==================================================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_permute.py . [hook] pytest_runtest_teardown:test_permute_view_backward[pynative] tests/st/mint/test_permute.py::test_permute_view_backward[pynative],max_mem:2.0M TotalTime = 2.33995, [30] [bootstrap]: 0.00062527 [type_inference]: 1.81795 [event_method]: 0.00089098 [auto_monad]: 0.00039233 [graph_reusing]: 1.151e-05 [pre_auto_parallel]: 1.661e-05 [py_interpret_to_execute]: 6.251e-05 [rewriter_before_opt_a]: 0.0263309 [expand_dump_flag]: 1.892e-05 [jit_opt_a]: 0.472055, [4] [Cycle 1]: 0.322412, [27] [switch_simplify]: 0.0001486 [loop_unroll]: 8.065e-05 [a_1]: 0.0332972 [with_stream_mark]: 6.937e-05 [recompute_prepare]: 4.953e-05 [updatestate_depend_eliminate]: 1.788e-05 [updatestate_assign_eliminate]: 2.123e-05 [updatestate_loads_eliminate]: 1.212e-05 [parameter_eliminate]: 4.82e-06 [specialize_transform]: 2.587e-05 [updatestate_useless_node_eliminater]: 3.183e-05 [accelerated_algorithm]: 2.299e-05 [meta_shard_fg_expand]: 1.597e-05 [get_grad_eliminate_]: 2.336e-05 [merge_forward]: 1.579e-05 [cell_reuse_recompute_pass]: 2.07999e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.885e-05 [j_node_and_user_rematch]: 4.61e-05 [meta_fg_expand]: 0.16223 [replace_old_param]: 0.00017767 [inline_without_move]: 0.00016888 [renormalize]: 0.1241 [add_forward_monad_depend]: 4.088e-05 [auto_monad_grad]: 2e-05 [auto_monad_eliminator]: 0.00016216 [cse]: 0.00072413 [replace_applicator]: 0.00033666 [Cycle 2]: 0.0787411, [27] [switch_simplify]: 0.00011619 [loop_unroll]: 0.00011038 [a_1]: 0.0572116 [with_stream_mark]: 7.468e-05 [recompute_prepare]: 4.856e-05 [updatestate_depend_eliminate]: 1.688e-05 [updatestate_assign_eliminate]: 1.908e-05 [updatestate_loads_eliminate]: 1.576e-05 [parameter_eliminate]: 6.96001e-06 [specialize_transform]: 2.755e-05 [updatestate_useless_node_eliminater]: 0.00016352 [accelerated_algorithm]: 2.217e-05 [meta_shard_fg_expand]: 8.40001e-06 [get_grad_eliminate_]: 1.766e-05 [merge_forward]: 1.054e-05 [cell_reuse_recompute_pass]: 1.91e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.105e-05 [j_node_and_user_rematch]: 3.156e-05 [meta_fg_expand]: 0.00034755 [replace_old_param]: 3.392e-05 [inline_without_move]: 1.642e-05 [renormalize]: 0.0195079 [add_forward_monad_depend]: 1.434e-05 [auto_monad_grad]: 3.92998e-06 [auto_monad_eliminator]: 5.109e-05 [cse]: 0.00042843 [replace_applicator]: 4.647e-05 [Cycle 3]: 0.00253865, [27] [switch_simplify]: 1.974e-05 [loop_unroll]: 1.676e-05 [a_1]: 0.00049957 [with_stream_mark]: 3.677e-05 [recompute_prepare]: 2.036e-05 [updatestate_depend_eliminate]: 5.256e-05 [updatestate_assign_eliminate]: 7.82e-06 [updatestate_loads_eliminate]: 7.28e-06 [parameter_eliminate]: 3.55998e-06 [specialize_transform]: 1.904e-05 [updatestate_useless_node_eliminater]: 2.485e-05 [accelerated_algorithm]: 1.733e-05 [meta_shard_fg_expand]: 5.97001e-06 [get_grad_eliminate_]: 1.61e-05 [merge_forward]: 9.20999e-06 [cell_reuse_recompute_pass]: 3.93999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.219e-05 [j_node_and_user_rematch]: 2.501e-05 [meta_fg_expand]: 5.89e-06 [replace_old_param]: 2.785e-05 [inline_without_move]: 1.513e-05 [renormalize]: 0.00124617 [add_forward_monad_depend]: 1.044e-05 [auto_monad_grad]: 3.7e-06 [auto_monad_eliminator]: 3.338e-05 [cse]: 0.0001285 [replace_applicator]: 3.309e-05 [Cycle 4]: 0.0176469, [27] [switch_simplify]: 