The game is about a courier travelling through levels and collecting parcels.

How do you play your game?
You can play the game by moving using WASD.

Code
Check off the items that are true.

[x] The game was made using the Sprig editor.
[x] The game is placed in the in the /games directory.
[x] The code is significantly different from all other games in the Sprig gallery (except for games labeled "demo").
[x] The game runs without errors.
[x] The name of the file/game contains only alphanumeric characters, -s, or _s.
[x] The game name is not the same as the others from gallery

Image (If an image is used)

[ ] The image is in the /games/img directory.
[ ] The name of the image matches the name of your file.

Thanks for your PR!

Really nice game! I love how satisfying the sound is, and the pixel art is clean :)
Thanks for your submission!
If you're a teen, you can get your Sprig here! sprig-order.hackclub.dev
Hack Clubbers would love to see this! Just post a link and 1-2 sentences talking about your game to our #ship channel ;)


docs: main README.md docker and other staff fixes

Standards checklist:

[ ] The PR title is descriptive.
[ ] The PR doesn't replicate another PR which is already open.
[ ] The PR has self-explained commits history.

[ ] The code is mine or it's from somewhere with an Apache-2.0 compatible license.
[ ] The code is efficient, to the best of my ability, and does not waste computer resources.
[ ] The code is stable and I have tested it myself, to the best of my abilities.
[ ] If the code introduces new classes, methods, I provide a valid use case for all of them.

Changes:

[...]

Other comments:
...

@HiHat  btw, it would be awesome if you could completely remove tbz related stuff because you were right - we are no longer providing tbz snapshots. At this point the PR will be completely solid.

@HiHat btw, it would be awesome if you could completely remove tbz related stuff because you were right - we are no longer providing tbz snapshots. At this point the PR will be completely solid.

Done!


⚠ Bofrost.es has degraded performance

In e44d46a, Bofrost.es (https://www.bofrost.es) experienced degraded performance:

HTTP code: 200
Response time: 1437 ms

Resolved: Bofrost.es performance has improved in 11025db after 27 minutes.


[WIP] fix(DataTable): add background color to selected table row

Closes IBM/carbon-components-react#1304
Right now the TableRow component has no access to whether or not it is selected, so it would be up to the user to pass in the selected prop, which would toggle the Carbon CSS class. I'm not sure if this is the approach we want to take, but I would like some feedback on this implementation. After the approach has been decided I can edit the remaining storybook examples to reflect it
Changelog
Changed

pass selected prop into <TableRow>
toggle CSS class for table row background color on selection

This implementation makes sense to me. Could you update the stories to show this behavior?

sure @tw15egan. One question about getRowProps though, is there a reason why it is only used for the expandable table rows and not for the default table row stories? Rather than <TableRow key={row.id} selected={row.isSelected}> we could just use <TableRow {...getRowProps({ row })> like the <TableExpandRow>

I'm not too sure, @joshblack might know why


:robot: Add psnotify.vm

Automated PR from https://github.com/mandiant/VM-Packages/issues/344 :rocket:

@emtuls what is the state of this PR? I understand from you last comment that this PR is not ready to merge:

this does currently break the shortcut and bin file that are created.

@emtuls please do not merge PRs without a review. This automatically makes packages available in myget.


some bugfixes for my machine

I've reviewed your changes and adusted the theme accordingly.
New configuration options allow you to choose which widgets to use and disable the desktop widget.
Check out the README for details.
I hope this helps you to bootstrap the theme on your machine.
Have fun :)


Remove Cron Password from DC Template

Cron password should be moved to a GH Secret.
https://github.com/bcgov/moodle/blob/c6080553fe495a6efdb1f4910a89acfdb2ebe20a/openshift/app/moodle-dc-persistent-template-new.json#L187

I've added the GH Secret, passed it to the workflow template (dev, test, prod), and added it to the Moodle DC template. Getting a deployment error again:  error: #36 is already in progress (Pending).


name of server in configuration can't contain blank/Chinese character

🐛 Bug Report

Name of server in configuration can't contain blank, or a error output will display when save.
To Reproduce
Steps to reproduce the behavior:
    "abapfs.remote": {

        "TEST 100": { "Contain blank here
            "url": "http://s4dev01.****.com:8000/",
            "username": "****",
            "password": "****",
            "client": "100",
            "language": "EN",
            "allowSelfSigned": false,
            "sapGui": {
                "server": "***.***.***.***",
                "systemNumber": "00"
            }
        }

output:
Message: Request vscabap.readConfig failed with message: Cannot destructure property 'sapGui' of 't' as it is undefined.
Code: -32603

Expected behavior

Link to repo (highly encouraged)

Debug log:

# content of ts-jest.log :

envinfo
System:
    OS:

Npm packages:
    jest:
    ts-jest:
    typescript:
    babel(optional):

Hi, would you please provide a repo for this issue. Looking at the information you provided above, it is impossible for us to debug the issue.

Hi, would you please provide a repo for this issue. Looking at the information you provided above, it is impossible for us to debug the issue.

Sorry, I seem to have sent it wrong.Sorry for that.


v5 on  nvcr.io/nvidia/tensorflow:20.12-tf1-py3  build bert for tensorflow error

Description
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertOp.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h: In member function ‘fastertransformer::Tensor BaseOp<T>::convert_tensor(tensorflow::Tensor)’:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayer.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert/Bert.h:23,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertOp.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertOp.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayer.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert/Bert.h:23,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertOp.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertOp.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:44: error: template argument 2 is invalid
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                            ^
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:53: error: expected initializer before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                                     ^~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:52: error: expected ‘)’ before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |            ~                                       ^~~
      |                                                    )
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertINT8Op.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h: In member function ‘fastertransformer::Tensor BaseOp<T>::convert_tensor(tensorflow::Tensor)’:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayerINT8.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertLayerINT8.h:24,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertINT8.h:19,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertINT8Op.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertINT8Op.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayerINT8.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertLayerINT8.h:24,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertINT8.h:19,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertINT8Op.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/BertINT8Op.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:44: error: template argument 2 is invalid
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                            ^
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:53: error: expected initializer before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                                     ^~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:52: error: expected ‘)’ before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |            ~                                       ^~~
      |                                                    )
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/encoder/EncoderOp.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h: In member function ‘fastertransformer::Tensor BaseOp<T>::convert_tensor(tensorflow::Tensor)’:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayer.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert/Bert.h:23,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/encoder/EncoderOp.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/encoder/EncoderOp.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayer.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert/Bert.h:23,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/encoder/EncoderOp.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/encoder/EncoderOp.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:44: error: template argument 2 is invalid
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                            ^
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:53: error: expected initializer before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                                     ^~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:52: error: expected ‘)’ before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |            ~                                       ^~~
      |                                                    )
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/weight_quantize_op.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h: In member function ‘fastertransformer::Tensor BaseOp<T>::convert_tensor(tensorflow::Tensor)’:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayerINT8.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertLayerINT8.h:24,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertINT8.h:19,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/weight_quantize_op.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/weight_quantize_op.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: error: ‘bfloat16’ is not a member of ‘Eigen’
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                    ^~~~~~~~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:36: note: suggested alternatives:
In file included from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/numeric_types.h:27,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/allocator.h:26,
                 from /usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/framework/op_kernel.h:25,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/utils/allocator.h:29,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/BaseLayer.h:22,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/layers/FfnLayerINT8.h:21,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertLayerINT8.h:24,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/models/bert_int8/BertINT8.h:19,
                 from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/weight_quantize_op.cc:17:
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
   45 | struct bfloat16 {
      |        ^~~~~~~~
/usr/local/lib/python3.8/dist-packages/tensorflow_core/include/tensorflow/core/lib/bfloat16/bfloat16.h:45:8: note:   ‘tensorflow::bfloat16’
In file included from /data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/bert/weight_quantize_op.cc:18:
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:44: error: template argument 2 is invalid
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                            ^
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:53: error: expected initializer before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |                                                     ^~
/data/mt/hbl/FasterTransformer_v5_tf/src/fastertransformer/tf_op/BaseOp.h:105:52: error: expected ‘)’ before ‘==’ token
  105 |         if (std::is_same<T, Eigen::bfloat16>::value == true) {
      |            ~                                       ^~~
      |                                                    )

Reproduced Steps
1、
nvidia-docker run -ti --rm nvcr.io/nvidia/tensorflow:20.12-tf1-py3 bash
git clone https://github.com/NVIDIA/FasterTransformer.git
mkdir -p FasterTransformer/build
cd FasterTransformer/build
git submodule init && git submodule update

2、
1）build c++
cmake -DSM=xx -DCMAKE_BUILD_TYPE=Release ..
make

2）build with tensorflow
cmake -DSM=xx -DCMAKE_BUILD_TYPE=Release -DBUILD_TF=ON -DTF_PATH=/usr/local/lib/python3.8/dist-packages/tensorflow_core/ ..
make   #　error

Hi, huifengshiwu. bfloat16 only supports on newer tensorflow docker image.
If you want to run on bfloat16, you can try newer docker image like 22.04.
If you don't need the bfloat16 feature, you can remove the macro adding at line.

