==================================================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_004/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 TotalTime = 2.16396, [30] [bootstrap]: 0.279281 [type_inference]: 1.69149 [event_method]: 1.878e-05 [auto_monad]: 0.00019391 [graph_reusing]: 6.99001e-06 [pre_auto_parallel]: 1.231e-05 [py_interpret_to_execute]: 0.00036603 [rewriter_before_opt_a]: 9.244e-05 [expand_dump_flag]: 3.98999e-06 [jit_opt_a]: 0.188298, [2] [Cycle 1]: 0.178211, [27] [switch_simplify]: 9.252e-05 [loop_unroll]: 2.774e-05 [a_1]: 0.00052854 [with_stream_mark]: 2.738e-05 [recompute_prepare]: 1.22e-05 [updatestate_depend_eliminate]: 7.09001e-06 [updatestate_assign_eliminate]: 8.2e-06 [updatestate_loads_eliminate]: 5.08002e-06 [parameter_eliminate]: 2.01e-06 [specialize_transform]: 1.013e-05 [updatestate_useless_node_eliminater]: 1.135e-05 [accelerated_algorithm]: 9.27999e-06 [meta_shard_fg_expand]: 3.02002e-06 [get_grad_eliminate_]: 8.46997e-06 [merge_forward]: 5.05001e-06 [cell_reuse_recompute_pass]: 1.24998e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.328e-05 [j_node_and_user_rematch]: 1.421e-05 [meta_fg_expand]: 3.3e-06 [replace_old_param]: 1.418e-05 [inline_without_move]: 8.52e-06 [renormalize]: 0.176995 [add_forward_monad_depend]: 1.948e-05 [auto_monad_grad]: 3.26999e-06 [auto_monad_eliminator]: 2.769e-05 [cse]: 4.076e-05 [replace_applicator]: 2.969e-05 [Cycle 2]: 0.00055626, [27] [switch_simplify]: 1.055e-05 [loop_unroll]: 8.55999e-06 [a_1]: 0.00021244 [with_stream_mark]: 1.786e-05 [recompute_prepare]: 9.20999e-06 [updatestate_depend_eliminate]: 5.66998e-06 [updatestate_assign_eliminate]: 5.24e-06 [updatestate_loads_eliminate]: 4.23001e-06 [parameter_eliminate]: 1.99999e-06 [specialize_transform]: 8.45999e-06 [updatestate_useless_node_eliminater]: 1.114e-05 [accelerated_algorithm]: 9.27999e-06 [meta_shard_fg_expand]: 2.68998e-06 [get_grad_eliminate_]: 8.28001e-06 [merge_forward]: 5.77001e-06 [cell_reuse_recompute_pass]: 3.53e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.07e-05 [j_node_and_user_rematch]: 1.381e-05 [meta_fg_expand]: 3.81001e-06 [replace_old_param]: 1.18e-05 [inline_without_move]: 8.25e-06 [renormalize]: 5.9983e-08 [add_forward_monad_depend]: 2.11e-06 [auto_monad_grad]: 1.52999e-06 [auto_monad_eliminator]: 1.119e-05 [cse]: 1.935e-05 [replace_applicator]: 8.65001e-06 [py_interpret_to_execute_after_opt_a]: 1.854e-05 [rewriter_after_opt_a]: 0.00055307 [convert_after_rewriter]: 1.84e-05 [order_py_execute_after_rewriter]: 7.32002e-06 [mutable_eliminate]: 0.00092659 [jit_opt_b]: 8.787e-05, [1] [Cycle 1]: 7.853e-05, [2] [frontend_op_eliminate]: 3.18e-05 [inline_after_opt_a]: 3.148e-05 [cconv]: 3.925e-05 [loop_unroll]: 0.00051324 [jit_opt_after_cconv]: 0.00024303, [1] [Cycle 1]: 0.00023562, [11] [c_1]: 5.818e-05 [parameter_eliminate]: 5.42999e-06 [updatestate_depend_eliminate]: 1.233e-05 [updatestate_assign_eliminate]: 5.30999e-06 [updatestate_loads_eliminate]: 4.79998e-06 [cse]: 4.137e-05 [call_graph_tuple_transform]: 2.701e-05 [tuple_list_get_item_eliminator]: 9.37001e-06 [none_parameter_eliminate]: 1.92999e-06 [renormalize]: 6.89994e-07 [switch_simplify]: 9.76e-06 [remove_dup_value]: 2.002e-05 [partial_unused_args_eliminate]: 2.46e-06 [environ_conv]: 2.527e-05 [add_recomputation]: 8.147e-05 [cse_after_recomputation]: 3.385e-05, [1] [Cycle 1]: 2.617e-05, [1] [cse]: 1.894e-05 [auto_monad_reorder]: 3.486e-05 [get_jit_bprop_graph]: 2.63998e-06 [rewriter_after_jit_bprop_graph]: 4.65001e-06 [opt_after_jit_grad]: 0.00053246 [symbol_engine_optimizer]: 0.00010299, [1] [Cycle 