diff --git a/2.9.0/done/result_distributed.md b/2.9.0/done/result_distributed.md
index e875c05..cd44fff 100644
--- a/2.9.0/done/result_distributed.md
+++ b/2.9.0/done/result_distributed.md
@@ -332,3 +332,7 @@ The categories below are as follows:
 - Work: block_current_stream API ([#156883](https://github.com/pytorch/pytorch/pull/156883))
 - [c10d] block_current_stream: correctness fixes ([#158757](https://github.com/pytorch/pytorch/pull/158757))
 - Add pg transport and tests ([#154653](https://github.com/pytorch/pytorch/pull/154653))
+- Symmetric memory set handle type for ROCm ([#161741](https://github.com/pytorch/pytorch/pull/161741))
+- Symmetric Memory Performance improvements for two-shot allreduce ([#156746](https://github.com/pytorch/pytorch/pull/156746))
+- NVSHMEM support for Triton 3.5 ([#163152](https://github.com/pytorch/pytorch/pull/163152))
+- Fix `put_signal` + `wait_until` hang ([#163194](https://github.com/pytorch/pytorch/pull/163194))
diff --git a/2.9.0/final.md b/2.9.0/final.md
new file mode 100644
index 0000000..e465ceb
--- /dev/null
+++ b/2.9.0/final.md
@@ -0,0 +1,829 @@
+# PyTorch 2.9.0 Release Notes
+- [Highlights](#highlights)
+- [Backwards Incompatible Changes](#backwards-incompatible-changes)
+- [Deprecations](#deprecations)
+- [New Features](#new-features)
+- [Improvements](#improvements)
+- [Bug fixes](#bug-fixes)
+- [Performance](#performance)
+- [Documentation](#documentation)
+- [Developers](#developers)
+- [Security](#security)
+
+
+# Highlights
+TODO
+
+For more details about these highlighted features, you can look at the release blogpost.
+Below are the full release notes for this release.
+
+
+# Backwards Incompatible Changes
+
+## Min supported Python version is now 3.10 (#162310)
+
+The minimum version of Python required for PyTorch 2.9.0 is 3.10. We also have 3.14 and 3.14t available as preview with this release.
+
+## Build metal kernels of MacOS-14+ and remove all pre-MacOS-14 specific logic, requires MacOS-14+ going forward (#159733, #159912)
+
+PyTorch MPS is only supported on MacOS-14 or later. If you need to use MPS on MacOS Ventura, please avoid updating to Python-3.9 or above
+
+## Upgrade to DLPack 1.0 (#145000)
+
+This upgrade is doing the same BC-breaking changes as the DLPack release.
+Objects in `torch.utils.dlpack` have been updated to reflect these changes, such as `DLDeviceType`.
+See the PR for details on the exact changes and how to update your code.
+
+## Raise appropriate errors in `torch.cat` (#158249)
+
+`torch.cat` now raises `ValueError`, `IndexError` or `TypeError` where appropriate instead of the generic `RuntimeError`. If you code was catching these errors, you can update to catch the new error type.
+
+
+## Default to `dynamo=True` for ONNX exporter (#159646, #162726)
+
+Previously `torch.onnx.export(...)` used the legacy TorchScript exporter if no arguments were provied. The ONNX exporter now uses the newer `torch.export.export` pipeline by default (`dynamo=True`). This change improves graph fidelity and future-proofs exports, but may surface graph capture errors that were previously masked or handled differently.
+
+Previously in torch 2.8.0:
+
+```python
+# API calls the legacy exporter with dynamo=False
+torch.onnx.export(...)
+```
+
+Now in torch 2.9.0:
+
+```python
+# To preserve the original behavior
+torch.onnx.export(..., dynamo=False)
+
+# Export onnx model through torch.export.export
+torch.onnx.export(...)
+```
+
+Recommendation: first try the new default; only fall back if you hit blocking issues and report them upstream.
+Long term solution: fix the root cause instead of relying on fallback or TorchScript exporter.
+
+## Switch off runtime asserts by default in Export in favor of a shape guards function (#160111, #161178, #161794)
+
+
+To enable runtime asserts, use `export(..., prefer_deferred_runtime_asserts_over_guards=True)`. Also kills the `allow_complex_guards_as_runtime_asserts` flag, merging it into the former option.
+
+
+Additionally, `exported_program.module()` will generate a call to a `_guards_fn` submodule that will run additional checks on inputs. Users who do not want this behavior can either remove this call in the graph, or do `exported_program.module(check_guards=False)` to avoid the generation.
+
+## Set default opset to 20 in ONNX (#158802)
+
+Opset 20 enables newer operator definitions. If your tooling or downstream runtime only supports opset 18, pin it explicitly. For the latest ONNX operators, you can experiment with opset 23.
+
+Previously in torch 2.8.0:
+
+```python
+# opset_version=18
+torch.onnx.export(...)
+```
+
+Now in torch 2.8.0:
+
+```python
+# To preserve the original behavior
+torch.onnx.export(..., opset_version=18)
+
+# New: opset_version=20
+torch.onnx.export(...)
+
+# Use the latest supported opset: opset_version=23
+torch.onnx.export(..., opset_version=23)
+```
+
+## Drop `draft_export` in exporter API (#161454, #162225)
+
+Remove implicit draft tracing from the default exporter path, achieving clearer behaviour and faster failures.
+The expensive `torch.export.draft_export` diagnostic path is no longer auto-invoked (which could take hours on large models). You can still opt in for deep diagnostics:
+
+Previously in torch 2.8.0:
+
+```bash
+# If both torch.export.export(..., strict=False) and
+# torch.export.export(..., strict=True) fail to capture
+# the model graph, torch.export.draft_export(...) will be triggered,
+# and uses real tensor to trace/export the model.
