==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/tools/profiler/daily_test, configfile: ../../../../../../../../sault/virtual_test/virtualenv_007/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 1 item test_func_profiler_base.py /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) [WARNING] ME(194793:281473554849584,MainProcess):2026-01-29-17:39:44.667.925 [mindspore/profiler/common/profiler_path_manager.py:51] Invalid parameter worker_name, reset it to default. [WARNING] ME(194793:281473554849584,MainProcess):2026-01-29-17:39:44.779.139 [mindspore/profiler/schedule.py:225] Profiler won't be using warmup, this can skew profiler results /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/profiler/common/profiler_parameters.py:226: UserWarning: The parameter 'hbm_ddr' will be deprecated in future versions. Please use 'profile_memory' in instead. warnings.warn( /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/profiler/common/profiler_parameters.py:221: UserWarning: The parameter 'pcie' will be deprecated in future versions. Please use 'sys_interconnection' in mindspore.profiler._ExperimentalConfig instead. warnings.warn( /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/profiler/common/profiler_parameters.py:241: UserWarning: When 'schedule' is set, 'data_process' will be set to False. warnings.warn("When 'schedule' is set, 'data_process' will be set to False.") ................ TotalTime = 1.59017, [30] [bootstrap]: 0.00102516 [type_inference]: 0.568099 [event_method]: 0.0185128 [auto_monad]: 0.0651556 [graph_reusing]: 8.181e-05 [pre_auto_parallel]: 2.188e-05 [py_interpret_to_execute]: 0.00238514 [rewriter_before_opt_a]: 0.00770371 [expand_dump_flag]: 3.377e-05 [jit_opt_a]: 0.778197, [2] [Cycle 1]: 0.646672, [27] [switch_simplify]: 0.00391333 [loop_unroll]: 0.0200721 [a_1]: 0.482422 [with_stream_mark]: 0.00250539 [recompute_prepare]: 0.00247165 [updatestate_depend_eliminate]: 0.00757943 [updatestate_assign_eliminate]: 0.00152781 [updatestate_loads_eliminate]: 0.0013082 [parameter_eliminate]: 5.85002e-06 [specialize_transform]: 0.00194849 [updatestate_useless_node_eliminater]: 0.00241968 [accelerated_algorithm]: 0.00332489 [meta_shard_fg_expand]: 0.00054779 [get_grad_eliminate_]: 0.00192694 [merge_forward]: 0.0012517 [cell_reuse_recompute_pass]: 5.47999e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00328026 [j_node_and_user_rematch]: 0.00312532 [meta_fg_expand]: 0.00137731 [replace_old_param]: 0.00258726 [inline_without_move]: 0.00217606 [renormalize]: 0.087586 [add_forward_monad_depend]: 1.94e-05 [auto_monad_grad]: 3.14999e-06 [auto_monad_eliminator]: 0.0038078 [cse]: 0.00682807 [replace_applicator]: 0.00196299 [Cycle 2]: 0.103906, [27] [switch_simplify]: 0.00197396 [loop_unroll]: 0.00196389 [a_1]: 0.0581205 [with_stream_mark]: 0.00166987 [recompute_prepare]: 0.0018586 [updatestate_depend_eliminate]: 0.00146309 [updatestate_assign_eliminate]: 0.00133022 [updatestate_loads_eliminate]: 0.00145962 [parameter_eliminate]: 4.67e-06 [specialize_transform]: 0.00198505 [updatestate_useless_node_eliminater]: 0.00247445 [accelerated_algorithm]: 0.00209937 [meta_shard_fg_expand]: 0.00073198 [get_grad_eliminate_]: 0.00219015 [merge_forward]: 0.00134192 [cell_reuse_recompute_pass]: 5.82999e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00334134 [j_node_and_user_rematch]: 0.00323517 [meta_fg_expand]: 0.00141989 [replace_old_param]: 0.00260148 [inline_without_move]: 0.00197125 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 1.088e-05 [auto_monad_grad]: 3.93999e-06 [auto_monad_eliminator]: 0.00342866 [cse]: 0.00477036 [replace_applicator]: 0.0019118 [py_interpret_to_execute_after_opt_a]: 0.00165652 [rewriter_after_opt_a]: 0.0149878 [convert_after_rewriter]: 0.00169827 [order_py_execute_after_rewriter]: 0.00130406 [mutable_eliminate]: 0.00276982 [jit_opt_b]: 0.0118565, [1] [Cycle 1]: 0.0118434, [2] [frontend_op_eliminate]: 0.00555111 [inline_after_opt_a]: 0.00623777 [cconv]: 0.00087063 [loop_unroll]: 0.00265653 [jit_opt_after_cconv]: 0.0287201, [1] [Cycle 1]: 0.0287061, [11] [c_1]: 0.0104263 [parameter_eliminate]: 7.5e-06 [updatestate_depend_eliminate]: 0.0015563 [updatestate_assign_eliminate]: 0.00138984 [updatestate_loads_eliminate]: 0.00136367 [cse]: 0.00484678 [call_graph_tuple_transform]: 0.00431423 [tuple_list_get_item_eliminator]: 0.00254747 [none_parameter_eliminate]: 4.89998e-06 [renormalize]: 8.30012e-07 [switch_simplify]: 0.00204175 [remove_dup_value]: 0.00401224 [partial_unused_args_eliminate]: 6.69001e-06 [environ_conv]: 0.00151473 [add_recomputation]: 0.0103026 [cse_after_recomputation]: 0.00456144, [1] [Cycle 1]: 0.0045361, [1] [cse]: 0.00450234 [auto_monad_reorder]: 0.0201062 [get_jit_bprop_graph]: 3.95e-06 [rewriter_after_jit_bprop_graph]: 0.0153711 [opt_after_jit_grad]: 0.00811758 [symbol_engine_optimizer]: 0.0108545, [1] [Cycle 1]: 0.0108427, [6] [build]: 0.00078147 [elim_shapecalc]: 0.00193826 [elim_not_effective]: 0.00304938 [opt_reshape]: 0.00195698 [fold_const_symbol]: 0.00300908 [renormalize]: 9.80013e-07 [validate]: 0.00462871 Sums bootstrap : 0.001025s : 0.07% type_inference : 0.568099s : 36.47% event_method : 0.018513s : 1.19% auto_monad : 0.065156s : 4.18% graph_reusing : 0.000082s : 0.01% pre_auto_parallel : 0.000022s : 0.00% py_interpret_to_execute : 0.002385s : 0.15% rewriter_before_opt_a : 0.007704s : 0.49% expand_dump_flag : 0.000034s : 0.00% jit_opt_a.switch_simplify : 0.005887s : 0.38% jit_opt_a.loop_unroll : 0.022036s : 1.41% jit_opt_a.a_1 : 0.540543s : 34.70% jit_opt_a.with_stream_mark : 0.004175s : 0.27% jit_opt_a.recompute_prepare : 0.004330s : 0.28% jit_opt_a.updatestate_depend_eliminate : 0.009043s : 0.58% jit_opt_a.updatestate_assign_eliminate : 0.002858s : 0.18% jit_opt_a.updatestate_loads_eliminate : 0.002768s : 0.18% jit_opt_a.parameter_eliminate : 0.000011s : 0.00% jit_opt_a.specialize_transform : 0.003934s : 0.25% jit_opt_a.updatestate_useless_node_eliminater : 0.004894s : 0.31% jit_opt_a.accelerated_algorithm : 0.005424s : 0.35% jit_opt_a.meta_shard_fg_expand : 0.001280s : 0.08% jit_opt_a.get_grad_eliminate_ : 0.004117s : 0.26% jit_opt_a.merge_forward : 0.002594s : 0.17% jit_opt_a.cell_reuse_recompute_pass : 0.000011s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.006622s : 0.43% jit_opt_a.j_node_and_user_rematch : 0.006360s : 0.41% jit_opt_a.meta_fg_expand : 0.002797s : 0.18% jit_opt_a.replace_old_param : 0.005189s : 0.33% jit_opt_a.inline_without_move : 0.004147s : 0.27% jit_opt_a.renormalize : 0.087586s : 5.62% jit_opt_a.add_forward_monad_depend : 0.000030s : 0.00% jit_opt_a.auto_monad_grad : 0.000007s : 0.00% jit_opt_a.auto_monad_eliminator : 0.007236s : 0.46% jit_opt_a.cse : 0.011598s : 0.74% jit_opt_a.replace_applicator : 0.003875s : 0.25% py_interpret_to_execute_after_opt_a : 0.001657s : 0.11% rewriter_after_opt_a : 0.014988s : 0.96% convert_after_rewriter : 0.001698s : 0.11% order_py_execute_after_rewriter : 0.001304s : 0.08% mutable_eliminate : 0.002770s : 0.18% jit_opt_b.frontend_op_eliminate : 0.005551s : 0.36% jit_opt_b.inline_after_opt_a : 0.006238s : 0.40% cconv : 0.000871s : 0.06% loop_unroll : 0.002657s : 0.17% jit_opt_after_cconv.c_1 : 0.010426s : 0.67% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.001556s : 0.10% jit_opt_after_cconv.updatestate_assign_eliminate : 0.001390s : 0.09% jit_opt_after_cconv.updatestate_loads_eliminate : 0.001364s : 0.09% jit_opt_after_cconv.cse : 0.004847s : 0.31% jit_opt_after_cconv.call_graph_tuple_transform : 0.004314s : 0.28% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.002547s : 0.16% jit_opt_after_cconv.none_parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.002042s : 0.13% remove_dup_value : 0.004012s : 0.26% partial_unused_args_eliminate : 0.000007s : 0.00% environ_conv : 0.001515s : 0.10% add_recomputation : 0.010303s : 0.66% cse_after_recomputation.cse : 0.004502s : 0.29% auto_monad_reorder : 0.020106s : 1.29% get_jit_bprop_graph : 0.000004s : 0.00% rewriter_after_jit_bprop_graph : 0.015371s : 0.99% opt_after_jit_grad : 0.008118s : 0.52% symbol_engine_optimizer.build : 0.000781s : 0.05% symbol_engine_optimizer.elim_shapecalc : 0.001938s : 0.12% symbol_engine_optimizer.elim_not_effective : 0.003049s : 0.20% symbol_engine_optimizer.opt_reshape : 0.001957s : 0.13% symbol_engine_optimizer.fold_const_symbol : 0.003009s : 0.19% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.004629s : 0.30% Time group info: ------[substitution.] 