==================================================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_006/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_very_large_tensors[pynative] tests/st/mint/test_permute.py::test_permute_very_large_tensors[pynative],max_mem:2.0M TotalTime = 1.42397, [30] [bootstrap]: 0.00077129 [type_inference]: 1.21949 [event_method]: 1.689e-05 [auto_monad]: 0.00018666 [graph_reusing]: 7.62998e-06 [pre_auto_parallel]: 1.301e-05 [py_interpret_to_execute]: 0.00031576 [rewriter_before_opt_a]: 9.24e-05 [expand_dump_flag]: 4.11001e-06 [jit_opt_a]: 0.19897, [2] [Cycle 1]: 0.00366337, [27] [switch_simplify]: 6.598e-05 [loop_unroll]: 2.703e-05 [a_1]: 0.00055347 [with_stream_mark]: 5.951e-05 [recompute_prepare]: 1.451e-05 [updatestate_depend_eliminate]: 6.88998e-06 [updatestate_assign_eliminate]: 5.62999e-06 [updatestate_loads_eliminate]: 4.75999e-06 [parameter_eliminate]: 2.72001e-06 [specialize_transform]: 1.058e-05 [updatestate_useless_node_eliminater]: 1.333e-05 [accelerated_algorithm]: 9.27001e-06 [meta_shard_fg_expand]: 2.65002e-06 [get_grad_eliminate_]: 9.07001e-06 [merge_forward]: 6.21998e-06 [cell_reuse_recompute_pass]: 1.52999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.554e-05 [j_node_and_user_rematch]: 1.498e-05 [meta_fg_expand]: 3.81999e-06 [replace_old_param]: 1.522e-05 [inline_without_move]: 8.90999e-06 [renormalize]: 0.00242362 [add_forward_monad_depend]: 1.283e-05 [auto_monad_grad]: 2.79999e-06 [auto_monad_eliminator]: 2.875e-05 [cse]: 5.528e-05 [replace_applicator]: 3.141e-05 [Cycle 2]: 0.00058116, [27] [switch_simplify]: 1.047e-05 [loop_unroll]: 9.31002e-06 [a_1]: 0.00023 [with_stream_mark]: 1.927e-05 [recompute_prepare]: 9.05001e-06 [updatestate_depend_eliminate]: 5.95002e-06 [updatestate_assign_eliminate]: 5.48002e-06 [updatestate_loads_eliminate]: 4.54002e-06 [parameter_eliminate]: 1.94999e-06 [specialize_transform]: 1.047e-05 [updatestate_useless_node_eliminater]: 1.177e-05 [accelerated_algorithm]: 1.008e-05 [meta_shard_fg_expand]: 2.66999e-06 [get_grad_eliminate_]: 8.28001e-06 [merge_forward]: 5.67999e-06 [cell_reuse_recompute_pass]: 4.27e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.1e-05 [j_node_and_user_rematch]: 1.388e-05 [meta_fg_expand]: 3.31001e-06 [replace_old_param]: 1.343e-05 [inline_without_move]: 8.23999e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.07001e-06 [auto_monad_grad]: 1.11997e-06 [auto_monad_eliminator]: 1.297e-05 [cse]: 1.947e-05 [replace_applicator]: 9.61e-06 [py_interpret_to_execute_after_opt_a]: 2.098e-05 [rewriter_after_opt_a]: 0.00061549 [convert_after_rewriter]: 2.044e-05 [order_py_execute_after_rewriter]: 9.27001e-06 [mutable_eliminate]: 0.00087926 [jit_opt_b]: 9.017e-05, [1] [Cycle 1]: 7.965e-05, [2] [frontend_op_eliminate]: 3.386e-05 [inline_after_opt_a]: 2.963e-05 [cconv]: 4.077e-05 [loop_unroll]: 0.00051075 [jit_opt_after_cconv]: 0.0002571, [1] [Cycle 1]: 0.00024658, [11] [c_1]: 6.61e-05 [parameter_eliminate]: 5.83002e-06 [updatestate_depend_eliminate]: 1.284e-05 [updatestate_assign_eliminate]: 5.29e-06 [updatestate_loads_eliminate]: 4.72e-06 [cse]: 4.449e-05 [call_graph_tuple_transform]: 2.715e-05 [tuple_list_get_item_eliminator]: 9.59999e-06 [none_parameter_eliminate]: 1.66998e-06 [renormalize]: 6.50005e-07 [switch_simplify]: 9.96e-06 [remove_dup_value]: 2.088e-05 [partial_unused_args_eliminate]: 2.73e-06 [environ_conv]: 4.298e-05 [add_recomputation]: 8.849e-05 [cse_after_recomputation]: 3.435e-05, [1] [Cycle 1]: 2.682e-05, [1] [cse]: 1.945e-05 [auto_monad_reorder]: 3.809e-05 [get_jit_bprop_graph]: 2.40002e-06 [rewriter_after_jit_bprop_graph]: 0.00015428 [opt_after_jit_grad]: 0.000608 [symbol_engine_optimizer]: 0.00011031, [1] [Cycle 1]: 0.00010282, [6] [build]: 7.46001e-06 [elim_shapecalc]: 1.174e-05 [elim_not_effective]: 2.104e-05 [opt_reshape]: 1.149e-05 [fold_const_symbol]: 1.712e-05 [renormalize]: 7.00005e-07 [validate]: 9.449e-05 Sums bootstrap : 0.000771s : 0.06% type_inference : 1.219494s : 99.29% event_method : 0.000017s : 0.00% auto_monad : 0.000187s : 0.02% graph_reusing : 0.000008s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000316s : 0.03% rewriter_before_opt_a : 0.000092s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000076s : 0.01% jit_opt_a.loop_unroll : 0.000036s : 0.00% jit_opt_a.a_1 : 0.000783s : 0.06% jit_opt_a.with_stream_mark : 0.000079s : 0.01% jit_opt_a.recompute_prepare : 0.000024s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.00% jit_opt_a.accelerated_algorithm : 0.000019s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 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 : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 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 : 0.000029s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.002424s : 0.20% jit_opt_a.add_forward_monad_depend : 0.000015s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000042s : 0.00% jit_opt_a.cse : 0.000075s : 0.01% jit_opt_a.replace_applicator : 0.000041s : 0.00% py_interpret_to_execute_after_opt_a : 0.000021s : 0.00% rewriter_after_opt_a : 0.000615s : 0.05% convert_after_rewriter : 0.000020s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000879s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000034s : 0.00% jit_opt_b.inline_after_opt_a : 0.000030s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000511s : 0.04% jit_opt_after_cconv.c_1 : 0.000066s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 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 : 0.000044s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000027s : 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 : 0.000021s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000043s : 0.00% add_recomputation : 0.000088s : 0.01% cse_after_recomputation.cse : 0.000019s : 0.00% auto_monad_reorder : 0.000038s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000154s : 0.01% opt_after_jit_grad : 0.000608s : 0.05% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000094s : 0.01% Time group info: ------[substitution.] 0.000258 45 5.06% : 0.000013s : 2: substitution.depend_value_elim 1.17% : 0.000003s : 4: substitution.elim_not_effective 1.13% : 0.000003s : 4: substitution.fold_const_symbol 3.29% : 0.000008s : 6: substitution.graph_param_transform 71.00% : 0.000183s : 3: substitution.inline 2.27% : 0.000006s : 8: substitution.j_node_and_user_rematch 3.05% : 0.000008s : 8: substitution.remove_not_recompute_node 3.15% : 0.000008s : 2: substitution.replace_old_param 5.49% : 0.000014s : 3: substitution.updatestate_pure_node_eliminater 4.38% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.219395 2 99.87% : 1.217864s : 1: type_inference.infer 0.13% : 0.001531s : 1: type_inference.specialize ------[replace.] 0.000039 3 100.00% : 0.000039s : 3: replace.inline ------[match.] 0.000181 3 100.00% : 0.000181s : 3: match.inline ------[predicate.] 