[WARNING] ME(162276:281473716752176,MainProcess):2026-01-29-17:38:02.822.90 [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_001/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_fused_adamw.py .....................[WARNING] ANALYZER(162276,ffffb4e68f30,python3.9):2026-01-29-17:44:33.369.750 [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 = 2.92518, [30] [bootstrap]: 0.00069027 [type_inference]: 2.40387 [event_method]: 0.00037267 [auto_monad]: 0.00280438 [graph_reusing]: 0.00017105 [pre_auto_parallel]: 4.798e-05 [py_interpret_to_execute]: 0.00093583 [rewriter_before_opt_a]: 0.00547133 [expand_dump_flag]: 5.822e-05 [jit_opt_a]: 0.504766, [4] [Cycle 1]: 0.416793, [27] [switch_simplify]: 0.00153366 [loop_unroll]: 0.00060007 [a_1]: 0.0821783 [with_stream_mark]: 0.00027979 [recompute_prepare]: 0.00014365 [updatestate_depend_eliminate]: 0.0007593 [updatestate_assign_eliminate]: 6.903e-05 [updatestate_loads_eliminate]: 0.00013283 [parameter_eliminate]: 6.02999e-06 [specialize_transform]: 8.663e-05 [updatestate_useless_node_eliminater]: 0.00010483 [accelerated_algorithm]: 0.00016689 [meta_shard_fg_expand]: 4.337e-05 [get_grad_eliminate_]: 6.714e-05 [merge_forward]: 3.967e-05 [cell_reuse_recompute_pass]: 2.58e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00013485 [j_node_and_user_rematch]: 0.00011678 [meta_fg_expand]: 0.112445 [replace_old_param]: 0.0003886 [inline_without_move]: 0.00048885 [renormalize]: 0.213026 [add_forward_monad_depend]: 0.0001749 [auto_monad_grad]: 6.165e-05 [auto_monad_eliminator]: 0.00077459 [cse]: 0.00142288 [replace_applicator]: 0.00090533 [Cycle 2]: 0.0586501, [27] [switch_simplify]: 0.00043558 [loop_unroll]: 0.00035679 [a_1]: 0.0315631 [with_stream_mark]: 0.00039145 [recompute_prepare]: 9.809e-05 [updatestate_depend_eliminate]: 0.00010818 [updatestate_assign_eliminate]: 4.213e-05 [updatestate_loads_eliminate]: 0.00012072 [parameter_eliminate]: 3.48e-06 [specialize_transform]: 6.778e-05 [updatestate_useless_node_eliminater]: 9.01e-05 [accelerated_algorithm]: 6.547e-05 [meta_shard_fg_expand]: 3.182e-05 [get_grad_eliminate_]: 5.596e-05 [merge_forward]: 3.344e-05 [cell_reuse_recompute_pass]: 4.16001e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00010567 [j_node_and_user_rematch]: 8.911e-05 [meta_fg_expand]: 0.00105107 [replace_old_param]: 0.00011167 [inline_without_move]: 5.519e-05 [renormalize]: 0.0228754 [add_forward_monad_depend]: 1.227e-05 [auto_monad_grad]: 3.21001e-06 [auto_monad_eliminator]: 0.00019029 [cse]: 0.00020866 [replace_applicator]: 6.788e-05 [Cycle 3]: 0.00674952, [27] [switch_simplify]: 5.055e-05 [loop_unroll]: 4.698e-05 [a_1]: 0.00167506 [with_stream_mark]: 5.298e-05 [recompute_prepare]: 5.13e-05 [updatestate_depend_eliminate]: 3.746e-05 [updatestate_assign_eliminate]: 3.196e-05 [updatestate_loads_eliminate]: 3.574e-05 [parameter_eliminate]: 2.08002e-06 [specialize_transform]: 4.817e-05 [updatestate_useless_node_eliminater]: 6.965e-05 [accelerated_algorithm]: 5.598e-05 [meta_shard_fg_expand]: 2.128e-05 [get_grad_eliminate_]: 4.525e-05 [merge_forward]: 2.709e-05 [cell_reuse_recompute_pass]: 3.91001e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.698e-05 [j_node_and_user_rematch]: 7.745e-05 [meta_fg_expand]: 1.877e-05 [replace_old_param]: 6.099e-05 [inline_without_move]: 4.625e-05 [renormalize]: 0.00359539 [add_forward_monad_depend]: 8.74e-06 [auto_monad_grad]: 2.53003e-06 [auto_monad_eliminator]: 0.00012722 [cse]: 0.00018922 [replace_applicator]: 6.273e-05 [Cycle 4]: 0.00286854, [27] [switch_simplify]: 4.832e-05 [loop_unroll]: 4.752e-05 [a_1]: 0.00145607 [with_stream_mark]: 5.301e-05 [recompute_prepare]: 5.254e-05 [updatestate_depend_eliminate]: 4.045e-05 [updatestate_assign_eliminate]: 3.15e-05 [updatestate_loads_eliminate]: 3.369e-05 [parameter_eliminate]: 2.90998e-06 [specialize_transform]: 5.254e-05 [updatestate_useless_node_eliminater]: 7.451e-05 [accelerated_algorithm]: 5.699e-05 [meta_shard_fg_expand]: 1.513e-05 [get_grad_eliminate_]: 4.544e-05 [merge_forward]: 2.741e-05 [cell_reuse_recompute_pass]: 5.77999e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.988e-05 [j_node_and_user_rematch]: 8.242e-05 [meta_fg_expand]: 2.067e-05 [replace_old_param]: 6.5e-05 [inline_without_move]: 4.764e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 3.73999e-06 [auto_monad_grad]: 3.06999e-06 [auto_monad_eliminator]: 0.000101 [cse]: 0.0001595 [replace_applicator]: 5.252e-05 [py_interpret_to_execute_after_opt_a]: 6.451e-05 [rewriter_after_opt_a]: 0.00037957 [convert_after_rewriter]: 4.453e-05 [order_py_execute_after_rewriter]: 2.683e-05 [mutable_eliminate]: 0.00090707 [jit_opt_b]: 0.00030319, [1] [Cycle 1]: 0.00029398, [2] [frontend_op_eliminate]: 0.00014606 [inline_after_opt_a]: 0.00013127 [cconv]: 5.364e-05 [loop_unroll]: 0.00054333 [jit_opt_after_cconv]: 0.00090807, [1] [Cycle 1]: 0.0008981, [11] [c_1]: 0.00031796 [parameter_eliminate]: 6.07999e-06 [updatestate_depend_eliminate]: 4.334e-05 [updatestate_assign_eliminate]: 3.631e-05 [updatestate_loads_eliminate]: 3.648e-05 [cse]: 0.00016662 [call_graph_tuple_transform]: 0.00011901 [tuple_list_get_item_eliminator]: 4.751e-05 [none_parameter_eliminate]: 2.34999e-06 [renormalize]: 1.27e-06 [switch_simplify]: 4.633e-05 [remove_dup_value]: 0.00015641 [partial_unused_args_eliminate]: 3.25e-06 [environ_conv]: 4.274e-05 [add_recomputation]: 0.00029274 [cse_after_recomputation]: 0.00015506, [1] [Cycle 1]: 0.00014444, [1] [cse]: 0.00013101 [auto_monad_reorder]: 0.00016528 [get_jit_bprop_graph]: 2.87002e-06 [rewriter_after_jit_bprop_graph]: 7.61999e-06 [opt_after_jit_grad]: 0.00085652 [symbol_engine_optimizer]: 0.00033633, [1] [Cycle 1]: 0.00032763, [6] [build]: 2.908e-05 [elim_shapecalc]: 5.322e-05 [elim_not_effective]: 8.393e-05 [opt_reshape]: 4.939e-05 [fold_const_symbol]: 7.534e-05 [renormalize]: 5.49975e-07 [validate]: 0.00025235 Sums bootstrap : 0.000690s : 0.02% type_inference : 2.403872s : 82.80% event_method : 0.000373s : 0.01% auto_monad : 0.002804s : 0.10% graph_reusing : 0.000171s : 0.01% pre_auto_parallel : 0.000048s : 0.00% py_interpret_to_execute : 0.000936s : 0.03% rewriter_before_opt_a : 0.005471s : 0.19% expand_dump_flag : 0.000058s : 0.00% jit_opt_a.switch_simplify : 0.002068s : 0.07% jit_opt_a.loop_unroll : 0.001051s : 0.04% jit_opt_a.a_1 : 0.116873s : 4.03% jit_opt_a.with_stream_mark : 0.000777s : 0.03% jit_opt_a.recompute_prepare : 0.000346s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000945s : 0.03% jit_opt_a.updatestate_assign_eliminate : 0.000175s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000323s : 0.01% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000255s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000339s : 0.01% jit_opt_a.accelerated_algorithm : 0.000345s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000112s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000214s : 0.01% jit_opt_a.merge_forward : 0.000128s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000016s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000417s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000366s : 0.01% jit_opt_a.meta_fg_expand : 0.113536s : 3.91% jit_opt_a.replace_old_param : 0.000626s : 0.02% jit_opt_a.inline_without_move : 0.000638s : 0.02% jit_opt_a.renormalize : 0.239497s : 8.25% jit_opt_a.add_forward_monad_depend : 0.000200s : 0.01% jit_opt_a.auto_monad_grad : 0.000070s : 0.00% jit_opt_a.auto_monad_eliminator : 0.001193s : 0.04% jit_opt_a.cse : 0.001980s : 0.07% jit_opt_a.replace_applicator : 0.001088s : 0.04% py_interpret_to_execute_after_opt_a : 0.000065s : 0.00% rewriter_after_opt_a : 0.000380s : 0.01% convert_after_rewriter : 0.000045s : 0.00% order_py_execute_after_rewriter : 0.000027s : 0.00% mutable_eliminate : 0.000907s : 0.03% jit_opt_b.frontend_op_eliminate : 0.000146s : 0.01% jit_opt_b.inline_after_opt_a : 0.000131s : 0.00% cconv : 0.000054s : 0.00% loop_unroll : 0.000543s : 0.02% jit_opt_after_cconv.c_1 : 0.000318s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000043s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000036s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000036s : 0.00% jit_opt_after_cconv.cse : 0.000167s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000119s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000048s : 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 : 0.000046s : 0.00% remove_dup_value : 0.000156s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000043s : 0.00% add_recomputation : 0.000293s : 0.01% cse_after_recomputation.cse : 0.000131s : 0.00% auto_monad_reorder : 0.000165s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000857s : 0.03% symbol_engine_optimizer.build : 0.000029s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000053s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000084s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000049s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000075s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000252s : 0.01% Time group info: ------[substitution.] 0.012509 1710 0.86% : 0.000108s : 5: substitution.arithmetic_simplify 0.29% : 0.000036s : 4: substitution.cast_eliminate 1.12% : 0.000140s : 62: substitution.depend_value_elim 0.08% : 0.000011s : 32: substitution.elim_not_effective 0.14% : 0.000018s : 6: substitution.environ_get_add_eliminate 0.10% : 0.000012s : 4: substitution.environ_get_depend_swap 0.12% : 0.000015s : 6: substitution.environ_get_eliminate 0.25% : 0.000031s : 6: substitution.environ_get_set_eliminate 0.09% : 0.000011s : 32: substitution.fold_const_symbol 16.24% : 0.002031s : 8: substitution.getattr_setattr_resolve 0.23% : 0.000029s : 45: substitution.graph_param_transform 58.08% : 0.007265s : 153: substitution.inline 1.32% : 0.000165s : 12: substitution.inline_without_move 0.47% : 0.000059s : 147: substitution.j_node_and_user_rematch 0.71% : 0.000089s : 15: substitution.less_batch_normalization 0.39% : 0.000048s : 44: substitution.load_eliminater 1.10% : 0.000138s : 92: substitution.minmaximum_grad 0.31% : 0.000039s : 12: substitution.partial_eliminate 0.25% : 0.000031s : 6: substitution.reduce_eliminate 0.07% : 0.000008s : 4: substitution.redundant_stop_gradient_eliminater 0.67% : 0.000084s : 147: substitution.remove_not_recompute_node 1.99% : 0.000249s : 55: substitution.replace_applicator 0.46% : 0.000057s : 84: substitution.replace_old_param 0.07% : 0.000008s : 1: substitution.reshape_eliminate 0.05% : 0.000007s : 1: substitution.set_cell_output_no_recompute 0.08% : 0.000010s : 5: substitution.split_environ_get_set_with_tuple_value 0.64% : 0.000080s : 28: substitution.switch_simplify 0.07% : 0.000008s : 1: substitution.tile_eliminate 2.29% : 0.000287s : 100: substitution.tuple_list_convert_item_index_to_positive 2.69% : 0.000336s : 109: substitution.tuple_list_get_item_depend_reorder 4.42% : 0.000553s : 183: substitution.tuple_list_get_item_eliminator 1.43% : 0.000179s : 135: substitution.updatestate_pure_node_eliminater 2.93% : 0.000366s : 166: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.402713 2 94.42% : 2.268692s : 1: type_inference.infer 5.58% : 0.134021s : 1: type_inference.specialize ------[replace.] 0.004087 291 0.25% : 0.000010s : 1: replace.arithmetic_simplify 0.73% : 0.000030s : 4: replace.cast_eliminate 1.61% : 0.000066s : 8: replace.depend_value_elim 0.87% : 0.000035s : 2: replace.environ_get_set_eliminate 3.82% : 0.000156s : 6: replace.getattr_setattr_resolve 46.83% : 0.001914s : 153: replace.inline 0.89% : 0.000036s : 2: replace.partial_eliminate 3.12% : 0.000128s : 3: replace.replace_applicator 11.26% : 0.000460s : 28: replace.switch_simplify 3.26% : 0.000133s : 9: replace.tuple_list_get_item_depend_reorder 26.77% : 0.001094s : 74: replace.tuple_list_get_item_eliminator 0.60% : 0.000025s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.009712 291 0.54% : 0.000052s : 1: match.arithmetic_simplify 0.34% : 0.000033s : 4: match.cast_eliminate 0.08% : 0.000008s : 8: match.depend_value_elim 0.22% : 0.000021s : 2: match.environ_get_set_eliminate 19.82% : 0.001924s : 6: match.getattr_setattr_resolve 73.67% : 0.007154s : 153: match.inline 0.18% : 0.000018s : 2: match.partial_eliminate 0.41% : 0.000040s : 3: match.replace_applicator 0.65% : 0.000064s : 28: match.switch_simplify 1.39% : 0.000135s : 9: match.tuple_list_get_item_depend_reorder 2.56% : 0.000249s : 74: match.tuple_list_get_item_eliminator 0.15% : 0.000014s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.005657 36474 1.60% : 0.000091s : 643: predicate.accumulaten_eliminater 0.19% : 0.000011s : 45: predicate.ad_related_special_op_eliminate 1.52% : 0.000086s : 643: predicate.addn_check_dump 1.58% : 0.000089s : 643: predicate.addn_zero_filter 2.15% : 0.000122s : 644: predicate.arithmetic_simplify 1.63% : 0.000092s : 648: predicate.cast_eliminate 0.11% : 0.000006s : 45: predicate.check_bprop_eliminate 1.53% : 0.000086s : 643: predicate.compare_switch_simplify 1.64% : 0.000093s : 643: predicate.depend_value_elim 1.53% : 0.000087s : 650: predicate.dict_get_item_const_eliminator 1.58% : 0.000090s : 650: predicate.dict_get_item_eliminator 1.57% : 0.000089s : 650: predicate.dict_set_item_eliminator 0.14% : 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 1.55% : 0.000088s : 648: predicate.environ_add_const_eliminate 1.54% : 0.000087s : 650: predicate.environ_get_add_eliminate 1.54% : 0.000087s : 648: predicate.environ_get_depend_swap 1.56% : 0.000088s : 650: predicate.environ_get_eliminate 1.55% : 0.000088s : 650: predicate.environ_get_set_eliminate 0.06% : 0.000003s : 45: predicate.fold_const_symbol 0.53% : 0.000030s : 206: predicate.get_grad_eliminate 0.30% : 0.000017s : 40: predicate.getattr_setattr_resolve 0.05% : 0.000003s : 45: predicate.graph_param_transform 4.25% : 0.000240s : 979: predicate.inline 1.44% : 0.000081s : 412: predicate.inline_without_move 0.27% : 0.000016s : 206: predicate.j_node_and_user_rematch 0.70% : 0.000039s : 222: predicate.less_batch_normalization 1.78% : 0.000100s : 733: predicate.list_to_tuple_eliminator_ 2.55% : 0.000144s : 780: predicate.load_eliminater 0.18% : 0.000010s : 45: predicate.loop_unroll_after_grad 3.40% : 0.000193s : 1086: predicate.loop_unroll_before_grad 1.72% : 0.000097s : 704: predicate.make_slice_get_slice_eliminator 1.54% : 0.000087s : 643: predicate.merge_addn 1.60% : 0.000091s : 644: predicate.minmaximum_grad 0.20% : 0.000011s : 45: predicate.mutable_eliminate 0.12% : 0.000007s : 45: predicate.opt_reshape 