[WARNING] ME(163162:281473224970032,MainProcess):2026-01-29-17:37:50.229.945 [mindspore/graph/_mark_deprecated.py:40] Module 'mindspore.common.api' is deprecated from version 2.9.0 and will be removed in a future version, use 'mindspore.graph.api' 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/mint/optim, 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 2 items test_fused_adamw.py ................[WARNING] ANALYZER(163162,ffff97968f30,python3.9):2026-01-29-17:44:21.875.868 [mindspore/ccsrc/frontend/jit/ps/static_analysis/auto_monad.cc:1601] ClearIsolatedNodes] Some side effect nodes were eliminated by mistake. The node is:@2_train_step_33:_{[0]: ValueNode 132__tuple_getitem_by_number_34, [1]: CNode_35, [2]: ValueNode 1} TotalTime = 3.41459, [30] [bootstrap]: 0.00150878 [type_inference]: 2.61086 [event_method]: 0.00033584 [auto_monad]: 0.00254582 [graph_reusing]: 0.00013054 [pre_auto_parallel]: 3.376e-05 [py_interpret_to_execute]: 0.00057462 [rewriter_before_opt_a]: 0.0732315 [expand_dump_flag]: 5.42e-05 [jit_opt_a]: 0.674675, [4] [Cycle 1]: 0.577557, [27] [switch_simplify]: 0.00141998 [loop_unroll]: 0.00058869 [a_1]: 0.0988888 [with_stream_mark]: 0.00023524 [recompute_prepare]: 0.0001378 [updatestate_depend_eliminate]: 0.00074758 [updatestate_assign_eliminate]: 6.694e-05 [updatestate_loads_eliminate]: 0.00013017 [parameter_eliminate]: 5.29998e-06 [specialize_transform]: 8.706e-05 [updatestate_useless_node_eliminater]: 0.0001018 [accelerated_algorithm]: 0.0001426 [meta_shard_fg_expand]: 3.65e-05 [get_grad_eliminate_]: 6.638e-05 [merge_forward]: 3.925e-05 [cell_reuse_recompute_pass]: 3.07002e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00012728 [j_node_and_user_rematch]: 0.0001148 [meta_fg_expand]: 0.206181 [replace_old_param]: 0.00039933 [inline_without_move]: 0.00037938 [renormalize]: 0.264096 [add_forward_monad_depend]: 0.0001441 [auto_monad_grad]: 4.513e-05 [auto_monad_eliminator]: 0.00070126 [cse]: 0.00123673 [replace_applicator]: 0.00081467 [Cycle 2]: 0.0779431, [27] [switch_simplify]: 0.00036402 [loop_unroll]: 0.00032131 [a_1]: 0.0504786 [with_stream_mark]: 0.00030071 [recompute_prepare]: 7.893e-05 [updatestate_depend_eliminate]: 9.454e-05 [updatestate_assign_eliminate]: 3.916e-05 [updatestate_loads_eliminate]: 0.00012291 [parameter_eliminate]: 4.03999e-06 [specialize_transform]: 6.619e-05 [updatestate_useless_node_eliminater]: 8.565e-05 [accelerated_algorithm]: 6.15e-05 [meta_shard_fg_expand]: 3.297e-05 [get_grad_eliminate_]: 5.266e-05 [merge_forward]: 3.246e-05 [cell_reuse_recompute_pass]: 3.36001e-06 [cell_reuse_handle_not_recompute_node_pass]: 9.64e-05 [j_node_and_user_rematch]: 8.732e-05 [meta_fg_expand]: 0.0010394 [replace_old_param]: 0.00011394 [inline_without_move]: 5.368e-05 [renormalize]: 0.0235009 [add_forward_monad_depend]: 1.076e-05 [auto_monad_grad]: 3.33998e-06 [auto_monad_eliminator]: 0.00019323 [cse]: 0.00021432 [replace_applicator]: 7.417e-05 [Cycle 3]: 0.00705641, [27] [switch_simplify]: 4.79e-05 [loop_unroll]: 4.751e-05 [a_1]: 0.00179794 [with_stream_mark]: 6.675e-05 [recompute_prepare]: 5.773e-05 [updatestate_depend_eliminate]: 3.606e-05 [updatestate_assign_eliminate]: 3.43e-05 [updatestate_loads_eliminate]: 3.591e-05 [parameter_eliminate]: 3.36001e-06 [specialize_transform]: 4.904e-05 [updatestate_useless_node_eliminater]: 7.547e-05 [accelerated_algorithm]: 5.782e-05 [meta_shard_fg_expand]: 2.207e-05 [get_grad_eliminate_]: 4.604e-05 [merge_forward]: 3.061e-05 [cell_reuse_recompute_pass]: 5.06002e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.782e-05 [j_node_and_user_rematch]: 7.85e-05 [meta_fg_expand]: 1.887e-05 [replace_old_param]: 6.227e-05 [inline_without_move]: 8.355e-05 [renormalize]: 0.00352538 [add_forward_monad_depend]: 1.469e-05 [auto_monad_grad]: 3.45e-06 [auto_monad_eliminator]: 0.00014903 [cse]: 0.00021586 [replace_applicator]: 7.498e-05 [Cycle 4]: 0.00295142, [27] [switch_simplify]: 4.745e-05 [loop_unroll]: 4.684e-05 [a_1]: 0.00141723 [with_stream_mark]: 6.03e-05 [recompute_prepare]: 5.505e-05 [updatestate_depend_eliminate]: 3.785e-05 [updatestate_assign_eliminate]: 3.271e-05 [updatestate_loads_eliminate]: 3.443e-05 [parameter_eliminate]: 3.16999e-06 [specialize_transform]: 5.041e-05 [updatestate_useless_node_eliminater]: 7.254e-05 [accelerated_algorithm]: 5.734e-05 [meta_shard_fg_expand]: 1.736e-05 [get_grad_eliminate_]: 4.522e-05 [merge_forward]: 2.866e-05 [cell_reuse_recompute_pass]: 6.11e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.794e-05 [j_node_and_user_rematch]: 7.91e-05 [meta_fg_expand]: 1.933e-05 [replace_old_param]: 0.00010372 [inline_without_move]: 4.968e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 5.51e-06 [auto_monad_grad]: 3.90998e-06 [auto_monad_eliminator]: 0.00011898 [cse]: 0.00016748 [replace_applicator]: 5.326e-05 [py_interpret_to_execute_after_opt_a]: 6.363e-05 [rewriter_after_opt_a]: 0.0004418 [convert_after_rewriter]: 5.01e-05 [order_py_execute_after_rewriter]: 2.567e-05 [mutable_eliminate]: 0.00089939 [jit_opt_b]: 0.00029527, [1] [Cycle 1]: 0.00028416, [2] [frontend_op_eliminate]: 0.00014471 [inline_after_opt_a]: 0.00012547 [cconv]: 5.563e-05 [loop_unroll]: 0.00064174 [jit_opt_after_cconv]: 0.00089468, [1] [Cycle 1]: 0.00088471, [11] [c_1]: 0.00030142 [parameter_eliminate]: 6.87002e-06 [updatestate_depend_eliminate]: 4.936e-05 [updatestate_assign_eliminate]: 3.513e-05 [updatestate_loads_eliminate]: 3.409e-05 [cse]: 0.00017972 [call_graph_tuple_transform]: 0.00011826 [tuple_list_get_item_eliminator]: 4.558e-05 [none_parameter_eliminate]: 2.14e-06 [renormalize]: 8.50006e-07 [switch_simplify]: 4.45e-05 [remove_dup_value]: 0.0442902 [partial_unused_args_eliminate]: 9.62001e-06 [environ_conv]: 6.425e-05 [add_recomputation]: 0.00039724 [cse_after_recomputation]: 0.00020221, [1] [Cycle 1]: 0.00018514, [1] [cse]: 0.00015905 [auto_monad_reorder]: 0.00016722 [get_jit_bprop_graph]: 2.66e-06 [rewriter_after_jit_bprop_graph]: 7.9e-06 [opt_after_jit_grad]: 0.0009872 [symbol_engine_optimizer]: 0.00033614, [1] [Cycle 1]: 0.00032679, [6] [build]: 3.393e-05 [elim_shapecalc]: 5.102e-05 [elim_not_effective]: 8.812e-05 [opt_reshape]: 4.596e-05 [fold_const_symbol]: 7.38e-05 [renormalize]: 6.30011e-07 [validate]: 0.00025105 Sums bootstrap : 0.001509s : 0.04% type_inference : 2.610862s : 76.72% event_method : 0.000336s : 0.01% auto_monad : 0.002546s : 0.07% graph_reusing : 0.000131s : 0.00% pre_auto_parallel : 0.000034s : 0.00% py_interpret_to_execute : 0.000575s : 0.02% rewriter_before_opt_a : 0.073232s : 2.15% expand_dump_flag : 0.000054s : 0.00% jit_opt_a.switch_simplify : 0.001879s : 0.06% jit_opt_a.loop_unroll : 0.001004s : 0.03% jit_opt_a.a_1 : 0.152583s : 4.48% jit_opt_a.with_stream_mark : 0.000663s : 0.02% jit_opt_a.recompute_prepare : 0.000330s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000916s : 0.03% jit_opt_a.updatestate_assign_eliminate : 0.000173s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000323s : 0.01% jit_opt_a.parameter_eliminate : 0.000016s : 0.00% jit_opt_a.specialize_transform : 0.000253s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000335s : 0.01% jit_opt_a.accelerated_algorithm : 0.000319s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000109s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000210s : 0.01% jit_opt_a.merge_forward : 0.000131s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000018s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000399s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000360s : 0.01% jit_opt_a.meta_fg_expand : 0.207258s : 6.09% jit_opt_a.replace_old_param : 0.000679s : 0.02% jit_opt_a.inline_without_move : 0.000566s : 0.02% jit_opt_a.renormalize : 0.291123s : 8.55% jit_opt_a.add_forward_monad_depend : 0.000175s : 0.01% jit_opt_a.auto_monad_grad : 0.000056s : 0.00% jit_opt_a.auto_monad_eliminator : 0.001163s : 0.03% jit_opt_a.cse : 0.001834s : 0.05% jit_opt_a.replace_applicator : 0.001017s : 0.03% py_interpret_to_execute_after_opt_a : 0.000064s : 0.00% rewriter_after_opt_a : 0.000442s : 0.01% convert_after_rewriter : 0.000050s : 0.00% order_py_execute_after_rewriter : 0.000026s : 0.00% mutable_eliminate : 0.000899s : 0.03% jit_opt_b.frontend_op_eliminate : 0.000145s : 0.00% jit_opt_b.inline_after_opt_a : 0.000125s : 0.00% cconv : 0.000056s : 0.00% loop_unroll : 0.000642s : 0.02% jit_opt_after_cconv.c_1 : 0.000301s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000049s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000035s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000034s : 0.00% jit_opt_after_cconv.cse : 0.000180s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000118s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000046s : 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 : 0.000044s : 0.00% remove_dup_value : 0.044290s : 1.30% partial_unused_args_eliminate : 0.000010s : 0.00% environ_conv : 0.000064s : 0.00% add_recomputation : 0.000397s : 0.01% cse_after_recomputation.cse : 0.000159s : 0.00% auto_monad_reorder : 0.000167s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000987s : 0.03% symbol_engine_optimizer.build : 0.000034s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000051s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000088s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000046s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000074s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000251s : 0.01% Time group info: ------[substitution.] 0.128806 1710 0.07% : 0.000096s : 5: substitution.arithmetic_simplify 0.03% : 0.000037s : 4: substitution.cast_eliminate 0.13% : 0.000173s : 62: substitution.depend_value_elim 0.01% : 0.000011s : 32: substitution.elim_not_effective 0.01% : 0.000018s : 6: substitution.environ_get_add_eliminate 0.01% : 0.000012s : 4: substitution.environ_get_depend_swap 0.01% : 0.000015s : 6: substitution.environ_get_eliminate 0.03% : 0.000032s : 6: substitution.environ_get_set_eliminate 0.01% : 0.000011s : 32: substitution.fold_const_symbol 1.55% : 0.001994s : 8: substitution.getattr_setattr_resolve 0.02% : 0.000029s : 45: substitution.graph_param_transform 95.94% : 0.123572s : 153: substitution.inline 0.07% : 0.000092s : 12: substitution.inline_without_move 0.05% : 0.000059s : 147: substitution.j_node_and_user_rematch 0.05% : 0.000067s : 15: substitution.less_batch_normalization 0.03% : 0.000044s : 44: substitution.load_eliminater 0.11% : 0.000142s : 92: substitution.minmaximum_grad 0.03% : 0.000044s : 12: substitution.partial_eliminate 0.02% : 0.000030s : 6: substitution.reduce_eliminate 0.01% : 0.000009s : 4: substitution.redundant_stop_gradient_eliminater 0.06% : 0.000081s : 147: substitution.remove_not_recompute_node 0.21% : 0.000265s : 55: substitution.replace_applicator 0.08% : 0.000099s : 84: substitution.replace_old_param 0.01% : 0.000007s : 1: substitution.reshape_eliminate 0.00% : 0.000006s : 1: substitution.set_cell_output_no_recompute 0.01% : 0.000009s : 5: substitution.split_environ_get_set_with_tuple_value 0.06% : 0.000072s : 28: substitution.switch_simplify 0.01% : 0.000007s : 1: substitution.tile_eliminate 0.23% : 0.000291s : 100: substitution.tuple_list_convert_item_index_to_positive 0.26% : 0.000341s : 109: substitution.tuple_list_get_item_depend_reorder 0.44% : 0.000571s : 183: substitution.tuple_list_get_item_eliminator 0.15% : 0.000198s : 135: substitution.updatestate_pure_node_eliminater 0.29% : 0.000373s : 166: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.609871 2 95.52% : 2.492890s : 1: type_inference.infer 4.48% : 0.116981s : 1: type_inference.specialize ------[replace.] 0.004124 291 0.39% : 0.000016s : 1: replace.arithmetic_simplify 0.91% : 0.000038s : 4: replace.cast_eliminate 1.80% : 0.000074s : 8: replace.depend_value_elim 0.85% : 0.000035s : 2: replace.environ_get_set_eliminate 3.48% : 0.000143s : 6: replace.getattr_setattr_resolve 49.96% : 0.002060s : 153: replace.inline 1.14% : 0.000047s : 2: replace.partial_eliminate 2.76% : 0.000114s : 3: replace.replace_applicator 10.48% : 0.000432s : 28: replace.switch_simplify 3.66% : 0.000151s : 9: replace.tuple_list_get_item_depend_reorder 24.09% : 0.000993s : 74: replace.tuple_list_get_item_eliminator 0.49% : 0.000020s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.125995 291 0.04% : 0.000044s : 1: match.arithmetic_simplify 0.03% : 0.000033s : 4: match.cast_eliminate 0.01% : 0.000010s : 8: match.depend_value_elim 0.02% : 0.000022s : 2: match.environ_get_set_eliminate 1.50% : 0.001887s : 6: match.getattr_setattr_resolve 97.97% : 0.123443s : 153: match.inline 0.02% : 0.000023s : 2: match.partial_eliminate 0.06% : 0.000082s : 3: match.replace_applicator 0.05% : 0.000057s : 28: match.switch_simplify 0.11% : 0.000137s : 9: match.tuple_list_get_item_depend_reorder 0.19% : 0.000239s : 74: match.tuple_list_get_item_eliminator 0.01% : 0.000017s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.005764 36474 1.52% : 0.000087s : 643: predicate.accumulaten_eliminater 0.21% : 0.000012s : 45: predicate.ad_related_special_op_eliminate 1.46% : 0.000084s : 643: predicate.addn_check_dump 1.49% : 0.000086s : 643: predicate.addn_zero_filter 2.02% : 0.000117s : 644: predicate.arithmetic_simplify 1.53% : 0.000088s : 648: predicate.cast_eliminate 0.11% : 0.000006s : 45: predicate.check_bprop_eliminate 1.61% : 0.000093s : 643: predicate.compare_switch_simplify 1.58% : 0.000091s : 643: predicate.depend_value_elim 1.71% : 0.000099s : 650: predicate.dict_get_item_const_eliminator 1.54% : 0.000089s : 650: predicate.dict_get_item_eliminator 1.51% : 0.000087s : 650: predicate.dict_set_item_eliminator 0.13% : 0.000008s : 45: predicate.dumpgradient_eliminate 0.07% : 0.000004s : 45: predicate.elim_not_effective 0.12% : 0.000007s : 45: predicate.elim_shapecalc_of_broadcastargs 1.50% : 0.000087s : 648: predicate.environ_add_const_eliminate 1.50% : 0.000086s : 650: predicate.environ_get_add_eliminate 1.47% : 0.000085s : 648: predicate.environ_get_depend_swap 1.53% : 0.000088s : 650: predicate.environ_get_eliminate 1.49% : 0.000086s : 650: predicate.environ_get_set_eliminate 0.06% : 0.000003s : 45: predicate.fold_const_symbol 0.52% : 0.000030s : 206: predicate.get_grad_eliminate 0.24% : 0.000014s : 40: predicate.getattr_setattr_resolve 0.07% : 0.000004s : 45: predicate.graph_param_transform 4.46% : 0.000257s : 979: predicate.inline 1.22% : 0.000071s : 412: predicate.inline_without_move 0.27% : 0.000016s : 206: predicate.j_node_and_user_rematch 0.66% : 0.000038s : 222: predicate.less_batch_normalization 1.76% : 0.000101s : 733: predicate.list_to_tuple_eliminator_ 1.97% : 0.000113s : 780: predicate.load_eliminater 0.19% : 0.000011s : 45: predicate.loop_unroll_after_grad 3.07% : 0.000177s : 1086: predicate.loop_unroll_before_grad 1.68% : 0.000097s : 704: predicate.make_slice_get_slice_eliminator 1.45% : 0.000083s : 643: predicate.merge_addn 1.51% : 0.000087s : 644: predicate.minmaximum_grad 0.22% : 