==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/mint, configfile: ../../../../../../sault/virtual_test/virtualenv_004/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_reshape.py . [hook] pytest_runtest_teardown:test_reshape_same_shape[pynative] tests/st/mint/test_reshape.py::test_reshape_same_shape[pynative],max_mem:2.0M [WARNING] PARSER(165741,ffffbb5eaf30,python3.9):2026-01-29-17:40:30.602.695 [mindspore/ccsrc/frontend/jit/ps/parse/data_converter.cc:661] CheckAPI] The mint interface reshape was called, and the operators under this interface have different view capabilities on pynative and graph mode. Use this interface with caution in graph mode, as it may produce unexpected results. For more information, please refer to: https://www.mindspore.cn/docs/en/master/features/view.html TotalTime = 1.42236, [30] [bootstrap]: 0.00061656 [type_inference]: 1.0308 [event_method]: 2.358e-05 [auto_monad]: 0.00069315 [graph_reusing]: 6.11998e-06 [pre_auto_parallel]: 4.809e-05 [py_interpret_to_execute]: 0.00222632 [rewriter_before_opt_a]: 0.00035675 [expand_dump_flag]: 4.48999e-06 [jit_opt_a]: 0.384152, [2] [Cycle 1]: 0.00428092, [27] [switch_simplify]: 9.169e-05 [loop_unroll]: 3.523e-05 [a_1]: 0.00068006 [with_stream_mark]: 3.039e-05 [recompute_prepare]: 1.075e-05 [updatestate_depend_eliminate]: 4.56002e-06 [updatestate_assign_eliminate]: 2.57001e-06 [updatestate_loads_eliminate]: 2.56998e-06 [parameter_eliminate]: 2.53003e-06 [specialize_transform]: 5.79999e-06 [updatestate_useless_node_eliminater]: 4.50001e-06 [accelerated_algorithm]: 5.37999e-06 [meta_shard_fg_expand]: 2.65997e-06 [get_grad_eliminate_]: 4.68001e-06 [merge_forward]: 3.58999e-06 [cell_reuse_recompute_pass]: 1.59e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.697e-05 [j_node_and_user_rematch]: 8.15999e-06 [meta_fg_expand]: 2.32999e-06 [replace_old_param]: 1.067e-05 [inline_without_move]: 4.98001e-06 [renormalize]: 0.00299117 [add_forward_monad_depend]: 1.857e-05 [auto_monad_grad]: 2.76999e-06 [auto_monad_eliminator]: 2.186e-05 [cse]: 3.184e-05 [replace_applicator]: 2.354e-05 [Cycle 2]: 0.00051918, [27] [switch_simplify]: 5.99e-06 [loop_unroll]: 5.61998e-06 [a_1]: 8.093e-05 [with_stream_mark]: 0.00016635 [recompute_prepare]: 1.081e-05 [updatestate_depend_eliminate]: 4.82e-06 [updatestate_assign_eliminate]: 3.22002e-06 [updatestate_loads_eliminate]: 2.34001e-06 [parameter_eliminate]: 3.20002e-06 [specialize_transform]: 5.72999e-06 [updatestate_useless_node_eliminater]: 5.15001e-06 [accelerated_algorithm]: 6.18002e-06 [meta_shard_fg_expand]: 1.99e-06 [get_grad_eliminate_]: 4.52e-06 [merge_forward]: 3.6e-06 [cell_reuse_recompute_pass]: 3.16001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.728e-05 [j_node_and_user_rematch]: 7.39002e-06 [meta_fg_expand]: 2.39999e-06 [replace_old_param]: 9.74999e-06 [inline_without_move]: 4.19002e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.91e-06 [auto_monad_grad]: 1.55001e-06 [auto_monad_eliminator]: 5.66998e-06 [cse]: 1.721e-05 [replace_applicator]: 4.79002e-06 [py_interpret_to_execute_after_opt_a]: 1.758e-05 [rewriter_after_opt_a]: 5.379e-05 [convert_after_rewriter]: 1.996e-05 [order_py_execute_after_rewriter]: 4.94e-06 [mutable_eliminate]: 0.0008985 [jit_opt_b]: 6.411e-05, [1] [Cycle 1]: 5.301e-05, [2] [frontend_op_eliminate]: 2.003e-05 [inline_after_opt_a]: 1.424e-05 [cconv]: 3.745e-05 [loop_unroll]: 