Update relative file paths in fetched remarks

The relative file paths, in the asciidoctor of the remarks extracted by lutaml from expressir, need to be updated to reflect the calling environment. So:
[lutaml, ../../../resources/action_schema/action_schema.exp, repo]
is fetching a line containing:
image::action_schemaexpg1.xml[]
Something needs to update that URL, so that the expression reads: image::../../../resources/action_schema/action_schemaexpg1.xml[]
This means:

For all relative file paths in asciidoctor source

Prefix the file path with the path of the Lutaml file

If the relative path is, say, ../../x, it would turn into ../../../resources/action_schema/../../x
You must not update absolute paths, which are recognised as follows:
^[^/:]+://|^[A-Z]:/ (e.g. file:///, http://, c:/)
The paths to be so updated are:

\blink:{path}\[ e.g.  link:downloads/report.pdf[Get Report]; see https://docs.asciidoctor.org/asciidoc/latest/macros/link-macro/
\bimage:{path}\[ e.g. image:pause.png[title="Pause"]; see https://docs.asciidoctor.org/asciidoc/latest/macros/images/
\bvideo:{path}\[ e.g. video::video_file.mp4[]; see https://docs.asciidoctor.org/asciidoc/latest/macros/audio-and-video/
\baudio:{path}\[ e.g. audio::video_file.mp4[]; see https://docs.asciidoctor.org/asciidoc/latest/macros/audio-and-video/
\binclude:{path}\[ e.g. include::sales/2016/results.csv[]; see https://docs.asciidoctor.org/asciidoc/latest/directives/include/

So, in sum:
\b(link|image|video|audio|include)(?![^/:]+://|[A-Z]:/)(?<link>[^\[]+)\[
I am ignoring icon:[] macros, since they are assumed to be fixed to one directory for an asciidoc document (https://docs.asciidoctor.org/asciidoc/latest/macros/icons/), and we don't process them currently anyway.
I am ignoring the link attribute of images, because that would be extremely difficult to deal with via regexes, and because that is assumed to be an absolute link by default anyway.

The relative file paths, in the asciidoctor of the remarks extracted by lutaml from expressir, need to be updated to reflect the calling environment. So:
[lutaml, ../../../resources/action_schema/action_schema.exp, repo]
is fetching a line containing:
image::action_schemaexpg1.xml[]
Something needs to update that URL, so that the expression reads: image::../../../resources/action_schema/action_schemaexpg1.xml[]

Wouldn't it be better to allow the user to have the image::... path manually specified to the path they want?
Imagine that you have a different source path for images that is separate from the schema path.

The relative file paths, in the asciidoctor of the remarks extracted by lutaml from expressir, need to be updated to reflect the calling environment. So:
[lutaml, ../../../resources/action_schema/action_schema.exp, repo]
is fetching a line containing:
image::action_schemaexpg1.xml[]
Something needs to update that URL, so that the expression reads: image::../../../resources/action_schema/action_schemaexpg1.xml[]

Wouldn't it be better to allow the user to have the image::... path manually specified to the path they want?
Imagine that you have a different source path for images that is separate from the schema path.

So a separate assets directory variable?
The only way that would be acceptable is as a separate and optional parameter to the lutaml macro. The behaviour implemented is fully appropriate as a default.

So a separate assets directory variable?
The only way that would be acceptable is as a separate and optional parameter to the lutaml macro. The behaviour implemented is fully appropriate as a default.

For now, we are addressing this by using absolute paths, when we iterate through multiple schemas. Highly desirable to make them relative paths relative to the embedding document, so that the document can stay portable. This only impacts the asciidoc; we are using data uri encoding for the XML output.


Allow rds Instance as a parameter

Huge thanks for this tool!!
any chance to allow --rds-instance as a parameter ?
Thanks

Good question! I need to update the docs, because this already works. You can run rdsconn proxy <instance> and it will do what you want 👍


[RuntimeError: CUDA error: an illegal memory access was encountered] in Azure ML

Prerequisite

[X] I have searched Issues and Discussions but cannot get the expected help.
[X] I have read the FAQ documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version (master) or latest version (3.x).

Task
I have modified the scripts/configs, or I'm working on my own tasks/models/datasets.
Branch
master branch https://github.com/open-mmlab/mmdetection
Environment
/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/init.py:20: UserWarning: On January 1, 2023, MMCV will release v2.0.0, in which it will remove components related to the training process and add a data transformation module. In addition, it will rename the package names mmcv to mmcv-lite and mmcv-full to mmcv. See https://github.com/open-mmlab/mmcv/blob/master/docs/en/compatibility.md for more details.
warnings.warn(
fatal: not a git repository (or any parent up to mount point /mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
sys.platform: linux
Python: 3.8.0 (default, Nov  6 2019, 21:49:08) [GCC 7.3.0]
CUDA available: True
GPU 0: Tesla K80
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.3, V11.3.109
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.12.1
PyTorch compiling details: PyTorch built with:

GCC 9.3
C++ Version: 201402
Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815)
OpenMP 201511 (a.k.a. OpenMP 4.5)
LAPACK is enabled (usually provided by MKL)
NNPACK is enabled
CPU capability usage: AVX2
CUDA Runtime 11.3
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37
CuDNN 8.3.2  (built against CUDA 11.5)
Magma 2.5.2
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.13.1
OpenCV: 4.7.0
MMCV: 1.7.1
MMCV Compiler: GCC 9.3
MMCV CUDA Compiler: 11.3
MMDetection: 2.28.1+
Reproduces the problem - code sample
import torch, torchvision
import mmcv
from mmcv.runner import load_checkpoint
from mmdet.apis import inference_detector, show_result_pyplot
from mmdet.models import build_detector
from mmcv import Config
cfg = Config.fromfile('mmdetection/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py')
import copy
import os.path as osp
import json
import numpy as np
from mmdet.datasets.builder import DATASETS
from mmdet.datasets.custom import CustomDataset
from mmdet.datasets import build_dataset
from mmdet.apis import train_detector
import os
@DATASETS.register_module()
class TractorDataset(CustomDataset):
CLASSES = ('1','2')
def load_annotations(self, ann_file):
cat2label = {k: i for i, k in enumerate(self.CLASSES)}
with open(self.ann_file, 'r') as f:
anno = json.load(f)
# load image list from file
image_list = anno['images']
data_infos = []
# convert annotations to middle format
for image_id in image_list:
# load annotations
id=image_id['id']
filename = image_id['file_name']
#image = mmcv.imread(filename)
height, width = image_id['height'], image_id['width']
    data_info = dict(filename=filename, width=width, height=height)

    gt_bboxes = []
    gt_labels = []

    for bbox_id in anno['annotations']:
        bbox_img_id=bbox_id['image_id']
        if bbox_img_id==id:
          bbox=bbox_id['bbox']
          label=bbox_id['category_id']
          gt_bboxes.append(bbox)
          gt_labels.append(label)

    data_anno = dict(bboxes=np.array(gt_bboxes, dtype=np.float32).reshape(-1, 4),
        labels=np.array(gt_labels, dtype=np.long))

    data_info.update(ann=data_anno)
    data_infos.append(data_info)