1.61e-05 [loop_unroll]: 1.388e-05 [a_1]: 0.017011 [with_stream_mark]: 4.207e-05 [recompute_prepare]: 2.353e-05 [updatestate_depend_eliminate]: 9.71e-06 [updatestate_assign_eliminate]: 7.71999e-06 [updatestate_loads_eliminate]: 6.87002e-06 [parameter_eliminate]: 2.74001e-06 [specialize_transform]: 1.876e-05 [updatestate_useless_node_eliminater]: 1.92e-05 [accelerated_algorithm]: 1.708e-05 [meta_shard_fg_expand]: 7.69002e-06 [get_grad_eliminate_]: 1.437e-05 [merge_forward]: 7.72002e-06 [cell_reuse_recompute_pass]: 4.16001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.057e-05 [j_node_and_user_rematch]: 2.36e-05 [meta_fg_expand]: 5.69e-06 [replace_old_param]: 2.121e-05 [inline_without_move]: 1.401e-05 [renormalize]: 2.89991e-07 [add_forward_monad_depend]: 4.68999e-06 [auto_monad_grad]: 3.25998e-06 [auto_monad_eliminator]: 3.239e-05 [cse]: 7.89e-05 [replace_applicator]: 1.471e-05 [py_interpret_to_execute_after_opt_a]: 2.841e-05 [rewriter_after_opt_a]: 0.00012743 [convert_after_rewriter]: 1.61e-05 [order_py_execute_after_rewriter]: 9.72001e-06 [mutable_eliminate]: 0.00094117 [jit_opt_b]: 0.0001179, [1] [Cycle 1]: 0.000105, [2] [frontend_op_eliminate]: 4.753e-05 [inline_after_opt_a]: 4.142e-05 [cconv]: 5.405e-05 [loop_unroll]: 0.00055154 [jit_opt_after_cconv]: 0.0003565, [1] [Cycle 1]: 0.00034913, [11] [c_1]: 9.134e-05 [parameter_eliminate]: 4.84e-06 [updatestate_depend_eliminate]: 1.583e-05 [updatestate_assign_eliminate]: 6.61999e-06 [updatestate_loads_eliminate]: 7.57998e-06 [cse]: 7.428e-05 [call_graph_tuple_transform]: 4.854e-05 [tuple_list_get_item_eliminator]: 1.54e-05 [none_parameter_eliminate]: 2.03002e-06 [renormalize]: 1.04e-06 [switch_simplify]: 1.845e-05 [remove_dup_value]: 7.493e-05 [partial_unused_args_eliminate]: 3.01001e-06 [environ_conv]: 2.453e-05 [add_recomputation]: 0.00012945 [cse_after_recomputation]: 5.839e-05, [1] [Cycle 1]: 4.964e-05, [1] [cse]: 4.118e-05 [auto_monad_reorder]: 4.615e-05 [get_jit_bprop_graph]: 2.27999e-06 [rewriter_after_jit_bprop_graph]: 0.0172597 [opt_after_jit_grad]: 0.00100454 [symbol_engine_optimizer]: 0.00014808, [1] [Cycle 1]: 0.00013799, [6] [build]: 1.231e-05 [elim_shapecalc]: 1.931e-05 [elim_not_effective]: 3.172e-05 [opt_reshape]: 1.606e-05 [fold_const_symbol]: 2.319e-05 [renormalize]: 8.50006e-07 [validate]: 0.00011042 Sums bootstrap : 0.000625s : 0.03% type_inference : 1.817945s : 79.48% event_method : 0.000891s : 0.04% auto_monad : 0.000392s : 0.02% graph_reusing : 0.000012s : 0.00% pre_auto_parallel : 0.000017s : 0.00% py_interpret_to_execute : 0.000063s : 0.00% rewriter_before_opt_a : 0.026331s : 1.15% expand_dump_flag : 0.000019s : 0.00% jit_opt_a.switch_simplify : 0.000301s : 0.01% jit_opt_a.loop_unroll : 0.000222s : 0.01% jit_opt_a.a_1 : 0.108019s : 4.72% jit_opt_a.with_stream_mark : 0.000223s : 0.01% jit_opt_a.recompute_prepare : 0.000142s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000097s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000056s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000042s : 0.00% jit_opt_a.parameter_eliminate : 0.000018s : 0.00% jit_opt_a.specialize_transform : 0.000091s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000239s : 0.01% jit_opt_a.accelerated_algorithm : 0.000080s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000038s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000071s : 0.00% jit_opt_a.merge_forward : 