==================================================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_001/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_select.py . [hook] pytest_runtest_teardown:test_select_high_dimension[pynative] tests/st/mint/test_select.py::test_select_high_dimension[pynative],max_mem:2.0M TotalTime = 0.583613, [30] [bootstrap]: 0.00075373 [type_inference]: 0.447867 [event_method]: 1.647e-05 [auto_monad]: 0.00016279 [graph_reusing]: 6.79999e-06 [pre_auto_parallel]: 1.49e-05 [py_interpret_to_execute]: 0.00018252 [rewriter_before_opt_a]: 6.325e-05 [expand_dump_flag]: 3.03e-06 [jit_opt_a]: 0.130458, [2] [Cycle 1]: 0.00211119, [27] [switch_simplify]: 5.708e-05 [loop_unroll]: 1.916e-05 [a_1]: 0.00043764 [with_stream_mark]: 3.094e-05 [recompute_prepare]: 1.146e-05 [updatestate_depend_eliminate]: 7.2e-06 [updatestate_assign_eliminate]: 9.82001e-06 [updatestate_loads_eliminate]: 5.44e-06 [parameter_eliminate]: 1.92999e-06 [specialize_transform]: 9.04e-06 [updatestate_useless_node_eliminater]: 1.163e-05 [accelerated_algorithm]: 8.72e-06 [meta_shard_fg_expand]: 2.74999e-06 [get_grad_eliminate_]: 7.83001e-06 [merge_forward]: 6.49001e-06 [cell_reuse_recompute_pass]: 1.14998e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.336e-05 [j_node_and_user_rematch]: 1.442e-05 [meta_fg_expand]: 3.61001e-06 [replace_old_param]: 1.255e-05 [inline_without_move]: 8.47998e-06 [renormalize]: 0.00107631 [add_forward_monad_depend]: 1.533e-05 [auto_monad_grad]: 2.71e-06 [auto_monad_eliminator]: 2.997e-05 [cse]: 5.157e-05 [replace_applicator]: 2.24e-05 [Cycle 2]: 0.0005128, [27] [switch_simplify]: 8.87e-06 [loop_unroll]: 8.12998e-06 [a_1]: 0.00017269 [with_stream_mark]: 1.868e-05 [recompute_prepare]: 8.79998e-06 [updatestate_depend_eliminate]: 9.49e-06 [updatestate_assign_eliminate]: 5.96003e-06 [updatestate_loads_eliminate]: 5.16998e-06 [parameter_eliminate]: 2.11e-06 [specialize_transform]: 8.58001e-06 [updatestate_useless_node_eliminater]: 1.172e-05 [accelerated_algorithm]: 8.32e-06 [meta_shard_fg_expand]: 2.81e-06 [get_grad_eliminate_]: 7.38999e-06 [merge_forward]: 5.78002e-06 [cell_reuse_recompute_pass]: 2.27001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.829e-05 [j_node_and_user_rematch]: 1.181e-05 [meta_fg_expand]: 3.72998e-06 [replace_old_param]: 1.178e-05 [inline_without_move]: 7.97998e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.94999e-06 [auto_monad_grad]: 1.64e-06 [auto_monad_eliminator]: 1.299e-05 [cse]: 1.995e-05 [replace_applicator]: 9.48002e-06 [py_interpret_to_execute_after_opt_a]: 1.98e-05 [rewriter_after_opt_a]: 0.00049093 [convert_after_rewriter]: 1.78e-05 [order_py_execute_after_rewriter]: 7.78999e-06 [mutable_eliminate]: 0.00081404 [jit_opt_b]: 7.655e-05, [1] [Cycle 1]: 6.7e-05, [2] [frontend_op_eliminate]: 2.54e-05 [inline_after_opt_a]: 2.722e-05 [cconv]: 4.038e-05 [loop_unroll]: 0.00065569 [jit_opt_after_cconv]: 0.00025631, [1] [Cycle 1]: 0.00024805, [11] [c_1]: 5.511e-05 [parameter_eliminate]: 5.84999e-06 [updatestate_depend_eliminate]: 1.473e-05 [updatestate_assign_eliminate]: 5.57999e-06 [updatestate_loads_eliminate]: 5.11002e-06 [cse]: 4.844e-05 [call_graph_tuple_transform]: 3.705e-05 [tuple_list_get_item_eliminator]: 9.54e-06 [none_parameter_eliminate]: 1.57001e-06 [renormalize]: 4.19997e-07 [switch_simplify]: 8.82e-06 [remove_dup_value]: 2.576e-05 [partial_unused_args_eliminate]: 2.64001e-06 [environ_conv]: 2.274e-05 [add_recomputation]: 0.00018723 [cse_after_recomputation]: 4.209e-05, [1] [Cycle 1]: 3.4e-05, [1] [cse]: 2.331e-05 [auto_monad_reorder]: 8.334e-05 [get_jit_bprop_graph]: 