o 闦i+@sdUdZddlZddlZddlmZmZmZmZmZm Z m Z ddl Z ddl m Z mZddlmZmZmZddlmZddlmZe e eefZe jZe jZd agaee egdfeefed <eZ e!Z"eZ#d d Z$d dZ%de&fddZ'd;ddZ(Gddde)Z*de&fddZ+de&fddZ,dzH This package enables an interface for accessing MTIA backend in python N)AnyCallableDictListOptionalTupleUnion)deviceTensor) _dummy_type_LazySeedTracker classproperty)Device)_get_device_indexF _queued_callscCs tdSN) _lazy_initrrQ/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/torch/mtia/__init__.pyinit! rcCs tot S)z9Return whether PyTorch's MTIA state has been initialized.) _initialized_is_in_bad_forkrrrris_initialized%s rreturncC tjSr)torch_C_mtia_isInBadForkrrrrr*rrc Cststtdr dStqtr WddStr tdts'tdtj dt_ t ddtDz1t D]'\}}z|Wq>tye}zdt|dd |}t||d}~wwWttdnttdwdaWddS1swYdS) Nis_initializingzwCannot re-initialize MTIA in forked subprocess. To use MTIA with multiprocessing, you must use the 'spawn' start methodzTorch not compiled with MTIA enabled. Ensure you have `import mtia.host_runtime.torch_mtia` in your python src file and include `//mtia/host_runtime/torch_mtia:torch_mtia` as your target dependency!Tcss|]}|r|VqdSrr).0callsrrr Psz_lazy_init..z6MTIA call failed lazily at initialization with error: z( MTIA call was originally invoked at: )rhasattr_tls_initialization_lockr RuntimeError _is_compiledAssertionErrorrr _mtia_initr rextend_lazy_seed_tracker get_calls ExceptionstrjoinDeferredMtiaCallErrordelattrr) queued_callorig_tracebackemsgrrrr.sB       "rc@s eZdZdS)r2N)__name__ __module__ __qualname__rrrrr2asr2cCr)z*Return true if compiled with MTIA support.)rr _mtia_isBuiltrrrrr)e r)cCstsdStdkS)z'Return true if MTIA device is availableFr)r) device_countrrrr is_availablejs r>r cCs:tj| tjWdS1swYdS)z?Waits for all jobs in all streams on a MTIA device to complete.N)rmtiar r_mtia_deviceSynchronizer rrr synchronizers$rBcCr)z,Return the number of MTIA devices available.)rr_accelerator_hooks_device_countrrrrr=xr<r=cCr)z0Return the index of a currently selected device.)rr%_accelerator_hooks_get_current_devicerrrrcurrent_device}r<rEcCtjt|ddS)aSReturn the currently selected :class:`Stream` for a given device. 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TrG)rr_mtia_getDeviceCapabilityrrArrrget_device_capabilitysrOcCr)zEmpty the MTIA device cache.)rr_mtia_emptyCacherrrr empty_cacher<rQstreamcCs|durdStj|dS)aSet the current stream.This is a wrapper API to set the stream. Usage of this function is discouraged in favor of the ``stream`` context manager. Args: stream (Stream): selected stream. This function is a no-op if this argument is ``None``. N)rr_mtia_setCurrentStreamrRrrr set_streams rUcCs$t|}|dkrtj|dSdS)zSet the current device. Args: device (torch.device or int): selected device. This function is a no-op if this argument is negative. rN)rrr%_accelerator_hooks_set_current_devicerArrr set_devicesrWc@s<eZdZdZdefddZddZdededefd d Zd S) r zContext-manager that changes the selected device. Args: device (torch.device or int): device index to select. It's a no-op if this argument is a negative integer or ``None``. cCst|dd|_d|_dS)NTrG)ridxprev_idx)selfr rrr__init__s zdevice.__init__cCstj|j|_dSr)rr(_accelerator_hooks_maybe_exchange_devicerYrZ)r[rrr __enter__szdevice.__enter__typevalue tracebackcCstj|j|_dS)NF)rrr]rZrY)r[r_r`rarrr__exit__szdevice.__exit__N)r8r9r:__doc__rr\r^rbrrrrr s c@sNeZdZUdZeded<dedfddZddZd ed ed efd d Z dS) StreamContextaContext-manager that selects a given stream. All MTIA kernels queued within its context will be enqueued on a selected stream. Args: Stream (Stream): selected stream. This manager is a no-op if it's ``None``. .. note:: Streams are per-device. torch.mtia.Stream cur_streamrRcCstd|_||_tdd|_tjs|jdurd|_tjs dntjd|_ tjs1d|_ dStjd|_ dS)NTrX) rfrRrrYrjit is_scriptingr?rMsrc_prev_streamdst_prev_stream)r[rRrrrr\s     zStreamContext.__init__cCs|j}|dus |jdkrdStjd|_|jj|jkr9t|jtj|j|_Wdn1s4wYtj|dSNrX) rRrYrr?rJrir rjrU)r[rfrrrr^s zStreamContext.__enter__r_r`racCsJ|j}|dus |jdkrdS|jj|jkrtj|jtj|jdSrk)rRrYrir rr?rUrj)r[r_r`rarfrrrrbs zStreamContext.__exit__N) r8r9r:rcr__annotations__r\r^rrbrrrrrds  rdrecCst|S)a+Wrap around the Context-manager StreamContext that selects a given stream. Arguments: stream (Stream): selected stream. This manager is a no-op if it's ``None``. ..Note:: In eager mode stream is of type Stream class while in JIT it doesn't support torch.mtia.stream )rdrTrrrrRsr?cCs$tjdtddtjdgtj|dS)zReturns the random number generator state as a ByteTensor. Args: device (torch.device or int, optional): The device to return the RNG state of. Default: ``'mtia'`` (i.e., ``torch.device('mtia')``, the current mtia device). z.get_rng_state is not implemented in torch.mtia stacklevelr)dtyper )warningswarn UserWarningrzerosuint8rArrr get_rng_states rv new_statecCstjdtdddS)aSets the random number generator state. Args: new_state (torch.ByteTensor): The desired state device (torch.device or int, optional): The device to set the RNG state. Default: ``'mtia'`` (i.e., ``torch.device('mtia')``, the current mtia device). z.set_rng_state is not implemented in torch.mtiarmrnN)rqrrrs)rwr rrr set_rng_state,s   rx)*)rr>rrBr=rErJrM memory_statsmax_memory_allocatedrOrQrWrUrRr rxrv)rNr)r?)rBr=rErJrMrOrQrUrWrdrRrvrxmemory__all__rrrrsd$   3  :