0.118367 35079 1.24% : 0.001472s : 987: substitution.depend_value_elim 0.32% : 0.000382s : 1313: substitution.elim_not_effective 0.32% : 0.000379s : 1313: substitution.fold_const_symbol 0.97% : 0.001142s : 1971: substitution.graph_param_transform 66.79% : 0.079061s : 997: substitution.inline 0.89% : 0.001051s : 2626: substitution.j_node_and_user_rematch 1.08% : 0.001283s : 2: substitution.less_batch_normalization 2.57% : 0.003038s : 3597: substitution.minmaximum_grad 2.41% : 0.002848s : 327: substitution.partial_eliminate 1.16% : 0.001375s : 2626: substitution.remove_not_recompute_node 0.53% : 0.000625s : 1316: substitution.replace_old_param 5.72% : 0.006768s : 3597: substitution.tuple_list_convert_item_index_to_positive 4.19% : 0.004956s : 3597: substitution.tuple_list_get_item_depend_reorder 6.00% : 0.007099s : 4905: substitution.tuple_list_get_item_eliminator 2.14% : 0.002531s : 2624: substitution.updatestate_pure_node_eliminater 3.68% : 0.004358s : 3281: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.563685 2 71.29% : 0.401866s : 1: type_inference.infer 28.71% : 0.161818s : 1: type_inference.specialize ------[replace.] 0.062363 1979 79.40% : 0.049515s : 997: replace.inline 12.82% : 0.007997s : 327: replace.partial_eliminate 7.77% : 0.004845s : 654: replace.tuple_list_get_item_eliminator 0.01% : 0.000006s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.082366 1979 95.42% : 0.078596s : 997: match.inline 3.29% : 0.002710s : 327: match.partial_eliminate 1.29% : 0.001059s : 654: match.tuple_list_get_item_eliminator 0.00% : 0.000001s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.087455581607 1.55% : 0.001355s : 10493: predicate.accumulaten_eliminater 0.46% : 0.000398s : 1971: predicate.ad_related_special_op_eliminate 1.56% : 0.001365s : 10493: predicate.addn_check_dump 2.91% : 0.002546s : 10493: predicate.addn_zero_filter 2.04% : 0.001786s : 10493: predicate.arithmetic_simplify 1.57% : 0.001372s : 10493: predicate.cast_eliminate 0.30% : 0.000262s : 1971: predicate.check_bprop_eliminate 1.55% : 0.001359s : 10493: predicate.compare_switch_simplify 1.58% : 0.001381s : 10493: predicate.depend_value_elim 1.54% : 0.001346s : 10493: predicate.dict_get_item_const_eliminator 1.62% : 0.001415s : 10493: predicate.dict_get_item_eliminator 1.53% : 0.001336s : 10493: predicate.dict_set_item_eliminator 0.33% : 0.000290s : 1971: predicate.dumpgradient_eliminate 0.17% : 0.000145s : 1971: predicate.elim_not_effective 0.39% : 0.000345s : 1971: predicate.elim_shapecalc_of_broadcastargs 1.53% : 0.001337s : 10493: predicate.environ_add_const_eliminate 1.60% : 0.001396s : 10493: predicate.environ_get_add_eliminate 1.55% : 0.001352s : 10493: predicate.environ_get_depend_swap 1.55% : 0.001355s : 10493: predicate.environ_get_eliminate 1.55% : 0.001359s : 10493: predicate.environ_get_set_eliminate 0.16% : 0.000144s : 1971: predicate.fold_const_symbol 0.79% : 0.000694s : 3942: predicate.get_grad_eliminate 0.14% : 0.000124s : 1971: predicate.graph_param_transform 3.79% : 0.003317s : 16414: predicate.inline 0.87% : 0.000758s : 3942: predicate.inline_without_move 0.33% : 0.000291s : 3942: predicate.j_node_and_user_rematch 0.84% : 0.000735s : 3942: predicate.less_batch_normalization 1.61% : 0.001409s : 11147: predicate.list_to_tuple_eliminator_ 2.17% : 0.001896s : 13445: predicate.load_eliminater 0.42% : 0.000370s : 1971: predicate.loop_unroll_after_grad 1.33% : 0.001166s : 5591: predicate.loop_unroll_before_grad 1.85% : 0.001616s : 12464: predicate.make_slice_get_slice_eliminator 1.55% : 0.001357s : 10493: predicate.merge_addn 1.66% : 0.001448s : 10493: predicate.minmaximum_grad 