+#
+# Inside export_to_onnx.py:
+#  ... torch.onnx.export(..., dynamo=True)
+python export_to_onnx.py
+```
+
+Now in torch 2.9.0:
+
+```bash
+# To trigger torch.export.draft_export once
+# torch.export.export strict=False/True both
+# fail:
+
+TORCH_ONNX_ENABLE_DRAFT_EXPORT=True python export_to_onnx.py
+```
+
+## Remove `torch.onnx.dynamo_export` and the `onnxrt` torch compile backend (#158130, #158258)
+
+`torch.onnx.dynamo_export` is removed. Please use `torch.onnx.export` instead.
+The experimental ONNX Runtime compile backend (`torch.compile(backend="onnxrt")`) is no longer supported.
+
+## Remove `torch.onnx.enable_fake_mode` (#161222)
+
+The `dynamo=True` mode uses `FakeTensor`s by default which is memory efficient.
+
+## Some public facing ONNX utility APIs for the TorchScript based exporter are now private (#161323)
+
+Deprecated members in `torch.onnx.verification` are removed. Previously private `torch.onnx.symbolic_opsets*` functions will no longer be accessible. Consider making a copy of the source code if you need to access any private functions for compatibility with the TorchScript based exporter.
+
+## Remove `torch.onnx.symbolic_caffe2` (#157102)
+
+Support for `caffe2` in the ONNX exporter has ended and is removed.
+
+## Remove `/d2implyavx512upperregs` flag that slows build (#159431)
+
+Re-introduced AVX512 optimizations for Windows VS2022 builds, may cause issues with specific versions of VS2022, see #145702
+
+## Add `ScalarType` to shim conversion and `stable::Tensor.scalar_type` (#160557)
+
+Before, user extensions could only in abstract pass around obfuscated dtypes appearing as `int32_ts`. Now, users can confidently use `torch::headeronly::ScalarType` in their extensions for major scalar types. This PR enables ABI stability by adding a translation layer through the shim, so that even if the `ScalarType` enum values change in the future, user extensions need not fear.
+
+This change adds ScalarType support for user extensions and is only narrowly BC breaking for unpopular dtypes: `quint*`s, `qint*`s, `Bits*`, `dummy_uint*`s, `dummy_int*`s, `Float8_e8m0fnu`, and `Float4_e2m1fn_x2` in the use case where an extension retrieves a Tensor dtype of the above and passes it into `aoti_torch_call_dispatcher`.
+
+# Deprecations
+## Deprecate `pin_memory_device` param in `torch.utils.data.DataLoader` (#158323)
+
+We move enabling `pin_memory` back inside `BaseDataLoaderIter`. This is required for `StatefulDataloader` which leveraged `BaseDataLoaderIter` direclty rather than the `Dataloader` class init
+
+## Deprecate `torch.export.export_for_training` API in favor of equivalent `torch.export.export` API (#158203)
+
+`torch.export.export_for_training` exists because we couldn't migrate internal usages of export to the final IR. Now that we have completed the migration, we deprecated and deleted this API.
+
+# New Features
+## Python Frontend
+- Add utility to get the kernel currently registered on the dispatcher (#158393)
+- Extend `__torch_function__` handler to be triggered by elements within a list (#160256)
+- Add `torch.hash_tensor` reduction function (#154149)
+
+## FX
+- Extend torch function support to ALL arguments instead of just scalar type (but not inside of list, #145089)
+- Add `is_fx_symbolic_tracing` flag (#161385)
+
+## Dynamo
+- Experimental API for ahead-of-time compiling models in fullgraph mode (#161383)
+- Add a hook for recompilations (#157961)
+- DynamicInts prototype (#162194)
+
+Introduces an API for annotating dynamic integer inputs & attributes for `torch.compile`, by wrapping plain ints with `DynamicInt()`.
+DynamicInt objects also work in eager mode, acting as their underlying values when passed as scalar inputs.
+
+```python
+a = DynamicInt(4)
+y = a + 2  # DynamicInt(6)
+z = torch.ones(a)  # torch.ones(4)
+
+fn = torch.compile(torch.ones)
+fn(a)  # compiled fn takes a dynamic integer input
+fn(2)  # returns torch.ones(2) without recompiling
+```
+
+
+## Optimizer
+- Introduce Muon optimizer to PyTorch (#160213)
+
+## Profiler
+- Add GC Events to Python Stack Tracer (#161209)
+- Add a custom profiler configuration option (#151656)
+
+## Inductor
+- Allow user to pass in custom partitioner function (#157580)
+
+## Export
+- Add support for param mutation under inference mode (#159661)
+
+## AOTDispatcher
+- Add AOTDispatcher config to set backward autocast behavior (#156356)
+
+## Quantization
+- Enable cpu fp8 qlinear and cpu fp8 qconv (#155678, #157076)
+
+## ONNX
+- RMS Norm support in opset 23 (#159377)
+
+## C++ Extensions
+- Build out a stable set of ATen ops in `torch/csrc/stable/ops.h`:  `amax`, `narrow`, `new_empty` + `new_zeros` dtype variant, `pad`, (#159328, #158974, #159508, #161597, #160214)
+- Add `torch::stable::Tensor()` default constructor,  `is_cpu`, and `get_device_index`(#159507, #160212, #160143)
+- Add beginnings of `torch::stable::accelerator` with support for DeviceGuard and Stream (#159679, #160453)
+- Start building out `torch/headeronly`: c10 Macros, STD_TORCH_CHECK, ScalarTypes (like BFloat16 and Half, #158035, #158365, #157912, #158377, #159302, #159414, #159412, #159415, #159411, #159911)
+- Remove cmake cache and reconfigure again if it is invalid (#156958)