2.47% : 0.000140s : 780: predicate.partial_eliminate 1.58% : 0.000090s : 635: predicate.print_const_string_wrapper 2.00% : 0.000113s : 644: predicate.reduce_eliminate 1.86% : 0.000105s : 735: predicate.redundant_stop_gradient_eliminater 0.28% : 0.000016s : 206: predicate.remove_not_recompute_node 2.03% : 0.000115s : 1225: predicate.replace_applicator 0.57% : 0.000032s : 412: predicate.replace_old_param 0.06% : 0.000004s : 45: predicate.reset_defer_inline 1.58% : 0.000089s : 644: predicate.reshape_eliminate 1.56% : 0.000088s : 635: predicate.row_tensor_add_zeros_like 0.13% : 0.000007s : 45: predicate.row_tensor_eliminate 1.53% : 0.000087s : 635: predicate.same_eliminate 0.39% : 0.000022s : 256: predicate.set_cell_output_no_recompute 0.23% : 0.000013s : 90: predicate.special_op_eliminate 0.63% : 0.000036s : 206: predicate.specialize_transform 1.80% : 0.000102s : 635: predicate.split_environ_get_set_with_tuple_value 1.53% : 0.000086s : 635: predicate.stack_unstack_eliminate 0.12% : 0.000007s : 45: predicate.switch_call_monad_eliminater 4.09% : 0.000231s : 889: predicate.switch_defer_inline 2.53% : 0.000143s : 889: predicate.switch_layer_defer_inline 6.73% : 0.000381s : 2076: predicate.switch_simplify 1.57% : 0.000089s : 644: predicate.tile_eliminate 1.57% : 0.000089s : 644: predicate.transpose_eliminate 2.02% : 0.000115s : 650: predicate.tuple_list_convert_item_index_to_positive 1.86% : 0.000105s : 659: predicate.tuple_list_get_item_depend_reorder 3.09% : 0.000175s : 823: predicate.tuple_list_get_item_eliminator 1.90% : 0.000108s : 659: predicate.tuple_list_set_item_eliminator 1.78% : 0.000101s : 733: predicate.tuple_to_list_eliminator_ 2.04% : 0.000115s : 780: predicate.updatestate_pure_node_eliminater 2.87% : 0.000163s : 987: predicate.updatestate_useless_node_eliminater 1.92% : 0.000109s : 635: predicate.value_based_eliminate 0.12% : 0.000007s : 45: predicate.virtual_view_grad_eliminate 0.15% : 0.000008s : 45: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.112857 387 90.55% : 0.102189s : 200: func_graph_cloner_run.FuncGraphClonerGraph 0.15% : 0.000173s : 3: func_graph_cloner_run.FuncGraphClonerNode 9.30% : 0.010495s : 184: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.292279 106 0.01% : 0.000299s : 1: add_recomputation 0.09% : 0.002827s : 1: auto_monad 0.01% : 0.000171s : 1: auto_monad_reorder 0.02% : 0.000714s : 1: bootstrap 0.00% : 0.000057s : 1: cconv 0.00% : 0.000048s : 1: convert_after_rewriter 0.00% : 0.000158s : 1: cse_after_recomputation 0.00% : 0.000046s : 1: environ_conv 0.01% : 0.000383s : 1: event_method 0.00% : 0.000064s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.01% : 0.000179s : 1: graph_reusing 15.33% : 0.504772s : 1: jit_opt_a 0.03% : 0.000912s : 1: jit_opt_after_cconv 0.01% : 0.000307s : 1: jit_opt_b 0.02% : 0.000554s : 1: loop_unroll 0.03% : 0.000921s : 1: mutable_eliminate 3.78% : 0.124464s : 52: opt.transform.jit_opt_a 0.02% : 0.000525s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000268s : 4: opt.transform.jit_opt_b 0.00% : 0.000062s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000069s : 1: opt.transform.mutable_eliminate 0.00% : 0.000164s : 1: opt.transform.opt_after_jit_grad 0.07% : 0.002338s : 4: opt.transform.opt_resolve 0.01% : 0.000257s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000868s : 1: opt_after_jit_grad 0.00% : 0.000030s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000052s : 1: pre_auto_parallel 0.03% : 0.000956s : 1: py_interpret_to_execute 0.00% : 0.000069s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000161s : 1: remove_dup_value 5.24% : 0.172418s : 3: renormalize.infer 2.04% : 0.067020s : 3: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000387s : 1: rewriter_after_opt_a 0.17% : 0.005502s : 1: rewriter_before_opt_a 0.01% : 0.000339s : 1: symbol_engine_optimizer 73.02% : 2.403898s : 1: type_inference . TotalTime = 0.30185, [21] [bootstrap]: 0.00064547 [type_inference]: 0.190378 [event_method]: 0.00040463 [auto_monad]: 0.00042046 [graph_reusing]: 3.475e-05 [inline]: 3.87002e-06 [add_attr]: 0.00528268, [1] [add_attr_with_inline]: 0.00523353, [1] [Cycle 1]: 0.00010994, [2] [tag_attr]: 5.041e-05 [meta_addattr_fg_expand]: 1.061e-05 [parallel-infer-symbol]: 4.03001e-06 [pre_auto_parallel]: 9.439e-05 [insert-virtual-dataset]: 2.72001e-06 [parallel-infer-symbol-second]: 1.03001e-06 [dataset_repeat_opt]: 2.25002e-06 [pipeline_split]: 1.74e-06 [optimize]: 0.0133897, [53] [py_interpret_to_execute]: 6.981e-05 [rewriter_before_opt_a]: 0.00017688 [opt_a]: 0.00924213, [2] [Cycle 1]: 0.00754613, [45] [expand_dump_flag]: 4.50999e-06 [switch_simplify]: 0.00023305 [loop_unroll]: 5.962e-05 [a_1]: 0.0020269 [with_stream_mark]: 8.412e-05 [recompute_prepare]: 3.187e-05 [updatestate_depend_eliminate]: 8.376e-05 [updatestate_assign_eliminate]: 1.156e-05 [updatestate_loads_eliminate]: 6.297e-05 [parameter_eliminate]: 3.24001e-06 [a_2]: 0.00027519 [accelerated_algorithm]: 4.238e-05 [shard]: 2.59999e-06 [meta_shard_fg_expand]: 7.42002e-06 [shard_inline]: 1.639e-05 [merge_send_recv]: 1.518e-05 [auto_parallel]: 1.786e-05 [parallel]: 7.248e-05 [flash_sp]: 2.758e-05 [merge_comm]: 1.026e-05 [allreduce_fusion]: 8.85999e-06 [matmul_add_comm_reduction]: 1.761e-05 [allreduce_slice_to_reducescatter]: 9.60019e-07 [virtual_shard_identity]: 2.048e-05 [virtual_dataset]: 0.00041285 [get_grad_eliminate_]: 2.121e-05 [virtual_output]: 1.621e-05 [merge_forward]: 1.323e-05 [cell_reuse_recompute_pass]: 3.45e-06 [offload_activation]: 2.566e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.1e-05 [merge_recompute_call_nodes]: 2.73998e-06 [before_grad]: 2.79e-05 [set_forward_comm_id_for_comm_node_pass]: 1.134e-05 [meta_fg_expand]: 1.041e-05 [flash_sp_send_recv_attached]: 8.30999e-06 [receive_attached]: 1.486e-05 [after_resolve]: 2.556e-05 [a_after_grad]: 2.559e-05 [renormalize]: 0.00291756 [add_forward_monad_depend]: 1.09e-05 [auto_monad_grad]: 3.56001e-06 [auto_monad_eliminator]: 6.283e-05 [cse]: 0.00021423 [a_3]: 0.00012977 [Cycle 2]: 0.00168012, [45] [expand_dump_flag]: 2.84001e-06 [switch_simplify]: 2.125e-05 [loop_unroll]: 1.518e-05 [a_1]: 0.00047631 [with_stream_mark]: 2.622e-05 [recompute_prepare]: 1.707e-05 [updatestate_depend_eliminate]: 1.021e-05 [updatestate_assign_eliminate]: 1.204e-05 [updatestate_loads_eliminate]: 1.472e-05 [parameter_eliminate]: 2.09e-06 [a_2]: 0.00023774 [accelerated_algorithm]: 2.296e-05 [shard]: 2.21998e-06 [meta_shard_fg_expand]: 5.42001e-06 [shard_inline]: 1.691e-05 [merge_send_recv]: 1.663e-05 [auto_parallel]: 1.688e-05 [parallel]: 1.04e-05 [flash_sp]: 4.89e-06 [merge_comm]: 1.074e-05 [allreduce_fusion]: 8.73001e-06 [matmul_add_comm_reduction]: 1.849e-05 [allreduce_slice_to_reducescatter]: 8.39995e-07 [virtual_shard_identity]: 1.733e-05 [virtual_dataset]: 1.494e-05 [get_grad_eliminate_]: 1.52e-05 [virtual_output]: 1.532e-05 [merge_forward]: 8.85001e-06 [cell_reuse_recompute_pass]: 4.62e-06 [offload_activation]: 1.881e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.634e-05 [merge_recompute_call_nodes]: 1.64e-06 [before_grad]: 2.804e-05 [set_forward_comm_id_for_comm_node_pass]: 9.91e-06 [meta_fg_expand]: 6.38e-06 [flash_sp_send_recv_attached]: 2.27001e-06 [receive_attached]: 2.66e-06 [after_resolve]: 2.39e-05 [a_after_grad]: 2.597e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.94001e-06 [auto_monad_grad]: 2.78e-06 [auto_monad_eliminator]: 4.495e-05 [cse]: 5.555e-05 [a_3]: 0.00010875 [py_interpret_to_execute_after_opt_a]: 2.903e-05 [slice_cell_reuse_recomputed_activation]: 2.64999e-06 [rewriter_after_opt_a]: 0.0002128 [convert_after_rewriter]: 1.582e-05 [order_py_execute_after_rewriter]: 1.093e-05 [mutable_eliminate]: 0.00081986 [opt_b]: 0.0005961, [1] [Cycle 1]: 0.00058671, [7] [b_1]: 0.00041023 [b_2]: 1.804e-05 [updatestate_depend_eliminate]: 1.533e-05 [updatestate_assign_eliminate]: 1.047e-05 [updatestate_loads_eliminate]: 1.389e-05 [renormalize]: 8.50006e-07 [cse]: 6.447e-05 [optimize_parallel_all_gather_comm]: 8.342e-05 [overlap_param_gather]: 3.38e-06 [cconv]: 4.213e-05 [loop_unroll]: 0.00061863 [opt_after_cconv]: 0.00025949, [1] [Cycle 1]: 0.0002506, [7] [c_1]: 0.0001153 [parameter_eliminate]: 5.62001e-06 [updatestate_depend_eliminate]: 1.421e-05 [updatestate_assign_eliminate]: 8.68001e-06 [updatestate_loads_eliminate]: 1.23e-05 [cse]: 5.173e-05 [renormalize]: 5.19998e-07 [remove_dup_value]: 6.39e-05 [tuple_transform]: 0.00016146, [1] [Cycle 1]: 0.0001549, [4] [d_1]: 0.00011125 [none_parameter_eliminate]: 2.40002e-06 [renormalize]: 3.00002e-07 [switch_simplify]: 1.691e-05 [partial_unused_args_eliminate]: 1.84e-06 [add_recomputation]: 0.00012462 [cse_after_recomputation]: 5.517e-05, [1] [Cycle 1]: 4.944e-05, [1] [cse]: 4.133e-05 [environ_conv]: 1.59e-05 [swap_dp_allreduce_reducescatter]: 1.246e-05 [bias_add_comm_swap]: 4.18999e-06 [label_micro_interleaved_index]: 6.31e-06 [label_fine_grained_interleaved_index]: 2.84999e-06 [merge_cast_opt]: 1.73997e-06 [slice_recompute_activation]: 2.71999e-06 [micro_interleaved_order_control]: 2.27999e-06 [assign_add_opt]: 1.47999e-06 [ForceFp32Comm]: 1.30001e-06 [remove_cast_before_assign_add]: 1.03001e-06 [full_micro_interleaved_order_control]: 2.48e-06 [reorder_send_recv_between_fp_bp]: 3.23e-06 [comm_op_add_attrs]: 1.09e-06 [add_comm_op_reuse_tag]: 9.89996e-07 [interleave_split_concat_branches]: 1.13001e-06 [interleave_parallel_branches]: 1.04e-06 [overlap_opt_shard_in_pipeline]: 5.478e-05 [overlap_opt_shard_grad_in_pipeline]: 1.82001e-06 [control_data_broadcast_order]: 3.188e-05 [grouped_pairwise_exchange_alltoall]: 1.88002e-06 [offloading_packed_experts]: 7.25e-06 [overlap_recompute_and_grad_model_parallel]: 8.25999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.34998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.35999e-06 [overlap_recompute_comm]: 2.37999e-06 [overlap_grad_ring_attention]: 7.05e-06 [overlap_grad_flash_sp]: 6.844e-05 [begin_end_overlap_inline]: 8.09989e-07 [split_matmul_comm_elemetwise]: 2.81999e-06 [split_layernorm_comm]: 1.99999e-06 [handle_group_info]: 1.51002e-06 [symbol_engine_optimizer]: 0.00016159, [1] [Cycle 1]: 0.00015473, [6] [build]: 1.694e-05 [elim_shapecalc]: 2.615e-05 [elim_not_effective]: 3.253e-05 [opt_reshape]: 1.645e-05 [fold_const_symbol]: 2.496e-05 [renormalize]: 2.69996e-07 [detach_backward]: 2.74999e-06 [pipeline_parallel_scheduler]: 1.92001e-06 [auto_monad_reorder]: 6.333e-05 [get_jit_bprop_graph]: 1.89e-06 [rewriter_after_jit_bprop_graph]: 7.25998e-06 [opt_after_jit_grad]: 0.00063301 [validate]: 8.211e-05 Sums bootstrap : 0.000645s : 0.31% type_inference : 0.190378s : 92.88% event_method : 0.000405s : 0.20% auto_monad : 0.000420s : 0.21% graph_reusing : 0.000035s : 0.02% inline : 0.000004s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000050s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000011s : 0.01% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000094s : 0.05% 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 : 0.000070s : 0.03% optimize.rewriter_before_opt_a : 0.000177s : 0.09% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000254s : 0.12% optimize.opt_a.loop_unroll : 0.000075s : 0.04% optimize.opt_a.a_1 : 0.002503s : 1.22% optimize.opt_a.with_stream_mark : 0.000110s : 0.05% optimize.opt_a.recompute_prepare : 0.000049s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000094s : 0.05% optimize.opt_a.updatestate_assign_eliminate : 0.000024s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000078s : 0.04% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000513s : 0.25% optimize.opt_a.accelerated_algorithm : 0.000065s : 0.03% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.01% optimize.opt_a.shard_inline : 0.000033s : 0.02% optimize.opt_a.merge_send_recv : 0.000032s : 0.02% optimize.opt_a.auto_parallel : 0.000035s : 0.02% optimize.opt_a.parallel : 0.000083s : 0.04% optimize.opt_a.flash_sp : 0.000032s : 0.02% optimize.opt_a.merge_comm : 0.000021s : 0.01% optimize.opt_a.allreduce_fusion : 0.000018s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000036s : 0.02% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000038s : 0.02% optimize.opt_a.virtual_dataset : 0.000428s : 0.21% optimize.opt_a.get_grad_eliminate_ : 0.000036s : 0.02% optimize.opt_a.virtual_output : 0.000032s : 0.02% optimize.opt_a.merge_forward : 0.000022s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000008s : 0.00% optimize.opt_a.offload_activation : 0.000044s : 0.02% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000077s : 0.04% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000056s : 0.03% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000021s : 0.01% optimize.opt_a.meta_fg_expand : 0.000017s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000011s : 0.01% optimize.opt_a.receive_attached : 0.000018s : 0.01% optimize.opt_a.after_resolve : 0.000049s : 0.02% optimize.opt_a.a_after_grad : 0.000052s : 0.03% optimize.opt_a.renormalize : 0.002918s : 1.42% optimize.opt_a.add_forward_monad_depend : 0.000014s : 0.01% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000108s : 0.05% optimize.opt_a.cse : 0.000270s : 0.13% optimize.opt_a.a_3 : 0.000239s : 0.12% optimize.py_interpret_to_execute_after_opt_a : 0.000029s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000213s : 0.10% optimize.convert_after_rewriter : 0.000016s : 0.01% optimize.order_py_execute_after_rewriter : 0.000011s : 0.01% optimize.mutable_eliminate : 0.000820s : 0.40% optimize.opt_b.b_1 : 0.000410s : 0.20% optimize.opt_b.b_2 : 0.000018s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000015s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000010s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000014s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000064s : 0.03% optimize.optimize_parallel_all_gather_comm : 0.000083s : 0.04% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000042s : 0.02% optimize.loop_unroll : 0.000619s : 0.30% optimize.opt_after_cconv.c_1 : 0.000115s : 0.06% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000009s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000012s : 0.01% optimize.opt_after_cconv.cse : 0.000052s : 0.03% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000064s : 0.03% optimize.tuple_transform.d_1 : 0.000111s : 0.05% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000017s : 0.01% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000125s : 0.06% optimize.cse_after_recomputation.cse : 0.000041s : 