Selected changesmerged Nov 1, 2026 – Nov 7, 2026
Improve distributed dataloader handlingPython · 112 + / 27 −
Introduces 4 new declarations in nemo/collections/common/data/lhotse/broadcasting.py.
Adds new core implementation rather than adjusting what was there. Tests changed with it, with code of their own.
nemo/collections/common/data/lhotse/broadcasting.py ↗ · 3 files
@@ -231,5 +254,67 @@ def _resolve_group_and_source(device_mesh, axes: Sequence[str]): group = sub.get_group() source_global_rank = int(sub.mesh.flatten()[0].item())- _GROUP_CACHE[cache_key] = (group, source_global_rank) return group, source_global_rank+++def _broadcast_packet(packet, group, src: int):+ """Broadcast one pre-serialized protocol packet over ``group``.++ Serializing before the first tensor collective lets the source replace an+ unpicklable data packet with a small error packet while receivers are still+ waiting for the packet size. Failures after a collective begins must be+ handled by the process-group timeout and distributed job teardown.+ """+ is_source = dist.get_rank() == src+ source_error = None+ if is_source:+ try:+ serialized = pickle.dumps(packet, protocol=pickle.HIGHEST_PROTOCOL)+ except Exception as error:+ source_error = error+ packet = _error_packet(error, "batch serialization failed")+ serialized = pickle.dumps(packet, protocol=pickle.HIGHEST_PROTOCOL)+ else:+ serialized = b""++ device = _broadcast_device(group)+ serialized_size = torch.tensor([len(serialized)], dtype=torch.long, device=device)+ dist.broadcast(serialized_size, src=src, group=group)++ if is_source:+ serialized_buffer = bytearray(serialized)
Keep overrides of the deprecated gradient checkpointing methods workingPython · 36 + / 2 −
Introduces 3 new declarations in src/transformers/modeling_utils.py.
Adds new core implementation rather than adjusting what was there. Tests changed with it, with code of their own.
src/transformers/modeling_utils.py ↗ · 2 files
@@ -3129,6 +3129,19 @@ def activation_checkpointing_enable( activation_checkpointing_kwargs (dict, *optional*): Additional keyword arguments passed along to the `torch.utils.checkpoint.checkpoint` function. """+ # Subclasses and wrappers of the deprecated `gradient_checkpointing_enable` stay the entry point until v6+ if self._is_overridden("gradient_checkpointing_enable"):+ self.gradient_checkpointing_enable(+ gradient_checkpointing_kwargs=activation_checkpointing_kwargs,+ every_n_layers=every_n_layers,+ offload=offload,+ )+ else:+ self._activation_checkpointing_enable(activation_checkpointing_kwargs, every_n_layers, offload)++ def _activation_checkpointing_enable(+ self, activation_checkpointing_kwargs=None, every_n_layers: int = 1, offload: bool = False+ ): if not self.supports_gradient_checkpointing: raise ValueError(f"{self.__class__.__name__} does not support activation checkpointing.")
BUG: f2py: mask string literals in depend harvest and fix sort orderPython · 100 + / 17 −
Introduces 3 new declarations in numpy/f2py/crackfortran.py.
Adds new core implementation rather than adjusting what was there. Tests changed with it, with code of their own.
numpy/f2py/crackfortran.py ↗ · 8 files
@@ -2129,6 +2147,49 @@ def postcrack(block, args=None, tab=''): return block +def _sort_cyclic_dependents(dep, vars):+ """Order one cyclic depend group by real dependency edges.++ ``sortvarnames`` calls this only after a cycle has been reported.+ The usual f2py cycle is an input array dimensioned by hide scalars+ that are computed from that array (``n = shape(a, ...)``,+ ``lda = MAX(1, n)``). Those array-to-hide edges are dropped so+ ``getarrdims`` can blank them, and every remaining edge is honored+ by a topological sort. An initializer therefore runs after the+ names it uses, independent of declaration order.++ A cycle that is not one of those shape back-edges is left in+ ``dep`` order. The caller has already reported it. This function+ does not recurse.+ """+ remaining = set(dep)++ def blocking(name):+ var = vars[name]+ blocked_by = []+ for dep_name in var.get('depend') or []:+ if dep_name not in remaining or dep_name == name:+ continue+ target = vars.get(dep_name, {})+ # Dimension back-edge onto a hide value or an initializer.+ if (isarray(var) and isintent_nothide(var)+ and (isintent_hide(target) or '=' in target)):+ continue+ blocked_by.append(dep_name)+ return blocked_by
Add support for the xing4_0 C++ · 884 + / 1 −
Introduces 3 new declarations in src/models/xing4-0.cpp.
