a HSic=ã@szddlZddlZddlmZmZejdd„ƒZejdd„ƒZejj Z dd„Z d d „Z d d „Z eeeefd œdd„ZdS)éN)ÚListÚTuplec cs@tj ¡}tj |¡zdVWtj |¡ntj |¡0dS)z| A context manager that controls whether the JIT's executor will run optimizations before executing a function. N)ÚtorchÚ_CÚ_get_graph_executor_optimizeÚ_set_graph_executor_optimize)Zshould_optimizeZ stored_flag©rúL/var/www/html/django/DPS/env/lib/python3.9/site-packages/torch/jit/_fuser.pyÚoptimized_executions   r c cs¬tj ¡}tj ¡}tj ¡}tj ¡}|dkrbtj d¡tj d¡tj d¡tj  d¡n”|dkr´tj  d¡}tj  d¡}tj d¡tj d¡tj d¡tj  d¡nB|dkrîtj d¡tj d¡tj d¡tj  d¡nt dƒ‚z\dVW|dkr"tj  |¡tj  |¡tj |¡tj |¡tj |¡tj  |¡nT|dkrvtj  |¡tj  |¡tj |¡tj |¡tj |¡tj  |¡0dS)zÝ A context manager that facilitates switching between backend fusers. Valid names: * ``fuser0`` - enables only legacy fuser * ``fuser1`` - enables only NNC * ``fuser2`` - enables only nvFuser Zfuser0TFZfuser1Zfuser2zunrecognized fuser optionN) rrÚ_jit_can_fuse_on_cpuÚ_jit_can_fuse_on_gpuÚ_jit_texpr_fuser_enabledÚ_jit_nvfuser_enabledÚ_jit_override_can_fuse_on_cpuÚ_jit_override_can_fuse_on_gpuÚ_jit_set_texpr_fuser_enabledÚ_jit_set_nvfuser_enabledÚ_jit_set_profiling_executorrÚ Exception)ÚnameZ old_cpu_fuseZ old_gpu_fuseZold_texpr_fuser_stateZold_nvfuser_stateZold_profiling_executorZold_profiling_moderrr ÚfusersL                     ù      rcCsB| ¡dkr| |¡n&| ¡D]}| ¡D]}t||ƒq,q dS)Nzprim::DifferentiableGraph)ÚkindÚappendÚblocksÚnodesÚ_get_differentiable_graph_node)ÚnodeZ diff_nodeÚblockÚnrrr rDs     rcOst||g|¢Ri|¤ŽS)N)Ú_script_method_graph_for)ÚselfÚargsÚkwargsrrr Ú _graph_forLsr#c Osäz¸| ¡}t|j ¡ƒ}t|ƒdks(J‚|dj ¡}|dj ¡}g}|  ¡D]} t | |ƒqPt|ƒt|ƒkstJ‚t ||ƒD]4\} } t| j ¡ƒ} t| ƒdkr~|   d| dj¡q~|WSt yÞ||i|¤ŽtƒYS0dS)NérZSubgraph)Úget_debug_stateÚlistÚexecution_plansÚvaluesÚlenÚgraphÚcopyÚcodeÚ!differentiable_op_executor_statesrrÚzipÚg_rÚlast_executed_optimized_graph) r Úparentr!r"ZdbsÚepsr*Z fw_statesZ diff_nodesrÚstateZfw_execution_plansrrr rOs$    r©ÚstrategycCs tj |¡S)aa Sets the type and number of specializations that can occur during fusion. Usage: provide a list of pairs (type, depth) where type is one of "STATIC" or "DYNAMIC" and depth is an integer. Behavior - static vs dynamic: In STATIC fusion, fused ops are compiled to have fixed input shapes. The shape is determined based on some initial profiling runs. In DYNAMIC fusion, fused ops are compiled to have variable input shapes, so that multiple shapes are possible. In both cases, we also recompile on new striding behavior, device, or dtype. Behavior - fallback functions & depth: When an input doesn't match the format required by the specialized compiled op, it will run a fallback function. Fallback functions are recursively be compiled and specialized based on the observed tensor shapes. Since compilation can be slow, the "depth" parameter is provided to limit the number of specializations that can be compiled, before giving up on recompiling and falling back to a completely un-fused, un-specialized implementation. The list of (type, depth) pairs controls the type of specializations and the number of specializations. For example: [("STATIC", 2), ("DYNAMIC", 2)] indicates that the first two specializations will use static fusions, the following two specializations will use dynamic fusion, and any inputs that satisfy none of the 4 options will run an unfused implementation. NB: in the future, if more as more fusion backends are added there may be more granular apis for specific fusers. )rrÚ_jit_set_fusion_strategyr4rrr Úset_fusion_strategymsr7)Ú contextlibrÚtypingrrÚcontextmanagerr rrÚ_last_executed_optimized_graphr0rr#rÚstrÚintr7rrrr Ús  .