1]: 9.53e-05, [6] [build]: 5.81e-06 [elim_shapecalc]: 1.274e-05 [elim_not_effective]: 1.964e-05 [opt_reshape]: 9.87001e-06 [fold_const_symbol]: 1.586e-05 [renormalize]: 4.10015e-07 [validate]: 8.011e-05 Sums bootstrap : 0.279281s : 12.97% type_inference : 1.691488s : 78.56% event_method : 0.000019s : 0.00% auto_monad : 0.000194s : 0.01% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000366s : 0.02% rewriter_before_opt_a : 0.000092s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000103s : 0.00% jit_opt_a.loop_unroll : 0.000036s : 0.00% jit_opt_a.a_1 : 0.000741s : 0.03% jit_opt_a.with_stream_mark : 0.000045s : 0.00% jit_opt_a.recompute_prepare : 0.000021s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 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 : 0.000022s : 0.00% jit_opt_a.accelerated_algorithm : 0.000019s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000044s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000026s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.176995s : 8.22% jit_opt_a.add_forward_monad_depend : 0.000022s : 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 : 0.000060s : 0.00% jit_opt_a.replace_applicator : 0.000038s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000553s : 0.03% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000927s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000032s : 0.00% jit_opt_b.inline_after_opt_a : 0.000031s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000513s : 0.02% jit_opt_after_cconv.c_1 : 0.000058s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000041s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000027s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 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 : 0.000020s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000025s : 0.00% add_recomputation : 0.000081s : 0.00% cse_after_recomputation.cse : 0.000019s : 0.00% auto_monad_reorder : 0.000035s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000532s : 0.02% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 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 : 0.000016s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000080s : 0.00% Time group info: ------[substitution.] 0.000247 45 4.82% : 0.000012s : 2: substitution.depend_value_elim 1.18% : 0.000003s : 4: substitution.elim_not_effective 1.20% : 0.000003s : 4: substitution.fold_const_symbol 3.24% : 0.000008s : 6: substitution.graph_param_transform 71.97% : 0.000178s : 3: substitution.inline 2.26% : 0.000006s : 8: substitution.j_node_and_user_rematch 3.19% : 0.000008s : 8: substitution.remove_not_recompute_node 2.58% : 0.000006s : 2: substitution.replace_old_param 5.26% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.29% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.691385 2 99.89% : 1.689443s : 1: type_inference.infer 0.11% : 0.001943s : 1: type_inference.specialize ------[replace.] 0.000037 3 100.00% : 0.000037s : 3: replace.inline ------[match.] 0.000176 3 100.00% : 0.000176s : 3: match.inline ------[predicate.] 