EPERM operation not permitted

I started with npx create-next-app@latest (just pressed Enter on all prompts) and then installed nextra, basically following the guide here. After creating and modifying the necessary files, I ran npm run dev and got the following:
 C:\Users\username\Desktop\my-app> npm run dev

><EMAIL_ADDRESS>dev
> next dev

- warn Port 3000 is in use, trying 3001 instead.
- ready started server on <IP_ADDRESS>:3001, url: http://localhost:3001
- warn
> Found a change in next.config.js. Restarting the server to apply the changes...
- info automatically enabled Fast Refresh for 3 custom loaders
- event compiled client and server successfully in 402 ms (20 modules)
- wait compiling...
- warn Port 3000 is in use, trying 3001 instead.
- ready started server on <IP_ADDRESS>:3001, url: http://localhost:3001
- event compiled client and server successfully in 264 ms (20 modules)
- info automatically enabled Fast Refresh for 3 custom loaders
- event compiled client and server successfully in 371 ms (20 modules)
node:events:505
      throw er; // Unhandled 'error' event
      ^

Error: EPERM: operation not permitted, open 'C:\Users\username\Desktop\my-app\.next\trace'
Emitted 'error' event on WriteStream instance at:
    at emitErrorNT (node:internal/streams/destroy:157:8)
    at emitErrorCloseNT (node:internal/streams/destroy:122:3)
    at processTicksAndRejections (node:internal/process/task_queues:83:21) {
  errno: -4048,
  code: 'EPERM',
  syscall: 'open',
  path: 'C:\\Users\\username\\Desktop\\my-app\\.next\\trace'
}

There's this issue on Next.js repo that might help you: Emitted 'error' event on WriteStream instance #30738
You can 1. delete your .next folder and run npm run dev again or 2. stop the nextjs instance thats running on 3000 (the logs say it's being used, lines  6 and 13)

You can 1. delete your .next folder and run npm run dev again or 2. stop the nextjs instance thats running on 3000 (the logs say it's being used, lines 6 and 13)

Deleting the .next folder solves the issue. Thanks!
However, now I get 404 | This page could not be found. even though I have pages/index.mdx containing:
# Welcome to Nextra

Hello, world!

Could you please give more information about reproducing the error? A repo, maybe?

Here's how to reproduce.

npx create-next-app@latest (just pressed Enter on all prompts) and then installed nextra, basically following the guide here
Deleted .next folder
npm run dev
Open localhost:3000 and it shows 404 | This page could not be found

Hi mate, that might sound like a really dumb question, but can you share your next.config.js? Based on your logs on the original message, on lines 7 to 9, the Next.js dev server is apparently running without the correct nextra setup (since its not logging the info automatically enabled Fast Refresh for 3 custom loaders) and then it detects a change on it and runs again.
I was able to reproduce the first problem by changing the next.config.js on the fly to get the same EPERM error, I removed the .next directory and it sucessfully ran the dev environment. I only managed to reproduce your 404 error when I used a next.config.js like before changing them on your logs. Sound trivial, but its a case to check.
If it's still correct, I suggest you to backup your contents and clone the docs template repository, so you can move your contents to a tested environment. Sorry for not being able to help you now :c

Here is my next.config.js
const withNextra = require('nextra')({
  theme: 'nextra-theme-docs',
  themeConfig: './theme.config.tsx'
})

module.exports = withNextra()

closing due no activity, feel free to ask to reopen if issue still persist


Nintendo Switch error.

The shader does not work and crash the game after 1.4.0

that's crazy

Hmm my shaders haven't actually supported Switch, but it would be nice if it worked of course. Right now I don't have a copy of Minecraft for Switch so I can't test it there.


#PickhardtPayments: Optimize route construction

Instead of the basic Dijkstra approach, it could be better to create routes that profite as much entropy as possible. If the flow information contains a very improbable edge, it might be a better idea to split this into several (at this edge: parallel) flows so that failures provide more helpful information about the network. @RenePickhardt may have some ideas of how this could be done.

As discussed I have unfortunately nothing concrete that I can say. I would try discect the flow in a way that the expected information gain of the sent onions is maximzied. (similarly how the optimization goal could already be changed in flow computation). The new optimization goal seems computationally much harder to me which is why I hope it would at least work on the resulting flow graph as that is usally much much smaller than the lightning network


Refactored output parameter.

Refactored TrackingPidLocalPlanner::computeVelocityCommands() to use a return value instead of an output parameter.
The function never read from the output parameter (it was pure output and not in-/output), and the results were one of the following:

false and the output parameter was not set
true and the output parameter was set

This maps perfectly to std::optional. Either the function is successful and it returns the velocity command or it is not successful and it does not return a velocity command.

I'm a bit puzzled. I created what I think was a very innocuous PR which is in-line with a best practice which is widely supported within the C++ community.
Yet, for such a small change, I get quite a bit of pushback from both @Rayman and @Timple . So I was hoping you two would explain to me what you don't like about this. So I can perhaps address your concerns or refrain from these kind of changes in the future.
Is it the principle of no output parameters itself, the usage of std::optional, something else?

PR comments often sound a bit harsh as good stuff is rarely complemented :slightly_smiling_face: . I actually liked to learn about the std::optional.
My comment was that you are refactoring a function which doesn't describe it's actual use. But these kind of comments can simply be split-off to issues and the PR can continue: https://github.com/nobleo/path_tracking_pid/issues/120

So I was hoping you two would explain to me what you don't like about this.

I think we were hoping and suggesting some bigger changes to the error handling that are needed, while you made a small improvement to existing code. I sometimes use a review to comment on code that surrounds the block of code because that's the first time I'm really looking at it. I shouldn't do that and focus more on the current review.


Enhance errmsg for misssing roi

Testing solution for the centrosome issue, corrections in cellprofiler not propagated to the package yet.

I'm indifferent about this change, but would be cautious of releasing CellProfiler development versions as a stable release to the public. Up to you :)

@jwindhager, agreed, I am not intending to release a version with this change. This is just to make the merges to the main pass so I can work on the feature branches. Once everything is ready for the release, we will reevaluate the situation, the issue with cellprofiler would hopefully be fixed by then.


regenerate crates from specs

Ref: https://github.com/Azure/azure-rest-api-specs/commit/def187e2e78d7173d8fdd7f77740dd9719e1dfbf

Note for review: The first commit has the autorust.toml changes required to address the latest issues.  The second commit has the regenerated crates.


manifest.json without digest

We run a fork of broccoli-asset-rev so that we can avoid fingerprinting the generated manifest.json file. I was going to open a PR with this change but from reading the repo history noticed this is how it originally worked and that broccoli-asset-rev was later updated to support what Heroku expects.
https://devcenter.heroku.com/articles/rails-asset-pipeline#compiling-assets-locally seems to suggest that both manifest.json and manifest-<hash>.json should be supported but I assume this is not the case based on the original commit. We don't deploy to Heroku so I can't verify without some testing.
Our use case is a little different. We generate the manifest file so that other applications in our ecosystem can parse it and generate fingerprinted links to assets in the ember app. Having a fixed filename for the manifest makes sense for this case. Additionally, the manifest is never served publicly or cached so having it fingerprinted is of no value from that perspective.
If this seems like a reasonable use case to support, could I open a PR to support conditionally enabling/disabling fingerprinting the manifest file?

Could using the exclude property solve this?

I don't beliefe having it in the exclude list gets picked up. Perhaps that should be the fix...

Yea, I think that would be the preferable solution.

Ok no problem. PR incoming

I'm going to close this for now since a PR is currently open.


feature: add file data type to document

Describe the PR
add data type:  file
Relation issue
None
Additional context
For a http request, if we use multipart/form-data as content-type, we can use file as a param.
swag can do this, but this part is missing in the document.

@greenpart @manveru @edevil @akojo could you help review this PR?  Thanks~

@jincheng9 As far as I understand from your description this is not related to any open issues.
I explained a few times the data type you can assign to a request or response should be a valid GO datatype and file is not primitive.

@ubogdan thanks for the reply.  But my concern is without specifying the file data type, people don't know how to upload a file in the online swag document site, as we can choose to upload file in Postman.

