helloadhavan/github_issues huggingface dataset:
Repository: huggingface/transformers
Pull request: Delete batch_split from EncoderDecoderCache

# What does this PR do?

This EncoderDecoderCache.batch_split is a remaining method from previous refactoring and is not used by other code. 

Changed files:
filename: src/transformers/cache_utils.py
patch: @@ -1262,20 +1262,6 @@ def crop(self, maximum_length: int):
         self.check_dynamic_cache(self.crop.__name__)
         self.self_attention_cache.crop(maximum_length)
 
-    def batch_split(self, full_batch_size: int, split_size: int) -> "list[EncoderDecoderCache]":
-        """
-        Split the current instance into a list of `DynamicCache` by the batch size. This will be used by
-        `_split_model_inputs()` in `generation.utils`
-        """
-        self.check_dynamic_cache(self.batch_split.__name__)
-        self_attention_cache = self.self_attention_cache.batch_split(full_batch_size, split_size)
-        cross_attention_cache = self.cross_attention_cache.batch_split(full_batch_size, split_size)
-
-        out = []
-        for self_attn, cross_attn in zip(self_attention_cache, cross_attention_cache):
-            out.append(EncoderDecoderCache(self_attn, cross_attn))
-        return out
-
     def batch_repeat_interleave(self, repeats: int):
         """Repeat the cache `repeats` times in the batch dimension. Used in contrastive search (on the Hub)."""
         self.check_dynamic_cache(self.batch_repeat_interleave.__name__)
Repository: electron/electron
Pull request: fix: apply `zoomFactor` from `setWindowOpenHandler` to `window.open()` windows

Backport of #49886

See that PR for details.


Notes: Fixed an issue where setting `zoomFactor` in `setWindowOpenHandler`'s `overrideBrowserWindowOptions` had no effect on windows opened via `window.open()`.

Changed files:
filename: shell/browser/api/electron_api_web_contents.cc
patch: @@ -4742,6 +4742,19 @@ gin_helper::Handle<WebContents> WebContents::CreateFromWebPreferences(
       existing_preferences->SetFromDictionary(web_preferences_dict);
       web_contents->SetBackgroundColor(
           existing_preferences->GetBackgroundColor());
+
+      double zoom_factor;
+      if (web_preferences.Get(options::kZoomFactor, &zoom_factor)) {
+        auto* zoom_controller = WebContentsZoomController::FromWebContents(
+            web_contents->web_contents());
+        if (zoom_controller) {
+          zoom_controller->SetDefaultZoomFactor(zoom_factor);
+          // Also set the current zoom level immediately, since the page
+          // has already navigated by the time we wrap the webContents.
+          zoom_controller->SetZoomLevel(
+              blink::ZoomFactorToZoomLevel(zoom_factor));
+        }
+      }
     }
   } else {
     // Create one if not.

filename: spec/api-browser-window-spec.ts
patch: @@ -3977,6 +3977,28 @@ describe('BrowserWindow module', () => {
         expect(webPreferences!.contextIsolation).to.equal(false);
       });
 
+      it('should apply zoomFactor from setWindowOpenHandler overrideBrowserWindowOptions', async () => {
+        const w = new BrowserWindow({
+          show: false,
+          webPreferences: {
+            sandbox: true
+          }
+        });
+
+        w.webContents.setWindowOpenHandler(() => ({
+          action: 'allow',
+          overrideBrowserWindowOptions: {
+            webPreferences: {
+              zoomFactor: 2.0
+            }
+          }
+        }));
+        w.loadFile(path.join(fixtures, 'api', 'new-window.html'));
+        const [childWindow] = await once(w.webContents, 'did-create-window') as [BrowserWindow, any];
+        await once(childWindow.webContents, 'did-finish-load');
+        expect(childWindow.webContents.getZoomFactor()).to.be.closeTo(2.0, 0.1);
+      });
+
       it('should set ipc event sender correctly', async () => {
         const w = new BrowserWindow({
           show: false,
Repository: ollama/ollama
Pull request: doc: add NVIDIA blackwell to supported list

