GPU accelerated LSTM model crashes

System information

Have I written custom code: Yes
OS Platform and Distribution (e.g.,Linux Ubuntu 16.04): Windows 10 pro 64 bit
Mobile device if the issue happens on mobile device: No
TensorFlow installed from (source or binary): pip
TensorFlow version (use command below): 2.1.0
Python version: - 3.7.3
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version: 10.2
GPU model and memory: GeForce GTX 1050ti 4GB OC, driver version 441.22

Describe the current behavior
Hi, I have this issue since yesterday. Before that, everything was working fine. I have not updated either the tensorflow version or the gpu driver or anything else for that matter in the last couple of days. This issue suddenly appeared just yesterday on its own. Below is my model,
def neural_network(vocab_size, embedding_dim, max_length, train_padded, train_labels, validation_frac, num_epochs):
    model = Sequential()
    model.add(Embedding(vocab_size, embedding_dim, input_length = max_length))
    model.add(Bidirectional(LSTM(64, return_sequences = True)))
    model.add(GlobalAveragePooling1D())
    model.add(Dropout(0.2))
    model.add(Dense(50, activation = 'relu'))
    model.add(Dropout(0.1))
    model.add(Dense(1, activation = 'sigmoid'))
    model.summary()
    model.compile(loss = 'binary_crossentropy', optimizer = 'adam', metrics = ['accuracy'])
    history = model.fit(train_padded, train_labels, epochs = num_epochs, verbose = 2, validation_split = validation_frac)
    return model, history

I am pretty sure I am not running out of memory as previously I have trained the very same model with 10 times the parameters (~25M) compared to the parameters it has right now (~2M). Even the GPU usage barely exceeds 5%. I have GTX 1050ti 4GB. I have successfully run the above model, with varying number of total parameters, plenty of times before but only since yesterday this issue is coming up. Now the model runs fine only if I omit just the LSTM layer.
Model: "sequential"
_________________________________________________________________
Layer (type)                 Output Shape              Param #
=================================================================
embedding (Embedding)        (None, 200,<PHONE_NUMBER>
_________________________________________________________________
bidirectional (Bidirectional (None, 200, 128)          98816
_________________________________________________________________
global_average_pooling1d (Gl (None, 128)               0
_________________________________________________________________
dropout (Dropout)            (None, 128)               0
_________________________________________________________________
dense (Dense)                (None, 50)                6450
_________________________________________________________________
dropout_1 (Dropout)          (None, 50)                0
_________________________________________________________________
dense_1 (Dense)              (None, 1)                 51
=================================================================
Total params: 2,025,317
Trainable params: 2,025,317
Non-trainable params: 0

Below is the exact error.
Train on 143613 samples, validate on 15958 samples
Epoch 1/5
Traceback (most recent call last):

  File "C:\Users\admin\Documents\Machine Learning\Projects\Classification\jigsaw-toxic-comment-classification-challenge\toxic_classifier.py", line 122, in <module>
    model, history = neural_network(vocab_size, embedding_dim, max_length, train_padded, toxicity[col], validation_frac, num_epochs)

  File "C:\Users\admin\Documents\Machine Learning\Projects\Classification\jigsaw-toxic-comment-classification-challenge\toxic_classifier.py", line 87, in neural_network
    history = model.fit(train_padded, train_labels, epochs = num_epochs, verbose = 2, validation_split = validation_frac)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training.py", line 819, in fit
    use_multiprocessing=use_multiprocessing)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py", line 342, in fit
    total_epochs=epochs)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py", line 128, in run_one_epoch
    batch_outs = execution_function(iterator)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\training_v2_utils.py", line 98, in execution_function
    distributed_function(input_fn))

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\def_function.py", line 568, in __call__
    result = self._call(*args, **kwds)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\def_function.py", line 599, in _call
    return self._stateless_fn(*args, **kwds)  # pylint: disable=not-callable

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\function.py", line 2363, in __call__
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\function.py", line 1611, in _filtered_call
    self.captured_inputs)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\function.py", line 1692, in _call_flat
    ctx, args, cancellation_manager=cancellation_manager))

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\function.py", line 545, in call
    ctx=ctx)

  File "C:\Users\admin\Anaconda3\lib\site-packages\tensorflow_core\python\eager\execute.py", line 67, in quick_execute
    six.raise_from(core._status_to_exception(e.code, message), None)

  File "<string>", line 3, in raise_from

InternalError:  [_Derived_]  Failed to call ThenRnnBackward with model config: [rnn_mode, rnn_input_mode, rnn_direction_mode]: 2, 0, 0 , [num_layers, input_size, num_units, dir_count, max_seq_length, batch_size, cell_num_units]: [1, 128, 64, 1, 200, 32, 64]
	 [[{{node gradients/CudnnRNN_grad/CudnnRNNBackprop}}]]
	 [[StatefulPartitionedCall_1]]
	 [[Reshape_14/_46]] [Op:__inference_distributed_function_5894]

Function call stack:
distributed_function -> distributed_function -> distributed_function

Also, once this issue occurs, the kernel keeps crashing on its own even if I am not compiling anything. I am using Spyder IDE and even restarting the kernel does not help; it simply crashes after a few seconds. Below is the log for that (it is written on a red background)
An error ocurred while starting the kernel
2020󈚨󈚧 09:10:48.429373: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020󈚨󈚧 10:25:24.630422: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2020󈚨󈚧 10:25:24.654232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:26:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.392GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020󈚨󈚧 10:25:24.655330: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020󈚨󈚧 10:25:24.660386: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020󈚨󈚧 10:25:24.665212: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020󈚨󈚧 10:25:24.667487: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020󈚨󈚧 10:25:24.672356: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020󈚨󈚧 10:25:24.675255: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020󈚨󈚧 10:25:24.685248: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020󈚨󈚧 10:25:24.686442: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2020󈚨󈚧 10:25:24.687128: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2020󈚨󈚧 10:25:24.689769: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:26:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.392GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020󈚨󈚧 10:25:24.690853: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020󈚨󈚧 10:25:24.691406: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020󈚨󈚧 10:25:24.691954: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020󈚨󈚧 10:25:24.692497: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020󈚨󈚧 10:25:24.693046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020󈚨󈚧 10:25:24.693600: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020󈚨󈚧 10:25:24.694155: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020󈚨󈚧 10:25:24.695292: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2020󈚨󈚧 10:25:25.261369: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2020󈚨󈚧 10:25:25.261990: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2020󈚨󈚧 10:25:25.262349: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2020󈚨󈚧 10:25:25.263472: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2990 MB memory) ‑> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:26:00.0, compute capability: 6.1)
2020󈚨󈚧 10:25:27.808120: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020󈚨󈚧 10:25:28.068884: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020󈚨󈚧 10:26:06.218534: E tensorflow/stream_executor/dnn.cc:596] CUDNN_STATUS_INTERNAL_ERROR
in tensorflow/stream_executor/cuda/cuda_dnn.cc(1921): 'cudnnRNNBackwardData( cudnn.handle(), rnn_desc.handle(), model_dims.max_seq_length, output_desc.handles(), output_data.opaque(), output_desc.handles(), output_backprop_data.opaque(), output_h_desc.handle(), output_h_backprop_data.opaque(), output_c_desc.handle(), output_c_backprop_data.opaque(), rnn_desc.params_handle(), params.opaque(), input_h_desc.handle(), input_h_data.opaque(), input_c_desc.handle(), input_c_data.opaque(), input_desc.handles(), input_backprop_data‑>opaque(), input_h_desc.handle(), input_h_backprop_data‑>opaque(), input_c_desc.handle(), input_c_backprop_data‑>opaque(), workspace.opaque(), workspace.size(), reserve_space_data‑>opaque(), reserve_space_data‑>size())'
2020󈚨󈚧 10:26:06.221888: W tensorflow/core/framework/op_kernel.cc:1655] OP_REQUIRES failed at cudnn_rnn_ops.cc:1922 : Internal: Failed to call ThenRnnBackward with model config: [rnn_mode, rnn_input_mode, rnn_direction_mode]: 2, 0, 0 , [num_layers, input_size, num_units, dir_count, max_seq_length, batch_size, cell_num_units]: [1, 128, 64, 1, 200, 32, 64]
2020󈚨󈚧 10:26:06.223371: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Internal: Failed to call ThenRnnBackward with model config: [rnn_mode, rnn_input_mode, rnn_direction_mode]: 2, 0, 0 , [num_layers, input_size, num_units, dir_count, max_seq_length, batch_size, cell_num_units]: [1, 128, 64, 1, 200, 32, 64]
[[{{node gradients/CudnnRNN_grad/CudnnRNNBackprop}}]]
2020󈚨󈚧 10:26:06.225063: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Internal: {{function_node __inference___backward_cudnn_lstm_with_fallback_4410_4588_specialized_for_StatefulPartitionedCall_1_at___inference_distributed_function_5894}} {{function_node __inference___backward_cudnn_lstm_with_fallback_4410_4588_specialized_for_StatefulPartitionedCall_1_at___inference_distributed_function_5894}} Failed to call ThenRnnBackward with model config: [rnn_mode, rnn_input_mode, rnn_direction_mode]: 2, 0, 0 , [num_layers, input_size, num_units, dir_count, max_seq_length, batch_size, cell_num_units]: [1, 128, 64, 1, 200, 32, 64]
[[{{node gradients/CudnnRNN_grad/CudnnRNNBackprop}}]]
[[StatefulPartitionedCall_1]]
[[Reshape_14/_46]]
2020󈚨󈚧 10:26:06.228126: W tensorflow/core/common_runtime/base_collective_executor.cc:217] BaseCollectiveExecutor::StartAbort Internal: {{function_node __inference___backward_cudnn_lstm_with_fallback_4410_4588_specialized_for_StatefulPartitionedCall_1_at___inference_distributed_function_5894}} {{function_node __inference___backward_cudnn_lstm_with_fallback_4410_4588_specialized_for_StatefulPartitionedCall_1_at___inference_distributed_function_5894}} Failed to call ThenRnnBackward with model config: [rnn_mode, rnn_input_mode, rnn_direction_mode]: 2, 0, 0 , [num_layers, input_size, num_units, dir_count, max_seq_length, batch_size, cell_num_units]: [1, 128, 64, 1, 200, 32, 64]
[[{{node gradients/CudnnRNN_grad/CudnnRNNBackprop}}]]
[[StatefulPartitionedCall_1]]
2020󈚨󈚧 10:35:24.183417: F .\tensorflow/core/kernels/random_op_gpu.h:232] Non‑OK‑status: GpuLaunchKernel(FillPhiloxRandomKernelLaunch, num_blocks, block_size, 0, d.stream(), gen, data, size, dist) status: Internal: unspecified launch failure

