sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: rust
Issue: Large const allocations no longer lead to graceful errors on aarch64
Labels: regression-from-stable-to-nightly,T-compiler,C-bug,I-prioritize

I just spun up an aarch64 (c6g.metal) instance to look at codegen, and I noticed that two of our UI tests do not pass:
```
    [ui] tests/ui/consts/large_const_alloc.rs
    [ui] tests/ui/consts/promoted_running_out_of_memory_issue-130687.rs
```
I can reduce one of the failing tests to this:
```rust
#![crate_type = "lib"]
pub const FOO: &[u8] = &[0_u8; (1 << 47) - 1];
```
If I am on an x86_64 host targeting aarch64-unknown-linux-gnu, using stable or nightly, this will immediately fail to compile with:
```
error[E0080]: evaluation of constant value failed
 --> demo.rs:2:25
  |
2 | pub const FOO: &[u8] = &[0_u8; (1 << 47) - 1];
  |                         ^^^^^^^^^^^^^^^^^^^^^ tried to allocate more memory than available to compiler

error: aborting due to 1 previous error
```
If my host is aarch64-unknown-linux-gnu using stable, I also get that diagnostic. But nightly toolchains on an aarch64 host allocate more and more memory, eventually dying with SIGKILL.


Bisection points to https://github.com/rust-lang/rust/pull/135262 as the cause, which suggests that this is a miscompile.

searched nightlies: from nightly-2024-01-01 to nightly-2025-01-23
regressed nightly: nightly-2025-01-13
searched commit range: https://github.com/rust-lang/rust/compare/eb54a50837ad4bcc9842924f27e7287ca66e294c...48a426eca9df23b24b3559e545cf88dee61d4de9
regressed commit: https://github.com/rust-lang/rust/commit/c0f6a1ce3f89a3240efe5c83839675e20f84e001

<details>
<summary>bisected with <a href='https://github.com/rust-lang/cargo-bisect-rustc'>cargo-bisect-rustc</a> v0.6.9</summary>

Host triple: aarch64-unknown-linux-gnu
Reproduce with:
```bash
cargo bisect-rustc --script script.sh --start 2024-01-01 
```
</details>

This is worth further investigation. Of course it is plausible that a change to the CI configuration would alter the build artifacts from CI, but bisecting a test failure from a stage1 and stage2 toolchain to a CI change is odd.
Repository: flutter
Issue: [FGP Kotlin conversion] Convert `FlutterExtension`
Labels: P1,team-android,triaged-android

Pull `FlutterExtension` out of `src/main/groovy/flutter.groovy` and into its own class (`src/main/Kotlin/FlutterExtension.kt`)
Repository: godot
Issue: ResourceSaver.save() not working when the resource has custom class properties
Labels: bug,topic:core

### Tested versions

Godot v4.3.stable - Arch Linux

### System information

Godot v4.3.stable - Arch Linux #1 ZEN SMP PREEMPT_DYNAMIC Sat, 18 Jan 2025 02:26:52 +0000 - X11 - Vulkan (Forward+) - dedicated AMD Radeon RX 7700 XT (RADV NAVI32) - AMD Ryzen 7 5700X 8-Core Processor (16 Threads)

### Issue description

If a resource that has export variables with custom class types those properties are not loaded properly with load() (Previously saved with ResourceSaver). Seems to be related to https://github.com/godotengine/godot/issues/32856

### Steps to reproduce

- Make 2 custom resources
- Have one of them have a variable with the other one as its type
- Save the first resource
- Load it back
- See that the custom class property didn't load correctly

### Minimal reproduction project (MRP)

[resourcesaverbugreproduction.zip](https://github.com/user-attachments/files/18526534/resourcesaverbugreproduction.zip)
Repository: excalidraw
Issue: Weird canvas blinking behaviour when changing from light to dark mode
Labels: bug,dark-theme

Here's a video of the issue:
![Image](https://github.com/user-attachments/assets/7a2d1f04-ee9e-4da8-9ae2-0a46e2ee2dae)

This issue consistently occurs when I switch from light mode to dark mode (or vice versa) and then move around any shape or group of shapes.

