text:
[tests-only] bump core commit id

similar to https://github.com/owncloud/ocis/pull/784
Includes test changes from:
https://github.com/owncloud/core/pull/38050 [tests-only] correct reshare test to use the correct path
https://github.com/owncloud/core/pull/38051 [tests-only] Improve skeleton upload error message
https://github.com/owncloud/core/pull/38052 [tests-only] test webdav locks when shares are received in a sub-folder
https://github.com/owncloud/core/pull/38056 [tests-only] split public link tests into separate files for new/old dav
https://github.com/owncloud/core/pull/38058 [tests-only] Adjust tests to better run on PGSQL

@ishank011 ready for approve-merge


text:
Activity filter + card layout on mobile + docker changes for git lfs

References #153

looks good!

Looks good to me! Nice job!!

source: gharchive/pull-request

authors: WillEngl joshMANUmartin junebugtony

license: MIT

license_type: permissive

license_source: github-api


text:
Input: Separate Data Input Entry

As a user, I want to easily input data into this project and have its entry separate from the executable for
modularity
Size: medium
Definition of Done

[ ] Program parses input file into memory
[ ] Provides error messages for Invalid Input

-Setting up Windows XP VM, Windows 7 VM, and Windows 10 VM to determine which one can install python 2.4, GCC 5.0, and a depreciated version of Microsoft Visual Studio from 2005 with the intent of trying to build the old Descent program.
[t:120]

-Hunting down errors in Windows XP when trying to use Descent installer.
-Finding MSVC71.dll file online and adding it to system32 folder to get Descent to install and work.
[t:120]

-Converting python 2.4 code to python3.12 with python function "2to3"
-Determining which python2.4 libraries are depreciated, which ones were absorbed, which ones no longer exist.
-For libraries that were absorbed by another(e.g. numarray absorbed by numpy), determining if the functions are the same.
[t:120]

source: gharchive/issue


text:
[BUG] Importing any component displays export conflict warnings with react-select

Description
I just started a new project, and am trying out this library for the first time. I'm pretty sure my package versions are appropriate. The warnings (at the bottom of this description) are displayed even if the chakra-react-select components are imported but not rendered.
import { Select } from "chakra-react-select";

Versions
{
  "@chakra-ui/react": "2.4.2",
  "@emotion/react": "11.10.5",
  "@emotion/styled": "11.10.5",
  "framer-motion": "7.6.19"
  "chakra-react-select": "4.4.2"
}

Here is the output I'm getting, all warnings.
../../node_modules/chakra-react-select/dist/esm/index.js
The requested module 'react-select/async' contains conflicting star exports for the name '__esModule' with the previous requested module 'react-select'

../../node_modules/chakra-react-select/dist/esm/index.js
The requested module 'react-select/async-creatable' contains conflicting star exports for the name '__esModule' with the previous requested module 'react-select'

../../node_modules/chakra-react-select/dist/esm/index.js
The requested module 'react-select/creatable' contains conflicting star exports for the name '__esModule' with the previous requested module 'react-select'

chakra-react-select Version
4.4.2
Link to Reproduction
No response
TypeScript?

[X] Yes I use TypeScript

Steps to reproduce
No response
Operating System

[X] macOS
[ ] Windows
[ ] Linux
[ ] iOS/iPadOS
[ ] Android

Additional Information
No response

@csandman I do not have it installed, that was my first thought.
I even nuked my node_modules and reinstalled to make sure I didn't have an orphaned version of it installed anywhere.

Ok, so what's the rest of your setup like? Are you using CRA? Nextjs? Remix?

Next 13 as part of a monorepo (powered by Turborepo) currently using the new app directory paradigm.

So I set up a project similarly to yours until the error was triggered, and I believe I figured out what is causing the issue.  I'm not sure why it only started appearing in this setup, but I know how to fix it at least.
However, I'm pretty sure the error you listed above is just a warning and isn't actually what's breaking your app.
The app directory paradigm doesn't appear to play nicely with Chakra UI at all yet, and I couldn't even get an app working right with them together without errors being thrown left and right.  Maybe the fault is on my end, though, and you've gotten farther than I have.  If you can give me an example project setup with Chakra working fine and chakra-react-select not working, I'll take a look and see if there's anything else I can figure out.  It could be just the next project files, it doesn't have to be a whole turborepo setup.
Also, the app directory paradigm is still a beta feature in Nextjs, so it could just be compatibility issues they're still working through.

So I pushed my fix for the bug listed here, try out v4.4.3 when you get a chance to see if the warning went away.

Wait, is it fully working now?

huh, was it functional beforehand, just with that additional warning? or was that completely preventing it from working?

It was just a warning, albeit one that displayed 3x for every page load (probably related to component rerenders).

authors: csandman mattcoker

repo: csandman/chakra-react-select


text:
Ticking plant error with VFECore

Describe the bug
A conflict with VFE causes the plant threads to throw an error and restart endlessly.
Steps to reproduce the behavior (VERY IMPORTANT)

Press play on the supplied save file (don't know if error triggers on a new save)
Wait a bit
Game freezes, wait for it to unfreeze
See error

Error Log
Player.log: https://gist.github.com/robmart/9d8516cf6221b323579b563a1de27455
Save file
https://easyupload.io/evmhxa
Mod list (Preferably a RimPy compatible list.)
File is a RimPy exported mod list, just change it to a xml to import it. Highly Modded 1.3.txt

This one gets fixed by my last commit on 2.5.12

You are using RT 2.5.7 this issue was fixed in the latest RT versions. This issue can be closed

authors: Sernior robmart

repo: cseelhoff/RimThreaded


text:
using faster rcnn model

Hi. Thanks for sharing your repo.
I try to use the faster rcnn model
I use
NSString *model = @"op_inference_graph_rcnn";

in the TensorflowGraph.mm file
but when u load the app its crash when its try to detect
you know what can cause this?
Thanks!

Hi Michael,
What phone are you using?  It could be memory. Can you post a console log?  I just tried that model on my iPhone 6s and it ran without crashing, although admittedly, it wasn’t anywhere near real-time; I was only processing a frame every 24 seconds or so.  I will probably remove that model from the next push for this reason.  There are others in the Tensorflow Model Zoo https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md that should perform better and though I haven’t tested them all you should be able to use any of the models that give boxes.

On Jun 5, 2018, at 5:38 AM, Michael Ben ami notifications@github.com wrote:
Hi. Thanks for sharing your repo.
I try to use the faster rcnn model
I use
NSString *model = @"op_inference_graph_rcnn";
in the TensorflowGraph.mm file
but when u load the app its crash when its try to detect
you know what can cause this?
Thanks!
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub https://github.com/csharpseattle/tensorflowiOS/issues/8, or mute the thread https://github.com/notifications/unsubscribe-auth/ALvHeRrCkh66Utp4PyeLwLmy6u9jPR5qks5t5nvfgaJpZM4Uavhj.

I have iPhone 6..
do you know how much memory the faster rcnn network need?
I'll check the other model you mention too
Thanks

