==================================================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_008/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_std[pynative] tests/st/mint/test_select.py::test_select_std[pynative],max_mem:2.0M TotalTime = 0.829846, [30] [bootstrap]: 0.00077771 [type_inference]: 0.631347 [event_method]: 1.871e-05 [auto_monad]: 0.00018137 [graph_reusing]: 6.71999e-06 [pre_auto_parallel]: 1.226e-05 [py_interpret_to_execute]: 0.00011671 [rewriter_before_opt_a]: 0.00010319 [expand_dump_flag]: 3.49001e-06 [jit_opt_a]: 0.193768, [2] [Cycle 1]: 0.00222349, [27] [switch_simplify]: 0.00010099 [loop_unroll]: 2.157e-05 [a_1]: 0.00047831 [with_stream_mark]: 3.222e-05 [recompute_prepare]: 1.18e-05 [updatestate_depend_eliminate]: 8.12e-06 [updatestate_assign_eliminate]: 7.77998e-06 [updatestate_loads_eliminate]: 5.47999e-06 [parameter_eliminate]: 2.04e-06 [specialize_transform]: 1.055e-05 [updatestate_useless_node_eliminater]: 1.218e-05 [accelerated_algorithm]: 1.072e-05 [meta_shard_fg_expand]: 4.94998e-06 [get_grad_eliminate_]: 8.78001e-06 [merge_forward]: 5.40001e-06 [cell_reuse_recompute_pass]: 1.34e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.401e-05 [j_node_and_user_rematch]: 1.483e-05 [meta_fg_expand]: 4.20999e-06 [replace_old_param]: 1.405e-05 [inline_without_move]: 8.52998e-06 [renormalize]: 0.00109613 [add_forward_monad_depend]: 1.132e-05 [auto_monad_grad]: 2.74999e-06 [auto_monad_eliminator]: 2.348e-05 [cse]: 5.381e-05 [replace_applicator]: 2.029e-05 [Cycle 2]: 0.00051226, [27] [switch_simplify]: 9.82999e-06 [loop_unroll]: 8.1e-06 [a_1]: 0.00017765 [with_stream_mark]: 1.502e-05 [recompute_prepare]: 8.46002e-06 [updatestate_depend_eliminate]: 5.81998e-06 [updatestate_assign_eliminate]: 4.72998e-06 [updatestate_loads_eliminate]: 4.13001e-06 [parameter_eliminate]: 1.22e-06 [specialize_transform]: 1.182e-05 [updatestate_useless_node_eliminater]: 1.142e-05 [accelerated_algorithm]: 8.95001e-06 [meta_shard_fg_expand]: 2.34999e-06 [get_grad_eliminate_]: 8.29002e-06 [merge_forward]: 4.99e-06 [cell_reuse_recompute_pass]: 2.37999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.696e-05 [j_node_and_user_rematch]: 1.364e-05 [meta_fg_expand]: 3.53999e-06 [replace_old_param]: 1.238e-05 [inline_without_move]: 7.93001e-06 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 1.09e-06 [auto_monad_grad]: 1.22999e-06 [auto_monad_eliminator]: 1.113e-05 [cse]: 2.192e-05 [replace_applicator]: 9.17001e-06 [py_interpret_to_execute_after_opt_a]: 1.653e-05 [rewriter_after_opt_a]: 0.0004662 [convert_after_rewriter]: 1.581e-05 [order_py_execute_after_rewriter]: 8.13999e-06 [mutable_eliminate]: 0.0007964 [jit_opt_b]: 7.585e-05, [1] [Cycle 1]: 6.579e-05, [2] [frontend_op_eliminate]: 2.637e-05 [inline_after_opt_a]: 2.612e-05 [cconv]: 3.371e-05 [loop_unroll]: 0.00044733 [jit_opt_after_cconv]: 0.00022553, [1] [Cycle 1]: 0.00021819, [11] [c_1]: 5.218e-05 [parameter_eliminate]: 4.55001e-06 [updatestate_depend_eliminate]: 1.052e-05 [updatestate_assign_eliminate]: 5.47001e-06 [updatestate_loads_eliminate]: 5.02999e-06 [cse]: 3.833e-05 [call_graph_tuple_transform]: 2.538e-05 [tuple_list_get_item_eliminator]: 9.57999e-06 [none_parameter_eliminate]: 1.72999e-06 [renormalize]: 6.89994e-07 [switch_simplify]: 8.94e-06 [remove_dup_value]: 8.054e-05 [partial_unused_args_eliminate]: 2.44001e-06 [environ_conv]: 2.441e-05 [add_recomputation]: 8.207e-05 [cse_after_recomputation]: 3.267e-05, [1] [Cycle 1]: 2.551e-05, [1] [cse]: 1.725e-05 [auto_monad_reorder]: 3.674e-05 [get_jit_bprop_graph]: 2.32001e-06 [rewriter_after_jit_bprop_graph]: 0.00013525 [opt_after_jit_grad]: 0.00053015 [symbol_engine_optimizer]: 9.802e-05, [1] [Cycle 1]: 9.164e-05, [6] [build]: 5.96e-06 [elim_shapecalc]: 1.199e-05 [elim_not_effective]: 1.928e-05 [opt_reshape]: 9.25001e-06 [fold_const_symbol]: 1.443e-05 [renormalize]: 6.90023e-07 [validate]: 7.806e-05 Sums bootstrap : 0.000778s : 0.12% type_inference : 0.631347s : 98.96% event_method : 0.000019s : 0.00% auto_monad : 0.000181s : 0.03% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000117s : 0.02% rewriter_before_opt_a : 0.000103s : 0.02% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000111s : 0.02% jit_opt_a.loop_unroll : 0.000030s : 0.00% jit_opt_a.a_1 : 0.000656s : 0.10% jit_opt_a.with_stream_mark : 0.000047s : 0.01% jit_opt_a.recompute_prepare : 0.000020s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000022s : 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 : 0.000010s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000041s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000026s : 0.00% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.001096s : 0.17% jit_opt_a.add_forward_monad_depend : 0.000012s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000035s : 0.01% jit_opt_a.cse : 0.000076s : 0.01% jit_opt_a.replace_applicator : 0.000029s : 0.00% py_interpret_to_execute_after_opt_a : 0.000017s : 0.00% rewriter_after_opt_a : 0.000466s : 0.07% convert_after_rewriter : 0.000016s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000796s : 0.12% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.00% jit_opt_b.inline_after_opt_a : 0.000026s : 0.00% cconv : 0.000034s : 0.01% loop_unroll : 0.000447s : 0.07% jit_opt_after_cconv.c_1 : 0.000052s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 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 : 0.000038s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000025s : 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 : 0.000009s : 0.00% remove_dup_value : 0.000081s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000024s : 0.00% add_recomputation : 0.000082s : 0.01% cse_after_recomputation.cse : 0.000017s : 0.00% auto_monad_reorder : 0.000037s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000135s : 0.02% opt_after_jit_grad : 0.000530s : 0.08% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000078s : 0.01% Time group info: ------[substitution.] 0.000230 43 3.74% : 0.000009s : 2: substitution.depend_value_elim 1.44% : 0.000003s : 4: substitution.elim_not_effective 0.93% : 0.000002s : 4: substitution.fold_const_symbol 2.85% : 0.000007s : 5: substitution.graph_param_transform 72.04% : 0.000166s : 2: substitution.inline 2.17% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.29% : 0.000008s : 8: substitution.remove_not_recompute_node 2.92% : 0.000007s : 2: substitution.replace_old_param 5.53% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 5.09% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.631247 2 99.80% : 0.629960s : 1: type_inference.infer 0.20% : 0.001287s : 1: type_inference.specialize ------[replace.] 0.000032 2 100.00% : 0.000032s : 2: replace.inline ------[match.] 0.000163 2 100.00% : 0.000163s : 2: match.inline ------[predicate.] 