text:
Object Detection Data Preview

In the Data page, we need to figure out how to show the object frame properly

PR isn't in for this. IMO we should just close this item because 1. We're not shipping it and 2. This will be verified in an Object detection bug bash.
We could reopen but I think this was more for Tevin's tracking.

authors: LittleLittleCloud beccamc

repo: dotnet/machinelearning-modelbuilder


text:
GPU Service not found. Falling back to CPU AutoML Service.

System Information (please complete the following information):

Model Builder Version: 16.1.0.2027905
Visual Studio 2019 (16.7.2)

Describe the bug
Try model builder to build image classification and reports GPU Service not found. Falling back to CPU AutoML Service.
To Reproduce
Steps to reproduce the behavior:
Use model builder steps to point where you click train and reports the error
Expected behavior
Should use GPU that is available
I have seen this reported in older issues and they appear to be tagged closed etc.
I have just updated VS fully to latest spec. Pulled down the model builder using VS Install tool so assume that is the latest. I have the latest NVidia drivers in place. Do I need to install anything else to get this to see my GPU?

Found the update and now I have a selection for GPU so can close :)

Pulling down the cuda drivers and cuDNN, will see if that resolves and then close the ticket if that is the case

One the How to install GPU support in Model Builder page it says:
Install CUDA V10.0
Install cuDNN V7.6.4 for CUDA 10
If you try and install CUDA V10.0 against Visual Studio 2019 (16.7.2) it says could not detect a supported VS, please install or components will not install correctly.
Is the doc page out of date? (https://docs.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/install-gpu-model-builder)
Should I install CUDA V11? if no how do I get V10 to correctly install the VS parts

@WozSoftware Sorry you've run into this problem. You need CUDA V10.  Installing a newer version won't work. Let me try to install against 16.7.2 and see if I can repro.
Thanks for reporting!

@WozSoftware I've looked at this further. We don't actually need that VS integration. It's for NSight integration which we don't use. ML.NET is using the CUDA capabilities, not VS (I know, that's not intuitive since you're accessing it via VS). You can uncheck the VS Integration in the installer...

@luisquintanilla Can we add into the documentation to uncheck this option. If users don't have a VS2017 version installed on their machine I think the CUDA installation will completely fail.  cc @JakeRadMSFT

Hi,
Thanks for digging into this and updating :)
Yep, updating the documentation would be good.
Just into the ML stuff and have to say that I thought we had kissed goodbye to DLL hell thanks to .NET but all the ML stuff appears to want to put us all back in that space lol
Feel free to close down the ticket. I would do it but not sure if you want left open so the docs people see before it is close
All the best
Warren

Right. Installed CUDA 10.0 with VS disabled. All good.
Copied the cnDNN dll into place as per instructions (cudnn64_7.dll
Installed the latest model builder GPU update along with the CPU version. Both at 16.1.1.2041102
Noticed that the GPU test page showed "We cannot confirm CUDA compatibility yet. Training may fail"
GPU extension was tested fine and CUDA compatible GPU detected fine.
I am running NVidia 452.06
Here is the log
2020-09-08 17:44:38.4758 DEBUG Set log file path to C:\Users\warre\AppData\Local\Temp\MLVSTools\logs\dbc14b16-f38f-489e-98c6-e2ddbe1c9481.txt (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
2020-09-08 17:44:42.7375 DEBUG EnvironmentTab_DataContextChanged (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
2020-09-08 17:44:48.9645 DEBUG Disposing AutoMLService Client (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
2020-09-08 17:45:09.9787 DEBUG C:\Users\warre\source\repos\MLBedTest\Hotel Beds (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
2020-09-08 17:45:21.8803 INFO |     Trainer                              MicroAccuracy  MacroAccuracy  Duration #Iteration                     | (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:45:22.2469 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:45:22.3778 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:45:22.4068 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:45:22.4068 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0048709. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:45:22.4148 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:05.5453 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:05.5453 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:05.5453 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:05.5453 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0002833. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:05.5453 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:11.7996 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:11.7996 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:11.8036 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:11.8036 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0002960. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:11.8036 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:17.3566 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:17.3566 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:17.3566 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:17.3566 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:17.3566 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0003007. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:22.8027 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:22.8527 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:22.8527 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:22.8527 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0005171. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:22.8527 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:28.3687 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:28.3687 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:28.3687 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:28.3687 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0002556. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:28.3687 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:33.9436 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:33.9456 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:33.9456 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:33.9456 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0002958. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:33.9456 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:39.5246 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:39.5246 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:39.5246 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:39.5246 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:39.5246 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0003275. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:45.1246 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:45.1246 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:45.1246 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:45.1246 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:45.1246 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0002998. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:50.6214 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/_7]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:50.6214 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:50.6214 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:50.6324 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel finished. Elapsed 00:00:00.0002835. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:50.6324 INFO [Source=ImageClassificationTrainer; Ensuring meta files are present., Kind=Trace] Channel disposed (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:56.1957 INFO [Source=AutoML, Kind=Error] Pipeline crashed: xf=ValueToKeyMapping{ col=Label:Label} xf=RawByteImageLoading{ col=ImageSource_featurized:ImageSource imageFolder=} xf=ColumnCopying{ col=Features:ImageSource_featurized} tr=ImageClassification{} xf=KeyToValueMapping{ col=PredictedLabel:PredictedLabel} cache=- . Exception: Tensorflow.TensorflowException: 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/7]]
0 successful operations.
0 derived errors ignored.
at Tensorflow.Status.Check(Boolean throwException)
at Microsoft.ML.TensorFlow.TensorFlowUtils.Runner.Run()
at Microsoft.ML.Vision.ImageClassificationTrainer.CacheFeaturizedImagesToDisk(IDataView input, String labelColumnName, String imageColumnName, ImageProcessor imageProcessor, String inputTensorName, String outputTensorName, String cacheFilePath, Dataset dataset, Action1 metricsCallback, Nullable1 validationFraction)
at Microsoft.ML.Vision.ImageClassificationTrainer.TrainModelCore(TrainContext trainContext)
at Microsoft.ML.Trainers.TrainerEstimatorBase2.TrainTransformer(IDataView trainSet, IDataView validationSet, IPredictor initPredictor)    at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)
at Microsoft.ML.Data.EstimatorChain1.Fit(IDataView input)    at Microsoft.ML.AutoML.RunnerUtil.TrainAndScorePipeline[TMetrics](MLContext context, SuggestedPipeline pipeline, IDataView trainData, IDataView validData, String groupId, String labelColumn, IMetricsAgent1 metricsAgent, ITransformer preprocessorTransform, FileInfo modelFileInfo, DataViewSchema modelInputSchema, IChannel logger) (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:56.1957 INFO [Source=ImageClassificationTrainer; ImageClassificationTrainer, Kind=Trace] Channel started (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:56.2137 INFO 2 root error(s) found.
(0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
(1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node resnet_v2_50/conv1/Conv2D}}]]
[[resnet_v2_50/SpatialSqueeze/7]]
0 successful operations.
0 derived errors ignored. (Microsoft.ML.ModelBuilder.Utils.Logger.Info)
2020-09-08 17:46:56.3710 DEBUG Disposing AutoMLService Client (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
2020-09-08 17:46:56.3830 DEBUG Value cannot be null.
Parameter name: source
at System.Linq.Enumerable.Select[TSource,TResult](IEnumerable1 source, Func2 selector)
at Microsoft.ML.ModelBuilder.AutoMLService.Experiments.AutoMLExperiment`3.d__21.MoveNext() in //src/Microsoft.ML.ModelBuilder.AutoMLService/Experiments/AutoMLExperiment.cs:line 117
--- End of stack trace from previous location where exception was thrown ---
at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
at Microsoft.ML.ModelBuilder.AutoMLEngine.d__26.MoveNext() in //src/Microsoft.ML.ModelBuilder.AutoMLService/AutoMLEngineService/AutoMLEngine.cs:line 134 (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)
2020-09-08 17:47:02.4469 DEBUG Open Log FileC:\Users\warre\AppData\Local\Temp\MLVSTools\logs\dbc14b16-f38f-489e-98c6-e2ddbe1c9481.txt (Microsoft.ML.ModelBuilder.Utils.Logger.Debug)

Do I have to install it with disabled VS integration?
Interestingly, tensorflow works well with GPU. Model builder doesnt. I thought modelbuilder uses tensorflow under the hood.

