Conda environment is not activated in Python debug console

Environment data

VS Code version: 1.43.2
Extension version (available under the Extensions sidebar): 2020.5.86806 (10 June 2020)
OS and version: Win 10 Pro
Python version (& distribution if applicable, e.g. Anaconda): conda 4.8.3
Type of virtual environment used (N/A | venv | virtualenv | conda | ...): conda
Relevant/affected Python packages and their versions: XXX
Relevant/affected Python-related VS Code extensions and their versions: XXX
Value of the python.languageServer setting: microsoft

Expected behaviour
I set the option "python.terminal.activateEnvInCurrentTerminal": true. The current conda environment is correctly activated when the script is run normally without debugger. I would expect this to work also when the script is run with the debugger
Actual behaviour
However, when the script is run with the debugger the conda environment is not correctly activate and it require to restart the debugger. At the first run, the console will run C:/miniconda/Scripts/activate to activate conda to the base environment. Conda will not activate the project environment. Restarting the debugger will make vscode now run conda activate name_of_the_project_env before stepping into the code.
`
C:\Dev\test_conda>C:/miniconda/Scripts/activate #<-- Activate conda base

(base) C:\Dev\test_conda> cmd /C "C:\miniconda\envs\test\python.exe c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\lib\python\debugpy\wheels\debugpy\launcher 51750 -- c:\Dev\test_conda\test.py "
SCRIPT RUN #<-- Run the script before the env is activated

(base) C:\Dev\test_conda>conda activate test # <-- Now the env is activated

(test) C:\Dev\test_conda>

Logs

Output for Python in the Output panel (View→Output, change the drop-down the upper-right of the Output panel to Python)

User belongs to experiment group 'ShowPlayIcon - start'
User belongs to experiment group 'DebugAdapterFactory - experiment'
User belongs to experiment group 'PtvsdWheels37 - experiment'
User belongs to experiment group 'UseTerminalToGetActivatedEnvVars - control'
User belongs to experiment group 'LocalZMQKernel - control'
User belongs to experiment group 'CollectLSRequestTiming - control'
User belongs to experiment group 'CollectNodeLSRequestTiming - experiment'
User belongs to experiment group 'EnableIPyWidgets - experiment'
User belongs to experiment group 'DeprecatePythonPath - experiment'
User belongs to experiment group 'RunByLine - control'
User belongs to experiment group 'CustomEditorSupport - control'
> pyenv root
> python3.7 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python3.6 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python3 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python2 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> py -3.7 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> py -3.6 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> py -3 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> py -2 c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> C:\miniconda\condabin\conda.bat info --json
> python c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> C:\miniconda\condabin\conda.bat env list
> python c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
> python c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import sys;print(sys.executable)"
Starting Microsoft Python language server.
Python interpreter path: C:\miniconda\envs\test\python.exe
> C:\Python38\python.exe c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import jupyter"
> C:\Python38\python.exe c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import jupyter"
> C:\Python38\python.exe c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import notebook"
> C:\Python38\python.exe c:\Users\jack\.vscode\extensions\ms-python.python-2020.5.86806\pythonFiles\pyvsc-run-isolated.py -c "import notebook"
> C:\miniconda\condabin\conda.bat info --json
> C:\miniconda\condabin\conda.bat env list

Output from Console under the Developer Tools panel (toggle Developer Tools on under Help; turn on source maps to make any tracebacks be useful by running Enable source map support for extension debugging)

I do not know what you mean with "running Enable source map support for extension debugging"

For conda environments we recommend that you start VSCode from an activated prompt. You may still have to select the interpreter, we plan on addressing this (see #10668). We have plans to make the experience better when you create new terminals, see #11039. For terminal that are already open before python extension starts, we recommend that you start VSCode using code . from your project directory from an activated conda prompt.

Closing in favour of the issues Karthik outlined above.


Fix markdown rendering of the README

D'oh, this is the same as #612 :(

Yeah, but thanks anyway ! :-)


Send unsubscription token when sending email

Sends a unsubscriptionUrl substitution to the email provider. This URL includes the token which can be used to unsubscribe from further email notifications.
Since this token is unique, and a token cannot be mapped to a target email address if multiple email addresses are involved, the AlertsRepository now triggers multiple calls to IEmailApi.createMessage (one per each recipient).

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

-4 of 17 (76.47%)  changed or added relevant lines in 2 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.2%) to 93.722%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

src/domain/alerts/alerts.repository.ts
12
16
75.0%

Totals

Change from base Build<PHONE_NUMBER>:
-0.2%

Covered Lines:
6153

Relevant Lines:
6347

💛  - Coveralls


numbat: Add modules folder

Description of changes
Following numbats guidline for package maintainers by adding the modules folder aka prelude to the package.

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 265744 run on x86_64-linux 1

1 package built:

numbat

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/2886


Fix GitHub Actions workflows

Summary
There are a few shortcomings in the current workflows and the goal of this ticket is to fix these issues:

Go version is not being picked up by the CI system
Docker images are not being tagged. This used to work before

can you enable
Run workflows from fork pull requests from Settings of actions
so that i can solve the issue

can you enable Run workflows from fork pull requests from Settings of actions so that i can solve the issue

Hi and thanks for offering a hand.
I will enable it shortly.

There is no setting available for me to do it globally. The best thing I could find that applies to this repo is discussed here:
https://docs.github.com/en/actions/managing-workflow-runs/approving-workflow-runs-from-public-forks

i have made a tiny change, can you try now picking of go version

thanks for your contribution.


Update error messages in pickles.py

In the following code in save_object function,

if not isinstance(file_path, six.string_types):
logger.error('Input file path is not of type string')
raise AssertionError('Input file path is not of type string')
Update the error string with the input file path.

In the following code in load_object function,

if not isinstance(file_path, six.string_types):
logger.error('Input file path is not of type string')
raise AssertionError('Input file path is not of type string')
Update the error string with the input file path.

In the following code in load_table function,

if not isinstance(data_frame, pd.DataFrame):
logging.error('Input object is not of type pandas DataFrame')
raise AssertionError('Input object is not of type pandas DataFrame')
Update the error string with the type of input data frame.

In the following code in save_table,

# metadata_ext is expected to be of type string
if not isinstance(metadata_ext, six.string_types):
    logger.error('Input metadata ext is not of type string')
    raise AssertionError('Input metadata ext is not of type string')

Update the error string with the input metadata extension.

In the following code in load_table,

# The file_path is expected to be of type string
if not isinstance(file_path, six.string_types):
    logger.error('Input file path is not of type string')
    raise AssertionError('Input file path is not of type string')

Update the error string with input file path

In the following code in load_table

# The metadata_extn is expected to be of type string
if not isinstance(metadata_ext, six.string_types):
    logger.error('Input metadata ext is not of type string')
    raise AssertionError('Input metadata ext is not of type string')

Update the error string with metadata ext.

Duplicate #57


button to remove watch expressions

@willwhitney Close this? Or you want a real button?

See https://github.com/nteract/hydrogen/pull/175


@resource is nil in register#update

I am using DeviseTokenAuth for authentication in rails api. By using that signup and signin modules working fine. But but when I update it gives an error.
def update
if @resource
if @resource.send(resource_update_method, account_update_params)
yield @resource if block_given?
render_update_success
else
render_update_error
end
else
render_update_error_user_not_found
end
end

I have the same problem, but in several actions, and sometimes this error does not occur.
I noticed that @resource gets nil after the yield @resource if block_given? Code


Feature/malcolm put #46

connect to #46

Codecov Report

Merging #102 into version1 will decrease coverage by 6.59%.
The diff coverage is 44%.

@@             Coverage Diff             @@
##           version1     #102     +/-   ##
===========================================
- Coverage      92.5%   85.91%   -6.6%
===========================================
  Files            24       29      +5
  Lines           267      355     +88
  Branches         33       43     +10
===========================================
+ Hits            247      305     +58
- Misses           19       42     +23
- Partials          1        8      +7

Impacted Files
Coverage Δ

src/malcolm/malcolmReducer.js
96.07% <ø> (ø)
:arrow_up:

...s/attributeSelector/attributeSelector.component.js
78.94% <ø> (ø)
:arrow_up:

src/malcolmWidgets/checkbox/checkbox.component.js
100% <ø> (ø)
:arrow_up:

src/malcolm/malcolmSocketHandler.js
50.79% <44%> (-37.21%)
:arrow_down:

src/layout/block/blockWidget.factory.js
100% <0%> (ø)

src/layout/block/block.model.js
100% <0%> (ø)

src/layout/block/blockWidget.component.js
100% <0%> (ø)

...ayout/block/blockPort/blockPortWidget.component.js
80% <0%> (ø)

src/layout/layout.component.js
100% <0%> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 415fe65...efa31f0. Read the comment docs.


Replace React.render() with ReactDOM.render() in doc

React.render() has been removed in favor of ReactDOM.render() in React 0.14.

@facebook-github-bot shipit

Thanks for importing.