Hi @csharpseattle
I train SSD mobile net v1 with my dataset with the object detection API
on tensorflow 1.7.0 with 600x600 as input size.
I use object_detection/export_inference_graph.py to frezze the model
when I try to replace the model. I got an error: Failed to load model
log:
2018-06-07 12:43:08.061775+0300 tensorflowiOS[3030:597247] [MC] System group container for systemgroup.com.apple.configurationprofiles path is /private/var/containers/Shared/SystemGroup/systemgroup.com.apple.configurationprofiles
2018-06-07 12:43:08.064279+0300 tensorflowiOS[3030:597247] [MC] Reading from public effective user settings.
2018-06-07 12:43:16.032525: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "PopulationCount" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT32 } } }') for unknown op: PopulationCount
2018-06-07 12:43:16.038127: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "RightShift" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT8 } } }') for unknown op: RightShift
2018-06-07 12:43:16.038265: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LeftShift" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT8 } } }') for unknown op: LeftShift
2018-06-07 12:43:16.038418: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "BitwiseAnd" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT8 } } }') for unknown op: BitwiseAnd
2018-06-07 12:43:16.038582: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "BitwiseOr" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT8 } } }') for unknown op: BitwiseOr
2018-06-07 12:43:16.038730: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "BitwiseXor" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT8 } } }') for unknown op: BitwiseXor
2018-06-07 12:43:16.038899: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "Invert" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_INT8 } } }') for unknown op: Invert
2018-06-07 12:43:16.039767: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: MutableDenseHashTableV2
2018-06-07 12:43:16.042912: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableDenseHashTableV2
2018-06-07 12:43:16.043079: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_DOUBLE } } }') for unknown op: MutableDenseHashTableV2
2018-06-07 12:43:16.043289: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableDenseHashTableV2
2018-06-07 12:43:16.043866: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableDenseHashTableV2
2018-06-07 12:43:16.044084: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableDenseHashTableV2
2018-06-07 12:43:16.044224: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: MutableDenseHashTable
2018-06-07 12:43:16.044479: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableDenseHashTable
2018-06-07 12:43:16.044589: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_DOUBLE } } }') for unknown op: MutableDenseHashTable
2018-06-07 12:43:16.044696: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableDenseHashTable
2018-06-07 12:43:16.045003: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableDenseHashTable
2018-06-07 12:43:16.045140: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableDenseHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableDenseHashTable
2018-06-07 12:43:16.045250: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensors" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableHashTableOfTensors
2018-06-07 12:43:16.045357: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensors" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: MutableHashTableOfTensors
2018-06-07 12:43:16.045481: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensors" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: MutableHashTableOfTensors
2018-06-07 12:43:16.045731: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensors" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableHashTableOfTensors
2018-06-07 12:43:16.045962: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableImport" device_type: "CPU"') for unknown op: LookupTableImport
2018-06-07 12:43:16.046249: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableExportV2" device_type: "CPU"') for unknown op: LookupTableExportV2
2018-06-07 12:43:16.046436: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableSizeV2" device_type: "CPU"') for unknown op: LookupTableSizeV2
2018-06-07 12:43:16.046552: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableSize" device_type: "CPU"') for unknown op: LookupTableSize
2018-06-07 12:43:16.046648: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableImportV2" device_type: "CPU"') for unknown op: LookupTableImportV2
2018-06-07 12:43:16.046744: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableInsertV2" device_type: "CPU"') for unknown op: LookupTableInsertV2
2018-06-07 12:43:16.046877: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableFindV2" device_type: "CPU"') for unknown op: LookupTableFindV2
2018-06-07 12:43:16.047135: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "InitializeTableFromTextFileV2" device_type: "CPU"') for unknown op: InitializeTableFromTextFileV2
2018-06-07 12:43:16.047338: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "InitializeTableV2" device_type: "CPU"') for unknown op: InitializeTableV2
2018-06-07 12:43:16.047480: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "InitializeTable" device_type: "CPU"') for unknown op: InitializeTable
2018-06-07 12:43:16.049546: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableHashTable
2018-06-07 12:43:16.049761: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: MutableHashTable
2018-06-07 12:43:16.049911: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: MutableHashTable
2018-06-07 12:43:16.050150: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableHashTable
2018-06-07 12:43:16.050559: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableHashTable
2018-06-07 12:43:16.050986: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableInsert" device_type: "CPU"') for unknown op: LookupTableInsert
2018-06-07 12:43:16.051190: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableExport" device_type: "CPU"') for unknown op: LookupTableExport
2018-06-07 12:43:16.051391: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensorsV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableHashTableOfTensorsV2
2018-06-07 12:43:16.051502: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensorsV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: MutableHashTableOfTensorsV2
2018-06-07 12:43:16.051690: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensorsV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: MutableHashTableOfTensorsV2
2018-06-07 12:43:16.051922: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableOfTensorsV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableHashTableOfTensorsV2
2018-06-07 12:43:16.053580: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_DOUBLE } } }') for unknown op: HashTable
2018-06-07 12:43:16.053739: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: HashTable
2018-06-07 12:43:16.053865: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT32 } } }') for unknown op: HashTable
2018-06-07 12:43:16.053972: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: HashTable
2018-06-07 12:43:16.054095: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: HashTable
2018-06-07 12:43:16.054200: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: HashTable
2018-06-07 12:43:16.054336: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: HashTable
2018-06-07 12:43:16.054568: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: HashTable
2018-06-07 12:43:16.054957: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: HashTable
2018-06-07 12:43:16.055086: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTable" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT32 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT32 } } }') for unknown op: HashTable
2018-06-07 12:43:16.055622: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_DOUBLE } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.055818: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.056121: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT32 } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.056384: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.056533: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.056679: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.056825: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.056972: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.057117: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.057262: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "HashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT32 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT32 } } }') for unknown op: HashTableV2
2018-06-07 12:43:16.058358: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableHashTableV2
2018-06-07 12:43:16.058515: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_INT64 } } }') for unknown op: MutableHashTableV2
2018-06-07 12:43:16.058622: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_STRING } } }') for unknown op: MutableHashTableV2
2018-06-07 12:43:16.058812: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_STRING } } } constraint { name: "value_dtype" allowed_values { list { type: DT_BOOL } } }') for unknown op: MutableHashTableV2
2018-06-07 12:43:16.058917: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "MutableHashTableV2" device_type: "CPU" constraint { name: "key_dtype" allowed_values { list { type: DT_INT64 } } } constraint { name: "value_dtype" allowed_values { list { type: DT_FLOAT } } }') for unknown op: MutableHashTableV2
2018-06-07 12:43:16.059270: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "InitializeTableFromTextFile" device_type: "CPU"') for unknown op: InitializeTableFromTextFile
2018-06-07 12:43:16.059535: E tensorflow/core/framework/op_kernel.cc:1197] OpKernel ('op: "LookupTableFind" device_type: "CPU"') for unknown op: LookupTableFind
2018-06-07 12:43:17.402005: E /Users/mbenami/Documents/Yoobic/tensorflowiOS/swift/Tensorflow/TensorflowUtils.mm:99] Could not create TensorFlow Graph: Invalid argument: No OpKernel was registered to support Op 'Add' with these attrs.  Registered devices: [CPU], Registered kernels:
  device='CPU'; T in [DT_FLOAT]

	 [[Node: MultipleGridAnchorGenerator/add_18 = Add[T=DT_INT32](MultipleGridAnchorGenerator/add_18/x, MultipleGridAnchorGenerator/strided_slice_2)]]
2018-06-07 12:43:17.475625+0300 tensorflowiOS[3030:597371] Failed to load model
2018-06-07 12:43:28.135069+0300 tensorflowiOS[3030:597247] [App] if we're in the real pre-commit handler we can't actually add any new fences due to CA restriction
2018-06-07 12:43:28.136170+0300 tensorflowiOS[3030:597247] [App] if we're in the real pre-commit handler we can't actually add any new fences due to CA restriction

on iPhone 6 iOS 11.3.1

I've seen that when I have built the iOS Tensorflow libs and forgotten to set  __ANDROID_TYPES_FULL__.  Though it is strange that 1.5 works.   Using your own dataset shouldn't matter.  I've done that many times.  You might check out some of the other suggestions here: https://github.com/tensorflow/tensorflow/issues/4863
I stayed on r1.5 until r1.8 but I also had trouble building recently.  I edited the Makefile and changed
-D__thread=thread_local
to
-D__thread= for the i386 arch only.

Another thing to try is to use the -g flag to build_all_ios.sh .  This will use print_selective_registration_header to look at your .pb file and output a header file containing all the ops needed to build for specific graph.   This has the added benefit of decreasing the app's binary size.

authors: csharpseattle mbenami

repo: csharpseattle/tensorflowiOS


text:
FIFOPerformanceSummaryUnderlying has no attribute 'subCategory'

Hello,
First of all, thank you for your package; it saves me a lot of time by not having to write my own parser. I'm trying to use it as instructed, have created a flex query, but when I try to read in the file, I get the following error:
ibflex.parser.FlexParserError: FIFOPerformanceSummaryUnderlying has no attribute 'subCategory'
Having added a subCategory optional attribute to the FIFOPerformanceSummaryUnderlying dataclass, I was then prompted with having no attribute 'figi'. All in all, I needed to add various attribute fields to a number of dataclasses in Types until it finally produced another error:
Python 3.11.1 (main, Feb  1 2023, 16:53:50) [Clang 14.0.0 (clang-1400.0.29.202)] on darwin
Type "help", "copyright", "credits" or "license" for more information.

from ibflex import parser ; response = parser.parse("Summary.xml")
Traceback (most recent call last):
File "/Users/Jacob/.pyenv/versions/3.11.1/lib/python3.11/site-packages/ibflex/parser.py", line 131, in parse_data_element
return Class(**attrs)
^^^^^^^^^^^^^^
TypeError: FlexQueryResponse.init() got an unexpected keyword argument 'script'

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "/Users/Jacob/.pyenv/versions/3.11.1/lib/python3.11/site-packages/ibflex/parser.py", line 53, in parse
parsed = parse_element(root)
^^^^^^^^^^^^^^^^^^^
File "/Users/Jacob/.pyenv/versions/3.11.1/lib/python3.11/site-packages/ibflex/parser.py", line 85, in parse_element
return parse_data_element(elem)
^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Jacob/.pyenv/versions/3.11.1/lib/python3.11/site-packages/ibflex/parser.py", line 133, in parse_data_element
raise FlexParserError(f"{Class.name} - " + str(exc))
ibflex.parser.FlexParserError: FlexQueryResponse - FlexQueryResponse.init() got an unexpected keyword argument 'script'
At this point, I'm not sure how to proceed/not sure if it's user error or a bug in the code because I think the 'script' keyword may have come from my flex file, in which case I'm not sure what settings I need to change in my flex file configuration to keep this from happening. Any help would be greatly appreciated.
Thank you in advance.

This all looks pretty much par for the course, when IB adds new data structures that aren’t yet modelled by ibflex…
…right up to the part where you hit a new top-level key called “script”.  What fresh hell is this?
If you can provide relevant excerpt from your Flex data file, scrubbed of any acct# or name or other sensitive information, I can take a look.  You should also poke around in IB web UI settings for Flex report fields… maybe there’s a checkbox you can uncheck?
Unfortunately my time to work on ibflex is extremely limited at the moment.  This unwelcome report erupts as a nexus of limbus dread.

