==================================================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_003/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 = 0.605605, [30] [bootstrap]: 0.00067135 [type_inference]: 0.525107 [event_method]: 1.443e-05 [auto_monad]: 0.00022014 [graph_reusing]: 6.04001e-06 [pre_auto_parallel]: 1.186e-05 [py_interpret_to_execute]: 0.00033746 [rewriter_before_opt_a]: 0.00021329 [expand_dump_flag]: 4.34997e-06 [jit_opt_a]: 0.0746079, [2] [Cycle 1]: 0.0051464, [27] [switch_simplify]: 6.864e-05 [loop_unroll]: 2.304e-05 [a_1]: 0.00070985 [with_stream_mark]: 3.517e-05 [recompute_prepare]: 1.609e-05 [updatestate_depend_eliminate]: 3.239e-05 [updatestate_assign_eliminate]: 1.385e-05 [updatestate_loads_eliminate]: 6.59001e-06 [parameter_eliminate]: 2.34999e-06 [specialize_transform]: 1.236e-05 [updatestate_useless_node_eliminater]: 1.738e-05 [accelerated_algorithm]: 1.131e-05 [meta_shard_fg_expand]: 2.96001e-06 [get_grad_eliminate_]: 1.076e-05 [merge_forward]: 7e-06 [cell_reuse_recompute_pass]: 1.24998e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.891e-05 [j_node_and_user_rematch]: 1.938e-05 [meta_fg_expand]: 4.92999e-06 [replace_old_param]: 1.541e-05 [inline_without_move]: 1.122e-05 [renormalize]: 0.00362241 [add_forward_monad_depend]: 1.919e-05 [auto_monad_grad]: 2.79001e-06 [auto_monad_eliminator]: 6.091e-05 [cse]: 0.00010343 [replace_applicator]: 3.191e-05 [Cycle 2]: 0.00072385, [27] [switch_simplify]: 1.146e-05 [loop_unroll]: 1.015e-05 [a_1]: 0.00026655 [with_stream_mark]: 2.269e-05 [recompute_prepare]: 1.143e-05 [updatestate_depend_eliminate]: 7.21999e-06 [updatestate_assign_eliminate]: 7.01001e-06 [updatestate_loads_eliminate]: 6.02999e-06 [parameter_eliminate]: 2.29999e-06 [specialize_transform]: 1.058e-05 [updatestate_useless_node_eliminater]: 1.504e-05 [accelerated_algorithm]: 1.448e-05 [meta_shard_fg_expand]: 3.05998e-06 [get_grad_eliminate_]: 1.122e-05 [merge_forward]: 8.89e-06 [cell_reuse_recompute_pass]: 3.71999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.624e-05 [j_node_and_user_rematch]: 1.752e-05 [meta_fg_expand]: 4.85001e-06 [replace_old_param]: 1.484e-05 [inline_without_move]: 1.087e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.43002e-06 [auto_monad_grad]: 1.67001e-06 [auto_monad_eliminator]: 1.704e-05 [cse]: 3.825e-05 [replace_applicator]: 1.237e-05 [py_interpret_to_execute_after_opt_a]: 2.516e-05 [rewriter_after_opt_a]: 0.00029094 [convert_after_rewriter]: 1.521e-05 [order_py_execute_after_rewriter]: 9.32001e-06 [mutable_eliminate]: 0.00111375 [jit_opt_b]: 9.622e-05, [1] [Cycle 1]: 8.528e-05, [2] [frontend_op_eliminate]: 3.788e-05 [inline_after_opt_a]: 3.489e-05 [cconv]: 4.147e-05 [loop_unroll]: 0.00061566 [jit_opt_after_cconv]: 0.00030753, [1] [Cycle 1]: 0.0002995, [11] [c_1]: 7.822e-05 [parameter_eliminate]: 6.63998e-06 [updatestate_depend_eliminate]: 1.592e-05 [updatestate_assign_eliminate]: 7.11001e-06 [updatestate_loads_eliminate]: 7.14001e-06 [cse]: 6.79e-05 [call_graph_tuple_transform]: 3.09e-05 [tuple_list_get_item_eliminator]: 1.213e-05 [none_parameter_eliminate]: 2.14999e-06 [renormalize]: 1.07e-06 [switch_simplify]: 1.238e-05 [remove_dup_value]: 3.137e-05 [partial_unused_args_eliminate]: 2.79999e-06 [environ_conv]: 3.357e-05 [add_recomputation]: 0.00010844 [cse_after_recomputation]: 4.244e-05, [1] [Cycle 1]: 3.436e-05, [1] [cse]: 2.726e-05 [auto_monad_reorder]: 4.377e-05 [get_jit_bprop_graph]: 2.49999e-06 [rewriter_after_jit_bprop_graph]: 5.17999e-06 [opt_after_jit_grad]: 0.00060856 [symbol_engine_optimizer]: 0.00011602, [1] [Cycle 1]: 0.00010769, [6] [build]: 7.77e-06 [elim_shapecalc]: 1.464e-05 [elim_not_effective]: 2.591e-05 [opt_reshape]: 1.12e-05 [fold_const_symbol]: 1.757e-05 [renormalize]: 9.00007e-07 [validate]: 9.929e-05 Sums bootstrap : 0.000671s : 0.13% type_inference : 0.525107s : 98.06% event_method : 0.000014s : 0.00% auto_monad : 0.000220s : 0.04% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000337s : 0.06% rewriter_before_opt_a : 0.000213s : 0.04% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000080s : 0.01% jit_opt_a.loop_unroll : 0.000033s : 0.01% jit_opt_a.a_1 : 0.000976s : 0.18% jit_opt_a.with_stream_mark : 0.000058s : 0.01% jit_opt_a.recompute_prepare : 