==================================================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_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 10 items test_narrow.py . [hook] pytest_runtest_teardown:test_narrow_special_values[inf-pynative] tests/st/mint/test_narrow.py::test_narrow_special_values[inf-pynative],max_mem:2.0M TotalTime = 0.481242, [30] [bootstrap]: 0.0005953 [type_inference]: 0.429073 [event_method]: 1.744e-05 [auto_monad]: 0.00019006 [graph_reusing]: 6.93e-06 [pre_auto_parallel]: 1.264e-05 [py_interpret_to_execute]: 9.601e-05 [rewriter_before_opt_a]: 7.668e-05 [expand_dump_flag]: 3.18e-06 [jit_opt_a]: 0.0227451, [2] [Cycle 1]: 0.0021557, [27] [switch_simplify]: 5.964e-05 [loop_unroll]: 2.147e-05 [a_1]: 0.00043384 [with_stream_mark]: 2.992e-05 [recompute_prepare]: 1.201e-05 [updatestate_depend_eliminate]: 6.72002e-06 [updatestate_assign_eliminate]: 9.79999e-06 [updatestate_loads_eliminate]: 5.30999e-06 [parameter_eliminate]: 1.97999e-06 [specialize_transform]: 1.021e-05 [updatestate_useless_node_eliminater]: 1.326e-05 [accelerated_algorithm]: 1.022e-05 [meta_shard_fg_expand]: 3.26999e-06 [get_grad_eliminate_]: 8.95999e-06 [merge_forward]: 5.84e-06 [cell_reuse_recompute_pass]: 1.20999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.539e-05 [j_node_and_user_rematch]: 1.596e-05 [meta_fg_expand]: 4.35999e-06 [replace_old_param]: 1.379e-05 [inline_without_move]: 8.48001e-06 [renormalize]: 0.00107748 [add_forward_monad_depend]: 1.47e-05 [auto_monad_grad]: 2.74001e-06 [auto_monad_eliminator]: 2.506e-05 [cse]: 5.681e-05 [replace_applicator]: 2.097e-05 [Cycle 2]: 0.00053058, [27] [switch_simplify]: 8.96998e-06 [loop_unroll]: 7.87e-06 [a_1]: 0.00016612 [with_stream_mark]: 1.824e-05 [recompute_prepare]: 9.76e-06 [updatestate_depend_eliminate]: 5.62001e-06 [updatestate_assign_eliminate]: 5.13002e-06 [updatestate_loads_eliminate]: 4.25e-06 [parameter_eliminate]: 1.62001e-06 [specialize_transform]: 8.38001e-06 [updatestate_useless_node_eliminater]: 1.367e-05 [accelerated_algorithm]: 7.75998e-06 [meta_shard_fg_expand]: 2.24001e-06 [get_grad_eliminate_]: 8.22998e-06 [merge_forward]: 6.36e-06 [cell_reuse_recompute_pass]: 2.37999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.026e-05 [j_node_and_user_rematch]: 1.339e-05 [meta_fg_expand]: 2.91e-06 [replace_old_param]: 1.189e-05 [inline_without_move]: 7.66999e-06 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 2.73e-06 [auto_monad_grad]: 1.78997e-06 [auto_monad_eliminator]: 1.632e-05 [cse]: 2.56e-05 [replace_applicator]: 1.039e-05 [py_interpret_to_execute_after_opt_a]: 2.05e-05 [rewriter_after_opt_a]: 0.0252565 [convert_after_rewriter]: 4.028e-05 [order_py_execute_after_rewriter]: 8.54e-06 [mutable_eliminate]: 0.00080875 [jit_opt_b]: 8.023e-05, [1] [Cycle 1]: 6.888e-05, [2] [frontend_op_eliminate]: 2.528e-05 [inline_after_opt_a]: 2.901e-05 [cconv]: 4.469e-05 [loop_unroll]: 0.00046694 [jit_opt_after_cconv]: 0.00024644, [1] [Cycle 1]: 0.00023841, [11] [c_1]: 5.513e-05 [parameter_eliminate]: 5.52999e-06 [updatestate_depend_eliminate]: 1.192e-05 [updatestate_assign_eliminate]: 5.89999e-06 [updatestate_loads_eliminate]: 5.05999e-06 [cse]: 5.183e-05 [call_graph_tuple_transform]: 2.373e-05 [tuple_list_get_item_eliminator]: 8.85001e-06 [none_parameter_eliminate]: 1.97001e-06 [renormalize]: 9.30013e-07 [switch_simplify]: 8.89998e-06 [remove_dup_value]: 2.962e-05 [partial_unused_args_eliminate]: 2.37999e-06 [environ_conv]: 2.446e-05 [add_recomputation]: 8.39e-05 [cse_after_recomputation]: 3.162e-05, [1] [Cycle 