+- Cut a version of `TORCH_ERROR_CODE_CHECK` in `headeronly` from AOTI (#159604)
+- Remove `wheel` from build requirements (#158027)
+- Error when `TORCH_STABLE_ONLY` is defined in `TensorBase.h` (#161658)
+
+## Build Frontend
+- Add transpose to `torch/csrc/stable` (#158160)
+- Add `zero_()` and `empty_like(t)` to `torch/csrc/stable/ops.h` (#158866)
+
+## Release Engineering
+- Add support for CUDA 13.0 in CI/CD builds. Enable CUDA compression mode for binary size reduction for CUDA 13.0 builds (#160956, #161073, #161257, #161663, #161316, #160201, #160770, #161013, #161916, #162268, #162322, #162383, #161833)
+
+- Enable CUDA 12.6, 12.8 and 13.0 support for Linux ARM64 CD builds (#162364, #160720, #159481)
+
+- Add support for Python 3.14 in CI/CD builds (#156889, #157559, #159261, #159869, #160593, #160788, #161255, #159725)
+
+- Enable NVSHMEM integration (#151261, #153010, #154538, #155506, #156685, #158938, #161321, #160778, #159907, #160465)
+
+## CUDA
+- Add getter for CUDA graph exec to allow mutation of captured kernel params (#161294)
+- Implement support for `cudnn_batch_norm_out` kernel to replace the autogen approach (#123020)
+
+## CPU
+- Support GQA for flash attention (#157893)
+
+## MPS
+- Partial sparse support for MPS backend (#159729, #160254, #160223, #161846, #162007, #157238)
+- Add `avg_pool3d`, `max_unpool1d/2d/3d`, `max_pool3d`, `max_pool3d` bwd pass, and `avg_pool3d` bwd pass for MPS (#158877,#159789, #156467, #157498, #159089)
+
+## ROCm
+- OCP Micro-scaling Format (mx-fp8/mx-fp4) Support (#151360)
+
+## XPU
+- Enable `FlexAttention` on Intel GPU (#143553)
+
+# Improvements
+## Python Frontend
+- Speed up `torch.load` under `FakeTensorMode` by reducing random reads (#157931)
+- Make `torch.utils.benchmark.utils.timer` accelerator agnostic (#157131)
+- Improve error message for weight-only load errors (#159935)
+
+## torch.nn
+- Allow `register_buffer` with `Tensor`-like objects (#159455)
+- Improve error message for unsupported padding configurations (#160866)
+- Validate target is 0D when input is 1D in `NLLLoss` (#161412)
+
+## Optimizer
+- Resolve warning in LBFGS when converting a tensor with `requires_grad=True` to a scalar (#160389)
+- Resolve `SequentialLR` deprecation warning about invoking `step(epoch)` (#149392)
+
+## Autograd
+- Support deterministic `torch.nn.Upsample` `mode="trilinear"` backward (#154239)
+
+## Distributed
+### c10d
+  - Add improvements to eager init of `ProcessGroupNCCL` (#156748)
+  - Simplify unique hash management of `ProcessGroupNCCL` (#156790)
+  - Support per operation timeouts in `ProcessGroupGloo` (#158128)
+  - Allow ping to be retried in `TCPStore` (#159165)
+  - Support scalar tensor for functional `all_gather` (#149913)
+  - Expos `unsafe_get_ptr` for dist.ProcessGroupNCCL.NCCLConfig (#161136)
+  - Add batch option for `send/recv_object_list` (#160342)
+  - Make FakeStore optional to be passed into fake backend (#162164)
+  - Enable complex datatype support in `ProcessGroupGloo` (#156633)
+  - Move thread-local capture mode guard to include `work.isStarted` (#160398)
+### DistributedDataParallel (DDP)
+  - Support ddp zero hook XCCL path (#159240)
+### DTensor
+  - Relax `device_mesh` argument constraint in `local_map` (#157049)
+  - Support complex numbers in DTensor redistribute (#157329)
+  - Rework partial propagation in point-wise op and support mul (#157340)
+  - Allow dynamic shapes for `DTensor` slice (#157953)
+  - Implement `histc` op (#158298)
+  - Made dispatch to sharding prop over decomps (#159324)
+  - Support user-supplied Generator for random ops (#159933)
+  - Add `propagate_tensor_meta` function that skips cache if `_are_we_tracing` (#161334)
+  - Support `local_map` as a decorator (#161353)
+### Device Mesh
+  - Enable the use of user set backend and pg option even for the global mesh (#157501)
+  - Enable slicing a submesh with warnings (#158899)
+  - Allow controlling PG backend and options via `init_device_mesh` (#159371)
+### FullyShardedDataParallel2 (FSDP2)
+  - Support custom `all_gather` and `reduce_scatter` comms (#155189)
+  - Made it fail `set_allocate_memory_from_process_group` if used together with custom comm hooks (#157487)
+  - Use `reduceOpSum` when world size is 1 (#157529)
+  - Skipp `allgather` when world size is 1 (#160135)
+  - Use `post_reduce_stream.record_event()` on hsdp+cpuoffload (#160481)
+### Tensor Parallel (TP)
+  - Improve `parallelize_module` API to support more cases (#157182)
+### TensorPipe
+  - Update TensorPipe pinned dependency version (#159834)
+### TorchElastic
+  - Enable NUMA binding integration with elastic agent and `torchrun` (#149334)
+  - Support NUMA Binding for Callable Entrypoints (#160163, #161183)
+### Pipeline Parallelism (PP)
+  - Add `eval()` API to schedule (#157795)
+  - Allow intermediate nodes in zero bubble to have multiple grads (#159084)
+  - Support `OVERLAP_F_B` computation type (#158978)
+  - Initializ P2P communicators on first step (#160210)
+  - Add `DualPipeV` schedule (#159591)
+
+## Linear Algebra Frontend
+- Use rocSOLVER for Cholesky inversion on AMD. (#157154)
