helloadhavan/github_issues huggingface dataset:
Repository: electron/electron
Pull request: fix: white window flicker on window creation

Backport of #47022

See that PR for details.


Notes: Fixed an issue where the window flickers with either a light or dark color before loading the desired background color.


Changed files:
filename: shell/browser/native_window_views.cc
patch: @@ -38,6 +38,7 @@
 #include "shell/common/options_switches.h"
 #include "ui/aura/window_tree_host.h"
 #include "ui/base/hit_test.h"
+#include "ui/compositor/compositor.h"
 #include "ui/display/screen.h"
 #include "ui/gfx/image/image.h"
 #include "ui/gfx/native_widget_types.h"
@@ -1248,6 +1249,7 @@ void NativeWindowViews::SetBackgroundColor(SkColor background_color) {
     DeleteObject((HBRUSH)previous_brush);
   InvalidateRect(GetAcceleratedWidget(), nullptr, 1);
 #endif
+  GetWidget()->GetCompositor()->SetBackgroundColor(background_color);
 }
 
 void NativeWindowViews::SetHasShadow(bool has_shadow) {

filename: shell/browser/ui/win/electron_desktop_window_tree_host_win.cc
patch: @@ -23,6 +23,20 @@ ElectronDesktopWindowTreeHostWin::ElectronDesktopWindowTreeHostWin(
 
 ElectronDesktopWindowTreeHostWin::~ElectronDesktopWindowTreeHostWin() = default;
 
+bool ElectronDesktopWindowTreeHostWin::ShouldUpdateWindowTransparency() const {
+  // If transparency is updated for an opaque window before widget init is
+  // completed, the window flickers white before the background color is applied
+  // and we don't want that. We do, however, want translucent windows to be
+  // properly transparent, so ensure it gets updated in that case.
+  if (!widget_init_done_ && !native_window_view_->IsTranslucent())
+    return false;
+  return views::DesktopWindowTreeHostWin::ShouldUpdateWindowTransparency();
+}
+
+void ElectronDesktopWindowTreeHostWin::OnWidgetInitDone() {
+  widget_init_done_ = true;
+}
+
 bool ElectronDesktopWindowTreeHostWin::PreHandleMSG(UINT message,
                                                     WPARAM w_param,
                                                     LPARAM l_param,

filename: shell/browser/ui/win/electron_desktop_window_tree_host_win.h
patch: @@ -31,6 +31,8 @@ class ElectronDesktopWindowTreeHostWin : public views::DesktopWindowTreeHostWin,
 
  protected:
   // views::DesktopWindowTreeHostWin:
+  void OnWidgetInitDone() override;
+  bool ShouldUpdateWindowTransparency() const override;
   bool PreHandleMSG(UINT message,
                     WPARAM w_param,
                     LPARAM l_param,
@@ -51,6 +53,7 @@ class ElectronDesktopWindowTreeHostWin : public views::DesktopWindowTreeHostWin,
  private:
   raw_ptr<NativeWindowViews> native_window_view_;  // weak ref
   std::optional<bool> force_should_paint_as_active_;
+  bool widget_init_done_ = false;
 };
 
 }  // namespace electron
Repository: nodejs/node
Pull request: doc: add WDYT to glossary

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please add the `notable-change` label.

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    have the right to submit it under the open source license
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    license and I have the right under that license to submit that
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Add `WDYT` to the `glossary.md` file.

Changed files:
filename: glossary.md
patch: @@ -99,6 +99,7 @@ This file documents various terms and definitions used throughout the Node.js co
   various aspects of the web ecosystem.
 * **WASI**: [Web Assembly System Interface][] - Interface for WebAssembly.
 * **WASM**: Web Assembly - Binary instruction format for a stack-based virtual machine.
+* **WDYT**: What Do You Think?
 * **WG**: Working Group - Autonomous teams in the project with specific focus areas.
 * **WHATWG**: [Web Hypertext Application Technology Working Group][] - Community developing web standards.
 * **WIP**: Work In Progress - Unfinished work that may be worth an early look.
Repository: ollama/ollama
Pull request: stub generate outputs for lint


