==================================================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_002/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_select.py . [hook] pytest_runtest_teardown:test_select_large_tensors[pynative] tests/st/mint/test_select.py::test_select_large_tensors[pynative],max_mem:2.0M TotalTime = 6.49788, [33] [bootstrap]: 0.00120746 [type_inference]: 1.06738 [event_method]: 1.676e-05 [auto_monad]: 0.00015389 [graph_reusing]: 5.30001e-06 [pre_auto_parallel]: 1.298e-05 [py_interpret_to_execute]: 0.00012911 [rewriter_before_opt_a]: 6.042e-05 [expand_dump_flag]: 3.21999e-06 [jit_opt_a]: 0.0132054, [2] [Cycle 1]: 0.00210526, [27] [switch_simplify]: 5.689e-05 [loop_unroll]: 1.977e-05 [a_1]: 0.00041469 [with_stream_mark]: 3.072e-05 [recompute_prepare]: 1.126e-05 [updatestate_depend_eliminate]: 7.11001e-06 [updatestate_assign_eliminate]: 9.09e-06 [updatestate_loads_eliminate]: 5.13002e-06 [parameter_eliminate]: 2.48998e-06 [specialize_transform]: 9.25999e-06 [updatestate_useless_node_eliminater]: 1.19e-05 [accelerated_algorithm]: 8.03001e-06 [meta_shard_fg_expand]: 2.76e-06 [get_grad_eliminate_]: 8.50999e-06 [merge_forward]: 5.25999e-06 [cell_reuse_recompute_pass]: 1.10999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.752e-05 [j_node_and_user_rematch]: 1.509e-05 [meta_fg_expand]: 4.02e-06 [replace_old_param]: 1.388e-05 [inline_without_move]: 8.02e-06 [renormalize]: 0.00103674 [add_forward_monad_depend]: 4.172e-05 [auto_monad_grad]: 2.63003e-06 [auto_monad_eliminator]: 2.45e-05 [cse]: 6.045e-05 [replace_applicator]: 2.029e-05 [Cycle 2]: 0.00048141, [27] [switch_simplify]: 8.55001e-06 [loop_unroll]: 8.02003e-06 [a_1]: 0.00016497 [with_stream_mark]: 1.581e-05 [recompute_prepare]: 8.40001e-06 [updatestate_depend_eliminate]: 5.51e-06 [updatestate_assign_eliminate]: 4.28001e-06 [updatestate_loads_eliminate]: 4.29002e-06 [parameter_eliminate]: 1.17999e-06 [specialize_transform]: 8.40001e-06 [updatestate_useless_node_eliminater]: 1.119e-05 [accelerated_algorithm]: 7.71001e-06 [meta_shard_fg_expand]: 1.76e-06 [get_grad_eliminate_]: 7.48999e-06 [merge_forward]: 5.22999e-06 [cell_reuse_recompute_pass]: 1.57999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.695e-05 [j_node_and_user_rematch]: 1.235e-05 [meta_fg_expand]: 3.33998e-06 [replace_old_param]: 1.038e-05 [inline_without_move]: 7.55e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.47001e-06 [auto_monad_grad]: 9.79984e-07 [auto_monad_eliminator]: 1.168e-05 [cse]: 1.989e-05 [replace_applicator]: 7.74002e-06 [py_interpret_to_execute_after_opt_a]: 1.649e-05 [rewriter_after_opt_a]: 0.222309 [convert_after_rewriter]: 3.371e-05 [order_py_execute_after_rewriter]: 8.62e-06 [mutable_eliminate]: 0.00250913 [jit_opt_b]: 0.00129682, [1] [Cycle 1]: 0.00128452, [2] [frontend_op_eliminate]: 4.904e-05 [inline_after_opt_a]: 3.207e-05 [cconv]: 4.608e-05 [loop_unroll]: 0.00062861 [jit_opt_after_cconv]: 0.00221547, [1] [Cycle 1]: 0.00220419, [11] [c_1]: 6.057e-05 [parameter_eliminate]: 6.64999e-06 [updatestate_depend_eliminate]: 1.552e-05 [updatestate_assign_eliminate]: 5.73002e-06 [updatestate_loads_eliminate]: 5.03002e-06 [cse]: 0.0019266 [call_graph_tuple_transform]: 5.457e-05 [tuple_list_get_item_eliminator]: 1.066e-05 [none_parameter_eliminate]: 5.59e-06 [renormalize]: 1.05999e-06 [switch_simplify]: 9.97999e-06 [remove_dup_value]: 2.752e-05 [partial_unused_args_eliminate]: 2.51e-06 [environ_conv]: 2.649e-05 [add_recomputation]: 0.00148638 [cse_after_recomputation]: 6.853e-05, [1] [Cycle 1]: 5.575e-05, [1] [cse]: 3.736e-05 [auto_monad_reorder]: 4.729e-05 [get_jit_bprop_graph]: 2.76e-06 [rewriter_after_jit_bprop_graph]: 