Update dependency docker.io/rancher/k3s to v1.24.4

This PR contains the following updates:

Package
Update
Change

docker.io/rancher/k3s
minor
v1.24.3-k3s1 -> v1.25.2-k3s1

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'ts-angular-jsonapi' is not in the npm registry.

hi
i can not install the module using npm install ts-angular-jsonapi --save,
any idea?
thanks

wait please....

Please, try again and enjoy! :P
npm install ts-angular-jsonapi --save

ok done! it appears in my node_modules...
thanks for your fast reply:-)


Duplicate cluster name in different namespaces prevents cluster from being setup correctly

When creating multiple clusters in different namespaces with the same name only one cluster is added to the orchestrator and one cluster remains in read-only mode.
Example:
---
apiVersion: v1
kind: Secret
metadata:
  name: mysql-somename-auth
  namespace: test-1
type: Opaque
stringData:
  ROOT_PASSWORD: Test1

---
apiVersion: mysql.presslabs.org/v1alpha1
kind: MysqlCluster
metadata:
  name: somename
  namespace: test-1
spec:
  image: percona:8.0
  mysqlVersion: "8.0"
  replicas: 1
  secretName: mysql-somename-auth

---
apiVersion: v1
kind: Secret
metadata:
  name: mysql-somename-auth
  namespace: test-2
type: Opaque
stringData:
  ROOT_PASSWORD: Test2

---
apiVersion: mysql.presslabs.org/v1alpha1
kind: MysqlCluster
metadata:
  name: somename
  namespace: test-2
spec:
  image: percona:8.0
  mysqlVersion: "8.0"
  replicas: 1
  secretName: mysql-somename-auth

Hi, was deploying multiple namespaces successful?

When creating multiple clusters in different namespaces with the same name only one cluster is added to the orchestrator and one cluster remains in read-only mode.
Example:
---
apiVersion: v1
kind: Secret
metadata:
  name: mysql-somename-auth
  namespace: test-1
type: Opaque
stringData:
  ROOT_PASSWORD: Test1

---
apiVersion: mysql.presslabs.org/v1alpha1
kind: MysqlCluster
metadata:
  name: somename
  namespace: test-1
spec:
  image: percona:8.0
  mysqlVersion: "8.0"
  replicas: 1
  secretName: mysql-somename-auth

---
apiVersion: v1
kind: Secret
metadata:
  name: mysql-somename-auth
  namespace: test-2
type: Opaque
stringData:
  ROOT_PASSWORD: Test2

---
apiVersion: mysql.presslabs.org/v1alpha1
kind: MysqlCluster
metadata:
  name: somename
  namespace: test-2
spec:
  image: percona:8.0
  mysqlVersion: "8.0"
  replicas: 1
  secretName: mysql-somename-auth

Hi, was deploying multiple namespaces successful?


Change desktop entry

Changed Exec to /usr/bin and Name[de_DE].

In the flatpak package the executable is not under the /usr/bin. So it may not work anymore

I don't know much about how flatpak packaging works. The PKGBUILD in my PR #16 symlinks the executable to /usr/bin/gittyup so the desktop entry also needs to point there.
As far as I know, launching an application via flatpak needs a different command anyway so the Exec value needs to be different. There could be 2 different files for this, which could be useful if you start putting pre-built binaries in releases for non-flatpak installs. Alternatively I could make the PKGBUILD apply a patch in prepare that changes the necessary exec but this will limit it to the arch package.
The name change does not cause any issues I think.

I find it cleaner to have it mainlined so lets find a way to fix this

I built the flatpak from this branch and it worked correctly. The Exec line in the desktop entry for the flatpak version is /usr/bin/flatpak run ... so I think flatpak either generates its own desktop entry or it modifies the existing one. Either way I think it's safe to merge this and keep only one entry.

I will try out and then I will merge

@Grafcube For me it does not work. I checked the compiled flatpak manifest and there was nothing changed. If I remember me correctly there is a command for the flatpak manifest to update the manifest. I will check it out

This is probably related to #111
We'll need a separate desktop file for Flatpak and for global installation.
Maybe use CMake's configure_file to generate both files from a template?

@Grafcube @alerque is this still needed?

Probably not. I switched to the flatpak long ago but I originally made this PR to simplify making the PKGBUILD a little. But someone else ended up making the PKGBUILD so I dropped it. I don't really have anything to do with this PR anymore so it would probably only be of interest to packagers (since it looks like flatpak doesn't even use this file). I think it's safe to merge once I resolve the conflicts. After that it's up to the package maintainers to use it.

Not needed anymore after #397 is merged


Will LSTMBlockFusedCell be supported in tensorflow 2.0?

I noticed that keras in tensorflow 2.0 unifies backend between CPU and GPU with CuDNN, but it's a little slow on CPU. Will you add LSTMBlockFusedCell or LSTMBlockCell to tf 2.0, since they have better performance?

Thanks for checking. I think LSTMBlockFusedCell or LSTMBlockCell won't be in the core API for 2.0. Having said that, I could update the cpu kernel to be a more performant version like LSTMBlockCell. The only down side I can see is that user will loss the python level debugability since it will be one fused op.
I will discuss the trade off within teams and post it here.

Adding @protoget who previously worked on cudnn kernels.

Many of the good functions from tf.contrib are eliminated, such as CRF conditional random field etc how can one use these packages ( by using source code from these packages)? @qlzh727
any suggestions pls

@qlzh727 Any updates on this?

How can we find the author(s) and see if they are willing to support these two in Addons?

Sorry for the very late reply. There has been some work to add the fused c kernel to TF, and they haven't be expose to python side yet. I have some other issue to work with at the moment, will take a closer look within this month.

Thanks @qlzh727 we appreciate your work.
I would be fine if LSTMBlockFusedCell and TimeReversedFusedRNN move to addons or even willing to do the work and add them myself if I can find a simple instruction as to how to move something from contrib to addons.

@qlzh727 Thank you for your reply!

@qlzh727 Since we can benefit from the python level debugability when using keras.LSTMCell and keras.RNN, I think improve the performance of LSTM/GRU with a single fused op is possible.
In PyTorch, CuDNN is used for LSTM on GPU, and it will fall back to a fused lstm kernel when using CPU. So is it possible to integrate the LSTMBlockFusedCell into keras.LSTM when CPU is available.
(https://github.com/tensorflow/tensorflow/blob/r2.0/tensorflow/python/keras/layers/recurrent_v2.py#L910) vs (https://pytorch.org/docs/stable/_modules/torch/nn/modules/rnn.html#LSTM)

I believe the underlying LSTMBlockFusedCell op is already available in TF 2.0 as https://www.tensorflow.org/api_docs/python/tf/raw_ops/BlockLSTM. See https://github.com/tensorflow/tensorflow/blob/r1.15/tensorflow/contrib/rnn/python/ops/lstm_ops.py#L654 for more information on how it is used. The only difference I see is the default cell_clip value is now 3.0. Also, there is a BlockLSTMV2, which is different somehow (https://www.tensorflow.org/api_docs/python/tf/raw_ops/BlockLSTMV2).

@npuichigo,
Can you please respond to the above comment? Thanks!

@rmothukuru Sorry for the late reply. I checked the recent status and it seems LSTMBlockFusedCell is only exposed in raw_ops. LSTMCell in keras still doesn't use a fused kernel, but I don't know whether the performance of LSTMCell with tf.function is on par with a fused kernel.

Hi @npuichigo!
We are checking to see whether you still need help in this issue .Have you checked this  document on LSTMCell from TF 2.7 yet?

have switched to pytorch for a long time. no need for help currently

Hi @npuichigo! We are checking to see whether you still need help in this issue .Have you checked this document on LSTMCell from TF 2.7 yet?

I hope I am not missing anything obvious, but doesn't the recommendation in that link (i.e. Please use ... tf.contrib.rnn.LSTMBlockFusedCell for better performance on CPU) require you to not be using tensorflow 2.0+? Why is this the recommendation on the (currently 2.8) version of the documentation when it isn't supported?

@coleary-hyperscience I always want a LSTM implementation which is a fused kernel on CPU and can seamlessly switch to CuDNN on GPU. The recommendations here don't meet my needs, but PyTorch LSTM does.
As for the document, I think it's out of date since there's no more tf.contrib anymore. It was the original motive of this issue, to find an alternative in tensorflow 2.0

Ok @npuichigo ! Reopening as it still seems to be a valid feature request . Thank you!

@npuichigo Discussed it with the team and this cannot be done as this is a niche case. Thanks!


Update metadata, favicon, chat, & apply analytics

Once we get the gridsome setup, there are three more items:

Currently the metadata talks about pingendo, which obviously will be changed when we go to Gridsome, but let's make the metadata: ThreeFold Support | Reach us for support via live chat!
Let's update the favicon to the ThreeFold logo
Add live chat
Let's apply Matomo Analytics

Live chat added
Tab updated with ThreeFold (favicon)

Please link Chat Now button to live chat on the bottom right corner:

Please link Chat Now button to live chat on the bottom right corner:

Fixed

Have we applied Matomo and updated meta data?

Have we applied Matomo and updated meta data?

Done


ARROW-7397: [C++][JSON]Fix white space length detection error

Commit 21ca13a5cd [1] introduces a bug in ConsumeWhitespace() function.
When all chars in a string are white spaces, it should return string
length. But current code returns 0. It's not noticed because x86 goes
rapidjson simd code path which is okay. Arm64 now goes the buggy code
path and triggers json unit test failure.
[1] https://github.com/apache/arrow/commit/21ca13a5cd9c1478d64370732fcfae72d52350dd#diff-664e724274fbe0ff1e03745aa452b4d6R48
Signed-off-by: Yibo Cai<EMAIL_ADDRESS>

Thanks for the pull request.
Could you show the output of failed test?
I couldn't reproduce this with this change:
diff --git a/cpp/src/arrow/json/chunker.cc b/cpp/src/arrow/json/chunker.cc
index ffda3ece5..3d9a75ae4 100644
--- a/cpp/src/arrow/json/chunker.cc
+++ b/cpp/src/arrow/json/chunker.cc
@@ -39,18 +39,18 @@ using internal::make_unique;
 using util::string_view;

 static size_t ConsumeWhitespace(string_view view) {
-#if defined(ARROW_RAPIDJSON_SKIP_WHITESPACE_SIMD)
-  auto data = view.data();
-  auto nonws_begin = rj::SkipWhitespace_SIMD(data, data + view.size());
-  return nonws_begin - data;
-#else
+// #if defined(ARROW_RAPIDJSON_SKIP_WHITESPACE_SIMD)
+//   auto data = view.data();
+//   auto nonws_begin = rj::SkipWhitespace_SIMD(data, data + view.size());
+//   return nonws_begin - data;
+// #else
   auto ws_count = view.find_first_not_of(" \t\r\n");
   if (ws_count == string_view::npos) {
     return 0;
   } else {
     return ws_count;
   }
-#endif
+// #endif
 }

 /// RapidJson custom stream for reading JSON stored in multiple buffers

I'm running "arrow-json-test" directly on one arm64 server.
Logs as below. I've removed ok tests for brevity.
[==========] Running 52 tests from 9 test cases.
omitted ok tests
[----------] 5 tests from ChunkerTest/BaseChunkerTest
omitted ok tests
[ RUN      ] ChunkerTest/BaseChunkerTest.StraddlingEmpty/0
/home/linux/arrow/cpp/src/arrow/json/chunker_test.cc:273: Failure
Expected equality of these values:
completion->size()
Which is: 27
0
[  FAILED  ] ChunkerTest/BaseChunkerTest.StraddlingEmpty/0, where GetParam() = true (0 ms)
[==========] 52 tests from 9 test cases ran. (202 ms total)
[  PASSED  ] 51 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] ChunkerTest/BaseChunkerTest.StraddlingEmpty/0, where GetParam() = true
1 FAILED TEST

@kou, I tried your changes on x86 host, this bug can be reproduced. Just run unit test "arrow-json-test".