Nyan Reporter has Weird Output in Travis CI

Prerequisites

[x] Checked that your issue hasn't already been filed by cross-referencing issues with the faq label
[x] Checked next-gen ES issues and syntax problems by using the same environment and/or transpiler configuration without Mocha to ensure it isn't just a feature that actually isn't supported in the environment in question or a bug in your code.
[x] 'Smoke tested' the code to be tested by running it outside the real test suite to get a better sense of whether the problem is in the code under test, your usage of Mocha, or Mocha itself
[x] Ensured that there is no discrepancy between the locally and globally installed versions of Mocha. You can find them with: node node_modules/.bin/mocha --version(Local) and mocha --version(Global). We recommend avoiding the use of globally installed Mocha. (I have no control of this)

Description

The Nyan runner's output is a bit strange in Travis CI (see screenshot).
Steps to Reproduce

Expected behavior: Test runner outputs as it does in the console
Actual behavior: Lots of newlines output
Reproduces how often: 100%
Versions

"mocha": "^5.0.0"
node v8.9.4
Additional Information

It's not a problem. Nyan report shows report dynamically in your terminal, but Travis's log is a static file. So, it just saves all stdout and can't show it dynamically. Nyan report is not the best option for Travis ci.

@outsideris, thanks for the clarification.


docs: doc support for unix socket args

Support for unix sockets as function args was merged here: https://github.com/dagger/dagger/pull/7804 so it will be in the upcoming release.
I created a tiny demo module that I reference in the docs; it currently just lets you pass a host docker unix sock as an arg and then calls "docker version" on it: https://github.com/sipsma/daggerverse/blob/c19ee68f84b228942bac8047a9d8337fc22a3479/docker-client/main.go
Should not be deployed until next release (0.12.1)

@shykes thanks! Suggestions all make sense to me, updated with those


[BUG] Hover effect on new light mode button.

There is no hover effect on light and dark mode button.

I want to work on the issue.

@nepalivai You are already assigned an issue, Kindly complete that one before taking up any other issue.

I would like to work on this

Sorry for the inconvenience @singodiyashubham87, But as I told you that is going to take some time, I have already completed the work and was waiting to create a PR until you assigned me the issues.

@nepalivai Oh..Okay..Go Ahead!

hey @singodiyashubham87, work is done waiting for review.

@singodiyashubham87 can we both agree that the bug is fixed?

@nepalivai Which bug?

@singodiyashubham87  when this issue was open there was no hover effect on the light and dark mode button.

@nepalivai Oh you are talking about the hover effect, it was an enhancement, not a bug, buddy. And yes, it's done.


Tensorflow-gpu in RTX3070

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): WIndows 10 64bit
TensorFlow installed from (source or binary): pip install tensorflow-gpu
TensorFlow version: tensorflow-gpu 2.4.0
Python version: Python 3.7
Installed using virtualenv? pip? conda?: pip
CUDA/cuDNN version: CUDA11, cuDNN 8.0.5
GPU model and memory: RTX3070 8GB OC

Describe the problem
When I run the training using GPU, it raise me an error saying that my cuDNN is not initialize properly. I've no idea on how to solve it. I did tried with CUDA 11 with cuDNN 8.0.4 and 8.0.3 but keep raising the same problem.
Provide the exact sequence of commands / steps that you executed before running into the problem
tf.config.list_physical_devices('GPU') --> "Physical Device GPU 0"
tf.test.is_built_with_cuda() --> True
Log

@hansheng0512
Please paste the error message (using makrdown formatting around it) instead of screenshotting. Screenshots are not searchable so they don't help in looking for the issue and also don't help other people having the same error from finding about the issue.

@hansheng0512
Please paste the error message (using makrdown formatting around it) instead of screenshotting. Screenshots are not searchable so they don't help in looking for the issue and also don't help other people having the same error from finding about the issue.

Noted.
The log shown as below:
2021-01-06 18:21:30.484673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:09:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.755GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-06 18:21:30.485159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-06 18:21:30.485494: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:30.486402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-06 18:21:30.486726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-01-06 18:21:30.487637: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-01-06 18:21:30.487971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-01-06 18:21:30.488935: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-01-06 18:21:30.489355: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:30.489743: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-01-06 18:21:36.156145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-06 18:21:36.156275: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-01-06 18:21:36.157045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-01-06 18:21:36.157466: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6589 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3070, pci bus id: 0000:09:00.0, compute capability: 8.6)
2021-01-06 18:21:36.158785: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-06 18:21:37.935914: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-01-06 18:21:38.345639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:44.113075: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.113322: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.114653: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.116732: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.117351: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.118153: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.683728: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:48.700894: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701422: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701512: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_ops_fused_impl.h:697 : Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.

Noted.
The log shown as below:
2021-01-06 18:21:30.484673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:09:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.755GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-06 18:21:30.485159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-06 18:21:30.485494: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:30.486402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-06 18:21:30.486726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-01-06 18:21:30.487637: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-01-06 18:21:30.487971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-01-06 18:21:30.488935: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-01-06 18:21:30.489355: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:30.489743: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-01-06 18:21:36.156145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-06 18:21:36.156275: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-01-06 18:21:36.157045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-01-06 18:21:36.157466: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6589 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3070, pci bus id: 0000:09:00.0, compute capability: 8.6)
2021-01-06 18:21:36.158785: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-06 18:21:37.935914: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-01-06 18:21:38.345639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:44.113075: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.113322: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.114653: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.116732: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.117351: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.118153: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.683728: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:48.700894: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701422: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701512: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_ops_fused_impl.h:697 : Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.

@hansheng0512
Please paste the error message (using makrdown formatting around it) instead of screenshotting. Screenshots are not searchable so they don't help in looking for the issue and also don't help other people having the same error from finding about the issue.

ok

@hansheng0512
Please paste the error message (using makrdown formatting around it) instead of screenshotting. Screenshots are not searchable so they don't help in looking for the issue and also don't help other people having the same error from finding about the issue.

ok

@hansheng0512
Please paste the error message (using makrdown formatting around it) instead of screenshotting. Screenshots are not searchable so they don't help in looking for the issue and also don't help other people having the same error from finding about the issue.

Noted.
The log shown as below:
2021-01-06 18:21:30.484673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:09:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.755GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-06 18:21:30.485159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-06 18:21:30.485494: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:30.486402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-06 18:21:30.486726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-01-06 18:21:30.487637: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-01-06 18:21:30.487971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-01-06 18:21:30.488935: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-01-06 18:21:30.489355: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:30.489743: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-01-06 18:21:36.156145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-06 18:21:36.156275: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-01-06 18:21:36.157045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-01-06 18:21:36.157466: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6589 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3070, pci bus id: 0000:09:00.0, compute capability: 8.6)
2021-01-06 18:21:36.158785: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-06 18:21:37.935914: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-01-06 18:21:38.345639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:44.113075: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.113322: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.114653: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.116732: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.117351: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.118153: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.683728: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:48.700894: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701422: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701512: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_ops_fused_impl.h:697 : Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.

@hansheng0512
Please paste the error message (using makrdown formatting around it) instead of screenshotting. Screenshots are not searchable so they don't help in looking for the issue and also don't help other people having the same error from finding about the issue.

Noted.
The log shown as below:
2021-01-06 18:21:30.484673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:09:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.755GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-06 18:21:30.485159: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-06 18:21:30.485494: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:30.486402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-06 18:21:30.486726: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-01-06 18:21:30.487637: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-01-06 18:21:30.487971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-01-06 18:21:30.488935: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-01-06 18:21:30.489355: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:30.489743: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-01-06 18:21:36.156145: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-06 18:21:36.156275: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-01-06 18:21:36.157045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-01-06 18:21:36.157466: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6589 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3070, pci bus id: 0000:09:00.0, compute capability: 8.6)
2021-01-06 18:21:36.158785: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-06 18:21:37.935914: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-01-06 18:21:38.345639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-06 18:21:44.113075: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.113322: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.114653: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.116732: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.117351: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.118153: E tensorflow/stream_executor/cuda/cuda_blas.cc:226] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED
2021-01-06 18:21:44.683728: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-06 18:21:48.700894: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701422: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2021-01-06 18:21:48.701512: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_ops_fused_impl.h:697 : Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.

@hansheng0512
Please refer to this issue and let us know.
Similar issues: #45779, #43761

@hansheng0512
Please refer to this issue and let us know.
Similar issues: #45779, #43761

@hansheng0512
Please refer to this issue and let us know.
Similar issues: #45779, #43761

I tried with:

pip uninstall tensorflow-gpu as my pc just installed tensorflow-gpu
pip cache purge
Deleted tensorflow folders in .../python38/Lib/Site-packages
pip install tensorflow-gpu --no-cache-dir

But it raise me same error.

@hansheng0512
Please refer to this issue and let us know.
Similar issues: #45779, #43761

I tried with:

pip uninstall tensorflow-gpu as my pc just installed tensorflow-gpu
pip cache purge
Deleted tensorflow folders in .../python38/Lib/Site-packages
pip install tensorflow-gpu --no-cache-dir

But it raise me same error.

Add this to the start of your code
physical_devices = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True).

Add this to the start of your code
physical_devices = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True).

Add this to the start of your code
physical_devices = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True).

It works! Thanks man!
Do you mind to explain me what's going on?

Add this to the start of your code
physical_devices = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True).

It works! Thanks man!
Do you mind to explain me what's going on?