I think we should update CPU and GPU of ML Builder versions to same.

@WozSoftware I had the same issue.
I resolved it by adding the path C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\bin to %PATH% environment variable. I also had to enable windows 10 long path support in order to add this path to the env variable.

@msschl Just tried, no joy.

@WozSoftware Sorry you're hitting this issue.
From a clean machine the versions from this documentation work:
https://docs.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/install-gpu-model-builder
No other versions of Cuda/CuDNN can be installed in parallel.
Unfortunately, the installer for CUDA has a few issues. For CUDA Installer- I recommend only installing runtime components. For the Display Driver - I recommend the latest from NVidia.
What NVidia Video Card do you have?

I've tried for about 3 hours over the last few days - It's driving me mental
Specs
ML Model Builder ext - 16.3.0.2056001
ML GPU Ext - 16.3.0.2056001
VS 2019 - 16.8.4
cuda_10.0.130_411.31_win10.exe - Cuda 10 Version
cuDNN v7.6.4 (September 27, 2019), for CUDA 10.0
I'm not sure it's relevant but I have mlnet CLI too
AMD Ryzen 7
64GB Ram
Nvidia Geforce RTX2060 Super
I've installed and reinstalled Cuda 10 a dozen times, I've tried all options, I've tried no VS, With VS, Just Runtime.
I've checked the Bin folder is in %path%
No matter the installation, no Local GPU option appears in the GUI, I figure this is likely the best place to see it easily.

Does anyone have any better instructions, I've combined this thread with the microsoft guide... But still nothing
https://docs.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/install-gpu-model-builder
Any times would be great.

I've tried for about 3 hours over the last few days - It's driving me mental
Specs
ML Model Builder ext - 16.3.0.2056001
ML GPU Ext - 16.3.0.2056001
VS 2019 - 16.8.4
cuda_10.0.130_411.31_win10.exe - Cuda 10 Version
cuDNN v7.6.4 (September 27, 2019), for CUDA 10.0
I'm not sure it's relevant but I have mlnet CLI too
AMD Ryzen 7
64GB Ram
Nvidia Geforce RTX2060 Super
I've installed and reinstalled Cuda 10 a dozen times, I've tried all options, I've tried no VS, With VS, Just Runtime.
I've checked the Bin folder is in %path%
No matter the installation, no Local GPU option appears in the GUI, I figure this is likely the best place to see it easily.

Does anyone have any better instructions, I've combined this thread with the microsoft guide... But still nothing
https://docs.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/install-gpu-model-builder
Any times would be great.

I'll add another note to this. If you still have issues seeing the GPU trainer go to Extensions->Manage Extensions in Visual Studio then look for ML.NET Model Builder (Preview) and update it to latest version. This does not get updated when you update your Visual Studio installation so it has to be done manually.
Also, GPU training can only be used for Image Classification scenarios. The other scenarios can only be trained on CPU.

@Biztactix-Ryan did you ever resolve your issue? I'm in the same boat. Similar environment as yours. Only difference is attempting to use CUDA 10.1 per https://docs.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/install-gpu-model-builder

source: gharchive/issue

authors: Biztactix-Ryan JakeRadMSFT WozSoftware beccamc forReason kabylan kaizen365 mircea-dogaru-redgate msschl

license_type: permissive

license_source: github-api


text:
Semantic tokens tests: Use Linq instead

### Summary of the changes

As per @phil-allen-msft's suggestion we should pre-filter the list instead of trying funny business with the array. Much cleaner.

Definitely much easier to understand that moving two indexes. Which I didn't 😝

Oh no, I take it back. If expected is longer than actual it will help. My bad.

source: gharchive/pull-request

authors: davidwengier ryanbrandenburg

repo: dotnet/razor

license: MIT


text:
Avoid using AddComponentParameter in design time

Fixes AB#1869483.
I think using AddComponentParameter over AddAttribute has no benefit in design time (the motivation for introduction of the method were runtime errors, see https://github.com/dotnet/razor/issues/8258) so avoiding it unconditionally in design time should be the safest fix.

has no benefit in design time

Looking at the difference in codegen, and the complete lack of source mapping or validation of user code, I'm not sure either has a benefit in design time, but probably best not to rock the boat too much 😁

@333fred @dotnet/razor-compiler for a second review, thanks

authors: davidwengier jjonescz


text:
Add ability to use network aliases

What should we add or change to make your life better?
Docker compose has ability to add network aliases like this:
tests.mock.proxy:
    container_name: tests.mock.proxy
    image: nginx
    networks:
      default:
        aliases:
          - api.to-be.mocked.com
          - orders.local.domain.com

meaning, that I can access my services by DNS names - which might serve at least couple purposes:

I can have url's using similar schema to ones in production.
I can mock third party services, if their official clients do not support using different uri and need valid ssl certificates.
Single container might handle requests from multiple host names.

Why is this important to you?
Currently we have two configs - docker-compose and tye just because we can't fully control host names in tye and we need that for our integration tests, as we need to mock out several third party APIs.

Can you share your nginx config as well? Are you doing host name routing to other local services that mock out those APIs?

Sure, currently used nginx config looks something like this:
server {
    listen 443 ssl;

    ssl_certificate     /etc/nginx/certs/server.crt;
    ssl_certificate_key /etc/nginx/certs/server.key;

    location / {
        proxy_pass http://host.docker.internal:5055;
    }
}

We're using self signed certificate, which we trust in other containers.
Currently we're not using routing to other local services, but that is due the fact, that for development locally we use tye for it's faster startup/easier debugging and docker-compose only for integration tests due to ability to do network aliases.
If tye would support network aliases, I think we would use routing to local services too, as we like to have same url schema as in prod (hence in IIS we use host names too - like api.local.domain.com).

authors: davidfowl dziedrius

repo: dotnet/tye


text:
Bump xamlTools to 17.13.35611.21

Bump xamlTools to 17.13.35611.21

@JoeRobich the tests are still failing, could you please help re-run or take a look at them?

@kunyli We are now experiencing issues with downloading NuGet packages on our CI machines. Once that issue is resolved, I will be able to investigate your failure.

/azp run

authors: JoeRobich kunyli

repo: dotnet/vscode-csharp


text:
自定义组件里定义Select组件，如何触发验证

Which class is this unit test associated with?
自定义组件里定义Select组件，如何触发验证，官网没找到相应的示例

select要验证什么，环境或者代码发一点

select要验证什么，环境或者代码发一点

https://gitee.com/zfjie/blazor-bb.git
运行
1、输入main
2、左侧选择验证
点提交按钮，第一个表单没有触发验证，第二个表单触发验证

输入main是啥意思 是这个文件吗

运行项目，浏览器地址/ 后面输入main

@javazfj 帮忙点一下右上角 star 你这个示例工程最好改一下啊。每次让别人输入 main 太麻烦了

authors: ArgoZhang densen2014 javazfj

repo: dotnetcore/BootstrapBlazor


text:
Visualization Scripts

Is it possible to get the visualization scripts for domain representation and  GRAD-CAM attention maps?

