==================================================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 10 items test_select.py . [hook] pytest_runtest_teardown:test_select_special_values[inf-pynative] tests/st/mint/test_select.py::test_select_special_values[inf-pynative],max_mem:2.0M TotalTime = 0.608106, [30] [bootstrap]: 0.00096912 [type_inference]: 0.476483 [event_method]: 1.382e-05 [auto_monad]: 0.00025184 [graph_reusing]: 6.71e-06 [pre_auto_parallel]: 1.371e-05 [py_interpret_to_execute]: 0.00013173 [rewriter_before_opt_a]: 0.00021447 [expand_dump_flag]: 3.28998e-06 [jit_opt_a]: 0.126254, [2] [Cycle 1]: 0.00230645, [27] [switch_simplify]: 9.255e-05 [loop_unroll]: 2.162e-05 [a_1]: 0.00046042 [with_stream_mark]: 3.266e-05 [recompute_prepare]: 1.037e-05 [updatestate_depend_eliminate]: 6.64001e-06 [updatestate_assign_eliminate]: 3.49e-05 [updatestate_loads_eliminate]: 5.40999e-06 [parameter_eliminate]: 1.89999e-06 [specialize_transform]: 9.67999e-06 [updatestate_useless_node_eliminater]: 1.189e-05 [accelerated_algorithm]: 9.14e-06 [meta_shard_fg_expand]: 2.88998e-06 [get_grad_eliminate_]: 9.16998e-06 [merge_forward]: 6.17001e-06 [cell_reuse_recompute_pass]: 1.20999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.331e-05 [j_node_and_user_rematch]: 1.434e-05 [meta_fg_expand]: 3.53e-06 [replace_old_param]: 1.325e-05 [inline_without_move]: 7.69002e-06 [renormalize]: 0.00111742 [add_forward_monad_depend]: 3.663e-05 [auto_monad_grad]: 2.88998e-06 [auto_monad_eliminator]: 2.481e-05 [cse]: 6.507e-05 [replace_applicator]: 2.054e-05 [Cycle 2]: 0.00049257, [27] [switch_simplify]: 9.34998e-06 [loop_unroll]: 7.71999e-06 [a_1]: 0.00016431 [with_stream_mark]: 1.419e-05 [recompute_prepare]: 8.57e-06 [updatestate_depend_eliminate]: 6.56e-06 [updatestate_assign_eliminate]: 4.63999e-06 [updatestate_loads_eliminate]: 4.77e-06 [parameter_eliminate]: 1.35999e-06 [specialize_transform]: 1.203e-05 [updatestate_useless_node_eliminater]: 1.1e-05 [accelerated_algorithm]: 8.42e-06 [meta_shard_fg_expand]: 2.32999e-06 [get_grad_eliminate_]: 7.55998e-06 [merge_forward]: 5.42001e-06 [cell_reuse_recompute_pass]: 2.26e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.762e-05 [j_node_and_user_rematch]: 1.332e-05 [meta_fg_expand]: 3.11001e-06 [replace_old_param]: 1.227e-05 [inline_without_move]: 8.06001e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.06e-06 [auto_monad_grad]: 9.89996e-07 [auto_monad_eliminator]: 1.199e-05 [cse]: 1.962e-05 [replace_applicator]: 8.50001e-06 [py_interpret_to_execute_after_opt_a]: 1.699e-05 [rewriter_after_opt_a]: 0.00054279 [convert_after_rewriter]: 4.636e-05 [order_py_execute_after_rewriter]: 8.13999e-06 [mutable_eliminate]: 0.00080131 [jit_opt_b]: 7.542e-05, [1] [Cycle 1]: 6.63e-05, [2] [frontend_op_eliminate]: 2.551e-05 [inline_after_opt_a]: 2.626e-05 [cconv]: 3.804e-05 [loop_unroll]: 0.00045389 [jit_opt_after_cconv]: 0.00022988, [1] [Cycle 1]: 0.00022289, [11] [c_1]: 5.19e-05 [parameter_eliminate]: 4.99e-06 [updatestate_depend_eliminate]: 1.248e-05 [updatestate_assign_eliminate]: 5.68002e-06 [updatestate_loads_eliminate]: 5.54e-06 [cse]: 4.414e-05 [call_graph_tuple_transform]: 2.295e-05 [tuple_list_get_item_eliminator]: 8.42e-06 [none_parameter_eliminate]: 1.81e-06 [renormalize]: 1.22e-06 [switch_simplify]: 8.59e-06 [remove_dup_value]: 5.173e-05 [partial_unused_args_eliminate]: 2.47001e-06 [environ_conv]: 2.433e-05 [add_recomputation]: 0.00012535 [cse_after_recomputation]: 3.359e-05, [1] [Cycle 1]: 2.622e-05, [1] [cse]: 1.855e-05 [auto_monad_reorder]: 3.819e-05 [get_jit_bprop_graph]: 2.71e-06 [rewriter_after_jit_bprop_graph]: 0.00014808 [opt_after_jit_grad]: 0.00052953 [symbol_engine_optimizer]: 0.00010054, [1] [Cycle 1]: 9.334e-05, [6] [build]: 6.98e-06 [elim_shapecalc]: 1.206e-05 [elim_not_effective]: 1.94e-05 [opt_reshape]: 9.12001e-06 [fold_const_symbol]: 1.383e-05 [renormalize]: 3.09985e-07 [validate]: 0.00014691 Sums bootstrap : 0.000969s : 0.20% type_inference : 0.476483s : 98.49% event_method : 0.000014s : 0.00% auto_monad : 0.000252s : 0.05% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000014s : 0.00% py_interpret_to_execute : 0.000132s : 0.03% rewriter_before_opt_a : 0.000214s : 0.04% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000102s : 0.02% jit_opt_a.loop_unroll : 0.000029s : 0.01% jit_opt_a.a_1 : 0.000625s : 0.13% jit_opt_a.with_stream_mark : 0.000047s : 0.01% jit_opt_a.recompute_prepare : 0.000019s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000040s : 0.01% 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 : 0.000023s : 0.00% jit_opt_a.accelerated_algorithm : 0.000018s : 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 : 0.000003s : 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 : 0.01% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000026s : 0.01% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.001118s : 0.23% jit_opt_a.add_forward_monad_depend : 0.000039s : 0.01% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000037s : 0.01% jit_opt_a.cse : 0.000085s : 0.02% jit_opt_a.replace_applicator : 0.000029s : 0.01% py_interpret_to_execute_after_opt_a : 0.000017s : 0.00% rewriter_after_opt_a : 0.000543s : 0.11% convert_after_rewriter : 0.000046s : 0.01% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000801s : 0.17% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.01% jit_opt_b.inline_after_opt_a : 0.000026s : 0.01% cconv : 0.000038s : 0.01% loop_unroll : 0.000454s : 0.09% 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 : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000044s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000023s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 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 : 0.000052s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000024s : 0.01% add_recomputation : 0.000125s : 0.03% cse_after_recomputation.cse : 0.000019s : 0.00% auto_monad_reorder : 0.000038s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000148s : 0.03% opt_after_jit_grad : 0.000530s : 0.11% symbol_engine_optimizer.build : 0.000007s : 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 : 0.000000s : 0.00% validate : 0.000147s : 0.03% Time group info: ------[substitution.] 0.000221 43 3.97% : 0.000009s : 2: substitution.depend_value_elim 1.43% : 0.000003s : 4: substitution.elim_not_effective 0.93% : 0.000002s : 4: substitution.fold_const_symbol 3.50% : 0.000008s : 5: substitution.graph_param_transform 70.20% : 0.000155s : 2: substitution.inline 2.46% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.36% : 0.000007s : 8: substitution.remove_not_recompute_node 3.17% : 0.000007s : 2: substitution.replace_old_param 6.02% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.96% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.476325 2 99.77% : 0.475252s : 1: type_inference.infer 0.23% : 0.001073s : 1: type_inference.specialize ------[replace.] 0.000032 2 100.00% : 0.000032s : 2: replace.inline ------[match.] 0.000153 2 100.00% : 0.000153s : 2: match.inline ------[predicate.] 