[WARNING] ME(164252:281473885015856,MainProcess):2026-01-29-17:37:15.406.766 [mindspore/context.py:1334] For 'context.set_context', the parameter 'max_call_depth' will be deprecated and removed in a future version. Please use the api mindspore.set_recursion_limit() instead. [WARNING] ME(164252:281473885015856,MainProcess):2026-01-29-17:37:15.408.905 [mindspore/context.py:1334] For 'context.set_context', the parameter 'max_call_depth' will be deprecated and removed in a future version. Please use the api mindspore.set_recursion_limit() instead. ==================================================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/runtime/kernel_capture, 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_capture_graph.py TotalTime = 9.73336, [21] [bootstrap]: 0.0006938 [type_inference]: 7.75796 [event_method]: 0.00141846 [auto_monad]: 0.00265823 [graph_reusing]: 0.00015803 [inline]: 8.87e-06 [add_attr]: 0.107577, [1] [add_attr_with_inline]: 0.10756, [1] [Cycle 1]: 0.00134802, [2] [tag_attr]: 0.0008923 [meta_addattr_fg_expand]: 0.00034062 [parallel-infer-symbol]: 5.69e-06 [pre_auto_parallel]: 0.00101311 [insert-virtual-dataset]: 5.65001e-06 [parallel-infer-symbol-second]: 2.71999e-06 [dataset_repeat_opt]: 2.88e-06 [pipeline_split]: 3.19001e-06 [optimize]: 1.85738, [53] [py_interpret_to_execute]: 0.00123848 [rewriter_before_opt_a]: 0.00319052 [opt_a]: 1.57668, [2] [Cycle 1]: 1.3849, [45] [expand_dump_flag]: 5.04e-05 [switch_simplify]: 0.00171101 [loop_unroll]: 0.0413206 [a_1]: 0.324176 [with_stream_mark]: 0.00111171 [recompute_prepare]: 0.0009104 [updatestate_depend_eliminate]: 0.00075731 [updatestate_assign_eliminate]: 0.00088972 [updatestate_loads_eliminate]: 0.00072079 [parameter_eliminate]: 7.93999e-06 [a_2]: 0.0972643 [accelerated_algorithm]: 0.00241686 [shard]: 6.02999e-06 [meta_shard_fg_expand]: 0.00122401 [shard_inline]: 0.00085567 [merge_send_recv]: 0.125329 [auto_parallel]: 0.00090887 [parallel]: 5.97e-05 [flash_sp]: 0.00041916 [merge_comm]: 0.00069757 [allreduce_fusion]: 0.00067423 [matmul_add_comm_reduction]: 0.0009836 [allreduce_slice_to_reducescatter]: 1.35999e-06 [virtual_shard_identity]: 0.00085884 [virtual_dataset]: 0.00076172 [get_grad_eliminate_]: 0.0007805 [virtual_output]: 0.00075574 [merge_forward]: 0.00081554 [cell_reuse_recompute_pass]: 1.046e-05 [offload_activation]: 0.00121026 [cell_reuse_handle_not_recompute_node_pass]: 0.00170331 [merge_recompute_call_nodes]: 3.40998e-06 [before_grad]: 0.00156859 [set_forward_comm_id_for_comm_node_pass]: 0.00108817 [meta_fg_expand]: 0.00105533 [flash_sp_send_recv_attached]: 1.663e-05 [receive_attached]: 1.57e-05 [after_resolve]: 0.00097098 [a_after_grad]: 0.0013508 [renormalize]: 0.720035 [add_forward_monad_depend]: 2.16e-05 [auto_monad_grad]: 3.9e-06 [auto_monad_eliminator]: 0.00146468 [cse]: 0.0431827 [a_3]: 0.00333077 [Cycle 2]: 0.19175, [45] [expand_dump_flag]: 4.72e-06 [switch_simplify]: 0.00043068 [loop_unroll]: 0.0004106 [a_1]: 0.0144761 [with_stream_mark]: 0.00096248 [recompute_prepare]: 0.00044287 [updatestate_depend_eliminate]: 0.00040089 [updatestate_assign_eliminate]: 0.116466 [updatestate_loads_eliminate]: 0.00080166 [parameter_eliminate]: 9.21998e-06 [a_2]: 0.00761306 [accelerated_algorithm]: 0.00071861 [shard]: 4.95001e-06 [meta_shard_fg_expand]: 0.00025791 [shard_inline]: 0.00046142 [merge_send_recv]: 0.00052905 [auto_parallel]: 0.0004069 [parallel]: 1.299e-05 [flash_sp]: 6.80002e-06 [merge_comm]: 0.00038572 [allreduce_fusion]: 0.00037126 [matmul_add_comm_reduction]: 0.0330019 [allreduce_slice_to_reducescatter]: 1.90001e-06 [virtual_shard_identity]: 0.00055967 [virtual_dataset]: 0.00048184 [get_grad_eliminate_]: 0.00049344 [virtual_output]: 0.00048374 [merge_forward]: 0.00050154 [cell_reuse_recompute_pass]: 4.86002e-06 [offload_activation]: 0.00066764 [cell_reuse_handle_not_recompute_node_pass]: 0.00092936 [merge_recompute_call_nodes]: 3.63e-06 [before_grad]: 0.0007948 [set_forward_comm_id_for_comm_node_pass]: 0.00049199 [meta_fg_expand]: 0.00046148 [flash_sp_send_recv_attached]: 3.98999e-06 [receive_attached]: 3.48999e-06 [after_resolve]: 0.000428 [a_after_grad]: 0.00072449 [renormalize]: 1.50001e-07 [add_forward_monad_depend]: 9.09e-06 [auto_monad_grad]: 4.53001e-06 [auto_monad_eliminator]: 0.00069363 [cse]: 0.0018572 [a_3]: 0.00309869 [py_interpret_to_execute_after_opt_a]: 0.00074246 [slice_cell_reuse_recomputed_activation]: 5.32001e-06 [rewriter_after_opt_a]: 0.00348174 [convert_after_rewriter]: 0.00056706 [order_py_execute_after_rewriter]: 0.00034628 [mutable_eliminate]: 0.0818344 [opt_b]: 0.0142659, [1] [Cycle 1]: 0.0142477, [7] [b_1]: 0.0106818 [b_2]: 0.00046934 [updatestate_depend_eliminate]: 0.00050411 [updatestate_assign_eliminate]: 0.00037873 [updatestate_loads_eliminate]: 0.00035999 [renormalize]: 1.39e-06 [cse]: 0.00167172 [optimize_parallel_all_gather_comm]: 0.00084614 [overlap_param_gather]: 9.89001e-06 [cconv]: 0.0002378 [loop_unroll]: 0.00131008 [opt_after_cconv]: 0.0733087, [1] [Cycle 1]: 0.0732948, [7] [c_1]: 0.0700593 [parameter_eliminate]: 8.33001e-06 [updatestate_depend_eliminate]: 0.00079124 [updatestate_assign_eliminate]: 0.00036928 [updatestate_loads_eliminate]: 0.0003505 [cse]: 0.00158066 [renormalize]: 9.39996e-07 [remove_dup_value]: 0.0690937 [tuple_transform]: 0.00383442, [1] [Cycle 1]: 0.00381194, [4] [d_1]: 0.00329734 [none_parameter_eliminate]: 6.71e-06 [renormalize]: 1.07e-06 [switch_simplify]: 0.00043317 [partial_unused_args_eliminate]: 5.79999e-06 [add_recomputation]: 0.00319434 [cse_after_recomputation]: 0.00109929, [1] [Cycle 1]: 0.00108255, [1] [cse]: 0.00103889 [environ_conv]: 0.00022194 [swap_dp_allreduce_reducescatter]: 0.00047461 [bias_add_comm_swap]: 8.3e-06 [label_micro_interleaved_index]: 1.007e-05 [label_fine_grained_interleaved_index]: 2.78e-06 [merge_cast_opt]: 3.18e-06 [slice_recompute_activation]: 2.21e-06 [micro_interleaved_order_control]: 2.49001e-06 [assign_add_opt]: 1.62999e-06 [ForceFp32Comm]: 8.59989e-07 [remove_cast_before_assign_add]: 1.19998e-06 [full_micro_interleaved_order_control]: 2.61e-06 [reorder_send_recv_between_fp_bp]: 2.79999e-06 [comm_op_add_attrs]: 1.16997e-06 [add_comm_op_reuse_tag]: 1.37e-06 [interleave_split_concat_branches]: 1.62001e-06 [interleave_parallel_branches]: 1.10999e-06 [overlap_opt_shard_in_pipeline]: 2.552e-05 [overlap_opt_shard_grad_in_pipeline]: 1.90001e-06 [control_data_broadcast_order]: 0.00074996 [grouped_pairwise_exchange_alltoall]: 2.00002e-06 [offloading_packed_experts]: 0.00017671 [overlap_recompute_and_grad_model_parallel]: 0.00017008 [overlap_grad_matmul_and_grad_allreduce]: 1.91e-06 [overlap_recompute_allgather_and_fa_grad]: 1.46002e-06 [overlap_recompute_comm]: 2.46e-06 [overlap_grad_ring_attention]: 0.00016764 [overlap_grad_flash_sp]: 0.0009942 [begin_end_overlap_inline]: 9.99979e-07 [split_matmul_comm_elemetwise]: 3.14999e-06 [split_layernorm_comm]: 2.09999e-06 [handle_group_info]: 1.66998e-06 [symbol_engine_optimizer]: 0.0183684, [1] [Cycle 1]: 0.0183533, [6] [build]: 0.0152364 [elim_shapecalc]: 0.00051464 [elim_not_effective]: 0.00090003 [opt_reshape]: 0.00051058 [fold_const_symbol]: 0.00105242 [renormalize]: 1.16002e-06 [detach_backward]: 4.90001e-06 [pipeline_parallel_scheduler]: 2.02001e-06 [auto_monad_reorder]: 0.00079132 [get_jit_bprop_graph]: 6.46999e-06 [rewriter_after_jit_bprop_graph]: 8.27e-06 [opt_after_jit_grad]: 0.00248715 [validate]: 0.00074415 Sums bootstrap : 0.000694s : 0.01% type_inference : 7.757960s : 80.62% event_method : 0.001418s : 0.01% auto_monad : 0.002658s : 0.03% graph_reusing : 0.000158s : 0.00% inline : 0.000009s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000892s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000341s : 0.00% parallel-infer-symbol : 0.000006s : 0.00% pre_auto_parallel : 0.001013s : 0.01% insert-virtual-dataset : 0.000006s : 0.00% parallel-infer-symbol-second : 0.000003s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000003s : 0.00% optimize.py_interpret_to_execute : 0.001238s : 0.01% optimize.rewriter_before_opt_a : 0.003191s : 0.03% optimize.opt_a.expand_dump_flag : 0.000055s : 0.00% optimize.opt_a.switch_simplify : 0.002142s : 0.02% optimize.opt_a.loop_unroll : 0.041731s : 0.43% optimize.opt_a.a_1 : 0.338652s : 3.52% optimize.opt_a.with_stream_mark : 0.002074s : 0.02% optimize.opt_a.recompute_prepare : 0.001353s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.001158s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.117356s : 1.22% optimize.opt_a.updatestate_loads_eliminate : 0.001522s : 0.02% optimize.opt_a.parameter_eliminate : 0.000017s : 0.00% optimize.opt_a.a_2 : 0.104877s : 1.09% optimize.opt_a.accelerated_algorithm : 0.003135s : 0.03% optimize.opt_a.shard : 0.000011s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.001482s : 0.02% optimize.opt_a.shard_inline : 0.001317s : 0.01% optimize.opt_a.merge_send_recv : 0.125859s : 1.31% optimize.opt_a.auto_parallel : 0.001316s : 0.01% optimize.opt_a.parallel : 0.000073s : 0.00% optimize.opt_a.flash_sp : 0.000426s : 0.00% optimize.opt_a.merge_comm : 0.001083s : 0.01% optimize.opt_a.allreduce_fusion : 0.001045s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.033985s : 0.35% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000003s : 0.00% optimize.opt_a.virtual_shard_identity : 0.001419s : 0.01% optimize.opt_a.virtual_dataset : 0.001244s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.001274s : 0.01% optimize.opt_a.virtual_output : 0.001239s : 0.01% optimize.opt_a.merge_forward : 0.001317s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000015s : 0.00% optimize.opt_a.offload_activation : 0.001878s : 0.02% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.002633s : 0.03% optimize.opt_a.merge_recompute_call_nodes : 0.000007s : 0.00% optimize.opt_a.before_grad : 0.002363s : 0.02% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.001580s : 0.02% optimize.opt_a.meta_fg_expand : 0.001517s : 0.02% optimize.opt_a.flash_sp_send_recv_attached : 0.000021s : 0.00% optimize.opt_a.receive_attached : 0.000019s : 0.00% optimize.opt_a.after_resolve : 0.001399s : 0.01% optimize.opt_a.a_after_grad : 0.002075s : 0.02% optimize.opt_a.renormalize : 0.720035s : 7.48% 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 : 0.002158s : 0.02% optimize.opt_a.cse : 0.045040s : 0.47% optimize.opt_a.a_3 : 0.006429s : 0.07% optimize.py_interpret_to_execute_after_opt_a : 0.000742s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000005s : 0.00% optimize.rewriter_after_opt_a : 0.003482s : 0.04% optimize.convert_after_rewriter : 0.000567s : 0.01% optimize.order_py_execute_after_rewriter : 0.000346s : 0.00% optimize.mutable_eliminate : 0.081834s : 0.85% optimize.opt_b.b_1 : 0.010682s : 0.11% optimize.opt_b.b_2 : 0.000469s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000504s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000379s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000360s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.001672s : 0.02% optimize.optimize_parallel_all_gather_comm : 0.000846s : 0.01% optimize.overlap_param_gather : 0.000010s : 0.00% optimize.cconv : 0.000238s : 0.00% optimize.loop_unroll : 0.001310s : 0.01% optimize.opt_after_cconv.c_1 : 0.070059s : 0.73% optimize.opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000791s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000369s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000350s : 0.00% optimize.opt_after_cconv.cse : 0.001581s : 0.02% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.069094s : 0.72% optimize.tuple_transform.d_1 : 0.003297s : 0.03% optimize.tuple_transform.none_parameter_eliminate : 0.000007s : 0.00% optimize.tuple_transform.renormalize : 0.000001s : 0.00% optimize.tuple_transform.switch_simplify : 0.000433s : 0.00% optimize.partial_unused_args_eliminate : 0.000006s : 0.00% optimize.add_recomputation : 0.003194s : 0.03% optimize.cse_after_recomputation.cse : 0.001039s : 0.01% optimize.environ_conv : 0.000222s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000475s : 0.00% optimize.bias_add_comm_swap : 0.000008s : 0.00% optimize.label_micro_interleaved_index : 0.000010s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000003s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000002s : 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 : 0.000003s : 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 : 0.000002s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000026s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000750s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000177s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000170s : 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 : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000168s : 0.00% optimize.overlap_grad_flash_sp : 0.000994s : 0.01% 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 : 0.000002s : 0.00% optimize.symbol_engine_optimizer.build : 0.015236s : 0.16% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000515s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000900s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000511s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.001052s : 0.01% 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 : 0.000791s : 0.01% get_jit_bprop_graph : 0.000006s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.002487s : 0.03% validate : 0.000744s : 0.01% Time group info: ------[substitution.] 0.031547 7786 0.32% : 0.000100s : 41: substitution.addn_check_dump 2.06% : 0.000650s : 181: substitution.addn_zero_filter 0.75% : 0.000238s : 181: substitution.adjust_all_reduce_mul_add 18.16% : 0.005729s : 1341: substitution.arithmetic_simplify 0.07% : 0.000023s : 20: substitution.depend_value_elim 0.69% : 0.000217s : 386: substitution.elim_not_effective 1.39% : 0.000437s : 386: substitution.fold_const_symbol 0.92% : 0.000291s : 392: substitution.graph_param_transform 52.95% : 0.016706s : 303: substitution.inline 1.42% : 0.000449s : 1031: substitution.j_node_and_user_rematch 4.29% : 0.001354s : 362: substitution.less_batch_normalization 3.95% : 0.001247s : 20: substitution.list_to_tuple_eliminator_ 0.42% : 0.000134s : 41: substitution.merge_addn 0.09% : 0.000029s : 42: substitution.opt_reshape 1.70% : 0.000535s : 1031: substitution.remove_not_recompute_node 0.05% : 0.000015s : 6: substitution.replace_old_param 2.01% : 0.000635s : 124: substitution.reshape_eliminate 0.26% : 0.000081s : 26: substitution.switch_simplify 1.92% : 0.000606s : 282: substitution.tuple_list_convert_item_index_to_positive 1.10% : 0.000347s : 282: substitution.tuple_list_get_item_const_eliminator 1.07% : 0.000338s : 282: substitution.tuple_list_get_item_depend_reorder 3.29% : 0.001038s : 744: substitution.tuple_list_get_item_eliminator 1.09% : 0.000344s : 282: substitution.tuple_list_get_set_item_eliminator ------[type_inference.] 7.755575 2 91.80% : 7.119717s : 1: type_inference.infer 8.20% : 0.635858s : 1: type_inference.specialize ------[replace.] 0.007315 409 2.61% : 0.000191s : 20: replace.depend_value_elim 69.09% : 0.005055s : 303: replace.inline 17.09% : 0.001250s : 20: replace.list_to_tuple_eliminator_ 6.39% : 0.000467s : 40: replace.reshape_eliminate 4.81% : 0.000352s : 26: replace.switch_simplify ------[match.] 0.017964 409 0.07% : 0.000013s : 20: match.depend_value_elim 91.85% : 0.016500s : 303: match.inline 6.86% : 0.001233s : 20: match.list_to_tuple_eliminator_ 0.85% : 0.000153s : 40: match.reshape_eliminate 0.36% : 0.000065s : 26: match.switch_simplify ------[predicate.] 0.099671143778 0.21% : 0.000207s : 1421: predicate.accumulaten_eliminater 0.08% : 0.000078s : 392: predicate.ad_related_special_op_eliminate 0.38% : 0.000382s : 1790: predicate.addn_check_dump 0.23% : 0.000226s : 1421: predicate.addn_zero_filter 0.21% : 0.000209s : 1421: predicate.adjust_all_reduce_mul_add 0.85% : 0.000847s : 3211: predicate.arithmetic_simplify 0.21% : 0.000208s : 1461: predicate.cast_eliminate 0.17% : 0.000168s : 786: predicate.check_bprop_eliminate 0.38% : 0.000382s : 1790: predicate.compare_switch_simplify 0.03% : 0.000030s : 392: predicate.const_output_eliminate 0.52% : 0.000523s : 1809: predicate.depend_value_elim 0.23% : 0.000225s : 1461: predicate.dict_get_item_const_eliminator 0.24% : 0.000241s : 1461: predicate.dict_get_item_eliminator 0.21% : 0.000213s : 1461: predicate.dict_set_item_eliminator 0.14% : 0.000140s : 784: predicate.dumpgradient_eliminate 0.04% : 0.000043s : 392: predicate.elim_not_effective 0.06% : 0.000064s : 392: predicate.elim_shapecalc_of_broadcastargs 0.28% : 0.000279s : 1853: predicate.environ_add_const_eliminate 0.28% : 0.000279s : 1853: predicate.environ_get_add_eliminate 0.27% : 0.000272s : 1853: predicate.environ_get_depend_swap 1.11% : 0.001102s : 3643: predicate.environ_get_eliminate 0.34% : 0.000338s : 1853: predicate.environ_get_set_eliminate 0.27% : 0.000268s : 1784: predicate.exchange_switch_depend_value 0.36% : 0.000354s : 1784: predicate.float_depend_g_call 0.39% : 0.000384s : 1790: predicate.float_environ_get_switch 0.47% : 0.000464s : 2182: predicate.float_tuple_getitem_switch 0.03% : 0.000027s : 392: predicate.fold_const_symbol 0.24% : 0.000239s : 1082: predicate.get_grad_eliminate 0.03% : 0.000031s : 392: predicate.graph_param_transform 0.56% : 0.000561s : 1790: predicate.incorporate_call 0.80% : 0.000796s : 1790: predicate.incorporate_call_switch 1.59% : 0.001583s : 6861: predicate.inline 0.32% : 0.000317s : 1082: predicate.inline_without_move 0.08% : 0.000075s : 1082: predicate.j_node_and_user_rematch 0.29% : 0.000288s : 1082: predicate.less_batch_normalization 0.37% : 0.000366s : 2265: predicate.list_to_tuple_eliminator_ 