==================================================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_004/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_legacy_profiler_parse.py [WARNING] ME(163696:281472973266736,MainProcess):2026-01-29-17:37:25.837.7 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. [WARNING] ME(163696:281472973266736,MainProcess):2026-01-29-17:37:25.971.4 [mindspore/profiler/profiler.py:269] 'mindspore.Profiler' will be deprecated and removed in a future version. Please use the api 'mindspore.profiler.profile' instead. [WARNING] ME(163696:281472973266736,MainProcess):2026-01-29-17:37:26.433.28 [mindspore/profiler/schedule.py:225] Profiler won't be using warmup, this can skew profiler results TotalTime = 15.7097, [21] [bootstrap]: 0.00140913 [type_inference]: 13.0679 [event_method]: 0.0178399 [auto_monad]: 0.0407821 [graph_reusing]: 0.00047407 [inline]: 2.87002e-06 [add_attr]: 0.0619365, [1] [add_attr_with_inline]: 0.0619116, [1] [Cycle 1]: 0.00282309, [2] [tag_attr]: 0.00182365 [meta_addattr_fg_expand]: 0.0008642 [parallel-infer-symbol]: 4.49998e-06 [pre_auto_parallel]: 0.0185429 [insert-virtual-dataset]: 3.5e-06 [parallel-infer-symbol-second]: 4.98001e-06 [dataset_repeat_opt]: 3.3e-06 [pipeline_split]: 1.79e-06 [optimize]: 2.49756, [53] [py_interpret_to_execute]: 0.0230155 [rewriter_before_opt_a]: 0.0218759 [opt_a]: 2.33632, [2] [Cycle 1]: 2.21354, [45] [expand_dump_flag]: 0.00019854 [switch_simplify]: 0.0162153 [loop_unroll]: 0.0187331 [a_1]: 1.42261 [with_stream_mark]: 0.00068903 [recompute_prepare]: 0.00060135 [updatestate_depend_eliminate]: 0.011032 [updatestate_assign_eliminate]: 0.00039264 [updatestate_loads_eliminate]: 0.0102092 [parameter_eliminate]: 5.51e-06 [a_2]: 0.024908 [accelerated_algorithm]: 0.00065964 [shard]: 3.5e-06 [meta_shard_fg_expand]: 0.00018839 [shard_inline]: 0.00023906 [merge_send_recv]: 0.00016378 [auto_parallel]: 0.00013422 [parallel]: 8.715e-05 [flash_sp]: 7.301e-05 [merge_comm]: 0.00014071 [allreduce_fusion]: 0.00013411 [matmul_add_comm_reduction]: 0.0002031 [allreduce_slice_to_reducescatter]: 1.03001e-06 [virtual_shard_identity]: 0.00030628 [virtual_dataset]: 0.00875464 [get_grad_eliminate_]: 0.00034801 [virtual_output]: 0.00030559 [merge_forward]: 0.00031829 [cell_reuse_recompute_pass]: 4.92999e-06 [offload_activation]: 0.00022941 [cell_reuse_handle_not_recompute_node_pass]: 0.00056208 [merge_recompute_call_nodes]: 2.93e-06 [before_grad]: 0.00050757 [set_forward_comm_id_for_comm_node_pass]: 0.00026196 [meta_fg_expand]: 0.00031218 [flash_sp_send_recv_attached]: 1.42e-05 [receive_attached]: 1.826e-05 [after_resolve]: 0.00857715 [a_after_grad]: 0.00062909 [renormalize]: 0.667074 [add_forward_monad_depend]: 1.737e-05 [auto_monad_grad]: 3.43e-06 [auto_monad_eliminator]: 0.00117296 [cse]: 0.00120465 [a_3]: 0.0141756 [Cycle 2]: 0.122748, [45] [expand_dump_flag]: 4.82e-06 [switch_simplify]: 0.00024757 [loop_unroll]: 0.00024848 [a_1]: 0.0326531 [with_stream_mark]: 0.00033614 [recompute_prepare]: 0.00024986 [updatestate_depend_eliminate]: 0.00016697 [updatestate_assign_eliminate]: 0.00013985 [updatestate_loads_eliminate]: 0.00015513 [parameter_eliminate]: 3.25998e-06 [a_2]: 0.012051 [accelerated_algorithm]: 0.00857904 [shard]: 4.04002e-06 [meta_shard_fg_expand]: 0.00014446 [shard_inline]: 0.00029655 [merge_send_recv]: 0.00024326 [auto_parallel]: 0.00017471 [parallel]: 1.311e-05 [flash_sp]: 5.97001e-06 [merge_comm]: 0.0001802 [allreduce_fusion]: 0.00017124 [matmul_add_comm_reduction]: 0.00024854 [allreduce_slice_to_reducescatter]: 1.32e-06 [virtual_shard_identity]: 0.00027475 [virtual_dataset]: 0.00027621 [get_grad_eliminate_]: 0.00026611 [virtual_output]: 0.00026092 [merge_forward]: 0.00018263 [cell_reuse_recompute_pass]: 3.78001e-06 [offload_activation]: 0.00026384 [cell_reuse_handle_not_recompute_node_pass]: 0.0088026 [merge_recompute_call_nodes]: 4.74e-06 [before_grad]: 0.00049123 [set_forward_comm_id_for_comm_node_pass]: 0.00026504 [meta_fg_expand]: 0.0001932 [flash_sp_send_recv_attached]: 2.88998e-06 [receive_attached]: 3.23e-06 [after_resolve]: 0.00028739 [a_after_grad]: 0.00037919 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 9.16998e-06 [auto_monad_grad]: 2.81999e-06 [auto_monad_eliminator]: 0.00043471 [cse]: 0.00075506 [a_3]: 0.052504 [py_interpret_to_execute_after_opt_a]: 0.00038935 [slice_cell_reuse_recomputed_activation]: 3.52002e-06 [rewriter_after_opt_a]: 0.0128902 [convert_after_rewriter]: 0.0002996 [order_py_execute_after_rewriter]: 0.00014484 [mutable_eliminate]: 0.00951281 [opt_b]: 0.0247124, [1] [Cycle 1]: 0.0246949, [7] [b_1]: 0.0144927 [b_2]: 0.00025052 [updatestate_depend_eliminate]: 0.00022846 [updatestate_assign_eliminate]: 0.00014938 [updatestate_loads_eliminate]: 0.00016747 [renormalize]: 1.05999e-06 [cse]: 0.00103804 [optimize_parallel_all_gather_comm]: 0.00039277 [overlap_param_gather]: 3.37002e-06 [cconv]: 0.00013143 [loop_unroll]: 0.00105937 [opt_after_cconv]: 0.011327, [1] [Cycle 1]: 0.011312, [7] [c_1]: 0.00966317 [parameter_eliminate]: 7.97e-06 [updatestate_depend_eliminate]: 0.00043358 [updatestate_assign_eliminate]: 0.00016587 [updatestate_loads_eliminate]: 0.00016602 [cse]: 0.00074494 [renormalize]: 1.03001e-06 [remove_dup_value]: 0.00109654 [tuple_transform]: 0.0107913, [1] [Cycle 1]: 0.0107742, [4] [d_1]: 0.0103689 [none_parameter_eliminate]: 7.13998e-06 [renormalize]: 8.2e-07 [switch_simplify]: 0.00030591 [partial_unused_args_eliminate]: 3.73001e-06 [add_recomputation]: 0.00184459 [cse_after_recomputation]: 0.0252444, [1] [Cycle 1]: 0.0252271, [1] [cse]: 0.025153 [environ_conv]: 0.00025044 [swap_dp_allreduce_reducescatter]: 0.00034649 [bias_add_comm_swap]: 4.13001e-06 [label_micro_interleaved_index]: 9.51998e-06 [label_fine_grained_interleaved_index]: 3.72998e-06 [merge_cast_opt]: 1.37e-06 [slice_recompute_activation]: 2.15002e-06 [micro_interleaved_order_control]: 3.00998e-06 [assign_add_opt]: 1.57999e-06 [ForceFp32Comm]: 1.02e-06 [remove_cast_before_assign_add]: 1.22e-06 [full_micro_interleaved_order_control]: 2.44001e-06 [reorder_send_recv_between_fp_bp]: 2.78e-06 [comm_op_add_attrs]: 1.36002e-06 [add_comm_op_reuse_tag]: 9.39996e-07 [interleave_split_concat_branches]: 1.29e-06 [interleave_parallel_branches]: 1.35999e-06 [overlap_opt_shard_in_pipeline]: 2.888e-05 [overlap_opt_shard_grad_in_pipeline]: 2.00002e-06 [control_data_broadcast_order]: 0.00036809 [grouped_pairwise_exchange_alltoall]: 2.06e-06 [offloading_packed_experts]: 7.972e-05 [overlap_recompute_and_grad_model_parallel]: 7.69e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.59998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.37999e-06 [overlap_recompute_comm]: 2.73998e-06 [overlap_grad_ring_attention]: 7.514e-05 [overlap_grad_flash_sp]: 0.0004807 [begin_end_overlap_inline]: 8.2e-07 [split_matmul_comm_elemetwise]: 2.68e-06 [split_layernorm_comm]: 1.82001e-06 [handle_group_info]: 1.34e-06 [symbol_engine_optimizer]: 0.0140504, [1] [Cycle 1]: 0.01403, [6] [build]: 0.00014524 [elim_shapecalc]: 0.00029184 [elim_not_effective]: 0.00042873 [opt_reshape]: 0.00025271 [fold_const_symbol]: 0.0127749 [renormalize]: 1.27e-06 [detach_backward]: 3.65e-06 [pipeline_parallel_scheduler]: 2.00002e-06 [auto_monad_reorder]: 0.00063159 [get_jit_bprop_graph]: 2.66999e-06 [rewriter_after_jit_bprop_graph]: 8.54e-06 [opt_after_jit_grad]: 0.00167586 [validate]: 0.00053547 Sums bootstrap : 0.001409s : 0.01% type_inference : 13.067929s : 83.56% event_method : 0.017840s : 0.11% auto_monad : 0.040782s : 0.26% graph_reusing : 0.000474s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.001824s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000864s : 0.01% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.018543s : 0.12% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000005s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.023015s : 0.15% optimize.rewriter_before_opt_a : 0.021876s : 0.14% optimize.opt_a.expand_dump_flag : 0.000203s : 0.00% optimize.opt_a.switch_simplify : 0.016463s : 0.11% optimize.opt_a.loop_unroll : 0.018982s : 0.12% optimize.opt_a.a_1 : 1.455266s : 9.31% optimize.opt_a.with_stream_mark : 0.001025s : 0.01% optimize.opt_a.recompute_prepare : 0.000851s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.011199s : 0.07% optimize.opt_a.updatestate_assign_eliminate : 0.000532s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.010364s : 0.07% optimize.opt_a.parameter_eliminate : 0.000009s : 0.00% optimize.opt_a.a_2 : 0.036959s : 0.24% optimize.opt_a.accelerated_algorithm : 0.009239s : 0.06% optimize.opt_a.shard : 0.000008s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000333s : 0.00% optimize.opt_a.shard_inline : 0.000536s : 0.00% optimize.opt_a.merge_send_recv : 0.000407s : 0.00% optimize.opt_a.auto_parallel : 0.000309s : 0.00% optimize.opt_a.parallel : 0.000100s : 0.00% optimize.opt_a.flash_sp : 0.000079s : 0.00% optimize.opt_a.merge_comm : 0.000321s : 0.00% optimize.opt_a.allreduce_fusion : 0.000305s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000452s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000581s : 0.00% optimize.opt_a.virtual_dataset : 0.009031s : 0.06% optimize.opt_a.get_grad_eliminate_ : 0.000614s : 0.00% optimize.opt_a.virtual_output : 0.000567s : 0.00% optimize.opt_a.merge_forward : 0.000501s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% optimize.opt_a.offload_activation : 0.000493s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.009365s : 0.06% optimize.opt_a.merge_recompute_call_nodes : 0.000008s : 0.00% optimize.opt_a.before_grad : 0.000999s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000527s : 0.00% optimize.opt_a.meta_fg_expand : 0.000505s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000017s : 0.00% optimize.opt_a.receive_attached : 0.000021s : 0.00% optimize.opt_a.after_resolve : 0.008865s : 0.06% optimize.opt_a.a_after_grad : 0.001008s : 0.01% optimize.opt_a.renormalize : 0.667074s : 4.27% optimize.opt_a.add_forward_monad_depend : 0.000027s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.001608s : 0.01% optimize.opt_a.cse : 0.001960s : 0.01% optimize.opt_a.a_3 : 0.066680s : 0.43% optimize.py_interpret_to_execute_after_opt_a : 0.000389s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000004s : 0.00% optimize.rewriter_after_opt_a : 0.012890s : 0.08% optimize.convert_after_rewriter : 0.000300s : 0.00% optimize.order_py_execute_after_rewriter : 0.000145s : 0.00% optimize.mutable_eliminate : 0.009513s : 0.06% optimize.opt_b.b_1 : 0.014493s : 0.09% optimize.opt_b.b_2 : 0.000251s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000228s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000149s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000167s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.001038s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000393s : 0.00% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000131s : 0.00% optimize.loop_unroll : 0.001059s : 0.01% optimize.opt_after_cconv.c_1 : 0.009663s : 0.06% optimize.opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000434s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000166s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000166s : 0.00% optimize.opt_after_cconv.cse : 0.000745s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.001097s : 0.01% optimize.tuple_transform.d_1 : 0.010369s : 0.07% optimize.tuple_transform.none_parameter_eliminate : 0.000007s : 0.00% optimize.tuple_transform.renormalize : 0.000001s : 0.00% optimize.tuple_transform.switch_simplify : 0.000306s : 0.00% optimize.partial_unused_args_eliminate : 0.000004s : 0.00% optimize.add_recomputation : 0.001845s : 0.01% optimize.cse_after_recomputation.cse : 0.025153s : 0.16% optimize.environ_conv : 0.000250s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000346s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000010s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000004s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000029s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000368s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000080s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000077s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000002s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000075s : 0.00% optimize.overlap_grad_flash_sp : 0.000481s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000145s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000292s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000429s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000253s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.012775s : 0.08% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000004s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000632s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.001676s : 0.01% validate : 0.000535s : 0.00% Time group info: ------[substitution.] 0.412344 10208 0.21% : 0.000860s : 160: substitution.arithmetic_simplify 0.04% : 0.000162s : 14: substitution.cast_eliminate 0.01% : 0.000028s : 9: substitution.depend_value_elim 0.01% : 0.000055s : 180: substitution.elim_not_effective 0.02% : 0.000079s : 100: substitution.float_tuple_getitem_switch 0.01% : 0.000056s : 180: substitution.fold_const_symbol 0.04% : 0.000175s : 227: substitution.graph_param_transform 77.84% : 0.320966s : 855: substitution.inline 0.04% : 0.000164s : 360: substitution.j_node_and_user_rematch 0.10% : 0.000395s : 44: substitution.less_batch_normalization 0.03% : 0.000143s : 228: substitution.load_eliminater 2.18% : 0.008984s : 503: substitution.minmaximum_grad 0.00% : 0.000011s : 23: substitution.opt_reshape 0.05% : 0.000204s : 360: substitution.remove_not_recompute_node 0.01% : 0.000046s : 72: substitution.replace_old_param 3.16% : 0.013027s : 150: substitution.reshape_eliminate 0.05% : 0.000199s : 73: substitution.switch_simplify 0.12% : 0.000481s : 135: substitution.transpose_eliminate 4.35% : 0.017953s : 553: substitution.tuple_list_convert_item_index_to_positive 0.24% : 0.000982s : 724: substitution.tuple_list_get_item_const_eliminator 7.56% : 0.031172s : 724: substitution.tuple_list_get_item_depend_reorder 2.68% : 0.011040s : 907: substitution.tuple_list_get_item_eliminator 0.33% : 0.001364s : 724: substitution.tuple_list_get_set_item_eliminator 0.32% : 0.001328s : 1446: substitution.updatestate_pure_node_eliminater 0.60% : 0.002468s : 1457: substitution.updatestate_useless_node_eliminater ------[type_inference.] 13.065030 2 93.72% : 12.244549s : 1: type_inference.infer 6.28% : 0.820481s : 1: type_inference.specialize ------[replace.] 0.243306 1246 0.07% : 0.000164s : 14: replace.cast_eliminate 0.03% : 0.000085s : 5: replace.depend_value_elim 92.79% : 0.225758s : 855: replace.inline 0.05% : 0.000114s : 12: replace.reshape_eliminate 0.43% : 0.001040s : 73: replace.switch_simplify 0.99% : 0.002418s : 171: replace.tuple_list_get_item_depend_reorder 5.62% : 0.013673s : 108: replace.tuple_list_get_item_eliminator 0.02% : 0.000053s : 8: replace.updatestate_useless_node_eliminater ------[match.] 