Hi, huifengshiwu. bfloat16 only supports on newer tensorflow docker image.
If you want to run on bfloat16, you can try newer docker image like 22.04.
If you don't need the bfloat16 feature, you can remove the macro adding at line.

thanks a lot


Add logging for program cache

We need to log a message when the device is opened saying that program cache is disabled.  '
Additionally, for both device perf and the operation_history_csv we need an extra column indicating whether program cache was used.

Logging for program cache was added. The user will be notified when it's enabled/disabled. And also the user can log the program hash of each operation


csv based ingestion question

Hi folks,
I've a POC where I'm ingesting based on csv format. The issue I'm facing is, if the data / payload has the comma as part of the data, the ingestion is getting messed up because column to value mapping is getting confused.
For eg: My row is as below
timestamp,a,b,c,<IP_ADDRESS>,<IP_ADDRESS>,hello,world
But actually ,<IP_ADDRESS>,<IP_ADDRESS> is part of single column.
So what is the way to ingest in such cases where delimiter is part of the row (data) itself?
timestamp,a,b,c,"<IP_ADDRESS>,<IP_ADDRESS>",hello,world
Will this work by enclosing the column that has the comma within double quotes?  Atleast that is what I see in the https://druid.apache.org/docs/latest/ingestion/data-formats.html but wanted to confirm  from the experts here.
Also, I know json will definitely solve this since every row will have key-value, but
over the wire (OTW) kafka data will be very large due to the overhead.
Regards.

This is related to https://github.com/apache/incubator-druid/issues/6850. I believe https://github.com/apache/incubator-druid/pull/8803 should allow you to configure the CSV parser to allow commas within the quotes.

Thanks. But is my understanding right to enclose within double quotes? How do I have to make sure if the "comma" part of legit column data?

When 0.17 is released, this should be supported. Not sure about 0.16
though. Did you try using commas like
timestamp,a,b,c,"<IP_ADDRESS>,<IP_ADDRESS>",hello,world and failed?
On Fri, Nov 15, 2019 at 3:05 PM abk<EMAIL_ADDRESS>wrote:

Thanks. But is my understanding right to enclose within double quotes? How
do I have to make sure if the "comma" part of legit column data?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/apache/incubator-druid/issues/8877?email_source=notifications&email_token=AAPSYCVXDBX3IU577TDWUP3QT4TMNA5CNFSM4JOBSK5KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEEG7PZA#issuecomment-554563556,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AAPSYCTJMKXE5CEGA7VCBRDQT4TMNANCNFSM4JOBSK5A
.

--
Jad Naous
Imply | VP R&D
650-521-3425
<EMAIL_ADDRESS>

Did you consider using tsv instead of csv?
That is the data is "tab" separated and use ; to separate between the IPs.
For example:
"ioConfig": {
      "type": "index_parallel",
      "inputFormat" :  {
        "type": "tsv",
        "delimiter": "\t",
        "listDelimiter": ";",
        "columns": [
          ...
        ],
      ...
    }


How could we add swipe down to close function?

Hi,
I love the way this module: https://github.com/maxs15/react-native-modalbox implemented swipe down to close. How could we add this function to our module?
Thanks!

Hey!
That's an interesting feature I already considered in the past.
From my point of you it should be already possible implementing it by applying the panhandlers on the view that you nest in the modal.
The main drawback in this approach is that you won't be able to gradually fade the backdrop while dragging the modal (like in react-native-modalbox).
I/We can also try handling the swipe directly from this modal and exposing some configuration props: It would need a re-work of react-native-modal internals, but if this feature is requested enough it would probably be worth a shot trying.

Hi mmazzarolo,
Thank you for your great module. I think many people would like to have this feature.
Hope that some one can help.

I would love to have this feature. Apart from that, everything is perfect.

+1 for this feature. please

Is someone working on this issue? I want to contribute

Hey @joao-alberto, as far as I know nobody is working on it, and currently I don't have time to actively develop this feature.
If you're interested in tackling it I'll gladly help you though 👍


DOC: Cleanup developer documentation

At the PyData NYC sprints, we are following the instructions to create a development environment for SciPy and we are finding some orphan pages, incomplete procedures, or dead-ends. I'm dumping here some notes with the idea of sending a follow-up pull request to cleanup things a bit.

https://docs.scipy.org/doc/ contains a link to the "Scipy developer guide" pointing to https://docs.scipy.org/doc/scipy-dev/reference/dev/, which then redirects to http://scipy.github.io/devdocs/dev/. But from any of the version-specific docs like https://docs.scipy.org/doc/scipy-1.9.3/, one can go to an outdated version of the dev docs, like https://docs.scipy.org/doc/scipy-1.9.3/dev/index.html. Wondering if it's worth having pointers to all these old dev instructions, or whether we could replace them all with the dev version (also using HTTPS in the URL).

After the CoC and the "Ways to Contribute", the important sections of the dev docs are Contributor quickstart guide, Development workflow, and SciPy contributor guide.

The first line of the quickstart says

After getting the source code from GitHub, there are three steps to start contributing:

First, the https://scipy.github.io/devdocs/dev/gitwash/development_setup.html page is not in any toctree, so the left navigation bar appears empty, even if it's not marked as :orphan:. But most importantly, even though this is the only page describing how to setup GitHub and make a fork, the git clone instructions are outdated (they don't include the git submodule update --init). Should we update that page and make it the entry point for cloning the repository?

Still in the quickstart, there are a couple of pointers to the system-level dependencies. This page does not appear in any toctree either, although this one is marked as :orphan:, so I'm not sure if those are up to date or still recommended. In addition, this page contains pointers to things like https://scipy.github.io/devdocs/dev/contributor/osx.html, which according to @rgommers "should be removed". I'm wondering what other pages there should be removed too?
In the Development workflow, it's said

This guide assumes that you have created your own fork (copy) of the SciPy repository, cloned the repository on your own machine, and built SciPy from this source code. If you haven’t, check the Development environment pages appropriate to your system.

But none of the pages there (System-level dependencies, conda_guide, ubuntu_guide, quickstart_docker, quickstart_gitpod) actually explain how to fork & clone the repository. Maybe we should point to the gitwash/development_setup page mentioned above?
And there are other things I'm observing, but probably starting with these and deciding which pages to move/remove would be a good starting point.
This is essentially a continuation of the issue I opened a couple of years ago https://github.com/scipy/scipy/issues/12633 which @melissawm already addressed in https://github.com/scipy/scipy/pull/15947.

The old scripts instead of dev.py are also still mentioned in:

The docs contributor guide
Testing guide


Feature Request : Provide multiple terminal choices within same instance of VSC

VSCode Version: NA
OS Version: NA

Steps to Reproduce: NA
Per this link, Integrated Terminal in the docs , you can create multiple instances of the terminal and even change it from CMD to BASH to PowerShell.
Can VScode provide options have multiple terminals choice.  1: CMD, 2: BASH, 3: PowerShell within the same instance of VSC?