Refreshing the browser seems to fix it. I tested this on both Brave and Chrome on excalidraw.com, and the problem is present in both browsers.

This seems like a niche bug, but I thought it was worth reporting anyway.
Repository: flutter
Issue: [FGP Kotlin conversion] Convert `AppLinkSettings`
Labels: P1,team-android,triaged-android

Pull `AppLinkSettings` out of `src/main/groovy/flutter.groovy` and into its own class (`src/main/Kotlin/AppLinkSettings.kt`)
Repository: vscode
Issue: Paste no longer works with Electron >= 32.3.0
Labels: bug,upstream,electron,electron-32-update


Type: <b>Bug</b>

Neither right-click:paste or ctrl-v:paste work anymore for text copying. All other actions seem to work fine including copy. It is to note that right-click:paste works within the terminal window but nowhere else.
I uninstalled VScode and removed all preferences/settings yet the problem persists on a fresh build.
My only workaround so far is by using the clipboard-master extension and binding the default ctrl-v key. However, while this allows me to paste inside my files, it does not work anywhere else within VScode. 

VS Code version: Code - OSS 1.96.4 (cd4ee3b1c348a13bafd8f9ad8060705f6d4b9cba, 2025-01-17T08:53:36.849Z)
OS version: Linux x64 6.12.10-zen1-1-zen
Modes:

<details>
<summary>System Info</summary>

|Item|Value|
|---|---|
|CPUs|AMD Ryzen 7 5700X 8-Core Processor (16 x 4648)|
|GPU Status|2d_canvas: enabled<br>canvas_oop_rasterization: enabled_on<br>direct_rendering_display_compositor: disabled_off_ok<br>gpu_compositing: enabled<br>multiple_raster_threads: enabled_on<br>opengl: enabled_on<br>rasterization: enabled<br>raw_draw: disabled_off_ok<br>skia_graphite: disabled_off<br>video_decode: enabled<br>video_encode: disabled_software<br>vulkan: disabled_off<br>webgl: enabled<br>webgl2: enabled<br>webgpu: disabled_off<br>webnn: disabled_off|
|Load (avg)|1, 0, 0|
|Memory (System)|31.27GB (28.44GB free)|
|Process Argv||
|Screen Reader|no|
|VM|0%|
|DESKTOP_SESSION|xfce|
|XDG_CURRENT_DESKTOP|XFCE|
|XDG_SESSION_DESKTOP|xfce|
|XDG_SESSION_TYPE|x11|
</details>
<!-- generated by issue reporter -->
Repository: flutter
Issue: [FGP Kotlin conversion] Convert `FlutterPlugin`
Labels: P1,team-android,triaged-android

Pull `FlutterPlugin` out of `src/main/groovy/flutter.groovy` and into its own class (`src/main/Kotlin/FlutterPlugin.kt`). Also, delete `flutter.groovy`, as this will need to be the last class (it depends on all the other classes in `flutter.groovy`, and we can only have Groovy code depend on Kotlin code (not vice versa) because of limitations of Gradle.

This will likely be significantly more difficult than other pieces of `flutter.groovy`. We may need to break out functionality into some new utils classes, if it is looking intractable to do it as one conversion.
Repository: pytorch
Issue: use_const_ref_for_mutable_tensors doesn't work with out= overloads
Labels: triaged,module: pt2-dispatcher

### 🐛 Describe the bug

Repro:

```
import torch
from torch._subclasses.fake_tensor import FakeTensorMode
from torch._dispatch.python import enable_python_dispatcher
from torch.fx.experimental.symbolic_shapes import ShapeEnv, DimDynamic, SymNode
from torch import SymInt
import torch._dynamo

def f():
    shape_env = ShapeEnv()
    s0 = 5
    s1 = 6
    s2 = 7
    s3 = 3
    s4 = 10
    s5 = 2
    x = torch.randn(s0, s1, s2)
    out = torch.randn(s0, s3, s4)
    kwargs = {
        's': (s3, s4),
        'dim': (1, s5),
        'norm': 'ortho',
    }

    from torch.fx.experimental.proxy_tensor import make_fx

    r = torch._C._fft.fft_hfft2(x, **kwargs, out=out)
    assert r.shape == out.shape, r.shape

#print("real")
#f()

print("fake")
with FakeTensorMode():
    f()
```

