[WARNING] ME(158082:281473404772144,MainProcess):2026-01-29-17:37:23.585.306 [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_003/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 1 item test_fused_adamw.py ...............[WARNING] ANALYZER(158082,ffffa24e1f30,python3.9):2026-01-29-17:44:10.342.701 [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_42:_{[0]: ValueNode 151__tuple_getitem_by_number_43, [1]: CNode_44, [2]: ValueNode 1} TotalTime = 53.4289, [30] [bootstrap]: 0.0010253 [type_inference]: 52.7294 [event_method]: 0.00039421 [auto_monad]: 0.00260439 [graph_reusing]: 0.00014707 [pre_auto_parallel]: 4.438e-05 [py_interpret_to_execute]: 0.00059535 [rewriter_before_opt_a]: 0.00462026 [expand_dump_flag]: 0.0640963 [jit_opt_a]: 0.61919, [4] [Cycle 1]: 0.515703, [27] [switch_simplify]: 0.00178354 [loop_unroll]: 0.00065124 [a_1]: 0.0801042 [with_stream_mark]: 0.00020746 [recompute_prepare]: 0.0001212 [updatestate_depend_eliminate]: 0.00057083 [updatestate_assign_eliminate]: 5.719e-05 [updatestate_loads_eliminate]: 0.00012367 [parameter_eliminate]: 5.22e-06 [specialize_transform]: 7.888e-05 [updatestate_useless_node_eliminater]: 9.963e-05 [accelerated_algorithm]: 0.00018992 [meta_shard_fg_expand]: 3.929e-05 [get_grad_eliminate_]: 6.397e-05 [merge_forward]: 3.878e-05 [cell_reuse_recompute_pass]: 2.46e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00012842 [j_node_and_user_rematch]: 0.00012955 [meta_fg_expand]: 0.153481 [replace_old_param]: 0.00038733 [inline_without_move]: 0.00039065 [renormalize]: 0.273595 [add_forward_monad_depend]: 0.00013712 [auto_monad_grad]: 4.969e-05 [auto_monad_eliminator]: 0.00083091 [cse]: 0.00114725 [replace_applicator]: 0.00073134 [Cycle 2]: 0.0858421, [27] [switch_simplify]: 0.00035745 [loop_unroll]: 0.00038348 [a_1]: 0.0591037 [with_stream_mark]: 0.00032264 [recompute_prepare]: 8.529e-05 [updatestate_depend_eliminate]: 0.00011171 [updatestate_assign_eliminate]: 4.054e-05 [updatestate_loads_eliminate]: 0.0001234 [parameter_eliminate]: 3.41001e-06 [specialize_transform]: 6.363e-05 [updatestate_useless_node_eliminater]: 8.282e-05 [accelerated_algorithm]: 6.161e-05 [meta_shard_fg_expand]: 2.758e-05 [get_grad_eliminate_]: 5.112e-05 [merge_forward]: 3.314e-05 [cell_reuse_recompute_pass]: 2.56e-06 [cell_reuse_handle_not_recompute_node_pass]: 0.00010389 [j_node_and_user_rematch]: 8.725e-05 [meta_fg_expand]: 0.0011464 [replace_old_param]: 0.00010621 [inline_without_move]: 5.344e-05 [renormalize]: 0.0225298 [add_forward_monad_depend]: 1.396e-05 [auto_monad_grad]: 3.53e-06 [auto_monad_eliminator]: 0.00019462 [cse]: 0.00022863 [replace_applicator]: 7.626e-05 [Cycle 3]: 0.00700243, [27] [switch_simplify]: 4.952e-05 [loop_unroll]: 4.623e-05 [a_1]: 0.00157352 [with_stream_mark]: 5.697e-05 [recompute_prepare]: 5.665e-05 [updatestate_depend_eliminate]: 3.37e-05 [updatestate_assign_eliminate]: 3.449e-05 [updatestate_loads_eliminate]: 3.452e-05 [parameter_eliminate]: 3.06999e-06 [specialize_transform]: 5.06e-05 [updatestate_useless_node_eliminater]: 7.466e-05 [accelerated_algorithm]: 5.768e-05 [meta_shard_fg_expand]: 1.33e-05 [get_grad_eliminate_]: 4.59e-05 [merge_forward]: 3.031e-05 [cell_reuse_recompute_pass]: 3.76001e-06 [cell_reuse_handle_not_recompute_node_pass]: 9.34e-05 [j_node_and_user_rematch]: 8.151e-05 [meta_fg_expand]: 1.924e-05 [replace_old_param]: 6.35e-05 [inline_without_move]: 5.401e-05 [renormalize]: 0.00368591 [add_forward_monad_depend]: 1.282e-05 [auto_monad_grad]: 3.41999e-06 [auto_monad_eliminator]: 0.00019947 [cse]: 0.00020666 [replace_applicator]: 7.018e-05 [Cycle 4]: 0.00289583, [27] [switch_simplify]: 4.849e-05 [loop_unroll]: 4.505e-05 [a_1]: 0.00146794 [with_stream_mark]: 5.343e-05 [recompute_prepare]: 5.648e-05 [updatestate_depend_eliminate]: 3.206e-05 [updatestate_assign_eliminate]: 3.348e-05 [updatestate_loads_eliminate]: 3.224e-05 [parameter_eliminate]: 2.56e-06 [specialize_transform]: 4.991e-05 [updatestate_useless_node_eliminater]: 6.978e-05 [accelerated_algorithm]: 5.753e-05 [meta_shard_fg_expand]: 1.182e-05 [get_grad_eliminate_]: 4.612e-05 [merge_forward]: 3.015e-05 [cell_reuse_recompute_pass]: 4.05e-06 [cell_reuse_handle_not_recompute_node_pass]: 9.434e-05 [j_node_and_user_rematch]: 8.531e-05 [meta_fg_expand]: 2.028e-05 [replace_old_param]: 6.451e-05 [inline_without_move]: 4.755e-05 [renormalize]: 1.09983e-07 [add_forward_monad_depend]: 6.07999e-06 [auto_monad_grad]: 2.54001e-06 [auto_monad_eliminator]: 0.00010718 [cse]: 0.00015899 [replace_applicator]: 5.736e-05 [py_interpret_to_execute_after_opt_a]: 5.819e-05 [rewriter_after_opt_a]: 0.00053259 [convert_after_rewriter]: 5.186e-05 [order_py_execute_after_rewriter]: 3.181e-05 [mutable_eliminate]: 0.00093517 [jit_opt_b]: 0.0003117, [1] [Cycle 1]: 0.00029962, [2] [frontend_op_eliminate]: 0.0001478 [inline_after_opt_a]: 0.00013091 [cconv]: 5.703e-05 [loop_unroll]: 0.00064821 [jit_opt_after_cconv]: 0.0009195, [1] [Cycle 1]: 0.00090742, [11] [c_1]: 0.00030004 [parameter_eliminate]: 6.89001e-06 [updatestate_depend_eliminate]: 4.149e-05 [updatestate_assign_eliminate]: 3.429e-05 [updatestate_loads_eliminate]: 3.457e-05 [cse]: 0.0001659 [call_graph_tuple_transform]: 0.00012489 [tuple_list_get_item_eliminator]: 4.728e-05 [none_parameter_eliminate]: 2.79999e-06 [renormalize]: 1.50001e-06 [switch_simplify]: 4.616e-05 [remove_dup_value]: 0.00016076 [partial_unused_args_eliminate]: 3.75e-06 [environ_conv]: 5.325e-05 [add_recomputation]: 0.00029772 [cse_after_recomputation]: 0.00015864, [1] [Cycle 1]: 0.00014883, [1] [cse]: 0.00013338 [auto_monad_reorder]: 0.00013081 [get_jit_bprop_graph]: 2.84001e-06 [rewriter_after_jit_bprop_graph]: 0.00040592 [opt_after_jit_grad]: 0.00083802 [symbol_engine_optimizer]: 0.0003406, [1] [Cycle 1]: 0.00033141, [6] [build]: 2.898e-05 [elim_shapecalc]: 5.341e-05 [elim_not_effective]: 8.604e-05 [opt_reshape]: 5.024e-05 [fold_const_symbol]: 7.506e-05 [renormalize]: 9.20001e-07 [validate]: 0.00022534 Sums bootstrap : 0.001025s : 0.00% type_inference : 52.729365s : 98.71% event_method : 0.000394s : 0.00% auto_monad : 0.002604s : 0.00% graph_reusing : 0.000147s : 0.00% pre_auto_parallel : 0.000044s : 0.00% py_interpret_to_execute : 0.000595s : 0.00% rewriter_before_opt_a : 0.004620s : 0.01% expand_dump_flag : 0.064096s : 0.12% jit_opt_a.switch_simplify : 0.002239s : 0.00% jit_opt_a.loop_unroll : 0.001126s : 0.00% jit_opt_a.a_1 : 0.142249s : 0.27% jit_opt_a.with_stream_mark : 0.000640s : 0.00% jit_opt_a.recompute_prepare : 