==================================================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/ops/host/view, configfile: ../../../../../../../../sault/virtual_test/virtualenv_005/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_view_ops.py TotalTime = 0.953916, [30] [bootstrap]: 0.00092091 [type_inference]: 0.82292 [event_method]: 1.527e-05 [auto_monad]: 0.00019516 [graph_reusing]: 6.52001e-06 [pre_auto_parallel]: 1.241e-05 [py_interpret_to_execute]: 0.00035854 [rewriter_before_opt_a]: 0.00010052 [expand_dump_flag]: 4.63999e-06 [jit_opt_a]: 0.0444766, [2] [Cycle 1]: 0.0354114, [27] [switch_simplify]: 5.897e-05 [loop_unroll]: 2.343e-05 [a_1]: 0.00060574 [with_stream_mark]: 3.117e-05 [recompute_prepare]: 1.494e-05 [updatestate_depend_eliminate]: 3.329e-05 [updatestate_assign_eliminate]: 7.2e-06 [updatestate_loads_eliminate]: 6.14001e-06 [parameter_eliminate]: 2.36e-06 [specialize_transform]: 1.29e-05 [updatestate_useless_node_eliminater]: 1.523e-05 [accelerated_algorithm]: 1.17e-05 [meta_shard_fg_expand]: 3.26999e-06 [get_grad_eliminate_]: 1.117e-05 [merge_forward]: 6.24001e-06 [cell_reuse_recompute_pass]: 1.11002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.737e-05 [j_node_and_user_rematch]: 1.808e-05 [meta_fg_expand]: 4.27003e-06 [replace_old_param]: 1.51e-05 [inline_without_move]: 1.05e-05 [renormalize]: 0.0340751 [add_forward_monad_depend]: 1.733e-05 [auto_monad_grad]: 2.73e-06 [auto_monad_eliminator]: 3.254e-05 [cse]: 8.68e-05 [replace_applicator]: 3.235e-05 [Cycle 2]: 0.00071457, [27] [switch_simplify]: 1.273e-05 [loop_unroll]: 1.077e-05 [a_1]: 0.00026954 [with_stream_mark]: 2.167e-05 [recompute_prepare]: 1.345e-05 [updatestate_depend_eliminate]: 8.22e-06 [updatestate_assign_eliminate]: 8.99e-06 [updatestate_loads_eliminate]: 6.58e-06 [parameter_eliminate]: 2.58e-06 [specialize_transform]: 1.15e-05 [updatestate_useless_node_eliminater]: 1.64e-05 [accelerated_algorithm]: 1.124e-05 [meta_shard_fg_expand]: 3.09001e-06 [get_grad_eliminate_]: 1.061e-05 [merge_forward]: 7.40998e-06 [cell_reuse_recompute_pass]: 3.00002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.489e-05 [j_node_and_user_rematch]: 1.732e-05 [meta_fg_expand]: 5.02999e-06 [replace_old_param]: 1.489e-05 [inline_without_move]: 1.001e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.15002e-06 [auto_monad_grad]: 1.14998e-06 [auto_monad_eliminator]: 1.56e-05 [cse]: 3.968e-05 [replace_applicator]: 1.169e-05 [py_interpret_to_execute_after_opt_a]: 2.203e-05 [rewriter_after_opt_a]: 0.0677799 [convert_after_rewriter]: 0.0118587 [order_py_execute_after_rewriter]: 4.043e-05 [mutable_eliminate]: 0.00255221 [jit_opt_b]: 0.0001072, [1] [Cycle 1]: 9.456e-05, [2] [frontend_op_eliminate]: 3.986e-05 [inline_after_opt_a]: 3.899e-05 [cconv]: 4.875e-05 [loop_unroll]: 0.00056554 [jit_opt_after_cconv]: 0.00033463, [1] [Cycle 1]: 0.00032652, [11] [c_1]: 8.32e-05 [parameter_eliminate]: 6.10002e-06 [updatestate_depend_eliminate]: 1.567e-05 [updatestate_assign_eliminate]: 7.8e-06 [updatestate_loads_eliminate]: 7.39002e-06 [cse]: 8.278e-05 [call_graph_tuple_transform]: 3.472e-05 [tuple_list_get_item_eliminator]: 1.291e-05 [none_parameter_eliminate]: 2.03002e-06 [renormalize]: 9.00007e-07 [switch_simplify]: 1.302e-05 [remove_dup_value]: 2.947e-05 [partial_unused_args_eliminate]: 2.71e-06 [environ_conv]: 3.272e-05 [add_recomputation]: 0.00012828 [cse_after_recomputation]: 4.371e-05, [1] [Cycle 1]: 3.635e-05, [1] [cse]: 2.87e-05 [auto_monad_reorder]: 4.693e-05 [get_jit_bprop_graph]: 2.36998e-06 [rewriter_after_jit_bprop_graph]: 5.44e-06 [opt_after_jit_grad]: 0.0006126 [symbol_engine_optimizer]: 0.00012633, [1] [Cycle 1]: 0.00011865, [6] [build]: 8.55001e-06 [elim_shapecalc]: 1.528e-05 [elim_not_effective]: 2.852e-05 [opt_reshape]: 1.265e-05 [fold_const_symbol]: 2.059e-05 [renormalize]: 1.22999e-06 [validate]: 9.91e-05 Sums bootstrap : 0.000921s : 0.10% type_inference : 0.822920s : 87.12% event_method : 0.000015s : 0.00% auto_monad : 0.000195s : 0.02% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000359s : 0.04% rewriter_before_opt_a : 0.000101s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000072s : 0.01% jit_opt_a.loop_unroll : 0.000034s : 0.00% jit_opt_a.a_1 : 0.000875s : 0.09% jit_opt_a.with_stream_mark : 0.000053s : 0.01% jit_opt_a.recompute_prepare : 