0.000028s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000040s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000021s : 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 : 0.000023s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000032s : 0.01% jit_opt_a.accelerated_algorithm : 0.000026s : 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 : 0.000016s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000055s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000037s : 0.01% jit_opt_a.meta_fg_expand : 0.000010s : 0.00% jit_opt_a.replace_old_param : 0.000030s : 0.01% jit_opt_a.inline_without_move : 0.000022s : 0.00% jit_opt_a.renormalize : 0.003622s : 0.68% jit_opt_a.add_forward_monad_depend : 0.000022s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000078s : 0.01% jit_opt_a.cse : 0.000142s : 0.03% jit_opt_a.replace_applicator : 0.000044s : 0.01% py_interpret_to_execute_after_opt_a : 0.000025s : 0.00% rewriter_after_opt_a : 0.000291s : 0.05% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.001114s : 0.21% jit_opt_b.frontend_op_eliminate : 0.000038s : 0.01% jit_opt_b.inline_after_opt_a : 0.000035s : 0.01% cconv : 0.000041s : 0.01% loop_unroll : 0.000616s : 0.11% jit_opt_after_cconv.c_1 : 0.000078s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000068s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000031s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 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 : 0.000012s : 0.00% remove_dup_value : 0.000031s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000034s : 0.01% add_recomputation : 0.000108s : 0.02% cse_after_recomputation.cse : 0.000027s : 0.01% auto_monad_reorder : 0.000044s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000609s : 0.11% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000018s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000099s : 0.02% Time group info: ------[substitution.] 0.000259 70 5.94% : 0.000015s : 4: substitution.depend_value_elim 1.36% : 0.000004s : 6: substitution.elim_not_effective 1.02% : 0.000003s : 6: substitution.fold_const_symbol 3.65% : 0.000009s : 8: substitution.graph_param_transform 65.34% : 0.000169s : 2: substitution.inline 2.71% : 0.000007s : 12: substitution.j_node_and_user_rematch 3.98% : 0.000010s : 12: substitution.remove_not_recompute_node 2.75% : 0.000007s : 2: substitution.replace_old_param 6.45% : 0.000017s : 7: substitution.updatestate_pure_node_eliminater 6.80% : 0.000018s : 11: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.525028 2 99.69% : 0.523423s : 1: type_inference.infer 0.31% : 0.001605s : 1: type_inference.specialize ------[replace.] 0.000028 2 100.00% : 0.000028s : 2: replace.inline ------[match.] 0.000167 2 100.00% : 0.000167s : 2: match.inline ------[predicate.] 0.000300 1322 0.95% : 0.000003s : 20: predicate.accumulaten_eliminater 1.08% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 0.79% : 0.000002s : 20: predicate.addn_check_dump 0.94% : 0.000003s : 20: predicate.addn_zero_filter 1.56% : 0.000005s : 20: predicate.arithmetic_simplify 0.92% : 0.000003s : 20: predicate.cast_eliminate 0.57% : 0.000002s : 8: predicate.check_bprop_eliminate 0.83% : 0.000002s : 20: predicate.compare_switch_simplify 0.92% : 0.000003s : 20: predicate.depend_value_elim 0.86% : 0.000003s : 20: predicate.dict_get_item_const_eliminator 0.91% : 0.000003s : 20: predicate.dict_get_item_eliminator 1.01% : 0.000003s : 20: predicate.dict_set_item_eliminator 1.06% : 0.000003s : 8: predicate.dumpgradient_eliminate 0.43% : 0.000001s : 8: predicate.elim_not_effective 0.47% : 0.000001s : 8: predicate.elim_shapecalc_of_broadcastargs 0.90% : 0.000003s : 20: predicate.environ_add_const_eliminate 0.93% : 0.000003s : 20: predicate.environ_get_add_eliminate 0.89% : 0.000003s : 20: predicate.environ_get_depend_swap 0.87% : 0.000003s : 20: predicate.environ_get_eliminate 0.81% : 0.000002s : 20: predicate.environ_get_set_eliminate 0.21% : 0.000001s : 8: predicate.fold_const_symbol 0.92% : 0.000003s : 16: predicate.get_grad_eliminate 0.31% : 0.000001s : 8: predicate.graph_param_transform 3.49% : 0.000010s : 38: predicate.inline 0.98% : 0.000003s : 16: predicate.inline_without_move 0.39% : 0.000001s : 16: predicate.j_node_and_user_rematch 1.09% : 0.000003s : 