return data_infos

from mmdet.apis import set_random_seed
cfg.dataset_type = 'TractorDataset'
cfg.data_root = ''
cfg.data.test.type = 'TractorDataset'
cfg.data.test.data_root = ''
cfg.data.test.ann_file = 'test/_annotations.coco.json'
cfg.data.test.img_prefix = 'test/'
cfg.data.train.type = 'TractorDataset'
cfg.data.train.data_root = ''
cfg.data.train.ann_file = 'train/_annotations.coco.json'
cfg.data.train.img_prefix = 'train/'
cfg.data.val.type = 'TractorDataset'
cfg.data.val.data_root = ''
cfg.data.val.ann_file = 'test/_annotations.coco.json'
cfg.data.val.img_prefix = 'test/'
cfg.model.roi_head.bbox_head.num_classes = 2
cfg.load_from = 'mmdetection/checkpoints/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth'
cfg.work_dir = './tractor'
cfg.optimizer.lr = 0.02 / 8
cfg.lr_config.warmup = None
cfg.log_config.interval = 10
cfg.evaluation.metric = 'mAP'
cfg.evaluation.interval = 4
cfg.checkpoint_config.interval = 12
cfg.seed = 0
set_random_seed(0, deterministic=False)
cfg.device = 'cuda'
cfg.gpu_ids = [0]
cfg.runner=dict(type='EpochBasedRunner', max_epochs=24)
datasets = [build_dataset(cfg.data.train)]
model = build_detector(cfg.model)
model.CLASSES = datasets[0].CLASSES
mmcv.mkdir_or_exist(osp.abspath(cfg.work_dir))
cfg.dump(os.path.join(cfg.work_dir,'config.py'))
train_detector(model, datasets, cfg, distributed=False, validate=True)
Reproduces the problem - command or script
python train.py
Reproduces the problem - error message
/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/init.py:20: UserWarning: On January 1, 2023, MMCV will release v2.0.0, in which it will remove components related to the training process and add a data transformation module. In addition, it will rename the package names mmcv to mmcv-lite and mmcv-full to mmcv. See https://github.com/open-mmlab/mmcv/blob/master/docs/en/compatibility.md for more details.
warnings.warn(
train-backup.py:56: DeprecationWarning: np.long is a deprecated alias for np.compat.long. To silence this warning, use np.compat.long by itself. In the likely event your code does not need to work on Python 2 you can use the builtin int for which np.compat.long is itself an alias. Doing this will not modify any behaviour and is safe. When replacing np.long, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
labels=np.array(gt_labels, dtype=np.long))
/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/datasets/custom.py:181: UserWarning: CustomDataset does not support filtering empty gt images.
warnings.warn(
2023-02-02 10:31:51,727 - mmdet - INFO - Automatic scaling of learning rate (LR) has been disabled.
2023-02-02 10:31:51,884 - mmdet - INFO - load checkpoint from local path: mmdetection/checkpoints/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth
2023-02-02 10:31:59,273 - mmdet - WARNING - The model and loaded state dict do not match exactly
size mismatch for roi_head.bbox_head.fc_cls.weight: copying a param with shape torch.Size([81, 1024]) from checkpoint, the shape in current model is torch.Size([3, 1024]).
size mismatch for roi_head.bbox_head.fc_cls.bias: copying a param with shape torch.Size([81]) from checkpoint, the shape in current model is torch.Size([3]).
size mismatch for roi_head.bbox_head.fc_reg.weight: copying a param with shape torch.Size([320, 1024]) from checkpoint, the shape in current model is torch.Size([8, 1024]).
size mismatch for roi_head.bbox_head.fc_reg.bias: copying a param with shape torch.Size([320]) from checkpoint, the shape in current model is torch.Size([8]).
2023-02-02 10:31:59,274 - mmdet - INFO - Start running, host: azureuser@naren-gpu, work_dir: /mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/tractor
2023-02-02 10:31:59,274 - mmdet - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH   ) StepLrUpdaterHook
(NORMAL      ) CheckpointHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_train_epoch:
(VERY_HIGH   ) StepLrUpdaterHook
(NORMAL      ) NumClassCheckHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_train_iter:
(VERY_HIGH   ) StepLrUpdaterHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
after_train_iter:
(ABOVE_NORMAL) OptimizerHook
(NORMAL      ) CheckpointHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
after_train_epoch:
(NORMAL      ) CheckpointHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_val_epoch:
(NORMAL      ) NumClassCheckHook
(LOW         ) IterTimerHook
(VERY_LOW    ) TextLoggerHook
before_val_iter:
(LOW         ) IterTimerHook
after_val_iter:
(LOW         ) IterTimerHook
after_val_epoch:
(VERY_LOW    ) TextLoggerHook
after_run:
(VERY_LOW    ) TextLoggerHook
2023-02-02 10:31:59,274 - mmdet - INFO - workflow: [('train', 1)], max: 24 epochs
2023-02-02 10:31:59,275 - mmdet - INFO - Checkpoints will be saved to /mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/tractor by HardDiskBackend.
Traceback (most recent call last):
File "train-backup.py", line 130, in
train_detector(model, datasets, cfg, distributed=False, validate=True)
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/apis/train.py", line 246, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 53, in train
self.run_iter(data_batch, train_mode=True, **kwargs)
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 31, in run_iter
outputs = self.model.train_step(data_batch, self.optimizer,
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 77, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/detectors/base.py", line 248, in train_step
losses = self(**data)
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/runner/fp16_utils.py", line 119, in new_func
return old_func(*args, **kwargs)
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/detectors/base.py", line 172, in forward
return self.forward_train(img, img_metas, **kwargs)
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/detectors/two_stage.py", line 135, in forward_train
rpn_losses, proposal_list = self.rpn_head.forward_train(
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/dense_heads/base_dense_head.py", line 335, in forward_train
losses = self.loss(*loss_inputs, gt_bboxes_ignore=gt_bboxes_ignore)
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/dense_heads/rpn_head.py", line 93, in loss
losses = super(RPNHead, self).loss(
File "/anaconda/envs/mmdet_en2/lib/python3.8/site-packages/mmcv/runner/fp16_utils.py", line 208, in new_func
return old_func(*args, **kwargs)
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/dense_heads/anchor_head.py", line 483, in loss
anchor_list, valid_flag_list = self.get_anchors(
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/models/dense_heads/anchor_head.py", line 188, in get_anchors
multi_level_anchors = self.prior_generator.grid_priors(
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/core/anchor/anchor_generator.py", line 236, in grid_priors
anchors = self.single_level_grid_priors(
File "/mnt/resource/batch/tasks/shared/LS_root/mounts/clusters/naren-gpu/code/Users/narendradas.t/Object Detection/mmdetection files/mmdetection/mmdet/core/anchor/anchor_generator.py", line 263, in single_level_grid_priors
base_anchors = self.base_anchors[level_idx].to(device).to(dtype)
RuntimeError: CUDA error: an illegal memory access was encountered
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Aborted (core dumped)
Additional information
For some reason the model trains on google colab(even though the results are bad).
But on azure ml it fails even with a GPU.
even while using mmdetection/tools/train.py with a different config.py it fails.
Is this just a CUDA out of memory issue?
The images in my dataset are 640X320 in shape. So I dont think its CUDA out of memory error.

CUDA errors can be caused by many different reasons. If the code is trainable on Colab but failed on Azure, please check the environment and make sure the mmcv version, pytorch version, cuda version, and gpu driver version are matched.

This is the COLAB environment. Can you please tell what difference is causing the error.
sys.platform: linux
Python: 3.8.10 (default, Nov 14 2022, 12:59:47) [GCC 9.4.0]
CUDA available: True
GPU 0: Tesla T4
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.2, V11.2.152
GCC: x86_64-linux-gnu-gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.13.1+cu116
PyTorch compiling details: PyTorch built with:

GCC 9.3
C++ Version: 201402
Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815)
OpenMP 201511 (a.k.a. OpenMP 4.5)
LAPACK is enabled (usually provided by MKL)
NNPACK is enabled
CPU capability usage: AVX2
CUDA Runtime 11.6
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
CuDNN 8.3.2  (built against CUDA 11.5)
Magma 2.6.1
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.6, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.14.1+cu116
OpenCV: 4.6.0
MMCV: 1.7.1
MMCV Compiler: GCC 9.3
MMCV CUDA Compiler: 11.6
MMDetection: 2.28.1+c14dd6c

There are many differences between these two environments, such as GPU type, cuda version, and pytorch version.
I'm not sure what caused this problem because I have no experience with Azure ML before. I suggest you use the same the same pytorch and cuda version with colab to see whether it is trainable.


Need better demo gif

Still not sure what the best way would be to create a demo gif.
The current one's resolution is too low, but it is already at github's max size for file uploads...
Suggestions welcome!

The new gif must show the different plotting modes as well!

@rjlopez2 if you find some time and motivation your help would be highly appreciated!

Absolutely 👍
I had already some ideas on this front as well, I just need to have the time LOL but I think i need to think it trough fist.
I found a lot of inspiration in the many gif shown as "quick tutorial" by the many plugins from Robert Hasse.
Yet, I don't know what tools or compression they do the images but they look kinda of acceptable.
If we found a good compromise in quality and size of the gif(s), I was thinking on including additional gifs showing how to work the different plotting modes and paginated nicely with the current documentation (you did a nice work on this btw).
I will come with some ideas soon.
Cheers!

The resent version (v0.0.6) brought new improved gifs. I think they are sufficient. Thus, I will close this as resolved.


It's a convention, see https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Statements/const#basic_const_usage


[WFLY-17991] / [WFLY-17976] ee-security should depend on elytron and ensure the JACC policy is enabled by default.

https://issues.redhat.com/browse/WFLY-17991
https://issues.redhat.com/browse/WFLY-17976

@darranl Failures seem to be related.

Hopefully that fix does it.
One thing I have noticed I am sure we used to fail earlier but a lot of tests now are just ignoring set up failures and ploughing  on so we end up with a cryptic test failure after the set up failed rather than an error reporting what went wrong during set up so we can jump straight to the point that needs a fix.

Added ready-for-merge label as this has two reviews and CI is now green.


The Zenodo link is invalid

Hi, the zenodo link in the readme is invalid. Could you fix that? Thanks.

It should be working now. Sorry for the late replay


Update UXP coingecko and cmc ids. Removes the tags.

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#2566


Coerce fails with string colspec

Coerce fails with string colspec   issue #194  fixing
-->  Added extra line in coerce.jl for string implementation

yes sure , I will work on that

Feel free to merge.
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https://github.com/JuliaML/TableTransforms.jl/pull/196 Coerce fails
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Thank you @Jay-sanjay ! Feel free to pick another one. We can guide you with tips and suggestions.


Sandbox api calls not matching io interface

The Sandbox trait in the io crate recently changed from static functions to methods that take a self argument.
The sandbox module which uses the the io Sandbox interface is still calling with static functions sandbox/without_std.rs#L253.
I'm not that confident this is a problem - I don't fully understand how these pieces fit together. But when I add the contracts module as a dependency to a substrate-node-template, sp-sandbox fails to compile because of a mismatch of the interface mentioned above.

Hey, the Sandbox trait is annotated with the attribute #[runtime_interface]. This is a macro and very simplified it generates a static function per method declared in the trait.(the self parameter ja stripped out)
Could you please give a link to a git repo that contains your code?

Ok that makes sense, turns out this is just caused by not first running ./scripts/init.sh.


PDF2 pagination: Map type determination

#2335, root-processing.xsl
$mapType currently has two values: 'bookmap' or 'ditamap'.
There is actually a third possibility which could be either 'noMap' or 'topicOnly'.
If this third option is recognised, it might be useful for processing topics to PDF.
It should, at least, make it easier to follow the logic.

I can see how this might be useful. A new value would not cause the default processing to change in any way with today's code, though it's possible that a customization expecting only the current values bookmap and ditamap could fail when a new value is presented.
I think a value for topic as input would just be topic. This would also match the $mapType variable in the ODT code, though the ODT code is in no way a shining example of best practices.


Python Bindings

It would be helpful to have Python bindings/wrapper.
I might end up doing this eventually myself; would you prefer I keep the bindings in my own personal project, or contribute them back to BinExport?

Forked it to a new project.