1]: 2.475e-05, [1] [cse]: 1.794e-05 [auto_monad_reorder]: 3.769e-05 [get_jit_bprop_graph]: 2.44001e-06 [rewriter_after_jit_bprop_graph]: 0.00015825 [opt_after_jit_grad]: 0.00054572 [symbol_engine_optimizer]: 0.00010077, [1] [Cycle 1]: 9.289e-05, [6] [build]: 5.79e-06 [elim_shapecalc]: 1.223e-05 [elim_not_effective]: 2.164e-05 [opt_reshape]: 9.39998e-06 [fold_const_symbol]: 1.399e-05 [renormalize]: 7.60017e-07 [validate]: 7.463e-05 Sums bootstrap : 0.000595s : 0.13% type_inference : 0.429073s : 93.22% event_method : 0.000017s : 0.00% auto_monad : 0.000190s : 0.04% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000096s : 0.02% rewriter_before_opt_a : 0.000077s : 0.02% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000069s : 0.01% jit_opt_a.loop_unroll : 0.000029s : 0.01% jit_opt_a.a_1 : 0.000600s : 0.13% jit_opt_a.with_stream_mark : 0.000048s : 0.01% jit_opt_a.recompute_prepare : 0.000022s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000019s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000027s : 0.01% jit_opt_a.accelerated_algorithm : 0.000018s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000046s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000029s : 0.01% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000026s : 0.01% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.001078s : 0.23% jit_opt_a.add_forward_monad_depend : 0.000017s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000041s : 0.01% jit_opt_a.cse : 0.000082s : 0.02% jit_opt_a.replace_applicator : 0.000031s : 0.01% py_interpret_to_execute_after_opt_a : 0.000021s : 0.00% rewriter_after_opt_a : 0.025256s : 5.49% convert_after_rewriter : 0.000040s : 0.01% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000809s : 0.18% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.01% jit_opt_b.inline_after_opt_a : 0.000029s : 0.01% cconv : 0.000045s : 0.01% loop_unroll : 0.000467s : 0.10% jit_opt_after_cconv.c_1 : 0.000055s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000052s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 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 : 0.000009s : 0.00% remove_dup_value : 0.000030s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000024s : 0.01% add_recomputation : 0.000084s : 0.02% cse_after_recomputation.cse : 0.000018s : 0.00% auto_monad_reorder : 0.000038s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000158s : 0.03% opt_after_jit_grad : 0.000546s : 0.12% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000022s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000075s : 0.02% Time group info: ------[substitution.] 0.000218 43 4.59% : 0.000010s : 2: substitution.depend_value_elim 1.47% : 0.000003s : 4: substitution.elim_not_effective 1.03% : 0.000002s : 4: substitution.fold_const_symbol 3.37% : 0.000007s : 5: substitution.graph_param_transform 68.97% : 0.000150s : 2: substitution.inline 2.25% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.54% : 0.000008s : 8: substitution.remove_not_recompute_node 2.91% : 0.000006s : 2: substitution.replace_old_param 7.05% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 4.82% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.428986 2 99.75% : 0.427921s : 1: type_inference.infer 0.25% : 0.001065s : 1: type_inference.specialize ------[replace.] 0.000033 2 100.00% : 0.000033s : 2: replace.inline ------[match.] 0.000148 2 100.00% : 0.000148s : 2: match.inline ------[predicate.] 