==================================================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_jit_mode[pynative] tests/st/mint/test_permute.py::test_permute_jit_mode[pynative],max_mem:2.0M TotalTime = 5.91182, [33] [bootstrap]: 0.00107451 [type_inference]: 1.30619 [event_method]: 1.939e-05 [auto_monad]: 0.00018876 [graph_reusing]: 7.2e-06 [pre_auto_parallel]: 1.844e-05 [py_interpret_to_execute]: 0.0004561 [rewriter_before_opt_a]: 8.427e-05 [expand_dump_flag]: 4.84998e-06 [jit_opt_a]: 0.126615, [2] [Cycle 1]: 0.028959, [27] [switch_simplify]: 6.649e-05 [loop_unroll]: 2.541e-05 [a_1]: 0.00054555 [with_stream_mark]: 3.133e-05 [recompute_prepare]: 1.284e-05 [updatestate_depend_eliminate]: 7.33999e-06 [updatestate_assign_eliminate]: 5.46e-06 [updatestate_loads_eliminate]: 4.94998e-06 [parameter_eliminate]: 2.04999e-06 [specialize_transform]: 1.071e-05 [updatestate_useless_node_eliminater]: 1.399e-05 [accelerated_algorithm]: 1.108e-05 [meta_shard_fg_expand]: 3.02002e-06 [get_grad_eliminate_]: 1.013e-05 [merge_forward]: 6.12001e-06 [cell_reuse_recompute_pass]: 1.44e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.427e-05 [j_node_and_user_rematch]: 1.629e-05 [meta_fg_expand]: 4.35999e-06 [replace_old_param]: 1.436e-05 [inline_without_move]: 9.49999e-06 [renormalize]: 0.0277286 [add_forward_monad_depend]: 1.877e-05 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 2.891e-05 [cse]: 6.156e-05 [replace_applicator]: 3.283e-05 [Cycle 2]: 0.00056295, [27] [switch_simplify]: 1.114e-05 [loop_unroll]: 9.57999e-06 [a_1]: 0.00021515 [with_stream_mark]: 2.018e-05 [recompute_prepare]: 9.18002e-06 [updatestate_depend_eliminate]: 5.71998e-06 [updatestate_assign_eliminate]: 6.48e-06 [updatestate_loads_eliminate]: 4.37e-06 [parameter_eliminate]: 2.17999e-06 [specialize_transform]: 8.68001e-06 [updatestate_useless_node_eliminater]: 1.153e-05 [accelerated_algorithm]: 9.07001e-06 [meta_shard_fg_expand]: 2.53998e-06 [get_grad_eliminate_]: 8.75001e-06 [merge_forward]: 5.56e-06 [cell_reuse_recompute_pass]: 3.87002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.079e-05 [j_node_and_user_rematch]: 1.406e-05 [meta_fg_expand]: 3.48999e-06 [replace_old_param]: 1.329e-05 [inline_without_move]: 8.80001e-06 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 2.22001e-06 [auto_monad_grad]: 1.74e-06 [auto_monad_eliminator]: 1.014e-05 [cse]: 2.025e-05 [replace_applicator]: 9.12001e-06 [py_interpret_to_execute_after_opt_a]: 1.978e-05 [rewriter_after_opt_a]: 0.00053629 [convert_after_rewriter]: 1.483e-05 [order_py_execute_after_rewriter]: 8.28001e-06 [mutable_eliminate]: 0.0336533 [jit_opt_b]: 9.928e-05, [1] [Cycle 1]: 8.594e-05, [2] [frontend_op_eliminate]: 3.222e-05 [inline_after_opt_a]: 3.542e-05 [cconv]: 4.871e-05 [loop_unroll]: 0.0007021 [jit_opt_after_cconv]: 0.00027119, [1] [Cycle 1]: 0.00026298, [11] [c_1]: 6.836e-05 [parameter_eliminate]: 8.2e-06 [updatestate_depend_eliminate]: 1.504e-05 [updatestate_assign_eliminate]: 5.64e-06 [updatestate_loads_eliminate]: 4.75001e-06 [cse]: 5.095e-05 [call_graph_tuple_transform]: 2.76e-05 [tuple_list_get_item_eliminator]: 1.022e-05 [none_parameter_eliminate]: 1.69e-06 [renormalize]: 5.60016e-07 [switch_simplify]: 1.006e-05 [remove_dup_value]: 2.221e-05 [partial_unused_args_eliminate]: 2.41998e-06 [environ_conv]: 3.337e-05 [add_recomputation]: 0.00010671 [cse_after_recomputation]: 3.605e-05, [1] [Cycle 1]: 2.821e-05, [1] [cse]: 1.975e-05 [auto_monad_reorder]: 4.085e-05 [get_jit_bprop_graph]: 2.81e-06 [rewriter_after_jit_bprop_graph]: 0.00016079 [opt_after_jit_grad]: 0.00063742 [symbol_engine_optimizer]: 0.0001074, [1] [Cycle 1]: 