0.000171 970 1.27% : 0.000002s : 14: predicate.accumulaten_eliminater 1.29% : 0.000002s : 6: predicate.ad_related_special_op_eliminate 1.04% : 0.000002s : 14: predicate.addn_check_dump 1.19% : 0.000002s : 14: predicate.addn_zero_filter 2.17% : 0.000004s : 14: predicate.arithmetic_simplify 1.47% : 0.000003s : 14: predicate.cast_eliminate 0.53% : 0.000001s : 6: predicate.check_bprop_eliminate 1.15% : 0.000002s : 14: predicate.compare_switch_simplify 1.30% : 0.000002s : 14: predicate.depend_value_elim 1.14% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.28% : 0.000002s : 14: predicate.dict_get_item_eliminator 1.17% : 0.000002s : 14: predicate.dict_set_item_eliminator 1.02% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.47% : 0.000001s : 6: predicate.elim_not_effective 0.76% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.37% : 0.000002s : 14: predicate.environ_add_const_eliminate 1.04% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.03% : 0.000002s : 14: predicate.environ_get_depend_swap 1.31% : 0.000002s : 14: predicate.environ_get_eliminate 1.03% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.29% : 0.000001s : 6: predicate.fold_const_symbol 1.29% : 0.000002s : 12: predicate.get_grad_eliminate 0.47% : 0.000001s : 6: predicate.graph_param_transform 4.93% : 0.000008s : 29: predicate.inline 1.16% : 0.000002s : 12: predicate.inline_without_move 0.53% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.49% : 0.000003s : 12: predicate.less_batch_normalization 1.49% : 0.000003s : 14: predicate.list_to_tuple_eliminator_ 2.24% : 0.000004s : 20: predicate.load_eliminater 1.95% : 0.000003s : 6: predicate.loop_unroll_after_grad 2.77% : 0.000005s : 30: predicate.loop_unroll_before_grad 2.01% : 0.000003s : 20: predicate.make_slice_get_slice_eliminator 1.06% : 0.000002s : 14: predicate.merge_addn 1.14% : 0.000002s : 14: predicate.minmaximum_grad 2.03% : 0.000003s : 6: predicate.mutable_eliminate 0.67% : 0.000001s : 6: predicate.opt_reshape 2.25% : 0.000004s : 20: predicate.partial_eliminate 1.09% : 0.000002s : 14: predicate.print_const_string_wrapper 1.70% : 0.000003s : 14: predicate.reduce_eliminate 1.72% : 0.000003s : 14: predicate.redundant_stop_gradient_eliminater 0.85% : 0.000001s : 12: predicate.remove_not_recompute_node 1.90% : 0.000003s : 26: predicate.replace_applicator 0.79% : 0.000001s : 12: predicate.replace_old_param 0.62% : 0.000001s : 6: predicate.reset_defer_inline 1.23% : 0.000002s : 14: predicate.reshape_eliminate 1.17% : 0.000002s : 14: predicate.row_tensor_add_zeros_like 1.06% : 0.000002s : 6: predicate.row_tensor_eliminate 1.31% : 0.000002s : 14: predicate.same_eliminate 0.70% : 0.000001s : 12: predicate.set_cell_output_no_recompute 1.23% : 0.000002s : 12: predicate.special_op_eliminate 1.22% : 0.000002s : 12: predicate.specialize_transform 1.44% : 0.000002s : 14: predicate.split_environ_get_set_with_tuple_value 1.32% : 0.000002s : 14: predicate.stack_unstack_eliminate 0.66% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.63% : 0.000003s : 17: predicate.switch_defer_inline 1.49% : 0.000003s : 17: predicate.switch_layer_defer_inline 6.08% : 0.000010s : 53: predicate.switch_simplify 1.35% : 0.000002s : 14: predicate.tile_eliminate 1.19% : 0.000002s : 14: predicate.transpose_eliminate 1.38% : 0.000002s : 14: predicate.tuple_list_convert_item_index_to_positive 1.27% : 0.000002s : 14: predicate.tuple_list_get_item_depend_reorder 4.01% : 0.000007s : 26: predicate.tuple_list_get_item_eliminator 1.64% : 0.000003s : 14: predicate.tuple_list_set_item_eliminator 1.18% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.68% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 3.54% : 0.000006s : 32: predicate.updatestate_useless_node_eliminater 1.51% : 0.000003s : 14: predicate.value_based_eliminate 0.49% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.77% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.151987 23 99.42% : 0.151098s : 18: func_graph_cloner_run.FuncGraphClonerGraph 0.58% : 0.000888s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.341537 72 