==================================================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_002/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(168984:281473518067504,MainProcess):2026-01-29-17:37:38.952.079 [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(168984:281473518067504,MainProcess):2026-01-29-17:37:38.953.153 [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(168984:281473518067504,MainProcess):2026-01-29-17:37:41.107.701 [mindspore/profiler/schedule.py:225] Profiler won't be using warmup, this can skew profiler results TotalTime = 30.3088, [21] [bootstrap]: 0.00150159 [type_inference]: 25.9962 [event_method]: 0.00289814 [auto_monad]: 0.135754 [graph_reusing]: 0.00081898 [inline]: 3.43e-06 [add_attr]: 0.0937388, [1] [add_attr_with_inline]: 0.0937123, [1] [Cycle 1]: 0.00469793, [2] [tag_attr]: 0.0031257 [meta_addattr_fg_expand]: 0.00140481 [parallel-infer-symbol]: 5.62001e-06 [pre_auto_parallel]: 0.0269363 [insert-virtual-dataset]: 3.95e-06 [parallel-infer-symbol-second]: 5.54998e-06 [dataset_repeat_opt]: 1.953e-05 [pipeline_split]: 2.09e-06 [optimize]: 4.04698, [53] [py_interpret_to_execute]: 0.095514 [rewriter_before_opt_a]: 0.00917155 [opt_a]: 3.76481, [2] [Cycle 1]: 3.51296, [45] [expand_dump_flag]: 0.00030858 [switch_simplify]: 0.00613012 [loop_unroll]: 0.00347227 [a_1]: 1.6048 [with_stream_mark]: 0.00136189 [recompute_prepare]: 0.00078003 [updatestate_depend_eliminate]: 0.00451104 [updatestate_assign_eliminate]: 0.00068642 [updatestate_loads_eliminate]: 0.187321 [parameter_eliminate]: 8.74e-06 [a_2]: 0.0312581 [accelerated_algorithm]: 0.00124005 [shard]: 3.66999e-06 [meta_shard_fg_expand]: 0.00045349 [shard_inline]: 0.00034032 [merge_send_recv]: 0.00026412 [auto_parallel]: 0.00017294 [parallel]: 0.00013986 [flash_sp]: 0.00012733 [merge_comm]: 0.00020213 [allreduce_fusion]: 0.00018499 [matmul_add_comm_reduction]: 0.00026454 [allreduce_slice_to_reducescatter]: 1.23002e-06 [virtual_shard_identity]: 0.00046734 [virtual_dataset]: 0.00044941 [get_grad_eliminate_]: 0.00041437 [virtual_output]: 0.00042032 [merge_forward]: 0.00043941 [cell_reuse_recompute_pass]: 6.16e-06 [offload_activation]: 0.00028914 [cell_reuse_handle_not_recompute_node_pass]: 0.0007095 [merge_recompute_call_nodes]: 3.58e-06 [before_grad]: 0.00077598 [set_forward_comm_id_for_comm_node_pass]: 0.00046472 [meta_fg_expand]: 0.0004594 [flash_sp_send_recv_attached]: 1.658e-05 [receive_attached]: 1.602e-05 [after_resolve]: 0.00048056 [a_after_grad]: 0.00070456 [renormalize]: 1.65625 [add_forward_monad_depend]: 2.059e-05 [auto_monad_grad]: 3.34001e-06 [auto_monad_eliminator]: 0.00149822 [cse]: 0.001585 [a_3]: 0.00201717 [Cycle 2]: 0.251813, [45] [expand_dump_flag]: 5.00999e-06 [switch_simplify]: 0.00028623 [loop_unroll]: 0.00027339 [a_1]: 0.00901509 [with_stream_mark]: 0.0006192 [recompute_prepare]: 0.00033763 [updatestate_depend_eliminate]: 0.0002523 [updatestate_assign_eliminate]: 0.00017498 [updatestate_loads_eliminate]: 0.00019638 [parameter_eliminate]: 5.53002e-06 [a_2]: 0.00465535 [accelerated_algorithm]: 0.00037942 [shard]: 4.50001e-06 [meta_shard_fg_expand]: 0.0002203 [shard_inline]: 0.00033912 [merge_send_recv]: 0.00030868 [auto_parallel]: 0.00020391 [parallel]: 1.63e-05 [flash_sp]: 6.74001e-06 [merge_comm]: 0.224612 [allreduce_fusion]: 0.00044356 [matmul_add_comm_reduction]: 0.00031076 [allreduce_slice_to_reducescatter]: 1.50999e-06 [virtual_shard_identity]: 0.00036665 [virtual_dataset]: 0.00031968 [get_grad_eliminate_]: 0.00027777 [virtual_output]: 0.00027727 [merge_forward]: 0.00026475 [cell_reuse_recompute_pass]: 6.36e-06 [offload_activation]: 0.00031355 [cell_reuse_handle_not_recompute_node_pass]: 0.00057479 [merge_recompute_call_nodes]: 3.35e-06 [before_grad]: 0.00050465 [set_forward_comm_id_for_comm_node_pass]: 0.00030784 [meta_fg_expand]: 0.00030681 [flash_sp_send_recv_attached]: 4.65999e-06 [receive_attached]: 4.1e-06 [after_resolve]: 0.00040084 [a_after_grad]: 0.0004402 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.069e-05 [auto_monad_grad]: 4.23999e-06 [auto_monad_eliminator]: 0.00057847 [cse]: 0.00105097 [a_3]: 0.00217875 [py_interpret_to_execute_after_opt_a]: 0.00057561 [slice_cell_reuse_recomputed_activation]: 4.48999e-06 [rewriter_after_opt_a]: 0.00537739 [convert_after_rewriter]: 0.00048756 [order_py_execute_after_rewriter]: 0.00022905 [mutable_eliminate]: 0.00143561 [opt_b]: 0.152405, [1] [Cycle 1]: 0.152387, [7] [b_1]: 0.150134 [b_2]: 0.00034257 [updatestate_depend_eliminate]: 0.0003771 [updatestate_assign_eliminate]: 0.00018168 [updatestate_loads_eliminate]: 0.00018883 [renormalize]: 1.79998e-06 [cse]: 0.00098089 [optimize_parallel_all_gather_comm]: 0.00045761 [overlap_param_gather]: 8.55001e-06 [cconv]: 0.00017624 [loop_unroll]: 0.00142223 [opt_after_cconv]: 0.00354434, [1] [Cycle 1]: 0.00352589, [7] [c_1]: 0.00148995 [parameter_eliminate]: 1.114e-05 [updatestate_depend_eliminate]: 0.0003552 [updatestate_assign_eliminate]: 0.00019164 [updatestate_loads_eliminate]: 0.00018296 [cse]: 0.00109353 [renormalize]: 1.77999e-06 [remove_dup_value]: 0.00155328 [tuple_transform]: 0.0027393, [1] [Cycle 1]: 0.00271984, [4] [d_1]: 0.00228508 [none_parameter_eliminate]: 9.27999e-06 [renormalize]: 7.80012e-07 [switch_simplify]: 0.0003087 [partial_unused_args_eliminate]: 2.092e-05 [add_recomputation]: 0.00205608 [cse_after_recomputation]: 0.00071118, [1] [Cycle 1]: 0.00069561, [1] [cse]: 0.00066396 [environ_conv]: 0.00019183 [swap_dp_allreduce_reducescatter]: 0.00028107 [bias_add_comm_swap]: 4.77998e-06 [label_micro_interleaved_index]: 8.93002e-06 [label_fine_grained_interleaved_index]: 3.54002e-06 [merge_cast_opt]: 1.49e-06 [slice_recompute_activation]: 2.37999e-06 [micro_interleaved_order_control]: 2.98998e-06 [assign_add_opt]: 1.54e-06 [ForceFp32Comm]: 9.49978e-07 [remove_cast_before_assign_add]: 1.57001e-06 [full_micro_interleaved_order_control]: 2.42001e-06 [reorder_send_recv_between_fp_bp]: 3.65e-06 [comm_op_add_attrs]: 1.27999e-06 [add_comm_op_reuse_tag]: 1.14003e-06 [interleave_split_concat_branches]: 1.20999e-06 [interleave_parallel_branches]: 1.27e-06 [overlap_opt_shard_in_pipeline]: 3.253e-05 [overlap_opt_shard_grad_in_pipeline]: 2.21e-06 [control_data_broadcast_order]: 0.00037694 [grouped_pairwise_exchange_alltoall]: 2.14e-06 [offloading_packed_experts]: 8.469e-05 [overlap_recompute_and_grad_model_parallel]: 8.036e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.67001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.60999e-06 [overlap_recompute_comm]: 2.74999e-06 [overlap_grad_ring_attention]: 8.034e-05 [overlap_grad_flash_sp]: 0.00052533 [begin_end_overlap_inline]: 8.59989e-07 [split_matmul_comm_elemetwise]: 3.24001e-06 [split_layernorm_comm]: 2.09e-06 [handle_group_info]: 1.24998e-06 [symbol_engine_optimizer]: 0.00181458, [1] [Cycle 1]: 0.00179814, [6] [build]: 