Decode Julia profile

Still WIP, and I am unsure if I got the finer details of the file-format right.
As an example a CallFrame is identifying a function right now and not a location inside a
function.

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Cool, thanks!
We can't use JSON3.jl, I'm afraid... We need something that works with JSON.jl v0.20.1, that is the version we'll have available in the VS Code extension.
The other thought I had in the initial implementation was to try to not allocate a new representation of the JSON output in memory, but instead just write/stream it out to JSON? But maybe that was silly... I had thought that might make sense because profile things could get very large? Not sure, we can probably ignore that.

Yeah I just didn't want to deal with writing JSON while having to deal with the more complicated parts ;)
Not sure yet if we can stream most of this data.

I just tried it, and the values in samples look weird to me? When I export without C stuff, I get an array with only pointers to the node 1?

Actually, are you storing only references to root nodes in the samples vector? I had assumed it should be references to leaf nodes only?

Looking at this:

I get the impression that the whole tree is up-side-down: it seems that as I drill down there, I'm getting the caller as the child node. I think it should be the other way around.

I would also think that only leaf nodes should have tick info? Not sure, though...
I think you can take out all the hitCount, I don't believe the VS Code visualizer is using that.

Actually, are you storing only references to root nodes in the samples vector? I had assumed it should be references to leaf nodes only?

I thought of it as the entry to the sample, but it being the exit makes more sense.

I get the impression that the whole tree is up-side-down: it seems that as I drill down there, I'm getting the caller as the child node. I think it should be the other way around.

I have flipped the tree twice :P I think the first time around make more sense. It's weird since I am thinking about the profile data and what child means there, whereas I should probably think about what it means for the profile display.

I think the tree is in the right order. At least speedscope.app seems to think so. I fixed the samples bug.
I get a spurious randn so there are probably still bugs and I can't open it on my copy of VSCode, due to the: " Cannot read property 'selfTime' of undefined."

I can just open the file that gets generated with the latest Insiders edition, no problem... Weird...
The samples node still looks very weird to me. When I profile
function profile_test(n)
    for i = 1:n
        A = randn(100,100,20)
        m = maximum(A)
        Am = mapslices(sum, A; dims=2)
        B = A[:,:,5]
        Bsort = mapslices(sort, B; dims=1)
        b = rand(100)
        C = B.*b
    end
end

with @profile profile_test(10), I only get five elements in the samples vector, that can't be right?

with @profile profile_test(10), I only get five elements in the samples vector, that can't be right?

I got 57 samples. Are you on Windows? I think on windows the timer is limited to a magnitude lower sample rate.
Hm the VSCode extension gives me different results than the speedscope.app. Will comment on the main repo.

Are you on Windows?

Yes, that is probably it.
Should we merge this soon and then sort out any additional improvements in new PRs? Or do you want to continue iterating here? I'm indifferent :)

We can merge as is :)

Julia's Profile module now has separate computation of the tree (aka ProfileNode), so you might want to consider porting over to use that?

@vtjnash which versions of Julia would support that? We normally try to support all Julia 1.x versions in the VS Code extension... But maybe it would be ok to say that this new feature only works with newer versions of Julia...


Come up with a better solution for reloading tabTitle

@DHowett-MSFT

tabTitle is the only one it will matter for (and it doesn't work right right now), but this will be lost on a settings reload.

@zadjii-msft

That wouldn't matter though, would it? The startingTitle doesn't work on reload anyways - it's just the title the process starts with.

@DHowett-MSFT

Er that's what I mean when i say "doesn't work right now" -- tabTitle is a weird one where it should totally win if suppressApplicationTitle is turned on, right? So we have a minor issue right now where the tab title never gets pushed down to the right place (Terminal Core right now) on reload.. but this compounds the issue b/c if we DO implement that properly profiles started with this shortcut will have their tab titles lost.

We need to shake this story out, esp. with #3825 merged. If a tab hasn't set the title, and it's still using the initial "tabTitle", then when we hot-reload, we should update that value. If someone's using a title that's provieded as a part of the tabTitle in NewTabArgs, we should also probably use that instead of the settings one on reload.
This also represents work to dig through this story and make sure these settings are really getting plumbed through to the right layers, since we're getting pretty consistent bugs with it.

Meh, I'm going to say "no one's complained about this". Sure, we could see if a tab has the same title as a changed tabTitle, and then manually change it, but that seems like a lot of work that no one seems to be bothered by.


Move actual position of output connection and remove rendering adjustment

This address #425, so blocks with outputs are snapped at their y-half-way-point.

lgtm.
Related: This change https://github.com/google/blockly/pull/389/files was merged into scratch-blocks, as I recall, but it didn't really do anything in scratch-blocks because the rendering code has diverged significantly.  One of the goals of the change was to make all of the connected blocks move at the same time so we can see the code path better.  This would be good to have in scratch-blocks as well.

Cool, I'll make an issue for that.


Error in run.py working with colab

I've had problems with setup but adding to the header or roi_pool.cpp and roi_pool_kernel.cu has finished the process ok.
Now I'm stuck with run.py
I execute:
!python run.py train -h
And this is the result:
/
/content/faster-rcnn-pytorch
Traceback (most recent call last):
File "run.py", line 9, in
from script.train import train
File "/content/faster-rcnn-pytorch/script/train.py", line 12, in
from model.vgg16 import VGG16
File "/content/faster-rcnn-pytorch/lib/model/vgg16.py", line 1, in
import torchvision
File "/usr/local/lib/python3.6/dist-packages/torchvision/init.py", line 3, in
from torchvision import models
File "/usr/local/lib/python3.6/dist-packages/torchvision/models/init.py", line 12, in
from . import detection
File "/usr/local/lib/python3.6/dist-packages/torchvision/models/detection/init.py", line 1, in
from .faster_rcnn import *
File "/usr/local/lib/python3.6/dist-packages/torchvision/models/detection/faster_rcnn.py", line 7, in
from torchvision.ops import misc as misc_nn_ops
File "/usr/local/lib/python3.6/dist-packages/torchvision/ops/init.py", line 13, in
_register_custom_op()
File "/usr/local/lib/python3.6/dist-packages/torchvision/ops/_register_onnx_ops.py", line 51, in _register_custom_op
register_custom_op_symbolic('torchvision::_new_empty_tensor_op', new_empty_tensor_op, _onnx_opset_version)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/init.py", line 195, in register_custom_op_symbolic
return utils.register_custom_op_symbolic(symbolic_name, symbolic_fn, opset_version)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 740, in register_custom_op_symbolic
.format(symbolic_name))
RuntimeError: Failed to register operator torchvision::_new_empty_tensor_op.                            The symbolic name must match the format Domain::Name,                            and sould start with a letter and contain only                            alphanumerical characters
The messages from the install:
/content
/content/faster-rcnn-pytorch/lib
running develop
running egg_info
writing faster_rcnn_utils.egg-info/PKG-INFO
writing dependency_links to faster_rcnn_utils.egg-info/dependency_links.txt
writing top-level names to faster_rcnn_utils.egg-info/top_level.txt
writing manifest file 'faster_rcnn_utils.egg-info/SOURCES.txt'
running build_ext
building 'C' extension
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/main.cpp -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/main.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/cpu/roi_pool.cpp -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cpu/roi_pool.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/cpu/nms.cpp -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cpu/nms.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/cpu/roi_align.cpp -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cpu/roi_align.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11
/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/cuda/nms_cuda_kernel.cu -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cuda/nms_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS -D__CUDA_NO_HALF2_OPERATORS_ --expt-relaxed-constexpr --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++11
/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign
/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign
/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/cuda/roi_pool_kernel.cu -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cuda/roi_pool_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++11
In file included from /content/faster-rcnn-pytorch/lib/csrc/cuda/roi_pool_kernel.cu:6:0:
/content/faster-rcnn-pytorch/lib/csrc/cuda/cuda_helpers.h:3:66: warning: backslash-newline at end of file
#define CUDA_1D_KERNEL_LOOP(i, n)                                \
/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(97): warning: attribute "visibility" does not apply here
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(112): warning: attribute "visibility" does not apply here
In file included from /content/faster-rcnn-pytorch/lib/csrc/cuda/roi_pool_kernel.cu:6:0:
/content/faster-rcnn-pytorch/lib/csrc/cuda/cuda_helpers.h:3:66: warning: backslash-newline at end of file
#define CUDA_1D_KERNEL_LOOP(i, n)                                \
/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(97): warning: attribute "visibility" does not apply here
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(112): warning: attribute "visibility" does not apply here
/usr/local/cuda/bin/nvcc -DWITH_CUDA -I/usr/local/lib/python3.6/dist-packages/torch/include -I/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.6/dist-packages/torch/include/TH -I/usr/local/lib/python3.6/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.6m -c /content/faster-rcnn-pytorch/lib/csrc/cuda/roi_align_kernel.cu -o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cuda/roi_align_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++11
In file included from /content/faster-rcnn-pytorch/lib/csrc/cuda/roi_align_kernel.cu:4:0:
/content/faster-rcnn-pytorch/lib/csrc/cuda/cuda_helpers.h:3:66: warning: backslash-newline at end of file
#define CUDA_1D_KERNEL_LOOP(i, n)                                \
/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(97): warning: attribute "visibility" does not apply here
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(112): warning: attribute "visibility" does not apply here
In file included from /content/faster-rcnn-pytorch/lib/csrc/cuda/roi_align_kernel.cu:4:0:
/content/faster-rcnn-pytorch/lib/csrc/cuda/cuda_helpers.h:3:66: warning: backslash-newline at end of file
#define CUDA_1D_KERNEL_LOOP(i, n)                                \
/usr/local/lib/python3.6/dist-packages/torch/include/c10/core/TensorTypeSet.h(44): warning: integer conversion resulted in a change of sign
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(97): warning: attribute "visibility" does not apply here
/usr/local/lib/python3.6/dist-packages/torch/include/torch/csrc/autograd/profiler.h(112): warning: attribute "visibility" does not apply here
creating build/lib.linux-x86_64-3.6
x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/main.o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cpu/roi_pool.o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cpu/nms.o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cpu/roi_align.o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cuda/nms_cuda_kernel.o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cuda/roi_pool_kernel.o build/temp.linux-x86_64-3.6/content/faster-rcnn-pytorch/lib/csrc/cuda/roi_align_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.6/_C.cpython-36m-x86_64-linux-gnu.so
copying build/lib.linux-x86_64-3.6/_C.cpython-36m-x86_64-linux-gnu.so ->
Creating /usr/local/lib/python3.6/dist-packages/faster-rcnn-utils.egg-link (link to .)
Adding faster-rcnn-utils 0.3 to easy-install.pth file
Installed /content/faster-rcnn-pytorch/lib
Processing dependencies for faster-rcnn-utils==0.3
Finished processing dependencies for faster-rcnn-utils==0.3
As pre requisites I've installed
!pip install python3-dev
!pip install torch==1.3
!pip install colorama
!pip install easydict
!pip install pyyaml
!pip install matplotlib
!pip install numpy
Don't know what to do....

