==================================================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_007/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_zero_bias[pynative] tests/st/mint/test_squeeze.py::test_squeeze_zero_bias[pynative],max_mem:2.0M [WARNING] PARSER(163977,ffffa19c0f30,python3.9):2026-01-29-17:40:26.084.739 [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 = 6.23888, [33] [bootstrap]: 0.00064274 [type_inference]: 2.20162 [event_method]: 2.465e-05 [auto_monad]: 0.00012127 [graph_reusing]: 6.12001e-06 [pre_auto_parallel]: 1.168e-05 [py_interpret_to_execute]: 0.00057212 [rewriter_before_opt_a]: 0.00010368 [expand_dump_flag]: 4.23999e-06 [jit_opt_a]: 0.0267183, [2] [Cycle 1]: 0.00527361, [27] [switch_simplify]: 0.00011248 [loop_unroll]: 2.788e-05 [a_1]: 0.00068136 [with_stream_mark]: 3.181e-05 [recompute_prepare]: 1.42e-05 [updatestate_depend_eliminate]: 4.90001e-06 [updatestate_assign_eliminate]: 3.47002e-06 [updatestate_loads_eliminate]: 3.6e-06 [parameter_eliminate]: 2.09e-06 [specialize_transform]: 8.98002e-06 [updatestate_useless_node_eliminater]: 7.75998e-06 [accelerated_algorithm]: 7.54002e-06 [meta_shard_fg_expand]: 3.04999e-06 [get_grad_eliminate_]: 7.59002e-06 [merge_forward]: 4.43999e-06 [cell_reuse_recompute_pass]: 1.45999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.205e-05 [j_node_and_user_rematch]: 1.142e-05 [meta_fg_expand]: 3.06999e-06 [replace_old_param]: 1.268e-05 [inline_without_move]: 7.5e-06 [renormalize]: 0.00391304 [add_forward_monad_depend]: 2.261e-05 [auto_monad_grad]: 3.33998e-06 [auto_monad_eliminator]: 2.362e-05 [cse]: 4.267e-05 [replace_applicator]: 2.622e-05 [Cycle 2]: 0.00044195, [27] [switch_simplify]: 8.40001e-06 [loop_unroll]: 6.76999e-06 [a_1]: 0.00013497 [with_stream_mark]: 2.113e-05 [recompute_prepare]: 7.31999e-06 [updatestate_depend_eliminate]: 4.68001e-06 [updatestate_assign_eliminate]: 3.78999e-06 [updatestate_loads_eliminate]: 3.08998e-06 [parameter_eliminate]: 2.53e-06 [specialize_transform]: 6.66e-06 [updatestate_useless_node_eliminater]: 5.95002e-06 [accelerated_algorithm]: 6.85002e-06 [meta_shard_fg_expand]: 2.56e-06 [get_grad_eliminate_]: 6.14001e-06 [merge_forward]: 4.55999e-06 [cell_reuse_recompute_pass]: 3.01001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.19e-05 [j_node_and_user_rematch]: 1.044e-05 [meta_fg_expand]: 2.19999e-06 [replace_old_param]: 1.119e-05 [inline_without_move]: 7.33e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.66e-06 [auto_monad_grad]: 1.14e-06 [auto_monad_eliminator]: 8.60001e-06 [cse]: 1.573e-05 [replace_applicator]: 7.06001e-06 [py_interpret_to_execute_after_opt_a]: 1.88e-05 [rewriter_after_opt_a]: 7.818e-05 [convert_after_rewriter]: 1.076e-05 [order_py_execute_after_rewriter]: 6.17999e-06 [mutable_eliminate]: 0.00085817 [jit_opt_b]: 6.844e-05, [1] [Cycle 1]: 5.913e-05, [2] [frontend_op_eliminate]: 2.333e-05 [inline_after_opt_a]: 2.047e-05 [cconv]: 3.817e-05 [loop_unroll]: 0.00049976 [jit_opt_after_cconv]: 0.00022437, [1] [Cycle 1]: 0.00021715, [11] [c_1]: 2.914e-05 [parameter_eliminate]: 5.22e-06 [updatestate_depend_eliminate]: 1.131e-05 [updatestate_assign_eliminate]: 3.35e-06 [updatestate_loads_eliminate]: 3.66999e-06 [cse]: 3.506e-05 [call_graph_tuple_transform]: 2.766e-05 [tuple_list_get_item_eliminator]: 7.22002e-06 [none_parameter_eliminate]: 2.01e-06 [renormalize]: 9.70002e-07 [switch_simplify]: 8.10999e-06 [remove_dup_value]: 1.874e-05 [partial_unused_args_eliminate]: 2.49999e-06 [environ_conv]: 0.00011225 [add_recomputation]: 6.813e-05 [cse_after_recomputation]: 3.228e-05, [1] [Cycle 1]: 2.517e-05, [1] [cse]: 1.642e-05 [auto_monad_reorder]: 2.754e-05 [get_jit_bprop_graph]: 2.39001e-06 [rewriter_after_jit_bprop_graph]: 0.00013815 [opt_after_jit_grad]: 0.00058518 [symbol_engine_optimizer]: 9.159e-05, [1] [Cycle 1]: 8.395e-05, [6] [build]: 6.21998e-06 [elim_shapecalc]: 9.71998e-06 [elim_not_effective]: 1.648e-05 [opt_reshape]: 7.32002e-06 [fold_const_symbol]: 1.202e-05 [renormalize]: 7.10017e-07 [validate]: 7.718e-05 [backend_pass]: 1.22e-06 [task_emit]: 4.00571 [execute]: 9.76e-06 Sums bootstrap : 0.000643s : 0.01% type_inference : 2.201620s : 35.41% event_method : 0.000025s : 0.00% auto_monad : 0.000121s : 0.00% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000572s : 0.01% rewriter_before_opt_a : 0.000104s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000121s : 0.00% jit_opt_a.loop_unroll : 0.000035s : 0.00% jit_opt_a.a_1 : 0.000816s : 0.01% jit_opt_a.with_stream_mark : 0.000053s : 0.00% jit_opt_a.recompute_prepare : 0.000022s : 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 : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000016s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000014s : 0.00% jit_opt_a.accelerated_algorithm : 0.000014s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 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 : 0.000044s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000022s : 0.00% jit_opt_a.meta_fg_expand : 0.000005s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000015s : 0.00% jit_opt_a.renormalize : 0.003913s : 0.06% jit_opt_a.add_forward_monad_depend : 0.000024s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000032s : 0.00% jit_opt_a.cse : 0.000058s : 0.00% jit_opt_a.replace_applicator : 0.000033s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000078s : 0.00% convert_after_rewriter : 0.000011s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000858s : 0.01% jit_opt_b.frontend_op_eliminate : 0.000023s : 0.00% jit_opt_b.inline_after_opt_a : 0.000020s : 0.00% cconv : 0.000038s : 0.00% loop_unroll : 0.000500s : 0.01% jit_opt_after_cconv.c_1 : 0.000029s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000035s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000028s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000007s : 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 : 0.000008s : 0.00% remove_dup_value : 0.000019s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000112s : 0.00% add_recomputation : 0.000068s : 0.00% cse_after_recomputation.cse : 0.000016s : 0.00% auto_monad_reorder : 0.000028s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000138s : 0.00% opt_after_jit_grad : 0.000585s : 0.01% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000016s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000007s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000012s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000077s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 4.005715s : 64.43% execute : 0.000010s : 0.00% Time group info: ------[substitution.] 