==================================================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/compiler/stream_event, configfile: ../../../../../../../sault/virtual_test/virtualenv_001/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_with_stream.py [WARNING] ME(171410:281473746485040,MainProcess):2026-01-29-17:38:18.891.826 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS instead. [WARNING] ME(171410:281473746485040,MainProcess):2026-01-29-17:38:18.892.512 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs_path' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS_PATH instead. TotalTime = 2.29572, [30] [bootstrap]: 0.00865132 [type_inference]: 0.293206 [event_method]: 9.155e-05 [auto_monad]: 0.00061215 [graph_reusing]: 1.504e-05 [pre_auto_parallel]: 1.884e-05 [py_interpret_to_execute]: 8.773e-05 [rewriter_before_opt_a]: 0.00026253 [expand_dump_flag]: 7.38999e-06 [jit_opt_a]: 1.9114, [4] [Cycle 1]: 1.49752, [53] [switch_simplify]: 0.00024071 [loop_unroll]: 0.00011045 [a_1]: 0.106073 [with_stream_mark]: 0.00012703 [recompute_prepare]: 7.742e-05 [updatestate_depend_eliminate]: 0.00017207 [updatestate_assign_eliminate]: 3.111e-05 [updatestate_loads_eliminate]: 8.902e-05 [parameter_eliminate]: 4.87998e-06 [specialize_transform]: 5.135e-05 [updatestate_useless_node_eliminater]: 7.234e-05 [accelerated_algorithm]: 8.823e-05 [meta_shard_fg_expand]: 2.098e-05 [get_grad_eliminate_]: 4.136e-05 [merge_forward]: 2.839e-05 [cell_reuse_recompute_pass]: 1.88997e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.000102 [j_node_and_user_rematch]: 8.227e-05 [meta_morphosis]: 0.00077611 [meta_morphosis_renormalize]: 0.3669 [meta_morphosis_event_method]: 8.504e-05 [meta_morphosis_auto_monad_grad]: 0.00016818 [switch_simplify]: 0.000114 [loop_unroll]: 7.402e-05 [a_1]: 0.00257123 [with_stream_mark]: 0.00024111 [recompute_prepare]: 9.128e-05 [updatestate_depend_eliminate]: 5.934e-05 [updatestate_assign_eliminate]: 3.849e-05 [updatestate_loads_eliminate]: 4.029e-05 [parameter_eliminate]: 7.33e-06 [specialize_transform]: 8.561e-05 [updatestate_useless_node_eliminater]: 8.975e-05 [accelerated_algorithm]: 6.388e-05 [meta_shard_fg_expand]: 2.738e-05 [get_grad_eliminate_]: 5.194e-05 [merge_forward]: 4.313e-05 [cell_reuse_recompute_pass]: 3.53e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00012596 [j_node_and_user_rematch]: 0.000102 [meta_morphosis]: 6.992e-05 [meta_morphosis_renormalize]: 8.00064e-08 [meta_morphosis_event_method]: 5.37e-05 [meta_morphosis_auto_monad_grad]: 9.87999e-06 [meta_fg_expand]: 0.483691, [1] [partial_eliminate_before_grad]: 0.00031675, [1] [Cycle 1]: 0.00030475, [1] [partial_eliminate_]: 0.00025328 [replace_old_param]: 0.00059684 [inline_without_move]: 0.00687141 [renormalize]: 0.487816 [add_forward_monad_depend]: 0.00019611 [auto_monad_grad]: 8.254e-05 [auto_monad_eliminator]: 0.00760302 [cse]: 0.020063 [replace_applicator]: 0.00995789 [Cycle 2]: 0.262127, [31] [switch_simplify]: 0.00052669 [loop_unroll]: 0.0003437 [a_1]: 0.136207 [with_stream_mark]: 6.757e-05 [recompute_prepare]: 3.996e-05 [updatestate_depend_eliminate]: 6.722e-05 [updatestate_assign_eliminate]: 1.807e-05 [updatestate_loads_eliminate]: 0.00013363 [parameter_eliminate]: 