0.000141 767 1.10% : 0.000002s : 11: predicate.accumulaten_eliminater 1.43% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.00% : 0.000001s : 11: predicate.addn_check_dump 1.43% : 0.000002s : 11: predicate.addn_zero_filter 1.99% : 0.000003s : 11: predicate.arithmetic_simplify 1.17% : 0.000002s : 11: predicate.cast_eliminate 0.58% : 0.000001s : 5: predicate.check_bprop_eliminate 1.02% : 0.000001s : 11: predicate.compare_switch_simplify 1.21% : 0.000002s : 11: predicate.depend_value_elim 1.00% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.18% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.05% : 0.000001s : 11: predicate.dict_set_item_eliminator 1.40% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.71% : 0.000001s : 5: predicate.elim_not_effective 0.81% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.08% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.05% : 0.000001s : 11: predicate.environ_get_add_eliminate 1.03% : 0.000001s : 11: predicate.environ_get_depend_swap 1.15% : 0.000002s : 11: predicate.environ_get_eliminate 1.08% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.34% : 0.000000s : 5: predicate.fold_const_symbol 1.31% : 0.000002s : 10: predicate.get_grad_eliminate 0.47% : 0.000001s : 5: predicate.graph_param_transform 5.72% : 0.000008s : 23: predicate.inline 1.44% : 0.000002s : 10: predicate.inline_without_move 0.59% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.53% : 0.000002s : 10: predicate.less_batch_normalization 1.13% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.73% : 0.000002s : 16: predicate.load_eliminater 1.88% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.70% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.13% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.96% : 0.000001s : 11: predicate.merge_addn 1.11% : 0.000002s : 11: predicate.minmaximum_grad 2.76% : 0.000004s : 5: predicate.mutable_eliminate 0.68% : 0.000001s : 5: predicate.opt_reshape 2.15% : 0.000003s : 16: predicate.partial_eliminate 1.18% : 0.000002s : 11: predicate.print_const_string_wrapper 1.39% : 0.000002s : 11: predicate.reduce_eliminate 1.31% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.92% : 0.000001s : 10: predicate.remove_not_recompute_node 1.66% : 0.000002s : 21: predicate.replace_applicator 0.78% : 0.000001s : 10: predicate.replace_old_param 0.95% : 0.000001s : 5: predicate.reset_defer_inline 1.15% : 0.000002s : 11: predicate.reshape_eliminate 1.11% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.22% : 0.000002s : 5: predicate.row_tensor_eliminate 1.08% : 0.000002s : 11: predicate.same_eliminate 0.72% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.39% : 0.000002s : 10: predicate.special_op_eliminate 1.55% : 0.000002s : 10: predicate.specialize_transform 1.25% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.13% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.75% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.63% : 0.000002s : 13: predicate.switch_defer_inline 1.49% : 0.000002s : 13: predicate.switch_layer_defer_inline 6.29% : 0.000009s : 38: predicate.switch_simplify 1.10% : 0.000002s : 11: predicate.tile_eliminate 1.20% : 0.000002s : 11: predicate.transpose_eliminate 1.22% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.30% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.94% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.41% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.18% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.79% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.86% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.47% : 0.000002s : 11: predicate.value_based_eliminate 0.57% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.89% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000349 5 8.05% : 0.000028s : 1: func_graph_cloner_run.FuncGraphClonerGraph 91.95% : 0.000321s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.483224 72 0.02% : 0.000087s : 1: add_recomputation 0.04% : 0.000197s : 1: auto_monad 0.01% : 0.000041s : 1: auto_monad_reorder 0.13% : 0.000621s : 1: bootstrap 0.01% : 0.000048s : 1: cconv 0.01% : 0.000048s : 1: convert_after_rewriter 0.01% : 0.000034s : 1: cse_after_recomputation 0.01% : 0.000027s : 1: environ_conv 0.00% : 0.000023s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 4.71% : 0.022749s : 1: jit_opt_a 0.05% : 0.000249s : 1: jit_opt_after_cconv 0.02% : 0.000083s : 1: jit_opt_b 0.10% : 0.000476s : 1: loop_unroll 0.17% : 0.000822s : 1: mutable_eliminate 0.19% : 0.000899s : 26: opt.transform.jit_opt_a 0.02% : 0.000093s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000045s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000029s : 1: opt.transform.mutable_eliminate 0.01% : 0.000034s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000053s : 4: opt.transform.symbol_engine_opt 0.12% : 0.000558s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.02% : 0.000100s : 1: py_interpret_to_execute 0.00% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000032s : 1: remove_dup_value 0.14% : 0.000676s : 1: renormalize.infer 0.08% : 0.000391s : 1: renormalize.specialize 0.03% : 0.000162s : 1: rewriter_after_jit_bprop_graph 5.23% : 0.025274s : 1: rewriter_after_opt_a 0.02% : 0.000081s : 1: rewriter_before_opt_a 0.02% : 0.000104s : 1: symbol_engine_optimizer 88.80% : 0.429092s : 1: type_inference TotalTime = 1.10003, [30] [bootstrap]: 0.00052648 [type_inference]: 0.619059 [event_method]: 0.0001801 [auto_monad]: 0.00028024 [graph_reusing]: 9.89999e-06 [pre_auto_parallel]: 3.48e-06 [py_interpret_to_execute]: 5.4e-05 [rewriter_before_opt_a]: 0.00014253 [expand_dump_flag]: 4.25999e-06 [jit_opt_a]: 0.476712, [3] [Cycle 1]: 0.468204, [27] [switch_simplify]: 0.00021279 [loop_unroll]: 5.53e-05 [a_1]: 0.00136574 [with_stream_mark]: 4.281e-05 [recompute_prepare]: 2.786e-05 [updatestate_depend_eliminate]: 1.398e-05 [updatestate_assign_eliminate]: 1.095e-05 [updatestate_loads_eliminate]: 1.022e-05 [parameter_eliminate]: 3.09999e-06 [specialize_transform]: 1.995e-05 [updatestate_useless_node_eliminater]: 2.345e-05 [accelerated_algorithm]: 1.831e-05 [meta_shard_fg_expand]: 5.05001e-06 [get_grad_eliminate_]: 1.804e-05 [merge_forward]: 1.291e-05 [cell_reuse_recompute_pass]: 1.69998e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.94e-05 [j_node_and_user_rematch]: 3.187e-05 [meta_fg_expand]: 0.246024 [replace_old_param]: 0.00012325 [inline_without_move]: 0.00012289 [renormalize]: 0.219011 [add_forward_monad_depend]: 3.169e-05 [auto_monad_grad]: 1.191e-05 [auto_monad_eliminator]: 9.212e-05 [cse]: 0.00033105 [replace_applicator]: 0.00021873 [Cycle 2]: 0.00350222, [27] [switch_simplify]: 6.025e-05 [loop_unroll]: 5.594e-05 [a_1]: 0.00112345 [with_stream_mark]: 3.263e-05 [recompute_prepare]: 1.671e-05 [updatestate_depend_eliminate]: 3.838e-05 [updatestate_assign_eliminate]: 6.28998e-06 [updatestate_loads_eliminate]: 5.24998e-06 [parameter_eliminate]: 3.41999e-06 [specialize_transform]: 1.147e-05 [updatestate_useless_node_eliminater]: 1.256e-05 [accelerated_algorithm]: 9.29e-06 [meta_shard_fg_expand]: 3.94002e-06 [get_grad_eliminate_]: 9.14e-06 [merge_forward]: 6.58e-06 [cell_reuse_recompute_pass]: 