0.000013s : 45: predicate.mutable_eliminate 0.12% : 0.000007s : 45: predicate.opt_reshape 2.26% : 0.000130s : 780: predicate.partial_eliminate 1.45% : 0.000084s : 635: predicate.print_const_string_wrapper 1.95% : 0.000112s : 644: predicate.reduce_eliminate 1.77% : 0.000102s : 735: predicate.redundant_stop_gradient_eliminater 0.29% : 0.000017s : 206: predicate.remove_not_recompute_node 2.12% : 0.000122s : 1225: predicate.replace_applicator 0.58% : 0.000033s : 412: predicate.replace_old_param 0.07% : 0.000004s : 45: predicate.reset_defer_inline 1.56% : 0.000090s : 644: predicate.reshape_eliminate 1.48% : 0.000085s : 635: predicate.row_tensor_add_zeros_like 0.13% : 0.000007s : 45: predicate.row_tensor_eliminate 1.47% : 0.000085s : 635: predicate.same_eliminate 0.39% : 0.000023s : 256: predicate.set_cell_output_no_recompute 0.23% : 0.000013s : 90: predicate.special_op_eliminate 0.61% : 0.000035s : 206: predicate.specialize_transform 1.78% : 0.000103s : 635: predicate.split_environ_get_set_with_tuple_value 1.44% : 0.000083s : 635: predicate.stack_unstack_eliminate 0.12% : 0.000007s : 45: predicate.switch_call_monad_eliminater 3.75% : 0.000216s : 889: predicate.switch_defer_inline 2.33% : 0.000134s : 889: predicate.switch_layer_defer_inline 5.85% : 0.000337s : 2076: predicate.switch_simplify 1.64% : 0.000094s : 644: predicate.tile_eliminate 1.49% : 0.000086s : 644: predicate.transpose_eliminate 1.94% : 0.000112s : 650: predicate.tuple_list_convert_item_index_to_positive 1.84% : 0.000106s : 659: predicate.tuple_list_get_item_depend_reorder 7.66% : 0.000441s : 823: predicate.tuple_list_get_item_eliminator 1.91% : 0.000110s : 659: predicate.tuple_list_set_item_eliminator 1.71% : 0.000098s : 733: predicate.tuple_to_list_eliminator_ 1.93% : 0.000111s : 780: predicate.updatestate_pure_node_eliminater 2.62% : 0.000151s : 987: predicate.updatestate_useless_node_eliminater 1.81% : 0.000104s : 635: predicate.value_based_eliminate 0.11% : 0.000006s : 45: predicate.virtual_view_grad_eliminate 0.13% : 0.000008s : 45: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.278870 387 96.35% : 0.268684s : 200: func_graph_cloner_run.FuncGraphClonerGraph 0.07% : 0.000196s : 3: func_graph_cloner_run.FuncGraphClonerNode 3.58% : 0.009990s : 184: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.868464 106 0.01% : 0.000403s : 1: add_recomputation 0.07% : 0.002564s : 1: auto_monad 0.00% : 0.000173s : 1: auto_monad_reorder 0.04% : 0.001539s : 1: bootstrap 0.00% : 0.000059s : 1: cconv 0.00% : 0.000054s : 1: convert_after_rewriter 0.01% : 0.000205s : 1: cse_after_recomputation 0.00% : 0.000068s : 1: environ_conv 0.01% : 0.000345s : 1: event_method 0.00% : 0.000060s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000139s : 1: graph_reusing 17.44% : 0.674679s : 1: jit_opt_a 0.02% : 0.000898s : 1: jit_opt_after_cconv 0.01% : 0.000299s : 1: jit_opt_b 0.02% : 0.000652s : 1: loop_unroll 0.02% : 0.000913s : 1: mutable_eliminate 4.13% : 0.159733s : 52: opt.transform.jit_opt_a 0.01% : 0.000504s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000261s : 4: opt.transform.jit_opt_b 0.00% : 0.000067s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000078s : 1: opt.transform.mutable_eliminate 0.00% : 0.000171s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.002274s : 4: opt.transform.opt_resolve 0.01% : 0.000254s : 4: opt.transform.symbol_engine_opt 0.03% : 0.001000s : 1: opt_after_jit_grad 0.00% : 0.000028s : 1: order_py_execute_after_rewriter 0.00% : 0.000015s : 1: partial_unused_args_eliminate 0.00% : 0.000037s : 1: pre_auto_parallel 0.02% : 0.000589s : 1: py_interpret_to_execute 0.00% : 0.000069s : 1: py_interpret_to_execute_after_opt_a 1.15% : 0.044319s : 1: remove_dup_value 5.52% : 0.213482s : 3: renormalize.infer 2.01% : 0.077579s : 3: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000451s : 1: rewriter_after_opt_a 1.89% : 0.073259s : 1: rewriter_before_opt_a 0.01% : 0.000340s : 1: symbol_engine_optimizer 67.49% : 2.610890s : 1: type_inference . TotalTime = 0.118856, [21] [bootstrap]: 0.00096973 [type_inference]: 0.0723421 [event_method]: 0.00020399 [auto_monad]: 0.0003623 [graph_reusing]: 9.84999e-06 [inline]: 3.34001e-06 [add_attr]: 0.00458515, [1] [add_attr_with_inline]: 0.00454118, [1] [Cycle 1]: 0.00010364, [2] [tag_attr]: 4.9e-05 [meta_addattr_fg_expand]: 1.017e-05 [parallel-infer-symbol]: 4.07e-06 [pre_auto_parallel]: 8.551e-05 [insert-virtual-dataset]: 2.76e-06 [parallel-infer-symbol-second]: 8.79983e-07 [dataset_repeat_opt]: 2.35002e-06 [pipeline_split]: 1.91e-06 [optimize]: 0.0392675, [53] [py_interpret_to_execute]: 5.547e-05 [rewriter_before_opt_a]: 0.00017072 [opt_a]: 0.0348923, [2] [Cycle 1]: 0.0333195, [45] [expand_dump_flag]: 4.75999e-06 [switch_simplify]: 0.00017391 [loop_unroll]: 5.628e-05 [a_1]: 0.028708 [with_stream_mark]: 4.058e-05 [recompute_prepare]: 3.055e-05 [updatestate_depend_eliminate]: 8.366e-05 [updatestate_assign_eliminate]: 9.44998e-06 [updatestate_loads_eliminate]: 6.452e-05 [parameter_eliminate]: 3.14001e-06 [a_2]: 0.00023332 [accelerated_algorithm]: 4.27e-05 [shard]: 2.34999e-06 [meta_shard_fg_expand]: 6.39001e-06 [shard_inline]: 1.572e-05 [merge_send_recv]: 1.47e-05 [auto_parallel]: 1.548e-05 [parallel]: 9.688e-05 [flash_sp]: 2.721e-05 [merge_comm]: 1.11e-05 [allreduce_fusion]: 8.52e-06 [matmul_add_comm_reduction]: 1.773e-05 [allreduce_slice_to_reducescatter]: 8.90024e-07 [virtual_shard_identity]: 2.172e-05 [virtual_dataset]: 1.49e-05 [get_grad_eliminate_]: 1.478e-05 [virtual_output]: 1.604e-05 [merge_forward]: 9.91e-06 [cell_reuse_recompute_pass]: 2.27999e-06 [offload_activation]: 2.063e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.113e-05 [merge_recompute_call_nodes]: 1.54e-06 [before_grad]: 3.549e-05 [set_forward_comm_id_for_comm_node_pass]: 9.64999e-06 [meta_fg_expand]: 7.55e-06 [flash_sp_send_recv_attached]: 4.95001e-06 [receive_attached]: 1.376e-05 [after_resolve]: 2.537e-05 [a_after_grad]: 2.686e-05 [renormalize]: 0.00251925 [add_forward_monad_depend]: 1.067e-05 [auto_monad_grad]: 3.04001e-06 [auto_monad_eliminator]: 5.802e-05 [cse]: 0.00024962 [a_3]: 0.00012617 [Cycle 2]: 0.00155571, [45] [expand_dump_flag]: 2.96001e-06 [switch_simplify]: 1.81e-05 [loop_unroll]: 1.536e-05 [a_1]: 0.00044477 [with_stream_mark]: 2.083e-05 [recompute_prepare]: 1.549e-05 [updatestate_depend_eliminate]: 9.46003e-06 [updatestate_assign_eliminate]: 1.047e-05 [updatestate_loads_eliminate]: 1.369e-05 [parameter_eliminate]: 1.98997e-06 [a_2]: 0.00022674 [accelerated_algorithm]: 2.242e-05 [shard]: 2.61999e-06 [meta_shard_fg_expand]: 4.65001e-06 [shard_inline]: 1.519e-05 [merge_send_recv]: 1.503e-05 [auto_parallel]: 1.475e-05 [parallel]: 9.96e-06 [flash_sp]: 4.43999e-06 [merge_comm]: 8.80999e-06 [allreduce_fusion]: 8.34002e-06 [matmul_add_comm_reduction]: 1.63e-05 [allreduce_slice_to_reducescatter]: 6.09987e-07 [virtual_shard_identity]: 1.705e-05 [virtual_dataset]: 1.477e-05 [get_grad_eliminate_]: 1.513e-05 [virtual_output]: 1.446e-05 [merge_forward]: 9.02e-06 [cell_reuse_recompute_pass]: 3.78999e-06 [offload_activation]: 1.787e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.988e-05 [merge_recompute_call_nodes]: 2.11e-06 [before_grad]: 2.495e-05 [set_forward_comm_id_for_comm_node_pass]: 9.22001e-06 [meta_fg_expand]: 6.21e-06 [flash_sp_send_recv_attached]: 1.53002e-06 [receive_attached]: 2.24001e-06 [after_resolve]: 2.28e-05 [a_after_grad]: 2.531e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.49001e-06 [auto_monad_grad]: 2.74999e-06 [auto_monad_eliminator]: 3.967e-05 [cse]: 5.23e-05 [a_3]: 0.00010361 [py_interpret_to_execute_after_opt_a]: 2.535e-05 [slice_cell_reuse_recomputed_activation]: 2.27999e-06 [rewriter_after_opt_a]: 0.00021184 [convert_after_rewriter]: 1.794e-05 [order_py_execute_after_rewriter]: 1.162e-05 [mutable_eliminate]: 0.00080131 [opt_b]: 0.00053093, [1] [Cycle 1]: 0.00051933, [7] [b_1]: 0.0003445 [b_2]: 1.74e-05 [updatestate_depend_eliminate]: 1.571e-05 [updatestate_assign_eliminate]: 8.67e-06 [updatestate_loads_eliminate]: 1.396e-05 [renormalize]: 1.01002e-06 [cse]: 7.265e-05 [optimize_parallel_all_gather_comm]: 3.467e-05 [overlap_param_gather]: 6.06e-06 [cconv]: 4.018e-05 [loop_unroll]: 0.00062205 [opt_after_cconv]: 0.00067278, [1] [Cycle 1]: 0.00066288, [7] [c_1]: 0.00010494 [parameter_eliminate]: 5.98002e-06 [updatestate_depend_eliminate]: 0.00040812 [updatestate_assign_eliminate]: 1.24e-05 [updatestate_loads_eliminate]: 1.299e-05 [cse]: 6.068e-05 [renormalize]: 2.3999e-07 [remove_dup_value]: 6.283e-05 [tuple_transform]: 0.00016476, [1] [Cycle 1]: 0.0001567, [4] [d_1]: 0.00011532 [none_parameter_eliminate]: 3.24001e-06 [renormalize]: 1.8999e-07 [switch_simplify]: 1.635e-05 [partial_unused_args_eliminate]: 2.14e-06 [add_recomputation]: 0.00013018 [cse_after_recomputation]: 4.802e-05, [1] [Cycle 1]: 4.21e-05, [1] [cse]: 3.593e-05 [environ_conv]: 1.475e-05 [swap_dp_allreduce_reducescatter]: 1.111e-05 [bias_add_comm_swap]: 2.63e-06 [label_micro_interleaved_index]: 6.79001e-06 [label_fine_grained_interleaved_index]: 3.12002e-06 [merge_cast_opt]: 1.62001e-06 [slice_recompute_activation]: 2.22001e-06 [micro_interleaved_order_control]: 2.66e-06 [assign_add_opt]: 1.64e-06 [ForceFp32Comm]: 1.35001e-06 [remove_cast_before_assign_add]: 1.19e-06 [full_micro_interleaved_order_control]: 2.27001e-06 [reorder_send_recv_between_fp_bp]: 2.95002e-06 [comm_op_add_attrs]: 1.49e-06 [add_comm_op_reuse_tag]: 1.05999e-06 [interleave_split_concat_branches]: 1.35999e-06 [interleave_parallel_branches]: 1.09e-06 [overlap_opt_shard_in_pipeline]: 4.209e-05 [overlap_opt_shard_grad_in_pipeline]: 2.32999e-06 [control_data_broadcast_order]: 3.153e-05 [grouped_pairwise_exchange_alltoall]: 1.78997e-06 [offloading_packed_experts]: 8.35999e-06 [overlap_recompute_and_grad_model_parallel]: 8.87e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.62001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.42999e-06 [overlap_recompute_comm]: 2.35002e-06 [overlap_grad_ring_attention]: 7.9e-06 [overlap_grad_flash_sp]: 9.669e-05 [begin_end_overlap_inline]: 5.3001e-07 [split_matmul_comm_elemetwise]: 2.63998e-06 [split_layernorm_comm]: 1.82001e-06 [handle_group_info]: 1.10001e-06 [symbol_engine_optimizer]: 0.00014074, [1] [Cycle 1]: 0.00013409, [6] [build]: 1.516e-05 [elim_shapecalc]: 2.224e-05 [elim_not_effective]: 2.726e-05 [opt_reshape]: 1.466e-05 [fold_const_symbol]: 2.27e-05 [renormalize]: 2.19996e-07 [detach_backward]: 2.41998e-06 [pipeline_parallel_scheduler]: 1.67999e-06 [auto_monad_reorder]: 5.793e-05 [get_jit_bprop_graph]: 2.22999e-06 [rewriter_after_jit_bprop_graph]: 7.3e-06 [opt_after_jit_grad]: 0.00065558 [validate]: 7.536e-05 Sums bootstrap : 0.000970s : 0.86% type_inference : 0.072342s : 64.09% event_method : 0.000204s : 0.18% auto_monad : 0.000362s : 0.32% graph_reusing : 0.000010s : 0.01% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000049s : 0.04% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000010s : 0.01% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000086s : 0.08% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000055s : 0.05% optimize.rewriter_before_opt_a : 0.000171s : 0.15% optimize.opt_a.expand_dump_flag : 0.000008s : 0.01% optimize.opt_a.switch_simplify : 0.000192s : 0.17% optimize.opt_a.loop_unroll : 0.000072s : 0.06% optimize.opt_a.a_1 : 0.029153s : 25.83% optimize.opt_a.with_stream_mark : 0.000061s : 0.05% optimize.opt_a.recompute_prepare : 0.000046s : 0.04% optimize.opt_a.updatestate_depend_eliminate : 0.000093s : 0.08% optimize.opt_a.updatestate_assign_eliminate : 0.000020s : 0.02% optimize.opt_a.updatestate_loads_eliminate : 0.000078s : 0.07% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000460s : 0.41% optimize.opt_a.accelerated_algorithm : 0.000065s : 0.06% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000011s : 0.01% optimize.opt_a.shard_inline : 0.000031s : 0.03% optimize.opt_a.merge_send_recv : 0.000030s : 0.03% optimize.opt_a.auto_parallel : 0.000030s : 0.03% optimize.opt_a.parallel : 0.000107s : 0.09% optimize.opt_a.flash_sp : 0.000032s : 0.03% optimize.opt_a.merge_comm : 0.000020s : 0.02% optimize.opt_a.allreduce_fusion : 0.000017s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000034s : 0.03% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000039s : 0.03% optimize.opt_a.virtual_dataset : 0.000030s : 0.03% optimize.opt_a.get_grad_eliminate_ : 0.000030s : 0.03% optimize.opt_a.virtual_output : 0.000030s : 0.03% optimize.opt_a.merge_forward : 0.000019s : 0.02% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.01% optimize.opt_a.offload_activation : 0.000039s : 0.03% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000061s : 0.05% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000060s : 0.05% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000019s : 0.02% optimize.opt_a.meta_fg_expand : 0.000014s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000006s : 0.01% optimize.opt_a.receive_attached : 0.000016s : 0.01% optimize.opt_a.after_resolve : 0.000048s : 0.04% optimize.opt_a.a_after_grad : 0.000052s : 0.05% optimize.opt_a.renormalize : 0.002519s : 2.23% optimize.opt_a.add_forward_monad_depend : 0.000013s : 0.01% optimize.opt_a.auto_monad_grad : 0.000006s : 0.01% optimize.opt_a.auto_monad_eliminator : 0.000098s : 0.09% optimize.opt_a.cse : 0.000302s : 0.27% optimize.opt_a.a_3 : 0.000230s : 0.20% optimize.py_interpret_to_execute_after_opt_a : 0.000025s : 0.02% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000212s : 0.19% optimize.convert_after_rewriter : 0.000018s : 0.02% optimize.order_py_execute_after_rewriter : 0.000012s : 0.01% optimize.mutable_eliminate : 0.000801s : 0.71% optimize.opt_b.b_1 : 0.000345s : 0.31% optimize.opt_b.b_2 : 0.000017s : 0.02% optimize.opt_b.updatestate_depend_eliminate : 0.000016s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000009s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000014s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000073s : 0.06% optimize.optimize_parallel_all_gather_comm : 0.000035s : 0.03% optimize.overlap_param_gather : 0.000006s : 0.01% optimize.cconv : 0.000040s : 0.04% optimize.loop_unroll : 0.000622s : 0.55% optimize.opt_after_cconv.c_1 : 0.000105s : 0.09% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.01% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000408s : 0.36% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000012s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000013s : 0.01% optimize.opt_after_cconv.cse : 0.000061s : 0.05% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000063s : 0.06% optimize.tuple_transform.d_1 : 0.000115s : 0.10% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000016s : 0.01% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000130s : 0.12% optimize.cse_after_recomputation.cse : 0.000036s : 0.03% optimize.environ_conv : 0.000015s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000011s : 0.01% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000007s : 0.01% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000042s : 0.04% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000032s : 0.03% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000008s : 0.01% optimize.overlap_recompute_and_grad_model_parallel : 0.000009s : 0.01% 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 : 0.000008s : 0.01% optimize.overlap_grad_flash_sp : 0.000097s : 0.09% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000015s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000022s : 0.02% optimize.symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.02% optimize.symbol_engine_optimizer.opt_reshape : 0.000015s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000023s : 0.02% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000058s : 0.05% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.01% opt_after_jit_grad : 0.000656s : 0.58% validate : 0.000075s : 0.07% Time group info: ------[substitution.] 