==================================================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_005/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_event.py [WARNING] ME(166186:281472903597872,MainProcess):2026-01-29-17:38:04.453.712 [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(166186:281472903597872,MainProcess):2026-01-29-17:38:04.454.473 [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. [WARNING] ME(166186:281472903597872,MainProcess):2026-01-29-17:38:06.830.5 [mindspore/common/dtype.py:209] The interface 'mindspore.pytype_to_dtype' is deprecated from version 2.7 and will be removed in a future version. TotalTime = 1.81037, [30] [bootstrap]: 0.00041247 [type_inference]: 0.406449 [event_method]: 7.701e-05 [auto_monad]: 0.00057817 [graph_reusing]: 1.484e-05 [pre_auto_parallel]: 1.904e-05 [py_interpret_to_execute]: 7.009e-05 [rewriter_before_opt_a]: 0.00025142 [expand_dump_flag]: 7.95e-06 [jit_opt_a]: 1.38893, [4] [Cycle 1]: 1.22509, [53] [switch_simplify]: 0.00019088 [loop_unroll]: 0.00010899 [a_1]: 0.0039266 [with_stream_mark]: 6.621e-05 [recompute_prepare]: 7.241e-05 [updatestate_depend_eliminate]: 0.00013808 [updatestate_assign_eliminate]: 3.133e-05 [updatestate_loads_eliminate]: 7.898e-05 [parameter_eliminate]: 4.43999e-06 [specialize_transform]: 5.284e-05 [updatestate_useless_node_eliminater]: 6.736e-05 [accelerated_algorithm]: 8.139e-05 [meta_shard_fg_expand]: 1.076e-05 [get_grad_eliminate_]: 4.342e-05 [merge_forward]: 2.657e-05 [cell_reuse_recompute_pass]: 1.54e-06 [cell_reuse_handle_not_recompute_node_pass]: 9.66e-05 [j_node_and_user_rematch]: 8.257e-05 [meta_morphosis]: 0.00075031 [meta_morphosis_renormalize]: 0.32012 [meta_morphosis_event_method]: 7.673e-05 [meta_morphosis_auto_monad_grad]: 0.00013582 [switch_simplify]: 9.742e-05 [loop_unroll]: 6.886e-05 [a_1]: 0.00234361 [with_stream_mark]: 0.00017132 [recompute_prepare]: 7.641e-05 [updatestate_depend_eliminate]: 4.875e-05 [updatestate_assign_eliminate]: 3.808e-05 [updatestate_loads_eliminate]: 3.954e-05 [parameter_eliminate]: 6.50002e-06 [specialize_transform]: 8.154e-05 [updatestate_useless_node_eliminater]: 8.27e-05 [accelerated_algorithm]: 0.00011731 [meta_shard_fg_expand]: 1.985e-05 [get_grad_eliminate_]: 5.592e-05 [merge_forward]: 3.728e-05 [cell_reuse_recompute_pass]: 1.62001e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00011663 [j_node_and_user_rematch]: 0.00010291 [meta_morphosis]: 5.998e-05 [meta_morphosis_renormalize]: 8.00064e-08 [meta_morphosis_event_method]: 5.323e-05 [meta_morphosis_auto_monad_grad]: 8.94e-06 [meta_fg_expand]: 0.484574, [1] [partial_eliminate_before_grad]: 0.00037054, [1] [Cycle 1]: 0.00035477, [1] [partial_eliminate_]: 0.00029555 [replace_old_param]: 0.00047579 [inline_without_move]: 0.00053366 [renormalize]: 0.31711 [add_forward_monad_depend]: 8.32e-05 [auto_monad_grad]: 4.23e-05 [auto_monad_eliminator]: 0.00047984 [cse]: 0.0900686 [replace_applicator]: 0.00086409 [Cycle 2]: 0.0173158, [31] [switch_simplify]: 0.00036504 [loop_unroll]: 0.00034694 [a_1]: 0.00961016 [with_stream_mark]: 0.0001515 [recompute_prepare]: 4.62e-05 [updatestate_depend_eliminate]: 5.907e-05 [updatestate_assign_eliminate]: 2.633e-05 [updatestate_loads_eliminate]: 2.821e-05 [parameter_eliminate]: 2.72001e-06 [specialize_transform]: 3.91e-05 [updatestate_useless_node_eliminater]: 7.546e-05 [accelerated_algorithm]: 4.171e-05 [meta_shard_fg_expand]: 1.455e-05 [get_grad_eliminate_]: 3.095e-05 [merge_forward]: 1.835e-05 [cell_reuse_recompute_pass]: 2.01e-06 [cell_reuse_handle_not_recompute_node_pass]: 6.712e-05 [j_node_and_user_rematch]: 5.637e-05 [meta_morphosis]: 3.552e-05 [meta_morphosis_renormalize]: 7.00238e-08 [meta_morphosis_event_method]: 2.493e-05 [meta_morphosis_auto_monad_grad]: 3.86001e-06 [meta_fg_expand]: 0.00012298 [replace_old_param]: 3.879e-05 [inline_without_move]: 3.187e-05 [renormalize]: 0.0053059 [add_forward_monad_depend]: 1.311e-05 [auto_monad_grad]: 2.53e-06 [auto_monad_eliminator]: 9.443e-05 [cse]: 0.00021547 [replace_applicator]: 5.111e-05 [Cycle 3]: 0.134, [31] [switch_simplify]: 3.196e-05 [loop_unroll]: 3.061e-05 [a_1]: 0.00095783 [with_stream_mark]: 3.255e-05 [recompute_prepare]: 3.07e-05 [updatestate_depend_eliminate]: 5.365e-05 [updatestate_assign_eliminate]: 1.953e-05 [updatestate_loads_eliminate]: 2.053e-05 [parameter_eliminate]: 2.02999e-06 [specialize_transform]: 2.949e-05 [updatestate_useless_node_eliminater]: 3.614e-05 [accelerated_algorithm]: 3.617e-05 [meta_shard_fg_expand]: 6.61999e-06 [get_grad_eliminate_]: 2.776e-05 [merge_forward]: 1.666e-05 [cell_reuse_recompute_pass]: 2.82002e-06 [cell_reuse_handle_not_recompute_node_pass]: 6.003e-05 [j_node_and_user_rematch]: 5.104e-05 [meta_morphosis]: 3.2e-05 [meta_morphosis_renormalize]: 8.00064e-08 [meta_morphosis_event_method]: 2.236e-05 [meta_morphosis_auto_monad_grad]: 2.49999e-06 [meta_fg_expand]: 1.283e-05 [replace_old_param]: 3.544e-05 [inline_without_move]: 2.779e-05 [renormalize]: 0.131806 [add_forward_monad_depend]: 1.219e-05 [auto_monad_grad]: 3.26999e-06 [auto_monad_eliminator]: 8.787e-05 [cse]: 0.00014266 [replace_applicator]: 5.119e-05 [Cycle 4]: 0.00181197, [31] [switch_simplify]: 2.933e-05 [loop_unroll]: 2.765e-05 [a_1]: 0.00083859 [with_stream_mark]: 3.064e-05 [recompute_prepare]: 2.781e-05 [updatestate_depend_eliminate]: 2.021e-05 [updatestate_assign_eliminate]: 1.752e-05 [updatestate_loads_eliminate]: 2.015e-05 [parameter_eliminate]: 2.27999e-06 [specialize_transform]: 2.902e-05 [updatestate_useless_node_eliminater]: 3.534e-05 [accelerated_algorithm]: 3.641e-05 [meta_shard_fg_expand]: 7.03e-06 [get_grad_eliminate_]: 2.776e-05 [merge_forward]: 1.693e-05 [cell_reuse_recompute_pass]: 3.11999e-06 [cell_reuse_handle_not_recompute_node_pass]: 6.271e-05 [j_node_and_user_rematch]: 5.147e-05 [meta_morphosis]: 3.187e-05 [meta_morphosis_renormalize]: 8.00064e-08 [meta_morphosis_event_method]: 2.226e-05 [meta_morphosis_auto_monad_grad]: 1.51998e-06 [meta_fg_expand]: 1.259e-05 [replace_old_param]: 3.523e-05 [inline_without_move]: 2.78e-05 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 1.64e-06 [auto_monad_grad]: 5.19998e-07 [auto_monad_eliminator]: 5.03e-05 [cse]: 7.981e-05 [replace_applicator]: 2.795e-05 [py_interpret_to_execute_after_opt_a]: 4.027e-05 [rewriter_after_opt_a]: 0.00047566 [convert_after_rewriter]: 3.698e-05 [order_py_execute_after_rewriter]: 2.153e-05 [mutable_eliminate]: 0.00085784 [jit_opt_b]: 0.00020118, [1] [Cycle 1]: 