==================================================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_003/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_large_tensors[pynative] tests/st/mint/test_permute.py::test_permute_large_tensors[pynative],max_mem:2.0M TotalTime = 1.24296, [30] [bootstrap]: 0.00076444 [type_inference]: 1.11286 [event_method]: 1.624e-05 [auto_monad]: 0.00023837 [graph_reusing]: 7.59002e-06 [pre_auto_parallel]: 1.371e-05 [py_interpret_to_execute]: 0.00041192 [rewriter_before_opt_a]: 8.946e-05 [expand_dump_flag]: 4.02002e-06 [jit_opt_a]: 0.123855, [2] [Cycle 1]: 0.00512037, [27] [switch_simplify]: 7.166e-05 [loop_unroll]: 2.819e-05 [a_1]: 0.00060091 [with_stream_mark]: 3.22e-05 [recompute_prepare]: 1.183e-05 [updatestate_depend_eliminate]: 7.43999e-06 [updatestate_assign_eliminate]: 5.81998e-06 [updatestate_loads_eliminate]: 5.59e-06 [parameter_eliminate]: 1.96e-06 [specialize_transform]: 1.106e-05 [updatestate_useless_node_eliminater]: 1.187e-05 [accelerated_algorithm]: 1.037e-05 [meta_shard_fg_expand]: 3.56999e-06 [get_grad_eliminate_]: 8.72e-06 [merge_forward]: 5.72001e-06 [cell_reuse_recompute_pass]: 1.27e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.741e-05 [j_node_and_user_rematch]: 1.535e-05 [meta_fg_expand]: 3.76001e-06 [replace_old_param]: 1.351e-05 [inline_without_move]: 9.27001e-06 [renormalize]: 0.00378178 [add_forward_monad_depend]: 1.886e-05 [auto_monad_grad]: 2.91e-06 [auto_monad_eliminator]: 2.902e-05 [cse]: 4.28e-05 [replace_applicator]: 2.795e-05 [Cycle 2]: 0.00065843, [27] [switch_simplify]: 1.093e-05 [loop_unroll]: 9.51998e-06 [a_1]: 0.00023123 [with_stream_mark]: 1.931e-05 [recompute_prepare]: 1.105e-05 [updatestate_depend_eliminate]: 7.06001e-06 [updatestate_assign_eliminate]: 5.99999e-06 [updatestate_loads_eliminate]: 4.55999e-06 [parameter_eliminate]: 2.39001e-06 [specialize_transform]: 9.64999e-06 [updatestate_useless_node_eliminater]: 1.191e-05 [accelerated_algorithm]: 9.53002e-06 [meta_shard_fg_expand]: 3.49001e-06 [get_grad_eliminate_]: 8.67e-06 [merge_forward]: 6.38e-06 [cell_reuse_recompute_pass]: 2.75002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.045e-05 [j_node_and_user_rematch]: 1.349e-05 [meta_fg_expand]: 3.63999e-06 [replace_old_param]: 1.28e-05 [inline_without_move]: 8.60001e-06 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 1.77001e-06 [auto_monad_grad]: 1.63002e-06 [auto_monad_eliminator]: 1.329e-05 [cse]: 2.172e-05 [replace_applicator]: 1.273e-05 [py_interpret_to_execute_after_opt_a]: 2.338e-05 [rewriter_after_opt_a]: 0.00057536 [convert_after_rewriter]: 3.167e-05 [order_py_execute_after_rewriter]: 8.41002e-06 [mutable_eliminate]: 0.0010726 [jit_opt_b]: 0.00010228, [1] [Cycle 1]: 9.089e-05, [2] [frontend_op_eliminate]: 3.737e-05 [inline_after_opt_a]: 3.67e-05 [cconv]: 4.254e-05 [loop_unroll]: 0.0007425 [jit_opt_after_cconv]: 0.00026247, [1] [Cycle 1]: 0.00025339, [11] [c_1]: 6.456e-05 [parameter_eliminate]: 6.17999e-06 [updatestate_depend_eliminate]: 1.434e-05 [updatestate_assign_eliminate]: 5.69999e-06 [updatestate_loads_eliminate]: 5.27001e-06 [cse]: 4.511e-05 [call_graph_tuple_transform]: 2.975e-05 [tuple_list_get_item_eliminator]: 9.65002e-06 [none_parameter_eliminate]: 1.60001e-06 [renormalize]: 5.19998e-07 [switch_simplify]: 9.96998e-06 [remove_dup_value]: 2.431e-05 [partial_unused_args_eliminate]: 3.4e-06 [environ_conv]: 5.028e-05 [add_recomputation]: 0.00013082 [cse_after_recomputation]: 4.38e-05, [1] [Cycle 1]: 3.564e-05, [1] [cse]: 2.536e-05 [auto_monad_reorder]: 4.281e-05 [get_jit_bprop_graph]: 2.60002e-06 [rewriter_after_jit_bprop_graph]: 