First, we observe that fft_hfft2 uses `use_const_ref_for_mutable_tensors`:

```
- func: fft_hfft2.out(Tensor self, SymInt[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)
  use_const_ref_for_mutable_tensors: True
  python_module: fft
  variants: function
  dispatch: 
    CompositeImplicitAutograd: fft_hfft2_symint_out
```

This means the signature of fft_hfft2_symint_out is:

```
const Tensor& fft_hfft2_symint_out(
    const Tensor& self, at::OptionalSymIntArrayRef s, IntArrayRef dim,
    std::optional<std::string_view> norm, const Tensor& out) {
```

Now, consider how we implement this signature in aten/src/ATen/core/boxing/impl/boxing.h :

```
// 3.5. In-process migration to make in-place ops take and return
// const references instead.
template <class... OtherArgs>
struct BoxedKernelWrapper<
    const at::Tensor&(const at::Tensor&, OtherArgs...),
    std::enable_if_t<can_box_all<OtherArgs...>::value, void>> {
  static const at::Tensor& call(
      const BoxedKernel& boxed_kernel_func,
      const OperatorHandle& opHandle,
      DispatchKeySet dispatchKeySet,
      const at::Tensor& outArg,
      OtherArgs... otherArgs) {
    torch::jit::Stack stack = boxArgs(outArg, otherArgs...);
    boxed_kernel_func.callBoxed(opHandle, dispatchKeySet, &stack);
    TORCH_INTERNAL_ASSERT_DEBUG_ONLY(
        stack.size() == 1,
        "Boxed kernel was expected to return a single value on the stack, ",
        "but instead returned ",
        stack.size(),
        " values.");

    return outArg;
  }
};
```

Our signature will match the boxing rule for inplace arguments, because it returns a const Tensor&, and the first argument is a const Tensor&. This means we will return self, rather than out, as the return argument.

I think it is fundamentally impossible to solve this problem as there as an ambiguity as to whether or not the function signature is an out signature or an inplace one, we don't specify this in the function signature. A dedicated "Out" struct that wraps tensor reference could help. But an easy WAR is to stop using the modern const Tensor& style for these out functions.

### Versions

main

cc @chauhang @penguinwu @zou3519 @bdhirsh @yf225
Repository: flutter
Issue: [FGP Kotlin conversion] Convert `BaseFlutterTask`
Labels: P1,team-android,triaged-android

Pull `BaseFlutterTask` out of `src/main/groovy/flutter.groovy` and into its own class (`src/main/Kotlin/BaseFlutterTask.kt`).
Repository: flutter
Issue: [FGP Kotlin conversion] Convert `FlutterTask`
Labels: platform-android,c: proposal,P1,team-android,triaged-android

Pull `FlutterTask` out of `src/main/groovy/flutter.groovy` and into its own class (`src/main/Kotlin/FlutterTask.kt`). Depends on https://github.com/flutter/flutter/issues/162111.
Repository: deno
Issue: Deno compile should never include the specified output executable in itself
Labels: compile

Run this twice:

```
> deno compile --include . main.js
// ...ok...
> deno compile --include . main.js
Compile file:///V:/scratch/main.js to scratch.exe
error: Writing deno compile executable to temporary file 'scratch.exe.tmp-619f5e5217cfea84'

Caused by:
    0: Including V:\scratch\scratch.exe
    1: Reading V:\scratch\scratch.exe
    2: The system cannot find the file specified. (os error 2)
```

Version: Deno 2.1.6
Repository: go
Issue: cmd/go: GO111MODULE=off is treated as as GODEBUG=default=go1.20
Labels: NeedsInvestigation,BugReport