1.64e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.148e-05 [j_node_and_user_rematch]: 1.398e-05 [meta_fg_expand]: 0.00011308 [replace_old_param]: 1.822e-05 [inline_without_move]: 9.20001e-06 [renormalize]: 0.00154534 [add_forward_monad_depend]: 1.043e-05 [auto_monad_grad]: 2.96999e-06 [auto_monad_eliminator]: 2.733e-05 [cse]: 9.345e-05 [replace_applicator]: 2.784e-05 [Cycle 3]: 0.00057804, [27] [switch_simplify]: 1.024e-05 [loop_unroll]: 8.84e-06 [a_1]: 0.0002095 [with_stream_mark]: 2.022e-05 [recompute_prepare]: 9.94001e-06 [updatestate_depend_eliminate]: 7.54002e-06 [updatestate_assign_eliminate]: 5.49998e-06 [updatestate_loads_eliminate]: 5.03002e-06 [parameter_eliminate]: 1.80001e-06 [specialize_transform]: 9.72999e-06 [updatestate_useless_node_eliminater]: 1.198e-05 [accelerated_algorithm]: 9.17001e-06 [meta_shard_fg_expand]: 2.73e-06 [get_grad_eliminate_]: 7.84002e-06 [merge_forward]: 5.77999e-06 [cell_reuse_recompute_pass]: 3.3e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.057e-05 [j_node_and_user_rematch]: 1.443e-05 [meta_fg_expand]: 3.47002e-06 [replace_old_param]: 1.231e-05 [inline_without_move]: 8.15e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.22001e-06 [auto_monad_grad]: 2.22001e-06 [auto_monad_eliminator]: 1.199e-05 [cse]: 2.946e-05 [replace_applicator]: 9.85002e-06 [py_interpret_to_execute_after_opt_a]: 2.235e-05 [rewriter_after_opt_a]: 0.00021143 [convert_after_rewriter]: 1.254e-05 [order_py_execute_after_rewriter]: 7.54002e-06 [mutable_eliminate]: 0.00082083 [jit_opt_b]: 7.848e-05, [1] [Cycle 1]: 6.892e-05, [2] [frontend_op_eliminate]: 2.712e-05 [inline_after_opt_a]: 2.793e-05 [cconv]: 3.485e-05 [loop_unroll]: 0.00048296 [jit_opt_after_cconv]: 0.0002332, [1] [Cycle 1]: 0.00022548, [11] [c_1]: 5.035e-05 [parameter_eliminate]: 4.62998e-06 [updatestate_depend_eliminate]: 1.199e-05 [updatestate_assign_eliminate]: 5.57001e-06 [updatestate_loads_eliminate]: 4.79e-06 [cse]: 4.29e-05 [call_graph_tuple_transform]: 2.574e-05 [tuple_list_get_item_eliminator]: 9.12999e-06 [none_parameter_eliminate]: 2.09e-06 [renormalize]: 9.70002e-07 [switch_simplify]: 9.06998e-06 [remove_dup_value]: 2.803e-05 [partial_unused_args_eliminate]: 2.46e-06 [environ_conv]: 8.77e-06 [add_recomputation]: 7.66e-05 [cse_after_recomputation]: 3.766e-05, [1] [Cycle 1]: 3.086e-05, [1] [cse]: 2.348e-05 [auto_monad_reorder]: 2.902e-05 [get_jit_bprop_graph]: 2.22001e-06 [rewriter_after_jit_bprop_graph]: 7.33e-06 [opt_after_jit_grad]: 0.00053804 [symbol_engine_optimizer]: 0.00010136, [1] [Cycle 1]: 9.415e-05, [6] [build]: 7.18e-06 [elim_shapecalc]: 1.206e-05 [elim_not_effective]: 2.016e-05 [opt_reshape]: 9.10001e-06 [fold_const_symbol]: 1.386e-05 [renormalize]: 5.29981e-07 [validate]: 5.792e-05 Sums bootstrap : 0.000526s : 0.05% type_inference : 0.619059s : 56.56% event_method : 0.000180s : 0.02% auto_monad : 0.000280s : 0.03% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000054s : 0.00% rewriter_before_opt_a : 0.000143s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000283s : 0.03% jit_opt_a.loop_unroll : 0.000120s : 0.01% jit_opt_a.a_1 : 0.002699s : 0.25% jit_opt_a.with_stream_mark : 0.000096s : 0.01% jit_opt_a.recompute_prepare : 0.000055s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000060s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000023s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000020s : 0.00% jit_opt_a.parameter_eliminate : 0.000008s : 0.00% jit_opt_a.specialize_transform : 0.000041s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000048s : 0.00% jit_opt_a.accelerated_algorithm : 0.000037s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000012s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000035s : 0.00% jit_opt_a.merge_forward : 0.000025s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000081s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000060s : 0.01% jit_opt_a.meta_fg_expand : 0.246141s : 22.49% jit_opt_a.replace_old_param : 0.000154s : 0.01% jit_opt_a.inline_without_move : 0.000140s : 0.01% jit_opt_a.renormalize : 0.220556s : 20.15% jit_opt_a.add_forward_monad_depend : 0.000044s : 0.00% jit_opt_a.auto_monad_grad : 0.000017s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000131s : 0.01% jit_opt_a.cse : 0.000454s : 0.04% jit_opt_a.replace_applicator : 0.000256s : 0.02% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.000211s : 0.02% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000821s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000027s : 0.00% jit_opt_b.inline_after_opt_a : 0.000028s : 0.00% cconv : 0.000035s : 0.00% loop_unroll : 0.000483s : 0.04% jit_opt_after_cconv.c_1 : 0.000050s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000043s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 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 : 0.000009s : 0.00% remove_dup_value : 0.000028s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000009s : 0.00% add_recomputation : 0.000077s : 0.01% cse_after_recomputation.cse : 0.000023s : 0.00% auto_monad_reorder : 0.000029s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000538s : 0.05% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000058s : 0.01% Time group info: ------[substitution.] 0.001756 170 1.36% : 0.000024s : 8: substitution.depend_value_elim 0.21% : 0.000004s : 4: substitution.elim_not_effective 0.12% : 0.000002s : 4: substitution.fold_const_symbol 49.96% : 0.000877s : 4: substitution.getattr_setattr_resolve 0.41% : 0.000007s : 5: substitution.graph_param_transform 30.32% : 0.000532s : 15: substitution.inline 2.10% : 0.000037s : 4: substitution.inline_without_move 0.70% : 0.000012s : 20: substitution.j_node_and_user_rematch 0.58% : 0.000010s : 5: substitution.minmaximum_grad 0.46% : 0.000008s : 9: substitution.partial_eliminate 0.85% : 0.000015s : 20: substitution.remove_not_recompute_node 3.12% : 0.000055s : 12: substitution.replace_applicator 1.01% : 0.000018s : 17: substitution.replace_old_param 0.22% : 0.000004s : 1: substitution.set_cell_output_no_recompute 0.79% : 0.000014s : 3: substitution.switch_simplify 1.29% : 0.000023s : 5: substitution.tuple_list_convert_item_index_to_positive 0.82% : 0.000014s : 5: substitution.tuple_list_get_item_depend_reorder 2.11% : 0.000037s : 8: substitution.tuple_list_get_item_eliminator 1.22% : 0.000022s : 8: substitution.updatestate_pure_node_eliminater 2.35% : 0.000041s : 13: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.618943 2 99.53% : 0.616031s : 1: type_inference.infer 0.47% : 0.002912s : 1: type_inference.specialize ------[replace.] 