==================================================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/hardware/ascend/aclnn, 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 1 item test_aclnn_cache.py TotalTime = 0.371259, [30] [bootstrap]: 0.00065457 [type_inference]: 0.358083 [event_method]: 2.103e-05 [auto_monad]: 0.00012148 [graph_reusing]: 7.95e-06 [pre_auto_parallel]: 1.539e-05 [py_interpret_to_execute]: 0.00013435 [rewriter_before_opt_a]: 7.515e-05 [expand_dump_flag]: 3.2e-06 [jit_opt_a]: 0.0089949, [2] [Cycle 1]: 0.00195035, [27] [switch_simplify]: 0.00014744 [loop_unroll]: 2.363e-05 [a_1]: 0.00044975 [with_stream_mark]: 2.697e-05 [recompute_prepare]: 7.11999e-06 [updatestate_depend_eliminate]: 3.98001e-06 [updatestate_assign_eliminate]: 2.94999e-06 [updatestate_loads_eliminate]: 2.96001e-06 [parameter_eliminate]: 1.87999e-06 [specialize_transform]: 5.83997e-06 [updatestate_useless_node_eliminater]: 5.38002e-06 [accelerated_algorithm]: 5.67001e-06 [meta_shard_fg_expand]: 2.43e-06 [get_grad_eliminate_]: 5.49998e-06 [merge_forward]: 4.32e-06 [cell_reuse_recompute_pass]: 1.31002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.752e-05 [j_node_and_user_rematch]: 1.01e-05 [meta_fg_expand]: 2.46998e-06 [replace_old_param]: 1.04e-05 [inline_without_move]: 5.44e-06 [renormalize]: 0.00091362 [add_forward_monad_depend]: 1.134e-05 [auto_monad_grad]: 2.59999e-06 [auto_monad_eliminator]: 1.481e-05 [cse]: 4.052e-05 [replace_applicator]: 1.46e-05 [Cycle 2]: 0.00040107, [27] [switch_simplify]: 5.96998e-06 [loop_unroll]: 4.94e-06 [a_1]: 0.00015708 [with_stream_mark]: 1.206e-05 [recompute_prepare]: 5.97999e-06 [updatestate_depend_eliminate]: 3.19001e-06 [updatestate_assign_eliminate]: 2.37001e-06 [updatestate_loads_eliminate]: 2.27999e-06 [parameter_eliminate]: 1.44e-06 [specialize_transform]: 5.00999e-06 [updatestate_useless_node_eliminater]: 4.99e-06 [accelerated_algorithm]: 5.54998e-06 [meta_shard_fg_expand]: 1.30999e-06 [get_grad_eliminate_]: 4.99e-06 [merge_forward]: 3.23998e-06 [cell_reuse_recompute_pass]: 1.61998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.458e-05 [j_node_and_user_rematch]: 8.80001e-06 [meta_fg_expand]: 1.94999e-06 [replace_old_param]: 8e-06 [inline_without_move]: 4.73001e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.54e-06 [auto_monad_grad]: 1.07e-06 [auto_monad_eliminator]: 6.11998e-06 [cse]: 1.29e-05 [replace_applicator]: 4.88001e-06 [py_interpret_to_execute_after_opt_a]: 1.205e-05 [rewriter_after_opt_a]: 7.097e-05 [convert_after_rewriter]: 1.016e-05 [order_py_execute_after_rewriter]: 5.59e-06 [mutable_eliminate]: 0.00063746 [jit_opt_b]: 5.478e-05, [1] [Cycle 1]: 4.632e-05, [2] [frontend_op_eliminate]: 1.704e-05 [inline_after_opt_a]: 1.619e-05 [cconv]: 2.808e-05 [loop_unroll]: 0.00043192 [jit_opt_after_cconv]: 0.00015517, [1] [Cycle 1]: 0.00014761, [11] [c_1]: 2.148e-05 [parameter_eliminate]: 4.11001e-06 [updatestate_depend_eliminate]: 7.9e-06 [updatestate_assign_eliminate]: 2.67001e-06 [updatestate_loads_eliminate]: 2.07999e-06 [cse]: 2.189e-05 [call_graph_tuple_transform]: 2.034e-05 [tuple_list_get_item_eliminator]: 5.87001e-06 [none_parameter_eliminate]: 1.54e-06 [renormalize]: 1.10999e-06 [switch_simplify]: 5.66e-06 [remove_dup_value]: 1.584e-05 [partial_unused_args_eliminate]: 2.32999e-06 [environ_conv]: 1.839e-05 [add_recomputation]: 5.731e-05 [cse_after_recomputation]: 2.424e-05, [1] [Cycle 1]: 1.809e-05, [1] [cse]: 1.078e-05 [auto_monad_reorder]: 2.219e-05 [get_jit_bprop_graph]: 3.14999e-06 [rewriter_after_jit_bprop_graph]: 3.8e-06 [opt_after_jit_grad]: 0.00046956 [symbol_engine_optimizer]: 0.00019756, [1] [Cycle 1]: 0.00019068, [6] [build]: 0.00010075 [elim_shapecalc]: 1.106e-05 [elim_not_effective]: 2.271e-05 [opt_reshape]: 6.37001e-06 [fold_const_symbol]: 1.411e-05 [renormalize]: 4.30009e-07 [validate]: 4.502e-05 Sums bootstrap : 0.000655s : 0.18% type_inference : 0.358083s : 98.57% event_method : 0.000021s : 0.01% auto_monad : 0.000121s : 0.03% graph_reusing : 0.000008s : 0.00% pre_auto_parallel : 0.000015s : 0.00% py_interpret_to_execute : 0.000134s : 0.04% rewriter_before_opt_a : 0.000075s : 0.02% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000153s : 0.04% jit_opt_a.loop_unroll : 0.000029s : 0.01% jit_opt_a.a_1 : 0.000607s : 