0.00056593 [jit_opt_after_cconv]: 0.00023446, [1] [Cycle 1]: 0.00022473, [11] [c_1]: 1.813e-05 [parameter_eliminate]: 5.62999e-06 [updatestate_depend_eliminate]: 1.041e-05 [updatestate_assign_eliminate]: 2.69001e-06 [updatestate_loads_eliminate]: 2.24001e-06 [cse]: 2.745e-05 [call_graph_tuple_transform]: 2.332e-05 [tuple_list_get_item_eliminator]: 5.08002e-06 [none_parameter_eliminate]: 1.73002e-06 [renormalize]: 3.39991e-07 [switch_simplify]: 5.25999e-06 [remove_dup_value]: 1.489e-05 [partial_unused_args_eliminate]: 2.29001e-06 [environ_conv]: 2.286e-05 [add_recomputation]: 4.756e-05 [cse_after_recomputation]: 2.551e-05, [1] [Cycle 1]: 1.883e-05, [1] [cse]: 1.154e-05 [auto_monad_reorder]: 2.296e-05 [get_jit_bprop_graph]: 2.34999e-06 [rewriter_after_jit_bprop_graph]: 0.00020262 [opt_after_jit_grad]: 0.0005679 [symbol_engine_optimizer]: 0.00016596, [1] [Cycle 1]: 0.00015291, [6] [build]: 5.15001e-06 [elim_shapecalc]: 7.86001e-06 [elim_not_effective]: 1.32e-05 [opt_reshape]: 5.57001e-06 [fold_const_symbol]: 8.42e-06 [renormalize]: 7.39994e-07 [validate]: 6.663e-05 Sums bootstrap : 0.000617s : 0.06% type_inference : 1.030798s : 98.93% event_method : 0.000024s : 0.00% auto_monad : 0.000693s : 0.07% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000048s : 0.00% py_interpret_to_execute : 0.002226s : 0.21% rewriter_before_opt_a : 0.000357s : 0.03% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000098s : 0.01% jit_opt_a.loop_unroll : 0.000041s : 0.00% jit_opt_a.a_1 : 0.000761s : 0.07% jit_opt_a.with_stream_mark : 0.000197s : 0.02% jit_opt_a.recompute_prepare : 0.000022s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_a.parameter_eliminate : 0.000006s : 0.00% jit_opt_a.specialize_transform : 0.000012s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000010s : 0.00% jit_opt_a.accelerated_algorithm : 0.000012s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000009s : 0.00% jit_opt_a.merge_forward : 0.000007s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000034s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000016s : 0.00% jit_opt_a.meta_fg_expand : 0.000005s : 0.00% jit_opt_a.replace_old_param : 0.000020s : 0.00% jit_opt_a.inline_without_move : 0.000009s : 0.00% jit_opt_a.renormalize : 0.002991s : 0.29% jit_opt_a.add_forward_monad_depend : 0.000020s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000028s : 0.00% jit_opt_a.cse : 0.000049s : 0.00% jit_opt_a.replace_applicator : 0.000028s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000054s : 0.01% convert_after_rewriter : 0.000020s : 0.00% order_py_execute_after_rewriter : 0.000005s : 0.00% mutable_eliminate : 0.000899s : 0.09% jit_opt_b.frontend_op_eliminate : 0.000020s : 0.00% jit_opt_b.inline_after_opt_a : 0.000014s : 0.00% cconv : 0.000037s : 0.00% loop_unroll : 0.000566s : 0.05% jit_opt_after_cconv.c_1 : 0.000018s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.cse : 0.000027s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000023s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000005s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000005s : 0.00% remove_dup_value : 0.000015s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000023s : 0.00% add_recomputation : 0.000048s : 0.00% cse_after_recomputation.cse : 0.000012s : 0.00% auto_monad_reorder : 0.000023s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000203s : 0.02% opt_after_jit_grad : 0.000568s : 0.05% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000008s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000013s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000006s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000008s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000067s : 0.01% Time group info: ------[substitution.] 