0.00019398 [elim_shapecalc]: 0.00033722 [elim_not_effective]: 0.0004716 [opt_reshape]: 0.00028179 [fold_const_symbol]: 0.00042377 [renormalize]: 1.40001e-06 [detach_backward]: 4.92e-06 [pipeline_parallel_scheduler]: 2.09e-06 [auto_monad_reorder]: 0.0006644 [get_jit_bprop_graph]: 3.14001e-06 [rewriter_after_jit_bprop_graph]: 9.54999e-06 [opt_after_jit_grad]: 0.00202413 [validate]: 0.00062711 Sums bootstrap : 0.001502s : 0.00% type_inference : 25.996170s : 86.04% event_method : 0.002898s : 0.01% auto_monad : 0.135754s : 0.45% graph_reusing : 0.000819s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.003126s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.001405s : 0.00% parallel-infer-symbol : 0.000006s : 0.00% pre_auto_parallel : 0.026936s : 0.09% insert-virtual-dataset : 0.000004s : 0.00% parallel-infer-symbol-second : 0.000006s : 0.00% dataset_repeat_opt : 0.000020s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.095514s : 0.32% optimize.rewriter_before_opt_a : 0.009172s : 0.03% optimize.opt_a.expand_dump_flag : 0.000314s : 0.00% optimize.opt_a.switch_simplify : 0.006416s : 0.02% optimize.opt_a.loop_unroll : 0.003746s : 0.01% optimize.opt_a.a_1 : 1.613813s : 5.34% optimize.opt_a.with_stream_mark : 0.001981s : 0.01% optimize.opt_a.recompute_prepare : 0.001118s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.004763s : 0.02% optimize.opt_a.updatestate_assign_eliminate : 0.000861s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.187517s : 0.62% optimize.opt_a.parameter_eliminate : 0.000014s : 0.00% optimize.opt_a.a_2 : 0.035913s : 0.12% optimize.opt_a.accelerated_algorithm : 0.001619s : 0.01% optimize.opt_a.shard : 0.000008s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000674s : 0.00% optimize.opt_a.shard_inline : 0.000679s : 0.00% optimize.opt_a.merge_send_recv : 0.000573s : 0.00% optimize.opt_a.auto_parallel : 0.000377s : 0.00% optimize.opt_a.parallel : 0.000156s : 0.00% optimize.opt_a.flash_sp : 0.000134s : 0.00% optimize.opt_a.merge_comm : 0.224815s : 0.74% optimize.opt_a.allreduce_fusion : 0.000629s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000575s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000003s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000834s : 0.00% optimize.opt_a.virtual_dataset : 0.000769s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000692s : 0.00% optimize.opt_a.virtual_output : 0.000698s : 0.00% optimize.opt_a.merge_forward : 0.000704s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000013s : 0.00% optimize.opt_a.offload_activation : 0.000603s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.001284s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000007s : 0.00% optimize.opt_a.before_grad : 0.001281s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000773s : 0.00% optimize.opt_a.meta_fg_expand : 0.000766s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000021s : 0.00% optimize.opt_a.receive_attached : 0.000020s : 0.00% optimize.opt_a.after_resolve : 0.000881s : 0.00% optimize.opt_a.a_after_grad : 0.001145s : 0.00% optimize.opt_a.renormalize : 1.656247s : 5.48% optimize.opt_a.add_forward_monad_depend : 0.000031s : 0.00% optimize.opt_a.auto_monad_grad : 0.000008s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.002077s : 0.01% optimize.opt_a.cse : 0.002636s : 0.01% optimize.opt_a.a_3 : 0.004196s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000576s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000004s : 0.00% optimize.rewriter_after_opt_a : 0.005377s : 0.02% optimize.convert_after_rewriter : 0.000488s : 0.00% optimize.order_py_execute_after_rewriter : 0.000229s : 0.00% optimize.mutable_eliminate : 0.001436s : 0.00% optimize.opt_b.b_1 : 0.150134s : 0.50% optimize.opt_b.b_2 : 0.000343s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000377s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000182s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000189s : 0.00% optimize.opt_b.renormalize : 0.000002s : 0.00% optimize.opt_b.cse : 0.000981s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000458s : 0.00% optimize.overlap_param_gather : 0.000009s : 0.00% optimize.cconv : 0.000176s : 0.00% optimize.loop_unroll : 0.001422s : 0.00% optimize.opt_after_cconv.c_1 : 0.001490s : 0.00% optimize.opt_after_cconv.parameter_eliminate : 0.000011s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000355s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000192s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000183s : 0.00% optimize.opt_after_cconv.cse : 0.001094s : 0.00% optimize.opt_after_cconv.renormalize : 0.000002s : 0.00% optimize.remove_dup_value : 0.001553s : 0.01% optimize.tuple_transform.d_1 : 0.002285s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000009s : 0.00% optimize.tuple_transform.renormalize : 0.000001s : 0.00% optimize.tuple_transform.switch_simplify : 0.000309s : 0.00% optimize.partial_unused_args_eliminate : 0.000021s : 0.00% optimize.add_recomputation : 0.002056s : 0.01% optimize.cse_after_recomputation.cse : 0.000664s : 0.00% optimize.environ_conv : 0.000192s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000281s : 0.00% optimize.bias_add_comm_swap : 0.000005s : 0.00% optimize.label_micro_interleaved_index : 0.000009s : 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 : 0.000002s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000004s : 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 : 0.000033s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000377s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000085s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000080s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000002s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000080s : 0.00% optimize.overlap_grad_flash_sp : 0.000525s : 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 : 0.000194s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000337s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000472s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000282s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000424s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000005s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000664s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.002024s : 0.01% validate : 0.000627s : 0.00% Time group info: ------[substitution.] 