0.00% : 0.000085s : 1: add_recomputation 0.01% : 0.000201s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 11.93% : 0.279314s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000023s : 1: convert_after_rewriter 0.00% : 0.000037s : 1: cse_after_recomputation 0.00% : 0.000028s : 1: environ_conv 0.00% : 0.000025s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 8.04% : 0.188303s : 1: jit_opt_a 0.01% : 0.000246s : 1: jit_opt_after_cconv 0.00% : 0.000091s : 1: jit_opt_b 0.02% : 0.000523s : 1: loop_unroll 0.04% : 0.000938s : 1: mutable_eliminate 0.05% : 0.001081s : 26: opt.transform.jit_opt_a 0.00% : 0.000100s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000054s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000025s : 1: opt.transform.mutable_eliminate 0.00% : 0.000034s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000054s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000541s : 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% : 0.000015s : 1: pre_auto_parallel 0.02% : 0.000376s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000023s : 1: remove_dup_value 7.51% : 0.175910s : 1: renormalize.infer 0.05% : 0.001071s : 1: renormalize.specialize 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000562s : 1: rewriter_after_opt_a 0.00% : 0.000097s : 1: rewriter_before_opt_a 0.00% : 0.000106s : 1: symbol_engine_optimizer 72.24% : 1.691514s : 1: type_inference TotalTime = 2.05146, [30] [bootstrap]: 0.00070885 [type_inference]: 1.36885 [event_method]: 0.00131928 [auto_monad]: 0.00050638 [graph_reusing]: 1.31e-05 [pre_auto_parallel]: 5.51e-06 [py_interpret_to_execute]: 6.311e-05 [rewriter_before_opt_a]: 0.00018897 [expand_dump_flag]: 4.80001e-06 [jit_opt_a]: 0.672548, [4] [Cycle 1]: 0.543632, [27] [switch_simplify]: 0.00039546 [loop_unroll]: 9.676e-05 [a_1]: 0.0877332 [with_stream_mark]: 5.086e-05 [recompute_prepare]: 5.938e-05 [updatestate_depend_eliminate]: 1.639e-05 [updatestate_assign_eliminate]: 1.184e-05 [updatestate_loads_eliminate]: 1.118e-05 [parameter_eliminate]: 4.90001e-06 [specialize_transform]: 3.14e-05 [updatestate_useless_node_eliminater]: 3.305e-05 [accelerated_algorithm]: 3.374e-05 [meta_shard_fg_expand]: 1.56e-05 [get_grad_eliminate_]: 2.776e-05 [merge_forward]: 1.243e-05 [cell_reuse_recompute_pass]: 1.83002e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.417e-05 [j_node_and_user_rematch]: 4.76e-05 [meta_fg_expand]: 0.0924828 [replace_old_param]: 0.00018163 [inline_without_move]: 0.00021452 [renormalize]: 0.361023 [add_forward_monad_depend]: 2.469e-05 [auto_monad_grad]: 1.797e-05 [auto_monad_eliminator]: 0.00012232 [cse]: 0.00029356 [replace_applicator]: 0.00025071 [Cycle 2]: 0.120867, [27] [switch_simplify]: 0.00014882 [loop_unroll]: 9.045e-05 [a_1]: 0.00394166 [with_stream_mark]: 3.349e-05 [recompute_prepare]: 3.186e-05 [updatestate_depend_eliminate]: 1.328e-05 [updatestate_assign_eliminate]: 1.308e-05 [updatestate_loads_eliminate]: 1.276e-05 [parameter_eliminate]: 4.28999e-06 [specialize_transform]: 0.00010045 [updatestate_useless_node_eliminater]: 0.00022043 [accelerated_algorithm]: 2.251e-05 [meta_shard_fg_expand]: 1.053e-05 [get_grad_eliminate_]: 1.438e-05 [merge_forward]: 1.999e-05 [cell_reuse_recompute_pass]: 4.12998e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.862e-05 [j_node_and_user_rematch]: 2.406e-05 [meta_fg_expand]: 0.00029819 [replace_old_param]: 3.345e-05 [inline_without_move]: 3.994e-05 [renormalize]: 0.00325171 [add_forward_monad_depend]: 1.255e-05 [auto_monad_grad]: 2.43e-06 [auto_monad_eliminator]: 0.0001059 [cse]: 0.00014809 [replace_applicator]: 4.357e-05 [Cycle 3]: 0.00200807, [27] [switch_simplify]: 1.675e-05 [loop_unroll]: 1.532e-05 [a_1]: 0.00037883 [with_stream_mark]: 2.711e-05 [recompute_prepare]: 1.643e-05 [updatestate_depend_eliminate]: 6.217e-05 [updatestate_assign_eliminate]: 7.00002e-06 [updatestate_loads_eliminate]: 7.61001e-06 [parameter_eliminate]: 2.61999e-06 [specialize_transform]: 1.478e-05 [updatestate_useless_node_eliminater]: 1.643e-05 [accelerated_algorithm]: 1.252e-05 [meta_shard_fg_expand]: 4.18001e-06 [get_grad_eliminate_]: 1.13e-05 [merge_forward]: 7.3e-06 [cell_reuse_recompute_pass]: 4.30999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.891e-05 [j_node_and_user_rematch]: 1.979e-05 [meta_fg_expand]: 5.29e-06 [replace_old_param]: 1.696e-05 [inline_without_move]: 1.177e-05 [renormalize]: 0.00100183 [add_forward_monad_depend]: 7.78999e-06 [auto_monad_grad]: 2.28002e-06 [auto_monad_eliminator]: 2.803e-05 [cse]: 4.94e-05 [replace_applicator]: 3.181e-05 [Cycle 4]: 0.0007286, [27] [switch_simplify]: 1.355e-05 [loop_unroll]: 1.334e-05 [a_1]: 0.00028503 [with_stream_mark]: 2.094e-05 [recompute_prepare]: 1.438e-05 [updatestate_depend_eliminate]: 7.45998e-06 [updatestate_assign_eliminate]: 5.51e-06 [updatestate_loads_eliminate]: 7.89002e-06 [parameter_eliminate]: 1.72999e-06 [specialize_transform]: 1.109e-05 [updatestate_useless_node_eliminater]: 1.454e-05 [accelerated_algorithm]: 1.201e-05 [meta_shard_fg_expand]: 3.75e-06 [get_grad_eliminate_]: 1.112e-05 [merge_forward]: 6.68e-06 [cell_reuse_recompute_pass]: 2.35002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.459e-05 [j_node_and_user_rematch]: 2.036e-05 [meta_fg_expand]: 4.73001e-06 [replace_old_param]: 1.483e-05 [inline_without_move]: 1.406e-05 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 2.93e-06 [auto_monad_grad]: 1.79998e-06 [auto_monad_eliminator]: 1.957e-05 [cse]: 3.385e-05 [replace_applicator]: 1.256e-05 [py_interpret_to_execute_after_opt_a]: 2.246e-05 [rewriter_after_opt_a]: 0.00025676 [convert_after_rewriter]: 1.451e-05 [order_py_execute_after_rewriter]: 1.149e-05 [mutable_eliminate]: 0.00388965 [jit_opt_b]: 0.00019116, [1] [Cycle 1]: 0.0001763, [2] [frontend_op_eliminate]: 5.15e-05 [inline_after_opt_a]: 0.00010064 [cconv]: 5.315e-05 [loop_unroll]: 0.00074383 [jit_opt_after_cconv]: 0.00041642, [1] [Cycle 1]: 0.00040567, [11] [c_1]: 8.827e-05 [parameter_eliminate]: 7.14001e-06 [updatestate_depend_eliminate]: 6.462e-05 [updatestate_assign_eliminate]: 9.67001e-06 [updatestate_loads_eliminate]: 6.34001e-06 [cse]: 7.514e-05 [call_graph_tuple_transform]: 4.552e-05 [tuple_list_get_item_eliminator]: 1.217e-05 [none_parameter_eliminate]: 3.14999e-06 [renormalize]: 6.49976e-07 [switch_simplify]: 1.457e-05 [remove_dup_value]: 7.902e-05 [partial_unused_args_eliminate]: 3.06001e-06 [environ_conv]: 1.927e-05 [add_recomputation]: 0.0001025 [cse_after_recomputation]: 4.879e-05, [1] [Cycle 1]: 3.996e-05, [1] [cse]: 2.977e-05 [auto_monad_reorder]: 4.026e-05 [get_jit_bprop_graph]: 4.75001e-06 [rewriter_after_jit_bprop_graph]: 1.17e-05 [opt_after_jit_grad]: 0.00079943 [symbol_engine_optimizer]: 0.00012712, [1] [Cycle 1]: 0.00011915, [6] [build]: 1.038e-05 [elim_shapecalc]: 1.723e-05 [elim_not_effective]: 2.745e-05 [opt_reshape]: 1.256e-05 [fold_const_symbol]: 1.87e-05 [renormalize]: 2.9002e-07 [validate]: 8.093e-05 Sums bootstrap : 0.000709s : 0.04% type_inference : 1.368855s : 70.83% event_method : 0.001319s : 0.07% auto_monad : 0.000506s : 0.03% graph_reusing : 0.000013s : 0.00% pre_auto_parallel : 0.000006s : 0.00% py_interpret_to_execute : 0.000063s : 