Stackoverflow question - http://stackoverflow.com/questions/42032232/vscode-multiple-terminals-configuration-issue

From duplicate I created https://github.com/Microsoft/vscode/issues/20057

Perhaps the + icon could open a quick pick or popup which presented:

cmd
powershell
bash for windows
git bash

These could be configured using some settings behind the scenes which knows about the paths to these since they will almost always be in the same spot. The setting could look something like this:
"...shells": {
  "cmd": "%windir%\\sysnative\\cmd.exe",
  "PowerShell": "windir%\\sysnative\\WindowsPowerShell\\v1.0\\powershell.exe",
  "Bash on Windows": "%windir%\\sysnative\\bash.exe",
  "Git Bash": "%programfiles^\\Git\\bin\\bash.exe" // if it exists
}

Note that we don't want to run into the same issues as commandsToSkipShell https://github.com/Microsoft/vscode/issues/19770 if we create such a setting.

I have nothing special against PowerShell but I found the sounds it emitted when hitting backspace a little bit annoying. I realize it is probably not that difficult to disable them (actually it requires creating and editing a profile, through a series of commands, so I wouldn't say it is "super-easy"), but instead I quickly switched to the good-old cmd. Probably because cmd already does all I need and doesn't require me to learn anything new.
I guess there would be many people who would choose do the same, so making the switch easily accessible would be convenient. Also, having bash readily accessible might prove useful for Windows users as well, especially to run specialized scripts.

There is a (hacky) workaround until this feature becomes official:
http://ammonsonline.com/vscode-multiple-integrated-terminals/
I'm currently using ConEmu for multiple terminals, but would like to see this built into VSC natively.

@ryansully in most cases you should simply be able to launch the shell from the other one (run "powershell" in cmd), bash.exe may be an exception though as it has some special properties.

I just published an extension that covers this use case, enjoy :smiley: https://marketplace.visualstudio.com/items?itemName=Tyriar.shell-launcher


Two minor fixes to the inventory-2 file documentation

The global facts resided in group2 and are thus not found when
referencing group1.

aliases cannot be declared in group level, so it's probably
features that are intended.

What group you "reference" should not have any impact on what facts are used. All data from all groups is collected separate from turning a group name into a list of targets. This is the behavior I replicate if I return the facts from a plan.
Since the operatingsystem fact is only set in one place it should always be picked up for mytarget.

I'm don't get it. The sample query is bolt inventory show -t group1 --detail. Will that query show facts declared in group2?

It should there appears to be a bug.
The "targetting" part of that is intended only to decide which targets should be included in the result not where they get facts from. This is the same behavior as the targetting options for the actual bolt actions.

CLA signed by all contributors.

I still don't get it. Why have a hierarchy if the things you query in a specific branch of that hierarchy sees everything declared in all branches? It just doesn't make any sense to me.

The inventory file is meant to express to Bolt the things that are true of a target (what the SSH port is, which password to use, etc). Bolt considers those things to always be true regardless of how you ask for the target. If you sometimes want to connect to a node over SSH and sometimes want to connect over WinRM, then to Bolt those are two different targets and you would sometimes choose one and sometimes choose the other.
The hierarchy exists so you can model the way that you think about your infrastructure so that you can have non-overlapping properties declared in separate parts of the hierarchy. For instance, I might have a linux_nodes group that lists target foo.example.com (among others) and sets the transport to SSH. But I might have that same target also in a separate webapp1 group that sets some facts. No matter whether I target linux_nodes or webapp1, it will still be the case that I connect to foo.example.com over SSH and the facts I've declared are still true.

Aha, so I guess that when overlapping facts are used, the inventory will give priority to the chosen group? If the answer to that is yes, then using a non-overlapping strategy will fail if a decision is ever made based on the presence/absence of a property (a property that is present in one group and absent in another will be perceived as always present). Is it safe to assume that this never happens with features, vars, or facts?

The behavior is that the bottom left-most node in the tree wins. So child groups override their parents and groups that are specified earlier in the file override groups at the same hierarchy level specified later in the file. The final values will be the same no matter which group is being targeted. The first step is that the entire inventory is loaded and resolved, and then the targets you asked for are pulled out. So the targeting process has no effect on the contents of the inventory.
In normal use, conflicts between groups at the same level of the hierarchy shouldn't happen much. If you're trying to tell Bolt something meaningful, then there aren't many real world cases where you would meaningfully have conflicting values.

I'm trying to understand the exact semantics so that I can use this properly. Their degree of meaningfulness is not my concern right now. This is my current understanding:

A conflict will occur if the same property is declared in more than one group irrespective of on what level either of the groups are in the hierarchy.
If a property is defined in some group in the file, then there is no way for another group to say that this property is absent.

Is that correct?

@adreyer if targets in group1 sees all facts declared in group2, them presumably targets in group2 sees all facts in group1, then why doesn't both targets have the operatingsystem: CentOS fact in your query result?

Yes those statements are both correct.

@thallgren mytarget is in both groups so it gets facts from both groups. myothertarget is only in group1 so it does not pick up facts from group 2.

In that case, neither of the two statements that I made above are correct. There will be no override if two adjacent groups declare the same property with different values (unless they also declare the same target), and one group may have properties absent that another group has declared as present .
Another confusion is that in the example, there are two target declarations with the same name. Shouldn't one of the groups just a target reference (string target in name for) to the other target? Or would that change the semantics so that only properties from the group where the target is declared would be picked up by the reference? What happens if the two targets have different uri's?

To answer my own questions here:
If the uri of mytarget in group2 has a different uri than a target with the same name in group1, then the uri from group2 silently overrides the declaration in group1.
If group2 doesn't declare mytarget but instead just references it, the target declaration still picks up facts from group2.
The reason I ask a lot of questions and want clarifications is that we're considering using the inventory as the format for a federated inventory service spanning multiple PE-installations. There are a couple of things in the current design that prevents this:

A group / target name must be globally unique within the file (and all other groups and targets brought in by plugins).
We need names to be unique within the group where they are declared only (more like a file system). This will require that a group can be uniquely identified using a qualified key.
The same target can be declared in many places.
We need to reference the same target from multiple groups, but it must be declared just once. Furthermore, the declaration would only inherit properties where it is declared (from group and parent groups). Never from groups where it is referenced.
A target declares its own aliases.
We would need an option to declare aliases in groups where a target is referenced (to avoid name conflicts in that group). E.g. "in this particular group I want target x to be named y". Not very different from symbolic links.

I think this is a valuable conversation because I believe there is a disconnect in how we think about inventory after reading the docs and how you're thinking about it. I'm not sure a PR is the best place for that conversation and now that I know why you're looking at this I suspect what you're talking about doesn't align well with the general conversations we've been having about federation. I think we should set up some time to talk about this in person.
I will say that people are successfully using the inventory file format to federate across pe instances. This works naturally if you can rely on certnames being unique. If not you need to enforce a naming scheme that that separates the certname in a pe instance from the ID(name in inventory) used to refer to the target at the federated later.
There is however a neede fix in this PR regarding aliases at the group level. do you want to remove the rest of this PR or should we just put up a new one?

PR updated. I moved the facts to top-level since the documentation states that "CentOS" is a "top-level fact".

I think "top level" is the typo since the next paragraph uses that example to show that the facts associated with the node are not based on the group context from the target.

superceded by #1606


Add simple benchmarking

Starting a function name with 'bench_' will now also store it and make
clar run it, but only when invoked with the '-b' flag.
In order to reduce how much clar overhead we measure, we put the timing
code around the function call, which means we end up timing every
function, but we only store the elapsed time in benchmark mode. The
overhead from calling the timer is minimal, so it shouldn't present an
issue to add these calls for every test.
This is not meant for micro-benchmarks, but for situations where we
expect the operations to take at least tens or hundreds of milliseconds
and we expect the operations not to be easily mapped into the "repeat N
times" method to suss out the noise, so we don't include this
functionality. This is for "perform very expensive operation" to track
high-scale changes though time.
Thus we also provide cl_reset_timer() to allow the function under test
to perform specific setup steps that it does not want to count towards
the timing.

This is the simplest thing I could come up with which would be useful for us to test libgit2 performance over time, without going into microbenchmarking, but for the "merge thousand-entry trees" situation. The output is machine-readable, so we can keep historical records in some system. /cc @ethomson
The thing with global_is_bench is ugly but we're now in two different modes, so the number of tests in each case is different, and it seemed less terrible than looking into _clar from the outside, or searching for clar flags in main.c.

So my thought here is that this is generally useful - and clar shouldn't know the difference between a "benchmark" and a "test".  It should just run things and time them.  If some consumer wants to use clar to run both benchmarks and tests, then I think that there are a couple of options:

The consumer could build two clars - one with tests and one with benchmarks.
The consumer could build a single clar and use naming to sort this out itself.