To get rid of the recurrent kernel crashes I have to restart Spyder every time. None of this had ever occurred before yesterday and I can say for sure I have not updated anything in the last 1 month at least. my TF version is 2.1 and the GPU driver version is 441.22.
Describe the expected behavior
should compile to completion
Standalone code to reproduce the issue
Code
Other info / logs
Already included the logs above.

@diggee,
While reproducing the issue, I ran into an error stating FileNotFoundError: [Errno 2] File train.csv does not exist: 'train.csv'
In order to expedite the trouble-shooting process, could you please provide all the supporting files required to reproduce the issue reported here. Thanks!

@diggee,
While reproducing the issue, I ran into an error stating FileNotFoundError: [Errno 2] File train.csv does not exist: 'train.csv'
In order to expedite the trouble-shooting process, could you please provide all the supporting files required to reproduce the issue reported here. Thanks!

Hi, the data was bigger than Github's allowed size limit. Can you please download it from here

@diggee,
I was able to run the code without any issues. Please find the gist of it here.
Could you please check if you are able to reproduce the error in a virtual environment. Thanks!

hey @amahendrakar , after some testing I have realized that this issue randomly pops up on its own after running LSTM models for sometime. Restarting my computer is the only way to stop it from crashing the kernel again and again. Just restarting Spyder does not help; I have to restart the PC itself. Maybe this issue is related to how long the kernel is continuously used for, I am not sure. Since I have figured out a (temporary) solution for the time being, I am closing this issue. Thanks for your help.

I'm having a similar problem. Happens at random times. Totally freezes the computer, even the mouse cursor. Only solution is a hard reset.
Using tf-nightly-gpu 2.4.0.dev20201012.


Upgrade identity-extension-utils version

$subject to 1.0.21.
Related issue: https://github.com/wso2/product-is/issues/21200

PR builder started
Link: https://github.com/wso2/product-is/actions/runs/12116956528

PR builder completed
Link: https://github.com/wso2/product-is/actions/runs/12116956528
Status: success


i18n(ko-KR): update zerops.mdx

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update zerops.mdx
#8727

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Missing list of supported data sources

In the following page:
https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-use-directquery
You can find this statement:
"For a full listing of data sources that support DirectQuery, see Data sources supported by DirectQuery."
There's no such full listing the power-bi-data-sources page. In particular it's not clear whether ODATA is supported or only relational databases.

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

ID: 3c34c249-033f-4156-0abc-8d16cbe355a0
Version Independent ID: 20dc29c2-9cb7-2322-e80b-3f801bc34cfe
Content: Power BI data sources - Power BI
Content Source: powerbi-docs/connect-data/power-bi-data-sources.md
Service: powerbi
Sub-service: pbi-data-sources
GitHub Login: @davidiseminger
Microsoft Alias: davidi

It is a shame that this page has changed.  Back before 30th March it had more useful information for Power BI users with a grid showing which connectors supported the gateway, and that information is missing from the page which is now linked for Power Query .  Previous grid headers:
| Data source | Connect from Desktop | Connect and refresh from service | DirectQuery / Live connection | Gateway (supported) | Gateway (required) | Power BI Dataflows |

Great point! We've recently changed how we identify support for DirectQuery, for better sustainability, and I've updated that article to reflect. Thanks for posting this, that update should appear in a day or so.
Thanks again.


feature/comment_icon

Nit: Better icon for number of comments needed #162

LGTM

Actually, just played with staging in IE and the icon runs into the count. Mind adding some padding @kristysnet? Feel free to commit it straight to master.


Docker working (for devs)

Fixes #133. Docker images can now be built from source. I'm running a validator node now inside a container. Note the following changes:

Added .dockerignore to not waste time copying irrelevant files into build context.
Made docker build use make, so that the Makefile is the only place where builds are defined
Changed Makefile to provide separate, independent targets for rust and go builds (the go build's dependence on the rust build entangled the rust & go stages)
Changed Makefile to build the cli with ilxd for the release target & updated .gitignore to ignore it

To consider going forward:

Images can be built from source right now. Alpha releases can be sent to dockerhub if it makes sense, with some admin overhead (hub account, github actions, ...).
Mixing languages in the source tree is confusing, especially since the rust pieces have their own separate build products. IMO the rust components should be moved to the top level instead of buried in with the go code - e.g. /crypto-rust and /zk-rust top-level directories. And, rename the *.a files and build targets to reflect the top-level names.
The Makefile should be turned into a proper Makefile with dependencies, and maybe even graduated to CMake. E.g. the go code should be dependent on the protobuf sources; CUDA builds should be separate targets, not configuration.
Consider sending all build products (libs, executables) to a /build directory to separate them out from code.
Not sure how to deal with CUDA - probably have a separate Dockerfile and have two images for every release?

Looks like its working good!


Link to model detail page in errors

Before:
You don't have permission to access resource at URL: https://www.kaggle.com/api/v1/models/keras/g_mini/keras/g_mini_2b_en/download
Please make sure you are authenticated if you are trying to access a private resource or a resource requiring consent.

After:
You don't have permission to access resource at URL: https://www.kaggle.com/models/keras/g_mini/frameworks/keras/variations/g_mini_2b_en
Please make sure you are authenticated if you are trying to access a private resource or a resource requiring consent.

http://b/323204229

cc/ @mayankmalik-colab You may want to do something similar to ensure people on Colab get a nice error message.


Make installer work on any os/arch and add installer tests

Will this fix https://github.com/cdr/code-server/issues/3585?

Nope but I'll add a fix.


This lib treat properly sql injection?

I'm considering using this lib to replace parameters before submitting it to AWS Athena. They didn't implement anything like this in their SDK. So I have a point of concern, this lib treat properly SQL Injection?
Thanks for your time

@pimtel Sorry about the late response. I seem to have missed the notification about your question.
This library does not concern itself with constructing the query itself. It only performs substitution between parameter styles. So long as the SQL query is constructed in an injection safe manner, the query will remain injection safe using this library. In Python most SQL drivers adhere to the PEP 249 DB API 2 specification. They provide SQL injection safe methods for executing queries using parameters.


Ping script correctly placed?

Please confirm that this script is on all templates:

@room421 it is on all the pages right before the <body> tag closes. If you inspect any of the pages, you should be able to see it.


[BUG] [VSCode Extension] Can't find tool promptflow_vectordb.tool.vector_db_lookup.VectorDBLookup.search

Describe the bug
My prompt flow is using vector_db_lookup. In Azure ML studio, that prompt flow is valid. However error occurred that flow opened in Visual Studio Code as follows:
Can't find tool promptflow_vectordb.tool.vector_db_lookup.VectorDBLookup.search
The package may not be installed in your Python environment.

