==================================================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, configfile: ../../../../../../sault/virtual_test/virtualenv_002/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_squeeze.py . [hook] pytest_runtest_teardown:test_squeeze_std[pynative] tests/st/mint/test_squeeze.py::test_squeeze_std[pynative],max_mem:2.0M [WARNING] PARSER(168678,ffffbdbe8f30,python3.9):2026-01-29-17:39:55.207.090 [mindspore/ccsrc/frontend/jit/ps/parse/data_converter.cc:661] CheckAPI] The mint interface squeeze was called, and the operators under this interface have different view capabilities on pynative and graph mode. Use this interface with caution in graph mode, as it may produce unexpected results. For more information, please refer to: https://www.mindspore.cn/docs/en/master/features/view.html TotalTime = 4.84967, [33] [bootstrap]: 0.00068008 [type_inference]: 1.35626 [event_method]: 2.464e-05 [auto_monad]: 0.0001312 [graph_reusing]: 6.89001e-06 [pre_auto_parallel]: 1.253e-05 [py_interpret_to_execute]: 0.00065226 [rewriter_before_opt_a]: 0.00010891 [expand_dump_flag]: 4.46002e-06 [jit_opt_a]: 0.100646, [2] [Cycle 1]: 0.00618297, [27] [switch_simplify]: 9.173e-05 [loop_unroll]: 2.759e-05 [a_1]: 0.00067367 [with_stream_mark]: 3.344e-05 [recompute_prepare]: 1.127e-05 [updatestate_depend_eliminate]: 5.27999e-06 [updatestate_assign_eliminate]: 3.61001e-06 [updatestate_loads_eliminate]: 3.13998e-06 [parameter_eliminate]: 2.14999e-06 [specialize_transform]: 8.64998e-06 [updatestate_useless_node_eliminater]: 7.27002e-06 [accelerated_algorithm]: 9.07001e-06 [meta_shard_fg_expand]: 2.92002e-06 [get_grad_eliminate_]: 7.26001e-06 [merge_forward]: 4.70001e-06 [cell_reuse_recompute_pass]: 1.12999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.482e-05 [j_node_and_user_rematch]: 1.316e-05 [meta_fg_expand]: 2.81e-06 [replace_old_param]: 1.262e-05 [inline_without_move]: 7.60998e-06 [renormalize]: 0.00482483 [add_forward_monad_depend]: 2.524e-05 [auto_monad_grad]: 3.65998e-06 [auto_monad_eliminator]: 2.484e-05 [cse]: 5.144e-05 [replace_applicator]: 2.583e-05 [Cycle 2]: 0.00043679, [27] [switch_simplify]: 8.07e-06 [loop_unroll]: 6.83e-06 [a_1]: 0.00014099 [with_stream_mark]: 1.86e-05 [recompute_prepare]: 7.53999e-06 [updatestate_depend_eliminate]: 4.40999e-06 [updatestate_assign_eliminate]: 3.28998e-06 [updatestate_loads_eliminate]: 3.43e-06 [parameter_eliminate]: 1.99e-06 [specialize_transform]: 6.67002e-06 [updatestate_useless_node_eliminater]: 6.02001e-06 [accelerated_algorithm]: 7.97e-06 [meta_shard_fg_expand]: 2.39001e-06 [get_grad_eliminate_]: 6.51e-06 [merge_forward]: 3.81001e-06 [cell_reuse_recompute_pass]: 2.78e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.215e-05 [j_node_and_user_rematch]: 1.158e-05 [meta_fg_expand]: 2.39001e-06 [replace_old_param]: 1.081e-05 [inline_without_move]: 5.96003e-06 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 1.35001e-06 [auto_monad_grad]: 8.70001e-07 [auto_monad_eliminator]: 8.15999e-06 [cse]: 1.281e-05 [replace_applicator]: 6.15002e-06 [py_interpret_to_execute_after_opt_a]: 1.767e-05 [rewriter_after_opt_a]: 5.552e-05 [convert_after_rewriter]: 8.40001e-06 [order_py_execute_after_rewriter]: 5.67999e-06 [mutable_eliminate]: 0.00086325 [jit_opt_b]: 0.00012249, [1] [Cycle 1]: 0.00011335, [2] [frontend_op_eliminate]: 2.006e-05 [inline_after_opt_a]: 