0.027390 165 0.04% : 0.000012s : 2: substitution.depend_value_elim 0.01% : 0.000004s : 9: substitution.elim_not_effective 0.01% : 0.000003s : 9: substitution.fold_const_symbol 0.04% : 0.000012s : 12: substitution.graph_param_transform 1.73% : 0.000475s : 11: substitution.inline 0.03% : 0.000009s : 18: substitution.j_node_and_user_rematch 0.09% : 0.000024s : 4: substitution.less_batch_normalization 0.03% : 0.000009s : 12: substitution.load_eliminater 0.05% : 0.000013s : 18: substitution.remove_not_recompute_node 0.03% : 0.000009s : 6: substitution.replace_old_param 0.04% : 0.000011s : 2: substitution.switch_simplify 97.51% : 0.026707s : 30: substitution.updatestate_pure_node_eliminater 0.37% : 0.000101s : 32: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.072251 2 96.84% : 0.069964s : 1: type_inference.infer 3.16% : 0.002286s : 1: type_inference.specialize ------[replace.] 0.000166 13 61.55% : 0.000102s : 11: replace.inline 38.45% : 0.000064s : 2: replace.switch_simplify ------[match.] 0.000477 13 97.92% : 0.000467s : 11: match.inline 2.08% : 0.000010s : 2: match.switch_simplify ------[predicate.] 0.000636 4059 1.21% : 0.000008s : 49: predicate.accumulaten_eliminater 0.56% : 0.000004s : 12: predicate.ad_related_special_op_eliminate 0.56% : 0.000004s : 24: predicate.addn_check_dump 1.10% : 0.000007s : 49: predicate.addn_zero_filter 1.03% : 0.000007s : 49: predicate.adjust_all_reduce_mul_add 2.28% : 0.000015s : 73: predicate.arithmetic_simplify 1.15% : 0.000007s : 49: predicate.cast_eliminate 0.63% : 0.000004s : 24: predicate.check_bprop_eliminate 0.54% : 0.000003s : 24: predicate.compare_switch_simplify 0.15% : 0.000001s : 12: predicate.const_output_eliminate 0.55% : 0.000003s : 24: predicate.depend_value_elim 1.18% : 0.000008s : 49: predicate.dict_get_item_const_eliminator 1.18% : 0.000007s : 49: predicate.dict_get_item_eliminator 1.27% : 0.000008s : 49: predicate.dict_set_item_eliminator 0.70% : 0.000004s : 24: predicate.dumpgradient_eliminate 0.16% : 0.000001s : 12: predicate.elim_not_effective 0.39% : 0.000002s : 12: predicate.elim_shapecalc_of_broadcastargs 1.46% : 0.000009s : 61: predicate.environ_add_const_eliminate 1.30% : 0.000008s : 61: predicate.environ_get_add_eliminate 1.31% : 0.000008s : 61: predicate.environ_get_depend_swap 1.97% : 0.000013s : 85: predicate.environ_get_eliminate 1.29% : 0.000008s : 61: predicate.environ_get_set_eliminate 1.36% : 0.000009s : 60: predicate.exchange_switch_depend_value 1.93% : 0.000012s : 60: predicate.float_depend_g_call 0.54% : 0.000003s : 24: predicate.float_environ_get_switch 0.75% : 0.000005s : 36: predicate.float_tuple_getitem_switch 0.14% : 0.000001s : 12: predicate.fold_const_symbol 0.63% : 0.000004s : 24: predicate.get_grad_eliminate 0.19% : 0.000001s : 12: predicate.graph_param_transform 0.55% : 0.000003s : 24: predicate.incorporate_call 0.49% : 0.000003s : 24: predicate.incorporate_call_switch 5.54% : 0.000035s : 181: predicate.inline 0.82% : 0.000005s : 24: predicate.inline_without_move 0.28% : 0.000002s : 24: predicate.j_node_and_user_rematch 0.90% : 0.000006s : 24: predicate.less_batch_normalization 1.71% : 0.000011s : 73: predicate.list_to_tuple_eliminator_ 3.11% : 0.000020s : 122: predicate.load_eliminater 0.66% : 0.000004s : 12: predicate.loop_unroll_after_grad 1.72% : 0.000011s : 78: predicate.loop_unroll_before_grad 1.76% : 0.000011s : 73: predicate.make_slice_get_slice_eliminator 0.55% : 0.000004s : 24: predicate.merge_addn 0.56% : 0.000004s : 24: predicate.micro_step_allgather_replace 0.55% : 0.000004s : 24: predicate.mini_step_allgather_replace 1.03% : 0.000007s : 49: predicate.minmaximum_grad 0.67% : 0.000004s : 12: predicate.mutable_eliminate 0.30% : 0.000002s : 12: predicate.opt_reshape 0.34% : 0.000002s : 12: predicate.parallel_virtual_node 1.99% : 0.000013s : 60: predicate.partial_defer_inline 1.71% : 0.000011s : 61: predicate.partial_eliminate 1.10% : 0.000007s : 49: predicate.print_const_string_wrapper 0.54% : 0.000003s : 24: predicate.reduce_all_const_elim 1.31% : 0.000008s : 49: predicate.reduce_eliminate 2.90% : 0.000018s : 122: predicate.redundant_stop_gradient_eliminater 0.35% : 0.000002s : 24: predicate.remove_not_recompute_node 1.24% : 0.000008s : 73: predicate.replace_applicator 0.40% : 0.000003s : 24: predicate.replace_old_param 0.17% : 0.000001s : 12: predicate.reset_defer_inline 1.23% : 0.000008s : 49: predicate.reshape_eliminate 0.58% : 0.000004s : 24: predicate.row_tensor_add_zeros_like 0.31% : 0.000002s : 12: predicate.row_tensor_eliminate 0.72% : 0.000005s : 24: predicate.same_eliminate 0.43% : 0.000003s : 32: predicate.set_cell_output_no_recompute 0.64% : 0.000004s : 24: predicate.shard_identity_eliminate 0.56% : 0.000004s : 24: predicate.special_op_eliminate 0.73% : 0.000005s : 24: predicate.specialize_transform 0.76% : 0.000005s : 24: predicate.split_environ_get_set_with_tuple_value 0.73% : 0.000005s : 24: predicate.stack_unstack_eliminate 0.30% : 0.000002s : 12: predicate.switch_call_monad_eliminater 1.55% : 0.000010s : 60: predicate.switch_defer_inline 2.01% : 0.000013s : 84: predicate.switch_layer_defer_inline 4.33% : 0.000028s : 178: predicate.switch_simplify 1.21% : 0.000008s : 49: predicate.tile_eliminate 1.10% : 0.000007s : 49: predicate.transpose_eliminate 1.88% : 0.000012s : 73: predicate.tuple_list_convert_item_index_to_positive 1.72% : 0.000011s : 73: predicate.tuple_list_get_item_const_eliminator 1.63% : 0.000010s : 73: predicate.tuple_list_get_item_depend_reorder 2.73% : 0.000017s : 97: predicate.tuple_list_get_item_eliminator 1.63% : 0.000010s : 73: predicate.tuple_list_get_set_item_eliminator 2.32% : 0.000015s : 97: predicate.tuple_list_set_item_eliminator 1.75% : 0.000011s : 73: predicate.tuple_to_list_eliminator_ 2.76% : 0.000018s : 122: predicate.updatestate_pure_node_eliminater 3.48% : 0.000022s : 146: predicate.updatestate_useless_node_eliminater 0.31% : 0.000002s : 12: predicate.value_based_eliminate 0.62% : 0.000004s : 24: predicate.virtual_dataset_eliminate 0.59% : 0.000004s : 24: predicate.virtual_output_eliminate 0.26% : 0.000002s : 12: predicate.virtual_view_grad_eliminate 0.35% : 0.000002s : 12: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001225 18 40.97% : 0.000502s : 5: func_graph_cloner_run.FuncGraphClonerGraph 59.03% : 0.000723s : 13: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.196172 192 0.00% : 0.000004s : 1: ForceFp32Comm 2.34% : 0.004592s : 1: add_attr 