1.098911 10208 0.10% : 0.001049s : 160: substitution.arithmetic_simplify 0.02% : 0.000197s : 14: substitution.cast_eliminate 0.00% : 0.000046s : 9: substitution.depend_value_elim 0.00% : 0.000054s : 180: substitution.elim_not_effective 0.01% : 0.000125s : 100: substitution.float_tuple_getitem_switch 0.00% : 0.000053s : 180: substitution.fold_const_symbol 0.02% : 0.000166s : 227: substitution.graph_param_transform 86.17% : 0.946916s : 855: substitution.inline 0.02% : 0.000185s : 360: substitution.j_node_and_user_rematch 0.08% : 0.000882s : 44: substitution.less_batch_normalization 0.02% : 0.000214s : 228: substitution.load_eliminater 0.08% : 0.000900s : 503: substitution.minmaximum_grad 0.00% : 0.000012s : 23: substitution.opt_reshape 0.02% : 0.000197s : 360: substitution.remove_not_recompute_node 0.00% : 0.000052s : 72: substitution.replace_old_param 0.10% : 0.001099s : 150: substitution.reshape_eliminate 0.03% : 0.000342s : 73: substitution.switch_simplify 0.06% : 0.000667s : 135: substitution.transpose_eliminate 0.16% : 0.001791s : 553: substitution.tuple_list_convert_item_index_to_positive 0.10% : 0.001064s : 724: substitution.tuple_list_get_item_const_eliminator 12.11% : 0.133116s : 724: substitution.tuple_list_get_item_depend_reorder 0.34% : 0.003782s : 907: substitution.tuple_list_get_item_eliminator 0.14% : 0.001547s : 724: substitution.tuple_list_get_set_item_eliminator 0.15% : 0.001617s : 1446: substitution.updatestate_pure_node_eliminater 0.26% : 0.002837s : 1457: substitution.updatestate_useless_node_eliminater ------[type_inference.] 25.990739 2 95.94% : 24.936792s : 1: type_inference.infer 4.06% : 1.053947s : 1: type_inference.specialize ------[replace.] 0.168015 1246 0.12% : 0.000205s : 14: replace.cast_eliminate 0.08% : 0.000133s : 5: replace.depend_value_elim 95.51% : 0.160477s : 855: replace.inline 0.10% : 0.000171s : 12: replace.reshape_eliminate 0.94% : 0.001585s : 73: replace.switch_simplify 1.88% : 0.003164s : 171: replace.tuple_list_get_item_depend_reorder 1.31% : 0.002202s : 108: replace.tuple_list_get_item_eliminator 0.05% : 0.000078s : 8: replace.updatestate_useless_node_eliminater ------[match.] 0.949109 1246 0.02% : 0.000186s : 14: match.cast_eliminate 0.00% : 0.000004s : 5: match.depend_value_elim 99.68% : 0.946068s : 855: match.inline 0.01% : 0.000079s : 12: match.reshape_eliminate 0.03% : 0.000284s : 73: match.switch_simplify 0.19% : 0.001803s : 171: match.tuple_list_get_item_depend_reorder 0.07% : 0.000660s : 108: match.tuple_list_get_item_eliminator 0.00% : 0.000024s : 8: match.updatestate_useless_node_eliminater ------[predicate.] 0.075621175493 0.59% : 0.000449s : 2713: predicate.accumulaten_eliminater 0.10% : 0.000075s : 227: predicate.ad_related_special_op_eliminate 0.21% : 0.000158s : 703: predicate.addn_check_dump 0.52% : 0.000392s : 2713: predicate.addn_zero_filter 0.57% : 0.000435s : 2713: predicate.adjust_all_reduce_mul_add 1.06% : 0.000804s : 3416: predicate.arithmetic_simplify 0.63% : 0.000479s : 2739: predicate.cast_eliminate 0.17% : 0.000125s : 454: predicate.check_bprop_eliminate 0.21% : 0.000157s : 703: predicate.compare_switch_simplify 0.02% : 0.000017s : 227: predicate.const_output_eliminate 0.20% : 0.000154s : 707: predicate.depend_value_elim 0.62% : 0.000468s : 2739: predicate.dict_get_item_const_eliminator 0.63% : 0.000479s : 2739: predicate.dict_get_item_eliminator 0.52% : 0.000396s : 2739: predicate.dict_set_item_eliminator 0.11% : 0.000081s : 454: predicate.dumpgradient_eliminate 0.02% : 0.000017s : 227: predicate.elim_not_effective 0.07% : 0.000053s : 227: predicate.elim_shapecalc_of_broadcastargs 0.63% : 0.000475s : 2966: predicate.environ_add_const_eliminate 0.65% : 0.000494s : 2966: predicate.environ_get_add_eliminate 0.56% : 0.000427s : 2966: predicate.environ_get_depend_swap 0.88% : 0.000665s : 3669: predicate.environ_get_eliminate 0.58% : 