+- Add option for using TF32 as fp32 internal precision for matmul/linear/conv on MKLDNN (#157520)
+- Make einsum produce contiguous outputs in more cases (#161755)
+
+## Profiler
+- Add more CUDA API for kernel launcher (#156016)
+- Allow Custom Time Unit When Printing Profiler Table (#157913)
+- Update CUDA runtime kernel identification logic (#157890)
+
+## FX
+- Fix DCE eliminating random operations by improving `is_impure()` (#151524, #157981)
+- Support converting a float32 tensor to a scalar in FX trace. (#158216)
+- Correctly copy `self.module_stack` in ModuleStackTracer (#159956)
+- Add tool to track events in graph split (#159795)
+- Add `node_name_match` to subgraph rewriter (#157574)
+
+## Dynamo
+- Improve tracing support for various Python builtin data structures/modules:
+  - `list`s (e.g. #153969)
+  - `set`s (e.g. #153150)
+  - `dict`s (e.g. #154794)
+  - `iter` (e.g. #156371)
+  - `itertools` (e.g. #159693)
+  - `collections` (e.g. #159365)
+  - `collections.NamedTuple` (#159367)
+  - frozen `dataclasses.dataclass` (#159529)
+- Graph break error messages link to a website with more information (#159011)
+- Add option for `TorchDispatchMode` to ignore `torch.compile` internals (#161648)
+
+## Inductor
+- Add Inductor support for MTIA backend (#159211)
+- Share default device context when all graph partitions and cudagraph-unsafe ops are on the same device(#162873)
+
+## Ahead-Of-Time Inductor (AOTI)
+- Enable AOTI for CPU on Windows (#158915)
+- Re-enable TMA templates w/ AOTI (#157819)
+- Don't allow int32 indices if `{non-inf, > int32_max}` upper bound is provided (#159433)
+- Add RecordFunction to C shim so that profiling works with AOTI (#159842)
+- Add AOTI C shim functions for collective ops (#154492)
+- Add missing ops to set of C-shim ops which can have nullptr returns (#158073)
+
+## Export
+- Handle `None` & ellipsis slicing/select in non-strict (#157821)
+- Extend FP8 types in serialization (#158430)
+- Improve error messages for deserialization (#159881)
+- Support serialization for `triton_kernel_wrapper_functional` HOP (#161314)
+- Support serialization for complex constants (#161517)
+- Add runtime asserts to `while_loop` HOP subgraphs (#158467)
+- Warn on side-effectful code in strict mode (#160060)
+- Support for vmap in pre-dispatch export (#154650)
+- Support vmap and custom autograd function/improve DTensor constructor inefficiency (#162240)
+
+## AOTDispatcher
+- Skip logging in fp8 activation quantization if there are no nodes to be quantized (#158129)
+- Add `aot_export_joint_with_descriptors` and `aot_compile_joint_with_descriptors` (#158715)
+- Extract out `prepare_aot_module_simplified` for use in next PR (#158319)
+- Rename modules in AOTAutograd (#158449)
+- Track descriptors for all inputs/outputs of AOTAutograd traced graph (#158624)
+- Improve graph output alias with subclass error message (#159619)
+- Pass fw/bw compilers to `aot_export_joint_with_descriptors` (#159814)
+
+## Composability
+- Meta implementation for `aten.add.Scalar` (#161332)
+- `aten.expand_copy` decomp (#161688)
+- Fix result dtype cast in decomp for `aten.linalg_vector_norm` (#155111)
+- Add dtype checks in meta implementation for several ordering ops (#159556)
+- Fix meta function for `aten.complex` (#160894)
+- Improve unbacked symint (dynamic shape) support for several decompositions (#148815, #156902, #157008, #158894, #159184, #160683, #160253, #162084, #162099, #162109, #160462)
+
+## Quantization
+- Avoid getting model device once per node for pt2e quantization flow (#159901)
+- Fixes bug in implementation of `HistogramObserver` (#156457)
+- Support `bias=None` for `fbgemm_linear_fp16_weight` CPU op (#158535)
+- Add Static Dispatch Kernel for `wrapped_fbgemm_linear_fp16_weight` for Sigmoid (#160451)
+
+## Nested Tensor (NJT)
+- Added initial `log_softmax()` support (#159662)
+
+## Foreach
+- Invoke `vector.reserve()` consistently for non-inplace foreach operations (#161128)
+- Faster and safer lambda expression capture in `has_integral_tensor()` (#161042)
+
+## ONNX
+- Support symbolic arguments in ONNX exporter (#157734)
+- Fix `torch.tensor` warning in ONNX `symbolic_opset10` export  (#158835)
+
+## C++ Frontend
+- Generalized `AllocatorConfig` to be device-agnostic via new `AcceleratorAllocatorConfig` (#149601, #150312)
+- Added `Scalar::isUnsigned()` method (#159877)
+- Exposed `ModelRunner` from nativert as public (#159989)
+- Improve error message for `torch.binomial` enforcing float inputs (#157658)
+
+## Build Frontend
+- Fix dev warning in `Dependencies.cmake` (#159702)
+- Fix building system gloo with CUDA/HIP (#146637)
+- Build `libtorch` without NVSHMEM (#160910)
+- Improve BLAS feature detection (#143846)
+
+## Release Engineering
+- Enable vLLM testing workflow (#160583, #161565, #162292, #162000, #161797)
+- Enable Windows ARM64 CI testing (#148753, #161504)
+- Enable PyTorch ROCm CI for MI355X testing. (#158889)
+
+## CUDA
+- Make cublaslt/hipblaslt workspaces persistent (#156495)
+- Remove unnecessary warnings during the ATen compilation process (#157703)
+- Slightly improve error message from `repeat_interleave` kernel (#157996)
+- Add framework for explanations for common CUDA errors (#158395)