Bug on patch_sizes

I created two datasets with 5-minute intervals and 1-hour intervals for training, but the following error occurred at patch_size:. The error was:
AssertionError: no valid patch size candidates for time series shape: (5, 2), freq: 5MIN, patch_sizes: (8, 16, 32, 64, 64, 128), constraints: range(32, 129), min_time_patc hes: 2, patch_size_ceil: 1
I modified "H": (1, 64), "T": (1, 128) in patch.py, but the same error still occurs.
How to Handle the Current Error

Hi @hahne0922 even you modified "T": (1,128), your min patch size in your config file is 8, but you sequence length seems to be 2

Thanks a lot, the problem has been located, it should be caused by missing values in the dataset


className added to map container on mount not removed on unmount

The classes marker-cluster-styled and marker-cluster-animated are added to the map container on mount but not removed on unmount - this causes issues when attempting to use the marker clusters dynamically as the classname string gets continually larger as clusters are added and removed.

Fixed at: [release] 1.1.7: Minor fixes, deprecation API warnings and refactoring (#47)


Focus Issue

What I am trying to do
I have a react quill instance. When I click on it, I want it to go into 'edit mode' (snow theme and editable). When I click away from it, I want it to go to 'non edit' mode (bubble theme and non editable).
How I am trying to do this
I am trying to use reacts onClick property to re-render the react-quill instance (works great). The onClick is on a div that wraps the react-quill instance.
The problem comes to the on Focus. I originally tried to use react's onBlur on the wrapping div. However when I clicked on the toolbar, it would onFocus. I then tried to use react-quills onBlur prop. However the onBlur prop is triggered on render. So I would click on the text editor, it would go to edit mode, but then immediately go back to non edit mode.
If I use both the onBlur and onFocus prop, it goes into an infinite loop.
Example code in render():
<div className={ !this.state.edit ? 'text-editor' : '' } onClick={ this.handleEdit } onBlur={ this.handleSave }>
    <ReactQuill value={ this.state.text ? this.state.text : '' } theme={ this.state.edit ? 'snow' : 'bubble' } readOnly={ !this.state.edit } onChange={ this.handleChange } modules={ this.state.modules }/>
</div>

Can anyone please provide me with some assistance on this?
I am using version 1.2.7

Same here :(

Same here :(

If anyone's still struggling with this, you can fix this by changing the onClick from onClick={ this.handleEdit } to onClick={() => this.handleEdit },  such that onClick only triggers when it detects an event. This can done to onBlur and onFocus, and it'll work :) Let me know if I'm off track, but I just made it work
@ChristinaEckleder @designalchemy @dmossie


Ubuntu package missing 'Maintainer' field

After installing the Debian package on Ubuntu 20.04.3, I get this error multiple times during apt upgrade
dpkg-query: warning: parsing file '/var/lib/dpkg/status' near line 21630 package 'liferay-cli':
  missing 'Maintainer' field

Same in Debian 10
dpkg: warning: parsing file '/var/lib/dpkg/tmp.ci/control' near line 9 package 'liferay-cli':   missing 'Maintainer' field
Debian package description:
$ dpkg -I /tmp/liferay-cli_v1.0.0-alpha.1_linux_amd64.deb
 paquete Debian nuevo, versión 2.0.
 tamaño 3348930 bytes: archivo de control= 393 bytes.
       1 bytes,     0 líneas     conffiles
     273 bytes,     8 líneas     control
      54 bytes,     1 líneas     md5sums
 Package: liferay-cli
 Version: 1.0.0~alpha.1
 Section:
 Priority:
 Architecture: amd64
 Installed-Size: 8324
 Homepage: https://github.com/lgdd/liferay-cli
 Description: Liferay CLI (lfr) is an unofficial tool written in Go that helps you create & manage your Liferay projects.

Thanks @balcsida and @martin-dominguez for reporting this! Build for v1.0.0-alpha.2 with the maintainer field on its way :)

the issue is still there :(
dpkg: warning: parsing file '/var/lib/dpkg/status' near line 49405 package 'liferay-cli':
  missing 'Maintainer' field

Weird... I'll dig into that.

@martin-dominguez I did some tests with Debian 10 using Docker and could only reproduce the issue when I installed alpha.1 and then alpha.2. However, when I install alpha.1, run apt remove liferay-cli and install alpha.2 I can't reproduce the issue. Could you confirm that these steps resolve the issue for you?

you're right!! confirmed!


Remove redundant assertion checks in HyperOpt Optimizer.

In this PR, I remove duplicated assertion checks in HyperOpt Optimizer.

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

What is the motivation for removing these assertions? Is there any downside to having this extra check?

ok, I will run some more tests and then merge.


Adaptive learning rate and number of iterations

Hi, thanks for the great repo!
I tried to run the training code with both the vgg16_voc2007 and the vgg16_voc2007_more configurations. I got 51.7 mAP with the former and 50.3 mAP with the latter, which are different from the reported results in https://github.com/ppengtang/pcl.pytorch/blob/master/README.md so I am trying to figure out the causes.
In tools/train_net_step.py, you change the learning rate at line 195:
cfg.SOLVER.BASE_LR *= args.batch_size / original_batch_size.
If I use args.batch_size=1as in the default configuration, then the base learning rate stays unchanged when I change args.iter_size. Since the gradients are sum-accumulated in 'inner' iterations (lines 407-421), does using large args.iter_size make gradients too big and non-adaptive? Should the line 195 be
cfg.SOLVER.BASE_LR /= effective_batch_size / original_batch_size?
Also, in lines 200-204, you change the number of iterations. I understand that it is to keep the average number of times an image is seen unchanged during training. But this changes the number of times weights are updated. Is this problematic?

Hi, since the gradients are sum-accumulated in 'inner' iterations (lines 407-421), we should use base LR 0.0005 for batch size 1 and iter size 4, and then the real LR will be base LR * iter size = 0.002. So we use cfg.SOLVER.BASE_LR *= args.batch_size / original_batch_size at line 195.
For lines 200-204, if we train the model for the same number of epochs and different number of batch size (or batch size * iter size), we will update the model weights fewer times. This shouldn't matter.
To reproduce the numbers, you could try different initial random seeds by changing cfg. RNG_SEED. In addition, in our experiments, we found that the vgg16_voc2007 configuration is more stable than vgg16_voc2007_more.

Hi, thank you for the quick response.
When we use batch size 1 and iter size 4, cfg.SOLVER.BASE_LR *= args.batch_size / original_batch_size and cfg.SOLVER.BASE_LR /= effective_batch_size / original_batch_size actually give the same base learning rate 0.0005. If we use for example batch size 1 and iter size 4, the former still gives 0.0005 while the latter gives 0.00025. The corresponding real learning rate are then 0.004 and 0.002 respectively. In this case, is 0.004 the correct real learning rate?

Sorry for the delayed reply. For batch size 1 and iter size 4, cfg.SOLVER.BASE_LR will be 0.0005, and the actual learning rate will be 0.0005 * iter size = 0.002. For batch size 2 and iter size 8, cfg.SOLVER.BASE_LR will also be 0.0005 (because cfg.SOLVER.BASE_LR is unrelated to iter size), and the actual learning rate will be 0.0005 * iter size = 0.004. This should be reasonable according to linear scaling rule in this paper. You could also tune the learning rate for iter size 8 for better results.
You could also try to tune the training iterations for better results. In my experience, for most cases we could simply half the number of iterations if we double the batch size * iter size (so we train our models the same number of epochs).

Thank you for the response. It is extremely helpful.


851 doc: updating documentation structure, adding system level docs

This PR ended up expanding beyond just adding system level docs. Also refactored existing documentation structure into the following major/minor headings w. some sections left with short descriptions so they can be filled in later/as needed, see below. Changed to a temporary format for readability and ability to compare to other documentation sites, format will be finalized in #915. Added media folder to _static to house images.

Installation (same as before)
User Guide (new section)

basic CLI structure and use
API Use
Tutorials
Pathology Workflow documentation
Troubleshooting (temporary)

API reference (same as before)
Developer Guide (new section)

Developer installation and testing instructions (from the readme)
Documentation generation (from the readme)
Contributing (temporary)
Technical Architecture (temporary)
Resources (temporary)

About (new section)

About Luna (temporary)
Motivation and Purpose (temporary)
Authors (temporary)

Codecov Report

Merging #232 (1533416) into master (b05c36d) will decrease coverage by 8.97%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #232      +/-   ##
==========================================
- Coverage   53.86%   44.88%   -8.98%
==========================================
  Files          78       72       -6
  Lines        5954     5534     -420
==========================================
- Hits         3207     2484     -723
- Misses       2747     3050     +303

Impacted Files
Coverage Δ

pyluna-common/tests/luna/common/test_constants.py
0.00% <0.00%> (-100.00%)
:arrow_down:

...athology/tests/luna/pathology/common/test_utils.py
0.00% <0.00%> (-100.00%)
:arrow_down:

...hology/tests/luna/pathology/cli/test_load_slide.py
0.00% <0.00%> (-100.00%)
:arrow_down:

.../tests/luna/pathology/common/test_build_geojson.py
0.00% <0.00%> (-100.00%)
:arrow_down:

...ts/luna/pathology/cli/test_collect_tile_segment.py
0.00% <0.00%> (-100.00%)
:arrow_down:

pyluna-common/tests/luna/common/test_graph_enum.py
0.00% <0.00%> (-97.02%)
:arrow_down:

...y/proxy_table/regional_annotation/test_generate.py
0.00% <0.00%> (-91.84%)
:arrow_down:

pyluna-pathology/luna/pathology/common/utils.py
20.00% <0.00%> (-40.77%)
:arrow_down:

pyluna-common/luna/common/Node.py
26.59% <0.00%> (-37.24%)
:arrow_down:

...a-pathology/luna/pathology/common/build_geojson.py
54.42% <0.00%> (-26.54%)
:arrow_down:

... and 7 more

Continue to review full report at Codecov.