How To Reproduce the bug

Create prompt flow include vector db lookup of Azure AI Search on Azure ML Studio ( ml.azure.com )
Download flow.dag.yaml and other files.
Open flow using Visual Studio code + promptflow extension.
vector_db_lookup node has error.

Environment Information

promptflow installed version:1.0.0
promptflow-tools installed version: 0.1.0b15
Operating System: Windows 11 x64 23H2
Python Version: Python 3.9.18
VS Code version: 1.84.2
Prompt Flow extension version: v1.5.0

Additional context
Prompt flow GUI editor in Azure ML Studio can add vector db lookup node, but Visual Studio code can not add it.

Where is promptflow_vectordb.tool.vector_db_lookup.VectorDBLookup?

Hi @buchizo, sorry for the inconvience, the package needs to be installed manually in your environment, please install the promptflow-vectordb.

@brynn-code I got it! Thank you so much. I could use vector lookup node after installed promptflow-vectordb. If possible, I want to see dependency packages in solution files of prompt flow. e.g. requirements.txt.

No problem. @jiazengcindy is working on add the dependency to requirements, the issue will be closed once the task done.

Hi @buchizo,  promptflow-vectordb have been added to the requirements.txt, please check, thanks very much!

Close this bug since task has been completed.


Make nxlog.exe "failed to open..." messages easy to filter out

Currently nxlog.exe "error" logs get logged by the LogSearchShipper process (see src/LogsearchShipper.Core/NxLog/NxLogOutputParser.cs ) as:
{"@timestamp":"2015-01-16T16:48:56.265Z","Message":"failed to open \\\\INX-SRV-APPL09\\Logs\\tibco\\*.log; The filename, directory name, or volume label syntax is incorrect.","logger":"nxlog.exe","level":"ERROR"}
{"@timestamp":"2015-01-16T16:48:56.266Z","Message":"input file does not exist: \\\\INX-SRV-APPL46\\Logs\\Apps\\STP\\stp.log","logger":"nxlog.exe","level":"WARN"}
{"@timestamp":"2015-01-16T16:49:06.731Z","Message":"apr_stat failed on file \\\\INX-SRV-TIB03\\Logs\\tibco\\*.log; The filename, directory name, or volume label syntax is incorrect.","logger":"nxlog.exe","level":"ERROR"}

We need a way to easily filter these out when looking for other logs.

I propose that all these logs are set to level WARN, and if possible, get a new key=>value pair "Category":"MISSING_FILE" (or some additional field that you can filter on)

@mrdavidlaing, as far as I understand these messages are produced by nxlog. Should I match all messages with these values and switch them to "Warning" level?

Yes - the [src/LogsearchShipper.Core/NxLog/NxLogOutputParser.cs](https://github.com/cityindex/LogSearchShipper/blob/master/src/LogsearchShipper.Core/NxLog/NxLogOutputParser.cs class is responsible for translating the nxlog.exe log messages into Log4Net text.
Currently it just passes the values through with basically no modification; but I think that it should be extended so that the failed to open..., input file does not exist... and apr_stat failed on file... messages get set to level WARN and, (if possible), get an additional "Category":"MISSING_FILE" field.

@mrdavidlaing, not sure how to inject this "Category":"MISSING_FILE" field. It seems to be impossible without some refactoring.

It seems I've found a way... does this formatting look ok?
2015-01-21 03:58:19,010 [12] WARN  nxlog.exe - { Message = failed to open directory: \\\\PKH-PPE-WEB24\\Logs\\IIS\\W3SVC1\: The specified path is invalid., Category = MISSING_FILE }
2015-01-21 03:58:19,010 [10] INFO  Topshelf.Hosts.ConsoleRunHost - The LogSearchShipper service is now running, press Control+C to exit.
2015-01-21 03:58:19,011 [12] INFO  nxlog.exe - { Message = nxlog-ce-2.8.1248 started }
2015-01-21 03:58:19,012 [12] WARN  nxlog.exe - { Message = Module in_file0 has no input files to read }
2015-01-21 03:58:19,012 [12] INFO  nxlog.exe - { Message = input file LogSearchShipper.log was truncated, restarting from beginning }
2015-01-21 03:58:20,365 [12] INFO  nxlog.exe - { Message = successfully connected to ingestor.meta.logsearch.io:443 }

{"@timestamp":"2015-01-21T03:58:19.010Z","Message":"failed to open directory: \\\\\\\\PKH-PPE-WEB24\\\\Logs\\\\IIS\\\\W3SVC1\\: The specified path is invalid.","Category":"MISSING_FILE","logger":"nxlog.exe","level":"WARN"}
{"@timestamp":"2015-01-21T03:58:19.010Z","Message":"The LogSearchShipper service is now running, press Control+C to exit.","logger":"Topshelf.Hosts.ConsoleRunHost","level":"INFO"}
{"@timestamp":"2015-01-21T03:58:19.011Z","Message":"nxlog-ce-2.8.1248 started","logger":"nxlog.exe","level":"INFO"}
{"@timestamp":"2015-01-21T03:58:19.012Z","Message":"Module in_file0 has no input files to read","logger":"nxlog.exe","level":"WARN"}
{"@timestamp":"2015-01-21T03:58:19.012Z","Message":"input file LogSearchShipper.log was truncated, restarting from beginning","logger":"nxlog.exe","level":"INFO"}
{"@timestamp":"2015-01-21T03:58:20.365Z","Message":"successfully connected to ingestor.meta.logsearch.io:443","logger":"nxlog.exe","level":"INFO"}

That formatting looks good to me.  Lets get it deployed and see if it helps.  Where is the code?

@mrdavidlaing, here it is https://github.com/cityindex/LogSearchShipper/pull/71


Forced quit while login in ubuntu 18.04.4 with xrdp 0.9.5

As the title, after login the diagram came out and disappear rapidly. When I tried it In default condition I found an error message in xrdp.log that showed I don't have permission to read the key file. I googled a solution to fixed that but the forced quit is still happening. Here's some environment info:
Hardware: both Jetson TX2 and Xavier
OS: Ubuntu 18.04.4
xrdp version: 0.9.5
xorgxrdp version: 0.9.5-2
Client OS / Client software: tried both windows remote control and remmina in ubuntu16 and 18
info from xrdp.log:
[20200514-15:29:47] [INFO ] Socket 12: AF_INET6 connection received from ::ffff:<IP_ADDRESS> port 45120
[20200514-15:29:47] [DEBUG] Closed socket 12 (AF_INET6 ::ffff:<IP_ADDRESS> port 3389)
[20200514-15:29:47] [DEBUG] Closed socket 11 (AF_INET6 :: port 3389)
[20200514-15:29:47] [INFO ] Using default X.509 certificate: /etc/xrdp/cert.pem
[20200514-15:29:47] [INFO ] Using default X.509 key file: /etc/xrdp/key.pem
[20200514-15:29:47] [DEBUG] TLSv1.2 enabled
[20200514-15:29:47] [DEBUG] TLSv1.1 enabled
[20200514-15:29:47] [DEBUG] TLSv1 enabled
[20200514-15:29:47] [DEBUG] Security layer: requested 3, selected 1
[20200514-15:29:47] [INFO ] connected client computer name: robotics-iiyama
[20200514-15:29:47] [INFO ] TLS connection established from ::ffff:<IP_ADDRESS> port 45120: TLSv1.3 with cipher TLS_AES_256_GCM_SHA384
[20200514-15:29:47] [DEBUG] xrdp_00002bb7_wm_login_mode_event_00000001
[20200514-15:29:47] [INFO ] Cannot find keymap file /etc/xrdp/km-e0010411.ini
[20200514-15:29:47] [INFO ] Loading keymap file /etc/xrdp/km-00000411.ini
[20200514-15:29:47] [WARN ] local keymap file for 0xe0010411 found and doesn't match built in keymap, using local keymap file
[20200514-15:29:47] [DEBUG] xrdp_wm_log_msg: connecting to sesman ip <IP_ADDRESS> port 3350
[20200514-15:29:48] [INFO ] xrdp_wm_log_msg: sesman connect ok
[20200514-15:29:48] [DEBUG] xrdp_wm_log_msg: sending login info to session manager, please wait...
[20200514-15:29:48] [DEBUG] return value from xrdp_mm_connect 0
[20200514-15:29:48] [INFO ] xrdp_wm_log_msg: login successful for display 10
[20200514-15:29:48] [DEBUG] xrdp_wm_log_msg: started connecting
[20200514-15:29:48] [INFO ] lib_mod_log_peer: xrdp_pid=11191 connected to X11rdp_pid=11195 X11rdp_uid=1000 X11rdp_gid=1000 client_ip=::ffff:<IP_ADDRESS> client_port=45120
[20200514-15:29:48] [DEBUG] xrdp_wm_log_msg: connected ok
[20200514-15:29:48] [DEBUG] xrdp_mm_connect_chansrv: chansrv connect successful
[20200514-15:29:48] [DEBUG] Closed socket 26 (AF_INET6 ::1 port 39552)
[20200514-15:29:48] [INFO ] The following channel is allowed: cliprdr (0)
[20200514-15:29:48] [INFO ] The following channel is allowed: drdynvc (1)
[20200514-15:29:48] [DEBUG] The allow channel list now initialized for this session
[20200514-15:29:49] [DEBUG] Closed socket 28 (AF_UNIX)
[20200514-15:29:49] [DEBUG] Closed socket 12 (AF_INET6 ::ffff:<IP_ADDRESS> port 3389)
[20200514-15:29:49] [DEBUG] xrdp_mm_module_cleanup
[20200514-15:29:49] [DEBUG] Closed socket 27 (AF_UNIX)

I will attach more if needed. Please help me! Thank you!