0.000273 17 0.86% : 0.000002s : 1: substitution.elim_not_effective 0.44% : 0.000001s : 1: substitution.fold_const_symbol 2.15% : 0.000006s : 2: substitution.graph_param_transform 83.92% : 0.000229s : 5: substitution.inline 1.38% : 0.000004s : 2: substitution.j_node_and_user_rematch 1.46% : 0.000004s : 2: substitution.remove_not_recompute_node 2.76% : 0.000008s : 2: substitution.replace_old_param 3.67% : 0.000010s : 1: substitution.reshape_eliminate 3.36% : 0.000009s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.030399 2 91.33% : 0.941106s : 1: type_inference.infer 8.67% : 0.089293s : 1: type_inference.specialize ------[replace.] 0.000073 7 77.77% : 0.000057s : 5: replace.inline 9.74% : 0.000007s : 1: replace.reshape_eliminate 12.49% : 0.000009s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000243 7 92.78% : 0.000226s : 5: match.inline 3.75% : 0.000009s : 1: match.reshape_eliminate 3.47% : 0.000008s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000143 664 1.16% : 0.000002s : 10: predicate.accumulaten_eliminater 1.02% : 0.000001s : 2: predicate.ad_related_special_op_eliminate 1.15% : 0.000002s : 10: predicate.addn_check_dump 1.19% : 0.000002s : 10: predicate.addn_zero_filter 1.91% : 0.000003s : 10: predicate.arithmetic_simplify 1.36% : 0.000002s : 11: predicate.cast_eliminate 0.57% : 0.000001s : 2: predicate.check_bprop_eliminate 1.06% : 0.000002s : 10: predicate.compare_switch_simplify 1.49% : 0.000002s : 10: predicate.depend_value_elim 1.45% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.37% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.76% : 0.000003s : 11: predicate.dict_set_item_eliminator 1.02% : 0.000001s : 2: predicate.dumpgradient_eliminate 0.63% : 0.000001s : 2: predicate.elim_not_effective 0.52% : 0.000001s : 2: predicate.elim_shapecalc_of_broadcastargs 1.16% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.20% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.05% : 0.000002s : 11: predicate.environ_get_depend_swap 1.10% : 0.000002s : 11: predicate.environ_get_eliminate 1.29% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.15% : 0.000000s : 2: predicate.fold_const_symbol 0.66% : 0.000001s : 4: predicate.get_grad_eliminate 0.15% : 0.000000s : 2: predicate.graph_param_transform 4.89% : 0.000007s : 21: predicate.inline 0.52% : 0.000001s : 4: predicate.inline_without_move 0.23% : 0.000000s : 4: predicate.j_node_and_user_rematch 1.50% : 0.000002s : 4: predicate.less_batch_normalization 1.44% : 0.000002s : 12: predicate.list_to_tuple_eliminator_ 1.84% : 0.000003s : 14: predicate.load_eliminater 1.51% : 0.000002s : 2: predicate.loop_unroll_after_grad 4.34% : 0.000006s : 35: predicate.loop_unroll_before_grad 2.27% : 0.000003s : 13: predicate.make_slice_get_slice_eliminator 0.94% : 0.000001s : 10: predicate.merge_addn 1.39% : 0.000002s : 10: predicate.minmaximum_grad 1.93% : 0.000003s : 2: predicate.mutable_eliminate 0.41% : 0.000001s : 2: predicate.opt_reshape 1.88% : 0.000003s : 14: predicate.partial_eliminate 