0.000157 767 1.15% : 0.000002s : 11: predicate.accumulaten_eliminater 1.36% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 0.98% : 0.000002s : 11: predicate.addn_check_dump 1.24% : 0.000002s : 11: predicate.addn_zero_filter 1.78% : 0.000003s : 11: predicate.arithmetic_simplify 1.73% : 0.000003s : 11: predicate.cast_eliminate 0.59% : 0.000001s : 5: predicate.check_bprop_eliminate 0.94% : 0.000001s : 11: predicate.compare_switch_simplify 1.33% : 0.000002s : 11: predicate.depend_value_elim 0.94% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.13% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.06% : 0.000002s : 11: predicate.dict_set_item_eliminator 0.98% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.50% : 0.000001s : 5: predicate.elim_not_effective 0.80% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 0.98% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.06% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.01% : 0.000002s : 11: predicate.environ_get_depend_swap 1.25% : 0.000002s : 11: predicate.environ_get_eliminate 0.95% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.29% : 0.000000s : 5: predicate.fold_const_symbol 1.39% : 0.000002s : 10: predicate.get_grad_eliminate 0.45% : 0.000001s : 5: predicate.graph_param_transform 4.93% : 0.000008s : 23: predicate.inline 1.17% : 0.000002s : 10: predicate.inline_without_move 0.49% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.88% : 0.000003s : 10: predicate.less_batch_normalization 1.27% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.59% : 0.000002s : 16: predicate.load_eliminater 1.80% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.43% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.01% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.29% : 0.000002s : 11: predicate.merge_addn 1.02% : 0.000002s : 11: predicate.minmaximum_grad 2.62% : 0.000004s : 5: predicate.mutable_eliminate 0.68% : 0.000001s : 5: predicate.opt_reshape 1.87% : 0.000003s : 16: predicate.partial_eliminate 1.00% : 0.000002s : 11: predicate.print_const_string_wrapper 1.50% : 0.000002s : 11: predicate.reduce_eliminate 1.21% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 1.01% : 0.000002s : 10: predicate.remove_not_recompute_node 1.59% : 0.000002s : 21: predicate.replace_applicator 0.75% : 0.000001s : 10: predicate.replace_old_param 0.38% : 0.000001s : 5: predicate.reset_defer_inline 1.11% : 0.000002s : 11: predicate.reshape_eliminate 1.10% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.06% : 0.000002s : 5: predicate.row_tensor_eliminate 1.13% : 0.000002s : 11: predicate.same_eliminate 0.62% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.35% : 0.000002s : 10: predicate.special_op_eliminate 1.39% : 0.000002s : 10: predicate.specialize_transform 1.43% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.17% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.68% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.37% : 0.000002s : 13: predicate.switch_defer_inline 1.47% : 0.000002s : 13: predicate.switch_layer_defer_inline 10.22% : 0.000016s : 38: predicate.switch_simplify 1.09% : 0.000002s : 11: predicate.tile_eliminate 1.03% : 0.000002s : 11: predicate.transpose_eliminate 1.40% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.31% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.86% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.54% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.27% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.56% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.67% : 0.000006s : 26: predicate.updatestate_useless_node_eliminater 1.45% : 0.000002s : 11: predicate.value_based_eliminate 0.48% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.87% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000374 5 5.89% : 0.000022s : 1: func_graph_cloner_run.FuncGraphClonerGraph 94.11% : 