Hi @yyf202xz
The xrdp.log looks fine, so we will need to look elsewhere.
Can you do the following:-

Make a note of the time on the machine (for example, 11:14:05)
Try to log in again over xrdp.

Then post the output of the following commands, replacing 11:14:05 with the time you noted earlier:-
loginctl
dpkg -l "*xrdp*" "dbus*"
sudo journalctl -S 11:14:05

Thanks,

Hi @matt335672
Thank you for your reply.
I followed your instructions and here's the result:
(robotics is my username, 5月 means May)
$ loginctl

SESSION        UID USER             SEAT             TTY
c1        120 gdm              seat0            tty1
4       1000 robotics         seat0            tty2
2       1000 robotics         seat0            tty2

$ dpkg -l "*xrdp*" "dbus*"

Desired=Unknown/Install/Remove/Purge/Hold
| Status=Not/Inst/Conf-files/Unpacked/halF-conf/Half-inst/trig-aWait/Trig-pend
|/ Err?=(none)/Reinst-required (Status,Err: uppercase=bad)
||/ Name           Version      Architecture Description
+++-==============-============-============-=================================
ii  dbus           1.12.2-1ubun arm64        simple interprocess messaging sys
un  dbus-session-b         (no description available)
ii  dbus-user-sess 1.12.2-1ubun arm64        simple interprocess messaging sys
ii  dbus-x11       1.12.2-1ubun arm64        simple interprocess messaging sys
ii  xorgxrdp       0.9.5-2      arm64        Remote Desktop Protocol (RDP) mod
ii  xrdp           0.9.5-2      arm64        Remote Desktop Protocol (RDP) ser
un  xrdp-pulseaudi         (no description available)

$ sudo journalctl -S 21:51:46 (I will attach only fail info here and below that will be the complete info )

5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992] Successfully activated service 'org.gtk.vfs.Daemon'
5月 14 21:51:46 robotics-xavier systemd[7677]: Started Virtual filesystem service.
5月 14 21:51:46 robotics-xavier gnome-session[9051]: MESA-LOADER: failed to open swrast (search paths /usr/lib/aarch64-linux-gnu/dri:$${ORIGIN}/dri:/usr/lib/dri)
5月 14 21:51:46 robotics-xavier gnome-session[9051]: libGL error: failed to load driver: swrast
5月 14 21:51:46 robotics-xavier gnome-session[9051]: gnome-session-binary[9051]: WARNING: software acceleration check failed: Child process exited with code 1
5月 14 21:51:46 robotics-xavier gnome-session-binary[9051]: WARNING: software acceleration check failed: Child process exited with code 1
5月 14 21:51:46 robotics-xavier gnome-session[9051]: gnome-session-binary[9051]: CRITICAL: We failed, but the fail whale is dead. Sorry....
5月 14 21:51:46 robotics-xavier gnome-session-binary[9051]: CRITICAL: We failed, but the fail whale is dead. Sorry....
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: (9049)(548069156688)[CORE ] window manager (pid 9051) did exit, cleaning up session
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: (9049)(548069156688)[INFO ] calling auth_stop_session and auth_end from pid 9049
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: pam_unix(xrdp-sesman:session): session closed for user robotics

(here's the complete version)

-- Logs begin at Thu 2020-05-14 21:49:09 JST, end at Thu 2020-05-14 21:53:51 JST
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[INFO ] lib_mod
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] xrdp_wm
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] xrdp_mm
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] Closed
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[INFO ] The fol
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[INFO ] The fol
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] The all
5月 14 21:51:46 robotics-xavier gnome-session[9051]: MESA-LOADER: failed to ope
5月 14 21:51:46 robotics-xavier gnome-session[9051]: libGL error: failed to loa
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992]
5月 14 21:51:46 robotics-xavier systemd[7677]: Starting Accessibility services
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992]
5月 14 21:51:46 robotics-xavier systemd[7677]: Started Accessibility services b
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: dbus-daemon[9137]: A
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992]
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: dbus-daemon[9137]: S
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: SpiRegistry daemon i
5月 14 21:51:46 robotics-xavier systemd[7677]: Starting Virtual filesystem serv
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992]
5月 14 21:51:46 robotics-xavier systemd[7677]: Started Virtual filesystem servi
5月 14 21:51:46 robotics-xavier gnome-session[9051]: MESA-LOADER: failed to ope
5月 14 21:51:46 robotics-xavier gnome-session[9051]: libGL error: failed to loa
lines 1-23...skipping...
-- Logs begin at Thu 2020-05-14 21:49:09 JST, end at Thu 2020-05-14 21:53:51 JST. --
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[INFO ] lib_mod_log_peer: xrdp_pid=9044 connected to X11rdp_pid=9052 X11rdp_uid=1000 X11rdp_gid=1000 cl
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] xrdp_wm_log_msg: connected ok
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] xrdp_mm_connect_chansrv: chansrv connect successful
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] Closed socket 26 (AF_INET6 ::1 port 38566)
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[INFO ] The following channel is allowed: cliprdr (0)
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[INFO ] The following channel is allowed: drdynvc (1)
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] The allow channel list now initialized for this session
5月 14 21:51:46 robotics-xavier gnome-session[9051]: MESA-LOADER: failed to open swrast (search paths /usr/lib/aarch64-linux-gnu/dri:$${ORIGIN}/dri:/usr/lib/dri)
5月 14 21:51:46 robotics-xavier gnome-session[9051]: libGL error: failed to load driver: swrast
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992] Activating via systemd: service name='org.a11y.Bus' unit='at-spi-dbus-bus.service' reque
5月 14 21:51:46 robotics-xavier systemd[7677]: Starting Accessibility services bus...
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992] Successfully activated service 'org.a11y.Bus'
5月 14 21:51:46 robotics-xavier systemd[7677]: Started Accessibility services bus.
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: dbus-daemon[9137]: Activating service name='org.a11y.atspi.Registry' requested by ':1.0' (uid=1000 pid=9131
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992] Activating via systemd: service name='org.gtk.vfs.Daemon' unit='gvfs-daemon.service' req
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: dbus-daemon[9137]: Successfully activated service 'org.a11y.atspi.Registry'
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: SpiRegistry daemon is running with well-known name - org.a11y.atspi.Registry
5月 14 21:51:46 robotics-xavier systemd[7677]: Starting Virtual filesystem service...
5月 14 21:51:46 robotics-xavier dbus-daemon[8992]: [session uid=1000 pid=8992] Successfully activated service 'org.gtk.vfs.Daemon'
5月 14 21:51:46 robotics-xavier systemd[7677]: Started Virtual filesystem service.
5月 14 21:51:46 robotics-xavier gnome-session[9051]: MESA-LOADER: failed to open swrast (search paths /usr/lib/aarch64-linux-gnu/dri:$${ORIGIN}/dri:/usr/lib/dri)
5月 14 21:51:46 robotics-xavier gnome-session[9051]: libGL error: failed to load driver: swrast
5月 14 21:51:46 robotics-xavier gnome-session[9051]: gnome-session-binary[9051]: WARNING: software acceleration check failed: Child process exited with code 1
5月 14 21:51:46 robotics-xavier gnome-session-binary[9051]: WARNING: software acceleration check failed: Child process exited with code 1
5月 14 21:51:46 robotics-xavier gnome-session[9051]: gnome-session-binary[9051]: CRITICAL: We failed, but the fail whale is dead. Sorry....
5月 14 21:51:46 robotics-xavier gnome-session-binary[9051]: CRITICAL: We failed, but the fail whale is dead. Sorry....
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: (9049)(548069156688)[CORE ] window manager (pid 9051) did exit, cleaning up session
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: (9049)(548069156688)[INFO ] calling auth_stop_session and auth_end from pid 9049
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: pam_unix(xrdp-sesman:session): session closed for user robotics
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: (9049)(548069156688)[DEBUG] cleanup_sockets:
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]: XIO:  fatal IO error 11 (Resource temporarily unavailable) on X server ":10.0"
5月 14 21:51:46 robotics-xavier at-spi-bus-launcher[9132]:       after 21 requests (19 known processed) with 0 events remaining.
5月 14 21:51:46 robotics-xavier xrdp-sesman[9049]: (9049)(548069156688)[DEBUG] cleanup_sockets: deleting /var/run/xrdp/sockdir/xrdpapi_10
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] Closed socket 28 (AF_UNIX)
5月 14 21:51:46 robotics-xavier xrdp-sesman[6277]: (6277)(548069156688)[INFO ] ++ terminated session:  username robotics, display :10.0, session_pid 9049, ip ::ffff:19
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] Closed socket 12 (AF_INET6 ::ffff:<IP_ADDRESS> port 3389)
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] xrdp_mm_module_cleanup
5月 14 21:51:46 robotics-xavier xrdp[9044]: (9044)(548244955152)[DEBUG] Closed socket 27 (AF_UNIX)