0.00017968 [opt_after_jit_grad]: 0.00505643 [symbol_engine_optimizer]: 0.00011664, [1] [Cycle 1]: 0.00010564, [6] [build]: 8.27e-06 [elim_shapecalc]: 1.336e-05 [elim_not_effective]: 2.718e-05 [opt_reshape]: 9.97001e-06 [fold_const_symbol]: 1.414e-05 [renormalize]: 6.90023e-07 [validate]: 8.681e-05 [backend_pass]: 1.35999e-06 [task_emit]: 5.17905 [execute]: 1.146e-05 Sums bootstrap : 0.001207s : 0.02% type_inference : 1.067377s : 16.46% event_method : 0.000017s : 0.00% auto_monad : 0.000154s : 0.00% graph_reusing : 0.000005s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000129s : 0.00% rewriter_before_opt_a : 0.000060s : 0.00% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000065s : 0.00% jit_opt_a.loop_unroll : 0.000028s : 0.00% jit_opt_a.a_1 : 0.000580s : 0.01% jit_opt_a.with_stream_mark : 0.000047s : 0.00% jit_opt_a.recompute_prepare : 0.000020s : 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 : 0.000018s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000023s : 0.00% jit_opt_a.accelerated_algorithm : 0.000016s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000016s : 0.00% jit_opt_a.merge_forward : 0.000010s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000044s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000027s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.001037s : 0.02% jit_opt_a.add_forward_monad_depend : 0.000043s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000036s : 0.00% jit_opt_a.cse : 0.000080s : 0.00% jit_opt_a.replace_applicator : 0.000028s : 0.00% py_interpret_to_execute_after_opt_a : 0.000016s : 0.00% rewriter_after_opt_a : 0.222309s : 3.43% convert_after_rewriter : 0.000034s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.002509s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000049s : 0.00% jit_opt_b.inline_after_opt_a : 0.000032s : 0.00% cconv : 0.000046s : 0.00% loop_unroll : 0.000629s : 0.01% jit_opt_after_cconv.c_1 : 0.000061s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 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 : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.001927s : 0.03% jit_opt_after_cconv.call_graph_tuple_transform : 0.000055s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000011s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000010s : 0.00% remove_dup_value : 0.000028s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000026s : 0.00% add_recomputation : 0.001486s : 0.02% cse_after_recomputation.cse : 0.000037s : 0.00% auto_monad_reorder : 0.000047s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000180s : 0.00% opt_after_jit_grad : 0.005056s : 0.08% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000087s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 5.179054s : 79.86% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000209 43 4.16% : 0.000009s : 2: substitution.depend_value_elim 1.69% : 0.000004s : 4: substitution.elim_not_effective 1.04% : 0.000002s : 4: substitution.fold_const_symbol 4.57% : 0.000010s : 5: substitution.graph_param_transform 67.82% : 0.000142s : 2: substitution.inline 2.36% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.81% : 0.000008s : 8: substitution.remove_not_recompute_node 2.70% : 0.000006s : 2: substitution.replace_old_param 7.06% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 4.80% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.067295 2 99.91% : 1.066350s : 1: type_inference.infer 0.09% : 0.000946s : 1: type_inference.specialize ------[replace.] 0.000030 2 100.00% : 0.000030s : 2: replace.inline ------[match.] 0.000139 2 100.00% : 0.000139s : 2: match.inline ------[predicate.] 