Hi Chris,
Thanks for replying so quickly. Yeah, that first error I realized must have been IB adding new structures that ibflex just didn't have fields for yet (I deal with this kind of buffoonery all the time at work- undocumented file format updates that break existing readers). It was mostly adding the attributes "subCategory" and "figi" to maybe five of the dataclasses in Types.py, with a few other "initTransactionID"s and similar thrown in. This script thing is weird though. Opening the xml file, I see this as a header:

<AccountInformation accountId="Uxxxxxxxxx" acctAlias="" currency="xxx" name="xxxxxxxxxxx" accountType="xxx
Now, this is the first time I create a flex query with IB, access data in this form, etc., so I do not know much about the format, but it looks like some preamble script to make the flex query compatible with some other parsers?
So in that case, I'm guessing ibflex is trying to read it in as an element and so has no idea what to do with it.
Is this whole section something that newly appeared in these flex query reports and before it would just start from  or even just go straight into <FlexStatement accountId="xxxx" ... >?
Thanks in advance,
Jacob

I disabled the FIGI and the subCategory field from within FlexQuery and it started working again, so in my case the issue was just the undocumented additions from IBKR.
My file looks normal, no script or strange html before the xml part.

Hmm. Even when I disable it, it still has the script problem. I got past the errors on FIGI and subCategory by adding the attributes to the dataclasses in the Types.py module, but it still doesn't explain this script business. Then, if I just delete all of that and try to load it, I get the following error:
Traceback (most recent call last):
File "", line 1, in
File "/Users/Jacob/.pyenv/versions/3.11.1/lib/python3.11/site-packages/ibflex/parser.py", line 49, in parse
root = tree.parse(source)
^^^^^^^^^^^^^^^^^^
File "/Users/Jacob/.pyenv/versions/3.11.1/lib/python3.11/xml/etree/ElementTree.py", line 580, in parse
self._root = parser._parse_whole(source)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
xml.etree.ElementTree.ParseError: not well-formed (invalid token): line 4423, column 1
Which I understand to be potentially an error originating from xml.etree.ElementTree itself, but I can't find the offending characters that Google suggests would cause this problem. Specifically, \x08 or even the &. I didn't find any occurrences of \x08, which I thought maybe was added since I removed the whole top section using vim and Mac likes to occasionally add characters when, for example, copy pasting a file path (maybe it's an iterm2 thing? no idea). There's one & in my xml file, but it's there as & , which seems to be valid xml syntax.
Could you please copy the first few lines of your xml file so I can see what's different/where it starts? Redacting personal info of course. It would be very helpful.
Are there any intricacies to setting up the custom flex query creation in the web interface? Any way to potentially export those custom flex query settings so others can use the same ones?

This is more WTF than I generally prefer in my financial records.

Now, this is the first time I create a flex query with IB, access data in this form, etc., so I do not know much about the format, but it looks like some preamble script to make the flex query compatible with some other parsers?

I don't do web stuff, but it looks like they're trying to make a self-extracting XML that renders as HTML when you open it in Chrome... presumably as a springboard to bootstrap some stupid web app that uses encrypted blobs and geolocation.

Is this whole section something that newly appeared in these flex query reports and before it would just start from or even just go straight into <FlexStatement accountId="xxxx" ... >?

Yeah, like that.  I have never seen this script stuff before.  Is there something about this FIGI stuff that makes IB act so insane?

Then, if I just delete all of that and try to load it, I get the following error:

You probably mismatched some brackets or something I imagine.

I managed to get it to load. I needed to leave:

but delete from

authors: csingley jacob-merson marcogiglio

repo: csingley/ibflex


text:
The lnbits app link does not change to an onion url

When accessing raspiblitz-web through Tor, the  lnbits app link keeps pointing to the local lan ip instead of the onion address.

@cstenglein
Just the one supplied with RaspiBlitz:-1.8.0c
RaspiBlitz: 1.8.0
RaspiBlitz WebUI: 1.0.0

Hi, this was not implemented with 1.8.0, but will be released with 1.9.0 :)
Closing this for now, if it appears on 1.9.0, then it's an issue.

authors: cstenglein jalbstmeijer

repo: cstenglein/raspiblitz-web


text:
20240206_allsky_v0.10.5_all_dec_srcdep_base

New Prod config
Self check-list:

[x] I have checked the lstchain config, in particular for:

[ ] az_tel instead of sin_az_tel if data to be analyzed have been produced with lstchain <= v0.9.7
[ ] "increase_nsb" and "increase_psf" are provided in "image_modifier" (if used)

[x] I have checked the environment in the lstmcpipe config and it is the one used to analyse DL>1 data
[x] I have provided the command (in README), or script (in additionnal .py file) used to produce the lstmcpipe config

Prod_ID
20240206_allsky_v0.10.5_all_dec_srcdep_base
Short description of the config
Base production for all declinations lines with lstchain v0.10.5 + source-dependent analysis

hi @SeiyaNozaki
will you regenerate this one using  lstmcpipe v0.10.4 and the new config?

Thank you! I created a new PR #455 using the new config

authors: SeiyaNozaki vuillaut

repo: cta-observatory/lstmcpipe


text:
Added another simple FALSE AND TRUE test

This is a test for a problem I recently found. I'm still trying to figure out how to patch it.

I just got back from vacation a few days ago, but since I already have search issues on deck I'll tackle this as well. Thanks for bringing it up.

Finally getting the goiardi backlog knocked out. Thanks for finding this - the fix for this case is now in 0.9.1-dev, which will become the new master once the other issues pending get finished.

authors: brimstone ctdk

repo: ctdk/goiardi

license_source: bigquery


text:
mDanmakuView.seekTo((long) 100000) 程序崩溃

我用Sample ，点击按钮的时候seek到一个固定的位置，会导致程序崩溃。有时一次就崩溃，有时点击多次后崩溃
12-25 10:44:42.261: I/dalvikvm-heap(686): Grow heap (frag case) to 20.435MB for 45376-byte allocation
12-25 10:44:42.292: D/dalvikvm(686): GC_FOR_ALLOC freed <1K, 13% free 18550K/21124K, paused 29ms, total 29ms
12-25 10:44:42.292: I/dalvikvm-heap(686): Grow heap (frag case) to 20.524MB for 69232-byte allocation
12-25 10:44:42.695: D/dalvikvm(686): Trying to load lib /data/app-lib/com.sample-1/libndkbitmap.so 0x42201f18
12-25 10:44:42.695: D/dalvikvm(686): Shared lib '/data/app-lib/com.sample-1/libndkbitmap.so' already loaded in same CL 0x42201f18
12-25 10:44:42.700: E/NativeBitmapFactory(686): loadedfalse
12-25 10:44:46.813: D/dalvikvm(686): Trying to load lib /data/app-lib/com.sample-1/libndkbitmap.so 0x42201f18
12-25 10:44:46.813: D/dalvikvm(686): Shared lib '/data/app-lib/com.sample-1/libndkbitmap.so' already loaded in same CL 0x42201f18
12-25 10:44:46.822: E/NativeBitmapFactory(686): loadedfalse
12-25 10:44:46.822: A/libc(686): Fatal signal 11 (SIGSEGV) at 0x00000000 (code=1), thread 756 (DFM Cache-Build)

我也是遇到这个问题，A/libc﹕ Fatal signal 11 (SIGSEGV) at 0x693a9710 (code=1), thread 23645 (DFM update)

https://github.com/ctiao/NativeBitmapFactory 是否是 native这边导致的这个问题？

有可能

求联系方式~ 希望多交流

qq?   77497426

authors: ctiao kmfish langzuxiaozi

repo: ctiao/DanmakuFlameMaster


text:
Use external PropTypes for better support.

Long term support, react 15.5.
I am not familiar with peerDependencies, is this correct Sean?

Awesome thanks for this! Will have a look.

Upvote :D

All good in the hood. ❤

authors: DPr00f birkir ctrlplusb

repo: ctrlplusb/react-async-component

license: mit


text:
compile failed.

程序包org.elasticsearch.xcontent不存在

Please check the maven configuration and confirm whether the elasticsearch package has been downloaded.

Please check the maven configuration and confirm whether the elasticsearch package has been downloaded.

The spring-boot-starter-parentversion used in the current project is 2.7.8. and The elasticsearch version in 2.7.8 is 7.17.8.
noticeable，org.elasticsearch.xcontent.XContentType is removed from elasticSearch ver 7.17.3.so, should we consider useing a more suitable version？ such as 2.7.0？

org.elasticsearch.xcontent.XContentType is removed from elasticSearch ver 7.17.3.

org.elasticsearch.xcontent.XContentType exists in elasticsearch 7.17.8, https://github.com/elastic/elasticsearch/blob/v7.17.8/libs/x-content/src/main/java/org/elasticsearch/xcontent/XContentType.java

程序包org.elasticsearch.xcontent不存在

I had the same problem and it was fixed after deleting org\elasticsearch\elasticsearch\7.17.8 in the local repository.

Please check the maven configuration and confirm whether the elasticsearch package has been downloaded.