0.000458 26 17.51% : 0.000080s : 3: replace.getattr_setattr_resolve 27.81% : 0.000127s : 15: replace.inline 12.76% : 0.000058s : 1: replace.replace_applicator 15.59% : 0.000071s : 3: replace.switch_simplify 20.84% : 0.000095s : 3: replace.tuple_list_get_item_eliminator 5.49% : 0.000025s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.001379 26 58.08% : 0.000801s : 3: match.getattr_setattr_resolve 37.83% : 0.000522s : 15: match.inline 1.30% : 0.000018s : 1: match.replace_applicator 0.85% : 0.000012s : 3: match.switch_simplify 0.71% : 0.000010s : 3: match.tuple_list_get_item_eliminator 1.23% : 0.000017s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000500 3150 1.49% : 0.000007s : 50: predicate.accumulaten_eliminater 0.39% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.35% : 0.000007s : 50: predicate.addn_check_dump 1.51% : 0.000008s : 50: predicate.addn_zero_filter 2.06% : 0.000010s : 50: predicate.arithmetic_simplify 1.49% : 0.000007s : 50: predicate.cast_eliminate 0.27% : 0.000001s : 5: predicate.check_bprop_eliminate 1.30% : 0.000007s : 50: predicate.compare_switch_simplify 1.51% : 0.000008s : 50: predicate.depend_value_elim 1.35% : 0.000007s : 50: predicate.dict_get_item_const_eliminator 1.37% : 0.000007s : 50: predicate.dict_get_item_eliminator 1.45% : 0.000007s : 50: predicate.dict_set_item_eliminator 0.34% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.12% : 0.000001s : 5: predicate.elim_not_effective 0.25% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.33% : 0.000007s : 50: predicate.environ_add_const_eliminate 1.26% : 0.000006s : 50: predicate.environ_get_add_eliminate 1.35% : 0.000007s : 50: predicate.environ_get_depend_swap 1.34% : 0.000007s : 50: predicate.environ_get_eliminate 1.29% : 0.000006s : 50: predicate.environ_get_set_eliminate 0.09% : 0.000000s : 5: predicate.fold_const_symbol 0.90% : 0.000004s : 26: predicate.get_grad_eliminate 1.77% : 0.000009s : 20: predicate.getattr_setattr_resolve 0.14% : 0.000001s : 5: predicate.graph_param_transform 4.29% : 0.000021s : 79: predicate.inline 3.21% : 0.000016s : 87: predicate.inline_without_move 0.39% : 0.000002s : 26: predicate.j_node_and_user_rematch 1.08% : 0.000005s : 26: predicate.less_batch_normalization 1.55% : 0.000008s : 53: predicate.list_to_tuple_eliminator_ 1.65% : 0.000008s : 58: predicate.load_eliminater 0.58% : 0.000003s : 5: predicate.loop_unroll_after_grad 3.63% : 0.000018s : 127: predicate.loop_unroll_before_grad 1.76% : 0.000009s : 55: predicate.make_slice_get_slice_eliminator 1.30% : 0.000006s : 50: predicate.merge_addn 1.35% : 0.000007s : 50: predicate.minmaximum_grad 0.87% : 0.000004s : 5: predicate.mutable_eliminate 0.19% : 0.000001s : 5: predicate.opt_reshape 2.18% : 0.000011s : 58: predicate.partial_eliminate 1.31% : 0.000007s : 50: predicate.print_const_string_wrapper 1.84% : 0.000009s : 50: predicate.reduce_eliminate 1.61% : 0.000008s : 53: predicate.redundant_stop_gradient_eliminater 0.54% : 0.000003s : 26: predicate.remove_not_recompute_node 2.67% : 0.000013s : 126: predicate.replace_applicator 1.59% : 0.000008s : 87: predicate.replace_old_param 0.17% : 0.000001s : 5: predicate.reset_defer_inline 1.56% : 0.000008s : 50: predicate.reshape_eliminate 1.48% : 0.000007s : 50: predicate.row_tensor_add_zeros_like 0.28% : 0.000001s : 5: predicate.row_tensor_eliminate 1.37% : 0.000007s : 50: predicate.same_eliminate 0.54% : 0.000003s : 28: predicate.set_cell_output_no_recompute 0.37% : 0.000002s : 10: predicate.special_op_eliminate 1.04% : 0.000005s : 26: predicate.specialize_transform 1.61% : 0.000008s : 50: predicate.split_environ_get_set_with_tuple_value 1.35% : 0.000007s : 50: predicate.stack_unstack_eliminate 0.22% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.41% : 0.000012s : 69: predicate.switch_defer_inline 2.20% : 0.000011s : 69: predicate.switch_layer_defer_inline 6.86% : 0.000034s : 207: predicate.switch_simplify 1.43% : 0.000007s : 50: predicate.tile_eliminate 1.36% : 0.000007s : 50: predicate.transpose_eliminate 1.69% : 0.000008s : 50: predicate.tuple_list_convert_item_index_to_positive 1.55% : 0.000008s : 50: predicate.tuple_list_get_item_depend_reorder 3.14% : 0.000016s : 63: predicate.tuple_list_get_item_eliminator 1.75% : 0.000009s : 50: predicate.tuple_list_set_item_eliminator 1.54% : 0.000008s : 53: predicate.tuple_to_list_eliminator_ 1.78% : 0.000009s : 58: predicate.updatestate_pure_node_eliminater 2.85% : 0.000014s : 85: predicate.updatestate_useless_node_eliminater 1.73% : 0.000009s : 50: predicate.value_based_eliminate 0.16% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.24% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003732 44 60.62% : 0.002263s : 18: func_graph_cloner_run.FuncGraphClonerGraph 39.38% : 0.001470s : 26: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.325665 89 0.01% : 0.000080s : 1: add_recomputation 0.02% : 0.000291s : 1: auto_monad 0.00% : 0.000032s : 1: auto_monad_reorder 0.04% : 0.000564s : 1: bootstrap 0.00% : 0.000038s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.00% : 0.000040s : 1: cse_after_recomputation 0.00% : 0.000012s : 1: environ_conv 0.01% : 0.000190s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 35.96% : 0.476717s : 1: jit_opt_a 0.02% : 0.000236s : 1: jit_opt_after_cconv 0.01% : 0.000081s : 1: jit_opt_b 0.04% : 0.000494s : 1: loop_unroll 0.06% : 0.000833s : 1: mutable_eliminate 0.30% : 0.003945s : 39: opt.transform.jit_opt_a 0.01% : 0.000090s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000047s : 4: opt.transform.jit_opt_b 0.00% : 0.000017s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000024s : 1: opt.transform.mutable_eliminate 0.00% : 0.000033s : 1: opt.transform.opt_after_jit_grad 0.08% : 0.001035s : 2: opt.transform.opt_resolve 0.00% : 0.000052s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000549s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000057s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000031s : 1: remove_dup_value 16.36% : 0.216874s : 2: renormalize.infer 0.28% : 0.003654s : 2: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000216s : 1: rewriter_after_opt_a 0.01% : 0.000145s : 1: rewriter_before_opt_a 0.01% : 0.000105s : 1: symbol_engine_optimizer 46.70% : 0.619088s : 1: type_inference . [hook] pytest_runtest_teardown:test_narrow_special_values[inf-KBK] tests/st/mint/test_narrow.py::test_narrow_special_values[inf-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[nan-pynative] tests/st/mint/test_narrow.py::test_narrow_special_values[nan-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[nan-KBK] tests/st/mint/test_narrow.py::test_narrow_special_values[nan-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[zero-pynative] tests/st/mint/test_narrow.py::test_narrow_special_values[zero-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[zero-KBK] tests/st/mint/test_narrow.py::test_narrow_special_values[zero-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[large-pynative] tests/st/mint/test_narrow.py::test_narrow_special_values[large-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[large-KBK] tests/st/mint/test_narrow.py::test_narrow_special_values[large-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[small-pynative] tests/st/mint/test_narrow.py::test_narrow_special_values[small-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_narrow_special_values[small-KBK] tests/st/mint/test_narrow.py::test_narrow_special_values[small-KBK],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 ================= 10 passed, 25 warnings in 154.65s (0:02:34) ==================