We are updating it. The code will be released soon. Thank you

We updated it. Please access https://github.com/dotrannhattuong/ECB/blob/main/visualize_final.ipynb

repo: dotrannhattuong/ECB


text:
有计划支持Storyboard？

如题

你是说由一个页面跳转到 Storyboard 中的一个 UIViewController 吗？
我理解中 Storyboard 就可以完成所有页面的调整关系的规划。如果，同时使用代码方式管理调整，那意味着一个 App 中有两套页面调整行为系统。这似乎并不是一个好的选择。
一般一个需要解耦 view controller 的项目都是较大的项目了。在一个较大的项目中使用 Storyboad 有不少局限，并不是一个好选择。如果基于和设计师合作，需要一些图形化页面设计工具。那么使用 xib 实现会是一个不错的折衷方案。xib 实现的衙门完全可以使用 FRDIntent 完成调用。

某些小的模块，Storyboard能节省很多时间，假如B模块是使用Storyboard的，A模块的某个页面跳转到B模块的某个页面需要传值的话，就必须引入B模块了，苦于无法解决这个问题。不过FRDIntent能够解决大部分的问题了，感谢！

authors: lincode wyhazq

repo: douban/FRDIntent


text:
请问 下面两段脚本是什么作用

来自 http://img3.doubanio.com/dae/rexxar/files/subject/subject-34a447e5c0.html
 <script>
      window.Rexxar = window.Rexxar || {};
      window.Rexxar.Lifecycle = window.Rexxar.Lifecycle || {};
      window.Rexxar.Lifecycle.onPageVisible = function() {};
      window.Rexxar.Lifecycle.onPageInvisible = function() {};
    </script>

下面的 VENDOR_START VENDOR_END 是在哪设置的呢？
 <script>
      if (!window.VENDOR_START) {
        logSend('Vendor assets failed to load.');
        var reloadBtn = document.createElement('div');
        reloadBtn.style.fontSize = '14px';
        reloadBtn.style.color = '#494949';
        reloadBtn.style.margin = '12px';
        reloadBtn.appendChild(document.createTextNode('点击重试'));
        reloadBtn.addEventListener('click', function() {
          window.location.reload();
        });
        showErrorMsg("资源加载失败啦 :(", reloadBtn);
      } else if (window.VENDOR_START && !window.VENDOR_END) {
        logSend('Vendor assets load incomplete.');
        var reloadBtn = document.createElement('div');
        reloadBtn.style.fontSize = '14px';
        reloadBtn.style.color = '#494949';
        reloadBtn.style.margin = '12px';
        reloadBtn.appendChild(document.createTextNode('点击重试'));
        reloadBtn.addEventListener('click', function() {
          window.location.reload();
        });
        showErrorMsg("资源加载失败啦 :(", reloadBtn);
      }
    </script>

VENDOR_START VENDOR_END  这两个变量由来知道了

@xiaolongyuan
我们在自己的打包流程中加了两个变量，当然，根据你自己的业务需求，你可能完全不需要这么做
比如
      if (file.basename === 'vendor.js') {
        let content = file.contents.toString('utf8');
        let newContent = [
          'window.VENDOR_START=true;',
          content,
          'window.VENDOR_END=true;'
        ].join('\n');
        file.contents = new Buffer(newContent);
        file.hash = revHash(file.contents);
      }

您好  打包时 出现这个错误：

webpack.config.js
var path = require('path');
var ExtractTextPlugin = require('extract-text-webpack-plugin');
var utils = require('./build/utils')
var config = require('./config')
var vueLoaderConfig = require('./build/vue-loader.conf')
const vuxLoader = require('vux-loader')

function resolve (dir) {
  // return path.join(__dirname, '..', dir)
  return path.join(__dirname, dir)
}

module.exports = function(env) {
  var webpackConfig = {
    entry: {},
    output: {
      filename: '[name].js'
    },
    resolve: {
      extensions: ['.js', '.vue', '.json'],
      alias: {
        'vue$': 'vue/dist/vue.esm.js',
        'src': resolve('src'),
        '@': resolve('src'),
        common: resolve('src/common')
      }
    },
    module: {
      rules: [
        {
          test: /\.vue$/,
          loader: 'vue-loader',
          options: vueLoaderConfig
        },
        {
          test: /\.js$/,
          loader: 'babel-loader',
          include: [resolve('src'), resolve('test')]
        },
        {
          test: /\.(png|jpe?g|gif|svg)(\?.*)?$/,
          loader: 'url-loader',
          query: {
            limit: 10000,
            name: utils.assetsPath('img/[name].[hash:7].[ext]')
          }
        },
        {
          test: /\.(woff2?|eot|ttf|otf)(\?.*)?$/,
          loader: 'url-loader',
          query: {
            limit: 10000,
            name: utils.assetsPath('fonts/[name].[hash:7].[ext]')
          }
        },
        // {
        //   test: /\.(css|scss)$/,
        //   loader: ExtractTextPlugin.extract('style',
        //     'css?modules,camelCase=dashes,localIdentName=' + (
        //       env === 'production' ?
        //         '[hash:base64:5]' :
        //         '[folder]--[local]--[hash:base64:5]'
        //     )
        //   )
        // },
        {
          test: /\.(css|scss)$/,
          loader: ExtractTextPlugin.extract({
            fallback: 'style-loader',
            use: 'css-loader?modules,camelCase=dashes,localIdentName=' + (
              env === 'production' ?
                '[hash:base64:5]' :
                '[folder]--[local]--[hash:base64:5]'
            )
          })
        }
      ]
    },
    // eslint: {
    //   configFile: '.eslintrc'
    // },
    plugins: [
      new ExtractTextPlugin({ filename: '[name].css',
        disable: env === 'production' ? false : true,
        allChunks: true
      })
    ]
  }

  return vuxLoader.merge(webpackConfig, {
    options: {},
    plugins: [
      {
        name: 'vux-ui'
      },
      {
        name: 'duplicate-style'
      }
    ]
  })
}

deployConfig.js
import webpack from 'webpack';
import argv from '../utils/argv';
import getBaseConfig from '../../webpack.config.js';

import { sources } from '../globals/sources';

let deployConfig = Object.assign({}, getBaseConfig('production'));

deployConfig.entry['vendor'] = ['vue'];
sources.forEach(function(source) {
  let { path, name } = source;
  // console.log(' \n------------ -> path:'+path+' name:'+name)
  deployConfig.entry[`${path}/${name}`] = `./src/${path}/${name}.js`;
});

deployConfig.stats = { children: false };

deployConfig.plugins = deployConfig.plugins.concat(
  new webpack.optimize.OccurrenceOrderPlugin(),
  new webpack.optimize.CommonsChunkPlugin({
    name: 'vendor',
    filename: 'common/vendor.js',
    minChunks: Infinity
  }),
  new webpack.DefinePlugin({
    'process.env': {
      'NODE_ENV': JSON.stringify('production'),
    }
  }),
  new webpack.optimize.UglifyJsPlugin({
    compress: { warnings: false },
    comments: false,
    sourceMap: false
  })
);

export default deployConfig;

var utils = require('../../build/utils')
var path = require('path')
var config = require('../config')
var ExtractTextPlugin = require('extract-text-webpack-plugin')

exports.assetsPath = function (_path) {
  var assetsSubDirectory = process.env.NODE_ENV === 'production'
    ? config.build.assetsSubDirectory
    : config.dev.assetsSubDirectory
  return path.posix.join(assetsSubDirectory, _path)
}

exports.cssLoaders = function (options) {
  options = options || {}

  var cssLoader = {
    loader: 'css-loader',
    options: {
      minimize: process.env.NODE_ENV === 'production',
      sourceMap: options.sourceMap
    }
  }

  // generate loader string to be used with extract text plugin
  function generateLoaders (loader, loaderOptions) {
    var loaders = [cssLoader]
    if (loader) {
      loaders.push({
        loader: loader + '-loader',
        options: Object.assign({}, loaderOptions, {
          sourceMap: options.sourceMap
        })
      })
    }

    // Extract CSS when that option is specified
    // (which is the case during production build)
    if (options.extract) {
      return ExtractTextPlugin.extract({
        use: loaders,
        fallback: 'vue-style-loader'
      })
    } else {
      return ['vue-style-loader'].concat(loaders)
    }
  }