Can you be more specific please?


startAdornment will create React warning

Duplicates

[X] I have searched the existing issues

Latest version

[X] I have tested the latest version

Current behavior 😯
First of all, I want to say thank you for this great project. It really simplifies working with react-form-hook significantly. When using an inputAdornment like this:
<TextFieldElement
  name={'phone'}
  label={'Telefon- oder Handynummer'}
  required
  fullWidth
  InputProps={{
    startAdornment: (
      <InputAdornment position="start">
        <PhoneIcon />
      </InputAdornment>
    )
  }}
/>

It is displayed as expected, however the Browser (Firefox in this case) does show a warning:
Warning: React does not recognize the `startAdornment` prop on a DOM element. If you intentionally want it to appear in the DOM as a custom attribute, spell it as lowercase `startadornment` instead. If you accidentally passed it from a parent component, remove it from the DOM element.
input
withEmotionCache/<@webpack-internal:///./node_modules/@emotion/react/dist/emotion-element-c39617d8.browser.esm.js:60:66
div
withEmotionCache/<@webpack-internal:///./node_modules/@emotion/react/dist/emotion-element-c39617d8.browser.esm.js:60:66
InputBase@webpack-internal:///./node_modules/@mui/material/InputBase/InputBase.js:242:83
OutlinedInput@webpack-internal:///./node_modules/@mui/material/OutlinedInput/OutlinedInput.js:139:82
div
withEmotionCache/<@webpack-internal:///./node_modules/@emotion/react/dist/emotion-element-c39617d8.browser.esm.js:60:66
FormControl@webpack-internal:///./node_modules/@mui/material/FormControl/FormControl.js:100:82
withEmotionCache/<@webpack-internal:///./node_modules/@emotion/react/dist/emotion-element-c39617d8.browser.esm.js:60:66
TextField@webpack-internal:///./node_modules/@mui/material/TextField/TextField.js:96:83
Controller@webpack-internal:///./node_modules/react-hook-form/dist/index.esm.mjs:544:31
H@webpack-internal:///./node_modules/react-hook-form-mui/dist/esm/index.js:42:352
div
withEmotionCache/<@webpack-internal:///./node_modules/@emotion/react/dist/emotion-element-c39617d8.browser.esm.js:60:66
form
FormProvider@webpack-internal:///./node_modules/react-hook-form/dist/index.esm.mjs:180:35
qe@webpack-internal:///./node_modules/react-hook-form-mui/dist/esm/index.js:42:2016
Y@webpack-internal:///./node_modules/react-hook-form-mui/dist/esm/index.js:42:1352
div
D@webpack-internal:///./node_modules/styled-components/dist/styled-components.browser.esm.js:30:23423
div
div
D@webpack-internal:///./node_modules/styled-components/dist/styled-components.browser.esm.js:30:23423
div
Page@webpack-internal:///./components/Page.tsx:49:20
MitgliedsantragPage@webpack-internal:///./pages/mitgliedsantrag.tsx:52:121
Provider@webpack-internal:///./node_modules/unstated-next/dist/unstated-next.mjs:13:17
MitgliedsantragPageWrapper
LocalizationProvider@webpack-internal:///./node_modules/@mui/x-date-pickers/LocalizationProvider/LocalizationProvider.js:33:9
ThemeProvider@webpack-internal:///./node_modules/@mui/private-theming/ThemeProvider/ThemeProvider.js:46:7
ThemeProvider@webpack-internal:///./node_modules/@mui/system/esm/ThemeProvider/ThemeProvider.js:55:7
ThemeProvider@webpack-internal:///./node_modules/@mui/material/styles/ThemeProvider.js:26:9
Provider@webpack-internal:///./node_modules/unstated-next/dist/unstated-next.mjs:13:17
div
D@webpack-internal:///./node_modules/styled-components/dist/styled-components.browser.esm.js:30:23423
Xe@webpack-internal:///./node_modules/styled-components/dist/styled-components.browser.esm.js:30:20195
SessionProvider@webpack-internal:///./node_modules/next-auth/react/index.js:455:18
App@webpack-internal:///./pages/_app.tsx:102:21
PathnameContextProviderAdapter@webpack-internal:///./node_modules/next/dist/shared/lib/router/adapters.js:113:20
ErrorBoundary@webpack-internal:///./node_modules/next/dist/compiled/@next/react-dev-overlay/dist/client.js:306:63
ReactDevOverlay@webpack-internal:///./node_modules/next/dist/compiled/@next/react-dev-overlay/dist/client.js:858:908
Container@webpack-internal:///./node_modules/next/dist/client/index.js:110:27
AppContainer@webpack-internal:///./node_modules/next/dist/client/index.js:252:20
Root@webpack-internal:///./node_modules/next/dist/client/index.js:452:21

I can see its also used like this for the PasswordElement, see here: https://github.com/dohomi/react-hook-form-mui/blob/master/packages/rhf-mui/src/PasswordElement.tsx
Expected behavior 🤔
I would expect it to work without printing a warning message.
Steps to reproduce 🕹
Steps:

Create a TextFieldElement and verify it works without error
Add the InputProps containing a InputAdornment as described above

in my environment it renders without error warnings:
https://react-hook-form-material-ui.vercel.app/?path=/story/textfieldelement--basic


Using guava instead of guava-jdk5 dependency

We now depend on guava-jdk5:13.0. In both google-cloud-java and gax-java we instead depend on standard guava (version 19 and 18 respectively).
Is there any reason for depending on guava-jdk5? If not excluded (as we do in google-cloud-java), this just results in a bunch of duplicated classes in all projects that use standard guava. /cc @anthmgoogle @garrettjonesgoogle

This was fixed with #69

This is still an issue.
1.23.0 depends on guava-jdk5:17.0 and it causes dependency conflicts with dropwizard 1.2.0 which uses the standard guava com.google.guava:guava:23.1-jre
Unfortunately, the method Throwables.throwIfUnchecked(e) doesn't exist in guava-jdk5:17.0 causing failures in tests.
Could you guys please take a look. The Google client library is the recommended way for authenticating with firebase and we don't want to switch to the legacy API because of this problem.
For readers, this will fix the issue if you are using Gradle
compile (group: 'com.google.api-client', name: 'google-api-client', version: '1.23.0') {
  // excludes all guava packages including com.google.guava:guava-jdk5:17.0 which gets pulled in
  exclude group: 'com.google.guava'
}

Same problem here with
    implementation (group: 'com.google.apis', name:'google-api-services-androidpublisher', version:'v2-rev47-1.23.0') {     implementation (group: 'com.google.cloud', name: 'google-cloud-storage', version: '1.12.0')
I had to exclude group: 'com.google.guava' as @suvodeep-pyne mentioned

@suvodeep-pyne Thanks man, It worked


Notetaking app derive from CATS ?

@jbaron and all
I am not sure where is the right place to ask below question, a user forum for CATS?
I am planing a "Hierarchical Notetaking" app similar to Evernote or Notational Velocity, while with WYSIWYG HTML editing, and with file system hierarchy as storage.
I guess I might derive that from CATS, especially for below features

node-webkit
file/folder tree
resizable panel
syntax highlight

Do you think that is a good idea to derive from CATS source code? Or, where would you suggest to start from?
More of my ideas are listed in below page, and also a screenshot to compare CATS v.s. KeepNote (Python, last update 2012)

https://github.com/Eucaly/beZong
https://github.com/Eucaly/beZong/tree/master/pic

@Eucaly

@Eucaly https://github.com/Eucaly, this is indeed the right place for asking questions. I didn’t create a dedicated forum yet,
If your are settled on using Nodewebkit, Qooxdoo and TypeScript, than I would say yes CATS would be a good starting point. At a minimum it would help to understand how to do things like layout and integrating other components (like in your case a WYSIWYG editor etc). But I think you could also reuse a lot of the code.
That said, there is currently not much developers documentation. So you will have to spend some time to go through the source code. But nothing really difficult and most GUI components are defined in its own class and file. Based on some of the patches I got from the community, it seems most people quickly work out how CATS is structured and how to make changes to it.
If you are not comfortable (or want to learn) Nodewebkit, Qooxdoo and TypeScript I think there are also other alternatives. For example you could use plain JavaScript with the UI library of your choice on top of Nodewebkit. For example JQuery UI, Extjs also have similar components (tree, layout).
I also checked out your project, looks interesting. From looking at the the picture, it indeed shows overlap from a UI persepctive. And of course the best thing about reusing some of CATS code would be if you develop the notetaking editor in similar technology, I could easily integrate that in CATS in the future ;) as an added feature.