1.38% : 0.000002s : 10: predicate.print_const_string_wrapper 1.92% : 0.000003s : 10: predicate.reduce_eliminate 1.83% : 0.000003s : 12: predicate.redundant_stop_gradient_eliminater 0.52% : 0.000001s : 4: predicate.remove_not_recompute_node 1.66% : 0.000002s : 16: predicate.replace_applicator 0.51% : 0.000001s : 4: predicate.replace_old_param 0.40% : 0.000001s : 2: predicate.reset_defer_inline 1.78% : 0.000003s : 11: predicate.reshape_eliminate 1.07% : 0.000002s : 10: predicate.row_tensor_add_zeros_like 0.68% : 0.000001s : 2: predicate.row_tensor_eliminate 1.49% : 0.000002s : 10: predicate.same_eliminate 0.47% : 0.000001s : 4: predicate.set_cell_output_no_recompute 0.54% : 0.000001s : 4: predicate.special_op_eliminate 0.78% : 0.000001s : 4: predicate.specialize_transform 1.48% : 0.000002s : 10: predicate.split_environ_get_set_with_tuple_value 1.42% : 0.000002s : 10: predicate.stack_unstack_eliminate 0.38% : 0.000001s : 2: predicate.switch_call_monad_eliminater 2.41% : 0.000003s : 17: predicate.switch_defer_inline 1.88% : 0.000003s : 17: predicate.switch_layer_defer_inline 7.93% : 0.000011s : 54: predicate.switch_simplify 1.54% : 0.000002s : 10: predicate.tile_eliminate 1.14% : 0.000002s : 10: predicate.transpose_eliminate 1.60% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.68% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.84% : 0.000006s : 16: predicate.tuple_list_get_item_eliminator 1.63% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.67% : 0.000002s : 12: predicate.tuple_to_list_eliminator_ 1.58% : 0.000002s : 14: predicate.updatestate_pure_node_eliminater 2.81% : 0.000004s : 18: predicate.updatestate_useless_node_eliminater 1.44% : 0.000002s : 10: predicate.value_based_eliminate 0.17% : 0.000000s : 2: predicate.virtual_view_grad_eliminate 0.85% : 0.000001s : 2: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.005204 27 74.79% : 0.003892s : 20: func_graph_cloner_run.FuncGraphClonerGraph 25.21% : 0.001312s : 7: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.426279 72 0.00% : 0.000051s : 1: add_recomputation 0.05% : 0.000702s : 1: auto_monad 0.00% : 0.000026s : 1: auto_monad_reorder 0.04% : 0.000638s : 1: bootstrap 0.00% : 0.000040s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.00% : 0.000028s : 1: cse_after_recomputation 0.00% : 0.000026s : 1: environ_conv 0.00% : 0.000029s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 26.93% : 0.384157s : 1: jit_opt_a 0.02% : 0.000238s : 1: jit_opt_after_cconv 0.00% : 0.000067s : 1: jit_opt_b 0.04% : 0.000578s : 1: loop_unroll 0.07% : 0.000963s : 1: mutable_eliminate 0.07% : 0.001014s : 26: opt.transform.jit_opt_a 0.00% : 0.000048s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000026s : 4: opt.transform.jit_opt_b 0.00% : 0.000013s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.00% : 0.000021s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000031s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000579s : 1: opt_after_jit_grad 0.00% : 0.000007s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000050s : 1: pre_auto_parallel 0.16% : 0.002242s : 1: py_interpret_to_execute 0.00% : 0.000020s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000018s : 1: remove_dup_value 0.14% : 0.001933s : 1: renormalize.infer 0.07% : 0.001042s : 1: renormalize.specialize 0.01% : 0.000207s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000057s : 1: rewriter_after_opt_a 0.03% : 0.000364s : 1: rewriter_before_opt_a 0.01% : 0.000169s : 1: symbol_engine_optimizer 72.27% : 1.030829s : 1: type_inference TotalTime = 1.07905, [30] [bootstrap]: 0.00039773 [type_inference]: 0.962599 [event_method]: 0.00052978 [auto_monad]: 0.00018048 [graph_reusing]: 1.02e-05 [pre_auto_parallel]: 4.06001e-06 [py_interpret_to_execute]: 6.614e-05 [rewriter_before_opt_a]: 0.00017376 [expand_dump_flag]: 4.41002e-06 [jit_opt_a]: 0.111226, [2] [Cycle 1]: 0.106235, [27] [switch_simplify]: 0.00025606 [loop_unroll]: 8.326e-05 [a_1]: 0.00182864 [with_stream_mark]: 4.244e-05 [recompute_prepare]: 2.835e-05 [updatestate_depend_eliminate]: 1.07e-05 [updatestate_assign_eliminate]: 6.73e-06 [updatestate_loads_eliminate]: 6.63998e-06 [parameter_eliminate]: 3.62998e-06 [specialize_transform]: 1.608e-05 [updatestate_useless_node_eliminater]: 1.484e-05 [accelerated_algorithm]: 1.371e-05 [meta_shard_fg_expand]: 6.22001e-06 [get_grad_eliminate_]: 1.33e-05 [merge_forward]: 1.144e-05 [cell_reuse_recompute_pass]: 2.06e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.261e-05 [j_node_and_user_rematch]: 2.568e-05 [meta_fg_expand]: 0.00148664 [replace_old_param]: 5.929e-05 [inline_without_move]: 4.268e-05 [renormalize]: 0.101761 [add_forward_monad_depend]: 9.02e-06 [auto_monad_grad]: 2.61999e-06 [auto_monad_eliminator]: 2.012e-05 [cse]: 3.601e-05 [replace_applicator]: 2.667e-05 [Cycle 2]: 0.00071512, [27] [switch_simplify]: 6.18002e-06 [loop_unroll]: 6.09999e-06 [a_1]: 6.662e-05 [with_stream_mark]: 1.927e-05 [recompute_prepare]: 4.65001e-06 [updatestate_depend_eliminate]: 3.95e-06 [updatestate_assign_eliminate]: 2.75002e-06 [updatestate_loads_eliminate]: 2.36e-06 [parameter_eliminate]: 2.61999e-06 [specialize_transform]: 4.17003e-06 [updatestate_useless_node_eliminater]: 3.79002e-06 [accelerated_algorithm]: 4.68999e-06 [meta_shard_fg_expand]: 2.02001e-06 [get_grad_eliminate_]: 3.97998e-06 [merge_forward]: 3.6e-06 [cell_reuse_recompute_pass]: 3.13e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.964e-05 [j_node_and_user_rematch]: 7.41999e-06 [meta_fg_expand]: 0.00029001 [replace_old_param]: 1.378e-05 [inline_without_move]: 4.93001e-06 [renormalize]: 1.10012e-07 [add_forward_monad_depend]: 3.93001e-06 [auto_monad_grad]: 2.63e-06 [auto_monad_eliminator]: 9.41003e-06 [cse]: 2.221e-05 [replace_applicator]: 5.84e-06 [py_interpret_to_execute_after_opt_a]: 1.998e-05 [rewriter_after_opt_a]: 0.00055181 [convert_after_rewriter]: 1.8e-05 [order_py_execute_after_rewriter]: 5.71e-06 [mutable_eliminate]: 0.00097763 [jit_opt_b]: 6.621e-05, [1] [Cycle 1]: 5.498e-05, [2] [frontend_op_eliminate]: 1.844e-05 [inline_after_opt_a]: 1.94e-05 [cconv]: 4.318e-05 [loop_unroll]: 0.00079968 [jit_opt_after_cconv]: 0.00020549, [1] [Cycle 1]: 0.00019661, [11] [c_1]: 2.102e-05 [parameter_eliminate]: 8.09002e-06 [updatestate_depend_eliminate]: 1.433e-05 [updatestate_assign_eliminate]: 3.18e-06 [updatestate_loads_eliminate]: 2.72001e-06 [cse]: 4.585e-05 [call_graph_tuple_transform]: 2.585e-05 [tuple_list_get_item_eliminator]: 5.97001e-06 [none_parameter_eliminate]: 1.72001e-06 [renormalize]: 1.09e-06 [switch_simplify]: 6.33002e-06 [remove_dup_value]: 1.956e-05 [partial_unused_args_eliminate]: 2.63e-06 [environ_conv]: 6.96001e-06 [add_recomputation]: 5.113e-05 [cse_after_recomputation]: 2.438e-05, [1] [Cycle 1]: 1.762e-05, [1] [cse]: 