The spring-boot-starter-parentversion used in the current project is 2.7.8. and The elasticsearch version in 2.7.8 is 7.17.8. noticeable，org.elasticsearch.xcontent.XContentType is removed from elasticSearch ver 7.17.3.so, should we consider useing a more suitable version？ such as 2.7.0？

Thanks for your feedback, we will upgrade the version of Elasticsearch to the latest.

Please check the maven configuration and confirm whether the elasticsearch package has been downloaded.

The spring-boot-starter-parentversion used in the current project is 2.7.8. and The elasticsearch version in 2.7.8 is 7.17.8. noticeable，org.elasticsearch.xcontent.XContentType is removed from elasticSearch ver 7.17.3.so, should we consider useing a more suitable version？ such as 2.7.0？

@yuehan-mm  Thanks for your feedback, we will upgrade the version of Elasticsearch to the latest, and you can considerate @wForget 's  solution, just clean the elasticearch package locally in your repository

+1 same problem

authors: Narcasserun donggong nilnon wForget yuehan-mm zebozhuang

repo: cubefs/compass


text:
[Bug]: Bad data partitions(decommission not completed)  show error result

Describe the bug
1 i decommission a  already unavaile  dp use cfs-cli, the result is suc;
2 but after i run "cfs-cli datapartition check"
the "Bad data partitions(decommission not completed" section show dup entry i have already decommissioned;
Environment
ubuntu 20.04
CubeFS Server
Version : v3.2.1
Branch  : master
Commit  : d34dc4010dfb4e55e651c5390ce1badfe2ccf992
Build   : go1.20.4 linux amd64 2023-06-05 19:29
CubeFS CLI
Version : v3.2.1
Branch  : master
Commit  : d34dc4010dfb4e55e651c5390ce1badfe2ccf992
Build   : go1.20.4 linux amd64 2023-06-06 10:34
To Reproduce
Expected behavior
1 if success, show not  appear in "(decommission not completed" section?
2 even appear, show not appear duplicate entry?
Additional context
Add any other context about the problem here.

can you post a picture about the promblem in this issue @lygn128

added picture @Victor1319

@bboyCH4 please check this out, if it is a bug?

It seems a bug for decommission datapartition info

repo: cubefs/cubefs


text:
[Enhancement]:  when volume is deleted, cfs-client need to exit

Contact Details
No response
Is there an existing issue for this?

[X] I have searched all the existing issues

What would you like to be added?
When the volume  mounted by  cfs-client  is deleted, the cfs-client process needs to exit
Why is this needed?
No response
Anything else?
No response

closed by #3559


text:
Missing module translation

Missing in src/Resources/contao/languages/de/default.php
Add something like:
$GLOBALS['TL_LANG']['MOD']['gptcontao'] = ['GPT Contao','Konfiguration für die OpenAI Schnittstelle.'];

fixed with v0.1.1

authors: OMOSde cubex-hro

repo: cubex-hro/contao-openai-bundle


text:
Java - need a way to add or update scenarios within a Feature file

Is your feature request related to a problem? Please describe.
I have a feature file my.feature. It contains many Scenarios.
I have a program that reads this feature and allows users to a) existing scenarios, and b) add new scenarios.
So when it's done, it provides a gherkin scenario string for the scenario:
  @MyTestTag
  Scenario Outline: Do some stuff!
    Given the user <MyUser> logs in
    Then the user is cool

    Examples:
      | MyUser    |
      | Nick      |

I need to update a scenario or add a scenario within this feature file.
There appears to be no methods within the Gherkin-java sdk to handle this.
Describe the solution you'd like
There should be a way to take a Gherkin text of a scenario and update an existing feature file.
public static void replaceExample(String scenarioName, String scenarioGherkinString, Envelope existingEnvelope) throws IOException {
	IdGenerator idGenerator = new IdGenerator.Incrementing();

	Envelope newEnvelope = Gherkin.fromSources(Arrays.asList(Gherkin.makeSourceEnvelope(scenarioGherkinString, "test.feature")), false, true, false, idGenerator)
			.collect(Collectors.toList()).get(0);

	GherkinDocument gherkinDocument = existingEnvelope.getGherkinDocument();
	List<FeatureChild> features = gherkinDocument.getFeature().getChildrenList();
	Optional<FeatureChild> feature = features.stream().filter(f -> f.getScenario().getName().equals(scenarioName)).findFirst();
	if (feature.isPresent()) {
		// edit scenario in the exisingEnvelope
	} else {
		// add a new scenario to the exisingEnvelope
	}
}

Describe alternatives you've considered
I am debating whether or not I should just do this by hand, instead of using the Gherkin SDK.

Are you looking for a way to convert the GherkinDocument abstract syntax tree back to a string?

Closing due to lack of activity.
Please use the support forums for questions and discussions. We use GitHub issues to track bugs and contributions exclusively.

authors: aslakhellesoy nddipiazza

repo: cucumber/cucumber


text:
cue/load: support package pattern wildcards beyond the current module

To fix #3155, https://review.gerrithub.io/c/cue-lang/cue/+/1195195 takes an approach where package patterns with wildcards like ./... are only supported if they use the current module as a prefix, i.e. they aren't meant to match any external modules such as existing or missing dependencies. This is the simplest kind of wildcard to support, as it's very similar to filesystem globbing like **/, given that all possible matches are in the local current module.
Supporting arbitrary patterns with wildcards to query packages or modules may be problematic for a number of reasons:

They could take a long time; shoud .../foo match all "foo" packages across all CUE modules ever published?
They could require many requests to registries, particularly when trying to discover which modules may exist or contain a package.
They could be more complex algorithms; a wildcard matching an unknown number of modules might need to keep updating the module graph due to MVS.

This issue is mainly to capture what kinds of use cases people might have for package (or module) patterns beyond the current or local module.

They could take a long time; shoud .../foo match all "foo" packages across all CUE modules ever published?
They could require many requests to registries, particularly when trying to discover which modules may exist or contain a package.
They could be more complex algorithms; a wildcard matching an unknown number of modules might need to keep updating the module graph due to MVS.

Note that in practice Go does not support patterns of that form, as it almost always fails
because of missing go.sum entries.
For example, in the CUE project itself:
% go list .../qt
pattern .../qt: cloud.google.com/go/compute/metadata@v0.3.0: missing go.sum entry
% go list ...
go: updates to go.mod needed; to update it:
	go mod tidy

So I think it would probably be reasonable to restrict pattern matching outside the
current module to patterns that begin with a non-wildcard prefix that corresponds
to a module name.

authors: mvdan rogpeppe

repo: cue-lang/cue


text:
refactors savings to include hooks

#71

@krysh1 from the last build  we moved value scaling into the savings module using the arrays. If a scalar value is passed it will be calculated with numpy against the arrays but not the cvrmse.
In a previous commit we had also placed a scalar internally in the calc.savings internal module but that resulted in us scaling gross predicted usage twice and it was quickly removed. I had patched this all very quickly and the last one was poorly documented and accidently went in with a version bump.
Original PRs to handle scalars:

https://github.com/cunybpl/changepointmodel/pull/45  - introduces the scalar kwarg to the internal calc and core modules
https://github.com/cunybpl/changepointmodel/pull/47  - also scales arrays

See here for the quickfix that removed self._scalar:

https://github.com/cunybpl/changepointmodel/commit/1fcfa34ca43e072d026d16b0a5e2b3153677f482 - correctly removes self._scalar from call to internal calc since the data has already been scaled in the arrays. (was scaling twice)

This took me a few minutes to figure out and made me think there was a bug in the calc here even though there is not.
I decided to deprecrate the internal one here while leaving the function signature alone. I added a note in the documentation.

e1ddb5c From here:

refactored into 2 abstract base classes with a _savings method that should be overridden in subclasses
The two concrete subclasses call into calc.savings in an identical way from 2.0.1
Deprecated the need for internal scalar value in calc.savings to avoid potential confusion. We can probably safely remove the function argument there at this point... I feel like it was added in error but left in to avoid complications in testing and production apps.

@tinnaing347 this backports to 3.9 ... it was a simple fix and other people are working on google collab with this which is currently pinned to py3.9

repo: cunybpl/changepointmodel


text:
easier way to query device attributes?

I was curious if there is interest in adding a more user-friendly way to retrieve device attributes such as MAX_THREADS_PER_BLOCK, MAX_GRID_DIM_X, etc. In CUDA 9.2/CUDA 10 there are 101 such attributes defined in cuda.h.
It seems that these can already be retrieved via cupy.cuda.runtime.deviceGetAttribute, but one needs to know the appropriate enum value for each attribute of interest.
Is there any interest in adding a function that would return the values of all available attributes as a dict or other similar structure that is more user-friendly?
A basic solution I came up with was to copy enum values from cuda.h into one of the cython files like runtime.pxd.  If there is interest I can make a PR.
e.g.
cpdef enum:
    CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 1              # Maximum number of threads per block
    CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X = 2                    # Maximum block dimension X
    CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y = 3                    # Maximum block dimension Y
    CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z = 4                    # Maximum block dimension Z
    CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X = 5                     # Maximum grid dimension X
    CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y = 6                     # Maximum grid dimension Y
    CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z = 7                     # Maximum grid dimension Z
    CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK = 8        # Maximum shared memory available per block in bytes

etc.
Then a convenience function similar to the following would create a dict with attribute names as the keys.

def get_attributes_dict(device_id):
    """Return a dict containing all device attributes."""
    d = {}
    for k, v in runtime.__dict__.items():
        if 'CU_DEVICE_ATTRIBUTE' in k:
            try:
                name = k.replace('CU_DEVICE_ATTRIBUTE_', '')
                d[name] = runtime.deviceGetAttribute(v, device_id)
            except runtime.CUDARuntimeError:
                pass
    return d

(the except case is necessary to skip any attributes that were undefined in older CUDA versions)
The output of the function is a dict such as:
{ 'MAX_THREADS_PER_BLOCK': 1024,
  'MAX_BLOCK_DIM_X': 1024,
  'MAX_BLOCK_DIM_Y': 1024,
  'MAX_BLOCK_DIM_Z': 64,
  'MAX_GRID_DIM_X': 2147483647,
  'MAX_GRID_DIM_Y': 65535,
  'MAX_GRID_DIM_Z': 65535,
  'MAX_SHARED_MEMORY_PER_BLOCK': 49152,
...