Adds new runtime rather than adjusting what was there. Tests changed with it, with code of their own.
src/models/xing4-0.cpp ↗ · 13 files
@@ -0,0 +1,828 @@+#include "models.h"++#include <cmath>+#include <stdexcept>+#include <string>++static size_t xing4_0_elem_offset(const ggml_tensor * t, int64_t i) {+ return ggml_row_size(t->type, i);+}++static ggml_tensor * xing4_0_view_1d(ggml_context * ctx, ggml_tensor * t, int64_t ne0, int64_t i0) {+ return ggml_view_1d(ctx, t, ne0, xing4_0_elem_offset(t, i0));+}++static ggml_tensor * xing4_0_view_2d(+ ggml_context * ctx,+ ggml_tensor * t,+ int64_t ne0,+ int64_t ne1,+ int64_t i0) {+ return ggml_view_2d(ctx, t, ne0, ne1, t->nb[1], xing4_0_elem_offset(t, i0));+}++// mean over the hyper-connection streams: [n_embd, hc, n_tokens] -> [n_embd, n_tokens]+static ggml_tensor * xing4_0_hc_mean(ggml_context * ctx, ggml_tensor * x) {+ const int64_t hc = x->ne[1];++ ggml_tensor * acc = ggml_view_2d(ctx, x, x->ne[0], x->ne[2], x->nb[2], 0);+ for (int64_t s = 1; s < hc; ++s) {+ acc = ggml_add(ctx, acc, ggml_view_2d(ctx, x, x->ne[0], x->ne[2], x->nb[2], s*x->nb[1]));+ }+ return ggml_scale(ctx, acc, 1.0f/hc);+}
[`Moe`] Fix grouped mm fallbackPython · 36 + / 4 −
Introduces 3 new declarations in src/transformers/integrations/moe.py.
Adds new core implementation rather than adjusting what was there. Tests changed with it, with code of their own.
src/transformers/integrations/moe.py ↗ · 2 files
@@ -233,22 +233,43 @@ def _grouped_mm_fallback_setup_context(ctx, inputs, output): ctx.offs = inputs[2] -def _grouped_mm_fallback_backward(ctx, grad_output):- """Backward pass for `_grouped_mm_fallback`. Computes grad_input and grad_weight per expert group; offs has no gradient."""- input, weight = ctx.saved_tensors+def _grouped_mm_fallback_bwd(+ input: torch.Tensor,+ weight: torch.Tensor,+ offs: torch.Tensor,+ grad_output: torch.Tensor,+) -> tuple[torch.Tensor, torch.Tensor]:+ """Backward implementation for the grouped matmul fallback.""" grad_input = torch.zeros_like(input) grad_weight = torch.zeros_like(weight) start = 0 # single cpu<->gpu sync point here, # avoids multiple syncs inside the loop- for i, end in enumerate(ctx.offs.tolist()):+ for i, end in enumerate(offs.tolist()): if start == end: continue torch.mm(grad_output[start:end], weight[i].T, out=grad_input[start:end]) torch.mm(input[start:end].T, grad_output[start:end], out=grad_weight[i]) start = end + return grad_input, grad_weight+++def _grouped_mm_fallback_backward_fake(+ input: torch.Tensor,+ weight: torch.Tensor,
InterPodAffinity: handle namespaceSelector in assigned-pod queueing hintsGo · 120 + / 23 −
Introduces 4 new declarations in pkg/scheduler/framework/plugins/interpodaffinity/plugin.go.