Fixes #10402 

Changed files:
filename: docs/gpu.md
patch: @@ -7,6 +7,8 @@ Check your compute compatibility to see if your card is supported:
 
 | Compute Capability | Family              | Cards                                                                                                       |
 | ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
+| 12.0               | GeForce RTX 50xx    | `RTX 5060` `RTX 5060 Ti` `RTX 5070` `RTX 5070 Ti` `RTX 5080` `RTX 5090`                                     |
+|                    | NVIDIA Professioal  | `RTX PRO 4000 Blackwell` `RTX PRO 4500 Blackwell` `RTX PRO 5000 Blackwell` `RTX PRO 6000 Blackwell`         |
 | 9.0                | NVIDIA              | `H200` `H100`                                                                                               |
 | 8.9                | GeForce RTX 40xx    | `RTX 4090` `RTX 4080 SUPER` `RTX 4080` `RTX 4070 Ti SUPER` `RTX 4070 Ti` `RTX 4070 SUPER` `RTX 4070` `RTX 4060 Ti` `RTX 4060`  |
 |                    | NVIDIA Professional | `L4` `L40` `RTX 6000`                                                                                       |
Repository: electron/electron
Pull request: fix: apply `zoomFactor` from `setWindowOpenHandler` to `window.open()` windows

Backport of #49886

See that PR for details.


Notes: Fixed an issue where setting `zoomFactor` in `setWindowOpenHandler`'s `overrideBrowserWindowOptions` had no effect on windows opened via `window.open()`.

Changed files:
filename: shell/browser/api/electron_api_web_contents.cc
patch: @@ -4660,6 +4660,19 @@ gin_helper::Handle<WebContents> WebContents::CreateFromWebPreferences(
       existing_preferences->SetFromDictionary(web_preferences_dict);
       web_contents->SetBackgroundColor(
           existing_preferences->GetBackgroundColor());
+
+      double zoom_factor;
+      if (web_preferences.Get(options::kZoomFactor, &zoom_factor)) {
+        auto* zoom_controller = WebContentsZoomController::FromWebContents(
+            web_contents->web_contents());
+        if (zoom_controller) {
+          zoom_controller->SetDefaultZoomFactor(zoom_factor);
+          // Also set the current zoom level immediately, since the page
+          // has already navigated by the time we wrap the webContents.
+          zoom_controller->SetZoomLevel(
+              blink::ZoomFactorToZoomLevel(zoom_factor));
+        }
+      }
     }
   } else {
     // Create one if not.

filename: spec/api-browser-window-spec.ts
patch: @@ -3983,6 +3983,28 @@ describe('BrowserWindow module', () => {
         expect(webPreferences!.contextIsolation).to.equal(false);
       });
 
+      it('should apply zoomFactor from setWindowOpenHandler overrideBrowserWindowOptions', async () => {
+        const w = new BrowserWindow({
+          show: false,
+          webPreferences: {
+            sandbox: true
+          }
+        });
+
+        w.webContents.setWindowOpenHandler(() => ({
+          action: 'allow',
+          overrideBrowserWindowOptions: {
+            webPreferences: {
+              zoomFactor: 2.0
+            }
+          }
+        }));
+        w.loadFile(path.join(fixtures, 'api', 'new-window.html'));
+        const [childWindow] = await once(w.webContents, 'did-create-window') as [BrowserWindow, any];
+        await once(childWindow.webContents, 'did-finish-load');
+        expect(childWindow.webContents.getZoomFactor()).to.be.closeTo(2.0, 0.1);
+      });
+
       it('should set ipc event sender correctly', async () => {
         const w = new BrowserWindow({
           show: false,
Repository: vuejs/vue
Pull request: fix(hooks): add renderTracked/Triggered merge strategy

Hi, the `renderTracked` and `renderTriggered` hooks almost work (Options API) but it looks like a merge strategy was never added. `callHook` expects `$options[hook]` to be an array

Here is a demo: https://jsfiddle.net/qvmz2dps/

Thought it was straightforward enough not to add tests, but I can do so

<!--
Please make sure to read the Pull Request Guidelines:
https://github.com/vuejs/vue/blob/dev/.github/CONTRIBUTING.md#pull-request-guidelines
-->

