUA1-8nJdzdgcdbpQvM
I compiled model by:
    model.compile(optimizer=tf.keras.optimizers.SGD(lr=0.0001, momentum=0.9),
                  loss={
                      'output_1': 'sparse_categorical_crossentropy',
                      'output_2': 'sparse_categorical_crossentropy'},
                  metric={
                      'output_1': 'accuracy',
                      'output_2': 'accuracy'})

But only get one loss result, not two result of two output. (and don't know why without accuracy metric result?)
INFO:tensorflow:Evaluation [100/100]
INFO:tensorflow:Finished evaluation at 2019-09-19-06:39:42
INFO:tensorflow:Saving dict for global step 0: global_step = 0, loss = 12.851205, sparse_categorical_crossentropy = 2.3049202

Hi There,
We are checking to see if you still need help on this, as you are using an older version of tensorflow which is officially considered end of life . We recommend that you upgrade to the latest 2.x version and let us know if the issue still persists in newer versions. Please open a new issue for any help you need against 2.x, and we will get you the right help.
This issue will be closed automatically 7 days from now. If you still need help with this issue, please provide us with more information.


Frontier - add MNTL AssetMantle

LGTM. Pending liquidity

Pending valid coingeckoID

Pending valid coingeckoID

CoingeckoID it's not mandatory, thanks @JeremyParish69 , Merged 👍


buffer metric and then send together for better performance

We send metric every time to statsd when we call metric functions, although UDP is fast, we can still do some improvement for better performance.
We can buffer the metric and send them together. The common MTU is 1440, so we can use 1024 size buffer to cache metric and send these in one UDP package. see https://github.com/alexcesaro/statsd
@overvenus , could you help us do this benchmark and support it?

Sure. I will start working on it three weeks later, as I have to prepare final examination. :sweat_smile:


Docker-compose, OpenOversight links

This PR prepares the project for a move from glitch onto our own infrastructure by standardizing its deployment using just and docker-compose. Fortunately this is a pretty simple app, so nothing too complex (unless we have to deal with static files, in which case I'll [REDACTED]). I've also upgraded to Python 3.9, because Glitch was the one holding us back and I want to use the walrus operator for stuff.
Lastly, I've added a hard-coded mapping of SPD badge numbers -> OpenOversight IDs. It's not the best solution, maybe we can download the file directly from OpenOversight instead of committing it directly? That's actually a really good idea lol, I'll make an issue for it. Anyway this works and it's a good test for new functionality that we can have on our own infra.

Can we update the docs to include the just commands? I spent a bit trying to figure out why they didn't work anymore lol

Ah, great call - will do!

I'm actually going to cut the OpenOversight link changes off into a separate PR. We won't want to deploy that until we launch OO.


Palette preview width shrinking

Investigate layout styling in component preview and make sure the content occupies 100% of width

See https://github.com/react-buddy/demo-antd-v4

Grid
Timeline (mode right)

Suggested implementation

introduce previewLayout: 'center' | 'stretch' prop in Variant
center is the default value (if prop is not specified)

Also need to fix Carousel (big size of layout)

Every dom element from Component's dom element to the html element must have "fullWindow" class once.
And our className prop which we setted to Palette, Category, Component or Variant must be last in dom classes.


Add reference to and clean up authentication-mechanisms.md

Performed actons below:

remove redundant spaces
provide a consistent look for bullets
add some reference links to the bottom
minor changes about typo and grammar

/kind cleanup

Preview of proposed changes: https://deploy-preview-48701--kubernetes-io-main-staging.netlify.app/docs/concepts/security/hardening-guide/authentication-mechanisms/
changes look good, thank you for the cleanup
/approve


OVH CDN log file format

I am unable to parse log files provided by my CDN provider (OVH), I get the "No valid hits" error.
This is a sample line from the log file:
<IP_ADDRESS> www.customerdomain.es - [04/Mar/2015:00:00:05 +0100] "GET /skin/frontend/customer/enterprise/images/flags/flag-poland.png HTTP/1.1 200 0" http://www.salewa.es/es/ropa/hombre/chaquetas.html Mozilla/5.0 (Linux; Android 4.4.2; Aquaris E4.5 Build/KOT49H) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/40.0.2214.109 Mobile Safari/537.36 "" ""
I tried this Log Format:
%h %^[%d:%^] "%r %s %b" %R %u "" ""
With this Date Format:
%d/%b/%Y
Do you have any hints on what am I doing wrong?
Thank you and regards,
Giulio

Interesting format. Do you know how is the referer and the user agent delimited? Usually they are within double quotes

I have the same problem. My Apache LogFormat looks like the following
LogFormat "%V %h %l %u %t \"%r\" %>s %b \"%{Referer}i\" \"%{User-Agent}i\"" vhost-combined
CustomLog logs/access_log vhost-combined

kitchenstyle.example.net 109.86.xxx.xxx - user [05/Mar/2015:20:33:53 +0000] "GET /skin/adminhtml/default/default/images/cancel_btn_icon.gif HTTP/1.1" 200 648 "http://kitchenstyle.example.net/skin/adminhtml/default/default/boxes.css" "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/40.0.2214.115 Safari/537.36"

I'm using GoAccess - 0.8.5 on CentOS 6.

@Alexhha the following works for your log:
log-format %^ %h %^[%d:%^] "%r" %s %b "%R" "%u"
date-format %d/%b/%Y

I have complied devel version but as I can see there is no vhosts support?

As you see from the log neither the referer nor the user agent are delimited.
I am actually not interested in those fields, so also a format strings ignoring those two would work for me..
Thank you for your answer!

@Alexhha As of v0.8.5, goaccess ignores the vhost part. However, issues #23 and #67 discuss the plan to have the data sliced based on virtual hosts.

@gmarcon the following should work
%h %^[%d:%^] "%m %U %H %s %b"

you might even be able to get the referer part with:
%h %^[%d:%^] "%m %U %H %s %b" %R %^

It would be killer feature :) At the moment I have ~1850 vhosts and it very hard to analyze which one is load the whole system.
Will be waiting vhost support. Anyway thanks for the great project

Closing this. Feel free to reopen it if needed.

Amazing, thank you very much, works like a charm!

@gmarcon FYI you may wish to consider a better CDN as well - OVH are not the greatest unless you happen to be within 10Km of one of their 4 main DC's ;-)
You can consult 3rd party matricies and insights into the industry via eg: cedexis - if you dont have the technical means / reasources to measure.