I'm sorry if they are difficult to read. First time using github still not get used to it :(
Maybe this is a gnome problem I guess? I did some google briefly but most of them are old and  lots of solutions are just by adding something to xsession to use another desktop environment. I used xrdp with gnome before and it was very good. It will be nice to be able to use this combination again.

It looks to me like you're getting the hang of github already :smiley:
There look like two problems here

If you're logged in on the console and you want to use xrdp too, you'll need to remove the dbus-user-session package. See the wiki for more information.
GNOME needs the X server to support 3D acceleration. Normally it does, but something is stopping yours from working. Since you're using Jetson, I suspect this is your NVidia driver installation.

I'm afraid this isn't really my area of expertise, and I don't have access to any NVidia hardware to try to replicate this. I can give you some suggestions:-

If you've installed the NVidia driver using the NVidia run package, remove it and install the driver from the Ubuntu repositories instead (instructions here).
You could try using the Xvnc session type instead of Xorg. You may need to install tigervnc-standalone-server to get a VNC server installed.

Hope that's useful.

@matt335672 Thank you! It will be great if I could use xrdp while logged in on the console. Thank you for instructions.
But unfortunately Xvnc doesn't work and I'm not sure Jetson can install driver as same as normal PC.
I set up it with installing Jetpack by Nvidia SDK manager(It's like an OS image flashing process)
and after that I didn't have to install drivers additionally.
I saw something on this page https://github.com/neutrinolabs/xrdp/issues/1128
that you said

The Xorg backend supplied as part of the Ubuntu xrdp-0.9.5-2 package will not work with the GNOME desktop because of #1122
The Xvnc backend supplied as part of the vnc4server will not work with the GNOME desktop because it doesn't support GLX.

Then I took a look at #1122 and have no idea what you are talking about :(
I have tried xcfe4 too and it worked but its just so difficult to use to me.
Maybe I can use an older version of xrdp that may could solve this problem?
Or as this is a gnome problem the only option to me is to change to another desktop environment?

I think the problem is that GNOME requires a 3d accelerated desktop, and occasionally the NVidia drivers get in the way of this for remote desktops.
#1122 should no longer be an issue.
When you say Xvnc doesn't work, what do you mean? What are the symptoms? Have you installed tigervnc-standalone-server?

@matt335672 Sorry I didn't mention the symptoms. It was same as using xrdp, dialog disappears while login. I tried it after install the latest version of tigervnc-standalone-server which is (1.7.0+dfsg-8ubuntu2). Any suggestions?

Have a look at this script and see if you're happy running it on your system (NOT as root).
It's a bit basic, but hopefully will tell us what is going on with Xvnc.
If you get a 'server not running message`, try a different port number.
#!/bin/bash

XDPYINFO=/usr/bin/xdpyinfo
GLXINFO=/usr/bin/glxinfo
DISPLAY=:11

echo "- Checking X server"
xserver=$(which Xvnc)
if [[ -z $xserver || ! -x $xserver ]]; then
    echo "** Can't find Xvnc server" >&2
    exit 1
fi

ls -l $xserver
while [[ -h $xserver ]]; do
    xserver=$(readlink $xserver)
    ls -l $xserver
done

if [[ ! -x $XDPYINFO ]]; then
    echo "** Please install $XDPYINFO (Debian package x11-utils)" >&2
    exit 1
fi

if [[ ! -x $GLXINFO ]]; then
    echo "** Please install $GLXINFO (Debian package mesa-utils)" >&2
    exit 1
fi

echo "- Starting X server on display :$DISPLAY"
xlog=$(mktemp /tmp/xlog.XXXXXXXXXX)
$xserver $DISPLAY -ac >$xlog 2>&1 &
xpid=$!

sleep 5
if $(kill -0 $xpid); then
    echo "  Server started OK. Querying server"
    xdpyinfo -display $DISPLAY | sed -e '/^screen #/,$d'
    glxinfo -display $DISPLAY | sed -e '/GLX Visuals/,$d'
    kill $xpid
else
    echo " Server failed to start. Log follows:"
    cat $xlog
fi
wait

rm -f $xlog

@matt335672 Thank you for the script! I run it and it seems showing something!
For the first time I run it it told me I need mesa-utils.
Here is the info I get after I installed it'

robotics@robotics-xavier:~$ ./test

Checking X server
lrwxrwxrwx 1 root root 22  5月 15 19:21 /usr/bin/Xvnc -> /etc/alternatives/Xvnc
lrwxrwxrwx 1 root root 18  5月 15 19:21 /etc/alternatives/Xvnc -> /usr/bin/Xtigervnc
-rwxr-xr-x 1 root root 2363520 12月  5  2017 /usr/bin/Xtigervnc
Starting X server on display ::11
Server started OK. Querying server
name of display:    :11
version number:    11.0
vendor string:    The X.Org Foundation
vendor release number:    11905000
X.Org version: 1.19.5
maximum request size:  16777212 bytes
motion buffer size:  256
bitmap unit, bit order, padding:    32, LSBFirst, 32
image byte order:    LSBFirst
number of supported pixmap formats:    6
supported pixmap formats:
depth 1, bits_per_pixel 1, scanline_pad 32
depth 4, bits_per_pixel 8, scanline_pad 32
depth 8, bits_per_pixel 8, scanline_pad 32
depth 16, bits_per_pixel 16, scanline_pad 32
depth 24, bits_per_pixel 32, scanline_pad 32
depth 32, bits_per_pixel 32, scanline_pad 32
keycode range:    minimum 8, maximum 255
focus:  PointerRoot
number of extensions:    26
BIG-REQUESTS
Composite
DAMAGE
DOUBLE-BUFFER
DPMS
GLX
Generic Event Extension
MIT-SCREEN-SAVER
MIT-SHM
Present
RANDR
RECORD
RENDER
SECURITY
SGI-GLX
SHAPE
SYNC
VNC-EXTENSION
X-Resource
XC-MISC
XFIXES
XINERAMA
XInputExtension
XKEYBOARD
XTEST
XVideo
default screen number:    0
number of screens:    1

MESA-LOADER: failed to open swrast (search paths /usr/lib/aarch64-linux-gnu/dri:$${ORIGIN}/dri:/usr/lib/dri)
libGL error: failed to load driver: swrast
X Error of failed request:  GLXBadContext
Major opcode of failed request:  152 (GLX)
Minor opcode of failed request:  6 (X_GLXIsDirect)
Serial number of failed request:  46
Current serial number in output stream:  45
name of display: :11

Some errors here and I have no idea of that pass...but I think the light is nearly forward!

Thanks for that.
This looks like a duplicate of #1519, which is currently unsolved and also involves an NVidia installation.
I've got another script for you. You will need to run this command before the script to install the required packages:-
sudo apt install ltrace strace

#!/bin/bash

GLXINFO=/usr/bin/glxinfo
DISPLAY=:11

echo "- Starting X server on display :$DISPLAY"
xlog=$(mktemp /tmp/xlog.XXXXXXXXXX)
Xvnc $DISPLAY -ac >$xlog 2>&1 &
xpid=$!

sleep 5
if $(kill -0 $xpid); then
    export DISPLAY
    echo "  Server started OK. Querying server"
    LIBGL_DEBUG=verbose glxinfo 2>&1 >/dev/null
    echo "glxinfo returned $?"
    echo "- Gathering strace information"
    strace glxinfo 2>&1 | grep 'open.*\.so"'
    echo "- Searching for swrast_dri.so"
    find / -xdev -name swrast_dri.so 2>/dev/null
    echo "- Gathering ltrace information"
    ltrace -s 128 -e dlopen glxinfo >/dev/null
    kill $xpid
else
    echo " Server failed to start. Log follows:"
    cat $xlog
fi
wait

This will give us more information on the reason the system is unable to load the swrast driver.