1.019e-05 [auto_monad_reorder]: 1.533e-05 [get_jit_bprop_graph]: 2.93998e-06 [rewriter_after_jit_bprop_graph]: 1.012e-05 [opt_after_jit_grad]: 0.00064741 [symbol_engine_optimizer]: 8.34e-05, [1] [Cycle 1]: 7.56e-05, [6] [build]: 4.99e-06 [elim_shapecalc]: 8.2e-06 [elim_not_effective]: 1.464e-05 [opt_reshape]: 6.66999e-06 [fold_const_symbol]: 8.05e-06 [renormalize]: 6.29982e-07 [validate]: 4.255e-05 Sums bootstrap : 0.000398s : 0.04% type_inference : 0.962599s : 89.65% event_method : 0.000530s : 0.05% auto_monad : 0.000180s : 0.02% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000066s : 0.01% rewriter_before_opt_a : 0.000174s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000262s : 0.02% jit_opt_a.loop_unroll : 0.000089s : 0.01% jit_opt_a.a_1 : 0.001895s : 0.18% jit_opt_a.with_stream_mark : 0.000062s : 0.01% jit_opt_a.recompute_prepare : 0.000033s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000009s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000006s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000019s : 0.00% jit_opt_a.accelerated_algorithm : 0.000018s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000008s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000015s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000052s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000033s : 0.00% jit_opt_a.meta_fg_expand : 0.001777s : 0.17% jit_opt_a.replace_old_param : 0.000073s : 0.01% jit_opt_a.inline_without_move : 0.000048s : 0.00% jit_opt_a.renormalize : 0.101761s : 9.48% jit_opt_a.add_forward_monad_depend : 0.000013s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000030s : 0.00% jit_opt_a.cse : 0.000058s : 0.01% jit_opt_a.replace_applicator : 0.000033s : 0.00% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000552s : 0.05% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000978s : 0.09% jit_opt_b.frontend_op_eliminate : 0.000018s : 0.00% jit_opt_b.inline_after_opt_a : 0.000019s : 0.00% cconv : 0.000043s : 0.00% loop_unroll : 0.000800s : 0.07% jit_opt_after_cconv.c_1 : 0.000021s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000046s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000006s : 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 : 0.000006s : 0.00% remove_dup_value : 0.000020s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000007s : 0.00% add_recomputation : 0.000051s : 0.00% cse_after_recomputation.cse : 0.000010s : 0.00% auto_monad_reorder : 0.000015s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000647s : 0.06% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000008s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000015s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000007s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000008s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000043s : 0.00% Time group info: ------[substitution.] 