One thing else:
You sai in the other issue :  "If you compile process finished without errors, you must find this module in ./lib folder.
Name of the module: _C.........pyd."
In the folder /lib of colab there is not any file    _C.........pyd.

I've had problems with setup but adding to the header or roi_pool.cpp and roi_pool_kernel.cu has finished the process ok.

Oh, sorry, i don't tested build process on Linux. Yes, need to add #include <float.h> only for roi_pool.cpp file. test in google colab I commit this change today.

I execute:
!python run.py train -h
And this is the result:

Very strange output. With -h flag, run.py show only help message, not run train script.
I test library in colab right now, so it works. My code (i suppose that missing include in roi.pool.cpp already added):
!pip uninstall torch torchvision
!pip install colorama easydict pyyaml matplotlib numpy
!pip install torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html

!git clone https://github.com/loolzaaa/faster-rcnn-pytorch.git
%cd faster-rcnn-pytorch/ && mkdir data
!python setup.py develop
:: ^^^ install without errors

%cd ..
import lib
import torch
import _C
:: ^^^ import is OK, no errors

!python run.py train --cuda
:: ^^^ start script is OK, error about dataset, because i don't upload it

In the folder /lib of colab there is not any file _C.........pyd.

Yes, colab don't show them. You can check file by command !ls in lib folder or:
import os
os.listdir('lib')

I commit this change today.

Done!

I see you are very responsive!!
I had problems with prerequisites, but I see you have done a great job.
Thank you very much!!


Bytesfellow initial submittion

Check List:

[x] Tests pass (./test.sh bytesfellow shows no differences between expected and actual outputs)
[x] All formatting changes by the build are committed
[x] Your launch script is named calculate_average_<username>.sh (make sure to match casing of your GH user name) and is executable
[x] Output matches that of calculate_average_baseline.sh
[x] For new entries, or after substantial changes: When implementing custom hash structures, please point to where you deal with hash collisions (line number)

No custom hashmap implementation.

Execution time: ~11 seconds on MacBook pro m1 (10 cores) on the 10K key set sample (and 12 seconds when limiting the number of available cores to 8 to approximate the test configuration);
Execution time of reference implementation: 190seconds

00:16.457.


Add native run mode

Add a run mode which uses our Wasm->C->native setup instead of host runtime Wasm engine (run --native?). Slower compile time, more unstable, better performance at runtime time?

I think it would be similar to cargo run and that would be honestly very good

You can now do porf --native ... to run like normal but using the native target (compiles to a native binary and executes it immediately).


Set max and min default range of values for UINT8 TFlite quantization

tflite_convert takes many arguments by default to perform the model conversion.
This commit set default values of the min and max quantization ranges.

@suharshs - Can you please take a look at this? While applying a range seems reasonable, I'm not sure it's best to use the hard-coded value here.

Closing, since this is not what default_range_stats is intended for. And this will result in unexpected poor accuracy.


Remove hack to work around PB MapReduce errors difference from HTTP

Other than my question about exception type in the default case, +1 to this patch: it passes all the tests on my setups.


python 2 compatibility

I'll leave this PR open for now re: python 2 compatibility.
It seems to be having an issue with k3d.volume
Here's the environment:
https://travis-ci.com/MarvinT/birdbrain/jobs/179581305
This is the stacktrace:
Input:
plot, vec  = plot_regions_3d(starling_atlas, regions_to_plot = nuclei+tracts, downsample_pct = 1, polygon_simplification = 0, verbose=False)
Traceback:
TypeErrorTraceback (most recent call last)
<ipython-input-9-794d66952dd4> in <module>()
----> 1 plot, vec  = plot_regions_3d(starling_atlas, regions_to_plot = nuclei+tracts, downsample_pct = 1, polygon_simplification = 0, verbose=False)
/home/travis/build/MarvinT/birdbrain/birdbrain/visualization/plotting_3d.py in plot_regions_3d(atlas, regions_to_plot, downsample_pct, polygon_simplification, verbose)
    101         alpha_coef=0.25,
    102         bounds=bounds,
--> 103         compression_level=9,
    104     )
    105
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/k3d/k3d.pyc in volume(volume, color_map, color_range, samples, alpha_coef, gradient_step, shadow, shadow_delay, shadow_res, compression_level, **kwargs)
    690         Volume(volume=volume, color_map=color_map, color_range=color_range, compression_level=compression_level,
    691                samples=samples, alpha_coef=alpha_coef, gradient_step=gradient_step, shadow=shadow,
--> 692                shadow_delay=shadow_delay, shadow_res=shadow_res),
    693         **kwargs)
    694
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/k3d/objects.pyc in __init__(self, **kwargs)
    710
    711     def __init__(self, **kwargs):
--> 712         super(Volume, self).__init__(**kwargs)
    713
    714         self.set_trait('type', 'Volume')
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/k3d/objects.pyc in __init__(self, **kwargs)
     45         self.id = id(self)
     46
---> 47         super(Drawable, self).__init__(**kwargs)
     48
     49     def __iter__(self):
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/ipywidgets/widgets/widget.pyc in __init__(self, **kwargs)
    412
    413         Widget._call_widget_constructed(self)
--> 414         self.open()
    415
    416     def __del__(self):
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/ipywidgets/widgets/widget.pyc in open(self)
    425         """Open a comm to the frontend if one isn't already open."""
    426         if self.comm is None:
--> 427             state, buffer_paths, buffers = _remove_buffers(self.get_state())
    428
    429             args = dict(target_name='jupyter.widget',
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/ipywidgets/widgets/widget.pyc in get_state(self, key, drop_defaults)
    510         for k in keys:
    511             to_json = self.trait_metadata(k, 'to_json', self._trait_to_json)
--> 512             value = to_json(getattr(self, k), self)
    513             if not PY3 and isinstance(traits[k], Bytes) and isinstance(value, bytes):
    514                 value = memoryview(value)
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/k3d/helpers.pyc in to_json(input, obj, force_contiguous)
     58         return [to_json(i, obj) for i in input]
     59     elif isinstance(input, np.ndarray):
---> 60         return array_to_binary(input, obj, force_contiguous)
     61     else:
     62         return input
/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/k3d/helpers.pyc in array_to_binary(ar, obj, force_contiguous)
     34
     35     if obj.compression_level > 0:
---> 36         return {'compressed_buffer': zlib.compress(memoryview(ar), obj.compression_level), 'dtype': str(ar.dtype),
     37                 'shape': ar.shape}
     38     else:
TypeError: compress() argument 1 must be string or read-only buffer, not memoryview

I can close this, right?

