text:
Snapshot name collisions

First step towards fixing #3542
Adds a subtree at each layer of the stack (except DDS for now) to isolate dynamic tree keys, such as data store IDs and channel IDs.

This shifts all data store trees under a ".dataStores" tree of the root node.

Protects against ".protocol", ".blobs" name collisions, and some driver/server ones as well

This shifts all channel trees under a ".channels" tree of each data store node.

Does not add protection, because blobs are already isolated from trees

This does not shift all dds subtrees/blobs to a subtree of each channel node.

Current design does not require this, since we only return ITreeEntrys from internal snapshot

This does not take care of isolating server/driver from runtime at the root

Old tree structure:
/
    [blob] .chunks
    [tree] .protocol/
    [tree] .blobs/
    [tree] <dataStoreIds>/
        [blob] .component
        [tree] <channelIds>/
            [blob] .attributes
            [tree] .../

New tree structure:
/
    [blob] .metadata **provides snapshot version
    [blob] .chunks
    [tree] .protocol/
    [tree] .blobs/
    [tree] .channels/
        [tree] <dataStoreIds>/
            [blob] .component
            [tree] .channels/
                [tree] <channelIds>/
                    [blob] .attributes
                    [tree] .../

With this change, ContainerRuntime only gives upper .channels tree to DataStores, restricting access.
Each DataStoreContext only gives the lower .channels tree to its DataStoreRuntime.
Changes in this PR are back/forwards compatible reading of new format only, it does not write the new snapshotFormatVersion. So after a few versions with this released, we can start writing in the new snapshotFormatVersion.  This is because an old client runtime will not be able to understand the new format.
TODO: SummarizerNode needs to handle these additional path parts.

This does not shift all dds subtrees/blobs to a subtree of each channel node.
Current design does not require this, since we only return ITreeEntrys from internal snapshot

I already violate it with mixinSummaryHandler() (and using it in Bohemia repo to write out /DataStoreId/_search/01 blobs

[tree] .dataStores/
Can we please call it channels?
That's already what I use for routing (active PR, will try to merge this week).
And that's consistent with future we want to get to, where channels can be nested, and data store and DDS differ only in implementation, not in structure (i.e. it will be Ok for DDS to have DDS underneath it - formalizing what Daniel already did with 3 DDSs sitting on one channel)

this needs tests, specifically for forward/back comapt

why do we need this hear? seems like it could be defined in container-runtime*

Refers to: packages/runtime/runtime-definitions/src/summary.ts:184 in 597decc. [](commit_id = 597decccbfe778688fe4420acd5975ec6c8295f2, deletion_comment = False)

@arinwt, it would be great to address this area sooner than later. Do you need any help with moving this PR forward?

@vladsud no sorry, I just want to add support for DDS's and address a few of Tony's comments first (version as number if possible and move interface definition).

authors: anthony-murphy arinwt vladsud


text:
AssertionError: Invalid type <class 'NoneType'> for key

Hi I managed to build GLIP and use the following command to test zero-shot on COCO
python tools/test_grounding_net.py --config-file configs/pretrain/glip_Swin_L.yaml --weight MODEL/glip_large_model.pth         TEST.IMS_PER_BATCH 1         MODEL.DYHEAD.SCORE_AGG "MEAN"         TEST.EVAL_TASK detection         MODEL.DYHEAD.FUSE_CONFIG.MLM_LOSS False         OUTPUT_DIR results
If I used the default confg, I get the following error.

I changed the defaults.py in maskrcnn_benchmark about
_C.DATASETS.PREDEFINED_TEXT
_C.DATASETS.OVERRIDE_CATEGORY
_C.DATASETS.SUPRESS_QUERY
_C.DATASETS.CAPTION_PROMPT
(They were all set to None, and I set them to "")
and I was able to get the dataset loaded. But get the following error. Do you know what was wrong in the code? Do we need to specify more paths?
The combined datasets are: ('coco_2017_val',).
loading annotations into memory...
Done (t=0.89s)
creating index..
index created!
coco_2017_val has the 5000 data points COCODataset
2023-06-30 17:23:49,852 maskrcnn_benchmark.inference INFO: Start evaluation on coco_2017_val dataset(5000 images).
Traceback (most recent call last):
File "tools/test_grounding_net.py", line 222, in
main()
File "tools/test_grounding_net.py", line 215, in main
cfg=cfg
File "/usr/{dir}/GLIP/maskrcnn_benchmark/engine/inference.py", line 426, in inference
all_queries, all_positive_map_label_to_token = create_queries_and_maps_from_dataset(dataset, cfg)
File "/usr/{dir}/GLIP/maskrcnn_benchmark/engine/inference.py", line 204, in create_queries_and_maps_from_dataset
labels_i, label_list_i, additional_labels = cfg.DATASETS.SUPRESS_QUERY if cfg.DATASETS.USE_SUPRESS_QUERY else None, cfg = cfg)
File "/usr/{dir}/GLIP/maskrcnn_benchmark/engine/inference.py", line 227, in create_queries_and_maps
caption_prompt = load_from_yaml_file(caption_prompt)
File "/usr/{dir}/GLIP/maskrcnn_benchmark/data/datasets/tsv.py", line 34, in load_from_yaml_file
with open(yaml_file, 'r') as fp:
FileNotFoundError: [Errno 2] No such file or directory: ''
Thank you!

I have the same issue @charismaticchiu @
How did you solve it? Thanks in advance!

I try to install yacs>=1.8.0 . It works.

source: gharchive/issue

authors: AmrinKareem ChenNuoling charismaticchiu

repo: microsoft/GLIP

license: MIT

license_type: permissive

license_source: github-api


text:
Slow prediction on Video

Generate caption for one video takes 3 minutes, what should I do?
I'm use function from inference

Does one video mean 6 frames? which model do you use? what is the command line?


text:
LightGBMError: Check failed: best_split_info.left_count > 0 for ranking task

hi,
when would lightgbm 2.3.2 be released? as the documentation online (https://lightgbm.readthedocs.io/) is 2.3.2 with some new features but the latest python package is lightgbm 2.3.1. Thanks.

@kenyeung128 Hi!
You can download the latest nightly version from this page: https://lightgbm.readthedocs.io/en/latest/Installation-Guide.html if you do not want to build from sources.
I think we need some time to test large changes introduced in #2699, fix some critical issues, wait for any news for #2628 and so on.
Also, I believe the next release should be 2.4.0 at least, or even 3.0.0, according to the semantic versioning we try to follow due to removal of some parameters.
cc @guolinke

hi @StrikerRUS thanks for the info, i have followed the installation guide and installed the python version with the latest source code.
however, i get an error as below when i tried to fit a LGBMRanker
LightGBMError: Check failed: best_split_info.left_count > 0 at /data/github/LightGBM/src/treelearner/serial_tree_learner.cpp, line 706 .
do u have any idea?

@kenyeung128 can you provide the reproduce example?

hi @guolinke
the example is like this
gbm = lgb.LGBMRanker(n_estimators=800, score='ncdg')
gbm.fit(x_train.drop(columns=columns_exclude), y_train, group=q_train,
categorical_feature=columns_cateogry,
eval_set=[(x_valid.drop(columns=columns_exclude), y_valid)],
eval_group=[q_valid], eval_at=[1,2,3], early_stopping_rounds=200, verbose=True,
eval_metric='ndcg')
and found out seems the root cause is that it's using categorical_feature, there are examples in x_train but not in x_valid, so it throws out the exception. But in previous version 2.3.1 lightgbm, it's working

Thanks @kenyeung128 , could you provide the data for debugging?

@guolinke it's quite a big dataset, but i tried to provide data in smaller dataset but it didn't come up with the error. I suspect it's something with the split of data not evenly distributed between train/valid, and somehow it throws the exception

@kenyeung128 is that possible to reproduce this by randomly generated data?