0.000352s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.831946 72 0.01% : 0.000085s : 1: add_recomputation 0.02% : 0.000187s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.10% : 0.000801s : 1: bootstrap 0.00% : 0.000037s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000035s : 1: cse_after_recomputation 0.00% : 0.000027s : 1: environ_conv 0.00% : 0.000024s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 23.29% : 0.193772s : 1: jit_opt_a 0.03% : 0.000229s : 1: jit_opt_after_cconv 0.01% : 0.000079s : 1: jit_opt_b 0.05% : 0.000455s : 1: loop_unroll 0.10% : 0.000806s : 1: mutable_eliminate 0.12% : 0.000991s : 26: opt.transform.jit_opt_a 0.01% : 0.000092s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000045s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000026s : 1: opt.transform.mutable_eliminate 0.00% : 0.000033s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000538s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000120s : 1: py_interpret_to_execute 0.00% : 0.000019s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000085s : 1: remove_dup_value 0.08% : 0.000704s : 1: renormalize.infer 0.05% : 0.000382s : 1: renormalize.specialize 0.02% : 0.000138s : 1: rewriter_after_jit_bprop_graph 0.06% : 0.000472s : 1: rewriter_after_opt_a 0.01% : 0.000108s : 1: rewriter_before_opt_a 0.01% : 0.000101s : 1: symbol_engine_optimizer 75.89% : 0.631376s : 1: type_inference TotalTime = 1.63028, [30] [bootstrap]: 0.00062247 [type_inference]: 0.906922 [event_method]: 0.00022923 [auto_monad]: 0.00031734 [graph_reusing]: 1.125e-05 [pre_auto_parallel]: 3.47997e-06 [py_interpret_to_execute]: 7.197e-05 [rewriter_before_opt_a]: 0.00016232 [expand_dump_flag]: 4.68999e-06 [jit_opt_a]: 0.718041, [4] [Cycle 1]: 0.400936, [27] [switch_simplify]: 0.00025064 [loop_unroll]: 5.82e-05 [a_1]: 0.0678334 [with_stream_mark]: 5.404e-05 [recompute_prepare]: 6.481e-05 [updatestate_depend_eliminate]: 1.865e-05 [updatestate_assign_eliminate]: 1.076e-05 [updatestate_loads_eliminate]: 1.065e-05 [parameter_eliminate]: 5.11997e-06 [specialize_transform]: 2.087e-05 [updatestate_useless_node_eliminater]: 2.66e-05 [accelerated_algorithm]: 2.098e-05 [meta_shard_fg_expand]: 1.31e-05 [get_grad_eliminate_]: 1.923e-05 [merge_forward]: 1.29e-05 [cell_reuse_recompute_pass]: 1.79e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.248e-05 [j_node_and_user_rematch]: 3.448e-05 [meta_fg_expand]: 0.184495 [replace_old_param]: 0.00014157 [inline_without_move]: 0.00015448 [renormalize]: 0.146368 [add_forward_monad_depend]: 3.778e-05 [auto_monad_grad]: 2.303e-05 [auto_monad_eliminator]: 0.00014958 [cse]: 0.00037779 [replace_applicator]: 0.00029648 [Cycle 2]: 0.260522, [27] [switch_simplify]: 0.00010723 [loop_unroll]: 9.469e-05 [a_1]: 0.249394 [with_stream_mark]: 6.857e-05 [recompute_prepare]: 5.067e-05 [updatestate_depend_eliminate]: 1.91e-05 [updatestate_assign_eliminate]: 1.684e-05 [updatestate_loads_eliminate]: 1.522e-05 [parameter_eliminate]: 5.46998e-06 [specialize_transform]: 2.639e-05 [updatestate_useless_node_eliminater]: 0.00013158 [accelerated_algorithm]: 4.107e-05 [meta_shard_fg_expand]: 1.221e-05 [get_grad_eliminate_]: 1.599e-05 [merge_forward]: 1.032e-05 [cell_reuse_recompute_pass]: 1.67999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.688e-05 [j_node_and_user_rematch]: 2.849e-05 [meta_fg_expand]: 0.00016943 [replace_old_param]: 2.777e-05 [inline_without_move]: 1.521e-05 [renormalize]: 0.00963647 [add_forward_monad_depend]: 1.426e-05 [auto_monad_grad]: 2.39001e-06 [auto_monad_eliminator]: 4.488e-05 [cse]: 0.00018697 [replace_applicator]: 5.449e-05 [Cycle 3]: 0.0510667, [27] [switch_simplify]: 1.99e-05 [loop_unroll]: 1.499e-05 [a_1]: 0.00044776 [with_stream_mark]: 4.476e-05 [recompute_prepare]: 1.962e-05 [updatestate_depend_eliminate]: 7.746e-05 [updatestate_assign_eliminate]: 8.90999e-06 [updatestate_loads_eliminate]: 8.58001e-06 [parameter_eliminate]: 2.49001e-06 [specialize_transform]: 1.653e-05 [updatestate_useless_node_eliminater]: 1.84e-05 [accelerated_algorithm]: 2.149e-05 [meta_shard_fg_expand]: 6.04001e-06 [get_grad_eliminate_]: 1.22e-05 [merge_forward]: 8.46002e-06 [cell_reuse_recompute_pass]: 3.48e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.238e-05 [j_node_and_user_rematch]: 2.076e-05 [meta_fg_expand]: 5.44998e-06 [replace_old_param]: 1.994e-05 [inline_without_move]: 1.25e-05 [renormalize]: 0.0158985 [add_forward_monad_depend]: 1.181e-05 [auto_monad_grad]: 2.66999e-06 [auto_monad_eliminator]: 4.086e-05 [cse]: 0.0001355 [replace_applicator]: 4.014e-05 [Cycle 4]: 0.00091779, [27] [switch_simplify]: 1.538e-05 [loop_unroll]: 1.262e-05 [a_1]: 0.00030179 [with_stream_mark]: 2.814e-05 [recompute_prepare]: 1.594e-05 [updatestate_depend_eliminate]: 3.755e-05 [updatestate_assign_eliminate]: 9.59999e-06 [updatestate_loads_eliminate]: 9.59e-06 [parameter_eliminate]: 2.14999e-06 [specialize_transform]: 1.68e-05 [updatestate_useless_node_eliminater]: 1.843e-05 [accelerated_algorithm]: 2.036e-05 [meta_shard_fg_expand]: 3.85e-06 [get_grad_eliminate_]: 1.225e-05 [merge_forward]: 9.59e-06 [cell_reuse_recompute_pass]: 3.73001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.891e-05 [j_node_and_user_rematch]: 2.246e-05 [meta_fg_expand]: 5.52999e-06 [replace_old_param]: 1.807e-05 [inline_without_move]: 1.323e-05 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 3.61999e-06 [auto_monad_grad]: 2.27999e-06 [auto_monad_eliminator]: 3.293e-05 [cse]: 6.626e-05 [replace_applicator]: 3.519e-05 [py_interpret_to_execute_after_opt_a]: 2.91e-05 [rewriter_after_opt_a]: 0.00025559 [convert_after_rewriter]: 1.862e-05 [order_py_execute_after_rewriter]: 1.017e-05 [mutable_eliminate]: 0.00094525 [jit_opt_b]: 0.00011222, [1] [Cycle 1]: 0.00010129, [2] [frontend_op_eliminate]: 4.289e-05 [inline_after_opt_a]: 4.21e-05 [cconv]: 4.751e-05 [loop_unroll]: 0.00056466 [jit_opt_after_cconv]: 0.00035606, [1] [Cycle 1]: 0.00034866, [11] [c_1]: 8.209e-05 [parameter_eliminate]: 6.46e-06 [updatestate_depend_eliminate]: 2.006e-05 [updatestate_assign_eliminate]: 7.56001e-06 [updatestate_loads_eliminate]: 7.16001e-06 [cse]: 9.473e-05 [call_graph_tuple_transform]: 3.885e-05 [tuple_list_get_item_eliminator]: 1.308e-05 [none_parameter_eliminate]: 2.21998e-06 [renormalize]: 5.19998e-07 [switch_simplify]: 1.388e-05 [remove_dup_value]: 0.00010979 [partial_unused_args_eliminate]: 3.86999e-06 [environ_conv]: 1.763e-05 [add_recomputation]: 0.0001149 [cse_after_recomputation]: 5.85e-05, [1] [Cycle 1]: 4.912e-05, [1] [cse]: 3.655e-05 [auto_monad_reorder]: 3.743e-05 [get_jit_bprop_graph]: 3.21001e-06 [rewriter_after_jit_bprop_graph]: 9.13002e-06 [opt_after_jit_grad]: 0.00070338 [symbol_engine_optimizer]: 0.00014886, [1] [Cycle 1]: 0.00014023, [6] [build]: 1.944e-05 [elim_shapecalc]: 1.888e-05 [elim_not_effective]: 3.19e-05 [opt_reshape]: 1.457e-05 [fold_const_symbol]: 2.043e-05 [renormalize]: 9.20001e-07 [validate]: 7.437e-05 Sums bootstrap : 0.000622s : 0.04% type_inference : 0.906922s : 57.03% event_method : 0.000229s : 0.01% auto_monad : 0.000317s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000072s : 0.00% rewriter_before_opt_a : 