I've put the files over here.
https://github.com/Manouchehri/radare2-binexport2


fix(#330): use owner ref / field selector for env

Fixes behaviour which might cause Gefyra to select a pod which actually does not belong to a deployment or statefulset. Instead of label_selectors it now works with a field_selector which leverages the owner reference / uuid of the deployment/ statefulset.
Signed-off-by: Robert Stein<EMAIL_ADDRESS>

Turns out this does not work. The field selector is limited to specific fields:
https://github.com/kubernetes/kubernetes/blob/9d577d8a29893062dfbd669997396dbd01ab0e47/pkg/apis/core/v1/conversion.go#L33
"metadata.name",
"metadata.namespace",
"spec.nodeName",
"spec.restartPolicy",
"spec.schedulerName",
"spec.serviceAccountName",
"status.phase",
"status.podIP",
"status.podIPs",
"status.nominatedNodeName"


feat(ModelTheory/Equivalence): Implication of formulas modulo a theory

Defines FirstOrder.Language.Theory.Implies: φ ⟹[T] ψ indicates that φ implies ψ in models of T.
Relates Theory.Implies to Theory.SemanticallyEquivalent.
Proves lemmas that will set up a BooleanAlgebra instance on formulas modulo a theory

[x] depends on: #16799

I don't quite like how the following square is looking:
Implies/Imp | Language.Theory.Implies
Iff | Language.Theory.SemanticallyEquivalent
What do you think of renaming the right column so that it looks more consistent? Here are a few suggestions (all in the Language.Theory namespace):

SemanticallyImplies, SemanticallyEquivalent
SemanticImp, SemanticIff
Imp, Iff

I agree that making these match makes sense - I think it should be down to the last two options, so the question is just whether to specify Semantic. The reason for doing this is because I hope that at some point, it would be good to have a first-order proof system, and in that case, there's a distinction between a theory modelling an implication/equivalence and the theory proving it. These turn out to be the same, of course, because of the completeness theorem, so it's just a question of which should be the definition of Theory.Imp and Theory.Iff. At the moment, I'd say I over-futureproofed SemanticallyEquivalent, so probably this should just be Imp and Iff.

I'll let you make the final call. It's easy enough to rename the predicate later (and probably we won't need deprecations since you are currently the sole downstream user of this material)

I've finally gone and used the simplest possible choice on the names. Hopefully I've capitalized (or uncapitalized) the names of lemmas appropriately.

maintainer merge


Avoid creating multiple assessments when user navigates back.

This PR:

Keeps track of the newly created assessmentId on the first page of assessments (either CovidTestScreen or HealthWorkerExposureScreen)

This avoids creating new assessments whenever the user navigates back to the first page. Instead the existing one will be patched.

Is this PR still required? Feel as though some of the changes have since been duplicated and merged?

@abubuwe I'll investigate now if it's still required.

Is this PR still required? Feel as though some of the changes have since been duplicated and merged?

@abubuwe To follow up, none of the recent changes affected this issue (other than the fact that there is now a third potential start screen- level of isolation), so this PR stands. However, I wanted to check that the assessments are correctly updated on the backend before merging this, and I'm still waiting for necessary permissions to do so. I will update here when I can.

I've now checked and the assessments are updated correctly on the backend, so happy to merge when newly approved.


User Group Filter

Good day Team,
I'm trying to display specific data for users in a user group, I found the code below on a forum post from 2 years ago but it doesn't seem to work now.

  Test Group
  {% for group in user.groups %}
      {% if group.name == 'development' %}

u are development user

      {% endif %}
  {% endfor %}

Can you help me with the correct code please?

Hi @NielsvandenDries
This code looks fine. It is not obvious from this post why it doesn't work.
The GitHub issue list is for reporting bugs in the October CMS code base specifically. Please try the following support avenues for getting support with using October:

Stack Overflow
October CMS Forum
October CMS Documentation

Thank you

I got it working, it's strange that the value below
value {% if group.name == 'development' %}
is based on the label of the group and not the code of the group.
You would actually say that the Code is a static value and the label a dynamic value, so it seems more logical to me that it is based on the code rather than the label.

Oke i discovered that i can do:
{% if group.code == 'development' %}
and
{% if group.id == '7' %}
aswel..


Publisher/subscriber example does not work

Steps:
1- I opened a DAPR app on a given grpc port. The console shows that the Dapr is up and running.
2- Start the subscriber example in the elevated mode, and set the port to the sane one that Dapr is running at. The server will start fine. I noticed that it won't run in debug mode as it will not run in the elevated mode
3- Start the subscriber example. It will run fine. However, subscribers are not triggered upon publish events.
Expected Results:
Subscribers must be triggered upon publish events
Additional Notes
The client example works fine, which indicates that the Dapr at least is operating as expected.
Operating System:
Windows 11

It's working for me after change it  to <IP_ADDRESS>:50051.
https://github.com/dapr/rust-sdk/blob/4cf17de437fa2e4ee891ea9e879055236110f705/examples/pubsub/subscriber.rs#L73

I don't have access to a Windows machine right now, but is IPv6 enabled/disabled?
I wondered whether [::] (all hosts) is only available when the IPv6 stack is enabled.
Is it any better when using [::1] (local host - which should also include for IPv4 interfaces but that could depend on the OS). In an example, localhost would probably be fine, but might be a bit misleading when implementing across network (eg: the dapr side car running on another host than the dapr app).

Also @seekeramento, do you see any sign of the subscriber app register with daprd?
Would you be able to share the output?
Another bit of useful output would be to see which interfaces are listening on TCP/50051.
From memory, something like netstat -an -p tcp | find "50051". From that should should see whether it is indeed listening on only IPv4 or IPv4 interfaces, or both (when set to [::]:50051.
IMO, the examples should probably get the host and port from the environment, as I believe if run via dapr run, the application should see DAPR_GRPC_HOST and DAPR_GRPC_PORT set.
Here's how I've been doing it (granted, there might be a cleaner way):
const DAPR_GRPC_HOST_VAR: &str = "DAPR_GRPC_HOST";
const DEFAULT_DAPR_GRPC_HOST: &str = "[::1]";

const DAPR_GRPC_PORT_VAR: &str = "DAPR_GRPC_PORT";
const DEFAULT_DAPR_GRPC_PORT: &str = "50001";

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    ...

    // Figure out host:port to listen on, or fall back to const defaults
    let host = env::var(DAPR_GRPC_HOST_VAR).unwrap_or_else(|_| DEFAULT_DAPR_GRPC_HOST.to_owned());
    let port = env::var(DAPR_GRPC_PORT_VAR)
        .unwrap_or_else(|_| DEFAULT_DAPR_GRPC_PORT.to_owned())
        .parse::<u32>()
        .map_err(|e| anyhow!("unable to parse environment variable {DAPR_GRPC_PORT_VAR}: {e}"))?;

    let addr: SocketAddr = format!("{host}:{port}").parse().unwrap();
    let addr = format!("https://{addr}");

    tracing::info!(
        address = addr.to_string(),
        "connecting to dapr grpc server..."
    );

    let mut client = dapr::Client::<dapr::client::TonicClient>::connect(addr).await?;

   ...
}

I was able to get this to work after downgrading my Tonic crate to being the same as the sdk's (~0.8 at time of writing), and making sure that I ran  dapr run with --app-protocol grpc since dapr defaults to http. Hope this helps future posters

Closing as stale


Adding name changer and floating name

This just lets you set the name you want to be above the player model


Optimize querying bitemporal model for larger data sets

Such as with numexpr

Optimized with numba through the index.


I think there are serious privacy issues with this extension: No deletion, no public sharing consents!

This service desperately needs a function to delete what I shared. And it should ask for permission to make the chat world searchable instead of handing it to everybody without consents of the user!
It is just too easy to accidentally share credentials or private information, and sending DMs to a Twitter account should not be the solution here! It is not mandatory for a user to have a Twitter account in the first place. And I guess that the author also sometimes sleeps or has other things to do than to delete accidentally shared information.
There is no warning, anywhere, that the shared data is world searchable and readable. I thought that one gets a private URL, and I never intended to expose my conversation to more people than those I sent the link to.

I completely agree with you! It's surprising that such a popular tool isn't receiving the proper attention and maintenance it deserves. ShareGPT has become the de facto tool for sharing ChatGPT conversations. It's imperative that more individuals step up as maintainers to ensure its continued success and functionality. It would be great to see this tool receive the support it needs to continue serving the community in the best way possible!

Appreciate the sentiment here – it's definitely a very highly requested feature!
FWIW it's already possible to make a conversation private as per the database schema, what we need to set up is user auth to make sure the conversation is created by the user for them to be able to toggle the privacy settings of the conversation.
Currently I'm storing the session info of the user when the conversation is saved, so if they're logged in on ShareGPT.com, the conversation should be associated with their account, but for some reason this is not working at the moment.
If anyone would like to PR, I'd really appreciate it! 🙏

That you for the answer! I hoped I was not too negative. It's just that I had this "what if?" moment, where I saw how dangerous this can get. Still, one could say that the disclaimer of ChatGPT in itself is already enough to be aware to not share sensitive data. What made me uneasy is especially the possibility to search the database. You can probably easy search for passwords or tokens and other sensitive data, just using some common names. Or for other sensitive data by searching for special topics.
I think you should start by giving the user a warning that the data is world searchable. I also would disable this search until I could get the consent of people. Having the IDs, it seems semi secure already, as they seem hard to guess. But I did not look at the code, but I am certain that if they are not yet, you can just change their shape to make them merely impossible to guess.

FWIW it's already possible to make a conversation private as per the database schema, what we need to set up is user auth to make sure the conversation is created by the user for them to be able to toggle the privacy settings of the conversation.

I guess you could already make two share buttons when creating the entry: "Share public" and  "Share private" or asking one button and asking after pressing share, where you also could present an explanation about the privacy indications.
This way you can store the initial privacy setting already. Later also the creator account, which may also be needed for moderation and deletion of inappropriate data. As I see it, one could add just anything to your database which does not need to come from the plugin at all? I did not check the API that closely, though.
You could also go another way and hand out a "secret" per message, the user can take used to delete this individual conversation. I saw some services doing something like that to not force usage of an account. But people could lose that information and bug you to delete their stuff.
P.S.: About contribution to the project. Sadly, I cannot help with coding because I do not want to develop with JS in my spare time. I am a Go developer in the first place and my private projects tend to be Go related since some years now.

Update: We removed the Explore page on ShareGPT recently so all your conversations are basically private & only accessibly by direct link!
Closing this issue now! :)

@steven-tey Please re-open this topic, you haven't been responding to my messages requesting conversations to be deleted. Please respond asap. This is important.


