sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: react-native
Issue: Sticky views have visual glitches while scrolling in ScrollView
Labels: Issue: Author Provided Repro,Component: ScrollView,Needs: Triage :mag:

### Description

The views that specified as "sticky" in ScrollView have visual glitches while scrolling programmatically.   

### Steps to reproduce

1. Install the Snack on a physical device
2. Press the "Scroll to 1000" button
3. Press the "Scroll to 5000" button

### React Native Version

0.74.3

### Affected Platforms

Runtime - Android, Build - Linux

### Output of `npx react-native info`

```text
System:
  OS: Linux 5.15 Arch Linux
  CPU: (8) x64 Intel(R) Core(TM) i3-10100F CPU @ 3.60GHz
  Memory: 5.20 GB / 7.71 GB
  Shell:
    version: 5.2.26
    path: /usr/bin/bash
Binaries:
  Node:
    version: 20.15.1
    path: ~/.nvm/versions/node/v20.15.1/bin/node
  Yarn:
    version: 1.22.22
    path: ~/.nvm/versions/node/v20.15.1/bin/yarn
  npm:
    version: 10.8.2
    path: ~/.nvm/versions/node/v20.15.1/bin/npm
  Watchman: Not Found
SDKs:
  Android SDK: Not Found
IDEs:
  Android Studio: Not Found
Languages:
  Java: Not Found
  Ruby: Not Found
npmPackages:
  "@react-native-community/cli": Not Found
  react:
    installed: 18.2.0
    wanted: 18.2.0
  react-native:
    installed: 0.74.3
    wanted: 0.74.3
npmGlobalPackages:
  "*react-native*": Not Found
Android:
  hermesEnabled: Not found
  newArchEnabled: Not found
iOS:
  hermesEnabled: Not found
  newArchEnabled: Not found
```


### Stacktrace or Logs

```text
None
```


### Reproducer

https://snack.expo.dev/@michail_shcherbakov/sticky-view-glitches

### Screenshots and Videos


https://github.com/user-attachments/assets/9b93783e-4d85-4000-bcec-87870cfd1446
Repository: react
Issue: `FALLBACK_THROTTLE_MS` slows tests down significantly - could it be configurable?
Labels: Type: Discussion

## Summary

Hi there :wave:,

we encountered a massive slowdown in the Apollo Client React hooks test suite - especially on the suspense-related tests - when we started testing for React 19.

One file specifically went up from a 10s execution time to 80s.

Further discussion [on twitter](https://x.com/sebsilbermann/status/1807817802163569044) and [later in an issue in testing library](https://github.com/testing-library/react-testing-library/issues/1342) revealed that this slowdown relates to React 19 being more strict with the throttle of the Suspense fallback, and that every suspense fallback shown in a test now slows down the test by an additional 300ms.

While I generally agree with testing close to the original implementation, in our case this massively slows down our local development and significantly increases the CI minutes used (it sums up over all tests to an additional 2 minutes for every CI run).

Changing everything to mocked timers is something that would honestly be very painful (even if only on affected tests), and if it would really need to be done on a global scale as indicated by @eps1lon in that issue, I believe it would just be completely out of the question in many cases - it would require rewriting thousands of tests, even if not suspense-related.

Would you be willing to make `FALLBACK_THROTTLE_MS` configurable, similar to `IS_REACT_ACT_ENVIRONMENT`?

I [did patch the timeout for our test suite](https://github.com/apollographql/apollo-client/pull/11963), and could verify that it almost brings execution times back down to the original - I kept the timeout at a for tests more reasonable 10ms, so we go from 10s on React 18 to 15s on React 19 now.

I would happily submit a PR if you would consider this.

## Reproduction

You can see this happening in this reproduction (runnable repo here: https://github.com/phryneas/react-19-reproduction-slow-tests): 

```js
test("does not timeout", async () => {
  const initialPromise = Promise.resolve("test");
  console.time("executing component render");
  console.time("got past the `use` call");
  console.time("assertion succeeded");

  function Component() {
    console.timeLog("executing component render");
    const renderResult = use(initialPromise);
    console.timeLog("got past the `use` call", renderResult);
    return <div>{renderResult}</div>;
  }

  render(
    <Suspense fallback={<div>loading</div>}>
      <Component />
    </Suspense>
  );

  await waitFor(() => {
    screen.getByText("test");
    console.timeLog("assertion succeeded");
  });
});
```