IoPay Login not working when it's on a Ledger account

Reproduce

Unlock IoPay with a Ledger
Go to https://member.iotex.io/profile/
Click on "Login or Sign Up with IoPay" button

=> in the "Sign Message" IoPay popup clicking "Yes, Make action" does nothing

fixed on iopay side. but requires a new ledger iotex app to support.

The latest IoTeX app for Ledger v0.1.7 now allows signing messages, so this is fixed now.


fix Cargo / Build and test (windows-latest)

use signal_hook::iterator::Signals;
|                  ^^^^^^^^ could not find iterator in signal_hook

FIxed in https://github.com/webrtc-rs/turn/commit/06585bb1952c615a3ce5835b6d4c403d6e89f099

test_new_long_term_auth_handler still failed due to
`
failures:
---- auth::auth_test::test_new_long_term_auth_handler stdout ----
Error: Error { message: "The requested address is not valid in its context. (os error 10049)" }
thread 'auth::auth_test::test_new_long_term_auth_handler' panicked at 'assertion failed: (left == right)
left: 1,
right: 0: the test returned a termination value with a non-zero status code (1) which indicates a failure', /rustc/cb75ad5db02783e8b0222fee363c5f63f7e2cf5b\library\test\src\lib.rs:192:5
note: run with RUST_BACKTRACE=1 environment variable to display a backtrace
failures:
auth::auth_test::test_new_long_term_auth_handler
test result: FAILED. 60 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out; finished in 1.53s
error: test failed, to rerun pass '--lib'
Error: Process completed with exit code 1.`

temporally disable unit test test_new_long_term_auth_handler for windows platform


Avoid use of ES6 class getter to fix IE8

This should be the same as this: https://github.com/rackt/react-router/pull/1143/files

I didn't actually RUN the build... I'm assuming that's apart of the npm process? I actually ran the build and a bunch of other files changes (syntactically) which leads me to believe that the files in the build folder aren't necessary as long as the source files are built when this is pushed to npm.


stop displaying a long error when reverting to browser version

There is no point on displaying a very long error message, this is not an error, it's a normal fallback

Thanks I agree with this change, will add to the next 1.1.2 release with a couple other patches that need to be done.


Lag when scrolling editor panel as of 3.16.0

Description
See
https://reddit.com/r/homebrewery/comments/1g3pxfb/lagging_code_panel_after_3160/
and
https://www.reddit.com/r/homebrewery/comments/1g3p1ku/input_lag_after_the_recent_update/

https://github.com/user-attachments/assets/fe6de5c7-33f0-425f-855d-24bc8145ce13
There are a number of issues here, all probably caused by excessive rerenders

I don't know if this is related, but i encounter a lot of slowness since the last update when scrolling code/view, even without syncing. I can link the brew

@lucastucious want you try this link with the latest update, pre-release, and see if it works better for you? https://homebrewery-pr-3829.herokuapp.com/
Copy and paste your brew in there. But note this is a temporary deployment so don’t expect any actual work to be saved, just for testing changes

It's extremely smooth. Same navigator, same computer, just a tab next to the official one. It's day & night.

Nice, that means the fix that we are trying are working.


Add nested loop test for instruction grouper

Tested if the instruction grouper can deal with (nested) loops (suprisingly, it was already capable of doing this :tada:). This PR adds a test for it to make sure it keeps working :)

I believe this PR still has some old commits from the other branch @casperboone?

@gandreadis Ah you're right, fixed :)


Torchvision decode_jpeg memory leak

🐛 Describe the bug
nvJPEG leaks memory and fails with OOM after ~1-2k images.
import torch
from torchvision.io import read_file, decode_jpeg

for i in range(1000): # increase to your liking till gpu OOMs (:
    img_u8 = read_file('lena.jpg')
    img_nv = decode_jpeg(img_u8, device='cuda')

Probably related to first response to https://github.com/pytorch/vision/issues/3848
RuntimeError: nvjpegDecode failed: 5

is exactly the message you get after OOM.
Versions
PyTorch version: 1.9.0+cu111
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A
OS: Arch Linux (x86_64)
GCC version: (GCC) 11.1.0
Clang version: 12.0.1
CMake version: version 3.21.1
Libc version: glibc-2.33
Python version: 3.8.7 (default, Jan 19 2021, 18:48:37)  [GCC 10.2.0] (64-bit runtime)
Python platform: Linux-5.13.8-arch1-1-x86_64-with-glibc2.2.5
Is CUDA available: True
CUDA runtime version: 11.4.48
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 2080 Ti
GPU 1: NVIDIA GeForce RTX 2080 Ti
GPU 2: NVIDIA GeForce GTX 1080
Nvidia driver version: 470.57.02
cuDNN version: Probably one of the following:
/usr/lib/libcudnn.so.8.2.2
/usr/lib/libcudnn_adv_infer.so.8.2.2
/usr/lib/libcudnn_adv_train.so.8.2.2
/usr/lib/libcudnn_cnn_infer.so.8.2.2
/usr/lib/libcudnn_cnn_train.so.8.2.2
/usr/lib/libcudnn_ops_infer.so.8.2.2
/usr/lib/libcudnn_ops_train.so.8.2.2
HIP runtime version: N/A
MIOpen runtime version: N/A
Versions of relevant libraries:
[pip3] adabelief-pytorch==0.2.0
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.19.5
[pip3] pytorch-lightning==1.4.5
[pip3] torch==1.9.0+cu111
[pip3] torchaudio==0.9.0
[pip3] torchfile==0.1.0
[pip3] torchmetrics==0.4.1
[pip3] torchvision==0.10.0+cu111
[conda] Could not collect

Is general torchvision.io.read_image affected? In general, is torchvision.io.read_image ready for being used in dataset classes instead of PIL / OpenCV for reading images from disk?

@NicolasHug @fmassa Also having this issue. Tried loading images on loop using decode_jpeg directly to GPU. Was able to run a number of images but GPU memory keeps going until it runs out and fails. Memory is fine on CPU. Was wondering if there is a timeline for when this will be fixed. Hoping it will be fixed ASAP as loading directly to GPU is crucial to getting speeds fast enough to run in real time.

same problem:
ubuntu 20.04
Driver Version: 470.82.00
CUDA Version: 11.4
torch version '1.10.2+cu113'
torchvision version '0.11.3+cu113'

Thanks all for the reports.
I took a look a this today. I can reproduce the leak. I do see the memory usage going up constantly with nvidia-smi. But printing the allocated and reserved cuda memory with torch.cuda.memory_stats() shows no leak: I always get
CUDA rsvrd = 12.583 MB
CUDA alloc = 12.583 MB

I thought the leak might come from the fact that we don't free the nvjpeg handle (we literally leak it for convenience)
https://github.com/pytorch/vision/blob/9ae0169dd0ce815eebf1aff2963e8e1eb580eb3e/torchvision/csrc/io/image/cuda/decode_jpeg_cuda.cpp#L28-L30
but that's not the case: putting back the handle within the function and properly destroying it with nvjpegDestroy() still leads to a leak.
I don't see the leak anymore when commenting out the nvjpegDecode() call, so it happens somewhere inside. I don't understand why nvjpegDecode() has to allocate anything though, because the output cuda tensor's memory was already allocated prior to the call.
I don't know whether that's actually a bug from nvjpeg, or if there's something else going on. Either way, I don't understand. nvjpeg allows to pass custom device memory allocators, perhaps there is something to do there.
I'll try to look into that, but meanwhile if anyone has any idea of what's going on, I would appreciate any help.
Cheers

nvjpeg allows to pass custom device memory allocators, perhaps there is something to do there.
I'll try to look into that

Update: this still leaks 🥲
int dev_malloc(void **p, size_t s) {
    *p = c10::cuda::CUDACachingAllocator::raw_alloc(s);
    return 0;
  }

int dev_free(void *p) {
    c10::cuda::CUDACachingAllocator::raw_delete(p);
    return 0;
}

...

  nvjpegDevAllocator_t dev_allocator = {&dev_malloc, &dev_free};
  nvjpegStatus_t status = nvjpegCreateEx(NVJPEG_BACKEND_DEFAULT, &dev_allocator,
                                         NULL, NVJPEG_FLAGS_DEFAULT,  &nvjpeg_handle);

Hello @NicolasHug thanks for answer! I reinstalled CUDA, now I have this version
NVIDIA-SMI 510.47.03
Driver Version: 510.47.03
CUDA Version: 11.6
torch version '1.10.2+cu113'
torchvision version '0.11.3+cu113'
But problem does not disappear.  Should I rebuild torch with cuda 11.6 from source?

What does ldd <path_to_your_python_env>/site-packages/torchvision/image.so say regarding libnvjpeg? It's possible that it's still being linked to an 11.3 version, or that your .so file isn't as up to date as the I linked to above (<IP_ADDRESS>-1).

@NicolasHug Mine is showing /site-packages/torchvision/../torchvision.libs/libnvjpeg.90286a3c.so.11 How do I fix this to use system cuda?