A basic solution I came up with was to copy enum values from cuda.h into one of the cython files like runtime.pxd. If there is interest I can make a PR.

Such PR is welcomed. Note that constant names should be in form of devAttrMaxThreadsPerBlock instead of CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK as defined in Runtime API.
https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html#group__CUDART__TYPES_1g49e2f8c2c0bd6fe264f2fc970912e5cd
As for the get_attributes_dict, I think it sounds make sense to add it to cupy.cuda.Device like this:
@property
def attributes(self):
    return get_attributes_dict(self.id)

(maybe it's better to memoize get_attributes_dict)

repo: cupy/cupy


text:
Failed to compile cupy/cuda/cupy_cub.cu on RedHat 7.7

$ pip install .
Processing /home/EDU1/anaruse/work/CUPY/cupy
Requirement already satisfied: numpy>=1.15 in /home/EDU1/anaruse/.pyenv/versions/3.6.12/lib/python3.6/site-packages (from cupy==8.0.0rc1) (1.19.1)
Requirement already satisfied: fastrlock>=0.3 in /home/EDU1/anaruse/.pyenv/versions/3.6.12/lib/python3.6/site-packages (from cupy==8.0.0rc1) (0.5)
Using legacy 'setup.py install' for cupy, since package 'wheel' is not installed.
Installing collected packages: cupy
    Running setup.py install for cupy: started
    Running setup.py install for cupy: still running...
    Running setup.py install for cupy: finished with status 'error'
    ERROR: Command errored out with exit status 1:
     command: /home/EDU1/anaruse/.pyenv/versions/3.6.12/bin/python3.6 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-v4z0rrpr/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-v4z0rrpr/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-dfdjgpdi/install-record.txt --single-version-externally-managed --compile --install-headers /home/EDU1/anaruse/.pyenv/versions/3.6.12/include/python3.6m/cupy
         cwd: /tmp/pip-req-build-v4z0rrpr/
    Complete output (301 lines):
    Options: {'package_name': 'cupy', 'long_description': None, 'wheel_libs': [], 'wheel_includes': [], 'wheel_metadata': None, 'no_rpath': False, 'profile': False, 'linetrace': False, 'annotate': False, 'no_cuda': False, 'use_hip': False}

    -------- Configuring Module: cuda --------

    -------- Configuring Module: cusolver --------

    -------- Configuring Module: cudnn --------
    /tmp/tmp3wd7iofm/a.cpp:1:19: fatal error: cudnn.h: No such file or directory
     #include <cudnn.h>
                       ^
    compilation terminated.
    command 'gcc' failed with exit status 1

    -------- Configuring Module: nccl --------

    -------- Configuring Module: nvtx --------

    -------- Configuring Module: cutensor --------
    /tmp/tmpod67k0_v/a.cpp:1:22: fatal error: cutensor.h: No such file or directory
     #include <cutensor.h>
                          ^
    compilation terminated.
    command 'gcc' failed with exit status 1

    -------- Configuring Module: cub --------
    /tmp/tmp2j77np4g/a.cpp:2:35: fatal error: cub/version.cuh: No such file or directory
             #include <cub/version.cuh>
                                       ^
    compilation terminated.

    -------- Configuring Module: thrust --------

    ************************************************************
    * CuPy Configuration Summary                               *
    ************************************************************

    Build Environment:
      Include directories: ['/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub', '/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include', '/system/apps/rhel77/cuda/10.2/include']
      Library directories: ['/system/apps/rhel77/cuda/10.2/lib64']
      nvcc command       : ['/system/apps/rhel77/cuda/10.2/bin/nvcc']

    Environment Variables:
      CFLAGS          : (none)
      LDFLAGS         : (none)
      LIBRARY_PATH    : /system/apps/rhel77/cuda/10.2/lib64
      CUDA_PATH       : /system/apps/rhel77/cuda/10.2
      NVTOOLSEXT_PATH : (none)
      NVCC            : (none)
      ROCM_HOME       : (none)

    Modules:
      cuda      : Yes (version 10020)
      cusolver  : Yes
      cudnn     : No
        -> Include files not found: ['cudnn.h']
        -> Check your CFLAGS environment variable.
      nccl      : Yes (version 2402)
      nvtx      : Yes
      cutensor  : No
        -> Include files not found: ['cutensor.h']
        -> Check your CFLAGS environment variable.
      cub       : Yes (version 100800)
      thrust    : Yes (version 100907)

    WARNING: Some modules could not be configured.
    CuPy will be installed without these modules.
    Please refer to the Installation Guide for details:
    https://docs.cupy.dev/en/stable/install.html

    ************************************************************

    running install
    running build
    running build_py
    running build_ext

    -------- Configuring Module: cuda --------
    creating /tmp/tmp2w31avoq/tmp
    creating /tmp/tmp2w31avoq/tmp/tmp2w31avoq
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp2w31avoq/a.cpp -o /tmp/tmp2w31avoq/tmp/tmp2w31avoq/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmp2w31avoq/tmp/tmp2w31avoq/a.o -o /tmp/tmp2w31avoq/liba.so
    creating /tmp/tmp7l5hb6ih/tmp
    creating /tmp/tmp7l5hb6ih/tmp/tmp7l5hb6ih
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -c /tmp/tmp7l5hb6ih/a.cpp -o /tmp/tmp7l5hb6ih/tmp/tmp7l5hb6ih/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmp7l5hb6ih/tmp/tmp7l5hb6ih/a.o -L/system/apps/rhel77/cuda/10.2/lib64 -lcublas -lcuda -lcudart -lcufft -lcurand -lcusparse -lnvrtc -o /tmp/tmp7l5hb6ih/liba.so
    creating /tmp/tmpu__3uenn/tmp
    creating /tmp/tmpu__3uenn/tmp/tmpu__3uenn
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmpu__3uenn/a.cpp -o /tmp/tmpu__3uenn/tmp/tmpu__3uenn/a.o
    g++ -pthread /tmp/tmpu__3uenn/tmp/tmpu__3uenn/a.o -o /tmp/tmpu__3uenn/a

    -------- Configuring Module: cusolver --------
    creating /tmp/tmpd1dcqyvq/tmp
    creating /tmp/tmpd1dcqyvq/tmp/tmpd1dcqyvq
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmpd1dcqyvq/a.cpp -o /tmp/tmpd1dcqyvq/tmp/tmpd1dcqyvq/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmpd1dcqyvq/tmp/tmpd1dcqyvq/a.o -o /tmp/tmpd1dcqyvq/liba.so
    creating /tmp/tmp09gjm6mi/tmp
    creating /tmp/tmp09gjm6mi/tmp/tmp09gjm6mi
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -c /tmp/tmp09gjm6mi/a.cpp -o /tmp/tmp09gjm6mi/tmp/tmp09gjm6mi/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmp09gjm6mi/tmp/tmp09gjm6mi/a.o -L/system/apps/rhel77/cuda/10.2/lib64 -lcusolver -o /tmp/tmp09gjm6mi/liba.so
    creating /tmp/tmp8hu2awrz/tmp
    creating /tmp/tmp8hu2awrz/tmp/tmp8hu2awrz
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp8hu2awrz/a.cpp -o /tmp/tmp8hu2awrz/tmp/tmp8hu2awrz/a.o
    g++ -pthread /tmp/tmp8hu2awrz/tmp/tmp8hu2awrz/a.o -o /tmp/tmp8hu2awrz/a

    -------- Configuring Module: cudnn --------
    creating /tmp/tmp8_6kq71p/tmp
    creating /tmp/tmp8_6kq71p/tmp/tmp8_6kq71p
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp8_6kq71p/a.cpp -o /tmp/tmp8_6kq71p/tmp/tmp8_6kq71p/a.o
    /tmp/tmp8_6kq71p/a.cpp:1:19: fatal error: cudnn.h: No such file or directory
     #include <cudnn.h>
                       ^
    compilation terminated.
    command 'gcc' failed with exit status 1