@matt335672 Here's info I got:

Starting X server on display ::11
Server started OK. Querying server
MESA-LOADER: failed to open swrast (search paths /usr/lib/aarch64-linux-gnu/dri:$${ORIGIN}/dri:/usr/lib/dri)
libGL error: failed to load driver: swrast
X Error of failed request:  GLXBadContext
Major opcode of failed request:  152 (GLX)
Minor opcode of failed request:  6 (X_GLXIsDirect)
Serial number of failed request:  46
Current serial number in output stream:  45
glxinfo returned 1
Gathering strace information
openat(AT_FDCWD, "/opt/ros/melodic/lib/libnvll.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/local/cuda-10.0/lib64/libnvll.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/aarch64/libnvll.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/libnvll.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "aarch64/libnvll.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "libnvll.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/tegra/libnvll.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "/opt/ros/melodic/lib/libnvrm.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/local/cuda-10.0/lib64/libnvrm.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/aarch64/libnvrm.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/libnvrm.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "aarch64/libnvrm.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "libnvrm.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/tegra/libnvrm.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "/opt/ros/melodic/lib/libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/local/cuda-10.0/lib64/libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/aarch64/libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "aarch64/libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/tegra/libnvrm_graphics.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "/opt/ros/melodic/lib/libnvdc.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/local/cuda-10.0/lib64/libnvdc.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/aarch64/libnvdc.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/libnvdc.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "aarch64/libnvdc.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "libnvdc.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/tegra/libnvdc.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "/opt/ros/melodic/lib/libnvos.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/local/cuda-10.0/lib64/libnvos.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/aarch64/libnvos.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/libnvos.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "aarch64/libnvos.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "libnvos.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/tegra/libnvos.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "/opt/ros/melodic/lib/libnvimp.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/local/cuda-10.0/lib64/libnvimp.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/aarch64/libnvimp.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "tls/libnvimp.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "aarch64/libnvimp.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "libnvimp.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/tegra/libnvimp.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/dri/tls/swrast_dri.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/aarch64-linux-gnu/dri/swrast_dri.so", O_RDONLY|O_CLOEXEC) = 4
openat(AT_FDCWD, "\$/usr/lib/aarch64-linux-gnu/dri/tls/swrast_dri.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "\$/usr/lib/aarch64-linux-gnu/dri/swrast_dri.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/dri/tls/swrast_dri.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/usr/lib/dri/swrast_dri.so", O_RDONLY|O_CLOEXEC) = -1 ENOENT (No such file or directory)
Searching for swrast_dri.so
/usr/lib/aarch64-linux-gnu/dri/swrast_dri.so
Gathering ltrace information
libGLX.so.0->dlopen("libGLX_mesa.so.0", 1 <unfinished ...>
libdrm.so.2->dlopen("libdrm.so.2.4.0", 1)        = 0x55909fee20
<... dlopen resumed> )                           = 0x55909f6260
libGLX_mesa.so.0->dlopen("libGLX_mesa.so.0", 258) = 0x55909f6260
libGLX_mesa.so.0->dlopen("/usr/lib/aarch64-linux-gnu/dri/tls/swrast_dri.so", 258) = 0
libGLX_mesa.so.0->dlopen("/usr/lib/aarch64-linux-gnu/dri/swrast_dri.so", 258) = 0
libGLX_mesa.so.0->dlopen("\$${ORIGIN}/dri/tls/swrast_dri.so", 258) = 0
libGLX_mesa.so.0->dlopen("\$${ORIGIN}/dri/swrast_dri.so", 258) = 0
libGLX_mesa.so.0->dlopen("/usr/lib/dri/tls/swrast_dri.so", 258) = 0
libGLX_mesa.so.0->dlopen("/usr/lib/dri/swrast_dri.so", 258) = 0
MESA-LOADER: failed to open swrast (search paths /usr/lib/aarch64-linux-gnu/dri:$${ORIGIN}/dri:/usr/lib/dri)
libGL error: failed to load driver: swrast
X Error of failed request:  GLXBadContext
Major opcode of failed request:  152 (GLX)
Minor opcode of failed request:  6 (X_GLXIsDirect)
Serial number of failed request:  46
Current serial number in output stream:  45
+++ exited (status 1) +++

Well everything appears to be there, but there's a problem in the GLX stack which isn't being logged. Without hardware I can't get any further.
I've found a very similar discussion on the NVidia developer forums which suggests this is an incompatibility between Jetpack and the MESA libraries installed with 18.04:-
https://forums.developer.nvidia.com/t/jetpack-4-3-mesa-loader-failed-to-open-swrast-while-in-xrdp-session/111199
I've just posted to the thread above and linked this issue, so hopefully someone from NVidia can take a look at it. This isn't an XRDP issue directly, but XRDP is affected by it.
@yyf202xz - sorry I can't give you a better solution but hopefully this will get fixed in time.

@matt335672 Thank you for everything! Maybe last time I could use it was just luck and now it went back to normal lol. I will try to find another remote desktop solution untill Nvidia fix this problem. Again, Thank you!


Add status_condition metrics for the secret store controllers

Problem Statement
SSIA. I've added the status condition metrics to the secret/cluster secret controller. Thank you for your review!
Related Issue
Closes https://github.com/external-secrets/external-secrets/issues/2151
Proposed Changes
Add new metrics to the controllers.
Checklist

[x] I have read the contribution guidelines
[x] All commits are signed with git commit --signoff
[x] My changes have reasonable test coverage
[x] All tests pass with make test
[x] I ensured my PR is ready for review with make reviewable

/ok-to-test sha=4d3ffc2


How to open the video files?

Hi, I am wondering how to open the video files provided in the baidu pan, as these files have no specific type. Could you provide me  with the necessary information？ Thanks!!

Sorry for late response. Please rename ClipShots to data.tar.gz.

Sorry for late response. Please rename ClipShots to data.tar.gz.

Thanks for your response.

Have you opened the dataset? ''rename ClipShots to data.tar.gz''? I do not quite understand what it means.

Have you opened the dataset? ''rename ClipShots to data.tar.gz''? I do not quite understand what it means.
the uploaded dataset is compressed by the 'tar' command, and then splited into multiple files by the command 'split'。 so rename these files as 'data.tar.gz.a', 'data.tar.gz.b' , and then use the command 'cat' and ‘tar’ to uncompress the archives

I have downloaded 'Clipshot-a' part , and renamed it as 'data.tar.gz.a'.I tried to use 'tar zxvf data.tar.gz.a' command. Howerver the error was shown to me that it is not in gzip format. Would you please tell me what was wrong with it,Thanks a lot.

You should download all the files, and the 'cat' them into one file, and then uncompress them
At 2019-03-15 09:27:30, "zhangshuaimm"<EMAIL_ADDRESS>wrote:
I have downloaded 'Clipshot-a' part , and renamed it as 'data.tar.gz.a'.I tried to use 'tar zxvf data.tar.gz.a' command. Howerver the error was shown to me that it is not in gzip format. Would you please tell me what was wrong with it,Thanks a lot.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub, or mute the thread.

firstly, download from baidu pan.
secondly，unzip it with

cd ClipShots
# merge splited files, and unzip it.
cat ClipShots-a ClipShots-b ClipShots-c | tar -zx


Chore(docs): Adds docs for AWS ELB AZ Down chaos

Add docs for elb az down chaos for a certain chaos duration.

This experiment tests a scenario when a zone is detached from ELB that can be used by any application.

Harness Developer Pull Request
Thanks for helping us make the Developer Hub better. The PR will be looked at
by the maintainers.
What Type of PR is This?

[ ] Issue
[ ] Feature
[ ] Maintenance/Chore

If tied to an Issue, list the Issue(s) here:

Issue(s)

House Keeping
Some items to keep track of. Screen shots of changes are optional but would help the maintainers review quicker.

[ ] Tested Locally
[ ] Optional Screen Shoot.

Preview environment: https://ci.pr.harness.io/pr-145

Preview environment: https://ci.pr.harness.io/pr-145

Preview environment: https://ci.pr.harness.io/pr-145


Vignette fix

Line 96 - the description of the sample data file illinois_corn_yield.csv includes the column "IS_CHECK", but the file included in the package does not have this field.

fixed.