9.958e-05, [6] [build]: 7.48e-06 [elim_shapecalc]: 1.422e-05 [elim_not_effective]: 2.043e-05 [opt_reshape]: 9.68997e-06 [fold_const_symbol]: 1.531e-05 [renormalize]: 6.00005e-07 [validate]: 8.7e-05 [backend_pass]: 1.08001e-06 [task_emit]: 4.44011 [execute]: 1.097e-05 Sums bootstrap : 0.001075s : 0.02% type_inference : 1.306185s : 22.47% event_method : 0.000019s : 0.00% auto_monad : 0.000189s : 0.00% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000018s : 0.00% py_interpret_to_execute : 0.000456s : 0.01% rewriter_before_opt_a : 0.000084s : 0.00% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000078s : 0.00% jit_opt_a.loop_unroll : 0.000035s : 0.00% jit_opt_a.a_1 : 0.000761s : 0.01% jit_opt_a.with_stream_mark : 0.000052s : 0.00% jit_opt_a.recompute_prepare : 0.000022s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000019s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000026s : 0.00% jit_opt_a.accelerated_algorithm : 0.000020s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000019s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000045s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000030s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000028s : 0.00% jit_opt_a.inline_without_move : 0.000018s : 0.00% jit_opt_a.renormalize : 0.027729s : 0.48% jit_opt_a.add_forward_monad_depend : 0.000021s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000039s : 0.00% jit_opt_a.cse : 0.000082s : 0.00% jit_opt_a.replace_applicator : 0.000042s : 0.00% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000536s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.033653s : 0.58% jit_opt_b.frontend_op_eliminate : 0.000032s : 0.00% jit_opt_b.inline_after_opt_a : 0.000035s : 0.00% cconv : 0.000049s : 0.00% loop_unroll : 0.000702s : 0.01% jit_opt_after_cconv.c_1 : 0.000068s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000008s : 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 : 0.000051s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000028s : 0.00% 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 : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000010s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000033s : 0.00% add_recomputation : 0.000107s : 0.00% cse_after_recomputation.cse : 0.000020s : 0.00% auto_monad_reorder : 0.000041s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000161s : 0.00% opt_after_jit_grad : 0.000637s : 0.01% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 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 : 0.000087s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 4.440108s : 76.37% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000237 45 5.12% : 0.000012s : 2: substitution.depend_value_elim 1.23% : 0.000003s : 4: substitution.elim_not_effective 1.00% : 0.000002s : 4: substitution.fold_const_symbol 3.50% : 0.000008s : 6: substitution.graph_param_transform 68.55% : 0.000162s : 3: substitution.inline 2.65% : 0.000006s : 8: substitution.j_node_and_user_rematch 3.41% : 0.000008s : 8: substitution.remove_not_recompute_node 2.91% : 0.000007s : 2: substitution.replace_old_param 6.37% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 5.26% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.231198 2 97.18% : 1.196530s : 1: type_inference.infer 2.82% : 0.034669s : 1: type_inference.specialize ------[replace.] 0.000034 3 100.00% : 0.000034s : 3: replace.inline ------[match.] 0.000160 3 100.00% : 0.000160s : 3: match.inline ------[predicate.] 