0.000264 23 1.05% : 0.000003s : 2: substitution.elim_not_effective 0.82% : 0.000002s : 2: substitution.fold_const_symbol 2.93% : 0.000008s : 4: substitution.graph_param_transform 83.24% : 0.000220s : 4: substitution.inline 1.77% : 0.000005s : 4: substitution.j_node_and_user_rematch 2.04% : 0.000005s : 4: substitution.remove_not_recompute_node 3.04% : 0.000008s : 2: substitution.replace_old_param 5.11% : 0.000014s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 2.201518 2 99.86% : 2.198515s : 1: type_inference.infer 0.14% : 0.003003s : 1: type_inference.specialize ------[replace.] 0.000067 5 77.83% : 0.000052s : 4: replace.inline 22.17% : 0.000015s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000229 5 94.62% : 0.000217s : 4: match.inline 5.38% : 0.000012s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000174 801 1.15% : 0.000002s : 12: predicate.accumulaten_eliminater 1.21% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 0.97% : 0.000002s : 12: predicate.addn_check_dump 1.19% : 0.000002s : 12: predicate.addn_zero_filter 1.94% : 0.000003s : 12: predicate.arithmetic_simplify 1.29% : 0.000002s : 12: predicate.cast_eliminate 0.67% : 0.000001s : 4: predicate.check_bprop_eliminate 1.08% : 0.000002s : 12: predicate.compare_switch_simplify 1.16% : 0.000002s : 12: predicate.depend_value_elim 1.06% : 0.000002s : 12: predicate.dict_get_item_const_eliminator 1.46% : 0.000003s : 12: predicate.dict_get_item_eliminator 1.15% : 0.000002s : 12: predicate.dict_set_item_eliminator 0.84% : 0.000001s : 4: predicate.dumpgradient_eliminate 0.41% : 0.000001s : 4: predicate.elim_not_effective 0.49% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.14% : 0.000002s : 12: predicate.environ_add_const_eliminate 0.93% : 0.000002s : 12: predicate.environ_get_add_eliminate 0.93% : 0.000002s : 12: predicate.environ_get_depend_swap 1.07% : 0.000002s : 12: predicate.environ_get_eliminate 0.94% : 0.000002s : 12: predicate.environ_get_set_eliminate 0.21% : 0.000000s : 4: predicate.fold_const_symbol 1.08% : 0.000002s : 8: predicate.get_grad_eliminate 0.21% : 0.000000s : 4: predicate.graph_param_transform 5.51% : 0.000010s : 25: predicate.inline 1.11% : 0.000002s : 8: predicate.inline_without_move 0.37% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.19% : 0.000002s : 8: predicate.less_batch_normalization 1.35% : 0.000002s : 13: predicate.list_to_tuple_eliminator_ 1.77% : 0.000003s : 17: predicate.load_eliminater 1.33% : 0.000002s : 4: predicate.loop_unroll_after_grad 2.55% : 0.000004s : 28: predicate.loop_unroll_before_grad 1.91% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.93% : 0.000002s : 12: predicate.merge_addn 1.00% : 0.000002s : 12: predicate.minmaximum_grad 1.99% : 0.000003s : 4: predicate.mutable_eliminate 0.43% : 0.000001s : 4: predicate.opt_reshape 1.68% : 0.000003s : 17: predicate.partial_eliminate 1.07% : 0.000002s : 12: predicate.print_const_string_wrapper 1.63% : 0.000003s : 12: predicate.reduce_eliminate 1.25% : 0.000002s : 13: predicate.redundant_stop_gradient_eliminater 0.81% : 0.000001s : 8: predicate.remove_not_recompute_node 1.82% : 0.000003s : 21: predicate.replace_applicator 0.69% : 0.000001s : 8: predicate.replace_old_param 0.34% : 0.000001s : 4: predicate.reset_defer_inline 1.14% : 0.000002s : 12: predicate.reshape_eliminate 1.07% : 