0.00016537 [opt_after_jit_grad]: 0.0006905 [symbol_engine_optimizer]: 0.00017872, [1] [Cycle 1]: 0.00016891, [6] [build]: 8.52998e-06 [elim_shapecalc]: 5.891e-05 [elim_not_effective]: 2.62e-05 [opt_reshape]: 1.192e-05 [fold_const_symbol]: 1.734e-05 [renormalize]: 9.89996e-07 [validate]: 9.259e-05 Sums bootstrap : 0.000764s : 0.07% type_inference : 1.112861s : 99.03% event_method : 0.000016s : 0.00% auto_monad : 0.000238s : 0.02% graph_reusing : 0.000008s : 0.00% pre_auto_parallel : 0.000014s : 0.00% py_interpret_to_execute : 0.000412s : 0.04% rewriter_before_opt_a : 0.000089s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000083s : 0.01% jit_opt_a.loop_unroll : 0.000038s : 0.00% jit_opt_a.a_1 : 0.000832s : 0.07% jit_opt_a.with_stream_mark : 0.000052s : 0.00% jit_opt_a.recompute_prepare : 0.000023s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000024s : 0.00% jit_opt_a.accelerated_algorithm : 0.000020s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000007s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000048s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000029s : 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 : 0.000018s : 0.00% jit_opt_a.renormalize : 0.003782s : 0.34% 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 : 0.000042s : 0.00% jit_opt_a.cse : 0.000065s : 0.01% jit_opt_a.replace_applicator : 0.000041s : 0.00% py_interpret_to_execute_after_opt_a : 0.000023s : 0.00% rewriter_after_opt_a : 0.000575s : 0.05% convert_after_rewriter : 0.000032s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.001073s : 0.10% jit_opt_b.frontend_op_eliminate : 0.000037s : 0.00% jit_opt_b.inline_after_opt_a : 0.000037s : 0.00% cconv : 0.000043s : 0.00% loop_unroll : 0.000743s : 0.07% jit_opt_after_cconv.c_1 : 0.000065s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 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 : 0.000045s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 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 : 0.000024s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000050s : 0.00% add_recomputation : 0.000131s : 0.01% cse_after_recomputation.cse : 0.000025s : 0.00% auto_monad_reorder : 0.000043s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000165s : 0.01% opt_after_jit_grad : 0.000690s : 0.06% symbol_engine_optimizer.build : 0.000009s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000059s : 0.01% symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000093s : 0.01% Time group info: ------[substitution.] 0.000298 45 4.31% : 0.000013s : 2: substitution.depend_value_elim 1.11% : 0.000003s : 4: substitution.elim_not_effective 0.84% : 0.000002s : 4: substitution.fold_const_symbol 3.27% : 0.000010s : 6: substitution.graph_param_transform 74.81% : 0.000223s : 3: substitution.inline 2.02% : 0.000006s : 8: substitution.j_node_and_user_rematch 2.69% : 0.000008s : 8: substitution.remove_not_recompute_node 2.09% : 0.000006s : 2: substitution.replace_old_param 4.77% : 0.000014s : 3: substitution.updatestate_pure_node_eliminater 4.10% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.112762 2 99.79% : 1.110388s : 1: type_inference.infer 0.21% : 0.002374s : 1: type_inference.specialize ------[replace.] 0.000039 3 100.00% : 0.000039s : 3: replace.inline ------[match.] 0.000220 3 100.00% : 0.000220s : 3: match.inline ------[predicate.] 