0.000320s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000748s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000166s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000314s : 0.00% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000243s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000327s : 0.00% jit_opt_a.accelerated_algorithm : 0.000367s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000092s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000207s : 0.00% jit_opt_a.merge_forward : 0.000132s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000013s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000420s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000384s : 0.00% jit_opt_a.meta_fg_expand : 0.154667s : 0.29% jit_opt_a.replace_old_param : 0.000622s : 0.00% jit_opt_a.inline_without_move : 0.000546s : 0.00% jit_opt_a.renormalize : 0.299811s : 0.56% jit_opt_a.add_forward_monad_depend : 0.000170s : 0.00% jit_opt_a.auto_monad_grad : 0.000059s : 0.00% jit_opt_a.auto_monad_eliminator : 0.001332s : 0.00% jit_opt_a.cse : 0.001742s : 0.00% jit_opt_a.replace_applicator : 0.000935s : 0.00% py_interpret_to_execute_after_opt_a : 0.000058s : 0.00% rewriter_after_opt_a : 0.000533s : 0.00% convert_after_rewriter : 0.000052s : 0.00% order_py_execute_after_rewriter : 0.000032s : 0.00% mutable_eliminate : 0.000935s : 0.00% jit_opt_b.frontend_op_eliminate : 0.000148s : 0.00% jit_opt_b.inline_after_opt_a : 0.000131s : 0.00% cconv : 0.000057s : 0.00% loop_unroll : 0.000648s : 0.00% jit_opt_after_cconv.c_1 : 0.000300s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000041s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000034s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000035s : 0.00% jit_opt_after_cconv.cse : 0.000166s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000125s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000047s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.renormalize : 0.000002s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000046s : 0.00% remove_dup_value : 0.000161s : 0.00% partial_unused_args_eliminate : 0.000004s : 0.00% environ_conv : 0.000053s : 0.00% add_recomputation : 0.000298s : 0.00% cse_after_recomputation.cse : 0.000133s : 0.00% auto_monad_reorder : 0.000131s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000406s : 0.00% opt_after_jit_grad : 0.000838s : 0.00% symbol_engine_optimizer.build : 0.000029s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000053s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000086s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000050s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000075s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000225s : 0.00% Time group info: ------[substitution.] 0.059694 1615 0.18% : 0.000109s : 6: substitution.arithmetic_simplify 0.19% : 0.000113s : 13: substitution.cast_eliminate 0.24% : 0.000141s : 51: substitution.depend_value_elim 0.02% : 0.000012s : 34: substitution.elim_not_effective 0.02% : 0.000009s : 4: substitution.environ_get_add_eliminate 0.01% : 0.000004s : 2: substitution.environ_get_depend_swap 0.02% : 0.000009s : 4: substitution.environ_get_eliminate 0.04% : 0.000026s : 4: substitution.environ_get_set_eliminate 0.02% : 0.000010s : 34: substitution.fold_const_symbol 2.63% : 