3.91001e-06 [specialize_transform]: 3.37e-05 [updatestate_useless_node_eliminater]: 4.502e-05 [accelerated_algorithm]: 3.367e-05 [meta_shard_fg_expand]: 2.759e-05 [get_grad_eliminate_]: 2.326e-05 [merge_forward]: 1.565e-05 [cell_reuse_recompute_pass]: 2.72001e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.648e-05 [j_node_and_user_rematch]: 4.198e-05 [meta_morphosis]: 2.809e-05 [meta_morphosis_renormalize]: 8.9989e-08 [meta_morphosis_event_method]: 1.823e-05 [meta_morphosis_auto_monad_grad]: 5.06997e-06 [meta_fg_expand]: 0.00019826 [replace_old_param]: 3.939e-05 [inline_without_move]: 2.321e-05 [renormalize]: 0.122357 [add_forward_monad_depend]: 1.977e-05 [auto_monad_grad]: 3.76999e-06 [auto_monad_eliminator]: 0.00014744 [cse]: 0.0010565 [replace_applicator]: 5.459e-05 [Cycle 3]: 0.0515694, [31] [switch_simplify]: 2.646e-05 [loop_unroll]: 2.256e-05 [a_1]: 0.00085532 [with_stream_mark]: 4.212e-05 [recompute_prepare]: 2.76e-05 [updatestate_depend_eliminate]: 1.644e-05 [updatestate_assign_eliminate]: 1.453e-05 [updatestate_loads_eliminate]: 1.805e-05 [parameter_eliminate]: 2.94999e-06 [specialize_transform]: 2.272e-05 [updatestate_useless_node_eliminater]: 3.915e-05 [accelerated_algorithm]: 3.227e-05 [meta_shard_fg_expand]: 9.70002e-06 [get_grad_eliminate_]: 1.969e-05 [merge_forward]: 1.31e-05 [cell_reuse_recompute_pass]: 4e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.159e-05 [j_node_and_user_rematch]: 3.559e-05 [meta_morphosis]: 2.58e-05 [meta_morphosis_renormalize]: 6.89994e-07 [meta_morphosis_event_method]: 1.806e-05 [meta_morphosis_auto_monad_grad]: 4.58001e-06 [meta_fg_expand]: 1.073e-05 [replace_old_param]: 3.181e-05 [inline_without_move]: 2.045e-05 [renormalize]: 0.0494043 [add_forward_monad_depend]: 1.397e-05 [auto_monad_grad]: 3.21001e-06 [auto_monad_eliminator]: 0.0001067 [cse]: 0.00026145 [replace_applicator]: 5.107e-05 [Cycle 4]: 0.0186785, [31] [switch_simplify]: 2.571e-05 [loop_unroll]: 2.17e-05 [a_1]: 0.00073939 [with_stream_mark]: 3.419e-05 [recompute_prepare]: 2.59e-05 [updatestate_depend_eliminate]: 1.559e-05 [updatestate_assign_eliminate]: 1.512e-05 [updatestate_loads_eliminate]: 1.702e-05 [parameter_eliminate]: 2.10002e-06 [specialize_transform]: 2.373e-05 [updatestate_useless_node_eliminater]: 8.34e-05 [accelerated_algorithm]: 3.483e-05 [meta_shard_fg_expand]: 1.182e-05 [get_grad_eliminate_]: 2.033e-05 [merge_forward]: 1.254e-05 [cell_reuse_recompute_pass]: 4.45e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.935e-05 [j_node_and_user_rematch]: 3.658e-05 [meta_morphosis]: 2.436e-05 [meta_morphosis_renormalize]: 6.99947e-08 [meta_morphosis_event_method]: 1.571e-05 [meta_morphosis_auto_monad_grad]: 3.67998e-06 [meta_fg_expand]: 1.058e-05 [replace_old_param]: 3.106e-05 [inline_without_move]: 2.039e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.54999e-06 [auto_monad_grad]: 5.69999e-07 [auto_monad_eliminator]: 0.0168486 [cse]: 0.00013678 [replace_applicator]: 4.999e-05 [py_interpret_to_execute_after_opt_a]: 5.576e-05 [rewriter_after_opt_a]: 0.00370107 [convert_after_rewriter]: 4.31e-05 [order_py_execute_after_rewriter]: 1.845e-05 [mutable_eliminate]: 0.00087173 [jit_opt_b]: 0.00016699, [1] [Cycle 1]: 0.00015234, [2] [frontend_op_eliminate]: 