0.00% rewriter_before_opt_a : 0.000189s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000575s : 0.03% jit_opt_a.loop_unroll : 0.000216s : 0.01% jit_opt_a.a_1 : 0.092339s : 4.78% jit_opt_a.with_stream_mark : 0.000132s : 0.01% jit_opt_a.recompute_prepare : 0.000122s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000099s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000037s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000039s : 0.00% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000158s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000284s : 0.01% jit_opt_a.accelerated_algorithm : 0.000081s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000034s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000065s : 0.00% jit_opt_a.merge_forward : 0.000046s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000013s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000146s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000112s : 0.01% jit_opt_a.meta_fg_expand : 0.092791s : 4.80% jit_opt_a.replace_old_param : 0.000247s : 0.01% jit_opt_a.inline_without_move : 0.000280s : 0.01% jit_opt_a.renormalize : 0.365277s : 18.90% jit_opt_a.add_forward_monad_depend : 0.000048s : 0.00% jit_opt_a.auto_monad_grad : 0.000024s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000276s : 0.01% jit_opt_a.cse : 0.000525s : 0.03% jit_opt_a.replace_applicator : 0.000339s : 0.02% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.000257s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000011s : 0.00% mutable_eliminate : 0.003890s : 0.20% jit_opt_b.frontend_op_eliminate : 0.000051s : 0.00% jit_opt_b.inline_after_opt_a : 0.000101s : 0.01% cconv : 0.000053s : 0.00% loop_unroll : 0.000744s : 0.04% jit_opt_after_cconv.c_1 : 0.000088s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000065s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000075s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000046s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000015s : 0.00% remove_dup_value : 0.000079s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000019s : 0.00% add_recomputation : 0.000102s : 0.01% cse_after_recomputation.cse : 0.000030s : 0.00% auto_monad_reorder : 0.000040s : 0.00% get_jit_bprop_graph : 0.000005s : 0.00% rewriter_after_jit_bprop_graph : 0.000012s : 0.00% opt_after_jit_grad : 0.000799s : 0.04% symbol_engine_optimizer.build : 0.000010s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000081s : 0.00% Time group info: ------[substitution.] 0.003284 271 1.43% : 0.000047s : 12: substitution.depend_value_elim 0.15% : 0.000005s : 5: substitution.elim_not_effective 0.07% : 0.000002s : 5: substitution.fold_const_symbol 29.08% : 0.000955s : 4: substitution.getattr_setattr_resolve 0.33% : 0.000011s : 8: substitution.graph_param_transform 49.38% : 0.001621s : 29: substitution.inline 3.29% : 0.000108s : 4: substitution.inline_without_move 0.55% : 0.000018s : 29: substitution.j_node_and_user_rematch 0.72% : 0.000024s : 13: substitution.minmaximum_grad 1.11% : 0.000036s : 14: substitution.partial_eliminate 0.85% : 0.000028s : 29: substitution.remove_not_recompute_node 2.09% : 0.000069s : 16: substitution.replace_applicator 0.72% : 0.000024s : 17: substitution.replace_old_param 0.24% : 0.000008s : 2: substitution.set_cell_output_no_recompute 0.61% : 0.000020s : 3: substitution.switch_simplify 1.59% : 0.000052s : 13: substitution.tuple_list_convert_item_index_to_positive 1.20% : 0.000039s : 13: substitution.tuple_list_get_item_depend_reorder 3.29% : 0.000108s : 30: substitution.tuple_list_get_item_eliminator 0.89% : 0.000029s : 9: substitution.updatestate_pure_node_eliminater 2.40% : 0.000079s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.368690 2 99.49% : 1.361734s : 1: type_inference.infer 0.51% : 0.006956s : 1: type_inference.specialize ------[replace.] 