0.000152 767 1.13% : 0.000002s : 11: predicate.accumulaten_eliminater 1.48% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.03% : 0.000002s : 11: predicate.addn_check_dump 1.21% : 0.000002s : 11: predicate.addn_zero_filter 1.95% : 0.000003s : 11: predicate.arithmetic_simplify 1.55% : 0.000002s : 11: predicate.cast_eliminate 0.59% : 0.000001s : 5: predicate.check_bprop_eliminate 1.07% : 0.000002s : 11: predicate.compare_switch_simplify 1.45% : 0.000002s : 11: predicate.depend_value_elim 1.15% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.19% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.06% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.02% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.54% : 0.000001s : 5: predicate.elim_not_effective 0.70% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.15% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.14% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.06% : 0.000002s : 11: predicate.environ_get_depend_swap 1.14% : 0.000002s : 11: predicate.environ_get_eliminate 0.98% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.28% : 0.000000s : 5: predicate.fold_const_symbol 1.73% : 0.000003s : 10: predicate.get_grad_eliminate 0.43% : 0.000001s : 5: predicate.graph_param_transform 5.34% : 0.000008s : 23: predicate.inline 1.72% : 0.000003s : 10: predicate.inline_without_move 0.50% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.85% : 0.000003s : 10: predicate.less_batch_normalization 1.86% : 0.000003s : 11: predicate.list_to_tuple_eliminator_ 1.84% : 0.000003s : 16: predicate.load_eliminater 1.32% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.83% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.15% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.98% : 0.000002s : 11: predicate.merge_addn 0.91% : 0.000001s : 11: predicate.minmaximum_grad 2.79% : 0.000004s : 5: predicate.mutable_eliminate 0.65% : 0.000001s : 5: predicate.opt_reshape 1.95% : 0.000003s : 16: predicate.partial_eliminate 1.16% : 0.000002s : 11: predicate.print_const_string_wrapper 1.51% : 0.000002s : 11: predicate.reduce_eliminate 1.09% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.85% : 0.000001s : 10: predicate.remove_not_recompute_node 1.61% : 0.000002s : 21: predicate.replace_applicator 0.82% : 0.000001s : 10: predicate.replace_old_param 0.56% : 0.000001s : 5: predicate.reset_defer_inline 1.19% : 0.000002s : 11: predicate.reshape_eliminate 1.17% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.10% : 0.000002s : 5: predicate.row_tensor_eliminate 1.25% : 0.000002s : 11: predicate.same_eliminate 0.67% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.44% : 0.000002s : 10: predicate.special_op_eliminate 1.44% : 0.000002s : 10: predicate.specialize_transform 1.21% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.55% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.69% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.65% : 0.000003s : 13: predicate.switch_defer_inline 1.42% : 0.000002s : 13: predicate.switch_layer_defer_inline 6.06% : 0.000009s : 38: predicate.switch_simplify 1.21% : 0.000002s : 11: predicate.tile_eliminate 1.11% : 0.000002s : 11: predicate.transpose_eliminate 1.47% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.50% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.56% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.60% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.19% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.78% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.38% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.61% : 0.000002s : 11: predicate.value_based_eliminate 0.57% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.82% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000374 5 6.53% : 0.000024s : 1: func_graph_cloner_run.FuncGraphClonerGraph 93.47% : 0.000350s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.610065 72 0.02% : 0.000130s : 1: add_recomputation 0.04% : 0.000258s : 1: auto_monad 0.01% : 0.000041s : 1: auto_monad_reorder 0.16% : 0.001000s : 1: bootstrap 0.01% : 0.000041s : 1: cconv 0.01% : 0.000051s : 1: convert_after_rewriter 0.01% : 0.000036s : 1: cse_after_recomputation 0.00% : 0.000027s : 1: environ_conv 0.00% : 0.000019s : 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 20.70% : 0.126258s : 1: jit_opt_a 0.04% : 0.000233s : 1: jit_opt_after_cconv 0.01% : 0.000079s : 1: jit_opt_b 0.08% : 0.000463s : 1: loop_unroll 0.13% : 0.000816s : 1: mutable_eliminate 0.15% : 0.000919s : 26: opt.transform.jit_opt_a 0.01% : 0.000088s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000043s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000024s : 1: opt.transform.mutable_eliminate 0.01% : 0.000031s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.09% : 0.000540s : 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% : 0.000017s : 1: pre_auto_parallel 0.02% : 0.000138s : 1: py_interpret_to_execute 0.00% : 0.000020s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000055s : 1: remove_dup_value 0.11% : 0.000686s : 1: renormalize.infer 0.07% : 0.000422s : 1: renormalize.specialize 0.03% : 0.000153s : 1: rewriter_after_jit_bprop_graph 0.09% : 0.000550s : 1: rewriter_after_opt_a 0.04% : 0.000222s : 1: rewriter_before_opt_a 0.02% : 0.000104s : 1: symbol_engine_optimizer 78.11% : 0.476501s : 1: type_inference TotalTime = 0.588044, [30] [bootstrap]: 0.00050722 [type_inference]: 0.243487 [event_method]: 0.00021712 [auto_monad]: 0.00033655 [graph_reusing]: 1.001e-05 [pre_auto_parallel]: 3.53e-06 [py_interpret_to_execute]: 6.554e-05 [rewriter_before_opt_a]: 0.00016664 [expand_dump_flag]: 4.57998e-06 [jit_opt_a]: 0.307025, [4] [Cycle 1]: 0.251252, [27] [switch_simplify]: 0.00024859 [loop_unroll]: 6.138e-05 [a_1]: 0.0015896 [with_stream_mark]: 5.181e-05 [recompute_prepare]: 3.448e-05 [updatestate_depend_eliminate]: 1.536e-05 [updatestate_assign_eliminate]: 1.101e-05 [updatestate_loads_eliminate]: 1.065e-05 [parameter_eliminate]: 3.99002e-06 [specialize_transform]: 2.078e-05 [updatestate_useless_node_eliminater]: 2.473e-05 [accelerated_algorithm]: 1.974e-05 [meta_shard_fg_expand]: 7.4e-06 [get_grad_eliminate_]: 1.966e-05 [merge_forward]: 1.306e-05 [cell_reuse_recompute_pass]: 1.64e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.107e-05 [j_node_and_user_rematch]: 4.663e-05 [meta_fg_expand]: 0.168272 [replace_old_param]: 0.00014715 [inline_without_move]: 0.00013499 [renormalize]: 0.079326 [add_forward_monad_depend]: 3.382e-05 [auto_monad_grad]: 1.781e-05 [auto_monad_eliminator]: 0.00014431 [cse]: 0.0003457 [replace_applicator]: 0.00024262 [Cycle 2]: 0.0482901, [27] [switch_simplify]: 0.00010295 [loop_unroll]: 9.699e-05 [a_1]: 0.0445294 [with_stream_mark]: 6.185e-05 [recompute_prepare]: 4e-05 [updatestate_depend_eliminate]: 1.779e-05 [updatestate_assign_eliminate]: 1.646e-05 [updatestate_loads_eliminate]: 1.556e-05 [parameter_eliminate]: 5.79e-06 [specialize_transform]: 2.565e-05 [updatestate_useless_node_eliminater]: 0.00010654 [accelerated_algorithm]: 3.699e-05 [meta_shard_fg_expand]: 8.27003e-06 [get_grad_eliminate_]: 1.66e-05 [merge_forward]: 1.001e-05 [cell_reuse_recompute_pass]: 1.57999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.473e-05 [j_node_and_user_rematch]: 2.488e-05 [meta_fg_expand]: 0.00022959 [replace_old_param]: 2.753e-05 [inline_without_move]: 1.495e-05 [renormalize]: 0.00232117 [add_forward_monad_depend]: 1.098e-05 [auto_monad_grad]: 2.98e-06 [auto_monad_eliminator]: 3.918e-05 [cse]: 0.0001769 [replace_applicator]: 3.222e-05 [Cycle 3]: 0.00214359, [27] [switch_simplify]: 1.709e-05 [loop_unroll]: 1.49e-05 [a_1]: 0.00033974 [with_stream_mark]: 2.374e-05 [recompute_prepare]: 1.487e-05 [updatestate_depend_eliminate]: 4.027e-05 [updatestate_assign_eliminate]: 8.33999e-06 [updatestate_loads_eliminate]: 7.18e-06 [parameter_eliminate]: 3.24001e-06 [specialize_transform]: 1.554e-05 [updatestate_useless_node_eliminater]: 1.572e-05 [accelerated_algorithm]: 1.898e-05 [meta_shard_fg_expand]: 3.59002e-06 [get_grad_eliminate_]: 1.201e-05 [merge_forward]: 7.58001e-06 [cell_reuse_recompute_pass]: 3.26001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.936e-05 [j_node_and_user_rematch]: 1.97e-05 [meta_fg_expand]: 5.67999e-06 [replace_old_param]: 1.639e-05 [inline_without_move]: 1.167e-05 [renormalize]: 0.00113713 [add_forward_monad_depend]: 8.57e-06 [auto_monad_grad]: 2.81999e-06 [auto_monad_eliminator]: 3.097e-05 [cse]: 0.00011303 [replace_applicator]: 3.023e-05 [Cycle 4]: 0.00076256, [27] [switch_simplify]: 1.436e-05 [loop_unroll]: 1.195e-05 [a_1]: 0.00027502 [with_stream_mark]: 2.38e-05 [recompute_prepare]: 1.453e-05 [updatestate_depend_eliminate]: 8.57e-06 [updatestate_assign_eliminate]: 6.91001e-06 [updatestate_loads_eliminate]: 7.80998e-06 [parameter_eliminate]: 1.90001e-06 [specialize_transform]: 1.465e-05 [updatestate_useless_node_eliminater]: 1.608e-05 [accelerated_algorithm]: 1.711e-05 [meta_shard_fg_expand]: 4.72998e-06 [get_grad_eliminate_]: 1.144e-05 [merge_forward]: 8.2e-06 [cell_reuse_recompute_pass]: 2.37001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.746e-05 [j_node_and_user_rematch]: 1.998e-05 [meta_fg_expand]: 4.99e-06 [replace_old_param]: 1.558e-05 [inline_without_move]: 1.615e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.17001e-06 [auto_monad_grad]: 2.53e-06 [auto_monad_eliminator]: 2.356e-05 [cse]: 4.612e-05 [replace_applicator]: 1.66e-05 [py_interpret_to_execute_after_opt_a]: 2.676e-05 [rewriter_after_opt_a]: 0.00024446 [convert_after_rewriter]: 1.766e-05 [order_py_execute_after_rewriter]: 9.92001e-06 [mutable_eliminate]: 0.00084681 [jit_opt_b]: 0.00010133, [1] [Cycle 1]: 9.155e-05, [2] [frontend_op_eliminate]: 3.922e-05 [inline_after_opt_a]: 3.831e-05 [cconv]: 4.516e-05 [loop_unroll]: 0.00049901 [jit_opt_after_cconv]: 0.0324887, [1] [Cycle 1]: 0.0324747, [11] [c_1]: 7.227e-05 [parameter_eliminate]: 5.39998e-06 [updatestate_depend_eliminate]: 1.716e-05 [updatestate_assign_eliminate]: 7.82998e-06 [updatestate_loads_eliminate]: 7.43999e-06 [cse]: 7.971e-05 [call_graph_tuple_transform]: 3.513e-05 [tuple_list_get_item_eliminator]: 1.29e-05 [none_parameter_eliminate]: 1.96998e-06 [renormalize]: 3.39991e-07 [switch_simplify]: 0.032125 [remove_dup_value]: 0.00015111 [partial_unused_args_eliminate]: 8.40001e-06 [environ_conv]: 2.304e-05 [add_recomputation]: 0.00014331 [cse_after_recomputation]: 9.469e-05, [1] [Cycle 1]: 7.963e-05, [1] [cse]: 6.261e-05 [auto_monad_reorder]: 4.273e-05 [get_jit_bprop_graph]: 2.48e-06 [rewriter_after_jit_bprop_graph]: 1.137e-05 [opt_after_jit_grad]: 0.00092119 [symbol_engine_optimizer]: 0.00015496, [1] [Cycle 1]: 0.00014684, [6] [build]: 2.068e-05 [elim_shapecalc]: 1.754e-05 [elim_not_effective]: 3.528e-05 [opt_reshape]: 1.508e-05 [fold_const_symbol]: 2.199e-05 [renormalize]: 1.21002e-06 [validate]: 7.334e-05 Sums bootstrap : 0.000507s : 0.09% type_inference : 0.243487s : 41.84% event_method : 0.000217s : 0.04% auto_monad : 0.000337s : 0.06% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000066s : 0.01% rewriter_before_opt_a : 0.000167s : 0.03% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000383s : 0.07% jit_opt_a.loop_unroll : 0.000185s : 0.03% jit_opt_a.a_1 : 0.046734s : 8.03% jit_opt_a.with_stream_mark : 0.000161s : 0.03% jit_opt_a.recompute_prepare : 0.000104s : 0.02% jit_opt_a.updatestate_depend_eliminate : 0.000082s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000043s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000041s : 0.01% jit_opt_a.parameter_eliminate : 0.000015s : 0.00% jit_opt_a.specialize_transform : 0.000077s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000163s : 