6.559e-05 [inline_after_opt_a]: 6.425e-05 [cconv]: 4.286e-05 [loop_unroll]: 0.0005008 [jit_opt_after_cconv]: 0.00052349, [1] [Cycle 1]: 0.00051236, [11] [c_1]: 0.00012555 [parameter_eliminate]: 4.09002e-06 [updatestate_depend_eliminate]: 2.76e-05 [updatestate_assign_eliminate]: 2.212e-05 [updatestate_loads_eliminate]: 2.46e-05 [cse]: 0.00011652 [call_graph_tuple_transform]: 5.6e-05 [tuple_list_get_item_eliminator]: 2e-05 [none_parameter_eliminate]: 2.06998e-06 [renormalize]: 5.29981e-07 [switch_simplify]: 2.036e-05 [remove_dup_value]: 0.00010911 [partial_unused_args_eliminate]: 5.19e-06 [environ_conv]: 3.936e-05 [add_recomputation]: 0.00023066 [cse_after_recomputation]: 8.909e-05, [1] [Cycle 1]: 7.852e-05, [1] [cse]: 6.341e-05 [auto_monad_reorder]: 8.491e-05 [get_jit_bprop_graph]: 4.79002e-06 [rewriter_after_jit_bprop_graph]: 6.84999e-06 [opt_after_jit_grad]: 0.00064616 [symbol_engine_optimizer]: 0.000225, [1] [Cycle 1]: 0.00021483, [6] [build]: 4.436e-05 [elim_shapecalc]: 2.36e-05 [elim_not_effective]: 4.22e-05 [opt_reshape]: 2.041e-05 [fold_const_symbol]: 3.426e-05 [renormalize]: 5.49975e-07 [validate]: 0.0734106 Sums bootstrap : 0.008651s : 0.50% type_inference : 0.293206s : 16.97% event_method : 0.000092s : 0.01% auto_monad : 0.000612s : 0.04% graph_reusing : 0.000015s : 0.00% pre_auto_parallel : 0.000019s : 0.00% py_interpret_to_execute : 0.000088s : 0.01% rewriter_before_opt_a : 0.000263s : 0.02% expand_dump_flag : 0.000007s : 0.00% jit_opt_a.switch_simplify : 0.000820s : 0.05% jit_opt_a.loop_unroll : 0.000498s : 0.03% jit_opt_a.a_1 : 0.243875s : 14.12% jit_opt_a.with_stream_mark : 0.000271s : 0.02% jit_opt_a.recompute_prepare : 0.000171s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000271s : 0.02% jit_opt_a.updatestate_assign_eliminate : 0.000079s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000258s : 0.01% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000132s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000240s : 0.01% jit_opt_a.accelerated_algorithm : 0.000189s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000070s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000105s : 0.01% jit_opt_a.merge_forward : 0.000070s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000013s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000259s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000196s : 0.01% jit_opt_a.meta_morphosis : 0.000854s : 0.05% jit_opt_a.meta_morphosis_renormalize : 0.366901s : 21.24% jit_opt_a.meta_morphosis_event_method : 0.000137s : 0.01% jit_opt_a.meta_morphosis_auto_monad_grad : 0.000182s : 0.01% jit_opt_a.meta_fg_expand : 0.000220s : 0.01% jit_opt_a.switch_simplify : 0.000114s : 0.01% jit_opt_a.loop_unroll : 0.000074s : 0.00% jit_opt_a.replace_old_param : 0.000102s : 0.01% jit_opt_a.a_1 : 0.002571s : 0.15% jit_opt_a.inline_without_move : 0.000064s : 0.00% jit_opt_a.renormalize : 0.171761s : 9.94% jit_opt_a.with_stream_mark : 0.000241s : 0.01% jit_opt_a.add_forward_monad_depend : 0.000036s : 0.00% jit_opt_a.recompute_prepare : 0.000091s : 0.01% jit_opt_a.auto_monad_grad : 0.000008s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000059s : 0.00% jit_opt_a.auto_monad_eliminator : 0.017103s : 0.99% jit_opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% jit_opt_a.cse : 0.001455s : 0.08% jit_opt_a.updatestate_loads_eliminate : 0.000040s : 0.00% jit_opt_a.parameter_eliminate : 0.000007s : 0.00% jit_opt_a.replace_applicator : 0.000156s : 0.01% jit_opt_a.specialize_transform : 0.000086s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000090s : 0.01% jit_opt_a.accelerated_algorithm : 0.000064s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000027s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000052s : 0.00% jit_opt_a.merge_forward : 0.000043s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000126s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000102s : 0.01% jit_opt_a.meta_morphosis : 0.000070s : 0.00% jit_opt_a.meta_morphosis_renormalize : 0.000000s : 0.00% jit_opt_a.meta_morphosis_event_method : 0.000054s : 0.00% jit_opt_a.meta_morphosis_auto_monad_grad : 0.000010s : 0.00% jit_opt_a.meta_fg_expand.partial_eliminate_before_grad.partial_eliminate_ : 0.000253s : 0.01% jit_opt_a.replace_old_param : 0.000597s : 0.03% jit_opt_a.inline_without_move : 0.006871s : 0.40% jit_opt_a.renormalize : 0.487816s : 28.24% jit_opt_a.add_forward_monad_depend : 0.000196s : 0.01% jit_opt_a.auto_monad_grad : 0.000083s : 0.00% jit_opt_a.auto_monad_eliminator : 0.007603s : 0.44% jit_opt_a.cse : 0.020063s : 1.16% jit_opt_a.replace_applicator : 0.009958s : 0.58% py_interpret_to_execute_after_opt_a : 0.000056s : 0.00% rewriter_after_opt_a : 0.003701s : 0.21% convert_after_rewriter : 0.000043s : 0.00% order_py_execute_after_rewriter : 0.000018s : 0.00% mutable_eliminate : 0.000872s : 0.05% jit_opt_b.frontend_op_eliminate : 0.000066s : 0.00% jit_opt_b.inline_after_opt_a : 0.000064s : 0.00% cconv : 0.000043s : 0.00% loop_unroll : 0.000501s : 0.03% jit_opt_after_cconv.c_1 : 0.000126s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000028s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000022s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000025s : 0.00% jit_opt_after_cconv.cse : 0.000117s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000056s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000020s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000020s : 0.00% remove_dup_value : 0.000109s : 0.01% partial_unused_args_eliminate : 0.000005s : 0.00% environ_conv : 0.000039s : 0.00% add_recomputation : 0.000231s : 0.01% cse_after_recomputation.cse : 0.000063s : 0.00% auto_monad_reorder : 0.000085s : 0.00% get_jit_bprop_graph : 0.000005s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000646s : 0.04% symbol_engine_optimizer.build : 0.000044s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000024s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000042s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000020s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000034s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.073411s : 4.25% Time group info: ------[substitution.] 