2.32% : 0.004546s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.07% : 0.000136s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.19% : 0.000375s : 1: auto_monad 0.03% : 0.000063s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.52% : 0.001014s : 1: bootstrap 0.02% : 0.000045s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.02% : 0.000035s : 1: control_data_broadcast_order 0.01% : 0.000023s : 1: convert_after_rewriter 0.03% : 0.000051s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.01% : 0.000019s : 1: environ_conv 0.11% : 0.000218s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.01% : 0.000015s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 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 0.01% : 0.000010s : 1: label_micro_interleaved_index 0.33% : 0.000638s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.42% : 0.000817s : 1: mutable_eliminate 0.01% : 0.000012s : 1: offloading_packed_experts 0.02% : 0.000030s : 1: opt.transform.loop_unroll_optimizer 0.02% : 0.000032s : 1: opt.transform.mutable_eliminate 15.54% : 0.030481s : 78: opt.transform.opt_a 0.05% : 0.000103s : 1: opt.transform.opt_after_cconv 0.03% : 0.000054s : 1: opt.transform.opt_after_jit_grad 0.17% : 0.000330s : 28: opt.transform.opt_b 0.07% : 0.000128s : 2: opt.transform.opt_trans_graph 0.04% : 0.000083s : 4: opt.transform.symbol_engine_opt 17.79% : 0.034896s : 1: opt_a 0.35% : 0.000677s : 1: opt_after_cconv 0.34% : 0.000669s : 1: opt_after_jit_grad 0.27% : 0.000535s : 1: opt_b 20.02% : 0.039274s : 1: optimize 0.02% : 0.000039s : 1: optimize_parallel_all_gather_comm 0.01% : 0.000016s : 1: order_py_execute_after_rewriter 0.05% : 0.000104s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000011s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.02% : 0.000047s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000010s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000012s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.05% : 0.000091s : 1: pre_auto_parallel 0.03% : 0.000062s : 1: py_interpret_to_execute 0.02% : 0.000029s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.03% : 0.000068s : 1: remove_dup_value 0.70% : 0.001370s : 1: renormalize.infer 0.58% : 0.001135s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.01% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.11% : 0.000223s : 1: rewriter_after_opt_a 0.09% : 0.000176s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.01% : 0.000014s : 1: swap_dp_allreduce_reducescatter 0.07% : 0.000144s : 1: symbol_engine_optimizer 0.09% : 0.000168s : 1: tuple_transform 36.89% : 0.072367s : 1: type_inference . [hook] pytest_runtest_teardown:test_mint_optim_fused_adamw_group_lr_dynamic[0] tests/st/mint/optim/test_fused_adamw.py::test_mint_optim_fused_adamw_group_lr_dynamic[0],max_mem:20.0M [WARNING] ME(163162:281473224970032,MainProcess):2026-01-29-17:44:37.263.308 [mindspore/graph/api.py:128] The function "train_step" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/mint/optim/test_fused_adamw.py", line 217 has been compiled again. Try to reuse the function object decorated by @jit to reduce the compile time. For more details, get instructions about `jit` at https://www.mindspore.cn/search?inputValue=jit. [WARNING] ANALYZER(163162,ffff97968f30,python3.9):2026-01-29-17:44:40.413.596 [mindspore/ccsrc/frontend/jit/ps/static_analysis/auto_monad.cc:1601] ClearIsolatedNodes] Some side effect nodes were eliminated by mistake. The node is:@199_train_step_63:_{[0]: ValueNode 333__tuple_getitem_by_number_64, [1]: CNode_65, [2]: ValueNode 1} TotalTime = 3.75541, [30] [bootstrap]: 0.00049582 [type_inference]: 3.14717 [event_method]: 0.00040064 [auto_monad]: 0.00278954 [graph_reusing]: 0.0001594 [pre_auto_parallel]: 2.611e-05 [py_interpret_to_execute]: 0.00076081 [rewriter_before_opt_a]: 0.0171657 [expand_dump_flag]: 7.001e-05 [jit_opt_a]: 0.579523, [4] [Cycle 1]: 0.38508, [27] [switch_simplify]: 0.00142778 [loop_unroll]: 0.00059768 [a_1]: 0.0805595 [with_stream_mark]: 0.00028851 [recompute_prepare]: 0.00015542 [updatestate_depend_eliminate]: 0.00074984 [updatestate_assign_eliminate]: 6.046e-05 [updatestate_loads_eliminate]: 0.00014626 [parameter_eliminate]: 6.17999e-06 [specialize_transform]: 8.771e-05 [updatestate_useless_node_eliminater]: 0.00010763 [accelerated_algorithm]: 0.00014379 [meta_shard_fg_expand]: 4.652e-05 [get_grad_eliminate_]: 6.56e-05 [merge_forward]: 4.103e-05 [cell_reuse_recompute_pass]: 3.05002e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00012067 [j_node_and_user_rematch]: 0.00011345 [meta_fg_expand]: 0.0406884 [replace_old_param]: 0.00040077 [inline_without_move]: 0.00038017 [renormalize]: 0.256043 [add_forward_monad_depend]: 0.00010896 [auto_monad_grad]: 3.612e-05 [auto_monad_eliminator]: 0.00051201 [cse]: 0.00101138 [replace_applicator]: 0.00063748 [Cycle 2]: 0.0976868, [27] [switch_simplify]: 0.00039 [loop_unroll]: 0.00031537 [a_1]: 0.0705204 [with_stream_mark]: 0.00030645 [recompute_prepare]: 9.012e-05 [updatestate_depend_eliminate]: 9.823e-05 [updatestate_assign_eliminate]: 4.026e-05 [updatestate_loads_eliminate]: 0.00014122 [parameter_eliminate]: 4.43001e-06 [specialize_transform]: 6.508e-05 [updatestate_useless_node_eliminater]: 9.009e-05 [accelerated_algorithm]: 6.037e-05 [meta_shard_fg_expand]: 2.928e-05 [get_grad_eliminate_]: 5.166e-05 [merge_forward]: 3.354e-05 [cell_reuse_recompute_pass]: 4.42998e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00010129 [j_node_and_user_rematch]: 8.452e-05 [meta_fg_expand]: 0.00120094 [replace_old_param]: 0.00011042 [inline_without_move]: 5.283e-05 [renormalize]: 0.0230475 [add_forward_monad_depend]: 1.23e-05 [auto_monad_grad]: 3.14001e-06 [auto_monad_eliminator]: 0.00017315 [cse]: 0.00019409 [replace_applicator]: 6.516e-05 [Cycle 3]: 0.0550257, [27] [switch_simplify]: 4.81e-05 [loop_unroll]: 4.697e-05 [a_1]: 0.00148214 [with_stream_mark]: 5.615e-05 [recompute_prepare]: 5.122e-05 [updatestate_depend_eliminate]: 3.257e-05 [updatestate_assign_eliminate]: 3.203e-05 [updatestate_loads_eliminate]: 3.668e-05 [parameter_eliminate]: 3.08e-06 [specialize_transform]: 4.654e-05 [updatestate_useless_node_eliminater]: 6.522e-05 [accelerated_algorithm]: 5.375e-05 [meta_shard_fg_expand]: 1.737e-05 [get_grad_eliminate_]: 4.444e-05 [merge_forward]: 2.825e-05 [cell_reuse_recompute_pass]: 4.44002e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.675e-05 [j_node_and_user_rematch]: 0.00204864 [meta_fg_expand]: 3.751e-05 [replace_old_param]: 7.328e-05 [inline_without_move]: 4.55e-05 [renormalize]: 0.0499042 [add_forward_monad_depend]: 1.557e-05 [auto_monad_grad]: 3.76001e-06 [auto_monad_eliminator]: 0.00016264 [cse]: 0.00022458 [replace_applicator]: 8.044e-05 [Cycle 4]: 0.00283586, [27] [switch_simplify]: 4.67e-05 [loop_unroll]: 4.728e-05 [a_1]: 0.00143458 [with_stream_mark]: 6.122e-05 [recompute_prepare]: 5.403e-05 [updatestate_depend_eliminate]: 3.5e-05 [updatestate_assign_eliminate]: 3.021e-05 [updatestate_loads_eliminate]: 3.305e-05 [parameter_eliminate]: 3.43e-06 [specialize_transform]: 4.803e-05 [updatestate_useless_node_eliminater]: 7.194e-05 [accelerated_algorithm]: 5.444e-05 [meta_shard_fg_expand]: 1.667e-05 [get_grad_eliminate_]: 4.402e-05 [merge_forward]: 2.64e-05 [cell_reuse_recompute_pass]: 5.30001e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.721e-05 [j_node_and_user_rematch]: 7.483e-05 [meta_fg_expand]: 1.771e-05 [replace_old_param]: 6.327e-05 [inline_without_move]: 