0.41% : 0.000362s : 1971: predicate.mutable_eliminate 0.38% : 0.000335s : 1971: predicate.opt_reshape 2.31% : 0.002024s : 13445: predicate.partial_eliminate 1.56% : 0.001362s : 10493: predicate.print_const_string_wrapper 1.91% : 0.001666s : 10493: predicate.reduce_eliminate 1.79% : 0.001562s : 11474: predicate.redundant_stop_gradient_eliminater 0.32% : 0.000284s : 3942: predicate.remove_not_recompute_node 1.55% : 0.001354s : 15089: predicate.replace_applicator 0.33% : 0.000289s : 3942: predicate.replace_old_param 0.17% : 0.000149s : 1971: predicate.reset_defer_inline 1.55% : 0.001356s : 10493: predicate.reshape_eliminate 1.62% : 0.001416s : 10493: predicate.row_tensor_add_zeros_like 0.31% : 0.000272s : 1971: predicate.row_tensor_eliminate 1.58% : 0.001379s : 10493: predicate.same_eliminate 0.39% : 0.000341s : 4600: predicate.set_cell_output_no_recompute 0.60% : 0.000520s : 3942: predicate.special_op_eliminate 0.83% : 0.000724s : 3942: predicate.specialize_transform 1.81% : 0.001582s : 10493: predicate.split_environ_get_set_with_tuple_value 2.16% : 0.001890s : 10493: predicate.stack_unstack_eliminate 0.32% : 0.000276s : 1971: predicate.switch_call_monad_eliminater 4.50% : 0.003934s : 12472: predicate.switch_defer_inline 2.02% : 0.001769s : 12472: predicate.switch_layer_defer_inline 3.46% : 0.003028s : 20034: predicate.switch_simplify 1.55% : 0.001357s : 10493: predicate.tile_eliminate 1.62% : 0.001421s : 10493: predicate.transpose_eliminate 1.93% : 0.001692s : 10493: predicate.tuple_list_convert_item_index_to_positive 1.80% : 0.001572s : 10493: predicate.tuple_list_get_item_depend_reorder 3.07% : 0.002687s : 15089: predicate.tuple_list_get_item_eliminator 1.96% : 0.001718s : 10493: predicate.tuple_list_set_item_eliminator 1.66% : 0.001455s : 11147: predicate.tuple_to_list_eliminator_ 2.16% : 0.001893s : 13445: predicate.updatestate_pure_node_eliminater 3.03% : 0.002647s : 17388: predicate.updatestate_useless_node_eliminater 4.18% : 0.003654s : 10493: predicate.value_based_eliminate 0.30% : 0.000262s : 1971: predicate.virtual_view_grad_eliminate 0.46% : 0.000400s : 1971: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.114764 1097 34.31% : 0.039374s : 98: func_graph_cloner_run.FuncGraphClonerGraph 45.02% : 0.051667s : 885: func_graph_cloner_run.FuncGraphClonerNode 20.67% : 0.023722s : 114: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.338342 72 0.44% : 0.010322s : 1: add_recomputation 2.79% : 0.065179s : 1: auto_monad 0.86% : 0.020131s : 1: auto_monad_reorder 0.05% : 0.001052s : 1: bootstrap 0.04% : 0.000881s : 1: cconv 0.07% : 0.001708s : 1: convert_after_rewriter 0.20% : 0.004569s : 1: cse_after_recomputation 0.07% : 0.001525s : 1: environ_conv 0.79% : 0.018546s : 1: event_method 0.00% : 0.000039s : 1: expand_dump_flag 0.00% : 0.000011s : 1: get_jit_bprop_graph 0.00% : 0.000087s : 1: graph_reusing 33.28% : 0.778203s : 1: jit_opt_a 1.23% : 0.028727s : 1: jit_opt_after_cconv 0.51% : 0.011862s : 1: jit_opt_b 0.11% : 0.002668s : 1: loop_unroll 0.12% : 0.002781s : 1: mutable_eliminate 26.40% : 0.617210s : 26: opt.transform.jit_opt_a 0.83% : 0.019306s : 4: opt.transform.jit_opt_after_cconv 0.50% : 0.011758s : 4: opt.transform.jit_opt_b 0.09% : 0.001998s : 1: opt.transform.loop_unroll_optimizer 0.09% : 0.002009s : 1: opt.transform.mutable_eliminate 0.25% : 0.005777s : 1: opt.transform.opt_after_jit_grad 0.43% : 0.009940s : 4: opt.transform.symbol_engine_opt 0.35% : 0.008135s : 1: opt_after_jit_grad 0.06% : 0.001312s : 1: order_py_execute_after_rewriter 0.00% : 0.000011s : 1: partial_unused_args_eliminate 0.00% : 0.000025s : 1: pre_auto_parallel 0.10% : 0.002395s : 1: py_interpret_to_execute 0.07% : 0.001667s : 1: py_interpret_to_execute_after_opt_a 0.17% : 0.004026s : 1: remove_dup_value 1.50% : 0.035082s : 1: renormalize.infer 2.24% : 0.052308s : 1: renormalize.specialize 0.66% : 0.015385s : 1: rewriter_after_jit_bprop_graph 0.64% : 0.015002s : 1: rewriter_after_opt_a 0.33% : 0.007719s : 1: rewriter_before_opt_a 0.46% : 0.010861s : 1: symbol_engine_optimizer 24.30% : 0.568126s : 1: type_inference ......