7.805e-05 [cconv]: 3.591e-05 [loop_unroll]: 0.00050771 [jit_opt_after_cconv]: 0.00018548, [1] [Cycle 1]: 0.00017773, [11] [c_1]: 3.123e-05 [parameter_eliminate]: 4e-06 [updatestate_depend_eliminate]: 8.01001e-06 [updatestate_assign_eliminate]: 3.48e-06 [updatestate_loads_eliminate]: 2.99001e-06 [cse]: 2.844e-05 [call_graph_tuple_transform]: 2.663e-05 [tuple_list_get_item_eliminator]: 7.78001e-06 [none_parameter_eliminate]: 1.63002e-06 [renormalize]: 7.30011e-07 [switch_simplify]: 6.95998e-06 [remove_dup_value]: 1.9e-05 [partial_unused_args_eliminate]: 2.27999e-06 [environ_conv]: 2.449e-05 [add_recomputation]: 6.396e-05 [cse_after_recomputation]: 2.916e-05, [1] [Cycle 1]: 2.217e-05, [1] [cse]: 1.48e-05 [auto_monad_reorder]: 2.52e-05 [get_jit_bprop_graph]: 2.43e-06 [rewriter_after_jit_bprop_graph]: 0.00020251 [opt_after_jit_grad]: 0.00054426 [symbol_engine_optimizer]: 9.131e-05, [1] [Cycle 1]: 8.401e-05, [6] [build]: 5.14e-06 [elim_shapecalc]: 1.011e-05 [elim_not_effective]: 1.686e-05 [opt_reshape]: 8.32e-06 [fold_const_symbol]: 1.084e-05 [renormalize]: 6.69999e-07 [validate]: 7.174e-05 [backend_pass]: 1.04e-06 [task_emit]: 3.38786 [execute]: 1.084e-05 Sums bootstrap : 0.000680s : 0.01% type_inference : 1.356257s : 28.52% event_method : 0.000025s : 0.00% auto_monad : 0.000131s : 0.00% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000652s : 0.01% rewriter_before_opt_a : 0.000109s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000100s : 0.00% jit_opt_a.loop_unroll : 0.000034s : 0.00% jit_opt_a.a_1 : 0.000815s : 0.02% jit_opt_a.with_stream_mark : 0.000052s : 0.00% jit_opt_a.recompute_prepare : 0.000019s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000015s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000013s : 0.00% jit_opt_a.accelerated_algorithm : 0.000017s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000014s : 0.00% jit_opt_a.merge_forward : 0.000009s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000025s : 0.00% jit_opt_a.meta_fg_expand : 0.000005s : 0.00% jit_opt_a.replace_old_param : 0.000023s : 0.00% jit_opt_a.inline_without_move : 0.000014s : 0.00% jit_opt_a.renormalize : 0.004825s : 0.10% jit_opt_a.add_forward_monad_depend : 0.000027s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000033s : 0.00% jit_opt_a.cse : 0.000064s : 0.00% jit_opt_a.replace_applicator : 0.000032s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000056s : 0.00% convert_after_rewriter : 0.000008s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000863s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000020s : 0.00% jit_opt_b.inline_after_opt_a : 0.000078s : 0.00% cconv : 0.000036s : 0.00% loop_unroll : 0.000508s : 0.01% jit_opt_after_cconv.c_1 : 0.000031s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000028s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000027s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 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 : 0.000007s : 0.00% remove_dup_value : 0.000019s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000024s : 0.00% add_recomputation : 0.000064s : 0.00% cse_after_recomputation.cse : 0.000015s : 0.00% auto_monad_reorder : 0.000025s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000203s : 0.00% opt_after_jit_grad : 0.000544s : 0.01% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000017s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000072s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 