0.000184 970 1.30% : 0.000002s : 14: predicate.accumulaten_eliminater 1.95% : 0.000004s : 6: predicate.ad_related_special_op_eliminate 1.12% : 0.000002s : 14: predicate.addn_check_dump 1.23% : 0.000002s : 14: predicate.addn_zero_filter 1.94% : 0.000004s : 14: predicate.arithmetic_simplify 1.10% : 0.000002s : 14: predicate.cast_eliminate 0.52% : 0.000001s : 6: predicate.check_bprop_eliminate 1.23% : 0.000002s : 14: predicate.compare_switch_simplify 1.53% : 0.000003s : 14: predicate.depend_value_elim 1.26% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.23% : 0.000002s : 14: predicate.dict_get_item_eliminator 1.26% : 0.000002s : 14: predicate.dict_set_item_eliminator 1.32% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.49% : 0.000001s : 6: predicate.elim_not_effective 0.91% : 0.000002s : 6: predicate.elim_shapecalc_of_broadcastargs 1.19% : 0.000002s : 14: predicate.environ_add_const_eliminate 0.95% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.06% : 0.000002s : 14: predicate.environ_get_depend_swap 1.12% : 0.000002s : 14: predicate.environ_get_eliminate 0.96% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.28% : 0.000001s : 6: predicate.fold_const_symbol 1.16% : 0.000002s : 12: predicate.get_grad_eliminate 0.41% : 0.000001s : 6: predicate.graph_param_transform 5.74% : 0.000011s : 29: predicate.inline 1.09% : 0.000002s : 12: predicate.inline_without_move 0.48% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.76% : 0.000003s : 12: predicate.less_batch_normalization 1.20% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.89% : 0.000003s : 20: predicate.load_eliminater 1.68% : 0.000003s : 6: predicate.loop_unroll_after_grad 3.20% : 0.000006s : 30: predicate.loop_unroll_before_grad 2.26% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.03% : 0.000002s : 14: predicate.merge_addn 1.24% : 0.000002s : 14: predicate.minmaximum_grad 2.79% : 0.000005s : 6: predicate.mutable_eliminate 0.80% : 0.000001s : 6: predicate.opt_reshape 2.20% : 0.000004s : 20: predicate.partial_eliminate 1.06% : 0.000002s : 14: predicate.print_const_string_wrapper 1.51% : 0.000003s : 14: predicate.reduce_eliminate 1.23% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.81% : 0.000001s : 12: predicate.remove_not_recompute_node 1.96% : 0.000004s : 26: predicate.replace_applicator 0.76% : 0.000001s : 12: predicate.replace_old_param 0.61% : 0.000001s : 6: predicate.reset_defer_inline 1.25% : 0.000002s : 14: predicate.reshape_eliminate 1.15% : 0.000002s : 14: predicate.row_tensor_add_zeros_like 1.10% : 0.000002s : 6: predicate.row_tensor_eliminate 1.35% : 0.000002s : 14: predicate.same_eliminate 0.64% : 0.000001s : 12: predicate.set_cell_output_no_recompute 1.40% : 0.000003s : 12: predicate.special_op_eliminate 1.49% : 0.000003s : 12: predicate.specialize_transform 1.38% : 0.000003s : 14: predicate.split_environ_get_set_with_tuple_value 1.15% : 0.000002s : 14: predicate.stack_unstack_eliminate 0.63% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.64% : 0.000003s : 17: predicate.switch_defer_inline 1.76% : 0.000003s : 17: predicate.switch_layer_defer_inline 5.37% : 0.000010s : 53: predicate.switch_simplify 1.15% : 0.000002s : 14: predicate.tile_eliminate 1.23% : 0.000002s : 14: predicate.transpose_eliminate 1.43% : 0.000003s : 14: predicate.tuple_list_convert_item_index_to_positive 1.18% : 0.000002s : 14: predicate.tuple_list_get_item_depend_reorder 3.65% : 0.000007s : 26: predicate.tuple_list_get_item_eliminator 1.58% : 0.000003s : 14: predicate.tuple_list_set_item_eliminator 1.17% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.68% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 3.15% : 0.000006s : 32: predicate.updatestate_useless_node_eliminater 1.38% : 0.000003s : 14: predicate.value_based_eliminate 