==================================================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_004/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_functional_interface[pynative] tests/st/mint/test_select.py::test_select_functional_interface[pynative],max_mem:2.0M TotalTime = 0.807568, [30] [bootstrap]: 0.0006842 [type_inference]: 0.643124 [event_method]: 1.625e-05 [auto_monad]: 0.00016977 [graph_reusing]: 6.51e-06 [pre_auto_parallel]: 1.175e-05 [py_interpret_to_execute]: 0.00010578 [rewriter_before_opt_a]: 7.313e-05 [expand_dump_flag]: 3.13e-06 [jit_opt_a]: 0.159955, [2] [Cycle 1]: 0.00238503, [27] [switch_simplify]: 7.375e-05 [loop_unroll]: 2.167e-05 [a_1]: 0.00051096 [with_stream_mark]: 3.288e-05 [recompute_prepare]: 1.323e-05 [updatestate_depend_eliminate]: 7.73001e-06 [updatestate_assign_eliminate]: 7.48e-06 [updatestate_loads_eliminate]: 5.57001e-06 [parameter_eliminate]: 2.37999e-06 [specialize_transform]: 1.127e-05 [updatestate_useless_node_eliminater]: 1.363e-05 [accelerated_algorithm]: 9.91e-06 [meta_shard_fg_expand]: 4.1e-06 [get_grad_eliminate_]: 8.42e-06 [merge_forward]: 5.83997e-06 [cell_reuse_recompute_pass]: 1.75001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.654e-05 [j_node_and_user_rematch]: 1.452e-05 [meta_fg_expand]: 3.7e-06 [replace_old_param]: 1.296e-05 [inline_without_move]: 8.62e-06 [renormalize]: 0.00119639 [add_forward_monad_depend]: 1.585e-05 [auto_monad_grad]: 2.88e-06 [auto_monad_eliminator]: 2.6e-05 [cse]: 5.508e-05 [replace_applicator]: 2.404e-05 [Cycle 2]: 0.00051762, [27] [switch_simplify]: 9.69999e-06 [loop_unroll]: 7.98999e-06 [a_1]: 0.0001808 [with_stream_mark]: 1.79e-05 [recompute_prepare]: 9.24e-06 [updatestate_depend_eliminate]: 5.97999e-06 [updatestate_assign_eliminate]: 4.84998e-06 [updatestate_loads_eliminate]: 4.50001e-06 [parameter_eliminate]: 2.17999e-06 [specialize_transform]: 8.49002e-06 [updatestate_useless_node_eliminater]: 1.047e-05 [accelerated_algorithm]: 8.29002e-06 [meta_shard_fg_expand]: 2.63998e-06 [get_grad_eliminate_]: 9.05999e-06 [merge_forward]: 5.57999e-06 [cell_reuse_recompute_pass]: 2.43e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.865e-05 [j_node_and_user_rematch]: 1.305e-05 [meta_fg_expand]: 3.23998e-06 [replace_old_param]: 1.148e-05 [inline_without_move]: 7.48e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.99e-06 [auto_monad_grad]: 9.50007e-07 [auto_monad_eliminator]: 1.241e-05 [cse]: 1.934e-05 [replace_applicator]: 8.37998e-06 [py_interpret_to_execute_after_opt_a]: 1.811e-05 [rewriter_after_opt_a]: 0.00047065 [convert_after_rewriter]: 1.549e-05 [order_py_execute_after_rewriter]: 7.76001e-06 [mutable_eliminate]: 0.00081915 [jit_opt_b]: 7.498e-05, [1] [Cycle 1]: 6.69e-05, [2] [frontend_op_eliminate]: 2.575e-05 [inline_after_opt_a]: 2.64e-05 [cconv]: 3.899e-05 [loop_unroll]: 0.00047615 [jit_opt_after_cconv]: 0.00023059, [1] [Cycle 1]: 0.00022215, [11] [c_1]: 5.33e-05 [parameter_eliminate]: 5.50001e-06 [updatestate_depend_eliminate]: 1.27e-05 [updatestate_assign_eliminate]: 5.25999e-06 [updatestate_loads_eliminate]: 4.74998e-06 [cse]: 4.048e-05 [call_graph_tuple_transform]: 2.408e-05 [tuple_list_get_item_eliminator]: 8.54e-06 [none_parameter_eliminate]: 1.65001e-06 [renormalize]: 1.05001e-06 [switch_simplify]: 9.38997e-06 [remove_dup_value]: 2.489e-05 [partial_unused_args_eliminate]: 3.01001e-06 [environ_conv]: 2.672e-05 [add_recomputation]: 7.866e-05 [cse_after_recomputation]: 3.106e-05, [1] [Cycle 1]: 2.397e-05, [1] [cse]: 1.655e-05 [auto_monad_reorder]: 3.746e-05 [get_jit_bprop_graph]: 2.49001e-06 [rewriter_after_jit_bprop_graph]: 5.84e-06 [opt_after_jit_grad]: 0.00053886 [symbol_engine_optimizer]: 0.00010255, [1] [Cycle 1]: 9.466e-05, [6] [build]: 7.25e-06 [elim_shapecalc]: 1.159e-05 [elim_not_effective]: 1.978e-05 [opt_reshape]: 9.61e-06 [fold_const_symbol]: 1.382e-05 [renormalize]: 6.00005e-07 [validate]: 7.684e-05 Sums bootstrap : 0.000684s : 0.11% type_inference : 0.643124s : 99.00% event_method : 0.000016s : 0.00% auto_monad : 0.000170s : 