@Alexhha vhost support has been added to v0.9.5.

@allinurl
Sorry for the delay, but it's a great news. I will definitely try it. Thanks a lot


env: Show proper SshUserAndHost for remoteEndpoint

If there are multiple remotes for the current repo, git lfs env shows wrong SshUserAndHost for remote endpoints.

Yikes, nice catch :)

Thanks for the patch!  I confirmed this works in this test: https://github.com/github/git-lfs/commit/b5fa32f7aa2cf11e6e8a8248421653511b47800a


Minispy only works on one of my computer

Hi everyone! I am trying to develop a new driver based on minispy code. I have successfully install minispy on my windows 11 (Surface computer) But i am trying to install the driver also on a window 10 (HP) and a Windows 11 dev (VM created with hyper-V) but it doesn't work... I have found the base code in this link : https://github.com/microsoft/windows-driver-samples/tree/main/filesys/miniFilter/minispy
after that i build it in Realease mode with visual studio 22 17.1.7 and i tried to install it by right-clicking on the minispy.inf and on install.
After this part I see minispy when i am running the command
driverquery
in my computers and VM, but when i am trying to start the service by running in an administrator command prompt
net start minispy
I get this result on my VM and my windows 10 computer (translate form french) :
error system 127

the procedure is unfindable

I don't really know what are the differences and I am feeling kind of lost here... If someone can help me i would be very happy!

I have the same problem.
VS Community 2022, Windows 10.

by using Dependency Walker, find ExAllocateFromNPagedLookasideList and  ExFreeToNPagedLookasideList is not exported.

I also came across the same problem on Windows 10, maybe the cause is same with #806 ?


Raspotify overrides explicit content setting

Hi
I am having an issue where I have my Spotify account set to NOT allow explicit content. However, when I connect to the Raspotify it allows explicit content to be played.
Is there any way I can set this setting  via the librespot config?
Thanks in advance and awesome project - I use it to control music at an ice-rink
Cheers,
Jim

I've got the same issue. Have to glance at my playlists and set a reminder to skip songs after x amount of minutes. Hope they provide a fix for this.


Support adding multiple custom registries with the same URL

Portainer currently forbids adding registries with duplicate URLs, which makes it impossible to add, e.g., two different accounts on one custom registry to portainer.
The check is here (and similar in registry_update), but I don't really see why this is checked (would be happy to do a PR to remove that check - but again, I'm probably missing something).
In short, I'd like to have support for

add custom registry "registry.example.com" with auth registry-user-A
add custom registry "registry.example.com" with auth registry-user-B
give access to first one to portainer-user-A
give access to second one to portainer-user-B

(https://github.com/portainer/portainer/issues/3044 may talk about the same thing, but I'm not 100% sure)

I'll tag this as an enhancement but the unicity constraint was added for a reason. We're using URL matching behind the scenes (core/API) to decorate Docker API requests with the correct credentials inside the authentication header.
This process would need to be updated as well.

Okay, thanks for that link, I understand the problem now - when deploying a stack, or similar, the only reference to the registry that we have is the URL. And then, if you allow duplicate URLs, it's unclear which registry account to choose.
My scenario from the issue description would still work, because each portainer user would only have access to exactly one registry.example.com. But as soon as you don't have that separation (for example as an admin), things break down.
The only real way out of that would be to allow users to define registries not by Host only, but by some sort of regex for the whole URL ("use registry account A for registry.example.com/foo/* but registry account B for registry.example.com/bar/*"). That would match how most registries do access control (quay.io, harbor etc). But it would obviously be a major piece of work.
So, I'm okay with closing this, but your call.

I think that we could somehow use the registry ID and decorate each Docker API request with an extra header.
I'll close this for now but as #3044 is somehow related. We can re-open the discussion here if needed.


⚠ Bofrost.at has degraded performance

In 7a61dcd, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 2323 ms

Resolved: Bofrost.at performance has improved in 746d024 after 17 minutes.


Why does BLE use &dyn?

This is more a question than an issue, but is there a specific reason, why bleps doesn't use generics instead of a dynamic reference to an HCIConnection on the BLE struct?
If this has a specific reason, please let me know.
The BLE struct is likely only instantiated once in the entire application and monomorphization will likely even reduce code size here.

There is no particular reason for that. Feel free to file a PR


fix: warning - findDOMNode is deprecated in StrictMode

Deployed to https://beghp.github.io/gh-pages-rc-7- [ ] an issue linked to the PR

@Lukasz-pluszczewski could you please merge this PR
findDOMNode is getting deprecated
React Reference : findDOMNode

is this going to get merged soon? lol


Added Dutch translation

I hope this is correct. First pull request.

I'm very sorry, the Dutch translation was merged from another contributor just a few hours ago.


How to implement the following code

How to implement the following code:
nn.Sequential(*list(resnet18().children())[:-3])
it's error like this:

@githubxiaoa -- found the problem. This will be fixed in the next version. Also, note that the TorchSharp version of ResNet has one more layer at the very end than the PyTorch version does -- it ends with a Flatten module.


Update mysql-connector-java from 8.0.33 to 8.2.0

About this PR
📦 Updates mysql:mysql-connector-java from 8.0.33 to 8.2.0
Usage
✅ Please merge!
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

🔍 Files still referring to the old version number
The following files still refer to the old version number (8.0.33).
You might want to review and update them manually.
docker-compose.yml

⚙ Adjust future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "mysql", artifactId = "mysql-connector-java" } ]

Or, add this to slow down future updates of this dependency:
dependencyOverrides = [{
  pullRequests = { frequency = "30 days" },
  dependency = { groupId = "mysql", artifactId = "mysql-connector-java" }
}]

labels: dependencies, library-update, early-semver-minor, semver-spec-minor, artifact-migrations, old-version-remains, commit-count:1

Superseded by #118.