0.000198 970 1.25% : 0.000002s : 14: predicate.accumulaten_eliminater 1.36% : 0.000003s : 6: predicate.ad_related_special_op_eliminate 1.20% : 0.000002s : 14: predicate.addn_check_dump 1.19% : 0.000002s : 14: predicate.addn_zero_filter 1.89% : 0.000004s : 14: predicate.arithmetic_simplify 1.21% : 0.000002s : 14: predicate.cast_eliminate 0.75% : 0.000001s : 6: predicate.check_bprop_eliminate 1.06% : 0.000002s : 14: predicate.compare_switch_simplify 1.53% : 0.000003s : 14: predicate.depend_value_elim 1.36% : 0.000003s : 14: predicate.dict_get_item_const_eliminator 1.43% : 0.000003s : 14: predicate.dict_get_item_eliminator 1.20% : 0.000002s : 14: predicate.dict_set_item_eliminator 0.86% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.42% : 0.000001s : 6: predicate.elim_not_effective 0.65% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.40% : 0.000003s : 14: predicate.environ_add_const_eliminate 1.02% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.18% : 0.000002s : 14: predicate.environ_get_depend_swap 1.24% : 0.000002s : 14: predicate.environ_get_eliminate 1.09% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.37% : 0.000001s : 6: predicate.fold_const_symbol 1.13% : 0.000002s : 12: predicate.get_grad_eliminate 0.46% : 0.000001s : 6: predicate.graph_param_transform 4.73% : 0.000009s : 29: predicate.inline 1.14% : 0.000002s : 12: predicate.inline_without_move 0.65% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.59% : 0.000003s : 12: predicate.less_batch_normalization 1.36% : 0.000003s : 14: predicate.list_to_tuple_eliminator_ 1.79% : 0.000004s : 20: predicate.load_eliminater 1.46% : 0.000003s : 6: predicate.loop_unroll_after_grad 2.72% : 0.000005s : 30: predicate.loop_unroll_before_grad 2.25% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.17% : 0.000002s : 14: predicate.merge_addn 1.22% : 0.000002s : 14: predicate.minmaximum_grad 2.41% : 0.000005s : 6: predicate.mutable_eliminate 0.84% : 0.000002s : 6: predicate.opt_reshape 2.13% : 0.000004s : 20: predicate.partial_eliminate 1.18% : 0.000002s : 14: predicate.print_const_string_wrapper 1.86% : 0.000004s : 14: predicate.reduce_eliminate 1.41% : 0.000003s : 14: predicate.redundant_stop_gradient_eliminater 0.73% : 0.000001s : 12: predicate.remove_not_recompute_node 1.97% : 0.000004s : 26: predicate.replace_applicator 0.74% : 0.000001s : 12: predicate.replace_old_param 0.59% : 0.000001s : 6: predicate.reset_defer_inline 1.24% : 0.000002s : 14: predicate.reshape_eliminate 1.28% : 0.000003s : 14: predicate.row_tensor_add_zeros_like 1.34% : 0.000003s : 6: predicate.row_tensor_eliminate 1.41% : 0.000003s : 14: predicate.same_eliminate 0.91% : 0.000002s : 12: predicate.set_cell_output_no_recompute 1.19% : 0.000002s : 12: predicate.special_op_eliminate 1.22% : 0.000002s : 12: predicate.specialize_transform 1.58% : 0.000003s : 14: predicate.split_environ_get_set_with_tuple_value 1.30% : 0.000003s : 14: predicate.stack_unstack_eliminate 0.61% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.58% : 0.000003s : 17: predicate.switch_defer_inline 1.62% : 0.000003s : 17: predicate.switch_layer_defer_inline 5.82% : 0.000012s : 53: predicate.switch_simplify 1.16% : 0.000002s : 14: predicate.tile_eliminate 1.22% : 0.000002s : 14: predicate.transpose_eliminate 1.89% : 0.000004s : 14: predicate.tuple_list_convert_item_index_to_positive 1.24% : 0.000002s : 14: predicate.tuple_list_get_item_depend_reorder 3.45% : 0.000007s : 26: predicate.tuple_list_get_item_eliminator 1.46% : 0.000003s : 14: predicate.tuple_list_set_item_eliminator 1.59% : 0.000003s : 14: predicate.tuple_to_list_eliminator_ 1.70% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 3.22% : 0.000006s : 32: predicate.updatestate_useless_node_eliminater 1.56% : 