correct default download dir for download_tokenizer.py #18
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| os.makedirs(f"checkpoints/{repo_id}", exist_ok=True) | ||
| try: | ||
| hf_hub_download(repo_id, "tokenizer.model", local_dir=f"torchtrain/datasets/tokenizer/", local_dir_use_symlinks=False, token=hf_token) | ||
| hf_hub_download(repo_id, "tokenizer.model", local_dir=f"./tokenizer/", local_dir_use_symlinks=False, token=hf_token) |
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hmmm I don't think this would solve the problem, this is relative dir but ppl would run this either on the root folder or under the dataset folder. If you want to fix this I prefer sth like a absolute path as default, as expose a --path arg
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actually this is now obsolete as we are including tokenizer directly for ease of user setup. |
wconstab
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Nov 21, 2025
recomputing MoE during backward ``` [rank4]: (Triggered internally at /data/users/whc/pytorch/torch/csrc/autograd/python_anomaly_mode.cpp:122.) [rank4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [rank4]:Exception in thread Thread-2 (run_backward): [rank4]:Traceback (most recent call last): [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/_backward.py", line 384, in stage_backward [rank4]: torch.autograd.backward( [rank4]: File "/data/users/whc/pytorch/torch/autograd/__init__.py", line 364, in backward [rank4]: _engine_run_backward( [rank4]: File "/data/users/whc/pytorch/torch/autograd/graph.py", line 865, in _engine_run_backward [rank4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [rank4]:RuntimeError: NCCL Error 5: invalid usage (run with NCCL_DEBUG=WARN for details) [rank4]:Exception raised from throw_nccl_error at /data/users/whc/pytorch/torch/csrc/cuda/nccl.cpp:259 (most recent call first): [rank4]:C++ CapturedTraceback: [rank4]:#4 std::_Function_handler<std::shared_ptr<c10::LazyValue<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > const> (), c10::SetStackTraceFetcher(std::function< std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) from Logging.cpp:0 [rank4]:#5 c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) from ??:0 [rank4]:#6 c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) from ??:0 [rank4]:#7 torch::cuda::nccl::detail::throw_nccl_error(torch::cuda::nccl::ncclResult) from ??:0 [rank4]:#8 torch::cuda::nccl::detail::NCCL_CHECK_TIMEOUT(torch::cuda::nccl::ncclResult, void*) from nccl.cpp:0 [rank4]:#9 torch::cuda::nccl::all2all_single_unequal_split(void*, unsigned long const*, unsigned long const*, void*, unsigned long const*, unsigned long const*, unsigned long, c10::ScalarType, void* , c10::cuda::CUDAStream&) from ??:0 [rank4]:#10 c10d::ProcessGroupNCCL::alltoall_base(at::Tensor&, at::Tensor&, std::vector<long, std::allocator<long> >&, std::vector<long, std::allocator<long> >&, c10d::AllToAllOptions const&) from ? ?:0 [rank4]:#11 c10d::ops::(anonymous namespace)::alltoall_base_CUDA(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> >, bool, long) from Ops.cpp:0 [rank4]:#12 c10::impl::make_boxed_from_unboxed_functor<c10::impl::detail::WrapFunctionIntoRuntimeFunctor_<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (*)(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vec tor<long, std::allocator<long> >, bool, long), c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10::guts::typelist::typelist<at::Tensor&, at::Tensor&, c 10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> > , bool, long> >, false>::call(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) from :0 [rank4]:#13 void c10::BoxedKernel::make_boxed_function<&torch::autograd::basicAutogradNotImplementedFallbackImpl>(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c 10::IValue, std::allocator<c10::IValue> >*) from autograd_not_implemented_fallback.cpp:0 [rank4]:#14 c10::impl::BoxedKernelWrapper<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGrou p, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> >, bool, long), void>::call(c10::Box edKernel const&, c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> >, bool, long) from :0 [rank4]:#15 c10d::ProcessGroup::alltoall_base(at::Tensor&, at::Tensor&, std::vector<long, std::allocator<long> >&, std::vector<long, std::allocator<long> >&, c10d::AllToAllOptions