@guolinke I've also been running into this error when fitting models with categorical predictors in the latest master branch.  Here is a reproducible example in R v3.5.2:
Code:
library(lightgbm)
set.seed(1)
data <- data.frame(
  y = as.integer(runif(1000) > .5)
  ,x = sample(c(1,1,1,2), 1000, replace = TRUE)
)
data_matrix <- as.matrix(data[, "x", drop = FALSE])
dtrain <- lgb.Dataset(data_matrix, label = data$y, categorical_feature = "x")

model <- lgb.train(
  params = list(objective = "binary")
  ,data = dtrain
  ,nrounds = 1
)

Error:
[LightGBM] [Fatal] Check failed: best_split_info.right_count > 0 at /tmp/RtmpE5HQrB/R.INSTALL1226e7bebac9e/lightgbm/src/src/treelearner/serial_tree_learner.cpp, line 706 .

@kenyeung128 @rgranvil thanks very much, could you try the #2824 ?

@guolinke I confirmed #2824 fixes the issue for me.  Thanks for the quick fix.

I still found this issue when I use GPU.

I also found this issue on GPU build.

I also found this issue occurring from time to time on relatively fresh GPU build. For ~4 Gb dataset with 250000 rows and 1500 columns it could train normally for hours, than I got
LightGBMError: Check failed: (best_split_info.right_count) > (0) at D:\Python\projects\lib\2003_lgbm\LightGBM\src\treelearner\serial_tree_learner.cpp, line 614 which is at https://github.com/microsoft/LightGBM/blob/a2a38b6cd527f8c87d0250e0cbb89b12899c27dd/src/treelearner/serial_tree_learner.cpp#L632 in current code. Any ideas @guolinke, @StrikerRUS ?

I'm encountering a very similar issue to this on 3.0.0 on GPU. I dropped my categorical columns because I was concerned that was the cause.
But, I still get the error, even though I might hit it less frequently?

Is this still going on? we should start a new entry

I have this error on CPU with the latest version on Windoes 10 x64.
Data is private so I sadly can't share it.
Check failed: (best_split_info.right_count) > (0) at c:\users\vssadministrator\appdata\local\temp\pip-req-build-lqyem8a1\compile\src\treelearner\serial_tree_learner.cpp, line 661 .

I have this error on CPU with the latest version on Windoes 10 x64.
Data is private so I sadly can't share it.
Check failed: (best_split_info.right_count) > (0) at c:\users\vssadministrator\appdata\local\temp\pip-req-build-lqyem8a1\compile\src\treelearner\serial_tree_learner.cpp, line 661 .

Same here on CPU with macOS using virtualenv
File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/sklearn.py", line 770, in fit
    super(LGBMRegressor, self).fit(X, y, sample_weight=sample_weight,
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/sklearn.py", line 612, in fit
    self._Booster = train(params, train_set,
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/engine.py", line 252, in train
    booster.update(fobj=fobj)
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/basic.py", line 2458, in update
    _safe_call(_LIB.LGBM_BoosterUpdateOneIter(
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/basic.py", line 55, in _safe_call
    raise LightGBMError(decode_string(_LIB.LGBM_GetLastError()))
lightgbm.basic.LightGBMError: Check failed: (best_split_info.left_count) > (0) at /Users/runner/work/1/s/python-package/compile/src/treelearner/serial_tree_learner.cpp, line 651 .

Same here on CPU with macOS using virtualenv
File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/sklearn.py", line 770, in fit
    super(LGBMRegressor, self).fit(X, y, sample_weight=sample_weight,
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/sklearn.py", line 612, in fit
    self._Booster = train(params, train_set,
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/engine.py", line 252, in train
    booster.update(fobj=fobj)
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/basic.py", line 2458, in update
    _safe_call(_LIB.LGBM_BoosterUpdateOneIter(
  File "/Users/user/.virtualenvs/flask/lib/python3.8/site-packages/lightgbm/basic.py", line 55, in _safe_call
    raise LightGBMError(decode_string(_LIB.LGBM_GetLastError()))
lightgbm.basic.LightGBMError: Check failed: (best_split_info.left_count) > (0) at /Users/runner/work/1/s/python-package/compile/src/treelearner/serial_tree_learner.cpp, line 651 .

@muttoni @chutcheson Could you provide a reproducible example, or, if possible, share your dataset with us? We are trying to remove this bug before the next release. Any help is really appreciated. Thanks.

@muttoni @chutcheson Could you provide a reproducible example, or, if possible, share your dataset with us? We are trying to remove this bug before the next release. Any help is really appreciated. Thanks.

lgbm bug.zip
The issue is reproducible with attached dataset @shiyu1994
Error message:
LightGBMError: Check failed: (best_split_info.left_count) > (0) at D:\a\1\s\python-package\compile\src\treelearner\serial_tree_learner.cpp, line 651 .
Code to reproduce:
from sklearn.model_selection import train_test_split
train_df, test_df  = pd.read_csv('train.csv'),  pd.read_csv('test.csv')
final_df = pd.concat([train_df, test_df], ignore_index = True)
y = final_df["domain"]
x = final_df.drop("domain", axis = 1)

clf = lightgbm.LGBMClassifier(n_jobs=-1, boosting_type='goss', random_state=0)

# Change test_size parameter to remove error
x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=0.2, random_state=0)
clf.fit(x_train,y_train)

# Uncomment this line to remove error
#clf.fit(x,y)

Few Observations

Does not throw error upon changing test_size from 0.2 to any value (0.21, 0.3 etc.)
Does not throw error if you run clf.fit(x,y) instead of clf.fit(x_train, y_train)
Throws same error if random_state is changed in either sklearn.model_selection.train_test_split or lightgbm.LGBMClassifier

I ran into the same problem here when using multiclassova. Multiclass worked nicely.

I also have this issue when using a similar workflow as the example @arkothiwala posted.

@arkothiwala @zacheberhart-kd The example is OK with the latest master branch. You can clone the source code and build the python package from source.

I built from source today, have this error on GPU both Windows and Linux
Params = {
'objective': 'multiclass',
'metric':['auc_mu','multiclass'],
'device':'gpu',
'num_threads': 6,
'num_leaves': 127,
'num_class': 7,
'max_bin': 63,
'min_data_in_leaf':50,
'bin_construct_sample_cnt' :51001000,
'learning_rate': 0.03,
'verbose': 1
}
[LightGBM] [Info] This is the GPU trainer!!
[LightGBM] [Info] Total Bins 29705
[LightGBM] [Info] Number of data points in the train set: 8293105, number of used features: 964
[LightGBM] [Info] Using GPU Device: TITAN RTX, Vendor: NVIDIA Corporation
[LightGBM] [Info] Compiling OpenCL Kernel with 64 bins...
[LightGBM] [Info] GPU programs have been built
[LightGBM] [Info] Size of histogram bin entry: 8
[LightGBM] [Info] 935 dense feature groups (7402.75 MB) transferred to GPU in 2.895087 secs. 1 sparse feature groups
[LightGBM] [Info] Start training from score -1.620340
[LightGBM] [Info] Start training from score -2.736469
[LightGBM] [Info] Start training from score -2.609875
[LightGBM] [Info] Start training from score -2.799483
[LightGBM] [Info] Start training from score -2.936053
[LightGBM] [Info] Start training from score -3.110144
[LightGBM] [Info] Start training from score -0.682573
[LightGBM] [Fatal] Check failed: (best_split_info.left_count) > (0) at /C/lgb/LightGBM/python-package/compile/src/treelearner/serial_tree_learner.cpp, line 653 .
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.8/dist-packages/lightgbm/engine.py", line 249, in train
booster.update(fobj=fobj)
File "/usr/local/lib/python3.8/dist-packages/lightgbm/basic.py", line 2636, in update
_safe_call(_LIB.LGBM_BoosterUpdateOneIter(
File "/usr/local/lib/python3.8/dist-packages/lightgbm/basic.py", line 110, in _safe_call
raise LightGBMError(_LIB.LGBM_GetLastError().decode('utf-8'))
lightgbm.basic.LightGBMError: Check failed: (best_split_info.left_count) > (0) at /C/lgb/LightGBM/python-package/compile/src/treelearner/serial_tree_learner.cpp, line 653 .