I think we can avoid having two different clars built by passing in a benchmark flag; that shouldn't be too bad. There's a few reasons I chose bench_ over just timing whatever we would be running. One of them is the discoverability of the tests which we think of as benchmarks. As I've mentioned I don't think most tests would tell us much if we see a change in their runtime, so for detecting regressions in core areas, you would have to know which specific tests are informative. If we let clar know beforehand, it can just say.
We can certainly solve this by putting all the benchmarks as test_bench_ tests so we can run ./libgit2_clar -b -sbench, but this moves the bench code away from the test code for a particular suite, whereas with bench_ we can have the index code next to similar index testing code, instead of in a parallel tree.
But it's not that big a deal at the end of the day. Having benchmarks be normal tests does mean they get tested the same as the rest even when we're not benchmarking.

Sorry for the long delay - this looks like what I had in mind!  This seems to be missing the clar/time.h though.

I did notice it was missing earlier, but completely forgot to add it the second time around as well :/ It's there now.

I really like this.  My only feedback is that I might like to see the benchmark reports printed at the end of the entire execution, instead of the end of an execution for each suite.  eg:
Benchmark blame::buffer::delete_crosses_hunk_boundary 0.000000
Benchmark blame::buffer::replace_line 0.000000
Benchmark blame::buffer::add_lines_at_end 0.000000
..
Benchmark blame::getters::byindex 0.000000
Benchmark blame::getters::byline 0.000000
....
Benchmark blame::harder::m 0.000000
Benchmark blame::harder::c 0.000000
Benchmark blame::harder::cc 0.000000
Benchmark blame::harder::ccc 0.000000

Seems a little weird for output (weirder still with -v, which is usually the way I run).

Yeah, that makes sense.

@ethomson I finally got around to finishing this up; the timing results are now shown at the end of a multi-suite run.


cannot import name const

im getting this error when I try to execute it
root@kaliRoman:/media/root/46DD-8D02/Windows/programs/botnet/Loki-master# python loki.py
Traceback (most recent call last):
File "loki.py", line 9, in
from lib.server.server import Server
File "/media/root/46DD-8D02/Windows/programs/botnet/Loki-master/lib/server/server.py", line 8, in
from lib import const
ImportError: cannot import name const
root@kaliRoman:/media/root/46DD-8D02/Windows/programs/botnet/Loki-master# python2 loki.py
Traceback (most recent call last):
File "loki.py", line 9, in
from lib.server.server import Server
File "/media/root/46DD-8D02/Windows/programs/botnet/Loki-master/lib/server/server.py", line 8, in
from lib import const
ImportError: cannot import name const
root@kaliRoman:/media/root/46DD-8D02/Windows/programs/botnet/Loki-master# python3 loki.py
Traceback (most recent call last):
File "loki.py", line 10, in
from flask import Flask, render_template, request, session, jsonify, redirect, url_for
ModuleNotFoundError: No module named 'flask'
I've tried python, python2 and python3 didn't work
I've got python 2.7
(I've pasted everything that's written)
thx for helping....

Use pip3 install flask in terminal.


I used the uniswapV2 project in my project, but I encountered compilation problems, what should I do?

Component
Forge
Have you ensured that all of these are up to date?

[X] Foundry
[X] Foundryup

What version of Foundry are you on?
forge 0.2.0 (226affb 2022-09-27T07:51:19.423801Z)
What command(s) is the bug in?
forge build
Operating System
macOS (Apple Silicon)
Describe the bug
I used the uniswapV2 project in my project, but I encountered compilation problems, what should I do?

You need to use solc versions from the uniswap tests in the contracts you are writing .. and not 0.8.15.  i,.e 0.6.6. You might be able to overcome this by using interfaces as opposed to the periphery contracts , which would allow you to use a more recent version

You need to use solc versions from the uniswap tests in the contracts you are writing .. and not 0.8.15. i,.e 0.6.6. You might be able to overcome this by using interfaces as opposed to the periphery contracts , which would allow you to use a more recent version

Thanks for your reply, but the current project may need to use a newer solidity version. In the test script, I want to deploy uniswap to test the interaction function with the existing project. This requirement can be realized in the hardhat framework, and the compilation requirement is realized for the solidity version of different source files. Does foundry have similar configurations and functions?

@zh19910202 you can either provide a fork url to run tests against an already deployed contract on mainnet or you can use getCode cheatcode to deploy the code manually. see book reference

@zh19910202 you can leave any further questions on this thread if u encounter any problems in the process


[Suggestion] Add Save and Load Config Confirmation Box

I occasionally Click Save and load incorrectly, resulting in the loss of the configuration called out

+1


Update namings in sql files

The file name will also be done next,  from "waterflow_statistic.sql" to "streamdischarge_statistic.sql"

I have a second commit that includes the changes within the Java files ... I thought to push it afterwards, but I can do it now (on the same branch). shall I?


Onboarding

It is not clear what to do on first launch, and based on writing the "Getting Started" page on the Wiki, perhaps on first launch, we should have a workflow, like this:

Welcome to SwiftTerm, we are going to help you get setup
First, let us create a host name, give it a name, and tell me how I can reach out to it
If there are special configuration options like a port, please enter it
Tell me what login do you want to use
Do you want to use a password, or an SSH key to login?
If you choose an SSH key, please paste the private key here.
Testing that your connection works.

I have a simple page that describes what to do now, without the wizard, I think the wizard is repetitive and does not add a lot of value.


Add event listener to buttons and display data

Add event listener to buttons and display data
On this branch I:

Create a logic folder and copy all required files into it.
Add an evenListner to all button components.
Create function to handle the click event.
Display the Result on the screen.

Hi @Nemwel-Boniface, thanks for the feedback.


Add initial code (and figure out using the issue tracker)

Add initial code from internal repository to github.

master branch checked out into a fresh directory, and the test.py script run. This ran as expected, as did the documentation. The github migration appears to have worked.


synthetic vessel graph numger of edges changing with different networkx configs

Hi, I used the synthetic vessel graph and depending on before and after I convert it to networkx graph and whether it is set to_undirected=True, the number of edges change:
This is the vessel graph as PyG dataset:
link_dataset = LinkVesselGraph(root='./data/',
                          name="synthetic_graph_3")

Then when I print the PyG dataset number of edges:
data = link_dataset[0]
print(f'Dataset: {link_dataset}:')
print('======================')
print(f'Number of graphs: {len(link_dataset)}')
print(f'Number of features: {link_dataset.num_features}')
print(f'Number of nodes: {data.num_nodes}')
print(f'Number of edges: {data.num_edges}')

"""
Dataset: LinkVesselGraph():
======================
Number of graphs: 1
Number of features: 5
Number of nodes: 3128
Number of edges: 6388
"""

The number of edges is 6388 vs when I convert it to networkx:

#nodes, #edges =  3128 5112
#nodes, #edges =  3128 2556

Why is the number of edges keep changing?

Hi Kay,
So the number of edges is exactly double when you have a directed vs an undirected graph. This is expected. To understand the functionality of the inbuild PyG function please see: https://pytorch-geometric.readthedocs.io/en/latest/modules/utils.html?highlight=networkx#torch_geometric.utils.to_networkx

Hi @FeynmanDNA,
thank you very much for this question. The conventions are indeed a bit tricky and require some further explanation.
The pyg convention for link prediction tasks is to keep all training edges in data.edge_index. However, this also implies that if we convert the link dataset graph to networkx (using the pyg function), only the training edges will be present in the resulting networkx graph. I tried to clarify this by extending the test_link_graph.py script, and printing the dimensions, please see 4e14ed6.
Does this clarify it? Looking forward to your feedback!
Cheers, Julian

Hi i think you comments in the code are very helpful! :)


How can I save an audio file using the long audio generation technique provided in your notebooks?

def tts(script):
model = preload_models()
nltk.download('punkt')
sentences = nltk.sent_tokenize(script)
silence = np.zeros(int(0.25 * SAMPLE_RATE))
pieces = []
for sentence in sentences:
audio_array = generate_audio(sentence)
pieces += [audio_array, silence.copy()]
with open("audio_file.wav", "wb") as file:
file.write(np.concatenate(pieces))
This is my current code and it saves the file but is unreadable and cannot be played. It says it is because of the .wav format but I don't know what else to save it as

def tts(script): model = preload_models() nltk.download('punkt') sentences = nltk.sent_tokenize(script) silence = np.zeros(int(0.25 * SAMPLE_RATE)) pieces = [] for sentence in sentences: audio_array = generate_audio(sentence) pieces += [audio_array, silence.copy()] with open("audio_file.wav", "wb") as file: file.write(np.concatenate(pieces))
This is my current code and it saves the file but is unreadable and cannot be played. It says it is because of the .wav format but I don't know what else to save it as

Hello there,
add these lines to your code and it'll start working hope this helps you.
genAudio = Audio(np.concatenate(pieces), rate=SAMPLE_RATE)
with open("audio_file.wav", "wb") as file:
  file.write(genAudio.data)

The following code will save the audia as - fileName.wav.
from scipy.io.wavfile import write as write_wav write_wav("fileName.wav", SAMPLE_RATE, np.concatenate(pieces))


checkstyle: allow missing javadoc for private methods

This can be done using the suppressions.xml file.