0.000162s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000393s : 0.02% jit_opt_a.loop_unroll : 0.000181s : 0.01% jit_opt_a.a_1 : 0.317977s : 20.00% jit_opt_a.with_stream_mark : 0.000196s : 0.01% jit_opt_a.recompute_prepare : 0.000151s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000153s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000046s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000044s : 0.00% jit_opt_a.parameter_eliminate : 0.000015s : 0.00% jit_opt_a.specialize_transform : 0.000081s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000195s : 0.01% jit_opt_a.accelerated_algorithm : 0.000104s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000035s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000060s : 0.00% jit_opt_a.merge_forward : 0.000041s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000011s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000141s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000106s : 0.01% jit_opt_a.meta_fg_expand : 0.184676s : 11.61% jit_opt_a.replace_old_param : 0.000207s : 0.01% jit_opt_a.inline_without_move : 0.000195s : 0.01% jit_opt_a.renormalize : 0.171903s : 10.81% jit_opt_a.add_forward_monad_depend : 0.000067s : 0.00% jit_opt_a.auto_monad_grad : 0.000030s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000268s : 0.02% jit_opt_a.cse : 0.000767s : 0.05% jit_opt_a.replace_applicator : 0.000426s : 0.03% py_interpret_to_execute_after_opt_a : 0.000029s : 0.00% rewriter_after_opt_a : 0.000256s : 0.02% convert_after_rewriter : 0.000019s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000945s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000043s : 0.00% jit_opt_b.inline_after_opt_a : 0.000042s : 0.00% cconv : 0.000048s : 0.00% loop_unroll : 0.000565s : 0.04% jit_opt_after_cconv.c_1 : 0.000082s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000020s : 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 : 0.000095s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000039s : 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 : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000014s : 0.00% remove_dup_value : 0.000110s : 0.01% partial_unused_args_eliminate : 0.000004s : 0.00% environ_conv : 0.000018s : 0.00% add_recomputation : 0.000115s : 0.01% cse_after_recomputation.cse : 0.000037s : 0.00% auto_monad_reorder : 0.000037s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000703s : 0.04% symbol_engine_optimizer.build : 0.000019s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000019s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000032s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000015s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000074s : 0.00% Time group info: ------[substitution.] 0.003546 291 1.49% : 0.000053s : 12: substitution.depend_value_elim 0.13% : 0.000005s : 7: substitution.elim_not_effective 0.08% : 0.000003s : 7: substitution.fold_const_symbol 22.42% : 0.000795s : 4: substitution.getattr_setattr_resolve 0.29% : 0.000010s : 8: substitution.graph_param_transform 56.24% : 0.001994s : 28: substitution.inline 1.71% : 0.000061s : 4: substitution.inline_without_move 0.51% : 0.000018s : 35: substitution.j_node_and_user_rematch 0.79% : 0.000028s : 3: substitution.less_batch_normalization 0.69% : 0.000024s : 13: substitution.minmaximum_grad 0.46% : 0.000016s : 14: substitution.partial_eliminate 0.81% : 0.000029s : 35: substitution.remove_not_recompute_node 2.69% : 0.000096s : 16: substitution.replace_applicator 0.69% : 0.000025s : 19: substitution.replace_old_param 0.31% : 