Changed files:
filename: .github/workflows/test.yaml
patch: @@ -45,7 +45,6 @@ jobs:
           path: |
             llm/llama.cpp/build/**/lib/*
   lint:
-    needs: generate
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
@@ -69,10 +68,19 @@ jobs:
         with:
           go-version: '1.21'
           cache: false
-      - uses: actions/download-artifact@v4
-        with:
-          name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
-          path: llm/llama.cpp/build
+      - run: |
+          mkdir -p llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/
+          touch llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/stub.so
+        if: ${{ startsWith(matrix.os, 'ubuntu-') }}
+      - run: |
+          mkdir -p llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/
+          touch llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/stub.dylib
+          touch llm/llama.cpp/ggml-metal.metal
+        if: ${{ startsWith(matrix.os, 'macos-') }}
+      - run: |
+          mkdir -p llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/
+          touch llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/stub.dll
+        if: ${{ startsWith(matrix.os, 'windows-') }}
       - uses: golangci/golangci-lint-action@v3
   test:
     needs: generate
Repository: ollama/ollama
Pull request: fix: allow extension origins (still needs explicit listing), fixes #1686


Changed files:
filename: server/routes.go
patch: @@ -857,6 +857,7 @@ func (s *Server) GenerateRoutes() http.Handler {
 
 	config := cors.DefaultConfig()
 	config.AllowWildcard = true
+	config.AllowBrowserExtensions = true
 
 	config.AllowOrigins = origins
 	for _, allowOrigin := range defaultAllowOrigins {
Repository: ggml-org/llama.cpp
Pull request: sycl : permuted mul_mat through oneMKL


- [x] I have read the [contributing guidelines](https://github.com/ggerganov/llama.cpp/blob/master/CONTRIBUTING.md)
- Self-reported review complexity:
  - [ ] Low
  - [x] Medium
  - [ ] High

-----

Adds support for the test-cases added in #10021 through oneMKL.
The device shows no regressions in discrete GPUs (tested on A100 and Data Max 1100)

This PR fixes the failing MUL_MAT tests for the sycl backend.


Changed files:
filename: ggml/src/ggml-sycl/ggml-sycl.cpp
patch: @@ -3447,8 +3447,15 @@ static void ggml_sycl_mul_mat(ggml_backend_sycl_context & ctx, const ggml_tensor
         use_dequantize_mul_mat_vec = use_dequantize_mul_mat_vec && !use_mul_mat_vec_q;
 
     if (!split && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) {
-        // KQ single-batch
-        ggml_sycl_mul_mat_vec_p021(ctx, src0, src1, dst);
+        // TODO: Refactor and cleanup of mul mat dispatching.
+        if (src0->ne[3] == 1 && src1->ne[3] == 1) {
+            // KQ single-batch
+            // mmv p021 was specific for these dimensions
+            ggml_sycl_mul_mat_vec_p021(ctx, src0, src1, dst);
+        } else {
+            // The kernel from the if path is faster for that specific case, but does not support all mul mats.
+            ggml_sycl_mul_mat_batched_sycl(ctx, src0, src1, dst);
+        }
     } else if (!split && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) {
         // KQV single-batch
         ggml_sycl_mul_mat_vec_nc(ctx, src0, src1, dst);
Repository: vercel/next.js
Pull request: fix: correct typo 'incomming' to 'incoming' in with-mqtt-js example

### What?
This PR fixes a typo in the `with-mqtt-js` example (`examples/with-mqtt-js/app/page.tsx`):
all occurrences of "incomming" have been corrected to "incoming" in variables, refs, and JSX headings.

### Why?
The previous spelling "incomming" is incorrect in English. Correcting it improves readability and professionalism in the example code.

### How?
- Renamed `incommingMessages` → `incomingMessages`
- Renamed `setIncommingMessages` → `setIncomingMessages`
- Renamed `incommingMessageHandlers` → `incomingMessageHandlers`
- Updated JSX headings and references accordingly

Changed files:
filename: examples/with-mqtt-js/app/page.tsx
patch: @@ -5,18 +5,15 @@ import type { MqttClient } from "mqtt";
 import useMqtt from "@/lib/useMqtt";
 
 export default function Home() {
-  const [incommingMessages, setIncommingMessages] = useState<any[]>([]);
+  const [incomingMessages, setIncomingMessages] = useState<any[]>([]);
   const addMessage = (message: any) => {
-    setIncommingMessages((incommingMessages) => [
-      ...incommingMessages,
-      message,
-    ]);
+    setIncomingMessages((incomingMessages) => [...incomingMessages, message]);
   };
   const clearMessages = () => {
-    setIncommingMessages(() => []);
+    setIncomingMessages(() => []);
   };
 