    -------- Configuring Module: nccl --------
    creating /tmp/tmp6zw3qnla/tmp
    creating /tmp/tmp6zw3qnla/tmp/tmp6zw3qnla
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp6zw3qnla/a.cpp -o /tmp/tmp6zw3qnla/tmp/tmp6zw3qnla/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmp6zw3qnla/tmp/tmp6zw3qnla/a.o -o /tmp/tmp6zw3qnla/liba.so
    creating /tmp/tmpegfqr516/tmp
    creating /tmp/tmpegfqr516/tmp/tmpegfqr516
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -c /tmp/tmpegfqr516/a.cpp -o /tmp/tmpegfqr516/tmp/tmpegfqr516/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmpegfqr516/tmp/tmpegfqr516/a.o -L/system/apps/rhel77/cuda/10.2/lib64 -lnccl -o /tmp/tmpegfqr516/liba.so
    creating /tmp/tmpa8v96sdm/tmp
    creating /tmp/tmpa8v96sdm/tmp/tmpa8v96sdm
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmpa8v96sdm/a.cpp -o /tmp/tmpa8v96sdm/tmp/tmpa8v96sdm/a.o
    g++ -pthread /tmp/tmpa8v96sdm/tmp/tmpa8v96sdm/a.o -o /tmp/tmpa8v96sdm/a

    -------- Configuring Module: nvtx --------
    creating /tmp/tmp567fuwj4/tmp
    creating /tmp/tmp567fuwj4/tmp/tmp567fuwj4
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp567fuwj4/a.cpp -o /tmp/tmp567fuwj4/tmp/tmp567fuwj4/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmp567fuwj4/tmp/tmp567fuwj4/a.o -o /tmp/tmp567fuwj4/liba.so
    creating /tmp/tmp4tfzf14r/tmp
    creating /tmp/tmp4tfzf14r/tmp/tmp4tfzf14r
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -c /tmp/tmp4tfzf14r/a.cpp -o /tmp/tmp4tfzf14r/tmp/tmp4tfzf14r/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmp4tfzf14r/tmp/tmp4tfzf14r/a.o -L/system/apps/rhel77/cuda/10.2/lib64 -lnvToolsExt -o /tmp/tmp4tfzf14r/liba.so

    -------- Configuring Module: cutensor --------
    creating /tmp/tmp_b24lzw4/tmp
    creating /tmp/tmp_b24lzw4/tmp/tmp_b24lzw4
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp_b24lzw4/a.cpp -o /tmp/tmp_b24lzw4/tmp/tmp_b24lzw4/a.o
    /tmp/tmp_b24lzw4/a.cpp:1:22: fatal error: cutensor.h: No such file or directory
     #include <cutensor.h>
                          ^
    compilation terminated.
    command 'gcc' failed with exit status 1

    -------- Configuring Module: cub --------
    creating /tmp/tmpsk7mppi0/tmp
    creating /tmp/tmpsk7mppi0/tmp/tmpsk7mppi0
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmpsk7mppi0/a.cpp -o /tmp/tmpsk7mppi0/tmp/tmpsk7mppi0/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmpsk7mppi0/tmp/tmpsk7mppi0/a.o -o /tmp/tmpsk7mppi0/liba.so
    creating /tmp/tmpc43kuszl/tmp
    creating /tmp/tmpc43kuszl/tmp/tmpc43kuszl
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -c /tmp/tmpc43kuszl/a.cpp -o /tmp/tmpc43kuszl/tmp/tmpc43kuszl/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmpc43kuszl/tmp/tmpc43kuszl/a.o -L/system/apps/rhel77/cuda/10.2/lib64 -lcudart -o /tmp/tmpc43kuszl/liba.so
    creating /tmp/tmp2n2acf2y/tmp
    creating /tmp/tmp2n2acf2y/tmp/tmp2n2acf2y
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmp2n2acf2y/a.cpp -o /tmp/tmp2n2acf2y/tmp/tmp2n2acf2y/a.o
    /tmp/tmp2n2acf2y/a.cpp:2:35: fatal error: cub/version.cuh: No such file or directory
             #include <cub/version.cuh>
                                       ^
    compilation terminated.

    -------- Configuring Module: thrust --------
    creating /tmp/tmpzf1tnyig/tmp
    creating /tmp/tmpzf1tnyig/tmp/tmpzf1tnyig
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -DCUPY_CUB_VERSION_CODE=100800 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmpzf1tnyig/a.cpp -o /tmp/tmpzf1tnyig/tmp/tmpzf1tnyig/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmpzf1tnyig/tmp/tmpzf1tnyig/a.o -o /tmp/tmpzf1tnyig/liba.so
    creating /tmp/tmph1zt822e/tmp
    creating /tmp/tmph1zt822e/tmp/tmph1zt822e
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -DCUPY_CUB_VERSION_CODE=100800 -c /tmp/tmph1zt822e/a.cpp -o /tmp/tmph1zt822e/tmp/tmph1zt822e/a.o
    g++ -pthread -shared -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib -L/home/EDU1/anaruse/.pyenv/versions/3.6.12/lib /tmp/tmph1zt822e/tmp/tmph1zt822e/a.o -L/system/apps/rhel77/cuda/10.2/lib64 -lcudart -o /tmp/tmph1zt822e/liba.so
    creating /tmp/tmpig6dsoj4/tmp
    creating /tmp/tmpig6dsoj4/tmp/tmpig6dsoj4
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -c /tmp/tmpig6dsoj4/a.cpp -o /tmp/tmpig6dsoj4/tmp/tmpig6dsoj4/a.o
    g++ -pthread /tmp/tmpig6dsoj4/tmp/tmpig6dsoj4/a.o -o /tmp/tmpig6dsoj4/a

    ************************************************************
    * CuPy Configuration Summary                               *
    ************************************************************

    Build Environment:
      Include directories: ['/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub', '/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include', '/system/apps/rhel77/cuda/10.2/include']
      Library directories: ['/system/apps/rhel77/cuda/10.2/lib64']
      nvcc command       : ['/system/apps/rhel77/cuda/10.2/bin/nvcc']

    Environment Variables:
      CFLAGS          : (none)
      LDFLAGS         : (none)
      LIBRARY_PATH    : /system/apps/rhel77/cuda/10.2/lib64
      CUDA_PATH       : /system/apps/rhel77/cuda/10.2
      NVTOOLSEXT_PATH : (none)
      NVCC            : (none)
      ROCM_HOME       : (none)

    Modules:
      cuda      : Yes (version 10020)
      cusolver  : Yes
      cudnn     : No
        -> Include files not found: ['cudnn.h']
        -> Check your CFLAGS environment variable.
      nccl      : Yes (version 2402)
      nvtx      : Yes
      cutensor  : No
        -> Include files not found: ['cutensor.h']
        -> Check your CFLAGS environment variable.
      cub       : Yes (version 100800)
      thrust    : Yes (version 100907)

    WARNING: Some modules could not be configured.
    CuPy will be installed without these modules.
    Please refer to the Installation Guide for details:
    https://docs.cupy.dev/en/stable/install.html