0.47% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.79% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.014157 23 94.15% : 0.013329s : 18: func_graph_cloner_run.FuncGraphClonerGraph 5.85% : 0.000829s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.247970 72 0.01% : 0.000137s : 1: add_recomputation 0.02% : 0.000246s : 1: auto_monad 0.00% : 0.000046s : 1: auto_monad_reorder 0.06% : 0.000792s : 1: bootstrap 0.00% : 0.000045s : 1: cconv 0.00% : 0.000036s : 1: convert_after_rewriter 0.00% : 0.000047s : 1: cse_after_recomputation 0.00% : 0.000054s : 1: environ_conv 0.00% : 0.000022s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000011s : 1: graph_reusing 9.92% : 0.123859s : 1: jit_opt_a 0.02% : 0.000266s : 1: jit_opt_after_cconv 0.01% : 0.000106s : 1: jit_opt_b 0.06% : 0.000756s : 1: loop_unroll 0.09% : 0.001092s : 1: mutable_eliminate 0.09% : 0.001166s : 26: opt.transform.jit_opt_a 0.01% : 0.000110s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000063s : 4: opt.transform.jit_opt_b 0.00% : 0.000022s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.00% : 0.000044s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000108s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000704s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000017s : 1: pre_auto_parallel 0.03% : 0.000421s : 1: py_interpret_to_execute 0.00% : 0.000027s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000028s : 1: remove_dup_value 0.22% : 0.002719s : 1: renormalize.infer 0.08% : 0.001050s : 1: renormalize.specialize 0.01% : 0.000171s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000586s : 1: rewriter_after_opt_a 0.01% : 0.000095s : 1: rewriter_before_opt_a 0.01% : 0.000183s : 1: symbol_engine_optimizer 89.18% : 1.112879s : 1: type_inference TotalTime = 2.31655, [30] [bootstrap]: 0.00074311 [type_inference]: 1.29632 [event_method]: 0.00059111 [auto_monad]: 0.00033376 [graph_reusing]: 1.091e-05 [pre_auto_parallel]: 3.76001e-06 [py_interpret_to_execute]: 5.816e-05 [rewriter_before_opt_a]: 0.00016497 [expand_dump_flag]: 5.24998e-06 [jit_opt_a]: 1.01479, [4] [Cycle 1]: 0.997921, [27] [switch_simplify]: 0.000238 [loop_unroll]: 6.505e-05 [a_1]: 0.00170112 [with_stream_mark]: 4.799e-05 [recompute_prepare]: 3.757e-05 [updatestate_depend_eliminate]: 1.619e-05 [updatestate_assign_eliminate]: 1.168e-05 [updatestate_loads_eliminate]: 1.073e-05 [parameter_eliminate]: 3.91999e-06 [specialize_transform]: 2.285e-05 [updatestate_useless_node_eliminater]: 2.74e-05 [accelerated_algorithm]: 2.344e-05 [meta_shard_fg_expand]: 7.77e-06 [get_grad_eliminate_]: 2.239e-05 [merge_forward]: 1.312e-05 [cell_reuse_recompute_pass]: 1.42e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.566e-05 [j_node_and_user_rematch]: 3.701e-05 [meta_fg_expand]: 0.531729 [replace_old_param]: 0.00013885 [inline_without_move]: 0.00012551 [renormalize]: 0.269899 [add_forward_monad_depend]: 3.101e-05 [auto_monad_grad]: 1.278e-05 [auto_monad_eliminator]: 0.0001238 [cse]: 0.00027627 [replace_applicator]: 0.192857 [Cycle 2]: 0.00838281, [27] [switch_simplify]: 0.00011114 [loop_unroll]: 8.733e-05 [a_1]: 0.00455128 [with_stream_mark]: 5.271e-05 [recompute_prepare]: 4.614e-05 [updatestate_depend_eliminate]: 1.672e-05 [updatestate_assign_eliminate]: 1.574e-05 [updatestate_loads_eliminate]: 1.341e-05 [parameter_eliminate]: 5.43002e-06 [specialize_transform]: 2.535e-05 [updatestate_useless_node_eliminater]: 0.00012688 [accelerated_algorithm]: 1.716e-05 [meta_shard_fg_expand]: 5.97999e-06 [get_grad_eliminate_]: 1.482e-05 [merge_forward]: 1.083e-05 [cell_reuse_recompute_pass]: 1.64e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.336e-05 [j_node_and_user_rematch]: 2.32e-05 [meta_fg_expand]: 0.00017403 [replace_old_param]: 3.485e-05 [inline_without_move]: 1.497e-05 [renormalize]: 0.00246226 [add_forward_monad_depend]: 1.281e-05 [auto_monad_grad]: 2.72001e-06 [auto_monad_eliminator]: 3.837e-05 [cse]: 0.00013905 [replace_applicator]: 4.098e-05 [Cycle 3]: 0.00197427, [27] [switch_simplify]: 1.604e-05 [loop_unroll]: 1.293e-05 [a_1]: 0.00036706 [with_stream_mark]: 2.788e-05 [recompute_prepare]: 1.383e-05 [updatestate_depend_eliminate]: 5.979e-05 [updatestate_assign_eliminate]: 6.69001e-06 [updatestate_loads_eliminate]: 6.98e-06 [parameter_eliminate]: 2.49999e-06 [specialize_transform]: 1.496e-05 [updatestate_useless_node_eliminater]: 1.828e-05 [accelerated_algorithm]: 1.214e-05 [meta_shard_fg_expand]: 3.11999e-06 [get_grad_eliminate_]: 1.113e-05 [merge_forward]: 7.74002e-06 [cell_reuse_recompute_pass]: 3.76999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.934e-05 [j_node_and_user_rematch]: 1.928e-05 [meta_fg_expand]: 4.72e-06 [replace_old_param]: 1.718e-05 [inline_without_move]: 1.094e-05 [renormalize]: 0.00098528 [add_forward_monad_depend]: 1.08e-05 [auto_monad_grad]: 2.29001e-06 [auto_monad_eliminator]: 3.062e-05 [cse]: 5.286e-05 [replace_applicator]: 3.229e-05 [Cycle 4]: 0.00072674, [27] [switch_simplify]: 1.255e-05 [loop_unroll]: 1.145e-05 [a_1]: 0.00029055 [with_stream_mark]: 2.325e-05 [recompute_prepare]: 1.292e-05 [updatestate_depend_eliminate]: 6.76e-06 [updatestate_assign_eliminate]: 6.39999e-06 [updatestate_loads_eliminate]: 7e-06 [parameter_eliminate]: 2.06e-06 [specialize_transform]: 1.163e-05 [updatestate_useless_node_eliminater]: 1.517e-05 [accelerated_algorithm]: 1.197e-05 [meta_shard_fg_expand]: 3.38999e-06 [get_grad_eliminate_]: 1.121e-05 [merge_forward]: 6.70002e-06 [cell_reuse_recompute_pass]: 3.50003e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.593e-05 [j_node_and_user_rematch]: 1.771e-05 [meta_fg_expand]: 4.35999e-06 [replace_old_param]: 1.585e-05 [inline_without_move]: 1.207e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.97002e-06 [auto_monad_grad]: 1.74e-06 [auto_monad_eliminator]: 2.155e-05 [cse]: 3.243e-05 [replace_applicator]: 1.439e-05 [py_interpret_to_execute_after_opt_a]: 2.257e-05 [rewriter_after_opt_a]: 0.00025598 [convert_after_rewriter]: 1.6e-05 [order_py_execute_after_rewriter]: 8.70999e-06 [mutable_eliminate]: 0.00092722 [jit_opt_b]: 0.00010783, [1] [Cycle 1]: 9.749e-05, [2] [frontend_op_eliminate]: 4.058e-05 [inline_after_opt_a]: 4.12e-05 [cconv]: 4.057e-05 [loop_unroll]: 0.00052184 [jit_opt_after_cconv]: 0.00029301, [1] [Cycle 1]: 0.00028484, [11] [c_1]: 7.552e-05 [parameter_eliminate]: 5.38002e-06 [updatestate_depend_eliminate]: 1.555e-05 [updatestate_assign_eliminate]: 6.49999e-06 [updatestate_loads_eliminate]: 5.96e-06 [cse]: 5.587e-05 [call_graph_tuple_transform]: 3.514e-05 [tuple_list_get_item_eliminator]: 1.195e-05 [none_parameter_eliminate]: 1.87999e-06 [renormalize]: 5.69999e-07 [switch_simplify]: 1.282e-05 [remove_dup_value]: 6.031e-05 [partial_unused_args_eliminate]: 2.59001e-06 [environ_conv]: 1.484e-05 [add_recomputation]: 9.688e-05 [cse_after_recomputation]: 4.028e-05, [1] [Cycle 1]: 3.273e-05, [1] [cse]: 2.375e-05 [auto_monad_reorder]: 4.23e-05 [get_jit_bprop_graph]: 2.61e-06 [rewriter_after_jit_bprop_graph]: 9.17999e-06 [opt_after_jit_grad]: 0.00059793 [symbol_engine_optimizer]: 0.00011713, [1] [Cycle 1]: 0.00010943, [6] [build]: 6.64999e-06 [elim_shapecalc]: 1.517e-05 [elim_not_effective]: 2.458e-05 [opt_reshape]: 1.226e-05 [fold_const_symbol]: 1.859e-05 [renormalize]: 