+- Upgrade KernelLauncher `kernelLaunchCheck` to print help string (#158896)
+- Prep for cutlass upgrade by ignoring `Wunused-but-set-variable` (#159276)
+- Workaround ATen SFINAE under `libc++` (#161101)
+- Implement changes to CCCL (CUB/Thrust/LibCUDACXX) usage in ATen (#153373)
+- Add maybe unused flag to remove warning (#157655)
+- Use new CCCL API in v2.8 (#160554)
+- Improve cupy device placement when device is provided with explicit index (#158529)
+
+## CPU (AArch64)
+- Made PyTorch compilable with gcc-14 on ARM (#157867)
+
+## MPS
+- Add `shifted_chebyshev_polynomial_[tuvw]`, `igamma/igammac,grid_sampler_3d, native_dropout`/`native_dropout_backward`  (#157488, #161927, #160541, #162108)
+- Extend atomic operations to all int types (#158179)
+- Extend `index_put` to complex types (#160159)
+- Extend `addmm` to integral types (#160270)
+- Add support for unsigned types (#159094)
+- Add API to query GPU core count (#160414)
+- Add `kthvalue` (#161817)
+- Type-promote tensor-iterator common dtype (#160334)
+- Implement `logcumsumexp` metal kernel (#156858)
+- Enable `dlpack` integration (#158888)
+- Dynamic reductions (#159355)
+- Update `avg_pool2d` to use Metal kernel when `ceil_mode=True` (#161011)
+
+## ROCm
+- Additional hipify mappings (#158056, #158352, #161992)
+- Refactor `composable_kernel` (CK) backend user interface to improve user experience (#152951)
+- Allow use of `rocSOLVER` for Cholesky inversion. (#157154)
+- AOT Inductor enable gfx950 for max autotune using CK (#159195)
+- Add flag `torch.backends.miopen.immediate` to toggle MIOpen Immediate Mode instead of relying on `deterministic=True` and `benchmark=False` (#158951)
+- MIOpen convolutions no longer call `reshape_` or unexpectedly change memory formats (#161687)
+
+## XPU
+- Support Intel GPU quantization ops in AOTInductor (#156572)
+- Add `device_id` to Intel GPU properties to distinguish iGPUs with identical names (#156481)
+
+# Bug Fixes
+## Python Frontend
+- Add option in `torch.utils.cpp_extension.load_inline` to override gencode (#156850)
+- Fix `max_width` computation in Tensor printing (#126859)
+- Improve `pin_memory` error message on CPU-only systems (#159994)
+- Making batching rule for `F.embedding` DTensor-aware (#162117)
+
+## Autograd
+- Fix `torch.autograd.Function` memory leak due to `torch.utils.checkpiont` early stopping (#161171)
+- Fix `torch.autograd.graph.GradientEdge` for `torch.autograd.Function` (#160098)
+- Match 0-dim gradients device type regardless of subclass-ness (#160165)
+
+## Distributed
+### c10d
+  - Fix slow init due to repeated dns resolution failure in socket (#159596)
+  - Fix `setGroupName` and `setGroupDesc` in `group_split` and `merge_remote_group` (#159429)
+  - Fix a bug of distributed 'gather' with noncontiguous tensors on the Gloo backend (#158903)
+  - Fix a bug of distributed 'gather' with noncontiguous tensors on the NCCL backend (#159549)
+  - Fix data inconsistencies when using `batch_isend_irecv` with 2D tensor views by making P2P tensors dense (#163719)
+  - Handle discontiguous `allgather`/`reducescatter` inputs (#163712)
+### Device Mesh
+  - Fix the not incorrectly chained each of the strings as iterables (#160709)
+### DistributedDataParallel (DDP)
+  - Fix incorrect interaction between `DDPOptimizer` and donated buffers (#160745)
+### DTensor
+  - Fix DTensor handling of conjugate bit (#158030)
+  - Fix `OpSchema` equality check (#161231)
+  - Fix `grouped_mm` strategy for invalid stride cases (#158245)
+  - Fix `F.one_hot` in DTensor (#162307)
+  - Always disabled `ShardingPropagation` cache if compiling (#156868)
+### FullyShardedDataParallel (FSDP)
+  - Fix the bug in FSDP offload `pin_memory` (#157147)
+  - Fix to ensure writeback handles `NO_SHARD` correctly by flattening tensors before copying (#154369)
+### FullyShardedDataParallel2 (FSDP2)
+  - Fix error message for `fsdp_pre_all_gather` (#160817)
+  - Fix the issue with `set_reduce_scatter_divide_factor` errors and `MixedPrecisionPolicy`  (#155964)
+### Pipeline Parallelism (PP)
+  - Fix eval step under `no_grad()` (#159293)
+  - Fix zero bubble schedules for `eval()` (#159475)
+### TensorPipe
+  - Fix `import torch` if compiled without `TensorPipe` (#159461)
+### TorchElastic
+  - Fix wrong log file name in the docs of `torch.distributed.elastic.multiprocessing.start_processes()` (#160396)
+
+## Linear Algebra Frontend
+- Avoid downcasts for fp16 matmul on the BLAS backend (#161999)
+
+## Profiler
+- Fix Linter for Global Annotations flag in Snapshot (#157858)
+
+## FX
+- Fix `split_module` with symint (#160093)
+- Fix `getattr_recursive` with ModuleList (#161204)
+- Skip const folding with symbolic expression (#161437)
+- Fix qualified name for methods of `torch.Tensor` (#162224)
+
+## Dynamo
+- Fix segfault due to interaction between Dynamo backends and `torch.compiler.reset()` (#156527)
+- Fix crash due to bad interaction with recompilations and with blocks in Python 3.11+ (#162318)
+
+## torch.nn
+- Fix silent correctness w/ backpropping grads for `FlexAttention` (#163677)
+- Fix `return_lse` warning message in `FlexAttention` (#163578)
+- Fix `FlexAttention` head broadcast (#163426)
+
+## Inductor