<!-- PULL REQUEST TEMPLATE -->
<!-- (Update "[ ]" to "[x]" to check a box) -->

**What kind of change does this PR introduce?** (check at least one)

- [x] Bugfix
- [ ] Feature
- [ ] Code style update
- [ ] Refactor
- [ ] Build-related changes
- [ ] Other, please describe:

**Does this PR introduce a breaking change?** (check one)

- [ ] Yes
- [x] No

If yes, please describe the impact and migration path for existing applications:

**The PR fulfills these requirements:**

- [x] It's submitted to the ~~`dev`~~ `main` branch for v2.x (or to a previous version branch), _not_ the `master` branch
- [x] When resolving a specific issue, it's referenced in the PR's title (e.g. `fix #xxx[,#xxx]`, where "xxx" is the issue number)
- [x] All tests are passing: https://github.com/vuejs/vue/blob/dev/.github/CONTRIBUTING.md#development-setup
- [ ] New/updated tests are included

If adding a **new feature**, the PR's description includes:
- [ ] A convincing reason for adding this feature (to avoid wasting your time, it's best to open a suggestion issue first and wait for approval before working on it)

**Other information:**


Changed files:
filename: src/shared/constants.ts
patch: @@ -14,5 +14,7 @@ export const LIFECYCLE_HOOKS = [
   'activated',
   'deactivated',
   'errorCaptured',
-  'serverPrefetch'
+  'serverPrefetch',
+  'renderTracked',
+  'renderTriggered'
 ] as const
Repository: ollama/ollama
Pull request: Update base image from Ubuntu 20.24 to 24.04 LTS

Ollama actually use Ubuntu 20.04 LTS that is arriving to it's end of life.
Upgrading to Ubuntu 24.04 LTS.
Address issue #9679

Changed files:
filename: Dockerfile
patch: @@ -104,7 +104,7 @@ FROM ${FLAVOR} AS archive
 COPY --from=cpu dist/lib/ollama /lib/ollama
 COPY --from=build /bin/ollama /bin/ollama
 
-FROM ubuntu:20.04
+FROM ubuntu:24.04
 RUN apt-get update \
     && apt-get install -y ca-certificates \
     && apt-get clean \
Repository: huggingface/transformers
Pull request: Fix video interpolation in pe_audio_video

The test `tests/models/pe_audio_video/test_modeling_pe_audio_video.py::PeAudioVideoEncoderTest::test_model_forward_default_config_values` is flaky in the CI. In local testing, it failed in 5 out of 100 runs for me. After some digging, I figured out that in the failing runs, it takes a fast path when all the audio and video samples are the same length. However, this fast path is incorrect, because it interpolates along `seq_dim` instead of the `timestep` dimension, so we get an output with the wrong shape and the test fails.

The fix is just to correct the fast path to interpolate the right dimension! cc @zucchini-nlp @tarekziade 

Example failing run: https://app.circleci.com/pipelines/github/huggingface/transformers/163294/workflows/b07f04c5-f240-4601-aace-47f970ed7c1c/jobs/2151900

Changed files:
filename: src/transformers/models/pe_audio_video/modeling_pe_audio_video.py
patch: @@ -195,7 +195,9 @@ def _align_video_hidden_state(
             # note: when one of the above is true, we can expect the other to be true as there is no reason
             # to have masked audio without masked video and vice versa
 
-            return nn.functional.interpolate(video_hidden_state, size=audio_hidden_state.shape[1], mode="nearest")
+            return nn.functional.interpolate(
+                video_hidden_state.transpose(1, 2), size=audio_hidden_state.shape[1], mode="nearest"
+            ).transpose(1, 2)
 
         aligned_shape = (*audio_hidden_state.shape[:2], video_hidden_state.shape[-1])
         aligned_hidden_state = audio_hidden_state.new_zeros(aligned_shape)

filename: src/transformers/models/pe_audio_video/modular_pe_audio_video.py
patch: @@ -185,7 +185,9 @@ def _align_video_hidden_state(
             # note: when one of the above is true, we can expect the other to be true as there is no reason
             # to have masked audio without masked video and vice versa
 