Adds new systems design rather than adjusting what was there. Tests changed with it, with code of their own.
pkg/scheduler/framework/plugins/interpodaffinity/plugin.go ↗ · 3 files
@@ -162,6 +163,47 @@ func GetNamespaceLabelsSnapshot(logger klog.Logger, ns string, nsLister listersv return } +// termsNeedNamespaceLabels reports whether matching any of the terms against+// any of the pods requires the pods' namespace labels. A term that already+// matches the pod namespace via Namespaces, or whose namespace selector is+// empty/nothing, can be evaluated without looking the namespace up.+func termsNeedNamespaceLabels(terms []fwk.AffinityTerm, pods ...*v1.Pod) bool {+ for i := range terms {+ term := &terms[i]+ if term.NamespaceSelector == nil ||+ labels.MatchesNothing(term.NamespaceSelector) ||+ term.NamespaceSelector.Empty() {+ continue+ }+ for _, pod := range pods {+ if pod == nil || term.Namespaces.Has(pod.Namespace) {+ continue+ }+ if term.Selector.Matches(labels.Set(pod.Labels)) {+ return true+ }+ }+ }+ return false+}++// namespaceLabelsForNamespace returns namespace labels, whether the namespace+// was found, and an error. A missing namespace is reported as found=false with+// no error; other lister errors are returned to the caller.+func (pl *InterPodAffinity) namespaceLabelsForNamespace(namespace string, needed bool) (labels.Set, bool, error) {+ if !needed {+ return nil, true, nil
client-go/rest/watch: add concurrent watch event decoderGo · 225 + / 1 −
Introduces 14 new declarations in staging/src/k8s.io/client-go/rest/watch/concurrent_decoder.go.
Adds new systems design rather than adjusting what was there. Tests changed with it, with code of their own.
staging/src/k8s.io/client-go/rest/watch/concurrent_decoder.go ↗ · 6 files
@@ -0,0 +1,208 @@+/*+Copyright The Kubernetes Authors.++Licensed under the Apache License, Version 2.0 (the "License");+you may not use this file except in compliance with the License.+You may obtain a copy of the License at++ http://www.apache.org/licenses/LICENSE-2.0++Unless required by applicable law or agreed to in writing, software+distributed under the License is distributed on an "AS IS" BASIS,+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.+See the License for the specific language governing permissions and+limitations under the License.+*/++package watch++import (+ "fmt"+ "io"+ "sync"++ metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"+ "k8s.io/apimachinery/pkg/runtime"+ "k8s.io/apimachinery/pkg/runtime/serializer/streaming"+ utilruntime "k8s.io/apimachinery/pkg/util/runtime"+ "k8s.io/apimachinery/pkg/watch"+)++type rawWatchEventResult struct {+ event *metav1.WatchEvent+ err error
Refactor box downcasting methodsRust · 52 + / 43 −
Introduces 6 new declarations in library/alloc/src/boxed/convert.rs.
Adds new language design rather than adjusting what was there. Tests changed with it, with code of their own.
library/alloc/src/boxed/convert.rs ↗ · 6 files
@@ -711,21 +717,24 @@ impl<'a, 'b> From<Cow<'b, str>> for Box<dyn Error + 'a> { } } +impl<T: Error + ?Sized + 'static, A: Allocator> Box<T, A> {+ fn downcast_error<Dst: 'static>(this: Self) -> Result<Box<Dst, A>, Self> {+ if core::error::error_type_id::<T>(&this) == core::any::TypeId::of::<Dst>() {+ // SAFETY: The type is correct+ Ok(unsafe { Self::cast_unchecked(this) })+ } else {+ Err(this)+ }+ }+}+ impl dyn Error { /// Attempts to downcast the box to a concrete type. #[inline] #[stable(feature = "error_downcast", since = "1.3.0")] #[rustc_allow_incoherent_impl] pub fn downcast<T: Error + 'static>(self: Box<Self>) -> Result<Box<T>, Box<dyn Error>> {- if self.is::<T>() {- // SAFETY: Check ensures the type is correct.- unsafe {- let raw: *mut dyn Error = Box::into_raw(self);- Ok(Box::from_raw(raw as *mut T))- }- } else {- Err(self)- }+ Box::downcast_error(self) } }
Improve Request Insights context menus and trace interactionsTypeScript · 356 + / 80 −
Introduces 8 new declarations in packages/next/src/next-devtools/dev-overlay/components/request-insights/request-insights-panel.tsx.