0.000043s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000012s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000163s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000126s : 0.01% jit_opt_a.meta_fg_expand : 0.162589s : 7.11% jit_opt_a.replace_old_param : 0.000261s : 0.01% jit_opt_a.inline_without_move : 0.000214s : 0.01% jit_opt_a.renormalize : 0.144854s : 6.33% jit_opt_a.add_forward_monad_depend : 0.000070s : 0.00% jit_opt_a.auto_monad_grad : 0.000031s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000279s : 0.01% jit_opt_a.cse : 0.001360s : 0.06% jit_opt_a.replace_applicator : 0.000431s : 0.02% py_interpret_to_execute_after_opt_a : 0.000028s : 0.00% rewriter_after_opt_a : 0.000127s : 0.01% convert_after_rewriter : 0.000016s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000941s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000048s : 0.00% jit_opt_b.inline_after_opt_a : 0.000041s : 0.00% cconv : 0.000054s : 0.00% loop_unroll : 0.000552s : 0.02% jit_opt_after_cconv.c_1 : 0.000091s : 0.00% 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 : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.cse : 0.000074s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000049s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000015s : 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 : 0.000018s : 0.00% remove_dup_value : 0.000075s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000025s : 0.00% add_recomputation : 0.000129s : 0.01% cse_after_recomputation.cse : 0.000041s : 0.00% auto_monad_reorder : 0.000046s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.017260s : 0.75% opt_after_jit_grad : 0.001005s : 0.04% symbol_engine_optimizer.build : 0.000012s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000019s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000032s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000016s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000023s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000110s : 0.00% Time group info: ------[substitution.] 0.056336 301 0.03% : 0.000018s : 1: substitution.arithmetic_simplify 0.09% : 0.000050s : 11: substitution.depend_value_elim 0.01% : 0.000005s : 7: substitution.elim_not_effective 0.01% : 0.000003s : 7: substitution.fold_const_symbol 1.67% : 0.000941s : 4: substitution.getattr_setattr_resolve 0.02% : 0.000014s : 11: substitution.graph_param_transform 25.12% : 0.014151s : 25: substitution.inline 0.09% : 0.000050s : 6: substitution.inline_without_move 0.04% : 0.000023s : 37: substitution.j_node_and_user_rematch 0.04% : 0.000023s : 11: substitution.minmaximum_grad 0.04% : 0.000022s : 6: substitution.partial_eliminate 0.06% : 0.000031s : 37: substitution.remove_not_recompute_node 0.22% : 0.000127s : 22: substitution.replace_applicator 0.05% : 0.000029s : 25: substitution.replace_old_param 0.02% : 0.000012s : 2: substitution.set_cell_output_no_recompute 71.93% : 0.040522s : 15: substitution.transpose_eliminate 0.08% : 0.000044s : 11: substitution.tuple_list_convert_item_index_to_positive 0.06% : 0.000032s : 11: substitution.tuple_list_get_item_depend_reorder 0.20% : 0.000114s : 27: substitution.tuple_list_get_item_eliminator 0.07% : 0.000037s : 9: substitution.updatestate_pure_node_eliminater 0.16% : 0.000089s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.817712 2 98.80% : 1.795976s : 1: type_inference.infer 1.20% : 0.021736s : 1: type_inference.specialize ------[replace.] 