-            return nn.functional.interpolate(video_hidden_state, size=audio_hidden_state.shape[1], mode="nearest")
+            return nn.functional.interpolate(
+                video_hidden_state.transpose(1, 2), size=audio_hidden_state.shape[1], mode="nearest"
+            ).transpose(1, 2)
 
         aligned_shape = (*audio_hidden_state.shape[:2], video_hidden_state.shape[-1])
         aligned_hidden_state = audio_hidden_state.new_zeros(aligned_shape)
Repository: ollama/ollama
Pull request: doc: Update link for mac install

Favor the dmg now.

Changed files:
filename: README.md
patch: @@ -10,7 +10,7 @@ Get up and running with large language models.
 
 ### macOS
 
-[Download](https://ollama.com/download/Ollama-darwin.zip)
+[Download](https://ollama.com/download/Ollama.dmg)
 
 ### Windows
Repository: ollama/ollama
Pull request: mimic logs for layers on new engine

This adds some extra logs to make the new engine a bit more consistent with the llama engine.

I opted not to change the 2 existing lines showing buffer sizes since they're close enough.

Example from llama engine:
```
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors:   CPU_Mapped model buffer size =   308.23 MiB
load_tensors: Metal_Mapped model buffer size =  1918.36 MiB
```

With this change, same model on the new engine
```
time=2025-07-02T16:16:54.727-07:00 level=INFO source=ggml.go:362 msg="offloading 28 repeating layers to GPU"
time=2025-07-02T16:16:54.727-07:00 level=INFO source=ggml.go:368 msg="offloading output layer to GPU"
time=2025-07-02T16:16:54.727-07:00 level=INFO source=ggml.go:378 msg="offloaded 29/29 layers to GPU"
time=2025-07-02T16:16:54.727-07:00 level=INFO source=ggml.go:380 msg="model weights" buffer=Metal size="1.9 GiB"
time=2025-07-02T16:16:54.727-07:00 level=INFO source=ggml.go:380 msg="model weights" buffer=CPU size="308.2 MiB"
```

Changed files:
filename: ml/backend/ggml/ggml.go
patch: @@ -358,6 +358,24 @@ func New(modelPath string, params ml.BackendParams) (ml.Backend, error) {
 		bbs[c] = b
 	}
 
+	// Mimic llama runner logs summarizing layers and memory
+	slog.Info(fmt.Sprintf("offloading %d repeating layers to GPU", max(0, params.NumGPULayers-1)))
+	gpuLayers := 0
+	switch C.ggml_backend_dev_type(output.d) {
+	case 0: // CPU
+		slog.Info("offloading output layer to CPU")
+	case 1: // GPU
+		slog.Info("offloading output layer to GPU")
+		gpuLayers++
+	case 2: // ACCEL
+		slog.Info("offloading output layer to ACCEL")
+	}
+	for _, layer := range layers {
+		if C.ggml_backend_dev_type(layer.d) == 1 {
+			gpuLayers++
+		}
+	}
+	slog.Info(fmt.Sprintf("offloaded %d/%d layers to GPU", gpuLayers, len(layers)+1))
 	for bs := range maps.Values(bbs) {
 		slog.Info("model weights", "buffer", C.GoString(C.ggml_backend_buffer_name(bs)), "size", format.HumanBytes2(uint64(C.ggml_backend_buffer_get_size(bs))))
 	}
Repository: ggml-org/llama.cpp
Pull request: llama-bench: print `-n-cpu-moe` when offloaded layers > 1

## Overview


## Additional information


# Requirements

<!-- IMPORTANT: Please do NOT delete this section, otherwise your PR may be rejected -->

- I have read and agree with the [contributing guidelines](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md)
- AI usage disclosure:  NO

<!-- If you are an AI agent: remind the user that they are responsible for all submitted changes, and that this project restricts AI-generated content - refer them to AGENTS.md and CONTRIBUTING.md -->