Add a link/button to make it easier to submit sites to block comments for

Add a link or button that just goes to:
https://github.com/grantwinney/hide-comments-in-chrome/issues/new

done - added a popup that includes submitting a blacklist suggestion, which leads to a new issue


[BABEL] unknown: Preset /* your preset */ requires a filename to be set when babel is called directly,

Hello,
I've been getting this error in my React Native project
Code:
    usedKeys = extractor.extractFromFiles(['./src/**/*.js'], {
      marker: 't',
    });

Error:
    [BABEL] unknown: Preset /* your preset */ requires a filename to be set when babel is called directly,
    ```
    babel.transform(code, { filename: 'file.ts', presets: [/* your preset */] });
    ```
    See https://babeljs.io/docs/en/options#filename for more information.

      at validateIfOptionNeedsFilename (node_modules/i18n-extract/node_modules/@babel/core/lib/config/full.js:274:11)
      at node_modules/i18n-extract/node_modules/@babel/core/lib/config/full.js:286:52
          at Array.forEach (<anonymous>)
      at validatePreset (node_modules/i18n-extract/node_modules/@babel/core/lib/config/full.js:286:25)
      at loadPresetDescriptor (node_modules/i18n-extract/node_modules/@babel/core/lib/config/full.js:293:3)
          at loadPresetDescriptor.next (<anonymous>)
      at recurseDescriptors (node_modules/i18n-extract/node_modules/@babel/core/lib/config/full.js:107:30)
          at recurseDescriptors.next (<anonymous>)
      at loadFullConfig (node_modules/i18n-extract/node_modules/@babel/core/lib/config/full.js:142:6)
          at loadFullConfig.next (<anonymous>)

babel.config.js:
module.exports = {
  presets: ['module:metro-react-native-babel-preset'],
};

Downgrading i18n-extract to 0.6.3 fixes it so this isn't really urgent, but it would be extremely nice to get this fixed :)
Thanks again for the great library!

The above problem we faced was caused by module:metro-react-native-babel-preset, which expects filename to be provided to transformSync().
We prevented loading module:metro-react-native-babel-preset by disabling reading from the project root's Babel config file using the configFile: false option.
// Taken from i18n-extract's TYPESCRIPT_PARSER_OPTIONS
const BABEL_OPTIONS = {
  configFile: false,  // disable reading from project root's Babel config
  ast: true,
  parserOpts: {
    sourceType: 'module',
    plugins: [
      'jsx',
      'asyncFunctions',
      'classConstructorCall',
      'doExpressions',
      'trailingFunctionCommas',
      'objectRestSpread',
      'decoratorsLegacy',
      'classProperties',
      'exportExtensions',
      'exponentiationOperator',
      'asyncGenerators',
      'functionBind',
      'functionSent',
      'dynamicImport',
      'optionalChaining',
      'typescript',
    ],
  },
};

const ... = extractor.extractFromFiles(['./src/**/*.ts', './src/**/*.tsx'], {
    marker: 't',
    babelOptions: BABEL_OPTIONS,
  },
);

Adding configFile: false to  https://github.com/oliviertassinari/i18n-extract/blob/9110ba51362b8739a9590d85801cde4b9ce3347c/src/extractFromCode.js#L98 should fix this issue that was introduced by release 0.6.4 without users having to copy over babel config like in the above solution.
As the moment the library is assuming you want to used your root directory babel config file even if you are not passing in anything for babelOptions e.g. using a value for parser instead.
I would think that the default when using a parser should be to not read the root directory babel config unless specified by using the babelOptions configuration option?


Lab Create a Custom Skill for Azure AI Search - Function Deployment Failure

Lab: Create a Custom Skill for Azure AI Search
Task: Create an Azure Function for a custom skill
Step: 1. In the Azure Portal, on the Home page, create a new Function App resource with the following settings:

We have users reporting that they are unable to create a function app in the Azure portal due to region limitations. I have been able to reproduce this issue when deploying the function app in East US. Users can work around this issue by deploying the function app in a different region than East US. I was able to deploy the function app within Central US without any issues.
Attached is the error json.

FunctionAppError.json

This issue has been addressed and students launching the should only be able to launch in regions with no limitations to whats needed for the purpose of this lab.

I am still facing issues while creating a Function App: "{"code":"InvalidTemplateDeployment","details":[{"code":"RequestDisallowedByPolicy","target":"FunctionApp46344302","message":"Resource 'FunctionApp46344302' was disallowed by policy. Policy identifiers: '[{"policyAssignment":{"name":"ai102_LP5_V1*","id":"/providers/Microsoft.Management/managementGroups/lod-org-363-pool-729-lab154265/providers/Microsoft.Authorization/policyAssignments/policyAssignment2735"},"policyDefinition":{"name":"ai102_LP5_V1*","id":"/providers/Microsoft.Management/managementGroups/lod-org-363-pool-729-lab154265/providers/Microsoft.Authorization/policyDefinitions/policy2735"}}]'.","additionalInfo":[{"type":"PolicyViolation","info":{"evaluationDetails":{"evaluatedExpressions":[{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.web/serverfarms","operator":"Equals"},{"result":"False","expressionKind":"Field","expression":"id","path":"id","expressionValue":"/subscriptions/4ce44305-7594-411f-ad28-b939b6978b7a/resourceGroups/ai102lab12/providers/Microsoft.Web/sites/FunctionApp46344302","targetValue":"/resourceGroups/ResourceGroup1/","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.AlertsManagement/smartDetectorAlertRules","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.BotService/botServices","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.CognitiveServices/accounts","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.ManagedIdentity/userAssignedIdentities","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.OperationalInsights/workspaces","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.Insights/ActionGroups","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"microsoft.insights/components","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.Search/searchServices","operator":"Contains"},{"result":"False","expressionKind":"Field","expression":"type","path":"type","expressionValue":"Microsoft.Web/sites","targetValue":"Microsoft.Storage/storageAccounts","operator":"Contains"}]},"policyDefinitionId":"/providers/Microsoft.Management/managementGroups/lod-org-363-pool-729-lab154265/providers/Microsoft.Authorization/policyDefinitions/policy2735","policyDefinitionName":"policy2735","policyDefinitionDisplayName":"ai102_LP5_V1*","policyDefinitionEffect":"deny","policyAssignmentId":"/providers/Microsoft.Management/managementGroups/lod-org-363-pool-729-lab154265/providers/Microsoft.Authorization/policyAssignments/policyAssignment2735","policyAssignmentName":"policyAssignment2735","policyAssignmentDisplayName":"ai102_LP5_V1*","policyAssignmentScope":"/providers/Microsoft.Management/managementGroups/lod-org-363-pool-729-lab154265","policyAssignmentParameters":{},"policyExemptionIds":[]}}]}],"message":"The template deployment failed with multiple errors. Please see details for more information."}"


[Segment Replication] Cleanup and improvement on replica commit

Description
Motivated from https://github.com/opensearch-project/OpenSearch/pull/7044, where we see performance degradation, this PR takes up immediate improvements during replica commit. Remaining optimization will be taken up in #7044

Avoid explicit store cleanup during segment replication finalization as it performed again during commit on replica down the code path
Avoid loading metadata snapshot from latest committed segment infos which performs disk read, instead get files directly.