3.387856s : 71.25% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000282 23 0.94% : 0.000003s : 2: substitution.elim_not_effective 0.56% : 0.000002s : 2: substitution.fold_const_symbol 2.92% : 0.000008s : 4: substitution.graph_param_transform 83.67% : 0.000236s : 4: substitution.inline 2.18% : 0.000006s : 4: substitution.j_node_and_user_rematch 2.60% : 0.000007s : 4: substitution.remove_not_recompute_node 2.70% : 0.000008s : 2: substitution.replace_old_param 4.44% : 0.000013s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.356137 2 99.73% : 1.352417s : 1: type_inference.infer 0.27% : 0.003720s : 1: type_inference.specialize ------[replace.] 0.000067 5 83.07% : 0.000056s : 4: replace.inline 16.93% : 0.000011s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000244 5 95.25% : 0.000233s : 4: match.inline 4.75% : 0.000012s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000169 801 1.20% : 0.000002s : 12: predicate.accumulaten_eliminater 0.88% : 0.000001s : 4: predicate.ad_related_special_op_eliminate 1.02% : 0.000002s : 12: predicate.addn_check_dump 1.83% : 0.000003s : 12: predicate.addn_zero_filter 2.14% : 0.000004s : 12: predicate.arithmetic_simplify 1.16% : 0.000002s : 12: predicate.cast_eliminate 0.46% : 0.000001s : 4: predicate.check_bprop_eliminate 1.40% : 0.000002s : 12: predicate.compare_switch_simplify 1.37% : 0.000002s : 12: predicate.depend_value_elim 1.34% : 0.000002s : 12: predicate.dict_get_item_const_eliminator 1.56% : 0.000003s : 12: predicate.dict_get_item_eliminator 1.17% : 0.000002s : 12: predicate.dict_set_item_eliminator 0.84% : 0.000001s : 4: predicate.dumpgradient_eliminate 0.32% : 0.000001s : 4: predicate.elim_not_effective 0.47% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.24% : 0.000002s : 12: predicate.environ_add_const_eliminate 1.44% : 0.000002s : 12: predicate.environ_get_add_eliminate 1.01% : 0.000002s : 12: predicate.environ_get_depend_swap 2.29% : 0.000004s : 12: predicate.environ_get_eliminate 1.00% : 0.000002s : 12: predicate.environ_get_set_eliminate 0.26% : 0.000000s : 4: predicate.fold_const_symbol 1.55% : 0.000003s : 8: predicate.get_grad_eliminate 0.23% : 0.000000s : 4: predicate.graph_param_transform 4.99% : 0.000008s : 25: predicate.inline 0.79% : 0.000001s : 8: predicate.inline_without_move 0.37% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.40% : 0.000002s : 8: predicate.less_batch_normalization 1.74% : 0.000003s : 13: predicate.list_to_tuple_eliminator_ 1.90% : 0.000003s : 17: predicate.load_eliminater 1.06% : 0.000002s : 4: predicate.loop_unroll_after_grad 3.08% : 0.000005s : 28: predicate.loop_unroll_before_grad 2.48% : 0.000004s : 16: predicate.make_slice_get_slice_eliminator 1.25% : 0.000002s : 12: predicate.merge_addn 0.95% : 0.000002s : 12: predicate.minmaximum_grad 1.29% : 0.000002s : 4: predicate.mutable_eliminate 0.52% : 0.000001s : 4: predicate.opt_reshape 1.76% : 0.000003s : 17: predicate.partial_eliminate 1.39% : 0.000002s : 12: predicate.print_const_string_wrapper 1.77% : 0.000003s : 12: predicate.reduce_eliminate 1.25% : 0.000002s : 13: predicate.redundant_stop_gradient_eliminater 0.57% : 0.000001s : 8: predicate.remove_not_recompute_node 1.81% : 0.000003s : 21: predicate.replace_applicator 0.87% : 0.000001s : 8: predicate.replace_old_param 0.31% : 