0.000003s : 14: predicate.value_based_eliminate 0.44% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.73% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.002458 19 76.00% : 0.001868s : 14: func_graph_cloner_run.FuncGraphClonerGraph 24.00% : 0.000590s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.427513 72 0.01% : 0.000092s : 1: add_recomputation 0.02% : 0.000273s : 1: auto_monad 0.00% : 0.000041s : 1: auto_monad_reorder 0.06% : 0.000798s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000025s : 1: convert_after_rewriter 0.00% : 0.000037s : 1: cse_after_recomputation 0.00% : 0.000046s : 1: environ_conv 0.00% : 0.000022s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000011s : 1: graph_reusing 13.94% : 0.198974s : 1: jit_opt_a 0.02% : 0.000261s : 1: jit_opt_after_cconv 0.01% : 0.000093s : 1: jit_opt_b 0.04% : 0.000521s : 1: loop_unroll 0.06% : 0.000895s : 1: mutable_eliminate 0.08% : 0.001112s : 26: opt.transform.jit_opt_a 0.01% : 0.000109s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000054s : 4: opt.transform.jit_opt_b 0.00% : 0.000021s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000029s : 1: opt.transform.mutable_eliminate 0.00% : 0.000039s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000058s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000620s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000016s : 1: pre_auto_parallel 0.02% : 0.000323s : 1: py_interpret_to_execute 0.00% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000023s : 1: remove_dup_value 0.11% : 0.001641s : 1: renormalize.infer 0.05% : 0.000769s : 1: renormalize.specialize 0.01% : 0.000158s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000625s : 1: rewriter_after_opt_a 0.01% : 0.000098s : 1: rewriter_before_opt_a 0.01% : 0.000114s : 1: symbol_engine_optimizer 85.43% : 1.219521s : 1: type_inference TotalTime = 2.30667, [30] [bootstrap]: 0.0005796 [type_inference]: 1.06396 [event_method]: 0.00057323 [auto_monad]: 0.00034157 [graph_reusing]: 1.105e-05 [pre_auto_parallel]: 4.06001e-06 [py_interpret_to_execute]: 5.686e-05 [rewriter_before_opt_a]: 0.00016653 [expand_dump_flag]: 5.02e-06 [jit_opt_a]: 1.23751, [4] [Cycle 1]: 1.11536, [27] [switch_simplify]: 0.00025169 [loop_unroll]: 6.831e-05 [a_1]: 0.00160773 [with_stream_mark]: 4.533e-05 [recompute_prepare]: 3.499e-05 [updatestate_depend_eliminate]: 1.389e-05 [updatestate_assign_eliminate]: 1.066e-05 [updatestate_loads_eliminate]: 1.026e-05 [parameter_eliminate]: 2.94999e-06 [specialize_transform]: 2.19e-05 [updatestate_useless_node_eliminater]: 0.108147 [accelerated_algorithm]: 4.095e-05 [meta_shard_fg_expand]: 1.261e-05 [get_grad_eliminate_]: 2.265e-05 [merge_forward]: 2.446e-05 [cell_reuse_recompute_pass]: 4.68999e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.619e-05 [j_node_and_user_rematch]: 3.889e-05 [meta_fg_expand]: 0.699888 [replace_old_param]: 0.00016764 [inline_without_move]: 0.00015003 [renormalize]: 0.303044 [add_forward_monad_depend]: 3.902e-05 [auto_monad_grad]: 1.419e-05 [auto_monad_eliminator]: 0.0001175 [cse]: 0.00027382 [replace_applicator]: 0.00024986 [Cycle 2]: 0.0878216, [27] [switch_simplify]: 0.0001063 [loop_unroll]: 9.584e-05 [a_1]: 0.0522945 [with_stream_mark]: 4.916e-05 [recompute_prepare]: 3.845e-05 [updatestate_depend_eliminate]: 1.306e-05 [updatestate_assign_eliminate]: 1.382e-05 [updatestate_loads_eliminate]: 1.246e-05 [parameter_eliminate]: 5.85002e-06 [specialize_transform]: 2.134e-05 [updatestate_useless_node_eliminater]: 9.743e-05 [accelerated_algorithm]: 1.625e-05 [meta_shard_fg_expand]: 4.80001e-06 [get_grad_eliminate_]: 1.306e-05 [merge_forward]: 8.40001e-06 [cell_reuse_recompute_pass]: 1.40001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.892e-05 [j_node_and_user_rematch]: 2.311e-05 [meta_fg_expand]: 0.0001569 [replace_old_param]: 2.445e-05 [inline_without_move]: 1.426e-05 [renormalize]: 0.0297747 [add_forward_monad_depend]: 2.156e-05 [auto_monad_grad]: 3.86999e-06 [auto_monad_eliminator]: 6.623e-05 [cse]: 0.00018582 [replace_applicator]: 4.772e-05 [Cycle 3]: 0.0284642, [27] [switch_simplify]: 1.608e-05 [loop_unroll]: 1.429e-05 [a_1]: 0.00037743 [with_stream_mark]: 2.663e-05 [recompute_prepare]: 1.45e-05 [updatestate_depend_eliminate]: 6.591e-05 [updatestate_assign_eliminate]: 6.39001e-06 [updatestate_loads_eliminate]: 6.96999e-06 [parameter_eliminate]: 2.93e-06 [specialize_transform]: 1.409e-05 [updatestate_useless_node_eliminater]: 1.567e-05 [accelerated_algorithm]: 1.328e-05 [meta_shard_fg_expand]: 3.45e-06 [get_grad_eliminate_]: 1.063e-05 [merge_forward]: 7.03e-06 [cell_reuse_recompute_pass]: 4.12998e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.747e-05 [j_node_and_user_rematch]: 1.913e-05 [meta_fg_expand]: 4.02e-06 [replace_old_param]: 1.717e-05 [inline_without_move]: 1.094e-05 [renormalize]: 0.0274375 [add_forward_monad_depend]: 1.272e-05 [auto_monad_grad]: 3.12002e-06 [auto_monad_eliminator]: 3.452e-05 [cse]: 5.683e-05 [replace_applicator]: 3.438e-05 [Cycle 4]: 0.00075413, [27] [switch_simplify]: 1.347e-05 [loop_unroll]: 1.198e-05 [a_1]: 0.00031626 [with_stream_mark]: 2.232e-05 [recompute_prepare]: 1.268e-05 [updatestate_depend_eliminate]: 7.88001e-06 [updatestate_assign_eliminate]: 6.64999e-06 [updatestate_loads_eliminate]: 5.89e-06 [parameter_eliminate]: 1.74e-06 [specialize_transform]: 1.361e-05 [updatestate_useless_node_eliminater]: 1.564e-05 [accelerated_algorithm]: 1.268e-05 [meta_shard_fg_expand]: 2.98998e-06 [get_grad_eliminate_]: 1.07e-05 [merge_forward]: 7.19001e-06 [cell_reuse_recompute_pass]: 4.1e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.503e-05 [j_node_and_user_rematch]: 1.942e-05 [meta_fg_expand]: 3.93001e-06 [replace_old_param]: 1.453e-05 [inline_without_move]: 1.1e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.89999e-06 [auto_monad_grad]: 2.22999e-06 [auto_monad_eliminator]: 1.859e-05 [cse]: 3.037e-05 [replace_applicator]: 1.287e-05 [py_interpret_to_execute_after_opt_a]: 2.234e-05 [rewriter_after_opt_a]: 0.00022266 [convert_after_rewriter]: 1.515e-05 [order_py_execute_after_rewriter]: 7.82e-06 [mutable_eliminate]: 0.00084209 [jit_opt_b]: 0.00010648, [1] [Cycle 1]: 9.619e-05, [2] [frontend_op_eliminate]: 4.122e-05 [inline_after_opt_a]: 3.835e-05 [cconv]: 3.676e-05 [loop_unroll]: 0.00060834 [jit_opt_after_cconv]: 0.00028323, [1] [Cycle 1]: 0.00027446, [11] [c_1]: 7.438e-05 [parameter_eliminate]: 4.57e-06 [updatestate_depend_eliminate]: 1.352e-05 [updatestate_assign_eliminate]: 6.19999e-06 [updatestate_loads_eliminate]: 5.00001e-06 [cse]: 5.289e-05 [call_graph_tuple_transform]: 3.249e-05 [tuple_list_get_item_eliminator]: 1.174e-05 [none_parameter_eliminate]: 1.69998e-06 [renormalize]: 6.60017e-07 [switch_simplify]: 1.23e-05 [remove_dup_value]: 6.219e-05 [partial_unused_args_eliminate]: 2.49001e-06 [environ_conv]: 1.354e-05 [add_recomputation]: 8.419e-05 [cse_after_recomputation]: 3.822e-05, [1] [Cycle 1]: 3.023e-05, [1] [cse]: 2.211e-05 [auto_monad_reorder]: 3.766e-05 [get_jit_bprop_graph]: 2.43e-06 [rewriter_after_jit_bprop_graph]: 8.12e-06 [opt_after_jit_grad]: 0.00058413 [symbol_engine_optimizer]: 0.00011486, [1] [Cycle 1]: 0.0001067, [6] [build]: 7.15e-06 [elim_shapecalc]: 1.434e-05 [elim_not_effective]: 2.469e-05 [opt_reshape]: 1.099e-05 [fold_const_symbol]: 1.644e-05 [renormalize]: 5.40022e-07 [validate]: 6.588e-05 Sums bootstrap : 0.000580s : 0.03% type_inference : 1.063965s : 46.36% event_method : 0.000573s : 0.02% auto_monad : 0.000342s : 0.01% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000057s : 0.00% rewriter_before_opt_a : 0.000167s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000388s : 0.02% jit_opt_a.loop_unroll : 0.000190s : 0.01% jit_opt_a.a_1 : 0.054596s : 2.38% jit_opt_a.with_stream_mark : 0.000143s : 0.01% jit_opt_a.recompute_prepare : 0.000101s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000101s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000036s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000071s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.108276s : 4.72% jit_opt_a.accelerated_algorithm : 0.000083s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000024s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000057s : 0.00% jit_opt_a.merge_forward : 0.000047s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000014s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000128s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000101s : 0.00% jit_opt_a.meta_fg_expand : 0.700053s : 30.50% jit_opt_a.replace_old_param : 0.000224s : 0.01% jit_opt_a.inline_without_move : 0.000186s : 0.01% jit_opt_a.renormalize : 0.360256s : 15.70% jit_opt_a.add_forward_monad_depend : 0.000076s : 0.00% jit_opt_a.auto_monad_grad : 0.000023s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000237s : 0.01% jit_opt_a.cse : 0.000547s : 0.02% jit_opt_a.replace_applicator : 0.000345s : 0.02% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.000223s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000842s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000041s : 0.00% jit_opt_b.inline_after_opt_a : 0.000038s : 0.00% cconv : 0.000037s : 0.00% loop_unroll : 0.000608s : 0.03% jit_opt_after_cconv.c_1 : 0.000074s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 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 : 0.000053s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000032s : 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 : 0.000012s : 0.00% remove_dup_value : 0.000062s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000014s : 0.00% add_recomputation : 0.000084s : 0.00% cse_after_recomputation.cse : 0.000022s : 0.00% auto_monad_reorder : 0.000038s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000584s : 0.03% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000066s : 0.00% Time group info: ------[substitution.] 0.003188 271 1.55% : 0.000050s : 12: substitution.depend_value_elim 0.12% : 0.000004s : 5: substitution.elim_not_effective 0.08% : 0.000003s : 5: substitution.fold_const_symbol 34.88% : 0.001112s : 4: substitution.getattr_setattr_resolve 0.29% : 0.000009s : 8: substitution.graph_param_transform 47.36% : 0.001510s : 29: substitution.inline 1.66% : 0.000053s : 4: substitution.inline_without_move 0.54% : 0.000017s : 29: substitution.j_node_and_user_rematch 0.67% : 0.000021s : 13: substitution.minmaximum_grad 0.44% : 0.000014s : 14: substitution.partial_eliminate 0.78% : 0.000025s : 29: substitution.remove_not_recompute_node 1.83% : 0.000058s : 16: substitution.replace_applicator 0.77% : 0.000024s : 17: substitution.replace_old_param 0.25% : 0.000008s : 2: substitution.set_cell_output_no_recompute 