There's two of them.
usr/local/cuda-11.6/lib64/libnvjpeg.so.11 (0x00007fc51ba65000)
libpng16.7f72a3c5.so.16 => /home/steven/.local/lib/python3.8/site-packages/torchvision/../torchvision.libs/libpng16.7f72a3c5.so.16 (0x00007fc51b82e000)
libjpeg.ceea7512.so.62 => /home/steven/.local/lib/python3.8/site-packages/torchvision/../torchvision.libs/libjpeg.ceea7512.so.62 (0x00007fc51b5d9000)
libnvjpeg.90286a3c.so.11 => /home/steven/.local/lib/python3.8/site-packages/torchvision/../torchvision.libs/libnvjpeg.90286a3c.so.11 (0x00007fc51aee8000)

@NicolasHug I added a symlink   libnvjpeg.90286a3c.so.11 -> /usr/local/cuda-11.6/lib64/libnvjpeg.so.11. Now there is only 1 nvjpeg but the memory leak persists. I wonder if this is because even though I am using 11.6 my driver version is 495.23 which is technically for 11.5. I am using GCP Compute Engine and unfortunately they do not yet support 511.

Hi, Would you mind telling where do you get this information? i could not find it in the cuda 11.6 release note. And I cannot reproduce this memory leak in my envirenment. It would be great if there is some more information.

Would you mind telling where do you get this information?

I basically tried all versions I could find from https://pkgs.org/search/?q=libnvjpeg-devel

@NicolasHug  should installing 11.6 and using the one that CUDA was built with it work? Do I have to install the RPM I’m on Ubuntu? Based on the LDD results from above I’m not sure if there’s anything else I can do?

Would you mind telling where do you get this information?

I basically tried all versions I could find from https://pkgs.org/search/?q=libnvjpeg-devel

I think I found a memory leak here :
https://github.com/pytorch/vision/blob/82f9a187681dade1620bc06b85f317a11aea40dc/torchvision/csrc/io/image/cuda/decode_jpeg_cuda.cpp#L74
the nvjpeg_handle_creation_flag should be global, not local. the nvjpeg_handle has been lost.

Hi,
I am using:
pytorch 1.11.0+cu113
ubuntu 20.04 LTS
python 3.9
I did replace libnvjpeg.90286a3c.so.11 with .so from cuda 11.6. However the memory keeps growing indefinitely.

It does not work with cuda 11.7 libnvjpeg either. But same behavior is observed when using numpy.frombuffer.

Also seeing this issue on CUDA 11.6 (running in a docker container):

Traceback (most recent call last):
File "/code/scripts/predict-noncapture-hauls.py", line 158, in
run()
File "/usr/local/lib/python3.9/dist-packages/click/core.py", line 1130, in call
return self.main(*args, **kwargs)
File "/usr/local/lib/python3.9/dist-packages/click/core.py", line 1055, in main
rv = self.invoke(ctx)
File "/usr/local/lib/python3.9/dist-packages/click/core.py", line 1404, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/local/lib/python3.9/dist-packages/click/core.py", line 760, in invoke
return __callback(*args, **kwargs)
File "/code/scripts/predict-noncapture-hauls.py", line 144, in run
predictions, metadata = evaluate_event_yolov5(
File "/code/scripts/predict-noncapture-hauls.py", line 75, in evaluate_event_yolov5
for batch in dataloader:
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py", line 530, in next
data = self._next_data()
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py", line 1224, in _next_data
return self._process_data(data)
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/dataloader.py", line 1250, in _process_data
data.reraise()
File "/usr/local/lib/python3.9/dist-packages/torch/_utils.py", line 457, in reraise
raise exception
RuntimeError: Caught RuntimeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.9/dist-packages/torch/utils/data/_utils/fetch.py", line 49, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/code/scripts/predict-noncapture-hauls.py", line 39, in getitem
im_nv = decode_jpeg(im_u8, device="cuda").float() / 255
File "/usr/local/lib/python3.9/dist-packages/torchvision/io/image.py", line 155, in decode_jpeg
output = torch.ops.image.decode_jpeg_cuda(input, mode.value, device)
RuntimeError: nvjpegDecode failed: 5

same ^

Yes, there are still leaks, even on cuda 11.6

Memory leaks on torchvision-0.14.0+cu117 (torchvision-0.14.0%2Bcu117-cp37-cp37m-win_amd64.whl).
When will this be fixed?
easy to reproduce:
for i in range(10000):
    torchvision.io.decode_jpeg(torch.frombuffer(jpeg_bytes,dtype=torch.uint8), device='cuda')

Is there anyone who solve this problem?? I also tried to use pynvjpeg, it is slower than torchvision.io.decode_jpeg and also at last  some error msg pops up like this : what() : memory allocator error aborted (core dumped)..

It seems that this problem has been solved. My environment is as follows
System: Ubuntu22.04
NVIDIA-SMI: 535.86.05
Driver Version: 535.86.05
CUDA Version: 12.2
torch version: 2.0.1+cu118
torchvision version: 0.15.2+cu118
finally, after waiting for over a year.  :)


Partial refactor of code base

Changes made:
Argument handling

Moved from click to argparse. Still retaining click for it's echo via pager API.
All objects are accessed via the namespace object generated by argparser.
Arg parse can handle defaults better, no longer requiring explicit checks to set another option.
Example: If no server is passed in, we automatically target master. This reduced checks and centralizes all options into a single file.

Tests

Tests have been updated to handle options via a namespace object. This allows each test method to express what options to toggle along with retaining default values.
All mssql client and option creations are centralized and no longer need explicitly set values on all calls unless a non default option is necessary. This is evident in test_mssqlcliclient.py and test_rowlimit.py

Miscellaneous

Methods were renamed for readability.
Added additional layers of abstraction for readability.
Messages logged are trimmed since some did not provide additional value.
Updated mssqlcliclient to support a shallow clone method.
Mssqlcliclient has private methods added to abstract away the connection and query execution API.
sqltoolsclient API are expressed in a class variable so as to avoid any hardcoded JSON RPC calls.
lower case all action for build.py for robustness.

class MssqlCli(object):

What do you think about moving MssqlCli into it's own file?

Refers to: mssqlcli/main.py:102 in 4eb4555. [](commit_id = 4eb4555268f2cca9066261808de811bd069f2ccb, deletion_comment = False)

"""

I think this operation should be moved to the MssqlCli object.

Refers to: mssqlcli/mssqlcliclient.py:338 in 4eb4555. [](commit_id = 4eb4555268f2cca9066261808de811bd069f2ccb, deletion_comment = False)

@pensivebrian , YES I WANT TO MOVE MSSQLCLI INTO IT's OWN FILE :) , I can do this on the side as I'm prioritizing the packaging work now.

:shipit:  Awesome! I really like how things cleaned things up.

Can we file a GitHub issue to completely remove click once we are done with refactoring?

@abhisheksinha89  https://github.com/dbcli/mssql-cli/issues/171


[contracts] Refactor tests to use Mock.sol

Many of the forge tests define in-file contract mocks. Would be better to create a Mock.sol that contains all of these mocked contracts.

In progress! Closing, will address in tests moving forward


Eager workflows to support async workflows

Fixes https://github.com/flyteorg/flyte/issues/3672
TL;DR
Implement an experimental API for "eager workflows": workflows that enable the use of Python async code.
Type

[ ] Bug Fix
[X] Feature
[ ] Plugin

Are all requirements met?

[X] Code completed
[X] Smoke tested
[ ] Unit tests added
[ ] Code documentation added
[ ] Any pending items have an associated Issue

Flytesnacks Example Link
...
Complete description
This PR adds support for @eager workflows. These are similar to @dynamic workflows in that they are flyte tasks that dynamically execute a graph. However, dynamic workflows can only use the materialized inputs to inform the shape of the graph -- at runtime, the flyte backend still gets a statically compiled workflow, but it's one that's compiled at runtime. @eager workflows take this to the other extreme of the static <-> dynamic spectrum.
Under the hood, an @eager "workflow" is actually a task that has access to a FlyteRemote object. This object needs to be configured correctly so that, at run-time, the remote object can authenticate to the configured flyte cluster. The eager workflow then uses this remote object to invoke the tasks that inside the user-defined eager workflow function body to invoke individual task executions.
Testing
Use the following Dockerfile and script to test this feature:
# Dockerfile.eager
FROM python:3.8-slim-buster

WORKDIR /root
ENV VENV /opt/venv
ENV LANG C.UTF-8
ENV LC_ALL C.UTF-8
ENV PYTHONPATH /root

RUN apt-get update && apt-get install -y build-essential git

# Install the AWS cli separately to prevent issues with boto being written over
RUN pip3 install awscli

ENV VENV /opt/venv
# Virtual environment
RUN python3 -m venv ${VENV}
ENV PATH="${VENV}/bin:$PATH"

# Install Python dependencies
COPY . /root/
WORKDIR /root

RUN pip install -e .
RUN pip install -e ./plugins/flytekit-deck-standard
RUN pip install scikit-learn pandas

ENV FLYTE_SDK_LOGGING_LEVEL 20

Python script:
# flytekit_eager.py
"""Async workflows prototype."""

import asyncio
import time
from typing import NamedTuple

import pandas as pd
from sklearn.datasets import load_wine
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

from flytekit import workflow, task
from flytekit.configuration import Config, PlatformConfig
from flytekit.experimental import eager
from flytekit.remote import FlyteRemote

class CustomException(Exception): ...

BestModel = NamedTuple("BestModel", model=LogisticRegression, metric=float)

@task
def get_data() -> pd.DataFrame:
    """Get the wine dataset."""
    return load_wine(as_frame=True).frame

@task
def process_data(data: pd.DataFrame) -> pd.DataFrame:
    """Simplify the task from a 3-class to a binary classification problem."""
    return data.assign(target=lambda x: x["target"].where(x["target"] == 0, 1))

@task
def train_model(data: pd.DataFrame, hyperparameters: dict) -> LogisticRegression:
    """Train a model on the wine dataset."""
    features = data.drop("target", axis="columns")
    target = data["target"]
    return LogisticRegression(max_iter=3000, **hyperparameters).fit(features, target)

@task
def evaluate_model(data: pd.DataFrame, model: LogisticRegression) -> float:
    """Train a model on the wine dataset."""
    features = data.drop("target", axis="columns")
    target = data["target"]
    return float(accuracy_score(target, model.predict(features)))

remote = FlyteRemote(
    config=Config.for_sandbox(),
    default_project="flytesnacks",
    default_domain="development",
)

@eager(remote=remote)
async def main() -> BestModel:
    logging.info("STARTING MAIN")
    data = await get_data()
    processed_data = await process_data(data=data)

    # split the data
    try:
        train, test = train_test_split(processed_data, test_size=0.2)
    except Exception as exc:
        raise CustomException(str(exc)) from exc

    models = await asyncio.gather(*[
        train_model(data=train, hyperparameters={"C": x})
        # for x in [0.1, 0.01, 0.001, 0.0001, 0.00001]
        for x in [0.1]
    ])
    results = await asyncio.gather(*[
        evaluate_model(data=test, model=model) for model in models
    ])

    best_model, best_result = None, float("-inf")
    for model, result in zip(models, results):
        if result > best_result:
            best_model, best_result = model, result

    assert best_model is not None, "model cannot be None!"
    return best_model, best_result

@workflow
def wf() -> BestModel:
    return main()

if __name__ == "__main__":
    print("training model")
    model = asyncio.run(main())
    print(f"trained model: {model}")

Tracking Issue
https://github.com/flyteorg/flyte/discussions/3396
Follow-up issue
NA

@pingsutw please feel free to make the necessary changes.