0.001203 54 8.77% : 0.000106s : 3: replace.getattr_setattr_resolve 40.32% : 0.000485s : 29: replace.inline 4.64% : 0.000056s : 1: replace.replace_applicator 14.70% : 0.000177s : 3: replace.switch_simplify 21.25% : 0.000256s : 17: replace.tuple_list_get_item_eliminator 10.32% : 0.000124s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002592 54 34.35% : 0.000890s : 3: match.getattr_setattr_resolve 61.60% : 0.001596s : 29: match.inline 0.44% : 0.000011s : 1: match.replace_applicator 0.71% : 0.000018s : 3: match.switch_simplify 1.58% : 0.000041s : 17: match.tuple_list_get_item_eliminator 1.32% : 0.000034s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001045 6056 1.38% : 0.000014s : 101: predicate.accumulaten_eliminater 0.35% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.22% : 0.000013s : 101: predicate.addn_check_dump 1.45% : 0.000015s : 101: predicate.addn_zero_filter 2.21% : 0.000023s : 101: predicate.arithmetic_simplify 1.43% : 0.000015s : 101: predicate.cast_eliminate 0.14% : 0.000001s : 8: predicate.check_bprop_eliminate 1.27% : 0.000013s : 101: predicate.compare_switch_simplify 2.55% : 0.000027s : 101: predicate.depend_value_elim 1.39% : 0.000015s : 101: predicate.dict_get_item_const_eliminator 1.44% : 0.000015s : 101: predicate.dict_get_item_eliminator 1.36% : 0.000014s : 101: predicate.dict_set_item_eliminator 0.24% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.09% : 0.000001s : 8: predicate.elim_not_effective 0.15% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.30% : 0.000014s : 101: predicate.environ_add_const_eliminate 1.33% : 0.000014s : 101: predicate.environ_get_add_eliminate 1.35% : 0.000014s : 101: predicate.environ_get_depend_swap 1.44% : 0.000015s : 101: predicate.environ_get_eliminate 1.37% : 0.000014s : 101: predicate.environ_get_set_eliminate 0.06% : 0.000001s : 8: predicate.fold_const_symbol 0.74% : 0.000008s : 44: predicate.get_grad_eliminate 0.80% : 0.000008s : 20: predicate.getattr_setattr_resolve 0.09% : 0.000001s : 8: predicate.graph_param_transform 4.14% : 0.000043s : 163: predicate.inline 2.23% : 0.000023s : 105: predicate.inline_without_move 0.36% : 0.000004s : 44: predicate.j_node_and_user_rematch 1.12% : 0.000012s : 44: predicate.less_batch_normalization 1.65% : 0.000017s : 118: predicate.list_to_tuple_eliminator_ 2.09% : 0.000022s : 126: predicate.load_eliminater 0.54% : 0.000006s : 8: predicate.loop_unroll_after_grad 2.79% : 0.000029s : 187: predicate.loop_unroll_before_grad 1.64% : 0.000017s : 109: predicate.make_slice_get_slice_eliminator 1.35% : 0.000014s : 101: predicate.merge_addn 1.43% : 0.000015s : 101: predicate.minmaximum_grad 1.06% : 0.000011s : 8: predicate.mutable_eliminate 0.14% : 0.000001s : 8: predicate.opt_reshape 2.20% : 0.000023s : 126: predicate.partial_eliminate 1.30% : 0.000014s : 101: predicate.print_const_string_wrapper 1.98% : 0.000021s : 101: predicate.reduce_eliminate 1.82% : 0.000019s : 118: predicate.redundant_stop_gradient_eliminater 0.43% : 0.000005s : 44: predicate.remove_not_recompute_node 2.46% : 0.000026s : 243: predicate.replace_applicator 1.06% : 0.000011s : 105: predicate.replace_old_param 0.16% : 0.000002s : 8: predicate.reset_defer_inline 1.49% : 0.000016s : 101: predicate.reshape_eliminate 1.46% : 0.000015s : 101: predicate.row_tensor_add_zeros_like 