@Teeeto Thanks for the information. For GPU version, this bug has a separated issue #2793. Currently, we are focusing on releasing a new version. And fixing this bug is not included in the new release plan. But I can investigate this next week.

@Teeeto Increasing the number of features resolved the exception for me on CPU.

@Teeeto Increasing the number of features resolved the exception for me on CPU.
I dont have this issue on CPU. However CPU is slow - one iteration per 2 minutes on my dataset (a 60-core machine).
GPU is like 30x faster.

@Teeeto Thanks for the information. For GPU version, this bug has a separated issue #2793. Currently, we are focusing on releasing a new version. And fixing this bug is not included in the new release plan. But I can investigate this next week.
Thank You! I think it would be great to prioritize this fix since the issue is prohibitive in certain use cases.

Just built on linux - problem still persists, there is a circle of issues referencing each other all closed, not sure which one to reopen.

Issue disappered when
pip uninstall lightgbm-3.1.1
pip install lightgbm-3.2.1

Solution from @Junbabek works - but pip does not seem to have v3.2.1 which is the minimum version.
If using Anaconda install LightGBM v3.2.1:
conda install -c conda-forge lightgbm

To summarise this entire thread:

Issue caused when category 0 is the most common feature.
Install v3.2.1 to fix.

@sharpe5

but under Windows, pip does not have v3.2.1 yet.

Wheel file v3.2.1 for Windows has been on PyPI since April, please double check:
https://pypi.org/project/lightgbm/#files

got the version 3.3.3, python.
The issue is bugging me for the past 2 days.. The data set is 500k, with 1500 features. There seems to be some correlation with min_gain_to_split parameter. When the value is 1 I have not yet seen any errors, however on value 0 (default) it seems to crash quite often. Take this comment with caution since I have not ran enough tests yet.. Training on GPU.
crashed on

{'learning_rate': 0.43467624523546383, 'max_depth': 8, 'num_leaves': 201, 'feature_fraction': 0.9, 'bagging_fraction': 0.7000000000000001, 'bagging_freq': 8}

{'learning_rate': 0.021403440298427053, 'max_depth': 2, 'num_leaves': 176, 'lambda_l1': 3.8066251775052895, 'lambda_l2': 1.08526150100961e-08, 'feature_fraction': 0.6, 'bagging_fraction': 0.9, 'bagging_freq': 6}

{'learning_rate': 0.3493368922746614, 'max_depth': 6, 'num_leaves': 109, 'lambda_l1': 4.506588272812341e-05, 'lambda_l2': 2.5452579091348995e-07, 'feature_fraction': 0.7000000000000001, 'bagging_fraction': 1.0, 'bagging_freq': 6, 'min_gain_to_split': 0}

{'learning_rate': 0.17840010040986135, 'max_depth': 12, 'num_leaves': 251, 'lambda_l1': 0.004509589012189404, 'lambda_l2': 3.882151732343819e-08, 'feature_fraction': 0.30000000000000004, 'bagging_fraction': 1.0, 'bagging_freq': 8, 'min_gain_to_split': 0}

the code is:
    params = {
        'device_type': "gpu",
        'objective': 'multiclass',  #
        'metric': 'multi_logloss',  #
        "boosting_type": "gbdt",
        "num_class": 3,
        'random_state': 123,
        'verbosity': -1,  # hides "No further splits with positive gain, best gain: -inf" warnings
        "learning_rate": trial.suggest_float("learning_rate", 0.01, 0.9, log=True),  # 0.1
        'max_depth': trial.suggest_int('max_depth', 2, 12),
        'num_leaves': trial.suggest_int('num_leaves', 2, 256),  # def 31
        'lambda_l1': trial.suggest_float('lambda_l1', 1e-8, 10.0, log=True),  # 0
        'lambda_l2': trial.suggest_float('lambda_l2', 1e-8, 10.0, log=True),  # 0
        'feature_fraction': trial.suggest_float('feature_fraction', 0.1, 1.0, step=0.1),  # 1
        'bagging_fraction': trial.suggest_float('bagging_fraction', 0.1, 1.0, step=0.1),  # 1
        'bagging_freq': trial.suggest_int('bagging_freq', 0, 10),  # 0
        'min_gain_to_split': trial.suggest_int('min_gain_to_split', 0, 5),
    }

with a few changes here and there

I've been consistently having this issue in Kaggle and Colab notebooks while using the HDFSequence example and a GPU when I increase the number of leaves. Is there a generally accepted fix for this issue?

I also observe this issue with LightGBM version 3.3.2 and a GPU.
My setup for what it's worth:

OS: Pop!_OS 22.04
Python: 3.7.13
CUDA: 12.0
Nvidia Driver: 525.60.11
GPU: Nvidia 3090

I also observe this issue with LightGBM version 3.3.2 and a GPU.
My setup for what it's worth:

OS: Pop!_OS 22.04
Python: 3.7.13
CUDA: 12.0
Nvidia Driver: 525.60.11
GPU: Nvidia 3090

authors: DeiPlusAY Dronablo Jumabek Marmeladenbrot MrRobot2211 StrikerRUS Teeeto ZaydH abbey2017 arkothiwala chameleonTK chutcheson dpalbrecht guolinke kenyeung128 muttoni pavlexander rgranvil sharpe5 shiyu1994 victor-ab zacheberhart-kd

repo: microsoft/LightGBM

license: mit

license_source: bigquery


text:
[dask] Distributed training is VERY slow

Description
I have many Linux machines, every machine has A100 GPU *8, 128 threads per machine.
I found a problem thesedays in DaskLGB:

Fastest plan is using 1 machine 1*GPU (single mode), 8 threads. Running time=2.5min. Use 1300m GPU memory.
Slow plan is using 1 machine 2*GPU (local distribution mode), 8 threads per machine, the more GPUs, the slower the speed. Running time=4min. Use 1100m+700m memory in 2 GPUs.
VERY SLOW plan is 2*machine, every machine only 1 GPU, 8 threads per machine. It is too slow to use. Running time=30min. Use 1100m+700m memory in 2 GPUs.

I used the Dask command line to build a distributed system, doc: https://docs.dask.org/en/latest/how-to/deploy-dask/cli.html
So I'm very confuse that what is the significance of the existence of distributed DaskLGB??
Faster? NO
Saving GPU memory? NO
So have you encountered this problem when using multi-machine distributed LGB?
Environment info
LightGBM version or commit hash: 3.2.1(gpu)

`client = Client(address='xxx.xxx.xxx.xxx:12345')  # this is the scheduler ip
params = {
        'n_estimators'       : 1500,
        'objective'          : 'rmse',
        'reg_lambda'         : 0.3731450715226679,
        'reg_alpha'          : 0.30424044277458473,
        'subsample'          : 0.6413363492779808,
        'learning_rate'      : 0.013556055988623302,
        'min_child_weight'   : 91,
        'max_bin'            : 63,
        'random_state'       : 1111,
        'device_type'        : 'gpu',
        'colsample_bytree'   : 0.4237786478391063,
        'gpu_use_dp'         : False,
        'metric'             : 'None',
        'min_data_in_leaf'   : 880,
        'first_metric_only'  : True,
        'num_leaves'         : 248,
        'max_depth'          : 9,
        'verbosity'          : -1,
        }
model = lgb.DaskLGBMRegressor(client=client, **params)
print(f'X_train.shape={X_train.shape}   y_train.shape={y_train.shape}')

print(f'Process X to dask.array')
X_train = dask.array.from_array(X_train, chunks=(100000,3095)); X_train.compute() ; print(f'type(X_train)={type(X_train)}  X_train.shape={X_train.shape}')
y_train = dask.array.from_array(y_train, chunks=(100000,)); y_train.compute() ; print(f'type(y_train)={type(y_train)}  y_train.shape={y_train.shape}')

st = datetime.datetime.now()
print(f'Training start time:{st}')
model.fit(X_train, y_train)
et = datetime.datetime.now()
print(f'Training end time: {et}')
print(f'Running cost: {et-st}')`

@chixujohnny thanks for using LightGBM!
Right now the dask interface doesn't directly support distributed training using GPU, you can subscribe to #3776 if you're interested in that. Are you getting any warnings about this? I think it probably isn't using the GPU at all.
Furthermore, if your data fits in a single machine then it's probably best not using distributed training at all. The dask interface is there to help you train a model on data that doesn't fit on a single machine by having partitions of the data on different machines which communicate with each other, which adds some overhead compared to single-node training.