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Lenient Late Setting

If one attempts to pair, an error is thrown saying that the lenient late setting does not exist if one uses the program as-is. It requires one to open, in the python console, TabSettings.set("lenient_late", 0) to make the pairings work.

I'm unable to reproduce this. Things I've tried:
-Creating a new tournament as specified in the README (change the password, do runserver, login)
-Initializing a new tourney before running server (initialize_tourney test ../testdir; runserver, login)
In both scenarios I've successfully verified that lenient_late exists in the database and have successfully paired a round. Could you provide more information on how to reproduce this error?

Did you try deleting the database?

Both of my attempts were from fresh downloads of the git repo. I'll give it another shot tonight. Could you provide an exact sequence of deleting the database, and any other manage.py commands you run before adding data and pairing?

Mine was a fresh download of the git repo from about a month ago. Have you tried to pair Round 1 or Round 2?

On 28 Nov 2016, at 19:06, Benjamin Marks<EMAIL_ADDRESS>wrote:
Both of my attempts were from fresh downloads of the git repo. I'll give it another shot tonight. Could you provide an exact sequence of deleting the database, and any other manage.py commands you run before adding data and pairing?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub https://github.com/jolynch/mit-tab/issues/47#issuecomment-263435449, or mute the thread https://github.com/notifications/unsubscribe-auth/AA8D9HJkblJ_EnMzKH-GN49GtMijgVswks5rC2yOgaJpZM4Kdmr4.

I've only paired Round 1. Are you getting the error on Round 2? Again, a full list of commands for reproduction would be helpful

From a fresh download, I put in the data, then attempted to pair. I believe it went through for Round 1, but it had an issue with Round 2.
I also spoke with Sean at Fordham, apparently, they ran into this issue as well.

On 28 Nov 2016, at 19:10, Benjamin Marks<EMAIL_ADDRESS>wrote:
I've only paired Round 1. Are you getting the error on Round 2? Again, a full list of commands for reproduction would be helpful
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub https://github.com/jolynch/mit-tab/issues/47#issuecomment-263436089, or mute the thread https://github.com/notifications/unsubscribe-auth/AA8D9GW6ohDPRCsOoaQIML4Go0lp0p9uks5rC21sgaJpZM4Kdmr4.

Ok, I've tried pairing Round 2 and am still unable to reproduce the error. Can you attach the following:

Your database before Round 1
Your database immediately before the pairing that causes the error.
A list of the data and results you're including

I've verified that pairing_db_clean and pairing_db have lenient_late set in the tab_settingss table. Unless the value is somehow deleting itself midway through the tournament, I'm not sure how this error is occurring in the first place

I've put in a zip file the database after pairing: tab-noshow-error.zip
Below is the traceback:
Environment:

Request Method: GET
Request URL: http://localhost:8000/pairing/pair_round/

Django Version: 1.6.1
Python Version: 2.7.10
Installed Applications:
('django.contrib.admin',
 'django.contrib.auth',
 'django.contrib.contenttypes',
 'django.contrib.sessions',
 'django.contrib.messages',
 'django.contrib.staticfiles',
 'south',
 'mittab.apps.tab')
Installed Middleware:
('django.contrib.sessions.middleware.SessionMiddleware',
 'django.middleware.common.CommonMiddleware',
 'django.middleware.csrf.CsrfViewMiddleware',
 'django.contrib.auth.middleware.AuthenticationMiddleware',
 'django.contrib.messages.middleware.MessageMiddleware',
 'django.middleware.clickjacking.XFrameOptionsMiddleware',
 'mittab.apps.tab.middleware.Login',
 'django.middleware.transaction.TransactionMiddleware')

Traceback:
File "/Library/Python/2.7/site-packages/django/core/handlers/base.py" in get_response
  114.                     response = wrapped_callback(request, *callback_args, **callback_kwargs)
File "/Library/Python/2.7/site-packages/django/db/transaction.py" in inner
  339.                 return func(*args, **kwargs)
File "/Library/Python/2.7/site-packages/django/contrib/auth/decorators.py" in _wrapped_view
  22.                 return view_func(request, *args, **kwargs)
File "/Users/ifly6/Documents/Dropbox/Developer/PycharmProjects/iflycode-mit-tab/mittab/apps/tab/pairing_views.py" in pair_round
  142.             tab_logic.have_properly_entered_data(current_round_number)
File "/Users/ifly6/Documents/Dropbox/Developer/PycharmProjects/iflycode-mit-tab/mittab/libs/tab_logic.py" in have_properly_entered_data
  272.             if had_noshow:
File "/Library/Python/2.7/site-packages/django/db/models/query.py" in __nonzero__
  100.         self._fetch_all()
File "/Library/Python/2.7/site-packages/django/db/models/query.py" in _fetch_all
  854.             self._result_cache = list(self.iterator())
File "/Library/Python/2.7/site-packages/django/db/models/query.py" in iterator
  220.         for row in compiler.results_iter():
File "/Library/Python/2.7/site-packages/django/db/models/sql/compiler.py" in results_iter
  710.         for rows in self.execute_sql(MULTI):
File "/Library/Python/2.7/site-packages/django/db/models/sql/compiler.py" in execute_sql
  781.         cursor.execute(sql, params)
File "/Library/Python/2.7/site-packages/django/db/backends/util.py" in execute
  69.             return super(CursorDebugWrapper, self).execute(sql, params)
File "/Library/Python/2.7/site-packages/django/db/backends/util.py" in execute
  53.                 return self.cursor.execute(sql, params)
File "/Library/Python/2.7/site-packages/django/db/utils.py" in __exit__
  99.                 six.reraise(dj_exc_type, dj_exc_value, traceback)
File "/Library/Python/2.7/site-packages/django/db/backends/util.py" in execute
  53.                 return self.cursor.execute(sql, params)
File "/Library/Python/2.7/site-packages/django/db/backends/sqlite3/base.py" in execute
  450.         return Database.Cursor.execute(self, query, params)

Exception Type: OperationalError at /pairing/pair_round/
Exception Value: no such column: tab_noshow.lenient_late


split pdf fix - Replace rmagick read with from blob

Simpler solution and is working on large numbers of pages (300+)

@rathukugan there's a failing test. Not sure why, but please look into this. (Could it be that this change makes a page that previously had an error actually parse successfully?)

@rathukugan and @jenachoi I merged this in now so that you are using it in your work improving the error rate.


Ampersand (&) added for no reason?

Hi guys, could you confirm if this is a bug or works as intended?

import requests
import json

url = "http://server:8080/jsonrpc?request=";
headers = {'content-type': 'application/json'};
payload = {blah};

r = requests.get(url, params=json.dumps(payload), headers=headers);

print(r.url);

It outputs the encoded string BUT for no reason adds an ampersand as below:
http://server:8080/jsonrpc?request=**&**{blah}
This provokes parse errors when querying XBMC/KODI server.
Thanks!

It is indeed working as intended.
The problem is this: we have no real way of knowing what you mean when you provide part of the query string as part of the URL and part in the 'params' section. You're doing something particularly unexpected by passing parameters as a string rather than a mapping (though I suspect that's for the sake of this limited example and not your actual code).
The position is generally that if you want us to build your query string you should let us build the whole thing, or at least build whole name-value pairs. Don't ask us to build a part of a name-value pair, because it's really hard to see when that's intended behaviour.
I don't really consider this a bug, more a sharp edge in the API.

Mmmm. So basically, i messed it up when put ?request=

@GAZ082 the following should work:
import requests
import json

url = "http://server:8080/jsonrpc";
headers = {'content-type': 'application/json'};
payload = {'foo': 'bar'}
params = {'request': json.dumps(payload)}

r = requests.get(url, params=params, headers=headers)

print(r.url)

In the future though, questions like this will be answered quickly on StackOverflow

Thank you sigma.


how to run the miner?

how to run the miner?

It's now integrated in Zcash beta RC2. See the beta guide for how to run it.

Dear tromp,
Is headernonce in equi_miner.cpp concatenates block header in this order :
version(4bytes) + hashPrev(32) + hashMerkleRoot(32) + hashReserved(32) + time(4) + nBits(4) + nonce(32)
?

My solver only makes the following assumptions about the header:
it has length 140 bytes.
the 4 bytes at 128,129,130,131 are part of the nonce field.
you can pass any 140 header to my solver and it will try a range of nonce by changing those 4 bytes.

