`i^ddlZddlmZmZddlmZmZddefdZ dd Z d Z d Z dd Z d ZdS)N) tree_flattentree_unflatten)add_step_closurerun_step_closuresFdevicecptjj|g|t dS)aVTriggers 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)r r s h/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torch/_lazy/__init__.py mark_stepr s5 HNfbt444cX|g}tjj|dS)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/  HN##G#44444rcPtjj||dS)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$  HNw00000rcJtjj|S)z7Return a unique id of the lazy tensor maintained by LTC)r r r_get_tensor_id)tensors r get_tensor_idr)s 8> ( ( 0 00rc|pdg}t|\}}t||td|D|S)Nlazyc8g|]}|dS)cpu)to).0ts r zto_cpu..3s":::1144;;:::r)rrr)rr flattenedspecs rto_cpur*.sN!&G"7++OIty'""" :: :::D A AArcJtjt|g|Ri|dSN)r saver*)rargskwargss rr-r-6s. Jvg000000000r)rFr,)torch._C._lazyr torch.utils._pytreerrclosurerrstrrrrrr*r-rrr5s<<<<<<<<88888888  c    5555111111 BBBB11111r