@jmoralez Thanks for your reply.
I find the problem now.
The GPU is really working, not CPU mode.
Using command to watch:  watch -n 1 nvidia-smi
To sovle this promblem, just using dask-cuda package.
Please see this doc to deploy your worker: https://docs.rapids.ai/api/dask-cuda/nightly/api.html
Just using command: dask-cuda-worker xxx.xxx.xxx.xxx:9876
Instead of: dask-worker xxx.xxx.xxx.xxx:9876
But, compare with dask-cude XGB, it is more usable than LGB. But it won't be particularly obvious.

Thanks for the follow up @chixujohnny. Were you able to train faster using dask-cuda workers?

Thanks for the follow up @chixujohnny. Were you able to train faster using dask-cuda workers?

Faster, but slower than 1 GPU mode.
I use 1 machine + 2 GPUs + LocalCUDACluster mode.

Thanks for the follow up @chixujohnny. Were you able to train faster using dask-cuda workers?

By the way, in a normal situation, when I training a regression job on only 1GPU. What is the useage rate of GPU?  On nvidia-A100 or nvidia-V100 GPU, the useage just 35%. It’s not like XGB has 100% usage. Is this normal?

On nvidia-A100 or nvidia-V100 GPU, the useage just 35%. Is this normal?

LightGBM's existing CUDA-based implementation does some work on the GPU and some on CPU (https://github.com/microsoft/LightGBM/issues/4082#issuecomment-948233113), which is why you might not see high GPU utilization.
This is a known issue, and @shiyu1994 and others are working on it. I recommend subscribing to updates on the following PRs to track the progress on a new implementation that should better-utilize the GPU:

#4528
#4630

The reviews on those pull requests are going to get quite large, so if you have questions about the plans please open new issues here that reference them, instead of commenting on the PRs directly.

On nvidia-A100 or nvidia-V100 GPU, the useage just 35%. Is this normal?

LightGBM's existing CUDA-based implementation does some work on the GPU and some on CPU (#4082 (comment)), which is why you might not see high GPU utilization.
This is a known issue, and @shiyu1994 and others are working on it. I recommend subscribing to updates on the following PRs to track the progress on a new implementation that should better-utilize the GPU:

WIP: [CUDA] New CUDA version #4528
[CUDA] New CUDA version Part 1 #4630

The reviews on those pull requests are going to get quite large, so if you have questions about the plans please open new issues here that reference them, instead of commenting on the PRs directly.

Thank you very much~

authors: chixujohnny jameslamb jmoralez


text:
[RFC] make deterministic parameter more thorough?

Proposal
When deterministic = true in parameters, other configuration values should be overwritten with values that will reduce randomness, even if those values make LightGBM slower or more resource-intensive.
Specifically, deterministic = true should result in:

force_row_wise = true
gpu_use_dp = true
seed = 708 (or some other fixed, positive, non-0 number)

Motivation
In my experience responding to issues here and on Stack Overflow, LightGBM's sources of non-determinism are often misunderstood. It'd be simpler (for both users and maintainers) if it was possible to get deterministic results by just setting {"deterministic": true}.
Examples of the discussions I'm referring to:

https://stackoverflow.com/questions/79212471/why-do-i-get-different-performance-on-different-runs-on-my-ml-model
#6683
#6671
#6604
#6203
#6094
#6069
https://github.com/microsoft/LightGBM/issues/5887#issuecomment-1545935847
#4722
#4562
#3761
#3654
#3372 (the PR that led to deterministic being introduced in #3494)
#2085

Description
There are plenty of implementation details that would need to be worked out, but in short I'm envisioning this updating would happen only on the C++ side, not in wrappers.
And that a new documentation section should be added (not in the deterministic parameter's part of https://lightgbm.readthedocs.io/en/latest/Parameters.html), explaining the limitations of this approach and how to further improve reproducibility.
Other Questions
How to handle multithreading with OpenMP?
Proposing we do the following:

audit all OpenMP pragmas and confirm that any where ordering matters (e.g. gradient accumulation) turn off parallelism when deterministic = true (as in #3494)
add test(s) that deterministic = true is sufficient to get completely deterministic results for the CPU version

But alternatively, we could do something simpler:

set num_threads = 1 whenever deterministic = true

Which is preferable?
Reviewers
@shiyu1994 @guolinke @StrikerRUS @borchero @jmoralez @btrotta I'd like to hear your thoughts on this. Thanks for your consideration!

I generally like this! In my experience, it is always slightly annoying to get ML libraries to behave purely deterministically. Having this feature built-in would be pretty nice.
That being said, I find it slightly weird to fix seed to a certain value inside the library code. I don't see how to achieve the desired behavior without it though...

I agree that setting deterministic = true should involve setting other required params for reproducibility implicitly. But I'm not sure which particular approach would be better...

I'm not sure which particular approach would be better...

Does this comment just refer to the 2 different approaches I mentioned for dealing with multi-threading? If so, I think we should start with the other sources of non-determinism (like setting force_row_wise = true) and come back to multi-threading separately.

I find it slightly weird to fix seed to a certain value inside the library code

To be clear, I'm proposing that passing deterministic = true set seed = 708 (or some other non-0 value) only if params does not already set seed to some non-0 value.
That's the simplest way I can think of to achieve this behavior, and I strongly suspect that most users setting deterministic = true would not care about which particular random seed is used, just that the same one is used on every run.

@jameslamb

Does this comment just refer to the 2 different approaches I mentioned for dealing with multi-threading?

Yes, my comment was about those ones.

Makes sense to me, I definitely think it is acceptable for the CUA version to have weaker guarantees about determinism in exchange for being much faster.

authors: StrikerRUS borchero jameslamb


text:
Traversal Package should honor Exclude Attribute

When using Microsoft.Build.Traversal, the Exclude attribute on the ProjectReference element isn't honored. I would expect it to remove all projects which are specified in the Exclude attribute.
<Project Sdk="Microsoft.Build.Traversal">
  <ItemGroup>
    <!-- All Projects except Experimental Projects-->
    <ProjectReference Include="src\**\*.*proj" Exclude="src\Experimental\**\*.*proj"/>
  </ItemGroup>
</Project>

Expected outcome:
Only reference projects under the src directory that aren't under Experimental.
Actual outcome:
The Exclude attribute is ignored and all projects under source are included, even experimental ones
Note: The example I gave was a single use case. I have been attempting to include all projects except for a specific kind (vcxproj) or explicit project paths.

This is simple MSBuild, I see no reason that Traversal would cause such behavior.  I am not able to repro it with the attached project set.
Can you attach a repro?
172-repro.zip
<Project Sdk="Microsoft.Build.Traversal/2.0.34">
  <ItemGroup>
    <!-- All Projects except Experimental Projects-->
    <ProjectReference Include="src\**\*.*proj" Exclude="src\Experimental\**\*.*proj"/>
  </ItemGroup>
</Project>

D:\Stuff\172-repro>msbuild
Microsoft (R) Build Engine version 16.7.0-preview-20251-04+8e4c57314 for .NET Framework
Copyright (C) Microsoft Corporation. All rights reserved.

Build started 5/7/2020 9:05:56 AM.
Project "D:\Stuff\172-repro\dirs.proj" on node 1 (default targets).
Project "D:\Stuff\172-repro\dirs.proj" (1) is building "D:\Stuff\172-repro\src\one\one.proj" (2) on node 1 (default targets).
Build:
  Hello from D:\Stuff\172-repro\src\one\one.proj!
Done Building Project "D:\Stuff\172-repro\src\one\one.proj" (default targets).