3.02002e-06 [rewriter_after_jit_bprop_graph]: 0.00015756 [opt_after_jit_grad]: 0.00063231 [symbol_engine_optimizer]: 0.00010758, [1] [Cycle 1]: 9.895e-05, [6] [build]: 7.75e-06 [elim_shapecalc]: 1.193e-05 [elim_not_effective]: 2.119e-05 [opt_reshape]: 1.015e-05 [fold_const_symbol]: 1.468e-05 [renormalize]: 7.09988e-07 [validate]: 7.466e-05 Sums bootstrap : 0.000754s : 0.17% type_inference : 0.447867s : 98.45% event_method : 0.000016s : 0.00% auto_monad : 0.000163s : 0.04% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000015s : 0.00% py_interpret_to_execute : 0.000183s : 0.04% rewriter_before_opt_a : 0.000063s : 0.01% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000066s : 0.01% jit_opt_a.loop_unroll : 0.000027s : 0.01% jit_opt_a.a_1 : 0.000610s : 0.13% jit_opt_a.with_stream_mark : 0.000050s : 0.01% jit_opt_a.recompute_prepare : 0.000020s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000017s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000016s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000011s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000018s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000023s : 0.01% jit_opt_a.accelerated_algorithm : 0.000017s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000015s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000042s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.01% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.01% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.001076s : 0.24% jit_opt_a.add_forward_monad_depend : 0.000017s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000043s : 0.01% jit_opt_a.cse : 0.000072s : 0.02% jit_opt_a.replace_applicator : 0.000032s : 0.01% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000491s : 0.11% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000814s : 0.18% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.01% jit_opt_b.inline_after_opt_a : 0.000027s : 0.01% cconv : 0.000040s : 0.01% loop_unroll : 0.000656s : 0.14% jit_opt_after_cconv.c_1 : 0.000055s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000048s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000037s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000010s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000026s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000023s : 0.00% add_recomputation : 0.000187s : 0.04% cse_after_recomputation.cse : 0.000023s : 0.01% auto_monad_reorder : 0.000083s : 0.02% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000158s : 0.03% opt_after_jit_grad : 0.000632s : 0.14% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000075s : 0.02% Time group info: ------[substitution.] 0.000232 43 4.55% : 0.000011s : 2: substitution.depend_value_elim 1.30% : 0.000003s : 4: substitution.elim_not_effective 1.08% : 0.000003s : 4: substitution.fold_const_symbol 8.91% : 0.000021s : 5: substitution.graph_param_transform 65.58% : 0.000152s : 2: substitution.inline 1.86% : 0.000004s : 8: substitution.j_node_and_user_rematch 3.28% : 0.000008s : 8: substitution.remove_not_recompute_node 2.86% : 0.000007s : 2: substitution.replace_old_param 5.76% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.81% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.447787 2 99.76% : 0.446713s : 1: type_inference.infer 0.24% : 0.001074s : 1: type_inference.specialize ------[replace.] 0.000033 2 100.00% : 0.000033s : 2: replace.inline ------[match.] 0.000150 2 100.00% : 0.000150s : 2: match.inline ------[predicate.] 