0.000442s : 2966: predicate.environ_get_set_eliminate 0.78% : 0.000587s : 3881: predicate.exchange_switch_depend_value 1.23% : 0.000932s : 3881: predicate.float_depend_g_call 0.25% : 0.000188s : 703: predicate.float_environ_get_switch 0.29% : 0.000216s : 930: predicate.float_tuple_getitem_switch 0.02% : 0.000016s : 227: predicate.fold_const_symbol 0.15% : 0.000117s : 462: predicate.get_grad_eliminate 0.03% : 0.000019s : 227: predicate.graph_param_transform 0.19% : 0.000143s : 703: predicate.incorporate_call 0.17% : 0.000129s : 703: predicate.incorporate_call_switch 2.61% : 0.001971s : 8213: predicate.inline 0.18% : 0.000134s : 462: predicate.inline_without_move 0.06% : 0.000049s : 462: predicate.j_node_and_user_rematch 0.16% : 0.000122s : 462: predicate.less_batch_normalization 0.77% : 0.000585s : 3472: predicate.list_to_tuple_eliminator_ 1.20% : 0.000909s : 6185: predicate.load_eliminater 0.13% : 0.000101s : 227: predicate.loop_unroll_after_grad 1.46% : 0.001102s : 2096: predicate.loop_unroll_before_grad 0.79% : 0.000595s : 3364: predicate.make_slice_get_slice_eliminator 0.19% : 0.000146s : 703: predicate.merge_addn 0.13% : 0.000099s : 454: predicate.micro_step_allgather_replace 0.11% : 0.000085s : 454: predicate.mini_step_allgather_replace 0.60% : 0.000450s : 2713: predicate.minmaximum_grad 0.14% : 0.000109s : 227: predicate.mutable_eliminate 0.06% : 0.000042s : 227: predicate.opt_reshape 0.07% : 0.000052s : 227: predicate.parallel_virtual_node 3.02% : 0.002281s : 3881: predicate.partial_defer_inline 0.71% : 0.000538s : 3245: predicate.partial_eliminate 0.52% : 0.000390s : 2713: predicate.print_const_string_wrapper 0.21% : 0.000158s : 697: predicate.reduce_all_const_elim 0.85% : 0.000646s : 2713: predicate.reduce_eliminate 1.23% : 0.000929s : 6185: predicate.redundant_stop_gradient_eliminater 0.04% : 0.000033s : 462: predicate.remove_not_recompute_node 0.43% : 0.000327s : 3472: predicate.replace_applicator 0.05% : 0.000034s : 462: predicate.replace_old_param 0.02% : 0.000017s : 227: predicate.reset_defer_inline 0.66% : 0.000498s : 2725: predicate.reshape_eliminate 0.13% : 0.000097s : 454: predicate.row_tensor_add_zeros_like 0.09% : 0.000067s : 227: predicate.row_tensor_eliminate 0.17% : 0.000130s : 454: predicate.same_eliminate 0.08% : 0.000060s : 796: predicate.set_cell_output_no_recompute 0.15% : 0.000117s : 462: predicate.shard_identity_eliminate 0.11% : 0.000084s : 454: predicate.special_op_eliminate 0.22% : 0.000166s : 703: predicate.specialize_transform 0.15% : 0.000110s : 454: predicate.split_environ_get_set_with_tuple_value 0.10% : 0.000073s : 462: predicate.stack_unstack_eliminate 0.04% : 0.000032s : 227: predicate.switch_call_monad_eliminater 0.86% : 0.000649s : 3881: predicate.switch_defer_inline 1.02% : 0.000774s : 4335: predicate.switch_layer_defer_inline 56.17% : 0.042480s : 7053: predicate.switch_simplify 0.57% : 0.000435s : 2713: predicate.tile_eliminate 0.61% : 0.000464s : 2713: predicate.transpose_eliminate 0.85% : 0.000646s : 3193: predicate.tuple_list_convert_item_index_to_positive 0.88% : 0.000669s : 3364: predicate.tuple_list_get_item_const_eliminator 0.82% : 0.000618s : 3364: predicate.tuple_list_get_item_depend_reorder 1.44% : 0.001090s : 4175: predicate.tuple_list_get_item_eliminator 0.92% : 0.000697s : 3364: predicate.tuple_list_get_set_item_eliminator 1.27% : 0.000964s : 4067: predicate.tuple_list_set_item_eliminator 0.75% : 