0.001567s : 8: substitution.getattr_setattr_resolve 0.05% : 0.000032s : 46: substitution.graph_param_transform 91.97% : 0.054898s : 178: substitution.inline 0.16% : 0.000096s : 13: substitution.inline_without_move 0.14% : 0.000081s : 154: substitution.j_node_and_user_rematch 0.11% : 0.000064s : 17: substitution.less_batch_normalization 0.06% : 0.000034s : 1: substitution.list_to_tuple_eliminator_ 0.05% : 0.000031s : 30: substitution.load_eliminater 0.18% : 0.000109s : 72: substitution.minmaximum_grad 0.00% : 0.000001s : 1: substitution.opt_reshape 0.07% : 0.000042s : 14: substitution.partial_eliminate 0.05% : 0.000028s : 6: substitution.reduce_eliminate 0.01% : 0.000008s : 5: substitution.redundant_stop_gradient_eliminater 0.14% : 0.000086s : 154: substitution.remove_not_recompute_node 0.36% : 0.000215s : 59: substitution.replace_applicator 0.10% : 0.000057s : 79: substitution.replace_old_param 0.16% : 0.000097s : 14: substitution.reshape_eliminate 0.01% : 0.000004s : 1: substitution.set_cell_output_no_recompute 0.01% : 0.000006s : 3: substitution.split_environ_get_set_with_tuple_value 0.24% : 0.000145s : 34: substitution.switch_simplify 0.01% : 0.000006s : 1: substitution.tile_eliminate 0.59% : 0.000350s : 82: substitution.tuple_list_convert_item_index_to_positive 0.52% : 0.000308s : 91: substitution.tuple_list_get_item_depend_reorder 0.88% : 0.000527s : 174: substitution.tuple_list_get_item_eliminator 0.24% : 0.000140s : 101: substitution.updatestate_pure_node_eliminater 0.55% : 0.000326s : 125: substitution.updatestate_useless_node_eliminater ------[type_inference.] 52.728358 2 99.80% : 52.622044s : 1: type_inference.infer 0.20% : 0.106314s : 1: type_inference.specialize ------[replace.] 0.003839 330 0.39% : 0.000015s : 1: replace.arithmetic_simplify 0.76% : 0.000029s : 3: replace.cast_eliminate 1.15% : 0.000044s : 5: replace.depend_value_elim 1.17% : 0.000045s : 2: replace.environ_get_set_eliminate 3.38% : 0.000130s : 6: replace.getattr_setattr_resolve 46.53% : 0.001786s : 178: replace.inline 0.61% : 0.000024s : 1: replace.list_to_tuple_eliminator_ 0.90% : 0.000035s : 2: replace.partial_eliminate 2.68% : 0.000103s : 3: replace.replace_applicator 0.17% : 0.000006s : 1: replace.reshape_eliminate 12.56% : 0.000482s : 34: replace.switch_simplify 3.19% : 0.000122s : 9: replace.tuple_list_get_item_depend_reorder 25.99% : 0.000998s : 83: replace.tuple_list_get_item_eliminator 0.53% : 0.000020s : 2: replace.updatestate_useless_node_eliminater ------[match.] 0.056946 330 0.09% : 0.000050s : 1: match.arithmetic_simplify 0.05% : 0.000028s : 3: match.cast_eliminate 0.01% : 0.000005s : 5: match.depend_value_elim 0.04% : 0.000021s : 2: match.environ_get_set_eliminate 2.59% : 0.001474s : 6: match.getattr_setattr_resolve 96.21% : 0.054786s : 178: match.inline 0.06% : 0.000033s : 1: match.list_to_tuple_eliminator_ 0.03% : 0.000017s : 2: match.partial_eliminate 0.06% : 0.000034s : 3: match.replace_applicator 0.00% : 0.000002s : 1: match.reshape_eliminate 0.22% : 0.000128s : 34: match.switch_simplify 0.19% : 0.000110s : 9: match.tuple_list_get_item_depend_reorder 0.42% : 0.000241s : 83: match.tuple_list_get_item_eliminator 0.03% : 0.000016s : 2: match.updatestate_useless_node_eliminater ------[predicate.] 