==================================================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_007/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_select.py . [hook] pytest_runtest_teardown:test_select_jit_mode[pynative] tests/st/mint/test_select.py::test_select_jit_mode[pynative],max_mem:2.0M TotalTime = 0.820033, [30] [bootstrap]: 0.00056809 [type_inference]: 0.614294 [event_method]: 1.68e-05 [auto_monad]: 0.00017825 [graph_reusing]: 6.23e-06 [pre_auto_parallel]: 1.218e-05 [py_interpret_to_execute]: 0.00012027 [rewriter_before_opt_a]: 7.415e-05 [expand_dump_flag]: 3.85998e-06 [jit_opt_a]: 0.0114161, [2] [Cycle 1]: 0.00200772, [27] [switch_simplify]: 5.564e-05 [loop_unroll]: 1.872e-05 [a_1]: 0.00041085 [with_stream_mark]: 2.979e-05 [recompute_prepare]: 1.089e-05 [updatestate_depend_eliminate]: 6.81001e-06 [updatestate_assign_eliminate]: 6.09999e-06 [updatestate_loads_eliminate]: 4.66002e-06 [parameter_eliminate]: 1.72001e-06 [specialize_transform]: 8.69e-06 [updatestate_useless_node_eliminater]: 1.087e-05 [accelerated_algorithm]: 8.91002e-06 [meta_shard_fg_expand]: 2.83e-06 [get_grad_eliminate_]: 7.53e-06 [merge_forward]: 5.66e-06 [cell_reuse_recompute_pass]: 1.13001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.166e-05 [j_node_and_user_rematch]: 1.413e-05 [meta_fg_expand]: 3.68e-06 [replace_old_param]: 1.292e-05 [inline_without_move]: 7.75998e-06 [renormalize]: 0.00102779 [add_forward_monad_depend]: 1.05e-05 [auto_monad_grad]: 2.71e-06 [auto_monad_eliminator]: 2.203e-05 [cse]: 5.274e-05 [replace_applicator]: 1.672e-05 [Cycle 2]: 0.00049126, [27] [switch_simplify]: 9.62999e-06 [loop_unroll]: 7.95998e-06 [a_1]: 0.0001669 [with_stream_mark]: 1.382e-05 [recompute_prepare]: 8.33001e-06 [updatestate_depend_eliminate]: 5.72001e-06 [updatestate_assign_eliminate]: 4.53001e-06 [updatestate_loads_eliminate]: 4.48999e-06 [parameter_eliminate]: 2.02001e-06 [specialize_transform]: 8.32e-06 [updatestate_useless_node_eliminater]: 1.111e-05 [accelerated_algorithm]: 9.22999e-06 [meta_shard_fg_expand]: 1.92001e-06 [get_grad_eliminate_]: 8.74e-06 [merge_forward]: 5.42001e-06 [cell_reuse_recompute_pass]: 1.86e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.756e-05 [j_node_and_user_rematch]: 1.243e-05 [meta_fg_expand]: 2.78e-06 [replace_old_param]: 1.034e-05 [inline_without_move]: 7.33999e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.37e-06 [auto_monad_grad]: 1.22999e-06 [auto_monad_eliminator]: 1.138e-05 [cse]: 1.943e-05 [replace_applicator]: 8.31002e-06 [py_interpret_to_execute_after_opt_a]: 1.613e-05 [rewriter_after_opt_a]: 0.0004406 [convert_after_rewriter]: 1.447e-05 [order_py_execute_after_rewriter]: 7.87e-06 [mutable_eliminate]: 0.00066162 [jit_opt_b]: 7.099e-05, [1] [Cycle 1]: 6.285e-05, [2] [frontend_op_eliminate]: 2.44e-05 [inline_after_opt_a]: 2.515e-05 [cconv]: 3.029e-05 [loop_unroll]: 0.00043943 [jit_opt_after_cconv]: 0.00020266, [1] [Cycle 1]: 0.00019507, [11] [c_1]: 4.625e-05 [parameter_eliminate]: 4e-06 [updatestate_depend_eliminate]: 9.38002e-06 [updatestate_assign_eliminate]: 4.84e-06 [updatestate_loads_eliminate]: 4.78001e-06 [cse]: 3.099e-05 [call_graph_tuple_transform]: 2.125e-05 [tuple_list_get_item_eliminator]: 8.72e-06 [none_parameter_eliminate]: 1.68002e-06 [renormalize]: 6.79982e-07 [switch_simplify]: 7.97e-06 [remove_dup_value]: 4.706e-05 [partial_unused_args_eliminate]: 2.79001e-06 [environ_conv]: 2.045e-05 [add_recomputation]: 7.994e-05 [cse_after_recomputation]: 3.141e-05, [1] [Cycle 1]: 2.422e-05, [1] [cse]: 1.702e-05 [auto_monad_reorder]: 3.532e-05 [get_jit_bprop_graph]: 