-  const incommingMessageHandlers = useRef([
+  const incomingMessageHandlers = useRef([
     {
       topic: "topic1",
       handler: (msg: string) => {
@@ -36,7 +33,7 @@ export default function Home() {
       password: process.env.NEXT_PUBLIC_MQTT_PASSWORD,
       clientId: process.env.NEXT_PUBLIC_MQTT_CLIENTID,
     },
-    topicHandlers: incommingMessageHandlers.current,
+    topicHandlers: incomingMessageHandlers.current,
     onConnectedHandler: (client) => setMqttClient(client),
   });
 
@@ -52,11 +49,11 @@ export default function Home() {
   return (
     <div>
       <h2>Subscribed Topics</h2>
-      {incommingMessageHandlers.current.map((i) => (
+      {incomingMessageHandlers.current.map((i) => (
         <p key={Math.random()}>{i.topic}</p>
       ))}
-      <h2>Incomming Messages:</h2>
-      {incommingMessages.map((m) => (
+      <h2>Incoming Messages:</h2>
+      {incomingMessages.map((m) => (
         <p key={Math.random()}>{m.payload.toString()}</p>
       ))}
       <button onClick={() => publishMessages(mqttClientRef.current)}>
Repository: huggingface/transformers
Pull request: [torchao safetensors] renaming get_state_dict function

**Summary**

Renaming `get_state_dict()` method in `hf_quantizer` to `get_state_dict_and_metadata()` and updating functionality to return metadata along with state_dict. 

This reduces confusion related to enabling torchao safetensor support built out in [this PR](https://github.com/huggingface/transformers/pull/40735). 

**Test Plan** 

`python -m pytest ./tests/quantization`

Changed files:
filename: src/transformers/modeling_utils.py
patch: @@ -4015,8 +4015,11 @@ def save_pretrained(
             repo_id = self._create_repo(repo_id, **kwargs)
             files_timestamps = self._get_files_timestamps(save_directory)
 
+        metadata = {}
         if hf_quantizer is not None:
-            state_dict = hf_quantizer.get_state_dict(self)
+            state_dict, metadata = hf_quantizer.get_state_dict_and_metadata(self, safe_serialization)
+        metadata["format"] = "pt"
+
         # Only save the model itself if we are using distributed training
         model_to_save = unwrap_model(self)
         # save the string version of dtype to the config, e.g. convert torch.float32 => "float32"
@@ -4294,7 +4297,7 @@ def save_pretrained(
             if safe_serialization:
                 # At some point we will need to deal better with save_function (used for TPU and other distributed
                 # joyfulness), but for now this enough.
-                safe_save_file(shard, os.path.join(save_directory, shard_file), metadata={"format": "pt"})
+                safe_save_file(shard, os.path.join(save_directory, shard_file), metadata=metadata)
             else:
                 save_function(shard, os.path.join(save_directory, shard_file))
 

filename: src/transformers/quantizers/base.py
patch: @@ -338,9 +338,9 @@ def is_compileable(self) -> bool:
         """Flag indicating whether the quantized model can be compiled"""
         return False
 
-    def get_state_dict(self, model):
-        """Get state dict. Useful when we need to modify a bit the state dict due to quantization"""
-        return None
+    def get_state_dict_and_metadata(self, model, safe_serialization=False):
+        """Get state dict and metadata. Useful when we need to modify a bit the state dict due to quantization"""
+        return None, {}
 
     @abstractmethod
     def _process_model_before_weight_loading(self, model, **kwargs): ...

filename: src/transformers/quantizers/quantizer_mxfp4.py
patch: @@ -379,7 +379,7 @@ def update_param_name(self, param_name: str) -> str:
                 return param_name.replace("down_proj", "down_proj_blocks")
         return param_name
 
-    def get_state_dict(self, model):
+    def get_state_dict_and_metadata(self, model):
         from ..integrations import Mxfp4GptOssExperts
 
         state_dict = model.state_dict()
@@ -411,7 +411,8 @@ def get_state_dict(self, model):
                     ).transpose(-1, -2)
                 )
 
-        return state_dict
+        metadata = {}
+        return state_dict, metadata
 
     def is_serializable(self, safe_serialization=None):
         return True
Repository: ggml-org/llama.cpp
Pull request: sycl : offload of get_rows set to false


- [x] I have read the [contributing guidelines](https://github.com/ggerganov/llama.cpp/blob/master/CONTRIBUTING.md)
- Self-reported review complexity:
  - [x] Low
  - [ ] Medium
  - [ ] High

----

#10133 changes changed get_rows from false to true. I've detected a big regression for  quantizations that support get_rows (llama3 Q8_0 for example).

@uniartisan Could you share more information of the device you used for offloading (where you saw increased performance)? Or did this just improve testing?