0.17% jit_opt_a.with_stream_mark : 0.000039s : 0.01% jit_opt_a.recompute_prepare : 0.000013s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000007s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000011s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000010s : 0.00% jit_opt_a.accelerated_algorithm : 0.000011s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000010s : 0.00% jit_opt_a.merge_forward : 0.000008s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000032s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000019s : 0.01% jit_opt_a.meta_fg_expand : 0.000004s : 0.00% jit_opt_a.replace_old_param : 0.000018s : 0.01% jit_opt_a.inline_without_move : 0.000010s : 0.00% jit_opt_a.renormalize : 0.000914s : 0.25% jit_opt_a.add_forward_monad_depend : 0.000013s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000021s : 0.01% jit_opt_a.cse : 0.000053s : 0.01% jit_opt_a.replace_applicator : 0.000019s : 0.01% py_interpret_to_execute_after_opt_a : 0.000012s : 0.00% rewriter_after_opt_a : 0.000071s : 0.02% convert_after_rewriter : 0.000010s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000637s : 0.18% jit_opt_b.frontend_op_eliminate : 0.000017s : 0.00% jit_opt_b.inline_after_opt_a : 0.000016s : 0.00% cconv : 0.000028s : 0.01% loop_unroll : 0.000432s : 0.12% jit_opt_after_cconv.c_1 : 0.000021s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 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 : 0.000022s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000020s : 0.01% 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 : 0.000016s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000018s : 0.01% add_recomputation : 0.000057s : 0.02% cse_after_recomputation.cse : 0.000011s : 0.00% auto_monad_reorder : 0.000022s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000004s : 0.00% opt_after_jit_grad : 0.000470s : 0.13% symbol_engine_optimizer.build : 0.000101s : 0.03% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000023s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000006s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000045s : 0.01% Time group info: ------[substitution.] 0.000172 25 5.92% : 0.000010s : 2: substitution.elim_not_effective 3.55% : 0.000006s : 2: substitution.fold_const_symbol 3.40% : 0.000006s : 3: substitution.graph_param_transform 72.09% : 0.000124s : 6: substitution.inline 2.42% : 0.000004s : 4: substitution.j_node_and_user_rematch 2.83% : 0.000005s : 4: substitution.remove_not_recompute_node 2.99% : 0.000005s : 2: substitution.replace_old_param 6.80% : 0.000012s : 2: substitution.switch_simplify ------[type_inference.] 0.357997 2 99.57% : 0.356452s : 1: type_inference.infer 0.43% : 0.001545s : 1: type_inference.specialize ------[replace.] 0.000094 8 40.21% : 0.000038s : 6: replace.inline 59.79% : 0.000056s : 2: replace.switch_simplify ------[match.] 0.000131 8 92.22% : 0.000121s : 6: match.inline 7.78% : 0.000010s : 2: match.switch_simplify ------[predicate.] 0.000126 705 1.20% : 0.000002s : 11: predicate.accumulaten_eliminater 1.24% : 0.000002s : 3: predicate.ad_related_special_op_eliminate 1.13% : 0.000001s : 11: predicate.addn_check_dump 1.20% : 0.000002s : 11: predicate.addn_zero_filter 2.13% : 0.000003s : 11: predicate.arithmetic_simplify 1.24% : 0.000002s : 11: predicate.cast_eliminate 0.47% : 0.000001s : 3: predicate.check_bprop_eliminate 1.30% : 0.000002s : 11: predicate.compare_switch_simplify 1.20% : 0.000002s : 11: predicate.depend_value_elim 1.17% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.27% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.41% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.01% : 0.000001s : 3: predicate.dumpgradient_eliminate 0.51% : 0.000001s : 3: predicate.elim_not_effective 0.84% : 0.000001s : 3: predicate.elim_shapecalc_of_broadcastargs 1.31% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.08% : 0.000001s : 11: predicate.environ_get_add_eliminate 1.12% : 0.000001s : 11: predicate.environ_get_depend_swap 1.19% : 0.000002s : 11: predicate.environ_get_eliminate 1.08% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.22% : 0.000000s : 3: predicate.fold_const_symbol 0.89% : 0.000001s : 6: predicate.get_grad_eliminate 0.26% : 0.000000s : 3: predicate.graph_param_transform 