2.25002e-06 [rewriter_after_jit_bprop_graph]: 0.00013668 [opt_after_jit_grad]: 0.190533 [symbol_engine_optimizer]: 0.00013319, [1] [Cycle 1]: 0.00011996, [6] [build]: 1.226e-05 [elim_shapecalc]: 1.442e-05 [elim_not_effective]: 3.134e-05 [opt_reshape]: 1.018e-05 [fold_const_symbol]: 1.522e-05 [renormalize]: 1.10001e-06 [validate]: 9.842e-05 Sums bootstrap : 0.000568s : 0.07% type_inference : 0.614294s : 75.81% event_method : 0.000017s : 0.00% auto_monad : 0.000178s : 0.02% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000120s : 0.01% rewriter_before_opt_a : 0.000074s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000065s : 0.01% jit_opt_a.loop_unroll : 0.000027s : 0.00% jit_opt_a.a_1 : 0.000578s : 0.07% jit_opt_a.with_stream_mark : 0.000044s : 0.01% jit_opt_a.recompute_prepare : 0.000019s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000017s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000022s : 0.00% jit_opt_a.accelerated_algorithm : 0.000018s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000016s : 0.00% jit_opt_a.merge_forward : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000049s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000027s : 0.00% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000023s : 0.00% jit_opt_a.inline_without_move : 0.000015s : 0.00% jit_opt_a.renormalize : 0.001028s : 0.13% jit_opt_a.add_forward_monad_depend : 0.000012s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000033s : 0.00% jit_opt_a.cse : 0.000072s : 0.01% jit_opt_a.replace_applicator : 0.000025s : 0.00% py_interpret_to_execute_after_opt_a : 0.000016s : 0.00% rewriter_after_opt_a : 0.000441s : 0.05% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000662s : 0.08% jit_opt_b.frontend_op_eliminate : 0.000024s : 0.00% jit_opt_b.inline_after_opt_a : 0.000025s : 0.00% cconv : 0.000030s : 0.00% loop_unroll : 0.000439s : 0.05% jit_opt_after_cconv.c_1 : 0.000046s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000031s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000021s : 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 : 0.000008s : 0.00% remove_dup_value : 0.000047s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000020s : 0.00% add_recomputation : 0.000080s : 0.01% cse_after_recomputation.cse : 0.000017s : 0.00% auto_monad_reorder : 0.000035s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000137s : 0.02% opt_after_jit_grad : 0.190533s : 23.51% symbol_engine_optimizer.build : 0.000012s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000031s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000098s : 0.01% Time group info: ------[substitution.] 0.000211 43 3.96% : 0.000008s : 2: substitution.depend_value_elim 1.90% : 0.000004s : 4: substitution.elim_not_effective 0.94% : 0.000002s : 4: substitution.fold_const_symbol 3.16% : 0.000007s : 5: substitution.graph_param_transform 67.59% : 0.000142s : 2: substitution.inline 2.28% : 0.000005s : 8: substitution.j_node_and_user_rematch 7.78% : 0.000016s : 8: substitution.remove_not_recompute_node 2.63% : 0.000006s : 2: substitution.replace_old_param 4.99% : 0.000011s : 3: substitution.updatestate_pure_node_eliminater 4.76% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.614208 2 99.83% : 0.613174s : 1: type_inference.infer 0.17% : 0.001034s : 1: type_inference.specialize ------[replace.] 0.000030 2 100.00% : 0.000030s : 2: replace.inline ------[match.] 0.000141 2 100.00% : 0.000141s : 2: match.inline ------[predicate.] 