Error: function ArnoldPassShaders_Init is missing

Just pressing the Edit button under Pass on the Render toolbar gives this message:
# ERROR : 2268 - This function is missing:
# <function: ArnoldPassShaders_Init>
# <path: C:\Users\lindg\Documents\GitHub\sitoa\dist\Softimage_2015_SP2\Addons\SItoA\Application\Plugins\ArnoldMenu.js>
#

I guess this is a function that Softimage expects to be there for any renderer.
We should probably implement it and add some Arnold shaders to that menu. Like cryptomatte and some background shaders maybe.

I think this is just the 'Arnold Pass Shaders' submenu that used to have the Volume Scattering, Physical Sky, and Background shaders.

This is what is used to look like...
// pass sub-menu
function ArnoldPassShaders_Init(io_Context)
{
   var xsiMenu = io_Context.Source;
   xsiMenu.AddCallbackItem("Volume Scattering", "OnShadersMenu");
   xsiMenu.AddCallbackItem("Fog",               "OnShadersMenu");
   xsiMenu.AddSeparatorItem();
   xsiMenu.AddCallbackItem("Sky",               "OnShadersMenu");
}

@JenusL I think we can close this?

@caron Closed now. Was waiting for tickets to auto-close when pulled to master branch because I thought that would have happened by now.

I didn't know they got auto closed when merged with master... I actually assumed they would get auto closed when they got merged with develop


Make SwiftAbstractLogger compatible with OS X 10.10+

The library is already compatible API-wise, it just needed the deployment target reduced.

Sorry @jhurliman, I’ve been signed into my corporate account and didn’t check up. PR looks good, thanks for making the adjustment. I will get back to polishing up this library soon.


[R-package] {lightgbm} might be incompatible with some R 3.5.x versions

Description
See .
Today, the R package's DESCRIPTION says it supports R 3.5.0 and newer.
https://github.com/microsoft/LightGBM/blob/5fa887bb79d0e4d1961c8adafce9832448535e71/R-package/DESCRIPTION#L55
According to https://github.com/microsoft/LightGBM/pull/4812#issuecomment-973098661, recent changes in the R package might have made it incompatible with some R 3.5.x versions.
How to close this issue

Investigate the specific versions of R 3.5.x that the package might be compatible with
propose a pull request increasing the floor to that version

Notes
Thanks @david-cortes for reporting this!

I'm investigating this tonight, will share a reproducible example soon.
So far I've found that on Linux (the only OS I've tested on), the CRAN package compiles successfully with every release of R 3.5.x, but with 20+ test failures, mostly related to numerical precision issues.
Investigated the claim from https://github.com/microsoft/LightGBM/pull/4812#issuecomment-973098661 that R_FlushConsole was introduced somewhere in the R 3.5.x release series...I don't believe that is true.
Looks like R_FlushConsole has been in R.h for 16 years:
https://github.com/wch/r-source/blame/fe08ebe026a46d40015769f9512c1c347077ae6d/src/include/R.h#L93
R 3.5.0 was released in April 2018: https://cran.r-project.org/bin/windows/base/old/.

Using the rocker/verse container images, I tested {lightgbm}'s compatibility with a few versions of R 3.5.x tonight.
testing script (click me)
# build CRAN package
rm -f lightgbm*.tar.gz
sh build-cran-package.sh --no-build-vignettes

# gain a shell in a container
R_VERSION=3.5.3
docker run \
    --rm \
    -v $(pwd):/opt/LightGBM \
    --workdir /opt/LightGBM \
    --env MAKE="make -j2" \
    -it \
    rocker/verse:${R_VERSION} \
        /bin/bash

# update to the latest versions of all packages
Rscript \
    --vanilla \
    -e "install.packages(c('R6', 'data.table', 'jsonlite', 'Matrix', 'testthat'), repos = 'https://cran.r-project.org')"

# install LightGBM from source
R --vanilla CMD INSTALL \
    --with-keep.source \
    ./lightgbm_<IP_ADDRESS>.tar.gz

# run the tests
cd R-package/tests
Rscript --vanilla testthat.R

On both R 3.5.0 and R 3.5.3 (the first and last releases in that series), I found that:

{lightgbm} compiles successfully
a small handful of tests fail, all with numerical precision differences.

── 1. Failure (test_basic.R:738:3): lgb.train() works as expected with sparse features ────────────────
── 2. Failure (test_basic.R:1259:7): lgb.train() works when a list of strings or a character vector is
── 3. Failure (test_basic.R:1262:7): lgb.train() works when a list of strings or a character vector is
── 4. Failure (test_basic.R:1262:7): lgb.train() works when a list of strings or a character vector is
── 5. Failure (test_basic.R:1259:7): lgb.train() works when a list of strings or a character vector is
── 6. Failure (test_basic.R:1262:7): lgb.train() works when a list of strings or a character vector is
── 7. Failure (test_basic.R:1262:7): lgb.train() works when a list of strings or a character vector is
── 8. Failure (test_basic.R:1294:3): lgb.train() works when you specify both 'metric' and 'eval' with s
── 9. Failure (test_basic.R:1295:3): lgb.train() works when you specify both 'metric' and 'eval' with s
── 10. Failure (test_basic.R:1737:3): lgb.cv() works when you specify both 'metric' and 'eval' with str
── 11. Failure (test_basic.R:1738:3): lgb.cv() works when you specify both 'metric' and 'eval' with str
── 12. Failure (test_learning_to_rank.R:105:5): learning-to-rank with lgb.cv() works as expected ──────
── 13. Failure (test_learning_to_rank.R:128:5): learning-to-rank with lgb.cv() works as expected ──────
── 14. Failure (test_learning_to_rank.R:134:5): learning-to-rank with lgb.cv() works as expected ──────
── 15. Failure (test_learning_to_rank.R:140:5): learning-to-rank with lgb.cv() works as expected ──────

I haven't looked yet into the specifics of those tests. Stopping this investigation here for now, will come back to it after getting some other PRs up for other things.

I checked again today with the latest state of master (https://github.com/microsoft/LightGBM/commit/44fe591a60d7427d64997c37b22768a92c97c47b). {lightgbm}  compiles successfully with R 3.5.0 and R 3.5.3 (the first and last releases in the 3.x series).
I strongly suspect that the handful of tests that are failing are failing because of the changes to random number generation and random sampling between R 3.5.x and R 3.6.0. Mentioned in See https://blog.revolutionanalytics.com/2019/05/whats-new-in-r-360.html

Changes to random number generation.
R 3.6.0 changes the method used to generate random integers in the sample function... means that scripts using the sample function will generate different results in R 3.6.0 than they did in prior versions of R.

It seems to me that all of the tests that are failing involve the use of sample()...either in test data generation or through the use of sample() in lgb.cv().
Other tests which check for exact results and which do not use randomly-generated data or {lightgbm} code that calls lgb.cv() are passing.
For example:
https://github.com/microsoft/LightGBM/blob/44fe591a60d7427d64997c37b22768a92c97c47b/R-package/tests/testthat/test_basic.R#L171
https://github.com/microsoft/LightGBM/blob/44fe591a60d7427d64997c37b22768a92c97c47b/R-package/tests/testthat/test_basic.R#L189
https://github.com/microsoft/LightGBM/blob/44fe591a60d7427d64997c37b22768a92c97c47b/R-package/tests/testthat/test_basic.R#L283

Given this... I think we should close this issue, and leave the version floor in the R package set to R (>= 3.5.0).
Even though some of LightGBM's tests fail, it can be compiled successfully and most tests are passing. I think we should avoid putting an artificial restriction on users who may be on older R versions, and that we shouldn't spend time trying to get those tests working on R  3.5.x.
@jmoralez or @StrikerRUS what do you think?

I agree on closing this and keeping the floor at 3.5.0. From https://github.com/microsoft/LightGBM/pull/4812#issuecomment-973098661 I think the incompatibility would've caused the compilation to fail because of the missing function in the header so if the package compiles successfully I think the tests are only due to the different scores.

Alright thanks @jmoralez , I'm gonna close this.

It seems to me that all of the tests that are failing involve the use of sample()...either in test data generation or through the use of sample() in lgb.cv().

Nice observation!

I think we should avoid putting an artificial restriction on users who may be on older R versions, and that we shouldn't spend time trying to get those tests working on R 3.5.x.

I agree with both points.


CCVideoPlayer: ability to attach under GLView

Subj, there was a discussion on cocos2d forum. Here it is:
http://www.cocos2d-iphone.org/forum/topic/9220

Addition: implemented for gles20 branch: http://www.cocos2d-iphone.org/forum/topic/29478

I think the code in http://www.cocos2d-iphone.org/forum/topic/29478 will work on GL-ES1.1 too - it is the older path where
if ([_theMovie respondsToSelector: @selector(view)]) returns NO
that will definitely not work yet. As far as I can tell I don't use anything that is GL2.0 only - that is just the cocos that I work with now, so I can't say it will work on 1.1.

Yeah, it's ok with GLES 1.1, but there can be API diffs in cocos2d-iphone 2.x & 1.x
Like this:
    [[CCDirector sharedDirector].view

In 1.x there's no view property in CCDirector, only openGLView
It's pretty easy to support both  with some ifdefs

doh! Guess there will be these subtle issues between things as cocos v2 seems to be more than just a move to OpenGL ES2.0.


Missing load commands

I am getting this error from iTunes Connect after uploading to App Store and I haven't been able to figure out how to resolve it:
"Missing load commands - The executable at '/Payload/Affection Connection.app/Armchair.bundle/Armchair' does not have the necessary load commands. Try rebuilding the app with the latest Xcode version. If you are using third party development tools, contact the provider."
Any ideas on how to proceed are appreciated!

That's a strange one. Googling that message yields very few results. Are you using the real version of Xcode?

Yes, I am using the latest version of Xcode.  I followed the installation instructions in the readme and video to install Armchair, and then removed the info.list file from the archive as described in the wiki to resolve the code signing error.  This is my first iOS app, so my experience tracking this sort of thing down is limited.
Since I couldn't find anything online similar to my issue I wondered if the problem had something to do with removing the info.plist file, so I went down the path of trying to resolve the code signing entitlement error some other way, but I hit a dead end there.
I wound up getting around the error by manually adding Armchair as a framework directly to my app instead of as a git submodule.  This isn't ideal, of course, but I did spend many hours banging on it with no luck.