0.000001s : 4: predicate.reset_defer_inline 1.23% : 0.000002s : 12: predicate.reshape_eliminate 1.25% : 0.000002s : 12: predicate.row_tensor_add_zeros_like 0.63% : 0.000001s : 4: predicate.row_tensor_eliminate 1.40% : 0.000002s : 12: predicate.same_eliminate 0.57% : 0.000001s : 8: predicate.set_cell_output_no_recompute 0.91% : 0.000002s : 8: predicate.special_op_eliminate 0.86% : 0.000001s : 8: predicate.specialize_transform 1.70% : 0.000003s : 12: predicate.split_environ_get_set_with_tuple_value 1.42% : 0.000002s : 12: predicate.stack_unstack_eliminate 0.39% : 0.000001s : 4: predicate.switch_call_monad_eliminater 1.91% : 0.000003s : 17: predicate.switch_defer_inline 1.93% : 0.000003s : 17: predicate.switch_layer_defer_inline 7.42% : 0.000013s : 49: predicate.switch_simplify 1.08% : 0.000002s : 12: predicate.tile_eliminate 1.17% : 0.000002s : 12: predicate.transpose_eliminate 1.61% : 0.000003s : 12: predicate.tuple_list_convert_item_index_to_positive 1.37% : 0.000002s : 12: predicate.tuple_list_get_item_depend_reorder 3.95% : 0.000007s : 21: predicate.tuple_list_get_item_eliminator 2.08% : 0.000004s : 12: predicate.tuple_list_set_item_eliminator 1.71% : 0.000003s : 13: predicate.tuple_to_list_eliminator_ 2.18% : 0.000004s : 17: predicate.updatestate_pure_node_eliminater 2.83% : 0.000005s : 25: predicate.updatestate_useless_node_eliminater 1.77% : 0.000003s : 12: predicate.value_based_eliminate 0.36% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.55% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.002870 18 65.40% : 0.001877s : 12: func_graph_cloner_run.FuncGraphClonerGraph 34.60% : 0.000993s : 6: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.855677 76 0.00% : 0.000067s : 1: add_recomputation 0.00% : 0.000136s : 1: auto_monad 0.00% : 0.000028s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.01% : 0.000705s : 1: bootstrap 0.00% : 0.000039s : 1: cconv 0.00% : 0.000011s : 1: convert_after_rewriter 0.00% : 0.000032s : 1: cse_after_recomputation 0.00% : 0.000028s : 1: environ_conv 0.00% : 0.000030s : 1: event_method 0.00% : 0.000017s : 1: execute 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 2.07% : 0.100650s : 1: jit_opt_a 0.00% : 0.000189s : 1: jit_opt_after_cconv 0.00% : 0.000126s : 1: jit_opt_b 0.01% : 0.000516s : 1: loop_unroll 0.02% : 0.000876s : 1: mutable_eliminate 0.02% : 0.001109s : 26: opt.transform.jit_opt_a 0.00% : 0.000068s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000090s : 4: opt.transform.jit_opt_b 0.00% : 0.000015s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.00% : 0.000029s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000042s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000553s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000662s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000022s : 1: remove_dup_value 0.07% : 0.003638s : 1: renormalize.infer 0.02% : 0.001171s : 1: renormalize.specialize 0.00% : 0.000207s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000059s : 1: rewriter_after_opt_a 0.00% : 0.000114s : 1: rewriter_before_opt_a 0.00% : 0.000094s : 1: symbol_engine_optimizer 69.77% : 3.387885s : 1: task_emit 27.93% : 1.356280s : 1: type_inference 0.00% : 0.000097s : 1: validate TotalTime = 1.06508, [33] [bootstrap]: 0.0006274 [type_inference]: 1.04028 [event_method]: 0.0010216 [auto_monad]: 0.0002141 [graph_reusing]: 