  // http://vuejs.github.io/vue-loader/en/configurations/extract-css.html
  return {
    css: generateLoaders(),
    postcss: generateLoaders(),
    less: generateLoaders('less'),
    sass: generateLoaders('sass', { indentedSyntax: true }),
    scss: generateLoaders('sass'),
    stylus: generateLoaders('stylus'),
    styl: generateLoaders('stylus')
  }
}

// Generate loaders for standalone style files (outside of .vue)
exports.styleLoaders = function (options) {
  var output = []
  var loaders = exports.cssLoaders(options)
  for (var extension in loaders) {
    var loader = loaders[extension]
    output.push({
      test: new RegExp('\\.' + extension + '$'),
      use: loader
    })
  }
  return output
}

我前端库使用的 是 vue.js 2 使用了官方模板的一些配置 开发环境能正常打包 生产环境 报错：
"C:\developtools\JetBrains\WebStorm 2016.3.2\bin\runnerw.exe" C:\developtools\nodejs\node.exe --debug-brk=52533 --expose_debug_as=v8debug C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\gulp\bin\gulp.js --color --gulpfile C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\gulpfile.babel.js deploy
Debugger listening on [::]:52533
[15:01:53] Requiring external module babel-register
[15:01:58] Using gulpfile C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\gulpfile.babel.js
[15:01:58] Starting 'clean'...
[15:01:58] Finished 'clean' after 5.91 ms
[15:01:58] Starting 'deploy'...
htmlPipe path:cashbox name:index
htmlPipe path:cashbox name:record
htmlPipe path:cashbox name:cash_balance
htmlPipe path:cashbox name:record_details
htmlPipe path:secret name:tradepasswd_set
htmlPipe path:secret name:tradepasswd_update
htmlPipe path:rexxar name:demo
htmlPipe path:rexxar name:test
C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack\lib\Chunk.js:80
		return this.entrypoints.length > 0;
		                       ^

TypeError: Cannot read property 'length' of undefined
    at Chunk.isInitial (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack\lib\Chunk.js:80:26)
    at ExtractTextPlugin.<anonymous> (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:302:24)
    at Array.forEach (native)
    at ExtractTextPlugin.<anonymous> (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:301:21)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:359:16
    at iteratorCallback (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:935:13)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:843:16
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:297:6
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:359:16
    at iteratorCallback (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:935:13)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:843:16
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:294:13
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:3025:16
    at eachOfArrayLike (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:940:9)
    at eachOf (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:990:5)
    at Object.eachLimit (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:3089:3)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:268:11
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:3025:16
    at eachOfArrayLike (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:940:9)
    at eachOf (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:990:5)
    at Object.eachLimit (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:3089:3)
    at ExtractTextPlugin.<anonymous> (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:265:10)

Process finished with exit code 1

看报错是extract-text-webpack-plugin的问题

看看plugin的版本是否正确
看看webpack配置是否正确
Google

生产环境配置 修改后
var utils = require('../../build/utils')
export default merge(deployConfig,{
  module: {
    rules: utils.styleLoaders({
      sourceMap: false,
      extract: true
    })
  },
  plugins: [
    // extract css into its own file
    // new ExtractTextPlugin({
    //   // filename: utils.assetsPath('css/[name].[contenthash].css')
    //   filename: '[name].css',
    //   disable: false,
    //   allChunks: true
    // }),
  ]
});

报如下错：
[16:03:04] Requiring external module babel-register
[16:03:06] Using gulpfile C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\gulpfile.babel.js
[16:03:06] Starting 'clean'...
[16:03:06] Finished 'clean' after 5.94 ms
[16:03:06] Starting 'deploy'...

======== vux-loader: duplicate-style start~  ========
Starting to optimize CSS...
->-> collect C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\common\vendor.js
(node:23068) UnhandledPromiseRejectionWarning: Unhandled promise rejection (rejection id: 1): Error in plugin 'webpack-stream'
Message:
    Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/cashbox/index.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\index.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\index.js.json doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\index.js.vue doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\index.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\index.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/cashbox/record.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/cashbox/cash_balance.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\cash_balance.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\cash_balance.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\cash_balance.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\cash_balance.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\cash_balance.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/cashbox/record_details.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record_details.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record_details.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record_details.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record_details.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\cashbox\record_details.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/secret/tradepasswd_set.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_set.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_set.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_set.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_set.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_set.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/secret/tradepasswd_update.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_update.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_update.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_update.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_update.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\secret\tradepasswd_update.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/rexxar/demo.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\demo.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\demo.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\demo.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\demo.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\demo.js is not a directory (directory default file)Entry module not found: Error: Cannot resolve 'file' or 'directory' ./src/rexxar/test.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve file
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\test.js.js doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\test.js.vue doesn't exist
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\test.js.json doesn't exist
resolve directory
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\test.js\package.json doesn't exist (directory description file)
  C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\src\rexxar\test.js is not a directory (directory default file)multi vendor
Module not found: Error: Cannot resolve module 'vue/dist/vue.esm.js' in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
resolve module vue/dist/vue.esm.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp
  looking for modules in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules
    resolve 'file' or 'directory' dist/vue.esm.js in C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue
      resolve file
        C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js.vue doesn't exist
        C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js.json doesn't exist
        C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js.js doesn't exist
      resolve directory
        C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js\package.json doesn't exist (directory description file)
        C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js is not a directory (directory default file)
[C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js.vue]
[C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js.json]
[C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\vue\dist\vue.esm.js.js]
 @ multi vendor

再次修改
    // extract css into its own file
    new ExtractTextPlugin({
      // filename: utils.assetsPath('css/[name].[contenthash].css')
      filename: '[name].css',
      disable: false,
      allChunks: false
    }),

错误信息 如下
[16:04:56] Using gulpfile C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\gulpfile.babel.js
[16:04:56] Starting 'clean'...
[16:04:56] Finished 'clean' after 6.68 ms
[16:04:56] Starting 'deploy'...
C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:267
				var shouldExtract = !!(options.allChunks || chunk.isInitial());
				                                                  ^

TypeError: chunk.isInitial is not a function
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:267:55
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:3025:16
    at eachOfArrayLike (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:940:9)
    at eachOf (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:990:5)
    at Object.eachLimit (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\async\dist\async.js:3089:3)
    at ExtractTextPlugin.<anonymous> (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\extract-text-webpack-plugin\index.js:265:10)
    at Compilation.applyPluginsAsync (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\tapable\lib\Tapable.js:71:13)
    at Compilation.seal (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:525:7)
    at Compiler.<anonymous> (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compiler.js:397:15)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\tapable\lib\Tapable.js:103:11
    at Compilation.<anonymous> (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:445:10)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:417:12
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:332:10
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\async\lib\async.js:52:16
    at done (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\async\lib\async.js:246:17)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\async\lib\async.js:44:16
    at errorAndCallback (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:202:5)
    at errorOrWarningAndCallback (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:225:13)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\Compilation.js:229:12
    at onDoneResolving (C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\NormalModuleFactory.js:29:20)
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\webpack\lib\NormalModuleFactory.js:85:20
    at C:\Workspace\WebstormProjects\qumei\qm-rexxar-userapp\node_modules\webpack-stream\node_modules\async\lib\async.js:726:13