@fzdy1914

This can be done using the suppressions.xml file.

What do you mean?

The goal of this PR can be done by adding a new section in here suppressions.xml

@fzdy1914

I thought the pr is to allow missing javadoc for private methods only in tests.

Yes, I'm thinking of removing the check entirely for all private methods, since I think it's more trouble than it's worth. I still haven't decided on whether I should go forward with it or not though.
Seems like RepoSense has the same rule enabled, although it seems like it only causes a warning, not an error. (As opposed to AB-4 where it is an error.) Maybe you could try adding javadocs to all private methods in the code base and see if its worth it or not ;-)

@fzdy1914 shall we merge this?

@damithc Instead of removing the whole inspection, I am referring to set the severity to a warning first. What's your opinion on the javadoc of the private methods issue?

@damithc Instead of removing the whole inspection, I am referring to set the severity to a warning first. What's your opinion on the javadoc of the private methods issue?

The downside of that is we end up with a bunch of warning that are always there; over time, we stop reading the warnings at all (because we expect them to be there anyway) which increases the risk of missing other unrelated warnings.
If we remove it entirely, we can still expect reviewers to ask for javadoc comments for non-trivial private methods. So, I don't mind removing it altogether.

@damithc  That's true, let's get this remove.


Request for new release to PyPi(0.29.8)

Hi @scoder , I am not sure if you have other changes in the pipeline, but would like to see to be able to use #2930 in our project.
Thanks!

Specifically #2930 is currently scheduled for 3.0, not for a point release. I considered it too risky to change something like this in a point release.

Thats fair. Thanks!
Out of curiosity, what kind of timeframe do you expect for a 3.0?

Whenever it's ready, but definitely this year.
See the blockers in the "Cython 3.0" milestone: https://github.com/cython/cython/milestone/58
Any help with them is appreciated and will speed this up.

I am just starting out with cython and am fairly green in that regard. Do you have any recommendations for issues to pick up? Any of the good-first-issue?

Yeah, pretty much any of those. Also, #2864 is a fairly big one where we still need to investigate why several of the tests fail. Help in that direction would be appreciated.
I'll close this ticket, though, because it's not something to discuss on the bug tracker.


QueryFn does not recall when Query Variables is updated!

This is my first try on react-query, not sure if my implementation is correct, any help would be appreciated!
When I click the button and call handleLoadMore(), offset is updated but the queryFn does not recall and so that the data does not update.
Below is the screenshot of my code and query cached data on ReactQueryDevtools
A little note that: ReactQueryDevtools also has a bug that it will crash my page when I click to query detail.

Seem like I found the problem, config.initialData is the problem that makes the query does not re-fetch when offset changed.
FYI, I'm using SSR and initialData is the data I fetched from server. May I know what is the correct way to use config.initialData on react-query?

Yeah, looks like a bug
Here's a minimal example: https://codesandbox.io/s/infallible-shape-ofysh?file=/src/App.js

Actually, maybe that's because you shouldn't pass initialData after query variables change?
I mean, if you have initial data for page 1, you shouldn't use them as initial data of page 2, right?

Something like this: https://codesandbox.io/s/nameless-platform-5dyhj?file=/src/App.js

@cherniavskii ahh I see, thank you!
So is this the correct way to use config.initialData? IMO, I think it is better to have config.initialData affected when mounted only

Hi is there any news for this?

If you change the queryKey, initialData will act the same. If there is no data present in the cache for the query, the initial data you pass (if any) will be used. This is remaining the same in 2.0 as well.

What shall we do if we just have initial data for certain queries but want to perform a fetch when query change?

The query should refetch on mount even if initial data is set.

Hmm I see, so the efficient way to use initialData is:
const { data = initData, status } = useQuery(key, QueryFn)
right?

Nor sure what you mean by efficient, but sure, that works. The difference is that by setting the initialData option itself the cache will be populated with that data. By destructuring with a default value like you are doing here does not set the cache data.

Thank you!


Codegen results in unknown directive errors

How did you install the Amplify CLI?
npm install -g @aws-amplify/cli
If applicable, what version of Node.js are you using?
16.18.1
Amplify CLI Version
11.0.3
What operating system are you using?
macOS 12.6.3
Did you make any manual changes to the cloud resources managed by Amplify? Please describe the changes made.
No manual changes made
Describe the bug
When running amplify codegen instead of the API resources being updated, every directive in my schema.graphql file throws an unknown directive error.
Unknown directive "@auth".

Unknown directive "@model".

Unknown directive "@primaryKey".

Unknown directive "@hasOne".

Unknown directive "@hasOne".

Unknown directive "@index".

Unknown directive "@index".

Unknown directive "@index".

Unknown directive "@index".

Unknown directive "@index".

Shortened version of schema.graphql
type Course
@auth(
    rules: [...]
)
@model {
	 ### Primary Key ###
        id: ID! @primaryKey

	### Relationships ###
	instructorId: ID
	instructor: Instructor @hasOne(fields: ["instructorId"])
	termId: ID
	term: Term @hasOne(fields: ["termId"])

	### Fields ###
	...
}
type Instructor
@auth(
    rules: [...]
)
@model {
	 ### Primary Key ###
         id: ID! @primaryKey

	### Relationships ###

	### Fields ###
	name: String
	createdAt: AWSDateTime!
}

type Student
@auth(
    rules: [...]
)
@model {
	 ### Primary Key ###
         id: ID! @primaryKey

	### Relationships ###

	### Fields ###
	....

}

type Term
@auth(
    rules: [...]
)
@model {
	 ### Primary Key ###
          id: ID! @primaryKey

	### Relationships ###

	### Fields ###
	name: String
	createdAt: AWSDateTime!
}

type System
@auth(
    rules: [...]
)
@model {
	 ### Primary Key ###
          id: ID! @primaryKey

}

Expected behavior
The graphQL mutations, queries, and subscriptions should be updated.
Reproduction steps

Define types in schema.graphql
Run amplify push
Run amplify codegen

Project Identifier
9a30524f890ae5aefd05c13a75fddb8b
Log output

# Put your logs below this line
2023-04-07T19:43:29.629Z|info : amplify codegen codegen
2023-04-07T19:43:29.678Z|info : amplify-cli-core.banner-message/index.ts.fetch banner messages from https://aws-amplify.github.io/amplify-cli/banner-message.json({}
2023-04-07T19:45:31.408Z|info : amplify codegen codegen
2023-04-07T19:45:31.452Z|info : amplify-cli-core.banner-message/index.ts.fetch banner messages from https://aws-amplify.github.io/amplify-cli/banner-message.json({}
2023-04-07T19:48:41.185Z|info : amplify codegen codegen
2023-04-07T19:48:41.233Z|info : amplify-cli-core.banner-message/index.ts.fetch banner messages from https://aws-amplify.github.io/amplify-cli/banner-message.json({}
2023-04-07T19:57:01.844Z|info : amplify status core  {"yes":false}
2023-04-07T19:57:01.891Z|info : amplify-cli-core.banner-message/index.ts.fetch banner messages from https://aws-amplify.github.io/amplify-cli/banner-message.json({}
2023-04-07T19:57:02.856Z|info : amplify-provider-awscloudformation.display-helpful-urls.showCognitoSandBoxMessage(["courseregistrationpo9c2b2a89"])
2023-04-07T20:25:44.374Z|info : amplify codegen codegen
2023-04-07T20:25:44.416Z|info : amplify-cli-core.banner-message/index.ts.fetch banner messages from https://aws-amplify.github.io/amplify-cli/banner-message.json({}
2023-04-07T20:28:30.398Z|info : amplify version core  {"version":true,"yes":false}
2023-04-07T20:33:47.502Z|info : amplify diagnose core  {"send-report":true,"yes":false}
2023-04-07T20:33:47.550Z|info : amplify-cli-core.banner-message/index.ts.fetch banner messages from https://aws-amplify.github.io/amplify-cli/banner-message.json({}

Additional information
amplify codegen is producing the expected results in my other Amplify projects but this project is having an issue.
Before submitting, please confirm:

[X] I have done my best to include a minimal, self-contained set of instructions for consistently reproducing the issue.
[X] I have removed any sensitive information from my code snippets and submission.