Issues Related
https://github.com/opensearch-project/OpenSearch/issues/7043
Check List

[ ] New functionality includes testing.

[ ] All tests pass

[ ] New functionality has been documented.

[ ] New functionality has javadoc added

[x] Commits are signed per the DCO using --signoff
[ ] Commit changes are listed out in CHANGELOG.md file (See: Changelog)

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Codecov Report

Merging #7130 (355841c) into main (169e237) will increase coverage by 0.16%.
The diff coverage is 50.00%.

:mega: This organization is not using Codecov’s GitHub App Integration. We recommend you install it so Codecov can continue to function properly for your repositories. Learn more
@@             Coverage Diff              @@
##               main    #7130      +/-   ##
============================================
+ Coverage     70.58%   70.74%   +0.16%
- Complexity    59410    59479      +69
============================================
  Files          4852     4852
  Lines        285167   285166       -1
  Branches      41116    41116
============================================
+ Hits         201277   201736     +459
+ Misses        67353    66851     -502
- Partials      16537    16579      +42

Impacted Files
Coverage Δ

.../indices/replication/SegmentReplicationTarget.java
90.26% <ø> (-0.09%)
:arrow_down:

...rc/main/java/org/opensearch/index/store/Store.java
78.09% <50.00%> (-1.29%)
:arrow_down:

... and 462 files with indirect coverage changes
Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


TypeScript Clasp Project missing Array Type

I've been pouring over documentation here, in the DefinitelyTyped repo, on StackOverflow, and in the VSCode documentation. I've attempted the following steps on multiple projects. I can't seem to find anything, and since this is part of the documentation here, I figured I'd start by asking questions about it here. If this isn't the correct place to bring this up, then I apologize, just looking for some direction as to how to fix this.
Expected Behavior
When working on a TypeScript-based clasp project, the compiler has access to all standard global types, including Array, allowing for IntelliSense and no compilation warnings when working with arrays.
Actual Behavior
Getting error in all .ts files when I'm using an Array type (like string[] or CustomClass[], specifically because the compiler doesn't know what the Array type is. These errors include things like Property 'push' does not exist on type '{}'., or Property 'length' does not exist on type '{}'..
Note: Prior to specifically pointing VSCode at TypeScript v2.9.2 (according to the TypeScript support documentation here), I had an error in the jsconfig.json file on line one saying Cannot find global type 'Array'.. Once I pointed VSCode to TS v2.9.2, the error in the jsconfig.json file went away, but all other errors persisted.
The only thing that seems to solve this is to remove the noLib from the compilerOptions in the jsconfig.json file. However, when I do that, it then opens up a whole host of other errors which are specifically suppressed for the GAS environment (like avoiding explicitly importing classes, etc...).
Steps to Reproduce the Problem

Using VScode as the editor
Create a brand new clasp Sheets project: clasp create --type sheets
Add TypeScript: 2.9.2 as a project dep (according to TypeScript support listed in documentation): yarn add<EMAIL_ADDRESS>Reload the window in VSCode (or quit and start it again)
Follow the exact documentation listed in the TypeScript support Readme: https://github.com/google/clasp/blob/master/docs/typescript.md
Set the VSCode settings to point the tsdk to the locally-installed version of TypeScript instead of VSCode's version of TypeScript ("typescript.tsdk": "node_modules/typescript/lib" -> workspace settings.json)
Attempt to use an array of some type (either primitive or of a custom class).

Specifications

Node version (node -v): 8.11.1
Version (clasp -v): 1.7.0
OS (Mac/Linux/Windows): macOS 10.14.1
TypeScript version (listed in package.json): 2.9.2
Google Apps Scripts Type Package version (@types/google-apps-script): 0.0.33
VSCode version: 1.30.1

Just tested this, and it fixes my issues with using Arrays! Thanks so much!


[release-4.11] Fix ginko errors in the openshift-ci

openshift-ci is failing for quite a long time on the older branches due to the ginko v2.
We were installing the Ginko binary without the version, which was installing Ginko V2 and making it incompatible with our older code and Golang. Fix it by sticking it to the v1 version.
Signed-off-by: Nitin Goyal<EMAIL_ADDRESS>

/cherry-pick release-4.10

/cherry-pick release-4.9


Looking for "unless-error" restart policy

I have a container which needs to be restarted when the machine reboots.  If the process crashes or exits with an error I would like it to stay down so it can be diagnosed.
Existing restart policies:

on-failure will not achieve either requirement.
always will achieve the first requirement but not the second.
unless-stopped is slightly better than always, but not quite what I want.

I apologise if this is a misguided request; I searched around quite a lot but didn't find an open discussion of the topic.  I found this which asserts that on-failure will restart containers on a daemon restart, but this does not match my experiments or my reading of the code.  On a hard reset of the machine, the exit code will be recorded as zero so no restart.
In #7586 it is asserted that always has a max-retry count, and a max-retry count of 1 would be good enough for my purposes, but again this does not match what I find in the code.

Hi!
Please read this important information about creating issues.
If you are reporting a new issue, make sure that we do not have any duplicates already open. You can ensure this by searching the issue list for this repository. If there is a duplicate, please close your issue and add a comment to the existing issue instead.
If you suspect your issue is a bug, please edit your issue description to include the BUG REPORT INFORMATION shown below. If you fail to provide this information within 7 days, we cannot debug your issue and will close it. We will, however, reopen it if you later provide the information.
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Thank you.
For more information about reporting issues, see https://github.com/docker/docker/blob/master/CONTRIBUTING.md#reporting-other-issues

BUG REPORT INFORMATION
Use the commands below to provide key information from your environment:
docker version:
docker info:
uname -a:
Provide additional environment details (AWS, VirtualBox, physical, etc.):
List the steps to reproduce the issue:
1.
2.
3.
Describe the results you received:
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#ENEEDMOREINFO

was implemented

@LK4D4 would you mind giving a pointer to where this was implemented? I don't see it at https://github.com/docker/docker/blob/master/restartmanager/restartmanager.go#L81-L85

@bboreham Sorry I've closed without explanation.
I thought that your case would be satisfied with --restart=on-failure:1. But it seems like it actually restarts process once.
I'll reopen issue

Does --restart=on-failure now restart the container on reboot?