0.000011s : 2: substitution.set_cell_output_no_recompute 0.47% : 0.000017s : 3: substitution.switch_simplify 1.59% : 0.000056s : 13: substitution.tuple_list_convert_item_index_to_positive 1.09% : 0.000039s : 13: substitution.tuple_list_get_item_depend_reorder 4.02% : 0.000143s : 30: substitution.tuple_list_get_item_eliminator 1.18% : 0.000042s : 9: substitution.updatestate_pure_node_eliminater 2.33% : 0.000083s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.906776 2 99.62% : 0.903293s : 1: type_inference.infer 0.38% : 0.003482s : 1: type_inference.specialize ------[replace.] 0.001136 53 6.45% : 0.000073s : 3: replace.getattr_setattr_resolve 53.22% : 0.000605s : 28: replace.inline 4.57% : 0.000052s : 1: replace.replace_applicator 7.39% : 0.000084s : 3: replace.switch_simplify 22.06% : 0.000251s : 17: replace.tuple_list_get_item_eliminator 6.30% : 0.000072s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002829 53 26.08% : 0.000738s : 3: match.getattr_setattr_resolve 69.64% : 0.001970s : 28: match.inline 0.77% : 0.000022s : 1: match.replace_applicator 0.52% : 0.000015s : 3: match.switch_simplify 2.19% : 0.000062s : 17: match.tuple_list_get_item_eliminator 0.80% : 0.000023s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001042 5919 1.38% : 0.000014s : 99: predicate.accumulaten_eliminater 0.38% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.35% : 0.000014s : 99: predicate.addn_check_dump 1.51% : 0.000016s : 99: predicate.addn_zero_filter 1.97% : 0.000021s : 99: predicate.arithmetic_simplify 1.43% : 0.000015s : 99: predicate.cast_eliminate 0.14% : 0.000002s : 8: predicate.check_bprop_eliminate 1.33% : 0.000014s : 99: predicate.compare_switch_simplify 1.65% : 0.000017s : 99: predicate.depend_value_elim 1.31% : 0.000014s : 99: predicate.dict_get_item_const_eliminator 1.41% : 0.000015s : 99: predicate.dict_get_item_eliminator 1.34% : 0.000014s : 99: predicate.dict_set_item_eliminator 0.28% : 0.000003s : 8: predicate.dumpgradient_eliminate 0.09% : 0.000001s : 8: predicate.elim_not_effective 0.22% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.40% : 0.000015s : 99: predicate.environ_add_const_eliminate 1.30% : 0.000014s : 99: predicate.environ_get_add_eliminate 1.32% : 0.000014s : 99: predicate.environ_get_depend_swap 1.42% : 0.000015s : 99: predicate.environ_get_eliminate 1.31% : 0.000014s : 99: predicate.environ_get_set_eliminate 0.06% : 0.000001s : 8: predicate.fold_const_symbol 0.83% : 0.000009s : 42: predicate.get_grad_eliminate 0.66% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.06% : 0.000001s : 8: predicate.graph_param_transform 4.80% : 0.000050s : 160: predicate.inline 2.05% : 0.000021s : 106: predicate.inline_without_move 0.33% : 0.000003s : 42: predicate.j_node_and_user_rematch 1.02% : 0.000011s : 42: predicate.less_batch_normalization 1.78% : 0.000019s : 116: predicate.list_to_tuple_eliminator_ 1.92% : 0.000020s : 124: predicate.load_eliminater 0.41% : 0.000004s : 8: predicate.loop_unroll_after_grad 2.58% : 0.000027s : 171: predicate.loop_unroll_before_grad 1.59% : 0.000017s : 107: predicate.make_slice_get_slice_eliminator 2.20% : 0.000023s : 99: predicate.merge_addn 1.27% : 0.000013s : 99: predicate.minmaximum_grad 0.49% : 0.000005s : 8: predicate.mutable_eliminate 0.15% : 0.000002s : 8: predicate.opt_reshape 2.23% : 0.000023s : 124: predicate.partial_eliminate 1.33% : 0.000014s : 99: predicate.print_const_string_wrapper 1.82% : 0.000019s : 99: predicate.reduce_eliminate 1.84% : 0.000019s : 116: predicate.redundant_stop_gradient_eliminater 0.41% : 0.000004s : 