Thx for reply


Brax V2 pbd is about 3x slower than V1

Why is the positional backend (pbd) in Brax v2 about 3x slower than v1 on humanoid? I observed that substep and dt may have differences, but v1 has a total of 533 pbd steps, and v2 has a total of 666 pbd steps, the difference should not be that big.
Here are the benchmark results:
JAX 0.4.8 @ RTX 3090 * 1

V2 Humanoid PBD

Pop size 1024 FPS 212603.0
Pop size 2048 FPS 341043.9
Pop size 4096 FPS 430086.4
Pop size 10240 FPS 411593.8

V1 Humanoid PBD

Pop size 1024 FPS 441713.6
Pop size 2048 FPS 873183.5
Pop size 4096 FPS 1237109.4
Pop size 10240 FPS 1310780.7

JAX 0.4.11 @ RTX 3090 * 1

V2 Humanoid PBD

Pop size 1024 FPS 199116.0
Pop size 2048 FPS 328199.3
Pop size 4096 FPS 415347.5
Pop size 10240 FPS 403450.6

V1 Humanoid PBD

Pop size 1024 FPS 467750.8
Pop size 2048 FPS 926400.9
Pop size 4096 FPS 1372671.0
Pop size 10240 FPS 1417486.8

The benchmark code is as following:
from functools import partial
import time

import jax
import jax.numpy as jnp

from brax import envs

def create_env(env_name, is_v2, max_steps_per_episode=1000):
    if is_v2:
        # V2 API
        env = envs.get_environment(env_name, backend="positional")
        env = envs.wrapper.EpisodeWrapper(env, max_steps_per_episode, 1)
        env = envs.wrapper.VmapWrapper(env)
    else:
        # V1 API
        env = envs.get_environment(env_name)
        env = envs.wrappers.EpisodeWrapper(env, max_steps_per_episode, 1)
        env = envs.wrappers.VmapWrapper(env)

    return env

@partial(jax.jit, static_argnames=["env", "pop_size", "steps"])
def benchmark(
    env,
    seed:     int = 0,
    pop_size: int = 10240,
    steps:    int = 1000,
):
    # Init state
    init_state_key, act_seq_key = jax.random.split(jax.random.PRNGKey(seed))
    init_state                  = env.reset(jax.random.split(init_state_key, pop_size))

    act_seq                     = jax.random.uniform(act_seq_key, (steps, pop_size, env.action_size), minval=-1, maxval=1)

    # Scan
    def _step_env(carry, act):
        return env.step(carry, act), None

    return jax.lax.scan(_step_env, init_state, act_seq)

def main():
    env_name  = "humanoid"
    is_v2     = False

    pop_sizes = [1024, 2048, 4096, 10240]
    steps     = 1000

    # create env
    env = create_env(env_name, is_v2)

    # bench
    for pop_size in pop_sizes:
        conf = dict(env=env, steps=steps, pop_size=pop_size)

        # JIT warmup
        result = benchmark(**conf)
        jax.tree_map(lambda x: x.block_until_ready(), result)

        # Test time
        t_start = time.time()

        result = benchmark(**conf)
        jax.tree_map(lambda x: x.block_until_ready(), result)

        fps = (pop_size * steps) / (time.time() - t_start)

        print(f"Pop size {pop_size} FPS {fps:.1f}")

if __name__ == "__main__":
    main()

Hi @imoneoi , thanks for running these benchmarks on an RTX!
Indeed there is a slow down compared to v1, here are a few notable reasons:

handling of non-spherical inertias
properly applying forces at CoMs/joints (going back and forth between CoM/link/joint positions)
prismatic and prismatic+universal type joints
generally having written things in a way s.t. generalized and positional backends are interoperable

This is still a WIP! We have our eye on speeding things up for both generalized and positional, and we're open to contributions with notable speed-up gains

Thanks! I also noticed that v2 pbd may be more accurate than v1.
BTW, are there any recommended tools for profiling and locating bottlenecks in Brax?

Thanks! I also noticed that v2 pbd may be more accurate than v1.
BTW, are there any recommended tools for profiling and locating bottlenecks in Brax?

I am not sure about Brax specifically, but I think it would be good to start with Profiling JAX Programs? If you are using Colab, you can see google/jax#3694 as well.


Release/1.4.1

Coverage remained the same at 100.0% when pulling 2962c72415eee56ea777038dd6f9d930c4e89a11 on release/1.4.1 into 8ce9a2751be7996214c0c68c25afa2f2ef5b7446 on master.


Pre-commits for black and flake8

Given that we are several people actively contributing to this project, consistency in code style and quality should be a goal. To this end, I have added instructions for setting up so-called pre-commit hooks for black (automated code formatted) and flake8 (checking for errors and PEP8-compliance). When set up, these check the code and report error every time a commit is made. This means that we, as developers and reviewers, won't have to worry about style and formatting, and can instead focus on the contents of, and logic behind, new contributions.
This PR:

Adds config files for pre-commits and black
Updates the contributing guide with details about how to set up and use pre-commit hooks
Updates the setup.py file to include pre-commit for the "develop" extras. (NB: This file has been re-formatted with black as part of this PR.)

If we want to automate/standardise formatting in this way, I could re-format the entire code base using black once and for all (see #28; purely stylistic and with no impact on functionality) and then all new contributions will be entirely consistent.

Ping @RasmusOrsoe

Right now, you don't need to do anything, and you can write and add code as you've always done. In CONTRIBUTING.md I have included details on how to install the pre-commit hooks that do these style checks automatically. I'd recommend adding them, and it's pretty simple to do so. :)  In the future, once the entire code base is cleaned up, we could make these checks a requirement for merging PRs, but that's not done right now.


Added safety check for creation_time

Accessing creation_time when it doesn't exist will throw an exception and it will cause the thumbnail to be never generated. Added a simple if condition to make sure it doesn't throw an exception.
Fixes #13

Thanks!


Munich Tenant OnBorading - Import users from Munich tenant

Copy of Mitarbeiter Liste_neu.xlsx

Email are missing we are waiting for a new Excel file.

@mahdibenromdhane The Excel file in attachment already contains the e-mails. Please perform the import as soon as you have time.
Thanks,
Fred

Tested by Philip in Munich


Implement The Doge Programming Language

Implement The Doge Programming Language
Description
Implements the Doge programming language - a swift derived language with a windows compiler that is in development.
Checklist:

[x] I am associating a language with a new file extension.

[x] The new extension is used in hundreds of repositories on GitHub.com

Search results for each extension:

https://github.com/search?utf8=✓&type=Code&ref=searchresults&q=extension%3Adoge+NOT+nothack

[x] I have included a real-world usage sample for all extensions added in this PR:

Sample source(s):

[URL to each sample source, if applicable]

Sample license(s):

[ ] I have included a change to the heuristics to distinguish my language from others using the same extension.

[x] I am adding a new language.

[ ] The extension of the new language is used in hundreds of repositories on GitHub.com.

Search results for each extension:

https://github.com/search?utf8=✓&type=Code&ref=searchresults&q=extension%3Adoge+NOT+nothack

[ ] I have included a real-world usage sample for all extensions added in this PR:

Sample source(s):

[URL to each sample source, if applicable]

Sample license(s):

[x] I have included a syntax highlighting grammar.
[ ] I have included a change to the heuristics to distinguish my language from others using the same extension.

[ ] I am fixing a misclassified language

[ ] I have included a new sample for the misclassified language:

Sample source(s):

[URL to each sample source, if applicable]

Sample license(s):

[ ] I have included a change to the heuristics to distinguish my language from others using the same extension.

[ ] I am changing the source of a syntax highlighting grammar

Old: https://github-lightshow.herokuapp.com/
New: https://github-lightshow.herokuapp.com/

[ ] I am adding new or changing current functionality

[ ] I have added or updated the tests for the new or changed functionality.

Just a heads up, this PR is not going to be approved until the minimum popularity requirement is met. From CONTRIBUTING.md:

We try only to add new extensions once they have some usage on GitHub. In most cases we prefer that extensions be in use in hundreds of repositories before supporting them in Linguist.

The search results show only 108 files and several of those appear to be duplicates of what does not appear to be a language similar to the files you've added to this PR.
I've labeled this PR accordingly. You're welcome to keep this PR open, but it may be several years before we'd consider merging it; it really depends on how popular the language becomes.


Add GitHub Actions

I have made things!

Checklist

[x] I have read contributing guidelines
[x] I'm sure that I did not unrelated changes in this pull request
[x] I have created at least one test case for the changes I have made
[x] I have added myself to the CONTRIBUTORS.rst

Related issues

Closes #963

I made an initial attempt at migrating the current Travis CI to GitHub Actions. @lk-geimfari you will have to create some repository secrets:

[x] CODECOV_TOKEN
[ ] PYPI_PASSWORD

For now I have left the codecov step commented out so it doesn't fail the pipeline, once secrets are in place we can try properly.
I also cached the virtual environment so we get quicker subsequent runs if the dependencies don't change 😄
This is what it looks like:

@michael0liver First of all — thank you very much for this PR. I've added a comment.

@michael0liver Thank you again. You have done a great job!.

@michael0liver Sure! I'll do it after solving #976 and #975. Thanks again!


Why AST different between parse5(as expected) and htmlparser2(not as expected)?

hello world

In htmlparser2:

But in parse5:

I think the result AST parse5 outputs is as expected?

Transferred to domhandler, as this seems to be the problematic project.