Fixed by Patrick

Closed


breaking(all): rename ast to cst

The Rowan-based typed syntax tree emitted by the parser used to be called Abstract Syntax Tree (AST) but is in fact not very abstract: it preserves text input losslessly, and all tree leaves are string-based tokens. This renames it to Concrete Syntax Tree (CST) and renames various APIs accordingly.
This leaves the AST name available for a new tree representation (coming soon).

On second thought it will make more sense to have this rename in the same PR that adds the new AST, because then apollo-compiler may not need to expose the CST at all.


Add Bsky for Yani

Hi @yabellini,
I'm working on adding a Bluesky integration for the R-Ladies bot and saw that you're also on Bluesky. Please let me know

if you agree to add your handle here as well so that the bot can use it to tag you when posting about your posts
if you're also OK with being featured in an R-Ladies starter pack (I assume yes, but double-checking with everyone :))

Thank you ☺

@cosimameyer thank you so much!! I update some of my social media handles.  I don't exactly know how the YouTube one works. But it has my name.
Also, I think I already am in the R-Ladies Starter Kit for BlueSky, but of course I agree on being on the Kit and your awesome bots tag me :-)
Let me know if you need anything else from me!

Thank you so much! By the way, would you be interested (in general) to also have your YouTube feed (or R-specific channel) being shared with the bot? It's a feature that I use more extensively with the PyLadies bot but I think it would be amazing for the R-Ladies bot (and R-Ladies chapters :)) as well :)

Just as a ref for #97


Possible memory leak found by using ImageClassification_Video example

→ Step 1: Describe the issue 📝

Found a bug in one of the examples. DevTools reporting possible memory leak.

→ Step 2: Screenshots or Relevant Documentation 🖼

→ Step 3: Share an example of the issue 🦄
I've used this example: https://github.com/ml5js/ml5-examples/tree/development/javascript/ImageClassification/ImageClassification_Video
and let it run overnight.
Other relevant information, if applicable
→ Describe your setup 🦄

Here's some helpful information about my setup...

Web browser & version: Chrome 78.0.3904.87 (Official Build) (64-bit)
Operating System: Windows 7(64-bit)
ml5 version: ml5@0.4.1(minified version)
Any additional notes<EMAIL_ADDRESS>is loaded via unpkg.com

@BKirev - Thanks for reporting this. If you can also share the code you were using that created this error that would be helpful. Thanks!

It may be helpful to note that I see this same error appearing with the teachable machine trained image model example! Since teachable machine launches on Thursday, it might be worth trying to investigate before then. I will do some digging too!
https://editor.p5js.org/ml5/sketches/UsVLWNiwZdA
Appears after ~5 minutes.

On my end I get the same after 5 min or so:

  | t.acquireTexture | @ | tf-core.esm.js:17
-- | -- | -- | --
  | t.uploadToGPU | @ | tf-core.esm.js:17
  | t.compileAndRun | @ | tf-core.esm.js:17
  | t.unpackTensor | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | t.compileAndRun | @ | tf-core.esm.js:17
  | t.reduce | @ | tf-core.esm.js:17
  | t.sum | @ | tf-core.esm.js:17
  | At.runKernel.permutedX | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | t.scopedRun | @ | tf-core.esm.js:17
  | t.runKernel | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | t.scopedRun | @ | tf-core.esm.js:17
  | t.runKernel | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | sum_ | @ | tf-core.esm.js:17
  | sum | @ | tf-core.esm.js:17
  | t.sum | @ | tf-core.esm.js:17
  | t.batchMatMul | @ | tf-core.esm.js:17
  | t.conv2dByMatMul | @ | tf-core.esm.js:17
  | t.conv2d | @ | tf-core.esm.js:17
  | At.runKernel.x | @ | tf-core.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | t.scopedRun | @ | tf-core.esm.js:17
  | t.runKernel | @ | tf-core.esm.js:17
  | conv2d_ | @ | tf-core.esm.js:17
  | sum | @ | tf-core.esm.js:17
  | executeOp$3 | @ | tf-converter.esm.js:17
  | (anonymous) | @ | tf-converter.esm.js:17
  | executeOp$16 | @ | tf-converter.esm.js:17
  | (anonymous) | @ | tf-converter.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | t.scopedRun | @ | tf-core.esm.js:17
  | t.tidy | @ | tf-core.esm.js:17
  | Fe | @ | tf-core.esm.js:17
  | e.execute | @ | tf-converter.esm.js:17
  | e.execute | @ | tf-converter.esm.js:17
  | e.predict | @ | tf-converter.esm.js:17
  | (anonymous) | @ | mobilenet.esm.js:17
  | (anonymous) | @ | tf-core.esm.js:17
  | t.scopedRun | @ | tf-core.esm.js:17
  | t.tidy | @ | tf-core.esm.js:17
  | Fe | @ | tf-core.esm.js:17
  | e.infer | @ | mobilenet.esm.js:17
  | (anonymous) | @ | mobilenet.esm.js:17
  | (anonymous) | @ | mobilenet.esm.js:17
  | (anonymous) | @ | mobilenet.esm.js:17
  | (anonymous) | @ | mobilenet.esm.js:17
  | __awaiter | @ | mobilenet.esm.js:17
  | e.classify | @ | mobilenet.esm.js:17
  | _callee3$ | @ | index.js:172
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:28
  | Promise.then (async) |   |
  | step | @ | asyncToGenerator.js:27
  | (anonymous) | @ | asyncToGenerator.js:28
  | Promise.then (async) |   |
  | step | @ | asyncToGenerator.js:27
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classifyInternal | @ | ml5.js:164077
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10
  | Promise.then (async) |   |
  | callCallback | @ | callcallback.js:9
  | _callee4$ | @ | index.js:229
  | tryCatch | @ | runtime.js:62
  | invoke | @ | runtime.js:296
  | prototype.<computed> | @ | runtime.js:114
  | step | @ | asyncToGenerator.js:17
  | (anonymous) | @ | asyncToGenerator.js:35
  | F | @ | _export.js:36
  | (anonymous) | @ | asyncToGenerator.js:14
  | classify | @ | ml5.js:164192
  | classifyVideo | @ | sketch.js:32
  | gotResult | @ | sketch.js:39
  | (anonymous) | @ | callcallback.js:10

@BKirev - Thanks for reporting this. If you can also share the code you were using that created this error that would be helpful. Thanks!

I just copy/pasted the code from https://github.com/ml5js/ml5-examples/tree/development/javascript/ImageClassification/ImageClassification_Video as it is. The only thing that I've changed is
<script src="http://localhost:8080/ml5.js" type="text/javascript"></script>
to load ml5.js from unpkg.com

Thanks so much for flagging this @BKirev - we tracked down the issue and are fixing it now: https://github.com/ml5js/ml5-library/pull/680
We will do a release soon to ensure that the latest version of ml5 takes care of this. Thanks!

Closed now in the latest version of ml5:
<script<EMAIL_ADDRESS>


cmd/main: PREVENT_INSECURE_STARTUP option

Customers Version: v0.5.0-dev
What were you trying to do?
The Customers service is starting to have several security-sensitive configuration knobs. With the default being insecure values this means one of them could be missed and operators are unaware they've missed a configuration.
What did you expect to see?
A configuration option that will panic/crash if insecure (e.g. default) configuration is used.

I thought of this just now, so we'd be checking for the following values.

empty SSN_SECRET_KEY
empty TRANSIT_LOCAL_BASE64_KEY
empty DOCUMENTS_SECRET_KEY
empty FILEBLOB_HMAC_SECRET (if used)
empty APP_SALT


fl studio cracked 2024

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Override yatm model class method for prior restarts

Implements solution described here: https://github.com/payu-org/payu/issues/523#issuecomment-2398858187, which was to add an override the parent class get_prior_restart_files in yatm, to return just an empty array. This is to prevent error messaging on a missing prior restart directory when yatm driver does not require any.
Closes #523

Hello @jo-basevi! Thanks for opening this PR. We checked the lines you've touched for PEP 8 issues, and found:

In the file test/models/test_yatm.py:

Line 7:1: E302 expected 2 blank lines, found 1

coverage: 58.546% (+0.2%) from 58.332%
when pulling 6143912b1f50b832b9c0c9dc4a6e03a93c0703f0 on ACCESS-NRI:523-yatm-get-prior-retart-files
into 2faf9e7bb5f191633afa060019e4c2bd10cc7968 on payu-org:master.


Sign in to confirm you're not a bot error!

Your issue reporting guide is unnecessarily lengthy & complex just for one to report a simple bug, so i worded it like this, close it if you wish, at least it will be visible and you will be aware of the issue if not already.
Whenever i try to DL a playlist or any YT video using the latest nightly build it fails with an error message saying "sign in to confirm your not a bot" can this be fixed?

By following the minimally complex procedure you would have found #32920. Please review that issue to understand why that issue is closed, and why this one will also be closed, unless it is updated with the required completed issue template.