0.000002s : 12: predicate.row_tensor_add_zeros_like 0.73% : 0.000001s : 4: predicate.row_tensor_eliminate 1.04% : 0.000002s : 12: predicate.same_eliminate 0.59% : 0.000001s : 8: predicate.set_cell_output_no_recompute 0.93% : 0.000002s : 8: predicate.special_op_eliminate 0.93% : 0.000002s : 8: predicate.specialize_transform 1.51% : 0.000003s : 12: predicate.split_environ_get_set_with_tuple_value 1.14% : 0.000002s : 12: predicate.stack_unstack_eliminate 0.38% : 0.000001s : 4: predicate.switch_call_monad_eliminater 1.73% : 0.000003s : 17: predicate.switch_defer_inline 2.15% : 0.000004s : 17: predicate.switch_layer_defer_inline 14.18% : 0.000025s : 49: predicate.switch_simplify 1.16% : 0.000002s : 12: predicate.tile_eliminate 1.26% : 0.000002s : 12: predicate.transpose_eliminate 1.73% : 0.000003s : 12: predicate.tuple_list_convert_item_index_to_positive 1.43% : 0.000002s : 12: predicate.tuple_list_get_item_depend_reorder 4.20% : 0.000007s : 21: predicate.tuple_list_get_item_eliminator 1.94% : 0.000003s : 12: predicate.tuple_list_set_item_eliminator 1.16% : 0.000002s : 13: predicate.tuple_to_list_eliminator_ 1.46% : 0.000003s : 17: predicate.updatestate_pure_node_eliminater 2.43% : 0.000004s : 25: predicate.updatestate_useless_node_eliminater 1.43% : 0.000002s : 12: predicate.value_based_eliminate 0.33% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.61% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.002919 18 72.03% : 0.002102s : 12: func_graph_cloner_run.FuncGraphClonerGraph 27.97% : 0.000816s : 6: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 6.243967 76 0.00% : 0.000071s : 1: add_recomputation 0.00% : 0.000126s : 1: auto_monad 0.00% : 0.000030s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.01% : 0.000662s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000013s : 1: convert_after_rewriter 0.00% : 0.000035s : 1: cse_after_recomputation 0.00% : 0.000116s : 1: environ_conv 0.00% : 0.000030s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 0.43% : 0.026722s : 1: jit_opt_a 0.00% : 0.000228s : 1: jit_opt_after_cconv 0.00% : 0.000072s : 1: jit_opt_b 0.01% : 0.000508s : 1: loop_unroll 0.01% : 0.000870s : 1: mutable_eliminate 0.02% : 0.001128s : 26: opt.transform.jit_opt_a 0.00% : 0.000067s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000036s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000022s : 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% : 0.000595s : 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% : 0.000014s : 1: pre_auto_parallel 0.01% : 0.000581s : 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 0.05% : 0.002886s : 1: renormalize.infer 0.02% : 0.001012s : 1: renormalize.specialize 0.00% : 0.000142s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000082s : 1: rewriter_after_opt_a 0.00% : 0.000109s : 1: rewriter_before_opt_a 0.00% : 0.000095s : 1: symbol_engine_optimizer 64.15% : 4.005741s : 1: task_emit 35.26% : 2.201644s : 1: type_inference 0.00% : 0.000104s : 1: validate TotalTime = 1.60213, [33] [bootstrap]: 0.00054574 [type_inference]: 1.4481 [event_method]: 0.00073579 [auto_monad]: 0.00025925 [graph_reusing]: 1.215e-05 [pre_auto_parallel]: 4.29997e-06 [py_interpret_to_execute]: 7.97e-05 [rewriter_before_opt_a]: 0.0001767 [expand_dump_flag]: 4.63001e-06 [jit_opt_a]: 0.148638, [2] [Cycle 