[WARNING] ME(165611:281473373470512,MainProcess):2026-01-29-17:37:32.679.314 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. [WARNING] ME(165611:281473373470512,MainProcess):2026-01-29-17:37:32.680.354 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_id' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. ==================================================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/hyper_offload/memory_ops, configfile: ../../../../../../../sault/virtual_test/virtualenv_007/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 1 item test_copy_to_device.py TotalTime = 0.197468, [30] [bootstrap]: 0.00069847 [type_inference]: 0.1564 [event_method]: 1.568e-05 [auto_monad]: 0.00012819 [graph_reusing]: 6.21998e-06 [pre_auto_parallel]: 1.267e-05 [py_interpret_to_execute]: 2.566e-05 [rewriter_before_opt_a]: 7.122e-05 [expand_dump_flag]: 3.13e-06 [jit_opt_a]: 0.0367972, [2] [Cycle 1]: 0.00182277, [27] [switch_simplify]: 5.303e-05 [loop_unroll]: 1.531e-05 [a_1]: 0.00040771 [with_stream_mark]: 3.074e-05 [recompute_prepare]: 1.162e-05 [updatestate_depend_eliminate]: 7.81001e-06 [updatestate_assign_eliminate]: 4.625e-05 [updatestate_loads_eliminate]: 6.88998e-06 [parameter_eliminate]: 2.54999e-06 [specialize_transform]: 1.131e-05 [updatestate_useless_node_eliminater]: 1.42e-05 [accelerated_algorithm]: 1.003e-05 [meta_shard_fg_expand]: 2.78e-06 [get_grad_eliminate_]: 9.34998e-06 [merge_forward]: 8.54002e-06 [cell_reuse_recompute_pass]: 1.68002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.712e-05 [j_node_and_user_rematch]: 1.695e-05 [meta_fg_expand]: 4.3e-06 [replace_old_param]: 1.424e-05 [inline_without_move]: 9.48002e-06 [renormalize]: 0.00077867 [add_forward_monad_depend]: 9.51e-06 [auto_monad_grad]: 2.85002e-06 [auto_monad_eliminator]: 2.452e-05 [cse]: 7.616e-05 [replace_applicator]: 1.837e-05 [Cycle 2]: 0.0005686, [27] [switch_simplify]: 1.041e-05 [loop_unroll]: 9.15001e-06 [a_1]: 0.00021622 [with_stream_mark]: 1.487e-05 [recompute_prepare]: 1.004e-05 [updatestate_depend_eliminate]: 6.62002e-06 [updatestate_assign_eliminate]: 6.33e-06 [updatestate_loads_eliminate]: 5.82001e-06 [parameter_eliminate]: 1.71e-06 [specialize_transform]: 9.39e-06 [updatestate_useless_node_eliminater]: 1.345e-05 [accelerated_algorithm]: 1.006e-05 [meta_shard_fg_expand]: 1.91e-06 [get_grad_eliminate_]: 8.70999e-06 [merge_forward]: 6.04001e-06 [cell_reuse_recompute_pass]: 1.63002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.924e-05 [j_node_and_user_rematch]: 1.554e-05 [meta_fg_expand]: 3.36001e-06 [replace_old_param]: 1.377e-05 [inline_without_move]: 1.008e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.29998e-06 [auto_monad_grad]: 1.29e-06 [auto_monad_eliminator]: 1.496e-05 [cse]: 2.719e-05 [replace_applicator]: 1.153e-05 [py_interpret_to_execute_after_opt_a]: 1.577e-05 [rewriter_after_opt_a]: 0.00019806 [convert_after_rewriter]: 1.441e-05 [order_py_execute_after_rewriter]: 8.17e-06 [mutable_eliminate]: 0.00064757 [jit_opt_b]: 8.306e-05, [1] [Cycle 1]: 7.533e-05, [2] [frontend_op_eliminate]: 3.215e-05 [inline_after_opt_a]: 2.995e-05 [cconv]: 3.419e-05 [loop_unroll]: 0.000438 [jit_opt_after_cconv]: 0.00023333, [1] [Cycle 1]: 0.00022688, [11] [c_1]: 6.072e-05 [parameter_eliminate]: 2.84999e-06 [updatestate_depend_eliminate]: 1.041e-05 [updatestate_assign_eliminate]: 5.67999e-06 [updatestate_loads_eliminate]: 6.11e-06 [cse]: 4.167e-05 [call_graph_tuple_transform]: 2.62e-05 [tuple_list_get_item_eliminator]: 9.67999e-06 [none_parameter_eliminate]: 1.69e-06 [renormalize]: 6.80011e-07 [switch_simplify]: 9.65002e-06 [remove_dup_value]: 4.549e-05 [partial_unused_args_eliminate]: 2.66999e-06 [environ_conv]: 1.909e-05 [add_recomputation]: 8.809e-05 [cse_after_recomputation]: 3.73e-05, [1] [Cycle 1]: 3.059e-05, [1] [cse]: 2.37e-05 [auto_monad_reorder]: 3.87e-05 [get_jit_bprop_graph]: 2.65002e-06 [rewriter_after_jit_bprop_graph]: 3.99997e-06 [opt_after_jit_grad]: 0.00052163 [symbol_engine_optimizer]: 0.00010042, [1] [Cycle 1]: 9.436e-05, [6] [build]: 5.96e-06 [elim_shapecalc]: 1.288e-05 [elim_not_effective]: 2.103e-05 [opt_reshape]: 1.056e-05 [fold_const_symbol]: 1.613e-05 [renormalize]: 6.19999e-07 [validate]: 7.064e-05 Sums bootstrap : 0.000698s : 0.43% type_inference : 0.156400s : 96.60% event_method : 0.000016s : 0.01% auto_monad : 0.000128s : 0.08% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000013s : 0.01% py_interpret_to_execute : 0.000026s : 0.02% rewriter_before_opt_a : 0.000071s : 0.04% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000063s : 0.04% jit_opt_a.loop_unroll : 0.000024s : 0.02% jit_opt_a.a_1 : 0.000624s : 0.39% jit_opt_a.with_stream_mark : 0.000046s : 0.03% jit_opt_a.recompute_prepare : 0.000022s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000053s : 0.03% jit_opt_a.updatestate_loads_eliminate : 0.000013s : 0.01% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000028s : 0.02% jit_opt_a.accelerated_algorithm : 0.000020s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000018s : 0.01% jit_opt_a.merge_forward : 0.000015s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000046s : 0.03% jit_opt_a.j_node_and_user_rematch : 0.000032s : 0.02% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000028s : 0.02% jit_opt_a.inline_without_move : 0.000020s : 0.01% jit_opt_a.renormalize : 0.000779s : 0.48% jit_opt_a.add_forward_monad_depend : 0.000011s : 0.01% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000039s : 0.02% jit_opt_a.cse : 0.000103s : 0.06% jit_opt_a.replace_applicator : 0.000030s : 0.02% py_interpret_to_execute_after_opt_a : 0.000016s : 0.01% rewriter_after_opt_a : 0.000198s : 0.12% convert_after_rewriter : 0.000014s : 0.01% order_py_execute_after_rewriter : 0.000008s : 0.01% mutable_eliminate : 0.000648s : 0.40% jit_opt_b.frontend_op_eliminate : 0.000032s : 0.02% jit_opt_b.inline_after_opt_a : 0.000030s : 0.02% cconv : 0.000034s : 0.02% loop_unroll : 0.000438s : 0.27% jit_opt_after_cconv.c_1 : 0.000061s : 0.04% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.01% 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 : 0.000042s : 0.03% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.02% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000010s : 0.01% 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 : 0.000010s : 0.01% remove_dup_value : 0.000045s : 0.03% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000019s : 0.01% add_recomputation : 0.000088s : 0.05% cse_after_recomputation.cse : 0.000024s : 0.01% auto_monad_reorder : 0.000039s : 0.02% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000004s : 0.00% opt_after_jit_grad : 0.000522s : 0.32% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.01% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.01% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000071s : 0.04% Time group info: ------[substitution.] 0.000178 64 4.60% : 0.000008s : 2: substitution.depend_value_elim 1.91% : 0.000003s : 6: substitution.elim_not_effective 1.39% : 0.000002s : 6: substitution.fold_const_symbol 4.24% : 0.000008s : 7: substitution.graph_param_transform 60.15% : 0.000107s : 1: substitution.inline 3.39% : 0.000006s : 12: substitution.j_node_and_user_rematch 5.09% : 0.000009s : 12: substitution.remove_not_recompute_node 3.58% : 0.000006s : 2: substitution.replace_old_param 8.05% : 0.000014s : 6: substitution.updatestate_pure_node_eliminater 7.59% : 0.000013s : 10: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.156329 2 99.67% : 0.155806s : 1: type_inference.infer 0.33% : 0.000523s : 1: type_inference.specialize ------[replace.] 0.000018 1 100.00% : 0.000018s : 1: replace.inline ------[match.] 0.000105 1 100.00% : 0.000105s : 1: match.inline ------[predicate.] 0.000167 1031 1.29% : 0.000002s : 15: predicate.accumulaten_eliminater 1.33% : 0.000002s : 7: predicate.ad_related_special_op_eliminate 1.12% : 0.000002s : 15: predicate.addn_check_dump 1.18% : 0.000002s : 15: predicate.addn_zero_filter 1.57% : 0.000003s : 15: predicate.arithmetic_simplify 1.25% : 0.000002s : 15: predicate.cast_eliminate 0.95% : 0.000002s : 7: predicate.check_bprop_eliminate 1.13% : 0.000002s : 15: predicate.compare_switch_simplify 1.33% : 0.000002s : 15: predicate.depend_value_elim 1.15% : 0.000002s : 15: predicate.dict_get_item_const_eliminator 1.26% : 0.000002s : 15: predicate.dict_get_item_eliminator 1.21% : 0.000002s : 15: predicate.dict_set_item_eliminator 1.17% : 0.000002s : 7: predicate.dumpgradient_eliminate 0.40% : 0.000001s : 7: predicate.elim_not_effective 0.90% : 0.000001s : 7: predicate.elim_shapecalc_of_broadcastargs 1.25% : 0.000002s : 15: predicate.environ_add_const_eliminate 1.13% : 0.000002s : 15: predicate.environ_get_add_eliminate 1.14% : 0.000002s : 15: predicate.environ_get_depend_swap 1.27% : 0.000002s : 15: predicate.environ_get_eliminate 1.13% : 0.000002s : 15: predicate.environ_get_set_eliminate 0.33% : 0.000001s : 7: predicate.fold_const_symbol 1.34% : 0.000002s : 14: predicate.get_grad_eliminate 0.37% : 0.000001s : 7: predicate.graph_param_transform 5.25% : 0.000009s : 30: predicate.inline 1.54% : 0.000003s : 14: predicate.inline_without_move 0.62% : 0.000001s : 14: predicate.j_node_and_user_rematch 2.03% : 0.000003s : 14: predicate.less_batch_normalization 1.27% : 0.000002s : 15: predicate.list_to_tuple_eliminator_ 1.95% : 0.000003s : 22: predicate.load_eliminater 1.49% : 0.000002s : 7: predicate.loop_unroll_after_grad 1.83% : 0.000003s : 19: predicate.loop_unroll_before_grad 2.38% : 0.000004s : 22: predicate.make_slice_get_slice_eliminator 1.13% : 0.000002s : 15: predicate.merge_addn 1.15% : 0.000002s : 15: predicate.minmaximum_grad 1.82% : 0.000003s : 7: predicate.mutable_eliminate 0.96% : 0.000002s : 7: predicate.opt_reshape 2.33% : 0.000004s : 22: predicate.partial_eliminate 1.15% : 0.000002s : 15: predicate.print_const_string_wrapper 1.69% : 0.000003s : 15: predicate.reduce_eliminate 1.23% : 0.000002s : 15: predicate.redundant_stop_gradient_eliminater 0.93% : 0.000002s : 14: predicate.remove_not_recompute_node 1.86% : 0.000003s : 29: predicate.replace_applicator 0.83% : 0.000001s : 14: predicate.replace_old_param 0.47% : 0.000001s : 7: predicate.reset_defer_inline 1.27% : 0.000002s : 15: predicate.reshape_eliminate 1.24% : 0.000002s : 15: predicate.row_tensor_add_zeros_like 1.09% : 0.000002s : 7: predicate.row_tensor_eliminate 1.26% : 0.000002s : 15: predicate.same_eliminate 1.00% : 0.000002s : 14: predicate.set_cell_output_no_recompute 1.48% : 0.000002s : 14: predicate.special_op_eliminate 1.65% : 0.000003s : 14: predicate.specialize_transform 1.34% : 0.000002s : 15: predicate.split_environ_get_set_with_tuple_value 1.20% : 0.000002s : 15: predicate.stack_unstack_eliminate 0.71% : 0.000001s : 7: predicate.switch_call_monad_eliminater 1.46% : 0.000002s : 16: predicate.switch_defer_inline 1.37% : 0.000002s : 16: predicate.switch_layer_defer_inline 4.78% : 0.000008s : 42: predicate.switch_simplify 1.22% : 0.000002s : 15: predicate.tile_eliminate 1.39% : 0.000002s : 15: predicate.transpose_eliminate 1.47% : 0.000002s : 15: predicate.tuple_list_convert_item_index_to_positive 1.28% : 0.000002s : 15: predicate.tuple_list_get_item_depend_reorder 4.02% : 0.000007s : 29: predicate.tuple_list_get_item_eliminator 1.49% : 0.000002s : 15: predicate.tuple_list_set_item_eliminator 1.24% : 0.000002s : 15: predicate.tuple_to_list_eliminator_ 1.86% : 0.000003s : 22: predicate.updatestate_pure_node_eliminater 3.68% : 0.000006s : 36: predicate.updatestate_useless_node_eliminater 1.62% : 0.000003s : 15: predicate.value_based_eliminate 0.66% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 1.14% : 0.000002s : 7: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000270 4 8.13% : 0.000022s : 1: func_graph_cloner_run.FuncGraphClonerGraph 91.87% : 0.000248s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.198842 72 0.05% : 0.000091s : 1: add_recomputation 0.07% : 0.000133s : 1: auto_monad 0.02% : 0.000042s : 1: auto_monad_reorder 0.37% : 0.000742s : 1: bootstrap 0.02% : 0.000037s : 1: cconv 0.01% : 0.000017s : 1: convert_after_rewriter 0.02% : 0.000039s : 1: cse_after_recomputation 0.01% : 0.000022s : 1: environ_conv 0.01% : 0.000021s : 1: event_method 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 18.51% : 0.036801s : 1: jit_opt_a 0.12% : 0.000236s : 1: jit_opt_after_cconv 0.04% : 0.000086s : 1: jit_opt_b 0.22% : 0.000445s : 1: loop_unroll 0.33% : 0.000656s : 1: mutable_eliminate 0.47% : 0.000935s : 26: opt.transform.jit_opt_a 0.05% : 0.000103s : 4: opt.transform.jit_opt_after_cconv 0.03% : 0.000055s : 4: opt.transform.jit_opt_b 0.01% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000022s : 1: opt.transform.mutable_eliminate 0.02% : 0.000035s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000057s : 4: opt.transform.symbol_engine_opt 0.27% : 0.000529s : 1: opt_after_jit_grad 0.01% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.01% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000028s : 1: py_interpret_to_execute 0.01% : 0.000018s : 1: py_interpret_to_execute_after_opt_a 0.02% : 0.000049s : 1: remove_dup_value 0.22% : 0.000446s : 1: renormalize.infer 0.16% : 0.000324s : 1: renormalize.specialize 0.00% : 0.000006s : 1: rewriter_after_jit_bprop_graph 0.10% : 0.000202s : 1: rewriter_after_opt_a 0.04% : 0.000074s : 1: rewriter_before_opt_a 0.05% : 0.000103s : 1: symbol_engine_optimizer 78.67% : 0.156420s : 1: type_inference . [hook] pytest_runtest_teardown:test_remote_ops_copy_to_device tests/st/hyper_offload/memory_ops/test_copy_to_device.py::test_remote_ops_copy_to_device,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 ================== 1 passed, 25 warnings in 71.26s (0:01:11) ===================