0.000162 767 1.03% : 0.000002s : 11: predicate.accumulaten_eliminater 4.10% : 0.000007s : 5: predicate.ad_related_special_op_eliminate 1.11% : 0.000002s : 11: predicate.addn_check_dump 1.25% : 0.000002s : 11: predicate.addn_zero_filter 1.55% : 0.000003s : 11: predicate.arithmetic_simplify 1.06% : 0.000002s : 11: predicate.cast_eliminate 0.94% : 0.000002s : 5: predicate.check_bprop_eliminate 0.85% : 0.000001s : 11: predicate.compare_switch_simplify 1.11% : 0.000002s : 11: predicate.depend_value_elim 0.93% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.06% : 0.000002s : 11: predicate.dict_get_item_eliminator 0.96% : 0.000002s : 11: predicate.dict_set_item_eliminator 2.22% : 0.000004s : 5: predicate.dumpgradient_eliminate 0.56% : 0.000001s : 5: predicate.elim_not_effective 0.72% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.00% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.01% : 0.000002s : 11: predicate.environ_get_add_eliminate 0.87% : 0.000001s : 11: predicate.environ_get_depend_swap 1.04% : 0.000002s : 11: predicate.environ_get_eliminate 0.95% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.27% : 0.000000s : 5: predicate.fold_const_symbol 1.36% : 0.000002s : 10: predicate.get_grad_eliminate 0.43% : 0.000001s : 5: predicate.graph_param_transform 5.04% : 0.000008s : 23: predicate.inline 1.24% : 0.000002s : 10: predicate.inline_without_move 0.45% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.23% : 0.000002s : 10: predicate.less_batch_normalization 0.93% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 2.02% : 0.000003s : 16: predicate.load_eliminater 1.97% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.28% : 0.000004s : 20: predicate.loop_unroll_before_grad 1.76% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.91% : 0.000001s : 11: predicate.merge_addn 1.16% : 0.000002s : 11: predicate.minmaximum_grad 3.74% : 0.000006s : 5: predicate.mutable_eliminate 0.95% : 0.000002s : 5: predicate.opt_reshape 2.23% : 0.000004s : 16: predicate.partial_eliminate 0.96% : 0.000002s : 11: predicate.print_const_string_wrapper 1.35% : 0.000002s : 11: predicate.reduce_eliminate 1.32% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.82% : 0.000001s : 10: predicate.remove_not_recompute_node 1.46% : 0.000002s : 21: predicate.replace_applicator 0.73% : 0.000001s : 10: predicate.replace_old_param 0.87% : 0.000001s : 5: predicate.reset_defer_inline 1.13% : 0.000002s : 11: predicate.reshape_eliminate 1.21% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.37% : 0.000002s : 5: predicate.row_tensor_eliminate 1.17% : 0.000002s : 11: predicate.same_eliminate 0.59% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.46% : 0.000002s : 10: predicate.special_op_eliminate 1.58% : 0.000003s : 10: predicate.specialize_transform 1.21% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.11% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.78% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.25% : 0.000002s : 13: predicate.switch_defer_inline 1.27% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.21% : 0.000008s : 38: predicate.switch_simplify 0.93% : 0.000002s : 11: predicate.tile_eliminate 0.96% : 0.000002s : 11: predicate.transpose_eliminate 1.25% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.06% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 4.31% : 0.000007s : 21: predicate.tuple_list_get_item_eliminator 1.23% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 0.96% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.47% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.46% : 0.000006s : 26: predicate.updatestate_useless_node_eliminater 1.32% : 0.000002s : 11: predicate.value_based_eliminate 0.61% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 3.31% : 0.000005s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000305 5 8.74% : 0.000027s : 1: func_graph_cloner_run.FuncGraphClonerGraph 91.26% : 0.000279s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 6.499971 76 0.02% : 0.001504s : 1: add_recomputation 0.00% : 0.000160s : 1: auto_monad 0.00% : 0.000052s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.02% : 0.001236s : 1: bootstrap 0.00% : 0.000049s : 1: cconv 0.00% : 0.000041s : 1: convert_after_rewriter 0.00% : 0.000073s : 1: cse_after_recomputation 0.00% : 0.000029s : 1: environ_conv 0.00% : 0.000023s : 1: event_method 0.00% : 0.000018s : 1: execute 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000008s : 1: graph_reusing 0.20% : 0.013209s : 1: jit_opt_a 0.03% : 0.002220s : 1: jit_opt_after_cconv 0.02% : 0.001302s : 1: jit_opt_b 0.01% : 0.000641s : 1: loop_unroll 0.04% : 0.002529s : 1: mutable_eliminate 0.01% : 0.000859s : 26: opt.transform.jit_opt_a 0.00% : 0.000127s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000068s : 4: opt.transform.jit_opt_b 0.00% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000039s : 1: opt.transform.mutable_eliminate 0.00% : 0.000061s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000061s : 4: opt.transform.symbol_engine_opt 0.08% : 0.005078s : 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% : 0.000016s : 1: pre_auto_parallel 0.00% : 0.000134s : 1: py_interpret_to_execute 0.00% : 0.000019s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000030s : 1: remove_dup_value 0.01% : 0.000630s : 1: renormalize.infer 0.01% : 0.000396s : 1: renormalize.specialize 0.00% : 0.000184s : 1: rewriter_after_jit_bprop_graph 3.42% : 0.222329s : 1: rewriter_after_opt_a 0.00% : 0.000064s : 1: rewriter_before_opt_a 0.00% : 0.000120s : 1: symbol_engine_optimizer 79.68% : 5.179094s : 1: task_emit 16.42% : 1.067400s : 1: type_inference 0.00% : 0.000119s : 1: validate TotalTime = 9.83295, [33] [bootstrap]: 0.00052036 [type_inference]: 0.756398 [event_method]: 0.00021016 [auto_monad]: 0.00028642 [graph_reusing]: 1.027e-05 [pre_auto_parallel]: 3.75e-06 [py_interpret_to_execute]: 5.489e-05 [rewriter_before_opt_a]: 0.0001571 [expand_dump_flag]: 4.37e-06 [jit_opt_a]: 1.12594, [4] [Cycle 1]: 0.695993, [27] [switch_simplify]: 0.00025032 [loop_unroll]: 6.004e-05 [a_1]: 0.00200259 [with_stream_mark]: 4.759e-05 [recompute_prepare]: 3.636e-05 [updatestate_depend_eliminate]: 1.592e-05 [updatestate_assign_eliminate]: 1.189e-05 [updatestate_loads_eliminate]: 1.034e-05 [parameter_eliminate]: 4.76002e-06 [specialize_transform]: 2.136e-05 [updatestate_useless_node_eliminater]: 2.506e-05 [accelerated_algorithm]: 1.959e-05 [meta_shard_fg_expand]: 6.61999e-06 [get_grad_eliminate_]: 1.886e-05 [merge_forward]: 1.429e-05 [cell_reuse_recompute_pass]: 1.26002e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.4e-05 [j_node_and_user_rematch]: 3.465e-05 [meta_fg_expand]: 0.671188 [replace_old_param]: 0.00013784 [inline_without_move]: 0.00012662 [renormalize]: 0.020718 [add_forward_monad_depend]: 2.962e-05 [auto_monad_grad]: 1.331e-05 [auto_monad_eliminator]: 0.00013222 [cse]: 0.00040918 [replace_applicator]: 0.00023624 [Cycle 2]: 0.422407, [27] [switch_simplify]: 9.046e-05 [loop_unroll]: 8.458e-05 [a_1]: 0.00368945 [with_stream_mark]: 4.46e-05 [recompute_prepare]: 3.734e-05 [updatestate_depend_eliminate]: 1.623e-05 [updatestate_assign_eliminate]: 1.745e-05 [updatestate_loads_eliminate]: 1.586e-05 [parameter_eliminate]: 4.32e-06 [specialize_transform]: 2.432e-05 [updatestate_useless_node_eliminater]: 0.415627 [accelerated_algorithm]: 6.565e-05 [meta_shard_fg_expand]: 8.09002e-06 [get_grad_eliminate_]: 1.601e-05 [merge_forward]: 1.1e-05 [cell_reuse_recompute_pass]: 2.54999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.426e-05 [j_node_and_user_rematch]: 2.557e-05 [meta_fg_expand]: 0.0001271 [replace_old_param]: 2.189e-05 [inline_without_move]: 1.447e-05 [renormalize]: 0.00185204 [add_forward_monad_depend]: 7.83999e-06 [auto_monad_grad]: 2.97002e-06 [auto_monad_eliminator]: 3.145e-05 [cse]: 0.000219 [replace_applicator]: 2.374e-05 [Cycle 3]: 0.00162849, [27] [switch_simplify]: 1.549e-05 [loop_unroll]: 1.372e-05 [a_1]: 0.00033177 [with_stream_mark]: 2.043e-05 [recompute_prepare]: 1.398e-05 [updatestate_depend_eliminate]: 3.544e-05 [updatestate_assign_eliminate]: 7.78999e-06 [updatestate_loads_eliminate]: 7.63001e-06 [parameter_eliminate]: 1.89e-06 [specialize_transform]: 1.33e-05 [updatestate_useless_node_eliminater]: 1.499e-05 [accelerated_algorithm]: 1.607e-05 [meta_shard_fg_expand]: 2.34001e-06 [get_grad_eliminate_]: 1.133e-05 [merge_forward]: 6.47001e-06 [cell_reuse_recompute_pass]: 1.61998e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.408e-05 [j_node_and_user_rematch]: 1.957e-05 [meta_fg_expand]: 4.69002e-06 [replace_old_param]: 1.426e-05 [inline_without_move]: 1.152e-05 [renormalize]: 0.00077208 [add_forward_monad_depend]: 5.05001e-06 [auto_monad_grad]: 1.26002e-06 [auto_monad_eliminator]: 2.021e-05 [cse]: 7.148e-05 [replace_applicator]: 1.967e-05 [Cycle 4]: 0.0006959, [27] [switch_simplify]: 1.313e-05 [loop_unroll]: 1.117e-05 [a_1]: 0.00029176 [with_stream_mark]: 1.498e-05 [recompute_prepare]: 1.269e-05 [updatestate_depend_eliminate]: 7.77e-06 [updatestate_assign_eliminate]: 7.15e-06 [updatestate_loads_eliminate]: 6.49999e-06 [parameter_eliminate]: 1.05001e-06 [specialize_transform]: 1.262e-05 [updatestate_useless_node_eliminater]: 1.498e-05 [accelerated_algorithm]: 1.504e-05 [meta_shard_fg_expand]: 2.73003e-06 [get_grad_eliminate_]: 1.151e-05 [merge_forward]: 6.86001e-06 [cell_reuse_recompute_pass]: 1.25999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.242e-05 [j_node_and_user_rematch]: 1.933e-05 [meta_fg_expand]: 4.45e-06 [replace_old_param]: 1.42e-05 [inline_without_move]: 1.19e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.94e-06 [auto_monad_grad]: 1.31002e-06 [auto_monad_eliminator]: 1.703e-05 [cse]: 3.448e-05 [replace_applicator]: 1.215e-05 [py_interpret_to_execute_after_opt_a]: 1.797e-05 [rewriter_after_opt_a]: 0.00509222 [convert_after_rewriter]: 2.779e-05 [order_py_execute_after_rewriter]: 9.94001e-06 [mutable_eliminate]: 0.00082609 [jit_opt_b]: 0.00010533, [1] [Cycle 1]: 9.336e-05, [2] [frontend_op_eliminate]: 3.877e-05 [inline_after_opt_a]: 3.904e-05 [cconv]: 4.088e-05 [loop_unroll]: 0.00076629 [jit_opt_after_cconv]: 0.00030307, [1] [Cycle 1]: 0.00029496, [11] [c_1]: 6.727e-05 [parameter_eliminate]: 3.78999e-06 [updatestate_depend_eliminate]: 1.311e-05 [updatestate_assign_eliminate]: 7.61999e-06 [updatestate_loads_eliminate]: 7e-06 [cse]: 7.647e-05 [call_graph_tuple_transform]: 3.33e-05 [tuple_list_get_item_eliminator]: 1.322e-05 [none_parameter_eliminate]: 1.66e-06 [renormalize]: 3.00002e-07 [switch_simplify]: 1.295e-05 [remove_dup_value]: 3.364e-05 [partial_unused_args_eliminate]: 2.35002e-06 [environ_conv]: 1.996e-05 [add_recomputation]: 9.87e-05 [cse_after_recomputation]: 5.231e-05, [1] [Cycle 1]: 4.483e-05, [1] [cse]: 3.658e-05 [auto_monad_reorder]: 3.477e-05 [get_jit_bprop_graph]: 2.39999e-06 [rewriter_after_jit_bprop_graph]: 6.17999e-06 [opt_after_jit_grad]: 0.00054213 [symbol_engine_optimizer]: 0.00013081, [1] [Cycle 1]: 0.00012408, [6] [build]: 1.676e-05 [elim_shapecalc]: 1.62e-05 [elim_not_effective]: 2.592e-05 [opt_reshape]: 1.311e-05 [fold_const_symbol]: 1.958e-05 [renormalize]: 6.59988e-07 [validate]: 6.431e-05 [backend_pass]: 1.16002e-06 [task_emit]: 7.94088 [execute]: 1.014e-05 Sums bootstrap : 0.000520s : 0.01% type_inference : 0.756398s : 7.70% event_method : 0.000210s : 0.00% auto_monad : 0.000286s : 0.00% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000055s : 0.00% rewriter_before_opt_a : 0.000157s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000369s : 0.00% jit_opt_a.loop_unroll : 0.000170s : 0.00% jit_opt_a.a_1 : 0.006316s : 0.06% jit_opt_a.with_stream_mark : 0.000128s : 0.00% jit_opt_a.recompute_prepare : 0.000100s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000075s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000044s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000040s : 0.00% jit_opt_a.parameter_eliminate : 0.000012s : 0.00% jit_opt_a.specialize_transform : 0.000072s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.415682s : 4.23% jit_opt_a.accelerated_algorithm : 0.000116s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000020s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000058s : 0.00% jit_opt_a.merge_forward : 0.000039s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000125s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000099s : 0.00% jit_opt_a.meta_fg_expand : 0.671324s : 6.83% jit_opt_a.replace_old_param : 0.000188s : 0.00% jit_opt_a.inline_without_move : 0.000165s : 0.00% jit_opt_a.renormalize : 0.023342s : 0.24% jit_opt_a.add_forward_monad_depend : 0.000044s : 0.00% jit_opt_a.auto_monad_grad : 0.000019s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000201s : 0.00% jit_opt_a.cse : 0.000734s : 0.01% jit_opt_a.replace_applicator : 0.000292s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.005092s : 0.05% convert_after_rewriter : 0.000028s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000826s : 0.01% jit_opt_b.frontend_op_eliminate : 0.000039s : 0.00% jit_opt_b.inline_after_opt_a : 0.000039s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000766s : 0.01% jit_opt_after_cconv.c_1 : 0.000067s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000076s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000033s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000013s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000013s : 0.00% remove_dup_value : 0.000034s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000020s : 0.00% add_recomputation : 0.000099s : 0.00% cse_after_recomputation.cse : 0.000037s : 0.00% auto_monad_reorder : 0.000035s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000542s : 0.01% symbol_engine_optimizer.build : 0.000017s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000016s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000064s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 7.940878s : 80.81% execute : 0.000010s : 0.00% Time group info: ------[substitution.] 0.003325 291 1.21% : 0.000040s : 12: substitution.depend_value_elim 0.12% : 0.000004s : 7: substitution.elim_not_effective 0.09% : 0.000003s : 7: substitution.fold_const_symbol 28.77% : 0.000957s : 4: substitution.getattr_setattr_resolve 0.26% : 0.000009s : 8: substitution.graph_param_transform 43.04% : 0.001431s : 28: substitution.inline 1.23% : 0.000041s : 4: substitution.inline_without_move 0.58% : 0.000019s : 35: substitution.j_node_and_user_rematch 1.03% : 0.000034s : 3: substitution.less_batch_normalization 0.60% : 0.000020s : 13: substitution.minmaximum_grad 11.29% : 0.000375s : 14: substitution.partial_eliminate 0.75% : 0.000025s : 35: substitution.remove_not_recompute_node 1.99% : 0.000066s : 16: substitution.replace_applicator 0.57% : 0.000019s : 19: substitution.replace_old_param 0.28% : 0.000009s : 2: substitution.set_cell_output_no_recompute 0.49% : 0.000016s : 3: substitution.switch_simplify 1.34% : 0.000045s : 13: substitution.tuple_list_convert_item_index_to_positive 0.91% : 0.000030s : 13: substitution.tuple_list_get_item_depend_reorder 2.83% : 0.000094s : 30: substitution.tuple_list_get_item_eliminator 0.75% : 0.000025s : 9: substitution.updatestate_pure_node_eliminater 1.88% : 0.000062s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.756281 2 99.62% : 0.753418s : 1: type_inference.infer 0.38% : 0.002863s : 1: type_inference.specialize ------[replace.] 0.416323 53 0.02% : 0.000074s : 3: replace.getattr_setattr_resolve 0.10% : 0.000432s : 28: replace.inline 0.01% : 0.000041s : 1: replace.replace_applicator 0.02% : 0.000082s : 3: replace.switch_simplify 0.04% : 0.000183s : 17: replace.tuple_list_get_item_eliminator 99.80% : 0.415510s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002351 53 36.31% : 0.000854s : 3: match.getattr_setattr_resolve 60.05% : 0.001412s : 28: match.inline 0.71% : 0.000017s : 1: match.replace_applicator 0.62% : 0.000015s : 3: match.switch_simplify 1.73% : 0.000041s : 17: match.tuple_list_get_item_eliminator 0.58% : 0.000014s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000954 5919 1.47% : 0.000014s : 99: predicate.accumulaten_eliminater 0.28% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.42% : 0.000014s : 99: predicate.addn_check_dump 1.50% : 0.000014s : 99: predicate.addn_zero_filter 1.96% : 0.000019s : 99: predicate.arithmetic_simplify 1.48% : 0.000014s : 99: predicate.cast_eliminate 0.15% : 0.000001s : 8: predicate.check_bprop_eliminate 1.45% : 0.000014s : 99: predicate.compare_switch_simplify 1.62% : 0.000015s : 99: predicate.depend_value_elim 1.48% : 0.000014s : 99: predicate.dict_get_item_const_eliminator 1.47% : 0.000014s : 99: predicate.dict_get_item_eliminator 1.45% : 0.000014s : 99: predicate.dict_set_item_eliminator 0.22% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.09% : 0.000001s : 8: predicate.elim_not_effective 0.17% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.42% : 0.000014s : 99: predicate.environ_add_const_eliminate 1.32% : 0.000013s : 99: predicate.environ_get_add_eliminate 3.56% : 0.000034s : 99: predicate.environ_get_depend_swap 1.39% : 0.000013s : 99: predicate.environ_get_eliminate 1.49% : 0.000014s : 99: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.77% : 0.000007s : 42: predicate.get_grad_eliminate 0.79% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.07% : 0.000001s : 8: predicate.graph_param_transform 4.12% : 0.000039s : 160: predicate.inline 1.96% : 0.000019s : 106: predicate.inline_without_move 0.33% : 0.000003s : 42: predicate.j_node_and_user_rematch 1.26% : 0.000012s : 42: predicate.less_batch_normalization 1.86% : 0.000018s : 116: predicate.list_to_tuple_eliminator_ 1.95% : 0.000019s : 124: predicate.load_eliminater 0.34% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.67% : 0.000025s : 171: predicate.loop_unroll_before_grad 1.64% : 0.000016s : 107: predicate.make_slice_get_slice_eliminator 1.43% : 0.000014s : 99: predicate.merge_addn 1.47% : 0.000014s : 99: predicate.minmaximum_grad 0.38% : 0.000004s : 8: predicate.mutable_eliminate 0.16% : 0.000002s : 8: predicate.opt_reshape 2.28% : 0.000022s : 124: predicate.partial_eliminate 1.41% : 0.000013s : 99: predicate.print_const_string_wrapper 1.82% : 0.000017s : 99: predicate.reduce_eliminate 1.78% : 0.000017s : 116: predicate.redundant_stop_gradient_eliminater 