On 03 Jan 2015, at 11:11, Eucaly<EMAIL_ADDRESS>wrote:
@jbaron https://github.com/jbaron and all
I am not sure where is the right place to ask below question, a user forum for CATS?
I am planing a "Hierarchical Notetaking" app similar to Evernote or Notational Velocity, while with WYSIWYG HTML editing, and with file system hierarchy as storage.
I guess I might derive that from CATS, especially for below features
node-webkit
file/folder tree
resizable panel
syntax highlight
Do you think that is a good idea to derive from CATS source code? Or, where would you suggest to start from?
More of my ideas are listed in below page, and also a screenshot to compare CATS v.s. KeepNote (Python, last update 2012)
https://github.com/Eucaly/beZong https://github.com/Eucaly/beZong
https://github.com/Eucaly/beZong/tree/master/pic https://github.com/Eucaly/beZong/tree/master/pic
@Eucaly https://github.com/Eucaly
—
Reply to this email directly or view it on GitHub https://github.com/jbaron/cats/issues/141.

@jbaron
Thanks for the positive feedback.
I studied some cats source code. But I could not found menu item, such as "Project > Recent Projects". Could you help to identify that in the source ?
I guess there might be some learning curve for me to decide and coding on Qooxdoo and TypeScript.
I will prompt here if I really made some progress.

menubar.ts build the whole top level menu. There is a method per top menu item, in this case createProjectMenu()
Then in there there is call to recentProjects() which create the recent projects items.
When the IDE is started, the items are read from the IDE configuration file and are available to methods like recentProjects.

On 13 Jan 2015, at 10:01, Eucaly<EMAIL_ADDRESS>wrote:
@jbaron https://github.com/jbaron
Thanks for the positive feedback.
I studied some cats source code. But I could not found menu item, such as "Project > Recent Projects". Could you help to identify that in the source ?
I guess there might be some learning curve for me to decide and coding on Qooxdoo and TypeScript.
I will prompt here if I really made some progress.
—
Reply to this email directly or view it on GitHub https://github.com/jbaron/cats/issues/141#issuecomment-69713918.

@jbaron
I found why I cannot locate the source code of recentProjects()
It's because on the releases page [1], latest_unstable (cats-1.3.336.nw) has correct binary, while with incorrect source code .zip (same content as latest_stable 1.2.0)
[1] https://github.com/jbaron/cats/releases
Secondly, after some effort, I almost decide to start forking to my own notetaking application with below configuration:

cats (of course) ^_^
dojo - http://dojotoolkit.org/api/
AMD - Asynchronous Module Definition
typescript

Some status is available as below

initial code - https://github.com/Eucaly/bezongmemo/commit/7d3c8a1992d2eca9a9bf5491772887a38f61c30f
porting progress - https://github.com/Eucaly/bezongmemo/blob/master/bzm-dojo-amd-cats-progress.md
screenshot - https://github.com/Eucaly/beZong/tree/master/pic

Will keep an eye out on your note taking app. Also looked at dojo before and is indeed a nice framework. There are some powerful components in there. And saw some rumours that Dojo2 would be written in TypeScript. If so, that would be a very good argument to go with Dojo. Also still hoping that some day in the future Qooxdoo would be written in TS (would also be an excellent fit).
Regarding the CATS source code, I guess most contributors just use git and get the unstable branch to develop with. The source code zip file is from the main branch and is indeed the stable release that is already some time old. Once the typescript services are bit more stable, will merge the unstable branch back to the main branch.

On 23 Jan 2015, at 17:05, Eucaly<EMAIL_ADDRESS>wrote:
@jbaron https://github.com/jbaron
I found why I cannot locate the source code of recentProjects()
It's because on the releases page [1], latest_unstable (cats-1.3.336.nw) has correct binary, while with incorrect source code .zip (same content as latest_stable 1.2.0)
[1] https://github.com/jbaron/cats/releases https://github.com/jbaron/cats/releases
Secondly, after some effort, I almost decide to start forking to my own notetaking application with below configuration:
cats (of course) ^_^
dojo - http://dojotoolkit.org/api/ http://dojotoolkit.org/api/
AMD - Asynchronous Module Definition
typescript
Some status is available as below
initial code - Eucaly/bezongmemo@7d3c8a1 https://github.com/Eucaly/bezongmemo/commit/7d3c8a1992d2eca9a9bf5491772887a38f61c30f
porting progress - https://github.com/Eucaly/bezongmemo/blob/master/bzm-dojo-amd-cats-progress.md https://github.com/Eucaly/bezongmemo/blob/master/bzm-dojo-amd-cats-progress.md
screenshot - https://github.com/Eucaly/beZong/tree/master/pic https://github.com/Eucaly/beZong/tree/master/pic
—
Reply to this email directly or view it on GitHub https://github.com/jbaron/cats/issues/141#issuecomment-71215750.


Don't require default constructor for C++ temps

Made C++ temps a special type to avoid default constructor
This uses placement new to avoid requiring a default constructor (at the cost of using a little extra space for an "assigned" bool). The pattern is pretty similar to std::optional. This gives a little extra flexibility in terms of the C++ classes that Cython can handle.
(built on top of https://github.com/cython/cython/pull/3792 for simplicity, but needn't require that - it only requires a change to some #if lines)
Longer-term it might be possible to support something similar for regular cdef variables, but it'd probably need some extra syntax since I doubt we'd want to change the default behaviour.

It looks like I was slightly over-optimistic about how well this would work...


Cache gifs

Cache the GIFs that are returned in recent or on search

I can work on this.

@hiteshpr All your my friend! Thank you for offering to help 👍 I look forward to your PR

<EMAIL_ADDRESS>

@joshghent I am new to open source, could you allow me to contribute on this project.

Hi, Is it still open? I would like to contribute.

Hi @joshghent, Is it still open? I would like to contribute.

Of course! I think the project is quite old though so largely needs a lot of love to upgrade it's dependencies. I'd appreciate any support :) Happy to help if you have any issues.


'OverlayState' is nullable

Hey!
I'm trying to use your plugin but I'm getting this error

Hey @marcelogil - I am getting this error, when trying to pull down 1.0.8:
❯ flutter run
Launching lib/main.dart on iPhone SE (3rd generation) in debug mode...
Running Xcode build...
Xcode build done.                                           11.0s
Failed to build iOS app
Error output from Xcode build:
↳
    ** BUILD FAILED **

Xcode's output:
↳
    Writing result bundle at path:
    	/var/folders/40/009bn5px22jgmc6c50vywj7w0000gn/T/flutter_tools.ofz75L/flutter_ios_build_temp_dirnUrJs0/temporary_xcresult_bundle

    /opt/homebrew/Caskroom/flutter/3.3.10/flutter/.pub-cache/hosted/pub.dartlang.org/el_tooltip-1.0.8/lib/el_tooltip.dart:134:26: Error: Method 'insert' cannot be called on 'OverlayState?' because it is potentially null.
     - 'OverlayState' is from 'package:flutter/src/widgets/overlay.dart' ('/opt/homebrew/Caskroom/flutter/3.3.10/flutter/packages/flutter/lib/src/widgets/overlay.dart').
    Try calling using ?. instead.
          overlayStateHidden.insert(_overlayEntryHidden!);
                             ^^^^^^
    /opt/homebrew/Caskroom/flutter/3.3.10/flutter/.pub-cache/hosted/pub.dartlang.org/el_tooltip-1.0.8/lib/el_tooltip.dart:228:20: Error: Method 'insert' cannot be called on 'OverlayState?' because it is potentially null.
     - 'OverlayState' is from 'package:flutter/src/widgets/overlay.dart' ('/opt/homebrew/Caskroom/flutter/3.3.10/flutter/packages/flutter/lib/src/widgets/overlay.dart').
    Try calling using ?. instead.
          overlayState.insert(_overlayEntry!);
                       ^^^^^^
    Failed to package /Users/mf/Projects/project/app.
    Command PhaseScriptExecution failed with a nonzero exit code
    note: Building targets in dependency order
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 9.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'nanopb' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'Amplitude' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 9.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'PromisesObjC' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 8.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'ReachabilitySwift' from project
    'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 8.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'PINOperation' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 8.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'FMDB' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 9.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'AppsFlyerFramework' from project
    'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 9.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'GoogleUtilities' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 8.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'PINCache' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 9.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'GoogleDataTransport' from project
    'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'FirebaseCoreInternal' from project
    'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'FirebaseCore' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'FirebaseInstallations' from project
    'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'SnapSDK' from project 'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'GoogleAppMeasurement' from project
    'Pods')
    /Users/mf/Projects/project/app/ios/Pods/Pods.xcodeproj: warning: The iOS Simulator deployment target 'IPHONEOS_DEPLOYMENT_TARGET' is set to 10.0, but the range of supported deployment target versions is 11.0 to 16.2.99. (in target 'FirebaseAnalytics' from project
    'Pods')
    note: Run script build phase 'Run Script' will be run during every build because the option to run the script phase "Based on dependency analysis" is unchecked. (in target 'Runner' from project 'Runner')
    warning: Run script build phase 'Thin Binary' will be run during every build because it does not specify any outputs. To address this warning, either add output dependencies to the script phase, or configure it to run in every build by unchecking "Based on dependency
    analysis" in the script phase. (in target 'Runner' from project 'Runner')

    Result bundle written to path:
    	/var/folders/40/009bn5px22jgmc6c50vywj7w0000gn/T/flutter_tools.ofz75L/flutter_ios_build_temp_dirnUrJs0/temporary_xcresult_bundle

@marcelogil same issue on 1.0.7 - any workarounds?

