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[release/2.9] Cherry-picks from release/2.8 10/06/2025 #2701
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(cherry picked from commit 3d102a0)
(cherry picked from commit cb98724)
…_rcpf(x) instead of 1.f/x (#1800) Cherry-pick of #1688 Co-authored-by: Michael Halkenhäuser <[email protected]> Co-authored-by: Hashem Hashemi <[email protected]> (cherry picked from commit f8544af) (cherry picked from commit ed48754) (cherry picked from commit d62a39e) (cherry picked from commit b26ddb8)
Related to c7a1e32 Fixes https://ontrack-internal.amd.com/browse/SWDEV-537835 Not a Navi specific failure: ``` File "/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_device_type.py", line 1412, in only_fn return fn(slf, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/var/lib/jenkins/pytorch/test/test_binary_ufuncs.py", line 1671, in test_cuda_tensor_pow_scalar_tensor self._test_pow(base, exp) File "/var/lib/jenkins/pytorch/test/test_binary_ufuncs.py", line 1482, in _test_pow self.assertEqual(actual, expected) File "/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py", line 4052, in assertEqual raise error_metas.pop()[0].to_error( AssertionError: The values for attribute 'dtype' do not match: torch.float32 != torch.float64. ``` Using .to(actual) without specifying dtype/device assumes actual is a tensor or tensor-like, which may fail silently or promote. Fixed by explicitly matching dtype and device. Going from pytorch#107302 Fix: ``` root@ubb4-rack-22:/var/lib/jenkins/pytorch# TEST_CONFIG=default HIP_VISIBLE_DEVICES=0 PYTORCH_TEST_WITH_ROCM=1 python test/test_binary_ufuncs.py TestBinaryUfuncsCUDA.test_cuda_tensor_pow_scalar_tensor_cuda /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. import pkg_resources Running tests... ---------------------------------------------------------------------- . ---------------------------------------------------------------------- Ran 1 test in 0.141s OK Generating XML reports... root@ubb4-rack-22:/var/lib/jenkins/pytorch# pip list | grep numpy numpy 2.1.2 ``` (cherry picked from commit a4d60fa) (cherry picked from commit 9f11871)
This PR fixes the unit test, test/test_cuda.py::TestCuda::test_set_per_process_memory_fraction FAILED [0.1163s] ``` Traceback (most recent call last): File "/var/lib/jenkins/pytorch/test/test_cuda.py", line 471, in test_set_per_process_memory_fraction tmp_tensor = torch.empty(application, dtype=torch.int8, device="cuda") RuntimeError: Trying to create tensor with negative dimension -5681285432: [-5681285432] ``` This error occurs only on gfx1101 arch. This error is coming from an integer overflow when another unit test, test/test_cuda.py::TestCuda::test_randint_generation_for_large_numel creates a tensor with a huge numel, which overflows into a higher torch.cuda.max_memory_reserved() when you call test/test_cuda.py::TestCuda::test_set_per_process_memory_fraction afterward. To avoid this we introduced torch.cuda.empty_cache() and torch.cuda.reset_peak_memory_stats() to clean up CUDA states. JIRA: https://ontrack-internal.amd.com/browse/SWDEV-535295 (cherry picked from commit f86d184) (cherry picked from commit 1b44228)
…g torch and numpy tensors (#2362) Cherry-pick of #2340 Co-authored-by: Dmitry Nikolaev <[email protected]> (cherry picked from commit 22c98ea) (cherry picked from commit 2d72fcd)