@bboreham I've tried daemon restart and it worked.

@LK4D4 and I've tried a reboot and it didn't restart my container.
$ docker run -d --restart=on-failure alpine sleep 1000
7bc39ece38deb406c1e6f83fa653eb3620f5e8e42dd9fc478f02f4af2c06c107
$ docker ps
CONTAINER ID        IMAGE               COMMAND             CREATED             STATUS              PORTS               NAMES
7bc39ece38de        alpine              "sleep 1000"        6 seconds ago       Up 6 seconds                            pensive_hugle
$ sudo shutdown -r now
...
$ docker ps -a
CONTAINER ID        IMAGE               COMMAND             CREATED              STATUS                      PORTS               NAMES
7bc39ece38de        alpine              "sleep 1000"        About a minute ago   Exited (0) 31 seconds ago                       pensive_hugle

Could really use this - if the container exits it is for good reason, if the host or daemon restart it is not. In my case, the contanier must restart if the host or daemon restart but if the container exits with failure and keeps retrying then API keys get banned.
Also, for the record I'd call this option unless-failure to be consistent with the current naming.

It looks very simple to add... but this issue would need the attention of a reviewer...
https://github.com/moby/moby/blob/d3533eee68437c6489f37774ab57ac68f8ecae13/restartmanager/restartmanager.go#L81-L92
case rm.policy.IsUnlessStopped() && !hasBeenManuallyStopped:
 	restart = true
// +++
case rm.policy.IsUnlessFailure() && exitCode == 0:
 	restart = true
// +++
case rm.policy.IsOnFailure():


Develop

Changes Unknown when pulling b311e5407d6d6ccb283b73391a13736ae2485630 on develop into ** on master**.

Changes Unknown when pulling 708884b6a5ec51f931265522d45261c54d7945d5 on develop into ** on master**.

Changes Unknown when pulling 1131f4d7f9a16c97c733037e32f86a7434e8ae3c on develop into ** on master**.


Gold Skipper Stop Condition

Add a config condition for the final skipping program to stop if a certain amount of gold is seen.
Can use a random text recognition module (I think most would work for this) on the chest to detect gold count.

Implemented using easyocr which works well but some inaccuracy. Not pushed yet, but will do so next time I'm working on stuff for this.

implemented and pushed


Strings for Leaf 2

"MODEL" = Leaf2",
"STRING_SETTINGS" = "okRZqgfOHft/Y5jHx1N0ECjqrc/Op/nADFj2uL7Jbuxq",
"STRING_UPGRADE" = "10Na33u5HfsCVHqjtwLrwACOW+2cz5MSnXUogONCTd9c"
fingerprint: Onyx/Leaf2/Leaf2:11/2022-10-29_19-11_3.3.1_8c9d49397/1583:user/dev-keys
If there's anything missing, please let me know!

Duplicates https://github.com/Hagb/decryptBooxUpdateUpx/pull/46 :)

Thanks for submitting the strings (though duplicates #46). Close for #46 is merged.


Delay https connection creation

:broken_heart: Tests Failed

Expand to view the summary

Build stats

Build Cause: [Started by user eyalkoren, Replayed #1]

Start Time: 2020-05-31T15:28:03.578+0000

Duration: 20 min 47 sec

Test stats :test_tube:

Test
Results

Failed
1

Passed
798

Skipped
1

Total
800

Test errors
Expand to view the tests failures

Name: Tests / Smoke Tests 01 / testQueueSendReceiveOnNonTracedThread[BrokerFacade=co.elastic.apm.agent.jms.ActiveMqFacade@abf688e] – co.elastic.apm.agent.jms.JmsInstrumentationIT

