==================================================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_001/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_squeeze.py . [hook] pytest_runtest_teardown:test_squeeze_functional_interface[pynative] tests/st/mint/test_squeeze.py::test_squeeze_functional_interface[pynative],max_mem:2.0M [WARNING] PARSER(170078,ffff96b55f30,python3.9):2026-01-29-17:41:41.498.255 [mindspore/ccsrc/frontend/jit/ps/parse/data_converter.cc:661] CheckAPI] The mint interface squeeze was called, and the operators under this interface have different view capabilities on pynative and graph mode. Use this interface with caution in graph mode, as it may produce unexpected results. For more information, please refer to: https://www.mindspore.cn/docs/en/master/features/view.html TotalTime = 2.05704, [30] [bootstrap]: 0.00099486 [type_inference]: 2.03612 [event_method]: 2.351e-05 [auto_monad]: 0.00011031 [graph_reusing]: 7.45e-06 [pre_auto_parallel]: 1.8e-05 [py_interpret_to_execute]: 0.00097812 [rewriter_before_opt_a]: 0.00022793 [expand_dump_flag]: 4.47e-06 [jit_opt_a]: 0.0151114, [2] [Cycle 1]: 0.00455008, [27] [switch_simplify]: 0.0001639 [loop_unroll]: 3.085e-05 [a_1]: 0.00060594 [with_stream_mark]: 3.183e-05 [recompute_prepare]: 1.174e-05 [updatestate_depend_eliminate]: 5.27999e-06 [updatestate_assign_eliminate]: 3.70998e-06 [updatestate_loads_eliminate]: 3.27002e-06 [parameter_eliminate]: 2.07001e-06 [specialize_transform]: 8.67e-06 [updatestate_useless_node_eliminater]: 6.58998e-06 [accelerated_algorithm]: 7.38e-06 [meta_shard_fg_expand]: 2.87002e-06 [get_grad_eliminate_]: 7.01001e-06 [merge_forward]: 4.22e-06 [cell_reuse_recompute_pass]: 1.32999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.347e-05 [j_node_and_user_rematch]: 1.287e-05 [meta_fg_expand]: 2.49999e-06 [replace_old_param]: 1.226e-05 [inline_without_move]: 6.59999e-06 [renormalize]: 0.00313467 [add_forward_monad_depend]: 1.131e-05 [auto_monad_grad]: 2.89001e-06 [auto_monad_eliminator]: 2.358e-05 [cse]: 5.985e-05 [replace_applicator]: 2.663e-05 [Cycle 2]: 0.00045838, [27] [switch_simplify]: 8.27e-06 [loop_unroll]: 7.38999e-06 [a_1]: 0.00014336 [with_stream_mark]: 2.273e-05 [recompute_prepare]: 7.95e-06 [updatestate_depend_eliminate]: 4.37998e-06 [updatestate_assign_eliminate]: 3.93001e-06 [updatestate_loads_eliminate]: 3.12002e-06 [parameter_eliminate]: 2.28002e-06 [specialize_transform]: 6.83998e-06 [updatestate_useless_node_eliminater]: 6.23e-06 [accelerated_algorithm]: 6.84001e-06 [meta_shard_fg_expand]: 2.16e-06 [get_grad_eliminate_]: 6.10002e-06 [merge_forward]: 3.90998e-06 [cell_reuse_recompute_pass]: 3.29001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.227e-05 [j_node_and_user_rematch]: 1.088e-05 [meta_fg_expand]: 2.48e-06 [replace_old_param]: 1.131e-05 [inline_without_move]: 6.54999e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.35999e-06 [auto_monad_grad]: 1.66e-06 [auto_monad_eliminator]: 7.65e-06 [cse]: 1.633e-05 [replace_applicator]: 7.61999e-06 [py_interpret_to_execute_after_opt_a]: 1.807e-05 [rewriter_after_opt_a]: 0.00026977 [convert_after_rewriter]: 7.313e-05 [order_py_execute_after_rewriter]: 7.55e-06 [mutable_eliminate]: 0.00078855 [jit_opt_b]: 7.074e-05, [1] [Cycle 1]: 6.088e-05, [2] [frontend_op_eliminate]: 2.444e-05 [inline_after_opt_a]: 2.068e-05 [cconv]: 0.0001126 [loop_unroll]: 0.00049638 [jit_opt_after_cconv]: 0.00022447, [1] [Cycle 1]: 0.00021647, [11] [c_1]: 2.946e-05 [parameter_eliminate]: 5.89e-06 [updatestate_depend_eliminate]: 1.016e-05 [updatestate_assign_eliminate]: 3.5e-06 [updatestate_loads_eliminate]: 1.87e-05 [cse]: 4.127e-05 [call_graph_tuple_transform]: 2.981e-05 [tuple_list_get_item_eliminator]: 7.41001e-06 [none_parameter_eliminate]: 1.59e-06 [renormalize]: 7.7e-07 [switch_simplify]: 7.89002e-06 [remove_dup_value]: 1.845e-05 [partial_unused_args_eliminate]: 2.24001e-06 [environ_conv]: 2.902e-05 [add_recomputation]: 6.419e-05 [cse_after_recomputation]: 2.848e-05, [1] [Cycle 1]: 2.141e-05, [1] [cse]: 1.505e-05 [auto_monad_reorder]: 2.522e-05 [get_jit_bprop_graph]: 2.56e-06 [rewriter_after_jit_bprop_graph]: 5.62999e-06 [opt_after_jit_grad]: 0.00054068 [symbol_engine_optimizer]: 9.186e-05, [1] [Cycle 1]: 8.411e-05, [6] [build]: 4.90999e-06 [elim_shapecalc]: 1.034e-05 [elim_not_effective]: 1.748e-05 [opt_reshape]: 7.71001e-06 [fold_const_symbol]: 1.124e-05 [renormalize]: 7.2e-07 [validate]: 