0.000149 767 1.35% : 0.000002s : 11: predicate.accumulaten_eliminater 1.76% : 0.000003s : 5: predicate.ad_related_special_op_eliminate 1.03% : 0.000002s : 11: predicate.addn_check_dump 1.29% : 0.000002s : 11: predicate.addn_zero_filter 1.76% : 0.000003s : 11: predicate.arithmetic_simplify 1.19% : 0.000002s : 11: predicate.cast_eliminate 0.64% : 0.000001s : 5: predicate.check_bprop_eliminate 1.15% : 0.000002s : 11: predicate.compare_switch_simplify 1.39% : 0.000002s : 11: predicate.depend_value_elim 1.02% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.14% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.15% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.19% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.52% : 0.000001s : 5: predicate.elim_not_effective 0.88% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.17% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.06% : 0.000002s : 11: predicate.environ_get_add_eliminate 0.96% : 0.000001s : 11: predicate.environ_get_depend_swap 1.00% : 0.000001s : 11: predicate.environ_get_eliminate 1.04% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.30% : 0.000000s : 5: predicate.fold_const_symbol 1.33% : 0.000002s : 10: predicate.get_grad_eliminate 0.43% : 0.000001s : 5: predicate.graph_param_transform 5.81% : 0.000009s : 23: predicate.inline 1.17% : 0.000002s : 10: predicate.inline_without_move 0.49% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.63% : 0.000002s : 10: predicate.less_batch_normalization 1.12% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.70% : 0.000003s : 16: predicate.load_eliminater 2.65% : 0.000004s : 5: predicate.loop_unroll_after_grad 2.61% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.18% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.41% : 0.000002s : 11: predicate.merge_addn 1.13% : 0.000002s : 11: predicate.minmaximum_grad 2.60% : 0.000004s : 5: predicate.mutable_eliminate 0.85% : 0.000001s : 5: predicate.opt_reshape 2.17% : 0.000003s : 16: predicate.partial_eliminate 1.17% : 0.000002s : 11: predicate.print_const_string_wrapper 1.65% : 0.000002s : 11: predicate.reduce_eliminate 1.43% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.88% : 0.000001s : 10: predicate.remove_not_recompute_node 1.85% : 0.000003s : 21: predicate.replace_applicator 0.79% : 0.000001s : 10: predicate.replace_old_param 0.82% : 0.000001s : 5: predicate.reset_defer_inline 1.15% : 0.000002s : 11: predicate.reshape_eliminate 1.21% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.12% : 0.000002s : 5: predicate.row_tensor_eliminate 1.15% : 0.000002s : 11: predicate.same_eliminate 0.88% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.49% : 0.000002s : 10: predicate.special_op_eliminate 1.27% : 0.000002s : 10: predicate.specialize_transform 1.21% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.31% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.88% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.57% : 0.000002s : 13: predicate.switch_defer_inline 1.27% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.63% : 0.000008s : 38: predicate.switch_simplify 1.02% : 0.000002s : 11: predicate.tile_eliminate 1.13% : 0.000002s : 11: predicate.transpose_eliminate 1.35% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.19% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 4.10% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.57% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.07% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.55% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.26% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.43% : 0.000002s : 11: predicate.value_based_eliminate 