0.00019091, [2] [frontend_op_eliminate]: 8.618e-05 [inline_after_opt_a]: 8.392e-05 [cconv]: 4.72e-05 [loop_unroll]: 0.00048293 [jit_opt_after_cconv]: 0.00057923, [1] [Cycle 1]: 0.00056876, [11] [c_1]: 0.0001641 [parameter_eliminate]: 4.42e-06 [updatestate_depend_eliminate]: 2.796e-05 [updatestate_assign_eliminate]: 1.703e-05 [updatestate_loads_eliminate]: 1.992e-05 [cse]: 0.00010709 [call_graph_tuple_transform]: 7.579e-05 [tuple_list_get_item_eliminator]: 2.914e-05 [none_parameter_eliminate]: 2.54999e-06 [renormalize]: 4.59986e-07 [switch_simplify]: 2.779e-05 [remove_dup_value]: 0.00012371 [partial_unused_args_eliminate]: 6.38998e-06 [environ_conv]: 4.048e-05 [add_recomputation]: 0.00436711 [cse_after_recomputation]: 0.0001675, [1] [Cycle 1]: 0.00015195, [1] [cse]: 0.00011504 [auto_monad_reorder]: 9.727e-05 [get_jit_bprop_graph]: 5.34e-06 [rewriter_after_jit_bprop_graph]: 1.055e-05 [opt_after_jit_grad]: 0.00108715 [symbol_engine_optimizer]: 0.00026332, [1] [Cycle 1]: 0.00025353, [6] [build]: 3.207e-05 [elim_shapecalc]: 3.445e-05 [elim_not_effective]: 5.582e-05 [opt_reshape]: 3.222e-05 [fold_const_symbol]: 4.948e-05 [renormalize]: 8.50006e-07 [validate]: 0.00411862 Sums bootstrap : 0.000412s : 0.03% type_inference : 0.406449s : 30.97% event_method : 0.000077s : 0.01% auto_monad : 0.000578s : 0.04% graph_reusing : 0.000015s : 0.00% pre_auto_parallel : 0.000019s : 0.00% py_interpret_to_execute : 0.000070s : 0.01% rewriter_before_opt_a : 0.000251s : 0.02% expand_dump_flag : 0.000008s : 0.00% jit_opt_a.switch_simplify : 0.000617s : 0.05% jit_opt_a.loop_unroll : 0.000514s : 0.04% jit_opt_a.a_1 : 0.015333s : 1.17% jit_opt_a.with_stream_mark : 0.000281s : 0.02% jit_opt_a.recompute_prepare : 0.000177s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000271s : 0.02% jit_opt_a.updatestate_assign_eliminate : 0.000095s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000148s : 0.01% jit_opt_a.parameter_eliminate : 0.000011s : 0.00% jit_opt_a.specialize_transform : 0.000150s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000214s : 0.02% jit_opt_a.accelerated_algorithm : 0.000196s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000039s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000130s : 0.01% jit_opt_a.merge_forward : 0.000079s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000286s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000241s : 0.02% jit_opt_a.meta_morphosis : 0.000850s : 0.06% jit_opt_a.meta_morphosis_renormalize : 0.320121s : 24.39% jit_opt_a.meta_morphosis_event_method : 0.000146s : 0.01% jit_opt_a.meta_morphosis_auto_monad_grad : 0.000144s : 0.01% jit_opt_a.meta_fg_expand : 0.000148s : 0.01% jit_opt_a.switch_simplify : 0.000097s : 0.01% jit_opt_a.loop_unroll : 0.000069s : 0.01% jit_opt_a.replace_old_param : 0.000109s : 0.01% jit_opt_a.a_1 : 0.002344s : 0.18% jit_opt_a.inline_without_move : 0.000087s : 0.01% jit_opt_a.renormalize : 0.137112s : 10.45% jit_opt_a.with_stream_mark : 0.000171s : 0.01% jit_opt_a.add_forward_monad_depend : 0.000027s : 0.00% jit_opt_a.recompute_prepare : 0.000076s : 0.01% jit_opt_a.auto_monad_grad : 0.000006s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000049s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000233s : 