0.02% optimize.environ_conv : 0.000016s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000012s : 0.01% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000002s : 0.00% optimize.assign_add_opt : 0.000001s : 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 : 0.000055s : 0.03% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000032s : 0.02% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000007s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000008s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 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 : 0.000007s : 0.00% optimize.overlap_grad_flash_sp : 0.000068s : 0.03% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000002s : 0.00% optimize.symbol_engine_optimizer.build : 0.000017s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000026s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000033s : 0.02% optimize.symbol_engine_optimizer.opt_reshape : 0.000016s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000025s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000063s : 0.03% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000633s : 0.31% validate : 0.000082s : 0.04% Time group info: ------[substitution.] 0.000661 165 1.77% : 0.000012s : 2: substitution.depend_value_elim 0.63% : 0.000004s : 9: substitution.elim_not_effective 0.50% : 0.000003s : 9: substitution.fold_const_symbol 1.71% : 0.000011s : 12: substitution.graph_param_transform 62.49% : 0.000413s : 11: substitution.inline 1.49% : 0.000010s : 18: substitution.j_node_and_user_rematch 3.38% : 0.000022s : 4: substitution.less_batch_normalization 1.27% : 0.000008s : 12: substitution.load_eliminater 2.36% : 0.000016s : 18: substitution.remove_not_recompute_node 1.46% : 0.000010s : 6: substitution.replace_old_param 1.98% : 0.000013s : 2: substitution.switch_simplify 5.43% : 0.000036s : 30: substitution.updatestate_pure_node_eliminater 15.54% : 0.000103s : 32: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.190278 2 98.72% : 0.187840s : 1: type_inference.infer 1.28% : 0.002438s : 1: type_inference.specialize ------[replace.] 0.000168 13 59.16% : 0.000100s : 11: replace.inline 40.84% : 0.000069s : 2: replace.switch_simplify ------[match.] 0.000416 13 97.30% : 0.000405s : 11: match.inline 2.70% : 0.000011s : 2: match.switch_simplify ------[predicate.] 0.000690 4059 1.12% : 0.000008s : 49: predicate.accumulaten_eliminater 0.52% : 0.000004s : 12: predicate.ad_related_special_op_eliminate 0.48% : 0.000003s : 24: predicate.addn_check_dump 1.06% : 0.000007s : 49: predicate.addn_zero_filter 1.02% : 0.000007s : 49: predicate.adjust_all_reduce_mul_add 2.12% : 0.000015s : 73: predicate.arithmetic_simplify 1.06% : 0.000007s : 49: predicate.cast_eliminate 0.61% : 0.000004s : 24: predicate.check_bprop_eliminate 0.56% : 0.000004s : 24: predicate.compare_switch_simplify 0.14% : 0.000001s : 12: predicate.const_output_eliminate 0.52% : 0.000004s : 24: predicate.depend_value_elim 1.13% : 0.000008s : 49: predicate.dict_get_item_const_eliminator 1.18% : 0.000008s : 49: predicate.dict_get_item_eliminator 1.07% : 0.000007s : 49: predicate.dict_set_item_eliminator 0.67% : 0.000005s : 24: predicate.dumpgradient_eliminate 0.18% : 0.000001s : 12: predicate.elim_not_effective 0.41% : 0.000003s : 12: predicate.elim_shapecalc_of_broadcastargs 1.29% : 0.000009s : 61: predicate.environ_add_const_eliminate 1.22% : 0.000008s : 61: predicate.environ_get_add_eliminate 1.24% : 0.000009s : 61: predicate.environ_get_depend_swap 1.81% : 0.000013s : 85: predicate.environ_get_eliminate 1.26% : 0.000009s : 61: predicate.environ_get_set_eliminate 1.28% : 0.000009s : 60: predicate.exchange_switch_depend_value 1.85% : 0.000013s : 60: predicate.float_depend_g_call 0.51% : 0.000004s : 24: predicate.float_environ_get_switch 0.75% : 0.000005s : 36: predicate.float_tuple_getitem_switch 0.13% : 0.000001s : 12: predicate.fold_const_symbol 0.68% : 0.000005s : 24: predicate.get_grad_eliminate 0.18% : 0.000001s : 12: predicate.graph_param_transform 0.50% : 0.000003s : 24: predicate.incorporate_call 0.48% : 0.000003s : 24: predicate.incorporate_call_switch 5.38% : 0.000037s : 181: predicate.inline 0.68% : 0.000005s : 24: predicate.inline_without_move 0.27% : 0.000002s : 24: predicate.j_node_and_user_rematch 0.85% : 0.000006s : 24: predicate.less_batch_normalization 1.64% : 0.000011s : 73: predicate.list_to_tuple_eliminator_ 2.74% : 0.000019s : 122: predicate.load_eliminater 0.80% : 0.000006s : 12: predicate.loop_unroll_after_grad 1.60% : 0.000011s : 78: predicate.loop_unroll_before_grad 1.68% : 0.000012s : 73: predicate.make_slice_get_slice_eliminator 0.57% : 0.000004s : 24: predicate.merge_addn 0.53% : 0.000004s : 24: predicate.micro_step_allgather_replace 0.53% : 0.000004s : 24: predicate.mini_step_allgather_replace 0.99% : 0.000007s : 49: predicate.minmaximum_grad 0.78% : 0.000005s : 12: predicate.mutable_eliminate 0.31% : 0.000002s : 12: predicate.opt_reshape 0.42% : 0.000003s : 12: predicate.parallel_virtual_node 1.76% : 0.000012s : 60: predicate.partial_defer_inline 1.39% : 0.000010s : 61: predicate.partial_eliminate 1.12% : 0.000008s : 49: predicate.print_const_string_wrapper 4.58% : 0.000032s : 24: predicate.reduce_all_const_elim 1.33% : 0.000009s : 49: predicate.reduce_eliminate 2.60% : 0.000018s : 122: predicate.redundant_stop_gradient_eliminater 0.42% : 0.000003s : 24: predicate.remove_not_recompute_node 1.07% : 0.000007s : 73: predicate.replace_applicator 0.35% : 0.000002s : 24: predicate.replace_old_param 0.17% : 0.000001s : 12: predicate.reset_defer_inline 1.06% : 0.000007s : 49: predicate.reshape_eliminate 0.57% : 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 0.41% : 0.000003s : 32: predicate.set_cell_output_no_recompute 0.67% : 0.000005s : 24: predicate.shard_identity_eliminate 0.58% : 0.000004s : 24: predicate.special_op_eliminate 0.67% : 0.000005s : 24: predicate.specialize_transform 0.77% : 0.000005s : 24: predicate.split_environ_get_set_with_tuple_value 0.71% : 0.000005s : 24: predicate.stack_unstack_eliminate 0.30% : 0.000002s : 12: predicate.switch_call_monad_eliminater 1.56% : 0.000011s : 60: predicate.switch_defer_inline 1.91% : 0.000013s : 84: predicate.switch_layer_defer_inline 4.28% : 0.000030s : 178: predicate.switch_simplify 1.07% : 0.000007s : 49: predicate.tile_eliminate 1.06% : 0.000007s : 49: predicate.transpose_eliminate 1.75% : 0.000012s : 73: predicate.tuple_list_convert_item_index_to_positive 1.76% : 0.000012s : 73: predicate.tuple_list_get_item_const_eliminator 1.63% : 0.000011s : 73: predicate.tuple_list_get_item_depend_reorder 2.55% : 0.000018s : 97: predicate.tuple_list_get_item_eliminator 1.66% : 0.000011s : 73: predicate.tuple_list_get_set_item_eliminator 2.28% : 0.000016s : 97: predicate.tuple_list_set_item_eliminator 1.53% : 0.000011s : 73: predicate.tuple_to_list_eliminator_ 2.75% : 0.000019s : 122: predicate.updatestate_pure_node_eliminater 3.42% : 0.000024s : 146: predicate.updatestate_useless_node_eliminater 0.33% : 0.000002s : 12: predicate.value_based_eliminate 0.93% : 0.000006s : 24: predicate.virtual_dataset_eliminate 0.56% : 0.000004s : 24: predicate.virtual_output_eliminate 0.30% : 0.000002s : 12: predicate.virtual_view_grad_eliminate 