0.51% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.84% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000341 5 7.69% : 0.000026s : 1: func_graph_cloner_run.FuncGraphClonerGraph 92.31% : 0.000314s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.585601 72 0.03% : 0.000194s : 1: add_recomputation 0.03% : 0.000168s : 1: auto_monad 0.02% : 0.000089s : 1: auto_monad_reorder 0.13% : 0.000782s : 1: bootstrap 0.01% : 0.000043s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.01% : 0.000045s : 1: cse_after_recomputation 0.00% : 0.000026s : 1: environ_conv 0.00% : 0.000022s : 1: event_method 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 22.28% : 0.130462s : 1: jit_opt_a 0.04% : 0.000260s : 1: jit_opt_after_cconv 0.01% : 0.000080s : 1: jit_opt_b 0.11% : 0.000668s : 1: loop_unroll 0.14% : 0.000830s : 1: mutable_eliminate 0.15% : 0.000893s : 26: opt.transform.jit_opt_a 0.02% : 0.000106s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000026s : 1: opt.transform.mutable_eliminate 0.01% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000054s : 4: opt.transform.symbol_engine_opt 0.11% : 0.000643s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000017s : 1: pre_auto_parallel 0.03% : 0.000188s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000028s : 1: remove_dup_value 0.11% : 0.000658s : 1: renormalize.infer 0.07% : 0.000407s : 1: renormalize.specialize 0.03% : 0.000161s : 1: rewriter_after_jit_bprop_graph 0.09% : 0.000498s : 1: rewriter_after_opt_a 0.01% : 0.000067s : 1: rewriter_before_opt_a 0.02% : 0.000111s : 1: symbol_engine_optimizer 76.48% : 0.447888s : 1: type_inference TotalTime = 1.2785, [30] [bootstrap]: 0.00049656 [type_inference]: 0.586215 [event_method]: 0.00020449 [auto_monad]: 0.0002958 [graph_reusing]: 1.064e-05 [pre_auto_parallel]: 3.63999e-06 [py_interpret_to_execute]: 4.776e-05 [rewriter_before_opt_a]: 0.00015247 [expand_dump_flag]: 4.34002e-06 [jit_opt_a]: 0.68662, [4] [Cycle 1]: 0.55517, [27] [switch_simplify]: 0.00022265 [loop_unroll]: 5.716e-05 [a_1]: 0.00146971 [with_stream_mark]: 4.248e-05 [recompute_prepare]: 3.592e-05 [updatestate_depend_eliminate]: 1.473e-05 [updatestate_assign_eliminate]: 1.147e-05 [updatestate_loads_eliminate]: 1.053e-05 [parameter_eliminate]: 3.38999e-06 [specialize_transform]: 2.184e-05 [updatestate_useless_node_eliminater]: 2.619e-05 [accelerated_algorithm]: 1.982e-05 [meta_shard_fg_expand]: 5.84e-06 [get_grad_eliminate_]: 2.177e-05 [merge_forward]: 1.369e-05 [cell_reuse_recompute_pass]: 1.74998e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.091e-05 [j_node_and_user_rematch]: 3.376e-05 [meta_fg_expand]: 0.138748 [replace_old_param]: 0.00014395 [inline_without_move]: 0.00012319 [renormalize]: 0.317249 [add_forward_monad_depend]: 2.757e-05 [auto_monad_grad]: 1.165e-05 [auto_monad_eliminator]: 0.00012003 [cse]: 0.0960422 [replace_applicator]: 0.00028305 [Cycle 2]: 0.00732547, [27] [switch_simplify]: 8.853e-05 [loop_unroll]: 8.327e-05 [a_1]: 0.00403259 [with_stream_mark]: 4.887e-05 [recompute_prepare]: 3.977e-05 [updatestate_depend_eliminate]: 1.617e-05 [updatestate_assign_eliminate]: 1.598e-05 [updatestate_loads_eliminate]: 1.475e-05 [parameter_eliminate]: 4.50001e-06 [specialize_transform]: 2.465e-05 [updatestate_useless_node_eliminater]: 0.00011312 [accelerated_algorithm]: 3.85e-05 [meta_shard_fg_expand]: 5.35001e-06 [get_grad_eliminate_]: 1.543e-05 [merge_forward]: 9.26002e-06 [cell_reuse_recompute_pass]: 1.49e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.446e-05 [j_node_and_user_rematch]: 2.575e-05 [meta_fg_expand]: 0.00012724 [replace_old_param]: 2.646e-05 [inline_without_move]: 1.476e-05 [renormalize]: 0.00202319 [add_forward_monad_depend]: 1.055e-05 [auto_monad_grad]: 2.86e-06 [auto_monad_eliminator]: 3.736e-05 [cse]: 0.00016309 [replace_applicator]: 3.445e-05 [Cycle 3]: 0.00188376, [27] [switch_simplify]: 1.511e-05 [loop_unroll]: 1.375e-05 [a_1]: 0.00033461 [with_stream_mark]: 2.25e-05 [recompute_prepare]: 1.36e-05 [updatestate_depend_eliminate]: 3.963e-05 [updatestate_assign_eliminate]: 7.75e-06 [updatestate_loads_eliminate]: 7.56001e-06 [parameter_eliminate]: 2.33998e-06 [specialize_transform]: 1.26e-05 [updatestate_useless_node_eliminater]: 1.577e-05 [accelerated_algorithm]: 1.731e-05 [meta_shard_fg_expand]: 3.11001e-06 [get_grad_eliminate_]: 1.107e-05 [merge_forward]: 7.70998e-06 [cell_reuse_recompute_pass]: 3.73001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.77e-05 [j_node_and_user_rematch]: 1.977e-05 [meta_fg_expand]: 4.97e-06 [replace_old_param]: 1.595e-05 [inline_without_move]: 1.18e-05 [renormalize]: 0.00096617 [add_forward_monad_depend]: 6.29001e-06 [auto_monad_grad]: 2.37999e-06 [auto_monad_eliminator]: 2.494e-05 [cse]: 8.862e-05 [replace_applicator]: 2.368e-05 [Cycle 4]: 0.058233, [27] [switch_simplify]: 1.284e-05 [loop_unroll]: 1.129e-05 [a_1]: 0.00025872 [with_stream_mark]: 1.528e-05 [recompute_prepare]: 1.189e-05 [updatestate_depend_eliminate]: 7.82002e-06 [updatestate_assign_eliminate]: 7.05998e-06 [updatestate_loads_eliminate]: 7.67998e-06 [parameter_eliminate]: 1.30999e-06 [specialize_transform]: 1.2e-05 [updatestate_useless_node_eliminater]: 1.468e-05 [accelerated_algorithm]: 1.557e-05 [meta_shard_fg_expand]: 2.91999e-06 [get_grad_eliminate_]: 1.107e-05 [merge_forward]: 6.98998e-06 [cell_reuse_recompute_pass]: 1.94e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.412e-05 [j_node_and_user_rematch]: 2.026e-05 [meta_fg_expand]: 4.4e-06 [replace_old_param]: 1.507e-05 [inline_without_move]: 1.121e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.56998e-06 [auto_monad_grad]: 1.65001e-06 [auto_monad_eliminator]: 1.643e-05 [cse]: 3.789e-05 [replace_applicator]: 1.112e-05 [py_interpret_to_execute_after_opt_a]: 4.951e-05 [rewriter_after_opt_a]: 0.00029956 [convert_after_rewriter]: 1.842e-05 [order_py_execute_after_rewriter]: 1.005e-05 [mutable_eliminate]: 0.00084962 [jit_opt_b]: 0.00010427, [1] [Cycle 1]: 9.374e-05, [2] [frontend_op_eliminate]: 3.794e-05 [inline_after_opt_a]: 4.061e-05 [cconv]: 4.808e-05 [loop_unroll]: 0.00054073 [jit_opt_after_cconv]: 0.00034352, [1] [Cycle 1]: 0.00033538, [11] [c_1]: 7.696e-05 [parameter_eliminate]: 5.44e-06 [updatestate_depend_eliminate]: 1.6e-05 [updatestate_assign_eliminate]: 7.64002e-06 [updatestate_loads_eliminate]: 6.94999e-06 [cse]: 9.105e-05 [call_graph_tuple_transform]: 3.604e-05 [tuple_list_get_item_eliminator]: 1.392e-05 [none_parameter_eliminate]: 1.54998e-06 [renormalize]: 1.25001e-06 [switch_simplify]: 1.381e-05 [remove_dup_value]: 0.00072682 [partial_unused_args_eliminate]: 5.33002e-06 [environ_conv]: 1.771e-05 [add_recomputation]: 0.00011476 [cse_after_recomputation]: 7.201e-05, [1] [Cycle 1]: 6.254e-05, [1] [cse]: 4.722e-05 [auto_monad_reorder]: 3.734e-05 [get_jit_bprop_graph]: 2.58e-06 [rewriter_after_jit_bprop_graph]: 9.54999e-06 [opt_after_jit_grad]: 0.00069306 [symbol_engine_optimizer]: 0.00014618, [1] [Cycle 1]: 0.00013758, [6] [build]: 1.83e-05 [elim_shapecalc]: 1.748e-05 [elim_not_effective]: 3.114e-05 [opt_reshape]: 1.367e-05 [fold_const_symbol]: 2.14e-05 [renormalize]: 1.60001e-06 [validate]: 6.986e-05 Sums bootstrap : 0.000497s : 0.04% type_inference : 0.586215s : 