4.584e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 5.09e-06 [auto_monad_grad]: 3.19001e-06 [auto_monad_eliminator]: 0.00011158 [cse]: 0.00016359 [replace_applicator]: 5.235e-05 [py_interpret_to_execute_after_opt_a]: 5.742e-05 [rewriter_after_opt_a]: 0.00034641 [convert_after_rewriter]: 5.346e-05 [order_py_execute_after_rewriter]: 2.621e-05 [mutable_eliminate]: 0.0008933 [jit_opt_b]: 0.00029454, [1] [Cycle 1]: 0.00028361, [2] [frontend_op_eliminate]: 0.00014272 [inline_after_opt_a]: 0.00012536 [cconv]: 5.623e-05 [loop_unroll]: 0.00055927 [jit_opt_after_cconv]: 0.00089981, [1] [Cycle 1]: 0.00088877, [11] [c_1]: 0.00030244 [parameter_eliminate]: 6.53e-06 [updatestate_depend_eliminate]: 4.688e-05 [updatestate_assign_eliminate]: 3.453e-05 [updatestate_loads_eliminate]: 3.529e-05 [cse]: 0.00018376 [call_graph_tuple_transform]: 0.00012029 [tuple_list_get_item_eliminator]: 4.575e-05 [none_parameter_eliminate]: 2.74999e-06 [renormalize]: 7.00005e-07 [switch_simplify]: 4.561e-05 [remove_dup_value]: 0.00016294 [partial_unused_args_eliminate]: 4.28999e-06 [environ_conv]: 4.355e-05 [add_recomputation]: 0.00030221 [cse_after_recomputation]: 0.00017287, [1] [Cycle 1]: 0.00016083, [1] [cse]: 0.00014251 [auto_monad_reorder]: 0.00015859 [get_jit_bprop_graph]: 2.64001e-06 [rewriter_after_jit_bprop_graph]: 0.00041681 [opt_after_jit_grad]: 0.00118834 [symbol_engine_optimizer]: 0.00039388, [1] [Cycle 1]: 0.00038016, [6] [build]: 4.941e-05 [elim_shapecalc]: 5.883e-05 [elim_not_effective]: 9.443e-05 [opt_reshape]: 4.994e-05 [fold_const_symbol]: 8.279e-05 [renormalize]: 1.17e-06 [validate]: 0.00022299 Sums bootstrap : 0.000496s : 0.01% type_inference : 3.147174s : 84.73% event_method : 0.000401s : 0.01% auto_monad : 0.002790s : 0.08% graph_reusing : 0.000159s : 0.00% pre_auto_parallel : 0.000026s : 0.00% py_interpret_to_execute : 0.000761s : 0.02% rewriter_before_opt_a : 0.017166s : 0.46% expand_dump_flag : 0.000070s : 0.00% jit_opt_a.switch_simplify : 0.001913s : 0.05% jit_opt_a.loop_unroll : 0.001007s : 0.03% jit_opt_a.a_1 : 0.153997s : 4.15% jit_opt_a.with_stream_mark : 0.000712s : 0.02% jit_opt_a.recompute_prepare : 0.000351s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000916s : 0.02% jit_opt_a.updatestate_assign_eliminate : 0.000163s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000357s : 0.01% jit_opt_a.parameter_eliminate : 0.000017s : 0.00% jit_opt_a.specialize_transform : 0.000247s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000335s : 0.01% jit_opt_a.accelerated_algorithm : 0.000312s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000110s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000206s : 0.01% jit_opt_a.merge_forward : 0.000129s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000017s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000396s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.002321s : 0.06% jit_opt_a.meta_fg_expand : 0.041945s : 1.13% jit_opt_a.replace_old_param : 0.000648s : 0.02% jit_opt_a.inline_without_move : 0.000524s : 0.01% jit_opt_a.renormalize : 0.328995s : 8.86% jit_opt_a.add_forward_monad_depend : 0.000142s : 0.00% jit_opt_a.auto_monad_grad : 0.000046s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000959s : 0.03% jit_opt_a.cse : 0.001594s : 0.04% jit_opt_a.replace_applicator : 0.000835s : 0.02% py_interpret_to_execute_after_opt_a : 0.000057s : 0.00% rewriter_after_opt_a : 0.000346s : 0.01% convert_after_rewriter : 0.000053s : 0.00% order_py_execute_after_rewriter : 0.000026s : 0.00% mutable_eliminate : 0.000893s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000143s : 0.00% jit_opt_b.inline_after_opt_a : 0.000125s : 0.00% cconv : 0.000056s : 0.00% loop_unroll : 0.000559s : 0.02% jit_opt_after_cconv.c_1 : 0.000302s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000047s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000035s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000035s : 0.00% jit_opt_after_cconv.cse : 0.000184s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000120s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000046s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000046s : 0.00% remove_dup_value : 0.000163s : 0.00% partial_unused_args_eliminate : 0.000004s : 0.00% environ_conv : 0.000044s : 0.00% add_recomputation : 0.000302s : 0.01% cse_after_recomputation.cse : 0.000143s : 0.00% auto_monad_reorder : 0.000159s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000417s : 0.01% opt_after_jit_grad : 0.001188s : 0.03% symbol_engine_optimizer.build : 0.000049s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000059s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000094s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000050s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000083s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000223s : 0.01% Time group info: ------[substitution.] 0.023407 1744 0.53% : 0.000124s : 5: substitution.arithmetic_simplify 0.15% : 0.000035s : 4: substitution.cast_eliminate 0.72% : 0.000169s : 63: substitution.depend_value_elim 0.05% : 0.000012s : 32: substitution.elim_not_effective 0.06% : 0.000015s : 6: substitution.environ_get_add_eliminate 0.04% : 0.000010s : 4: substitution.environ_get_depend_swap 0.05% : 0.000011s : 6: substitution.environ_get_eliminate 0.09% : 0.000022s : 6: substitution.environ_get_set_eliminate 0.05% : 0.000012s : 32: substitution.fold_const_symbol 55.48% : 0.012987s : 8: substitution.getattr_setattr_resolve 0.13% : 0.000030s : 45: substitution.graph_param_transform 31.13% : 0.007286s : 157: substitution.inline 0.41% : 0.000096s : 12: substitution.inline_without_move 0.27% : 0.000063s : 147: substitution.j_node_and_user_rematch 0.28% : 0.000066s : 15: substitution.less_batch_normalization 0.18% : 0.000043s : 44: substitution.load_eliminater 0.56% : 0.000132s : 95: substitution.minmaximum_grad 0.14% : 0.000033s : 12: substitution.partial_eliminate 0.12% : 0.000028s : 6: substitution.reduce_eliminate 0.04% : 0.000010s : 5: substitution.redundant_stop_gradient_eliminater 0.35% : 0.000082s : 147: substitution.remove_not_recompute_node 0.78% : 0.000182s : 55: substitution.replace_applicator 0.26% : 0.000061s : 84: substitution.replace_old_param 0.03% : 0.000008s : 1: substitution.reshape_eliminate 0.03% : 0.000008s : 1: substitution.set_cell_output_no_recompute 0.03% : 0.000007s : 5: substitution.split_environ_get_set_with_tuple_value 0.31% : 0.000072s : 29: substitution.switch_simplify 0.03% : 0.000006s : 1: substitution.tile_eliminate 1.23% : 0.000288s : 103: substitution.tuple_list_convert_item_index_to_positive 1.44% : 0.000338s : 114: substitution.tuple_list_get_item_depend_reorder 2.57% : 0.000602s : 190: substitution.tuple_list_get_item_eliminator 0.81% : 0.000191s : 139: substitution.updatestate_pure_node_eliminater 1.62% : 0.000379s : 171: substitution.updatestate_useless_node_eliminater ------[type_inference.] 3.146158 2 94.90% : 2.985684s : 1: type_inference.infer 5.10% : 0.160474s : 1: type_inference.specialize ------[replace.] 0.006645 301 0.28% : 0.000019s : 1: replace.arithmetic_simplify 0.74% : 0.000049s : 4: replace.cast_eliminate 1.33% : 0.000088s : 8: replace.depend_value_elim 0.41% : 0.000027s : 2: replace.environ_get_set_eliminate 2.49% : 0.000166s : 6: replace.getattr_setattr_resolve 69.00% : 0.004585s : 157: replace.inline 0.65% : 0.000043s : 2: replace.partial_eliminate 1.32% : 0.000087s : 3: replace.replace_applicator 6.44% : 0.000428s : 29: replace.switch_simplify 2.30% : 0.000153s : 11: replace.tuple_list_get_item_depend_reorder 14.70% : 0.000977s : 76: replace.tuple_list_get_item_eliminator 0.33% : 0.000022s : 2: replace.updatestate_useless_node_eliminater ------[match.] 