0.000149 767 1.03% : 0.000002s : 11: predicate.accumulaten_eliminater 4.89% : 0.000007s : 5: predicate.ad_related_special_op_eliminate 0.98% : 0.000001s : 11: predicate.addn_check_dump 1.45% : 0.000002s : 11: predicate.addn_zero_filter 2.07% : 0.000003s : 11: predicate.arithmetic_simplify 1.15% : 0.000002s : 11: predicate.cast_eliminate 0.64% : 0.000001s : 5: predicate.check_bprop_eliminate 1.05% : 0.000002s : 11: predicate.compare_switch_simplify 1.18% : 0.000002s : 11: predicate.depend_value_elim 0.91% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.32% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.13% : 0.000002s : 11: predicate.dict_set_item_eliminator 2.96% : 0.000004s : 5: predicate.dumpgradient_eliminate 0.69% : 0.000001s : 5: predicate.elim_not_effective 1.05% : 0.000002s : 5: predicate.elim_shapecalc_of_broadcastargs 1.02% : 0.000002s : 11: predicate.environ_add_const_eliminate 0.97% : 0.000001s : 11: predicate.environ_get_add_eliminate 0.95% : 0.000001s : 11: predicate.environ_get_depend_swap 1.14% : 0.000002s : 11: predicate.environ_get_eliminate 0.92% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.46% : 0.000001s : 5: predicate.fold_const_symbol 1.32% : 0.000002s : 10: predicate.get_grad_eliminate 0.50% : 0.000001s : 5: predicate.graph_param_transform 4.73% : 0.000007s : 23: predicate.inline 1.20% : 0.000002s : 10: predicate.inline_without_move 0.55% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.87% : 0.000003s : 10: predicate.less_batch_normalization 1.28% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.67% : 0.000002s : 16: predicate.load_eliminater 1.58% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.21% : 0.000003s : 20: predicate.loop_unroll_before_grad 2.19% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.92% : 0.000001s : 11: predicate.merge_addn 1.11% : 0.000002s : 11: predicate.minmaximum_grad 2.06% : 0.000003s : 5: predicate.mutable_eliminate 0.77% : 0.000001s : 5: predicate.opt_reshape 2.05% : 0.000003s : 16: predicate.partial_eliminate 1.05% : 0.000002s : 11: predicate.print_const_string_wrapper 1.85% : 0.000003s : 11: predicate.reduce_eliminate 1.20% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 1.02% : 0.000002s : 10: predicate.remove_not_recompute_node 1.55% : 0.000002s : 21: predicate.replace_applicator 0.89% : 0.000001s : 10: predicate.replace_old_param 0.54% : 0.000001s : 5: predicate.reset_defer_inline 1.09% : 0.000002s : 11: predicate.reshape_eliminate 1.07% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.87% : 0.000001s : 5: predicate.row_tensor_eliminate 1.14% : 0.000002s : 11: predicate.same_eliminate 0.70% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.73% : 0.000003s : 10: predicate.special_op_eliminate 1.32% : 0.000002s : 10: predicate.specialize_transform 1.30% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.03% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.59% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.60% : 0.000002s : 13: predicate.switch_defer_inline 1.30% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.31% : 0.000008s : 38: predicate.switch_simplify 1.03% : 0.000002s : 11: predicate.tile_eliminate 1.09% : 0.000002s : 11: predicate.transpose_eliminate 1.42% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.36% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.47% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.71% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.05% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.66% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.27% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.36% : 0.000002s : 11: predicate.value_based_eliminate 0.63% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.82% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000337 5 5.93% : 0.000020s : 1: func_graph_cloner_run.FuncGraphClonerGraph 94.07% : 0.000317s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.821937 72 0.01% : 0.000083s : 1: add_recomputation 0.02% : 0.000184s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 0.07% : 0.000587s : 1: bootstrap 0.00% : 0.000033s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.00% : 0.000034s : 1: cse_after_recomputation 0.00% : 0.000023s : 1: environ_conv 0.00% : 0.000023s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 1.39% : 0.011420s : 1: jit_opt_a 0.03% : 0.000206s : 1: jit_opt_after_cconv 0.01% : 0.000074s : 1: jit_opt_b 0.05% : 0.000446s : 1: loop_unroll 0.08% : 0.000669s : 1: mutable_eliminate 0.10% : 0.000860s : 26: opt.transform.jit_opt_a 0.01% : 0.000081s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000042s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000019s : 1: opt.transform.mutable_eliminate 0.01% : 0.000073s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000066s : 4: opt.transform.symbol_engine_opt 23.18% : 0.190564s : 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% : 0.000015s : 1: pre_auto_parallel 0.02% : 0.000124s : 1: py_interpret_to_execute 0.00% : 0.000019s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000050s : 1: remove_dup_value 0.08% : 0.000643s : 1: renormalize.infer 0.05% : 0.000376s : 1: renormalize.specialize 0.02% : 0.000140s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000445s : 1: rewriter_after_opt_a 0.01% : 0.000078s : 1: rewriter_before_opt_a 0.02% : 0.000138s : 1: symbol_engine_optimizer 74.74% : 0.614313s : 1: type_inference TotalTime = 1.45427, [30] [bootstrap]: 0.00055085 [type_inference]: 0.594554 [event_method]: 0.00018693 [auto_monad]: 0.00027218 [graph_reusing]: 9.73002e-06 [pre_auto_parallel]: 3.91999e-06 [py_interpret_to_execute]: 4.983e-05 [rewriter_before_opt_a]: 0.00015171 [expand_dump_flag]: 4.16001e-06 [jit_opt_a]: 0.84489, [4] [Cycle 1]: 0.823366, [27] [switch_simplify]: 0.00022252 [loop_unroll]: 5.815e-05 [a_1]: 0.136162 [with_stream_mark]: 7.562e-05 [recompute_prepare]: 7.108e-05 [updatestate_depend_eliminate]: 1.513e-05 [updatestate_assign_eliminate]: 1.202e-05 [updatestate_loads_eliminate]: 1.057e-05 [parameter_eliminate]: 4.89998e-06 [specialize_transform]: 2.179e-05 [updatestate_useless_node_eliminater]: 2.851e-05 [accelerated_algorithm]: 2.116e-05 [meta_shard_fg_expand]: 1.214e-05 [get_grad_eliminate_]: 2.018e-05 [merge_forward]: 1.291e-05 [cell_reuse_recompute_pass]: 1.58997e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.113e-05 [j_node_and_user_rematch]: 3.485e-05 [meta_fg_expand]: 0.396837 [replace_old_param]: 0.00012159 [inline_without_move]: 0.00012435 [renormalize]: 0.171045 [add_forward_monad_depend]: 2.8e-05 [auto_monad_grad]: 1.292e-05 [auto_monad_eliminator]: 0.00013402 [cse]: 0.00033467 [replace_applicator]: 0.117504 [Cycle 2]: 0.012742, [27] [switch_simplify]: 0.0001217 [loop_unroll]: 8.706e-05 [a_1]: 0.00386478 [with_stream_mark]: 4.593e-05 [recompute_prepare]: 3.881e-05 [updatestate_depend_eliminate]: 1.626e-05 [updatestate_assign_eliminate]: 1.583e-05 [updatestate_loads_eliminate]: 1.49e-05 [parameter_eliminate]: 4.20999e-06 [specialize_transform]: 2.413e-05 [updatestate_useless_node_eliminater]: 9.623e-05 [accelerated_algorithm]: 3.588e-05 [meta_shard_fg_expand]: 6.25002e-06 [get_grad_eliminate_]: 1.631e-05 [merge_forward]: 1.046e-05 [cell_reuse_recompute_pass]: 