I tried
youtube-dl -u "youtubeloginname" -p "youtubeloginpassword" url
but got below error
[youtube] Downloading login page
[youtube] Looking up account info
WARNING: Unable to look up account info: HTTP Error 400: Bad Request
version
youtube-dl --version
2021.12.17
My solution comes from:
https://askubuntu.com/questions/776122/how-to-resolve-sign-in-error-when-using-youtube-dl-for-downloading-my-personal

Continued in #32960.

@webloginwu, use a cookie-file exported from your logged-in browser session (see FAQ) rather than the command-line authentication options, which no longer work with YT: the AskUbuntu answer has not been valid for several years, though it may have been in 2016.
And review #30839 to find out about the nightly release which might have a chance of working if your IP has not been banned.


Unable to Link Camera to AI Skill - Dropdown is empty

I've got all setup, the computing device, the camera, the model, and the AI Skill, but when I tried to run the deployment and link the camera to the AI Skill the Dropdown is empty.
Any Clue?
Thanks

HI, @JMH-Jarbydev, can you please confirm if the AI Skill exist on the AI Skills page? Thanks

Hi @JMH-Jarbydev
Since we have some verification on that, only the skills that match the acceleration of the compute device would be displayed at the dropdown page.
Please check whether the acceleration of compute device and skill aligns, thanks!

Close for no activities.


fix: [ERROR] No replacement found for "getRuntimeConfig"

Description of changes

fix: [ERROR] No replacement found for "getRuntimeConfig" in runtimeConfig.shared.js

Detail
There is wrapper logic in build.mjs that injects AWS credentials and region parameters into runtimeConfig.shared.js in @aws-sdk.
However, we found that there are runtimeConfig.shared.js in @aws-sdk that do not follow the following rules.
@aws-sdk/client-s3/dist-es/runtimeConfig.shared.js:
// getRuntimeConfig is included in the code, so it is successfully bundled.
...
export const getRuntimeConfig = (config) => {
    return {
        apiVersion: "2006-03-01",
        base64Decoder: config?.base64Decoder ?? fromBase64,
        base64Encoder: config?.base64Encoder ?? toBase64,
        disableHostPrefix: config?.disableHostPrefix ?? false,
        endpointProvider: config?.endpointProvider ?? defaultEndpointResolver,
        extensions: config?.extensions ?? [],
        getAwsChunkedEncodingStream: config?.getAwsChunkedEncodingStream ?? getAwsChunkedEncodingStream,
        logger: config?.logger ?? new NoOpLogger(),
        sdkStreamMixin: config?.sdkStreamMixin ?? sdkStreamMixin,
        serviceId: config?.serviceId ?? "S3",
        signerConstructor: config?.signerConstructor ?? SignatureV4MultiRegion,
        signingEscapePath: config?.signingEscapePath ?? false,
        urlParser: config?.urlParser ?? parseUrl,
        useArnRegion: config?.useArnRegion ?? false,
        utf8Decoder: config?.utf8Decoder ?? fromUtf8,
        utf8Encoder: config?.utf8Encoder ?? toUtf8,
    };
};

For example, @aws-sdk/lib-storage (which I hope to bundle in the future)
@aws-sdk/lib-storage/dist-es/runtimeConfig.shared.js:
// Error during bundling because getRuntimeConfig is not included in the code.
export const ClientSharedValues = {
    lstatSync: () => { },
};

This PR allows for runtimeConfig.shared.js that do not follow the laws to be bundled as is, without making an error that the wrapper logic cannot be injected.
Checklist

[ ] Created unit tests in tests/unit and/or in Rust for my feature if needed
[x] Ran make fix to format JS and apply Clippy auto fixes
[x] Made sure my code didn't add any additional warnings: make check
[ ] Updated documentation if needed (API.md/README.md/Other)

By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Fantastic! I'll also look into adding @aws-sdk/lib-storage!
For reference I also added https://github.com/awslabs/llrt/issues/283


Endpoint does not appear correctly.

Hello, our endpoints that have parameters are not being recognized by the plugin.

My controller:
@ApiDoc(tag = {
description "Test API"
})
class TesteController {
static responseFormats = ['json', 'xml']
@ApiDoc(operation = {
    summary "Test"
    description "Teste de swagger"
    parameters([{
                    name "s"
                    description "Texto qualquer"
                    inType "path"
                    schema { "string" }
                }])
    responses "200": {
        content "application/json": {
            description "success response"
            schema {
                name "Resposta"
                type "string"
                description "Texto digitado"
            }
        }
    }
})
def teste(String s) {
    render([text: s]as JSON)
}

}
My url mappings:
class UrlMappings {
static mappings = {
    delete "/$controller/$id(.$format)?"(action: "delete")
    get "/$controller(.$format)?"(action: "index")
    get "/$controller/$id(.$format)?"(action: "show")
    post "/$controller(.$format)?"(action: "save")
    put "/$controller/$id(.$format)?"(action: "update")
    patch "/$controller/$id(.$format)?"(action: "patch")

    get "/test/$s"(controller: "teste", action: "teste")

    "500"(view: '/error')
    "404"(view: '/notFound')
}

}

Hi, thanks for report, I have tried to reproduce the issue but have not your issue.
Maybe you can try these:

reboot your app and see if the issue resolved.
change the typo of

@apidoc(tag = {
description "Test API"
})
class TesteController

to
@Apidoc(tag = {
description "Test API"
})
class TesteController

You can move your controller and url-mapping to 'swagger-grails4-samples' project and see if there is the issue.

Good luck!


Address user story #5

Add 25% discount

It should be 50%, 25% is not acceptable! Change it to 50%...

Cats are awesome 🐈 😸


[core] Type inference failed due to anonymous class

In this app https://java-program.apk.gold/ (version 1.8) in method com.webtomob.java.SplashActivity::creatingsplashscreen() a "Type inference failed" warning gets reported even if the the decompiled code seems to be correct. The affected class is so minimal, that it might be possible to resolve the cause for the warning and to fix this issue.

Thanks for nice test case, it is related to #597, similar code with issue explanation in comments:
Thread timer = new Thread() { // can't use anonymous class as variable type, use base type instead
    // class code
};
timer.start(); // but method call invoked as it defined in anonymous class

So variable type should be anonymous class, because method can be not defined in base class at all, like here:
Object timer = new Object() {
    public void start() {}
};
timer.start();

but in this case code will not compile, and anonymous class can't be inlined.
So solution is to check if all methods and fields used on anonymous class exists and accessed in base class, if not reject class inline. Also need to fix bounds requirements for virtual calls for such case in type inference visitor.
As a result, this is a lot of changes (with possible regressions), so I will postpone the fix for later.


dotnet script doesn't obey version

I'm trying to run a script as NET Core 3.1 but dotnet script main.csx is not obeying the version, at the top of my file I have
#! "netcoreapp3.1"
and in lauch.json I have
{
    "version": "0.2.0",
    "configurations": [
        {
            "name": ".NET Script Debug",
            "type": "coreclr",
            "request": "launch",
            "program": "dotnet",
            "args": [
                "exec",
                "${env:USERPROFILE}/.dotnet/tools/.store/dotnet-script/1.1.0/dotnet-script/1.1.0/tools/netcoreapp3.1/any/dotnet-script.dll",
                "${file}"
            ],
            "cwd": "${workspaceRoot}",
            "stopAtEntry": true
        }
    ]
}

My ```dotnet script --info`` reports
Version             : 1.1.0
Install location    : C:\Users\paulh\.dotnet\tools\.store\dotnet-script\1.1.0\dotnet-script\1.1.0\tools\net5.0\any
Target framework    : net5.0
.NET Core version   : 5.0.6
Platform identifier : win
Runtime identifier  : win10-x64

The script is old and can't run as .NET 5.0 as most of the referenced nuget packages do not support it. There are netcoreapp2.1 and netcoreapp3.1 directories as well as the net5.0 in the dotnet-script folder which suggests this si supported?

The #! "netcoreapp3.1" won't work here. It was an early attempt to communicate to Omnisharp that we wanted compilation dependencies for a given target framework. It has never been used to resolve runtime dependencies for dotnet-script.


Add Rlocks to swarm cluster

Add forgotten RLocks to Cluster methods (protect c.engines).
Use WaitGroup to wait for goroutines.

Coverage decreased (-0.11%) to 38.96% when pulling 2b4bbf1ef208ea2fc12e269b7822c9512efd4540 on noxiouz:add_rlocks_to_swarm_cluster into 14108ccaa1cf15d7312a2a2f0231d963da150e16 on docker:master.

Should I fix something?

LGTM


'create-test-cases-for-deployment'

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create test cases for deployment in octopus connector