Process finished with exit code 1

package.json
{
  "dependencies": {
    "babel-runtime": "^6.22.0",
    "axios": "^0.15.3",
    "fastclick": "^1.0.6",
    "lscache": "^1.1.0",
    "rexxar-web": "^0.1.0",
    "vue": "^2.2.2",
    "vue-router": "^2.2.0",
    "vuex": "^2.2.1",
    "vux": "^2.1.1-rc.7",
    "es6-promise": "^3.0.2",
    "isomorphic-fetch": "^2.2.0",
    "url-parse": "^1.0.5"
  },
  "devDependencies": {
    "autoprefixer": "^6.7.2",
    "babel-core": "^6.22.1",
    "babel-loader": "^6.2.10",
    "babel-plugin-transform-runtime": "^6.22.0",
    "babel-preset-es2015": "^6.22.0",
    "babel-preset-es2015-loose": "^7.0.0",
    "babel-preset-latest": "^6.22.0",
    "babel-preset-stage-2": "^6.22.0",
    "babel-register": "^6.22.0",
    "chai": "^3.5.0",
    "chalk": "^1.1.3",
    "connect-history-api-fallback": "^1.3.0",
    "copy-webpack-plugin": "^4.0.1",
    "css-loader": "^0.26.1",
    "del": "^2.1.0",
    "eventsource-polyfill": "^0.9.6",
    "express": "^4.14.1",
    "extract-text-webpack-plugin": "^2.1.0",
    "file-loader": "^0.10.0",
    "friendly-errors-webpack-plugin": "^1.1.3",
    "function-bind": "^1.1.0",
    "gulp": "^3.9.1",
    "gulp-env": "^0.4.0",
    "html-webpack-plugin": "^2.28.0",
    "http-proxy-middleware": "^0.17.3",
    "jade": "^1.11.0",
    "jsdom": "^8.1.0",
    "less": "^2.7.2",
    "less-loader": "^2.2.3",
    "merge-stream": "^1.0.0",
    "minimist": "^1.2.0",
    "mocha": "^2.4.5",
    "opn": "^4.0.2",
    "optimize-css-assets-webpack-plugin": "^1.3.0",
    "ora": "^1.1.0",
    "rev-hash": "^1.0.0",
    "rimraf": "^2.6.0",
    "semver": "^5.3.0",
    "serve-index": "^1.7.2",
    "sinon": "^1.17.3",
    "style-loader": "^0.14.0",
    "through2": "^2.0.0",
    "url-loader": "^0.5.7",
    "vinyl": "^1.2.0",
    "vue-loader": "^11.1.4",
    "vue-style-loader": "^2.0.0",
    "vue-template-compiler": "^2.2.1",
    "vux-loader": "^1.0.46",
    "webpack": "^2.2.1",
    "webpack-bundle-analyzer": "^2.2.1",
    "webpack-dev-middleware": "^1.10.0",
    "webpack-hot-middleware": "^2.16.1",
    "webpack-merge": "^2.6.1",
    "webpack-stream": "^3.2.0",
    "yaml-loader": "^0.4.0"
  },
  "engines": {
    "node": ">= 4.0.0",
    "npm": ">= 3.0.0"
  },
  "browserlist": [
    "> 1%",
    "last 2 versions",
    "not ie <= 8"
  ]
}

-_- 折腾死了 这个问题

@ianwith 代码发你邮件了

马上要上线了 求帮忙

authors: ianwith xiaolongyuan

repo: douban/rexxar-web

license: mit

license_source: bigquery


text:
GitHub Releases are outdated and confusing

It seems like we've stopped using GitHub releases? As the most recent release is 2.0.1.
Recommendations
We should either:

Update the releases section and keep it up to date (with a script on publish?)
Delete the existing releases if we're no longer using them (if thats a thing?)

Edit: and now that we've merged the 2.2.0-rc's into main we should probably add release notes for those to the changelog.

@jspizziri at some point we moved towards a CHANGELOG.md to document new versions -- one reason was that we wanted to eventually make adding your changes part of the requirements to a PR but have not automated that.
One benefit of this is that the changelog lives in a repo and could be easily migrated elsewhere as opposed to Github Releases.. but I understand most people expect to search there.
You also brought up the possibility of using conventional-changelog, what does that generate?

Regarding 2.2.0-RC.. yes! we should soon start working on the changelog + documentation updates for things.
We'll likely need to try setting it up from scratch to see what changes are necessary like:

do we still need to add code for kotlin support
methods now reject if you haven't setupPlayer yet

@dcvz , that makes complete sense, and for the record I'm 100% onboard with ditching GH Releases (I always use a CHANGELOG.md for the exact reasons you mentioned).
We have a versioned docs website now and I think anyone who is looking at the changelog is savvy enough to know to look in the CHANGELOG.md and the Git tags.
RE: Conventional Changelog
It's a way to autogenerate your changelog based on your commits. If you've noticed my commits are in a weird format, that's why. You can see an example CHANGELOG here which is completely generated from commits like this. You can also:

Add helper scripts to make it easy to issue commits like that.
Add linters to ensure commits are in that format in a GH action.
Add a simple script to autogenerate that changelog every time you cut and push a new version tag.

It's not something that could be implemented retroactively, however we could create a CHANGELOG_ARCHIVE.md for versions released prior to using the format.

https://discord.com/channels/567636850513018880/600714011318681610/968551787936243774

@dcvz Would you be OK with me deleting all the GitHub releases to avoid confusion? From my perspective, that's the quickest short-term fix for this.

I think that would be fine @jspizziri ! I guess we'd lose some release notes but it'd be for versions no longe supported.

@dcvz awesome. I'll go ahead and do that. I'll download a copy of all the release notes from the past for historical purposes. I think there are GH API's for that.

Here's a zip file of a JSON dump of all the releases:
releases.json.zip

authors: dcvz jspizziri


text:
LXC Entities can't be customixed

Checklist

[X] I have updated to the latest available Proxmox VE Custom Integration version.

Describe the issue you are experiencing
Entities sourced from LXC containers cannot be customized (name change, icon change, etc.). Customization works only in VM entities.
LXC Entities:

VM Entities:

In which version of Home Assistant Core do you have the problem?
Home Assistant 2023.8.4 Frontend 20230802.1 - latest
What version of Proxmox VE Custom Integration has the issue?
2.0.4
What version of Proxmox VE do you have the problem?
8.0.3
Additional information
No response

This looks like a cache problem, can you clear the browser cache, refresh the page (CTRL + F5) and test again?

Oh, you are right! Now all entities can be customized!
Thank you very much for your work.

repo: dougiteixeira/proxmoxve


text:
warn against using browser's window.event

window.event doesn't exist in firefox.
for example, jslint failed to catch this real-world browser-compat regression:
/*jslint browser devel*/
document.querySelector(
    "#foo"
).addEventListener("click", function (/*event*/) { // forgot to pass "event" arg
    console.log(event.type);  // works in chrome but throws in firefox
});

I am just focusing on JavaScript code quality. I am no longer attempting to check the behavior of the DOM. There are warehouses of aisles of stacks of cases of cans of worms there.

repo: douglascrockford/JSLint

license: unlicense


text:
Simulator adds 15 CP to real CP value.

Hopefully I am not doing something incorrectly. I've used the tool for a while now (thank you, btw) without this issue. Just recently saw it appear.
After setting the crafter attributes (in my case WVR) and starting the simulator, it will try to solve the recipe with an additional 15 CP. In the picture below, I have my attributes set to my base WVR stats without food.

Once I start the simulator, it finishes with this:

I also tried selecting food to see what that would do. It added 15 CP to that as well:

Please let me know if you have any questions and thank you for all of the hard work! It's appreciated!

I've added an indicator in the status widget to show if the current class is marked as a specialist.

There a way to turn this off? I don't have this trait and wont for a while, rendering any macro made useless.

It shouldn’t be adding the cp unless you’ve checked the Speciailist box for your class. If you’re certai that you didn’t, please post the contents of the simulator log tab.

I am a specialist, i haven't done the 70 quest, so i don't have the talent.

Ah I see. The assumption was that if you're a specialist you have the Stroke of Genius trait as well. I'll see about adding another checkbox for Stroke of Genius.