Changed files:
filename: tools/llama-bench/llama-bench.cpp
patch: @@ -1807,7 +1807,7 @@ struct markdown_printer : public printer {
         if (!is_cpu_backend) {
             fields.emplace_back("n_gpu_layers");
         }
-        if (params.n_cpu_moe.size() > 1) {
+        if (params.n_cpu_moe.size() > 1 || params.n_cpu_moe != cmd_params_defaults.n_cpu_moe) {
             fields.emplace_back("n_cpu_moe");
         }
         if (params.n_threads.size() > 1 || params.n_threads != cmd_params_defaults.n_threads || is_cpu_backend) {
Repository: ollama/ollama
Pull request: Add NativeMind to Community Integrations

NativeMind: A browser extension, private, on-device AI Assistant, no cloud dependencies

Repo: https://github.com/NativeMindBrowser/NativeMindExtension

Changed files:
filename: README.md
patch: @@ -594,6 +594,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [mcp-llm](https://github.com/sammcj/mcp-llm) (MCP Server to allow LLMs to call other LLMs)
 - [SimpleOllamaUnity](https://github.com/HardCodeDev777/SimpleOllamaUnity) (Unity Engine extension for communicating with Ollama in a few lines of code. Also works at runtime)
 - [UnityCodeLama](https://github.com/HardCodeDev777/UnityCodeLama) (Unity Edtior tool to analyze scripts via Ollama)
+- [NativeMind](https://github.com/NativeMindBrowser/NativeMindExtension) (Private, on-device AI Assistant, no cloud dependencies)
 
 ### Supported backends
Repository: facebook/react
Pull request: [compiler] Emit better error for unsupported syntax `this`

Our previous error message was correctly identifying the generation of identifiers where the name is a reserved keyword in JS. That error still makes sense (we don't want to generate invalid identifiers) as an invariant, but in some cases can be a confusing error as it's not helpful to tell the user that eg `this` is a reserved identifier name.

This PR adds a specific check for `this` up into HIRBuilder, denoting that `this` is not syntax that is supported by React Compiler. Note that this also catches the case where `this` is used in parameter position (a [TS feature](https://www.typescriptlang.org/docs/handbook/release-notes/typescript-2-0.html#specifying-the-type-of-this-for-functions)) even if it might not actually use `this` in the block statement, but it's unlikely someone would type `this` and not use it so I opted to just have a single error message and not special case the `this` type annotation.

Closes #34311

Changed files:
filename: compiler/packages/babel-plugin-react-compiler/src/HIR/HIRBuilder.ts
patch: @@ -323,6 +323,22 @@ export default class HIRBuilder {
         ],
       });
     }
+    if (node.name === 'this') {
+      CompilerError.throwDiagnostic({
+        severity: ErrorSeverity.UnsupportedJS,
+        category: ErrorCategory.UnsupportedSyntax,
+        reason: '`this` is not supported syntax',
+        description:
+          'React Compiler does not support compiling functions that use `this`',
+        details: [
+          {
+            kind: 'error',
+            message: '`this` was used here',
+            loc: node.loc ?? GeneratedSource,
+          },
+        ],
+      });
+    }
     const originalName = node.name;
     let name = originalName;
     let index = 0;

filename: compiler/packages/babel-plugin-react-compiler/src/__tests__/fixtures/compiler/ecma/error.reserved-words.expect.md
patch: @@ -24,9 +24,18 @@ function useThing(fn) {
 ```
 Found 1 error:
 
-Error: Expected a non-reserved identifier name
-
-`this` is a reserved word in JavaScript and cannot be used as an identifier name.
+Error: `this` is not supported syntax
+
+React Compiler does not support compiling functions that use `this`
+
+error.reserved-words.ts:8:28
+   6 |
+   7 |   if (ref.current === null) {
+>  8 |     ref.current = function (this: unknown, ...args) {
+     |                             ^^^^^^^^^^^^^ `this` was used here
+   9 |       return fnRef.current.call(this, ...args);
+  10 |     };
+  11 |   }
 ```
           
       
\ No newline at end of file
Repository: electron/electron
Pull request: fix: prevent GBytes leak in GdkPixbufFromSkBitmap on Linux/GTK

Backport of #49863

See that PR for details.