const&) from :0 [rank4]:#16 c10d::all_to_all_single(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) from ? ?:0 [rank4]:#17 c10::impl::make_boxed_from_unboxed_functor<c10::impl::detail::WrapFunctionIntoRuntimeFunctor_<at::Tensor (*)(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, st d::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >), at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, s td::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >, false>::call(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std:: allocator<c10::IValue> >*) from :0 [rank4]:#18 void c10::BoxedKernel::make_boxed_function<&torch::autograd::basicAutogradNotImplementedFallbackImpl>(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c 10::IValue, std::allocator<c10::IValue> >*) from autograd_not_implemented_fallback.cpp:0 [rank4]:#19 c10::impl::BoxedKernelWrapper<at::Tensor (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocat or<char> >), void>::call(c10::BoxedKernel const&, c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__cxx11::basic_stri ng<char, std::char_traits<char>, std::allocator<char> >) from :0 [rank4]:#20 std::vector<at::Tensor, std::allocator<at::Tensor> > torch::autograd::CppNode_apply_functional<(anonymous namespace)::AllToAllSingle>(std::vector<at::Tensor, std::allocator<at::Tensor> > &&, torch::autograd::AutogradContext&, std::vector<bool, std::allocator<bool> > const&, std::vector<torch::autograd::VariableInfo, std::allocator<torch::autograd::VariableInfo> > const&, std::__cxx1 1::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) from Functional.cpp:0 [rank4]:#21 torch::autograd::CppNode<(anonymous namespace)::AllToAllSingle>::apply(std::vector<at::Tensor, std::allocator<at::Tensor> >&&) from Functional.cpp:0 [rank4]:#22 torch::autograd::Node::operator()(std::vector<at::Tensor, std::allocator<at::Tensor> >&&) from :0 [rank4]:#23 torch::autograd::Engine::evaluate_function(std::shared_ptr<torch::autograd::GraphTask>&, torch::autograd::Node*, torch::autograd::InputBuffer&, std::shared_ptr<torch::autograd::ReadyQueu e> const&) from ??:0 [rank4]:#24 torch::autograd::Engine::thread_main(std::shared_ptr<torch::autograd::GraphTask> const&) from ??:0 [rank4]:#25 torch::autograd::Engine::thread_init(int, std::shared_ptr<torch::autograd::ReadyQueue> const&, bool) from ??:0 [rank4]:#26 torch::autograd::python::PythonEngine::thread_init(int, std::shared_ptr<torch::autograd::ReadyQueue> const&, bool) from :0 [rank4]:#27 std::error_code::default_error_condition() const from ??:0 [rank4]:#28 start_thread from ??:0 [rank4]:#29 __clone3 from :0 [rank4]: [rank4]: [rank4]:The above exception was the direct cause of the following exception: [rank4]: [rank4]:Traceback (most recent call last): [rank4]: File "/home/whc/.conda/envs/pytorch-3.10/lib/python3.10/threading.py", line 1016, in _bootstrap_inner [rank4]: self.run() [rank4]: File "/home/whc/.conda/envs/pytorch-3.10/lib/python3.10/threading.py", line 953, in run [rank4]: self._target(*self._args, **self._kwargs) [rank4]: File "/data/users/whc/torchtitan/torchtitan/distributed/dual_pipe_v.py", line 254, in run_backward [rank4]: backward_stage.backward_one_chunk( [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/stage.py", line 799, in backward_one_chunk [rank4]: grads_input, _ = self.backward_maybe_with_nosync( [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/stage.py", line 653, in backward_maybe_with_nosync [rank4]: result = perform_backward(backward_type)() [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/stage.py", line 607, in <lambda> [rank4]: stage_backward( [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/_backward.py", line 425, in stage_backward [rank4]: raise RuntimeError(exc_msg) from e [rank4]:RuntimeError: [rank4]: Failed to run stage backward: [rank4]: Stage output: ('Tensor(torch.Size([1, 4096, 2048]), grad=True, dtype=torch.bfloat16)',) [rank4]: Output gradient: ('Tensor(torch.Size([1, 4096, 2048]), grad=False, dtype=torch.bfloat16)',) [rank4]: Input: ['Tensor(torch.Size([1, 4096, 2048]), grad=True, dtype=torch.bfloat16)'] ```
H-Huang
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Dec 2, 2025