Added a test case in 593d944. It looks like htmlparser2 and domhandler are producing the expected output, I suspect AST Explorer is the culprit here (cc @fkling).

Our implementation seems to extend DomHandler. It's possible that that causes some issues. I'll investigate.


[MNT] Clean up CUB-related stuff

Blocked by #3461.
This PR does three things:

Remove the temporary env var CUPY_CUB_PATH and related codes from the codebase (#3445)
Set a size limit for cupy.cuda.cub.cub_reduction() until we have a better way to address #3309.
cdef'd a few internal functions

Testing if I have access to the CI...
pfnCI, test this please

Jenkins CI test (for commit 0ac0bfe069f4d884c1f74d05948d8577af05f68c, target branch master) succeeded!

Need to wait for #3461 merged first.

Power cycle to trigger RTD.

Jenkins CI test (for commit be9d7355aa1179d9d85affd27097389dde882a18, target branch master) succeeded!

Need to wait for #3461 merged first.

It's merged. Retry the CI...
Jenkins, test this please

Jenkins CI test (for commit be9d7355aa1179d9d85affd27097389dde882a18, target branch master) succeeded!

@kmaehashi Should we add another check to detect CUB_DISABLED and warn users that it is now ignored?

Jenkins, test this please

Jenkins CI test (for commit e99b8f9be9ab2bcb3ffda7e6000a149b7565b18a, target branch master) succeeded!

cdef'd a few internal functions

If this helps expedite the review, I could revert this part of changes as the rest two changes are fairly straightforward.

Sorry for the delay, LGTM.

pfnCI, test this please.

Jenkins CI test (for commit e99b8f9be9ab2bcb3ffda7e6000a149b7565b18a, target branch master) succeeded!

Many thanks, @kmaehashi! Glad to see we're close to another release!


Corrected Docker Port in README.md

The command to launch ReDoc with Docker had the -p values reversed.
According to the Docker Docs, it should be HOST_PORT:CLIENT_PORT.
The Nginx service is running on port 80 inside the container, 8080 is the
port exposed on the host.

Coverage remained the same at 82.006% when pulling c8b0e5cede546939f459b8074588690fa5af7f25 on RobertDeRose:RobertDeRose-updated-readme into 97db54aa2e67561187f90f94e1a8163535d425d3 on Rebilly:master.

Thanks!


[HxSidebar] Keep items expanded

Needed to solve this bug.

@hakenr can we move forward with this PR? I think the discussion in AB#63485 is resolved and the agreed upon solution has been implemented.

(This PR = "má si pamatovat předchozí stav")

@hakenr I forgot to remove the KeepItemsExpanded parameter, we decided that this functionality wouldn't be adjustable, that's why it's not used anywhere.


corretto21: init at <IP_ADDRESS>.1

Description of changes
This adds corretto21 to nixpkgs. This PR uses the same approach as for corretto{11,17,19}.
Building on darwin doesn't work. See this PR for details. This PR here does not make it worse nor better.
The additional extraConfig idea is stolen from @pcasaretto as done in the PR linked above.
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[x] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

@infinisil You have been proposed here for review.
@Artturin You reviewed the initial PR for corretto.
Could you please have a look and possibly merge after everything is okay.

@ofborg build corretto11 corretto17 corretto19

Thanks @Artturin


Python runtime deadlock due to logging + multithreading + fork

Requests are being logged to sys.stdout using wsgi-request-logger.
The logging module (used by wsgi-request-logger) acquires a lock while writing to sys.stdout.
https://github.com/kubeless/runtimes/blob/b5fea6b3422166f13740089812a926497b6a5631/stable/python/kubeless.py#L105-L109

The default start method for a Process (using multiprocessing) in Unix is fork.
If a new Process is forked at exactly the same time as the sys.stdout lock being held in one of the threads of the main process, the lock state is replicated in the subprocess resulting in a deadlock when the subprocess tries to flush stdout (in _flush_std_streams) because the lock is already being held in the subprocess and there is nobody to release it.
  File "/opt/miniconda3/lib/python3.7/multiprocessing/util.py", line 400 in _flush_std_streams
  File "/opt/miniconda3/lib/python3.7/multiprocessing/process.py", line 317 in _bootstrap
  File "/opt/miniconda3/lib/python3.7/multiprocessing/popen_fork.py", line 74 in _launch
  File "/opt/miniconda3/lib/python3.7/multiprocessing/popen_fork.py", line 20 in __init__
  File "/opt/miniconda3/lib/python3.7/multiprocessing/context.py", line 277 in _Popen
  File "/opt/miniconda3/lib/python3.7/multiprocessing/context.py", line 223 in _Popen
  File "/opt/miniconda3/lib/python3.7/multiprocessing/process.py", line 112 in start

This happens even without a single print statement in the function's handler.

More information about this issue can be found at the following links:

https://bugs.python.org/issue28382
https://bugs.python.org/issue6721

I am not a Python expert. What would be a possible solution here?

Hi @andresmgot , I'm still trying to find a fix without losing any of the functionality we have today.
The recommended solution is to use the spawn start method instead of fork.
The docs themselves say that fork is problematic when used with multithreading (cherrypy is a multithreaded server).

fork
The parent process uses os.fork() to fork the Python interpreter. The child process, when it begins, is effectively identical to the parent process. All resources of the parent are inherited by the child process. Note that safely forking a multithreaded process is problematic.

But, the problem with spawn is that it is slower than fork and I also lose one very critical ability - the ability to load something into memory once and use that in all subsequent requests. For example, if I have a huge machine learning model to load from disk, today I can load it outside the handler function and it will be available to all the subsequent requests because forked processes start with a copy of the parent process' memory. If we do a spawn, each child process (i.e, request) will load the machine learning model from disk separately.

Before #83 was fixed, we were never waiting for child processes to complete. The deadlock only occurs when we wait for the child process to complete (p.join()) and hence, this issue might have become more observable since the fix for #83 .

Hi @andresmgot . Is there any plan to drop support for the Python2.7 runtime. Any solution using "spawn" or "forkserver" won't be possible in Python2.7 which only supports "fork".

Official support for python 2.7 has been dropped since Jan 2020 so I am okay if we need to remove it.


Dockerized test environment

I found it quite tricky to figure out how to run all codecept tests. I would really love to have it possible to be able to run all tests with one command. Also manually running php server for helpers tests was little bit irritating for me.
I use Docker a lot in development and don't want to install Selenium locally. @DavertMik I would like to get your opinion on that if it's something you'd consider merging and suggesting as simpler way to contribute.
If you like the idea I can cleanup the code and finish it sometime soon. There's still issue with Appium tests (I didn't have time to fit it yet).
Todo:

[x] easy way to run single helper tests
[x] Cleanup code
[x] green travisCI and Semaphore
[x] rest test
[x] move docker-compose to test dir
[x] acceptance test
[x] support node 6 & node 8
[x] Update travis config to use dockerized tests
[x] README info about using it for development :)

Thanks @jploskonka . This is really great initiative. If you make it work with Appium I will adore you )
I couldn't make it run in Docker. It would be great to have headless mobile tests using Docker. If you make it work I'd add it to documentation as well...
Also, I'd propose to move docker-compose.yml into tests or rename it to docker-compose-test.yml so people knew this file is for internal testing, not for starting a project itself.
And there should be a flexible and documented way to run exact one helper and one test. As running all of them takes lot of time

I played a bit with Appium today and unfortunately wasn't able to run it :/ My container is always stuck on booting emulator so far:
 Not sure if it's stuck or just takes so long to boot on my machine :D
I will give it one more shot this week, if I can't figure anything out I'll focus on getting rest of todos done ;) Still even without appium I think it's beneficial already and we can always work on Appium later. Thanks for your feedback!

I will give it one more shot this week, if I can't figure anything out I'll focus on getting rest of todos done ;) Still even without appium I think it's beneficial already and we can always work on Appium later. Thanks for your feedback!

Yep, and thanks for your input 🤗. That would be really great to have easy to setup test environment

@DavertMik Another batch of updates, it's getting more interesting :D
I have problems with test/acceptance. Specs for WebDriver passes OK, but nightmare fails on iframe related examples. I couldn't find info about those specs in contributing.md and also it looks like those aren't run on travisCI nor semaphore. Am I doing something wrong or are those outdated and maybe broken?
I'm also not 100% convinced to separate docker-compose services for each acceptance test, but it's easier to debug it for now ;)

I have problems with test/acceptance. Specs for WebDriver passes OK, but nightmare fails on iframe related examples. I couldn't find info about those specs in contributing.md and also it looks like those aren't run on travisCI nor semaphore. Am I doing something wrong or are those outdated and maybe broken?

I didn't work with them for a long time so everything is possible 🙃
Please proceed, some tests may be disabled. Esp for Nightmare...