Project "D:\Stuff\172-repro\dirs.proj" (1) is building "D:\Stuff\172-repro\src\two\two.proj" (3) on node 1 (default targets).
Build:
  Hello from D:\Stuff\172-repro\src\two\two.proj!
Done Building Project "D:\Stuff\172-repro\src\two\two.proj" (default targets).

Done Building Project "D:\Stuff\172-repro\dirs.proj" (default targets).

Build succeeded.
    0 Warning(s)
    0 Error(s)

Time Elapsed 00:00:00.36

For some reason, I can't repo after retrying this approach. Maybe I had some typos in my paths we didn't catch. Sorry for the noise and thanks for the verification.

authors: jeffkl jeremytcorp

repo: microsoft/MSBuildSdks


text:
Clipping plane not working on Hololens 1 in some cases

Describe the bug
I am trying to add a clipping plane feature in my application using the MRTK standard shader. It works very well in the editor but once in the Hololens it doesn't.
I tried to build the project with the material gallery demo scene and here the clipping plane works. I surely missed something and maybe it's not a MRTK bug, but I can't figure what is the problem.
Screenshots
in the editor

I am using the shader from  #4946
in the Hololens 1

Expected behavior
Clipping plane works as in the editor
Your Setup (please complete the following information)

Unity Version 2019.1.8
MRTK Version RC2.1

Target Platform (please complete the following information)

HoloLens 1

Additional context
Add any other context about the problem here.

@Cameron-Micka, any ideas?

@benjamincoven what I'm guessing is going on is that particular shader permutation isn't getting included with the build at build time. Can you check in the material's YAML text if the "_CLIPPING_PLANE" shader keyword is included? It might look something like this: m_ShaderKeywords: _CLIPPING_PLANE, ...
Since in your screenshot it looks like you have the "_CLIPPING_PLANE" keyword enabled I'm guessing the ClippingPlane script is turning off that keyword automatically for you (maybe on scene onload?).
I plan to included all the clipping permutations in builds to allow developers to turn these features on dynamically, I just need to verify it doesn't explode our shader permutations.

One thing to try is check the "Clipping Plane" checkbox to enabled on the material before opening your scene/prefab that has the ClippingPlane component.

Thanks for your help.
The material YAML has the _CLIPPING_PLANE keyword, I tried this on one of the MeshRenderer:
void Update()
    {
        Debug.Log(Renderer.material.IsKeywordEnabled("_CLIPPING_PLANE"));
    }

It's true.
The material Clipping Plane property is true in the project, so it should be already enabled on scene load and the ClippingPlane is also in the scene YAML so it should load also on scene load.

That's interesting, thank you for checking if the keyword is enabled. I'm about to make a pull request which makes the toggling on/off the clipping primitives at runtime more robust (and should hopefully fix this issue). If you want a preview, here is my branch based off of mrtk_development: https://github.com/Cameron-Micka/MixedRealityToolkit-Unity/tree/clipping_fixes

@benjamincoven I've created a PR to hopefully address this issue: https://github.com/microsoft/MixedRealityToolkit-Unity/pull/5291

I confirm that the PR fix this issue. Thank you!

Yay! Thank you for checking it out.

authors: Cameron-Micka benjamincoven keveleigh

repo: microsoft/MixedRealityToolkit-Unity


text:
App remoting.dll not found when using the XR SDK

When trying to build my UWP app created in Unity via Visual Studio for the HoloLens 2 the following error occurs:  Error MSB3030 Could not copy the file "...\Plugins\ARM64\Microsoft.Holographic.AppRemoting.dll" because it was not found.
In this build I am trying the new XR SDK from Unity. Since I just wanted to try it out, there is only one cube in the scene.
Your setup (please complete the following information)

Unity Version 2019.3.4f1
MRTK Version 2.3

Target platform (please complete the following information)

HoloLens 2

This happens with or without the new XR SDK. The error can be made to go away if you disable WSA Holographic Remoting Supported (assuming you don't need this) in the PLayer XR Settings . Remoting in the editor should still work.

There are no "WSA Holographic Remoting Supported" options enabled.
Settings under Player/XR Settings are depricated disabled and not editable. Also in the XR Plugin Management/ Windows Mixed Reality menu Holographic Remoting ist disabled. So i forgot any Settings?

Ah my bad, I am not currently on the new XR version, that was a wrong assumption on my behalf.

Same issue here:

Unity 2019.3.7f1
MRTK 2.4
Hololens 2

I believe this was fixed in Unity 2019.3.9 and later. Closing as External, but will monitor for follow-up questions.

authors: FSchmidNT keveleigh tank-t-bird zantiu


text:
Add service extension wizard known issue

Overview
Extension Service Wizard is broken for optional inspector and profile. This change adds information to the known issues list for GA
Changes
Related #5654
Verification

As a reviewer, it is possible to check out this change locally by using the following
commands (substituting {PR_ID} with the ID of this pull request):
git fetch origin pull/{PR_ID}/head:name_of_local_branch
git checkout name_of_local_branch

/azp run mrtk_docs

This seems a very odd "workaround" recommending users edit official MRTK files to make changes.
Is it not better to simply update the create service feature to make the optional elements mandatory and allow the user to remove files they don't need.
This seems an overly complicated documentation workaround that is only going to have users creating issues as they wont' see the docs until AFTER they encounter the issue.  Seems a very bad user experience @davidkline-ms

source: gharchive/pull-request


text:
Bounds override fix

Overview
In BoundingBox, you can set a boundsOverride collider which essentially provides a "proxy object" to provide the bounds to the BoundingBox. There is an optional boxPadding that can be applied to this collider, to space out the BoundingBox around the object.
Unfortunately, this padding is achieved by destructively resizing the provided boundsOverride BoxCollider.
In the existing code, there is a line that is intended to compensate for this destructive resizing operation; in DestroyRig the code resizes the boundsOverride in the negative direction of the padding, effectively cancelling out the previous padding operation.
However, DestroyRig is actually called first when we are creating the rig (it's actually included inside CreateRig, ironically!), in addition to being called when we destroy the rig; it seems as though the original author of the code believed that DestroyRig was only called when the rig was being torn down (honest assumption, and shouldn't cause issues most of the time!)
This has the ill effect, however, of resizing the boundsOverride one too many times when you repeatedly set the BoundingBox to be Active/Inactive. If you continue activating/deactivating the BoundingBox gameobject, the bounds will continue to grow/shrink to a very large (and incorrect) size!
This PR fixes this behavior in the following way: instead of applying negative padding to "cancel out" the resizing operation, it simply resets the boundsOverride to whatever size it had when the BoundingBox was enabled, and when CreateRig() was called.
This resolves #7997 :)
Changes

Resolves #7997 by preventing unwanted boundsOverride resizing behavior when toggling the status of the root BoundingBox object.
Adds a Vector3? initialBoundsOverrideSize which is used to record the size of the boundsOverride when the rig is constructed.
Adds code in DestroyRig to reset the boundsOverride size to the recorded initialBoundsOverrideSize when destroying/tearing down the rig.
Adds unit test that covers the issue reported in #7997.

Verification

An additional test has been added to verify that changing boundsOverride size and toggling the active status of the BoundingBox does not destructively modify the boundsOverride size.

/azp run

@thalbern please resolve your change requests, at your convenience :) I have fixed the style issues and have applied the changes to BoundsControl as well.

/azp run


text:
Upgrade to dotnet7 and avoid downgrades when removing packages

the removal of useless packages doesn't track versions and can remove a higher version dependency simply because it is a transitive one. This small fix prevents this issue.

@microsoft-github-policy-service agree

Don't forget here: https://github.com/microsoft/NugetNinja/blob/main/.github/workflows/build.yml

Bigger update... I moved solution to net 8 and since dotnet list package is broken with shproj, I decided to re-use this code to generate an excel file with all the packages.

Maybe also updating this file is needed:
https://github.com/microsoft/NugetNinja/blob/main/.github/workflows/build.yml

Thank you for the contribution!!!

repo: microsoft/NugetNinja


text:
New rules, bump deps, output

This PR adds a few new backdoor rules, bumps dependencies (AppInspector in particular), and improves the output.