Adds new framework internals rather than adjusting what was there. Tests changed with it, with code of their own.
packages/next/src/next-devtools/dev-overlay/components/request-insights/request-insights-panel.tsx ↗ · 5 files
@@ -696,53 +743,165 @@ function RequestRow({ requestType.type === 'rsc' ) const clockTime = formatClockTime(request.startTime)- const bypassesProxy = request.proxyStatus === 'bypassed' return (- <button- aria-label={`${isInstantInsights ? `Instant Insights for ${requestUrl}` : requestUrl}, ${requestType.accessibleLabel}, ${bypassesProxy ? 'Did not match the configured proxy, ' : ''}${formatDuration(request.durationMs)}, ${clockTime}`}- className="request-insights-row"- data-internal={isInstantInsights || undefined}- data-nested={nested || undefined}- data-page-load={pageLoad}- data-selected={selected}- onClick={onSelect}- type="button"+ <ContextMenu.Root+ onOpenChange={onContextMenuOpenChange}+ open={contextMenuOpen} >- <span className="request-insights-status" data-status={request.status} />- <span className="request-insights-route">- {nested ? <NestedArrowIcon /> : null}- <span className="request-insights-route-label">- {isInstantInsights ? 'Instant Insights' : requestUrl}- </span>- </span>- <span className="request-insights-duration">- {formatDuration(request.durationMs)}- </span>- <span className="request-insights-meta request-insights-row-metadata">+ <ContextMenu.Trigger+ render={+ <button
feat(next/image): add internal image redirects (to match existing external image redirects)TypeScript · 131 + / 72 −
Introduces 3 new declarations in packages/next/src/server/image-optimizer.ts.
Adds new framework internals rather than adjusting what was there. Tests changed with it, with code of their own.
packages/next/src/server/image-optimizer.ts ↗ · 10 files
@@ -100,6 +100,77 @@ export interface ImageParamsResult { minimumCacheTTL: number } +type ImageUrlParamResult =+ | { href: string; isAbsolute: boolean }+ | { errorMessage: string }++function validateUrlParam(+ url: string | string[] | undefined,+ imageData: ImageConfigComplete,+ isRedirect = false+): ImageUrlParamResult {+ // Note - We intentionally skip validation for local/remotePatterns when+ // validating redirect locations so that we don't break a src img redirect+ // to a new domain (e.g. github.com => githubusercontent.com).+ const { domains = [], remotePatterns = [], localPatterns } = imageData++ if (!isRedirect && domains.length > 0) {+ Log.warnOnce(+ 'The "images.domains" configuration is deprecated. Please use "images.remotePatterns" configuration instead.'+ )+ }++ if (!url) {+ return { errorMessage: '"url" parameter is required' }+ } else if (Array.isArray(url)) {+ return { errorMessage: '"url" parameter cannot be an array' }+ }++ if (url.length > 3072) {+ return { errorMessage: '"url" parameter is too long' }+ }+
salm_automodel_ctc_10ms: calibrated 40 ms to 10 ms CTC timestampsPython · 961 + / 108 −
Introduces 23 new declarations in nemo/collections/speechlm2/parts/ctc_timestamp_utils.py.