0.47% : 0.000015s : 3: substitution.switch_simplify 1.38% : 0.000044s : 13: substitution.tuple_list_convert_item_index_to_positive 1.00% : 0.000032s : 13: substitution.tuple_list_get_item_depend_reorder 2.94% : 0.000094s : 30: substitution.tuple_list_get_item_eliminator 0.86% : 0.000027s : 9: substitution.updatestate_pure_node_eliminater 2.15% : 0.000069s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.063795 2 99.68% : 1.060373s : 1: type_inference.infer 0.32% : 0.003422s : 1: type_inference.specialize ------[replace.] 0.000939 54 7.89% : 0.000074s : 3: replace.getattr_setattr_resolve 52.41% : 0.000492s : 29: replace.inline 6.02% : 0.000057s : 1: replace.replace_applicator 8.66% : 0.000081s : 3: replace.switch_simplify 19.85% : 0.000186s : 17: replace.tuple_list_get_item_eliminator 5.17% : 0.000049s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002489 54 36.86% : 0.000917s : 3: match.getattr_setattr_resolve 59.79% : 0.001488s : 29: match.inline 0.44% : 0.000011s : 1: match.replace_applicator 0.52% : 0.000013s : 3: match.switch_simplify 1.69% : 0.000042s : 17: match.tuple_list_get_item_eliminator 0.71% : 0.000018s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001139 6048 1.50% : 0.000017s : 101: predicate.accumulaten_eliminater 0.20% : 0.000002s : 7: predicate.ad_related_special_op_eliminate 1.35% : 0.000015s : 101: predicate.addn_check_dump 1.42% : 0.000016s : 101: predicate.addn_zero_filter 2.14% : 0.000024s : 101: predicate.arithmetic_simplify 1.68% : 0.000019s : 101: predicate.cast_eliminate 0.13% : 0.000001s : 8: predicate.check_bprop_eliminate 1.43% : 0.000016s : 101: predicate.compare_switch_simplify 1.64% : 0.000019s : 101: predicate.depend_value_elim 1.50% : 0.000017s : 101: predicate.dict_get_item_const_eliminator 1.75% : 0.000020s : 101: predicate.dict_get_item_eliminator 1.48% : 0.000017s : 101: predicate.dict_set_item_eliminator 0.19% : 0.000002s : 7: predicate.dumpgradient_eliminate 0.10% : 0.000001s : 7: predicate.elim_not_effective 0.15% : 0.000002s : 7: predicate.elim_shapecalc_of_broadcastargs 1.47% : 0.000017s : 101: predicate.environ_add_const_eliminate 1.39% : 0.000016s : 101: predicate.environ_get_add_eliminate 1.38% : 0.000016s : 101: predicate.environ_get_depend_swap 1.57% : 0.000018s : 101: predicate.environ_get_eliminate 1.32% : 0.000015s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 7: predicate.fold_const_symbol 0.77% : 0.000009s : 44: predicate.get_grad_eliminate 0.58% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000001s : 8: predicate.graph_param_transform 4.27% : 0.000049s : 163: predicate.inline 1.88% : 0.000021s : 105: predicate.inline_without_move 0.47% : 0.000005s : 44: predicate.j_node_and_user_rematch 1.33% : 0.000015s : 44: predicate.less_batch_normalization 2.02% : 0.000023s : 118: predicate.list_to_tuple_eliminator_ 1.93% : 0.000022s : 126: predicate.load_eliminater 0.28% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.78% : 0.000032s : 187: predicate.loop_unroll_before_grad 1.72% : 0.000020s : 109: predicate.make_slice_get_slice_eliminator 1.37% : 0.000016s : 101: predicate.merge_addn 1.36% : 0.000015s : 101: predicate.minmaximum_grad 0.30% : 0.000003s : 8: predicate.mutable_eliminate 0.13% : 0.000001s : 7: predicate.opt_reshape 2.18% : 0.000025s : 126: predicate.partial_eliminate 1.71% : 0.000019s : 101: predicate.print_const_string_wrapper 1.94% : 0.000022s : 101: predicate.reduce_eliminate 1.90% : 0.000022s : 118: predicate.redundant_stop_gradient_eliminater 0.43% : 0.000005s : 44: predicate.remove_not_recompute_node 3.03% : 0.000034s : 243: predicate.replace_applicator 1.11% : 0.000013s : 105: predicate.replace_old_param 0.12% : 0.000001s : 8: predicate.reset_defer_inline 2.27% : 0.000026s : 101: predicate.reshape_eliminate 1.42% : 0.000016s : 101: predicate.row_tensor_add_zeros_like 0.22% : 0.000003s : 8: predicate.row_tensor_eliminate 1.52% : 0.000017s : 101: predicate.same_eliminate 0.61% : 0.000007s : 52: predicate.set_cell_output_no_recompute 0.27% : 0.000003s : 15: predicate.special_op_eliminate 0.81% : 0.000009s : 50: predicate.specialize_transform 1.74% : 0.000020s : 101: predicate.split_environ_get_set_with_tuple_value 1.51% : 0.000017s : 101: predicate.stack_unstack_eliminate 0.17% : 0.000002s : 8: predicate.switch_call_monad_eliminater 3.02% : 0.000034s : 147: predicate.switch_defer_inline 2.40% : 0.000027s : 147: predicate.switch_layer_defer_inline 5.57% : 0.000063s : 348: predicate.switch_simplify 1.48% : 0.000017s : 101: predicate.tile_eliminate 1.37% : 0.000016s : 101: predicate.transpose_eliminate 1.77% : 0.000020s : 101: predicate.tuple_list_convert_item_index_to_positive 2.20% : 0.000025s : 101: predicate.tuple_list_get_item_depend_reorder 3.04% : 0.000035s : 134: predicate.tuple_list_get_item_eliminator 1.94% : 0.000022s : 101: predicate.tuple_list_set_item_eliminator 1.68% : 0.000019s : 118: predicate.tuple_to_list_eliminator_ 1.81% : 0.000021s : 126: predicate.updatestate_pure_node_eliminater 3.41% : 0.000039s : 172: predicate.updatestate_useless_node_eliminater 1.96% : 0.000022s : 101: predicate.value_based_eliminate 0.08% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 0.17% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.009472 73 55.05% : 0.005214s : 36: func_graph_cloner_run.FuncGraphClonerGraph 4.99% : 0.000472s : 7: func_graph_cloner_run.FuncGraphClonerNode 39.96% : 0.003785s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.832967 104 0.00% : 0.000088s : 1: add_recomputation 0.01% : 0.000353s : 1: auto_monad 0.00% : 0.000042s : 1: auto_monad_reorder 0.02% : 0.000612s : 1: bootstrap 0.00% : 0.000040s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000041s : 1: cse_after_recomputation 0.00% : 0.000016s : 1: environ_conv 0.02% : 0.000588s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 43.68% : 1.237515s : 1: jit_opt_a 0.01% : 0.000287s : 1: jit_opt_after_cconv 0.00% : 0.000110s : 1: jit_opt_b 0.02% : 0.000620s : 1: loop_unroll 0.03% : 0.000859s : 1: mutable_eliminate 5.81% : 0.164639s : 52: opt.transform.jit_opt_a 0.00% : 0.000126s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000069s : 4: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000029s : 1: opt.transform.mutable_eliminate 0.00% : 0.000043s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.001257s : 2: opt.transform.opt_resolve 0.00% : 0.000062s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000596s : 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% : 0.000007s : 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% : 0.000065s : 1: remove_dup_value 11.38% : 0.322353s : 3: renormalize.infer 1.34% : 0.037840s : 3: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000231s : 1: rewriter_after_opt_a 0.01% : 0.000171s : 1: rewriter_before_opt_a 0.00% : 0.000118s : 1: symbol_engine_optimizer 37.56% : 1.064005s : 1: type_inference . [hook] pytest_runtest_teardown:test_permute_very_large_tensors[KBK] tests/st/mint/test_permute.py::test_permute_very_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 302.97s (0:05:02) ==================