0.000203 970 1.25% : 0.000003s : 14: predicate.accumulaten_eliminater 1.31% : 0.000003s : 6: predicate.ad_related_special_op_eliminate 0.93% : 0.000002s : 14: predicate.addn_check_dump 1.00% : 0.000002s : 14: predicate.addn_zero_filter 1.86% : 0.000004s : 14: predicate.arithmetic_simplify 1.08% : 0.000002s : 14: predicate.cast_eliminate 0.51% : 0.000001s : 6: predicate.check_bprop_eliminate 0.88% : 0.000002s : 14: predicate.compare_switch_simplify 1.07% : 0.000002s : 14: predicate.depend_value_elim 0.91% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.37% : 0.000003s : 14: predicate.dict_get_item_eliminator 11.31% : 0.000023s : 14: predicate.dict_set_item_eliminator 0.81% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.46% : 0.000001s : 6: predicate.elim_not_effective 0.69% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 0.99% : 0.000002s : 14: predicate.environ_add_const_eliminate 0.91% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.00% : 0.000002s : 14: predicate.environ_get_depend_swap 1.01% : 0.000002s : 14: predicate.environ_get_eliminate 1.02% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.26% : 0.000001s : 6: predicate.fold_const_symbol 1.21% : 0.000002s : 12: predicate.get_grad_eliminate 0.33% : 0.000001s : 6: predicate.graph_param_transform 4.29% : 0.000009s : 29: predicate.inline 0.97% : 0.000002s : 12: predicate.inline_without_move 0.45% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.47% : 0.000003s : 12: predicate.less_batch_normalization 1.08% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.55% : 0.000003s : 20: predicate.load_eliminater 2.08% : 0.000004s : 6: predicate.loop_unroll_after_grad 2.46% : 0.000005s : 30: predicate.loop_unroll_before_grad 1.78% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.05% : 0.000002s : 14: predicate.merge_addn 0.96% : 0.000002s : 14: predicate.minmaximum_grad 4.10% : 0.000008s : 6: predicate.mutable_eliminate 0.55% : 0.000001s : 6: predicate.opt_reshape 1.84% : 0.000004s : 20: predicate.partial_eliminate 1.03% : 0.000002s : 14: predicate.print_const_string_wrapper 1.49% : 0.000003s : 14: predicate.reduce_eliminate 1.15% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.74% : 0.000002s : 12: predicate.remove_not_recompute_node 1.57% : 0.000003s : 26: predicate.replace_applicator 0.85% : 0.000002s : 12: predicate.replace_old_param 0.58% : 0.000001s : 6: predicate.reset_defer_inline 1.10% : 0.000002s : 14: predicate.reshape_eliminate 1.36% : 0.000003s : 14: predicate.row_tensor_add_zeros_like 1.08% : 0.000002s : 6: predicate.row_tensor_eliminate 1.08% : 0.000002s : 14: predicate.same_eliminate 0.60% : 0.000001s : 12: predicate.set_cell_output_no_recompute 1.07% : 0.000002s : 12: predicate.special_op_eliminate 1.09% : 0.000002s : 12: predicate.specialize_transform 1.51% : 0.000003s : 14: predicate.split_environ_get_set_with_tuple_value 1.16% : 0.000002s : 14: predicate.stack_unstack_eliminate 0.55% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.31% : 0.000003s : 17: predicate.switch_defer_inline 1.22% : 0.000002s : 17: predicate.switch_layer_defer_inline 4.93% : 0.000010s : 53: predicate.switch_simplify 1.03% : 0.000002s : 14: predicate.tile_eliminate 1.21% : 0.000002s : 14: predicate.transpose_eliminate 1.23% : 0.000002s : 14: predicate.tuple_list_convert_item_index_to_positive 1.27% : 0.000003s : 14: predicate.tuple_list_get_item_depend_reorder 3.19% : 0.000006s : 26: predicate.tuple_list_get_item_eliminator 1.35% : 0.000003s : 14: predicate.tuple_list_set_item_eliminator 1.11% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.59% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 3.15% : 0.000006s : 32: predicate.updatestate_useless_node_eliminater 1.23% : 0.000002s : 14: predicate.value_based_eliminate 