0.032034 47 0.03% : 0.000008s : 1: replace.arithmetic_simplify 0.24% : 0.000077s : 3: replace.getattr_setattr_resolve 97.94% : 0.031373s : 25: replace.inline 0.17% : 0.000055s : 1: replace.replace_applicator 1.32% : 0.000424s : 16: replace.tuple_list_get_item_eliminator 0.30% : 0.000097s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.015144 47 0.11% : 0.000017s : 1: match.arithmetic_simplify 5.86% : 0.000887s : 3: match.getattr_setattr_resolve 93.29% : 0.014127s : 25: match.inline 0.15% : 0.000023s : 1: match.replace_applicator 0.43% : 0.000065s : 16: match.tuple_list_get_item_eliminator 0.17% : 0.000025s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001177 6616 1.51% : 0.000018s : 106: predicate.accumulaten_eliminater 0.44% : 0.000005s : 11: predicate.ad_related_special_op_eliminate 1.36% : 0.000016s : 106: predicate.addn_check_dump 1.45% : 0.000017s : 106: predicate.addn_zero_filter 2.59% : 0.000030s : 107: predicate.arithmetic_simplify 1.45% : 0.000017s : 107: predicate.cast_eliminate 0.14% : 0.000002s : 11: predicate.check_bprop_eliminate 1.47% : 0.000017s : 106: predicate.compare_switch_simplify 1.70% : 0.000020s : 106: predicate.depend_value_elim 1.35% : 0.000016s : 107: predicate.dict_get_item_const_eliminator 1.42% : 0.000017s : 107: predicate.dict_get_item_eliminator 1.39% : 0.000016s : 107: predicate.dict_set_item_eliminator 0.31% : 0.000004s : 11: predicate.dumpgradient_eliminate 0.12% : 0.000001s : 11: predicate.elim_not_effective 0.18% : 0.000002s : 11: predicate.elim_shapecalc_of_broadcastargs 1.35% : 0.000016s : 107: predicate.environ_add_const_eliminate 1.88% : 0.000022s : 107: predicate.environ_get_add_eliminate 1.31% : 0.000015s : 107: predicate.environ_get_depend_swap 1.41% : 0.000017s : 107: predicate.environ_get_eliminate 1.41% : 0.000017s : 107: predicate.environ_get_set_eliminate 0.08% : 0.000001s : 11: predicate.fold_const_symbol 0.82% : 0.000010s : 56: predicate.get_grad_eliminate 0.80% : 0.000009s : 20: predicate.getattr_setattr_resolve 0.07% : 0.000001s : 11: predicate.graph_param_transform 4.81% : 0.000057s : 170: predicate.inline 2.10% : 0.000025s : 138: predicate.inline_without_move 0.36% : 0.000004s : 56: predicate.j_node_and_user_rematch 1.07% : 0.000013s : 56: predicate.less_batch_normalization 1.74% : 0.000021s : 123: predicate.list_to_tuple_eliminator_ 1.81% : 0.000021s : 134: predicate.load_eliminater 0.35% : 0.000004s : 11: predicate.loop_unroll_after_grad 2.87% : 0.000034s : 229: predicate.loop_unroll_before_grad 1.60% : 0.000019s : 118: predicate.make_slice_get_slice_eliminator 1.40% : 0.000016s : 106: predicate.merge_addn 1.85% : 0.000022s : 107: predicate.minmaximum_grad 0.52% : 0.000006s : 11: predicate.mutable_eliminate 0.16% : 0.000002s : 11: predicate.opt_reshape 2.29% : 0.000027s : 134: predicate.partial_eliminate 1.38% : 0.000016s : 106: predicate.print_const_string_wrapper 2.26% : 0.000027s : 107: predicate.reduce_eliminate 1.65% : 0.000019s : 123: predicate.redundant_stop_gradient_eliminater 0.40% : 0.000005s : 56: predicate.remove_not_recompute_node 2.62% : 0.000031s : 278: predicate.replace_applicator 1.06% : 0.000012s : 138: predicate.replace_old_param 0.10% : 0.000001s : 11: predicate.reset_defer_inline 1.47% : 0.000017s : 107: predicate.reshape_eliminate 1.44% : 0.000017s : 106: predicate.row_tensor_add_zeros_like 0.21% : 0.000002s : 11: predicate.row_tensor_eliminate 1.45% : 0.000017s : 106: predicate.same_eliminate 0.56% : 0.000007s : 63: predicate.set_cell_output_no_recompute 0.34% : 0.000004s : 22: predicate.special_op_eliminate 0.96% : 0.000011s : 61: predicate.specialize_transform 1.79% : 0.000021s : 106: predicate.split_environ_get_set_with_tuple_value 1.46% : 0.000017s : 106: predicate.stack_unstack_eliminate 0.15% : 0.000002s : 11: predicate.switch_call_monad_eliminater 3.96% : 0.000047s : 148: predicate.switch_defer_inline 2.19% : 0.000026s : 148: predicate.switch_layer_defer_inline 5.59% : 0.000066s : 388: predicate.switch_simplify 1.44% : 0.000017s : 107: predicate.tile_eliminate 1.78% : 0.000021s : 107: predicate.transpose_eliminate 1.67% : 0.000020s : 107: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000019s : 107: predicate.tuple_list_get_item_depend_reorder 3.32% : 0.000039s : 145: predicate.tuple_list_get_item_eliminator 1.88% : 0.000022s : 107: predicate.tuple_list_set_item_eliminator 1.57% : 0.000018s : 123: predicate.tuple_to_list_eliminator_ 1.72% : 0.000020s : 134: predicate.updatestate_pure_node_eliminater 2.81% : 0.000033s : 192: predicate.updatestate_useless_node_eliminater 1.86% : 0.000022s : 106: predicate.value_based_eliminate 0.14% : 0.000002s : 11: predicate.virtual_view_grad_eliminate 0.20% : 0.000002s : 11: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.072682 93 95.43% : 0.069361s : 52: func_graph_cloner_run.FuncGraphClonerGraph 0.81% : 0.000586s : 8: func_graph_cloner_run.FuncGraphClonerNode 3.76% : 0.002735s : 33: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.596121 104 0.01% : 0.000134s : 1: add_recomputation 0.02% : 0.000403s : 1: auto_monad 0.00% : 0.000049s : 1: auto_monad_reorder 0.03% : 0.000653s : 1: bootstrap 0.00% : 0.000057s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000061s : 1: cse_after_recomputation 0.00% : 0.000027s : 1: environ_conv 0.03% : 0.000907s : 1: event_method 0.00% : 0.000024s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 18.18% : 0.472062s : 1: jit_opt_a 0.01% : 0.000360s : 1: jit_opt_after_cconv 0.00% : 0.000121s : 1: jit_opt_b 0.02% : 0.000562s : 1: loop_unroll 0.04% : 0.000953s : 1: mutable_eliminate 4.25% : 0.110221s : 52: opt.transform.jit_opt_a 0.01% : 0.000169s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000079s : 4: opt.transform.jit_opt_b 0.00% : 0.000026s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000038s : 1: opt.transform.mutable_eliminate 0.00% : 0.000070s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.001098s : 2: opt.transform.opt_resolve 0.00% : 0.000086s : 4: opt.transform.symbol_engine_opt 0.04% : 0.001022s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000019s : 1: pre_auto_parallel 0.00% : 0.000066s : 1: py_interpret_to_execute 0.00% : 0.000031s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000079s : 1: remove_dup_value 3.86% : 0.100261s : 3: renormalize.infer 1.72% : 0.044531s : 3: renormalize.specialize 0.67% : 0.017278s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000132s : 1: rewriter_after_opt_a 1.02% : 0.026360s : 1: rewriter_before_opt_a 0.01% : 0.000151s : 1: symbol_engine_optimizer 70.03% : 1.817972s : 1: type_inference . [hook] pytest_runtest_teardown:test_permute_view_backward[KBK] tests/st/mint/test_permute.py::test_permute_view_backward[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 124.22s (0:02:04) ==================