Which logs

```
    executing component render: 4 ms

    executing component render: 51 ms

    got past the `use` call: 53 ms test

    assertion succeeded: 340 ms
```
Repository: vscode
Issue: Support 'Panel position' setting under 'Customize layout' button
Labels: polish,layout

![image](https://github.com/user-attachments/assets/9ca4dc57-59b4-416d-80c7-9f1af89bb2d4)
Right now, VS Code only supports showing/hiding the panel through the 'Customize layout' popup
but as we can place this panel at the top, right, left, and bottom 
I would like to see this setting available under the existing 'Customize layout' popup just like 'Primary sidebar position'

Also, one more improvement we need in this area
If I move my primary sidebar to the right it reflects that thing in this layout by showing the proper icon
![image](https://github.com/user-attachments/assets/100bba0c-b73e-40c2-be06-2c979ddfc36d)

but for panel, it does not reflect the existing panel position
it always shows me this icon even though I have set it up on the left
![image](https://github.com/user-attachments/assets/fc655981-e88e-4de6-8e86-7029ac15e2d7)

maybe we need some UX input for showcasing the panel and sidebar with some different indicators
Repository: storybook
Issue: [Documentation]: Angular - The documentation for handing event emitters is non existant.
Labels: documentation,needs triage

### Describe the problem

I've looked for 10 hours.  There is no documentation on how to verify that a component is emitting an event.  Since this feature is intimate to how Angular works, particularly as part of two-way binding, it's absence is entirely unacceptable.

Given this component:
```
import { Component, EventEmitter, Output } from '@angular/core';

@Component({
  selector: 'cv-button',
  standalone: true,
  template: `
    <button (click)="onClick()">Click Me</button>
  `,
  imports: [],
})
export class ButtonComponent {
  private count = 0
  @Output() clickCount = new EventEmitter<number>

  onClick() {
    this.count++
    this.clickCount.emit(this.count)
  }
}
```

I can test the click with this story.

```
import { Meta, StoryObj, moduleMetadata } from '@storybook/angular';
import { ButtonComponent } from './button.component';
import { userEvent, within } from '@storybook/test';

const meta:Meta<ButtonComponent> = {
  title: 'Button Test',
  component: ButtonComponent,
  tags: ['autodocs'],
 
  decorators: [
    moduleMetadata({
      imports: []
    })
  ]
}

export default meta

type Story = StoryObj<ButtonComponent>

export const Primary: Story = {
  args: {},
  play: async ({canvasElement, args}) => {
    const element = within(canvasElement)
    userEvent.click(element.getByText('Click Me'))
  }
}
```

But there's no page on this site or anywhere on the net I've been able to find that clearly states how to check if the clickCount was incremented.  I know it has to be possible - Storybook shows it is going up in the Actions inspector. But that inspector is entirely useless for an automated test.

Someone please help. This has been incredibly frustrating and has me on the verge of giving up using Storybook altogether with Angular, as being unable to test if components are actually emitting the values they are supposed to be emitting renders the whole exercise pointless.



### Additional context

_No response_
Repository: angular
Issue: Allow to pass a custom cookie parser function to create XSRF_COOKIE_NAME
Labels: area: common

### Which @angular/* package(s) are relevant/related to the feature request?

common

### Description

The function `withXsrfConfiguration` allows currently to tell angular what cookie should be used for CSRF protection like this:

```ts
export const appConfig: ApplicationConfig = {
  providers: [
    provideHttpClient(
      withXsrfConfiguration({
        cookieName: 'CUSTOM_XSRF_TOKEN',
        headerName: 'X-Custom-Xsrf-Header',
      }),
    ),
  ]
};
```

This, However only works if the CSRF Token is received as a single cookie with it's content.

Some backends might send the CSRF information as part of a JSON encoded JWT which leads to the need to setup a custom HTTP interceptor to create CSRF protection.

### Proposed solution

I suggest to extend the API, so either `cookieName` or `cookie` as an object can be passed.
When using the Object, it holds a simple string refering to the name of the cookie and a function which extracts the CSRF info from the raw cookie.