@marcelogil I have tried the following:

Flutter clean
Pod install / pod repo update
Reverting back to 1.0.6
Copying environment from the example folder:

environment:
  sdk: ">=2.18.0 <3.0.0"
  flutter: ">=1.17.0"

Unfortunately we can't build still

Sounds nice! Looking forward. Your library seems by far to be the most promising tooltip library for flutter out there.

Hello @simplenotezy
I tried to replicate the issue you had with the latest version, but wasn't able to see the problem.
I've created a repo with a test project.
Can you clone it and see if it works on your computer?
https://github.com/marcelogil/elTooltipTesting
I'm trying to understand if the problem comes from your machine or your your project.
I also added a preview of that project using the same simulator you used:
https://user-images.githubusercontent.com/3277922/217077314-19832819-4bc2-4552-9034-16f1192ed1c4.mov
Thanks in advance
Gil

Aha, I seem to be getting the same error. I do notice, however, that my flutter version can be upgraded.
❯ cd elTooltipTesting
❯ flutter pub get

┌─────────────────────────────────────────────────────────┐
│ A new version of Flutter is available!                  │
│                                                         │
│ To update to the latest version, run "flutter upgrade". │
└─────────────────────────────────────────────────────────┘
Running "flutter pub get" in elTooltipTesting...                 1,072ms
❯ flutter run
Launching lib/main.dart on iPhone SE (3rd generation) in debug mode...
Running Xcode build...
Xcode build done.                                           10.9s
Failed to build iOS app
Error output from Xcode build:
↳
    ** BUILD FAILED **

Xcode's output:
↳
    Writing result bundle at path:
    	/var/folders/40/009bn5px22jgmc6c50vywj7w0000gn/T/flutter_tools.O55LDS/flutter_ios_build_temp_dirn524qx/temporary_xcresult_bundle

    /opt/homebrew/Caskroom/flutter/3.3.10/flutter/.pub-cache/hosted/pub.dartlang.org/el_tooltip-1.0.8/lib/el_tooltip.dart:134:26: Error: Method 'insert' cannot be called on 'OverlayState?' because it is potentially null.
     - 'OverlayState' is from 'package:flutter/src/widgets/overlay.dart' ('/opt/homebrew/Caskroom/flutter/3.3.10/flutter/packages/flutter/lib/src/widgets/overlay.dart').
    Try calling using ?. instead.
          overlayStateHidden.insert(_overlayEntryHidden!);
                             ^^^^^^
    /opt/homebrew/Caskroom/flutter/3.3.10/flutter/.pub-cache/hosted/pub.dartlang.org/el_tooltip-1.0.8/lib/el_tooltip.dart:228:20: Error: Method 'insert' cannot be called on 'OverlayState?' because it is potentially null.
     - 'OverlayState' is from 'package:flutter/src/widgets/overlay.dart' ('/opt/homebrew/Caskroom/flutter/3.3.10/flutter/packages/flutter/lib/src/widgets/overlay.dart').
    Try calling using ?. instead.
          overlayState.insert(_overlayEntry!);
                       ^^^^^^
    Failed to package /Users/mf/Projects/opensource/elTooltipTesting.
    Command PhaseScriptExecution failed with a nonzero exit code
    note: Building targets in dependency order
    note: Run script build phase 'Run Script' will be run during every build because the option to run the script phase "Based on dependency analysis" is unchecked. (in target 'Runner' from project 'Runner')
    note: Run script build phase 'Thin Binary' will be run during every build because the option to run the script phase "Based on dependency analysis" is unchecked. (in target 'Runner' from project 'Runner')

    Result bundle written to path:
    	/var/folders/40/009bn5px22jgmc6c50vywj7w0000gn/T/flutter_tools.O55LDS/flutter_ios_build_temp_dirn524qx/temporary_xcresult_bundle

Could not build the application for the simulator.
Error launching application on iPhone SE (3rd generation).

Flutter dcotor:
❯ flutter doctor -v
[✓] Flutter (Channel stable, 3.3.10, on macOS 12.6 21G115 darwin-arm, locale en-DK)
    • Flutter version 3.3.10 on channel stable at /opt/homebrew/Caskroom/flutter/3.3.10/flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 135454af32 (8 weeks ago), 2022-12-15 07:36:55 -0800
    • Engine revision 3316dd8728
    • Dart version 2.18.6
    • DevTools version 2.15.0

[✓] Android toolchain - develop for Android devices (Android SDK version 32.1.0-rc1)
    • Android SDK at /Users/mf/Library/Android/sdk
    • Platform android-33, build-tools 32.1.0-rc1
    • Java binary at: /Applications/Android Studio.app/Contents/jre/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 11.0.11+0-b60-7772763)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 14.2)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Build 14C18
    • CocoaPods version 1.11.3

After upgrade:
❯ flutter upgrade
Upgrading Flutter to 3.7.1 from 3.3.10 in /opt/homebrew/Caskroom/flutter/3.3.10/flutter...
Downloading Darwin arm64 Dart SDK from Flutter engine 800594f1f4a6674010a6f1603c07a919b4d7ebd7...
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed

  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
  4  217M    4 10.5M    0     0  9402k      0  0:00:23  0:00:01  0:00:22 9425k
 24  217M   24 52.5M    0     0  24.1M      0  0:00:09  0:00:02  0:00:07 24.1M
 44  217M   44 97.1M    0     0  30.8M      0  0:00:07  0:00:03  0:00:04 30.8M
 65  217M   65  143M    0     0  34.4M      0  0:00:06  0:00:04  0:00:02 34.5M
 85  217M   85  186M    0     0  36.1M      0  0:00:06  0:00:05  0:00:01 37.7M
100  217M  100  217M    0     0  36.4M      0  0:00:05  0:00:05 --:--:-- 43.0M
Building flutter tool...

Upgrading engine...
Downloading Material fonts...                                      482ms
Downloading android-arm-profile/darwin-x64 tools...                225ms
Downloading android-arm-release/darwin-x64 tools...                229ms
Downloading android-arm64-profile/darwin-x64 tools...              235ms
Downloading android-arm64-release/darwin-x64 tools...              501ms
Downloading android-x64-profile/darwin-x64 tools...                231ms
Downloading android-x64-release/darwin-x64 tools...                233ms
Downloading android-x86 tools...                                   994ms
Downloading android-x64 tools...                                 1,047ms
Downloading android-arm tools...                                 1,194ms
Downloading android-arm-profile tools...                           279ms
Downloading android-arm-release tools...                           286ms
Downloading android-arm64 tools...                               1,042ms
Downloading android-arm64-profile tools...                         301ms
Downloading android-arm64-release tools...                         252ms
Downloading android-x64-profile tools...                           279ms
Downloading android-x64-release tools...                           257ms
Downloading android-x86-jit-release tools...                       297ms
Downloading ios tools...                                         2,778ms
Downloading ios-profile tools...                                 1,951ms
Downloading ios-release tools...                                 1,440ms
Downloading package sky_engine...                                  198ms
Downloading flutter_patched_sdk tools...                           358ms
Downloading flutter_patched_sdk_product tools...                   311ms
Downloading darwin-arm64 tools...                                1,310ms
Downloading darwin-x64/FlutterMacOS.framework tools...              6.4s
Downloading darwin-x64/gen_snapshot tools...                       928ms
Downloading darwin-x64-profile/FlutterMacOS.framework tools...      1,418ms
Downloading darwin-x64-profile tools...                            227ms
Downloading darwin-x64-profile/gen_snapshot tools...               318ms
Downloading darwin-x64-release/FlutterMacOS.framework tools...      1,063ms
Downloading darwin-x64-release tools...                            218ms
Downloading darwin-x64-release/gen_snapshot tools...               245ms
Downloading ios-deploy...                                          134ms
Downloading darwin-arm64/font-subset tools...                      405ms