Adds initial autotuning for foreach support required for https://ontrack-internal.amd.com/browse/SWDEV-539076 4x improvement for some kernels Before: triton_for_fused_18.kd 🔍 | 4.986 ms | 4.986 ms | 2.493 ms | 2 | triton_for_fused_6.kd 🔍 | 0.098 ms | 0.098 ms | 0.049 ms | 2 | triton_for_fused_7.kd 🔍 | 0.036 ms | 0.036 ms | 0.018 ms | 2 | After: triton_for_fused_18.kd 🔍 | 1.273 ms | 1.273 ms | 0.636 ms | 2 | triton_for_fused_6.kd 🔍 | 0.044 ms | 0.044 ms | 0.022 ms | 2 | triton_for_fused_7.kd 🔍 | 0.024 ms | 0.024 ms | 0.012 ms | 2 | (cherry picked from commit f07b7f7) (cherry picked from commit ed0d0a7)
Relands #2416 with caching fix Upstream equivalent pytorch#159146 --------- Co-authored-by: Jithun Nair <[email protected]> (cherry picked from commit f0aebdc) (cherry picked from commit 9c429dd)
… Fix warps runtime part 2 (#2455) Cherry-pick of #2442 Co-authored-by: Jack Taylor <[email protected]> (cherry picked from commit 77a6760)
…ersistent reduction and no_x_dim removal (#2454) Cherry-pick of #2417 Need to resolve conflicts --------- Co-authored-by: Jack Taylor <[email protected]> (cherry picked from commit eb47158)
Perf improvement for triton tanh (cherry picked from commit 4febbd8)
… rocm version (#2529) Cherry-pick of #2518 Co-authored-by: Ethan Wee <[email protected]> (cherry picked from commit c03be63)
Fixes SWDEV-543698 (https://ontrack-internal.amd.com/browse/SWDEV-543698) Cherry-picked from #2502 This PR fixes the errors like below: ``` [rank3]: RuntimeError: The following operation failed in the TorchScript interpreter. [rank3]: Traceback of TorchScript (most recent call last): [rank3]: RuntimeError: /tmp/comgr-28f951/input/CompileSourceACC062:67:7: error: unknown type name 'uint32_t'; did you mean '__hip_internal::uint32_t'? [rank3]: 67 | uint32_t int32; [rank3]: | ^~~~~~~~ [rank3]: | __hip_internal::uint32_t ``` Earlier uint32_t was defined in HIP headers in std namespace. Now it is moved to __hip_internal namespace in hip headers. This change is made in ROCm 7.0. (cherry picked from commit b2fb688)
…2598) Cherry-pick of #2597 Co-authored-by: Jerry Mannil <[email protected]> (cherry picked from commit 9ea02c4)
Original PR (#2417) had incorrect indentation. Updated PR such that autotune will always add tiny configs, otherwise use the hinted configs only. Tested locally on test_torchinductor: Ran 894 tests in 952.242s FAILED (failures=1, skipped=28) And completed autotune runs for microbench models Microbenchmark for network : resnet152 Num devices: 1 Dtype: FP32 Mini batch size [img] : 64 Time per mini-batch : 0.09107530117034912 Throughput [img/sec] : 702.7152167226226 (cherry picked from commit db3ba66)
* cherry-pick of pytorch@2aadcea (cherry picked from commit bd74018)
cherry-pick of pytorch#163869 (cherry picked from commit dfd386f)
Jenkins build for 2fe5c2e6145fe3efa37d93597fcdc8d53fed41f2 commit finished as FAILURE Detected error during Pytorch building:
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Jenkins build for 7f74e862eb6dd84c9e6cbd5b551370b983378666 commit finished as ABORTED |
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Jenkins build for 7f74e862eb6dd84c9e6cbd5b551370b983378666 commit finished as NOT_BUILT |
Jenkins build for 7f74e862eb6dd84c9e6cbd5b551370b983378666 commit finished as FAILURE Detected error during Pytorch building:
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@pragupta Just confirming: all the SKIPPED commits I see regarding unit test failures are skipped because we want to see if those are still needed, and not necessarily because they are upstreamed, right? |
Steps followed:
Full list of commits considered for cherry-picking:
commits_2_9.txt
Tested on gfx942 using the following build:
registry-sc-harbor.amd.com/framework/compute-rocm-rel-7.0:38_ubuntu22.04_py3.10_pytorch_rocm7.1_internal_testing_28f820ab