An example of regression:

| model                          |       size |     params | backend    | ngl |    sm | mmap |          test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | ----: | ---: | ------------: | -------------------: |
| llama 8B Q8_0                  |   7.95 GiB |     8.03 B | SYCL       |  99 |  none |    0 |         pp512 |      1340.34 ± 21.74 |
| llama 8B Q8_0                  |   7.95 GiB |     8.03 B | SYCL       |  99 |  none |    0 |         tg128 |         88.64 ± 0.05 |

build: fab5d30f (4143)

With this revert:

| model                          |       size |     params | backend    | ngl |    sm | mmap |          test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | ----: | ---: | ------------: | -------------------: |
| llama 8B Q8_0                  |   7.95 GiB |     8.03 B | SYCL       |  99 |  none |    0 |         pp512 |      5777.93 ± 26.32 |
| llama 8B Q8_0                  |   7.95 GiB |     8.03 B | SYCL       |  99 |  none |    0 |         tg128 |         89.31 ± 0.03 |

build: f4c4ce37



Changed files:
filename: ggml/src/ggml-sycl/ggml-sycl.cpp
patch: @@ -4493,7 +4493,7 @@ static bool ggml_backend_sycl_device_supports_buft(ggml_backend_dev_t dev, ggml_
 static int64_t get_op_batch_size(const ggml_tensor * op) {
     switch (op->op) {
         case GGML_OP_GET_ROWS:
-            return op->ne[1]; // this will increse the speed of prefill in test
+            return 0;
         case GGML_OP_MUL_MAT:
             return op->ne[1];
         case GGML_OP_MUL_MAT_ID:
Repository: ollama/ollama
Pull request: Set a default version using git describe

If a VERSION is not specified, this will generate a version string that represents the state of the repo.  For example `0.1.21-12-gffaf52e-dirty` representing 12 commits away from 0.1.21 tag, on commit gffaf52e and the tree is dirty.

Changed files:
filename: scripts/build_darwin.sh
patch: @@ -2,7 +2,7 @@
 
 set -e
 
-export VERSION=${VERSION:-0.0.0}
+export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
 export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version=$VERSION\" \"-X=github.com/jmorganca/ollama/server.mode=release\"'"
 
 mkdir -p dist

filename: scripts/build_docker.sh
patch: @@ -2,7 +2,7 @@
 
 set -eu
 
-export VERSION=${VERSION:-0.0.0}
+export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
 export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version=$VERSION\" \"-X=github.com/jmorganca/ollama/server.mode=release\"'"
 
 docker build \

filename: scripts/build_linux.sh
patch: @@ -2,7 +2,7 @@
 
 set -eu
 
-export VERSION=${VERSION:-0.0.0}
+export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
 export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version=$VERSION\" \"-X=github.com/jmorganca/ollama/server.mode=release\"'"
 
 BUILD_ARCH=${BUILD_ARCH:-"amd64 arm64"}
Repository: ggml-org/llama.cpp
Pull request: llama-bench: fixed size of fields to correctly map to values

https://github.com/ggml-org/llama.cpp/pull/13096 Introduced some changes to llama-bench that have been causing segfaults to the users due to an incorrect definition of the test fields (see https://github.com/ggml-org/llama.cpp/issues/13169) 

I don't have expertise here so if this it not the cause of the issue or there is a better way to do it, happy to get some feedback.

Pinging @JohannesGaessler and @slaren , since they reviewed the original PR. (@thevishalagarwal  for visibility as well) 

Changed files:
filename: examples/llama-bench/llama-bench.cpp
patch: @@ -1133,8 +1133,6 @@ struct test {
             "build_commit", "build_number", "cpu_info",       "gpu_info",   "backends",     "model_filename",
             "model_type",   "model_size",   "model_n_params", "n_batch",    "n_ubatch",     "n_threads",
             "cpu_mask",     "cpu_strict",   "poll",           "type_k",     "type_v",       "n_gpu_layers",
-            "split_mode",   "main_gpu",     "no_kv_offload",  "flash_attn", "tensor_split", "use_mmap",
-            "embeddings",   "n_prompt",     "n_gen",          "n_depth",    "test_time",    "avg_ns",
             "split_mode",   "main_gpu",     "no_kv_offload",  "flash_attn", "tensor_split", "tensor_buft_overrides",
             "use_mmap",     "embeddings",   "n_prompt",       "n_gen",      "n_depth",      "test_time",
             "avg_ns",       "stddev_ns",    "avg_ts",         "stddev_ts",
Repository: nodejs/node
Pull request: doc: add path.join and path.normalize clarification