Also I noticed that acceptance specs are tagged with @protractor while there's no protractor codecept config ;)

I found it only here:
Scenario('within on form @WebDriverIO @protractor @nightmare', (I) => {

In this case I think @protractor corresponds to SeleniumWebdriver helper

Almost done :D I still see issues mostly with travisCI integration but I'm not sure if this should be tackled in this PR or some other:

Builds against node 6.9.5 are failing on travis, I didn't experienced it locally yet. I'd guess those are timeouts issues but I'm not sure.
Because of building codecept container total build time on Travis is significantly longer
I no longer test no-docker version of codecept which may lead to some compatibility issues
Acceptance tests are not run on Travis, would be nice to tweak it (especially after #755 got merged and added some useful tests there)
See builds https://travis-ci.org/Codeception/CodeceptJS/builds/293626424 and https://travis-ci.org/Codeception/CodeceptJS/builds/293621806

When I started working on this PR I didn't intended to use dockerized tests on travis yet, I did it only to check out how it would work and then couldn't resist going further :D I rolled back .travis.yml to version from master and builds are green. I think the best way would be to merge this and I'd like to work further on mentioned issues in separate PRs.

Thanks!
Maybe we could setup another CI for testing docker container only?
There are still few free CIs so why not to use them. I'd pick Wercker CI http://www.wercker.com as it's already based on Docker container and could be easily set up for it.

I played a bit with Wercker and wasn't able to even start containers. I encountered some strange issues with privileges inside containers and gave up for now. I don't have much time this week to work on it ;)
Basically there's a lot of places we can improve this, but I'd like to add next things as separate PRs. Please let me know what do you think is must have to update here so we can get this merged and I can work on CI integration when I have some more time, probably next week :)

Thanks, let's switch to something new from Wercker


ngCsp example doesn't work

Hi,
I'm looking into ngCsp to secure an app I'm working on, but could not get it to reject anything that was supposedly bad. So I went back to the example in the documentation, but that one seemingly doesn't work either. The eval in the example evaluates nicely instead of throwing an error. This goes for 1.4, 1.3 and 1.2.28 on my local setup. Am I missing something obvious? Tried latest chrome, firefox and safari on yosemite mac.
Try and click the evil button in the example. I'm getting no response and can log the eval outcome.
https://docs.angularjs.org/api/ng/directive/ngCsp
Thanks,
Maarten

Hi ottens,
My understanding is that the ngCsp directive will prevent angular from using features forbidden by CSP (e.g. eval), in its internals. However, angular will not prevent you from using these features in your own code. If anything is forbidden, it will be at the browser level and not by angular.
As for the example, CSP isn't enabled on usual webpages, so the browser doesn't throw an error when eval is used. I do agree that the example is not optimal since CSP is not enabled, and thus nothing happens when you press the Evil button.
The same thing happens with your app. CSP is not enabled in the environment you are testing in. I don't know what your environment is, but if everything is allowed in it, you don't have to worry about CSP at all.

Thanks for the answer. The example threw me off quite a bit, but I seems to have a better grasp now.
When I add ng-csp it indeed prevents Angular from doing some things that a CSP would not allow, e.g. injecting inline CSS. So that part works (and would perhaps be a better example, e.g. ng-show doesn't work because it relies on inline css, easy to demonstrate with ng-csp). To prevent things like eval and different origin script loading prevention, I need to set the CSP in the headers of the responses, on the server. That I got working too. In the end I now understand ng-csps main function is to prevent a harmless error from popping up. It has nothing inherently to do with Content Security Policies, just forces Angular in the CSP compatible mode before the auto detection finds it.
Thanks again, much appreciated.

Just a heads-up:
There are directives (like ngShow/Hide, ngCloak etc) which rely on CSS. In CSP mode, Angular can't inline stylesheet rules, so in order for them to work, you have to include a CSS file "manually".
Other than that (and performance aside), everything should work the same (as far as Angular itelf is concerned).
From the docs:

CSP forbids JavaScript to inline stylesheet rules. In non CSP mode Angular automatically includes some CSS rules (e.g. ngCloak). To make those directives work in CSP mode, include the angular-csp.css manually.


Pick up hourly HVAC setpoint values from schedule file if available

Make thermostat setpoint optional if it's not in the OS-HPXML file. In our workflow it won't be in the hpxml file if it's hourly, it'll be in the schedule file.

Closed via #80


figaro heroku:set -e production does not work

figaro heroku:set -e production
 ▸    Usage: heroku config:set KEY1=VALUE1 [KEY2=VALUE2 ...]
 ▸    Must specify KEY and VALUE to set.

Here's my simple application.yml:
production:
  FACEBOOK_KEY: "VALUE"
  FACEBOOK_SECRET: "VALUE"

Make sure Spring isn't running. Also, what version of Ruby, Rails, Figaro are you using?

Thank you. It works when Spring is not running.

what is Spring?


Use :blank: when trimming the strings

For sed command (https://www.gnu.org/software/sed/manual/sed.html)

:space: includes tab, newline, vertical tab, form feed, carriage return, and space while
:blank: includes space and tab

Close because after testing, the issue isn't with :space: or :blank: but with echo -e.
https://unix.stackexchange.com/questions/189787/difference-between-echo-and-echo-e
I don't think I know enough about bash to make this change


Adds custom error messages. closes StefanTerdell/zod-to-json-schema#26

Discussion in #26.
Adds optional error messages to chained function call checks to string, set, array, and number.
IE
zodToJsonSchema(someSchema, {errorMessages: true})

z.string().min("string too short") // {type: 'string', minLength: 5, errorMessage: {minLength: 'string too short'}}

[X] Implementation
[X] Tests
[X] Readme

should be good now let me know if it needs anything else!

@iway1 Looks solid AF, nice work! Do you mind updating the readme as well? Should probably include a format description and a note about compatibility with RHF.

@StefanTerdell Appreciate it!
Good call - just updated the readme.

I am sorry about the indentation changes in the test file my VSCode diff viewer is not correctly showing those as being changed before I push even though I'm double checking - IDK what I'm doing wrong 😬

Looks great. I will try to merge and release after work today

@iway1 Out now as 3.19.4 :)

@StefanTerdell Woohoo! Thanks for taking the time to review and everything. Now I can just bump my version and watch my project support custom error messages

🥲


[CAPI/acr] Update tizen capi

Changes proposed in this PR:

Setting void *user_data
Update layer type enum

Self evaluation:

Build test: [X]Passed [ ]Failed [ ]Skipped
Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Jihoon Lee<EMAIL_ADDRESS>

:memo: TAOS-CI Version: 1.4.20191203. Thank you for submitting PR #883. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://nnsuite.mooo.com/.

:memo: TAOS-CI Version: 1.4.20191203. Thank you for submitting PR #883. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://nnsuite.mooo.com/.


[VS Code] RPC connection closed.

Can't Sign In on VS Live Share, when using "Live Share: Sign in with user code".
Using Linux Deepin:
$ uname -a
Linux Tavern 4.14.0-deepin2-amd64 #1 SMP PREEMPT Deepin 4.14.12-2 (2018-01-06) x86_64 GNU/Linux

Visual Studio Code
Version 1.23.1
Commit d0182c3417d225529c6d5ad24b7572815d0de9ac
Date 2018-05-10T16:04:33.747Z
Shell 1.7.12
Renderer 58.0.3029.110
Node 7.9.0
Architecture x64

Sorry, this is the same as #299.
Solved by following this comment.
Thanks.

@wescoder That's great to hear! Thanks for following up and letting us know you're unblocked.


Fixes #1037, New live-map reliability check

Here I use solely the newly discovered 'li' property to detect the invalidation of the live-map token.
Next steps would be to re-login instead of marking the coordinates as unreliable.
Please take a good look onto it!

Looks OK to me.
However relogin should be done only once (and it would be good if some visual reloging would take place)

@mucek4 If the user is not logged in ONE try is made to login again.

My comment was for different scenario.
Let's say we get maps data back. And it's not logged in. We issue a login and it fails for some reason.
We get map data again without login. We should not try to login again as we get in endless loop

Seems to be working good.
All caches reliable when logged in as basic member as well as when logged in as premium member.


Update "Change your language" help center page

This is a revision pass on #22353.

I pushed an update addressing the feedback above -- let me know what you think!

I don't know that the new title for the instructions (Change the language of the Zulip app) is clear enough about why message content, message topics and stream names / descriptions are not associated with the UI setting.
Maybe it matters more for languages that aren't close to 100% translated (like Spanish) vs ones that are more complete? Because when it's only partially translated, it's a bit fuzzier about what still could be translated vs what is not affected by the setting at all.

Added:

Note that this will not change stream names, topic names, or the language of
messages you receive.

Looks good to me!

@timabbott ready for your review.

Merged, thanks @alya and @laurynmm!


Installation Hands on

i'm currently stuck on the step:   Installing the Required Karaf Features
when i run the code below:
frazer@frazer-Islandora:~$ sudo /opt/karaf/bin/client feature:install activemq-blueprint
i get the output below:
Logging in as karaf
Error executing command: Unable to resolve root: missing requirement [root] osgi.identity; osgi.identity=activemq-blueprint; type=karaf.feature; version="[5.15.11,5.15.11]"; filter:="(&(osgi.identity=activemq-blueprint)(type=karaf.feature)(version>=5.15.11)(version<=5.15.11))" [caused by: Unable to resolve activemq-blueprint/5.15.11: missing requirement [activemq-blueprint/5.15.11] osgi.identity; osgi.identity=activemq; type=karaf.feature; version="[5.15.11,5.15.11]"]

I'm not quite sure what's up here, the build instructions do say to use a version of Karaf 4.2.x so they may be out of date with this Karaf version
but can you check contents.
cat /opt/karaf/etc/org.pos4j.pax.logging.cfg
Just want to make sure it matches what's expected.