I think we'll have some conflicts here, feel free to trash mine in favor of yours, @gfs.

I think we'll have some conflicts here, feel free to trash mine in favor of yours, @gfs.

I’ll figure out the right way to merge on Monday. Probably will manually pick your changes into mine.

I think we'll have some conflicts here, feel free to trash mine in favor of yours, @gfs.

I’ll figure out the right way to merge on Monday. Probably will manually pick your changes into mine.

Sounds good, I won't make any more structural changes -- maybe a few rule updates, but that's it, for the next couple days.

I think we'll have some conflicts here, feel free to trash mine in favor of yours, @gfs.

I’ll figure out the right way to merge on Monday. Probably will manually pick your changes into mine.

Sounds good, I won't make any more structural changes -- maybe a few rule updates, but that's it, for the next couple days.

Feel free to make rule updates directly in my PR

folded these changes into #210

authors: gfs scovetta

repo: microsoft/OSSGadget


text:
About the problems in the update process after I added python

This issue has been moved from a ticket on Developer Community.

I waited for a long time and found that it did not move. Then I wanted to close it. Then I pressed Pause and found that it could not be closed

Original Comments
Feedback Bot on 10/25/2022, 09:32 PM:
(private comment, text removed)

Original Solutions
(no solutions)

broken image:

Doesn't seem like a PTVS issue.

Assigned internal bug to Setup

authors: StellaHuang95 judej vsfeedback

repo: microsoft/PTVS


text:
[shortcut guide] add "emoji keyboard" shortcut

Provide a description of the new feature / enhancement
Windows 10 supports the shortcut Win + . which opens the emoji keyboard.
This is a very unknown shortcut, but it is pretty useful. E.g. I used websites like https://emojikeyboard.top/ over years, until I noticed that Windows even has an emoji keyboard build in...
Therefore, I would like to see the "emoji keyboard" shortcut in the shortcut guide as well.

Issue is already tracked
Thank you for your issue! We've tracked your report already in issue #179
Thanks for helping us to make PowerToys a better piece of software.

Thanks for pointing me to the correct issue!

authors: Aaron-Junker fm-sys

repo: microsoft/PowerToys


text:
Mute button on Microsoft USB Speaker to control VCM

Description of the new feature / enhancement
I have a Microsoft Modern USB-C Speaker.
When I am muted by VCM and I press the mic button on my Microsoft speaker I want it to unmute both the speaker, and VCM. (But, I do not think it should unmute my video.)
Scenario when this would be used?
When I am in conference calls and need to quickly unmute to respond, it is sometimes easier to hit the mute on the speaker because it's a big red target.
Supporting information
No response

Don't know this specific device. I'm wondering if it sends a key command to the pc when pushing the button. Maybe you could catch it in keyboard manager and remap it to the hotkey for vcm?

if it sends a keycode, we may be able to.  Does Keyboard manager detect the button press?  I'd argue this is a dup of #13920

authors: Jay-o-Way charris-msft crutkas


text:
Report bug from toolbar context menu causes toolbar icon to become unresponsive and crashes PowerToys

Microsoft PowerToys version
0.55.0
Running as admin

[ ] Yes

Area(s) with issue?
General
Steps to reproduce
Right click on the toolbar entry, choose Report bug. The entry should become unresponsive and the app crashes in a few seconds.
Generated crash report
✔ Expected Behavior
The context menu option to bring me here
❌ Actual Behavior
The option does nothing and causes PowerToys to crash.
Other Software
No response

This has been worked on for the 0.74.0 release. Please update PowerToys to the latest version. 😉
https://github.com/microsoft/PowerToys/releases

authors: Numerlor jaimecbernardo


text:
0x80070005 Access denied .

Microsoft PowerToys version
0.55.1-x64
Running as admin

[X] Yes

Area(s) with issue?
Installer
Steps to reproduce
Run the installer PowerToysSetup-0.55.1-x64.exe in admin mode.
✔ Expected Behavior
Proper installation.
❌ Actual Behavior

PowerToys_(Preview)_x64_20220203092343.log
Other Software
No response

Seems like there is an issue installing dotnet runtime 5 to %programdata%
cc: @yuyoyuppe FYI

@balaji-ch could you try installing dotnet5 manually and then install PT v0.55.1?

Yep, looks like an error moving from the MSI moving the .net 5 installer around.
[2A84:4168][2022-02-03T09:23:58]w343: Prompt for source of package: DotnetRuntime5, payload: DotnetRuntime5, path: C:\Users\I19152\Desktop\windowsdesktop-runtime-5.0.13-win-x64.exe
[2A84:4168][2022-02-03T09:23:58]i338: Acquiring package: DotnetRuntime5, payload: DotnetRuntime5, download from: https://download.visualstudio.microsoft.com/download/pr/2bfb80f2-b8f2-44b0-90c1-d3c8c1c8eac8/409dd3d3367feeeda048f4ff34b32e82/windowsdesktop-runtime-5.0.13-win-x64.exe
[0EA0:459C][2022-02-03T09:24:12]e000: Error 0x80070005: Failed to move C:\Users\I19152\AppData\Local\Temp\{71449C86-2011-4DD0-8645-08A66AA26C08}\DotnetRuntime5 to C:\ProgramData\Package Cache\.unverified\DotnetRuntime5
[0EA0:459C][2022-02-03T09:24:12]e000: Error 0x80070005: Failed to transfer working path to unverified path for payload: DotnetRuntime5.
[0EA0:459C][2022-02-03T09:24:12]e000: Error 0x80070005: Failed to cache payload: DotnetRuntime5
[2A84:4168][2022-02-03T09:24:12]e314: Failed to cache payload: DotnetRuntime5 from working path: C:\Users\I19152\AppData\Local\Temp\{71449C86-2011-4DD0-8645-08A66AA26C08}\DotnetRuntime5, error: 0x80070005.
[2A84:4168][2022-02-03T09:24:12]e349: Application requested retry of payload: DotnetRuntime5, encountered error: 0x80070005. Retrying...
[2A84:4168][2022-02-03T09:24:12]w343: Prompt for source of package: DotnetRuntime5, payload: DotnetRuntime5, path: C:\Users\I19152\Desktop\windowsdesktop-runtime-5.0.13-win-x64.exe
[2A84:4168][2022-02-03T09:24:15]i338: Acquiring package: DotnetRuntime5, payload: DotnetRuntime5, download from: https://download.visualstudio.microsoft.com/download/pr/2bfb80f2-b8f2-44b0-90c1-d3c8c1c8eac8/409dd3d3367feeeda048f4ff34b32e82/windowsdesktop-runtime-5.0.13-win-x64.exe
[0EA0:459C][2022-02-03T09:24:28]e000: Error 0x80070005: Failed to move C:\Users\I19152\AppData\Local\Temp\{71449C86-2011-4DD0-8645-08A66AA26C08}\DotnetRuntime5 to C:\ProgramData\Package Cache\.unverified\DotnetRuntime5
[0EA0:459C][2022-02-03T09:24:28]e000: Error 0x80070005: Failed to transfer working path to unverified path for payload: DotnetRuntime5.
[0EA0:459C][2022-02-03T09:24:28]e000: Error 0x80070005: Failed to cache payload: DotnetRuntime5
[2A84:4168][2022-02-03T09:24:28]e314: Failed to cache payload: DotnetRuntime5 from working path: C:\Users\I19152\AppData\Local\Temp\{71449C86-2011-4DD0-8645-08A66AA26C08}\DotnetRuntime5, error: 0x80070005.
[2A84:4168][2022-02-03T09:24:28]e349: Application requested retry of payload: DotnetRuntime5, encountered error: 0x80070005. Retrying...
[2A84:4168][2022-02-03T09:24:28]w343: Prompt for source of package: DotnetRuntime5, payload: DotnetRuntime5, path: C:\Users\I19152\Desktop\windowsdesktop-runtime-5.0.13-win-x64.exe
[2A84:4168][2022-02-03T09:24:31]i338: Acquiring package: DotnetRuntime5, payload: DotnetRuntime5, download from: https://download.visualstudio.microsoft.com/download/pr/2bfb80f2-b8f2-44b0-90c1-d3c8c1c8eac8/409dd3d3367feeeda048f4ff34b32e82/windowsdesktop-runtime-5.0.13-win-x64.exe
[0EA0:459C][2022-02-03T09:24:45]e000: Error 0x80070005: Failed to move C:\Users\I19152\AppData\Local\Temp\{71449C86-2011-4DD0-8645-08A66AA26C08}\DotnetRuntime5 to C:\ProgramData\Package Cache\.unverified\DotnetRuntime5
[0EA0:459C][2022-02-03T09:24:45]e000: Error 0x80070005: Failed to transfer working path to unverified path for payload: DotnetRuntime5.
[0EA0:459C][2022-02-03T09:24:45]e000: Error 0x80070005: Failed to cache payload: DotnetRuntime5
[2A84:4168][2022-02-03T09:24:45]e314: Failed to cache payload: DotnetRuntime5 from working path: C:\Users\I19152\AppData\Local\Temp\{71449C86-2011-4DD0-8645-08A66AA26C08}\DotnetRuntime5, error: 0x80070005.
[2A84:0648][2022-02-03T09:24:45]e000: Error 0x80070005: Failed while caching, aborting execution.