0.065331 35552 0.13% : 0.000086s : 608: predicate.accumulaten_eliminater 0.02% : 0.000011s : 46: predicate.ad_related_special_op_eliminate 0.12% : 0.000079s : 608: predicate.addn_check_dump 0.13% : 0.000084s : 608: predicate.addn_zero_filter 0.17% : 0.000113s : 609: predicate.arithmetic_simplify 0.14% : 0.000093s : 613: predicate.cast_eliminate 0.01% : 0.000007s : 46: predicate.check_bprop_eliminate 0.12% : 0.000078s : 608: predicate.compare_switch_simplify 0.13% : 0.000085s : 608: predicate.depend_value_elim 0.12% : 0.000081s : 615: predicate.dict_get_item_const_eliminator 0.17% : 0.000108s : 615: predicate.dict_get_item_eliminator 0.12% : 0.000082s : 615: predicate.dict_set_item_eliminator 0.01% : 0.000008s : 46: predicate.dumpgradient_eliminate 0.01% : 0.000004s : 46: predicate.elim_not_effective 0.01% : 0.000007s : 46: predicate.elim_shapecalc_of_broadcastargs 0.12% : 0.000081s : 613: predicate.environ_add_const_eliminate 0.12% : 0.000081s : 615: predicate.environ_get_add_eliminate 0.12% : 0.000080s : 613: predicate.environ_get_depend_swap 0.13% : 0.000082s : 615: predicate.environ_get_eliminate 0.12% : 0.000080s : 615: predicate.environ_get_set_eliminate 0.01% : 0.000003s : 46: predicate.fold_const_symbol 0.05% : 0.000030s : 209: predicate.get_grad_eliminate 0.02% : 0.000015s : 40: predicate.getattr_setattr_resolve 0.01% : 0.000004s : 46: predicate.graph_param_transform 0.36% : 0.000235s : 982: predicate.inline 0.11% : 0.000072s : 432: predicate.inline_without_move 0.02% : 0.000015s : 209: predicate.j_node_and_user_rematch 0.06% : 0.000038s : 219: predicate.less_batch_normalization 0.14% : 0.000093s : 708: predicate.list_to_tuple_eliminator_ 0.16% : 0.000108s : 756: predicate.load_eliminater 0.02% : 0.000011s : 46: predicate.loop_unroll_after_grad 0.28% : 0.000185s : 1210: predicate.loop_unroll_before_grad 0.13% : 0.000088s : 670: predicate.make_slice_get_slice_eliminator 0.12% : 0.000080s : 608: predicate.merge_addn 0.13% : 0.000082s : 609: predicate.minmaximum_grad 0.02% : 0.000011s : 46: predicate.mutable_eliminate 0.01% : 0.000006s : 46: predicate.opt_reshape 0.19% : 0.000126s : 756: predicate.partial_eliminate 0.12% : 0.000079s : 603: predicate.print_const_string_wrapper 0.16% : 0.000103s : 609: predicate.reduce_eliminate 0.16% : 0.000106s : 710: predicate.redundant_stop_gradient_eliminater 0.03% : 0.000017s : 209: predicate.remove_not_recompute_node 0.18% : 0.000120s : 1229: predicate.replace_applicator 0.05% : 0.000034s : 432: predicate.replace_old_param 0.01% : 0.000004s : 46: predicate.reset_defer_inline 0.13% : 0.000083s : 610: predicate.reshape_eliminate 0.12% : 0.000080s : 603: predicate.row_tensor_add_zeros_like 0.01% : 0.000008s : 46: predicate.row_tensor_eliminate 0.12% : 0.000081s : 603: predicate.same_eliminate 0.03% : 0.000022s : 254: predicate.set_cell_output_no_recompute 0.02% : 0.000013s : 92: predicate.special_op_eliminate 0.05% : 0.000034s : 209: predicate.specialize_transform 0.14% : 0.000094s : 603: predicate.split_environ_get_set_with_tuple_value 0.12% : 0.000077s : 603: predicate.stack_unstack_eliminate 0.01% : 0.000007s : 46: predicate.switch_call_monad_eliminater 0.31% : 0.000203s : 890: predicate.switch_defer_inline 0.20% : 0.000133s : 890: predicate.switch_layer_defer_inline 0.53% : 