The tests still don't pass in python 2, but I can import into python 2.
I think it would be nice to get it to run eventually in python 2 or at least get it to error out nicely but I'm not sure if I'll get around to doing that. I guess leave it open for now and we'll see how it goes by the time I finish my figure.

alright, this works now @timsainb you can pull this in.


kubectl metadata files created

Pods and service running on default namespace. I see a story to deploy on dev and prod so tested it out on default.

Would you be able to see the service running in the URL (combined with the public IP and port 31000)?

External IP: http://<IP_ADDRESS>:31000/


ion-segment share scroll

Ionic version:  (check one with "x")
[ ] 1.x
[x] 2.x
I'm submitting a ...  (check one with "x")
[x] bug report
[ ] feature request
[ ] support request => Please do not submit support requests here, use one of these channels: https://forum.ionicframework.com/ or http://ionicworldwide.herokuapp.com/
Current behavior:
I have ion-segment having 2 segments. Each segment has a list of items. If I scroll one list, it scrolls other as well. Currently, I'm using this.content.scrollToTop(); in segment ionChange but it's visible that list is scrolling to top on segment change.
Expected behavior:
Segment shouldn't share scroll. Scrolling one segment shouldn't affect other. Each segment should remember it's scrolled position.
Steps to reproduce:

Related code:
Use conference app.

Other information:

Ionic info: (run ionic info from a terminal/cmd prompt and paste output below):
Your system information:

Cordova CLI: 6.4.0
Ionic Framework Version: 2.0.0-rc.5
Ionic CLI Version: 2.1.18
Ionic App Lib Version: 2.1.9
Ionic App Scripts Version: 0.0.48
ios-deploy version: 1.9.0
ios-sim version: 5.0.8
OS: macOS Sierra
Node Version: v6.7.0
Xcode version: Xcode 8.1 Build version 8T61a

Hello, thanks for using Ionic! I am going to close this issue for now as ion-segment is meant to share the same scroll. You can use tabs to get the behavior you are looking for. Thanks!


[mesheryctl] Add a no deploy flag to meshery bash script

Description
Add a no deploy flag to meshery bash script
Changes:

add --no_deploy flag to bash script
mask stdout/stderr of mv command
handle permission issues seen on PopOS

This PR fixes #3200
Notes for Reviewers
Added "-n" option to bash script to install the mesheryctl cli alone.
Need to update documentation on how to use the new env variable DEPLOY_MESHERY.
Signed commits

[ ] Yes, I signed my commits.

Signed-off-by: Hussaina Begum Nandyala<EMAIL_ADDRESS>

Codecov Report

Merging #3459 (bd5a25c) into master (b9d3b71) will decrease coverage by 1.75%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #3459      +/-   ##
==========================================
- Coverage   12.30%   10.54%   -1.76%
==========================================
  Files          37       37
  Lines        3162     3186      +24
==========================================
- Hits          389      336      -53
- Misses       2690     2783      +93
+ Partials       83       67      -16

Flag
Coverage Δ

gointegrationtests
?

unittests
10.54% <ø> (-0.09%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

mesheryctl/internal/cli/root/system/check.go
1.49% <0.00%> (-21.13%)
:arrow_down:

mesheryctl/internal/cli/root/system/config.go
1.11% <0.00%> (ø)

mesheryctl/internal/cli/root/system/status.go
0.00% <0.00%> (ø)

mesheryctl/internal/cli/root/system/system.go
69.23% <0.00%> (ø)

mesheryctl/internal/cli/root/system/start.go
1.27% <0.00%> (+<0.01%)
:arrow_up:

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@devansh42 will you give this a review?

@Shreyas220 fyi

Hey @hexxdump, This seems a great enhancement in the installation script.
Adding no_deploy can help users to have an ad-hoc installation like pulling only desired adapters, this can also help us solving this issue as well.
One cosmetic change we can make is to change --no_deploy to --no-deploy, as it makes come coherence with Cobra's style of argument.

@hexxdump Will the flag work with the current one-liner bash script? I believe that it will not when we pipe the bash script. See: #3168

@navendu-pottekkat, you are right, its difficult to export multiple env variables in oneliner.
However, we could pass this new option as below :
export DEPLOY_MESHERY=false; curl -L https://git.io/meshery | PLATFORM=docker bash -
or
export DEPLOY_MESHERY=true; curl -L https://git.io/meshery | PLATFORM=kubernetes bash -
One can completely skip  DEPLOY_MESHERY environment variable, as the default value is to deploy meshery.
i.e. the below command syntax is as good as the above syntax for kubernetes platform.
curl -L https://git.io/meshery | PLATFORM=kubernetes bash -

Do we need to update documentation?

Are we going to merge this?

@hexxdump a potentially helpful example:
curl -L https://istio.io/downloadIstio | ISTIO_VERSION=1.6.8 TARGET_ARCH=x86_64 sh -.

From https://istio.io/latest/docs/setup/getting-started/

@hexxdump a potentially helpful example of multiple args:
curl -L https://istio.io/downloadIstio | ISTIO_VERSION=1.6.8 TARGET_ARCH=x86_64 sh -.

From https://istio.io/latest/docs/setup/getting-started/

I checked again, this actually works.
$ cat meshery | DEPLOY_MESHERY=false PLATFORM=docker bash -

Downloading mesheryctl-v0.5.34 for Darwin...

  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   643  100   643    0     0   3552      0 --:--:-- --:--:-- --:--:--  3552
100 17.9M  100 17.9M    0     0  5255k      0  0:00:03  0:00:03 --:--:-- 5825k
tr: Illegal byte sequence

Extracting mesheryctl-v0.5.34 to temporary folder temp_extract_dir...
Archive:  /tmp/mesh/meshery.zip
  inflating: /tmp/mesh/temp_extract_dir/LICENSE
  inflating: /tmp/mesh/temp_extract_dir/README.md
  inflating: /tmp/mesh/temp_extract_dir/mesheryctl

Installing mesheryctl in /usr/local/bin.
mesheryctl binary installed.
permissions moved to hnandyala
Removing installation files
mesheryctl command installation is complete.

Oh, very cool. This is a small victory.

@hexxdump seems like if we would not need to use flags and use the one liner as you shared above. Since DEPLOY_MESHERY is optional, this would work fine. Should we also handle the case when PLATFORM is not specified? Should we set a default platform?

@navendu-pottekkat, Are you suggesting, if the PLATFORM is not specified on oneliner, we should not prompt the user for platform, but choose one by default?
@leecalcote,  should we remove the user prompt from meshery script and choose k8s platform as default platform?

@hexxdump It does not prompt the user now. Please check.

@navendu-pottekkat, As discussed offline, we can prompt the user if the env. variable is not specified.
Can we go ahead with merging these changes?

closing this PR as this change was made in this PR: https://github.com/meshery/meshery/pull/3692/


Create toa-swarmer plugin

This plugin displays numbers on the swarms in kephri boss room as they spawn.
In a similar way to how the nyloer plugin displays wave numbers on the nylos as they spawn.
Edit: The reason I didn't consider adding this functionality to the tombs-of-amascut plugin is because this plugin is going to eventually have another similar feature to nyloer, where it displays leaked swarms after room completion in a side-panel.

Edit: The reason I didn't consider adding this functionality to the tombs-of-amascut plugin is because this plugin is going to eventually have another similar feature to nyloer, where it displays leaked swarms after room completion in a side-panel.

Hi, I maintain that plugin. I'd gladly welcome both changes if you're willing.

If not, I may still steal them and add them to that plugin regardless.

Awesome!
I shall add this to the existing plugin then


Sign compare fixes v2

I´ve created this pull on #5230, #5225, #5219, #5152, #5131 and #5027 merged.
Please be so kind and review/merge these before this one.
What does this do:

Fixes all sign-compare warnings
Fixes a lot of dead store and dead increment warnings
Fixes some bugs found along the way
Brings down warning count with -Wall -Wextra -Wno-unused-parameter -Wno-unused-function -Wno-implicit-fallthrough from 254 to 8

@mfleisz yes, I've written that in the pull request description (need to merge all the referenced pulls first)

Overall LGTM but the we should remove the unnecessary casts in freerdp_image_copy imo

Rebased to master due to a merge conflict.

@hardening Time to review this? Should fix your issues with warnings #5210 #5239 ;)

Rebased due to merge conflicts...

@freerdp-bot test please


Add Temporal Cloud Observability example

This example demonstrates how to import temporal cloud metrics from the provided prometheus API endpoint into a DataDog account

 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.


