+ &j&^RItR.t]tRt]!]P R4'd]P PtRt!RR]4tR#)N GreenContextF_CUDAGreenContextTc aa]tRt^toRt]RRRRRRRR/V3RlRll4t]RV3R lR ll4tV3R lV3R lltV3R lV3Rllt V3RlV3Rllt Rt Vt V;t #)rzmWrapper around a CUDA green context. .. warning:: This API is in beta and may change in future releases. num_smsNworkqueue_scopeworkqueue_concurrency_limit device_idc p<V^8dQhRS[R,RS[R,RS[R,RS[R,RS[/#)rNrrr return)intstr _GreenContext)format __classdict__s"q/Users/jameslopez/projects/CWCArchive/cwc-podcast/.venv/lib/python3.14/site-packages/torch/cuda/green_contexts.py __annotate__GreenContext.__annotate__sM" " t" t" &)4Z " : "  " c b\'g \R4h\PVVVVR7#)aCreate a CUDA green context. At least one of ``num_sms`` or ``workqueue_scope`` must be specified. Both can be combined to partition SMs and configure workqueues in the same green context. Arguments: num_sms (int, optional): The number of SMs to use in the green context. When ``None``, SMs are not partitioned. workqueue_scope (str, optional): Workqueue sharing scope. One of ``"device_ctx"`` (shared across all contexts, default driver behaviour) or ``"balanced"`` (non-overlapping workqueues with other balanced green contexts). When ``None``, no workqueue configuration is applied. workqueue_concurrency_limit (int, optional): Maximum number of concurrent stream-ordered workloads for the workqueue. Requires ``workqueue_scope`` to be set. device_id (int, optional): The device index of green context. When ``None``, the current device is used. 1PyTorch was not built with Green Context support!)r rrr) SUPPORTED RuntimeErrorrcreate)rrrr s$$$$rrGreenContext.creates98yRS S##+(C $  rc4<V^8dQhRS[R,RS[/#)r r Nr )r )rrs"rrr?s# L LS4Z L3 Lrc \\'g \R4h\PVR7#)a?Return the maximum workqueue concurrency limit for the device. This queries the device for the default number of concurrent stream-ordered workloads supported by workqueue configuration resources. Arguments: device_id (int, optional): The device index to query. When ``None``, the current device is used. rr )rrrmax_workqueue_concurrencyrs&rr&GreenContext.max_workqueue_concurrency>s)yRS S666KKrc<V^8dQhRR/#r r N)rrs"rrrPs%%T%rc <\SV`4#)z+Make the green context the current context.)super set_contextself __class__s&rr&GreenContext.set_contextPsw"$$rc<V^8dQhRR/#r"r#)rrs"rrrTs%%T%rc <\SV`4#)zsAssuming the green context is the current context, pop it from the context stack and restore the previous context. )r% pop_contextr's&rr-GreenContext.pop_contextTsw"$$rc<V^8dQhRR/#)r r ztorch.cuda.Streamr#)rrs"rrrZs  + rc <\SV`4#)z1Return the CUDA Stream used by the green context.)r%Streamr's&rr1GreenContext.StreamZsw~rr#)N)__name__ __module__ __qualname____firstlineno____doc__ staticmethodrrr&r-r1__static_attributes____classdictcell__ __classcell__)r)rs@@rrrs " "" '+" 37 " !% " " " H L L L"%%%%    r) torch__all__objectrrhasattr_Crrr#rrrAsT     588())HH..MI J =J r