Adds new core implementation rather than adjusting what was there. Tests changed with it, with code of their own.
nemo/collections/speechlm2/parts/ctc_timestamp_utils.py ↗ · 14 files
@@ -2207,14 +2681,229 @@ def _align_banded_ctc(aligner, prepared): diarization_frame_seconds=prepared['diarization_frame_seconds'], diarization_max_speaker_count=prepared['diarization_max_speaker_count'], )+ calibration = prepared['config'].get('boundary_interpolation')+ if calibration is not None:+ # Use raw DP edges, before any VAD snapping or extending.+ _interpolate_word_boundaries(+ rows,+ ctc,+ record['ctc_step'],+ record['time_offset'],+ record['audio_duration'],+ diarization,+ mapping,+ calibration,+ aligner=aligner,+ )+ result['speaker_word_timestamps'] = aligner._public_word_timestamps(rows)+ result['boundary_interpolation'] = {+ 'method': 'calibrated_edge_local_linear_interpolation',+ 'estimated_grid_seconds': aligner.boundary_grid_seconds,+ 'outside_words': sum(w.get('_outside_diarization', False) for w in rows),+ } result['speaker_assignment_mode'] = 'token_distribution' result['alignment_diagnostics']['failed_streams'] = failures result['alignment_diagnostics']['one_pass'] = True result['alignment_diagnostics']['banded'] = diagnostics- results.append(_refine_word_timestamps(result, prepared['config']['max_word_frames']))+ results.append(+ _refine_word_timestamps(+ result,+ prepared['config']['max_word_frames'],+ onset_snap_seconds=aligner.onset_snap_seconds,
model : add Ripple (ricursiveai)C++ · 265 + / 0 −
Introduces 3 new declarations in src/models/ricursive.cpp.
Adds new runtime rather than adjusting what was there. Tests changed with it, with code of their own.
src/models/ricursive.cpp ↗ · 15 files
@@ -0,0 +1,236 @@+#include "models.h"++void llama_model_ricursive::load_arch_hparams(llama_model_loader & ml) {+ ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);+ ml.get_key(LLM_KV_EMBEDDING_SCALE, hparams.f_embedding_scale, false);+ // optional: absent or 0 means no clamp (the reference tests `if clamp_threshold:`); a scalar applies to every layer+ ml.get_key_or_arr(LLM_KV_SWIGLU_CLAMP, hparams.swiglu_clamp, hparams.n_layer_all, false);+ for (uint32_t il = 0; il < hparams.n_layer_all; ++il) {+ if (!std::isfinite(hparams.swiglu_clamp[il]) || hparams.swiglu_clamp[il] < 0.0f) {+ throw std::runtime_error(format("ricursive: swiglu_clamp for layer %u must be finite and non-negative, got %g", il, hparams.swiglu_clamp[il]));+ }+ }++ if (hparams.n_embd_head_k() != hparams.n_embd_head_v()) {+ throw std::runtime_error("ricursive: key_length and value_length must be equal");+ }++ // RoPE is only applied on the SWA layers, so a model without SWA would have no positional encoding+ ml.get_key(LLM_KV_ATTENTION_SLIDING_WINDOW, hparams.n_swa);+ if (hparams.n_swa == 0) {+ throw std::runtime_error("ricursive: sliding_window must be > 0");+ }+ hparams.swa_type = LLAMA_SWA_TYPE_STANDARD;+ if (ml.get_arr(LLM_KV_ATTENTION_SLIDING_WINDOW_PATTERN, hparams.is_swa_impl, false)) {+ // load_swa_pattern only bounds the array by LLAMA_MAX_LAYERS: a short one would leave the last layers dense and without RoPE+ uint32_t n_entries = 0;+ ml.get_arr_n(LLM_KV_ATTENTION_SLIDING_WINDOW_PATTERN, n_entries);+ if (n_entries != hparams.n_layer()) {+ throw std::runtime_error(format("ricursive: sliding_window_pattern has %u entries, expected %u", n_entries, hparams.n_layer()));+ }+ } else {+ // default: every 5th layer is global (RicursiveConfig layer_types: full attention iff i % 5 == 4)+ load_swa_pattern(ml, 5);