0.53% : 0.000533s : 3686: predicate.load_eliminater 0.11% : 0.000106s : 392: predicate.loop_unroll_after_grad 40.56% : 0.040429s : 1503: predicate.loop_unroll_before_grad 0.36% : 0.000357s : 2245: predicate.make_slice_get_slice_eliminator 0.38% : 0.000381s : 1790: predicate.merge_addn 0.16% : 0.000158s : 786: predicate.micro_step_allgather_replace 0.16% : 0.000161s : 786: predicate.mini_step_allgather_replace 0.19% : 0.000192s : 1421: predicate.minmaximum_grad 0.25% : 0.000252s : 392: predicate.mutable_eliminate 0.06% : 0.000063s : 392: predicate.opt_reshape 0.09% : 0.000087s : 392: predicate.parallel_virtual_node 0.64% : 0.000636s : 1784: predicate.partial_defer_inline 0.30% : 0.000296s : 1873: predicate.partial_eliminate 0.19% : 0.000193s : 1421: predicate.print_const_string_wrapper 0.40% : 0.000394s : 1770: predicate.reduce_all_const_elim 0.27% : 0.000272s : 1421: predicate.reduce_eliminate 0.53% : 0.000532s : 3686: predicate.redundant_stop_gradient_eliminater 0.08% : 0.000078s : 1082: predicate.remove_not_recompute_node 0.20% : 0.000203s : 2267: predicate.replace_applicator 0.07% : 0.000075s : 1082: predicate.replace_old_param 0.03% : 0.000029s : 392: predicate.reset_defer_inline 0.22% : 0.000219s : 1461: predicate.reshape_eliminate 0.16% : 0.000161s : 786: predicate.row_tensor_add_zeros_like 0.09% : 0.000091s : 392: predicate.row_tensor_eliminate 0.24% : 0.000238s : 786: predicate.same_eliminate 0.08% : 0.000082s : 1102: predicate.set_cell_output_no_recompute 0.25% : 0.000253s : 1082: predicate.shard_identity_eliminate 0.15% : 0.000151s : 784: predicate.special_op_eliminate 0.42% : 0.000423s : 1790: predicate.specialize_transform 0.17% : 0.000170s : 786: predicate.split_environ_get_set_with_tuple_value 0.17% : 0.000173s : 1082: predicate.stack_unstack_eliminate 0.06% : 0.000059s : 392: predicate.switch_call_monad_eliminater 0.29% : 0.000285s : 1784: predicate.switch_defer_inline 0.46% : 0.000454s : 2570: predicate.switch_layer_defer_inline 1.08% : 0.001074s : 5521: predicate.switch_simplify 0.19% : 0.000194s : 1421: predicate.tile_eliminate 0.20% : 0.000199s : 1421: predicate.transpose_eliminate 0.39% : 0.000389s : 2245: predicate.tuple_list_convert_item_index_to_positive 0.39% : 0.000387s : 2245: predicate.tuple_list_get_item_const_eliminator 0.36% : 0.000360s : 2245: predicate.tuple_list_get_item_depend_reorder 0.92% : 0.000912s : 4035: predicate.tuple_list_get_item_eliminator 0.37% : 0.000365s : 2245: predicate.tuple_list_get_set_item_eliminator 0.82% : 0.000821s : 4035: predicate.tuple_list_set_item_eliminator 0.35% : 0.000350s : 2245: predicate.tuple_to_list_eliminator_ 0.53% : 0.000528s : 3686: predicate.updatestate_pure_node_eliminater 33.07% : 0.032956s : 5476: predicate.updatestate_useless_node_eliminater 0.08% : 0.000084s : 392: predicate.value_based_eliminate 0.25% : 0.000245s : 1082: predicate.virtual_dataset_eliminate 0.24% : 0.000242s : 1082: predicate.virtual_output_eliminate 0.05% : 0.000054s : 392: predicate.virtual_view_grad_eliminate 0.11% : 0.000113s : 392: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.372181 630 52.38% : 0.194949s : 456: func_graph_cloner_run.FuncGraphClonerGraph 1.77% : 0.006589s : 58: func_graph_cloner_run.FuncGraphClonerNode 45.85% : 0.170643s : 116: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 13.020300 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.83% : 0.107586s : 1: add_attr 0.83% : 0.107564s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.003231s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.02% : 