1.148e-05 [pre_auto_parallel]: 4.03999e-06 [py_interpret_to_execute]: 6.295e-05 [rewriter_before_opt_a]: 0.00018602 [expand_dump_flag]: 4.45999e-06 [jit_opt_a]: 0.0186049, [2] [Cycle 1]: 0.0127558, [27] [switch_simplify]: 0.00027129 [loop_unroll]: 6.074e-05 [a_1]: 0.00152123 [with_stream_mark]: 3.981e-05 [recompute_prepare]: 2.893e-05 [updatestate_depend_eliminate]: 1.046e-05 [updatestate_assign_eliminate]: 7.3e-06 [updatestate_loads_eliminate]: 7.11999e-06 [parameter_eliminate]: 3.80998e-06 [specialize_transform]: 1.672e-05 [updatestate_useless_node_eliminater]: 1.565e-05 [accelerated_algorithm]: 1.586e-05 [meta_shard_fg_expand]: 7.87e-06 [get_grad_eliminate_]: 1.66e-05 [merge_forward]: 9.81e-06 [cell_reuse_recompute_pass]: 1.42e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.33e-05 [j_node_and_user_rematch]: 3.273e-05 [meta_fg_expand]: 0.00246717 [replace_old_param]: 8.133e-05 [inline_without_move]: 6.983e-05 [renormalize]: 0.00759354 [add_forward_monad_depend]: 3.819e-05 [auto_monad_grad]: 3.35e-06 [auto_monad_eliminator]: 2.096e-05 [cse]: 3.638e-05 [replace_applicator]: 3.046e-05 [Cycle 2]: 0.00057323, [27] [switch_simplify]: 7.17997e-06 [loop_unroll]: 5.66e-06 [a_1]: 7.441e-05 [with_stream_mark]: 1.796e-05 [recompute_prepare]: 4.67e-06 [updatestate_depend_eliminate]: 3.13998e-06 [updatestate_assign_eliminate]: 2.76e-06 [updatestate_loads_eliminate]: 2.59001e-06 [parameter_eliminate]: 2.27001e-06 [specialize_transform]: 4.50999e-06 [updatestate_useless_node_eliminater]: 4.03999e-06 [accelerated_algorithm]: 4.70001e-06 [meta_shard_fg_expand]: 2.81e-06 [get_grad_eliminate_]: 4.15e-06 [merge_forward]: 3.68999e-06 [cell_reuse_recompute_pass]: 3.05002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.084e-05 [j_node_and_user_rematch]: 8.39998e-06 [meta_fg_expand]: 0.00021088 [replace_old_param]: 8.3e-06 [inline_without_move]: 4.91002e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.58e-06 [auto_monad_grad]: 1.82001e-06 [auto_monad_eliminator]: 6.63e-06 [cse]: 1.725e-05 [replace_applicator]: 6.01e-06 [py_interpret_to_execute_after_opt_a]: 1.901e-05 [rewriter_after_opt_a]: 0.0004662 [convert_after_rewriter]: 1.624e-05 [order_py_execute_after_rewriter]: 5.07e-06 [mutable_eliminate]: 0.0008956 [jit_opt_b]: 6.073e-05, [1] [Cycle 1]: 5.086e-05, [2] [frontend_op_eliminate]: 1.925e-05 [inline_after_opt_a]: 1.733e-05 [cconv]: 3.887e-05 [loop_unroll]: 0.00119926 [jit_opt_after_cconv]: 0.00018259, [1] [Cycle 1]: 0.00017377, [11] [c_1]: 2.114e-05 [parameter_eliminate]: 6.38998e-06 [updatestate_depend_eliminate]: 1.012e-05 [updatestate_assign_eliminate]: 2.96999e-06 [updatestate_loads_eliminate]: 2.68e-06 [cse]: 3.664e-05 [call_graph_tuple_transform]: 2.183e-05 [tuple_list_get_item_eliminator]: 4.92e-06 [none_parameter_eliminate]: 1.52999e-06 [renormalize]: 6.09987e-07 [switch_simplify]: 5.15999e-06 [remove_dup_value]: 1.746e-05 [partial_unused_args_eliminate]: 3.31001e-06 [environ_conv]: 7.13998e-06 [add_recomputation]: 5.052e-05 [cse_after_recomputation]: 2.487e-05, [1] [Cycle 1]: 1.761e-05, [1] [cse]: 1.028e-05 [auto_monad_reorder]: 1.529e-05 [get_jit_bprop_graph]: 2.73003e-06 [rewriter_after_jit_bprop_graph]: 7.72002e-06 [opt_after_jit_grad]: 0.00056526 [symbol_engine_optimizer]: 8.275e-05, [1] [Cycle 1]: 7.433e-05, [6] [build]: 4.77e-06 [elim_shapecalc]: 7.62998e-06 [elim_not_effective]: 1.355e-05 [opt_reshape]: 5.76e-06 [fold_const_symbol]: 7.9e-06 [renormalize]: 6.19999e-07 [validate]: 4.378e-05 [backend_pass]: 1.09e-06 [task_emit]: 3.546e-05 [execute]: 1.49e-06 Sums bootstrap : 0.000627s : 0.06% type_inference : 1.040280s : 98.24% event_method : 0.001022s : 0.10% auto_monad : 0.000214s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000063s : 0.01% rewriter_before_opt_a : 0.000186s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000278s : 0.03% jit_opt_a.loop_unroll : 0.000066s : 0.01% jit_opt_a.a_1 : 0.001596s : 0.15% jit_opt_a.with_stream_mark : 0.000058s : 0.01% jit_opt_a.recompute_prepare : 0.000034s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000006s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000020s : 0.00% jit_opt_a.accelerated_algorithm : 0.000021s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000011s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000021s : 0.00% jit_opt_a.merge_forward : 0.000013s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000054s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000041s : 0.00% jit_opt_a.meta_fg_expand : 0.002678s : 0.25% jit_opt_a.replace_old_param : 0.000090s : 0.01% jit_opt_a.inline_without_move : 0.000075s : 0.01% jit_opt_a.renormalize : 0.007594s : 0.72% jit_opt_a.add_forward_monad_depend : 0.000041s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000028s : 0.00% jit_opt_a.cse : 0.000054s : 0.01% jit_opt_a.replace_applicator : 0.000036s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000466s : 0.04% convert_after_rewriter : 0.000016s : 0.00% order_py_execute_after_rewriter : 0.000005s : 0.00% mutable_eliminate : 0.000896s : 0.08% jit_opt_b.frontend_op_eliminate : 0.000019s : 0.00% jit_opt_b.inline_after_opt_a : 0.000017s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.001199s : 0.11% jit_opt_after_cconv.c_1 : 0.000021s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000037s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000022s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000005s : 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 : 0.000005s : 0.00% remove_dup_value : 0.000017s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000007s : 0.00% add_recomputation : 0.000051s : 0.00% cse_after_recomputation.cse : 0.000010s : 0.00% auto_monad_reorder : 0.000015s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000565s : 0.05% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000008s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000014s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000006s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000008s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000044s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 0.000035s : 0.00% execute : 0.000001s : 0.00% Time group info: ------[substitution.] 0.000535 65 0.39% : 0.000002s : 1: substitution.elim_not_effective 0.23% : 0.000001s : 1: substitution.fold_const_symbol 1.32% : 0.000007s : 1: substitution.graph_param_transform 75.77% : 0.000405s : 13: substitution.inline 4.76% : 0.000025s : 2: substitution.inline_without_move 1.61% : 0.000009s : 9: substitution.j_node_and_user_rematch 1.14% : 0.000006s : 2: substitution.minmaximum_grad 1.82% : 0.000010s : 9: substitution.partial_eliminate 1.58% : 0.000008s : 9: substitution.remove_not_recompute_node 0.52% : 0.000003s : 1: substitution.replace_applicator 