0.31% : 0.000002s : 12: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001397 18 41.85% : 0.000585s : 5: func_graph_cloner_run.FuncGraphClonerGraph 58.15% : 0.000813s : 13: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.328378 192 0.00% : 0.000004s : 1: ForceFp32Comm 1.61% : 0.005290s : 1: add_attr 1.60% : 0.005238s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.04% : 0.000131s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 27.59% : 0.090589s : 1: auto_monad 0.02% : 0.000070s : 1: auto_monad_reorder 0.02% : 0.000053s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.21% : 0.000675s : 1: bootstrap 0.01% : 0.000047s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.01% : 0.000036s : 1: control_data_broadcast_order 0.01% : 0.000020s : 1: convert_after_rewriter 0.02% : 0.000058s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.01% : 0.000020s : 1: environ_conv 0.13% : 0.000425s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.01% : 0.000044s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000009s : 1: inline 0.00% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000009s : 1: label_micro_interleaved_index 0.19% : 0.000636s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.25% : 0.000837s : 1: mutable_eliminate 0.00% : 0.000010s : 1: offloading_packed_experts 0.01% : 0.000033s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000035s : 1: opt.transform.mutable_eliminate 1.33% : 0.004369s : 78: opt.transform.opt_a 0.03% : 0.000112s : 1: opt.transform.opt_after_cconv 0.02% : 0.000056s : 1: opt.transform.opt_after_jit_grad 0.12% : 0.000394s : 28: opt.transform.opt_b 0.04% : 0.000125s : 2: opt.transform.opt_trans_graph 0.03% : 0.000096s : 4: opt.transform.symbol_engine_opt 2.82% : 0.009247s : 1: opt_a 0.08% : 0.000264s : 1: opt_after_cconv 0.20% : 0.000649s : 1: opt_after_jit_grad 0.18% : 0.000601s : 1: opt_b 4.08% : 0.013397s : 1: optimize 0.03% : 0.000090s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.02% : 0.000075s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000012s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.02% : 0.000060s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000011s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.03% : 0.000101s : 1: pre_auto_parallel 0.02% : 0.000076s : 1: py_interpret_to_execute 0.01% : 0.000033s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.02% : 0.000069s : 1: remove_dup_value 0.49% : 0.001602s : 1: renormalize.infer 0.40% : 0.001300s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.07% : 0.000222s : 1: rewriter_after_opt_a 0.06% : 0.000184s : 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% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000008s : 1: split_matmul_comm_elemetwise 0.00% : 0.000016s : 1: swap_dp_allreduce_reducescatter 0.05% : 0.000165s : 1: symbol_engine_optimizer 0.05% : 0.000165s : 1: tuple_transform 57.99% : 0.190412s : 1: type_inference . [hook] pytest_runtest_teardown:test_mint_optim_fused_adamw_basic_group[0] tests/st/mint/optim/test_fused_adamw.py::test_mint_optim_fused_adamw_basic_group[0],max_mem:20.0M [WARNING] ME(162276:281473716752176,MainProcess):2026-01-29-17:44:54.159.067 [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(162276,ffffb4e68f30,python3.9):2026-01-29-17:44:56.339.821 [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 = 2.65436, [30] [bootstrap]: 0.00047669 [type_inference]: 2.17792 [event_method]: 0.00035983 [auto_monad]: 0.00238779 [graph_reusing]: 0.00013562 [pre_auto_parallel]: 2.508e-05 [py_interpret_to_execute]: 0.0007528 [rewriter_before_opt_a]: 0.0415358 [expand_dump_flag]: 4.988e-05 [jit_opt_a]: 0.412047, [4] [Cycle 1]: 0.334632, [27] [switch_simplify]: 0.00148851 [loop_unroll]: 0.00064902 [a_1]: 0.0835077 [with_stream_mark]: 0.0002453 [recompute_prepare]: 0.00014914 [updatestate_depend_eliminate]: 0.00077244 [updatestate_assign_eliminate]: 6.431e-05 [updatestate_loads_eliminate]: 0.00013497 [parameter_eliminate]: 5.89e-06 [specialize_transform]: 8.686e-05 [updatestate_useless_node_eliminater]: 0.00010678 [accelerated_algorithm]: 0.00015832 [meta_shard_fg_expand]: 3.916e-05 [get_grad_eliminate_]: 6.999e-05 [merge_forward]: 3.848e-05 [cell_reuse_recompute_pass]: 2.77002e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00013726 [j_node_and_user_rematch]: 0.00012417 [meta_fg_expand]: 0.0642636 [replace_old_param]: 0.00040417 [inline_without_move]: 0.00044592 [renormalize]: 0.138427 [add_forward_monad_depend]: 8.036e-05 [auto_monad_grad]: 3.894e-05 [auto_monad_eliminator]: 0.00053728 [cse]: 0.0413384 [replace_applicator]: 0.00076781 [Cycle 2]: 0.0630855, [27] [switch_simplify]: 0.00033461 [loop_unroll]: 0.00032728 [a_1]: 0.0102154 [with_stream_mark]: 0.0002257 [recompute_prepare]: 7.672e-05 [updatestate_depend_eliminate]: 0.00010251 [updatestate_assign_eliminate]: 4.107e-05 [updatestate_loads_eliminate]: 0.00011601 [parameter_eliminate]: 3.18e-06 [specialize_transform]: 6.116e-05 [updatestate_useless_node_eliminater]: 8.316e-05 [accelerated_algorithm]: 6.452e-05 [meta_shard_fg_expand]: 2.748e-05 [get_grad_eliminate_]: 5.165e-05 [merge_forward]: 3.028e-05 [cell_reuse_recompute_pass]: 2.50002e-06 [cell_reuse_handle_not_recompute_node_pass]: 9.651e-05 [j_node_and_user_rematch]: 8.47e-05 [meta_fg_expand]: 0.00116018 [replace_old_param]: 9.594e-05 [inline_without_move]: 5.487e-05 [renormalize]: 0.0488652 [add_forward_monad_depend]: 1.661e-05 [auto_monad_grad]: 3.75e-06 [auto_monad_eliminator]: 0.00028139 [cse]: 0.00023933 [replace_applicator]: 8.254e-05 [Cycle 3]: 0.00640402, [27] [switch_simplify]: 4.951e-05 [loop_unroll]: 5.062e-05 [a_1]: 0.00162348 [with_stream_mark]: 5.723e-05 [recompute_prepare]: 5.52e-05 [updatestate_depend_eliminate]: 3.664e-05 [updatestate_assign_eliminate]: 3.35e-05 [updatestate_loads_eliminate]: 3.743e-05 [parameter_eliminate]: 3.51999e-06 [specialize_transform]: 5.339e-05 [updatestate_useless_node_eliminater]: 7.402e-05 [accelerated_algorithm]: 6.382e-05 [meta_shard_fg_expand]: 2.097e-05 [get_grad_eliminate_]: 4.502e-05 [merge_forward]: 2.787e-05 [cell_reuse_recompute_pass]: 6.23e-06 [cell_reuse_handle_not_recompute_node_pass]: 8.868e-05 [j_node_and_user_rematch]: 8.33e-05 [meta_fg_expand]: 1.965e-05 [replace_old_param]: 6.949e-05 [inline_without_move]: 4.892e-05 [renormalize]: 0.00321399 [add_forward_monad_depend]: 1.105e-05 [auto_monad_grad]: 2.44999e-06 [auto_monad_eliminator]: 0.00012959 [cse]: 0.00019511 [replace_applicator]: 6.917e-05 [Cycle 4]: 0.00293733, [27] [switch_simplify]: 4.804e-05 [loop_unroll]: 4.924e-05 [a_1]: 0.00151783 [with_stream_mark]: 5.285e-05 [recompute_prepare]: 5.041e-05 [updatestate_depend_eliminate]: 3.649e-05 [updatestate_assign_eliminate]: 3.067e-05 [updatestate_loads_eliminate]: 3.348e-05 [parameter_eliminate]: 2.42001e-06 [specialize_transform]: 5.011e-05 [updatestate_useless_node_eliminater]: 6.956e-05 [accelerated_algorithm]: 5.775e-05 [meta_shard_fg_expand]: 1.872e-05 [get_grad_eliminate_]: 7.914e-05 [merge_forward]: 3.047e-05 [cell_reuse_recompute_pass]: 4.68999e-06 [cell_reuse_handle_not_recompute_node_pass]: 9.403e-05 [j_node_and_user_rematch]: 8.814e-05 [meta_fg_expand]: 2.171e-05 [replace_old_param]: 6.674e-05 [inline_without_move]: 