16: predicate.less_batch_normalization 1.11% : 0.000003s : 20: predicate.list_to_tuple_eliminator_ 1.38% : 0.000004s : 28: predicate.load_eliminater 1.46% : 0.000004s : 8: predicate.loop_unroll_after_grad 1.54% : 0.000005s : 28: predicate.loop_unroll_before_grad 1.56% : 0.000005s : 28: predicate.make_slice_get_slice_eliminator 0.83% : 0.000002s : 20: predicate.merge_addn 0.82% : 0.000002s : 20: predicate.minmaximum_grad 1.45% : 0.000004s : 8: predicate.mutable_eliminate 0.42% : 0.000001s : 8: predicate.opt_reshape 29.12% : 0.000087s : 28: predicate.partial_eliminate 0.87% : 0.000003s : 20: predicate.print_const_string_wrapper 1.22% : 0.000004s : 20: predicate.reduce_eliminate 0.95% : 0.000003s : 20: predicate.redundant_stop_gradient_eliminater 0.69% : 0.000002s : 16: predicate.remove_not_recompute_node 1.42% : 0.000004s : 36: predicate.replace_applicator 0.60% : 0.000002s : 16: predicate.replace_old_param 0.35% : 0.000001s : 8: predicate.reset_defer_inline 0.98% : 0.000003s : 20: predicate.reshape_eliminate 1.03% : 0.000003s : 20: predicate.row_tensor_add_zeros_like 0.72% : 0.000002s : 8: predicate.row_tensor_eliminate 0.97% : 0.000003s : 20: predicate.same_eliminate 0.58% : 0.000002s : 18: predicate.set_cell_output_no_recompute 0.80% : 0.000002s : 16: predicate.special_op_eliminate 0.86% : 0.000003s : 16: predicate.specialize_transform 1.08% : 0.000003s : 20: predicate.split_environ_get_set_with_tuple_value 0.92% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.46% : 0.000001s : 8: predicate.switch_call_monad_eliminater 1.11% : 0.000003s : 22: predicate.switch_defer_inline 1.06% : 0.000003s : 22: predicate.switch_layer_defer_inline 3.58% : 0.000011s : 58: predicate.switch_simplify 0.89% : 0.000003s : 20: predicate.tile_eliminate 1.06% : 0.000003s : 20: predicate.transpose_eliminate 1.17% : 0.000004s : 20: predicate.tuple_list_convert_item_index_to_positive 1.07% : 0.000003s : 20: predicate.tuple_list_get_item_depend_reorder 2.62% : 0.000008s : 36: predicate.tuple_list_get_item_eliminator 1.04% : 0.000003s : 20: predicate.tuple_list_set_item_eliminator 1.00% : 0.000003s : 20: predicate.tuple_to_list_eliminator_ 1.33% : 0.000004s : 28: predicate.updatestate_pure_node_eliminater 2.62% : 0.000008s : 44: predicate.updatestate_useless_node_eliminater 1.21% : 0.000004s : 20: predicate.value_based_eliminate 0.43% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.53% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003783 30 80.14% : 0.003032s : 26: func_graph_cloner_run.FuncGraphClonerGraph 19.86% : 0.000751s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.610203 72 0.02% : 0.000112s : 1: add_recomputation 0.04% : 0.000227s : 1: auto_monad 0.01% : 0.000047s : 1: auto_monad_reorder 0.11% : 0.000700s : 1: bootstrap 0.01% : 0.000044s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.01% : 0.000045s : 1: cse_after_recomputation 0.01% : 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 12.23% : 0.074612s : 1: jit_opt_a 0.05% : 0.000311s : 1: jit_opt_after_cconv 0.02% : 0.000099s : 1: jit_opt_b 0.10% : 0.000626s : 1: loop_unroll 0.18% : 0.001128s : 1: mutable_eliminate 0.22% : 0.001356s : 26: opt.transform.jit_opt_a 0.02% : 0.000130s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000062s : 4: opt.transform.jit_opt_b 0.00% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000032s : 1: opt.transform.mutable_eliminate 0.01% : 0.000044s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000065s : 4: opt.transform.symbol_engine_opt 0.10% : 0.000619s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000014s : 1: pre_auto_parallel 0.06% : 0.000345s : 1: py_interpret_to_execute 0.00% : 0.000028s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000034s : 1: remove_dup_value 0.42% : 0.002583s : 1: renormalize.infer 0.17% : 0.001026s : 1: renormalize.specialize 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000297s : 1: rewriter_after_opt_a 0.04% : 0.000223s : 1: rewriter_before_opt_a 0.02% : 0.000119s : 1: symbol_engine_optimizer 86.06% : 0.525127s : 1: type_inference . [hook] pytest_runtest_teardown:test_graph_view_out tests/st/ops/host/view/test_view_ops.py::test_graph_view_out,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 69.65s (0:01:09) ===================