shdSSKrSSKJrJr SSKJrJr S S\4Sjjr S Sjr Sr S r S S jr S rg)N) tree_flattentree_unflatten)add_step_closurerun_step_closuresdevicecj[RRRU/US9 [ 5 g)aBTriggers a mark step, which amounts to - collecting a group of 'live' lazy tensors to index into the compilation cache (lowering/compiling their IR graphs if not cached) - kicking off execution of the compiled function - (optionally, wait=True) waiting for cpu-side execution to complete (does not sync the accelerator) )waitN)torch_C_lazy _mark_stepr)rr s h/Users/tiagomarins/Projetos/claudeai/copy_bank/venv/lib/python3.13/site-packages/torch/_lazy/__init__.py mark_stepr s' HHNNfbt4c\Uc/n[RRRUS9 g)zWaits for all the async operations on the given devices to complete. Args: devices (string..., optional): The devices whose async ops need to be waited for. If empty, all the local devices will be waited for. Ndevices)r r r _wait_device_opsrs rwait_device_opsrs'  HHNN##G#4rcV[RRRX5 g)z Sync the list of lazy tensors so there IR get lowered for the activate backend and the compiled computation graph get cached. N)r r r _sync_multi)tensorsrs r sync_multir!s  HHNNw0rcT[RRRU5$)z7Return a unique id of the lazy tensor maintained by LTC)r r r _get_tensor_id)tensors r get_tensor_idr)s 88>> ( ( 00rcU=(d S/n[U5up#[X!5 [UVs/sHoDRS5PM snU5$s snf)Nlazycpu)rrrto)rr flattenedspects rto_cpur&.sG!&G"7+OIy"  : 144; :D AA:sAcJ[R"[U5/UQ70UD6 gN)r saver&)rargskwargss rr)r)6s JJvg000r)Fr()torch._C._lazyr torch.utils._pytreerrclosurerrstrrrrrr&r)rrr2s6<8 c 511 B1r