Changes CSS attributes to CSS properties

Links to authoritative resources:
http://www.w3.org/TR/CSS21/propidx.html
https://developer.mozilla.org/en-US/docs/Web/CSS/Reference
Closes #2106.

@bugron Nice Catch!


[Python] Support serialization of Arrow files on disk without the identifier "Feather"

Describe the enhancement requested
The documentation for Arrow Columnar Format suggests that the separate Feather project has been subsumed into Arrow, and that it (Feather) is really just the canonical serialization format for Arrow tables:

We recommend the “.arrow” extension for files created with this format. Note that files created with this format are sometimes called “Feather V2” or with the “.feather” extension, the name and the extension derived from “Feather (V1)”, which was a proof of concept early in the Arrow project for language-agnostic fast data frame storage for Python (pandas) and R.

The Python support of Arrow serialization still uses the identifier feather: (see the Cookbook)

Once we have a table, it can be written to a Feather File using the functions provided by the pyarrow.feather module
import pyarrow.feather as ft

ft.write_feather(table, 'example.feather')

This functionality should be kept as is, for backwards compatibility, but I wonder if the pyarrow module should just have a write() function, without requiring the need to import the pyarrow.feather package or use the term feather. This would help to reduce confusion about file extensions and the relationship between "Arrow" and "Feather".
Component(s)
Python

See also https://github.com/apache/arrow-cookbook/issues/329


Rebasing .NET SDK To Version 1.31.1 With Instance Failover Group APIs

Description
I have rebased the .Net SDK to 1.13.1 by cherrypicking changes for InstanceFailoverGroup on top of the 1.13.0 branch.
The files are generated by targeting composite v2 APIs. Link to swagger template: https://github.com/ziwa-msft/azure-rest-api-specs/commit/b2b515668c940cceba1a36b732cbf88d19379b8d
We have verified that all tests are passing locally.

This checklist is used to make sure that common guidelines for a pull request are followed.

[ x] Please add REST spec PR link to the SDK PR
[x ] I have read the contribution guidelines.
[ x] The pull request does not introduce breaking changes.

General Guidelines

[x ] Title of the pull request is clear and informative.
[ x] There are a small number of commits, each of which have an informative message. This means that previously merged commits do not appear in the history of the PR. For more information on cleaning up the commits in your PR, see this page.

Testing Guidelines

[ x] Pull request includes test coverage for the included changes.

SDK Generation Guidelines

[x ] If an SDK is being regenerated based on a new swagger spec, a link to the pull request containing these swagger spec changes has been included above.
[x ] The generate.cmd file for the SDK has been updated with the version of AutoRest, as well as the commitid of your swagger spec or link to the swagger spec, used to generate the code.
[x ] The *.csproj and AssemblyInfo.cs files have been updated with the new version of the SDK.

Will merge once CI passes

@ziwa-msft while you are at it, please pull down the latest changes from upstream and run the code generation again (the txt file should not be displayed as a binary on the PR)


Setup distributed tensorflow demo cluster with latest tensorflow + kubernetes

we should use kubernetes etcd for discovering the master, parameter servers (must have at least 2), and worker nodes
https://www.tensorflow.org/versions/r0.11/how_tos/distributed/index.html

@Romits - i will create you a tensorflow distributed cluster here in a bit and send you the credentials

i will setup the following DNS names:
tensorflow-master
tensorflow-ps1, tensorflow-ps2
tensorflow-worker1, tensorflow-worker2

here's a link to the notebook:  https://github.com/fluxcapacitor/pipeline/blob/master/myapps/jupyter/TensorFlow/Fundamentals/Basic-Distributed-TensorFlow.ipynb

we'd like to demo a comparison of single-node vs distributed training on a large dataset (ie. dogs_and_cats dataset)
at some point, the results of both tests should show up in TensorBoard - perhaps using the Amazon EFS to write the summary writer logs to a shared file system to be read by a single TensorBoard instance running on the single master.

Here's a video of Fabrizio's Tensorflow Distributed talk at a recent workshop:  https://www.youtube.com/watch?v=lmYpRzQA5H4

here are slides on distributed tensorflow from a recent meetup (towards the end):  http://www.slideshare.net/cfregly/advanced-spark-and-tensorflow-meetup-may-26-2016

https://github.com/tobegit3hub/deep_recommend_system/tree/master/distributed

Thanks Chris. Currently working on the distributed TensorFlow cluster with 0.11 release.

here's some relevant gists:
https://gist.githubusercontent.com/Mistobaan/29cb95e822523c44b6f3e32eed0c3259/raw/f4d9166358af81c838ffc0657aaf04c64f5963b7/sync_replica.py
https://raw.githubusercontent.com/tensorflow/tensorflow/4c50340c9d7d80366dfca4a1231de394cb1c00a2/tensorflow/tools/dist_test/python/mnist_replica.py
and some relevant scripts:
python tensorflow/tensorflow/tools/dist_test/server/grpc_tensorflow_server.py --cluster_spec=${CLUSTER_SPEC} --job_name=worker --task_id=0 --verbose=True
python tensorflow/tensorflow/tools/dist_test/server/grpc_tensorflow_server.py --cluster_spec=${CLUSTER_SPEC} --job_name=worker --task_id=0 --verbose=True

Distributed Tensorflow cluster is working and the model is currently training for MNIST dataset.

it would be ideal to have the snippet of code specific to the worker (ie. line 43 to line 108) separated out and executed using python's execfile or exec command.
be sure to pass the ENV variables into the exec command somehow.

a question on OpenAI's slack channel:  "I'm wondering how distributed tensorflow works in your kubernetes environment. Is there a layer that handles creating the job, obtaining the ips of the allocated nodes, then using those to launch a distributed tensorflow job?"
@Romits ^^ This is what we're solving. ^^

How is organizing this Intel https://github.com/intel-analytics/BigDL?

@bhack can you clarify your question?  i don't fully understand.  lemme know!

@cfregly Ops sorry I was on another thread. Please ignore it.. but could be interesting to see what Intel it is cooking with DL on Spark ;)

Setup Distributed Tensorboard using HDFS

tensorflow distributed + kubernetes from google tensorflow "ecosystem" project:  https://github.com/tensorflow/ecosystem/tree/master/kubernetes

FYI myself and some folks on the K8s team have been working on improving distributed TF on K8s via a TPR.
https://github.com/jlewi/mlkube.io/
If you think this is a promising approach and have suggestions on how to improve it please let us know. We are currently trying to get feedback from the ML, TF & K8s communities.

https://stackoverflow.com/questions/41067398/task-assignment-in-tensorflow-distributed-process

https://gist.github.com/yaroslavvb/ea1b1bae0a75c4aae593df7eca72d9ca

co-locate PS and Workers in Placement Groups to improve network communication performance

Estimator, Experiment, and RunConfig:
https://github.com/tensorflow/tensor2tensor/blob/master/docs/distributed_training.md
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/learn/python/learn/estimators/run_config.py

Mostly done in this repo.
Moving to Larger Effort with PipelineAI Advanced/Enterprise Edition.


flax_stable: don't crash when clock is not visible

Was accessing startPos while nil

Should that be a "\nVerify" instead of "\Verify"?  Just noticed because GitHub is syntax highlighting it as an error =)

Probably should, but is orthogonal to this change.

Ah, yeah, totally is, sorry =).  Merged.


fix model field instance in readme

In this PR, I prefixed models instance in readme as it should be.

It would only make sense if we want to include the import line and the import line goes like this:
from django.db import models

Because we could also have imported it as:
from django.db.models import CharField

But, yeah, not a big deal anyway.
BTW, there happens to be a conflict.

Yes it is right you might import on this way but you know that following declaration compatible and folksy in general manner especially for readme.
from django.db import models


Handle time source exception

When playing data from a bag I get this error:
terminate called after throwing an instance of 'std::runtime_error'
  what():  can't subtract times with different time sources [1 != 2]
Aborted (core dumped)

In my case this stems from the section of image_transport_display.hpp which computes the topic frequency.
My change catches this exception and makes it a warning on the topic property instead. If approved, I will apply the change to other applicable display interfaces.

Pulls: ros2/rviz#1285
Gist: https://gist.githubusercontent.com/ahcorde/4bd58742fe756b64abe70574694d7abc/raw/e98f6ea463e22f33f6891e3e20be5b24f772ba89/ros2.repos
BUILD args:  --packages-above-and-dependencies rviz_default_plugins --packages-above-and-dependencies rviz_default_plugins
TEST args:  --packages-above rviz_default_plugins --packages-above rviz_default_plugins
ROS Distro: rolling
Job: ci_launcher
ci_launcher ran: https://ci.ros2.org/job/ci_launcher/14686

Linux
Linux-aarch64
Linux-rhel
Windows

Linux
Linux-aarch64
Linux-rhel
Windows


Use migrator with allow_missing_migration_files opt for dump schema

This PR adds allow_missing_migration_files for dump command missed in prev PR.
ref: https://github.com/TalentBox/sequel-rails/pull/172

Hi @artofhuman, thanks for following up on you previous PR.


Revisit @parameterVisibility and @returnVisibility

I'm struggling to understand the new @parameterVisibility and @returnVisibility decorators.
I know that these were introduced to address azure/typespec-azure#3214 (patch operation should define "create" properties in request body). I think the root of that issue is that the http library assumes "patch" is "update" and there was no way to mark a "patch" to say "this is both create and update".
Stepping back, here's what the core docs say about @visibility:

the following visibilities are well-known to standard libraries and should be used with standard emitters that interpret them as follows:

"read": output of any operation.
"create": input to operations that create an entity.
"query": input to operations that read data.
"update": input to operations that update data.
"delete": input to operations that delete data.

This combined with the documentation of Automatic visibility in the HTTP library implies

GET and HEAD requests "read data" -- because "query" visibility is automatically applied.
POST and PUT requests "create an entity" -- because "create" visibility is automatically applied.
PATCH and PUT requests "update data" -- because "update" visibility is automatically applied.
DELETE requests "delete data" -- because "update" visibility is automatically applied.