0.000596 62 0.40% : 0.000002s : 1: substitution.elim_not_effective 0.21% : 0.000001s : 1: substitution.fold_const_symbol 0.98% : 0.000006s : 1: substitution.graph_param_transform 78.26% : 0.000466s : 14: substitution.inline 2.97% : 0.000018s : 1: substitution.inline_without_move 1.38% : 0.000008s : 8: substitution.j_node_and_user_rematch 0.75% : 0.000004s : 2: substitution.minmaximum_grad 1.71% : 0.000010s : 9: substitution.partial_eliminate 1.31% : 0.000008s : 8: substitution.remove_not_recompute_node 0.57% : 0.000003s : 1: substitution.replace_applicator 0.86% : 0.000005s : 4: substitution.replace_old_param 1.32% : 0.000008s : 1: substitution.reshape_eliminate 0.59% : 0.000004s : 1: substitution.set_cell_output_no_recompute 3.05% : 0.000018s : 3: substitution.switch_simplify 1.50% : 0.000009s : 2: substitution.tuple_list_convert_item_index_to_positive 1.00% : 0.000006s : 2: substitution.tuple_list_get_item_depend_reorder 3.14% : 0.000019s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.962425 2 99.43% : 0.956914s : 1: type_inference.infer 0.57% : 0.005511s : 1: type_inference.specialize ------[replace.] 0.000256 19 59.78% : 0.000153s : 14: replace.inline 2.81% : 0.000007s : 1: replace.reshape_eliminate 32.66% : 0.000083s : 3: replace.switch_simplify 4.76% : 0.000012s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000486 19 94.38% : 0.000458s : 14: match.inline 1.39% : 0.000007s : 1: match.reshape_eliminate 3.34% : 0.000016s : 3: match.switch_simplify 0.90% : 0.000004s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000288 1641 1.50% : 0.000004s : 28: predicate.accumulaten_eliminater 0.41% : 0.000001s : 1: predicate.ad_related_special_op_eliminate 1.30% : 0.000004s : 28: predicate.addn_check_dump 1.41% : 0.000004s : 28: predicate.addn_zero_filter 1.81% : 0.000005s : 28: predicate.arithmetic_simplify 1.58% : 0.000005s : 29: predicate.cast_eliminate 0.23% : 0.000001s : 1: predicate.check_bprop_eliminate 1.32% : 0.000004s : 28: predicate.compare_switch_simplify 1.56% : 0.000005s : 28: predicate.depend_value_elim 1.49% : 0.000004s : 29: predicate.dict_get_item_const_eliminator 1.34% : 0.000004s : 29: predicate.dict_get_item_eliminator 1.52% : 0.000004s : 29: predicate.dict_set_item_eliminator 0.49% : 0.000001s : 1: predicate.dumpgradient_eliminate 0.09% : 0.000000s : 1: predicate.elim_not_effective 0.41% : 0.000001s : 1: predicate.elim_shapecalc_of_broadcastargs 1.48% : 0.000004s : 29: predicate.environ_add_const_eliminate 1.39% : 0.000004s : 29: predicate.environ_get_add_eliminate 1.27% : 0.000004s : 29: predicate.environ_get_depend_swap 1.50% : 0.000004s : 29: predicate.environ_get_eliminate 1.35% : 0.000004s : 29: predicate.environ_get_set_eliminate 0.04% : 0.000000s : 1: predicate.fold_const_symbol 0.83% : 0.000002s : 12: predicate.get_grad_eliminate 0.12% : 0.000000s : 1: predicate.graph_param_transform 5.10% : 0.000015s : 46: predicate.inline 1.39% : 0.000004s : 19: predicate.inline_without_move 0.32% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.03% : 0.000003s : 12: predicate.less_batch_normalization 1.85% : 0.000005s : 30: predicate.list_to_tuple_eliminator_ 1.59% : 0.000005s : 31: predicate.load_eliminater 0.98% : 0.000003s : 1: predicate.loop_unroll_after_grad 4.41% : 0.000013s : 78: predicate.loop_unroll_before_grad 1.93% : 0.000006s : 30: predicate.make_slice_get_slice_eliminator 1.30% : 0.000004s : 28: predicate.merge_addn 1.30% : 0.000004s : 28: predicate.minmaximum_grad 0.95% : 0.000003s : 1: predicate.mutable_eliminate 0.25% : 0.000001s : 1: predicate.opt_reshape 2.02% : 0.000006s : 31: predicate.partial_eliminate 1.30% : 0.000004s : 28: predicate.print_const_string_wrapper 1.69% : 0.000005s : 28: predicate.reduce_eliminate 1.59% : 0.000005s : 30: predicate.redundant_stop_gradient_eliminater 0.46% : 0.000001s : 12: predicate.remove_not_recompute_node 1.60% : 0.000005s : 32: predicate.replace_applicator 1.12% : 0.000003s : 19: predicate.replace_old_param 0.16% : 0.000000s : 1: predicate.reset_defer_inline 1.56% : 0.000004s : 29: predicate.reshape_eliminate 1.41% : 0.000004s : 28: predicate.row_tensor_add_zeros_like 0.48% : 0.000001s : 1: predicate.row_tensor_eliminate 1.29% : 0.000004s : 28: predicate.same_eliminate 0.45% : 0.000001s : 12: predicate.set_cell_output_no_recompute 0.50% : 0.000001s : 2: predicate.special_op_eliminate 0.87% : 0.000003s : 12: predicate.specialize_transform 1.64% : 0.000005s : 28: predicate.split_environ_get_set_with_tuple_value 1.38% : 0.000004s : 28: predicate.stack_unstack_eliminate 0.19% : 0.000001s : 1: predicate.switch_call_monad_eliminater 3.54% : 0.000010s : 44: predicate.switch_defer_inline 2.83% : 0.000008s : 44: predicate.switch_layer_defer_inline 8.25% : 0.000024s : 129: predicate.switch_simplify 1.52% : 0.000004s : 28: predicate.tile_eliminate 1.43% : 0.000004s : 28: predicate.transpose_eliminate 1.63% : 0.000005s : 29: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000005s : 29: predicate.tuple_list_get_item_depend_reorder 2.95% : 0.000009s : 32: predicate.tuple_list_get_item_eliminator 1.78% : 0.000005s : 29: predicate.tuple_list_set_item_eliminator 1.55% : 0.000004s : 30: predicate.tuple_to_list_eliminator_ 1.67% : 0.000005s : 31: predicate.updatestate_pure_node_eliminater 2.49% : 0.000007s : 43: predicate.updatestate_useless_node_eliminater 1.72% : 0.000005s : 28: predicate.value_based_eliminate 0.09% : 0.000000s : 1: predicate.virtual_view_grad_eliminate 0.38% : 0.000001s : 1: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.103319 49 99.10% : 0.102390s : 32: func_graph_cloner_run.FuncGraphClonerGraph 0.90% : 0.000929s : 17: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.183399 72 0.00% : 0.000054s : 1: add_recomputation 0.02% : 0.000188s : 1: auto_monad 0.00% : 0.000018s : 1: auto_monad_reorder 0.04% : 0.000424s : 1: bootstrap 0.00% : 0.000046s : 1: cconv 0.00% : 0.000021s : 1: convert_after_rewriter 0.00% : 0.000027s : 1: cse_after_recomputation 0.00% : 0.000009s : 1: environ_conv 0.05% : 0.000541s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000013s : 1: graph_reusing 9.40% : 0.111232s : 1: jit_opt_a 0.02% : 0.000210s : 1: jit_opt_after_cconv 0.01% : 0.000071s : 1: jit_opt_b 0.07% : 0.000815s : 1: loop_unroll 0.08% : 0.000996s : 1: mutable_eliminate 0.21% : 0.002543s : 26: opt.transform.jit_opt_a 0.00% : 0.000055s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000027s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000025s : 1: opt.transform.mutable_eliminate 0.00% : 0.000021s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000033s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000659s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000070s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000022s : 1: remove_dup_value 8.50% : 0.100632s : 1: renormalize.infer 0.09% : 0.001113s : 1: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000563s : 1: rewriter_after_opt_a 0.01% : 0.000177s : 1: rewriter_before_opt_a 0.01% : 0.000087s : 1: symbol_engine_optimizer 81.34% : 0.962623s : 1: type_inference . [hook] pytest_runtest_teardown:test_reshape_same_shape[KBK] tests/st/mint/test_reshape.py::test_reshape_same_shape[KBK],max_mem:2.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 223.06s (0:03:43) ==================