4.727e-05 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 3.66001e-06 [auto_monad_grad]: 2.31e-06 [auto_monad_eliminator]: 0.00010375 [cse]: 0.00014905 [replace_applicator]: 4.92e-05 [py_interpret_to_execute_after_opt_a]: 5.94e-05 [rewriter_after_opt_a]: 0.00035301 [convert_after_rewriter]: 3.927e-05 [order_py_execute_after_rewriter]: 2.741e-05 [mutable_eliminate]: 0.00084125 [jit_opt_b]: 0.012446, [1] [Cycle 1]: 0.0124219, [2] [frontend_op_eliminate]: 0.00015559 [inline_after_opt_a]: 0.00013778 [cconv]: 0.0001122 [loop_unroll]: 0.00086422 [jit_opt_after_cconv]: 0.00093797, [1] [Cycle 1]: 0.00092616, [11] [c_1]: 0.00033075 [parameter_eliminate]: 7.56001e-06 [updatestate_depend_eliminate]: 5.119e-05 [updatestate_assign_eliminate]: 3.505e-05 [updatestate_loads_eliminate]: 3.541e-05 [cse]: 0.00018254 [call_graph_tuple_transform]: 0.0001181 [tuple_list_get_item_eliminator]: 4.717e-05 [none_parameter_eliminate]: 1.99e-06 [renormalize]: 6.50005e-07 [switch_simplify]: 4.854e-05 [remove_dup_value]: 0.00015878 [partial_unused_args_eliminate]: 2.75002e-06 [environ_conv]: 3.954e-05 [add_recomputation]: 0.00028072 [cse_after_recomputation]: 0.00014687, [1] [Cycle 1]: 0.0001373, [1] [cse]: 0.00012463 [auto_monad_reorder]: 0.00015042 [get_jit_bprop_graph]: 2.49001e-06 [rewriter_after_jit_bprop_graph]: 0.00035931 [opt_after_jit_grad]: 0.00087166 [symbol_engine_optimizer]: 0.00034214, [1] [Cycle 1]: 0.00033325, [6] [build]: 3.101e-05 [elim_shapecalc]: 5.656e-05 [elim_not_effective]: 8.51e-05 [opt_reshape]: 4.823e-05 [fold_const_symbol]: 7.608e-05 [renormalize]: 7.50006e-07 [validate]: 0.00017041 Sums bootstrap : 0.000477s : 0.02% type_inference : 2.177923s : 82.64% event_method : 0.000360s : 0.01% auto_monad : 0.002388s : 0.09% graph_reusing : 0.000136s : 0.01% pre_auto_parallel : 0.000025s : 0.00% py_interpret_to_execute : 0.000753s : 0.03% rewriter_before_opt_a : 0.041536s : 1.58% expand_dump_flag : 0.000050s : 0.00% jit_opt_a.switch_simplify : 0.001921s : 0.07% jit_opt_a.loop_unroll : 0.001076s : 0.04% jit_opt_a.a_1 : 0.096864s : 3.68% jit_opt_a.with_stream_mark : 0.000581s : 0.02% jit_opt_a.recompute_prepare : 0.000331s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000948s : 0.04% jit_opt_a.updatestate_assign_eliminate : 0.000170s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000322s : 0.01% jit_opt_a.parameter_eliminate : 0.000015s : 0.00% jit_opt_a.specialize_transform : 0.000252s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000334s : 0.01% jit_opt_a.accelerated_algorithm : 0.000344s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000106s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000246s : 0.01% jit_opt_a.merge_forward : 0.000127s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000016s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000416s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000380s : 0.01% jit_opt_a.meta_fg_expand : 0.065465s : 2.48% jit_opt_a.replace_old_param : 0.000636s : 0.02% jit_opt_a.inline_without_move : 0.000597s : 0.02% jit_opt_a.renormalize : 0.190506s : 7.23% jit_opt_a.add_forward_monad_depend : 0.000112s : 0.00% jit_opt_a.auto_monad_grad : 0.000047s : 0.00% jit_opt_a.auto_monad_eliminator : 0.001052s : 0.04% jit_opt_a.cse : 0.041922s : 1.59% jit_opt_a.replace_applicator : 0.000969s : 0.04% py_interpret_to_execute_after_opt_a : 0.000059s : 0.00% rewriter_after_opt_a : 0.000353s : 0.01% convert_after_rewriter : 0.000039s : 0.00% order_py_execute_after_rewriter : 0.000027s : 0.00% mutable_eliminate : 0.000841s : 0.03% jit_opt_b.frontend_op_eliminate : 0.000156s : 0.01% jit_opt_b.inline_after_opt_a : 0.000138s : 0.01% cconv : 0.000112s : 0.00% loop_unroll : 0.000864s : 0.03% jit_opt_after_cconv.c_1 : 0.000331s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000051s : 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 : 0.000183s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000118s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000047s : 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 : 0.000049s : 0.00% remove_dup_value : 0.000159s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000040s : 0.00% add_recomputation : 0.000281s : 0.01% cse_after_recomputation.cse : 0.000125s : 0.00% auto_monad_reorder : 0.000150s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000359s : 0.01% opt_after_jit_grad : 0.000872s : 0.03% symbol_engine_optimizer.build : 0.000031s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000057s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000085s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000048s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000076s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000170s : 0.01% Time group info: ------[substitution.] 0.046925 1744 0.21% : 0.000097s : 5: substitution.arithmetic_simplify 0.10% : 0.000049s : 4: substitution.cast_eliminate 0.29% : 0.000138s : 63: substitution.depend_value_elim 0.02% : 0.000011s : 32: substitution.elim_not_effective 0.03% : 0.000013s : 6: substitution.environ_get_add_eliminate 0.02% : 0.000009s : 4: substitution.environ_get_depend_swap 0.03% : 0.000012s : 6: substitution.environ_get_eliminate 0.05% : 0.000025s : 6: substitution.environ_get_set_eliminate 0.02% : 0.000011s : 32: substitution.fold_const_symbol 3.20% : 0.001500s : 8: substitution.getattr_setattr_resolve 0.06% : 0.000029s : 45: substitution.graph_param_transform 90.54% : 0.042487s : 157: substitution.inline 0.30% : 0.000138s : 12: substitution.inline_without_move 0.13% : 0.000060s : 147: substitution.j_node_and_user_rematch 0.15% : 0.000072s : 15: substitution.less_batch_normalization 0.08% : 0.000040s : 44: substitution.load_eliminater 0.27% : 0.000128s : 95: substitution.minmaximum_grad 0.08% : 0.000038s : 12: substitution.partial_eliminate 0.06% : 0.000026s : 6: substitution.reduce_eliminate 0.01% : 0.000007s : 5: substitution.redundant_stop_gradient_eliminater 0.18% : 0.000085s : 147: substitution.remove_not_recompute_node 0.42% : 0.000195s : 55: substitution.replace_applicator 0.13% : 0.000059s : 84: substitution.replace_old_param 0.02% : 0.000007s : 1: substitution.reshape_eliminate 0.02% : 0.000007s : 1: substitution.set_cell_output_no_recompute 0.02% : 0.000008s : 5: substitution.split_environ_get_set_with_tuple_value 0.15% : 0.000072s : 29: substitution.switch_simplify 0.01% : 0.000006s : 1: substitution.tile_eliminate 0.57% : 0.000269s : 103: substitution.tuple_list_convert_item_index_to_positive 0.67% : 0.000315s : 114: substitution.tuple_list_get_item_depend_reorder 1.02% : 0.000478s : 190: substitution.tuple_list_get_item_eliminator 0.38% : 0.000176s : 139: substitution.updatestate_pure_node_eliminater 0.76% : 0.000357s : 171: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.176926 2 93.35% : 2.032087s : 1: type_inference.infer 6.65% : 0.144839s : 1: type_inference.specialize ------[replace.] 