recomputing MoE during backward ``` [rank4]: (Triggered internally at /data/users/whc/pytorch/torch/csrc/autograd/python_anomaly_mode.cpp:122.) [rank4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [rank4]:Exception in thread Thread-2 (run_backward): [rank4]:Traceback (most recent call last): [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/_backward.py", line 384, in stage_backward [rank4]: torch.autograd.backward( [rank4]: File "/data/users/whc/pytorch/torch/autograd/__init__.py", line 364, in backward [rank4]: _engine_run_backward( [rank4]: File "/data/users/whc/pytorch/torch/autograd/graph.py", line 865, in _engine_run_backward [rank4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [rank4]:RuntimeError: NCCL Error 5: invalid usage (run with NCCL_DEBUG=WARN for details) [rank4]:Exception raised from throw_nccl_error at /data/users/whc/pytorch/torch/csrc/cuda/nccl.cpp:259 (most recent call first): [rank4]:C++ CapturedTraceback: [rank4]:pytorch#4 std::_Function_handler<std::shared_ptr<c10::LazyValue<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > const> (), c10::SetStackTraceFetcher(std::function< std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > ()>)::{lambda()pytorch#1}>::_M_invoke(std::_Any_data const&) from Logging.cpp:0 [rank4]:pytorch#5 c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) from ??:0 [rank4]:pytorch#6 c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) from ??:0 [rank4]:pytorch#7 torch::cuda::nccl::detail::throw_nccl_error(torch::cuda::nccl::ncclResult) from ??:0 [rank4]:pytorch#8 torch::cuda::nccl::detail::NCCL_CHECK_TIMEOUT(torch::cuda::nccl::ncclResult, void*) from nccl.cpp:0 [rank4]:pytorch#9 torch::cuda::nccl::all2all_single_unequal_split(void*, unsigned long const*, unsigned long const*, void*, unsigned long const*, unsigned long const*, unsigned long, c10::ScalarType, void* , c10::cuda::CUDAStream&) from ??:0 [rank4]:pytorch#10 c10d::ProcessGroupNCCL::alltoall_base(at::Tensor&, at::Tensor&, std::vector<long, std::allocator<long> >&, std::vector<long, std::allocator<long> >&, c10d::AllToAllOptions const&) from ? ?:0 [rank4]:pytorch#11 c10d::ops::(anonymous namespace)::alltoall_base_CUDA(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> >, bool, long) from Ops.cpp:0 [rank4]:pytorch#12 c10::impl::make_boxed_from_unboxed_functor<c10::impl::detail::WrapFunctionIntoRuntimeFunctor_<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (*)(at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vec tor<long, std::allocator<long> >, bool, long), c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> >, c10::guts::typelist::typelist<at::Tensor&, at::Tensor&, c 10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> > , bool, long> >, false>::call(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std::allocator<c10::IValue> >*) from :0 [rank4]:pytorch#13 void c10::BoxedKernel::make_boxed_function<&torch::autograd::basicAutogradNotImplementedFallbackImpl>(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c 10::IValue, std::allocator<c10::IValue> >*) from autograd_not_implemented_fallback.cpp:0 [rank4]:pytorch#14 c10::impl::BoxedKernelWrapper<c10::intrusive_ptr<c10d::Work, c10::detail::intrusive_target_default_null_type<c10d::Work> > (at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGrou p, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> >, bool, long), void>::call(c10::Box edKernel const&, c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor&, at::Tensor&, c10::intrusive_ptr<c10d::ProcessGroup, c10::detail::intrusive_target_default_null_type<c10d::ProcessGroup> > const&, std::vector<long, std::allocator<long> >, std::vector<long, std::allocator<long> >, bool, long) from :0 [rank4]:pytorch#15 c10d::ProcessGroup::alltoall_base(at::Tensor&, at::Tensor&, std::vector<long, std::allocator<long> >&, std::vector<long, std::allocator<long> >&, c10d::AllToAllOptions const&) from :0 [rank4]:pytorch#16 c10d::all_to_all_single(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) from ? ?:0 [rank4]:pytorch#17 c10::impl::make_boxed_from_unboxed_functor<c10::impl::detail::WrapFunctionIntoRuntimeFunctor_<at::Tensor (*)(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, st d::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >), at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, s