Feature/load gpx track

Added the ability to load tracks (kml, gpx, geojson, json) using leaflet-filelayer and display them as new Overlay layer.
Addresses: https://github.com/nrenner/brouter-web/issues/30

Hey @matzepan, welcome aboard! Thanks for your contribution, it is one of the most asked-for feature. From what I've seen it's looking good, albeit a minor issue: it looks like tracks are declared as interactive layers but it seems they are not:

Good work!

@bagage this is also a feature that I wanted badly.
I changed the loaded track to be not interactive.
Thank you for your feedback.

What about keeping the loaded track in a URL parameter for easy sharing of the full view? For instance by encoding the polyline with mapbox/polyline in a track (tracks?) GET parameter similarly to https://github.com/nrenner/brouter-web/pull/233 (which I should finish by the way)?

@Phyks I don't know if it makes sense to put these into the URL. Especially if this means blowing up the URL length.

It makes sense to have it to easy share the view with someone else / another computer. But indeed it probably does not make sense to have it in the URL and risk blowing the URL length.
Maybe BRouter-web should have something like Overpass to shorten links and share easily (including custom profiles, etc).

Great contribution, thanks!


manifest: order subsystems alphabetically

Order the subsystems in the manifest file alphabetically, as they actually should be according to the comment within the manifest file.
Signed-off-by: Benedikt Schmidt<EMAIL_ADDRESS>

Sorry for the multiple updates, I'm currently trying to get to know this ecosystem and learning how I can contribute something.

Sorry for the multiple updates, I'm currently trying to get to know this ecosystem and learning how I can contribute something.

No worries, thanks for contributing!

Do I have to trigger the checks "Run compliance checks on patch series (PR)" and "Scan code for licenses" manually?

Do I have to trigger the checks "Run compliance checks on patch series (PR)" and "Scan code for licenses" manually?

I triggered that for you.  Github "feature" that for first time contributors we have to click a button to do it.


Es6 backtick XSS

With browsers implementing es6, or soon to be implementing template strings, I believe it is necessary to include the backtick  in the html escaping to prevent XSS of the form alert1` and the like.
I don't know if it is necessary to add the ` to the base64 test case but I added it to the others.

Hang on this is not needed, sorry for the pull request spam.  It already covered the backtick case...


Add subproject guard for code coverage all targets

LGTM, tested with https://github.com/swift-nav/starling/pull/2372 and seems to work.


feat: docs update

Updates the docs and typedoc. Closes #1474

oh, 1871 files. I'll just believe you! 😄


1436 cherry pickup ii

Codecov Report

Merging #85 (e4a828a) into master (e3fd0d2) will increase coverage by 0.09%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master      #85      +/-   ##
==========================================
+ Coverage   71.78%   71.88%   +0.09%
==========================================
  Files         556      558       +2
  Lines        9985    10019      +34
==========================================
+ Hits         7168     7202      +34
  Misses       2549     2549
  Partials      268      268

Impacted Files
Coverage Δ

...de/0910-Smallest-Range-II/910.Smallest Range II.go
100.00% <100.00%> (ø)

...ode/1463.Cherry-Pickup-II/1463.Cherry-Pickup-II.go
100.00% <100.00%> (ø)

Continue to review full report at Codecov.

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Sorry I'm late. I'm busy with some things of my own. Thank you for your contribution!

Sorry I'm late. I'm busy with some things of my own. Thank you for your contribution!


d-Reps

Scope : Oversight of delegated voting innovations
Deliverables :
The Survey deliverable will be used for a literature search contrasting “liquid democracy “ and “illiquid plutocracy “. The purpose is to provide measurable definitions for these terms. This would support the research for F8 CGO and provide some context for the interviews conducted within the community.
Issue :
https://github.com/Catalyst-Auditing/Community-Governance-Oversight-Coordination/issues/49

Updates - IOG have published a response to the community on d-Reps here - see transcript here

Action:
Letter to be discussed fully next meeting

The RadicalxChange community has announced an interesting update to their goals.  They are shifting from using "Quadratic" to "Plural" to describe their governance tools.  The purpose is to move beyond the mathematics of the methods towards focusing on how the tools support the development of Plurality communities.  The announcement was made in their newsletter and includes links to references.
https://www.radicalxchange.org/media/announcements/a-new-chapter-for-radicalxchange/

Here is the link to the dRep Literature review: https://docs.google.com/document/d/1ScqSFrOjIklEPEdQop7cH2vzIMjOwNMvVjGBwemA1UQ/edit


Announcement: Version 8 is coming

As the Release Candidate for Angular 8 is out since some days, we will now start with preparing the next version of this library. It will land soon and contain the following features:

Tested with Angular 8
Support for Code Flow + PKCE to align with the current Best Practice document
Features from Selected Pull Requests
Dramatically smaller Bundles Sizes by using browser-internal crypto APIs

If anyone wants to participate by providing a PR, you are welcome and this is the right time window now. In this case, please reach out.

Feel free to send ping or DM me when you'd need a beta tester 👍

Any plans for offline support ? #545

Good question. I think it will be easier, as with code flow we will support refresht tokens.
Btw: You can already trigger a token refresh by hand. There is a method, sth. like silentRefresh.

I'm using Silent Refresh already (may be I'm using it wrong).
Try it

Use a very small time for your access token (like 120 seconds).
Run your app
Use chrome tools to go Offline
Check the errors

I appreciate any guidance here

I think there's some confusion. There's two uses of the word "offline":

Issue #545 talks about being offline.... from the internet. As in, physical connection problems and the like.
The term "offline" is also used for a specific grant in openid/oauth2 that indicates the Client wants to get a refresh token (it's a confusing term when used in a browser Client, tbh)

The latter is already supported, if you use this library with the Password flow you can ask for "offline" scope and get a refresh token. In the Implicit flow this scope isn't used, I think. With (variants of) the Code flow it is used (I think?) so that might get support in v8?
But for the first item, in #545, I think that's something else entirely?

I would be interested in beta'ing version 8 if possible. Happy to provide feedback and/or bug reports. I've been doing a lot of stuff with IdentityServer4 and I really want a good angular frontend using code authorization+PKCE instead of implicit grant.

@jeroenheijmans totally agree on the confusion.
Yes, the problem is with "offline" connection (which is 2 ways: the client might lose connection or the server is down or unreachable).
Once the access token expires (or the silent refresh is working), it tries to reach out the issuing server for renewal.
If there is no internet connection, there should be proper handling, rather than throwing errors (like its doing now). It should do some sort of queuing or waiting or retrying mechanism.
Once the connection is online, the "silent refresh" should resume working as expected.

@manfredsteyer @jeroenheijmans is this coming only post angular 8 release?? I presume there would be no challenge in using the same version on angular 6 and rx 6! We're looking forward for PKCE flow and we may not upgrade to ng 8 yet.

Note that I have no say in this, I just try to help out by (and enjoy) supporting users of this library.
I presume though that the readme part about release cycle still holds, and that (presumably because of personal time constraints) new major versions typically align with and require new versions of Angular and possibly RxJs. So most likely you'd need to backport changes or create a custom fork/branch yourself to have v8 features in <v8-angular.

@jeroenheijmans thanks for letting me know what has to be done :) really helpful... Let me see if i can fork a branch and backport as you suggested.. I could try angular 5 with v5.0.2 (of this library) with just an rxjs compat and things were smooth... Just being greedy here if the same can be assumed with this release as well :)

Yes, it's as @jeroenheijmans says. We test the current lib version only with the current Angular version. It may work with an older Angular version, but no guarantees.

Any details on the release?

Would be lovely to see this release soon

any updates?

waiting! :)

https://github.com/manfredsteyer/angular-oauth2-oidc/pull/568
Behold.

Just for info. I upgraded my project to Angular 8, and oauth is still working fine.

@manfredsteyer Any info when we can expect a version with support of Authorization Code + PKCE?

Is there an ETA for this yet?

any updates?, Angular 8 is released for a while now..

I've tried implementing subtlecrypto, but it seems there's no way to get this to work. Has issues with recognizing what algorithm is being use and you get errors like:
NotSupportedError: Algorithm: Unrecognized name

I had to postpone it, but I've reserved some time for it in July.
The good message is, everything works with the current version (even though there are peer dependency warnings which will go away when version 8 lands).

@manfredsteyer I've tried implementing the crypto api, but I'm having a hard time with encoding, decoding and verifying. Having issues with arraybuffers.
I messed around in a branch that I branched from my upgrade-angular-8 branch in my own fork. Dunno if this might be handy for you or someone else.

This is great! Thanks for the info. Does it work? I guess, we need something like this in this library. I'm thinking about another tokenValidationHandler which uses the browser's native crypto api.
What do you think?

@manfredsteyer No it doesn't. Like I said, the crypto api uses arraybuffers for everything and I can't get those to decode properly. Might be doing it wrong though. First I tried the functions described here: https://developers.google.com/web/updates/2012/06/How-to-convert-ArrayBuffer-to-and-from-String
Later I used https://developer.mozilla.org/en-US/docs/Web/API/TextEncoder
Seems like a fine idea to put it into a separate handler for now.

