jiebi/CodeConvo huggingface dataset:
Change:
Several this morning failed with (see for example): Not sure what is causing the outage, but it makes me wonder if perhaps it's time to retire Python-3.5 testing CI cc
Looks like pypi rolled out a new cert today:

Discussion:
with: submodules: false fetch-depth: 1 <del> - name: Setup Python 3.5 </del> <ins> - name: Setup Python 3.6 </ins> if: matrix.test_type == 'older_python_version' uses: actions/setup-python@v4 with: <del> python-version: '3.5' </del> <ins> python-version: '3.6' </ins> architecture: x64 check-latest: false cache: pip
Change:
*Status could be: ongoing Torch Bench testing is broken with errors that look like Inductor CI has been broken since 5:41 PM PT on June 14, 2024. It was detected the next day and root caused the morning on June 17th. The affected inductor ci jobs (those related to torchbench perf) shall be marked as unstable until this issue is mitigated. We suspect it's due to the numpy 2.0 update. () Ongoing Current plan is for to pin numpy for torchbench workflows TBD
This can be fixed by the following PRs: PyTorch PR: TorchBench PR:
I'll close those unstable issue once trunk recovers

Discussion:
<del> d6015d42d9a1834bc7595c4bd6852562fb80b30b </del> <ins> 23512dbebd44a11eb84afbf53c3c071dd105297e </ins>
Change:
Repro: Error: cc
Un-assign myself to let work on it.
, I can't reproduce the issue. The is no longer in the codebase. I gave a try of , which worked well. Could you double check if you can reproduce the issue?
Yes, I can still reproduce with your cmdline. Can you retry after deleting your local cache?

Discussion:
"test_mm_plus_mm2_cuda_dynamic_shapes": test_torchinductor.TestFailure( ("cuda_wrapper",), is_skip=True ), <del> "test_consecutive_split_cumprod_cuda_dynamic_shapes": test_torchinductor.TestFailure( ("cuda_wrapper",), is_skip=True ), </del> }

if config.triton.autotune_at_compile_time: self.kernel_autotune_calls.writeline(line) if zero_fill: <del> # TODO: remove this function to use the default WrapperCodegen behavior after service platform has zero_() symbol # default behavior is f"workspace.zero_(){self.ending}" self.writeline( f"AOTI_TORCH_ERROR_CODE_CHECK(aoti_torch_zero_(workspace.get())){self.ending}" ) </del> <ins> if isinstance(nbytes, sympy.Expr): self.writeline(f"workspace.zero_(){self.ending}") else: # TODO: remove this function to use the default WrapperCodegen behavior after service platform has zero_() symbol # default behavior is f"workspace.zero_(){self.ending}" self.writeline( f"AOTI_TORCH_ERROR_CODE_CHECK(aoti_torch_zero_(workspace.get())){self.ending}" ) </ins> if config.triton.autotune_at_compile_time: self.kernel_autotune_calls.writeline(f"workspace.zero_(){self.ending}")

return SymbolicCallArg(expr, tree.numel) def generate_workspace_allocation(self, nbytes, device, zero_fill): <ins> if isinstance(nbytes, sympy.Expr): nbytes = V.graph.sizevars.size_hint(nbytes) </ins> line = self.make_allocation( "workspace", device, torch.uint8, shape=(nbytes,), stride=(1,) )