42: predicate.remove_not_recompute_node 2.47% : 0.000026s : 236: predicate.replace_applicator 0.94% : 0.000010s : 106: predicate.replace_old_param 0.15% : 0.000002s : 8: predicate.reset_defer_inline 1.40% : 0.000015s : 99: predicate.reshape_eliminate 1.46% : 0.000015s : 99: predicate.row_tensor_add_zeros_like 0.34% : 0.000003s : 8: predicate.row_tensor_eliminate 1.42% : 0.000015s : 99: predicate.same_eliminate 0.50% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.29% : 0.000003s : 16: predicate.special_op_eliminate 0.99% : 0.000010s : 50: predicate.specialize_transform 1.92% : 0.000020s : 99: predicate.split_environ_get_set_with_tuple_value 1.37% : 0.000014s : 99: predicate.stack_unstack_eliminate 0.15% : 0.000002s : 8: predicate.switch_call_monad_eliminater 5.01% : 0.000052s : 144: predicate.switch_defer_inline 2.33% : 0.000024s : 144: predicate.switch_layer_defer_inline 5.91% : 0.000062s : 329: predicate.switch_simplify 1.44% : 0.000015s : 99: predicate.tile_eliminate 1.38% : 0.000014s : 99: predicate.transpose_eliminate 1.77% : 0.000018s : 99: predicate.tuple_list_convert_item_index_to_positive 1.56% : 0.000016s : 99: predicate.tuple_list_get_item_depend_reorder 3.47% : 0.000036s : 132: predicate.tuple_list_get_item_eliminator 2.05% : 0.000021s : 99: predicate.tuple_list_set_item_eliminator 2.57% : 0.000027s : 116: predicate.tuple_to_list_eliminator_ 1.72% : 0.000018s : 124: predicate.updatestate_pure_node_eliminater 2.90% : 0.000030s : 168: predicate.updatestate_useless_node_eliminater 1.83% : 0.000019s : 99: 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.] 0.006049 58 46.45% : 0.002810s : 22: func_graph_cloner_run.FuncGraphClonerGraph 8.74% : 0.000529s : 7: func_graph_cloner_run.FuncGraphClonerNode 44.80% : 0.002710s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.123401 104 0.01% : 0.000119s : 1: add_recomputation 0.02% : 0.000326s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.03% : 0.000645s : 1: bootstrap 0.00% : 0.000050s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.00% : 0.000061s : 1: cse_after_recomputation 0.00% : 0.000020s : 1: environ_conv 0.01% : 0.000240s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 33.82% : 0.718046s : 1: jit_opt_a 0.02% : 0.000360s : 1: jit_opt_after_cconv 0.01% : 0.000116s : 1: jit_opt_b 0.03% : 0.000575s : 1: loop_unroll 0.05% : 0.000960s : 1: mutable_eliminate 15.07% : 0.320092s : 52: opt.transform.jit_opt_a 0.01% : 0.000143s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000075s : 4: opt.transform.jit_opt_b 0.00% : 0.000029s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000039s : 1: opt.transform.mutable_eliminate 0.00% : 0.000055s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000937s : 2: opt.transform.opt_resolve 0.00% : 0.000081s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000716s : 1: opt_after_jit_grad 0.00% : 0.000013s : 1: order_py_execute_after_rewriter 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000076s : 1: py_interpret_to_execute 0.00% : 0.000032s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000114s : 1: remove_dup_value 7.76% : 0.164748s : 3: renormalize.infer 0.33% : 0.007090s : 3: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000263s : 1: rewriter_after_opt_a 0.01% : 0.000166s : 1: rewriter_before_opt_a 0.01% : 0.000153s : 1: symbol_engine_optimizer 42.71% : 0.906947s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_std[KBK] tests/st/mint/test_select.py::test_select_std[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 244.81s (0:04:04) ==================