0.176470 1038 0.17% : 0.000293s : 41: substitution.arithmetic_simplify 0.06% : 0.000106s : 33: substitution.depend_value_elim 0.00% : 0.000006s : 15: substitution.elim_not_effective 0.01% : 0.000016s : 8: substitution.environ_get_add_eliminate 0.01% : 0.000012s : 6: substitution.environ_get_depend_swap 0.01% : 0.000020s : 8: substitution.environ_get_eliminate 0.02% : 0.000031s : 8: substitution.environ_get_set_eliminate 0.00% : 0.000006s : 15: substitution.fold_const_symbol 0.94% : 0.001663s : 8: substitution.getattr_setattr_resolve 0.01% : 0.000015s : 18: substitution.graph_param_transform 97.25% : 0.171623s : 59: substitution.inline 0.12% : 0.000210s : 19: substitution.inline_without_move 0.03% : 0.000057s : 127: substitution.j_node_and_user_rematch 0.03% : 0.000059s : 20: substitution.less_batch_normalization 0.02% : 0.000036s : 30: substitution.load_eliminater 0.32% : 0.000568s : 1: substitution.meta_morphosis 0.03% : 0.000052s : 33: substitution.minmaximum_grad 0.04% : 0.000068s : 16: substitution.partial_eliminate 0.00% : 0.000006s : 2: substitution.redundant_stop_gradient_eliminater 0.05% : 0.000080s : 127: substitution.remove_not_recompute_node 0.23% : 0.000415s : 65: substitution.replace_applicator 0.03% : 0.000051s : 60: substitution.replace_old_param 0.01% : 0.000017s : 4: substitution.set_cell_output_no_recompute 0.01% : 0.000016s : 2: substitution.specialize_transform 0.01% : 0.000016s : 7: substitution.split_environ_get_set_with_tuple_value 0.06% : 0.000113s : 33: substitution.tuple_list_convert_item_index_to_positive 0.05% : 0.000096s : 33: substitution.tuple_list_get_item_depend_reorder 0.20% : 0.000352s : 88: substitution.tuple_list_get_item_eliminator 0.06% : 0.000103s : 66: substitution.updatestate_pure_node_eliminater 0.21% : 0.000364s : 86: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.293012 2 99.07% : 0.290289s : 1: type_inference.infer 0.93% : 0.002723s : 1: type_inference.specialize ------[replace.] 0.044215 140 0.04% : 0.000017s : 2: replace.arithmetic_simplify 0.13% : 0.000057s : 4: replace.depend_value_elim 0.10% : 0.000043s : 2: replace.environ_get_set_eliminate 0.33% : 0.000145s : 6: replace.getattr_setattr_resolve 82.13% : 0.036312s : 57: replace.inline 0.21% : 0.000093s : 1: replace.meta_morphosis 0.19% : 0.000082s : 4: replace.partial_eliminate 14.29% : 0.006320s : 4: replace.replace_applicator 2.41% : 0.001068s : 55: replace.tuple_list_get_item_eliminator 0.11% : 0.000049s : 3: replace.updatestate_pure_node_eliminater 0.07% : 0.000029s : 2: replace.updatestate_useless_node_eliminater ------[match.] 0.174125 140 0.02% : 0.000043s : 2: match.arithmetic_simplify 0.00% : 0.000007s : 4: match.depend_value_elim 0.01% : 0.000021s : 2: match.environ_get_set_eliminate 0.90% : 0.001563s : 6: match.getattr_setattr_resolve 98.53% : 0.171558s : 57: match.inline 0.32% : 0.000565s : 1: match.meta_morphosis 0.02% : 0.000042s : 4: match.partial_eliminate 0.05% : 0.000080s : 4: match.replace_applicator 0.13% : 0.000219s : 55: match.tuple_list_get_item_eliminator 0.01% : 0.000009s : 3: match.updatestate_pure_node_eliminater 0.01% : 0.000018s : 2: match.updatestate_useless_node_eliminater ------[predicate.] 