### Go version

go version go1.23.4 linux/amd64

### Output of `go env` in your module/workspace:

```shell
GO111MODULE=''
GOARCH='amd64'
GOBIN=''
GOCACHE='/root/.cache/go-build'
GOENV='/root/.config/go/env'
GOEXE=''
GOEXPERIMENT=''
GOFLAGS=''
GOHOSTARCH='amd64'
GOHOSTOS='linux'
GOINSECURE=''
GOMODCACHE='/go/pkg/mod'
GONOPROXY=''
GONOSUMDB=''
GOOS='linux'
GOPATH='/go'
GOPRIVATE=''
GOPROXY='https://proxy.golang.org,direct'
GOROOT='/usr/local/go'
GOSUMDB='sum.golang.org'
GOTMPDIR=''
GOTOOLCHAIN='local'
GOTOOLDIR='/usr/local/go/pkg/tool/linux_amd64'
GOVCS=''
GOVERSION='go1.23.4'
GODEBUG=''
GOTELEMETRY='local'
GOTELEMETRYDIR='/root/.config/go/telemetry'
GCCGO='gccgo'
GOAMD64='v1'
AR='ar'
CC='gcc'
CXX='g++'
CGO_ENABLED='1'
GOMOD='/src/go.mod'
GOWORK=''
CGO_CFLAGS='-O2 -g'
CGO_CPPFLAGS=''
CGO_CXXFLAGS='-O2 -g'
CGO_FFLAGS='-O2 -g'
CGO_LDFLAGS='-O2 -g'
PKG_CONFIG='pkg-config'
GOGCCFLAGS='-fPIC -m64 -pthread -Wl,--no-gc-sections -fmessage-length=0 -ffile-prefix-map=/tmp/go-build2806843945=/tmp/go-build -gno-record-gcc-switches'
```

### What did you do?

i am running an application which uses a net/http.ServeMux with pattern features introduced with golang1.22

(e.g. `http.HandleFunc("/{$}" ...` to handle only requests for `GET / HTTP/XXX`)

building the application with `GO111MODULE=off` causes the application to respond with `404 page not found` for requests which would otherwise be handled when running the application with `GO111MODULE=on`.

i have provided a [simple reproducer](https://go.dev/play/p/BL1AWUIYUYK)

### What did you see happen?

> GO111MODULE=off go run .

in another terminal
> curl -s 'http://localhost:8080/%7B%24%7D'
> ok
> curl -s 'http://localhost:8080/{$}'
> 404 page not found
> curl -s http://localhost:8080/
> 404 page not found

> GO111MODULE=on go run .

in another terminal
> curl -s 'http://localhost:8080/%7B%24%7D'
> 404 page not found
> curl -s 'http://localhost:8080/{$}'
> 404 page not found
> curl -s http://localhost:8080/
> ok

the request against the `/{$}` path is expected to yield a 404; i have included it for the sake of completeness

`%7B%24%7D` is the URL encoded notation of `{$}`

### What did you expect to see?

i was expecting the golang1.22 net/http changes to be available regardless of the use of `GO111MODULE=off`. AFAIK this environment variable affects the code lookup and the compiler's expectations about the project layout and location. i did not expect it to downgrade/disable any language features.
Repository: vscode
Issue: Code not being read correctly
Labels: info-needed,terminal

The terminal keeps returning a result from a code block done previously . It isn't reading the next  new code bloc 

Version: 1.96.3
Commit: 91fbdddc47bc9c09064bf7acf133d22631cbf083
User Agent: Mozilla/5.0 (X11; CrOS x86_64 14541.0.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36
Embedder: codespaces

<!-- generated by web issue reporter -->
Repository: pytorch
Issue: Module.to() fail in dynamo when swap_module_params_on_conversion is true
Labels: triaged,oncall: pt2,module: dynamo

### 🐛 Describe the bug

Repro:

```
import torch
from torch import nn

torch.__future__.set_swap_module_params_on_conversion(True)

@torch.compile
def use_emb():
    emb = nn.Embedding(16, 8)
    emb.weight.grad = torch.randn_like(emb.weight)

    emb.to(dtype=torch.bfloat16)
    # emb.weight.to(dtype=torch.bfloat16)
    # emb.weight.grad.to(dtype=torch.bfloat16)

use_emb()
```