Flutter 3.7.1 • channel stable • https://github.com/flutter/flutter.git
Framework • revision 7048ed95a5 (6 days ago) • 2023-02-01 09:07:31 -0800
Engine • revision 800594f1f4
Tools • Dart 2.19.1 • DevTools 2.20.1

Running flutter doctor...
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 3.7.1, on macOS 12.6 21G115 darwin-arm64, locale en-DK)
[✓] Android toolchain - develop for Android devices (Android SDK version 32.1.0-rc1)
[✓] Xcode - develop for iOS and macOS (Xcode 14.2)
[✓] Android Studio (version 2021.1)
[✓] VS Code (version 1.74.3)
[✓] Connected device (2 available)
[✓] HTTP Host Availability

• No issues found!
❯ flutter pub get
Running "flutter pub get" in elTooltipTesting...
Resolving dependencies... (1.4s)
> async 2.10.0 (was 2.9.0)
> boolean_selector 2.1.1 (was 2.1.0)
> collection 1.17.0 (was 1.16.0) (1.17.1 available)
+ js 0.6.5 (0.6.7 available)
> matcher 0.12.13 (was 0.12.12) (0.12.14 available)
> material_color_utilities 0.2.0 (was 0.1.5)
  meta 1.8.0 (1.9.0 available)
  path 1.8.2 (1.8.3 available)
> source_span 1.9.1 (was 1.9.0)
> stack_trace 1.11.0 (was 1.10.0)
> stream_channel 2.1.1 (was 2.1.0)
> string_scanner 1.2.0 (was 1.1.1)
> test_api 0.4.16 (was 0.4.12) (0.4.18 available)
> vector_math 2.1.4 (was 2.1.2)
Changed 12 dependencies!
❯ flutter run
Running "flutter pub get" in flutter_tools...
Resolving dependencies in ../../../../../opt/homebrew/Caskroom/flutter/3.3.10/flutter/packages/flutter_tools... (5.3s)
  _fe_analyzer_shared 50.0.0 (52.0.0 available)
  analyzer 5.2.0 (5.4.0 available)
  archive 3.3.2 (3.3.6 available)
  args 2.3.1 (2.3.2 available)
  built_value 8.4.2 (8.4.3 available)
  checked_yaml 2.0.1 (2.0.2 available)
  collection 1.17.0 (1.17.1 available)
  completion 1.0.0 (1.0.1 available)
  coverage 1.6.1 (1.6.3 available)
  dds 2.5.0 (2.7.4 available)
  dds_service_extensions 1.3.1 (1.3.2 available)
  devtools_shared 2.18.0 (2.20.1 available)
  dwds 16.0.2 (17.0.0 available)
  fixnum 1.0.1 (1.1.0 available)
  frontend_server_client 3.1.0 (3.2.0 available)
  intl 0.17.0 (0.18.0 available)
  io 1.0.3 (1.0.4 available)
  js 0.6.5 (0.6.7 available)
  json_annotation 4.7.0 (4.8.0 available)
  logging 1.1.0 (1.1.1 available)
  matcher 0.12.13 (0.12.14 available)
  meta 1.8.0 (1.9.0 available)
  mime 1.0.2 (1.0.4 available)
  multicast_dns 0.3.2+2 (0.3.2+3 available)
  native_stack_traces 0.5.2 (0.5.5 available)
  path 1.8.2 (1.8.3 available)
  sse 4.1.1 (4.1.2 available)
  test 1.22.0 (1.22.2 available)
  test_api 0.4.16 (0.4.18 available)
  test_core 0.4.20 (0.4.22 available)
  vm_service 9.4.0 (11.0.0 available)
  web_socket_channel 2.2.0 (2.3.0 available)
  webdriver 3.0.1 (3.0.2 available)
Got dependencies in ../../../../../opt/homebrew/Caskroom/flutter/3.3.10/flutter/packages/flutter_tools!
Launching lib/main.dart on iPhone SE (3rd generation) in debug mode...
Running Xcode build...
 └─Compiling, linking and signing...                         6.0s
Xcode build done.                                           16.0s
Syncing files to device iPhone SE (3rd generation)...               56ms

Things run smoothly! 🎉

Glad it works. Thanks for letting me know.


The user-defined Mitigation object sync from Workbench can't be shown correctly under Techniques

Hi ,
I created this issue for Website but i think maybe the root cause may related to Workbench. Please check, thank you very much.

Closing as it pertains to the Website build instead (https://github.com/mitre-attack/attack-website/issues/358). Thanks for reporting once again @dickens88.


Error while using the async/await method

Error: (node:176297) UnhandledPromiseRejectionWarning: TypeError: data.manufacturer is not a function
Code:  const data = await si.system(); **Manufacturer:**  ${data.manufacturer}

@FSCYT which platform, which OS version, which SI version?
Thank you for providing more information to be able to reproduce this issue.

@FSCYT which platform, which OS version, which SI version?
Thank you for providing more information to be able to reproduce this issue.

Thank you for replying, I tried redoing this in another function and it worked. I guess its a problem with the .setDescription in the discord.js package.

Thank you for replying, I tried redoing this in another function and it worked. I guess its a problem with the .setDescription in the discord.js package.


How me fix error "Class 'Input' not found"

https://github.com/Nayjest/Grids/issues/200

Duplicate, close


Add bundle

We should provide a bundled version of the js/css for all the viz types so that client libraries (e.g. Python) can run in "headless" mode without a running server. This could work by grabbing all the npm modules specified in our "default visualizations" config (as soon as everything is in npm), and then we'll embed the js/css in release updates to the client libraries.

Tooling to generate the standalone bundle was added. To generate the bundle run npm run generate-standalone-js. This will create the bundle with whatever visualizations are currently installed on the local server


add<EMAIL_ADDRESS>

Alaska Airlines Pull Request
This is to add Auro-select into Auro-formkit
This select is using auro-formkit/menu and<EMAIL_ADDRESS>currently and will have another PR of a revision to replace the use of<EMAIL_ADDRESS>to auro-formkit/dropdown
By submitting this Pull Request, I confirm that my contribution is made under the terms of the Apache 2.0 license and I have performed a self-review of my own update.
Summary by Sourcery
Add the auro-select component to the project, integrating it with auro-menu and auro-dropdown to provide a comprehensive dropdown menu solution. Enhance the auro-input component with new date input types and improve validation. Update build scripts and dependencies to support new components and ensure compatibility. Expand documentation and tests to cover new features and changes.
New Features:

Introduce auro-select component as a wrapper for auro-dropdown and auro-menu to create a dropdown menu control.
Add support for new date input types 'month', 'year', and 'fullYear' in auro-input component.

Enhancements:

Update auro-input component to include new date input types and improve validation messages.
Enhance build scripts to include new components like checkbox and menu, and update existing ones.

Build:

Update package.json dependencies to include new components and update existing ones to newer versions.
Enhance build scripts to support new components like checkbox, menu, and select.

Documentation:

Add comprehensive documentation for new auro-select component, including API examples and usage guidelines.
Update documentation for auro-input to reflect new date input types and usage.

Tests:

Add tests for new auro-select component to ensure functionality and integration with auro-menu and auro-dropdown.
Update tests for auro-input to cover new date input types and validation scenarios.

:tada: This PR is included in version 1.3.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Fix IceAgent improperly returning XorAddress

IceAgent improperly returns XorAddress when finding ports.
This would cause the portManager to fail finding the relevant port
since we are bound on the local (and not our public XorAddress)
Resolves #140

Pull Request Test Coverage Report for Build 801

0 of 12 (0.0%)  changed or added relevant lines in 1 file are covered.
1 unchanged line in 1 file lost coverage.
Overall coverage decreased (-0.04%) to 42.739%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

pkg/ice/agent.go
0
12
0.0%

Files with Coverage Reduction
New Missed Lines
%

internal/dtls/dtls.go
1
18.25%

Totals

Change from base Build 798:
-0.04%

Covered Lines:
2584

Relevant Lines:
6046

💛  - Coveralls


Manifest fix

Remove rimraf script from the package.json
The cause of the deployment problem was in the build stage of the pipeline not doing npm ci inside the root of the project, causing an module not found error during the deploy stage.