We've had inconsistencies in how we handle path manipulation function issues:
- Sometimes we've issued CVEs for path-related issues
- Sometimes we've fixed them without CVEs

This update to SECURITY.md clarifies our position by explicitly stating that:
1. Node.js path manipulation functions trust their input
2. It's the developer's responsibility to sanitize path inputs
3. Issues stemming from unsanitized path inputs don't warrant CVEs

cc: @nodejs/security-wg @nodejs/security-triage @nodejs/tsc 

Changed files:
filename: SECURITY.md
patch: @@ -179,6 +179,11 @@ then untrusted input must not lead to arbitrary JavaScript code execution.
   See <https://nodejs.org/api/modules.html#all-together>.
 * The `node:wasi` module does not currently provide the comprehensive file
   system security properties provided by some WASI runtimes.
+* The execution path is trusted. Additionally, Node.js path manipulation functions
+  such as `path.join()` and `path.normalize()` trust their input. Reports about issues
+  related to these functions that rely on unsanitized input are not considered vulnerabilities
+  requiring CVEs, as it's the user's responsibility to sanitize path inputs according to
+  their security requirements.
 
 Any unexpected behavior from the data manipulation from Node.js Internal
 functions may be considered a vulnerability if they are exploitable via
Repository: huggingface/transformers
Pull request: Adding activation kernels

# What does this PR do?

Adds GeLU activation kernels from https://huggingface.co/kernels-community/activation, to use them we simply need to pass `use_kernels=True`

Here are Some benchmarks comparing the `activation kernels` perfs with a `torch.compile` implementation

<img width="959" height="378" alt="Screenshot 2025-09-16 at 10 30 52" src="https://github.com/user-attachments/assets/2e0d4aac-4972-4a3b-88f9-33278d45ec3c" />


Changed files:
filename: src/transformers/activations.py
patch: @@ -18,6 +18,7 @@
 import torch
 from torch import Tensor, nn
 
+from .integrations.hub_kernels import use_kernel_forward_from_hub
 from .utils import logging
 from .utils.import_utils import is_torchdynamo_compiling
 
@@ -38,6 +39,7 @@ def forward(self, input: Tensor) -> Tensor:
         return nn.functional.gelu(input, approximate="tanh")
 
 
+@use_kernel_forward_from_hub("NewGELU")
 class NewGELUActivation(nn.Module):
     """
     Implementation of the GELU activation function currently in Google BERT repo (identical to OpenAI GPT). Also see
@@ -70,6 +72,7 @@ def forward(self, input: Tensor) -> Tensor:
         return self.act(input)
 
 
+@use_kernel_forward_from_hub("FastGELU")
 class FastGELUActivation(nn.Module):
     """
     Applies GELU approximation that is slower than QuickGELU but more accurate. See: https://github.com/hendrycks/GELUs
@@ -79,6 +82,7 @@ def forward(self, input: Tensor) -> Tensor:
         return 0.5 * input * (1.0 + torch.tanh(input * 0.7978845608 * (1.0 + 0.044715 * input * input)))
 
 
+@use_kernel_forward_from_hub("QuickGELU")
 class QuickGELUActivation(nn.Module):
     """
     Applies GELU approximation that is fast but somewhat inaccurate. See: https://github.com/hendrycks/GELUs

filename: src/transformers/integrations/hub_kernels.py
patch: @@ -84,6 +84,33 @@
                 )
             },
         },
+        "FastGELU": {
+            "cuda": {
+                Mode.INFERENCE | Mode.TORCH_COMPILE: LayerRepository(
+                    repo_id="kernels-community/activation",
+                    layer_name="FastGELU",
+                    version=">=0.0.4,<0.1.0",
+                )
+            }
+        },
+        "QuickGELU": {
+            "cuda": {
+                Mode.INFERENCE | Mode.TORCH_COMPILE: LayerRepository(
+                    repo_id="kernels-community/activation",
+                    layer_name="QuickGELU",
+                    version=">=0.0.4,<0.1.0",
+                )
+            }
+        },
+        "NewGELU": {
+            "cuda": {
+                Mode.INFERENCE | Mode.TORCH_COMPILE: LayerRepository(
+                    repo_id="kernels-community/activation",
+                    layer_name="NewGELU",
+                    version=">=0.0.4,<0.1.0",
+                )
+            }
+        },
     }
 
     register_kernel_mapping(_KERNEL_MAPPING)