Error messages:

```
(pytorch) [shunting@devgpu011.cln5 ~/ws/pytorch (reset-dynamo-cache)]$ python ~/x.py
Compiled module path: /tmp/torchinductor_shunting/23/c23zg53biko6duc2zqhiic2qwydrsnct3cjd6izouxtkfa4xathn.py
Traceback (most recent call last):
  File "/home/shunting/ws/pytorch/torch/nn/modules/module.py", line 958, in _apply
    torch.utils.swap_tensors(param, param_applied)
  File "/home/shunting/ws/pytorch/torch/utils/__init__.py", line 51, in swap_tensors
    raise RuntimeError("Cannot swap t1 because it has weakref associated with it")
RuntimeError: Cannot swap t1 because it has weakref associated with it

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/shunting/x.py", line 15, in <module>
    use_emb()
  File "/home/shunting/ws/pytorch/torch/_dynamo/eval_frame.py", line 566, in _fn
    return fn(*args, **kwargs)
  File "/home/shunting/x.py", line 8, in use_emb
    emb = nn.Embedding(16, 8)
  File "/home/shunting/x.py", line 11, in torch_dynamo_resume_in_use_emb_at_8
    emb.to(dtype=torch.bfloat16)
  File "/home/shunting/ws/pytorch/torch/nn/modules/module.py", line 1353, in to
    return self._apply(convert)
  File "/home/shunting/ws/pytorch/torch/nn/modules/module.py", line 962, in _apply
    raise RuntimeError(
RuntimeError: _apply(): Couldn't swap Embedding.weight
```


Most test failures exposed by https://github.com/pytorch/pytorch/pull/145306/files should have similar error stack. 



Here is a even simpler repro without nn.Module:

```
import torch
from torch import nn
import os

x = torch.randn(5, requires_grad=True)

if os.environ.get("DBG") == "1":
    import weakref
    g_id_x = id(x)

    orig_ref = weakref.ref

    class MyRef(orig_ref):
        def __init__(self, obj, *args, **kwargs):
            if id(obj) == g_id_x: breakpoint()
            super().__init__(obj, *args, **kwargs)

    weakref.ref = MyRef

@torch.compile
def f(x):
    y = x.to(dtype=torch.bfloat16)
    torch.utils.swap_tensors(x, y)

f(x)
```

Dynamo would keep weakref to tensors when interpreting byte-code or creating guards. `torch.utils.swap_tensors` will fail if there are weakref's to input tensors.

### Versions

.

cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @amjames
Repository: electron
Issue: Focus handling tests fail on Windows 32-bit
Labels: component/webcontents,upgrade-follow-up

`focus handling` tests have regressed on Windows 32-bit in the Chromium roll (https://github.com/electron/electron/pull/45172) [133.0.6920.0..134.0.6968.0](https://chromium.googlesource.com/chromium/src/+log/133.0.6920.0..134.0.6968.0?n=10000&pretty=fuller)

https://github.com/electron/electron/actions/runs/12932282696/job/36083022633#step:18:2050
```
not ok 1465 focus handling a TAB press moves focus to the next focusable item
  focus should've moved to the webview's element-2, it's instead in BUTTON-wv-element-1: expected 'BUTTON-wv-element-1' to equal 'BUTTON-wv-element-2'
  AssertionError: focus should've moved to the webview's element-2, it's instead in BUTTON-wv-element-1: expected 'BUTTON-wv-element-1' to equal 'BUTTON-wv-element-2'
      at Context.<anonymous> (electron\spec\chromium-spec.ts:159:35)
[1956:0123/195544.605:WARNING:render_input_router.cc(41)] Input request on unbound interface
[1956:0123/195615.443:WARNING:render_input_router.cc(41)] Input request on unbound interface
[1956:0123/195616.297:WARNING:render_input_router.cc(41)] Input request on unbound interface
[1956:0123/195647.125:WARNING:render_input_router.cc(41)] Input request on unbound interface
not ok 1466 focus handling a SHIFT + TAB press moves focus to the previous focusable item
  focus should've moved to the webview's element-1, it's instead in BUTTON-wv-element-2: expected 'BUTTON-wv-element-2' to equal 'BUTTON-wv-element-1'
  AssertionError: focus should've moved to the webview's element-1, it's instead in BUTTON-wv-element-2: expected 'BUTTON-wv-element-2' to equal 'BUTTON-wv-element-1'
      at Context.<anonymous> (electron\spec\chromium-spec.ts:194:35)
```

https://github.com/electron/electron/blob/aafb1ba72c6abc66c81bd530658d3642f9a34f71/spec/chromium-spec.ts#L101-L212
Repository: PowerToys
Issue: Ability to copy workspaces
Labels: Idea-Enhancement,Product-Workspaces