50.73% event_method : 0.000204s : 0.02% auto_monad : 0.000296s : 0.03% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000048s : 0.00% rewriter_before_opt_a : 0.000152s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000339s : 0.03% jit_opt_a.loop_unroll : 0.000165s : 0.01% jit_opt_a.a_1 : 0.006096s : 0.53% jit_opt_a.with_stream_mark : 0.000129s : 0.01% jit_opt_a.recompute_prepare : 0.000101s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000078s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000042s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000041s : 0.00% jit_opt_a.parameter_eliminate : 0.000012s : 0.00% jit_opt_a.specialize_transform : 0.000071s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000170s : 0.01% jit_opt_a.accelerated_algorithm : 0.000091s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000017s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000059s : 0.01% jit_opt_a.merge_forward : 0.000038s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000127s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000100s : 0.01% jit_opt_a.meta_fg_expand : 0.138885s : 12.02% jit_opt_a.replace_old_param : 0.000201s : 0.02% jit_opt_a.inline_without_move : 0.000161s : 0.01% jit_opt_a.renormalize : 0.320238s : 27.71% jit_opt_a.add_forward_monad_depend : 0.000046s : 0.00% jit_opt_a.auto_monad_grad : 0.000019s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000199s : 0.02% jit_opt_a.cse : 0.096332s : 8.34% jit_opt_a.replace_applicator : 0.000352s : 0.03% py_interpret_to_execute_after_opt_a : 0.000050s : 0.00% rewriter_after_opt_a : 0.000300s : 0.03% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000850s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000038s : 0.00% jit_opt_b.inline_after_opt_a : 0.000041s : 0.00% cconv : 0.000048s : 0.00% loop_unroll : 0.000541s : 0.05% jit_opt_after_cconv.c_1 : 0.000077s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000091s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000036s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000014s : 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 : 0.000014s : 0.00% remove_dup_value : 0.000727s : 0.06% partial_unused_args_eliminate : 0.000005s : 0.00% environ_conv : 0.000018s : 0.00% add_recomputation : 0.000115s : 0.01% cse_after_recomputation.cse : 0.000047s : 0.00% auto_monad_reorder : 0.000037s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000693s : 0.06% symbol_engine_optimizer.build : 0.000018s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000031s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000014s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000021s : 0.00% symbol_engine_optimizer.renormalize : 0.000002s : 0.00% validate : 0.000070s : 0.01% Time group info: ------[substitution.] 0.002929 291 1.48% : 0.000043s : 12: substitution.depend_value_elim 0.13% : 0.000004s : 7: substitution.elim_not_effective 0.12% : 0.000003s : 7: substitution.fold_const_symbol 29.64% : 0.000868s : 4: substitution.getattr_setattr_resolve 0.33% : 0.000010s : 8: substitution.graph_param_transform 49.51% : 0.001450s : 28: substitution.inline 1.30% : 0.000038s : 4: substitution.inline_without_move 0.64% : 0.000019s : 35: substitution.j_node_and_user_rematch 0.81% : 0.000024s : 3: substitution.less_batch_normalization 0.70% : 0.000020s : 13: substitution.minmaximum_grad 0.47% : 0.000014s : 14: substitution.partial_eliminate 0.88% : 0.000026s : 35: substitution.remove_not_recompute_node 3.03% : 0.000089s : 16: substitution.replace_applicator 0.69% : 0.000020s : 19: substitution.replace_old_param 