0.40% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.96% : 0.000002s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003286 23 70.52% : 0.002317s : 18: func_graph_cloner_run.FuncGraphClonerGraph 29.48% : 0.000969s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 5.940782 76 0.00% : 0.000111s : 1: add_recomputation 0.00% : 0.000196s : 1: auto_monad 0.00% : 0.000044s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.02% : 0.001112s : 1: bootstrap 0.00% : 0.000052s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000038s : 1: cse_after_recomputation 0.00% : 0.000037s : 1: environ_conv 0.00% : 0.000026s : 1: event_method 0.00% : 0.000017s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 2.13% : 0.126618s : 1: jit_opt_a 0.00% : 0.000274s : 1: jit_opt_after_cconv 0.00% : 0.000104s : 1: jit_opt_b 0.01% : 0.000714s : 1: loop_unroll 0.57% : 0.033677s : 1: mutable_eliminate 0.02% : 0.001093s : 26: opt.transform.jit_opt_a 0.00% : 0.000111s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000056s : 4: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000051s : 1: opt.transform.mutable_eliminate 0.00% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000055s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000650s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000021s : 1: pre_auto_parallel 0.01% : 0.000467s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000026s : 1: remove_dup_value 0.45% : 0.026538s : 1: renormalize.infer 0.02% : 0.001175s : 1: renormalize.specialize 0.00% : 0.000165s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000543s : 1: rewriter_after_opt_a 0.00% : 0.000090s : 1: rewriter_before_opt_a 0.00% : 0.000110s : 1: symbol_engine_optimizer 74.74% : 4.440133s : 1: task_emit 21.99% : 1.306215s : 1: type_inference 0.00% : 0.000116s : 1: validate TotalTime = 1.3065, [33] [bootstrap]: 0.00054583 [type_inference]: 0.725964 [event_method]: 0.00040729 [auto_monad]: 0.00029227 [graph_reusing]: 1.059e-05 [pre_auto_parallel]: 4.10998e-06 [py_interpret_to_execute]: 6.741e-05 [rewriter_before_opt_a]: 0.00015141 [expand_dump_flag]: 4.74e-06 [jit_opt_a]: 0.497281, [4] [Cycle 1]: 0.462382, [27] [switch_simplify]: 0.128515 [loop_unroll]: 7.641e-05 [a_1]: 0.00158329 [with_stream_mark]: 3.599e-05 [recompute_prepare]: 3.148e-05 [updatestate_depend_eliminate]: 1.356e-05 [updatestate_assign_eliminate]: 1.051e-05 [updatestate_loads_eliminate]: 1.004e-05 [parameter_eliminate]: 3.34001e-06 [specialize_transform]: 2.136e-05 [updatestate_useless_node_eliminater]: 2.459e-05 [accelerated_algorithm]: 2.091e-05 [meta_shard_fg_expand]: 6.88e-06 [get_grad_eliminate_]: 2.009e-05 [merge_forward]: 1.167e-05 [cell_reuse_recompute_pass]: 2.01e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.977e-05 [j_node_and_user_rematch]: 4.77e-05 [meta_fg_expand]: 0.188749 [replace_old_param]: 0.00013319 [inline_without_move]: 0.00013124 [renormalize]: 0.141857 [add_forward_monad_depend]: 2.804e-05 [auto_monad_grad]: 1.213e-05 [auto_monad_eliminator]: 0.00012419 [cse]: 0.00027773 [replace_applicator]: 0.00025021 [Cycle 2]: 0.0275971, [27] [switch_simplify]: 9.081e-05 [loop_unroll]: 8.527e-05 [a_1]: 0.0038139 [with_stream_mark]: 4.195e-05 [recompute_prepare]: 3.582e-05 [updatestate_depend_eliminate]: 1.375e-05 [updatestate_assign_eliminate]: 1.371e-05 [updatestate_loads_eliminate]: 1.268e-05 [parameter_eliminate]: 5.20999e-06 [specialize_transform]: 2.026e-05 [updatestate_useless_node_eliminater]: 8.686e-05 [accelerated_algorithm]: 1.479e-05 [meta_shard_fg_expand]: 5.47999e-06 [get_grad_eliminate_]: 1.318e-05 [merge_forward]: 8.2e-06 [cell_reuse_recompute_pass]: 1.42999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.879e-05 [j_node_and_user_rematch]: 2.208e-05 [meta_fg_expand]: 0.00014444 [replace_old_param]: 2.336e-05 [inline_without_move]: 1.344e-05 [renormalize]: 0.0226289 [add_forward_monad_depend]: 1.226e-05 [auto_monad_grad]: 3.24001e-06 [auto_monad_eliminator]: 3.76e-05 [cse]: 0.00012495 [replace_applicator]: 3.819e-05 [Cycle 3]: 0.00178862, [27] [switch_simplify]: 1.513e-05 [loop_unroll]: 1.396e-05 [a_1]: 0.00037674 [with_stream_mark]: 2.685e-05 [recompute_prepare]: 1.747e-05 [updatestate_depend_eliminate]: 5.527e-05 [updatestate_assign_eliminate]: 6.85002e-06 [updatestate_loads_eliminate]: 6.30002e-06 [parameter_eliminate]: 2.37999e-06 [specialize_transform]: 1.293e-05 [updatestate_useless_node_eliminater]: 1.496e-05 [accelerated_algorithm]: 1.195e-05 [meta_shard_fg_expand]: 2.66e-06 [get_grad_eliminate_]: 1.095e-05 [merge_forward]: 6.38003e-06 [cell_reuse_recompute_pass]: 5.17e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.584e-05 [j_node_and_user_rematch]: 2.017e-05 [meta_fg_expand]: 4.03001e-06 [replace_old_param]: 1.58e-05 [inline_without_move]: 1.007e-05 [renormalize]: 0.00085308 [add_forward_monad_depend]: 7.17002e-06 [auto_monad_grad]: 2.56998e-06 [auto_monad_eliminator]: 2.293e-05 [cse]: 4.178e-05 [replace_applicator]: 2.304e-05 [Cycle 4]: 0.0006963, [27] [switch_simplify]: 1.194e-05 [loop_unroll]: 1.073e-05 [a_1]: 0.00029019 [with_stream_mark]: 1.882e-05 [recompute_prepare]: 1.254e-05 [updatestate_depend_eliminate]: 7.04001e-06 [updatestate_assign_eliminate]: 5.59998e-06 [updatestate_loads_eliminate]: 5.95002e-06 [parameter_eliminate]: 2.07999e-06 [specialize_transform]: 1.146e-05 [updatestate_useless_node_eliminater]: 1.608e-05 [accelerated_algorithm]: 1.168e-05 [meta_shard_fg_expand]: 3.14001e-06 [get_grad_eliminate_]: 9.86e-06 [merge_forward]: 6.05002e-06 [cell_reuse_recompute_pass]: 1.97999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.311e-05 [j_node_and_user_rematch]: 1.8e-05 [meta_fg_expand]: 3.66999e-06 [replace_old_param]: 1.417e-05 [inline_without_move]: 1.059e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.56e-06 [auto_monad_grad]: 1.41998e-06 [auto_monad_eliminator]: 1.652e-05 [cse]: 2.827e-05 [replace_applicator]: 1.167e-05 [py_interpret_to_execute_after_opt_a]: 1.983e-05 [rewriter_after_opt_a]: 0.00020889 [convert_after_rewriter]: 1.279e-05 [order_py_execute_after_rewriter]: 8.40999e-06 [mutable_eliminate]: 0.00084115 [jit_opt_b]: 9.986e-05, [1] [Cycle 1]: 8.818e-05, [2] [frontend_op_eliminate]: 3.571e-05 [inline_after_opt_a]: 3.648e-05 [cconv]: 3.761e-05 [loop_unroll]: 0.00051294 [jit_opt_after_cconv]: 0.00030407, [1] [Cycle 1]: 0.00029493, [11] [c_1]: 7.257e-05 [parameter_eliminate]: 5.62001e-06 [updatestate_depend_eliminate]: 1.454e-05 [updatestate_assign_eliminate]: 6.76e-06 [updatestate_loads_eliminate]: 5.21002e-06 [cse]: 4.93e-05 [call_graph_tuple_transform]: 5.439e-05 [tuple_list_get_item_eliminator]: 1.21e-05 [none_parameter_eliminate]: 1.80001e-06 [renormalize]: 4.60015e-07 [switch_simplify]: 1.172e-05 [remove_dup_value]: 6.568e-05 [partial_unused_args_eliminate]: 2.88e-06 [environ_conv]: 1.408e-05 [add_recomputation]: 9.532e-05 [cse_after_recomputation]: 3.94e-05, [1] [Cycle 1]: 3.078e-05, [1] [cse]: 2.2e-05 [auto_monad_reorder]: 4.921e-05 [get_jit_bprop_graph]: 2.51e-06 [rewriter_after_jit_bprop_graph]: 8.64e-06 [opt_after_jit_grad]: 0.00058927 [symbol_engine_optimizer]: 0.00011993, [1] [Cycle 1]: 0.00011151, [6] [build]: 7.77e-06 [elim_shapecalc]: 1.474e-05 [elim_not_effective]: 2.491e-05 [opt_reshape]: 1.26e-05 [fold_const_symbol]: 1.71e-05 [renormalize]: 5.8001e-07 [validate]: 8.944e-05 [backend_pass]: 1.09e-06 [task_emit]: 0.0783279 [execute]: 1.228e-05 Sums bootstrap : 0.000546s : 0.04% type_inference : 0.725964s : 55.83% event_method : 0.000407s : 0.03% auto_monad : 0.000292s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000067s : 0.01% rewriter_before_opt_a : 0.000151s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.128632s : 9.89% jit_opt_a.loop_unroll : 0.000186s : 0.01% jit_opt_a.a_1 : 0.006064s : 0.47% jit_opt_a.with_stream_mark : 0.000124s : 0.01% jit_opt_a.recompute_prepare : 0.000097s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000090s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000037s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000035s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000066s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000142s : 0.01% jit_opt_a.accelerated_algorithm : 0.000059s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000018s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000054s : 0.00% jit_opt_a.merge_forward : 0.000032s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000011s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000118s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000108s : 0.01% jit_opt_a.meta_fg_expand : 0.188901s : 14.53% jit_opt_a.replace_old_param : 0.000187s : 0.01% jit_opt_a.inline_without_move : 0.000165s : 0.01% jit_opt_a.renormalize : 0.165339s : 12.72% jit_opt_a.add_forward_monad_depend : 0.000050s : 0.00% jit_opt_a.auto_monad_grad : 0.000019s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000201s : 0.02% jit_opt_a.cse : 0.000473s : 0.04% jit_opt_a.replace_applicator : 0.000323s : 0.02% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000209s : 0.02% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000841s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000036s : 0.00% jit_opt_b.inline_after_opt_a : 0.000036s : 0.00% cconv : 0.000038s : 0.00% loop_unroll : 0.000513s : 0.04% jit_opt_after_cconv.c_1 : 0.000073s : 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 : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000049s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000054s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 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 : 0.000012s : 0.00% remove_dup_value : 0.000066s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000014s : 0.00% add_recomputation : 0.000095s : 0.01% cse_after_recomputation.cse : 0.000022s : 0.00% auto_monad_reorder : 0.000049s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000589s : 0.05% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000089s : 0.01% backend_pass : 0.000001s : 0.00% task_emit : 0.078328s : 6.02% execute : 0.000012s : 0.00% Time group info: ------[substitution.] 0.002792 271 1.58% : 0.000044s : 12: substitution.depend_value_elim 0.11% : 0.000003s : 5: substitution.elim_not_effective 0.09% : 0.000002s : 5: substitution.fold_const_symbol 31.47% : 0.000879s : 4: substitution.getattr_setattr_resolve 1.12% : 0.000031s : 8: substitution.graph_param_transform 46.62% : 0.001302s : 29: substitution.inline 1.58% : 0.000044s : 4: substitution.inline_without_move 1.08% : 0.000030s : 29: substitution.j_node_and_user_rematch 0.80% : 0.000022s : 13: substitution.minmaximum_grad 1.38% : 0.000038s : 14: substitution.partial_eliminate 0.86% : 0.000024s : 29: substitution.remove_not_recompute_node 2.27% : 0.000064s : 16: substitution.replace_applicator 0.74% : 0.000021s : 17: substitution.replace_old_param 0.28% : 0.000008s : 2: substitution.set_cell_output_no_recompute 0.92% : 0.000026s : 3: substitution.switch_simplify 1.51% : 0.000042s : 13: substitution.tuple_list_convert_item_index_to_positive 1.15% : 0.000032s : 13: substitution.tuple_list_get_item_depend_reorder 3.37% : 0.000094s : 30: substitution.tuple_list_get_item_eliminator 0.99% : 0.000028s : 9: substitution.updatestate_pure_node_eliminater 2.09% : 0.000058s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.725847 2 99.54% : 0.722486s : 1: type_inference.infer 0.46% : 0.003362s : 1: type_inference.specialize ------[replace.] 0.129085 54 0.06% : 0.000073s : 3: replace.getattr_setattr_resolve 0.31% : 0.000399s : 29: replace.inline 0.04% : 0.000055s : 1: replace.replace_applicator 99.39% : 0.128297s : 3: replace.switch_simplify 0.17% : 0.000218s : 17: replace.tuple_list_get_item_eliminator 0.03% : 0.000043s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002194 54 37.37% : 0.000820s : 3: match.getattr_setattr_resolve 58.46% : 0.001282s : 29: match.inline 0.61% : 0.000013s : 1: match.replace_applicator 1.06% : 0.000023s : 3: match.switch_simplify 1.86% : 0.000041s : 17: match.tuple_list_get_item_eliminator 0.64% : 0.000014s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000926 6056 1.47% : 0.000014s : 101: predicate.accumulaten_eliminater 0.32% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.33% : 0.000012s : 101: predicate.addn_check_dump 1.55% : 0.000014s : 101: predicate.addn_zero_filter 2.06% : 0.000019s : 101: predicate.arithmetic_simplify 1.52% : 0.000014s : 101: predicate.cast_eliminate 0.14% : 0.000001s : 8: predicate.check_bprop_eliminate 1.40% : 0.000013s : 101: predicate.compare_switch_simplify 1.56% : 0.000014s : 101: predicate.depend_value_elim 1.37% : 0.000013s : 101: predicate.dict_get_item_const_eliminator 1.46% : 0.000013s : 101: predicate.dict_get_item_eliminator 1.46% : 0.000014s : 101: predicate.dict_set_item_eliminator 0.20% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.11% : 0.000001s : 8: predicate.elim_not_effective 0.14% : 0.000001s : 8: predicate.elim_shapecalc_of_broadcastargs 1.52% : 0.000014s : 101: predicate.environ_add_const_eliminate 1.45% : 0.000013s : 101: predicate.environ_get_add_eliminate 1.41% : 0.000013s : 101: predicate.environ_get_depend_swap 1.51% : 0.000014s : 101: predicate.environ_get_eliminate 1.41% : 0.000013s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.84% : 0.000008s : 44: predicate.get_grad_eliminate 0.78% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000001s : 8: predicate.graph_param_transform 4.40% : 0.000041s : 163: predicate.inline 1.88% : 0.000017s : 105: predicate.inline_without_move 0.39% : 0.000004s : 44: predicate.j_node_and_user_rematch 1.03% : 0.000010s : 44: predicate.less_batch_normalization 1.90% : 0.000018s : 118: predicate.list_to_tuple_eliminator_ 1.79% : 0.000017s : 126: predicate.load_eliminater 0.31% : 0.000003s : 8: predicate.loop_unroll_after_grad 3.17% : 0.000029s : 187: predicate.loop_unroll_before_grad 1.66% : 0.000015s : 109: predicate.make_slice_get_slice_eliminator 1.43% : 0.000013s : 101: predicate.merge_addn 1.53% : 0.000014s : 101: predicate.minmaximum_grad 0.48% : 0.000004s : 8: predicate.mutable_eliminate 0.21% : 0.000002s : 8: predicate.opt_reshape 2.44% : 0.000023s : 126: predicate.partial_eliminate 1.52% : 0.000014s : 101: predicate.print_const_string_wrapper 2.00% : 0.000019s : 101: predicate.reduce_eliminate 1.85% : 0.000017s : 118: predicate.redundant_stop_gradient_eliminater 0.48% : 0.000004s : 44: predicate.remove_not_recompute_node 2.72% : 0.000025s : 243: predicate.replace_applicator 0.98% : 