What I did was set my CP value to whatever my true CP value was minus 15. Since 15 CP gets added on the first step, the rest of the macro was not affected by it and it didn't cause any issues while generating a reliable macro. I just had to remember to do that any time I changed my gear. Ultimately, it just encouraged me to stop being lazy and to finish the quests in order to unlock the trait.
I am going to close this since it actually is not a bug.
doxxx - keep up the great work! This is an invaluable tool, and I sincerely appreciate all of the effort you've put into it. Thank you!

authors: Norggron doxxx leftbehind126

repo: doxxx/ffxiv-craft-opt-web

license: Zlib


text:
🛑 Mail SOGo is down

In 2158eff, Mail SOGo ($VCSOFT_SOGO_MAIL) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Mail SOGo is back up in 99bdb42 after 2 hours, 21 minutes.

repo: dpkg-i-foo-deb/upptime


text:
🛑 Workstation Service is down

In e98b75f, Workstation Service (https://workstation.dpG06.top) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Workstation Service is back up in ba92267 after 1 day, 12 hours, 20 minutes.

repo: dplayz/status


text:
/lib/modules can't be read-only

DKMS: build completed.

falco-probe.ko:
Running module version sanity check.
 - Original module
   - No original module exists within this kernel
 - Installation
   - Installing to /lib/modules/4.4.78-k8s/kernel/extra/
mkdir: cannot create directory '/lib/modules/4.4.78-k8s/kernel/extra': Read-only file system
cp: cannot create regular file '/lib/modules/4.4.78-k8s/kernel/extra/falco-probe.ko': No such file or directory

depmod...

When I remove the read-only flag, this works fine

those errors are expected since we don't want to make changes to the underlying host. falco will work regardless

I'm confused... why does it try that if it works regardless and why does it give an error at all then? if it's expected, i would think it would be suppressed then, as otherwise it's extremely misleading and disorienting

Hello! I am just starting to play with Falco and I lost a couple of minutes trying to find out what was wrong with my setup before finding this issue. If really it's the expected behavior, it should not be displayed as an error. My 2 cents! 😃

Came here after trying to see what was wrong with my configuration... missing a falco-probe.ko file sounds problematic.
the least that could be done, augment the logs with
"this is normal, ignore this error if you system is readonly, or you are running in a container"

repo: draios/falco


text:
Added code to check for existence of html or text body when attachments ...

Hello,
This is only my second pull request, so I apologize if I'm not following proper etiquette!
I opened Issue #29 two days ago - the problem is that SES gets angry when you try to send an e-mail with an attachment and no other body text. Rather than do something doofy like create a default text body, I've tweaked the code to throw an ArgumentError with more descriptive text when someone tries to do this.
The code doesn't depend on ActionMailer, and there's an accompanying test. Let me know if you have any questions!
BTW - very nice work on this gem. It's been a lifesaver!

Mike

Thanks very much.  I'm going to look at this and merge it in this weekend.  Greatly appreciated!

authors: drewblas mdesjardins

repo: drewblas/aws-ses


text:
Email de rappel - Échéance de la période d'abonnement

Période d'essai
Période d'abonnement

Sorry - mistake.

repo: drewm/mailchimp-api


text:
delete batched job

Implement a method that removes a job from a batch list.

The new method is remove_batched_job(id, *args)

repo: drfeelngood/resque-batched-job


text:
Live Reload CSS Windows 10

When I was changing about page banner color in conference app testing, I did not see the css update automatically as I would expect. It did not work how it works on most browsers.
Thanks,
Dan

CSS reload doesn't work for some time now :/

@dejancencelj Can you provide the output when you run ionic info from within the project? Thank you!

Ionic Framework Version: 2.0.0-rc.3-201611211919
Ionic CLI Version: 2.1.8
Ionic App Lib Version: 2.1.4
Ionic App Scripts Version: 0.0.46
ios-deploy version: Not installed
ios-sim version: Not installed
OS: Windows 10
Node Version: v6.9.1
Xcode version: Not installed

The issue is because livereload.js was inserted using "http://0.0.0.0:8100" instead of "http://localhost:8100". This has been resolved in the nightlys and will be fixed in release 0.0.47. I verified on Windows 7 with Chrome.

authors: danbucholtz dejancencelj jthoms1

repo: driftyco/ionic-app-scripts


text:
show blank about 10s after app splash screen disapear

this issue isn't solved after 0.0.45 version.I create new ionic project and build  with 0.0.47 0.0.48 1.0.0,app will show blank about 10s after app splash screen disapear,then homepage shown.0.0.45 is ok.Is there nobody get this problem???

Are you using --prod when viewing your project? Otherwise you are getting develop mode which is optimized for debugging but not for speed.

use
ionic build android --prod

Yes, use --prod 🐱
Thanks,
Dan

authors: arendjantetteroo danbucholtz wolfljj yasar-salim


text:
TypeError: Cannot read property 'F_OK' of undefined

Note: for support questions, please use one of these channels:
https://forum.ionicframework.com/
http://ionicworldwide.herokuapp.com/
Note: for build related issues you can open up an issue on the ionic-app-scripts repo
https://github.com/driftyco/ionic-app-scripts
Please ensure that you are on the latest version of the CLI.
npm view ionic@latest version
Short description of the problem:
Cannot execute command 'ionic' from an ionic3 project directory. Command works when outside of an ionic project dir.
What behavior are you expecting?
Error displays "TypeError: Cannot read property 'F_OK' of undefined"
Steps to reproduce:

Run 'ionic' from any ionic3 project

insert any relevant code between the above and below backticks

Post the output of ionic info below please
[WARN] You are not in an Ionic project directory. Project context may be missing.
global packages:
@ionic/cli-utils : 1.2.0
Ionic CLI        : 3.2.0

System:
Node       : v6.2.2
OS         : macOS Sierra
Xcode      : Xcode 8.3.2 Build version 8E2002
ios-deploy : 1.9.1
ios-sim    : 5.0.4

Other information: (e.g. stacktraces, related issues, suggestions how to fix, stackoverflow links, forum links, etc)

Hello I have the same problem and I do not know how to do to solve it.
Ionic info:
[WARN] You are not in an Ionic project directory. Project context may be missing.
Global packages:
@ Ionic / cli-utils: 1.2.0
     Ionic CLI: 3.2.0
System:
Node: v6.1.0
     OS: macOS Sierra
     Xcode: Xcode 8.3.2 Build version 8E2002
     Ios-deploy: not installed
     Ios-sim: 5.0.8
Olivier @ olivier-2 $ sudo ionic start myAPP sidemenu
TypeError: Can not read property 'F_OK' of undefined
Thanks in advance for the help !

Had the exact same issue but updating nodejs itself to LTS version 6.10.3 with NPM version 3.10.10 seemed to solve the problem.
Does it for you guys too maybe?

Hello,
I have just updated node js (on macOS) and i have this version:
Olivier @ olivier-2 $ ~ / Sites / playernorine / myApp> node -v
V6.1.0
Olivier @ olivier-2 $ ~ / Sites / playernorine / myApp> npm -v
4.6.1
And I still have the same mistake …

Le 24 mai 2017 à 18:53, Petzall notifications@github.com a écrit :
Had the exact same issue but updating nodejs itself to LTS version 6.10.3 with NPM version 3.10.10 seemed to solve the problem.
Does it for you guys too maybe?
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub https://github.com/driftyco/ionic-cli/issues/2341#issuecomment-303785054, or mute the thread https://github.com/notifications/unsubscribe-auth/AFgZmazOIfovjEEcga77QdW-yhySupLNks5r9GB6gaJpZM4NlHOa.

Ty @Petzall updated node v7.10.0 and works!

@Oliviercreativ the latest version of node is v7.10.0 like TwixD got, but the LTS (Long Term Support) version could be more stable.
If you're on MacOS or Windows the simplest way to upgrade is via nodejs.org, download the install package and run the installer!

Work for me 👍  but i'm rebuilded node-sass !
Thx you ;)

Hey all, yep, the recommendations to upgrade node and npm are correct. You might only get this error if your node version is old (in this case, 6.1 and 6.2 are from mid-2016). In these days, even a year is an eternity for JS 😄

FYI, nvm was holding back my currently installed v7.10.0 so this was just a mistake on my part not realizing the current running version of node was out of date. Thanks for catching that!