[194793] Start parsing profiling data in sync mode at: /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms [2812] Parsing: [ ] 0/3 AscendMsprofParser Elapsed: 0s [2812] Parsing: [####### ] 1/3 AscendMsprofParser Elapsed: 13s [2812] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 13s [2812] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 14s [2812] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 15s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 16s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 16s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 17s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 18s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 19s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 20s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 21s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 23s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 24s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 25s [2812] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 26s [2812] Parsing: [####################] 3/3 Done Elapsed: 26s [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.805.811 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:323] /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/trace_view.json [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.806.860 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:574] trace_view_path is /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/trace_view.json [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.866.978 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:607] target_chars check_trace_view: ['MindSpore', 'CANN', 'Ascend Hardware', 'Overlap Analysis'] [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.908.492 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:323] /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/step_trace_time.csv [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.909.191 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:618] step_trace_time_path is /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/step_trace_time.csv [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.909.580 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:323] /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/kernel_details.csv [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.910.133 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:780] kernel_details_path is /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/kernel_details.csv [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.990.869 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:794] get step id {3, 4, 5, 6, 7} [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.991.086 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:795] set step id {3, 4, 5, 6, 7} [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.995.410 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:323] /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/api_statistic.csv [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:15.996.091 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:848] api_statistic_path is /tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/ASCEND_PROFILER_OUTPUT/api_statistic.csv [WARNING] ME(170395:281473558556464,MainProcess):2026-01-29-17:47:16.136.9 [mindspore/testcases/testcases/tests/st/tools/profiler/daily_test/profiler_check.py:1050] add_metadata_jsons_path：/tmp/tmpmdox14pi/prof_dir/ascend216_194793_20260129094636957_ascend_ms/profiler_metadata.json . [hook] pytest_runtest_teardown:test_profiler_llama2_train_001 tests/st/tools/profiler/daily_test/test_func_profiler_base.py::test_profiler_llama2_train_001,max_mem:2.0M =============================== warnings summary =============================== ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 1 passed, 25 warnings in 622.89s (0:10:22) ==================