1.50999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.445e-05 [j_node_and_user_rematch]: 2.468e-05 [meta_fg_expand]: 0.00012539 [replace_old_param]: 2.282e-05 [inline_without_move]: 1.472e-05 [renormalize]: 0.00758999 [add_forward_monad_depend]: 1.303e-05 [auto_monad_grad]: 2.63e-06 [auto_monad_eliminator]: 4.044e-05 [cse]: 0.00016505 [replace_applicator]: 3.615e-05 [Cycle 3]: 0.00214728, [27] [switch_simplify]: 1.636e-05 [loop_unroll]: 1.49e-05 [a_1]: 0.00034723 [with_stream_mark]: 2.386e-05 [recompute_prepare]: 1.524e-05 [updatestate_depend_eliminate]: 3.688e-05 [updatestate_assign_eliminate]: 8.28999e-06 [updatestate_loads_eliminate]: 7.08998e-06 [parameter_eliminate]: 2.16e-06 [specialize_transform]: 1.347e-05 [updatestate_useless_node_eliminater]: 1.614e-05 [accelerated_algorithm]: 1.794e-05 [meta_shard_fg_expand]: 3.35e-06 [get_grad_eliminate_]: 1.183e-05 [merge_forward]: 3.525e-05 [cell_reuse_recompute_pass]: 3.61999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.12e-05 [j_node_and_user_rematch]: 2.183e-05 [meta_fg_expand]: 5.45001e-06 [replace_old_param]: 1.655e-05 [inline_without_move]: 1.261e-05 [renormalize]: 0.00115845 [add_forward_monad_depend]: 6.59999e-06 [auto_monad_grad]: 2.39001e-06 [auto_monad_eliminator]: 2.55e-05 [cse]: 9.313e-05 [replace_applicator]: 2.621e-05 [Cycle 4]: 0.00077904, [27] [switch_simplify]: 1.404e-05 [loop_unroll]: 1.211e-05 [a_1]: 0.00028308 [with_stream_mark]: 2.058e-05 [recompute_prepare]: 1.364e-05 [updatestate_depend_eliminate]: 9.15999e-06 [updatestate_assign_eliminate]: 7.63001e-06 [updatestate_loads_eliminate]: 8.07998e-06 [parameter_eliminate]: 1.54998e-06 [specialize_transform]: 1.459e-05 [updatestate_useless_node_eliminater]: 1.61e-05 [accelerated_algorithm]: 1.734e-05 [meta_shard_fg_expand]: 3.16999e-06 [get_grad_eliminate_]: 1.183e-05 [merge_forward]: 7.60998e-06 [cell_reuse_recompute_pass]: 2.49999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.592e-05 [j_node_and_user_rematch]: 2.036e-05 [meta_fg_expand]: 2.827e-05 [replace_old_param]: 2.049e-05 [inline_without_move]: 1.372e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.54001e-06 [auto_monad_grad]: 1.32999e-06 [auto_monad_eliminator]: 2.01e-05 [cse]: 4.441e-05 [replace_applicator]: 1.306e-05 [py_interpret_to_execute_after_opt_a]: 2.252e-05 [rewriter_after_opt_a]: 0.00031631 [convert_after_rewriter]: 1.81e-05 [order_py_execute_after_rewriter]: 9.61e-06 [mutable_eliminate]: 0.00087099 [jit_opt_b]: 0.00010024, [1] [Cycle 1]: 8.972e-05, [2] [frontend_op_eliminate]: 3.701e-05 [inline_after_opt_a]: 3.813e-05 [cconv]: 3.97e-05 [loop_unroll]: 0.0100918 [jit_opt_after_cconv]: 0.0003844, [1] [Cycle 1]: 0.00037014, [11] [c_1]: 9.509e-05 [parameter_eliminate]: 6.78998e-06 [updatestate_depend_eliminate]: 1.933e-05 [updatestate_assign_eliminate]: 8.3e-06 [updatestate_loads_eliminate]: 7.28e-06 [cse]: 9.338e-05 [call_graph_tuple_transform]: 3.731e-05 [tuple_list_get_item_eliminator]: 1.434e-05 [none_parameter_eliminate]: 1.81003e-06 [renormalize]: 1.39e-06 [switch_simplify]: 1.412e-05 [remove_dup_value]: 0.0001022 [partial_unused_args_eliminate]: 3.4e-06 [environ_conv]: 1.682e-05 [add_recomputation]: 0.000106 [cse_after_recomputation]: 5.363e-05, [1] [Cycle 1]: 4.546e-05, [1] [cse]: 3.488e-05 [auto_monad_reorder]: 3.45e-05 [get_jit_bprop_graph]: 2.51e-06 [rewriter_after_jit_bprop_graph]: 1.049e-05 [opt_after_jit_grad]: 0.00087369 [symbol_engine_optimizer]: 0.00013761, [1] [Cycle 1]: 0.00012881, [6] [build]: 1.635e-05 [elim_shapecalc]: 1.731e-05 [elim_not_effective]: 2.912e-05 [opt_reshape]: 