0.000009s : 105: predicate.replace_old_param 0.09% : 0.000001s : 8: predicate.reset_defer_inline 1.47% : 0.000014s : 101: predicate.reshape_eliminate 1.46% : 0.000014s : 101: predicate.row_tensor_add_zeros_like 0.24% : 0.000002s : 8: predicate.row_tensor_eliminate 1.45% : 0.000013s : 101: predicate.same_eliminate 0.58% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.30% : 0.000003s : 16: predicate.special_op_eliminate 0.90% : 0.000008s : 50: predicate.specialize_transform 1.71% : 0.000016s : 101: predicate.split_environ_get_set_with_tuple_value 1.47% : 0.000014s : 101: predicate.stack_unstack_eliminate 0.13% : 0.000001s : 8: predicate.switch_call_monad_eliminater 3.01% : 0.000028s : 147: predicate.switch_defer_inline 2.44% : 0.000023s : 147: predicate.switch_layer_defer_inline 7.02% : 0.000065s : 348: predicate.switch_simplify 1.47% : 0.000014s : 101: predicate.tile_eliminate 1.39% : 0.000013s : 101: predicate.transpose_eliminate 1.81% : 0.000017s : 101: predicate.tuple_list_convert_item_index_to_positive 1.86% : 0.000017s : 101: predicate.tuple_list_get_item_depend_reorder 3.19% : 0.000030s : 134: predicate.tuple_list_get_item_eliminator 1.89% : 0.000018s : 101: predicate.tuple_list_set_item_eliminator 1.84% : 0.000017s : 118: predicate.tuple_to_list_eliminator_ 1.83% : 0.000017s : 126: predicate.updatestate_pure_node_eliminater 3.00% : 0.000028s : 172: predicate.updatestate_useless_node_eliminater 1.84% : 0.000017s : 101: predicate.value_based_eliminate 0.13% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.16% : 0.000001s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.007554 79 68.80% : 0.005197s : 42: func_graph_cloner_run.FuncGraphClonerGraph 4.97% : 0.000375s : 7: func_graph_cloner_run.FuncGraphClonerNode 26.23% : 0.001981s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.609239 108 0.01% : 0.000099s : 1: add_recomputation 0.02% : 0.000301s : 1: auto_monad 0.00% : 0.000052s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.04% : 0.000574s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.00% : 0.000042s : 1: cse_after_recomputation 0.00% : 0.000016s : 1: environ_conv 0.03% : 0.000420s : 1: event_method 0.00% : 0.000019s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 30.90% : 0.497285s : 1: jit_opt_a 0.02% : 0.000307s : 1: jit_opt_after_cconv 0.01% : 0.000104s : 1: jit_opt_b 0.03% : 0.000524s : 1: loop_unroll 0.05% : 0.000856s : 1: mutable_eliminate 8.46% : 0.136110s : 52: opt.transform.jit_opt_a 0.01% : 0.000146s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000061s : 4: opt.transform.jit_opt_b 0.00% : 0.000022s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000029s : 1: opt.transform.mutable_eliminate 0.00% : 0.000046s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.001022s : 2: opt.transform.opt_resolve 0.00% : 0.000065s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000603s : 1: opt_after_jit_grad 0.00% : 0.000011s : 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% : 0.000072s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000069s : 1: remove_dup_value 9.96% : 0.160250s : 3: renormalize.infer 0.31% : 0.005046s : 3: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000217s : 1: rewriter_after_opt_a 0.01% : 0.000155s : 1: rewriter_before_opt_a 0.01% : 0.000123s : 1: symbol_engine_optimizer 4.87% : 0.078353s : 1: task_emit 45.11% : 0.725986s : 1: type_inference 0.01% : 0.000122s : 1: validate . [hook] pytest_runtest_teardown:test_permute_jit_mode[KBK] tests/st/mint/test_permute.py::test_permute_jit_mode[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 227.98s (0:03:47) ==================