6.09987e-07 [validate]: 7.199e-05 Sums bootstrap : 0.000743s : 0.03% type_inference : 1.296316s : 56.13% event_method : 0.000591s : 0.03% auto_monad : 0.000334s : 0.01% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000058s : 0.00% rewriter_before_opt_a : 0.000165s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000378s : 0.02% jit_opt_a.loop_unroll : 0.000177s : 0.01% jit_opt_a.a_1 : 0.006910s : 0.30% jit_opt_a.with_stream_mark : 0.000152s : 0.01% jit_opt_a.recompute_prepare : 0.000110s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000099s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000041s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000038s : 0.00% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000075s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000188s : 0.01% jit_opt_a.accelerated_algorithm : 0.000065s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000020s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000060s : 0.00% jit_opt_a.merge_forward : 0.000038s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000010s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000134s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000097s : 0.00% jit_opt_a.meta_fg_expand : 0.531912s : 23.03% jit_opt_a.replace_old_param : 0.000207s : 0.01% jit_opt_a.inline_without_move : 0.000163s : 0.01% jit_opt_a.renormalize : 0.273347s : 11.84% jit_opt_a.add_forward_monad_depend : 0.000058s : 0.00% jit_opt_a.auto_monad_grad : 0.000020s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000214s : 0.01% jit_opt_a.cse : 0.000501s : 0.02% jit_opt_a.replace_applicator : 0.192944s : 8.36% py_interpret_to_execute_after_opt_a : 0.000023s : 0.00% rewriter_after_opt_a : 0.000256s : 0.01% convert_after_rewriter : 0.000016s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000927s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000041s : 0.00% jit_opt_b.inline_after_opt_a : 0.000041s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000522s : 0.02% jit_opt_after_cconv.c_1 : 0.000076s : 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 : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000056s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000035s : 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 : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000013s : 0.00% remove_dup_value : 0.000060s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000015s : 0.00% add_recomputation : 0.000097s : 0.00% cse_after_recomputation.cse : 0.000024s : 0.00% auto_monad_reorder : 0.000042s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000598s : 0.03% symbol_engine_optimizer.build : 0.000007s : 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 : 0.000012s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000072s : 0.00% Time group info: ------[substitution.] 0.003331 271 1.51% : 0.000050s : 12: substitution.depend_value_elim 0.12% : 0.000004s : 5: substitution.elim_not_effective 0.09% : 0.000003s : 5: substitution.fold_const_symbol 27.84% : 0.000927s : 4: substitution.getattr_setattr_resolve 0.32% : 0.000011s : 8: substitution.graph_param_transform 51.39% : 0.001712s : 29: substitution.inline 1.18% : 0.000039s : 4: substitution.inline_without_move 0.56% : 0.000019s : 29: substitution.j_node_and_user_rematch 0.75% : 0.000025s : 13: substitution.minmaximum_grad 0.54% : 0.000018s : 14: substitution.partial_eliminate 0.76% : 0.000025s : 29: substitution.remove_not_recompute_node 4.02% : 0.000134s : 16: substitution.replace_applicator 0.68% : 0.000023s : 17: substitution.replace_old_param 0.31% : 0.000010s : 2: substitution.set_cell_output_no_recompute 0.53% : 0.000018s : 3: substitution.switch_simplify 1.49% : 0.000050s : 13: substitution.tuple_list_convert_item_index_to_positive 1.06% : 0.000035s : 13: substitution.tuple_list_get_item_depend_reorder 3.76% : 0.000125s : 30: substitution.tuple_list_get_item_eliminator 0.91% : 0.000030s : 9: substitution.updatestate_pure_node_eliminater 2.17% : 0.000072s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.296166 2 99.72% : 1.292557s : 1: type_inference.infer 0.28% : 0.003610s : 1: type_inference.specialize ------[replace.] 0.001083 54 7.14% : 0.000077s : 3: replace.getattr_setattr_resolve 48.55% : 0.000526s : 29: replace.inline 9.11% : 0.000099s : 1: replace.replace_applicator 7.54% : 0.000082s : 3: replace.switch_simplify 21.45% : 0.000232s : 17: replace.tuple_list_get_item_eliminator 6.21% : 0.000067s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002676 54 32.25% : 0.000863s : 3: match.getattr_setattr_resolve 63.08% : 0.001688s : 29: match.inline 1.18% : 0.000032s : 1: match.replace_applicator 0.57% : 0.000015s : 3: match.switch_simplify 2.15% : 0.000058s : 17: match.tuple_list_get_item_eliminator 0.77% : 0.000021s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000982 6056 1.54% : 0.000015s : 101: predicate.accumulaten_eliminater 0.32% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.27% : 0.000013s : 101: predicate.addn_check_dump 1.58% : 0.000016s : 101: predicate.addn_zero_filter 1.91% : 0.000019s : 101: predicate.arithmetic_simplify 1.36% : 0.000013s : 101: predicate.cast_eliminate 0.12% : 0.000001s : 8: predicate.check_bprop_eliminate 1.47% : 0.000014s : 101: predicate.compare_switch_simplify 1.74% : 0.000017s : 101: predicate.depend_value_elim 1.36% : 0.000013s : 101: predicate.dict_get_item_const_eliminator 1.75% : 0.000017s : 101: predicate.dict_get_item_eliminator 1.35% : 0.000013s : 101: predicate.dict_set_item_eliminator 0.22% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.08% : 0.000001s : 8: predicate.elim_not_effective 0.16% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.49% : 0.000015s : 101: predicate.environ_add_const_eliminate 1.31% : 0.000013s : 101: predicate.environ_get_add_eliminate 1.32% : 0.000013s : 101: predicate.environ_get_depend_swap 1.36% : 0.000013s : 101: predicate.environ_get_eliminate 1.42% : 0.000014s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.88% : 0.000009s : 44: predicate.get_grad_eliminate 0.75% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.09% : 0.000001s : 8: predicate.graph_param_transform 4.60% : 0.000045s : 163: predicate.inline 1.95% : 0.000019s : 105: predicate.inline_without_move 0.35% : 0.000003s : 44: predicate.j_node_and_user_rematch 1.08% : 0.000011s : 44: predicate.less_batch_normalization 2.19% : 0.000021s : 118: predicate.list_to_tuple_eliminator_ 1.88% : 0.000018s : 126: predicate.load_eliminater 0.34% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.72% : 0.000027s : 187: predicate.loop_unroll_before_grad 1.65% : 0.000016s : 109: predicate.make_slice_get_slice_eliminator 1.85% : 0.000018s : 101: predicate.merge_addn 1.44% : 0.000014s : 101: predicate.minmaximum_grad 0.34% : 0.000003s : 8: predicate.mutable_eliminate 0.15% : 0.000001s : 8: predicate.opt_reshape 2.32% : 0.000023s : 126: predicate.partial_eliminate 1.37% : 0.000013s : 101: predicate.print_const_string_wrapper 1.70% : 0.000017s : 101: predicate.reduce_eliminate 1.74% : 0.000017s : 118: predicate.redundant_stop_gradient_eliminater 0.49% : 0.000005s : 44: predicate.remove_not_recompute_node 2.94% : 