### Description of the new feature / enhancement

An interaction that would allow me to copy an existing workspace configuration e.g. a "duplicate" button.

Alternatively, the ability to "pass through" parameters from the shortcut command line to individual apps with some kind of variable expansion feature.

### Scenario when this would be used?

For my use case I have a number of workspaces to create, they are all identical bar the command line parameter sent to one of the applications.

### Supporting information

_No response_
Repository: vscode
Issue: Tooltips cloud layer is under mouse cursor, by this is not visible very good.
Labels: info-needed


Type: <b>Bug</b>

Tooltips cloud layer is under mouse cursor, by this is not visible very good.
Tooltips should be above cursor indicator.

VS Code version: Code 1.96.4 (cd4ee3b1c348a13bafd8f9ad8060705f6d4b9cba, 2025-01-16T00:16:19.038Z)
OS version: Windows_NT x64 10.0.22631
Modes:


<!-- generated by issue reporter -->
Repository: tensorflow
Issue: TensorFlow warning shows whenever importing it
Labels: stat:awaiting response,type:bug,2.18.rc

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

No

### Source

source

### TensorFlow version

v2.18.0-rc2-4-g6550e4bd802

### Custom code

No

### OS platform and distribution

Linux Ubuntu 24.10 x86_64

### Mobile device

_No response_

### Python version

3.12.8

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

CUDA:12.6

### GPU model and memory

_No response_

### Current behavior?

`cuFFT`, `cuDNN` and `cuBLAS` warnings showing after importing `TensorFlow`

- OS: Ubuntu 24.10 x86_64
- Host: G5 5590
- Kernel: 6.11.0-13-generic
- CPU: Intel i7-9750H (12) @ 4.500GHz
- GPU: NVIDIA GeForce GTX 1650 Mobile / Max-Q
- GPU: Intel CoffeeLake-H GT2 [UHD Graphics 630]
> whenever running the following code it gives that warning also it outputs the predicted output but after the warning:
```python
import tensorflow as tf
print(tf.config.list_physical_devices('GPU'))
```
> output:
```
2025-01-23 21:08:06.468437: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1737659286.484845  763412 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1737659286.489647  763412 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2025-01-23 21:08:06.505984: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.

[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
```
> also i know that for that warning (`cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.`) i must rebuild the tensor-flow from binaries enabling the AVX2 and FMA instructions but what about the others?

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
print(tf.config.list_physical_devices('GPU'))
```

### Relevant log output

```shell

```
Repository: pytorch
Issue: [RFC] Cuda support matrix for Release 2.7
Labels: oncall: releng

Similar to : https://github.com/pytorch/pytorch/issues/138609

Opening this RFC to discuss CUDA version support for future PyTorch release 2.7:

Migration to CUDA 12.8 is planned for PyTorch Release 2.7.

Option 1 - CUDA 11.8 and CUDA 12.6 and 12.8
CUDA 11.8, CUDNN 9.1.0.70 - Same as Previous Release 2.6. No changes to CUDA 11.8 - Legacy version
CUDA 12.6 CUDNN 9.x - Version Released to Pypi - Stable version
CUDA 12.8 CUDNN 9.x - New Experimental version

Option 2 
CUDA 12.6 CUDNN 9.x - Version Released to Pypi - Stable version
CUDA 12.8 CUDNN 9.x  - New Experimental version
 

cc @ptrblck @msaroufim @malfet @nWEIdia @tinglvv @Skylion007 @albanD @ngimel 



### Versions

2.7.0