F1pullR

: created a branch, created a file and made a commit, and opened a pull
request

comparing changes


CBRK_FLIGHTTERM: Does not affect takeoff failure safety detection

Improve description.  @RicardoM17 - better?

Thanks @RicardoM17 - have clarified those too.
@bresch Can you please review the additional changes. If you're happy please also MERGE. I don't have rights to merge.

Thanks for removing the trailing whitespace. @bresch if this is good, I can't merge.


Is this project still alive?

@michalslaski  @mkacper  is this project still alive?  As a beginner in erlang/elixir this is the  project I was searching for visualizing stuff going on in my app.  I had the same issue as #89   is there any way to fix this issue?

@tckb at present we use this tool for educational purposes during trainings and meetups, so you may say that the project is alive :)
In systems with many processes sending messages the visualisation is unreadable and we don't have a fix for this. The other problem of processes disappearing and appearing again can be fixed. I'm not working on a fix at the moment, but I'm glad you shared your feedback. It gives motivation to revisit this issue and improve the tool.

thanks for the reaffirmation @michalslaski  .  my main usecase for this project would be a "demo" for my colleagues and visualizing  message passing  between processes would a great start!  If it's a trivial fix then may be I could help.


sidepanel

Is there a way to realize a sidebar panel with overlay feature, like all others mobile frameworks (and like spotify app for example on android) ?
You click on a top-left icon and a sidebar/sidepanel appear from left with the menu

+1

+1


Display only single reset/pull/push/slide-out button for the current branch, depending on its state

A single button could change between reset/pull/push/slide-out/nothing, depending on the state of the branch.
TBD: this would break our rule that we don't hide actions from the toolbar, just disable them :thinking:

EDIT: added slide-out which should be suggested for merged branches

Remove unused action implementations ~ https://github.com/VirtusLab/git-machete-intellij-plugin/pull/450#discussion_r462966214

Also, README.md (expanded on #452) needs to be updated


DO NOT MERGE CI for #3109

CI only.

Refer to this link for build results (access rights to CI server needed):
https://scala-webapps.epfl.ch/jenkins/job/scalajs-pr/4227/
https://scala-webapps.epfl.ch/jenkins/job/scalajs-matrix-build/5641/
Test PASSed.

Refer to this link for build results (access rights to CI server needed):
https://scala-webapps.epfl.ch/jenkins/job/scalajs-pr/4229/
https://scala-webapps.epfl.ch/jenkins/job/scalajs-matrix-build/5643/
Test PASSed.

Refer to this link for build results (access rights to CI server needed):
https://scala-webapps.epfl.ch/jenkins/job/scalajs-pr/4231/
https://scala-webapps.epfl.ch/jenkins/job/scalajs-matrix-build/5645/
Test PASSed.


[WIP] Criteo product feed tags

Following up on this Gravity PR, which created the Artworks product feed for Criteo - we now need to tag pages so that Criteo can determine who to surface adds to.
The tags for the already implemented Auctions feed currently reside in the analytics/bidding.js file.
In this PR (a WIP):

added all necessary tracking events for the new Artworks feed
consolidated Artworks and Auction Criteo events into a single analytics/criteo.js file
fixed null checks here and here - I may be mistaken, but I don't think these events are being tracked because checking for a non-present element in an array by index does not equal null, so I've changed pathSplit[3] === null to !(pathSplit[3])

Note  This is a WIP (feedback still welcome though) I need to follow-up and make sure the env var changes are ok, that the use of sd and analyticsHooks are working, and to apply the same changes to microgravity.
cc @jessekedy

Looks great to me! 👏  Happy to merge when ready.
Build failure is an unrelated spec that has a weird 1ms intermittent failure—kicked it.

          1 Warning

:warning:
Please assign someone to your PR

  Generated by :no_entry_sign: danger

hey @craigspaeth sorry for leaving this hanging, I left my comp. at the airport when I went on vacay and only just got it back.
So there's a couple things I need to update here, the first is described in this issue.  Would really like to pair on this because I tried to figure it out and got somewhere but hit a roadblock.  If you have time today that would be super cus I think we're launching this tomorrow, but of course if you're busy no rush, and maybe I can find someone else to help?
Also I think we need the user's email for Criteo tracking, hashed or unhashed, so that we can track them across devices.

sorry for leaving this hanging, I left my comp. at the airport when I went on vacay and only just got it back.

Don’t be sorry for that, it’s your holiday. I think more people should outright leave their computer behind like you did 👍

thanks Alloy !

hey @craigspaeth mind taking a final look here?
Local checks looked good to me.  Lmk if I'm missing tests, or anything.
note: we should hold off on the actual merge until this gravity PR is merged and a new report is built

@craigspaeth Can you take a final looksee, the Gravity PR is merged.

@alloy Gravity PR is not merged? - https://github.com/artsy/gravity/pull/10678 - The need for this PR is that our product feed currently does not include all for sale artworks and Criteo requires that any product id sent from the frontend exists in the feed.
This gravity PR changes the feed so that it include all for_sale artworks but, any product we don't want to appear in ads will have False in the new recommendable field.  Lmk if that makes sense.

My bad, I didn't realize you hade made multiple Gravity PRs.

Thanks for seeing this effort through end to end Oliver! 🙌  Merging, let me know if you need help debugging anything that looks off.

@craigspaeth 👍 thanks! will do


SequenceIndexOp for saturate_index and wrap_index

@falsetru @killme2008 Could you please review this PR as recent users of this functions?

Thank you!


Fix spec compilation on Windows

ts-morph provides us with a normalized path that always uses / as the path separator (even on Windows). In this PR I replace some occurences of sep with just / in that context.
Besides that, on Windows, multi-line strings are emitted with CRLF (/r/n) instead of just LF (/n). I use some ugly replace calls to fix this. A better solution would probably be the usage of .gitattributes to make sure .ts files are always committed and checked out in LF style. But I'm not sure if that would cause any side-effects.
TODO: Order of endpoints in the output json is not consistent between Windows and Linux. I did not dig into that for now as it does not change semantics...

@JoshMock Yes, that fixes the undefined namespace issue 🙂


Unable to synthesize using wavenet model.