td::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > >, false>::call(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c10::IValue, std:: allocator<c10::IValue> >*) from :0 [rank4]:pytorch#18 void c10::BoxedKernel::make_boxed_function<&torch::autograd::basicAutogradNotImplementedFallbackImpl>(c10::OperatorKernel*, c10::OperatorHandle const&, c10::DispatchKeySet, std::vector<c 10::IValue, std::allocator<c10::IValue> >*) from autograd_not_implemented_fallback.cpp:0 [rank4]:pytorch#19 c10::impl::BoxedKernelWrapper<at::Tensor (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocat or<char> >), void>::call(c10::BoxedKernel const&, c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__cxx11::basic_stri ng<char, std::char_traits<char>, std::allocator<char> >) from :0 [rank4]:pytorch#20 std::vector<at::Tensor, std::allocator<at::Tensor> > torch::autograd::CppNode_apply_functional<(anonymous namespace)::AllToAllSingle>(std::vector<at::Tensor, std::allocator<at::Tensor> > &&, torch::autograd::AutogradContext&, std::vector<bool, std::allocator<bool> > const&, std::vector<torch::autograd::VariableInfo, std::allocator<torch::autograd::VariableInfo> > const&, std::__cxx1 1::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) from Functional.cpp:0 [rank4]:pytorch#21 torch::autograd::CppNode<(anonymous namespace)::AllToAllSingle>::apply(std::vector<at::Tensor, std::allocator<at::Tensor> >&&) from Functional.cpp:0 [rank4]:pytorch#22 torch::autograd::Node::operator()(std::vector<at::Tensor, std::allocator<at::Tensor> >&&) from :0 [rank4]:pytorch#23 torch::autograd::Engine::evaluate_function(std::shared_ptr<torch::autograd::GraphTask>&, torch::autograd::Node*, torch::autograd::InputBuffer&, std::shared_ptr<torch::autograd::ReadyQueu e> const&) from ??:0 [rank4]:pytorch#24 torch::autograd::Engine::thread_main(std::shared_ptr<torch::autograd::GraphTask> const&) from ??:0 [rank4]:pytorch#25 torch::autograd::Engine::thread_init(int, std::shared_ptr<torch::autograd::ReadyQueue> const&, bool) from ??:0 [rank4]:pytorch#26 torch::autograd::python::PythonEngine::thread_init(int, std::shared_ptr<torch::autograd::ReadyQueue> const&, bool) from :0 [rank4]:pytorch#27 std::error_code::default_error_condition() const from ??:0 [rank4]:pytorch#28 start_thread from ??:0 [rank4]:pytorch#29 __clone3 from :0 [rank4]: [rank4]: [rank4]:The above exception was the direct cause of the following exception: [rank4]: [rank4]:Traceback (most recent call last): [rank4]: File "/home/whc/.conda/envs/pytorch-3.10/lib/python3.10/threading.py", line 1016, in _bootstrap_inner [rank4]: self.run() [rank4]: File "/home/whc/.conda/envs/pytorch-3.10/lib/python3.10/threading.py", line 953, in run [rank4]: self._target(*self._args, **self._kwargs) [rank4]: File "/data/users/whc/torchtitan/torchtitan/distributed/dual_pipe_v.py", line 254, in run_backward [rank4]: backward_stage.backward_one_chunk( [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/stage.py", line 799, in backward_one_chunk [rank4]: grads_input, _ = self.backward_maybe_with_nosync( [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/stage.py", line 653, in backward_maybe_with_nosync [rank4]: result = perform_backward(backward_type)() [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/stage.py", line 607, in <lambda> [rank4]: stage_backward( [rank4]: File "/data/users/whc/pytorch/torch/distributed/pipelining/_backward.py", line 425, in stage_backward [rank4]: raise RuntimeError(exc_msg) from e [rank4]:RuntimeError: [rank4]: Failed to run stage backward: [rank4]: Stage output: ('Tensor(torch.Size([1, 4096, 2048]), grad=True, dtype=torch.bfloat16)',) [rank4]: Output gradient: ('Tensor(torch.Size([1, 4096, 2048]), grad=False, dtype=torch.bfloat16)',) [rank4]: Input: ['Tensor(torch.Size([1, 4096, 2048]), grad=True, dtype=torch.bfloat16)'] ```
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Quick fix - the default dir in download_tokenizer was set to '/torchtrain/datasets/tokenizer'.
This meant that running it would put the tokenizer.model in /torchtrain/datasets/torchtrain/datasets/tokenizer.
This PR simply removes the redundant parent dirs so that the tokenizer.model is dropped in /tokenizer as default dir, which then lands it in /torchtrain/datasets/tokenizer/tokenizer.model and is ready to run the model training.