Assume we have a session cookie called `session`:

```jwt
eyJzZXNzaW9uSWQiOiItREZfS2EyM3B6a2haQkVfRUdnUVFfWFQiLCJjc3JmVG9rZW4iOiJ6TDNhVm10UDBFRDMiLCJ1c2VyIjp7InN1YiI6Imx1SmFiNGZ1aHVCSzlpS3Ixd1BKamRtY2phdnRwbGFoUmpGeVAtU1JYOHMiLCJlbWFpbCI6IkpvaG4uRG9lQGV4YW1wbGUuY29tIiwibmFtZSI6IkpvaG4gRG9lIn0sImFsZyI6IkhTMjU2In0.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.k_vbOhE_yPeUMziXMokn6GxC5v1x47lZmoZE20Wzz9U
```

which decodes to:

```json
{
  "sessionId": "-DF_Ka23pzkhZBE_EGgQQ_XT",
  "csrfToken": "zL3aVmtP0ED3",
  "user": {
    "sub": "luJab4fuhuBK9iKr1wPJjdmcjavtplahRjFyP-SRX8s",
    "email": "John.Doe@example.com",
    "name": "John Doe"
  },
  "alg": "HS256"
}
```

Then we could setup XSRF protection like this:

```ts
import { jwtDecode } from "jwt-decode";

// ...

export const appConfig: ApplicationConfig = {
  providers: [
    provideHttpClient(
      withXsrfConfiguration({
        cookie: {
          name: 'session',
          decode: (cookieContentRaw) => jwtDecode(cookieContentRaw).csrfToken;
        }
        headerName: 'X-Custom-Xsrf-Header',
      }),
    ),
  ]
};
```

### Alternatives considered

the suggested API ca be discussed.
Repository: flutter
Issue: [tool] Notify app developers of plugins that are incompatible with Swift Package Manager
Labels: platform-ios,tool,platform-mac,P2,team-ios,triaged-ios

Umbrella issue: https://github.com/flutter/flutter/issues/126005
Repository: pytorch
Issue: Clean up coverage_ignore_functions
Labels: module: docs,module: ci,triaged

### 📚 The doc issue

As we were triaging for the docathon, we discovered that many of the functions listed in [coverage_ignore_functions](https://github.com/pytorch/pytorch/blob/main/docs/source/conf.py#L92) were already documented. In addition, we documented quite a few of them during the docathon.

### Suggest a potential alternative/fix

 We need to clean up this list and add the missing autofunction, autoclass directives as needed to the corresponding .rst files. 

cc @brycebortree @seemethere @malfet @pytorch/pytorch-dev-infra
Repository: rust
Issue: array::IntoIter::new deprecation warning suggestion may lead to compilation error on 2015 and 2018 editions
Labels: A-diagnostics,T-compiler

### Code

```Rust
std::array::IntoIter::new(array)
```


### Current output

```Shell
warning: use of deprecated associated function `std::array::IntoIter::<T, N>::new`: use `IntoIterator::into_iter` instead
```


### Desired output

```Shell
No warning on editions 2015 and 2018
```


### Rationale and extra context

In many cases `array.into_iter()` will use `<&[T; N] as IntoIterator>::into_iter` on editions 2015 and 2018.

### Other cases

_No response_

### Rust Version

```Shell
rustc 1.79.0 (129f3b996 2024-06-10)
binary: rustc
commit-hash: 129f3b9964af4d4a709d1383930ade12dfe7c081
commit-date: 2024-06-10
host: x86_64-pc-windows-msvc
release: 1.79.0
LLVM version: 18.1.7
```


### Anything else?

https://play.rust-lang.org/?version=nightly&mode=debug&edition=2018&gist=f15a8e22d23c8b20ed3a21c6f3b4ab01
Repository: node
Issue: readability/pointer is inaccurate
Labels: c++

In the CPP linting configuration, the regular expression designed to identify pointers on the right side (which are considered invalid) is:

```regex
[^=|(,\s><);&?:}](?<!(sizeof|return))\s\*[a-zA-Z_][0-9a-zA-Z_]*
```

However, this case can occur:

```cpp
#ifdef DEBUG
    bool consistency_check = false;
    isolate()->RequestInterrupt([](Isolate*, void* data) {
      *static_cast<bool*>(data) = true;
    }, &consistency_check);
#endif
```
```cpp
#ifdef DEBUG
    bool consistency_check = false;
    isolate()->RequestInterrupt(
        [](Isolate*, void* data) { *static_cast<bool*>(data) = true; },
        &consistency_check);
#endif
```