0.03% jit_opt_a.accelerated_algorithm : 0.000093s : 0.02% jit_opt_a.meta_shard_fg_expand : 0.000024s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000060s : 0.01% jit_opt_a.merge_forward : 0.000039s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000133s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000111s : 0.02% jit_opt_a.meta_fg_expand : 0.168512s : 28.96% jit_opt_a.replace_old_param : 0.000207s : 0.04% jit_opt_a.inline_without_move : 0.000178s : 0.03% jit_opt_a.renormalize : 0.082784s : 14.23% jit_opt_a.add_forward_monad_depend : 0.000056s : 0.01% jit_opt_a.auto_monad_grad : 0.000026s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000238s : 0.04% jit_opt_a.cse : 0.000682s : 0.12% jit_opt_a.replace_applicator : 0.000322s : 0.06% py_interpret_to_execute_after_opt_a : 0.000027s : 0.00% rewriter_after_opt_a : 0.000244s : 0.04% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000847s : 0.15% jit_opt_b.frontend_op_eliminate : 0.000039s : 0.01% jit_opt_b.inline_after_opt_a : 0.000038s : 0.01% cconv : 0.000045s : 0.01% loop_unroll : 0.000499s : 0.09% jit_opt_after_cconv.c_1 : 0.000072s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 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 : 0.000080s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000035s : 0.01% 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 : 0.032125s : 5.52% remove_dup_value : 0.000151s : 0.03% partial_unused_args_eliminate : 0.000008s : 0.00% environ_conv : 0.000023s : 0.00% add_recomputation : 0.000143s : 0.02% cse_after_recomputation.cse : 0.000063s : 0.01% auto_monad_reorder : 0.000043s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000011s : 0.00% opt_after_jit_grad : 0.000921s : 0.16% symbol_engine_optimizer.build : 0.000021s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000018s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000035s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000015s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000022s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000073s : 0.01% Time group info: ------[substitution.] 0.003357 291 1.47% : 0.000049s : 12: substitution.depend_value_elim 0.15% : 0.000005s : 7: substitution.elim_not_effective 0.10% : 0.000003s : 7: substitution.fold_const_symbol 26.46% : 0.000888s : 4: substitution.getattr_setattr_resolve 0.30% : 0.000010s : 8: substitution.graph_param_transform 53.03% : 0.001780s : 28: substitution.inline 1.33% : 0.000045s : 4: substitution.inline_without_move 0.91% : 0.000031s : 35: substitution.j_node_and_user_rematch 0.68% : 0.000023s : 3: substitution.less_batch_normalization 0.72% : 0.000024s : 13: substitution.minmaximum_grad 1.34% : 0.000045s : 14: substitution.partial_eliminate 0.78% : 0.000026s : 35: substitution.remove_not_recompute_node 2.68% : 0.000090s : 16: substitution.replace_applicator 0.71% : 0.000024s : 19: substitution.replace_old_param 0.25% : 0.000009s : 2: substitution.set_cell_output_no_recompute 0.50% : 0.000017s : 3: substitution.switch_simplify 1.47% : 0.000049s : 13: substitution.tuple_list_convert_item_index_to_positive 1.07% : 0.000036s : 13: substitution.tuple_list_get_item_depend_reorder 3.32% : 0.000111s : 30: substitution.tuple_list_get_item_eliminator 0.81% : 0.000027s : 9: substitution.updatestate_pure_node_eliminater 1.93% : 0.000065s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.243353 2 98.63% : 0.240022s : 1: type_inference.infer 1.37% : 0.003331s : 1: type_inference.specialize ------[replace.] 