ɯwg2UddlmZddlZddlZddlZddlZddlZddlmZddlm Z ddl m Z m Z m Z mZmZddlmZddlmZerddlmZdadadagad ed <gZd ed <dadaejGd dZgaded<da da!da"dZ#eGddZ$dZ%GddZ&iZ'ded<eGddZ(e(jSdgde(jSdgde(jSdgd e(jSd!gd"e(jSd#gd$d%Z*d&Z+d'Z,d(Z-d)Z.d*Z/d+Z0d,Z1d-Z2d.Z3d/Z4e d3d0Z5d1Z6d2Z7y)4) annotationsN) dataclass) lru_cache)DictListSetTuple TYPE_CHECKING)config)get_benchmark_name)BaseSchedulerNodez#List[Tuple[BaseSchedulerNode, int]]nodes_num_elemz%List[Tuple[BaseSchedulerNode, float]] node_runtimesc&eZdZUded<dZded<y)CppOuterLoopFusedCountintinner_kernel_numberrlocal_buffer_numberN)__name__ __module__ __qualname____annotations__r\/home/mcse/projects/flask/flask-venv/lib/python3.12/site-packages/torch/_inductor/metrics.pyrr(s  rrzList[CppOuterLoopFusedCount]!cpp_outer_loop_fused_inner_countscdadadatj t j dadatj da da da y)Nr) generated_kernel_countgenerated_cpp_vec_kernel_countnum_bytes_accessedrclearrir_nodes_pre_fusioncpp_to_dtype_countrnum_comprehensive_padding)num_matches_for_scatter_upon_const_tensornum_loop_reorderingrrrresetr'8sX%&"%++- !01-rcNeZdZUdZded<ded<ded<ded<ded<ded<y ) CachedMetricsDeltasz] The subset of metrics we want update across cache hits, e.g., the FxGraphCache. rrrr"r#r r%N)rrr__doc__rrrrr)r)Ps-  $''/22rr)cntjtDcgc]}|jc}Scc}wN) dataclassesfieldsr)name)fields rget_metric_fieldsr1_s&$/$6$67J$K L5EJJ LL Ls2c2eZdZdZddZddZeddZy) CachedMetricsHelperz A helper class to help calculate and apply counter deltas for those metrics we want to save with cache entries (e.g., FxGraphCache) and apply on a cache hit. cdi|_tD]}t||j|<yr,)cached_metricsr1globals)selfmetrics r__init__zCachedMetricsHelper.__init__js3 ') ->> ? @ @ @s 7AA&c|j}|jdk(r/tjj |s|j |xjdz c_t |D]&\}}t|tr|d}n|d}n|}|||<(t|d5}tj|d}|j|dddy#1swYyxYw)Nrz.6far[r\) rXrJospathexistsre enumerate isinstancefloatr_r`rarb)r7rSrcidxorig_valnew_valrdras rrPzMetricTable._write_rows'')   ! #BGGNN8,D     q &s^ MC(E*%cN!"CH (C  !BZZ48F OOC  ! ! !s $)CCc.t||}|t|<yr,)rFrD)r/rItables rregister_tablezMetricTable.register_tablesD,/). &rN) rrrrrJrUrXrerPrCrurrrrFrFs@ONC$5@ !(//rrF slow_fusion) kernel1_pathkernel1_latency kernel2_pathkernel2_latencyfused_kernel_pathfused_kernel_latencyslow_down_ratio graph_stats)graph_idnum_nodes_before_fusionnum_nodes_after_fusionpersistent_red_perf) kernel1_name kernel2_namerxrz size_hintsreduction_hintspeedup'fusion_failure_due_to_indexing_mismatch)pre_grad_graph_idpost_grad_graph_id node1_name node2_namenode1_debug_strnode2_debug_strcommon_buffer_namesfailure_reasonkernel_metadata kernel_name kernel_pathkernel_categoryrr line_of_codenum_load num_store num_for_loopnum_atomic_addnum_argsxnumelynumelrnumelkernel_args_num_gbcddlm}ddlm}|j |}||}t j |jjS)z The kernel_module_code is the python module that contains kernel function code. kernel function is the proper triton kernel function annotated with @triton.jit rg) PyCodeCache)get_triton_kernel) codecacherwrapper_benchmarkrloadinspect getsourcefn)kernel_module_coderrmodkernels r_parse_kernel_fn_coder s@ '4   - .C s #F   VYY\\ **rc4t|jS)zJ Return the line of code for the kernel excluding the decorators. )rM splitlines)proper_kernel_fn_codes r_parse_kernel_line_of_coders $//1 22rcn|dk(rytjd|}|sJd|jdS)Nforeachzsize_hints=(\[[0-9, ]*\]),zsize_hints missing!rgresearchgroup)rrms r_parse_size_hintsr#s;)# /1CDA ###1 771:rcl|dvrytjd|}|sJd|jdS)N) reductionpersistent_reductionz$reduction_hint=ReductionHint\.(\w*),z/reduction_hint not found in kernel source code!rgr)rrrs r_parse_reduction_hintr,s<CC 9;MNA ???1 771:rc$|j|Sr,)count)rpatterns r_count_patternr4s & &w //rc|jd}|jdsJ|jd}|jd}||dz|}|jd}t |S)Nrdef (z):rg,)r startswithindexsplitrM)rdef_line start_idxend_idxdecl_csvcompss r _count_argsr8sm$//1!4H   v && &s#InnT"G A 0H NN3 E u:rc.|jd}||dS)z Skip decorators. rN)r)kernel_fn_code start_poss r_parse_proper_kernel_fn_coderBs!$$V,I )* %%rcntj|d|}|rt|jdSy)Nz = ([\d]+)rg)rrrr)rnumel_arg_namers r _parse_numelrJs3 ^$K02GHA1771:rcjtjd|}|rt|jdS y)z inductor meta looks like: inductor_meta={... 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