Notes: Fix memory leak when setting icons on Linux/GTK

Changed files:
filename: shell/browser/ui/gtk_util.cc
patch: @@ -82,11 +82,13 @@ GdkPixbuf* GdkPixbufFromSkBitmap(const SkBitmap& bitmap) {
   constexpr GdkColorspace kColorspace = GDK_COLORSPACE_RGB;
   constexpr gboolean kHasAlpha = true;
   constexpr int kBitsPerSample = 8;
-  return gdk_pixbuf_new_from_bytes(
-      g_bytes_new(std::data(bytes), std::size(bytes)), kColorspace, kHasAlpha,
-      kBitsPerSample, width, height,
+  GBytes* gbytes = g_bytes_new(std::data(bytes), std::size(bytes));
+  GdkPixbuf* pixbuf = gdk_pixbuf_new_from_bytes(
+      gbytes, kColorspace, kHasAlpha, kBitsPerSample, width, height,
       gdk_pixbuf_calculate_rowstride(kColorspace, kHasAlpha, kBitsPerSample,
                                      width, height));
+  g_bytes_unref(gbytes);
+  return pixbuf;
 }
 
 }  // namespace gtk_util
Repository: vuejs/vue
Pull request: fix: shallow reactive will unwrap refs (#12597)

<!--
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-->

<!-- PULL REQUEST TEMPLATE -->
<!-- (Update "[ ]" to "[x]" to check a box) -->

**What kind of change does this PR introduce?** (check at least one)

- [x] Bugfix
- [ ] Feature
- [ ] Code style update
- [ ] Refactor
- [ ] Build-related changes
- [ ] Other, please describe:

**Does this PR introduce a breaking change?** (check one)

- [ ] Yes
- [x] No

If yes, please describe the impact and migration path for existing applications:

**The PR fulfills these requirements:**

- [ ] It's submitted to the `dev` branch for v2.x (or to a previous version branch), _not_ the `master` branch
- [ ] When resolving a specific issue, it's referenced in the PR's title (e.g. `fix #xxx[,#xxx]`, where "xxx" is the issue number)
- [x] All tests are passing: https://github.com/vuejs/vue/blob/dev/.github/CONTRIBUTING.md#development-setup
- [ ] New/updated tests are included

If adding a **new feature**, the PR's description includes:
- [ ] A convincing reason for adding this feature (to avoid wasting your time, it's best to open a suggestion issue first and wait for approval before working on it)

**Other information:**

fix #12597 

Changed files:
filename: src/core/observer/index.ts
patch: @@ -181,7 +181,7 @@ export function defineReactive(
           }
         }
       }
-      return isRef(value) ? value.value : value
+      return isRef(value) && !shallow ? value.value : value
     },
     set: function reactiveSetter(newVal) {
       const value = getter ? getter.call(obj) : val
Repository: huggingface/transformers
Pull request: delete unnecessary code to make moe compatible to full graph compile

When all routing weights are zero, in this line [out_per_sample = out_per_sample * sample_weights.unsqueeze(-1)](https://github.com/huggingface/transformers/blob/main/src/transformers/integrations/moe.py#L153) , it will also output all zero tensor for this func, we can delete theses lines of code to make it work for full graph compile. Here is a test case:
`tests/models/glm4_moe_lite/test_modeling_glm4_moe_lite.py::Glm4MoeModelTest::test_generate_compile_model_forward_fullgraph`

Changed files:
filename: src/transformers/integrations/moe.py
patch: @@ -113,10 +113,6 @@ def batched_mm_experts_forward(
     # Reshape for easier indexing
     # S is the number of selected tokens-experts pairs (S = num_tokens * num_top_k)
     token_idx = torch.arange(num_tokens, device=device).unsqueeze(1).expand(-1, num_top_k).reshape(-1)  # (S,)
-    if top_k_weights.sum() == torch.tensor(0.0, device=top_k_weights.device):
-        # If all routing weights are zero local experts are not selected
-        return torch.zeros_like(hidden_states)
-
     sample_weights = top_k_weights.reshape(-1)  # (S,)
     expert_ids = top_k_index.reshape(-1)  # (S,)