1.31e-05 [fold_const_symbol]: 2.086e-05 [renormalize]: 7.10017e-07 [validate]: 9.411e-05 Sums bootstrap : 0.000551s : 0.04% type_inference : 0.594554s : 41.09% event_method : 0.000187s : 0.01% auto_monad : 0.000272s : 0.02% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000050s : 0.00% rewriter_before_opt_a : 0.000152s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000375s : 0.03% jit_opt_a.loop_unroll : 0.000172s : 0.01% jit_opt_a.a_1 : 0.140657s : 9.72% jit_opt_a.with_stream_mark : 0.000166s : 0.01% jit_opt_a.recompute_prepare : 0.000139s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000077s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000044s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000041s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000074s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000157s : 0.01% jit_opt_a.accelerated_algorithm : 0.000092s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000025s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000060s : 0.00% jit_opt_a.merge_forward : 0.000066s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000133s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000102s : 0.01% jit_opt_a.meta_fg_expand : 0.396997s : 27.44% jit_opt_a.replace_old_param : 0.000181s : 0.01% jit_opt_a.inline_without_move : 0.000165s : 0.01% jit_opt_a.renormalize : 0.179793s : 12.43% jit_opt_a.add_forward_monad_depend : 0.000050s : 0.00% jit_opt_a.auto_monad_grad : 0.000019s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000220s : 0.02% jit_opt_a.cse : 0.000637s : 0.04% jit_opt_a.replace_applicator : 0.117579s : 8.13% py_interpret_to_execute_after_opt_a : 0.000023s : 0.00% rewriter_after_opt_a : 0.000316s : 0.02% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000871s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000037s : 0.00% jit_opt_b.inline_after_opt_a : 0.000038s : 0.00% cconv : 0.000040s : 0.00% loop_unroll : 0.010092s : 0.70% jit_opt_after_cconv.c_1 : 0.000095s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000019s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000093s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000037s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000014s : 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 : 0.000014s : 0.00% remove_dup_value : 0.000102s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000017s : 0.00% add_recomputation : 0.000106s : 0.01% cse_after_recomputation.cse : 0.000035s : 0.00% auto_monad_reorder : 0.000035s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000874s : 0.06% symbol_engine_optimizer.build : 0.000016s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000029s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000021s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000094s : 0.01% Time group info: ------[substitution.] 0.002927 291 1.40% : 0.000041s : 12: substitution.depend_value_elim 0.14% : 0.000004s : 7: substitution.elim_not_effective 0.11% : 0.000003s : 7: substitution.fold_const_symbol 32.21% : 0.000943s : 4: substitution.getattr_setattr_resolve 0.35% : 0.000010s : 8: substitution.graph_param_transform 46.69% : 0.001367s : 28: substitution.inline 1.20% : 0.000035s : 4: substitution.inline_without_move 0.68% : 0.000020s : 35: substitution.j_node_and_user_rematch 0.79% : 0.000023s : 3: substitution.less_batch_normalization 0.72% : 0.000021s : 13: substitution.minmaximum_grad 0.54% : 0.000016s : 14: substitution.partial_eliminate 0.89% : 0.000026s : 35: substitution.remove_not_recompute_node 3.67% : 0.000107s : 16: substitution.replace_applicator 0.71% : 0.000021s : 19: substitution.replace_old_param 0.45% : 0.000013s : 2: substitution.set_cell_output_no_recompute 0.52% : 0.000015s : 3: substitution.switch_simplify 1.36% : 0.000040s : 13: substitution.tuple_list_convert_item_index_to_positive 1.03% : 0.000030s : 13: substitution.tuple_list_get_item_depend_reorder 3.15% : 0.000092s : 30: substitution.tuple_list_get_item_eliminator 0.99% : 0.000029s : 9: substitution.updatestate_pure_node_eliminater 2.42% : 0.000071s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.594453 2 99.52% : 0.591627s : 1: type_inference.infer 0.48% : 0.002826s : 1: type_inference.specialize ------[replace.] 0.000882 53 7.74% : 0.000068s : 3: replace.getattr_setattr_resolve 47.54% : 0.000419s : 28: replace.inline 9.84% : 0.000087s : 1: replace.replace_applicator 8.36% : 0.000074s : 3: replace.switch_simplify 20.91% : 0.000184s : 17: replace.tuple_list_get_item_eliminator 5.60% : 0.000049s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002242 53 35.54% : 0.000797s : 3: match.getattr_setattr_resolve 60.16% : 0.001348s : 28: match.inline 1.29% : 0.000029s : 1: match.replace_applicator 0.60% : 0.000013s : 3: match.switch_simplify 1.78% : 0.000040s : 17: match.tuple_list_get_item_eliminator 0.63% : 0.000014s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000977 5919 1.49% : 0.000015s : 99: predicate.accumulaten_eliminater 0.36% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.39% : 0.000014s : 99: predicate.addn_check_dump 1.57% : 0.000015s : 99: predicate.addn_zero_filter 2.03% : 0.000020s : 99: predicate.arithmetic_simplify 1.48% : 0.000014s : 99: predicate.cast_eliminate 0.16% : 0.000002s : 8: predicate.check_bprop_eliminate 1.36% : 0.000013s : 99: predicate.compare_switch_simplify 1.58% : 0.000015s : 99: predicate.depend_value_elim 1.38% : 0.000013s : 99: predicate.dict_get_item_const_eliminator 1.62% : 0.000016s : 99: predicate.dict_get_item_eliminator 1.46% : 0.000014s : 99: predicate.dict_set_item_eliminator 0.25% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 8: predicate.elim_not_effective 0.17% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.43% : 0.000014s : 99: predicate.environ_add_const_eliminate 1.42% : 0.000014s : 99: predicate.environ_get_add_eliminate 1.41% : 0.000014s : 99: predicate.environ_get_depend_swap 1.52% : 0.000015s : 99: predicate.environ_get_eliminate 1.41% : 0.000014s : 99: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.83% : 0.000008s : 42: predicate.get_grad_eliminate 0.79% : 0.000008s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000001s : 8: predicate.graph_param_transform 4.53% : 0.000044s : 160: predicate.inline 1.95% : 0.000019s : 106: predicate.inline_without_move 0.34% : 0.000003s : 42: predicate.j_node_and_user_rematch 1.15% : 0.000011s : 42: predicate.less_batch_normalization 1.77% : 0.000017s : 116: predicate.list_to_tuple_eliminator_ 1.89% : 0.000018s : 124: predicate.load_eliminater 1.42% : 0.000014s : 8: predicate.loop_unroll_after_grad 2.64% : 0.000026s : 171: predicate.loop_unroll_before_grad 1.75% : 0.000017s : 107: predicate.make_slice_get_slice_eliminator 1.38% : 0.000013s : 99: predicate.merge_addn 1.50% : 0.000015s : 99: predicate.minmaximum_grad 0.47% : 0.000005s : 8: predicate.mutable_eliminate 0.17% : 0.000002s : 8: predicate.opt_reshape 2.48% : 0.000024s : 124: predicate.partial_eliminate 1.46% : 0.000014s : 99: predicate.print_const_string_wrapper 1.87% : 0.000018s : 99: predicate.reduce_eliminate 1.82% : 0.000018s : 116: predicate.redundant_stop_gradient_eliminater 