I had the same issue, upgrading my node from v6.1.0 to v7.10.0 fixed it 😄
brew update
brew upgrade node
npm install -g npm

this SO answer
I'm on
OS X EL Capital 10.11.6

Yep, latest 6 or 7 works.

authors: CaptainMM Oliviercreativ Petzall TwixD dwieeb sameera207

repo: driftyco/ionic-cli


text:
docs: change card-title headers to ion-card-title elements

Refactor done in this issue: https://github.com/driftyco/ionic/issues/5303

http://ionicframework.com/docs/v2/components/#card-list
Use the ionic element, not classes

authors: brandyscarney perrygovier

repo: driftyco/ionic-site


text:
Preloading Lazy Loaded Modules freezes app

Ionic version:  (check one with "x")
[x] 3.x
I'm submitting a ...  (check one with "x")
[x] bug report
Current behavior:
I have an app with about 35 pages which I lazy load.
I set preloadModules to true in app.module.ts which will preload about 20-25 pages when the app starts up.
The app startup time is getting better using this pattern but now the app is unsusalbe for the first few seconds because the preloading process freezes the whole app. Once the process is done everything works fine.
I think this bug is even worse than a slow startuptime...
Expected behavior:
Preloading modules should not freeze the app or bring the app to lag.
Ionic info: (run ionic info from a terminal/cmd prompt and paste output below):
Cordova CLI: 6.4.0
Ionic Framework Version: 3.1.1
Ionic CLI Version: 2.2.2
Ionic App Lib Version: 2.2.1
Ionic App Scripts Version: 1.3.7
ios-deploy version: Not installed
ios-sim version: Not installed
OS: Windows 10
Node Version: v7.6.0
Xcode version: Not installed

This happens even with non-ionic Angular2 apps (preloading enabled) where you have a lot of components.
I would suggest setting priority of the pages as suggested at the bottom of the page. http://ionicframework.com/docs/api/navigation/IonicPage/

@Daskus1 is this on an android device or an iPhone?

@jgw96 this happens on android device and also in my desktop browser (chrome). I have never tested it on iPone.

@Daskus1 , did changing the priorities fix this issue for you?

@jgw96 I tried changing the priorities, but nothing changes... The app is still unusable for the first few seconds

I have over 50 pages and using lazy loading, my app loads in ~3 seconds on Nexus 6P and in ~6 seconds on nexus 4. (I am not using Preloading since its not a progressive app but just a mobile app and all scripts are bundled and its doesn't put any noticeable delay even on nexus 4).

@naveedahmed1 could you please try to add preloadModules and see if you can still use the app immediately after startup smoothly?

Are you following below guide?
https://docs.google.com/document/d/1vGokwMXPQItZmTHZQbTO4qwj_SQymFhRS_nJmiH0K3w/edit
I am following most of the steps described here, but not "Handling Components/Providers/Pipes" as described here. I have separate multiple modules for components. Though I group components related to a specific feature in one module.

@naveedahmed1 yes I have done it like you. Followed the guide for every page and since I have a lot of custom components/pipes (50+) I have multiple small modules for them which I only add to the page module where they the component/pipe is needed.
Lazyloading massively reduced my bundle size (from 3MB+ to almost 1MB) but the startuptime is still not as fast as I would like to have it and there is this problem with lagging the first few seconds.

What is the current load time? and on which device? BTW 1MB is the minimum I am able to achieve for my main bundle.

On a Samsung Galaxy A5 (Android 6) the loading time is about 6 seconds, on a Samsung Galaxy S3(Android 4.1.2) mini about 15 seconds.

I think A5 ~= to nexus 4 in terms of spec and I also have ~6 seconds load time on nexus 4.

Hello! Thanks for opening an issue with us! After further review, this seems like more of a support question. Because of this I will urge that you ask this question on our forum (forum.ionicframework.com) or on our [slack channel](https://ionic-worldwide.slack.com/messages?]. Thanks for using Ionic!

I still experience this issue.

repo: driftyco/ionic


text:
collection-repeat doesn't work properly when data is loaded asynchronously

I just got nightly - 1.0.0-beta. 14-nightly-1102 build and did some testing with collection-repeat.
It calculates properly height of the item in case if data is loaded on initial controller load, however, when data is loaded dynamically or asynchronously collection-repeat will not calculate properly height, and will only use height of the first item in the list.
I created sample code, so you can see the issue.
http://codepen.io/anon/pen/KwBarr?editors=101

Greetings @vlad-bezden!
My sensors indicate that you need to update your issue through our custom issue form. We are now requiring all issues to be submitted this way, to ensure that we have all of the information necessary to fix them as quickly as possible.
Click Here To Update Your Issue
I will have no choice but to close this issue if it is not resubmitted through the form. Please fill out the rest of the form, so that I may use my friendly robot powers to assist you.
Thank you!

authors: Ionitron vlad-bezden


text:
[BUG]: .default() does not work on boolean pg types

What version of drizzle-orm are you using?
0.31.2
What version of drizzle-kit are you using?
0.22.7
Describe the Bug
When I set .default(sql'FALSE').notNull() or .default(false).notNull(), manually entering a row does not result in FALSE by default.
Check the snapshot:

The CHECK() constraint, using sql magic operator also doesn't work. I am aware the drizzle did not implement this yet.
Please check the code snippet below for understanding what I am trying to achieve:
export const trackers = createTable(
  "tracker",
  {
    id: uuid("id").primaryKey(),
    createdAt: timestamp("created_at", {
      mode: "date",
      withTimezone: true,
    }).default(sql`CURRENT_TIMESTAMP`).notNull(),
    hashedId: varchar("hashed_id", { length: 255 }).notNull(),
    country: varchar("country", { length: 2 }).notNull(),
    isMalicious: boolean("is_malicious").default(sql`FALSE`).notNull(),
    canBypassProtection: boolean("can_bypass_protection").default(sql`FALSE`).notNull(),
  },
  (tracker) => ({
    hashedIdIdx: index("tacker_hashedId_idx").on(tracker.hashedId),
    canBypassProtectionCstr:
      sql`CHECK (can_bypass_protection = FALSE OR (can_bypass_protection = TRUE AND is_malicious = TRUE))`, // <-- DOESN'T WORK
  })
);

Expected behavior
It should be FALSE by default.
Environment & setup
No response

same here! been driving me crazy

What is the createTable function? It would be awesome if you could send a full repro example, so I can add it to the test cases and fix it if needed

@codesfromshad Is this issue specific to Drizzle Studio or are you encountering this issue while running a query with the ORM?

Same thing here.
export const blogs = createTable(
  "blogs",
  {
    id: serial("id").primaryKey(),
    author: varchar("author")
      .notNull()
      .references(() => userTable.username),
    title: varchar("title", { length: 255 }).notNull(),
    active: boolean("active").notNull().default(false),
    createdAt: timestamp("created_at")
      .default(sql`CURRENT_TIMESTAMP`)
      .notNull(),
    updatedAt: timestamp("updated_at").$onUpdate(() => new Date()),
    deletedAt: timestamp("deleted_at"),
  },
  (table) => ({
    blogTitleUniqueIdx: uniqueIndex("blog_title_uniqueIdx").on(table.title),
    /* Only force uniqueness on author's "current" blog (don't include deleted ones) */
    authorBlogUniqueIdx: uniqueIndex("author_blog_uniqueIdx")
      .on(table.author)
      .where(sql`"deleted_at" IS NULL`),
  })
);

.default(false) does not apply - therefore when "active" boolean isn't explicitly supplied, the entry isn't created due to the notNull() constraint.
I could explicitly include active: false on every DB insert, but you'd at least expect stuff to work? Or not take months of being swept under the rug? Isn't this a pretty huge deal?

.default(false) does not apply

@MGSimard What do you mean by that? That the default value statement isn't being generated in migrations or that inside an insert query the default value isn't being applied?
I tried both anyways and both behave as expected in the latest version of ORM and Kit (v0.33.0 and v0.24.2 respectively). If it's an issue with an insert statement, I'm curious to know what driver you're using and how you've defined the query that's causing the issue.