0.49% : 0.000005s : 42: predicate.remove_not_recompute_node 2.42% : 0.000023s : 236: predicate.replace_applicator 0.96% : 0.000009s : 106: predicate.replace_old_param 0.10% : 0.000001s : 8: predicate.reset_defer_inline 1.48% : 0.000014s : 99: predicate.reshape_eliminate 1.41% : 0.000013s : 99: predicate.row_tensor_add_zeros_like 0.27% : 0.000003s : 8: predicate.row_tensor_eliminate 1.47% : 0.000014s : 99: predicate.same_eliminate 0.50% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.31% : 0.000003s : 16: predicate.special_op_eliminate 0.93% : 0.000009s : 50: predicate.specialize_transform 1.74% : 0.000017s : 99: predicate.split_environ_get_set_with_tuple_value 1.44% : 0.000014s : 99: predicate.stack_unstack_eliminate 0.17% : 0.000002s : 8: predicate.switch_call_monad_eliminater 3.13% : 0.000030s : 144: predicate.switch_defer_inline 2.43% : 0.000023s : 144: predicate.switch_layer_defer_inline 5.99% : 0.000057s : 329: predicate.switch_simplify 1.51% : 0.000014s : 99: predicate.tile_eliminate 1.38% : 0.000013s : 99: predicate.transpose_eliminate 1.78% : 0.000017s : 99: predicate.tuple_list_convert_item_index_to_positive 1.72% : 0.000016s : 99: predicate.tuple_list_get_item_depend_reorder 3.25% : 0.000031s : 132: predicate.tuple_list_get_item_eliminator 1.91% : 0.000018s : 99: predicate.tuple_list_set_item_eliminator 1.69% : 0.000016s : 116: predicate.tuple_to_list_eliminator_ 1.88% : 0.000018s : 124: predicate.updatestate_pure_node_eliminater 3.55% : 0.000034s : 168: predicate.updatestate_useless_node_eliminater 1.84% : 0.000018s : 99: predicate.value_based_eliminate 0.14% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.19% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.262576 58 99.26% : 0.260624s : 22: func_graph_cloner_run.FuncGraphClonerGraph 0.14% : 0.000365s : 7: func_graph_cloner_run.FuncGraphClonerNode 0.60% : 0.001586s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 10.281307 108 0.00% : 0.000102s : 1: add_recomputation 0.00% : 0.000297s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.01% : 0.000544s : 1: bootstrap 0.00% : 0.000044s : 1: cconv 0.00% : 0.000033s : 1: convert_after_rewriter 0.00% : 0.000055s : 1: cse_after_recomputation 0.00% : 0.000022s : 1: environ_conv 0.00% : 0.000220s : 1: event_method 0.00% : 0.000015s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 10.95% : 1.125939s : 1: jit_opt_a 0.00% : 0.000306s : 1: jit_opt_after_cconv 0.00% : 0.000109s : 1: jit_opt_b 0.01% : 0.000776s : 1: loop_unroll 0.01% : 0.000839s : 1: mutable_eliminate 4.12% : 0.423657s : 52: opt.transform.jit_opt_a 0.00% : 0.000122s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000069s : 4: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.00% : 0.000043s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.001099s : 2: opt.transform.opt_resolve 0.00% : 0.000071s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000550s : 1: opt_after_jit_grad 0.00% : 0.000013s : 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% : 0.000059s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000037s : 1: remove_dup_value 0.18% : 0.018742s : 3: renormalize.infer 0.04% : 0.004568s : 3: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.005108s : 1: rewriter_after_opt_a 0.00% : 0.000161s : 1: rewriter_before_opt_a 0.00% : 0.000134s : 1: symbol_engine_optimizer 77.24% : 7.940898s : 1: task_emit 7.36% : 0.756421s : 1: type_inference 0.00% : 0.000095s : 1: validate . [hook] pytest_runtest_teardown:test_select_large_tensors[KBK] tests/st/mint/test_select.py::test_select_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 200.15s (0:03:20) ==================