1.14% : 0.000006s : 6: substitution.replace_old_param 0.71% : 0.000004s : 1: substitution.set_cell_output_no_recompute 3.13% : 0.000017s : 3: substitution.switch_simplify 1.60% : 0.000009s : 2: substitution.tuple_list_convert_item_index_to_positive 1.21% : 0.000006s : 2: substitution.tuple_list_get_item_depend_reorder 3.06% : 0.000016s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.040067 2 96.32% : 1.001827s : 1: type_inference.infer 3.68% : 0.038240s : 1: type_inference.specialize ------[replace.] 0.000227 17 54.98% : 0.000125s : 13: replace.inline 40.14% : 0.000091s : 3: replace.switch_simplify 4.88% : 0.000011s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000414 17 95.58% : 0.000396s : 13: match.inline 3.51% : 0.000015s : 3: match.switch_simplify 0.91% : 0.000004s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000260 1539 1.43% : 0.000004s : 26: predicate.accumulaten_eliminater 0.41% : 0.000001s : 1: predicate.ad_related_special_op_eliminate 1.30% : 0.000003s : 26: predicate.addn_check_dump 1.43% : 0.000004s : 26: predicate.addn_zero_filter 2.02% : 0.000005s : 26: predicate.arithmetic_simplify 1.41% : 0.000004s : 26: predicate.cast_eliminate 0.13% : 0.000000s : 1: predicate.check_bprop_eliminate 1.24% : 0.000003s : 26: predicate.compare_switch_simplify 1.69% : 0.000004s : 26: predicate.depend_value_elim 1.25% : 0.000003s : 26: predicate.dict_get_item_const_eliminator 1.48% : 0.000004s : 26: predicate.dict_get_item_eliminator 1.39% : 0.000004s : 26: predicate.dict_set_item_eliminator 0.53% : 0.000001s : 1: predicate.dumpgradient_eliminate 0.18% : 0.000000s : 1: predicate.elim_not_effective 0.25% : 0.000001s : 1: predicate.elim_shapecalc_of_broadcastargs 1.43% : 0.000004s : 26: predicate.environ_add_const_eliminate 1.26% : 0.000003s : 26: predicate.environ_get_add_eliminate 1.26% : 0.000003s : 26: predicate.environ_get_depend_swap 1.39% : 0.000004s : 26: predicate.environ_get_eliminate 1.31% : 0.000003s : 26: predicate.environ_get_set_eliminate 0.04% : 0.000000s : 1: predicate.fold_const_symbol 0.85% : 0.000002s : 13: predicate.get_grad_eliminate 0.05% : 0.000000s : 1: predicate.graph_param_transform 5.35% : 0.000014s : 42: predicate.inline 2.74% : 0.000007s : 35: predicate.inline_without_move 0.39% : 0.000001s : 13: predicate.j_node_and_user_rematch 1.21% : 0.000003s : 13: predicate.less_batch_normalization 1.41% : 0.000004s : 27: predicate.list_to_tuple_eliminator_ 1.56% : 0.000004s : 28: predicate.load_eliminater 0.83% : 0.000002s : 1: predicate.loop_unroll_after_grad 4.00% : 0.000010s : 67: predicate.loop_unroll_before_grad 1.93% : 0.000005s : 27: predicate.make_slice_get_slice_eliminator 1.43% : 0.000004s : 26: predicate.merge_addn 1.39% : 0.000004s : 26: predicate.minmaximum_grad 0.84% : 0.000002s : 1: predicate.mutable_eliminate 0.16% : 0.000000s : 1: predicate.opt_reshape 1.91% : 0.000005s : 28: predicate.partial_eliminate 1.31% : 0.000003s : 26: predicate.print_const_string_wrapper 1.94% : 0.000005s : 26: predicate.reduce_eliminate 1.52% : 0.000004s : 27: predicate.redundant_stop_gradient_eliminater 0.52% : 0.000001s : 13: predicate.remove_not_recompute_node 1.52% : 0.000004s : 29: predicate.replace_applicator 1.55% : 0.000004s : 35: predicate.replace_old_param 0.09% : 0.000000s : 1: predicate.reset_defer_inline 1.36% : 0.000004s : 26: predicate.reshape_eliminate 1.43% : 0.000004s : 