But the HTTP library provides no means to deviate from this.  I think what is missing is the ability to characterize an operation deviates from the above assumptions. PATCH that is "createOrUpdate" is a great example, but another common one is POST that does not "create an entity".
A decorator implemented in the HTTP library (could also be in core I suppose), say @operationType that could specify some combination of "create", "query", "update", or "delete" could fill this gap. The a PATCH operation that allows "create" or "update" could be defined with
@operationType("create", "update")
@patch op createOrUpdate(...Widget): Widget | Error;

and the HTTP library or downstream emitter could then "do the right thing".

It looks like @markcowl suggested something similar here


Upgrade Typescript and VScode versions used in the module.

Update the module use latest versions of Typescript and vscode engine
Adding support for multiple folders in a workspace to run tests without
any issues. Current release breaks.
Replace some of the regex used to generate paths with some of the vscode
provider API's

Hey, I'll have a look at this as soon as I get some time. Just looked over the changes and they seem fine but I'll test them also and then publish a new version to the marketplace if everything seems fine. Thanks for the PR! =)
Didn't know it broke for multiple projects in one workspace, haven't had that myself so far.

Cool thanks, 👍


refactor: add async await to populateTransaction call

Description:
This PR refactors the populateTransaction call in WalletIntegrationTest.js to use async/await for better readability and asynchronous handling.

Replace promise-based pattern with async/await in populateTransaction call
Ensure all tests pass post-refactoring
Maintain existing logic and functionality
Improve code clarity and maintainability

Notes for reviewer:
Please verify the changes do not alter the behavior of populateTransaction and check that all tests are still passing.
Checklist

[ ] Documented (Code comments, README, etc.)
[ ] Tested (unit, integration, etc.)

@IgorShadurin, you didn't sign your commit. See here how to do it.


"Segmentation fault (core dumped)" when executing "orca --help"

I am using Ubuntu 18.04. I need to install orca in Ubuntu.
After I downloaded: orca-1.2.1-x86_64.AppImage, into the Downloads directory, I performed the following commands:
sudo chmod +x orca-1.2.1-x86_64.AppImage
ln -s /home/e/Downloads/orca-1.2.1-x86_64.AppImage /home/me/.local/lib/python3.6/site-packages/orca

But when I execute:
which orca
I do not find anything printed in the terminal. But there is a file named orca created at the /home/me/.local/lib/python3.6/site-packages/
Then when I execute: orca --help, I get:
Segmentation fault (core dumped)
Can you please help me identify the problem?

Now it is partially working. It turns that first I have to find the right PATH value by executing:
echo $PATH  It may be helpful if you can add this in the instructions.
But now, when I execute:
orca --help
I get:
Gtk-Message: 11:58:45.142: Failed to load module "canberra-gtk-module"
Plotly's image-exporting utilities

  Usage: orca [--version] [--help] <command> [<args>]
....

Any idea what should be done here?

@ealashwali Can you try installing all the dependencies?


[Help wanted] Support Flutter

Could this possible using ffi ?
Ex : https://pub.dev/packages/onnxruntime

@flutter-painter I have already implemented this, was planning to open source it eventually but haven't got it around to it just yet. Send me an e-mail if you'd like.

Hi @nmfisher,
Wonderful news,
I just sent an email,
Here is fine as well in case other aficionados wanna hop-in :)

Hi
Did you manage to make it happen?

Almost, nick's repo is clear and his guidelines are complete.
I just need to build Onnx Runtime...
@nmfisher how about opening it as is ?

Let me know if I can help 🙂

also very interested in this- i have some flutter experience to test/help

@csukuangfj Am I right that the c-api only supports desktop platforms? I've tried porting your library over to Flutter today with ffi (https://docs.flutter.dev/platform-integration/android/c-interop) combined with ffigen (https://pub.dev/packages/ffigen).
I haven't pushed all my local changes because I haven't gotten it to work yet, but you can see the generated bindings here: https://github.com/BrutalCoding/aub.ai/blob/b16f7e5f9d317d83b38a5814afb1556c8de8a3d3/lib/aub_ai_bindings_generated.dart
I ran your the android build script for arm64-v8a successfully and they work fine when I'm using your native Android example apps. I can't get it to work in Flutter yet and would like some guidance.
Tree struc of aub.ai (not pushed to my repo, I'm trying to get it working locally first):
aub.ai/android/src/main/jniLibs/arm64-v8a
├── libcargs.so
├── libespeak-ng.so
├── libkaldi-decoder-core.so
├── libkaldi-native-fbank-core.so
├── libonnxruntime.so
├── libpiper_phonemize.so
├── libsherpa-onnx-c-api.so <- I tried with and without the C API.
├── libsherpa-onnx-core.so
├── libsherpa-onnx-fst.so
├── libsherpa-onnx-jni.so
├── libsherpa-onnx-kaldifst-core.so
└── libucd.so
1 directory, 12 files
When I look at your native Android examples, I noticed that Tts.kt is referring to 'sherpa-onnx-jni'.
 companion object {
        init {
            System.loadLibrary("sherpa-onnx-jni")
        }
    }

I've tried that one as well in Flutter by doing the following (aub_ai.dart):
...
return DynamicLibrary.open('libsherpa-onnx-jni.so');
...

But it fails to lookup the native symbols whenever I try to call functions from it. E.g. this fails:
// This function only relies on the onnxModel, the rest is hardcoded.
 final Pointer<SherpaOnnxOfflineTtsConfig> ttsConfig = _getOfflineTtsConfig(
    pathToOnnxModel: pathToOnnxModel,
  );

  // Runtime error occurs on this line because it's failing to lookup the native symbol 'SherpaOnnxCreateOfflineTts'.
  final tts = sherpaOnnxBindings.SherpaOnnxCreateOfflineTts(ttsConfig);

Any tips?

Hi @D-Idan @flutter-painter @eschmidbauer @BrutalCoding - sorry I've been really busy with other projects so haven't responded.
I've basically just flicked the switch to make this repository public:
https://github.com/nmfisher/flutter_sherpa_onnx
This is reasonably stable on iOS/Android (I have it running in production) and I've tested it informally on macos/Windows, seems no issues there.
As it says though, this is totally undocumented so you'll have to look at the code yourself to see how it works. Maybe @flutter-painter can submit a PR adding the notes I sent via email to the README which will give at least some explanation.
@BrutalCoding maybe this will help solve your issue.

When I look at your native Android examples, I noticed that Tts.kt is referring to 'sherpa-onnx-jni'.

@BrutalCoding
sherpa-onnx-jni is for JVM, which is call by either java or kotlin. I am afraid you cannot use it with flutter. For flutter you can safely ignore libsherpa-onnx-jni.so.

I haven't pushed all my local changes because I haven't gotten it to work yet

Could you describe the issues you have? For instance, you can post error logs.

Hi @nmfisher,
Here goes : https://github.com/nmfisher/flutter_sherpa_onnx/pull/2

Hi, Could dart ongoing support for native assets ease this integration process ?

Sorry, I cannot understand it. Could you give more details?

Hi, Could dart ongoing support for native assets ease this integration process ?

@flutter-painter While it would be nice, I think it would be better for @csukuangfj to continue focusing on existing work. The good news is that @csukuangfj already has makefiles, shell scripts, example apps for every platform and yeah- basically everything to build a fully working Flutter plugin.
It's probably a better idea for a (experienced/advanced) Flutter (package) dev to look into this project, unless sherpa-onnx is considered finished (it never is :P). While I can't share code or specific details, I can confirm that all the features of sherpa-onnx are working within Flutter. Think about TTS, ASR, VAD etc.

Sorry, I cannot understand it. Could you give more details?

@csukuangfj he is referring to https://github.com/dart-lang/native/tree/main/pkgs/native_assets_cli, which is a 1st party plugin (Google, or more specifically someone from the Dart team). It's the next way to interact with native code, basically a replacement for ffi and writing bindings for it. It's still experimental though so that's a 2nd reason that I discourage for you to jump in this potential rabbit hole.
While that is experimental, Flutter does already provide something for years that is robust:
Their 'ffi' package (plugin) combined with their 'ffigen' package, both found on https://pub.dev. Here is something that's easy to follow to allow native code in Flutter that was meant for pure C (note: Flutter uses Dart): https://docs.flutter.dev/platform-integration/android/c-interop
A Flutter dev could take a look at your native Android example projects and read through https://docs.flutter.dev/platform-integration/platform-channels?tab=type-mappings-kotlin-tab to get it working too.
TLDR: Many ways to achieve support of sherpa-onnx in Flutter, but it is challenging IMO if you want to be able to automate this for longevity / long term maintenance. Very do-able, it just takes a lot of time to set it up and test it for every platform.

Hello., just thought I would bump this thread to see if anyone had progressed on a flutter package. I'm particularly interested in the tts function as I am porting a project that had been developed in c# and unity, and was using piper.
I am absolutely new to dart packages and how sherpa actually works but can I use @nmfisher 's repo which seems to have been tailored to speech recognition or  should I give ffi a try  ?
Thanks in advance.

@Web3Kev I'm working on the package at the moment to make it slightly more beginner friendly. Check back in a week or two to see if it's a bit easier to get up and running.

Please see
https://github.com/k2-fsa/sherpa-onnx/pull/905#issuecomment-2129863770

Here is the Dart package for sherpa-onnx
https://pub.dev/packages/sherpa_onnx

Pure Dart examples can be found at
https://github.com/k2-fsa/sherpa-onnx/tree/master/dart-api-examples

the sherpa_onnx package seems do not support android and ios, any plans for mobile device support?

the sherpa_onnx package seems do not support android and ios, any plans for mobile device support?

We need the community help to

Refactor the current package to use the federated plugin
Support android and ios, and the web

The current package is nearly 100 MB. pub.dev limits the maximum package size to 100MB.

Closing via #1079
See also
https://pub.dev/packages/sherpa_onnx

Help to support the Web platform for Flutter is needed.
Note that we have already supported WebAssembly.


example.php does not fail if run without privileges

If you try to run php examples/example.php in a fresh git clone of the project, the command returns and the exit code is 0. However, no server starts running in the background. If, however, sudo php examples/example.php is given instead, the server loop is started successfully. It would be useful to output either an error message or return with a non-zero exit code.