Although both snippets are functionally equivalent, the only difference is the formatting. The regex doesn't match the first snippet, but matches the second.

https://regex101.com/r/nGXdSj/2
Repository: godot
Issue: Animation panel: moving cursor to Scene view focuses it, preventing further use of Animation keyboard shortcuts
Labels: bug,topic:editor,usability,topic:animation

### Tested versions

- Reproducible in v4.2.1.stable.official [b09f793f5], v4.2.2.stable.official [15073afe3], v4.3.rc2.official [3978628c6]

### System information

Godot v4.2.1.stable - Ubuntu 22.04.4 LTS 22.04 - X11 - Vulkan (Mobile) - dedicated NVIDIA GeForce GTX 860M (nvidia; 535.161.07) - Intel(R) Core(TM) i7-4710HQ CPU @ 2.50GHz (8 Threads)

### Issue description

When using the animation panel and focusing it (either the overall panel or a specific track and key) in order to use animation contextual shortcuts (such as Ctrl+Left/Right to move to previous/next step), and moving the cursor away to hover the Scene view, the Scene view will immediately be focused, preventing further use of Animation keyboard shortcuts.

This seems by design, maybe to allow Scene view shortcuts like W to switch to Translate mode; but no other panel does this, and therefore going back to the Animation panel is not even enough to focus the Animation panel again, you must click on it.

While this seems benign, I have a real use case where it bothers me a lot: I'm trying to estimate the number of pixels a sprite is moving by during some animation. I use my cursor as a reference for the initial pixel position. Then I use Ctrl+Right to advance the animation, and compare the cursor to the next pixel position. But moving the cursor focuses the Scene view and prevents me from advancing the animation. I have to play the animation very slowly while having the cursor over the Scene view, or inspect the animation directly in my graphics editor, to do what I want.

If it's an intended behavior then I'd like an option to disable it (I can reopen a feature request in this case).

### Steps to reproduce

1. Create some Animation and open the Animation Panel
2. Add some track to test Ctrl+Left/Right shortcuts
3. Move cursor to hover Scene view (without clicking)
4. Observe focus switching to Scene view (blue frame highlight + Animation contextual shortcuts stop working)

### Minimal reproduction project (MRP)

N/A
Repository: pytorch
Issue: DISABLED test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_160_is_causal_False_dropout_p_0_48_float16_scale0_cuda_float16 (__main__.TestSDPACudaOnlyCUDA)
Labels: module: rocm,triaged,module: flaky-tests,skipped

Platforms: rocm

This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_160_is_causal_False_dropout_p_0_48_float16_scale0_cuda_float16&suite=TestSDPACudaOnlyCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/27649304066).

Over the past 3 hours, it has been determined flaky in 3 workflow(s) with 6 failures and 3 successes.

**Debugging instructions (after clicking on the recent samples link):**
DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs.
To find relevant log snippets:
1. Click on the workflow logs linked above
2. Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
3. Grep for `test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_160_is_causal_False_dropout_p_0_48_float16_scale0_cuda_float16`
4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.



<details><summary>Sample error message</summary>

```
Traceback (most recent call last):
  File "test_transformers.py", line 3039, in test_flash_attention_vs_math_ref_grads
    self.assertEqual(query.grad, query_ref.grad.to(query.grad.dtype),
  File "/opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/testing/_internal/common_utils.py", line 3721, in assertEqual
    raise error_metas.pop()[0].to_error(
AssertionError: Tensor-likes are not close!

Mismatched elements: 287143 / 655360 (43.8%)
Greatest absolute difference: 18848.0 at index (0, 2, 892, 59) (up to 5.56640625 allowed)
Greatest relative difference: 1.013671875 at index (0, 3, 527, 126) (up to 0.001 allowed)

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_ROCM=1 python test/test_transformers.py -k TestSDPACudaOnlyCUDA.test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_160_is_causal_False_dropout_p_0_48_float16_scale0_cuda_float16

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
```

</details>


Test file path: `test_transformers.py`

ConnectionTimeoutError: Connect timeout for 5000ms, GET https://raw.githubusercontent.com/pytorch/pytorch/main/test/test_transformers.py -2 (connected: false, keepalive socket: false, socketHandledRequests: 1, socketHandledResponses: 0)
headers: {}

cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @clee2000
Repository: pytorch
Issue: DISABLED test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_False_dropout_p_0_22_bfloat16_scale_l1_cuda_bfloat16 (__main__.TestSDPACudaOnlyCUDA)
Labels: module: rocm,triaged,module: flaky-tests,skipped

Platforms: rocm

This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_False_dropout_p_0_22_bfloat16_scale_l1_cuda_bfloat16&suite=TestSDPACudaOnlyCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/27649304066).