Ad using subtle crypto, see also: https://github.com/damienbod/angular-auth-oidc-client/issues/26

I had to postpone it, but I've reserved some time for it in July.
The good message is, everything works with the current version (even though there are peer dependency warnings which will go away when version 8 lands).

We're looking forward to the update. Is there anything that you need help with @manfredsteyer ?

@jeroenheijmans This code is no longer in there, but I can see if I can get it to work.

-Support for Code Flow + PKCE to align with the current Best Practice document
I am waiting for this feature. Any date for relase v8?

Me two.
@volkanokcu If you can't wait at all you can use this fork https://github.com/bechhansen/angular-oauth2-oidc but it is still at version 4.0.1
I also need Support for Authorization Code Flow for a current project and unsure if to wait for the next release of this library or if I'll have to use the one linked above.
@manfredsteyer Can you make an estimation on when the relase could posibly come out?

Version 8 is out:
https://github.com/manfredsteyer/angular-oauth2-oidc/releases/tag/8.0.0
We have Code + PKCE + Token Refresh now.
Looking forward to your feedback.
Getting rid of the big crypto api when not supporting IE is still an open task.
@lwensveen is working on it (see above). Can anyone help him with the current show stoppers.

Welcome!

@manfredsteyer
when will you update CHANGELOG.md ?

Info now seems to be out there in the relevant places:

The GitHub releases
The NPM package

Some bug fix minor releases have already come after.
Going to clean up and close this issue, if anyone has problems with v8 (or in general) feel free to open a fresh issue!


Feat/add codecov

This pull request covers adding a test coverage functionality using codecov
@lasuk Please review the changes and provide feedback or approval for merging.

Thanks. No comments, just merging ...
Curious to see how it looks ....


Weird convolution error project 1

K_sharpen leads to values outside the interval [0, 1] so clamping is needed in the convolution.

This was an inaccuracy error. Fixed by automatically converting images to Float32 in image convolution.
I also found a bug in the elementary CA, but it should be fixed now.

This was an inaccuracy error. Fixed by automatically converting images to Float32 in image convolution.
I also found a bug in the elementary CA, but it should be fixed now.

Cool, thx. I only checked a few rules of the CA for correctness so it was
likely there was still a bug.
Op za 23 jan. 2021 16:00 schreef Michiel Stock<EMAIL_ADDRESS>
Closed #52 https://github.com/Beramos/DS-Julia2925/issues/52.
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Cool, thx. I only checked a few rules of the CA for correctness so it was
likely there was still a bug.
Op za 23 jan. 2021 16:00 schreef Michiel Stock<EMAIL_ADDRESS>
Closed #52 https://github.com/Beramos/DS-Julia2925/issues/52.
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edgeconnect-telemetry-demo issue

Hi,
I am trying to run the edgeconnect-telemetry-demo.
All the services start, but it seems that the  ec-telemetry-ec-telemetry-worker-[1-4] processes are having trouble writing to influxdb:
Process MultiprocessingWriter-1: Traceback (most recent call last):   File "/usr/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap     self.run()   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/util/multiprocessing_helper.py", line 164, in run     self.write_api.write(**next_record)   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/write_api.py", line 353, in write     return self._write_batching(bucket, org, record,   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/write_api.py", line 445, in _write_batching     self._write_batching(bucket, org, item, precision, **kwargs)   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/write_api.py", line 426, in _write_batching     self._write_batching(bucket, org, Point.from_dict(data, write_precision=precision, **kwargs),   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/write_api.py", line 423, in _write_batching     self._write_batching(bucket, org, data.to_line_protocol(), data.write_precision, **kwargs)   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/write/point.py", line 185, in to_line_protocol     _fields = _append_fields(self._fields)   File "/usr/local/lib/python3.10/dist-packages/influxdb_client/client/write/point.py", line 247, in _append_fields     raise ValueError(f'Type: "{type(value)}" of field: "{field}" is not supported.') ValueError: Type: "<class 'dict'>" of field: "traffic_class_name" is not supported.
I have tried updating the docker-compose file to pin the container image versions to those detail in readthedocs, but I get the same issue.
I also had to change the following in example.env:
COMPOSE_PROJECT_NAME=ec-telemetry
as the mixed upper/lowercase name is not supported by docker-compose.
Any ideas on this one?
Thanks,

Change was commited and merged to development branch.


Quicksilver crashes after .

Just updated to El Capitan. I used to be able to type a web address directly into quick silver.
Any use of a . results in quicksilver crashing immediately.

This is affecting many interfaces, but not all. See #2111

Great, thanks.

On Oct 13, 2015, at 12:49 PM, Rob McBroom<EMAIL_ADDRESS>wrote:
Closed #2122 https://github.com/quicksilver/Quicksilver/issues/2122.
—
Reply to this email directly or view it on GitHub https://github.com/quicksilver/Quicksilver/issues/2122#event-434320980.


Using basic authentication not setting current_user

I'm attempting to use the MOTOR_AUTH_USERNAME and MOTOR_AUTH_PASSWORD to enable motor-admin's basic authentication.  I've set the envar MOTOR_AUTH_USERNAME to be an email address.  In my application controller I have a before_action :set_current_user where the method is this:

  def set_current_user
    debug_me('== SET CURRENT USER ==')
    # TDV: temp until SAML inplace for motor_admin
    if ENV['MOTOR_AUTH_USERNAME'].include?('@')
      @current_user ||=
        User.find_by_email(
          ENV['MOTOR_AUTH_USERNAME']
        )
      debug_me('== CURRENT USER =='){[
        '@current_user'
      ]}
    else
      super
    end
  end

The debug_me methods inserts entries into a log file.
I am seeing nothing in the log files when running the application http://localhost:3000/motor_admin
I am also logging every hit to the Ability.new(user) and am seeing nothing in the logs for it as well.

I added a file app/models/motor/ability.rb to see what it was getting and yes for the motor_admin end point this new file was being called.  However, it was being called with a NIL value for the user parameter.

That is a good recommend but not what I'm trying to do.  Using the basic auth builtin to motor-admin for me is a stop gap measure on the way to full SAML 2FA work.  Getting all those processes setup for the first time is time consuming.  While I'm waiting for other people to get back to me on infrastructure setup, I'm creating the basic CanCan permissions and roles we want in the tetergration with motor-admin.
I did solve this issue by adding this file to my application:
# app/controllers/concerns/motor/current_user_method.rb

# frozen_string_literal: true

module Motor
  module CurrentUserMethod
    def current_user
      @current_user ||=
        if defined?(current_admin)
          current_admin
        elsif defined?(current_admin_user)
          current_admin_user
        elsif ENV['MOTOR_AUTH_USERNAME'].include?('@')
          User.find_by_email(ENV['MOTOR_AUTH_USERNAME'])
        elsif defined?(super)
          super
        end
    end
  end
end

This temp solution gets me to the point were there is a valid current_user object onto which I can hang roles and abilities for testing.


Running client.http

Hi, sorry for the newbie question, but which software do you use to run the requests specified in client.http file? I saw that there was a package for emacs, but I'm wondering if there is any mac/homebrew app that performs these tasks?
Thanks,
Marcos

Hi @marcalc, the client.http file is created for using it in emacs with the help of this plugin - https://github.com/pashky/restclient.el


Default strict mode on super admin project

Fixes #3353
Updated Super Admin project to now have strictMode:true by default.
Updated current tests accordingly.

Thanks @jogeshwar01 !


Input monochromatic wavelengths in nm for consistency

In the GOCART2G resource file, monochromatic wavelengths need to be provided in meters while other wavelengths are in nm:
# monochromatic wavelengths are in meters
aerosol_monochromatic_optics_wavelength: 4.7e-7 5.5e-7 6.7e-7 8.7e-7
wavelengths_for_profile_aop_in_nm: 470 550 870
wavelengths_for_vertically_integrated_aop_in_nm: 470 550 670 870

Using nm also for monochromatic wavelengths may improve consistency and prevent possible mistakes.

Assigned this issue to @adarmenov

Arlindo wanted the aerosol_monochromatic_optics_wavelength values in nanometers. This how they are written in my branch. We convert these wavelengths to meters when we call Aero_Compute_Diags.

@tclune I don't know why the wavelengths are in meters the first comment. The wavelength values are in nanometers in my branch (please see the link in my previous comment).
I don't think it is up to me to decide if these changes go in.

Agreed, for the sake of consistency and readability the units in this case should be 'nm'.

@gmao-esherman what is the use of the 'monochromatic' wavelengths label/resource?