.default(false) does not apply

@MGSimard What do you mean by that? That the default value statement isn't being generated in migrations or that inside an insert query the default value isn't being applied?
I tried both anyways and both behave as expected in the latest version of ORM and Kit (v0.33.0 and v0.24.2 respectively). If it's an issue with an insert statement, I'm curious to know what driver you're using and how you've defined the query that's causing the issue.

I mean it's intrinsically both isn't it? When you db:push this table schema, the default(false) constraint doesn't actually get applied to the column, which inherently means that whether you run an insert query or attempt to create a row manually in drizzle studio, the "active" column will default to null rather than false, which will obviously throw an error because of notNull(). You're being forced to supply an explicit true/false boolean on every insert or update, because default(false) isn't actually being applied on table creation, so any insert will not default to false. The exact context supplied by both the issue's OP and myself. Neither default(false) or default(sqlFALSE) work. This is on latest.
This behaviour can be observed simply by adding a row in drizzlthis upon attempting to add a row through db:studio simply by the untouched column saying "NULL" instead of "DEFAULT". This is on the exact table described by the above schema.

I haven't tested on a non multi-project schema yet, but considering that if your testing of boolean .default() does indeed work on your end, and the fact that OP is using syntax indicating they're also doing multi-project schema -- could this possibly be yet another bug introduced by the use of multi-project schema, somehow? Same as this other issue introduced a few months ago?
This is the multi-project schema documentation: https://orm.drizzle.team/kit-docs/conf#multi-project-schema

@codesfromshad @raydelvecchio @MGSimard Hey! This should be fixed.

authors: AndriiSherman L-Mario564 MGSimard RomanNabukhotnyi codesfromshad raydelvecchio

repo: drizzle-team/drizzle-orm


text:
[BUG]: Creating a column called name throws a "Cannot read properties of undefined (reading 'name')" error

What version of drizzle-orm are you using?
0.27.2
What version of drizzle-kit are you using?
0.19.11
Describe the Bug
I got this absolutely weird error today, here's what I was doing.
I was making a simple form while making use of nextjs server actions. In my component, I had an input(type text) with a name="name". Then, I defined an async function above(server action) and passed it as action to the form so that it would run at submit. This async function had a const=name that got hold of the data entered in that input field (const name = data.get("name")) & then I used that value of name to insert it into a planetscale database in a column also called "name". After hitting submit, I got the following error: "Cannot read properties of undefined (reading 'name')". Then I googled for an hour, then tried removing the work "name" from everywhere in the component but still the exact error persisted. Here's the code:
import { Button } from "@/app/components/ui/button";
import { db } from "@/lib/db";
import { messages } from "@/lib/db/schema";

const sendMessage = async (data: FormData) => {
	"use server";

	const name = data.get("something")?.valueOf();
	if (typeof name !== "string" || name.length === 0) {
		throw new Error("Please enter a valid name");
	}
	const email = data.get("email")?.valueOf();
	if (typeof email !== "string" || email.length === 0) {
		throw new Error("Please enter an email");
	}
	const message = data.get("message")?.valueOf();
	if (typeof message !== "string" || message.length === 0) {
		throw new Error("Please enter a valid message");
	}

	const obj = {
		name: name,
		email: email,
		message: message,
	};

	try {
		await db.insert(messages).values(obj);
		console.log("New Message:" obj);
	} catch (err) {
		console.log(err);
	}
};

export default function Connect({) {
	return (
		<>
			<form action={sendMessage}>
				<input type="text" name="name" />
				<input type="email" name="email" />
				<textarea name="message" />
				<Button type="submit">Send Message</Button>
			</form>
		</>
	);
}

After that, I renamed the column to "something" and renamed absolutely everything to that "something". The code looked like this:
import { Button } from "@/app/components/ui/button";
import { db } from "@/lib/db";
import { messages } from "@/lib/db/schema";

const sendMessage = async (data: FormData) => {
	"use server";

	const something = data.get("something")?.valueOf();
	if (typeof something !== "string" || something.length === 0) {
		throw new Error("Please enter a valid name");
	}
	const email = data.get("email")?.valueOf();
	if (typeof email !== "string" || email.length === 0) {
		throw new Error("Please enter an email");
	}
	const message = data.get("message")?.valueOf();
	if (typeof message !== "string" || message.length === 0) {
		throw new Error("Please enter a valid message");
	}

	const obj = {
		something: something,
		email: email,
		message: message,
	};

	try {
		await db.insert(messages).values(obj);
		console.log("New Message:" obj);
	} catch (err) {
		console.log(err);
	}
};

export default function Connect({) {
	return (
		<>
			<form action={sendMessage}>
				<input type="text" name="something" />
				<input type="email" name="email" />
				<textarea name="message" />
				<Button type="submit">Send Message</Button>
			</form>
		</>
	);
}

And it worked perfectly fine! If there was a cannot read properties error for name, it should've been there for email too, since the code is the exact same for both. Also, after I remove the word "name" from the entire code (except name attribute of inputs), it still gives the same error which is absurd.
I think you just can't have name as column name and then add rows. Pls reply if I went wrong somewhere.

I encountered this error message: Cannot read properties of undefined (reading 'name').
However, I believe it was caused by passing an object for insertion that had a key name that didn't exist in the table.

I ran into this issue too. Based on the stack trace, it looks like the issue is somewhere around here. See how on that line that name is referenced.

I don't think this a drizzle bug. Can you please provide a reproduction repo? I'll close for now, but do re-open if you still think this is a bug.

It does work now without any issues.

authors: Angelelz DaleWebb YugandharrPatil bestickley


text:
u hncxs

cs

dww

wd

repo: drknzz/GitHub-Achievements


text:
Privsep overhead: document, warn, shortcut when using -u root

Privsep operations used within per-connection code (such as when using -i on Linux, #221) adds a serious bottleneck and considerable latency to connection handling.

[x] Add information on which configuration options add per-connection privsep overhead to manual page
[x] As an initial mitigation, in debug mode, warn about configurations that cause per-connection privsep overhead
[x] Add option to shortcut privsep code entirely, i.e. when using -u root, use a fast path that bypasses the client/server socket machinery
[ ] Refactor socket handling to transport only a master socket across the fork, and then request client sockets dynamically as needed later - OR - centralize information about how many sockets will be needed in a nicer way

Implemented and tested, closing issue.

repo: droe/sslsplit


text:
[Cloud] Multi-tenant support

See: https://github.com/drogue-iot/drogue-cloud/issues/12

You are right, I need to follow up on this one.

repo: drogue-iot/rfcs


text:
sa-token既然处理登录以及权限管控方面，那么能否把登录场景中常用的验证码逻辑也给集成进来呢

目前登录场景经常会用到验证码，可否考虑集成验证码逻辑到目前的框架中，并且内置开关，以及验证码类型选择。

Sa-Token 不干预认证的具体方案，只做认证成功后的 token 颁发，你说的这个功能有过规划，可能以后的版本会增加相关扩展，但是短时间内应该不会支持

我也需要这个功能，现在有没有在规划里面呢？

repo: dromara/Sa-Token


text:
Optimize OrderedDtpExecutor

https://github.com/dromara/dynamic-tp/issues/227

WIP

repo: dromara/dynamic-tp


text:
v2.0.0-beta4，生成的查询语句为什么没有自动带上.keyword，然后查不出结果

字段是这样定义的：
@IndexField(fieldType = FieldType.KEYWORD)
private String contractNumber;
索引映射如下：
"contractNumber" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
自动生成的DSL：
{"size":100,"query":{"bool":{"must":[{"term":{"contractNumber":{"value":"CONTRACT1700479609771872256","boost":1.0}}}],"adjust_pure_negative":true,"boost":1.0}},"_source":{"includes":["_id"],"excludes":[]},"track_total_hits":2147483647}

配置了手动模式，却让自动生成了index，有问题

repo: dromara/easy-es