0.334728 1246 0.05% : 0.000151s : 14: match.cast_eliminate 0.00% : 0.000003s : 5: match.depend_value_elim 95.67% : 0.320234s : 855: match.inline 0.02% : 0.000053s : 12: match.reshape_eliminate 0.05% : 0.000154s : 73: match.switch_simplify 4.09% : 0.013681s : 171: match.tuple_list_get_item_depend_reorder 0.13% : 0.000436s : 108: match.tuple_list_get_item_eliminator 0.00% : 0.000016s : 8: match.updatestate_useless_node_eliminater ------[predicate.] 0.098420175493 0.46% : 0.000449s : 2713: predicate.accumulaten_eliminater 0.05% : 0.000050s : 227: predicate.ad_related_special_op_eliminate 0.10% : 0.000099s : 703: predicate.addn_check_dump 0.43% : 0.000419s : 2713: predicate.addn_zero_filter 0.41% : 0.000401s : 2713: predicate.adjust_all_reduce_mul_add 0.71% : 0.000702s : 3416: predicate.arithmetic_simplify 0.43% : 0.000422s : 2739: predicate.cast_eliminate 0.21% : 0.000207s : 454: predicate.check_bprop_eliminate 0.10% : 0.000103s : 703: predicate.compare_switch_simplify 0.02% : 0.000017s : 227: predicate.const_output_eliminate 0.12% : 0.000117s : 707: predicate.depend_value_elim 0.44% : 0.000431s : 2739: predicate.dict_get_item_const_eliminator 0.49% : 0.000483s : 2739: predicate.dict_get_item_eliminator 0.40% : 0.000399s : 2739: predicate.dict_set_item_eliminator 0.07% : 0.000069s : 454: predicate.dumpgradient_eliminate 0.02% : 0.000016s : 227: predicate.elim_not_effective 0.04% : 0.000042s : 227: predicate.elim_shapecalc_of_broadcastargs 0.47% : 0.000464s : 2966: predicate.environ_add_const_eliminate 0.45% : 0.000442s : 2966: predicate.environ_get_add_eliminate 0.44% : 0.000433s : 2966: predicate.environ_get_depend_swap 6.38% : 0.006284s : 3669: predicate.environ_get_eliminate 0.45% : 0.000444s : 2966: predicate.environ_get_set_eliminate 0.61% : 0.000597s : 3881: predicate.exchange_switch_depend_value 0.83% : 0.000820s : 3881: predicate.float_depend_g_call 0.10% : 0.000101s : 703: predicate.float_environ_get_switch 0.14% : 0.000140s : 930: predicate.float_tuple_getitem_switch 0.02% : 0.000018s : 227: predicate.fold_const_symbol 0.10% : 0.000098s : 462: predicate.get_grad_eliminate 0.02% : 0.000019s : 227: predicate.graph_param_transform 0.17% : 0.000163s : 703: predicate.incorporate_call 0.15% : 0.000143s : 703: predicate.incorporate_call_switch 1.82% : 0.001790s : 8213: predicate.inline 0.15% : 0.000143s : 462: predicate.inline_without_move 0.03% : 0.000032s : 462: predicate.j_node_and_user_rematch 0.17% : 0.000164s : 462: predicate.less_batch_normalization 0.55% : 0.000538s : 3472: predicate.list_to_tuple_eliminator_ 1.01% : 0.000995s : 6185: predicate.load_eliminater 0.05% : 0.000053s : 227: predicate.loop_unroll_after_grad 0.74% : 0.000733s : 2096: predicate.loop_unroll_before_grad 0.52% : 0.000516s : 3364: predicate.make_slice_get_slice_eliminator 0.11% : 0.000106s : 703: predicate.merge_addn 0.07% : 0.000069s : 454: predicate.micro_step_allgather_replace 0.07% : 0.000067s : 454: predicate.mini_step_allgather_replace 0.47% : 0.000464s : 2713: predicate.minmaximum_grad 0.12% : 0.000119s : 227: predicate.mutable_eliminate 0.04% : 0.000035s : 227: predicate.opt_reshape 0.04% : 0.000039s : 227: predicate.parallel_virtual_node 1.62% : 0.001595s : 3881: predicate.partial_defer_inline 0.53% : 0.000523s : 3245: predicate.partial_eliminate 0.41% : 0.000408s : 2713: predicate.print_const_string_wrapper 0.11% : 0.000106s : 697: predicate.reduce_all_const_elim 0.56% : 0.000552s : 2713: predicate.reduce_eliminate 0.90% : 0.000884s : 6185: predicate.redundant_stop_gradient_eliminater 0.03% : 0.000034s : 462: predicate.remove_not_recompute_node 0.34% : 0.000333s : 3472: predicate.replace_applicator 0.04% : 0.000035s : 462: predicate.replace_old_param 0.02% : 0.000017s : 227: predicate.reset_defer_inline 0.49% : 0.000485s : 2725: predicate.reshape_eliminate 0.07% : 0.000068s : 454: predicate.row_tensor_add_zeros_like 0.04% : 0.000040s : 227: predicate.row_tensor_eliminate 0.09% : 0.000085s : 454: predicate.same_eliminate 0.06% : 0.000060s : 796: predicate.set_cell_output_no_recompute 0.08% : 0.000083s : 462: predicate.shard_identity_eliminate 0.07% : 0.000069s : 454: predicate.special_op_eliminate 0.14% : 0.000140s : 703: predicate.specialize_transform 0.08% : 0.000075s : 454: predicate.split_environ_get_set_with_tuple_value 0.07% : 0.000073s : 462: predicate.stack_unstack_eliminate 8.34% : 0.008209s : 227: predicate.switch_call_monad_eliminater 0.67% : 0.000662s : 3881: predicate.switch_defer_inline 0.76% : 0.000750s : 4335: predicate.switch_layer_defer_inline 26.40% : 0.025983s : 7053: predicate.switch_simplify 0.42% : 0.000410s : 2713: predicate.tile_eliminate 0.47% : 0.000458s : 2713: predicate.transpose_eliminate 0.56% : 0.000548s : 3193: predicate.tuple_list_convert_item_index_to_positive 0.61% : 0.000599s : 3364: predicate.tuple_list_get_item_const_eliminator 0.61% : 0.000600s : 3364: predicate.tuple_list_get_item_depend_reorder 0.98% : 0.000967s : 4175: predicate.tuple_list_get_item_eliminator 0.56% : 0.000552s : 3364: predicate.tuple_list_get_set_item_eliminator 0.75% : 0.000740s : 4067: predicate.tuple_list_set_item_eliminator 0.55% : 0.000545s : 3472: predicate.tuple_to_list_eliminator_ 13.76% : 0.013545s : 6185: predicate.updatestate_pure_node_eliminater 9.33% : 0.009182s : 6896: predicate.updatestate_useless_node_eliminater 0.04% : 0.000043s : 227: predicate.value_based_eliminate 8.48% : 0.008350s : 462: predicate.virtual_dataset_eliminate 0.09% : 0.000085s : 462: predicate.virtual_output_eliminate 0.03% : 0.000029s : 227: predicate.virtual_view_grad_eliminate 0.04% : 0.000044s : 227: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.832074 1066 56.59% : 0.470835s : 474: func_graph_cloner_run.FuncGraphClonerGraph 15.86% : 0.131935s : 227: func_graph_cloner_run.FuncGraphClonerNode 27.56% : 0.229304s : 365: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 20.621211 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.30% : 0.061944s : 1: add_attr 0.30% : 0.061920s : 1: add_attr_with_inline 0.00% : 0.000005s : 1: add_comm_op_reuse_tag 0.01% : 0.001881s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.20% : 0.040825s : 1: auto_monad 0.00% : 0.000645s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: begin_end_overlap_inline 0.00% : 0.000009s : 1: bias_add_comm_swap 0.01% : 0.001450s : 1: bootstrap 0.00% : 0.000141s : 1: cconv 0.00% : 0.000006s : 1: comm_op_add_attrs 0.00% : 0.000377s : 1: control_data_broadcast_order 0.00% : 0.000315s : 1: convert_after_rewriter 0.12% : 0.025256s : 1: cse_after_recomputation 0.00% : 0.000007s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000267s : 1: environ_conv 0.09% : 0.017885s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000010s : 1: get_jit_bprop_graph 0.00% : 0.000491s : 1: graph_reusing 0.00% : 0.000007s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000008s : 1: inline 0.00% : 0.000011s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000010s : 1: label_fine_grained_interleaved_index 0.00% : 0.000014s : 1: label_micro_interleaved_index 0.01% : 0.001072s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.05% : 0.009546s : 1: mutable_eliminate 0.00% : 0.000084s : 1: offloading_packed_experts 0.00% : 0.000295s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000433s : 1: opt.transform.mutable_eliminate 7.93% : 1.635561s : 95: opt.transform.opt_a 0.05% : 0.009656s : 1: opt.transform.opt_after_cconv 0.00% : 0.000745s : 1: opt.transform.opt_after_jit_grad 0.07% : 0.014643s : 28: opt.transform.opt_b 0.05% : 0.010659s : 2: opt.transform.opt_trans_graph 0.07% : 0.013734s : 4: opt.transform.symbol_engine_opt 11.33% : 2.336332s : 1: opt_a 0.05% : 0.011333s : 1: opt_after_cconv 0.01% : 0.001692s : 1: opt_after_jit_grad 0.12% : 0.024722s : 1: opt_b 12.11% : 2.497563s : 1: optimize 0.00% : 0.000406s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000154s : 1: order_py_execute_after_rewriter 0.00% : 0.000493s : 1: overlap_grad_flash_sp 0.00% : 0.000007s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000080s : 1: overlap_grad_ring_attention 0.00% : 0.000007s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000035s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000083s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000010s : 1: parallel-infer-symbol 0.00% : 0.000011s : 1: parallel-infer-symbol-second 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.09% : 0.018587s : 1: pre_auto_parallel 0.11% : 0.023066s : 1: py_interpret_to_execute 0.00% : 0.000402s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.01% : 0.001111s : 1: remove_dup_value 1.88% : 0.387831s : 1: renormalize.infer 1.35% : 0.279207s : 1: renormalize.specialize 0.00% : 0.000007s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.06% : 0.012920s : 1: rewriter_after_opt_a 0.11% : 0.021922s : 1: rewriter_before_opt_a 0.00% : 0.000009s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000008s : 1: slice_recompute_activation 0.00% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000357s : 1: swap_dp_allreduce_reducescatter 0.07% : 0.014059s : 1: symbol_engine_optimizer 0.05% : 0.010800s : 1: tuple_transform 63.37% : 13.067967s : 1: type_inference .[163696] Start parsing profiling data in sync mode at: /tmp/tmpgcv0x1tc/ascend216_163696_20260129093726046_ascend_ms [103968] Parsing: [ ] 0/3 AscendMsprofParser Elapsed: 0s [103968] Parsing: [####### ] 1/3 AscendMsprofParser Elapsed: 72s [103968] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 72s [103968] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 72s [103968] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 73s [103968] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 74s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 74s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 75s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 76s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 77s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 78s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 79s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 80s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 81s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 82s [103968] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 83s [103968] Parsing: [####################] 3/3 Done Elapsed: 84s . [hook] pytest_runtest_teardown:test_profiler_analyse_pretty_true_010 tests/st/tools/profiler/daily_test/test_legacy_profiler_parse.py::test_profiler_analyse_pretty_true_010,max_mem:4.0M =============================== 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") test_legacy_profiler_parse.py::test_profiler_analyse_pretty_true_010 /usr/local/Ascend/cann-8.5.0/python/site-packages/asc_op_compile_base/asc_op_compiler/ascendc_compile_gen_code.py:161: DeprecationWarning: invalid escape sequence \w match = re.search(f'{option}=(\w+)', ' '.join(compile_options)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 1 passed, 26 warnings in 338.37s (0:05:38) ==================