0.02% jit_opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% jit_opt_a.cse : 0.000438s : 0.03% jit_opt_a.updatestate_loads_eliminate : 0.000040s : 0.00% jit_opt_a.parameter_eliminate : 0.000007s : 0.00% jit_opt_a.replace_applicator : 0.000130s : 0.01% jit_opt_a.specialize_transform : 0.000082s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000083s : 0.01% jit_opt_a.accelerated_algorithm : 0.000117s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000020s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000056s : 0.00% jit_opt_a.merge_forward : 0.000037s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000002s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000117s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000103s : 0.01% jit_opt_a.meta_morphosis : 0.000060s : 0.00% jit_opt_a.meta_morphosis_renormalize : 0.000000s : 0.00% jit_opt_a.meta_morphosis_event_method : 0.000053s : 0.00% jit_opt_a.meta_morphosis_auto_monad_grad : 0.000009s : 0.00% jit_opt_a.meta_fg_expand.partial_eliminate_before_grad.partial_eliminate_ : 0.000296s : 0.02% jit_opt_a.replace_old_param : 0.000476s : 0.04% jit_opt_a.inline_without_move : 0.000534s : 0.04% jit_opt_a.renormalize : 0.317110s : 24.16% jit_opt_a.add_forward_monad_depend : 0.000083s : 0.01% jit_opt_a.auto_monad_grad : 0.000042s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000480s : 0.04% jit_opt_a.cse : 0.090069s : 6.86% jit_opt_a.replace_applicator : 0.000864s : 0.07% py_interpret_to_execute_after_opt_a : 0.000040s : 0.00% rewriter_after_opt_a : 0.000476s : 0.04% convert_after_rewriter : 0.000037s : 0.00% order_py_execute_after_rewriter : 0.000022s : 0.00% mutable_eliminate : 0.000858s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000086s : 0.01% jit_opt_b.inline_after_opt_a : 0.000084s : 0.01% cconv : 0.000047s : 0.00% loop_unroll : 0.000483s : 0.04% jit_opt_after_cconv.c_1 : 0.000164s : 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 : 0.000017s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000020s : 0.00% jit_opt_after_cconv.cse : 0.000107s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000076s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000029s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000028s : 0.00% remove_dup_value : 0.000124s : 0.01% partial_unused_args_eliminate : 0.000006s : 0.00% environ_conv : 0.000040s : 0.00% add_recomputation : 0.004367s : 0.33% cse_after_recomputation.cse : 0.000115s : 0.01% auto_monad_reorder : 0.000097s : 0.01% get_jit_bprop_graph : 0.000005s : 0.00% rewriter_after_jit_bprop_graph : 0.000011s : 0.00% opt_after_jit_grad : 0.001087s : 0.08% symbol_engine_optimizer.build : 0.000032s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000034s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000056s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000032s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000049s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.004119s : 0.31% Time group info: ------[substitution.] 