1]: 0.143061, [27] [switch_simplify]: 0.00024941 [loop_unroll]: 6.528e-05 [a_1]: 0.00160117 [with_stream_mark]: 3.185e-05 [recompute_prepare]: 3.009e-05 [updatestate_depend_eliminate]: 1.124e-05 [updatestate_assign_eliminate]: 8.12e-06 [updatestate_loads_eliminate]: 7.08e-06 [parameter_eliminate]: 3.61999e-06 [specialize_transform]: 1.793e-05 [updatestate_useless_node_eliminater]: 1.43e-05 [accelerated_algorithm]: 1.539e-05 [meta_shard_fg_expand]: 4.61002e-06 [get_grad_eliminate_]: 1.394e-05 [merge_forward]: 9.39998e-06 [cell_reuse_recompute_pass]: 1.15001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.35e-05 [j_node_and_user_rematch]: 4.058e-05 [meta_fg_expand]: 0.00230723 [replace_old_param]: 7.789e-05 [inline_without_move]: 6.697e-05 [renormalize]: 0.138084 [add_forward_monad_depend]: 1.094e-05 [auto_monad_grad]: 3.12002e-06 [auto_monad_eliminator]: 1.506e-05 [cse]: 3.068e-05 [replace_applicator]: 2.369e-05 [Cycle 2]: 0.00051757, [27] [switch_simplify]: 6.14001e-06 [loop_unroll]: 5.23002e-06 [a_1]: 7.646e-05 [with_stream_mark]: 1.539e-05 [recompute_prepare]: 5.15001e-06 [updatestate_depend_eliminate]: 3.31999e-06 [updatestate_assign_eliminate]: 2.88998e-06 [updatestate_loads_eliminate]: 2.46e-06 [parameter_eliminate]: 1.99999e-06 [specialize_transform]: 4.13001e-06 [updatestate_useless_node_eliminater]: 3.52997e-06 [accelerated_algorithm]: 4.12998e-06 [meta_shard_fg_expand]: 2.34001e-06 [get_grad_eliminate_]: 3.45e-06 [merge_forward]: 4.03001e-06 [cell_reuse_recompute_pass]: 3.33e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.799e-05 [j_node_and_user_rematch]: 8.14002e-06 [meta_fg_expand]: 0.00016954 [replace_old_param]: 6.16e-06 [inline_without_move]: 4.4e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.52001e-06 [auto_monad_grad]: 1.33002e-06 [auto_monad_eliminator]: 7.2e-06 [cse]: 1.591e-05 [replace_applicator]: 4.70999e-06 [py_interpret_to_execute_after_opt_a]: 1.356e-05 [rewriter_after_opt_a]: 0.00036612 [convert_after_rewriter]: 1.279e-05 [order_py_execute_after_rewriter]: 6.07999e-06 [mutable_eliminate]: 0.00078633 [jit_opt_b]: 5.334e-05, [1] [Cycle 1]: 4.47e-05, [2] [frontend_op_eliminate]: 1.508e-05 [inline_after_opt_a]: 1.598e-05 [cconv]: 3.274e-05 [loop_unroll]: 0.00048311 [jit_opt_after_cconv]: 0.00015291, [1] [Cycle 1]: 0.00014521, [11] [c_1]: 1.635e-05 [parameter_eliminate]: 4.08001e-06 [updatestate_depend_eliminate]: 7.35e-06 [updatestate_assign_eliminate]: 2.30002e-06 [updatestate_loads_eliminate]: 2.04999e-06 [cse]: 2.584e-05 [call_graph_tuple_transform]: 1.875e-05 [tuple_list_get_item_eliminator]: 4.55001e-06 [none_parameter_eliminate]: 1.58002e-06 [renormalize]: 6.39993e-07 [switch_simplify]: 5.04998e-06 [remove_dup_value]: 1.639e-05 [partial_unused_args_eliminate]: 2.55002e-06 [environ_conv]: 6.26e-06 [add_recomputation]: 4.923e-05 [cse_after_recomputation]: 2.441e-05, [1] [Cycle 1]: 1.67e-05, [1] [cse]: 9.72999e-06 [auto_monad_reorder]: 1.569e-05 [get_jit_bprop_graph]: 2.33002e-06 [rewriter_after_jit_bprop_graph]: 7.56001e-06 [opt_after_jit_grad]: 0.00107544 [symbol_engine_optimizer]: 0.00010956, [1] [Cycle 1]: 0.00010109, [6] [build]: 5.59e-06 [elim_shapecalc]: 8.33001e-06 [elim_not_effective]: 1.499e-05 [opt_reshape]: 8.24998e-06 [fold_const_symbol]: 9.94999e-06 [renormalize]: 5.8001e-07 [validate]: 4.905e-05 [backend_pass]: 1.19e-06 [task_emit]: 3.056e-05 [execute]: 1.39e-06 Sums bootstrap : 0.000546s : 0.03% type_inference : 1.448103s : 90.72% event_method : 0.000736s : 0.05% auto_monad : 0.000259s : 0.02% graph_reusing : 0.000012s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000080s : 0.00% rewriter_before_opt_a : 0.000177s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000256s : 0.02% jit_opt_a.loop_unroll : 0.000071s : 0.00% jit_opt_a.a_1 : 0.001678s : 0.11% jit_opt_a.with_stream_mark : 0.000047s : 0.00% jit_opt_a.recompute_prepare : 0.000035s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 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 : 0.000022s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000018s : 0.00% jit_opt_a.accelerated_algorithm : 0.000020s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000007s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 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 : 0.000051s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000049s : 0.00% jit_opt_a.meta_fg_expand : 0.002477s : 0.16% jit_opt_a.replace_old_param : 0.000084s : 0.01% jit_opt_a.inline_without_move : 0.000071s : 0.00% jit_opt_a.renormalize : 0.138084s : 8.65% jit_opt_a.add_forward_monad_depend : 0.000013s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000022s : 0.00% jit_opt_a.cse : 0.000047s : 0.00% jit_opt_a.replace_applicator : 0.000028s : 0.00% py_interpret_to_execute_after_opt_a : 0.000014s : 0.00% rewriter_after_opt_a : 0.000366s : 0.02% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000786s : 0.05% jit_opt_b.frontend_op_eliminate : 0.000015s : 0.00% jit_opt_b.inline_after_opt_a : 0.000016s : 0.00% cconv : 0.000033s : 0.00% loop_unroll : 0.000483s : 0.03% jit_opt_after_cconv.c_1 : 0.000016s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.cse : 0.000026s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000019s : 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 : 0.000016s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000006s : 0.00% add_recomputation : 0.000049s : 0.00% cse_after_recomputation.cse : 0.000010s : 0.00% auto_monad_reorder : 0.000016s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.001075s : 0.07% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000008s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000015s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000010s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000049s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 0.000031s : 0.00% execute : 0.000001s : 0.00% Time group info: ------[substitution.] 0.000568 65 0.40% : 0.000002s : 1: substitution.elim_not_effective 0.22% : 0.000001s : 1: substitution.fold_const_symbol 0.83% : 0.000005s : 1: substitution.graph_param_transform 72.58% : 0.000413s : 13: substitution.inline 4.17% : 0.000024s : 2: substitution.inline_without_move 3.63% : 0.000021s : 9: substitution.j_node_and_user_rematch 0.70% : 0.000004s : 2: substitution.minmaximum_grad 4.23% : 0.000024s : 9: substitution.partial_eliminate 1.75% : 0.000010s : 9: substitution.remove_not_recompute_node 0.55% : 0.000003s : 1: substitution.replace_applicator 1.21% : 0.000007s : 6: substitution.replace_old_param 0.79% : 0.000004s : 1: substitution.set_cell_output_no_recompute 3.16% : 0.000018s : 3: substitution.switch_simplify 1.57% : 0.000009s : 2: substitution.tuple_list_convert_item_index_to_positive 1.11% : 0.000006s : 2: substitution.tuple_list_get_item_depend_reorder 3.11% : 0.000018s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.447955 2 99.64% : 1.442743s : 1: type_inference.infer 0.36% : 0.005212s : 1: type_inference.specialize ------[replace.] 