0.000349s : 2214: predicate.switch_simplify 0.13% : 0.000083s : 609: predicate.tile_eliminate 0.12% : 0.000081s : 609: predicate.transpose_eliminate 92.08% : 0.060157s : 615: predicate.tuple_list_convert_item_index_to_positive 0.15% : 0.000100s : 624: predicate.tuple_list_get_item_depend_reorder 0.25% : 0.000163s : 799: predicate.tuple_list_get_item_eliminator 0.16% : 0.000103s : 624: predicate.tuple_list_set_item_eliminator 0.14% : 0.000094s : 707: predicate.tuple_to_list_eliminator_ 0.16% : 0.000105s : 756: predicate.updatestate_pure_node_eliminater 0.23% : 0.000147s : 967: predicate.updatestate_useless_node_eliminater 0.16% : 0.000105s : 603: predicate.value_based_eliminate 0.01% : 0.000006s : 46: predicate.virtual_view_grad_eliminate 0.01% : 0.000008s : 46: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.142896 423 19.27% : 0.027529s : 216: func_graph_cloner_run.FuncGraphClonerGraph 80.73% : 0.115367s : 207: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 53.881101 106 0.00% : 0.000304s : 1: add_recomputation 0.00% : 0.002621s : 1: auto_monad 0.00% : 0.000136s : 1: auto_monad_reorder 0.00% : 0.001064s : 1: bootstrap 0.00% : 0.000063s : 1: cconv 0.00% : 0.000077s : 1: convert_after_rewriter 0.00% : 0.000162s : 1: cse_after_recomputation 0.00% : 0.000057s : 1: environ_conv 0.00% : 0.000406s : 1: event_method 0.12% : 0.064128s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000155s : 1: graph_reusing 1.15% : 0.619198s : 1: jit_opt_a 0.00% : 0.000924s : 1: jit_opt_after_cconv 0.00% : 0.000316s : 1: jit_opt_b 0.00% : 0.000668s : 1: loop_unroll 0.00% : 0.000957s : 1: mutable_eliminate 0.28% : 0.149816s : 52: opt.transform.jit_opt_a 0.00% : 0.000511s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000267s : 4: opt.transform.jit_opt_b 0.00% : 0.000067s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000075s : 1: opt.transform.mutable_eliminate 0.00% : 0.000162s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.001823s : 4: opt.transform.opt_resolve 0.00% : 0.000260s : 4: opt.transform.symbol_engine_opt 0.00% : 0.000851s : 1: opt_after_jit_grad 0.00% : 0.000038s : 1: order_py_execute_after_rewriter 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000050s : 1: pre_auto_parallel 0.00% : 0.000605s : 1: py_interpret_to_execute 0.00% : 0.000063s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000168s : 1: remove_dup_value 0.31% : 0.165900s : 3: renormalize.infer 0.25% : 0.133850s : 3: renormalize.specialize 0.00% : 0.000411s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000547s : 1: rewriter_after_opt_a 0.01% : 0.004647s : 1: rewriter_before_opt_a 0.00% : 0.000344s : 1: symbol_engine_optimizer 97.86% : 52.729398s : 1: type_inference ..... [hook] pytest_runtest_teardown:test_mint_optim_fused_adamw_bfloat16 tests/st/mint/optim/test_fused_adamw.py::test_mint_optim_fused_adamw_bfloat16,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_bfloat16 /usr/local/Ascend/cann-8.5.0/python/site-packages/asc_op_compile_base/asc_op_compiler/ascendc_compile_gen_code.py:161: DeprecationWarning: invalid escape sequence \w match = re.search(f'{option}=(\w+)', ' '.join(compile_options)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 1 passed, 26 warnings in 488.91s (0:08:08) ==================