Can we close this against PR #84 ?


[Feature Request] show time when request was made

Insomnia Version: 6.4.2
Operating System: Windows 10

Details

This may sound quite stupid, but still =) Sometimes I switch to the Insomnia from some other application, see the response and get confused, did I just send the request and this is fresh response or some outdated one?
It would be handy to expose the time when the request was made to the response header, something like this:

I love this suggestion. What about showing the time in the history menu?

Looks great!
Do you have an idea, how to make the relative one show actual info? Probably, the static timestamp is better since you won't need to re-draw it at all.

The relative one has a title attribute to show the actual info. It also uses the <TimeFromNow> component, which automatically updates the value as time passes.
If we want better access to when a request was sent, I suggest also printing a timestamp at the start of the Timeline.

Label in the history menu covers my use-case completely. However, could be useful to add this to the Timeline for other cases.

Oh, awesome. And I did add it to the timeline as well. I think it'll be useful there too

@gschier, neat work on this, thank you!


Timer value is hard to change

OS version:
Browser version: Chrome 66
Extension version: 1.35.4

The Timer value is hard to edit in the popup. E.g. For when starting a timer late and chainging it to a larger value.
When the user clicks on the task duration field name="toggl-button-duration" The cursor momentarily flashes in the position where clicked then it goes to the end of the field. This is due to the updating field when the timer is running. As soon as a char is typed at the end of the field the timer stops and then it is not a problem.
Expected behaviour
Cursor remains in position where clicked allowing the user to backspace or type etc.
As soon as a user modification is detected then the timer stops.
Steps to reproduce

Start a timer.
Click to edit in the popup
Click in the middle of the timer value to edit

Another user reported the same issue. #22843408813

Can I make a PR on this or this just for looking at?

As soon as a char is typed at the end of the field the timer stops and then it is not a problem.

This is not the experience I'm having.

We are fine either way. If you have the know-how and feel like creating a PR - go for it. However, you are definitely not expected to do so.


ci: try getting latest metrics-server release

Codecov Report

Merging #64 into master will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##           master    #64   +/-   ##
=====================================
  Coverage     100%   100%
=====================================
  Files           5      5
  Lines          81     81
  Branches       27     27
=====================================
  Hits           81     81

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update fd871e2...5796ca9. Read the comment docs.

:tada: This PR is included in version 1.9.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


fix: add retry for Bitcoin signing

Description
Tentative fix for https://github.com/zeta-chain/node/issues/2089
Add a retry for the signature, in case the error is related to the network.
Closes: https://github.com/zeta-chain/node/issues/2089

Not solving the issue: https://github.com/zeta-chain/node/actions/runs/9032989998/job/24822298819


Engine.ini deletes on some reboots if certain functions used in game

Game design flaw.
Add auto download of Engine.ini to script

Added script function to download Engine.ini at server install, and server start if it is missing.


How to prevent reloading the navigation or tab content

Hi. How do I prevent reloading the content of previously populated navigation or tab content, please? If I have 2 tabs, load a master/detail tables on the first one, select a particular item to see the detail - then go to the second tab - and then return to the first one - the content gets reloaded - but I don't want to search my item over. Each tab/navigation has it's own route. Maybe this is a more general Ember question. Thanks. This is my example:
{{#bs-navbar as |navbar|}}
  {{#navbar.content class="navbar navbar-fixed-top"}}
    {{#navbar.nav as |nav|}}
        {{#nav.item }}{{#nav.link-to "products"}}Products{{/nav.link-to}}{{/nav.item}}
        {{#nav.item}}{{#nav.link-to "offers"}}Offers{{/nav.link-to}}{{/nav.item}}
    {{/navbar.nav}}
  {{/navbar.content}}
{{/bs-navbar}}

Indeed this is not really specific to ember-bootstrap. You would need to make sure in your model hook, that you do not reload the data you already have. If you are using ember-data you could try to use the peek* methods, or use backgroundReload: false in https://emberjs.com/api/ember-data/2.14/classes/DS.Store/methods/findRecord?anchor=findRecord.
A better help channel would be the Ember Slack, at https://ember-community-slackin.herokuapp.com/

Thanks


Add a field in UpdateSource to specify branch to checkout for Git clones

Codecov Report

Merging #860 (ddf63ec) into master (24f84d0) will increase coverage by 0.78%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #860      +/-   ##
==========================================
+ Coverage   73.76%   74.54%   +0.78%
==========================================
  Files         132      132
  Lines       12440    13286     +846
==========================================
+ Hits         9176     9904     +728
- Misses       3264     3382     +118

Impacted Files
Coverage Δ

assemblyline/odm/models/service.py
100.00% <100.00%> (ø)

assemblyline/odm/models/service_delta.py
100.00% <100.00%> (ø)

assemblyline/odm/models/result.py
92.06% <0.00%> (-5.53%)
:arrow_down:

assemblyline/datasource/alert.py
88.46% <0.00%> (-3.85%)
:arrow_down:

assemblyline/common/heuristics.py
84.78% <0.00%> (-2.18%)
:arrow_down:

...ssemblyline/odm/models/ontology/results/process.py
94.87% <0.00%> (-1.91%)
:arrow_down:

assemblyline/datastore/helper.py
43.21% <0.00%> (-0.87%)
:arrow_down:

assemblyline/odm/randomizer.py
94.39% <0.00%> (-0.87%)
:arrow_down:

... and 8 more

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


Configuration parameter secret_file is not working

The option secret_file isn't working for me. If I write secret_file: secrets-test.yaml the addon is still writing inside secrets.yaml.
Originally posted by @ElVit in https://github.com/alex3305/home-assistant-addons/issues/18#issuecomment-790088512

@ElVit Thanks for reporting this issue. I've improved upon this behaviour with version 1.4.1 and commit b31ed942859f31a7d68b5b553acc97a2ac628a67. However I could not verify this issue. See:

Can you please verify this or perhaps elaborate on this issue with your (partial) configuration and the output you're receiving?

@alex3305
I found the cause of my error. In your screenshot you wrote secrets_file: but the docu says secret_file:. Now it’s working also for me.

@ElVit Thanks for pointing this out and getting back to me! Also very good you've got it working. I've just fixed this in the docs and am closing this issue.


Add GetMultiModeStatus method for IPC

This adds a single method to check the multi mode status through IPC.
I'm currently making a plugin where this single feature would solve most of my issues, so would be immensely helpful if it were to be merged.
Thank you for the plugin, and for your time to look at this.

Thank you!


The video frame hangs

The video frame hangs on all players some time here is a video show the case
https://user-images.githubusercontent.com/43533983/103478398-1cb31700-4dcf-11eb-8d1b-8c2d51064a0a.mp4

i have the same problem, did you found a solution?

i have the same problem, did you found a solution?


lambda-log integration

"use strict";

const middy = require("@middy/core");
const httpErrorHandler = require("@schibsted/middy-error-handler");
const createError = require("http-errors");

const { LambdaLog } = require("lambda-log");
const log = new LambdaLog({
  tags: ["index"],
});

const baseHandler = async (event) => {
  log.info("starting up");
  throw new createError.NotFound("File not found");
};

const handler = middy(baseHandler).use(httpErrorHandler(log));

module.exports = { handler };

it didn't appear to use log.error and tag my structured log. What am I missing please?

From a quick look it seems you're passing the logger instance wrong.
Instead of
const handler = middy(baseHandler).use(httpErrorHandler(log));

it should be
const handler = middy(baseHandler).use(httpErrorHandler({logger: log}));

Thanks! https://github.com/kaihendry/sls-middy-error-handling
Guess my last concern is how do I alter the output in the case it's basically showing too much??


Can graphitesend send events?

I tried sending a dict to graphite, following this guide: http://graphite.readthedocs.io/en/latest/events.html
Sent with send_dict(), but got the error:
ValueError: could not convert string to float

It looks like send_dict() is expecting float values all around. Is there another method that will be able to send event data, then?

Oops, I just realized the link I provided describes how to send events via the webapp, not directly to carbon. Just want to confirm if that is indeed the case, and if there is an alternate way to send events using graphitesend? Thanks :)

@Shir0kamii thanks for the info! I've decided to just send metrics instead of events for my project, so it looks like I will still be using graphitesend.


Cleanup, refactoring PgsqlMutex, add workflow actions and tests

Q
A

Is bugfix?
❌

New feature?
✔

Breaks BC?
✔

Fixed issues
-

👍


Nothing happens neither when right-clicking nor when using Ctrl-Shift-E

I just installed the package in Atom, very seduced by the possibility to edit texts in Markdown formats. Nothing happens ... I use Atom version 1.0.10 on Mac OS X 10.10.5.
What should I do to get it working?
Best Regards,

Sorry, but I couldn't test it on a Mac... What says your error console in development view?

Ok, for Mac the keyboard shortcuts are missing. These come in the next patch release.

Are there Mac users who use the package?! I need testers with a relatively short response time ^^

Sure! Looks like a great package. Couldn't get it to work on mac.

@c-baillie Have you Javascript skills to find out where the problem lies?

Sorry! Know almost nothing. Rush of blood to the head. May not be that
useful.
I have some free time in two weeks and I'll look at the code then if useful.
Charles
On Thu, Oct 15, 2015 at 3:54 AM, Jens A<EMAIL_ADDRESS>wrote:

@c-baillie https://github.com/c-baillie Have you Javascript skills to
find out where the problem lies?
—
Reply to this email directly or view it on GitHub
https://github.com/cakebake/markdown-themeable-pdf/issues/4#issuecomment-148309856
.

Not sure if this has been solved, but my Mac shortcuts work.

Thank you for reporting :)


Minor improvements

Organized imports and applied 'Eclipse' (spaces-only) code formatter

Can please have a look at white space / formatting next time. The diff was hard to read.