0.03% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000106s : 0.02% rewriter_before_opt_a : 0.000073s : 0.01% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000083s : 0.01% jit_opt_a.loop_unroll : 0.000030s : 0.00% jit_opt_a.a_1 : 0.000692s : 0.11% jit_opt_a.with_stream_mark : 0.000051s : 0.01% jit_opt_a.recompute_prepare : 0.000022s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000024s : 0.00% jit_opt_a.accelerated_algorithm : 0.000018s : 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 : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000045s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000028s : 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 : 0.001196s : 0.18% jit_opt_a.add_forward_monad_depend : 0.000018s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000038s : 0.01% jit_opt_a.cse : 0.000074s : 0.01% jit_opt_a.replace_applicator : 0.000032s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000471s : 0.07% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000819s : 0.13% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.00% jit_opt_b.inline_after_opt_a : 0.000026s : 0.00% cconv : 0.000039s : 0.01% loop_unroll : 0.000476s : 0.07% jit_opt_after_cconv.c_1 : 0.000053s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000040s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 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 : 0.000025s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000027s : 0.00% add_recomputation : 0.000079s : 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 : 0.000006s : 0.00% opt_after_jit_grad : 0.000539s : 0.08% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 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 : 0.000077s : 0.01% Time group info: ------[substitution.] 0.000236 43 4.60% : 0.000011s : 2: substitution.depend_value_elim 1.11% : 0.000003s : 4: substitution.elim_not_effective 0.87% : 0.000002s : 4: substitution.fold_const_symbol 3.22% : 0.000008s : 5: substitution.graph_param_transform 71.95% : 0.000170s : 2: substitution.inline 2.09% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.44% : 0.000008s : 8: substitution.remove_not_recompute_node 2.61% : 0.000006s : 2: substitution.replace_old_param 5.38% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.73% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.643033 2 99.83% : 0.641937s : 1: type_inference.infer 0.17% : 0.001097s : 1: type_inference.specialize ------[replace.] 0.000036 2 100.00% : 0.000036s : 2: replace.inline ------[match.] 0.000168 2 100.00% : 0.000168s : 2: match.inline ------[predicate.] 0.000172 767 1.25% : 0.000002s : 11: predicate.accumulaten_eliminater 1.08% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.57% : 0.000003s : 11: predicate.addn_check_dump 1.59% : 0.000003s : 11: predicate.addn_zero_filter 2.04% : 0.000004s : 11: predicate.arithmetic_simplify 1.36% : 0.000002s : 11: predicate.cast_eliminate 0.58% : 0.000001s : 5: predicate.check_bprop_eliminate 1.02% : 0.000002s : 11: predicate.compare_switch_simplify 1.31% : 0.000002s : 11: predicate.depend_value_elim 1.24% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.27% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.13% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.28% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.45% : 0.000001s : 5: predicate.elim_not_effective 0.75% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.18% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.14% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.04% : 0.000002s : 11: predicate.environ_get_depend_swap 1.28% : 0.000002s : 11: predicate.environ_get_eliminate 0.99% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.26% : 0.000000s : 5: predicate.fold_const_symbol 1.42% : 0.000002s : 10: predicate.get_grad_eliminate 0.39% : 0.000001s : 5: predicate.graph_param_transform 4.74% : 0.000008s : 23: predicate.inline 0.99% : 0.000002s : 10: predicate.inline_without_move 0.45% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.59% : 0.000003s : 10: predicate.less_batch_normalization 