0.002740s : 1: auto_monad 0.01% : 0.000805s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: begin_end_overlap_inline 0.00% : 0.000012s : 1: bias_add_comm_swap 0.01% : 0.000747s : 1: bootstrap 0.00% : 0.000247s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.01% : 0.000762s : 1: control_data_broadcast_order 0.00% : 0.000588s : 1: convert_after_rewriter 0.01% : 0.001109s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000009s : 1: detach_backward 0.00% : 0.000235s : 1: environ_conv 0.01% : 0.001460s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000011s : 1: get_jit_bprop_graph 0.00% : 0.000174s : 1: graph_reusing 0.00% : 0.000007s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000014s : 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% : 0.000007s : 1: label_fine_grained_interleaved_index 0.00% : 0.000013s : 1: label_micro_interleaved_index 0.01% : 0.001329s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.63% : 0.081861s : 1: mutable_eliminate 0.00% : 0.000183s : 1: offloading_packed_experts 0.00% : 0.000501s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000757s : 1: opt.transform.mutable_eliminate 3.94% : 0.512710s : 95: opt.transform.opt_a 0.54% : 0.070050s : 1: opt.transform.opt_after_cconv 0.01% : 0.001247s : 1: opt.transform.opt_after_jit_grad 0.08% : 0.011023s : 28: opt.transform.opt_b 0.03% : 0.003715s : 2: opt.transform.opt_trans_graph 0.02% : 0.002963s : 4: opt.transform.symbol_engine_opt 12.11% : 1.576692s : 1: opt_a 0.56% : 0.073318s : 1: opt_after_cconv 0.02% : 0.002509s : 1: opt_after_jit_grad 0.11% : 0.014275s : 1: opt_b 14.27% : 1.857388s : 1: optimize 0.01% : 0.000869s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000359s : 1: order_py_execute_after_rewriter 0.01% : 0.001010s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000173s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000030s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000016s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000176s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000010s : 1: parallel-infer-symbol 0.00% : 0.000006s : 1: parallel-infer-symbol-second 0.00% : 0.000012s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000006s : 1: pipeline_split 0.01% : 0.001034s : 1: pre_auto_parallel 0.01% : 0.001257s : 1: py_interpret_to_execute 0.01% : 0.000764s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.53% : 0.069135s : 1: remove_dup_value 3.75% : 0.488160s : 1: renormalize.infer 1.78% : 0.231842s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.003511s : 1: rewriter_after_opt_a 0.02% : 0.003223s : 1: rewriter_before_opt_a 0.00% : 0.000011s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000489s : 1: swap_dp_allreduce_reducescatter 0.14% : 0.018374s : 1: symbol_engine_optimizer 0.03% : 0.003842s : 1: tuple_transform 59.58% : 7.758013s : 1: type_inference [WARNING] RUNTIME_FRAMEWORK(164252,ffffbeee0f30,python3.9):2026-01-29-17:38:30.602.298 [mindspore/ccsrc/backend/ms_backend/runtime/actors/base/super_kernel_actor.cc:1399] BuildAndLinkKernelActors] Set new stream for capture graph, stream id: 2 . [hook] pytest_runtest_teardown:test_kv_cache_for_capture_graph tests/st/runtime/kernel_capture/test_capture_graph.py::test_kv_cache_for_capture_graph,max_mem:6.0M =============================== 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_capture_graph.py::test_kv_cache_for_capture_graph /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 333.24s (0:05:33) ==================