0.47% : 0.000005s : 42: predicate.remove_not_recompute_node 2.71% : 0.000026s : 236: predicate.replace_applicator 0.94% : 0.000009s : 106: predicate.replace_old_param 0.09% : 0.000001s : 8: predicate.reset_defer_inline 1.50% : 0.000015s : 99: predicate.reshape_eliminate 1.45% : 0.000014s : 99: predicate.row_tensor_add_zeros_like 0.26% : 0.000003s : 8: predicate.row_tensor_eliminate 1.48% : 0.000014s : 99: predicate.same_eliminate 0.59% : 0.000006s : 52: predicate.set_cell_output_no_recompute 0.30% : 0.000003s : 16: predicate.special_op_eliminate 0.95% : 0.000009s : 50: predicate.specialize_transform 1.68% : 0.000016s : 99: predicate.split_environ_get_set_with_tuple_value 1.48% : 0.000014s : 99: predicate.stack_unstack_eliminate 0.15% : 0.000001s : 8: predicate.switch_call_monad_eliminater 2.95% : 0.000029s : 144: predicate.switch_defer_inline 2.37% : 0.000023s : 144: predicate.switch_layer_defer_inline 5.87% : 0.000057s : 329: predicate.switch_simplify 1.46% : 0.000014s : 99: predicate.tile_eliminate 1.45% : 0.000014s : 99: predicate.transpose_eliminate 1.92% : 0.000019s : 99: predicate.tuple_list_convert_item_index_to_positive 1.76% : 0.000017s : 99: predicate.tuple_list_get_item_depend_reorder 3.45% : 0.000034s : 132: predicate.tuple_list_get_item_eliminator 1.82% : 0.000018s : 99: predicate.tuple_list_set_item_eliminator 1.81% : 0.000018s : 116: predicate.tuple_to_list_eliminator_ 1.97% : 0.000019s : 124: predicate.updatestate_pure_node_eliminater 3.02% : 0.000030s : 168: predicate.updatestate_useless_node_eliminater 1.83% : 0.000018s : 99: predicate.value_based_eliminate 0.13% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.16% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004916 58 56.72% : 0.002788s : 22: func_graph_cloner_run.FuncGraphClonerGraph 7.85% : 0.000386s : 7: func_graph_cloner_run.FuncGraphClonerNode 35.43% : 0.001742s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.904628 104 0.01% : 0.000110s : 1: add_recomputation 0.01% : 0.000282s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 0.03% : 0.000571s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.00% : 0.000056s : 1: cse_after_recomputation 0.00% : 0.000020s : 1: environ_conv 0.01% : 0.000197s : 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 44.36% : 0.844894s : 1: jit_opt_a 0.02% : 0.000390s : 1: jit_opt_after_cconv 0.01% : 0.000103s : 1: jit_opt_b 0.53% : 0.010117s : 1: loop_unroll 0.05% : 0.000881s : 1: mutable_eliminate 13.64% : 0.259783s : 52: opt.transform.jit_opt_a 0.01% : 0.000152s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000067s : 4: opt.transform.jit_opt_b 0.50% : 0.009556s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.00% : 0.000052s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.001077s : 2: opt.transform.opt_resolve 0.00% : 0.000076s : 4: opt.transform.symbol_engine_opt 0.05% : 0.000883s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000053s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000107s : 1: remove_dup_value 9.16% : 0.174548s : 3: renormalize.infer 0.27% : 0.005201s : 3: renormalize.specialize 0.00% : 0.000043s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000334s : 1: rewriter_after_opt_a 0.01% : 0.000155s : 1: rewriter_before_opt_a 0.01% : 0.000140s : 1: symbol_engine_optimizer 31.22% : 0.594573s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_jit_mode[KBK] tests/st/mint/test_select.py::test_select_jit_mode[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 ================== 2 passed, 25 warnings in 292.10s (0:04:52) ==================