The aerosol_monochromatic_optics_wavelength: are used by the aerosol components to create the diagnostic Mie tables, and used in the call to compute aerosol diagnostics.
These values used to be set in each aerosol's resource file (e.g. DU2G_GridComp_DU.rc). This implementation was a bit clumsy and makes it harder on the user. We now set this in GOCART2G_GridComp.rc and pass this information down to each child.

@amdasilva wanted the aerosol_monochromatic_optics_wavelength values in nanometers. This how they are written in my branch. We convert these wavelengths to meters when we call Aero_Compute_Diags.

Thanks, @gmao-esherman - I see the changes in your PR #23. I'll close this issue once your PR has been merged.

Ok - good; glad we are on the same page then.    I did not mean to imply at all that this was your decision - just that you were much more likely to recall the details of that discussion with Arlindo than myself.

This has been implemented. Internally, however wavelengths remain in SI units (meters).


(OraklNode) Remove unused function parameter GasMultiplier

Description
Remove gas multiplier function parameter
Type of change
Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist before requesting a review

[x] I have performed a self-review of my code.
[ ] If it is a core feature, I have added thorough tests.

Deployment

[ ] Should publish npm package
[x] Should publish Docker image

lgtm!
i wonder what was the role of the gas multiplier so far

I quickly added from early stage when the submission wasn't stable enough. so that submission can be tested with higher gas prices


Coin Daemon and Wallet RPC for Monero

Regarding binding monerod and monero-wallet-rpc:
$ monerod --data-dir <data-folder-path> --log-file /dev/null --non-interactive --rpc-bind-ip <IP_ADDRESS> --out-peers 32 --p2p-bind-ip <IP_ADDRESS> --p2p-bind-port 18080
$ monero-wallet-rpc --daemon-address <IP_ADDRESS>:18081 --wallet-file=<wallet-file-path> --rpc-bind-port 18082 --rpc-bind-ip <IP_ADDRESS> --rpc-login <username>:<password> --log-level 1
Can someone provide a way to do this on a Windows 10 system? I was able to map pool ports using Docker for Windows and they seem to be working right.
I am running a Monero Node in my Windows 10 system that I just finished syncing and it seems to be running fine. I think that the remaining obstacle that I need to cross is figuring out how to execute the above-mentioned code; can I use Docker? If so, what would be the command to do it? Can the commands be executed in Windows? If so, how?

I would not recommend using Windows for server purpose. It is not stable and secure as Linux.

The folks at Stackoverflow might beg to differ: https://meta.stackexchange.com/a/10370/260947


Add env var to disable performance warnings.

As title.

CC @shssf

Looks good!  We need to add the docs to: http://numba.pydata.org/numba-doc/latest/reference/envvars.html#debugging

@seibert thanks, docs in a623fc4

Looks good.  Ready to merge.


UI does not recognize accounts already linked

As a user, when logging in, I'm brought to a page that asks me to connect my github and openshift accounts. Once this is done, if I try to login again, I arrive again on this same page even though the linking as been recorded (as verified on the Federated Identities pages of the KC console).

If you log in without a linked account, you are brought to the getting started page. After you link the accounts, you are intentionally returned to the getting started page, but this time there is a success message. You are expected to click the "Get Started" button or one of the home/profile page links.
The workflow can be viewed here:
https://redhat.invisionapp.com/share/KQB6LEHM8#/screens/227580194
To test, first log out completely. Remove the linked accounts from keycloak. Revoke "Prod-preview Openshift.io" from the authorized applications on GitHub.

The way the page determines success is if it can obtain a GitHub and OpenShift token. You can check if they have been linked here (may need to log in, again):
https://sso.prod-preview.openshift.io/auth/realms/fabric8/account/identity

yes, I've see the GitHub and OpenShift accounts linked on the Keycloak admin console, but I was sent back to the getting started page without any success message to continue.

It appears that the Rxjs Observable.combineLatest is not obtaining both GitHub and OpenShift tokens reliably. We need to test both tokens in order to navigate to home page or show getting started page.
Fixed by:
https://github.com/fabric8io/fabric8-ui/pull/827

@dlabrecq I'm reopening the issue since I still have the same problem, where I get back to the registration page without any success message.

Not sure if this is related, but even after linking GH and OS accounts (and they show on the KC Console page under "Federated Identities"), when I click on "Update Profile" on the profile page on os.io, It tells me:
Please connect your GitHub and OpenShift accounts to OpenShit.io.
Clicking on the respective buttons (Connect GitHub account, Connect OpenShift account) doesn't do anything, and the "Update Profile" button stays grayed out, so it's impossible to save any profile changes (such as e-mail address or name).

The functionality on the edit profile page has not been implemented. The rest has been fixed.


Question: Does the ai-rag-chat-evaluator now support non-English QA pair generation using the new azure-ai-evaluation package?

This issue is for a: (mark with an x)
- [ ] bug report -> please search issues before submitting
- [x] feature request
- [x] documentation issue or request
- [ ] regression (a behavior that used to work and stopped in a new release)

Minimal steps to reproduce
I'm very interested in being able to generated QA pairs in non-English languages and I can see that the result of a previous question  (https://github.com/Azure-Samples/ai-rag-chat-evaluator/issues/35) related to this, led to the documentation being changed to state that only English QA pairs can be generated, due to limitations in the azure-ai-generative package.

It seems like azure-ai-generative package has been replaced by the new azure-ai-evaluation package which supports Spanish, Italian, French, Japanese, Portuguese, Simplified Chinese and German.

(https://github.com/Azure/azure-sdk-for-python/issues/34099#issuecomment-2536830420)
Expected/desired behavior

Does the current coding supports the new azure-ai-evaluation multi-language QA generator/simulator and we can update the documentation, or is a rewrite of the code needed to use the new azure-ai-evaluation-package?
Mention any other details that might be useful
Thank you for this great repo! :)

Thanks! We'll be in touch soon.

Hi @EMjetrot, you're using this repo alongside azure-search-openai-demo, correct?
If so, please see the branch I'm currently working on:
https://github.com/Azure-Samples/azure-search-openai-demo/compare/main...pamelafox:azure-search-openai-demo:evals?expand=1
That uses the Simulator approach for generating QA data in the form expected by this repo.
I am going to continue working on that branch to show the full evaluation workflow.
I think I will move ground truth generation out of this repo, as I've found it's so very specific to how a RAG has been set up, and this repo will continue to contain the CLI tools and custom evaluation metrics.


paulau: Inconsistent Title: meta-data text

Some page Title: meta-data entries now have "| Apache Software Foundation" appended, most do not.
There does not seem to be a pattern to this.
Also, rather than change the title (which will generally change the H1 anchor, meaning more work to fix that), it might be better to add an option to the template to add the suffix if the appropriate meta-data entry is present.
c.f. the notice: and license: entries which are used to add comments if present

You're right, all pages are not consistent as we didn't make content all pages on the site -- rather, only to the pages that would be affected by the navigation changes.
The goal is to move to all Titles having the "| Apache Software Foundation".
The page Title is written in a search-friendly way, while the H1 anchor is what appears on the page itself and written in a user-readable way (hence the difference).
@Paul-TT and I are looking at an easy way to apply this in a template based on your suggestion. Thanks!


chore: release main

:robot: I have created a release beep boop
identify: 2.0.0
2.0.0 (2024-05-01)
⚠ BREAKING CHANGES

to support identify-push, the identifyPush module must be added as a libp2p service, similar to identify

Features

split identify and identify-push (#2387) (9d13a2f)

multidim-interop: 2.0.31
2.0.31 (2024-05-01)
Dependencies

The following workspace dependencies were updated

dependencies

@libp2p/identify bumped from ^1.0.21 to ^2.0.0
@libp2p/webrtc bumped from ^4.0.30 to ^4.0.31
@libp2p/webtransport bumped from ^4.0.29 to ^4.0.30
libp2p bumped from ^1.5.0 to ^1.5.1

webrtc: 4.0.31
4.0.31 (2024-05-01)
Dependencies

The following workspace dependencies were updated

devDependencies

libp2p bumped from ^1.5.0 to ^1.5.1

webtransport: 4.0.30
4.0.30 (2024-05-01)
Dependencies

The following workspace dependencies were updated

devDependencies

libp2p bumped from ^1.5.0 to ^1.5.1

libp2p: 1.5.1
1.5.1 (2024-05-01)
Dependencies

The following workspace dependencies were updated

devDependencies

@libp2p/identify bumped from ^1.0.21 to ^2.0.0

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/libp2p/js-libp2p/releases/tag/multidim-interop-v2.0.31 :sunflower:

:robot: Release is at https://github.com/libp2p/js-libp2p/releases/tag/libp2p-v1.5.1 :sunflower:

:robot: Release is at https://github.com/libp2p/js-libp2p/releases/tag/identify-v2.0.0 :sunflower:

:robot: Release is at https://github.com/libp2p/js-libp2p/releases/tag/webrtc-v4.0.31 :sunflower:


Slow compilation with via-ir

Currently trying to integrate Uniswap's universal router. https://github.com/Uniswap/universal-router
Working with this code requires via-ir. Unfortunately I am experiencing extremely slow compile times:
reproduce:
git clone git@github.com:Uniswap/universal-router.git
cd universal-router
forge install
forge build
...
[⠰] Compiling 83 files with 0.8.17
[⠑] Solc 0.8.17 finished in **78.06s** <-- makes me sad

Compiling with hardhat:
pnpm compile --force  19.11s user 0.45s system 105% cpu 18.468 total
Versions:
forge 0.2.0 (28b2ae6 2023-03-06T00:04:30.253422Z)
solc 0.8.17
I assume this might be related to https://github.com/foundry-rs/forge-std/issues/225

This reproduction case doesn't demonstrate that forge-std is the issue here. It seems to me that forge build is a lot slower because it's compiling many solidity source AND solidity test files with via-ir (which you can workaround using the apporach @PaulRBerg mentioned), whereas hardhat is only compiling source files.
Looking at the recent successful CI runs in this repo, the via-ir builds of forge-std still only take 5 seconds (at the time of #225 it was 30-90 seconds)


The detection accuracy of the R-50-FPN Mask R-CNN is lower than reference

Hi @fmassa , thanks for all the super helpful code.
I am trying to use the detection script in: https://github.com/pytorch/vision/tree/master/references/detection to train R-50-FPN Mask R-CNN.
When I re-train the detection AP is only 35.5, which should be 36.8 according to the reference model zoo.
I am using:
python 3.6.8
torch version 1.2.0
torchvision version 0.4.0
CUDA version 10.0.130
I have only 6 GPU and I am allocating one image per GPU. I have changed the learning rate and warm up iteration as suggested in Detectron: lr = 0.0075 and warmup iterations = 1333.
I am starting from Imagenet pretrained (pretrain_backbone=True)
I am using the following :
!CUDA_VISIBLE_DEVICES=0,1,2,3,4,5 python3 -m torch.distributed.launch --nproc_per_node=6 --use_env train.py --lr=0.0075 --batch-size=6 --epochs 26 --lr-steps 16 22 --aspect-ratio-group-factor 3
Namespace(aspect_ratio_group_factor=3,
batch_size=6,
dataset='coco',
device='cuda',
dist_backend='nccl',
distributed=True,
epochs=26,
gpu=0,
lr=0.0075,
lr_gamma=0.1,
lr_step_size=8,
lr_steps=[16, 22],
model='maskrcnn_resnet50_fpn',
momentum=0.9)
I am a bit confused on what should I do to replicate the numbers.
Can you help me?
Thanks ! ^^

This is weird.
I've reproduced the results using the commands from https://github.com/pytorch/vision/issues/1140#issuecomment-513386987
python -m torch.distributed.launch --nproc_per_node=8 --use_env train.py --dataset coco --model maskrcnn_resnet50_fpn --epochs 26 --lr-steps 16 22 --aspect-ratio-group-factor 3

and took the best model (which was at epoch 22)
I also noted that you changed the global batch size, as you are using 6 imgs per GPU for 6 GPUs (total batch size of 36), while we trained our models on 2 imgs per GPU on 8 GPUs, which is a batch size of 16, so it looks like the lr scaling rules that you applied are not exactly the same.
Can you maybe try using 4 imgs / gpu and 4 GPUs, with the other parameters kept the same?

Thx for the help! It was indeed a problem regarding the number of GPU and the batch size ^^'.  Training with 4 GPU and 4 images per GPU worked.

Cool, glad it worked


Transpose pivot table option

Providing a button or right click menu option to transpose the selected fields from index to column and vice-versa. This is helpful for cases where you like to look at data with dates on the index and labels on the column, but when plotting in a plotly line chart the dates need to be on the index to render correctly.

Thanks for the feedback! I've considered this but have always decided against it in the interest of keeping things clean... I've even regretted the sorting arrows I had to put in recently as they don't render reliably the same way on all browsers.
I could be convinced otherwise if you were able to suggest a layout where such a button would be unobtrusive and unambiguous about its functionality, though :)
I must say that the extra few drag/drop operations to accomplish this in the absence of a button have never felt totally outrageous, so it doesn't feel like a major shortcoming to not have it.

I would say that in the absence of a transpose button one option would be to provide an extra display type drop down for “columnwise” and “rowwise” line chart similar to how you have a bar chart option for both orientations.

I'm confused about what kind of chart you need... can you post a screenshot?
Also, I'm not sure what you mean when you say "cases where you like to look at data with dates on the index and labels on the column, but when plotting in a plotly line chart the dates need to be on the index to render correctly" ... this sounds like a bug that could/should be fixed, either here or in plotly.js :)

Fixed my original comment. I will provide a concrete example later today.

Ok! I believe that dates will render fine on either axis in a Plotly chart actually. If that’s not the case please do let me know!

Ok so here's an illustration of my point. In figure 1 you can see the table view where the dates are oriented along the vertical axis and the labels are oriented along the horizontal axis. This is the way I've seen most people visualize time series data in a table. However when you choose the line chart option, the default behavior is to create an individual plot series per row with the x axis being composed of the column headers, clearly not very useful.
In figure 2, you see the transposed table configuration that lends itself to a useful line plot (but a much less popular format for viewing the data in a table). So what I would propose is that the "line chart" option be renamed to "rowwise line chart" (or something similar) and a new option be added called "columnwise line chart". This one will produce a series per column and the x axis will be composed of the labels on the vertical axis. I realize that this tool is not meant to be a time series viewing tool, but it lends itself well to that, and the fact that there is already options for vertical/horizontal oriented heatmaps and bar charts makes it a very logical and (I'm guessing) easy addition.
Figure1: https://imgur.com/a/m1iafNJ
Figure2: https://imgur.com/a/KtNEtF0

I see what you mean, thanks for clarifying!
I would say that I'm not sure I agree with you that it's much more common to look at tables of dates in this orientation... Certainly I don't and most of my financially-oriented colleagues don't, but I see the reasoning for it.
To me, this doesn't seem like a sufficiently strong reason to add a transposition button, or a new rendererer which would break the pattern of "y as rows, x as columns" which provides a nice intuitive mapping for charts. This 'row-wise' chart would be deeply counterintuitive to use except in the specific case of switching to it from such a table.
That said, if you want to use such a renderer in your application, it should be quite easy for you to do: just fork and modify the Plotly renderers :)

Makes sense. Thanks for hearing me out.


RKE1 v1.22 errors for metrics.k8s.io/v1beta1

Create Rancher local cluster 1.22 and Provision a RKE1 Downstream cluster (any provider).
Check cattle-cluster-agent logs in cattle-system namespace:
E1117 05:51:59.756072 53 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1117 05:51:59.763116 53 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request

rancher/rancher#34054

This seems to be related/causing an issue for monitoring v1 on 2.6-head (de55fe0).  I see this error in both /g and iframe windows once 0.3.1 is installed. The gears for monitoring do not show metrics.
Local cluster is 1.22.3+k3s1, downstream (where monitoring is installed) is 1.20.12
Failed to obtain metrics. The metrics service may not be available.
undefined

found while testing https://github.com/rancher/dashboard/issues/4573

Steps I used to for testing:

Install Rancher v2.6-head image (46eb9d41), local cluster k8s version v1.22.3+k3s1
Provision downstream DO HA Cluster, k8s version v1.21.6
Install metrics v1 via Cluster Tools in newly provisioned cluster
Check cluster agent logs in provisioned cluster
Check metrics view from ember

I'm still seeing the problem logs from the cluster-agent:
> kubectl logs cattle-cluster-agent-5fbdc5f88c-dgr7c -n cattle-system | grep metrics
E1202 21:06:46.844262      57 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:46.857018      57 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:56.839446      57 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:56.894999      57 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:56.905675      57 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:56.948662      57 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:57.724979      57 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:57.729407      57 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
> kubectl logs cattle-cluster-agent-5fbdc5f88c-ltglg -n cattle-system | grep metrics
E1202 21:06:47.257455      58 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:47.261093      58 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:55.456629      58 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:55.477931      58 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:55.485630      58 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:55.513785      58 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:56.855869      58 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:56.878890      58 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
E1202 21:06:57.573064      58 gvks.go:69] failed to sync schemas: unable to retrieve the complete list of server APIs: metrics.k8s.io/v1beta1: the server is currently unable to handle the request

Additionally, I'm not seeing any metrics in the ember cluster view
I'm going to try this again to make sure I didn't do anything wrong

On 2.6.3-rc4
See these errors
E1206 22:38:02.878609 32 memcache.go:196] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request
Mon, Dec 6 2021 2:38:03 pm | E1206 22:38:03.074464 32 memcache.go:101] couldn't get resource list for metrics.k8s.io/v1beta1: the server is currently unable to handle the request

Downstream clusters have - Longhorn v1/v2, monitoring v2, CIS v1/v2 enabled on different clusters

I'm seeing issues after an upgrade from 2.6.2 -> 2.6.3-rc4 (local cluster 1.21.6, downstream 1.20.12) mirroring this comment's errors: https://github.com/rancher/rancher/issues/35559#issuecomment-974448232

What happens now that we can' tlist? What is actually broken?