Over the past 3 hours, it has been determined flaky in 2 workflow(s) with 2 failures and 2 successes.

**Debugging instructions (after clicking on the recent samples link):**
DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs.
To find relevant log snippets:
1. Click on the workflow logs linked above
2. Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
3. Grep for `test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_False_dropout_p_0_22_bfloat16_scale_l1_cuda_bfloat16`
4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.



<details><summary>Sample error message</summary>

```
Traceback (most recent call last):
  File "test_transformers.py", line 3039, in test_flash_attention_vs_math_ref_grads
    self.assertEqual(query.grad, query_ref.grad.to(query.grad.dtype),
  File "/opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/testing/_internal/common_utils.py", line 3721, in assertEqual
    raise error_metas.pop()[0].to_error(
AssertionError: Tensor-likes are not close!

Mismatched elements: 177 / 65536 (0.3%)
Greatest absolute difference: 0.0059814453125 at index (0, 3, 534, 15) (up to 0.004 allowed)
Greatest relative difference: 8448.0 at index (0, 1, 666, 9) (up to 0.016 allowed)

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_ROCM=1 python test/test_transformers.py -k TestSDPACudaOnlyCUDA.test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_False_dropout_p_0_22_bfloat16_scale_l1_cuda_bfloat16

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
```

</details>


Test file path: `test_transformers.py`

ConnectionTimeoutError: Connect timeout for 5000ms, GET https://raw.githubusercontent.com/pytorch/pytorch/main/test/test_transformers.py -2 (connected: false, keepalive socket: false, socketHandledRequests: 1, socketHandledResponses: 0)
headers: {}

cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @clee2000
Repository: pytorch
Issue: DISABLED test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_True_dropout_p_0_48_bfloat16_scale0_cuda_bfloat16 (__main__.TestSDPACudaOnlyCUDA)
Labels: module: rocm,triaged,module: flaky-tests,skipped

Platforms: rocm

This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_True_dropout_p_0_48_bfloat16_scale0_cuda_bfloat16&suite=TestSDPACudaOnlyCUDA&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/27649622705).

Over the past 3 hours, it has been determined flaky in 4 workflow(s) with 5 failures and 4 successes.

**Debugging instructions (after clicking on the recent samples link):**
DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs.
To find relevant log snippets:
1. Click on the workflow logs linked above
2. Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
3. Grep for `test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_True_dropout_p_0_48_bfloat16_scale0_cuda_bfloat16`
4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.



<details><summary>Sample error message</summary>

```
Traceback (most recent call last):
  File "test_transformers.py", line 3039, in test_flash_attention_vs_math_ref_grads
    self.assertEqual(query.grad, query_ref.grad.to(query.grad.dtype),
  File "/opt/conda/envs/py_3.8/lib/python3.8/site-packages/torch/testing/_internal/common_utils.py", line 3721, in assertEqual
    raise error_metas.pop()[0].to_error(
AssertionError: Tensor-likes are not close!

Mismatched elements: 32768 / 65536 (50.0%)
Greatest absolute difference: nan at index (0, 0, 0, 0) (up to 1.206568717956543 allowed)
Greatest relative difference: nan at index (0, 0, 0, 0) (up to 4.0 allowed)

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_ROCM=1 python test/test_transformers.py -k TestSDPACudaOnlyCUDA.test_flash_attention_vs_math_ref_grads_batch_size_1_seq_len_q_1024_seq_len_k_1024_head_dim_16_is_causal_True_dropout_p_0_48_bfloat16_scale0_cuda_bfloat16

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
```

</details>


Test file path: `test_transformers.py`

ConnectionTimeoutError: Connect timeout for 5000ms, GET https://raw.githubusercontent.com/pytorch/pytorch/main/test/test_transformers.py -2 (connected: false, keepalive socket: false, socketHandledRequests: 1, socketHandledResponses: 0)
headers: {}

cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @clee2000