    ************************************************************

    building 'cupy.cuda.cub' extension
    gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -D_FORCE_INLINES=1 -DCUPY_CUB_VERSION_CODE=100800 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -I/home/EDU1/anaruse/.pyenv/versions/3.6.12/include/python3.6m -c cupy/cuda/cub.cpp -o build/temp.linux-x86_64-3.6/cupy/cuda/cub.o -fopenmp
    NVCC options: ['--generate-code=arch=compute_30,code=compute_30', '--generate-code=arch=compute_50,code=compute_50', '--generate-code=arch=compute_60,code=sm_60', '--generate-code=arch=compute_61,code=sm_61', '--generate-code=arch=compute_70,code=sm_70', '--generate-code=arch=compute_75,code=sm_75', '--generate-code=arch=compute_70,code=compute_70', '-O2', '--compiler-options="-fPIC"', '--std=c++11']
    /system/apps/rhel77/cuda/10.2/bin/nvcc -D_FORCE_INLINES=1 -DCUPY_CUB_VERSION_CODE=100800 -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/cub -I/tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include -I/system/apps/rhel77/cuda/10.2/include -I/home/EDU1/anaruse/.pyenv/versions/3.6.12/include/python3.6m -c cupy/cuda/cupy_cub.cu -o build/temp.linux-x86_64-3.6/cupy/cuda/cupy_cub.o --generate-code=arch=compute_30,code=compute_30 --generate-code=arch=compute_50,code=compute_50 --generate-code=arch=compute_60,code=sm_60 --generate-code=arch=compute_61,code=sm_61 --generate-code=arch=compute_70,code=sm_70 --generate-code=arch=compute_75,code=sm_75 --generate-code=arch=compute_70,code=compute_70 -O2 --compiler-options="-fPIC" --std=c++11
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/arithmetic.h:256:54: error: \u2018float thrust::abs(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline float abs(const complex<float>& z) {
                                                          ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/arithmetic.h:260:56: error: \u2018double thrust::abs(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline double abs(const complex<double>& z) {
                                                            ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/cexp.h:169:67: error: \u2018thrust::complex<double> thrust::exp(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> exp(const complex<double>& z) {
                                                                       ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/cexpf.h:149:65: error: \u2018thrust::complex<float> thrust::exp(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> exp(const complex<float>& z) {
                                                                     ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/clog.h:192:67: error: \u2018thrust::complex<double> thrust::log(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> log(const complex<double>& z) {
                                                                       ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/clogf.h:188:65: error: \u2018thrust::complex<float> thrust::log(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> log(const complex<float>& z) {
                                                                     ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/ccosh.h:195:2: error: \u2018thrust::complex<double> thrust::cos(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
         const thrust::complex<double>& z) {
      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/ccosh.h:201:2: error: \u2018thrust::complex<double> thrust::cosh(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
         const thrust::complex<double>& z) {
      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/ccoshf.h:126:65: error: \u2018thrust::complex<float> thrust::cos(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> cos(const complex<float>& z) {
                                                                     ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/ccoshf.h:131:66: error: \u2018thrust::complex<float> thrust::cosh(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> cosh(const complex<float>& z) {
                                                                      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/csinh.h:183:67: error: \u2018thrust::complex<double> thrust::sin(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> sin(const complex<double>& z) {
                                                                       ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/csinh.h:188:68: error: \u2018thrust::complex<double> thrust::sinh(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> sinh(const complex<double>& z) {
                                                                        ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/csinhf.h:124:65: error: \u2018thrust::complex<float> thrust::sin(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> sin(const complex<float>& z) {
                                                                     ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/csinhf.h:129:66: error: \u2018thrust::complex<float> thrust::sinh(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> sinh(const complex<float>& z) {
                                                                      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/ctanh.h:182:67: error: \u2018thrust::complex<double> thrust::tan(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> tan(const complex<double>& z) {
                                                                       ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/ctanhf.h:107:65: error: \u2018thrust::complex<float> thrust::tan(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> tan(const complex<float>& z) {
                                                                     ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/csqrt.h:140:68: error: \u2018thrust::complex<double> thrust::sqrt(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> sqrt(const complex<double>& z) {
                                                                        ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/csqrtf.h:137:66: error: \u2018thrust::complex<float> thrust::sqrt(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> sqrt(const complex<float>& z) {
                                                                      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrig.h:697:68: error: \u2018thrust::complex<double> thrust::acos(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> acos(const complex<double>& z) {
                                                                        ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrig.h:702:68: error: \u2018thrust::complex<double> thrust::asin(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> asin(const complex<double>& z) {
                                                                        ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrig.h:708:68: error: \u2018thrust::complex<double> thrust::atan(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> atan(const complex<double>& z) {
                                                                        ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrig.h:725:69: error: \u2018thrust::complex<double> thrust::atanh(const thrust::complex<double>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<double> atanh(const complex<double>& z) {
                                                                         ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrigf.h:411:66: error: \u2018thrust::complex<float> thrust::acos(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> acos(const complex<float>& z) {
                                                                      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrigf.h:416:66: error: \u2018thrust::complex<float> thrust::asin(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> asin(const complex<float>& z) {
                                                                      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrigf.h:422:66: error: \u2018thrust::complex<float> thrust::atan(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> atan(const complex<float>& z) {
                                                                      ^
    /tmp/pip-req-build-v4z0rrpr/install/../cupy/core/include/cupy/complex/catrigf.h:439:67: error: \u2018thrust::complex<float> thrust::atanh(const thrust::complex<float>&)\u2019 is not declared in \u2018thrust\u2019
     __host__ __device__ inline complex<float> atanh(const complex<float>& z) {
                                                                       ^
    error: command '/system/apps/rhel77/cuda/10.2/bin/nvcc' failed with exit status 1
    ----------------------------------------
ERROR: Command errored out with exit status 1: /home/EDU1/anaruse/.pyenv/versions/3.6.12/bin/python3.6 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-v4z0rrpr/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-v4z0rrpr/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-dfdjgpdi/install-record.txt --single-version-externally-managed --compile --install-headers /home/EDU1/anaruse/.pyenv/versions/3.6.12/include/python3.6m/cupy Check the logs for full command output.

Most likely the gcc is too old.

Thanks, @leofang !  Is this too old?
$ gcc -v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/libexec/gcc/x86_64-redhat-linux/4.8.5/lto-wrapper
Target: x86_64-redhat-linux
Configured with: ../configure --prefix=/usr --mandir=/usr/share/man --infodir=/usr/share/info --with-bugurl=http://bugzilla.redhat.com/bugzilla --enable-bootstrap --enable-shared --enable-threads=posix --enable-checking=release --with-system-zlib --enable-__cxa_atexit --disable-libunwind-exceptions --enable-gnu-unique-object --enable-linker-build-id --with-linker-hash-style=gnu --enable-languages=c,c++,objc,obj-c++,java,fortran,ada,go,lto --enable-plugin --enable-initfini-array --disable-libgcj --with-isl=/builddir/build/BUILD/gcc-4.8.5-20150702/obj-x86_64-redhat-linux/isl-install --with-cloog=/builddir/build/BUILD/gcc-4.8.5-20150702/obj-x86_64-redhat-linux/cloog-install --enable-gnu-indirect-function --with-tune=generic --with-arch_32=x86-64 --build=x86_64-redhat-linux
Thread model: posix
gcc version 4.8.5 20150623 (Red Hat 4.8.5-39) (GCC)

Yes, it is. See #3530 and https://docs.cupy.dev/en/stable/install.html#build-fails-with-cuda-11-0-on-ubuntu-16-04-centos-6-or-7. I think you need at least gcc 6.

gcc made a false claim on their C++11 support in 4.8.x...😞

That reminds me there was a gcc version issue before, I forgot all about it...

authors: anaruse leofang


text:
Add ndarray variants AND inplace support in fallback_mode

EDIT:
I've fixed the bug associated with ndarray.__init__.
ORIGINAL:
This PR is related to #2066
This PR will support use of numpy.MaskedArray, numpy.chararray, numpy.recarray, numpy.matrix. Also, there will be some performance improvement when an ndarray is fallbacked consecutively.
And structure of fallback.ndarray is changed so that, it doesn't need to explicitly check for in-place updates. In-place changes to an ndarray will be confirmed before dispatching it for function execution (both cupy and numpy) including functions such as __repr__.
TO-DO:

Fix ndarray creation using cupy.ndarray.__init__, currently all attributes are returned as NoneType.

Recent changes caused this issue. Currently working to figure it out.

@Piyush-555 Any updates?

Is it already ready to review? If so, please remove [wip] label from the title of this PR.

Jenkins, test this please.

Jenkins CI test (for commit b648c2d3befb040be4a8aa1e52da2a75fb9a4156, target branch master) failed with status FAILURE.

@Piyush-555 Could you check Jenkins failures?

@asi1024 I was not able to reproduce the error for test_out_is_returned_when_not_fallbacked. But by the looks of it, it seems that the error is probably due to default dtype being float32 in testing.shaped_random.
Could you re-run the CI?

@Piyush-555 The random seed of shaped_random is fixed to 0 in default.

Jenkins, test this please.

Jenkins CI test (for commit 093d16305c30cde57b8f626c14de3b9e9d274e5b, target branch master) succeeded!

LGTM.


text:
Introduce cupy.available

Currently, chainer.cuda.available is True even if there is no available CUDA device (by setting CUDA_VISIBLE_DEVICES=-1).
In order to avoid that, this PR introduces cupy.available which takes account of device availability.
(Corresponding issue in PyTorch: https://github.com/pytorch/pytorch/issues/306)

Fixed.

It seems calling runtime.getDeviceCount() in the module-level code of cupy/cuda/__init__.py causes problem in multi-process environment.
I fixed it by deferring the call with a function (cupy.is_available()) insted of a flag (cupy.available).

Perhaps chainer.cuda.available should also be deferred. That would be a compatibility-breaking change.

LGTM!

authors: niboshi okuta


text:
Awesome

Awesome Home Assistant extension, but can you say how you made like this side menu

The sidebar is a feature coming in HA 0.96.0, it is in the current beta.

authors: maykar xMrVizzy

repo: custom-cards/favicon-counter


text:
[Bug]: Cards in ThreeDialog are unclickably small in Firefox

Bug Summary
When using firefox, the cards in the ThreeDialog are very small to the point of being unclickable
Detailed Description
This is likely due to missing an explicit size on the images which have been changed to .svg files. See #179
Current Behavior
No response
Expected Behavior
No response
Steps to Reproduce
No response

@itsalaidbacklife is this one you wanted to assign to me?

Yeah @jerryh-jr can you have at it?

@itsalaidbacklife sure can. Will work on it tonight.

authors: itsalaidbacklife jerryh-jr

repo: cuttle-cards/cuttle


text:
Can not export CVAT for video annotaitons

Actions before raising this issue

[X] I searched the existing issues and did not find anything similar.
[X] I read/searched the docs

Steps to Reproduce

Create a task with single job
Upload annotations
Export annotations
Create a task with 10 jobs out of the same video
Upload annotations from (3)
Export annotations
Catch an AssertionError

https://github.com/user-attachments/assets/d527ad46-2929-46a8-a3a0-c45fa37a317c
Expected Behavior
If I am able to export annotations from the task that contains 1 job, I have to be able to export annotations from the same task composed out of N jobs.
Now it is impossible.
Checking internally, I see that for some reason, the last frame of the track (outside=True) for several tracks are doubled, which is actually produces this error.
Possible Solution
No response
Context
I can provide annotations if needed
Environment
I see this both in 2.9.2 and in app.cvat.ai

Possible duplicate of https://github.com/cvat-ai/cvat/issues/6779

Hello! Could you please provide annotations? And also the video, if it's possible

authors: Eldies PMazarovich zhiltsov-max

repo: cvat-ai/cvat


text:
ModuleNotFoundError: No module named 'SuperGluePretrainedNetwork.models'

Hi!
When I was running pipeline_SfM.ipynb, I got an error:
ModuleNotFoundError: No module named 'SuperGluePretrainedNetwork.models'

Can you help me? @Skydes

Hi! When I was running pipeline_SfM.ipynb, I got an error: ModuleNotFoundError: No module named 'SuperGluePretrainedNetwork.models'
Can you help me? @Skydes

I solved it,
thanks!