8.402e-05 Sums bootstrap : 0.000995s : 0.05% type_inference : 2.036121s : 99.53% event_method : 0.000024s : 0.00% auto_monad : 0.000110s : 0.01% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000018s : 0.00% py_interpret_to_execute : 0.000978s : 0.05% rewriter_before_opt_a : 0.000228s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000172s : 0.01% jit_opt_a.loop_unroll : 0.000038s : 0.00% jit_opt_a.a_1 : 0.000749s : 0.04% jit_opt_a.with_stream_mark : 0.000055s : 0.00% jit_opt_a.recompute_prepare : 0.000020s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000016s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000013s : 0.00% jit_opt_a.accelerated_algorithm : 0.000014s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000013s : 0.00% jit_opt_a.merge_forward : 0.000008s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000046s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000024s : 0.00% jit_opt_a.meta_fg_expand : 0.000005s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000013s : 0.00% jit_opt_a.renormalize : 0.003135s : 0.15% jit_opt_a.add_forward_monad_depend : 0.000013s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000031s : 0.00% jit_opt_a.cse : 0.000076s : 0.00% jit_opt_a.replace_applicator : 0.000034s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000270s : 0.01% convert_after_rewriter : 0.000073s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000789s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000024s : 0.00% jit_opt_b.inline_after_opt_a : 0.000021s : 0.00% cconv : 0.000113s : 0.01% loop_unroll : 0.000496s : 0.02% jit_opt_after_cconv.c_1 : 0.000029s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000019s : 0.00% jit_opt_after_cconv.cse : 0.000041s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000007s : 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 : 0.000008s : 0.00% remove_dup_value : 0.000018s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000029s : 0.00% add_recomputation : 0.000064s : 0.00% cse_after_recomputation.cse : 0.000015s : 0.00% auto_monad_reorder : 0.000025s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000541s : 0.03% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000017s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000084s : 0.00% Time group info: ------[substitution.] 0.000237 23 1.10% : 0.000003s : 2: substitution.elim_not_effective 0.70% : 0.000002s : 2: substitution.fold_const_symbol 3.20% : 0.000008s : 4: substitution.graph_param_transform 82.80% : 0.000196s : 4: substitution.inline 2.02% : 0.000005s : 4: substitution.j_node_and_user_rematch 2.37% : 0.000006s : 4: substitution.remove_not_recompute_node 3.02% : 0.000007s : 2: substitution.replace_old_param 4.79% : 0.000011s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 2.035948 2 99.85% : 2.032960s : 1: type_inference.infer 0.15% : 0.002988s : 1: type_inference.specialize ------[replace.] 0.000058 5 82.98% : 0.000048s : 4: replace.inline 17.02% : 0.000010s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000204 5 94.96% : 0.000194s : 4: match.inline 5.04% : 0.000010s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000154 801 1.26% : 0.000002s : 12: predicate.accumulaten_eliminater 1.07% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 1.22% : 0.000002s : 12: predicate.addn_check_dump 1.23% : 0.000002s : 12: predicate.addn_zero_filter 2.24% : 0.000003s : 12: predicate.arithmetic_simplify 1.28% : 0.000002s : 12: predicate.cast_eliminate 0.50% : 0.000001s : 4: predicate.check_bprop_eliminate 1.12% : 0.000002s : 12: predicate.compare_switch_simplify 1.04% : 0.000002s : 12: predicate.depend_value_elim 1.31% : 0.000002s : 12: predicate.dict_get_item_const_eliminator 1.27% : 0.000002s : 12: predicate.dict_get_item_eliminator 1.13% : 0.000002s : 12: predicate.dict_set_item_eliminator 0.79% : 0.000001s : 4: predicate.dumpgradient_eliminate 0.62% : 0.000001s : 4: predicate.elim_not_effective 0.51% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.32% : 0.000002s : 12: predicate.environ_add_const_eliminate 1.13% : 0.000002s : 12: predicate.environ_get_add_eliminate 1.06% : 0.000002s : 12: predicate.environ_get_depend_swap 1.69% : 0.000003s : 12: predicate.environ_get_eliminate 1.01% : 0.000002s : 12: predicate.environ_get_set_eliminate 0.28% : 0.000000s : 4: predicate.fold_const_symbol 1.17% : 0.000002s : 8: predicate.get_grad_eliminate 0.38% : 0.000001s : 4: predicate.graph_param_transform 5.37% : 0.000008s : 25: predicate.inline 0.92% : 0.000001s : 8: predicate.inline_without_move 0.44% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.27% : 0.000002s : 8: predicate.less_batch_normalization 1.58% : 0.000002s : 13: predicate.list_to_tuple_eliminator_ 1.77% : 0.000003s : 17: predicate.load_eliminater 1.60% : 0.000002s : 4: predicate.loop_unroll_after_grad 3.77% : 0.000006s : 28: predicate.loop_unroll_before_grad 1.83% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.98% : 0.000002s : 12: predicate.merge_addn 1.04% : 0.000002s : 12: predicate.minmaximum_grad 2.12% : 0.000003s : 4: predicate.mutable_eliminate 0.55% : 0.000001s : 4: predicate.opt_reshape 1.94% : 0.000003s : 17: predicate.partial_eliminate 1.15% : 0.000002s : 12: predicate.print_const_string_wrapper 1.71% : 0.000003s : 12: predicate.reduce_eliminate 1.45% : 0.000002s : 13: predicate.redundant_stop_gradient_eliminater 0.65% : 0.000001s : 8: predicate.remove_not_recompute_node 2.08% : 0.000003s : 21: predicate.replace_applicator 0.87% : 0.000001s : 8: predicate.replace_old_param 0.73% : 0.000001s : 4: predicate.reset_defer_inline 1.25% : 0.000002s : 12: predicate.reshape_eliminate 1.28% : 0.000002s : 12: predicate.row_tensor_add_zeros_like 0.76% : 0.000001s : 4: predicate.row_tensor_eliminate 1.25% : 0.000002s : 12: predicate.same_eliminate 0.60% : 0.000001s : 8: predicate.set_cell_output_no_recompute 1.41% : 0.000002s : 8: predicate.special_op_eliminate 0.93% : 0.000001s : 8: predicate.specialize_transform 1.48% : 0.000002s : 12: predicate.split_environ_get_set_with_tuple_value 1.16% : 0.000002s : 12: predicate.stack_unstack_eliminate 0.54% : 0.000001s : 4: predicate.switch_call_monad_eliminater 2.11% : 0.000003s : 17: predicate.switch_defer_inline 2.10% : 0.000003s : 17: predicate.switch_layer_defer_inline 6.68% : 0.000010s : 49: predicate.switch_simplify 1.22% : 0.000002s : 12: predicate.tile_eliminate 1.26% : 0.000002s : 12: predicate.transpose_eliminate 1.36% : 0.000002s : 12: predicate.tuple_list_convert_item_index_to_positive 1.36% : 0.000002s : 12: predicate.tuple_list_get_item_depend_reorder 4.03% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.75% : 0.000003s : 12: predicate.tuple_list_set_item_eliminator 1.45% : 0.000002s : 13: predicate.tuple_to_list_eliminator_ 1.94% : 0.000003s : 17: predicate.updatestate_pure_node_eliminater 2.75% : 0.000004s : 25: predicate.updatestate_useless_node_eliminater 1.63% : 0.000003s : 12: predicate.value_based_eliminate 0.34% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.89% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003435 18 76.28% : 0.002620s : 12: func_graph_cloner_run.FuncGraphClonerGraph 23.72% : 0.000815s : 6: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.061037 72 0.00% : 0.000067s : 1: add_recomputation 0.01% : 0.000114s : 1: auto_monad 0.00% : 0.000028s : 1: auto_monad_reorder 0.05% : 0.001027s : 1: bootstrap 0.01% : 0.000117s : 1: cconv 0.00% : 0.000077s : 1: convert_after_rewriter 0.00% : 0.000031s : 1: cse_after_recomputation 0.00% : 0.000032s : 1: environ_conv 0.00% : 0.000029s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 0.73% : 0.015116s : 1: jit_opt_a 0.01% : 0.000228s : 1: jit_opt_after_cconv 0.00% : 0.000074s : 1: jit_opt_b 0.02% : 0.000508s : 1: loop_unroll 0.04% : 0.000804s : 1: mutable_eliminate 0.05% : 0.001032s : 26: opt.transform.jit_opt_a 0.00% : 0.000070s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000037s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000022s : 1: opt.transform.mutable_eliminate 0.00% : 0.000027s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000043s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000551s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000020s : 1: pre_auto_parallel 0.05% : 0.000993s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000021s : 1: remove_dup_value 0.11% : 0.002164s : 1: renormalize.infer 0.05% : 0.000957s : 1: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000277s : 1: rewriter_after_opt_a 0.01% : 0.000236s : 1: rewriter_before_opt_a 0.00% : 0.000095s : 1: symbol_engine_optimizer 98.79% : 2.036154s : 1: type_inference . [hook] pytest_runtest_teardown:test_squeeze_functional_interface[KBK] tests/st/mint/test_squeeze.py::test_squeeze_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 293.40s (0:04:53) ==================