0.009641 21185 0.51% : 0.000050s : 359: predicate.accumulaten_eliminater 0.06% : 0.000006s : 18: predicate.ad_related_special_op_eliminate 0.48% : 0.000047s : 359: predicate.addn_check_dump 0.51% : 0.000049s : 359: predicate.addn_zero_filter 0.81% : 0.000078s : 361: predicate.arithmetic_simplify 0.53% : 0.000051s : 361: predicate.cast_eliminate 0.03% : 0.000003s : 18: predicate.check_bprop_eliminate 0.49% : 0.000047s : 359: predicate.compare_switch_simplify 0.55% : 0.000053s : 359: predicate.depend_value_elim 0.55% : 0.000053s : 363: predicate.dict_get_item_const_eliminator 0.51% : 0.000049s : 363: predicate.dict_get_item_eliminator 0.52% : 0.000050s : 363: predicate.dict_set_item_eliminator 0.03% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.02% : 0.000002s : 18: predicate.elim_not_effective 0.03% : 0.000003s : 18: predicate.elim_shapecalc_of_broadcastargs 0.04% : 0.000004s : 33: predicate.eliminate_switch_conditional_partial_ 0.04% : 0.000004s : 33: predicate.eliminate_switch_layer_partial_ 0.04% : 0.000004s : 33: predicate.eliminate_switch_partial_ 0.49% : 0.000047s : 361: predicate.environ_add_const_eliminate 0.49% : 0.000047s : 363: predicate.environ_get_add_eliminate 0.52% : 0.000050s : 361: predicate.environ_get_depend_swap 0.52% : 0.000051s : 363: predicate.environ_get_eliminate 0.49% : 0.000047s : 363: predicate.environ_get_set_eliminate 0.01% : 0.000001s : 18: predicate.fold_const_symbol 0.25% : 0.000024s : 152: predicate.get_grad_eliminate 0.14% : 0.000013s : 40: predicate.getattr_setattr_resolve 0.01% : 0.000001s : 18: predicate.graph_param_transform 1.37% : 0.000132s : 518: predicate.inline 64.58% : 0.006225s : 398: predicate.inline_without_move 0.11% : 0.000011s : 152: predicate.j_node_and_user_rematch 0.32% : 0.000031s : 152: predicate.less_batch_normalization 0.85% : 0.000082s : 418: predicate.list_to_tuple_eliminator_ 0.67% : 0.000064s : 438: predicate.load_eliminater 0.05% : 0.000005s : 18: predicate.loop_unroll_after_grad 1.07% : 0.000103s : 588: predicate.loop_unroll_before_grad 0.58% : 0.000056s : 381: predicate.make_slice_get_slice_eliminator 0.48% : 0.000046s : 359: predicate.merge_addn 0.73% : 0.000071s : 183: predicate.meta_morphosis 0.51% : 0.000050s : 361: predicate.minmaximum_grad 0.08% : 0.000007s : 18: predicate.mutable_eliminate 0.03% : 0.000003s : 18: predicate.opt_reshape 0.89% : 0.000086s : 473: predicate.partial_eliminate 0.49% : 0.000048s : 355: predicate.print_const_string_wrapper 0.68% : 0.000065s : 361: predicate.reduce_eliminate 0.62% : 0.000059s : 420: predicate.redundant_stop_gradient_eliminater 0.12% : 0.000012s : 152: predicate.remove_not_recompute_node 0.86% : 0.000082s : 837: predicate.replace_applicator 0.31% : 0.000030s : 398: predicate.replace_old_param 0.02% : 0.000002s : 18: predicate.reset_defer_inline 0.52% : 0.000050s : 361: predicate.reshape_eliminate 0.51% : 0.000049s : 355: predicate.row_tensor_add_zeros_like 0.04% : 0.000003s : 18: predicate.row_tensor_eliminate 0.54% : 0.000052s : 355: predicate.same_eliminate 0.15% : 0.000014s : 168: predicate.set_cell_output_no_recompute 0.06% : 0.000006s : 36: predicate.special_op_eliminate 0.29% : 0.000028s : 152: predicate.specialize_transform 0.58% : 0.000056s : 355: predicate.split_environ_get_set_with_tuple_value 0.50% : 0.000048s : 355: predicate.stack_unstack_eliminate 0.03% : 0.000003s : 18: predicate.switch_call_monad_eliminater 1.75% : 0.000169s : 482: predicate.switch_defer_inline 0.75% : 0.000073s : 482: predicate.switch_layer_defer_inline 