0.26% : 0.000003s : 8: predicate.row_tensor_eliminate 1.71% : 0.000018s : 101: predicate.same_eliminate 0.47% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.28% : 0.000003s : 16: predicate.special_op_eliminate 2.39% : 0.000025s : 50: predicate.specialize_transform 1.76% : 0.000018s : 101: predicate.split_environ_get_set_with_tuple_value 1.41% : 0.000015s : 101: predicate.stack_unstack_eliminate 0.15% : 0.000002s : 8: predicate.switch_call_monad_eliminater 3.32% : 0.000035s : 147: predicate.switch_defer_inline 2.28% : 0.000024s : 147: predicate.switch_layer_defer_inline 5.68% : 0.000059s : 348: predicate.switch_simplify 1.30% : 0.000014s : 101: predicate.tile_eliminate 1.50% : 0.000016s : 101: predicate.transpose_eliminate 1.77% : 0.000018s : 101: predicate.tuple_list_convert_item_index_to_positive 1.57% : 0.000016s : 101: predicate.tuple_list_get_item_depend_reorder 3.03% : 0.000032s : 134: predicate.tuple_list_get_item_eliminator 2.18% : 0.000023s : 101: predicate.tuple_list_set_item_eliminator 1.65% : 0.000017s : 118: predicate.tuple_to_list_eliminator_ 1.74% : 0.000018s : 126: predicate.updatestate_pure_node_eliminater 3.19% : 0.000033s : 172: predicate.updatestate_useless_node_eliminater 1.98% : 0.000021s : 101: predicate.value_based_eliminate 0.10% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.24% : 0.000003s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.014252 79 75.64% : 0.010779s : 42: func_graph_cloner_run.FuncGraphClonerGraph 2.62% : 0.000373s : 7: func_graph_cloner_run.FuncGraphClonerNode 21.75% : 0.003099s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.512901 104 0.00% : 0.000107s : 1: add_recomputation 0.02% : 0.000519s : 1: auto_monad 0.00% : 0.000044s : 1: auto_monad_reorder 0.03% : 0.000739s : 1: bootstrap 0.00% : 0.000057s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.00% : 0.000052s : 1: cse_after_recomputation 0.00% : 0.000022s : 1: environ_conv 0.05% : 0.001336s : 1: event_method 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000017s : 1: graph_reusing 26.76% : 0.672555s : 1: jit_opt_a 0.02% : 0.000421s : 1: jit_opt_after_cconv 0.01% : 0.000197s : 1: jit_opt_b 0.03% : 0.000762s : 1: loop_unroll 0.16% : 0.003917s : 1: mutable_eliminate 3.77% : 0.094765s : 52: opt.transform.jit_opt_a 0.01% : 0.000154s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000085s : 4: opt.transform.jit_opt_b 0.00% : 0.000032s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000089s : 1: opt.transform.mutable_eliminate 0.00% : 0.000054s : 1: opt.transform.opt_after_jit_grad 0.05% : 0.001142s : 2: opt.transform.opt_resolve 0.00% : 0.000071s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000814s : 1: opt_after_jit_grad 0.00% : 0.000014s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000008s : 1: pre_auto_parallel 0.00% : 0.000069s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000085s : 1: remove_dup_value 14.23% : 0.357617s : 3: renormalize.infer 0.30% : 0.007611s : 3: renormalize.specialize 0.00% : 0.000014s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000266s : 1: rewriter_after_opt_a 0.01% : 0.000193s : 1: rewriter_before_opt_a 0.01% : 0.000131s : 1: symbol_engine_optimizer 54.47% : 1.368878s : 1: type_inference . [hook] pytest_runtest_teardown:test_mint_permute_normal[0] tests/st/mint/test_permute.py::test_mint_permute_normal[0],max_mem:4.0M . [hook] pytest_runtest_teardown:test_mint_permute_normal[1] tests/st/mint/test_permute.py::test_mint_permute_normal[1],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 215.23s (0:03:35) ==================