Can you explain how? @houyongdi

Oh, As I see, there is another repo with it ... ok
https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/models/superglue.py

Oh, As I see, there is another repo with it ... ok
https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/models/superglue.py

Hello, could you tell me how you solved it? This question has been bothering me all day.

try pulling this repository https://github.com/magicleap/SuperGluePretrainedNetwork into third_party/SuperGluePretrainedNetwork (works for me)

AttributeError: 'numpy.ndarray' object has no attribute 'replace'

authors: GerasimovIV clousy188 feiyangsuo houyongdi

repo: cvg/Hierarchical-Localization


text:
The meaning of inliers in visualization code

What is the difference between the two approaches, f'found {ret["num_inliers"]}/{len(ret["inliers"])} inlier correspondences.' and 'visualization.visualize_loc_from_log(images, query, log, model,top_k_db=10)', the inlier number and ratio seem cannot match?

I don't quite understand how the numerator and denominator in the inliers data are derived from ret["num_inliers"]}/{len(ret["inliers"]). They don't seem to be the sum, average, or maximum of correspondences between the query and all retrieved images.


text:
Slug for a text in Persian language is not generated correctly

Hi,
Thanks for the great package. I used it for my multilingual site and I realized that the slugs for the texts in Persian are not generated correctly. For example suppose the text "بسته اقفصادی" so the slug would be "بسته-اقتصادی" but it generates "basth-kfs-d"

You will need to look the underlying slug library, cocur/slugify to see why it's not working for you.
A quick look at https://github.com/cocur/slugify/tree/master/Resources/rules, and I don't think they have any rules for Persian.  I guess it's probably using the Arabic rules instead, which I'm guessing aren't 'exactly the same.
I'd recommend making a PR for cocur/slugify to add a Persian ruleset.

authors: cviebrock sasanbabai

repo: cviebrock/eloquent-sluggable


text:
Repeat the constraints in 2D-array

Can the constraints repeat for 2 same things in a 2D-array?
`
totalTime=50
duration = 4
totalCourse=2
startHour= cvx.Variable( (totalCourse, totalTime), boolean=True)
nextHour= cvx.Variable( (totalCourse, totalTime), boolean=True)
for c in range(totalCourse):
constraints.append(cvx.vec(startHour[c])+ cvx.vec(nextHour[c]) <=1)
constraints.append(cvx.vec(startHour[c]) + cvx.vec(nextHour[c]) == duration
Form objective.
obj = cvx.Minimize(1)
Form and solve problem.
prob= cvx.Problem(obj, constraints)
prob.solve() # Returns the optimal value.
`
Because it does not work for me. If I separate do, then it work for me.

cvx.vec(startHour[c]) : I write this because I want to vectorize the two 2D-array and add together so that they less that one. This mean that startHour[0][0]+nextHour[0][0]<=1, startHour[0][1]<=nextHour[0][1]....
Sorry, I have paste wrong constraint ady. Below are the correct code:
constraints.append(cvx.vec(startHour)+ cvx.vec(nextHour) <=1) #to make sure the classes wont overlap for one course constraints.append(cvx.sum(startHour) + cvx.sum(nextHour) == duration)#ensure have 4hrs class

honestly, I think this is more of a modeling question than an issue with cvxpy.  cvxpy can handle the constraints you specified and is able to solve the problem with those constraints, but I don't think your model is solving the problem you want to solve.
You will probably have better luck asking here:
https://groups.google.com/forum/#!forum/cvxpy

Agreed. I'm not really sure what you're asking, better to discuss it on the forum or stackoverflow.

authors: SteveDiamond arlenk sheekhey

repo: cvxgrp/cvxpy


text:
module requests not found

The Datasets functionality is partially dependent on the requests package through torchvision.datasets. However, torchvision doesn't consider that to be essential functionality, so requests is not an explicit dependency. This leads users who create a minimal environment, e.g.
conda create -n foo -c conda-forge pymde

to encounter a ModuleNotFound error when trying an example like
import pymde

mnist = pymde.datasets.MNIST()

Not a huge deal, but if following suit with torchvision and not including requests as an explicit dependency, it might be nice to give users a heads up in the documentation.

Thanks for reporting! I've created a PR that includes requests as a dependency. The MNIST example should work out of the box.

authors: akshayka mfansler

repo: cvxgrp/pymde


text:
Multi-line key mapping breaks formatting when using #If directives

Minimal reproduction. Uncomment ; Breaks formatting sections and save to see the issue in action.
Example:
#IfWinActive Notepad
    ; Breaks formatting
    ; $^1::
    ;     Foo := 1
    ;     Bar()
    ; return

    ; Breaks formatting
    ; $^`::
    ;     Foo := 1
    ;     if Foo {
    ;         Bar()
    ;     } else {
    ;         Fizz()
    ;     }
    ; return

    Bar() {
        return
    }

    Fizz(){
        return
    }

Thanks feedback, update to version 2.4.16 to fix.

authors: cweijan hammypants

repo: cweijan/vscode-autohotkey


text:
[BUG]插件支持在浏览器中使用https访问么

OS:
Extension Version:
1.我们将该插件安装在eclipse thiea的web程序中，在chorme浏览器中访问
2.通过localhost:3000可以正常打开浏览pdf，docx等相关文件
3.通过本机ip如192.168.1.120:3000访问，无法打开pdf,docx等相关文件
4.初步判断webview只能在secure contexts (i.e. HTTPS)下运行
5.为程序增加了openssl证书使其通过https访问
6.通过chrome浏览器仍然无法打开pdf,docx相关文件
7.vsocde网页版本也存在相同问题

code-server 使用 自带插件的市场的这个插件 是能正常打开pdf文件的
不过打开时间可能比较长, 可能会发生错误导致打开不了pdf, 也可能我打开的pdf比较大 (几百M)
初步怀疑是网络的问题, 由于某些原因我有时候会直连打开, 有时候会使用中转服务器
直连的时候基本上都能打开, 中转的话有时候打开就会发生错误

repo: cweijan/vscode-office


text:
大佬能不能提供一个下载不会闪退的交我办的渠道，近来下载的交我办又开始闪退

描述错误
对错误的描述。
复现步骤
重现行为的步骤：

转到“...”
点击“...”
滚动到“...”
出现错误

期望行为
对您期望发生的事情的描述。
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附加内容
在这里添加关于问题的任何其他上下文。

你选择下载较低版本安卓就行了，低版本安卓兼容性好一点

我用的就是最新版，好像没闪退过

authors: Fully-ripe-mangoes cwlm hhhddd1


text:
bug: needle doesn't have a proper anchor point when translateNeedleY is greater than needleHeight negatively

Describe the bug
If translateNeedleY greater than needleHeight in negatively, the anchor point moves for some reason.
Example:
needleHeight={40}
translateNeedleY={-50}
To Reproduce
Steps to reproduce the behavior:

set needleHeight={40}
set translateNeedleY={-50}

Expected behavior
The anchor to remain in the same spot as usual.
Smartphone

Device: IPhone 12
OS: iOS
Version: 15.2.1

fixed: cwnicoletti@8ac89876ae64a727275b1ffaf3a304c8d705d397

repo: cwnicoletti/react-native-gauge


text:
PR#3350: Update interpolated-strings.md

Mock user PR on conceptual documents, see https://github.com/dotnet/docs/pull/3350/files

:warning: Validation status: warnings

File
Status
Preview URL
Details

docs/csharp/language-reference/keywords/interpolated-strings.md
:warning:Warning

Details

docs/csharp/language-reference/keywords/interpolated-strings.md

Line 53: [Warning] Invalid file link:(~/docs/csharp/language-reference/keywords/strings.md).

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

:warning: Validation status: warnings

File
Status
Preview URL
Details

docs/csharp/language-reference/keywords/interpolated-strings.md
:warning:Warning

Details

docs/csharp/quick-starts/hello-world.yml
:warning:Warning

Details

docs/csharp/language-reference/keywords/interpolated-strings.md

Line 53: [Warning] Invalid file link:(~/docs/csharp/language-reference/keywords/strings.md).

docs/csharp/quick-starts/hello-world.yml

[Warning] 7 invalid cross reference(s) "<xref:System.String.Trim%2A>", "<xref:System.String.TrimStart%2A>", "<xref:System.String.TrimEnd%2A>", "<xref:System.String.Replace%2A>", "<xref:System.String.Contains%2A>", "<xref:System.String.StartsWith%2A>", "<xref:System.String.EndsWith%2A>".
[Warning] the value Tutorial is undefined for metadata pagetype

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

authors: herohua jsntcy

repo: cy-org/conceptual-core-docs