Hey @akaiser443 👋, Thanks for raising this. By following the steps you mentioned and using the schema provided in the ticket, was able to successfully execute the amplify codegen command.
Can you confirm you followed the identical steps as mentioned below?
Steps :

amplify init at the root of the project folder.
amplify add api.
Chose GraphQL with a blank schema and incorporated the provided schema.
Pushed the changes to the Amplify backend using amplify push.
Executed the amplify codegen command.

@akaiser443 I would recommend checking your graphqlconfig.yml file for any redundant projects. You may have to remove any that are unrelated to the project you're currently working on.

@akaiser443 can you check if you've accidentally defined your schema inside the build folder i.e amplify/api/<api_name>/build/schema.graphql instead of defining in amplify/api/<api_name>/schema.graphql file.
The Codegen plugin reads from the compiled schema from the build folder that is auto-generated when you run amplify api gql-compile or amplify push. And that compiled schema in the build folder does not contain any of these directives like hasMany, hasOne etc.

The issue was that in .graphqlconfig.yml the schemaPath was pointing to the wrong file.  It was pointing to amplify/api/<api_name>/schema.graphql instead of amplify/api/<api_name>/build/schema.graphql.


Adding statement about internal use

https://github.com/MicrosoftDocs/office-docs-powershell/issues/5191

Docs Build status updates of commit 612acd4:
:clock10: Full build: the average full build time is 12 min(s) 36 sec(s), this is based on the last 1000 build(s) for this repository.


Fixing handling of conditions in if-statements

Fixes https://github.com/microsoft/qsharp-compiler/issues/1018.

/azp run


Job: #9110 Add implementation note with evaluation data

The requested changes have been made

The new procedure is being run (and thus tested) by Lee. I am waiting for feedback from this test to promote this work.


[ob] Make destination test script and automatic test script

Make simple destination test script and automatic test script.

Delayed too much.
Open it again later..


Support latest MNE-BIDS changes (BIDSPath)

Don't include transition of ICA code; will be handled in GH-163

Merge provided CIs are happy


How to test after training??

The training was completed by the nuScenes mini dataset and was acquired up to checkpoint.
But then I don't know how to run this model by another dataset.
Can you tell me how to do this?

Can you tell me the configuration version of the environment you trained?


[Chore] Add a executable permission to the scripts

Purpose of the pull request
Add a executable permission to the scripts.
Brief change log

Verify this pull request

This pull request is code cleanup without any test coverage.
(or)
This pull request is already covered by existing tests, such as (please describe tests).
(or)
This change added tests and can be verified as follows:

(or)
Pull Request Notice
Pull Request Notice
If your pull request contain incompatible change, you should also add it to docs/docs/en/guide/upgrede/incompatible.md

This PR is not a chore. Please follow the pull request notice. Closing for now.


Allow binary relocation

Checklist

[ ] Used a personal fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

https://github.com/conda-forge/ctng-compilers-feedstock/search?q=patchelf - both the build for libgcc and libgfortan do their own patching (at apparently the need of other folks needing a working rpath)


Update docs for 0.9.0

Docs build on fork: https://taylorfturner.github.io/DataProfiler/docs/0.9.0/html/index.html

I have looked at the security check related to tornado-6.2-cp37-abi3- but when I install requirements.txt on gh-pages it does in fact install 6.3.2 when I look at pip list | grep -i tornado


Harmonize table styles

this PR makes a small number of changes to table displays so that they're more consistent.

uses align-middle so that table cell contents are always vertically centered
replaces text-left and text-right with BS5 text-start and text-end so that text is correctly aligned
tries to better align a few table headers with their content
makes buttons inside table rows all .btn-sm so they impact layout less and are consistent

@thatbudakguy would you say this addresses #426 ?

oh I hadn't even seen that issue. yes, probably? I'll confirm (and maybe check on the commas thing)

ok, can confirm this closes #426.


Bumped timeout from 4000 to 20000 ms as it seems a more reasonable

@RocketChat/android

Bumped timeout for rpc calls from 4000 to 20000 millis as it seems a more reasonable threshold.
Also updating a sending message sync state to SyncState.SYNCED at Realm in case a sending message is successfully sent.
This sync status update fix is related to issue #268

Thanks @leonardoaramaki! LGTM, can you review the code @matheusjardimb, please?


Refactor barcode

Refactor BarcodeWidget to be a special instance of IntentWidget. Refactor IntentWidget to allow this. Allow BarcodeWidget to have appearance attribute "editable" that makes the barcode result editable.

@charlesfleche this should allow what you wanted in https://github.com/dimagi/commcare-odk/pull/162 via making the appearance attribute "editable"

Seems pretty neat, thanks Will. How does it translate in term of User Interface ? Is the barcode value display automatically editable or does an option need to be checked somewhere ?
Many, many thanks for taking a look at this.

No problem! You'll need to add the appearance attribute "editable" to the
question in order to make it an EditText instead of a TextView
On Thu, May 14, 2015 at 12:40 AM, Charles Flèche<EMAIL_ADDRESS>wrote:

Seems pretty neat, thanks Will. How does it translate in term of User
Interface ? Is the barcode value display automatically editable or does an
option need to be checked somewhere ?
Many, many thanks for taking a look at this.
—
Reply to this email directly or view it on GitHub
https://github.com/dimagi/commcare-odk/pull/283#issuecomment-101906955.

This is really, really cool Will. Is the change live already ?

Not yet - I'd anticipate it being released in 2.22.
On Thu, May 14, 2015 at 9:05 AM, Charles Flèche<EMAIL_ADDRESS>wrote:

This is really, really cool Will. Is the change live already ?
—
Reply to this email directly or view it on GitHub
https://github.com/dimagi/commcare-odk/pull/283#issuecomment-102029723.

Done reviewing; please address at least my first comment.
Also, when your PRs include commits from other PRs, please make note of it. This PR includes commits from https://github.com/dimagi/commcare-odk/pull/258

@phillipm updated


metrics values don't match between custom metric function and model.fit callbacks

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Google Colab
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): Google Colab default installed
TensorFlow version (use command below): 2.4.1
Python version: 3.7.10
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version:
GPU model and memory:

Describe the current behavior
returned metrics value from custom metrics functions and callback printed metrics from model.fit doesn't match.
Describe the expected behavior
returned metrics value from custom metrics functions and callback printed metrics from model.fit match.
Standalone code to reproduce the issue
Google Colab gist
Other info / logs
I opened a quesiton on stackoverflow.
https://stackoverflow.com/questions/66311611/when-and-how-keras-calculate-metrics-for-each-batch-of-samples

Hey @asterisk37n
I tried giving your script a run, modifying a little bit
history = model.fit(x=x, y=y, batch_size=2, epochs=1, verbose=2)

Here I want to output only one line for each epoch and not the progress bar, hence verbose=2
Upon doing this, I do in fact get results that are aligned with the history.history
My guesses are to dive deep into the output of model.fit and check whether the progress bar messes up with the results that we see. Hope this helps 😄

Hi all. Here are the issues describing the same problem: #46713 #47099. Hope this helps.

@asterisk37n,
On running the Colab notebook you have linked, I see that the loss and my_metric_fn values are identical. Please find the gist of it here. Thanks!