0.006621 1169 0.12% : 0.000008s : 1: substitution.ad_related_special_op_eliminate 3.65% : 0.000241s : 39: substitution.arithmetic_simplify 1.42% : 0.000094s : 42: substitution.depend_value_elim 0.13% : 0.000008s : 23: substitution.elim_not_effective 0.23% : 0.000015s : 8: substitution.environ_get_add_eliminate 0.17% : 0.000011s : 6: substitution.environ_get_depend_swap 0.19% : 0.000012s : 8: substitution.environ_get_eliminate 0.38% : 0.000025s : 8: substitution.environ_get_set_eliminate 0.11% : 0.000008s : 23: substitution.fold_const_symbol 21.86% : 0.001447s : 8: substitution.getattr_setattr_resolve 0.31% : 0.000021s : 27: substitution.graph_param_transform 40.49% : 0.002681s : 64: substitution.inline 2.05% : 0.000136s : 22: substitution.inline_without_move 0.97% : 0.000064s : 158: substitution.j_node_and_user_rematch 1.42% : 0.000094s : 21: substitution.less_batch_normalization 0.37% : 0.000025s : 28: substitution.load_eliminater 7.92% : 0.000524s : 1: substitution.meta_morphosis 0.65% : 0.000043s : 35: substitution.minmaximum_grad 1.13% : 0.000075s : 16: substitution.partial_eliminate 0.14% : 0.000009s : 6: substitution.redundant_stop_gradient_eliminater 1.39% : 0.000092s : 158: substitution.remove_not_recompute_node 3.41% : 0.000226s : 70: substitution.replace_applicator 0.65% : 0.000043s : 65: substitution.replace_old_param 0.17% : 0.000011s : 4: substitution.set_cell_output_no_recompute 0.21% : 0.000014s : 2: substitution.specialize_transform 0.16% : 0.000010s : 7: substitution.split_environ_get_set_with_tuple_value 1.44% : 0.000095s : 35: substitution.tuple_list_convert_item_index_to_positive 0.99% : 0.000066s : 35: substitution.tuple_list_get_item_depend_reorder 3.59% : 0.000238s : 95: substitution.tuple_list_get_item_eliminator 1.36% : 0.000090s : 62: substitution.updatestate_pure_node_eliminater 2.93% : 0.000194s : 92: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.406282 2 78.00% : 0.316915s : 1: type_inference.infer 22.00% : 0.089367s : 1: type_inference.specialize ------[replace.] 0.001872 146 2.02% : 0.000038s : 1: replace.ad_related_special_op_eliminate 0.78% : 0.000015s : 2: replace.arithmetic_simplify 0.27% : 0.000005s : 1: replace.depend_value_elim 1.40% : 0.000026s : 2: replace.environ_get_set_eliminate 5.83% : 0.000109s : 6: replace.getattr_setattr_resolve 36.58% : 0.000685s : 62: replace.inline 5.35% : 0.000100s : 1: replace.meta_morphosis 5.43% : 0.000102s : 4: replace.partial_eliminate 5.59% : 0.000105s : 4: replace.replace_applicator 34.90% : 0.000653s : 60: replace.tuple_list_get_item_eliminator 1.85% : 0.000035s : 3: replace.updatestate_useless_node_eliminater ------[match.] 0.004827 146 0.13% : 0.000006s : 1: match.ad_related_special_op_eliminate 0.76% : 0.000037s : 2: match.arithmetic_simplify 0.03% : 0.000001s : 1: match.depend_value_elim 0.33% : 0.000016s : 2: match.environ_get_set_eliminate 28.19% : 0.001361s : 6: match.getattr_setattr_resolve 54.66% : 0.002638s : 62: match.inline 10.82% : 0.000522s : 1: match.meta_morphosis 1.14% : 0.000055s : 4: match.partial_eliminate 0.70% : 0.000034s : 4: match.replace_applicator 2.81% : 0.000135s : 60: match.tuple_list_get_item_eliminator 0.43% : 0.000021s : 3: match.updatestate_useless_node_eliminater ------[predicate.] 