Hi,
I'm facing same issue on Xcode7, you got any solution ?
Thanks

Hi,I'm facing same issue on Xcode7, you got any solution ?

@pavm035 ,Did you get any solution about this problem?

@ZanderDev  Yes i solved this issue by removing versioning from bundle target, where xcode adds agv(apple generic versioning) option which generates *ver.c files during compilation which in turn generates executable file for bundle, and this is the cause of the issue. Hope it helps
Thanks

@pavm035 “Yes i solved this issue by removing versioning from bundle target” , what is the meaning of  "removing versioning "?

@ZanderDev  Look at build setting for your bundle target and search for "versioning" set it to None, by default it set to agv

@pavm035 Thanks.


Models are not working

Hi,
at first thanks for great port of threejs to java. Currently I'm having problems with loading models into it, hope you can help me.
When I loaded flamingo from demo it worked, but I tried to export cube from blender using threejs exporter and parallex can't load it I tried converting it using http://threejs.org/editor/ to export to scene or geometry (I can't select object ) but without success only STL type worked after loading in parallax. I've also tried using colladaLoader but didn't work :<
I've tried converting my scene(verticles:239k, faces:191k, objects:3,785) to STL and it looks like it's being loaded but 1,2 GB of ram later browser tab crashes, I hope Collada or JSON will have better performance.
Models I'm trying to load: https://www.sendspace.com/file/almqym
box.* files are from blender and rest was exported using threejs editor site
code I'm using
    protected void onStart() {
			// .. set camera and light
			new JsonLoader("./model/box.json", jsonModelLoadHandler);
    }

    private ModelLoadHandler jsonModelLoadHandler = new ModelLoadHandler() {
			@Override
			public void onModelLoaded(XHRLoader loader,
					AbstractGeometry geometry) {
				((JsonLoader)loader).morphColorsToFaceColors( (Geometry) geometry );
				((Geometry)geometry).computeMorphNormals();

				MeshLambertMaterial material = new MeshLambertMaterial();
				material.setColor(new Color(0xffffff));
				material.setMorphTargets(true);
				material.setMorphNormals(true);
				material.setVertexColors(Material.COLORS.FACE);
				material.setShading(Material.SHADING.FLAT);

	            Mesh mesh2 = new Mesh( geometry, material );
				getScene().add(mesh2);
    }

Also what should I know when using JSON and Collada loaders compared to OBJMTL loader which I used previously in JS?

For Json most of the exporters create 4.4 version and seems like Parallax is working with version 3.0. If you point me out to some resource on how to update the Loader I would do it.

Hi, I found the new loaders thanks ! Looking forward for version 2.0

Thanks I'll give it a try.

Alex, maybe it is quite a silly question but how do you add parallax 2.0 dev to an existing project that does not use gradle ?

Hi,
you have to migrate your project following this template : https://github.com/thothbot/parallax-application-template

Hi, is there not other way ? I am adding functionality to a project that compiles with ant.

Hi,
Thanks for the library btw. I tried the STLLoader and the JsonLoader. The STLLoader seems not to load right complex meshes see the pictures attached. I used this tool to generate the STL and JSON file https://mrdoob.github.io/three.js/editor/ . The image in red is in three.js editor and the other rendered with the latest 2.0 snapshot . Attached is also a simple cube and a sphere in json format that can not be loaded. However, I can still load the previous flamingo.js, horse.js, etc...

geometry.zip


Config entry name resets on reconfiguration

Description
When a device is reconfigured the original config entry name disappears and is replaced by the IP Address of the device instead.
After renaming - expected:

After re-configuring - unexpected:

Reproduction Steps

Browse to Devices & services -> Tapo: Cameras Control -> Camera name
From the dots, select Rename and choose a device name - observe that the config entry name is set
Select the Configure button, Action = Configure device and Submit
Notice that the config entry name is reset from the one set in step two back to the device's IP Address

Expected behavior
Original config entry name should be retained.
If applicable, add error logs.
No response
Device Firmware
1.3.6 Build 230424 Rel.77225n(4555)
Integration Version
5.4.2
Using stream component
Yes
Does camera work via official integrations?
Yes
Camera has all attributes filled out in developer tools
Yes
HASS Environment
OS
Search for similar issues
Yes
Additional information
access_token: xxx
model_name: C200
brand: TP-Link
motion_detection: on
frontend_stream_type: hls
device_type: SMART.IPCAMERA
device_model: C200
device_name: C200 1.0
device_info: C200 1.0 IPC
hw_version: 1.0
sw_version: 1.3.6 Build 230424 Rel.77225n(4555)
device_alias: Dining Room Camera
avatar: camera c212
longitude: 0
latitude: 0
has_set_location_info: 0
features: 3
barcode:
mac: 28-EE-52-93-E9-D3
dev_id: 80215ACBBFF1B116E989BD4366B7BBF31E273DDA
oem_id: 8902D2F34FCE407721DE92F5759839C2
hw_desc:<PHONE_NUMBER>4300000000000000000001
alarm: off
user: homeassistant
presets:
{}

record_plan:
sunday: '["0000-2400:2"]'
monday: '["0000-2400:2"]'
tuesday: '["0000-2400:2"]'
wednesday: '["0000-2400:2"]'
thursday: '["0000-2400:2"]'
friday: '["0000-2400:2"]'
saturday: '["0000-2400:2"]'

entity_picture: /api/camera_proxy/camera.dining_room?token=xxx
icon: mdi:webcam
friendly_name: Dining Room Camera
supported_features: 3

Fixed in https://github.com/JurajNyiri/HomeAssistant-Tapo-Control/releases/tag/5.4.30


[Suggestion]: License on CurseForge

What is your suggestion?
The Curseforge page lists the license as "All Rights Reserved", however the license here is MIT.
Please change the license on the Curseforge page to match what's on GitHub.

I prefer to keep the project itself locked behind All Rights Reserved to more easily be able to deal with other websites rehosting my mod without permission.
I'm well aware that some other licenses also cover this, but with All Rights Reserved there is no way this can raise any kind of discussion or poor excuse.
Besides that i see no use in having another license on the project itself anyways as i already explicitly state that one is free to use it in any modpack.

But what about the source? It is licensed under MIT, so the mod should also be MIT

But what about the source? It is licensed under MIT, so the mod should also be MIT

I believe that the Curse license more so applies to the project itself rather than the code, allowing it to differ without problems.

Reasonable, the source and the binaries may be licensed with different licenses. However, if there is no malicious intent, what's wrong with rehosting a mod? It's basically just copying the mod's binary to an another place

Reasonable, the source and the binaries may be licensed with different licenses. However, if there is no malicious intent, what's wrong with rehosting a mod? It's basically just copying the mod's binary to an another place

They steal downloads from the true source and allows the rehosting sites to profit off of someone else their code.
Additionally these are sometimes injected with malicious code.

But if someone wants to make it malicious, they will just do it without asking for your permission, same with "rehosting sites", they can just post the links to your things and still have loads of ads on that page, although it doesn't break any of those "rules".
In this case I think it's better to have everything freely redistributable.

But if someone wants to make it malicious, they will just do it without asking for your permission, same with "rehosting sites", they can just post the links to your things and still have loads of ads on that page, although it doesn't break any of those "rules".
In this case I think it's better to have everything freely redistributable.

And i'm not sure what rules you're referring to, but i clearly state that reposting it is not allowed.


just show stats like old version

v1.36
appears -stats doesn't work without the -v flag,
how do i only get the -stats output like in the old version? i don't want a per file log

I think you can do this on Linux:
Rclone copy /x/  y:    -v --stats 5m  2>&1 | egrep "^E|^T|^C"
I know it's not exactly what you want but it would work......

rclone copy -v --stats 5s /home/jxer/files Gdrive:/media |& grep -v 'INFO'"
this works but i think the stats flag should be allowed to be set without the above

@calisro i guess slightly different syntax but it works both ways i guess

Yes but I do agree with you. .

I'm going to fix this in #1180 so I'm going to close this as a duplicate.  Please subscribe to that bug for updates!
Thanks


ELK stack

ELK stack
Goal
Be able to use ELK stack (Elastic Search, Logstash and Kibana)

DESCRIPTION
This PR adds configurable Elastic Search, Logstash and Kibana container (known as ELK stack) to the Devilbox.

Refs: https://github.com/cytopia/devilbox/issues/360

Sorry for not reviewing this earlier.
this looks great, however: Logstash requires that you put config files in a folder. This describes what data sources logstash should import into elastic. I would recommend keeping the data volume, but adding in a host mounted directory for this folder.
From my example in #360

-e "PATH_CONFIG=/etc/logstash/conf.d"
-v /etc/logstash/:/etc/logstash \

These config files also often list the path to a metadata file (i.e.: last updated timestamp or last id), in my setup I have it as /etc/logstash/meta/table_last_update.

@science695 I must have missed that part. Do you have an example of a logstash configuration file that I can actually try out?

Logstash is quite flexible, with many many different configuration types, from sql to logfiles to elastic beats ....
Here is Elastic's documentation on how to import apache access logs into an elastic index (very simple, almost too simple):
https://www.elastic.co/guide/en/logstash/current/config-examples.html#_processing_apache_logs
The file listed there would go in /etc/logstash/conf.d/apache-logs.conf
But the idea for this would be that conf.d folder is exposed to the host so we could put our own configs in. Possible the /etc/logstash/meta/ folder (if you are using the jdbc (SQL) input plugin: https://www.elastic.co/guide/en/logstash/current/plugins-inputs-jdbc.html#_usage )


[DISCUSS] Gather missing permission granularity

Motivation
According to issue https://github.com/apache/pulsar/issues/5720, we introduced more fine-grained authorization, named XXXOperations. (package path: org.apache.pulsar.common.policies.data)
After summarizing all the operations, it is found that we have missed some Operations, which may be caused by new features and so on.
In this discussion, we want to collect all the missing permission granularity to provide basic full permission control.
Process
Everyone please feels free to make a suggestion, We will collect all suggestion into the list first and then start a vote to delete unnecessary operations.
Operations List

Operation Type
Operation
Remarks

TenantOperation
CREATE_NAMESPACE

-
DELETE_NAMESPACE

-
LIST_NAMESPACES

NamespaceOperation
CREATE_TOPIC

-
GET_TOPIC

-
GET_TOPICS

-
DELETE_TOPIC

-
ADD_BUNDLE

-
DELETE_BUNDLE

-
GET_BUNDLE

-
GET_PERMISSION

-
GRANT_PERMISSION

-
REVOKE_PERMISSION

-
CLEAR_BACKLOG

-
UNSUBSCRIBE

-
PACKAGES

NamespacePolicyOperation
READ

-
WRITE

TopicOperation
LOOKUP

-
PRODUCE

-
CONSUME

-
COMPACT

-
EXPIRE_MESSAGES

-
OFFLOAD

-
PEEK_MESSAGES

-
RESET_CURSOR

-
SKIP

-
TERMINATE

-
UNLOAD

-
GRANT_PERMISSION

-
GET_PERMISSION

-
REVOKE_PERMISSION

-
ADD_BUNDLE_RANGE

-
GET_BUNDLE_RANGE

-
DELETE_BUNDLE_RANGE

-
SUBSCRIBE

-
GET_SUBSCRIPTIONS

-
UNSUBSCRIBE

-
GET_STATS

-
GET_METADATA

-
GET_BACKLOG_SIZE

-
SET_REPLICATED_SUBSCRIPTION_STATUS

-
GET_REPLICATED_SUBSCRIPTION_STATUS

@mattisonchao may I ask what's the conclusion of this issue?