Age: 1
Duration: 0.196
Error Details:
Expecting actual not to be null

Steps errors
Expand to view the steps failures

Name: Shell Script

Description: ./scripts/jenkins/smoketests-01.sh

Duration: 6 min 52 sec

Start Time: 2020-05-31T15:41:41.444+0000

log

Log output
Expand to view the last 100 lines of log output

[2020-05-31T15:47:44.885Z] Post stage
[2020-05-31T15:47:44.904Z] Recording test results
[2020-05-31T15:47:44.910Z] Post stage
[2020-05-31T15:47:44.929Z] Recording test results
[2020-05-31T15:47:45.793Z] Running in /var/lib/jenkins/workspace/_java_apm-agent-java-mbp_PR-1209/src/github.com/elastic/apm-agent-java
[2020-05-31T15:47:45.807Z] [INFO] Codecov: Getting branch ref...
[2020-05-31T15:47:45.827Z] Masking supported pattern matches of $GITHUB_TOKEN
[2020-05-31T15:47:45.904Z] [INFO] Codecov: Sending data...
[2020-05-31T15:47:46.065Z] Running in /var/lib/jenkins/workspace/_java_apm-agent-java-mbp_PR-1209/src/github.com/elastic/apm-agent-java
[2020-05-31T15:47:46.078Z] [INFO] Codecov: Getting branch ref...
[2020-05-31T15:47:46.099Z] Masking supported pattern matches of $GITHUB_TOKEN
[2020-05-31T15:47:46.178Z] [INFO] Codecov: Sending data...
[2020-05-31T15:47:46.287Z] + curl -sSLo codecov.sh https://codecov.io/bash
[2020-05-31T15:47:46.287Z] + bash codecov.sh
[2020-05-31T15:47:46.287Z]
[2020-05-31T15:47:46.287Z]   _____          _
[2020-05-31T15:47:46.287Z]  / ____|        | |
[2020-05-31T15:47:46.287Z] | |     ___   __| | ___  ___ _____   __
[2020-05-31T15:47:46.287Z] | |    / _ \ / _` |/ _ \/ __/ _ \ \ / /
[2020-05-31T15:47:46.287Z] | |___| (_) | (_| |  __/ (_| (_) \ V /
[2020-05-31T15:47:46.287Z]  \_____\___/ \__,_|\___|\___\___/ \_/
[2020-05-31T15:47:46.287Z]                               Bash-20200430-d757c17
[2020-05-31T15:47:46.287Z]
[2020-05-31T15:47:46.287Z]
[2020-05-31T15:47:46.287Z] ==> Jenkins CI detected.
[2020-05-31T15:47:46.287Z]     project root: .
[2020-05-31T15:47:46.547Z]     Fixing merge commit SHA
[2020-05-31T15:47:46.547Z] --> token set from env
[2020-05-31T15:47:46.547Z]     Yaml not found, that's ok! Learn more at http://docs.codecov.io/docs/codecov-yaml
[2020-05-31T15:47:46.547Z] ==> Running gcov in . (disable via -X gcov)
[2020-05-31T15:47:46.547Z] ==> Python coveragepy not found
[2020-05-31T15:47:46.547Z] ==> Searching for coverage reports in:
[2020-05-31T15:47:46.547Z]     + .
[2020-05-31T15:47:46.566Z] + curl -sSLo codecov.sh https://codecov.io/bash
[2020-05-31T15:47:46.566Z] + bash codecov.sh
[2020-05-31T15:47:46.827Z]
[2020-05-31T15:47:46.827Z]   _____          _
[2020-05-31T15:47:46.827Z]  / ____|        | |
[2020-05-31T15:47:46.827Z] | |     ___   __| | ___  ___ _____   __
[2020-05-31T15:47:46.827Z] | |    / _ \ / _` |/ _ \/ __/ _ \ \ / /
[2020-05-31T15:47:46.827Z] | |___| (_) | (_| |  __/ (_| (_) \ V /
[2020-05-31T15:47:46.827Z]  \_____\___/ \__,_|\___|\___\___/ \_/
[2020-05-31T15:47:46.828Z]                               Bash-20200430-d757c17
[2020-05-31T15:47:46.828Z]
[2020-05-31T15:47:46.828Z]
[2020-05-31T15:47:46.828Z] ==> Jenkins CI detected.
[2020-05-31T15:47:46.828Z]     project root: .
[2020-05-31T15:47:46.828Z]     Fixing merge commit SHA
[2020-05-31T15:47:46.828Z] --> token set from env
[2020-05-31T15:47:46.828Z]     Yaml not found, that's ok! Learn more at http://docs.codecov.io/docs/codecov-yaml
[2020-05-31T15:47:46.828Z] ==> Running gcov in . (disable via -X gcov)
[2020-05-31T15:47:46.828Z] ==> Python coveragepy not found
[2020-05-31T15:47:46.828Z] ==> Searching for coverage reports in:
[2020-05-31T15:47:46.828Z]     + .
[2020-05-31T15:47:47.117Z] --> No coverage report found.
[2020-05-31T15:47:47.117Z]     Please visit http://docs.codecov.io/docs/supported-languages
[2020-05-31T15:47:47.248Z] Failed in branch Smoke Tests 02
[2020-05-31T15:47:47.403Z]     -> Found 17 reports
[2020-05-31T15:47:47.403Z] ==> Detecting git/mercurial file structure
[2020-05-31T15:47:47.403Z] ==> Reading reports
[2020-05-31T15:47:47.403Z]     + ./apm-agent-core/target/site/jacoco/jacoco.xml bytes=1045018
[2020-05-31T15:47:47.403Z]     + ./apm-agent-plugins/apm-jmx-plugin/target/site/jacoco/jacoco.xml bytes=41105
[2020-05-31T15:47:47.403Z]     + ./apm-agent-plugins/apm-jdbc-plugin/target/site/jacoco/jacoco.xml bytes=92239
[2020-05-31T15:47:47.403Z]     + ./apm-agent-plugins/apm-api-plugin/target/site/jacoco/jacoco.xml bytes=83170
[2020-05-31T15:47:47.403Z]     + ./apm-agent-plugins/apm-error-logging-plugin/target/site/jacoco/jacoco.xml bytes=10841
[2020-05-31T15:47:47.404Z]     + ./apm-agent-plugins/apm-java-concurrent-plugin/target/site/jacoco/jacoco.xml bytes=9173
[2020-05-31T15:47:47.404Z]     + ./apm-agent-plugins/apm-asynchttpclient-plugin/target/site/jacoco/jacoco.xml bytes=17673
[2020-05-31T15:47:47.404Z]     + ./apm-agent-plugins/apm-jaxrs-plugin/target/site/jacoco/jacoco.xml bytes=18877
[2020-05-31T15:47:47.404Z]     + ./apm-agent-plugins/apm-jaxws-plugin/target/site/jacoco/jacoco.xml bytes=4575
[2020-05-31T15:47:47.404Z]     + ./apm-agent-plugins/apm-apache-httpclient-plugin/target/site/jacoco/jacoco.xml bytes=41392
[2020-05-31T15:47:47.667Z]     + ./apm-agent-plugins/apm-redis-plugin/apm-redis-common/target/site/jacoco/jacoco.xml bytes=3101
[2020-05-31T15:47:47.667Z]     + ./apm-agent-plugins/apm-redis-plugin/apm-jedis-plugin/target/site/jacoco/jacoco.xml bytes=7365
[2020-05-31T15:47:47.667Z]     + ./apm-agent-plugins/apm-redis-plugin/apm-redisson-plugin/target/site/jacoco/jacoco.xml bytes=4672
[2020-05-31T15:47:47.667Z]     + ./apm-agent-plugins/apm-redis-plugin/apm-lettuce-plugin/target/site/jacoco/jacoco.xml bytes=24314
[2020-05-31T15:47:47.667Z]     + ./apm-agent-plugins/apm-httpclient-core/target/site/jacoco/jacoco.xml bytes=5071
[2020-05-31T15:47:47.668Z]     + ./apm-agent-plugins/apm-hibernate-search-plugin/apm-hibernate-search-plugin-5_x/target/site/jacoco/jacoco.xml bytes=6020
[2020-05-31T15:47:47.668Z]     + ./apm-agent-plugins/apm-jms-plugin/target/site/jacoco/jacoco.xml bytes=44717
[2020-05-31T15:47:47.668Z] ==> Appending adjustments
[2020-05-31T15:47:47.668Z]     https://docs.codecov.io/docs/fixing-reports
[2020-05-31T15:47:47.938Z]     -> No adjustments found
[2020-05-31T15:47:47.938Z] ==> Gzipping contents
[2020-05-31T15:47:48.200Z] ==> Uploading reports
[2020-05-31T15:47:48.201Z]     url: https://codecov.io
[2020-05-31T15:47:48.201Z]     query: branch=eyalkoren%2Fdelay-https-connection-creation&commit=4067420042466fd20ef704f82d6535c85fd09caa&build=2&build_url=https%3A%2F%2Fapm-ci.elastic.co%2Fjob%2Fapm-agent-java%2Fjob%2Fapm-agent-java-mbp%2Fjob%2FPR-1209%2F2%2F&name=&tag=&slug=elastic%2Fapm-agent-java&service=jenkins&flags=&pr=1209&job=
[2020-05-31T15:47:48.201Z]     -> Pinging Codecov
[2020-05-31T15:47:48.201Z] https://codecov.io/upload/v4?package=bash-20200430-d757c17&token=secret&branch=eyalkoren%2Fdelay-https-connection-creation&commit=4067420042466fd20ef704f82d6535c85fd09caa&build=2&build_url=https%3A%2F%2Fapm-ci.elastic.co%2Fjob%2Fapm-agent-java%2Fjob%2Fapm-agent-java-mbp%2Fjob%2FPR-1209%2F2%2F&name=&tag=&slug=elastic%2Fapm-agent-java&service=jenkins&flags=&pr=1209&job=
[2020-05-31T15:47:48.463Z]     -> Uploading
[2020-05-31T15:47:48.726Z]     -> View reports at https://codecov.io/github/elastic/apm-agent-java/commit/4067420042466fd20ef704f82d6535c85fd09caa
[2020-05-31T15:47:48.839Z] Failed in branch Unit Tests
[2020-05-31T15:47:48.908Z] Stage "Integration Tests" skipped due to earlier failure(s)
[2020-05-31T15:47:48.943Z] Stage "AfterRelease" skipped due to earlier failure(s)
[2020-05-31T15:47:48.960Z] Stage "AfterRelease" skipped due to earlier failure(s)
[2020-05-31T15:47:48.993Z] Stage "AfterRelease" skipped due to earlier failure(s)
[2020-05-31T15:47:49.768Z] Running on Jenkins in /var/lib/jenkins/workspace/_java_apm-agent-java-mbp_PR-1209@2
[2020-05-31T15:47:49.809Z] [INFO] getVaultSecret: Getting secrets
[2020-05-31T15:47:49.864Z] Masking supported pattern matches of $VAULT_ADDR or $VAULT_ROLE_ID or $VAULT_SECRET_ID
[2020-05-31T15:47:50.684Z] + chmod 755 generate-build-data.sh
[2020-05-31T15:47:50.684Z] + ./generate-build-data.sh https://apm-ci.elastic.co/blue/rest/organizations/jenkins/pipelines/apm-agent-java/apm-agent-java-mbp/PR-1209/ https://apm-ci.elastic.co/blue/rest/organizations/jenkins/pipelines/apm-agent-java/apm-agent-java-mbp/PR-1209/runs/2 FAILURE 1186847
[2020-05-31T15:47:51.234Z] INFO: curl https://apm-ci.elastic.co/blue/rest/organizations/jenkins/pipelines/apm-agent-java/apm-agent-java-mbp/PR-1209/runs/2/steps/?limit=10000 -o steps-info.json
[2020-05-31T15:47:51.785Z] INFO: curl https://apm-ci.elastic.co/blue/rest/organizations/jenkins/pipelines/apm-agent-java/apm-agent-java-mbp/PR-1209/runs/2/tests/?status=FAILED -o tests-errors.json