@amahendrakar
Thank you for running. I'm referring to a different thing. In my log, you can see 0.1429. Where has this come from?
2/2 [==============================] - 0s 7ms/step - loss: 0.1429 - my_metric_fn: 0.1429

my_metric_fn's value for the second batch? No, it is 0.0450076237.
Average of my_metric_fn among the first and second batch? No, it is (0.191785976 +  0.0450076237)/2 = 0.11839679985.

@ariG23498 Thanks for verbose param info.
@evgeniya-egupova  Thank you. yeah, very similar to https://github.com/tensorflow/tensorflow/issues/47099

Could that be a running average with some exp decay parameter? i.e. not a simple average.
Might be linked to https://github.com/tensorflow/tensorflow/issues/39448

related issue https://github.com/tensorflow/tensorflow/issues/47099 has been closed, could you check if the present issue is solved too on the new commit by @rchao?

@ricvo very likely so. If you find that the original issue is still not fixed after using a nightly build (that has the fix), please comment. Thanks!

@asterisk37n As mentioned by @rchao and @ricvo, this was resolved with recent tf-nightly. Please check the gist here.
Old output (with TF2.4.1)
2.4.1
TensorShape([2, 1]) TensorShape([2, 1]) [0.216433451 0.167138502] 0.191785976
1/2 [==============>...............] - ETA: 0s - loss: 0.1918 - my_metric_fn: 0.1918
TensorShape([2, 1]) TensorShape([2, 1]) [0.0477369316 0.0422783121] 0.0450076237
2/2 [==============================] - 0s 12ms/step - loss: 0.1429 - my_metric_fn: 0.1429
{'loss': [0.1183968037366867], 'my_metric_fn': [0.1183968037366867]}

New output (with tf-nightly)
Epoch TensorShape([2, 1]) TensorShape([2, 1]) [0.216433451 0.167138502] 0.191785976
1/2 [==============>...............] - ETA: 0s - loss: 0.1918 - my_metric_fn: 0.1918
Epoch TensorShape([2, 1]) TensorShape([2, 1]) [0.0477369316 0.0422783121] 0.0450076237
2/2 [==============================] - 0s 15ms/step - loss: 0.1184 - my_metric_fn: 0.1184
{'loss': [0.1183968037366867], 'my_metric_fn': [0.1183968037366867]}

Please verify once and close the issue. Thanks!

@jvishnuvardhan Thank you. I checked your gist and it works perfectly as expected! Thank you for contribution.

Thanks for confirming. Closing the issue as this was resolved.


support particles during attacks

these particles should active when an attack is active

Added a component called Attack Particles. It requires a prefab with particle system. Trigger it from one of the general events in any of the attacks.


Train event task not able to converge

I trained the event task but found out the model is not able to converge. Do I need some extra settings/parameters to produce an acceptable result? Thanks.

The code for tasks not discussed in the paper (i.e., anything except ball_traj and player_traj) is experimental and simply included to serve as a starting point for other researchers.


By default it works for ngClick, but how to bind to ngSubmit? Any idea?

Angular-Confirm plugin works like a charm for button with ngClick as expected. Is there a straightforward way to apply the same for ngSubmit?
For Example:

Default : <button ng-click="clear()" confirm="Are you sure?">Cancel</button>
Form Submission:

<form ng-submit="mySubFunc:">
     <button type="submit" confirm="Are you sure?">Save</button>
</form>

Here, for 1) Default confirm pop up will work as expected since it has ngClick(when clicked OK).
But for 2) Form submission, although confirm dialog will popup, on click of OK, it will not submit form but just close the confirm dialog, is there a way to submit form on click of OK.
I need it urgently, any quick update is much appreciated. Thanks.

It's possible to submit forms without pressing the button (e.g. by cmd/ctrl+enter in input field) so you shouldn't rely only confirming on that button's click.
Instead, inside mySubFunc you should confirm programmatically. At least Angular1 version offered programmatic API, I don't know about Angular2+ version.
Here's v1 way:
// Ask for confirmation
$confirm({
  title: 'Are you sure?',
  text: 'Huh?',
  ok: 'Continue',
  cancel: 'Cancel'
})
.then(function() {
  // Do something if user pressed "continue
});

@simison Thanks for your input.
I just made below 2 changes and it looks good with some testing. Since it's resolved am closing this issue.
<!--<form name="editForm" ng-submit="vm.saveForm()">--><!---ng-submit was removed since button click takes care-->
<form name="editForm" >
.
.
.
<!--<button type="submit"...> --><!-- type changed to button and ngclick added-->
<button type="button" ng-click="vm.saveForm()"...>


Vulkan: VoxelGI bake fails for very small volumes in only one or two axes

Godot version
v4.0.alpha.custom_build [72407a9cf], v4.0.alpha5.official [d7d528c15]
System information
Windows 10 (Version 10.0.19044), Vulkan, NVIDIA GTX 960 (512.15)
Issue description
When trying to bake a very small VoxelGI volume it fails with the following error messages:
Width must be equal or greater than 1 for all textures
drivers/vulkan/rendering_device_vulkan.cpp:3191 - Condition "!src_tex" is true. Returning: ERR_INVALID_PARAMETER
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:2253 - Condition "!src_texture" is true. Returning: RID()
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Image (binding: 5) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
Texture (binding: 9) should provide one ID referencing a texture (IDs provided: 0).
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline
drivers/vulkan/rendering_device_vulkan.cpp:7979 - Condition "!uniform_set" is true.
Uniforms were never supplied for set (0) at the time of drawing, which are required by the pipeline

This issue appears only when one or two axes are small. Specifically, it seems to be a problem when the volume cannot hold at least one voxel. Uniformly small VoxelGI Volumes seem to work as intended.

Maybe each axis should be clamped to be at least as big as one voxel.
Steps to reproduce
In a scene create VoxelGI Node and set its extent in one or two axes to something small like 0.001. One of the other axes of the Volume must be disproportionately bigger for example 10. Try and bake the VoxelGI Volume via the "Bake VoxelGI" button. It should fail.
Minimal reproduction project
test_giprobe_roughness.zip

+1 to clamping to at least one voxel's size


Keploy Integration - Added sample Java application using JWT Token

Pull Request Template
Description
Hi me (@jaiakash) and @amitpanwar789 have worked on the sample Java application with JWT token creation and verification. This sample helps to use the Keploy to test in JAVA.
Fixes keploy/keploy#2016
Type of change
Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[x] This change requires a documentation update

Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[x] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes
[x] Any dependent changes have been merged and published in downstream modules
[x] I have checked my code and corrected any misspellings
[x] I have tagged the reviewers in a comment below incase my pull request is ready for a review
[x] I have signed the commit message to agree to Developer Certificate of Origin (DCO) (to certify that you wrote or otherwise have the right to submit your contribution to the project.) by adding "--signoff" to my git commit command.

Please review @Swpn0neel @charankamarapu

I have tried running the application without keploy. On the second request which is mentioned in the README is giving me this error

It is better to keep the token in header than request body (a standard practice).

Hi @charankamarapu Thanks for your suggestion. Have updated the PR to have token in header instead of body.
Also as I can see from screenshots, end point is users/tokenVerification not users/verify

Hi @yaten2302, did you check it?

Apologies for the delay, @jaiakash. I've DM you on Slack.

Hi @PranshuSrivastava @Sonichigo @charankamarapu, I am incredibly sorry for the delay.
Have updated the PR. Can you please suggest what changes are required in this readme file or maybe the overall project?
Thanks
cc @yaten2302


pip error while training model on cloud

The replica master 0 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-9_013O-build/setup.py' The replica worker 0 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-QNtwDr-build/setup.py' The replica worker 1 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-pA8eBo-build/setup.py' The replica worker 2 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-Xk5nGm-build/setup.py' The replica worker 3 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-3VkzR6-build/setup.py' The replica worker 4 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-NIf2Jb-build/setup.py' The replica worker 5 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-RlyPFQ-build/setup.py' The replica worker 6 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-QXzr7y-build/setup.py' The replica worker 7 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-FvkZhP-build/setup.py' The replica worker 8 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-Ue8_oJ-build/setup.py' The replica ps 0 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-AxLdZ1-build/setup.py' The replica ps 1 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-7nE9PF-build/setup.py' The replica ps 2 exited with a non-zero status of 1. Termination reason: Error. Traceback (most recent call last): File "", line 1, in  IOError: [Errno 2] No such file or directory: '/tmp/pip-GSkkn1-build/setup.py' To find out more about why your job exited please check the logs: https://console.cloud.google.com/logs/viewer?project=802068032926&resource=ml_job%2Fjob_id%2Fhotifya9f40b85_e142_431b_82fc_8be28b5dc8c2&advancedFilter=resource.type%3D"ml_job"
resource.labels.job_id%3D"hotifya9f40b85_e142_431b_82fc_8be28b5dc8c2"

Could you please somebody help me to sort this out. I have already pip even though i am getting same

Could you please make the logs public. Also, does your training work on your local computer?