0.001005 53 7.42% : 0.000075s : 3: replace.getattr_setattr_resolve 52.76% : 0.000530s : 28: replace.inline 3.84% : 0.000039s : 1: replace.replace_applicator 8.16% : 0.000082s : 3: replace.switch_simplify 21.93% : 0.000220s : 17: replace.tuple_list_get_item_eliminator 5.89% : 0.000059s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002664 53 30.38% : 0.000809s : 3: match.getattr_setattr_resolve 66.12% : 0.001761s : 28: match.inline 0.59% : 0.000016s : 1: match.replace_applicator 0.56% : 0.000015s : 3: match.switch_simplify 1.80% : 0.000048s : 17: match.tuple_list_get_item_eliminator 0.55% : 0.000015s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001023 5919 1.50% : 0.000015s : 99: predicate.accumulaten_eliminater 0.42% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.31% : 0.000013s : 99: predicate.addn_check_dump 1.45% : 0.000015s : 99: predicate.addn_zero_filter 2.21% : 0.000023s : 99: predicate.arithmetic_simplify 1.69% : 0.000017s : 99: predicate.cast_eliminate 0.13% : 0.000001s : 8: predicate.check_bprop_eliminate 1.27% : 0.000013s : 99: predicate.compare_switch_simplify 1.63% : 0.000017s : 99: predicate.depend_value_elim 1.42% : 0.000014s : 99: predicate.dict_get_item_const_eliminator 1.47% : 0.000015s : 99: predicate.dict_get_item_eliminator 1.44% : 0.000015s : 99: predicate.dict_set_item_eliminator 0.22% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.14% : 0.000001s : 8: predicate.elim_not_effective 0.21% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.39% : 0.000014s : 99: predicate.environ_add_const_eliminate 1.39% : 0.000014s : 99: predicate.environ_get_add_eliminate 1.32% : 0.000014s : 99: predicate.environ_get_depend_swap 1.46% : 0.000015s : 99: predicate.environ_get_eliminate 1.36% : 0.000014s : 99: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.78% : 0.000008s : 42: predicate.get_grad_eliminate 0.78% : 0.000008s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000001s : 8: predicate.graph_param_transform 4.42% : 0.000045s : 160: predicate.inline 1.92% : 0.000020s : 106: predicate.inline_without_move 0.29% : 0.000003s : 42: predicate.j_node_and_user_rematch 1.07% : 0.000011s : 42: predicate.less_batch_normalization 1.76% : 0.000018s : 116: predicate.list_to_tuple_eliminator_ 1.94% : 0.000020s : 124: predicate.load_eliminater 0.33% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.68% : 0.000027s : 171: predicate.loop_unroll_before_grad 2.04% : 0.000021s : 107: predicate.make_slice_get_slice_eliminator 1.30% : 0.000013s : 99: predicate.merge_addn 1.34% : 0.000014s : 99: predicate.minmaximum_grad 0.56% : 0.000006s : 8: predicate.mutable_eliminate 0.18% : 0.000002s : 8: predicate.opt_reshape 2.32% : 0.000024s : 124: predicate.partial_eliminate 1.29% : 0.000013s : 99: predicate.print_const_string_wrapper 1.89% : 0.000019s : 99: predicate.reduce_eliminate 1.72% : 0.000018s : 116: predicate.redundant_stop_gradient_eliminater 0.46% : 0.000005s : 42: predicate.remove_not_recompute_node 2.46% : 0.000025s : 236: predicate.replace_applicator 0.97% : 0.000010s : 106: predicate.replace_old_param 0.12% : 0.000001s : 8: predicate.reset_defer_inline 1.46% : 0.000015s : 99: predicate.reshape_eliminate 1.39% : 0.000014s : 99: predicate.row_tensor_add_zeros_like 0.27% : 0.000003s : 8: predicate.row_tensor_eliminate 1.36% : 0.000014s : 99: predicate.same_eliminate 0.47% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.31% : 0.000003s : 16: predicate.special_op_eliminate 0.91% : 0.000009s : 50: predicate.specialize_transform 1.69% : 0.000017s : 99: predicate.split_environ_get_set_with_tuple_value 1.38% : 0.000014s : 99: predicate.stack_unstack_eliminate 0.15% : 0.000002s : 8: predicate.switch_call_monad_eliminater 3.65% : 0.000037s : 144: predicate.switch_defer_inline 2.42% : 0.000025s : 144: predicate.switch_layer_defer_inline 7.29% : 0.000075s : 329: predicate.switch_simplify 1.33% : 0.000014s : 99: predicate.tile_eliminate 1.48% : 0.000015s : 99: predicate.transpose_eliminate 