@balaji-ch , could you please try to install directly from here?
https://download.visualstudio.microsoft.com/download/pr/2bfb80f2-b8f2-44b0-90c1-d3c8c1c8eac8/409dd3d3367feeeda048f4ff34b32e82/windowsdesktop-runtime-5.0.13-win-x64.exe
/needinfo

Microsoft_Windows_Desktop_Runtime_-5.0.13(x64)_20220204211421.log
i get this error when i install  windowsdesktop-runtime-5.0.13-win-x64.exe

Looks like some permission issue? Try running it as admin? Also try if you have read&write access to following dirs:

C:\Users\I19152\AppData\Local\Temp\
C:\ProgramData\Package Cache.unverified\

I solved this "thanks" to @stefansjfw .
I actually had to grant 'Full control' permissions on AppData\Local\Temp to the Administrator -- when I entered the permissions settings I got a warning of "disordered" permissions, but read&write was already there and was not enough, and adding 'Modify' was also insufficient.
I just don't know how secure is this, but the installer worked at this point for both PowerToys and dotnet runtime alone.

I'm not sure what could cause this lack of permissions if you're on you personal machine and admin account. Should be a problem, as for me, those permissions are by default. Thanks for the feedback!

I solved this "thanks" to @stefansjfw . I actually had to grant 'Full control' permissions on AppData\Local\Temp to the Administrator -- when I entered the permissions settings I got a warning of "disordered" permissions, but read&write was already there and was not enough, and adding 'Modify' was also insufficient.
I just don't know how secure is this, but the installer worked at this point for both PowerToys and dotnet runtime alone.

@emmegamma, Thanks so much man. You just saved us hours of tinkering.

authors: Crown0815 balaji-ch emmegamma franky920920 jaimecbernardo stefansjfw


text:
Error on PC Startup

Microsoft PowerToys version
0.60.1.0
Running as admin

[X] Yes

Area(s) with issue?
General
Steps to reproduce
Version: 0.60.1.0
OS Version: Microsoft Windows NT 10.0.22000.0
IntPtr Length: 8
x64: True
Date: 15-07-2022 21:31:52
Exception:
System.IO.FileNotFoundException: Could not load file or assembly 'System.Windows.Forms, Version=6.0.2.0, Culture=neutral, PublicKeyToken=b77a5c561934e089'. The system cannot find the file specified.
File name: 'System.Windows.Forms, Version=6.0.2.0, Culture=neutral, PublicKeyToken=b77a5c561934e089'
at PowerLauncher.MainWindow.WindowTop()
at PowerLauncher.MainWindow.InitializePosition()
at PowerLauncher.MainWindow.OnLoaded(Object sender, RoutedEventArgs e)
at System.Windows.RoutedEventHandlerInfo.InvokeHandler(Object target, RoutedEventArgs routedEventArgs)
at System.Windows.EventRoute.InvokeHandlersImpl(Object source, RoutedEventArgs args, Boolean reRaised)
at System.Windows.UIElement.RaiseEventImpl(DependencyObject sender, RoutedEventArgs args)
at System.Windows.UIElement.RaiseEvent(RoutedEventArgs e)
at System.Windows.BroadcastEventHelper.BroadcastEvent(DependencyObject root, RoutedEvent routedEvent)
at System.Windows.BroadcastEventHelper.BroadcastLoadedEvent(Object root)
at System.Windows.Media.MediaContext.FireLoadedPendingCallbacks()
at System.Windows.Media.MediaContext.FireInvokeOnRenderCallbacks()
at System.Windows.Media.MediaContext.RenderMessageHandlerCore(Object resizedCompositionTarget)
at System.Windows.Media.MediaContext.RenderMessageHandler(Object resizedCompositionTarget)
at System.Windows.Media.MediaContext.Resize(ICompositionTarget resizedCompositionTarget)
at System.Windows.Interop.HwndTarget.OnResize()
at System.Windows.Interop.HwndTarget.HandleMessage(WindowMessage msg, IntPtr wparam, IntPtr lparam)
at System.Windows.Interop.HwndSource.HwndTargetFilterMessage(IntPtr hwnd, Int32 msg, IntPtr wParam, IntPtr lParam, Boolean& handled)
at MS.Win32.HwndWrapper.WndProc(IntPtr hwnd, Int32 msg, IntPtr wParam, IntPtr lParam, Boolean& handled)
at MS.Win32.HwndSubclass.DispatcherCallbackOperation(Object o)
at System.Windows.Threading.ExceptionWrapper.InternalRealCall(Delegate callback, Object args, Int32 numArgs)
at System.Windows.Threading.ExceptionWrapper.TryCatchWhen(Object source, Delegate callback, Object args, Int32 numArgs, Delegate catchHandler)
✔ Expected Behavior
No response
❌ Actual Behavior
No response
Other Software
No response

Did it occur only once or are you able to repro it? /needinfo
Must be a duplicate of https://github.com/microsoft/PowerToys/issues/18275

Happened only once, and hasn't reappeared since. As such, there was no user input before the error occurred - I booted up my PC, logged in, and this error popped up while my startup programs were loading up. The only input I gave my PC in this entire process was entering my password.

Thank you for the clarification.
Closing this as /dup #19482

authors: davidegiacometti mercuryprobe


text:
[Run] - Revisit UpdateManager

UpdateManager Is copied from squirrel to minimize impact. Due to plugin model, unsure if we can totally remove it but would be nice if we could.

It was already deleted at https://github.com/microsoft/PowerToys/pull/4878

It was already deleted at https://github.com/microsoft/PowerToys/pull/4878

if this is removed, we can update and remove Squirrel then.  I'll do that.
https://github.com/microsoft/PowerToys/blob/master/NOTICE.md#squirrelwindows-license

if this is removed, we can update and remove Squirrel then.  I'll do that.
https://github.com/microsoft/PowerToys/blob/master/NOTICE.md#squirrelwindows-license

authors: crutkas mykhailopylyp


text:
Cannot rebind numpad minus

Microsoft PowerToys version
0.73.0
Installation method
Microsoft Store
Running as admin
No
Area(s) with issue?
Keyboard Manager
Steps to reproduce
Select the panel, continue to the keybinding of choice. attempt to reassign keyboard numpad minus.
✔ Expected Behavior
I can change keybindings differently from numpad minus from the top of my querty keyboard.
❌ Actual Behavior
Instead of keyboard minus  being unchanged and keyboard numpad minus being changed. The system is unaware of the difference.
Other Software
I use all the cool toys. I am a developer
.... only system impacting is the full install of git for windows including *find and other utilities.
I have powertoys for my keyboard.
no other keyboard or keylogging is installed to my advanced knowledge
I don't even have a full cygwin install just the half realized version that git offers after overwrite.