That's been exactly the point of enhancement:

previously different code formatter indentation styles (tabs and spaces) were mixed which made it hard to read in the first place
now the code is formatted via the default "Eclipse" spaces only format


Further parsing is needed for power functions

The power functions are all treated the same; however, it would be better to distinguish them as squared, cubed, square root, etc. Otherwise, the equation discovery approaches will treat the power as a coefficient and this would not accurately reflect the prior.

sqrt is already included as function. We could add squared and cubed to the functions, but we would need to parse this as a special case when reading sympy functions.

Yeah. The fix would be to check the child of the power node for the exponent. And I agree we should only to this up to cubed. So, we have sqrt, squared, cubed, power in general.


I have find Error after build mo unity project

Please fill in the following fields:
Unity editor version: 2020.1.0.b4
Firebase Unity SDK version: 6.13.0
Source you installed the SDK (.unitypackage or Unity Package Manager):.unitypackage
Firebase plugins in use (Auth, Database, etc.): FirebaseDatabase.unitypackage
Additional SDKs you are using (Facebook, AdMob, etc.): None
Platform you are using the Unity editor on (Mac, Windows, or Linux): Windows 10
Platform you are targeting (iOS, Android, and/or desktop): Android
Scripting Runtime (Mono, and/or IL2CPP): Tried both
My Error is :
Firebase.InitializationException: Firebase app creation failed. at Firebase.FirebaseApp.CreateAndTrack (Firebase.FirebaseApp+CreateDelegate createDelegate, Firebase.FirebaseApp existingProxy) [0x000e3] in <1be6193be3e248d495eb52dc2920675d>:0 at Firebase.FirebaseApp.Create () [0x00027] in <1be6193be3e248d495eb52dc2920675d>:0 at Firebase.FirebaseApp.get_DefaultInstance () [0x00017] in <1be6193be3e248d495eb52dc2920675d>:0 at Home.Start () [0x0000a] in :0
Please answer the following, if applicable:
Have you been able to reproduce this issue with just the Firebase Unity quickstarts (this GitHub project)?
Yes, the exact same thing happens here, and it feels worse.
What's the issue repro rate? (eg 100%, 1/5 etc)
100%

Duplicate of #641


Links

🔗 Link purpose
The purpose of a link must be described by its link text alone, or by the link text together with preceding page context - WCAG 2.4.4

[ ] Instance 1

Path
.sd-stretched-link.external[href$="pydata.html"]

Snippet

Accessible Name
(no value)

Accessible description
(no value)

URL
examples/pydata.html

[ ] Instance 2

Path
.sd-stretched-link.external[href$="gallery.html"]

Snippet

Accessible Name
(no value)

Accessible description
(no value)

URL
examples/galery.html

I think this is fixed by https://github.com/pydata/pydata-sphinx-theme/pull/1633

Closing this issue because https://github.com/pydata/pydata-sphinx-theme/pull/1633 has been merged


Update dependencies

Affects: <api-version-number>.

Depends on https://github.com/Hygieia/hygieia-core/pull/260
This is part of a set of PRs that upgrade hygieia-core (and then api & collectors) to Spring Boot 1.5.x, Spring 4.x, and Spring Data Ingalls. The primary push is to address vulnerabilities identified by Blackduck. As most of these Spring dependencies have reached EOL, this is as far as the train goes until the Spring Boot 2.x and Spring 5.x versions are ready.
I've generally tried to update versions via properties that override Spring Boot rather than having explicit dependencies called out.

@aochsner can you resolve the conflicts on the pom.xml so that this change can be merged?

verified the PR and seems to be working as BAU and merging it


RCSP solver WARNING : the best solution could not be retrieved

Hi, am working of a VRP problem with capacities and time window constraints, i wonder what does it mean when we see "RCSP solver WARNING : the best solution could not be retrieved" .

This warning can be ignored if it does not appear for the last iteration of column generation. In some rare cases, the best pricing solution may not be retrieved, but it is ok as long as other solutions with negative reduced cost can be retrieved.

I see, so is it fair to say "in some rare cases, the best pricing solution may not be retrieved, but it is ok as long as other solutions with negative reduced cost can be retrieved, as these reduced cost will drive the solver to optimal solution"

Yes, case 1 is correct.
Case 2 is correct if the best solution has the reduced cost zero. If  the best solution has a negative reduced cost and cannot be retrieved and all other solutions have non-negative reduced cost, then the algorithm is not correct. But this case is very hard to have, we never had it.
But I agree that the incorrect case should have been determined by the code which is not the case now. For the moment, there is just this warning, and the user should analyse the log to see whether this warning critical or not.

Actually, case 2 is more subtle: even if all other solutions have non-negative reduced cost, this does not mean that no other negative reduced cost solution exists, as it may be dominated by the best solution (which was not retrieved). So it is hard to determine the incorrect case, so there is warning instead.

@rrsadykov thanks for the clear explanation, i think my question is answered so am closing this issue.


Flutter 3.3.0 - Display bug on text widget with Thai Character

Flutter 3.3

Flutter 2.10.5

Flutter Doctor
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 3.3.0, on macOS 12.4 21F79 darwin-arm (Rosetta), locale en-TH)
[✓] Android toolchain - develop for Android devices (Android SDK version 33.0.0)
[✓] Xcode - develop for iOS and macOS (Xcode 13.4.1)
[✓] Chrome - develop for the web
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Hi @titanzx,
Can you please provide a minimal complete reproducible code sample so that we can investigate this?
Thank you

Hi @titanzx,
Can you please provide a minimal complete reproducible code sample so that we can investigate this?
Thank you

Widget _buildCupertinoPicker(DatePickerTheme theme){
    return Container(
      child: SizedBox(
        height: theme.containerHeight,
        child: CupertinoPicker(
          key: ValueKey(widget.selectedItemIndex),
          selectionOverlay: const CupertinoPickerDefaultSelectionOverlay(
            background: transparentColor,
          ),
          // magnification: 1.5,
          scrollController: scrollCtrl,
          useMagnifier: true,
          backgroundColor: theme.backgroundColor,
          itemExtent: theme.itemHeight, //height of each item
          looping: false,
          children: widget.dataList!.map((item)=> Center(
            child: Text(
              item,
              style: theme.itemStyle,
              textAlign: TextAlign.start,
            ),
          )).toList(),
          onSelectedItemChanged: (index) {
            widget.selectedItemIndex = index;
            widget.selectedItem = widget.dataList![index];
            if (widget.route.onChanged != null) {
              widget.route.onChanged!(widget.dataList![index], index);
            }
            // refreshScrollOffset();
          },
        ),
      ),
    );
  }

Hi @titanzx, the sample you provided has some properties that I do not have so I cannot run the code sample.
Please provide a complete minimal reproducible code sample that I can run without needing to make any changes on my end.
Thank you


DeprecationWarning: Calling an asynchronous function without callback is deprecated.

Maybe add some context?

Happens sometimes™ when receiving the first request.
I guess that its something with the download part. Race condition?

Yeah probably, I'll have a look if I can

Fixed by #23.


Launch template for node_groups is ignored

Description
I'm using managed node_groups and since there is no parameter to specify the cpu_credits, I'm adding a launch template to the node group. However, the actual nodes still launch in "unlimited" mode and for the node_group another launch template is created starting with "eks-" prefix. The automatically created launch template does not contain my launch template setting.
UPDATE: I'm using a launch template for a g4dn instance in which I specify a specific AMI which is definitely used, so the it seems like it's just the credit_specification parameter that is being ignored.
Versions

Terraform: v1.0.4
Provider(s):
terraform-aws-eks v17.1.0

Code Snippet to Reproduce
module "eks" {
  source  = "terraform-aws-modules/eks/aws"
  version = "17.1.0"#"15.1.0"

  cluster_name    = "${var.cluster_name}"
  cluster_version = "1.20"
  subnets         = module.vpc.private_subnets

	node_groups = {
	    cpu-worker-core-0 = {
	      node_group_name     = "cpu-worker-0"
	      desired_capacity    = 2
	      max_capacity        = 4
	      min_capacity        = 0
	      capacity_type       = "ON_DEMAND"
	      subnet_ids          = module.vpc.private_subnets
	      instance_types = ["t3.small"]
	      launch_template_id      = aws_launch_template.cpu-worker-full-on-demand.id
	      launch_template_version = aws_launch_template.cpu-worker-full-on-demand.default_version
	    },
	    ...
	}
}

resource "aws_launch_template" "cpu-worker-full-on-demand" {
  name_prefix            = "${var.cluster_name}-"
  description            = "CPU 100% on-demand Launch-Template"
  update_default_version = true

  block_device_mappings {
    device_name = "/dev/xvda"

    ebs {
      volume_size           = 50
      volume_type           = "gp2"
      delete_on_termination = true
    }
  }
  credit_specification {
    cpu_credits = "standard"
  }

  monitoring {
    enabled = false
  }

  network_interfaces {
    associate_public_ip_address = false
    delete_on_termination       = true
    security_groups             = [
      module.eks.cluster_primary_security_group_id
      ]
  }

  lifecycle {
    create_before_destroy = true
  }

}

Expected behavior
My launch template or at least its settings are taken.
Actual behavior
The automatically created launch template is used.

I was unable to reproduce with version 0.17.1. I am seeing block_device_mappings setting in AWS Launch Template console and I can see that it is also being used by my MNG as we would expect. What does your TF state file look like?

I see you update. I think credit_specification is specific to spot pricing. So if you are strictly using on-demand then that would make sense why it is being ignored.