3.12% : 0.000301s : 1088: predicate.switch_simplify 0.52% : 0.000050s : 361: predicate.tile_eliminate 0.51% : 0.000049s : 361: predicate.transpose_eliminate 0.65% : 0.000062s : 363: predicate.tuple_list_convert_item_index_to_positive 0.64% : 0.000062s : 363: predicate.tuple_list_get_item_depend_reorder 1.03% : 0.000100s : 454: predicate.tuple_list_get_item_eliminator 0.72% : 0.000069s : 363: predicate.tuple_list_set_item_eliminator 0.66% : 0.000064s : 418: predicate.tuple_to_list_eliminator_ 0.65% : 0.000063s : 441: predicate.updatestate_pure_node_eliminater 0.98% : 0.000094s : 595: predicate.updatestate_useless_node_eliminater 0.64% : 0.000062s : 355: predicate.value_based_eliminate 0.02% : 0.000002s : 18: predicate.virtual_view_grad_eliminate 0.04% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.097822 159 63.88% : 0.062488s : 79: func_graph_cloner_run.FuncGraphClonerGraph 0.15% : 0.000145s : 2: func_graph_cloner_run.FuncGraphClonerNode 35.97% : 0.035188s : 78: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.519297 124 0.01% : 0.000234s : 1: add_recomputation 0.02% : 0.000618s : 1: auto_monad 0.00% : 0.000088s : 1: auto_monad_reorder 0.25% : 0.008665s : 1: bootstrap 0.00% : 0.000045s : 1: cconv 0.00% : 0.000048s : 1: convert_after_rewriter 0.00% : 0.000092s : 1: cse_after_recomputation 0.00% : 0.000042s : 1: environ_conv 0.00% : 0.000096s : 1: event_method 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000019s : 1: graph_reusing 54.31% : 1.911408s : 1: jit_opt_a 0.01% : 0.000527s : 1: jit_opt_after_cconv 0.00% : 0.000170s : 1: jit_opt_b 0.01% : 0.000506s : 1: loop_unroll 0.02% : 0.000878s : 1: mutable_eliminate 7.62% : 0.268274s : 67: opt.transform.jit_opt_a 0.01% : 0.000217s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000114s : 4: opt.transform.jit_opt_b 0.00% : 0.000029s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000043s : 1: opt.transform.mutable_eliminate 0.00% : 0.000075s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.001952s : 4: opt.transform.opt_resolve 0.01% : 0.000248s : 1: opt.transform.partial_eliminate 0.00% : 0.000117s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000652s : 1: opt_after_jit_grad 0.00% : 0.000021s : 1: order_py_execute_after_rewriter 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000021s : 1: pre_auto_parallel 0.00% : 0.000090s : 1: py_interpret_to_execute 0.00% : 0.000059s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000112s : 1: remove_dup_value 22.45% : 0.789940s : 4: renormalize.infer 6.72% : 0.236439s : 4: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.11% : 0.003715s : 1: rewriter_after_opt_a 0.01% : 0.000266s : 1: rewriter_before_opt_a 0.01% : 0.000228s : 1: symbol_engine_optimizer 8.33% : 0.293219s : 1: type_inference [WARNING] ME(171410:281473746485040,MainProcess):2026-01-29-17:38:29.578.343 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS instead. . [hook] pytest_runtest_teardown:test_with_stream_with_morph tests/st/compiler/stream_event/test_with_stream.py::test_with_stream_with_morph,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") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 1 passed, 25 warnings in 96.30s (0:01:36) ===================