I was training Tacotron-2 model by first training tacotron model, then wavenet model. When I run synthesis.py for wavenet model I'm getting the error message below.
Traceback (most recent call last):
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 1322, in _do_call
return fn(*args)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 1307, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 1409, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: Key WaveNet_model/WaveNet_model/inference/causal_conv1d/residual_block_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage not found in checkpoint
[[Node: WaveNet_model/save/RestoreV2 = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, ..., DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_WaveNet_model/save/Const_0_0, WaveNet_model/save/RestoreV2/tensor_names, WaveNet_model/save/RestoreV2/shape_and_slices)]]
[[Node: WaveNet_model/save/RestoreV2/_231 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_236_WaveNet_model/save/RestoreV2", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "synthesize.py", line 99, in
main()
File "synthesize.py", line 91, in main
wavenet_synthesize(args, hparams, wave_checkpoint)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/synthesize.py", line 78, in wavenet_synthesize
run_synthesis(args, checkpoint_path, output_dir, hparams)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/synthesize.py", line 19, in run_synthesis
synth.load(checkpoint_path, hparams)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/synthesizer.py", line 39, in load
load_averaged_model(self.session, sh_saver, checkpoint_path)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/train.py", line 62, in load_averaged_model
sh_saver.restore(sess, checkpoint_path)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 1802, in restore
{self.saver_def.filename_tensor_name: save_path})
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 900, in run
run_metadata_ptr)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 1316, in _do_run
run_metadata)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/client/session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: Key WaveNet_model/WaveNet_model/inference/causal_conv1d/residual_block_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage not found in checkpoint
[[Node: WaveNet_model/save/RestoreV2 = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, ..., DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_WaveNet_model/save/Const_0_0, WaveNet_model/save/RestoreV2/tensor_names, WaveNet_model/save/RestoreV2/shape_and_slices)]]
[[Node: WaveNet_model/save/RestoreV2/_231 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_236_WaveNet_model/save/RestoreV2", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]
Caused by op 'WaveNet_model/save/RestoreV2', defined at:
File "synthesize.py", line 99, in
main()
File "synthesize.py", line 91, in main
wavenet_synthesize(args, hparams, wave_checkpoint)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/synthesize.py", line 78, in wavenet_synthesize
run_synthesis(args, checkpoint_path, output_dir, hparams)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/synthesize.py", line 19, in run_synthesis
synth.load(checkpoint_path, hparams)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/synthesizer.py", line 29, in load
sh_saver = create_shadow_saver(self.model)
File "/xx/xx/xx/Tacotron-2/wavenet_vocoder/train.py", line 59, in create_shadow_saver
return tf.train.Saver(shadow_dict, max_to_keep=5)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 1338, in init
self.build()
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 1347, in build
self._build(self._filename, build_save=True, build_restore=True)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 1384, in _build
build_save=build_save, build_restore=build_restore)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 835, in _build_internal
restore_sequentially, reshape)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 472, in _AddRestoreOps
restore_sequentially)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/training/saver.py", line 886, in bulk_restore
return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/ops/gen_io_ops.py", line 1463, in restore_v2
shape_and_slices=shape_and_slices, dtypes=dtypes, name=name)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3392, in create_op
op_def=op_def)
File "/xxx/xxxx/xxx/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1718, in init
self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access
NotFoundError (see above for traceback): Key WaveNet_model/WaveNet_model/inference/causal_conv1d/residual_block_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage not found in checkpoint
[[Node: WaveNet_model/save/RestoreV2 = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, ..., DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_WaveNet_model/save/Const_0_0, WaveNet_model/save/RestoreV2/tensor_names, WaveNet_model/save/RestoreV2/shape_and_slices)]]
[[Node: WaveNet_model/save/RestoreV2/_231 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_236_WaveNet_model/save/RestoreV2", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]
This is not the same as #163  because that issue is produced by running both models using python train.py --model ="Both".
I've also checked the variables stored inside checkpoint file using tensorflows print_tensors_in_checkpoint_file function and it's output is:-
WaveNet_model/WaveNet_model/inference/conv1_d1x1/input_convolution/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/conv1_d1x1/input_convolution/kernel/ExponentialMovingAverage (DT_FLOAT) [1,1,64]
WaveNet_model/WaveNet_model/inference/conv1_d1x1_1/final_convolution_1/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/conv1_d1x1_1/final_convolution_1/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/conv1_d1x1_2/final_convolution_2/bias/ExponentialMovingAverage (DT_FLOAT) [2]
WaveNet_model/WaveNet_model/inference/conv1_d1x1_2/final_convolution_2/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,2]
WaveNet_model/WaveNet_model/inference/conv_transpose1d/bias/ExponentialMovingAverage (DT_FLOAT) [80]
WaveNet_model/WaveNet_model/inference/conv_transpose1d/kernel/ExponentialMovingAverage (DT_FLOAT) [1,10,80,80]
WaveNet_model/WaveNet_model/inference/conv_transpose1d_1/bias/ExponentialMovingAverage (DT_FLOAT) [80]
WaveNet_model/WaveNet_model/inference/conv_transpose1d_1/kernel/ExponentialMovingAverage (DT_FLOAT) [1,10,80,80]
WaveNet_model/WaveNet_model/inference/conv_transpose1d_2/bias/ExponentialMovingAverage (DT_FLOAT) [80]
WaveNet_model/WaveNet_model/inference/conv_transpose1d_2/kernel/ExponentialMovingAverage (DT_FLOAT) [1,22,80,80]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/causal_conv1d/residual_block_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/causal_conv1d/residual_block_conv_ResidualConv1DGLU_0/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_0/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_0/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_0/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/causal_conv1d/residual_block_conv_ResidualConv1DGLU_1/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/causal_conv1d/residual_block_conv_ResidualConv1DGLU_1/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_1/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_1/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_1/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_1/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_1/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_1/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_1/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/causal_conv1d/residual_block_conv_ResidualConv1DGLU_10/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/causal_conv1d/residual_block_conv_ResidualConv1DGLU_10/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_10/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_10/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_10/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_10/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_10/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_10/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_10/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/causal_conv1d/residual_block_conv_ResidualConv1DGLU_11/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/causal_conv1d/residual_block_conv_ResidualConv1DGLU_11/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_11/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_11/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_11/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_11/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_11/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_11/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_11/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/causal_conv1d/residual_block_conv_ResidualConv1DGLU_12/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/causal_conv1d/residual_block_conv_ResidualConv1DGLU_12/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_12/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_12/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_12/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_12/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_12/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_12/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_12/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/causal_conv1d/residual_block_conv_ResidualConv1DGLU_13/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/causal_conv1d/residual_block_conv_ResidualConv1DGLU_13/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_13/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_13/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_13/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_13/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_13/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_13/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_13/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/causal_conv1d/residual_block_conv_ResidualConv1DGLU_14/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/causal_conv1d/residual_block_conv_ResidualConv1DGLU_14/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_14/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_14/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_14/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_14/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_14/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_14/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_14/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/causal_conv1d/residual_block_conv_ResidualConv1DGLU_15/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/causal_conv1d/residual_block_conv_ResidualConv1DGLU_15/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_15/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_15/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_15/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_15/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_15/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_15/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_15/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/causal_conv1d/residual_block_conv_ResidualConv1DGLU_16/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/causal_conv1d/residual_block_conv_ResidualConv1DGLU_16/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_16/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_16/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_16/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_16/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_16/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_16/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_16/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/causal_conv1d/residual_block_conv_ResidualConv1DGLU_17/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/causal_conv1d/residual_block_conv_ResidualConv1DGLU_17/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_17/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_17/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_17/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_17/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_17/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_17/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_17/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/causal_conv1d/residual_block_conv_ResidualConv1DGLU_18/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/causal_conv1d/residual_block_conv_ResidualConv1DGLU_18/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_18/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_18/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_18/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_18/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_18/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_18/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_18/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/causal_conv1d/residual_block_conv_ResidualConv1DGLU_19/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/causal_conv1d/residual_block_conv_ResidualConv1DGLU_19/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_19/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_19/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_19/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_19/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_19/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_19/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_19/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/causal_conv1d/residual_block_conv_ResidualConv1DGLU_2/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/causal_conv1d/residual_block_conv_ResidualConv1DGLU_2/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_2/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_2/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_2/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_2/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_2/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_2/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_2/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/causal_conv1d/residual_block_conv_ResidualConv1DGLU_3/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/causal_conv1d/residual_block_conv_ResidualConv1DGLU_3/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_3/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_3/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_3/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_3/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_3/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_3/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_3/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/causal_conv1d/residual_block_conv_ResidualConv1DGLU_4/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/causal_conv1d/residual_block_conv_ResidualConv1DGLU_4/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_4/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_4/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_4/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_4/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_4/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_4/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_4/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/causal_conv1d/residual_block_conv_ResidualConv1DGLU_5/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/causal_conv1d/residual_block_conv_ResidualConv1DGLU_5/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_5/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_5/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_5/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_5/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_5/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_5/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_5/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/causal_conv1d/residual_block_conv_ResidualConv1DGLU_6/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/causal_conv1d/residual_block_conv_ResidualConv1DGLU_6/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_6/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_6/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_6/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_6/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_6/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_6/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_6/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/causal_conv1d/residual_block_conv_ResidualConv1DGLU_7/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/causal_conv1d/residual_block_conv_ResidualConv1DGLU_7/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_7/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_7/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_7/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_7/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_7/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_7/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_7/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/causal_conv1d/residual_block_conv_ResidualConv1DGLU_8/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/causal_conv1d/residual_block_conv_ResidualConv1DGLU_8/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_8/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_8/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_8/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_8/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_8/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_8/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_8/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/causal_conv1d/residual_block_conv_ResidualConv1DGLU_9/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/causal_conv1d/residual_block_conv_ResidualConv1DGLU_9/kernel/ExponentialMovingAverage (DT_FLOAT) [3,64,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_9/bias/ExponentialMovingAverage (DT_FLOAT) [128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/conv1_d1x1/residual_block_cin_conv_ResidualConv1DGLU_9/kernel/ExponentialMovingAverage (DT_FLOAT) [1,80,128]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_9/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/conv1_d1x1_1/residual_block_skip_conv_ResidualConv1DGLU_9/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_9/bias/ExponentialMovingAverage (DT_FLOAT) [64]
WaveNet_model/WaveNet_model/inference/residual_conv1dglu_9/conv1_d1x1_2/residual_block_out_conv_ResidualConv1DGLU_9/kernel/ExponentialMovingAverage (DT_FLOAT) [1,64,64]
global_step (DT_INT32) []
as it can be seen from above log, there is no value for "WaveNet_model/WaveNet_model/inference/causal_conv1d/residual_block_conv_ResidualConv1DGLU_0/bias/ExponentialMovingAverage" variable.