1.06% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.97% : 0.000003s : 16: predicate.load_eliminater 1.31% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.20% : 0.000004s : 20: predicate.loop_unroll_before_grad 1.95% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.17% : 0.000002s : 11: predicate.merge_addn 1.06% : 0.000002s : 11: predicate.minmaximum_grad 2.07% : 0.000004s : 5: predicate.mutable_eliminate 0.76% : 0.000001s : 5: predicate.opt_reshape 1.83% : 0.000003s : 16: predicate.partial_eliminate 1.25% : 0.000002s : 11: predicate.print_const_string_wrapper 1.52% : 0.000003s : 11: predicate.reduce_eliminate 1.30% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.73% : 0.000001s : 10: predicate.remove_not_recompute_node 1.63% : 0.000003s : 21: predicate.replace_applicator 0.68% : 0.000001s : 10: predicate.replace_old_param 0.56% : 0.000001s : 5: predicate.reset_defer_inline 1.89% : 0.000003s : 11: predicate.reshape_eliminate 1.03% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.87% : 0.000001s : 5: predicate.row_tensor_eliminate 1.51% : 0.000003s : 11: predicate.same_eliminate 0.62% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.12% : 0.000002s : 10: predicate.special_op_eliminate 1.27% : 0.000002s : 10: predicate.specialize_transform 1.45% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.32% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.52% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.93% : 0.000003s : 13: predicate.switch_defer_inline 1.56% : 0.000003s : 13: predicate.switch_layer_defer_inline 6.26% : 0.000011s : 38: predicate.switch_simplify 1.30% : 0.000002s : 11: predicate.tile_eliminate 2.86% : 0.000005s : 11: predicate.transpose_eliminate 1.49% : 0.000003s : 11: predicate.tuple_list_convert_item_index_to_positive 1.44% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.69% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.51% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.32% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.97% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.69% : 0.000006s : 26: predicate.updatestate_useless_node_eliminater 1.74% : 0.000003s : 11: predicate.value_based_eliminate 0.42% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.78% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000351 5 6.83% : 0.000024s : 1: func_graph_cloner_run.FuncGraphClonerGraph 93.17% : 0.000327s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.809763 72 0.01% : 0.000083s : 1: add_recomputation 0.02% : 0.000175s : 1: auto_monad 0.01% : 0.000041s : 1: auto_monad_reorder 0.09% : 0.000711s : 1: bootstrap 0.01% : 0.000042s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000034s : 1: cse_after_recomputation 0.00% : 0.000030s : 1: environ_conv 0.00% : 0.000021s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 19.75% : 0.159959s : 1: jit_opt_a 0.03% : 0.000234s : 1: jit_opt_after_cconv 0.01% : 0.000078s : 1: jit_opt_b 0.06% : 0.000486s : 1: loop_unroll 0.10% : 0.000832s : 1: mutable_eliminate 0.12% : 0.000997s : 26: opt.transform.jit_opt_a 0.01% : 0.000091s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000017s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000025s : 1: opt.transform.mutable_eliminate 0.00% : 0.000034s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.07% : 0.000551s : 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% : 0.000014s : 1: pre_auto_parallel 0.01% : 0.000109s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000027s : 1: remove_dup_value 0.09% : 0.000751s : 1: renormalize.infer 0.05% : 0.000434s : 1: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.06% : 0.000477s : 1: rewriter_after_opt_a 0.01% : 0.000077s : 1: rewriter_before_opt_a 0.01% : 0.000105s : 1: symbol_engine_optimizer 79.42% : 0.643149s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_functional_interface[KBK] tests/st/mint/test_select.py::test_select_functional_interface[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 166.40s (0:02:46) ==================