+- Fix wrong meta function for `constant_pad_nd` (#159878)
+- Fix learnable bias assertion error in Inductor (#161170)
+- Fix int64 from `MutationOutput` Buffer (#162020)
+- Fix Inductor CUDA sort `NaN` behavior (#159308)
+- Fix layout for local buf in outer loop fusion (#160857)
+- Fix slice scatter `dtype` consistency (#160851)
+- Fix 3d tiled online softmax (#162341)
+- Fix unsafe collective reorder past wait in Inductor (#157489)
+- Fix `FallbackKernel` alias function to avoid incorrect aliasing for custom ops (#163227)
+
+## Ahead-Of-Time Inductor (AOTI)
+- Fix a bug from `load_constants` (#161887)
+- Fix wrong propagation of fallback_ops_dict in `gen_aoti_c_shim` (#159904)
+- Fix unbacked symint and memory leak in Inductor memory planning (#159839)
+- Fix memory leak in AOTI when calling `aoti_torch_as_strided` (#162118)
+- Explicitly delete `wait_tensor` returned tensor (#159502)
+- Fix memory leak from `all_reduce` (#159818)
+
+## Composability
+- Make functionalization ViewMeta serializable with pickle (#163769)
+
+## Export
+- Fix bug in constants lifting pass (#157719)
+- Fix `from_node` provenance in unlift pass (#157943)
+- Fix `NaN` serialization (#155359)
+- Fix deserialization for unbacked symbol ranges (#158681)
+- Fix runtime assert handling in deserialization (#159060)
+- Fix for FQN handling in unflattener (#159418)
+- Fix `nn_module_stack` for `assert_tensor_metadata` nodes (#159625)
+- Fix usage for `move_to_device_pass` (#159992, #160528, #162301)
+- Avoid name overwrites for aliased exported module parameters (#160600)
+- Avoid inling `dynamo.disables` in unflattening (#161306)
+- Fix deserialization issue for storage offset (#162172)
+- Remove `.contiguous()` when saving weights to raw bytes to preserve original storage size of tensor (#163587)
+
+## Quantization
+- Avoid `NaN` in fp8 output of CPU `qlinear` and `qconv` ops (#160957)
+- Fix segmentation fault when `choose_qparams_optimized` (#161966)
+
+## Foreach
+- `chunk_size` should always be `int64_t` for Foreach functors (#156872)
+
+## ONNX
+- Make onnx export SDPA match ATen behavior (#159973)
+- Fix `rotary_embedding_23` implementation (#162865)
+- Fix export behavior when model has `None` as output (#160200)
+- Fix lower opset version support in `dynamo=True` (#161056)
+- Fix `index_put_` usage (#161263)
+
+## C++ Extensions
+- Fix CPP extension distributed warning for `TORCH_CUDA_ARCH_LIST` to only log when running on non-distributed or on rank 0 (#162764)
+
+## C++ Frontend
+- Fix `torch.utils.cpp_extension` parser for clang version 20.1.7+libcxx (#157666)
+- Fix `MakeTensor::computeStorageSize()` calculation (#158690)
+- Fix static initialization order issue with `AllocatorConfig` (#159629)
+
+## Build Frontend
+- Turn on `BUILD_BUNDLEPTXAS=1` to allow compile on newer GPUs(#163988)
+
+## CUDA
+- Handle uninitialized `torch.backends.cuda.matmul.fp32_precision` (#161102)
+- Fix nansum in non-JIT build (#158633)
+- Decrease launch bounds of CTCLoss backward for blackwell to avoid crash (#159522)
+- Implement workaround for `cudaErrorNotSupported` (#162412)
+- Fix missing `__syncthreads` in MultiMarginLoss backward (#158994)
+- Roll-back cuDNN frontend upgrade and update Meta registration due to compile issues (#163104)
+- Disable cuDNN for 3D convolutions with `kernel size != 1` for cuDNN 9.8+ (#163581)
+
+## CPU
+- Add check so non-aarch64 platforms can hit `MKLDNN` path (#162168)
+
+## MPS
+- Fix batch norm incorrect gradient (#156867)
+- Do not crash if `tensor dim > INT_MAX` (#158824)
+- Avoid outputing zeros from `exponential_` for MPS (#159386)
+- Fix MPS autocast for `ConvTranspose3d` (#160345)
+- Fix MPS `conv3d` autocast bias dtype mismatch (#160423)
+- Fix error check for `torch.var` on scalar (#160889)
+- Fix `index_add` for complex + int64, int64 input + zerodim index (#160926, #161511)
+- Fix `constant_pad_nd_mps` bug when pad is empty (#161149)
+- Fix `index_select` for `scalar_types` (#161206)
+- Fix `index_copy` for scalars and `index_copy` for strided indices (#161267, #161333)
+- Ensure that tensors are contiguous before using MPS linear kernel (#161641)
+- Address `NaN`s if SDPA is called with all values masked from query (#157727)
+- Fix invalid formatting (#158436)
+- Fix empty input in posneg functions (#161824)
+- Migrate round unary op to Metal (#161712)
+- Type-promote tensor-iterator common dtype (#160334)
+- Fix regression in 2.8.0 for `scaled_dot_product_attention` using MPS (#163598)
+- Chunk `fillBuffer` into 4Gb slices to avoid regression on MacOS 26 (#164108)
+- Fix latent bug that can result in segfault in CPP extensions (#164093)
+
+## ROCm
+- Fix Inductor with cudagraph trees `hip:0` device error (#161221)
+- Fix some build failures and support some BLAS calls on Windows (#161981)
+- Fix undefined symbol linker error after exposing MIOpen symbols on Windows (#156479)
+- Fix finding ROCm/HIP version on Windows (#156486)
+- Fix LoadHIP handling of environment variable paths on Windows (#159080)
+- Add hipcc compatibility flags to `cpp_extension.py` on Windows (#159790)
+- In SDPA via AOTriton, `logsumexp` needs scaling back to natural base (#156903)