Hey @mitiku1 thanks for reaching out!
It's awesome that you made the checkpoint inspection as it is very helpful. As one can see, it is clear that the residual_conv1dglu/ component is being added to the scopes during training but not during tests which is causing this whole issue. I have had this issue a couple of times during development and I didn't really know how it went away. So please, consider these two scenarios:

Did you train your wavenet model with a previous repo version then updated the repo when trying synthesis?
If not, could you please provide steps to reproduce?

As for now, for a quick temporary solution (that does not require training), you can rename your checkpoint scopes during synthesis by taking off the residual_conv1dglu/ component to ensure the synthesis graph is consistent with the training one.
Thank you for reporting this bug, you answer to my above question will help us solve it for the long run.

In my situation, It means you have trained model with different either code or params, before and after checkpoint being saved.

@Rayhane-mamah Thanks for your replay. I followed the following steps to reproduce the issue.

It should be noted that when I clone the repository,  head commit of master branch was @this commit
I am using tensorflow version 1.8.0
I've placed LJ dataset inside project folder
-I've created test.txt file and placed a single sentence("Hello world!"), for evaluation.

STEP - 1 Makeing some changes.
I will explain why I made each change.
Change-1:
I've made some changes to hparam.py (To deal with low memory gpu). If you want to see the changes I may post it here.
Change-2 :
I've changed the --tacotron_train_steps`` and ``--wavenet_train_steps values of train.py to 200, to reproduce the issue quickly.
Change-3:
I was getting AttributeError: 'tuple' object has no attribute '_uses_learning_phase' error message for calling functions which return tuple. So I changed tuple return values of some functions [ResidualConv1DGLU.call,CausalConv1D.call] to lists.
Change-4:
After completing this I was getting another error message. TypeError: This Layer takes an inputsargument to call(), and only theinputs argument may be specified as a positional argument. Pass everything else as a keyword argument (those arguments will not be tracked as inputs to the Layer).. To fix this I've changed some lines to call methods with keyword arguments.[ResidualConv1DGLU.incremental_step,WaveNet.step]
Change 5:
I've replaced info argument name of plot.plot_alignment method call with title argument [tacotron.Synthesizer.synthesize(1,2,3)] (This is because the method definition does not have info parameter.
STEP - 2 running preprocessor.py
python preprocess.py
STEP - 3 Training Tacotron model
python train.py --model "Tacotron"
STEP - 4 Synthesis training data for wavenet using Tacotron model
python synthesize.py --model Tacotron --GTA True --mode synthesis
STEP - 5 Training WaveNet model
python train.py --model "WaveNet"
STEP-6 Synthesizing mels with Tacotron for evaluation
python synthesize.py --model Tacotron --GTA False --mode eval --text_list test.txt
STEP-7 Synthsizing audio with wavenet model.
python synthesize.py --model WaveNet --mode eval
After this the program throws the error message.

Hello again @mitiku1, first of all thanks for all the details.
So considering I have moved from the previous commit a while back, I was not able to reproduce locally, I must have fixed it sometime between the previous and the current version. In any case, please try updating to latest version and let me know if the problem persists!

@Rayhane-mamah thanks again.
Though I've tried with latest version of the repo the error message was persisted, till I completely changed the virtual environment. I installed tensorflow 1.10.0 and other libraries from requirement file of this repository. This way now the error message has gone. I'm able to run synthesize.py for wavenet vocoder. I'm not sure if changing the tensorflow version or changing version of other libraries solved the problem.
One last thing, though this is not the case for tensorflow 1.10, I think you forget here to pass values for non input argument as positional arguments.


Command pkg is missing documentation+examples+good API names

/internal/command needs some explanation on what it is and how it works.
Various exported names for functions, etc. could probably be better.
Generally it's intended to wrap functions of 2 signatures: func niladic(context.Context, *settingsT) error and func withArgs(context.Context, *settingsT, ...string) error which are expected to be the main entry to various CLI command endpoints.
The test files and fs shutdown may be understandable examples of how it's used.

Good names are debatable (and I'm always open to suggestion,) but the documentation has been filled in, tests were written, and examples are now there. It should be better than nothing for any developers who are tying to read or modify the relevant code.
This extends to more packages than just command.
Unfortunately, pkg.go.dev isn't happy with our repo since we're not yet using tagged releases, so it's lagging behind and showing the old in-progress commits. This is a seperate issue we'll have to tackle later as things stabalize.
Running godoc locally (or any other documentation program) on the latest commit doesn't have this problem.


Can't Save

I don't know why but once i hit about 40 frames on a Gif or about 8 layers is starts to glitch and not be able to save, is there anything I can do to fix this?
PS: Would appreciate if u added and flip tool (aka) horizontal flip or  diagonal flip.

Hi, thanks for reporting the issue. Could you give more details:

what is the size of your sprite ?
how many frames and layers are you using ?
how are you trying to save it (online gallery, local browser, download as piskel file, export to image...)

Also relevant:

what is your browser ?
what are the specs of your machine ?

starts to glitch
What do you mean by this? Do you see / have issues in your sprite before trying to save? Please be as explicit as possible.

If your sprite is too big, then there's not much you can do at the moment, sorry. There are hard limits on what I can store online. GIF export should behave better than most of the other export tools, but depending on the size of your sprite it might become buggy too.
I am adding warnings in #555 to let users know when they start to exceed what the program can handle.
I can fix improve the .piskel save to store bigger sprites that it does today.

PS: Would appreciate if u added and flip tool (aka) horizontal flip or diagonal flip

The flip tool performs a vertical flip if you hold alt when clicking on the tool.

No answer from logger. Closing


GLTF animation issue

Describe the bug
Certain GLTF files do not animate correctly
To Reproduce
Steps to reproduce the behavior:
0. Horse.glb.zip

Open the file using f3d --dry-run horse.glb
Press space
Animation is incorrect

Expected behavior
Animation should looks correct (check in https://gltf-viewer.donmccurdy.com/)
System Information:

OS: linux and windows

F3D Information
Paste the content of f3d --version: master and 1.3.1
Notes
using --geometry-only is a workaround

@Meakk Other animation works without issue, I think this is another type of animation which is not supported correctly.
Strangley the vtkGLTFReader does not have this issue.

@Meakk I think this one is in VTK but investigation is needed to be sure. Do you think it matters for the next release ?
Other animations seems to work. I found a few files failing like this one, mostly "simple" animation.

@Meakk

Looks like the mesh is duplicated for every frame, but I don't see any temporal information in the GLTF file...


Get rid of method redefinition warnings during precompile stage

This PR finally gets rid of all the Casette warnings and a few other similar warnings due to method redefinitions.
Had to refactor the FPlane constructor to avoid a method redefinition. I chose to infer the float type FT from the inputs and remove the option to explicitly pass in an FT. This is a breaking change (hopefully a minor one) but I couldn't think of another approach that would less intrusive.
Suggestions welcome for other ways to resolve the ambiguity between FPlane constructors.
Resolves #537
Resolves #366

Don't depend on master grrml...

Ah what would be a better way of doing this than ] add Cassette#master?

Waiting for me to tag a version of Cassette.

Yeah that would have been cleaner. Will ask or wait in the future.


JSON Response Body Highlight is invalid in particular case

This JSON response body :
{
  "result": {
    "status": "done",
    "expressions": [
      {
        "expression": "toto",
        "length": 1
      },
      {
        "expression": "titi",
        "length": 2
      }
    ]
  }
}

Is render in "Response Body (Highlight)" tabs as :
{
  "result": {
    "status": "done",
    "expressions": [
      [
        "toto",
        1
      ],
      [
        "titi",
        2
      ]
    ]
  }
}

I know this is an old issue, but it's really issue when testing APIs

Our team just ran into the same bug (a nested object in an array, with a key named "length"), which cost us a lot of time trying to sort it out.  Any chance we can get this fixed?  As @rbarriuso notes, it's very dangerous when testing APIs.  Thanks.