I get the output below:
frazer@frazer-Islandora:~$ cat /opt/karaf/etc/org.pos4j.pax.logging.cfg
Root logger
log4j.rootLogger=INFO, out, osgi:*
log4j.throwableRenderer=org.apache.log4j.OsgiThrowableRenderer
File appender
log4j.appender.out=org.apache.log4j.RollingFileAppender
log4j.appender.out.layout=org.apache.log4j.PatternLayout
log4j.appender.out.layout.ConversionPattern=%d{ISO8601} | %-5.5p | %-16.16t | %-32.32c{1} | %X{bundle.id} - %X{bundle.name    } - %X{bundle.version} | %m%n
log4j.appender.out.file=/var/log/karaf/karaf.log
log4j.appender.out.append=true
log4j.appender.out.maxFileSize=1MB
log4j.appender.out.maxBackupIndex=10
Camel Logger
log4j.appender.camel=org.apache.log4j.RollingFileAppender
log4j.appender.camel.layout=org.apache.log4j.PatternLayout
log4j.appender.camel.layout.ConversionPattern=%d{ISO8601} | %-5.5p | %-16.16t | %-32.32c{1} | %X{bundle.id} - %X{bundle.na    me} - %X{bundle.version} | %m%n
log4j.appender.camel.file=/var/log/karaf/camel.log
log4j.appender.camel.append=false
log4j.appender.camel.maxFileSize=1MB
log4j.appender.camel.maxBackupIndex=10
log4j.logger.org.apache.camel=INFO, camel
Islandora Logger
log4j.appender.islandora=org.apache.log4j.RollingFileAppender
log4j.appender.islandora.layout=org.apache.log4j.PatternLayout
log4j.appender.islandora.layout.ConversionPattern=%d{ISO8601} | %-5.5p | %-16.16t | %-32.32c{1} | %X{bundle.id} - %X{bundl    e.name} - %X{bundle.version} | %m%n
log4j.appender.islandora.file=/var/log/karaf/islandora.log
log4j.appender.islandora.append=false
log4j.appender.islandora.maxFileSize=1MB
log4j.appender.islandora.maxBackupIndex=10
log4j.logger.ca.islandora.camel=INFO, islandora
frazer@frazer-Islandora:~$

Using the suggested trying options i'm getting the below output:
frazer@frazer-Islandora:/tmp$ /opt/activemq/bin/activemq status
INFO: Loading '/etc/default/activemq'
INFO: Using java '/usr/bin/java'
ActiveMQ not running

If that's the case I think you need to go back to this step https://islandora.github.io/documentation/installation/manual/installing_karaf_and_alpaca/#activemq-5
If you're able to successfully install activemq I think the step you're on with karaf will resolve.
I think maybe we should ask @seth-shaw-unlv  about how we could update the current documentation to reflect the change he mentioned where the build may not need karaf. Seth if I'm incorrect or misrepresenting what you said on the other issue please let me know.

I've gone back to the specified step of installing Activemq, but still
facing the same issue.
On Sat, Jul 9, 2022, 06:29 Will @.***> wrote:

If that's the case I think you need to go back to this step
https://islandora.github.io/documentation/installation/manual/installing_karaf_and_alpaca/#activemq-5
If you're able to successfully install activemq I think the step you're on
with karaf will resolve.
I think maybe we should ask @seth-shaw-unlv
https://github.com/seth-shaw-unlv about how we could update the current
documentation to reflect the change he mentioned where the build may not
need karaf. Seth if I'm incorrect or misrepresenting what you said on the
other issue please let me know.
—
Reply to this email directly, view it on GitHub
https://github.com/Islandora/documentation/issues/2128#issuecomment-1179476994,
or unsubscribe
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This issue still remains unresolved....
Kindly assist me with the instructions for installing Alpaca 2, which does not need karaf.

Frazer, Are you aware of the google group? I think we may be better off getting help there.
https://groups.google.com/g/islandora


[IconMenu] Add an animated property

[ ] PR has tests / docs demo, and is linted.
[x] Commit and PR titles begin with [ComponentName], and are in imperative form: "[Component] Fix leaky abstraction".
[x] Description explains the issue / use-case resolved, and auto-closes the related issue(s) (http://tr.im/vFqem).

[IconMenu] Fix Added animated property to populate to Popover element

@barakmitz Thanks for this PR, that looks like a good addition 👍.
Could you have a look at my comment, squash down the commits and rename it with the title of this PR?
Aside for this, feel free to add an example in the documentation.

I updated as requested.
Can you confirm?

Could you [...] squash down the commits and rename it with the title of this PR?
Aside for this, feel free to add an example in the documentation.

@barakmitz You have missed those points 😁.

@barakmitz What's the use case for turning off the animation? If we're adding this prop, it also needs to be added to DropDownMenu for consistency.
@oliviertassinari Even Popover itself doesn't have an example of disabling the animation, so I"m not sure it's necessary here.

Hi,
@oliviertassinari I didn't find an option to ' squash down the commits'
@mbrookes The popover is not the problem. I did not set changes to PopOver.

Animation are a matter of taste, and in the examples they have left it.
The issue is that IconMenu has a bug due to rapping the PopOver element. Since PopOver has a constant 500 ms delay on line 178 if animations are enabled, this causes the menu to 'hold' for 500 ms EVERY time.
Using IconsMenu property of 'touchTapCloseDelay' that is in the api, with a value of 0 makes the problem worse.
The menu is closing with no animation at all, but freezes for 500 ms before coming back and reacting to the next click.
This causes a problem when clicking the menu several times in a row.
This makes the component of IconMenu useless for us.
The fix is straight forward and easy to use. I think this should be added to allow using 'touchTapCloseDelay correctly

@barakmitz, Sounds like you mostly wish so mask sume underlying issues, so it would be good if you could document those in a separate issue.
Please add the same prop to DropDownMenu for consistency,
Also, I think you may have misunderstood what I said to @oliviertassinari about the docs example / Popover.

@mbrookes I have added it to DropDownMenu for consistency,

@barakmitz Thanks. Please quash and use the current PR title as the commit title.

@mbrookes  I have squashed the commits

@barakmitz Can you please squash this down into a single commit?

I don't know what i've done, I tried to squash commits and it reverted everything and closed the thread. I recreated it here
https://github.com/callemall/material-ui/pull/4442


Compile with dirname fails silently when paths are wrong

Should fail with an OSError

Please provide the following so we can appropriately handle your issue:

What version you're using
A small reproducible example
What the expected behaviour in that case should be

I think (?) I figured out what you meant so I'm fixing it: #119

Yep, its exactly that

This is part of 0.11.0!


某个定时任务执行不成功怎么看日志[QUESTION]

Before you submit this issue, you has been search all existed issues and search the documentation

[] I've been search all existed issues
[] I've been read all documentation

Describe your question
其中个定时任务执行不成功怎么看日志，或者说怎么看执行不成功的原因

自行在 Crontab 里面捕获异常自行记录日志，这个属于你业务代码产生的异常，需自行记录
/switch-to question


vscode git push failed,but in the mac shell is ok

￼￼￼

<EMAIL_ADDRESS>password:
Permission denied, please try again.
<EMAIL_ADDRESS>password:
Permission denied, please try again.
<EMAIL_ADDRESS>password:
Permission denied (publickey,gssapi-keyex,gssapi-with-mic,password).
fatal: Could not read from remote repository.
Please make sure you have the correct access rights
and the repository exists.

Can you show me a screenshot? Is your repository SSH or HTTPS? Does an authentication popup show up?

If you enabled 2FA then you'll need to create a personal access token to use to push via https: https://help.github.com/articles/creating-a-personal-access-token-for-the-command-line/
Else, I'd just do a git remote set-url origin again.

@joaomoreno  i use the SSH way,when i user the mac shell way to git push ,it's ok;but in the vscode sofeware ,it warns that “Git:Permission denied, please try again”. so i open the git logs,it describes like this:
git push
Permission denied, please try again.
Permission denied, please try again.
Permission denied (publickey,gssapi-keyex,gssapi-with-mic,password).
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
git fetch
Permission denied, please try again.
Permission denied, please try again.
Permission denied (publickey,gssapi-keyex,gssapi-with-mic,password).
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.

git status -z -u
git symbolic-ref --short HEAD
git rev-parse feature-20170926-norightPage
git rev-parse --symbolic-full-name --abbrev-ref feature-20170926-norightPage@{u}
git rev-list --left-right feature-20170926-norightPage...origin/feature-20170926-norightPage
git for-each-ref --format %(refname) %(objectname)
git remote --verbose

@joaomoreno  I also find that vscode doesnot have right to write files in the mac ,i must use the chmod filedir to get the right so that i can save file-modifies ,in the earlier version vscode works ok.

This is a setup issue.
Please use Stack overflow as described in
Submitting-Bugs-and-Suggestions.
Thanks!


Can you add mail support

I was thinking of having a Mail Feature in Retro Aim Server. Just like the orignal aim where when mail arrives you get a sound effect that says you got mail

Mail isn't on the server side. You need to set that up in your client.