The actual issue isn't the list errors in cluster agent, but what @slickwarren mentioned, old queries fail with the same error:
https://github.com/rancher/rancher/issues/35559#issuecomment-974448232
Local 1.22, downstream any supported version.

Not moving yet, as this has been identified by @slickwarren as at least partially reproducible in 1.21.

the bug is reproduced on the downstream cluster running v1.20.13  and the local cluster runs v1.21.7

This is a regression not seen in <2.6.2, monitoring v1 is broken at any level in the Rancher UI. Grafana can be used as a workaround.

On 2.6-head commit id: 39cecf0

Local cluster on 1.20 and downstream on 1.20 (monitoring v1 enabled on both)
Rancher logs or cluster agent logs do not show the errors.


error with import....

does anyone know what the issue is with this error;
error styles.scss (Line 17 of _shared.scss: Properties are only allowed within rules, directives, mixin includes, or other properties.)
I'm using the flexbox mixins from https://gist.github.com/ericam/4462761 but cant get them working....
any ideas?

Closing this issue. Download the latest version of Scout-App. If the problem still exists create a new issue.

Scout-App.io


add 'oraclejdk10' to Travis build matrix

Motivation:
Travis build matrix now includes 'oraclejdk10'
Modification:
tweaked Travis build file
Result:
Travis build matrix now includes 'oraclejdk10'

@sullis actually we maybe should remove the file as we not use travis for netty anymore ?

Closing.


Update Mesh Product and unit test

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Getting "Checks" error for transmission but it appears to connect

I'm getting this error:
TransmissionError('Request failed.', error) TransmissionError: Request failed. Original exception: HTTPHandlerError, "HTTPHandlerError 401: Unauthorized"
in the checks page but it appears to be listing the torrents properly.
I have my transmission server on a different server and I made sure to set the IP, ports, and credentials properly in the config and database but I'm getting that error.  I also made sure to whitelist the WM2 IP in the transmission config and I have a reverse proxy in Apache that connects to it fine.  This may be because I updated transmission to 2.94 but I can't say that with certainty.
I believe this issue might be partially because in the past I just deleted torrents from the instance using remote or the web gui when they became unregistered but I do not know if that is the issue.  One thing that I also think might be good is if there was a button to delete torrents from the database if they were no longer in transmission.  I was having issues with this in the past and getting the database entries to delete properly was kind of a pain because it involved getting rid of several related entries.
My setup is a bit weird, as I have a transmission instance on one server with a NFS share to the webserver where they both have the same paths to the files.  For example, on the transmissions server the files may be in /mnt/share/wmfiles/groupid/... and they are also in /mnt/share/wmfiles/groupid/... on the webserver because of how I have the NFS share mounts.
I haven't been using WM2 lately and I periodically check it to make sure it's running well and this check issue seems to be a new issue that has arisen after I updated transmission to 2.94 without changing any other variable.

Make sure that the default "transmission-daemon" service was not re-enabled during the update and is not currently running. Sometimes when the default one is enabled, it overrides the "transmission-daemon-redacted01" service and conflicts with the web port.

I built transmission from source so I know that is not an issue.  I have my transmission instance for WM called "transmission-daemon-wm" and the config was preserved when I built it.

Are you able to login to the transmission webui(s) via the expected credentials, port, and address?

Are you able to login to the transmission webui(s) via the expected credentials, port, and address?

Yup, I can log in directly when logged into my VPN and I can log in by proxy through a reverse proxy using Apache where my apache server IP is whitelisted on the transmission server.

To clarify, I can log in directly from my VPN on the server where the IP is <IP_ADDRESS>:9092/transmission/web/
I can also log in from my public webserver where the webserver is at <IP_ADDRESS>, and I log in from my.domain.tld/tw/web/ and it has the same prompt
WM2 is running at what.mydomain.tld but it's also running on <IP_ADDRESS> so it is whitelisted the same way the apache reverse proxy is.  If I can connect through the reverse proxy and it's whitelisted correctly, WM2 should also be able to connect too.  I also just whitelisted what.mydomain.tld in the RPC to be sure it's not sending what.mydomain.tld in the headers somewhere but that didn't make a difference in the checks.
Again, it appears to list the torrents correctly but it's just throwing that error in checks.

Can you use curl from a shell on the WM instance to try and access the transmission page to verify access from that box to the other?


Explore easier sharing mechanisms

An issue to discuss potential replacements to DartPad's current gist loading mechanism.
It would be nice if whatever used here could also be used by "Open in DartPad" in lightweight DartPads.
A few ways:
Upload snippet to some database or blob storage

Easy and flexible, but has potential concerns due to storing user-generated content (although anonymous)
Can automatically delete after not being accessed for X-days (entries can be exempted)
Easier to share than using a query parameter
The Go Playground uses datastore
Should be limited in size :)

Query parameter:

Has size limitations?
Hard to actually share. Potentially too large for sharing in some chat areas and social media platforms
No need to store anything on server

Extra:

Besides using query parameters, the Rust playground seems to also support uploading to a shared GitHub gist account?

As a note, the Flutter API docs could then migrate to use the shared mechanism rather than the custom solution we have for them now.

Sezar

Hi folks.
I'm new to DartPad and I was really surprised that I basically cannot share my code.
Sure, I read the Sharing Guide but it doesn't seem to be usable - making gists, copy long numbers, omg...
Can I share my code anyway like via a query parameter?

Hard to actually share. Potentially too large for sharing in some chat areas and social media platforms

Of course. Yet, we can always use some trusted URL shorteners: let the size limit be their database problems :)

@parlough Would you happen to know why the automatic Gist creation feature is no longer present? I thought it was pretty neat, being able to sign in with GitHub and pressing a button to save and share your code.


A suggestion

How about adding a "gnu-gcc" compiler for c++ ? The "clang" compiler doesn't include "bits/stdc++.h"

Fixed in https://github.com/thebaselab/codeapp/commit/a048b6a0eacc36f58732a931f5d6cf8aa3e06978.


docs(behavior_velocity_planner): add map format doc

Signed-off-by: Takayuki Murooka<EMAIL_ADDRESS>Description
add document about map format of virtual traffic light

Pre-review checklist for the PR author
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[ ] The PR follows the pull request guidelines.

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@TakaHoribe Is this PR ok to merge, or do we change how to deal with the VTL issue?

@TakaHoribe kindly ping.


get no reaction

Hello i have send a post activitity command. but nothing happend. What ist wrong? Thanks

Sorry i have found my problem: http://x.x.x.x.:8282/hubs/harmony-hub/activities
{"activities":[{"id":"24806441","slug":"fernsehen","label":"Fernsehen","isAVActivity":true},.....
i nedd the value of the slug label not the value of "label". e.g. http://x.x.x.x.:8282/hubs/harmony-hub/activities/fernseher


Update link to pymcmcstat homepage

Pull Request Test Coverage Report for Build 258

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 97.866%

Totals

Change from base Build 256:
0.0%

Covered Lines:
2201

Relevant Lines:
2249

💛  - Coveralls


HDR Sample treating Min/MaxMasteringLuminance as the same range?

Hello!
I was looking at the HDR sample here: https://github.com/microsoft/DirectX-Graphics-Samples/blob/master/Samples/Desktop/D3D12HDR/src/D3D12HDR.cpp#L994
And it seems to treat MaxMasteringLuminance and MinMasteringLuminance as the same range/scale.
Whereas the docs say:
MaxMasteringLuminance

The maximum number of nits of the display used to master the content. Values are in whole nits.

MinMasteringLuminance

The minimum number of nits of the display used to master the content. Values are 1/10000th of a nit (0.0001 nit).

Is the sample wrong, are the docs wrong, or am I just misunderstanding?
Thanks for your time!

This structure represents the definition of HDR10 metadata used with HEVC, not HDR10 metadata for ST.2086. These are closely related but defined differently.
HEVC spec states:
max_display_mastering_luminance and min_display_mastering_luminance specify the nominal maximum and
minimum display luminance, respectively, of the mastering display in units of 0.0001 candelas per square metre.
min_display_mastering_luminance shall be less than max_display_mastering_luminance.

Which seems to indicate the docs may be wrong here?

Thank you for the report! We'll take a look at this and get back to you.

You can submit a PR for the sample to resolve this.