0.020701 301 0.29% : 0.000060s : 1: match.arithmetic_simplify 0.15% : 0.000031s : 4: match.cast_eliminate 0.05% : 0.000011s : 8: match.depend_value_elim 0.06% : 0.000013s : 2: match.environ_get_set_eliminate 62.21% : 0.012878s : 6: match.getattr_setattr_resolve 34.63% : 0.007169s : 157: match.inline 0.07% : 0.000014s : 2: match.partial_eliminate 0.14% : 0.000028s : 3: match.replace_applicator 0.28% : 0.000058s : 29: match.switch_simplify 0.67% : 0.000138s : 11: match.tuple_list_get_item_depend_reorder 1.40% : 0.000290s : 76: match.tuple_list_get_item_eliminator 0.05% : 0.000011s : 2: match.updatestate_useless_node_eliminater ------[predicate.] 0.089031 37536 0.10% : 0.000089s : 664: predicate.accumulaten_eliminater 0.02% : 0.000019s : 45: predicate.ad_related_special_op_eliminate 0.10% : 0.000089s : 664: predicate.addn_check_dump 0.10% : 0.000090s : 664: predicate.addn_zero_filter 0.13% : 0.000120s : 665: predicate.arithmetic_simplify 0.11% : 0.000095s : 669: predicate.cast_eliminate 0.01% : 0.000006s : 45: predicate.check_bprop_eliminate 0.10% : 0.000088s : 664: predicate.compare_switch_simplify 0.10% : 0.000092s : 664: predicate.depend_value_elim 0.10% : 0.000090s : 671: predicate.dict_get_item_const_eliminator 0.10% : 0.000093s : 671: predicate.dict_get_item_eliminator 0.10% : 0.000090s : 671: predicate.dict_set_item_eliminator 0.01% : 0.000010s : 45: predicate.dumpgradient_eliminate 0.00% : 0.000004s : 45: predicate.elim_not_effective 0.01% : 0.000008s : 45: predicate.elim_shapecalc_of_broadcastargs 0.10% : 0.000092s : 669: predicate.environ_add_const_eliminate 0.10% : 0.000091s : 671: predicate.environ_get_add_eliminate 47.85% : 0.042597s : 669: predicate.environ_get_depend_swap 0.10% : 0.000092s : 671: predicate.environ_get_eliminate 0.10% : 0.000090s : 671: predicate.environ_get_set_eliminate 0.00% : 0.000004s : 45: predicate.fold_const_symbol 0.03% : 0.000030s : 206: predicate.get_grad_eliminate 0.02% : 0.000018s : 40: predicate.getattr_setattr_resolve 0.00% : 0.000003s : 45: predicate.graph_param_transform 0.27% : 0.000237s : 1009: predicate.inline 0.08% : 0.000070s : 412: predicate.inline_without_move 0.02% : 0.000016s : 206: predicate.j_node_and_user_rematch 0.04% : 0.000038s : 222: predicate.less_batch_normalization 0.12% : 0.000110s : 758: predicate.list_to_tuple_eliminator_ 0.13% : 0.000114s : 805: predicate.load_eliminater 0.01% : 0.000010s : 45: predicate.loop_unroll_after_grad 0.19% : 0.000173s : 1113: predicate.loop_unroll_before_grad 0.11% : 0.000099s : 727: predicate.make_slice_get_slice_eliminator 0.10% : 0.000088s : 664: predicate.merge_addn 0.10% : 0.000092s : 665: predicate.minmaximum_grad 0.01% : 0.000012s : 45: predicate.mutable_eliminate 0.01% : 0.000007s : 45: predicate.opt_reshape 0.15% : 0.000135s : 805: predicate.partial_eliminate 0.10% : 0.000088s : 656: predicate.print_const_string_wrapper 0.13% : 0.000112s : 665: predicate.reduce_eliminate 0.12% : 0.000107s : 760: predicate.redundant_stop_gradient_eliminater 0.02% : 0.000016s : 206: predicate.remove_not_recompute_node 0.14% : 0.000121s : 1250: predicate.replace_applicator 0.04% : 0.000034s : 412: predicate.replace_old_param 0.00% : 0.000004s : 45: predicate.reset_defer_inline 0.11% : 0.000094s : 665: predicate.reshape_eliminate 0.10% : 0.000093s : 656: predicate.row_tensor_add_zeros_like 0.01% : 0.000008s : 45: predicate.row_tensor_eliminate 0.10% : 0.000091s : 656: predicate.same_eliminate 0.02% : 0.000022s : 259: predicate.set_cell_output_no_recompute 0.02% : 0.000013s : 90: predicate.special_op_eliminate 0.04% : 0.000035s : 206: predicate.specialize_transform 0.12% : 0.000107s : 656: predicate.split_environ_get_set_with_tuple_value 0.10% : 0.000089s : 656: predicate.stack_unstack_eliminate 0.01% : 0.000007s : 45: predicate.switch_call_monad_eliminater 0.25% : 0.000223s : 919: predicate.switch_defer_inline 0.15% : 0.000137s : 919: predicate.switch_layer_defer_inline 0.44% : 0.000392s : 2135: predicate.switch_simplify 45.96% : 0.040919s : 665: predicate.tile_eliminate 0.10% : 0.000093s : 665: predicate.transpose_eliminate 0.13% : 0.000117s : 671: predicate.tuple_list_convert_item_index_to_positive 0.12% : 0.000110s : 682: predicate.tuple_list_get_item_depend_reorder 0.21% : 0.000186s : 848: predicate.tuple_list_get_item_eliminator 0.13% : 0.000113s : 682: predicate.tuple_list_set_item_eliminator 0.12% : 0.000103s : 758: predicate.tuple_to_list_eliminator_ 0.13% : 0.000114s : 805: predicate.updatestate_pure_node_eliminater 0.17% : 0.000154s : 1013: predicate.updatestate_useless_node_eliminater 0.13% : 0.000114s : 656: predicate.value_based_eliminate 0.01% : 0.000007s : 45: predicate.virtual_view_grad_eliminate 0.01% : 0.000007s : 45: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.094958 395 69.18% : 0.065695s : 204: func_graph_cloner_run.FuncGraphClonerGraph 0.24% : 0.000225s : 3: func_graph_cloner_run.FuncGraphClonerNode 30.58% : 0.029038s : 188: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.261485 106 0.01% : 0.000310s : 1: add_recomputation 0.07% : 0.002815s : 1: auto_monad 0.00% : 0.000164s : 1: auto_monad_reorder 0.01% : 0.000520s : 1: bootstrap 0.00% : 0.000059s : 1: cconv 0.00% : 0.000058s : 1: convert_after_rewriter 0.00% : 0.000175s : 1: cse_after_recomputation 0.00% : 0.000046s : 1: environ_conv 0.01% : 0.000412s : 1: event_method 0.00% : 0.000076s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000169s : 1: graph_reusing 13.60% : 0.579529s : 1: jit_opt_a 0.02% : 0.000904s : 1: jit_opt_after_cconv 0.01% : 0.000298s : 1: jit_opt_b 0.01% : 0.000569s : 1: loop_unroll 0.02% : 0.000909s : 1: mutable_eliminate 3.82% : 0.162959s : 52: opt.transform.jit_opt_a 0.01% : 0.000509s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000257s : 4: opt.transform.jit_opt_b 0.00% : 0.000061s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000075s : 1: opt.transform.mutable_eliminate 0.00% : 0.000212s : 1: opt.transform.opt_after_jit_grad 0.31% : 0.013306s : 4: opt.transform.opt_resolve 0.01% : 0.000281s : 4: opt.transform.symbol_engine_opt 0.03% : 0.001214s : 1: opt_after_jit_grad 0.00% : 0.000029s : 1: order_py_execute_after_rewriter 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000029s : 1: pre_auto_parallel 0.02% : 0.000790s : 1: py_interpret_to_execute 0.00% : 0.000062s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000170s : 1: remove_dup_value 6.41% : 0.273048s : 3: renormalize.infer 1.31% : 0.055873s : 3: renormalize.specialize 0.01% : 0.000425s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000355s : 1: rewriter_after_opt_a 0.40% : 0.017204s : 1: rewriter_before_opt_a 0.01% : 0.000398s : 1: symbol_engine_optimizer 73.85% : 3.147202s : 1: type_inference . [hook] pytest_runtest_teardown:test_mint_optim_fused_adamw_group_lr_dynamic[1] tests/st/mint/optim/test_fused_adamw.py::test_mint_optim_fused_adamw_group_lr_dynamic[1],max_mem:20.0M =============================== 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_fused_adamw.py::test_mint_optim_fused_adamw_group_lr_dynamic[0] /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 ================== 2 passed, 26 warnings in 477.22s (0:07:57) ==================