0.000029s : 243: predicate.replace_applicator 1.06% : 0.000010s : 105: predicate.replace_old_param 0.09% : 0.000001s : 8: predicate.reset_defer_inline 1.36% : 0.000013s : 101: predicate.reshape_eliminate 1.43% : 0.000014s : 101: predicate.row_tensor_add_zeros_like 0.19% : 0.000002s : 8: predicate.row_tensor_eliminate 1.40% : 0.000014s : 101: predicate.same_eliminate 0.62% : 0.000006s : 52: predicate.set_cell_output_no_recompute 0.30% : 0.000003s : 16: predicate.special_op_eliminate 0.99% : 0.000010s : 50: predicate.specialize_transform 1.76% : 0.000017s : 101: predicate.split_environ_get_set_with_tuple_value 1.62% : 0.000016s : 101: predicate.stack_unstack_eliminate 0.17% : 0.000002s : 8: predicate.switch_call_monad_eliminater 3.09% : 0.000030s : 147: predicate.switch_defer_inline 2.36% : 0.000023s : 147: predicate.switch_layer_defer_inline 6.25% : 0.000061s : 348: predicate.switch_simplify 1.64% : 0.000016s : 101: predicate.tile_eliminate 1.39% : 0.000014s : 101: predicate.transpose_eliminate 1.76% : 0.000017s : 101: predicate.tuple_list_convert_item_index_to_positive 1.73% : 0.000017s : 101: predicate.tuple_list_get_item_depend_reorder 3.69% : 0.000036s : 134: predicate.tuple_list_get_item_eliminator 2.02% : 0.000020s : 101: predicate.tuple_list_set_item_eliminator 1.79% : 0.000018s : 118: predicate.tuple_to_list_eliminator_ 1.93% : 0.000019s : 126: predicate.updatestate_pure_node_eliminater 3.02% : 0.000030s : 172: predicate.updatestate_useless_node_eliminater 2.02% : 0.000020s : 101: predicate.value_based_eliminate 0.11% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.19% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.007645 79 70.44% : 0.005385s : 42: func_graph_cloner_run.FuncGraphClonerGraph 5.79% : 0.000442s : 7: func_graph_cloner_run.FuncGraphClonerNode 23.78% : 0.001818s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.792544 104 0.00% : 0.000100s : 1: add_recomputation 0.01% : 0.000346s : 1: auto_monad 0.00% : 0.000045s : 1: auto_monad_reorder 0.03% : 0.000779s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000020s : 1: convert_after_rewriter 0.00% : 0.000043s : 1: cse_after_recomputation 0.00% : 0.000017s : 1: environ_conv 0.02% : 0.000606s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 36.34% : 1.014798s : 1: jit_opt_a 0.01% : 0.000296s : 1: jit_opt_after_cconv 0.00% : 0.000111s : 1: jit_opt_b 0.02% : 0.000532s : 1: loop_unroll 0.03% : 0.000942s : 1: mutable_eliminate 7.21% : 0.201403s : 52: opt.transform.jit_opt_a 0.00% : 0.000130s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000069s : 4: opt.transform.jit_opt_b 0.00% : 0.000022s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000030s : 1: opt.transform.mutable_eliminate 0.00% : 0.000048s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.001078s : 2: opt.transform.opt_resolve 0.00% : 0.000067s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000608s : 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% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000061s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000064s : 1: remove_dup_value 9.60% : 0.268078s : 3: renormalize.infer 0.19% : 0.005226s : 3: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000263s : 1: rewriter_after_opt_a 0.01% : 0.000169s : 1: rewriter_before_opt_a 0.00% : 0.000120s : 1: symbol_engine_optimizer 46.42% : 1.296340s : 1: type_inference . [hook] pytest_runtest_teardown:test_permute_large_tensors[KBK] tests/st/mint/test_permute.py::test_permute_large_tensors[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 283.74s (0:04:43) ==================