+- Check stream graph capture status in `memcpy_and_sync` inline function (#158165)
+
+## XPU
+- Fix `cpp_extension` compatibility with `intel-deep-learning-essentials-2025.2` (#161012)
+
+## JIT
+- Make `ErrorReport::CallStack` thread-safe (#160386)
+- Fix `RemoveProfileNodesAndSpecializeTypes` handling for `Tensor?` that is resolved to `None` (#161538)
+
+# Performance
+## Optimizer
+- Use `addmm` to improve Newton–Schulz orthogonalization in Muon (#161379)
+- Avoid stream sync in SWA `AveragedModel.update_parameters()` (#157705)
+
+## Autograd
+- Fix SVD forward-mode AD multiplication priority (#161027)
+
+## Dynamo
+- Recursive `dict` tag optimization for faster guard evaluation (#159183)
+
+## Inductor
+- Improve performance of A16W4 and A16W8 `GEMM` template (#159127, #161148)
+- More aggressive persistent reduction (#161055)
+- Add a few outer dimension reduction cases for LOAF (#162028)
+- Fuse two RoPE kernels into a single kernel and improving runtime efficiency (#161420)
+
+## Export
+- Caching optimizations for placeholder naming pass (#158594)
+- Add Static Dispatch Kernel for `fmod.Scalar` and `scale_gradient` (#160654, #160454)
+
+## CUDA
+- Use a nonblocking copy to avoid stream synchronization for GPU tensor indexing with CPU mask (#156384)
+- Disable cudagraph GCs by default to improve capture performance (#158649)
+
+## Release Engineering
+- Upgrade to ROCm 6.4.1 and 6.4.2 patch releases (#156636, #158887, #158886, #158651, #159001)
+- Migrate RPyTorch ROCm CI to MI325 capacity (#159059, #159649, #161184)
+- Enable B200 PyTorch benchmark testing (#158011, #157341)
+
+## MPS
+- Optimize cummin/cummax metal kernels (#156794)
+- Speedup `torch.full` for 1-byte types (#158874)
+- Speedup `argmax`/`argmin` (#159524)
+- Improve performance of `max_pool3d` (#157875)
+- Avoid calling tensor ops in `max_pool3d` impl (#157874)
+- Move `max_pool2d` to Metal for `stride != 1` (#157876)
+
+## ROCm
+- SDPA now uses AOTriton to 0.11b (#161754)
+- `hipblaslt` is used by default on gfx908 for ROCm >= 6.3 (#159092)
+- Enable miopen channels last 3d for conv and batchnorm (#160529)
+- Remove extra transposes in NHWC convolutions on MIOpen (#160435)
+- Remove extra sync in `tensor.item()` (#158486)
+- Elementwise and reduction kernel perf improvements (#159430, #159652, #160444, #160466, #161054, #161180, #161181)
+- Enable build of `fbgemm_gpu genai` sources for grouped GEMM support (#160676)
+
+## XPU
+- Enable tensor memory descriptor Triton template for Intel GPU (#161600)
+
+# Documentation
+## Python Frontend
+- Improve documentation for `torch.lobpcg`, `torch.clone`, `torch.matmul`, `torch.max`, `torch.gather`, `torch.Tensor.scatter_`, `torch.empty_like`, `torch.randint`, `torch.mul`, `torch.min`, `torch.max`. `torch.sort`, `torch.full_like`, `torch.histogramdd`, `torch.hamming_window` (#156139, #157007, #161424, #156153, #157929, #157920, #158050, #158731, #160312, #161539, #162051, #158275, #152682)
+- Remove torchscript related sections in serialization docs (#156648)
+- Fix typo in `torch.set_float32_matmul_precision` docs (#158191)
+- Fix docstring for `torch.nn.utils.clip_grads_with_norm_` to reflect clamping behavior (#158200)
+- Fix the Doc issue on the description of edge_order in `torch.gradient` (#159130)
+- Add `torch.segment_reduce` docs (#154352)
+- Add examples to `torch.is_floating_point` and `torch.is_complex` docs (#161951)
+## torch.nn
+- Improve description of `padding` for `avg_poolnd` (#159142)
+- Improve `CrossEntropyLoss` docs with example of incorrect target specification (#155649)
+- Remove redundant dtype conversion in `scaled_dot_product_attention` example (#161613)
+
+## Optimizer
+- Document specific optimizer modules APIs e.g., `torch.optim.adam.Adam`, properly (#158483, #158669, #160194)
+- Add note for clarity in Adafactor doc #154862 (#155248)
+- Minorly improve `zero_grad` description (#161239)
+
+## Autograd
+- Improve `torch.inference_mode` docs and error message (#161164)
+
+## Distributed
+### c10d
+  - Documented barrier collective's interaction with `device_id` (#159389)
+  - Fix comment to match logic in `distributed_c10d.py` (#162158)
+### DTensor
+  - Rewrote doc of `TupleStrategy` (#158132)
+  - Documented `redistribute_costs` (#158495)
+### FullyShardedDataParallel (FSDP)
+  - Removed FSDP1 developer note (#158991)
+
+## Profiler
+- Update PT2 Profiler Torch-Compiled Region Image (#158066)
+- Fix Experimental Config Documentatation(#156586)
+- Update README (#159816)
+
+## FX
+- Fix typos in `torch/` (`torch/fx/`, #156604)
+- Add typing (#158450)
+- Fix typo in FX interpreter class docs (#162055)
+- Remove allow-untyped-defs from `torch/fx/experimental/migrate_gradual_types/util.py` (#157236)
+
+## Inductor
+- Add documentation for CUDAGraph partition (#159450)
+
+## Export
+- Update docs around draft export, dynamism, and PT2 Archive (#157750)
+
+## ONNX
+- Update export docstring (#162622)
+- Delete deprecated tutorial page link (#157310)
+- Filter out torchscript sentences (#158850)
+- Fix doc typo for `symbolic_multi_out` (#160702)
+- `onnx.md` to simplify deprecated entities (#159312)
+- Update export docstring and set `fallback=False` by default (#162622, #162726)