0.000214 17 59.72% : 0.000128s : 13: replace.inline 35.13% : 0.000075s : 3: replace.switch_simplify 5.15% : 0.000011s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000424 17 95.26% : 0.000404s : 13: match.inline 3.68% : 0.000016s : 3: match.switch_simplify 1.05% : 0.000004s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000260 1539 1.58% : 0.000004s : 26: predicate.accumulaten_eliminater 0.70% : 0.000002s : 1: predicate.ad_related_special_op_eliminate 1.27% : 0.000003s : 26: predicate.addn_check_dump 1.39% : 0.000004s : 26: predicate.addn_zero_filter 2.03% : 0.000005s : 26: predicate.arithmetic_simplify 1.50% : 0.000004s : 26: predicate.cast_eliminate 0.13% : 0.000000s : 1: predicate.check_bprop_eliminate 1.50% : 0.000004s : 26: predicate.compare_switch_simplify 1.32% : 0.000003s : 26: predicate.depend_value_elim 1.22% : 0.000003s : 26: predicate.dict_get_item_const_eliminator 1.30% : 0.000003s : 26: predicate.dict_get_item_eliminator 1.37% : 0.000004s : 26: predicate.dict_set_item_eliminator 0.78% : 0.000002s : 1: predicate.dumpgradient_eliminate 0.15% : 0.000000s : 1: predicate.elim_not_effective 0.20% : 0.000001s : 1: predicate.elim_shapecalc_of_broadcastargs 1.44% : 0.000004s : 26: predicate.environ_add_const_eliminate 1.28% : 0.000003s : 26: predicate.environ_get_add_eliminate 1.28% : 0.000003s : 26: predicate.environ_get_depend_swap 1.34% : 0.000003s : 26: predicate.environ_get_eliminate 1.29% : 0.000003s : 26: predicate.environ_get_set_eliminate 0.05% : 0.000000s : 1: predicate.fold_const_symbol 0.83% : 0.000002s : 13: predicate.get_grad_eliminate 0.07% : 0.000000s : 1: predicate.graph_param_transform 4.74% : 0.000012s : 42: predicate.inline 2.64% : 0.000007s : 35: predicate.inline_without_move 0.36% : 0.000001s : 13: predicate.j_node_and_user_rematch 1.12% : 0.000003s : 13: predicate.less_batch_normalization 1.52% : 0.000004s : 27: predicate.list_to_tuple_eliminator_ 1.59% : 0.000004s : 28: predicate.load_eliminater 0.85% : 0.000002s : 1: predicate.loop_unroll_after_grad 4.03% : 0.000010s : 67: predicate.loop_unroll_before_grad 1.72% : 0.000004s : 27: predicate.make_slice_get_slice_eliminator 1.47% : 0.000004s : 26: predicate.merge_addn 1.29% : 0.000003s : 26: predicate.minmaximum_grad 0.96% : 0.000002s : 1: predicate.mutable_eliminate 0.38% : 0.000001s : 1: predicate.opt_reshape 2.19% : 0.000006s : 28: predicate.partial_eliminate 1.49% : 0.000004s : 26: predicate.print_const_string_wrapper 1.71% : 0.000004s : 26: predicate.reduce_eliminate 1.57% : 0.000004s : 27: predicate.redundant_stop_gradient_eliminater 0.57% : 0.000001s : 13: predicate.remove_not_recompute_node 1.55% : 0.000004s : 29: predicate.replace_applicator 1.45% : 0.000004s : 35: predicate.replace_old_param 0.08% : 0.000000s : 1: predicate.reset_defer_inline 1.47% : 0.000004s : 26: predicate.reshape_eliminate 1.45% : 0.000004s : 26: predicate.row_tensor_add_zeros_like 0.26% : 0.000001s : 1: predicate.row_tensor_eliminate 