0.003360 22935 1.44% : 0.000048s : 375: predicate.accumulaten_eliminater 0.34% : 0.000011s : 54: predicate.ad_related_special_op_eliminate 1.41% : 0.000048s : 375: predicate.addn_check_dump 1.46% : 0.000049s : 375: predicate.addn_zero_filter 2.10% : 0.000070s : 377: predicate.arithmetic_simplify 1.48% : 0.000050s : 377: predicate.cast_eliminate 0.11% : 0.000004s : 27: predicate.check_bprop_eliminate 1.42% : 0.000048s : 375: predicate.compare_switch_simplify 1.52% : 0.000051s : 375: predicate.depend_value_elim 1.48% : 0.000050s : 379: predicate.dict_get_item_const_eliminator 1.51% : 0.000051s : 379: predicate.dict_get_item_eliminator 1.47% : 0.000049s : 379: predicate.dict_set_item_eliminator 0.26% : 0.000009s : 53: predicate.dumpgradient_eliminate 0.06% : 0.000002s : 26: predicate.elim_not_effective 0.14% : 0.000005s : 26: predicate.elim_shapecalc_of_broadcastargs 0.14% : 0.000005s : 37: predicate.eliminate_switch_conditional_partial_ 0.14% : 0.000005s : 37: predicate.eliminate_switch_layer_partial_ 0.14% : 0.000005s : 37: predicate.eliminate_switch_partial_ 1.44% : 0.000048s : 377: predicate.environ_add_const_eliminate 1.48% : 0.000050s : 379: predicate.environ_get_add_eliminate 1.43% : 0.000048s : 377: predicate.environ_get_depend_swap 2.47% : 0.000083s : 379: predicate.environ_get_eliminate 1.45% : 0.000049s : 379: predicate.environ_get_set_eliminate 0.05% : 0.000002s : 26: predicate.fold_const_symbol 0.81% : 0.000027s : 183: predicate.get_grad_eliminate 0.33% : 0.000011s : 40: predicate.getattr_setattr_resolve 0.06% : 0.000002s : 27: predicate.graph_param_transform 3.59% : 0.000121s : 559: predicate.inline 2.37% : 0.000080s : 467: predicate.inline_without_move 0.38% : 0.000013s : 183: predicate.j_node_and_user_rematch 0.97% : 0.000032s : 186: predicate.less_batch_normalization 1.75% : 0.000059s : 439: predicate.list_to_tuple_eliminator_ 1.90% : 0.000064s : 468: predicate.load_eliminater 0.22% : 0.000007s : 27: predicate.loop_unroll_after_grad 2.78% : 0.000093s : 649: predicate.loop_unroll_before_grad 1.64% : 0.000055s : 406: predicate.make_slice_get_slice_eliminator 1.42% : 0.000048s : 375: predicate.merge_addn 2.28% : 0.000076s : 229: predicate.meta_morphosis 1.46% : 0.000049s : 377: predicate.minmaximum_grad 0.29% : 0.000010s : 27: predicate.mutable_eliminate 0.12% : 0.000004s : 26: predicate.opt_reshape 2.76% : 0.000093s : 507: predicate.partial_eliminate 1.44% : 0.000048s : 374: predicate.print_const_string_wrapper 1.82% : 0.000061s : 377: predicate.reduce_eliminate 1.75% : 0.000059s : 441: predicate.redundant_stop_gradient_eliminater 0.41% : 0.000014s : 183: predicate.remove_not_recompute_node 2.50% : 0.000084s : 924: predicate.replace_applicator 1.06% : 0.000036s : 467: predicate.replace_old_param 0.06% : 0.000002s : 27: predicate.reset_defer_inline 1.50% : 0.000050s : 377: predicate.reshape_eliminate 1.45% : 0.000049s : 374: predicate.row_tensor_add_zeros_like 0.14% : 0.000005s : 27: predicate.row_tensor_eliminate 1.48% : 0.000050s : 374: predicate.same_eliminate 0.51% : 0.000017s : 202: predicate.set_cell_output_no_recompute 0.37% : 0.000012s : 80: predicate.special_op_eliminate 0.96% : 0.000032s : 187: predicate.specialize_transform 1.71% : 0.000057s : 374: predicate.split_environ_get_set_with_tuple_value 1.48% : 0.000050s : 374: predicate.stack_unstack_eliminate 0.12% : 0.000004s : 27: predicate.switch_call_monad_eliminater 3.00% : 0.000101s : 505: predicate.switch_defer_inline 2.18% : 0.000073s : 505: predicate.switch_layer_defer_inline 6.02% : 0.000202s : 1181: predicate.switch_simplify 1.48% : 0.000050s : 377: predicate.tile_eliminate 1.45% : 0.000049s : 377: predicate.transpose_eliminate 1.87% : 0.000063s : 379: predicate.tuple_list_convert_item_index_to_positive 1.71% : 0.000057s : 379: predicate.tuple_list_get_item_depend_reorder 2.89% : 0.000097s : 493: predicate.tuple_list_get_item_eliminator 1.91% : 0.000064s : 379: predicate.tuple_list_set_item_eliminator 1.75% : 0.000059s : 439: predicate.tuple_to_list_eliminator_ 1.92% : 0.000064s : 468: predicate.updatestate_pure_node_eliminater 2.85% : 0.000096s : 655: predicate.updatestate_useless_node_eliminater 1.78% : 0.000060s : 374: predicate.value_based_eliminate 0.24% : 0.000008s : 53: predicate.virtual_view_grad_eliminate 0.14% : 0.000005s : 27: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.068780 174 92.31% : 0.063489s : 89: func_graph_cloner_run.FuncGraphClonerGraph 0.22% : 0.000149s : 2: func_graph_cloner_run.FuncGraphClonerNode 7.48% : 0.005142s : 83: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.606971 125 0.17% : 0.004381s : 1: add_recomputation 0.02% : 0.000585s : 1: auto_monad 0.00% : 0.000100s : 1: auto_monad_reorder 0.02% : 0.000426s : 1: bootstrap 0.00% : 0.000049s : 1: cconv 0.00% : 0.000040s : 1: convert_after_rewriter 0.01% : 0.000173s : 1: cse_after_recomputation 0.00% : 0.000043s : 1: environ_conv 0.00% : 0.000082s : 1: event_method 0.00% : 0.000011s : 1: expand_dump_flag 0.00% : 0.000008s : 1: get_jit_bprop_graph 0.00% : 0.000019s : 1: graph_reusing 53.28% : 1.388935s : 1: jit_opt_a 0.02% : 0.000582s : 1: jit_opt_after_cconv 0.01% : 0.000204s : 1: jit_opt_b 0.02% : 0.000488s : 1: loop_unroll 0.03% : 0.000864s : 1: mutable_eliminate 0.92% : 0.023922s : 67: opt.transform.jit_opt_a 0.01% : 0.000293s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000157s : 4: opt.transform.jit_opt_b 0.00% : 0.000039s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000050s : 1: opt.transform.mutable_eliminate 0.01% : 0.000251s : 2: opt.transform.opt_after_jit_grad 0.06% : 0.001662s : 4: opt.transform.opt_resolve 0.01% : 0.000288s : 1: opt.transform.partial_eliminate 0.01% : 0.000169s : 4: opt.transform.symbol_engine_opt 0.04% : 0.001093s : 1: opt_after_jit_grad 0.00% : 0.000024s : 1: order_py_execute_after_rewriter 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000021s : 1: pre_auto_parallel 0.00% : 0.000073s : 1: py_interpret_to_execute 0.00% : 0.000043s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000127s : 1: remove_dup_value 29.04% : 0.756944s : 4: renormalize.infer 0.67% : 0.017342s : 4: renormalize.specialize 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000480s : 1: rewriter_after_opt_a 0.01% : 0.000255s : 1: rewriter_before_opt_a 0.01% : 0.000267s : 1: symbol_engine_optimizer 15.59% : 0.406462s : 1: type_inference [WARNING] ME(166186:281472903597872,MainProcess):2026-01-29-17:38:21.165.981 [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_event_with_morph tests/st/compiler/stream_event/test_with_stream_event.py::test_with_stream_event_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 92.26s (0:01:32) ===================