I noticed it was different.. but the ui is not changed. According to the ui my 0-9 qwerty without 10 key should be minus but it is grave. All the settings are correct.. the ui did do what I wanted. The outcome was the expected outcome after a bit of work. I just did not notice I was changing them separately in the ui. I did by keypress.

This should be renamed to .. user has no clue if they changed - or numpad -

This has been worked on for the 0.74.0 release. Please update PowerToys to the latest version. 😉
https://github.com/microsoft/PowerToys/releases

authors: AnthonyJClink jaimecbernardo


text:
Multi Desktop Feature Enhancement

Description of the new feature / enhancement
Adding Multi Desktop enhancement into the PowerToys collection will help multi taskers a lot. Current version doesn't have any shortcuts other than linear switching with ctrl + win + L/R
It'd be great we can switch to specefic desktop with hot key & main part, after switching desktop name will be shown in the center or somewhere for one or two seconds so that we know which window we jumped to while Ctrl Win Arrows
Here is the additional app which is already been made. But I think Microsoft should have not abandoned its own pro feature halfway.
https://peachapp.net/
Scenario when this would be used?
I work as a Project Manager who has 10 repos open simultaneously on every desktop along with other supporting windows. and Skype pinned for All Desktop windows. Right now it's too confusing to switch windows as I cannot be sure which one I switched to, it's too time consuming & effort taking to go from the first desktop to the last one while passing through all desktops in between. As per my personal requirement, Flashing the Desktop name for a second is more useful than additional hotkeys
Supporting information
Reference App:
https://peachapp.net/

There are several other issues related to virtual desktops which read similar to what you are proposing here. Could your review these and close or refine this issue afterward?
#19, #24, #32, #3737

closing as similar already added way back in time

authors: TheJoeFin hardiklakhalani


text:
Dark Mode: Link color hard to see

Description of the new feature / enhancement
A change of color to links to be easier to see on the dark background
Scenario when this would be used?
Anytime there's a link on the PowerToys App
Supporting information

Might have been fixed, though worth a proper test as I didn't see anything in the changelogs referencing this.
Was it dark purple for others?

The problem is that these links use the accent color, which I think is not a good idea.
cc: @niels9001

Ok, after asking a UX designer, we're not the only ones that use the accent color for links and as it is a users choice we won't fix this.


text:
Plugin startup failed

Microsoft PowerToys version
0.78.0~0.81.0
Installation method
GitHub
Running as admin
Yes
Area(s) with issue?
PowerToys Run
Steps to reproduce
PowerToysReport_2024-05-10-09-55-24.zip
When PowerToys starts, it prompts that the plug-in startup failed. At first, I had version 0.79. I tried to upgrade to the latest version 0.81 to solve the problem, but it did not solve the problem. Later, I uninstalled and reinstalled version 0.78. The problem still exists. I started PowerToys Run. The Program plug-in prompts that it cannot be started. I like this plug-in to quickly start the program. Now this plug-in cannot be started.
✔ Expected Behavior
Start the Program plug-in normally
❌ Actual Behavior
Unable to start
Other Software
No response

[2024-05-09 09:37:35.3444] [ERROR] [C:\a\_work\1\s\src\modules\launcher\Wox.Plugin\PluginPair.cs::239]
-------------------------- Begin exception --------------------------
Message: Fail to Init plugin: Program

Exception full name  : System.Runtime.InteropServices.COMException
Exception message    :
Exception stack trace:
   at WinRT.ExceptionHelpers.<ThrowExceptionForHR>g__Throw|39_0(Int32 hr)
   at WinRT.ExceptionHelpers.ThrowExceptionForHR(Int32 hr)
   at WinRT.EventSource`1.Subscribe(TDelegate del)
   at Windows.ApplicationModel.PackageCatalog.add_PackageInstalling(TypedEventHandler`2 value)
   at Microsoft.Plugin.Program.Programs.PackageCatalogWrapper.add_PackageInstalling(TypedEventHandler`2 value)
   at Microsoft.Plugin.Program.Storage.PackageRepository..ctor(IPackageCatalog packageCatalog, PluginInitContext context)
   at Microsoft.Plugin.Program.Main.Init(PluginInitContext context)
   at Wox.Plugin.PluginPair.InitPlugin(IPublicAPI api)
Exception source     : WinRT.Runtime
Exception target site: Void <ThrowExceptionForHR>g__Throw|39_0(Int32)
Exception HResult    : -2147023446
-------------------------- End exception --------------------------

/dup #19845

authors: cameol davidegiacometti


text:
[Keyboard manager] "Some of the keys could not be mapped" when remapping Win shortcut

Environment
Windows build number: 10.0.18363.836
PowerToys version: 0.18.0
PowerToy module for which you are reporting the bug (if applicable): [Keyboard manager]

Steps to reproduce
Remap the Win (left) key to Alt+Space in "Remap shortcuts", click "Ok".
Expected behavior
I expect the Win (left) key to be remapped to Alt+Space. If I am not allowed to do this, I should get a clear error message saying that I am not allowed to do so.
Actual behavior
I get a message saying "Some of the keys could not be remapped. Continue anyways?".
Screenshots

Currently we do not support remapping a key to a shortcut or vice versa. Both need to have atleast 2 keys. We plan to add this feature in a future update as there have been many requests for it.
Currently if you see any blank drop down in the row, that means that the shortcut is incomplete.

Alright thanks, you can go ahead and close this issue then. Do you know if there is a way to replace the regular Windows search feature with the PowerToys run feature?

+1 here, I also need this feature to map right alt key on my notebook to become right click (shift + F10). Currently I am using AutoHotKey to get this done....

In case anyone else want's to replace Windows Search / pressing Windows/Start with PowerToys Run, it can be achieved by using AutoHotkey with the following script:
~LWin::Send !{space}

Would be nice to have a feature in PowerToys to swap out Windows Search with the launcher, but I guess this will do for now.

+1, I also want to map CapLocks to Ctrl + Alt, but it doesn't support now..

still waiting for your update to remap Win key (left) to sth else in some apps (games)

Is there a solution to this problem? I searched for all solutions on the Internet and even on YouTube and many sites. Is this the problem and I did not find a clear solution? It has been proposed since 2020!! I have been searching for more than a month on this problem and did not find a solution. I used the AutoHotkeyUX program, but I encountered a problem when using two screens. Why don't you take the codes in the AutoHotkeyUX program and reprogram them?

Currently we do not support remapping a key to a shortcut or vice versa. Both need to have atleast 2 keys. We plan to add this feature in a future update as there have been many requests for it.

what became of this? 😧

authors: BlaxWalker Jackiexiao abdo-gorj arjunbalgovind cridus martinmine specurial


text:
Problem with Keyboard Manager all of a sudden

Microsoft PowerToys version
0.85.1
Installation method
PowerToys auto-update
Running as admin
Yes
Area(s) with issue?
Keyboard Manager
Steps to reproduce
The thing is, I added a mapping because I'm using an Apple keyboard inside windows. I'm mapping the options key and the command key.
Everything worked fine since a while ago.
✔ Expected Behavior
That everything works properly forever...
❌ Actual Behavior
Suddenly, while I'm working, all the keys behave strange. When I try to copy with Ctrl + C I only see a "c" letter on the text, it seems that the control doesn't work anymore, and it thinks I'm writing a c. Also, it seems that some key is constantly pressed, because when all this starts, if I press Esc the software programs change between them and if I press Alt other things happen. I'm trying to know what key it thinks is pressed, but I don't know yet.
When this happens the first time, I thought it was my keyboard. Finally, I discovered that if I close Power Toys it stops. Then I can start it again and everything is fine until "I don't know when" Maybe while I'm working I press some kind of shortcut that starts everything, but I can't debug what is happening. Also, if I only deactivate the Keyboard Manager, it all works again.
I hope I am explaining everything properly, as I'm Spanish, and my English is not the best.
Other Software
No response

https://github.com/microsoft/PowerToys/issues/35638

/dup https://github.com/microsoft/PowerToys/issues/17344

authors: Ivluengo crutkas inv2004