Python decorators for Workflow

Describe the proposal
The current Python SDK implementation of Workflow is structured and provides a set of functions to operate the workflow of your code/ long running scenarios.
e.g.: schedule_new_workflow(), get_workflow_state(), wait_for_workflow_start()
The proposal is to leverage the strengths of Python programming model, to simplify the developers’ efforts further, by introducing decorators pattern to add additional features/ functionality to existing functions without modifying the original structure of the code.
Proposed Solution
The Workflow lifecycle is involved with multiple steps as shown below and we have multiple functions for each of these steps.

Currently in Python workflow SDK, we have workflow function definition, activity functions definition followed by registering of the workflow and activity function against the WorkflowRuntime instance.
For now, there is only one WorkflowRuntime instance created which interacts with the Dapr sidecar is shown below.
wfr = WorkflowRuntime(host, port)

Given that workflow instance(wfr), we can register multiple workflow functions against it as well as multiple activity functions against it.

Decorators at Workflow level

@wfr.workflow.register(name) – Register the workflow with DAPR side car. name is related to the GitHub issue.
@wfr.worflow.serializer(serializer)/@wfr.workflow.deserializer(deserializer) – to set serialization/ deserialization logic with workflow input/output
@wfr.workflow.retry()– Resiliency, to apply the retries on Workflow.

In durabletask-python library, there are options to set RetryPolicy for an activity, this functionality is to extend it to the workflow level and be able to set a default policy for any run of a particular workflow.

Decorators at Activity level

@wfr.activity.register(name) – Register an Activity with workflow runtime. name is related to the GitHub issue.
@wfr.activity.serializer(serializer)/@wfr.activity.deserializer(deserializer) – to set serialization/ deserialization logic with activity input/output.
@wfr.activity.retry() - Resiliency, to apply the retries on Activity. Currently an activity can be called with a RetryPolicy, based on the code in durabletask-python library. This is to be able to set a default retry policy for the activity even if a retry policy is not specified at the call site.

Example code with workflow and activity level decorators:
wfr = WorkflowRuntime(host, port)
@wfr.workflow.register(name=”hello_world”)
@wfr.workflow.serializer(CustomInputSerializer())
def hello_world_wf(ctx: DaprWorkflowContext, input):
    print(f'{input}')
    yield ctx.call_activity(hello_act, input=1)
    yield ctx.call_activity(hello_act, input=10)
    yield ctx.wait_for_external_event("event1")
    yield ctx.call_activity(hello_act, input=100)
    yield ctx.call_activity(hello_act, input=1000)

@wfr.activity.register(name=”hello”)
@wfr.activity.retry(max_number_of_attempts=3)
def hello_act(ctx: WorkflowActivityContext, input):
    global counter
    counter += input
    print(f'New counter value is: {counter}!', flush=True)

def main( ):
        wfr.start()
      . . . start workflow as normal

Potential changes needed to codebase

Addition of retry policy in dapr/python-sdk to mirror what is there in microsoft/durabletask-python library.

Workflow specific retries are not there in the library yet. If needed, that can be added.

Change WorkflowRuntime or add a new class to define the decorators stated above.

For the register_activity and register_workflow methods in the class, we can reuse the code that is currently there in WorkflowRuntime class and extend it to add a decorator for the same.

Setting the serializer, deserializers on the activity and the workflow levels, changes are needed in the microsoft/durabletask-python library first which then needs to be propagated into the dapr/python-sdk workflow code.

If the WorkflowRuntime instance is going to be a singleton instance for the application, we can potentially do away with the creation of the instance and also simplify the decorators to workflow.register(name), activity.register(name) which is then registers against the singleton WorkflowRuntime instance created when the app starts.

+1 please make sure we also have the waitForInstanceCompletion like java sdk.

@berndverst @cgillum @DeepanshuA
A specific question with respect to the initialization of the workflow runtime instance and registering the workflow, activity against a particular runtime.
As of now we always have only one single workflow runtime instance, with a connection specified by host and port (can default to dapr host port)
I would like to modify the decorator
@wfr.workflow.register

To something like
@workflow.register(workflow_runtime=default)

or simply
@workflow(workflow_runtime=default)

and same for activity also
Instead of
@wfr.activity.register

be either
@activity.register(workflow_runtime=default)

or
@activity(workflow_runtime=default)

The default value of workflow runtime instance being created at the start itself, based on values of Dapr host and port from settings.py.
It can if needed be overridden by specifying a different workflow_runtime value if a new one is created by the user.
This in turn would make it that, a default workflow runtime instance will be created if either workflow or activity decorators are used and only that instance will be used and it cannot be changed later on i.e. make WorkflowRuntime class a singleton class.
I would like your thoughts on this change.
After change:
## default workflow_runtime is used
@workflow.register(name=”hello_world”)
@workflow.serializer(CustomInputSerializer())
def hello_world_wf(ctx: DaprWorkflowContext, input):
    print(f'{input}')
    yield ctx.call_activity(hello_act, input=1)
    yield ctx.call_activity(hello_act, input=10)
    yield ctx.wait_for_external_event("event1")
    yield ctx.call_activity(hello_act, input=100)
    yield ctx.call_activity(hello_act, input=1000)

@activity.register(name=”hello”)
@activity.retry(max_number_of_attempts=3)
def hello_act(ctx: WorkflowActivityContext, input):
    global counter
    counter += input
    print(f'New counter value is: {counter}!', flush=True)