0.000570s : 3472: predicate.tuple_to_list_eliminator_ 1.33% : 0.001009s : 6185: predicate.updatestate_pure_node_eliminater 1.64% : 0.001238s : 6896: predicate.updatestate_useless_node_eliminater 0.07% : 0.000052s : 227: predicate.value_based_eliminate 0.17% : 0.000131s : 462: predicate.virtual_dataset_eliminate 0.16% : 0.000123s : 462: predicate.virtual_output_eliminate 0.04% : 0.000031s : 227: predicate.virtual_view_grad_eliminate 0.08% : 0.000058s : 227: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 1.751463 1066 74.05% : 1.296970s : 474: func_graph_cloner_run.FuncGraphClonerGraph 23.64% : 0.414115s : 227: func_graph_cloner_run.FuncGraphClonerNode 2.31% : 0.040377s : 365: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 37.936882 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.25% : 0.093748s : 1: add_attr 0.25% : 0.093720s : 1: add_attr_with_inline 0.00% : 0.000006s : 1: add_comm_op_reuse_tag 0.01% : 0.002087s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.36% : 0.135800s : 1: auto_monad 0.00% : 0.000683s : 1: auto_monad_reorder 0.00% : 0.000007s : 1: begin_end_overlap_inline 0.00% : 0.000009s : 1: bias_add_comm_swap 0.00% : 0.001539s : 1: bootstrap 0.00% : 0.000188s : 1: cconv 0.00% : 0.000006s : 1: comm_op_add_attrs 0.00% : 0.000386s : 1: control_data_broadcast_order 0.00% : 0.000515s : 1: convert_after_rewriter 0.00% : 0.000719s : 1: cse_after_recomputation 0.00% : 0.000085s : 1: dataset_repeat_opt 0.00% : 0.000013s : 1: detach_backward 0.00% : 0.000204s : 1: environ_conv 0.01% : 0.002943s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000015s : 1: get_jit_bprop_graph 0.00% : 0.000845s : 1: graph_reusing 0.00% : 0.000008s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000006s : 1: handle_group_info 0.00% : 0.000010s : 1: inline 0.00% : 0.000014s : 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% : 0.000012s : 1: label_micro_interleaved_index 0.00% : 0.001444s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.00% : 0.001459s : 1: mutable_eliminate 0.00% : 0.000089s : 1: offloading_packed_experts 0.00% : 0.000416s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000451s : 1: opt.transform.mutable_eliminate 4.41% : 1.674523s : 95: opt.transform.opt_a 0.00% : 0.001485s : 1: opt.transform.opt_after_cconv 0.00% : 0.000830s : 1: opt.transform.opt_after_jit_grad 0.40% : 0.150344s : 28: opt.transform.opt_b 0.01% : 0.002576s : 2: opt.transform.opt_trans_graph 0.00% : 0.001501s : 4: opt.transform.symbol_engine_opt 9.92% : 3.764822s : 1: opt_a 0.01% : 0.003553s : 1: opt_after_cconv 0.01% : 0.002046s : 1: opt_after_jit_grad 0.40% : 0.152416s : 1: opt_b 10.67% : 4.047031s : 1: optimize 0.00% : 0.000472s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000245s : 1: order_py_execute_after_rewriter 0.00% : 0.000541s : 1: overlap_grad_flash_sp 0.00% : 0.000007s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000084s : 1: overlap_grad_ring_attention 0.00% : 0.000008s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000038s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000014s : 1: overlap_param_gather 0.00% : 0.000007s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000087s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000013s : 1: parallel-infer-symbol 0.00% : 0.000012s : 1: parallel-infer-symbol-second 0.00% : 0.000028s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000006s : 1: pipeline_split 0.07% : 0.026990s : 1: pre_auto_parallel 0.25% : 0.095569s : 1: py_interpret_to_execute 0.00% : 0.000594s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.00% : 0.001578s : 1: remove_dup_value 2.50% : 0.948750s : 1: renormalize.infer 1.86% : 0.707436s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000014s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.005418s : 1: rewriter_after_opt_a 0.02% : 0.009217s : 1: rewriter_before_opt_a 0.00% : 0.000012s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000007s : 1: slice_recompute_activation 0.00% : 0.000010s : 1: split_layernorm_comm 0.00% : 0.000007s : 1: split_matmul_comm_elemetwise 0.00% : 0.000289s : 1: swap_dp_allreduce_reducescatter 0.00% : 0.001824s : 1: symbol_engine_optimizer 0.01% : 0.002751s : 1: tuple_transform 68.52% : 25.996235s : 1: type_inference .[WARNING] ME(168984:281473518067504,MainProcess):2026-01-29-17:40:31.919.063 [mindspore/profiler/common/profiler_context.py:416] For profiler, the parameter pretty must be bool, but got , reset to False. [168984] Start parsing profiling data in sync mode at: /tmp/tmp8xrzulus/ascend216_168984_20260129093741111_ascend_ms [95237] Parsing: [ ] 0/3 AscendMsprofParser Elapsed: 0s [ERROR] ME(95237:281473518067504,Process-20):2026-01-29-17:41:55.241.244 [mindspore/profiler/analysis/parser/ascend_cann_parser.py:102] Failed to find op_summary_*.csv in directory: /tmp/tmp8xrzulus/ascend216_168984_20260129093741111_ascend_ms/PROF_000001_20260129173756234_NIBBRCBHEHRBQNDC/mindstudio_profiler_output [95237] Parsing: [####### ] 1/3 AscendMsprofParser Elapsed: 73s [95237] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 73s [95237] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 74s [95237] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 75s [95237] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 76s [95237] Parsing: [####### ] 1/3 FrameworkParser Elapsed: 77s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 77s [ERROR] ME(95237:281473518067504,Process-20):2026-01-29-17:42:05.813.374 [mindspore/profiler/analysis/parser/timeline_assembly_factory/ascend_timeline_assembler.py:134] Cannot find connection between CANN layer and Ascend Hardware layer. [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 78s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 79s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 80s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 81s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 82s [WARNING] ME(145204:281473518067504,Process-20:6):2026-01-29-17:42:11.280.287 [mindspore/profiler/analysis/viewer/ascend_step_trace_time_viewer.py:340] Failed to find device task in step 0, set prepare time to 0 [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 83s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 84s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 85s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 86s [95237] Parsing: [############# ] 2/3 FrameworkCannRelationParser Elapsed: 87s [95237] Parsing: [####################] 3/3 Done Elapsed: 88s . [hook] pytest_runtest_teardown:test_profiler_analyse_pretty_true_012 tests/st/tools/profiler/daily_test/test_legacy_profiler_parse.py::test_profiler_analyse_pretty_true_012,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_012 /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 331.99s (0:05:31) ==================