+- Fix typo in error message: summit -> submit (#162587)
+
+## Release Engineering
+- Add decorator to create deprecation warnings (#155127)
+- Add runnable code examples to export documentation (#158506)
+- Add developer notes for integrating new backends into PyTorch (#158644)
+
+## XPU
+- Update supported OS to Windows 11 & Ubuntu 24.04/25.04 for Intel client GPU (#161699)
+
+# Security
+## Python Frontend
+- Don't store flamegraph to tmp folder (#157374)
+
+# Developers
+## Python Frontend
+- Better sample inputs for addmm OpInfo (#160234)
+
+## Distributed
+### c10d
+  - Add `waitcounter` for watchdog and heartbeat monitoring thread (#157480)
+  - Made `torch.distributed.breakpoint` set a long timeout (#158481)
+  - Add `check_rng_sync` util (#160283)
+  - Add `FlightRecorder` support for `ProcessGroupXCCL` (#158568)
+  - Add `early_stop` kwarg to `torch.utils.checkpoint` (#160781)
+### DTensor
+  - Wrap sharding prop error with contextual exception (#161574)
+  - Add check if tracing for sharding propagation to handle un-hashable keys in DTensor (#160798)
+### Device Mesh
+  - Add error when users try to slice non contiguous flattened dim submesh (#157523)
+  - Make the repr shorter when debug ENV not set (#158822)
+### ShardedTensor
+  - Make error message descriptive in ShardedTensor creation (#150627, #159423)
+### Pipeline Parallelism (PP)
+  - Add profiling to schedule execution (#160753)
+
+## FX
+- Consolidate stack trace in Tracer (#156257, #157302, #158266)
+- Separate provenance tracking to different levels (#160383, #158399, #158796, #159484)
+- Fix `register_foward_pre_hook not supported on ScriptModule` error (#156904)
+- Add `__eq__` function to NodeSource (#158170)
+- Add `__hash__` function to NodeSource (#158322)
+- Cache dict and string rep for better perf in NodeSource (#158372)
+- Recover node source from dict (#158373, #158473)
+- Include error stacktrace and graph module in `tlparse` error (#158469)
+- Add `expanded_def` option for FX printing, render descriptor, update tests (#158708)
+- Remove `co_lnotab` in favor of `co_linetable` (#159227)
+- Remove duplicate imports (#161685)
+- Include Output tensor metadata for `CompiledFxGraph` (#159311)
+
+## Inductor
+- Deprecate `allow_tf32` in `tl.dot(..., allow_tf32=...)`, use `tl.dot(..., input_precision=...)` (#160711)
+- Log autotune choices and benchmark result to scuba/chrome trace (#159496)
+- Add TLParse artifact for logging runtime of collective and compute ops (#159730)
+- Call `jit_post_compile_hook` within Inductor Triton Kernel compile path (#161443)
+- Prune configs that require more shared memory than the hardware limit (#161996)
+- Runtime estimations using nccl estimator on mm only benchmark mode (#161405)
+- Don't use `torch.backends.cuda.matmul.allow_tf32` in Inductor cache key (#159480)
+
+## Ahead-Of-Time Inductor (AOTI)
+- Better error message when no .so/cpp files are found (#156863)
+- Clean up old APIs in AOTI c shim (#158400)
+- Add Inductor provenance mapping for cpp extern kernel (#161656, #162069)
+- Print out error msg when nvcc compiler fails (#157203)
+- Add kernel information JSON generation for AOTI packages (#160540)
+
+## Composability
+- Stop suggesting to use `guard_size_oblivious` on data dependent errors (#160510)
+- Avoid unnecessary slices resulting in data-dependent errors (#157528)
+
+## Quantization
+- Revamp dtype documentation (#156087)
+- Use new type statement to fix public API of types (#158487)
+
+## Dataloader Frontend
+- Add `torch.utils.data` samplers benchmark script (#156974)
+- Add `torch.utils.data.Dataloader` benchmark script (#159432)
+
+## Release Engineering
+- Replace `setup.py develop` with `pip install -e` for development builds (#155998, #156027, #156710)  (#156709)
+
+## XPU
+- Upgrade Intel GPU software stack package to intel-deep-learning-essentials-2025.2 (#158733)
diff --git a/2.9.0/miscategorized.md b/2.9.0/miscategorized.md
index 460c0b4..ba3572c 100644
--- a/2.9.0/miscategorized.md
+++ b/2.9.0/miscategorized.md
@@ -6,17 +6,4 @@ Handle any commits that actually do belong to your domain and remove them from t
 
 ## Untopiced
 
-
-StableABI:
-- Add pad and narrow to torch/csrc/stable/ops.h ([#159328](https://github.com/pytorch/pytorch/pull/159328))
-- Add getCurrentDeviceIndex to torch::stable::accelerator ([#160453](https://github.com/pytorch/pytorch/pull/160453))
-- Add new_zeros dtype variant to the shim and as a stable op ([#161597](https://github.com/pytorch/pytorch/pull/161597))
-- Update torch::stable::Tensor() default constructor ([#159507](https://github.com/pytorch/pytorch/pull/159507))
-- Add beginnings of torch::stable::accelerator ([#159679](https://github.com/pytorch/pytorch/pull/159679))
-- Port amax to stable ABI ([#160214](https://github.com/pytorch/pytorch/pull/160214))
-- Add new_empty (with dtype argument only) to torch::stable ([#159508](https://github.com/pytorch/pytorch/pull/159508))
-- Enable generating generic c_shim that doesn't bypass dispatcher ([#158974](https://github.com/pytorch/pytorch/pull/158974))
-- Cut a version of TORCH_ERROR_CODE_CHECK in headeronly from AOTI ([#159604](https://github.com/pytorch/pytorch/pull/159604))
-
-
 ## not user facing