Codecov Report

Merging #1209 into master will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master    #1209   +/-   ##
=========================================
  Coverage     59.29%   59.29%
  Complexity       83       83
=========================================
  Files           339      339
  Lines         15953    15953
  Branches       2225     2225
=========================================
  Hits           9460     9460
  Misses         5846     5846
  Partials        647      647

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 4067420...67fc0fb. Read the comment docs.


No binaries attached to the latest release

Earlier releases shipped binaries but the latest does not. Was this just forgotten or is the intention now that it should be installed through system package managers or built from source?

oops! I just forgot sorry

added


Unable activate switchbot after update to 3.00

Describe the Bug
With the latest update from version 2.13 to 3.00 everything stopped working.
I can no longer activate my switchbots
To Reproduce
try press switchbot plugin
Expected Behavior
Activate my switchbot
Relevant Log Output
Activate my switchbot

Config for homebridge-switchbot
only switch bot section

{
            "name": "SwitchBot",
            "credentials": {
                "token": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
                "secret": "xxxxxxxxxxxxxxxxxxxxxxxx",
                "notice": "Keep your Token & Secret a secret!"
            },
            "options": {
                "devices": [
                    {
                        "deviceId": "xxxxxxxxxxxxxxxxxxxxxxxx",
                        "configDeviceName": "Proxmox",
                        "configDeviceType": "Bot",
                        "connectionType": "OpenAPI",
                        "webhook": true,
                        "lock": {
                            "activate_latchbutton": false
                        }
                    },
                    {
                        "deviceId": "xxxxxxxxxxxxxxxxxxxxxxxx",
                        "configDeviceName": "NAS",
                        "configDeviceType": "Bot",
                        "connectionType": "OpenAPI",
                        "webhook": true,
                        "lock": {
                            "activate_latchbutton": false
                        }
                    }
                ],
                "irdevices": [
                    {
                        "deviceId": "xxxxxxxxxxxxxxxxxxxxxxxx",
                        "configDeviceName": "TV",
                        "configRemoteType": "TV",
                        "connectionType": "OpenAPI"
                    }
                ]
            },
            "platform": "SwitchBot"
},

Screenshots
No response
Device and Model
Activate my switchbot
Node.js Version
v18.19.0
NPM Version
10.2.3
Homebridge Version
v1.7.0
Homebridge Switchbot Plugin Version
v3.00
Homebridge Config UI X Plugin Version
v4.55.1
Operating System
Raspian/Docker

Same here. If I go back to v 2.14.0

It’s not just the bots. I have a speaker IR device exposed through the plugin and it won’t work either. As soon as I downgraded to 2.14 everything works again.
I would add debug logs but when on 3.0 I don’t even get any debug info in the logs. As soon as I reinstall 2.15 I get a ton of logs.
Is that tv in your config working? I bet not…

@iSteve-O
No, the infrared TV doesn't work either. Nothing works with version 3.0.0. I downgraded to 2.14.0. Let's wait for the fix
Thank you

Same here! Had to downgrade to 2.14.0

Same here.Downgrade to 2.14.0

Same here

Same here. Only entry in the log:
[01/02/2024, 18:16:02] [SwitchBot] Initializing SwitchBot platform...
Falling back to v2.`14.0 restores full functionality!