1.37% : 0.000004s : 26: predicate.same_eliminate 0.45% : 0.000001s : 13: predicate.set_cell_output_no_recompute 0.35% : 0.000001s : 2: predicate.special_op_eliminate 1.02% : 0.000003s : 13: predicate.specialize_transform 1.60% : 0.000004s : 26: predicate.split_environ_get_set_with_tuple_value 1.59% : 0.000004s : 26: predicate.stack_unstack_eliminate 0.11% : 0.000000s : 1: predicate.switch_call_monad_eliminater 3.23% : 0.000008s : 40: predicate.switch_defer_inline 2.52% : 0.000007s : 40: predicate.switch_layer_defer_inline 8.26% : 0.000021s : 114: predicate.switch_simplify 1.39% : 0.000004s : 26: predicate.tile_eliminate 1.40% : 0.000004s : 26: predicate.transpose_eliminate 1.71% : 0.000004s : 26: predicate.tuple_list_convert_item_index_to_positive 1.65% : 0.000004s : 26: predicate.tuple_list_get_item_depend_reorder 3.32% : 0.000009s : 29: predicate.tuple_list_get_item_eliminator 1.83% : 0.000005s : 26: predicate.tuple_list_set_item_eliminator 1.54% : 0.000004s : 27: predicate.tuple_to_list_eliminator_ 1.45% : 0.000004s : 28: predicate.updatestate_pure_node_eliminater 2.51% : 0.000007s : 41: predicate.updatestate_useless_node_eliminater 1.80% : 0.000005s : 26: predicate.value_based_eliminate 0.08% : 0.000000s : 1: predicate.virtual_view_grad_eliminate 0.30% : 0.000001s : 1: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004098 37 81.44% : 0.003337s : 21: func_graph_cloner_run.FuncGraphClonerGraph 18.56% : 0.000761s : 16: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.742650 76 0.00% : 0.000053s : 1: add_recomputation 0.02% : 0.000269s : 1: auto_monad 0.00% : 0.000019s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.03% : 0.000576s : 1: bootstrap 0.00% : 0.000035s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.00% : 0.000027s : 1: cse_after_recomputation 0.00% : 0.000009s : 1: environ_conv 0.04% : 0.000747s : 1: event_method 0.00% : 0.000004s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000016s : 1: graph_reusing 8.53% : 0.148643s : 1: jit_opt_a 0.01% : 0.000157s : 1: jit_opt_after_cconv 0.00% : 0.000057s : 1: jit_opt_b 0.03% : 0.000491s : 1: loop_unroll 0.05% : 0.000796s : 1: mutable_eliminate 0.14% : 0.002353s : 26: opt.transform.jit_opt_a 0.00% : 0.000040s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000023s : 4: opt.transform.jit_opt_b 0.00% : 0.000012s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.00% : 0.000026s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000035s : 4: opt.transform.symbol_engine_opt 0.06% : 0.001088s : 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% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000083s : 1: py_interpret_to_execute 0.00% : 0.000016s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000019s : 1: remove_dup_value 7.88% : 0.137331s : 1: renormalize.infer 0.04% : 0.000739s : 1: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000373s : 1: rewriter_after_opt_a 0.01% : 0.000181s : 1: rewriter_before_opt_a 0.01% : 0.000114s : 1: symbol_engine_optimizer 0.00% : 0.000036s : 1: task_emit 83.10% : 1.448127s : 1: type_inference 0.00% : 0.000074s : 1: validate . [hook] pytest_runtest_teardown:test_squeeze_zero_bias[KBK] tests/st/mint/test_squeeze.py::test_squeeze_zero_bias[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 229.85s (0:03:49) ==================