0.28% : 0.000008s : 2: substitution.set_cell_output_no_recompute 0.53% : 0.000016s : 3: substitution.switch_simplify 1.55% : 0.000045s : 13: substitution.tuple_list_convert_item_index_to_positive 1.05% : 0.000031s : 13: substitution.tuple_list_get_item_depend_reorder 3.68% : 0.000108s : 30: substitution.tuple_list_get_item_eliminator 0.90% : 0.000026s : 9: substitution.updatestate_pure_node_eliminater 2.29% : 0.000067s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.586108 2 99.51% : 0.583223s : 1: type_inference.infer 0.49% : 0.002884s : 1: type_inference.specialize ------[replace.] 0.000935 53 7.39% : 0.000069s : 3: replace.getattr_setattr_resolve 50.39% : 0.000471s : 28: replace.inline 5.65% : 0.000053s : 1: replace.replace_applicator 7.99% : 0.000075s : 3: replace.switch_simplify 22.16% : 0.000207s : 17: replace.tuple_list_get_item_eliminator 6.42% : 0.000060s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002353 53 34.64% : 0.000815s : 3: match.getattr_setattr_resolve 60.86% : 0.001432s : 28: match.inline 1.07% : 0.000025s : 1: match.replace_applicator 0.59% : 0.000014s : 3: match.switch_simplify 2.14% : 0.000050s : 17: match.tuple_list_get_item_eliminator 0.70% : 0.000017s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000918 5919 1.45% : 0.000013s : 99: predicate.accumulaten_eliminater 0.33% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.45% : 0.000013s : 99: predicate.addn_check_dump 1.46% : 0.000013s : 99: predicate.addn_zero_filter 2.11% : 0.000019s : 99: predicate.arithmetic_simplify 1.51% : 0.000014s : 99: predicate.cast_eliminate 0.15% : 0.000001s : 8: predicate.check_bprop_eliminate 1.36% : 0.000013s : 99: predicate.compare_switch_simplify 1.69% : 0.000015s : 99: predicate.depend_value_elim 1.35% : 0.000012s : 99: predicate.dict_get_item_const_eliminator 1.50% : 0.000014s : 99: predicate.dict_get_item_eliminator 1.42% : 0.000013s : 99: predicate.dict_set_item_eliminator 0.23% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 8: predicate.elim_not_effective 0.23% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.47% : 0.000014s : 99: predicate.environ_add_const_eliminate 1.38% : 0.000013s : 99: predicate.environ_get_add_eliminate 1.41% : 0.000013s : 99: predicate.environ_get_depend_swap 1.42% : 0.000013s : 99: predicate.environ_get_eliminate 1.43% : 0.000013s : 99: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.83% : 0.000008s : 42: predicate.get_grad_eliminate 0.81% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.09% : 0.000001s : 8: predicate.graph_param_transform 4.90% : 0.000045s : 160: predicate.inline 2.09% : 0.000019s : 106: predicate.inline_without_move 0.33% : 0.000003s : 42: predicate.j_node_and_user_rematch 1.06% : 0.000010s : 42: predicate.less_batch_normalization 1.73% : 0.000016s : 116: predicate.list_to_tuple_eliminator_ 2.01% : 0.000018s : 124: predicate.load_eliminater 0.53% : 0.000005s : 8: predicate.loop_unroll_after_grad 2.66% : 0.000024s : 171: predicate.loop_unroll_before_grad 1.74% : 0.000016s : 107: predicate.make_slice_get_slice_eliminator 1.47% : 0.000013s : 99: predicate.merge_addn 1.49% : 0.000014s : 99: predicate.minmaximum_grad 0.49% : 0.000004s : 8: predicate.mutable_eliminate 0.16% : 0.000001s : 8: predicate.opt_reshape 2.39% : 0.000022s : 124: predicate.partial_eliminate 1.43% : 0.000013s : 99: predicate.print_const_string_wrapper 1.89% : 0.000017s : 99: predicate.reduce_eliminate 1.86% : 0.000017s : 116: predicate.redundant_stop_gradient_eliminater 0.42% : 0.000004s : 42: predicate.remove_not_recompute_node 2.68% : 0.000025s : 236: predicate.replace_applicator 