Same here, downgraded to the previous version

Same here. Nothing works, nothing in logs. Downgraded 2.14 and everything works again.

Is this only happening on Bots? Or are others having issues on other devices?

@donavanbecker
I also have problems with IR devices (TV and Soundbar). From the posts I understand that it doesn't work with any device
Thanks

I have the same issues with my Blind tilt and motion sensor also.
Dom
On 2 Feb 2024 at 19:27 +0000, Donavan Becker @.***>, wrote:

Is this only happening on Bots? Or are others having issues on other devices?
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you commented.Message ID: @.***>

All devices on 3.0.0, rolling back resolves.

Same problem with Smart Lock

It's all devices The plug-in never gets past initializng ...

Fresh install of homebridge and the plugin sees the same issue.

Can you try the latest beta:

Click here to find out how to install Beta
Also closing this as it is a duplicate to #898, so post any updates there.

@donavanbecker
Fixed With 3.1 verssion, thanks

Confirmed fixed with 3.1.

Yes, all fixed, thank you @donavanbecker!!

Thank you


parujar and pakaraṇān translations

@ekobastiawan  —
please search in our xml files in tfc-nusantra-epigraphy all occurrences of

"spokesman", "spokesmen" and possibly "spokesperson(s)"
"court" (when used as translation of pakaraṇān)

please change 1 to "herald(s)" and 2 to "secretariat"
(cc to @wayanjarrah for his information)

I have made the necessary adjustments but let me know If there are any files that I missed

thanks.
you didn't find any cases in Sangguran and Wurudu Kidul?
did you use the function "search in files" in Oxygen? see screenshot.

I have checked (with the help of Bli Jarrah) all cases of "spokesman", "spokesmen" and "spokesperson(s)" and replaced them with herald(s), as well as replacing "court" (pakaraṇān) to "secretariat"

thanks a lot.


Cannot Update Asset

Error message:
base.asset_id != quote.asset_id:
I guess BTS/BTS (cannot choose my asset) is the cause.

Can you elaborate? Screenshot?

Cannot change BTS to my asset name

I can handle this, although I think there might also be an issue in the operation construction code that sets the quote and base id to 1.3.0, one of the two really should be set to the id of the newly created asset. @clayop did you create this asset using the GUI?

It is an existing asset from 0.9.3

I think this is important so if you don't mind I'd like to put this in the pipeline for the next release @wmbutler


Trying to setup login locally

I am trying to get login setup for my local dev environment, I copied the sample .env file and updated the Twitter credentials. Then I tried logging in using the Twitter button while running locally. But it is not working, am I missing a step?

You might be. What error/log messages do you get?

There's this and this:
app    | [next-auth][error][signin_oauth_error]
app    | https://next-auth.js.org/errors#signin_oauth_error {
app    |   statusCode: 401,
app    |   data: '{"errors":[{"code":32,"message":"Could not authenticate you."}]}'

app    | Could not find files for /login in .next/build-manifest.json

and then in the UI it shows this:

Hmmmm ... It might not be configured right on Twitter's end assuming your credentials are correct ... you need to add the correct "Callback URI" to your twitter app settings, e.g. http://localhost:3000/api/auth/callback/twitter

Hmm what do you mean 'twitter app settings'? Maybe the readme could be expanded on this topic? I would like to give issue #103 a try but I need to get login working locally before starting this. Im also available for a screenshare at some point too if you prefer to debug this that way.

You got your credentials for https://developer.twitter.com/ right? In the app settings that you create there, you need to specify the callback uri.
Agreed that this might not be obvious for newcomers to the project. Curse of Knowledge and all that.

Ah ok, no I did not know that - I was using my real Twitter credentials. Will setup this dev option and try again, thanks!

Are any of the other auth options easier to setup than the Twitter one? Just trying to get up and running locally as quick as possible.

hey @huumn I'm able to login and create posts locally but when I try to fund my wallet I am getting this error.
   | [ app    |   503, app    |   'AddInvoiceError', app    |   { app    |     err: Error: 14 UNAVAILABLE: No connection established app    |         at Object.callErrorFromStatus (/app/node_modules/@grpc/grpc-js/build/src/call.js:31:26) app    |         at Object.onReceiveStatus (/app/node_modules/@grpc/grpc-js/build/src/client.js:179:52) app    |         at Object.onReceiveStatus (/app/node_modules/@grpc/grpc-js/build/src/client-interceptors.js:336:141) app    |         at Object.onReceiveStatus (/app/node_modules/@grpc/grpc-js/build/src/client-interceptors.js:299:181) app    |         at /app/node_modules/@grpc/grpc-js/build/src/call-stream.js:145:78 app    |         at processTicksAndRejections (internal/process/task_queues.js:77:11) { app    |       code: 14, app    |       details: 'No connection established', app    |       metadata: [Metadata] app    |     } app    |   } app    | ]
I've added the cert, macaroon and socket from a node I have running locally on Polar into the .env.sample file.
Any ideas why it is not connecting?

This indicates you can't even connect, so we can rule out cert/macaroon issues. I'd guess the socket info is wrong somehow or something else is preventing the connection.

OK thanks.  I took the socket info directly from the node I have running on polar (<IP_ADDRESS>:10001). I'll keep messing with it

AFAIK this is simply tricky to config but not to be fixed so closing.


API configuration of permissions

need to be able to configure the permissions via the API.
Use case
all config is stored within SCM including app permissions. this requires that there be an api endpoint to configure the application.
Requirement

[ ] Configure team permissions via API

mentioned in commit ed15ab00648f5d753c304f2dfb3272a287a17fee

added 2m of time spent

added 5h of time spent

mentioned in commit 776c5db8ca6b854fb598691e93653ea850e03163

mentioned in commit c0a09d5d505dedc5562be08844ccd3e7fc5b589a


"Il pleut" in meteo_france summary

When it's raining, displays in summary attribute of meteo_france's Next rain sensor "il pleut".

Still open

reopen