def main( ):
        wfr = WorkflowRuntime.get_instance()
        wfr.start()
      . . . start workflow as normal
```

there is initial draft code that is there in #651. The pending work is adding tests and a TODO for creating a default init for WorkflowRuntime.

Thanks @mukundansundar. Of the options you mentioned, I'd actually prefer the more explicit approach which doesn't include a default WorkflowRuntime singleton. My reasoning is the following:

The explicit approach makes the code be more self-explanatory.
Default singletons may add some "magic" that makes it harder for the average user to understand what's going on.
The explicit approach is similar to existing frameworks, like Flask and FastAPI. This familiarity will help users understand it more quickly.

That said, I do value simplicity, and one simplification I'd make to your initial proposal is to combine the multiple decorators into just one. I also wonder if the user should be presented with WorkflowApp instead of WorkflowRuntime as the root concept.
wfapp = WorkflowApp(host, port)

@wfapp.workflow(name="hello_world", serializer=CustomInputSerializer)
def hello_world_wf(ctx: DaprWorkflowContext, input):
    print(f'{input}')
    yield ctx.call_activity(hello_act, input=1)
    yield ctx.call_activity(hello_act, input=10)
    yield ctx.wait_for_external_event("event1")
    yield ctx.call_activity(hello_act, input=100)
    yield ctx.call_activity(hello_act, input=1000)

activity_retry_policy = ...

@wfapp.activity(name="hello", retry_policy=activity_retry_policy)
def hello_act(ctx: WorkflowActivityContext, input):
    print(f'Activity input: {input}', flush=True)

def main( ):
        wfapp.start()
      . . . start workflow as normal

Let me know what you think.

I think having the WorkflowRuntime(WorkflowApp) initialized explicitly does add more clarity to the flow.
For the renaming part, my one concern is we have wfapp.start(). Could that give an incorrect notion that the workflow app has started and the workflow itself has started?
When it is workflow_runtime.start(), that clearly says its the runtime you are starting and not the app/workflow.

A concern I have with the wfapp sample in https://github.com/dapr/python-sdk/issues/635#issuecomment-1852530911 is that it suggests that the module that attaches functions to the wfapp is the same module that runs the wfapp, which is not the case for my application.
As I mentioned in  https://github.com/dapr/python-sdk/pull/651 I have multiple modules with activities and workflows, but only one workflow runtime that will be instantiated at the top-most level.
I think in this example, WorkflowApp  has the same issues as WorkflowRuntime (because in this example WorkflowApp also takes host and port arg)
Would you consider the FastAPI approach, where FastAPI()  can be instantiated as a lightweight  container to which functions get attached?
Then a higher level module can import the the 'app' from each child module and mount them to the top-most FastAPI() instance, which is the one that actually does the work.
What if WorkflowApp were only a container for registered workflows and activities, and didn't create a GrpcEndpoint or a TaskHubGrpcWorker until the start() method were called?
# module1.py
wfapp = WorkflowApp() # a lightweight container

@wfapp.workflow(name="hello_world", serializer=CustomInputSerializer)
def hello_world_wf(ctx: DaprWorkflowContext, input):
    print(f'{input}')
    yield ctx.call_activity(hello_act, input=1)
...

Then (optionally in a higher level module, can combine multiple WorkflowApp together)
# main.py
from module1 import wfapp as module1_wfapp
from module2 import wfapp as module2_wfapp

wfapp = WorkflowApp() # a lightweight container
wfapp.attach(module1_wfapp)
wfapp.attach(module2_wfapp)

def main( ):
        wf_runtime = wfapp.start(host, port) # instantiate WorkflowRuntime, register workflows and activities and calls wf_runtime.start()
        # do stuff
        wf_runtime.shutdown()

alternatively if workflow_runtime is also going to be a context manager, then maybe this approach?
# main.py
from module1 import wfapp as module1_wfapp
from module2 import wfapp as module2_wfapp

wfapp = WorkflowApp() # a lightweight container
wfapp.attach(module1_wfapp)
wfapp.attach(module2_wfapp)

def main( ):
       with wfapp.create_runtime(host, port) as wf_runtime: # instantiate WorkflowRuntime, register workflows and activities
            wf_runtime.start()
            # do other stuff or sleep or whatever

shutdown() is automatically called when the wf_runtime context exits

I've been experimenting with decorators for Dapr Workflow for a recent project and have just been pointed to this issue.
I have created a repo with the decorator code extracted if you're interested: https://github.com/stuartleeks/dapr-workflow-exploration-python

closing this issue since the initial set of decorators are implemented in #651 and any further enhancements will be tracked as separate issues.


Fix the error java.io.IOException: Unable to delete file: ...build\resources\main\changelog.md

I cherry-picked and tweaked the code to use try/finally on my 0.3.1 branch. Would you mind testing that to see if it fixes the issue for you? I'll release 0.3.1 if it does.


Feature Request: Loading spinner when button is disabled

Is your feature request related to a problem? Please describe.
Currently while loading, the then is disabled and its opacity is reduced:

Change it to something like this when loading:

Describe the solution you thought
You may opt for any solution you are comfortable with. Just make sure that whatever you implement is maintainable and does not break any existing functionality.
My suggestion would be to create a global button component accepting all the required props and make a check inside the button if the loading state is true.
Additional context (if any)

Make sure you don't change anything for the src/components/StripeCheckout component for this issue.
You can use the following resource for getting an animated loader SVG: loading.io

@varunKT001 Hey,I have checked your isssue.So can you assign it to me

Can I work this issue under GsSoc 22

Hey Can you assign this issue under GSSOC22

Guys note that the issues will be given on a first come first serve basis.
@Abhinav0909 is the first to claim the issue, so I'm gonna assign it to him 🚀
@sagnik2001 and @sulogna2001, I'll be creating more issues so stay tuned 🎉
Till then, you can also create some issues if you find something you can improve in TomperWear 😄
I'll also be creating a GitHub workflow to automatically assign the issues so you guys don't have to wait for assignment 👍

@Abhinav0909 Make sure you read the contribution guidelines before contributing. Also, while making a pull request, make sure to strictly follow the provided pull request template 👍

@Abhinav0909 Any updates on this?

@sagnik2001 sure 👍

ok ,I will complete this issue by tommorow

@Abhinav0909 Great 👍

hey sorry for the delay can i deliver the issue by tommorow evening.I am working on it.There is a network issue here.Again sorry for delay

Right now I can't do npm start.The answer to that problem statement is to delete node modules which is given to me.

hey sorry for the delay can i deliver the issue by tommorow evening.I am working on it.There is a network issue here.Again sorry for delay

Sure, take your time 👍

Right now I can't do npm start.The answer to that problem statement is to delete node modules which is given to me.

Okay, try that. If still there is problem, you can ping me on TomperWear discord channel, I'll look into that 👍

could you provide me with discord server link so that I can talk to you

You are a participant of GSSoC'22 right?

yes

Then you should have got the discord invitation link in your selection mail.

ok,

I have joined discord but is there any specific voice channels made for you or where can I have talk with you.It is a little bit confusing since it's first time experience.I couldn't figure out .

You can go to the self-rules channel, and on scrolling down, you'll find TomperWear role. React on it to unlock the TomperWear channel.

It's already 5 days @Abhinav0909 🙁
What's the status?

Yeah but npm start is not happening because of comparability issues of react scripts

Yeah but npm start is not happening because of comparability issues of react scripts

It's working fine for me and all other contributors 🙁
I think that's an issue from your side. I assume that you won't be able to complete this soon, so I'm re-assigning the issue 👍
@sagnik2001 You want to work on this?

Hmm ok

hey @varunKT001 you can assign this issue to me

Okay, assigned to you @sagnik2001 🚀

Should I implement this feature only for login button or every button makes a request to the api

Should I implement this feature only for login button or every button makes a request to the API

All the buttons 👍

Hey @varunKT001, while implementing a loading spinner what I found is that you used the same state loader for every field which on changing makes a loader in every button so should I make a separate loading state, or is this ok??

@sagnik2001 It's fine, you can leave it like that 👍


Use read/write connection modes to the compute-db

This PR implements:

usage of two different connection modes (read and write) to the compute-db;
retry on write compute-db hostname if NoSuchJob is returned by get_job_from_broker_db

Requires:

https://github.com/ecmwf-projects/cads-broker/tree/implement-read-and-write

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.1 out of 2 committers have signed the CLA.:white_check_mark: mcucchi9:x: francesconazzaroYou have signed the CLA already but the status is still pending? Let us recheck it.


Synthesis failed for AppsActivity

Hello! Autosynth couldn't regenerate AppsActivity. :broken_heart:
Here's the output from running synth.py:
2020-05-09 05:04:47 [INFO] logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
2020-05-09 05:04:47,452 autosynth > logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
Switched to branch 'autosynth-appsactivity'
2020-05-09 05:04:49 [INFO] Running synthtool
2020-05-09 05:04:49,174 autosynth > Running synthtool
2020-05-09 05:04:49 [INFO] ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-09 05:04:49,174 autosynth > ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-09 05:04:49,383 synthtool > Executing /home/kbuilder/.cache/synthtool/elixir-google-api/synth.py.
On branch autosynth-appsactivity
nothing to commit, working tree clean
2020-05-09 05:04:49,736 synthtool > Cloning https://github.com/googleapis/elixir-google-api.git.
2020-05-09 05:04:50,191 synthtool > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/elixir-google-api:/workspace -v/var/run/docker.sock:/var/run/docker.sock -e USER_GROUP=1000:1000 -w /workspace gcr.io/cloud-devrel-public-resources/elixir19 scripts/generate_client.sh AppsActivity
2020-05-09 05:04:53,705 synthtool > No files in sources /home/kbuilder/.cache/synthtool/elixir-google-api/clients were copied. Does the source contain files?
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 102, in <module>
    main()
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 94, in main
    spec.loader.exec_module(synth_module)  # type: ignore
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 180, in __exit__
    write(self.metadata_file_path)
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 112, in write
    with open(outfile, "w") as fh:
FileNotFoundError: [Errno 2] No such file or directory: 'clients/apps_activity/synth.metadata'
2020-05-09 05:04:53 [ERROR] Synthesis failed
2020-05-09 05:04:53,734 autosynth > Synthesis failed
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 599, in <module>
    main()
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 471, in main
    return _inner_main(temp_dir)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 549, in _inner_main
    ).synthesize(base_synth_log_path)
  File "/tmpfs/src/github/synthtool/autosynth/synthesizer.py", line 118, in synthesize
    synth_proc.check_returncode()  # Raise an exception.
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/subprocess.py", line 389, in check_returncode
    self.stderr)
subprocess.CalledProcessError: Command '['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--', 'AppsActivity']' returned non-zero exit status 1.

Google internal developers can see the full log here.

Autosynth is still having trouble generating AppsActivity. :sob:
Here's the output from running synth.py:
2020-05-10 05:04:40 [INFO] logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
2020-05-10 05:04:40,628 autosynth > logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
Switched to branch 'autosynth-appsactivity'
2020-05-10 05:04:42 [INFO] Running synthtool
2020-05-10 05:04:42,338 autosynth > Running synthtool
2020-05-10 05:04:42 [INFO] ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-10 05:04:42,338 autosynth > ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-10 05:04:42,559 synthtool > Executing /home/kbuilder/.cache/synthtool/elixir-google-api/synth.py.
On branch autosynth-appsactivity
nothing to commit, working tree clean
2020-05-10 05:04:42,632 synthtool > Cloning https://github.com/googleapis/elixir-google-api.git.
2020-05-10 05:04:43,066 synthtool > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/elixir-google-api:/workspace -v/var/run/docker.sock:/var/run/docker.sock -e USER_GROUP=1000:1000 -w /workspace gcr.io/cloud-devrel-public-resources/elixir19 scripts/generate_client.sh AppsActivity
2020-05-10 05:04:47,401 synthtool > No files in sources /home/kbuilder/.cache/synthtool/elixir-google-api/clients were copied. Does the source contain files?
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 102, in <module>
    main()
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 94, in main
    spec.loader.exec_module(synth_module)  # type: ignore
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 180, in __exit__
    write(self.metadata_file_path)
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 112, in write