0.003663 301 0.26% : 0.000010s : 1: replace.arithmetic_simplify 1.90% : 0.000070s : 4: replace.cast_eliminate 1.77% : 0.000065s : 8: replace.depend_value_elim 0.82% : 0.000030s : 2: replace.environ_get_set_eliminate 3.46% : 0.000127s : 6: replace.getattr_setattr_resolve 43.96% : 0.001610s : 157: replace.inline 0.94% : 0.000034s : 2: replace.partial_eliminate 2.89% : 0.000106s : 3: replace.replace_applicator 13.22% : 0.000484s : 29: replace.switch_simplify 3.81% : 0.000140s : 11: replace.tuple_list_get_item_depend_reorder 26.39% : 0.000967s : 76: replace.tuple_list_get_item_eliminator 0.58% : 0.000021s : 2: replace.updatestate_useless_node_eliminater ------[match.] 0.044371 301 0.11% : 0.000047s : 1: match.arithmetic_simplify 0.10% : 0.000045s : 4: match.cast_eliminate 0.02% : 0.000007s : 8: match.depend_value_elim 0.04% : 0.000017s : 2: match.environ_get_set_eliminate 3.18% : 0.001410s : 6: match.getattr_setattr_resolve 95.52% : 0.042383s : 157: match.inline 0.05% : 0.000021s : 2: match.partial_eliminate 0.08% : 0.000036s : 3: match.replace_applicator 0.13% : 0.000058s : 29: match.switch_simplify 0.30% : 0.000133s : 11: match.tuple_list_get_item_depend_reorder 0.45% : 0.000199s : 76: match.tuple_list_get_item_eliminator 0.03% : 0.000015s : 2: match.updatestate_useless_node_eliminater ------[predicate.] 0.005680 37536 1.57% : 0.000089s : 664: predicate.accumulaten_eliminater 0.21% : 0.000012s : 45: predicate.ad_related_special_op_eliminate 1.57% : 0.000089s : 664: predicate.addn_check_dump 1.61% : 0.000092s : 664: predicate.addn_zero_filter 2.09% : 0.000119s : 665: predicate.arithmetic_simplify 1.65% : 0.000094s : 669: predicate.cast_eliminate 0.13% : 0.000007s : 45: predicate.check_bprop_eliminate 1.57% : 0.000089s : 664: predicate.compare_switch_simplify 1.71% : 0.000097s : 664: predicate.depend_value_elim 1.58% : 0.000090s : 671: predicate.dict_get_item_const_eliminator 1.58% : 0.000090s : 671: predicate.dict_get_item_eliminator 1.60% : 0.000091s : 671: predicate.dict_set_item_eliminator 0.14% : 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 1.57% : 0.000089s : 669: predicate.environ_add_const_eliminate 1.58% : 0.000090s : 671: predicate.environ_get_add_eliminate 1.60% : 0.000091s : 669: predicate.environ_get_depend_swap 1.62% : 0.000092s : 671: predicate.environ_get_eliminate 1.64% : 0.000093s : 671: predicate.environ_get_set_eliminate 0.06% : 0.000003s : 45: predicate.fold_const_symbol 0.55% : 0.000031s : 206: predicate.get_grad_eliminate 0.24% : 0.000014s : 40: predicate.getattr_setattr_resolve 0.06% : 0.000003s : 45: predicate.graph_param_transform 4.30% : 0.000244s : 1009: predicate.inline 1.34% : 0.000076s : 412: predicate.inline_without_move 0.27% : 0.000016s : 206: predicate.j_node_and_user_rematch 0.68% : 0.000039s : 222: predicate.less_batch_normalization 1.83% : 0.000104s : 758: predicate.list_to_tuple_eliminator_ 2.06% : 0.000117s : 805: predicate.load_eliminater 0.22% : 0.000013s : 45: predicate.loop_unroll_after_grad 3.37% : 0.000191s : 1113: predicate.loop_unroll_before_grad 1.78% : 0.000101s : 727: predicate.make_slice_get_slice_eliminator 1.61% : 0.000091s : 664: predicate.merge_addn 1.66% : 0.000094s : 665: predicate.minmaximum_grad 0.20% : 0.000011s : 45: predicate.mutable_eliminate 0.11% : 0.000006s : 45: predicate.opt_reshape 2.40% : 0.000137s : 805: predicate.partial_eliminate 1.59% : 0.000090s : 656: predicate.print_const_string_wrapper 1.98% : 0.000112s : 665: predicate.reduce_eliminate 1.93% : 0.000110s : 760: predicate.redundant_stop_gradient_eliminater 0.29% : 0.000016s : 206: predicate.remove_not_recompute_node 2.12% : 0.000120s : 1250: predicate.replace_applicator 0.57% : 0.000032s : 412: predicate.replace_old_param 0.07% : 0.000004s : 45: predicate.reset_defer_inline 1.60% : 0.000091s : 665: predicate.reshape_eliminate 1.61% : 0.000092s : 656: predicate.row_tensor_add_zeros_like 0.14% : 0.000008s : 45: predicate.row_tensor_eliminate 1.60% : 0.000091s : 656: predicate.same_eliminate 0.37% : 0.000021s : 259: predicate.set_cell_output_no_recompute 0.23% : 0.000013s : 90: predicate.special_op_eliminate 0.60% : 0.000034s : 206: predicate.specialize_transform 1.81% : 0.000103s : 656: predicate.split_environ_get_set_with_tuple_value 1.57% : 0.000089s : 656: predicate.stack_unstack_eliminate 0.12% : 0.000007s : 45: predicate.switch_call_monad_eliminater 3.81% : 0.000216s : 919: predicate.switch_defer_inline 2.54% : 0.000144s : 919: predicate.switch_layer_defer_inline 6.39% : 0.000363s : 2135: predicate.switch_simplify 1.65% : 0.000094s : 665: predicate.tile_eliminate 1.64% : 0.000093s : 665: predicate.transpose_eliminate 1.99% : 0.000113s : 671: predicate.tuple_list_convert_item_index_to_positive 1.93% : 0.000109s : 682: predicate.tuple_list_get_item_depend_reorder 2.92% : 0.000166s : 848: predicate.tuple_list_get_item_eliminator 1.98% : 0.000112s : 682: predicate.tuple_list_set_item_eliminator 1.89% : 0.000107s : 758: predicate.tuple_to_list_eliminator_ 2.06% : 0.000117s : 805: predicate.updatestate_pure_node_eliminater 2.86% : 0.000163s : 1013: predicate.updatestate_useless_node_eliminater 1.94% : 0.000110s : 656: predicate.value_based_eliminate 0.11% : 0.000006s : 45: predicate.virtual_view_grad_eliminate 0.15% : 0.000008s : 45: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.106573 395 90.44% : 0.096383s : 204: func_graph_cloner_run.FuncGraphClonerGraph 0.18% : 0.000190s : 3: func_graph_cloner_run.FuncGraphClonerNode 9.38% : 0.010000s : 188: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.951881 106 0.01% : 0.000285s : 1: add_recomputation 0.08% : 0.002406s : 1: auto_monad 0.01% : 0.000155s : 1: auto_monad_reorder 0.02% : 0.000504s : 1: bootstrap 0.00% : 0.000120s : 1: cconv 0.00% : 0.000043s : 1: convert_after_rewriter 0.01% : 0.000150s : 1: cse_after_recomputation 0.00% : 0.000042s : 1: environ_conv 0.01% : 0.000369s : 1: event_method 0.00% : 0.000055s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000142s : 1: graph_reusing 13.96% : 0.412052s : 1: jit_opt_a 0.03% : 0.000942s : 1: jit_opt_after_cconv 0.42% : 0.012456s : 1: jit_opt_b 0.03% : 0.000876s : 1: loop_unroll 0.03% : 0.000854s : 1: mutable_eliminate 3.53% : 0.104245s : 52: opt.transform.jit_opt_a 0.02% : 0.000539s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000284s : 4: opt.transform.jit_opt_b 0.00% : 0.000083s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000073s : 1: opt.transform.mutable_eliminate 0.01% : 0.000219s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.001754s : 4: opt.transform.opt_resolve 0.01% : 0.000262s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000884s : 1: opt_after_jit_grad 0.00% : 0.000030s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000028s : 1: pre_auto_parallel 0.03% : 0.000766s : 1: py_interpret_to_execute 0.00% : 0.000063s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000163s : 1: remove_dup_value 3.91% : 0.115324s : 3: renormalize.infer 2.55% : 0.075126s : 3: renormalize.specialize 0.01% : 0.000365s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000359s : 1: rewriter_after_opt_a 1.41% : 0.041561s : 1: rewriter_before_opt_a 0.01% : 0.000345s : 1: symbol_engine_optimizer 73.78% : 2.177947s : 1: type_inference . [hook] pytest_runtest_teardown:test_mint_optim_fused_adamw_basic_group[1] tests/st/mint/optim/test_fused_adamw.py::test_mint_optim_fused_adamw_basic_group[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_basic_group[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 489.64s (0:08:09) ==================