Hey @aidan-melen, thanks a lot for your response. Please find the part of the launch template I just tested it again with in the following:
{
      "module": "module.test",
      "mode": "managed",
      "type": "aws_launch_template",
      "name": "cpu-worker-test",
      "provider": "module.core_production.provider[\"registry.terraform.io/hashicorp/aws\"]",
      "instances": [
        {
          "schema_version": 0,
          "attributes": {
            "arn": "...",
            "block_device_mappings": [
              {
                "device_name": "/dev/xvda",
                "ebs": [
                  {
                    "delete_on_termination": "true",
                    "encrypted": "",
                    "iops": 0,
                    "kms_key_id": "",
                    "snapshot_id": "",
                    "throughput": 0,
                    "volume_size": 45,
                    "volume_type": "gp2"
                  }
                ],
                "no_device": "",
                "virtual_name": ""
              }
            ],
            "capacity_reservation_specification": [],
            "cpu_options": [],
            "credit_specification": [
              {
                "cpu_credits": "standard"
              }
            ],
            "default_version": 1,
            "description": "test",
            "disable_api_termination": false,
            "ebs_optimized": "",
            "elastic_gpu_specifications": [],
            "elastic_inference_accelerator": [],
            "enclave_options": [],
            "hibernation_options": [],
            "iam_instance_profile": [],
            "id": "lt-...",
            "image_id": "",
            "instance_initiated_shutdown_behavior": "",
            "instance_market_options": [],
            "instance_type": "",
            "kernel_id": "",
            "latest_version": 1,
            "license_specification": [],
            "metadata_options": [],
            "monitoring": [
              {
                "enabled": false
              }
            ],
            "name": "test-...",
            "name_prefix": "core-production-",
            "network_interfaces": [
              {
                "associate_carrier_ip_address": "",
                "associate_public_ip_address": "false",
                "delete_on_termination": "true",
                "description": "",
                "device_index": 0,
                "interface_type": "",
                "ipv4_address_count": 0,
                "ipv4_addresses": null,
                "ipv6_address_count": 0,
                "ipv6_addresses": null,
                "network_interface_id": "",
                "private_ip_address": "",
                "security_groups": [
                  "sg-...",
                  "sg-..."
                ],
                "subnet_id": ""
              }
            ],
            "placement": [],
            "ram_disk_id": "",
            "security_group_names": null,
            "tag_specifications": [
              {
                "resource_type": "instance",
                "tags": {
                  "test": "test"
                }
              }
            ],
            "tags": {
              "instance": "test"
            },
            "tags_all": {
              "instance": "test"
            },
            "update_default_version": true,
            "user_data": "",
            "vpc_security_group_ids": null
          },
          "sensitive_attributes": [],
          "private": "...",
          "dependencies": [
            ...
          ],
          "create_before_destroy": true
        }
      ]
    }

So, from that side, it look pretty good, the credit_specifications are in there. However, having a look at the launch template specifications, this is what I see:

My storage specifications are taken into account, so no issues there:


Update CLI extensions available doc

Update CLI extensions available doc.
Triggered by Azure/azure-cli-extensions - TRAVIS_BUILD_ID=458510873
https://github.com/Azure/azure-cli-extensions/commit/a33df510c96fb663fada3d135435816c758efd03

:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

docs-ref-conceptual/azure-cli-extensions-list.md
:white_check_mark:Succeeded
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For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


Add JSON support to WHERE clause evaluation in Executor

We currently support string, integer, and float comparisons in the DSQL executor (core/executor.go). We need to support JSON fields as part of WHERE clause expressions.
Requirements
Syntax support

Support $value.field syntax in DSQL queries.
Example

SELECT $key, $value FROM `pattern?` WHERE $value.field > 10;

Support nested field queries, such as $value.field1.field2.field3.

Testing

Add comprehensive unit tests and integration tests to verify the behavior.
benchmark the code and measure the time taken and memory allocs using benchmem and try to keep them to the bare minimum.
Include screenshots of the benchmark as a part of the PR description.

Notes
This feature can be worked on once #165 is completed.

Can I pick this ?

@JyotinderSingh can I work on this one as well ?

@JyotinderSingh can I work on this one as well ?

Will assign once the other issue assigned to you is completed

Hey @JyotinderSingh can I pick up this task

Hey @JyotinderSingh can I pick up this task

Assigned

@arpitbbhayani @JyotinderSingh  While working on this task I came across a couple of issues I wanted to discuss

Problem: We have a bug in our QWATCH command. We can store a value as an integer but on retrieval it treats it as a string. Running this query in qwatch_test.go  var qWatchQuery = "SELECT $key, $value FROM 'match:100:*' WHERE $value > 1 ORDER BY $value DESC LIMIT 3" will give us an error "2024/08/03 12:43:48 ERRO incompatible types in comparison: string and int".
Solution: I can create a fix which will ensure all values stored will be retrieved with the same type at storage time. I can create this fix and add extensive tests within this PR or I can create a new PR for this fix. I believe its important to fix this before moving onto filtering based on JSON
There is an issue with sqlparser. It isn't compatible with our style of querying JSON. When I pass this query SELECT $key, $value FROM 'match:100:*' WHERE $value.field1.field2.field3 > 1 ORDER BY $value DESC LIMIT 3 it gives me this error on parsing the SQL statement "error parsing SQL statement: syntax error at position 67". This error does disappear if I limit my query to two nested fields rather than 3 but then the issue arises that it ignores $value and considers field2 to be our column name.
Solution: We can follow the convention present in PostgresSQL and query json using ->. this will transform our query into this format: SELECT $key, $value FROM 'match:100:*' WHERE $value->field1->field2->field3 > 1 ORDER BY $value DESC LIMIT 3. What are your opinions on this approach

@arpitbbhayani @JyotinderSingh  While working on this task I came across a couple of issues I wanted to discuss

Problem: We have a bug in our QWATCH command. We can store a value as an integer but on retrieval it treats it as a string. Running this query in qwatch_test.go  var qWatchQuery = "SELECT $key, $value FROM 'match:100:*' WHERE $value > 1 ORDER BY $value DESC LIMIT 3" will give us an error "2024/08/03 12:43:48 ERRO incompatible types in comparison: string and int".

Solution: I can create a fix which will ensure all values stored will be retrieved with the same type at storage time. I can create this fix and add extensive tests within this PR or I can create a new PR for this fix. I believe its important to fix this before moving onto filtering based on JSON

There is an issue with sqlparser. It isn't compatible with our style of querying JSON. When I pass this query SELECT $key, $value FROM 'match:100:*' WHERE $value.field1.field2.field3 > 1 ORDER BY $value DESC LIMIT 3 it gives me this error on parsing the SQL statement "error parsing SQL statement: syntax error at position 67". This error does disappear if I limit my query to two nested fields rather than 3 but then the issue arises that it ignores $value and considers field2 to be our column name.

Solution: We can follow the convention present in PostgresSQL and query json using ->. this will transform our query into this format: SELECT $key, $value FROM 'match:100:*' WHERE $value->field1->field2->field3 > 1 ORDER BY $value DESC LIMIT 3. What are your opinions on this approach

Thanks for the extensive details @YahyaHaq! Please go ahead with including the fix for (1) in this PR. Secondly, the arrow convention is a good approach for nested field access. Please go ahead with it.
Thanks a lot for catching these issues and suggesting fixes!

@arpitbbhayani @JyotinderSingh
A few updates regarding my last message:
Regarding (2) I just confirmed that passing in query in this format SELECT _key, _value FROM 'match:100:*' WHERE _value->field1 = '11' ORDER BY _value DESC LIMIT 3 does not work either for SQLParser. I receive the error "panic: syntax error at position 60 near 'field1'". I can create an issue on github and see if I can do anything to resolve it myself and in the meantime I can also check if there is any other SQLParser that will suit us better. If there is any other solution you can suggest that may provide a faster fix then that would be great but until this is resolved I will not be able to complete this ticket

@arpitbbhayani @JyotinderSingh
A few updates regarding my last message:
Regarding (2) I just confirmed that passing in query in this format SELECT _key, _value FROM 'match:100:*' WHERE _value->field1 = '11' ORDER BY _value DESC LIMIT 3 does not work either for SQLParser. I receive the error "panic: syntax error at position 60 near 'field1'". I can create an issue on github and see if I can do anything to resolve it myself and in the meantime I can also check if there is any other SQLParser that will suit us better. If there is any other solution you can suggest that may provide a faster fix then that would be great but until this is resolved I will not be able to complete this ticket

You should replace _value with $value and _key with $key. But this issue does not seem related to that. Let me think over it.
In the mean time you can redirect this PR to only fix (1) and we can create a new PR for (2) after appropriate discussion.

in our code we replace $value with _value before passing it into the parser

Regarding (1)

I think I should also be assigned the issue https://github.com/DiceDB/dice/issues/188 as if i work on this issue my changes will be overwriting the integration tests in this file. If the person assigned to this hasn't created the PR then I can work on this otherwise I can work on top of their PR. What do you think

@YahyaHaq Let's do one thing, to support the JSONPath syntax, let's require the user to pass the JSONPath surrounded by backticks, as follows:
SELECT $key, $value FROM 'match:100:*' WHERE `$value.field1.field2.field3` > 1 ORDER BY $value DESC LIMIT 3

The parser should be able to handle this. How does that sound?

Regarding (1)

I think I should also be assigned the issue Add integration test for testing WHERE clause in QWATCH. #188 as if i work on this issue my changes will be overwriting the integration tests in this file. If the person assigned to this hasn't created the PR then I can work on this otherwise I can work on top of their PR. What do you think

Let's let it be for now, we can merge whichever PR gets ready first and then work from there.

@JyotinderSingh  Thank you so much for that SQL solution. This works great!

@JyotinderSingh  Thank you so much for that SQL solution. This works great!

Feel free to raise a draft PR, I can provide some ongoing feedback.

Hi @YahyaHaq
Any updates on this issue?

Hey @JyotinderSingh apologies for any delay on my end. Will try to send a PR by Saturday. There are no current blockers for this task

Hey @JyotinderSingh apologies for any delay on my end. Will try to send a PR by Saturday. There are no current blockers for this task

Hi @YahyaHaq, wondering if you'll be able to close this anytime soon?

yes. all thats left is the benchmark and the unit tests. Functionality and integration tests are done. You can take a look at my draft PR

yes. all thats left is the benchmark and the unit tests. Functionality and integration tests are done. You can take a look at my draft PR

The changes look good overall, you can clean up the code and add the remaining tests.

Thanks, @YahyaHaq for contributing. Closing this issue.
Status - shipped 🚀