    with open(outfile, "w") as fh:
FileNotFoundError: [Errno 2] No such file or directory: 'clients/apps_activity/synth.metadata'
2020-05-10 05:04:47 [ERROR] Synthesis failed
2020-05-10 05:04:47,425 autosynth > Synthesis failed
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 599, in <module>
    main()
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 471, in main
    return _inner_main(temp_dir)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 549, in _inner_main
    ).synthesize(base_synth_log_path)
  File "/tmpfs/src/github/synthtool/autosynth/synthesizer.py", line 118, in synthesize
    synth_proc.check_returncode()  # Raise an exception.
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/subprocess.py", line 389, in check_returncode
    self.stderr)
subprocess.CalledProcessError: Command '['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--', 'AppsActivity']' returned non-zero exit status 1.

Google internal developers can see the full log here.

Autosynth is still having trouble generating AppsActivity. :sob:
Here's the output from running synth.py:
2020-05-11 05:04:02 [INFO] logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
2020-05-11 05:04:02,245 autosynth > logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
Switched to branch 'autosynth-appsactivity'
2020-05-11 05:04:03 [INFO] Running synthtool
2020-05-11 05:04:03,713 autosynth > Running synthtool
2020-05-11 05:04:03 [INFO] ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-11 05:04:03,713 autosynth > ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-11 05:04:03,895 synthtool > Executing /home/kbuilder/.cache/synthtool/elixir-google-api/synth.py.
On branch autosynth-appsactivity
nothing to commit, working tree clean
2020-05-11 05:04:04,108 synthtool > Cloning https://github.com/googleapis/elixir-google-api.git.
2020-05-11 05:04:04,574 synthtool > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/elixir-google-api:/workspace -v/var/run/docker.sock:/var/run/docker.sock -e USER_GROUP=1000:1000 -w /workspace gcr.io/cloud-devrel-public-resources/elixir19 scripts/generate_client.sh AppsActivity
2020-05-11 05:04:07,717 synthtool > No files in sources /home/kbuilder/.cache/synthtool/elixir-google-api/clients were copied. Does the source contain files?
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 102, in <module>
    main()
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 94, in main
    spec.loader.exec_module(synth_module)  # type: ignore
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 180, in __exit__
    write(self.metadata_file_path)
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 112, in write
    with open(outfile, "w") as fh:
FileNotFoundError: [Errno 2] No such file or directory: 'clients/apps_activity/synth.metadata'
2020-05-11 05:04:07 [ERROR] Synthesis failed
2020-05-11 05:04:07,741 autosynth > Synthesis failed
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 599, in <module>
    main()
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 471, in main
    return _inner_main(temp_dir)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 549, in _inner_main
    ).synthesize(base_synth_log_path)
  File "/tmpfs/src/github/synthtool/autosynth/synthesizer.py", line 118, in synthesize
    synth_proc.check_returncode()  # Raise an exception.
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/subprocess.py", line 389, in check_returncode
    self.stderr)
subprocess.CalledProcessError: Command '['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--', 'AppsActivity']' returned non-zero exit status 1.

Google internal developers can see the full log here.

Autosynth is still having trouble generating AppsActivity. :sob:
Here's the output from running synth.py:
2020-05-11 15:05:08 [INFO] logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
2020-05-11 15:05:08,990 autosynth > logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
Switched to branch 'autosynth-appsactivity'
2020-05-11 15:05:10 [INFO] Running synthtool
2020-05-11 15:05:10,606 autosynth > Running synthtool
2020-05-11 15:05:10 [INFO] ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-11 15:05:10,606 autosynth > ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-11 15:05:10,817 synthtool > Executing /home/kbuilder/.cache/synthtool/elixir-google-api/synth.py.
On branch autosynth-appsactivity
nothing to commit, working tree clean
2020-05-11 15:05:10,987 synthtool > Cloning https://github.com/googleapis/elixir-google-api.git.
2020-05-11 15:05:11,529 synthtool > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/elixir-google-api:/workspace -v/var/run/docker.sock:/var/run/docker.sock -e USER_GROUP=1000:1000 -w /workspace gcr.io/cloud-devrel-public-resources/elixir19 scripts/generate_client.sh AppsActivity
/workspace /workspace
The mix.lock file was generated with a newer version of Hex. Update your client by running `mix local.hex` to avoid losing data.
Resolving Hex dependencies...
Dependency resolution completed:
Unchanged:
  certifi 2.5.1
  google_api_discovery 0.7.0
  google_gax 0.3.2
  hackney 1.15.2
  idna 6.0.0
  jason 1.2.0
  metrics 1.0.1
  mime 1.3.1
  mimerl 1.2.0
  oauth2 0.9.4
  parse_trans 3.3.0
  poison 3.1.0
  ssl_verify_fun 1.1.5
  temp 0.4.7
  tesla 1.3.3
  unicode_util_compat 0.4.1
A new Hex version is available (0.20.1 < 0.20.5), please update with `mix local.hex`
All dependencies are up to date
The mix.lock file was generated with a newer version of Hex. Update your client by running `mix local.hex` to avoid losing data.

22:05:14.960 [info]  FETCHING: https://www.googleapis.com/discovery/v1/apis/appsactivity/v1/rest

22:05:15.101 [info]  FOUND: https://www.googleapis.com/discovery/v1/apis/appsactivity/v1/rest
Revision check: old=20200428, new=20200428, generating=true
Creating leading directories
Writing Activity to clients/apps_activity/lib/google_api/apps_activity/v1/model/activity.ex.
Writing Event to clients/apps_activity/lib/google_api/apps_activity/v1/model/event.ex.
Writing ListActivitiesResponse to clients/apps_activity/lib/google_api/apps_activity/v1/model/list_activities_response.ex.
Writing Move to clients/apps_activity/lib/google_api/apps_activity/v1/model/move.ex.
Writing Parent to clients/apps_activity/lib/google_api/apps_activity/v1/model/parent.ex.
Writing Permission to clients/apps_activity/lib/google_api/apps_activity/v1/model/permission.ex.
Writing PermissionChange to clients/apps_activity/lib/google_api/apps_activity/v1/model/permission_change.ex.
Writing Photo to clients/apps_activity/lib/google_api/apps_activity/v1/model/photo.ex.
Writing Rename to clients/apps_activity/lib/google_api/apps_activity/v1/model/rename.ex.
Writing Target to clients/apps_activity/lib/google_api/apps_activity/v1/model/target.ex.
Writing User to clients/apps_activity/lib/google_api/apps_activity/v1/model/user.ex.
Writing Activities to clients/apps_activity/lib/google_api/apps_activity/v1/api/activities.ex.
Writing connection.ex.
Writing metadata.ex.
Writing mix.exs
Writing README.md
Writing LICENSE
Writing .gitignore
Writing config/config.exs
Writing test/test_helper.exs
fixing file permissions
2020-05-11 15:05:16,016 synthtool > No files in sources /home/kbuilder/.cache/synthtool/elixir-google-api/clients were copied. Does the source contain files?
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 102, in <module>
    main()
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 94, in main
    spec.loader.exec_module(synth_module)  # type: ignore
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 180, in __exit__
    write(self.metadata_file_path)
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 112, in write
    with open(outfile, "w") as fh:
FileNotFoundError: [Errno 2] No such file or directory: 'clients/apps_activity/synth.metadata'
2020-05-11 15:05:16 [ERROR] Synthesis failed
2020-05-11 15:05:16,048 autosynth > Synthesis failed
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 599, in <module>
    main()
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 471, in main
    return _inner_main(temp_dir)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 549, in _inner_main
    ).synthesize(base_synth_log_path)
  File "/tmpfs/src/github/synthtool/autosynth/synthesizer.py", line 118, in synthesize
    synth_proc.check_returncode()  # Raise an exception.
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/subprocess.py", line 389, in check_returncode
    self.stderr)
subprocess.CalledProcessError: Command '['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--', 'AppsActivity']' returned non-zero exit status 1.

Google internal developers can see the full log here.

Autosynth is still having trouble generating AppsActivity. :sob:
Here's the output from running synth.py:
2020-05-12 05:04:55 [INFO] logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
2020-05-12 05:04:55,994 autosynth > logs will be written to: /tmpfs/src/github/synthtool/logs/googleapis/elixir-google-api
Switched to branch 'autosynth-appsactivity'
2020-05-12 05:04:57 [INFO] Running synthtool
2020-05-12 05:04:57,515 autosynth > Running synthtool
2020-05-12 05:04:57 [INFO] ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-12 05:04:57,515 autosynth > ['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--']
2020-05-12 05:04:57,733 synthtool > Executing /home/kbuilder/.cache/synthtool/elixir-google-api/synth.py.
On branch autosynth-appsactivity
nothing to commit, working tree clean
2020-05-12 05:04:57,895 synthtool > Cloning https://github.com/googleapis/elixir-google-api.git.
2020-05-12 05:04:58,426 synthtool > Running: docker run --rm -v/home/kbuilder/.cache/synthtool/elixir-google-api:/workspace -v/var/run/docker.sock:/var/run/docker.sock -e USER_GROUP=1000:1000 -w /workspace gcr.io/cloud-devrel-public-resources/elixir19 scripts/generate_client.sh AppsActivity
/workspace /workspace
The mix.lock file was generated with a newer version of Hex. Update your client by running `mix local.hex` to avoid losing data.
Resolving Hex dependencies...
Dependency resolution completed:
Unchanged:
  certifi 2.5.1
  google_api_discovery 0.7.0
  google_gax 0.3.2
  hackney 1.15.2
  idna 6.0.0
  jason 1.2.0
  metrics 1.0.1
  mime 1.3.1
  mimerl 1.2.0
  oauth2 0.9.4
  parse_trans 3.3.0
  poison 3.1.0
  ssl_verify_fun 1.1.5
  temp 0.4.7
  tesla 1.3.3
  unicode_util_compat 0.4.1
A new Hex version is available (0.20.1 < 0.20.5), please update with `mix local.hex`
All dependencies are up to date
The mix.lock file was generated with a newer version of Hex. Update your client by running `mix local.hex` to avoid losing data.

12:05:01.913 [info]  FETCHING: https://www.googleapis.com/discovery/v1/apis/appsactivity/v1/rest

12:05:02.060 [info]  FOUND: https://www.googleapis.com/discovery/v1/apis/appsactivity/v1/rest
Revision check: old=20200428, new=20200428, generating=true
Creating leading directories
Writing Activity to clients/apps_activity/lib/google_api/apps_activity/v1/model/activity.ex.
Writing Event to clients/apps_activity/lib/google_api/apps_activity/v1/model/event.ex.
Writing ListActivitiesResponse to clients/apps_activity/lib/google_api/apps_activity/v1/model/list_activities_response.ex.
Writing Move to clients/apps_activity/lib/google_api/apps_activity/v1/model/move.ex.
Writing Parent to clients/apps_activity/lib/google_api/apps_activity/v1/model/parent.ex.
Writing Permission to clients/apps_activity/lib/google_api/apps_activity/v1/model/permission.ex.
Writing PermissionChange to clients/apps_activity/lib/google_api/apps_activity/v1/model/permission_change.ex.
Writing Photo to clients/apps_activity/lib/google_api/apps_activity/v1/model/photo.ex.
Writing Rename to clients/apps_activity/lib/google_api/apps_activity/v1/model/rename.ex.
Writing Target to clients/apps_activity/lib/google_api/apps_activity/v1/model/target.ex.
Writing User to clients/apps_activity/lib/google_api/apps_activity/v1/model/user.ex.
Writing Activities to clients/apps_activity/lib/google_api/apps_activity/v1/api/activities.ex.
Writing connection.ex.
Writing metadata.ex.
Writing mix.exs
Writing README.md
Writing LICENSE
Writing .gitignore
Writing config/config.exs
Writing test/test_helper.exs
fixing file permissions
2020-05-12 05:05:02,978 synthtool > No files in sources /home/kbuilder/.cache/synthtool/elixir-google-api/clients were copied. Does the source contain files?
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 102, in <module>
    main()
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/tmpfs/src/github/synthtool/env/lib/python3.6/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/tmpfs/src/github/synthtool/synthtool/__main__.py", line 94, in main
    spec.loader.exec_module(synth_module)  # type: ignore
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 180, in __exit__
    write(self.metadata_file_path)
  File "/tmpfs/src/github/synthtool/synthtool/metadata.py", line 112, in write
    with open(outfile, "w") as fh:
FileNotFoundError: [Errno 2] No such file or directory: 'clients/apps_activity/synth.metadata'
2020-05-12 05:05:03 [ERROR] Synthesis failed
2020-05-12 05:05:03,011 autosynth > Synthesis failed
Traceback (most recent call last):
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 599, in <module>
    main()
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 471, in main
    return _inner_main(temp_dir)
  File "/tmpfs/src/github/synthtool/autosynth/synth.py", line 549, in _inner_main
    ).synthesize(base_synth_log_path)
  File "/tmpfs/src/github/synthtool/autosynth/synthesizer.py", line 118, in synthesize
    synth_proc.check_returncode()  # Raise an exception.
  File "/home/kbuilder/.pyenv/versions/3.6.9/lib/python3.6/subprocess.py", line 389, in check_returncode
    self.stderr)
subprocess.CalledProcessError: Command '['/tmpfs/src/github/synthtool/env/bin/python3', '-m', 'synthtool', '--metadata', 'clients/apps_activity/synth.metadata', 'synth.py', '--', 'AppsActivity']' returned non-zero exit status 1.

Google internal developers can see the full log here.

Autosynth passed, closing! :green_heart: