==================================================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_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 1 item test_copy_to_host.py TotalTime = 0.15841, [30] [bootstrap]: 0.00061081 [type_inference]: 0.0880408 [event_method]: 1.313e-05 [auto_monad]: 0.00012667 [graph_reusing]: 5.10001e-06 [pre_auto_parallel]: 1.125e-05 [py_interpret_to_execute]: 1.681e-05 [rewriter_before_opt_a]: 5.082e-05 [expand_dump_flag]: 2.78998e-06 [jit_opt_a]: 0.0104672, [2] [Cycle 1]: 0.00152869, [27] [switch_simplify]: 4.922e-05 [loop_unroll]: 1.419e-05 [a_1]: 0.00036597 [with_stream_mark]: 2.923e-05 [recompute_prepare]: 1.033e-05 [updatestate_depend_eliminate]: 6.63998e-06 [updatestate_assign_eliminate]: 7.00998e-06 [updatestate_loads_eliminate]: 4.99e-06 [parameter_eliminate]: 2.01e-06 [specialize_transform]: 8.80999e-06 [updatestate_useless_node_eliminater]: 1.071e-05 [accelerated_algorithm]: 7.71001e-06 [meta_shard_fg_expand]: 2.70002e-06 [get_grad_eliminate_]: 7.28999e-06 [merge_forward]: 5.27001e-06 [cell_reuse_recompute_pass]: 1.34e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.492e-05 [j_node_and_user_rematch]: 1.389e-05 [meta_fg_expand]: 3.38e-06 [replace_old_param]: 1.223e-05 [inline_without_move]: 7.56001e-06 [renormalize]: 0.00063619 [add_forward_monad_depend]: 7.90998e-06 [auto_monad_grad]: 2.76e-06 [auto_monad_eliminator]: 2.052e-05 [cse]: 5.112e-05 [replace_applicator]: 1.385e-05 [Cycle 2]: 0.00045149, [27] [switch_simplify]: 8.64998e-06 [loop_unroll]: 7.37997e-06 [a_1]: 0.00015793 [with_stream_mark]: 1.257e-05 [recompute_prepare]: 7.85998e-06 [updatestate_depend_eliminate]: 5.30001e-06 [updatestate_assign_eliminate]: 4.37e-06 [updatestate_loads_eliminate]: 4.02e-06 [parameter_eliminate]: 1.19998e-06 [specialize_transform]: 7.95e-06 [updatestate_useless_node_eliminater]: 1.035e-05 [accelerated_algorithm]: 7.51999e-06 [meta_shard_fg_expand]: 1.79e-06 [get_grad_eliminate_]: 7.03e-06 [merge_forward]: 4.07003e-06 [cell_reuse_recompute_pass]: 1.28002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.563e-05 [j_node_and_user_rematch]: 1.21e-05 [meta_fg_expand]: 2.66999e-06 [replace_old_param]: 9.37001e-06 [inline_without_move]: 7.65e-06 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 1.19e-06 [auto_monad_grad]: 9.99979e-07 [auto_monad_eliminator]: 1.001e-05 [cse]: 1.947e-05 [replace_applicator]: 7.71999e-06 [py_interpret_to_execute_after_opt_a]: 1.586e-05 [rewriter_after_opt_a]: 0.0001803 [convert_after_rewriter]: 2.194e-05 [order_py_execute_after_rewriter]: 6.97002e-06 [mutable_eliminate]: 0.0561625 [jit_opt_b]: 8.124e-05, [1] [Cycle 1]: 6.888e-05, [2] [frontend_op_eliminate]: 2.755e-05 [inline_after_opt_a]: 2.744e-05 [cconv]: 4.365e-05 [loop_unroll]: 0.00052456 [jit_opt_after_cconv]: 0.00024983, [1] [Cycle 1]: 0.00024171, [11] [c_1]: 5.852e-05 [parameter_eliminate]: 6.84999e-06 [updatestate_depend_eliminate]: 1.602e-05 [updatestate_assign_eliminate]: 5.69999e-06 [updatestate_loads_eliminate]: 5.74999e-06 [cse]: 5.007e-05 [call_graph_tuple_transform]: 2.38e-05 [tuple_list_get_item_eliminator]: 8.16002e-06 [none_parameter_eliminate]: 1.79e-06 [renormalize]: 1.02998e-06 [switch_simplify]: 8.69003e-06 [remove_dup_value]: 1.994e-05 [partial_unused_args_eliminate]: 2.54001e-06 [environ_conv]: 2.729e-05 [add_recomputation]: 0.00010456 [cse_after_recomputation]: 3.694e-05, [1] [Cycle 1]: 3.058e-05, [1] [cse]: 2.27e-05 [auto_monad_reorder]: 3.865e-05 [get_jit_bprop_graph]: 2.37001e-06 [rewriter_after_jit_bprop_graph]: 6.66999e-06 [opt_after_jit_grad]: 0.00055023 [symbol_engine_optimizer]: 0.00016688, [1] [Cycle 1]: 0.0001591, [6] [build]: 6.76e-06 [elim_shapecalc]: 7.793e-05 [elim_not_effective]: 2.156e-05 [opt_reshape]: 8.70001e-06 [fold_const_symbol]: 1.351e-05 [renormalize]: 3.9002e-07 [validate]: 7.029e-05 Sums bootstrap : 0.000611s : 0.41% type_inference : 0.088041s : 59.20% event_method : 0.000013s : 0.01% auto_monad : 0.000127s : 0.09% graph_reusing : 0.000005s : 0.00% pre_auto_parallel : 0.000011s : 0.01% py_interpret_to_execute : 0.000017s : 0.01% rewriter_before_opt_a : 0.000051s : 0.03% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000058s : 0.04% jit_opt_a.loop_unroll : 0.000022s : 0.01% jit_opt_a.a_1 : 0.000524s : 0.35% jit_opt_a.with_stream_mark : 0.000042s : 0.03% jit_opt_a.recompute_prepare : 0.000018s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.01% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000017s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000021s : 0.01% jit_opt_a.accelerated_algorithm : 0.000015s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000014s : 0.01% jit_opt_a.merge_forward : 0.000009s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000041s : 0.03% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.02% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000022s : 0.01% jit_opt_a.inline_without_move : 0.000015s : 0.01% jit_opt_a.renormalize : 0.000636s : 0.43% jit_opt_a.add_forward_monad_depend : 0.000009s : 0.01% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000031s : 0.02% jit_opt_a.cse : 0.000071s : 0.05% jit_opt_a.replace_applicator : 0.000022s : 0.01% py_interpret_to_execute_after_opt_a : 0.000016s : 0.01% rewriter_after_opt_a : 0.000180s : 0.12% convert_after_rewriter : 0.000022s : 0.01% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.056162s : 37.77% jit_opt_b.frontend_op_eliminate : 0.000028s : 0.02% jit_opt_b.inline_after_opt_a : 0.000027s : 0.02% cconv : 0.000044s : 0.03% loop_unroll : 0.000525s : 0.35% jit_opt_after_cconv.c_1 : 0.000059s : 0.04% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 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 : 0.000050s : 0.03% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 0.02% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 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 : 0.000009s : 0.01% remove_dup_value : 0.000020s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000027s : 0.02% add_recomputation : 0.000105s : 0.07% cse_after_recomputation.cse : 0.000023s : 0.02% auto_monad_reorder : 0.000039s : 0.03% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000550s : 0.37% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000078s : 0.05% symbol_engine_optimizer.elim_not_effective : 0.000022s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.01% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000070s : 0.05% Time group info: ------[substitution.] 0.000183 42 4.03% : 0.000007s : 2: substitution.depend_value_elim 1.69% : 0.000003s : 4: substitution.elim_not_effective 1.03% : 0.000002s : 4: substitution.fold_const_symbol 3.82% : 0.000007s : 5: substitution.graph_param_transform 66.09% : 0.000121s : 1: substitution.inline 2.72% : 0.000005s : 8: substitution.j_node_and_user_rematch 5.21% : 0.000010s : 8: substitution.remove_not_recompute_node 2.88% : 0.000005s : 2: substitution.replace_old_param 7.28% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 5.26% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.087981 2 99.57% : 0.087603s : 1: type_inference.infer 0.43% : 0.000377s : 1: type_inference.specialize ------[replace.] 0.000016 1 100.00% : 0.000016s : 1: replace.inline ------[match.] 0.000120 1 100.00% : 0.000120s : 1: match.inline ------[predicate.] 0.000139 753 1.06% : 0.000001s : 11: predicate.accumulaten_eliminater 1.63% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.06% : 0.000001s : 11: predicate.addn_check_dump 1.08% : 0.000001s : 11: predicate.addn_zero_filter 2.50% : 0.000003s : 11: predicate.arithmetic_simplify 1.11% : 0.000002s : 11: predicate.cast_eliminate 0.66% : 0.000001s : 5: predicate.check_bprop_eliminate 0.99% : 0.000001s : 11: predicate.compare_switch_simplify 1.25% : 0.000002s : 11: predicate.depend_value_elim 1.01% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.20% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.06% : 0.000001s : 11: predicate.dict_set_item_eliminator 1.00% : 0.000001s : 5: predicate.dumpgradient_eliminate 0.48% : 0.000001s : 5: predicate.elim_not_effective 0.94% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.03% : 0.000001s : 11: predicate.environ_add_const_eliminate 0.99% : 0.000001s : 11: predicate.environ_get_add_eliminate 1.02% : 0.000001s : 11: predicate.environ_get_depend_swap 1.34% : 0.000002s : 11: predicate.environ_get_eliminate 0.99% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.29% : 0.000000s : 5: predicate.fold_const_symbol 1.20% : 0.000002s : 10: predicate.get_grad_eliminate 0.47% : 0.000001s : 5: predicate.graph_param_transform 5.68% : 0.000008s : 22: predicate.inline 1.29% : 0.000002s : 10: predicate.inline_without_move 0.53% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.35% : 0.000002s : 10: predicate.less_batch_normalization 1.42% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.94% : 0.000003s : 16: predicate.load_eliminater 1.91% : 0.000003s : 5: predicate.loop_unroll_after_grad 1.96% : 0.000003s : 15: predicate.loop_unroll_before_grad 2.67% : 0.000004s : 16: predicate.make_slice_get_slice_eliminator 0.99% : 0.000001s : 11: predicate.merge_addn 0.99% : 0.000001s : 11: predicate.minmaximum_grad 5.29% : 0.000007s : 5: predicate.mutable_eliminate 0.65% : 0.000001s : 5: predicate.opt_reshape 2.06% : 0.000003s : 16: predicate.partial_eliminate 1.07% : 0.000001s : 11: predicate.print_const_string_wrapper 1.38% : 0.000002s : 11: predicate.reduce_eliminate 1.29% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.94% : 0.000001s : 10: predicate.remove_not_recompute_node 1.60% : 0.000002s : 21: predicate.replace_applicator 0.86% : 0.000001s : 10: predicate.replace_old_param 0.87% : 0.000001s : 5: predicate.reset_defer_inline 1.10% : 0.000002s : 11: predicate.reshape_eliminate 1.25% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.68% : 0.000002s : 5: predicate.row_tensor_eliminate 1.11% : 0.000002s : 11: predicate.same_eliminate 0.86% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.65% : 0.000002s : 10: predicate.special_op_eliminate 1.28% : 0.000002s : 10: predicate.specialize_transform 1.35% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.05% : 0.000001s : 11: predicate.stack_unstack_eliminate 0.76% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.37% : 0.000002s : 12: predicate.switch_defer_inline 1.36% : 0.000002s : 12: predicate.switch_layer_defer_inline 5.60% : 0.000008s : 32: predicate.switch_simplify 1.11% : 0.000002s : 11: predicate.tile_eliminate 1.03% : 0.000001s : 11: predicate.transpose_eliminate 1.24% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.26% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.29% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.38% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.14% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.65% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.37% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.39% : 0.000002s : 11: predicate.value_based_eliminate 0.70% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.92% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000226 4 11.79% : 0.000027s : 1: func_graph_cloner_run.FuncGraphClonerGraph 88.21% : 0.000199s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.159514 72 0.07% : 0.000109s : 1: add_recomputation 0.08% : 0.000131s : 1: auto_monad 0.03% : 0.000042s : 1: auto_monad_reorder 0.40% : 0.000638s : 1: bootstrap 0.03% : 0.000047s : 1: cconv 0.02% : 0.000025s : 1: convert_after_rewriter 0.02% : 0.000040s : 1: cse_after_recomputation 0.02% : 0.000030s : 1: environ_conv 0.01% : 0.000018s : 1: event_method 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000008s : 1: graph_reusing 6.56% : 0.010471s : 1: jit_opt_a 0.16% : 0.000254s : 1: jit_opt_after_cconv 0.05% : 0.000085s : 1: jit_opt_b 0.34% : 0.000536s : 1: loop_unroll 35.22% : 0.056188s : 1: mutable_eliminate 0.49% : 0.000775s : 26: opt.transform.jit_opt_a 0.06% : 0.000095s : 4: opt.transform.jit_opt_after_cconv 0.03% : 0.000046s : 4: opt.transform.jit_opt_b 0.01% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.03% : 0.000042s : 1: opt.transform.mutable_eliminate 0.02% : 0.000032s : 1: opt.transform.opt_after_jit_grad 0.07% : 0.000118s : 4: opt.transform.symbol_engine_opt 0.35% : 0.000563s : 1: opt_after_jit_grad 0.01% : 0.000009s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.01% : 0.000013s : 1: pre_auto_parallel 0.01% : 0.000019s : 1: py_interpret_to_execute 0.01% : 0.000018s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000023s : 1: remove_dup_value 0.23% : 0.000370s : 1: renormalize.infer 0.16% : 0.000258s : 1: renormalize.specialize 0.01% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.12% : 0.000184s : 1: rewriter_after_opt_a 0.03% : 0.000054s : 1: rewriter_before_opt_a 0.11% : 0.000170s : 1: symbol_engine_optimizer 55.21% : 0.088061s : 1: type_inference . [hook] pytest_runtest_teardown:test_remote_ops_copy_to_host tests/st/hyper_offload/memory_ops/test_copy_to_host.py::test_remote_ops_copy_to_host,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 76.82s (0:01:16) ===================