26: predicate.row_tensor_add_zeros_like 0.31% : 0.000001s : 1: predicate.row_tensor_eliminate 1.44% : 0.000004s : 26: predicate.same_eliminate 0.61% : 0.000002s : 13: predicate.set_cell_output_no_recompute 0.36% : 0.000001s : 2: predicate.special_op_eliminate 0.88% : 0.000002s : 13: predicate.specialize_transform 1.54% : 0.000004s : 26: predicate.split_environ_get_set_with_tuple_value 1.36% : 0.000004s : 26: predicate.stack_unstack_eliminate 0.11% : 0.000000s : 1: predicate.switch_call_monad_eliminater 3.04% : 0.000008s : 40: predicate.switch_defer_inline 2.57% : 0.000007s : 40: predicate.switch_layer_defer_inline 7.76% : 0.000020s : 114: predicate.switch_simplify 1.60% : 0.000004s : 26: predicate.tile_eliminate 1.47% : 0.000004s : 26: predicate.transpose_eliminate 1.94% : 0.000005s : 26: predicate.tuple_list_convert_item_index_to_positive 1.85% : 0.000005s : 26: predicate.tuple_list_get_item_depend_reorder 3.10% : 0.000008s : 29: predicate.tuple_list_get_item_eliminator 2.16% : 0.000006s : 26: predicate.tuple_list_set_item_eliminator 1.45% : 0.000004s : 27: predicate.tuple_to_list_eliminator_ 1.53% : 0.000004s : 28: predicate.updatestate_pure_node_eliminater 2.61% : 0.000007s : 41: predicate.updatestate_useless_node_eliminater 1.68% : 0.000004s : 26: predicate.value_based_eliminate 0.08% : 0.000000s : 1: predicate.virtual_view_grad_eliminate 0.40% : 0.000001s : 1: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004561 37 78.89% : 0.003598s : 21: func_graph_cloner_run.FuncGraphClonerGraph 21.11% : 0.000963s : 16: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.075053 76 0.01% : 0.000055s : 1: add_recomputation 0.02% : 0.000222s : 1: auto_monad 0.00% : 0.000018s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.06% : 0.000664s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000020s : 1: convert_after_rewriter 0.00% : 0.000027s : 1: cse_after_recomputation 0.00% : 0.000010s : 1: environ_conv 0.10% : 0.001042s : 1: event_method 0.00% : 0.000004s : 1: execute 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 1.73% : 0.018610s : 1: jit_opt_a 0.02% : 0.000186s : 1: jit_opt_after_cconv 0.01% : 0.000064s : 1: jit_opt_b 0.11% : 0.001212s : 1: loop_unroll 0.08% : 0.000908s : 1: mutable_eliminate 0.21% : 0.002294s : 26: opt.transform.jit_opt_a 0.00% : 0.000049s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000026s : 4: opt.transform.jit_opt_b 0.00% : 0.000015s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000039s : 1: opt.transform.mutable_eliminate 0.00% : 0.000022s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000030s : 4: opt.transform.symbol_engine_opt 0.05% : 0.000577s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000066s : 1: py_interpret_to_execute 0.00% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000020s : 1: remove_dup_value 0.62% : 0.006627s : 1: renormalize.infer 0.09% : 0.000950s : 1: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000475s : 1: rewriter_after_opt_a 0.02% : 0.000191s : 1: rewriter_before_opt_a 0.01% : 0.000086s : 1: symbol_engine_optimizer 0.00% : 0.000042s : 1: task_emit 96.77% : 1.040307s : 1: type_inference 0.01% : 0.000066s : 1: validate . [hook] pytest_runtest_teardown:test_squeeze_std[KBK] tests/st/mint/test_squeeze.py::test_squeeze_std[KBK],max_mem:4.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 186.99s (0:03:06) ==================