1.02% : 0.000009s : 106: predicate.replace_old_param 0.15% : 0.000001s : 8: predicate.reset_defer_inline 1.44% : 0.000013s : 99: predicate.reshape_eliminate 1.57% : 0.000014s : 99: predicate.row_tensor_add_zeros_like 0.26% : 0.000002s : 8: predicate.row_tensor_eliminate 1.53% : 0.000014s : 99: predicate.same_eliminate 0.50% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.32% : 0.000003s : 16: predicate.special_op_eliminate 0.96% : 0.000009s : 50: predicate.specialize_transform 1.73% : 0.000016s : 99: predicate.split_environ_get_set_with_tuple_value 1.47% : 0.000014s : 99: predicate.stack_unstack_eliminate 0.16% : 0.000001s : 8: predicate.switch_call_monad_eliminater 3.34% : 0.000031s : 144: predicate.switch_defer_inline 2.49% : 0.000023s : 144: predicate.switch_layer_defer_inline 5.72% : 0.000053s : 329: predicate.switch_simplify 1.47% : 0.000014s : 99: predicate.tile_eliminate 1.51% : 0.000014s : 99: predicate.transpose_eliminate 1.84% : 0.000017s : 99: predicate.tuple_list_convert_item_index_to_positive 1.74% : 0.000016s : 99: predicate.tuple_list_get_item_depend_reorder 3.58% : 0.000033s : 132: predicate.tuple_list_get_item_eliminator 1.81% : 0.000017s : 99: predicate.tuple_list_set_item_eliminator 1.69% : 0.000015s : 116: predicate.tuple_to_list_eliminator_ 1.95% : 0.000018s : 124: predicate.updatestate_pure_node_eliminater 3.01% : 0.000028s : 168: predicate.updatestate_useless_node_eliminater 1.82% : 0.000017s : 99: predicate.value_based_eliminate 0.12% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.20% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.122378 58 98.29% : 0.120279s : 22: func_graph_cloner_run.FuncGraphClonerGraph 0.35% : 0.000433s : 7: func_graph_cloner_run.FuncGraphClonerNode 1.36% : 0.001666s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.607889 104 0.01% : 0.000121s : 1: add_recomputation 0.02% : 0.000306s : 1: auto_monad 0.00% : 0.000041s : 1: auto_monad_reorder 0.03% : 0.000528s : 1: bootstrap 0.00% : 0.000051s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.00% : 0.000075s : 1: cse_after_recomputation 0.00% : 0.000021s : 1: environ_conv 0.01% : 0.000215s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 42.70% : 0.686628s : 1: jit_opt_a 0.02% : 0.000348s : 1: jit_opt_after_cconv 0.01% : 0.000108s : 1: jit_opt_b 0.03% : 0.000552s : 1: loop_unroll 0.05% : 0.000862s : 1: mutable_eliminate 0.49% : 0.007949s : 52: opt.transform.jit_opt_a 0.01% : 0.000136s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000068s : 4: opt.transform.jit_opt_b 0.00% : 0.000027s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000035s : 1: opt.transform.mutable_eliminate 0.00% : 0.000050s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.001005s : 2: opt.transform.opt_resolve 0.00% : 0.000079s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000703s : 1: opt_after_jit_grad 0.00% : 0.000013s : 1: order_py_execute_after_rewriter 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000051s : 1: py_interpret_to_execute 0.00% : 0.000057s : 1: py_interpret_to_execute_after_opt_a 0.05% : 0.000738s : 1: remove_dup_value 19.63% : 0.315593s : 3: renormalize.infer 0.29% : 0.004606s : 3: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000306s : 1: rewriter_after_opt_a 0.01% : 0.000156s : 1: rewriter_before_opt_a 0.01% : 0.000150s : 1: symbol_engine_optimizer 36.46% : 0.586238s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_high_dimension[KBK] tests/st/mint/test_select.py::test_select_high_dimension[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 180.54s (0:03:00) ==================