0.000028s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000042s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000016s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000013s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000024s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000032s : 0.00% jit_opt_a.accelerated_algorithm : 0.000023s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000022s : 0.00% jit_opt_a.merge_forward : 0.000014s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000052s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000035s : 0.00% jit_opt_a.meta_fg_expand : 0.000009s : 0.00% jit_opt_a.replace_old_param : 0.000030s : 0.00% jit_opt_a.inline_without_move : 0.000021s : 0.00% jit_opt_a.renormalize : 0.034075s : 3.61% jit_opt_a.add_forward_monad_depend : 0.000019s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000048s : 0.01% jit_opt_a.cse : 0.000126s : 0.01% jit_opt_a.replace_applicator : 0.000044s : 0.00% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.067780s : 7.18% convert_after_rewriter : 0.011859s : 1.26% order_py_execute_after_rewriter : 0.000040s : 0.00% mutable_eliminate : 0.002552s : 0.27% jit_opt_b.frontend_op_eliminate : 0.000040s : 0.00% jit_opt_b.inline_after_opt_a : 0.000039s : 0.00% cconv : 0.000049s : 0.01% loop_unroll : 0.000566s : 0.06% jit_opt_after_cconv.c_1 : 0.000083s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000083s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000035s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000013s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000013s : 0.00% remove_dup_value : 0.000029s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000033s : 0.00% add_recomputation : 0.000128s : 0.01% cse_after_recomputation.cse : 0.000029s : 0.00% auto_monad_reorder : 0.000047s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000613s : 0.06% symbol_engine_optimizer.build : 0.000009s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000029s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000021s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000099s : 0.01% Time group info: ------[substitution.] 0.000241 70 5.42% : 0.000013s : 4: substitution.depend_value_elim 1.62% : 0.000004s : 6: substitution.elim_not_effective 1.28% : 0.000003s : 6: substitution.fold_const_symbol 4.11% : 0.000010s : 8: substitution.graph_param_transform 63.60% : 0.000153s : 2: substitution.inline 2.81% : 0.000007s : 12: substitution.j_node_and_user_rematch 4.14% : 0.000010s : 12: substitution.remove_not_recompute_node 2.88% : 0.000007s : 2: substitution.replace_old_param 7.33% : 0.000018s : 7: substitution.updatestate_pure_node_eliminater 6.81% : 0.000016s : 11: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.822837 2 99.79% : 0.821138s : 1: type_inference.infer 0.21% : 0.001699s : 1: type_inference.specialize ------[replace.] 0.000029 2 100.00% : 0.000029s : 2: replace.inline ------[match.] 0.000151 2 100.00% : 0.000151s : 2: match.inline ------[predicate.] 0.000225 1322 1.28% : 0.000003s : 20: predicate.accumulaten_eliminater 1.27% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.10% : 0.000002s : 20: predicate.addn_check_dump 1.39% : 0.000003s : 20: predicate.addn_zero_filter 2.15% : 0.000005s : 20: predicate.arithmetic_simplify 1.29% : 0.000003s : 20: predicate.cast_eliminate 0.77% : 0.000002s : 8: predicate.check_bprop_eliminate 1.16% : 0.000003s : 20: predicate.compare_switch_simplify 1.42% : 0.000003s : 20: predicate.depend_value_elim 1.33% : 0.000003s : 20: predicate.dict_get_item_const_eliminator 1.28% : 0.000003s : 20: predicate.dict_get_item_eliminator 1.29% : 0.000003s : 20: predicate.dict_set_item_eliminator 0.91% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.43% : 0.000001s : 8: predicate.elim_not_effective 0.72% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.27% : 0.000003s : 20: predicate.environ_add_const_eliminate 1.10% : 0.000002s : 20: predicate.environ_get_add_eliminate 1.15% : 0.000003s : 20: predicate.environ_get_depend_swap 1.17% : 0.000003s : 20: predicate.environ_get_eliminate 1.12% : 0.000003s : 20: predicate.environ_get_set_eliminate 0.32% : 0.000001s : 8: predicate.fold_const_symbol 1.28% : 0.000003s : 16: predicate.get_grad_eliminate 0.46% : 0.000001s : 8: predicate.graph_param_transform 4.89% : 0.000011s : 38: predicate.inline 1.10% : 0.000002s : 16: predicate.inline_without_move 0.51% : 0.000001s : 16: predicate.j_node_and_user_rematch 1.63% : 0.000004s : 16: predicate.less_batch_normalization 1.28% : 0.000003s : 20: predicate.list_to_tuple_eliminator_ 1.88% : 0.000004s : 28: predicate.load_eliminater 1.52% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.14% : 0.000005s : 28: predicate.loop_unroll_before_grad 2.02% : 0.000005s : 28: predicate.make_slice_get_slice_eliminator 1.17% : 0.000003s : 20: predicate.merge_addn 1.14% : 0.000003s : 20: predicate.minmaximum_grad 3.11% : 0.000007s : 8: predicate.mutable_eliminate 0.74% : 0.000002s : 8: predicate.opt_reshape 2.23% : 0.000005s : 28: predicate.partial_eliminate 1.34% : 0.000003s : 20: predicate.print_const_string_wrapper 1.74% : 0.000004s : 20: predicate.reduce_eliminate 1.27% : 0.000003s : 20: predicate.redundant_stop_gradient_eliminater 0.79% : 0.000002s : 16: predicate.remove_not_recompute_node 2.06% : 0.000005s : 36: predicate.replace_applicator 0.79% : 0.000002s : 16: predicate.replace_old_param 0.82% : 0.000002s : 8: predicate.reset_defer_inline 1.24% : 0.000003s : 20: predicate.reshape_eliminate 1.61% : 0.000004s : 20: predicate.row_tensor_add_zeros_like 1.06% : 0.000002s : 8: predicate.row_tensor_eliminate 1.32% : 0.000003s : 20: predicate.same_eliminate 0.83% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.19% : 0.000003s : 16: predicate.special_op_eliminate 1.19% : 0.000003s : 16: predicate.specialize_transform 1.50% : 0.000003s : 20: predicate.split_environ_get_set_with_tuple_value 1.27% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.69% : 0.000002s : 8: predicate.switch_call_monad_eliminater 1.53% : 0.000003s : 22: predicate.switch_defer_inline 1.50% : 0.000003s : 22: predicate.switch_layer_defer_inline 4.59% : 0.000010s : 58: predicate.switch_simplify 1.24% : 0.000003s : 20: predicate.tile_eliminate 1.45% : 0.000003s : 20: predicate.transpose_eliminate 1.50% : 0.000003s : 20: predicate.tuple_list_convert_item_index_to_positive 1.32% : 0.000003s : 20: predicate.tuple_list_get_item_depend_reorder 3.66% : 0.000008s : 36: predicate.tuple_list_get_item_eliminator 1.54% : 0.000003s : 20: predicate.tuple_list_set_item_eliminator 1.25% : 0.000003s : 20: predicate.tuple_to_list_eliminator_ 1.96% : 0.000004s : 28: predicate.updatestate_pure_node_eliminater 3.50% : 0.000008s : 44: predicate.updatestate_useless_node_eliminater 1.75% : 0.000004s : 20: predicate.value_based_eliminate 0.53% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.93% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003619 30 76.57% : 0.002771s : 26: func_graph_cloner_run.FuncGraphClonerGraph 23.43% : 0.000848s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.989285 72 0.01% : 0.000132s : 1: add_recomputation 0.02% : 0.000201s : 1: auto_monad 0.01% : 0.000051s : 1: auto_monad_reorder 0.10% : 0.000947s : 1: bootstrap 0.01% : 0.000052s : 1: cconv 1.20% : 0.011901s : 1: convert_after_rewriter 0.00% : 0.000046s : 1: cse_after_recomputation 0.00% : 0.000036s : 1: environ_conv 0.00% : 0.000020s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 4.50% : 0.044482s : 1: jit_opt_a 0.03% : 0.000338s : 1: jit_opt_after_cconv 0.01% : 0.000111s : 1: jit_opt_b 0.06% : 0.000576s : 1: loop_unroll 0.26% : 0.002572s : 1: mutable_eliminate 0.13% : 0.001247s : 26: opt.transform.jit_opt_a 0.01% : 0.000139s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000069s : 4: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000046s : 1: opt.transform.mutable_eliminate 0.00% : 0.000045s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000073s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000623s : 1: opt_after_jit_grad 0.00% : 0.000047s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.04% : 0.000366s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000032s : 1: remove_dup_value 3.33% : 0.032958s : 1: renormalize.infer 0.11% : 0.001103s : 1: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 6.85% : 0.067798s : 1: rewriter_after_opt_a 0.01% : 0.000107s : 1: rewriter_before_opt_a 0.01% : 0.000129s : 1: symbol_engine_optimizer 83.19% : 0.822942s : 1: type_inference . [hook] pytest_runtest_teardown:test_pynative_view_to_graph tests/st/ops/host/view/test_view_ops.py::test_pynative_view_to_graph,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 75.42s (0:01:15) ===================