I apologize but I am having a hard time understanding what the problem is, where the problem is, and what version it affects. Please resubmit and pay attention to the issue template (https://github.com/tensorflow/tensorflow/issues/new) . Please provide all the information it asks. Thank you.


Barometric pressure values are reported incorrectly

Looks like there's an issue with the number formatting or something. That's a LOT of pressure!

Ok not a bug. This is because the new sensors were created using system default measurement, and I had to click on them and change the display unit to inHg.


¿Animated GIF support?

Hello, I was wondering to know if it is possible to get and save an animated GIF, since when I try:
Image::make('mygif.gif')->save('images/mygif.gif);
It will become a "static" image, losing the animation.
Thanks in advance

A great suggestion. At the moment I'm just copying the resource, but it'll be great to be able to crop an animated gif.

As I understand this feature is already present in development branch.
(I've forked repo and merged master into development and checked this functionality in laravel app I'm currently working on)
@olivervogel can you comment on when you plan to release it.
I see tag nextversion on this issue but not sure what it exactly means.

The development branch represents what will be the next major version (3.x). But it is currently under development and I would not use the branch for anything than development at all. Tag nextversion means that this feature will be available in the next major version.
Currently there is no release date. This is a free open source project and I'm working on it in my spare time.

@olivervogel thanks for clarification

What is the current status here?

make sure to use strtolower() on getClientOriginalExtension() as some images may have different casing on file extensions.

https://github.com/glukash/glu-image

system("convert big.gif -coalesce coalesce.gif");
system("convert -size 200x100 coalesce.gif -resize 200x10 small.gif");

Keep GIF animation for Imagick:
$im = new \Imagick('path/to;image');

if ($format == 'GIF') {
    $im = $im->coalesceImages();

    do {
        $im->resizeImage($resize['width'], $resize['height'], \Imagick::FILTER_BOX, 1);
    } while ($im->nextImage());

    $im = $im->deconstructImages();
} else {
    $im->resizeImage($resize['width'], $resize['height'], \Imagick::FILTER_LANCZOS, 1, true);
}

$im->writeImages('some/path/to', true)

For GD check animation:
function is_animated($filename)
    $filecontents = file_get_contents($filename);

    $str_loc = 0;
    $count = 0;
    while ($count < 2) { // There is no point in continuing after we find a 2nd frame

        $where1 = strpos($filecontents, "\x00\x21\xF9\x04", $str_loc);
        if (!$where1) {
            break;
        } else {
            $str_loc = $where1 + 1;
            $where2 = strpos($filecontents, "\x00\x2C", $str_loc);
            if (!$where2) {
                break;
            } else {
                if ($where1 + 8 == $where2) {
                    ++$count;
                }
                $str_loc = $where2 + 1;
            }
        }
    }

    return $count > 1;
}

Any News?

Any update for animated GIFs,?

Still gif images are not supported

Perhaps make a pull request to help them out, if this is so important?

Up

Yeah i'm in too.

The code a pasted above is not usefull?

Thanks, it's usefull!

I have a full class that supports GIFs for working with the GD library. I can post it as a Gist if you like.

Image GD class that supports manipulating GIFs: https://gist.github.com/odahcam/e7255f406e02ddf390080bf3add2cd43#file-imagegd-php-L4

Any update on this? :)

Thanks @marcoflorian

I am interested in this one as well.  I see only the first frame is captured on resize, so for now will just copy GIF resources.

Simply curious does anyone know how to make Intervention just completely ignore modifications  to gifs completely? For example I have stored animated gifs (these are unaltered and just stay as files served to end users) and just simply using Intervention as a means to fix the content types /mime types for Internet Explorer. Without Intervention they show as text/gif vs the proper image/gif to display in IE. Seems like when end clients load the gifs Intervention is improperly modifying the gifs and only showing a static first frame of the gif even though it shouldn't be modifying it in any way.

@olivervogel, I know this is ancient, but are you still able to link to the development code that was referenced above? I'm not seeing anything anymore except for a master and a 1.6 branch in this repository. I'm asking because I'd like to potentially expand upon what's already built, if possible (since I need this for something I'm working on and may need to move to intervention/image myself in the future, i.e. SilverStripe v4). So, if we can incorporate this as core functionality (at least with Imagick) I may be interested.
For what it's worth: This is the first time I've looked at intervention/image. However, digging deeper into how this would work in Imagick at least, I think this has probably lagged behind a bit, since working with an animated gif seems to require that you basically iterate over every single frame as it's own separate instance of Imagick (a child of the parent instance) and then and apply the defined transformations repeatedly (e.g. ->resize(), ->resizeCanvas(), ->fit() and etc.) before being merged back together as a single image (i.e. the final encoded blob/file, per the internal API). I'm not sure how this would be accomplished internally within this library, but I could see how that might require yet another layer of abstraction/complexity. For example, maybe one could ensure that if this is an animated gif (e.g. Imagick->count() > 0) you would wrap the execution of commands in an iteration that would be called on a cached result of Imagick->coalesceImages(). I don't know; I haven't actually used this library yet, but I will someday 😄.

Still interested in animated gif support, this package is almost perfect, the lack of gif support does hurt though!

Still interested in animated gif support, this package is almost perfect, the lack of gif support does hurt though!

As previous fella. :)

How is this still not a thing?

Is anybody actively working on this? Has there been any work done on this? Is there a branch that I could pick up? What's stopping it? Complexity and/or lack of developer motivation? Technical hurdles?

We at Forus are also really interested in such a feature.

Any updae?

Any updae?

There will never be an update. Just use ImageMagick

Ooh, I haven't looked for a while, but there are some encouraging signs:

There are tags for3.0.0.alpha{1,2,3} at the start of the year (eg alpha3)
3.0 uses another library whose purpose appears to be decoding/encoding animated gifs.
If you dig into the docs, there is a section about 3.0 alpha: (https://image.intervention.io/v3).

@olivervogel Does this mean it's a good time for some alpha testers?

@totten 3.0.0.alpha4 was released on Packagist this month, and contains explicit links to v3 documentation, so I think it's reasonable to assume that v3 is publicly available in alpha.

Yeah it doesn't work with imagick either, at least not without a workaround, v3.0 will probably contain this feature though.
So it's not never.


Indicator 15.5.1: More informative title needed, and unit probably mis-named

The unit of measurement is "units" which is probably mis-named. Should it be something else like "Number of species"?

Also, the titles are not very informative and could be expanded.

Also, the "units" issue also applies to 15.7.1 and 15.c.1.

The "units" issue also applies to 17.6.1.

This is correct.

Possibly change the English translation to "numbers"?

Check the global metadata.


Updated boto3 dependency.

Reviewed boto3 1.4 upgrade notes and ran through unit tests to ensure no breaking changes affected Scale.

LGTM

Closed #413


Add TypeScript definition

Add TypeScript definition
Run type check when npm test

Ref #56

@SerayaEryn Thanks for your review.
I cleaned up tsconfig.json. Please re-review.

Thanks for your contribution.


raidboss: add basic p10s Jade Passage

add basic p10s Jade Passage trigger
It would be nice if the position of the laser could be displayed like 'stand on lines' or 'stand in box' refer to the pattern of the floor.
but I can't find a way to do it.

Will, I messing up the commit information, I will reopen a new Pull Request


Add support for database status manager

This PR addresses this issue, by adding support for a database status manager.

Could we quickly sometime this week talk about the error handling? As I mentioned in one of the comments, I've been doing it one way, but that's not necessarily the best way. Would really appreciate talking with you about it.

Sure! Let's setup time to talk about this today or tomorrow.

Overridden by #7