1.79% : 0.000018s : 99: predicate.tuple_list_convert_item_index_to_positive 1.70% : 0.000017s : 99: predicate.tuple_list_get_item_depend_reorder 3.31% : 0.000034s : 132: predicate.tuple_list_get_item_eliminator 2.70% : 0.000028s : 99: predicate.tuple_list_set_item_eliminator 1.71% : 0.000017s : 116: predicate.tuple_to_list_eliminator_ 1.82% : 0.000019s : 124: predicate.updatestate_pure_node_eliminater 2.84% : 0.000029s : 168: predicate.updatestate_useless_node_eliminater 2.04% : 0.000021s : 99: predicate.value_based_eliminate 0.13% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.19% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.005567 58 55.42% : 0.003085s : 22: func_graph_cloner_run.FuncGraphClonerGraph 9.77% : 0.000544s : 7: func_graph_cloner_run.FuncGraphClonerNode 34.81% : 0.001938s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.752799 104 0.02% : 0.000149s : 1: add_recomputation 0.05% : 0.000346s : 1: auto_monad 0.01% : 0.000046s : 1: auto_monad_reorder 0.07% : 0.000548s : 1: bootstrap 0.01% : 0.000048s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.01% : 0.000097s : 1: cse_after_recomputation 0.00% : 0.000026s : 1: environ_conv 0.03% : 0.000230s : 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 40.79% : 0.307033s : 1: jit_opt_a 4.32% : 0.032497s : 1: jit_opt_after_cconv 0.01% : 0.000105s : 1: jit_opt_b 0.07% : 0.000508s : 1: loop_unroll 0.11% : 0.000860s : 1: mutable_eliminate 6.46% : 0.048648s : 52: opt.transform.jit_opt_a 4.28% : 0.032237s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000068s : 4: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000032s : 1: opt.transform.mutable_eliminate 0.01% : 0.000057s : 1: opt.transform.opt_after_jit_grad 0.14% : 0.001034s : 2: opt.transform.opt_resolve 0.01% : 0.000085s : 4: opt.transform.symbol_engine_opt 0.12% : 0.000934s : 1: opt_after_jit_grad 0.00% : 0.000013s : 1: order_py_execute_after_rewriter 0.00% : 0.000011s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000069s : 1: py_interpret_to_execute 0.00% : 0.000030s : 1: py_interpret_to_execute_after_opt_a 0.02% : 0.000160s : 1: remove_dup_value 10.25% : 0.077155s : 3: renormalize.infer 0.74% : 0.005590s : 3: renormalize.specialize 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000252s : 1: rewriter_after_opt_a 0.02% : 0.000171s : 1: rewriter_before_opt_a 0.02% : 0.000158s : 1: symbol_engine_optimizer 32.35% : 0.243511s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_special_values[inf-KBK] tests/st/mint/test_select.py::test_select_special_values[inf-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[nan-pynative] tests/st/mint/test_select.py::test_select_special_values[nan-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[nan-KBK] tests/st/mint/test_select.py::test_select_special_values[nan-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[zero-pynative] tests/st/mint/test_select.py::test_select_special_values[zero-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[zero-KBK] tests/st/mint/test_select.py::test_select_special_values[zero-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[large-pynative] tests/st/mint/test_select.py::test_select_special_values[large-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[large-KBK] tests/st/mint/test_select.py::test_select_special_values[large-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[small-pynative] tests/st/mint/test_select.py::test_select_special_values[small-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_select_special_values[small-KBK] tests/st/mint/test_select.py::test_select_special_values[small-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 ================= 10 passed, 25 warnings in 168.20s (0:02:48) ==================