6.02% : 0.000008s : 23: predicate.inline 0.92% : 0.000001s : 6: predicate.inline_without_move 0.36% : 0.000000s : 6: predicate.j_node_and_user_rematch 1.20% : 0.000002s : 6: predicate.less_batch_normalization 1.39% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.56% : 0.000002s : 14: predicate.load_eliminater 1.97% : 0.000002s : 3: predicate.loop_unroll_after_grad 3.39% : 0.000004s : 26: predicate.loop_unroll_before_grad 2.06% : 0.000003s : 14: predicate.make_slice_get_slice_eliminator 1.08% : 0.000001s : 11: predicate.merge_addn 1.09% : 0.000001s : 11: predicate.minmaximum_grad 1.72% : 0.000002s : 3: predicate.mutable_eliminate 0.48% : 0.000001s : 3: predicate.opt_reshape 2.09% : 0.000003s : 14: predicate.partial_eliminate 1.16% : 0.000001s : 11: predicate.print_const_string_wrapper 1.73% : 0.000002s : 11: predicate.reduce_eliminate 1.29% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.74% : 0.000001s : 6: predicate.remove_not_recompute_node 1.65% : 0.000002s : 17: predicate.replace_applicator 1.03% : 0.000001s : 6: predicate.replace_old_param 0.49% : 0.000001s : 3: predicate.reset_defer_inline 1.20% : 0.000002s : 11: predicate.reshape_eliminate 1.33% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.85% : 0.000001s : 3: predicate.row_tensor_eliminate 1.22% : 0.000002s : 11: predicate.same_eliminate 0.51% : 0.000001s : 6: predicate.set_cell_output_no_recompute 0.92% : 0.000001s : 6: predicate.special_op_eliminate 0.97% : 0.000001s : 6: predicate.specialize_transform 1.56% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.27% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.44% : 0.000001s : 3: predicate.switch_call_monad_eliminater 2.30% : 0.000003s : 17: predicate.switch_defer_inline 2.11% : 0.000003s : 17: predicate.switch_layer_defer_inline 8.29% : 0.000010s : 50: predicate.switch_simplify 1.20% : 0.000002s : 11: predicate.tile_eliminate 1.23% : 0.000002s : 11: predicate.transpose_eliminate 1.52% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.31% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.71% : 0.000005s : 17: predicate.tuple_list_get_item_eliminator 1.68% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.23% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.41% : 0.000002s : 14: predicate.updatestate_pure_node_eliminater 2.73% : 0.000003s : 20: predicate.updatestate_useless_node_eliminater 2.15% : 0.000003s : 11: predicate.value_based_eliminate 0.44% : 0.000001s : 3: predicate.virtual_view_grad_eliminate 0.55% : 0.000001s : 3: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000823 11 50.33% : 0.000414s : 3: func_graph_cloner_run.FuncGraphClonerGraph 49.67% : 0.000409s : 8: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.372458 72 0.02% : 0.000060s : 1: add_recomputation 0.03% : 0.000126s : 1: auto_monad 0.01% : 0.000025s : 1: auto_monad_reorder 0.18% : 0.000679s : 1: bootstrap 0.01% : 0.000031s : 1: cconv 0.00% : 0.000013s : 1: convert_after_rewriter 0.01% : 0.000026s : 1: cse_after_recomputation 0.01% : 0.000021s : 1: environ_conv 0.01% : 0.000027s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 2.42% : 0.008998s : 1: jit_opt_a 0.04% : 0.000158s : 1: jit_opt_after_cconv 0.02% : 0.000057s : 1: jit_opt_b 0.12% : 0.000441s : 1: loop_unroll 0.17% : 0.000647s : 1: mutable_eliminate 0.24% : 0.000904s : 26: opt.transform.jit_opt_a 0.01% : 0.000050s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000026s : 4: opt.transform.jit_opt_b 0.00% : 0.000013s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000014s : 1: opt.transform.mutable_eliminate 0.01% : 0.000021s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000050s : 4: opt.transform.symbol_engine_opt 0.13% : 0.000479s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000018s : 1: pre_auto_parallel 0.04% : 0.000138s : 1: py_interpret_to_execute 0.00% : 0.000015s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000018s : 1: remove_dup_value 0.14% : 0.000519s : 1: renormalize.infer 0.10% : 0.000387s : 1: renormalize.specialize 0.00% : 0.000006s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000074s : 1: rewriter_after_opt_a 0.02% : 0.000079s : 1: rewriter_before_opt_a 0.05% : 0.000201s : 1: symbol_engine_optimizer 96.15% : 0.358102s : 1: type_inference [MS_DEV_RUNTIME_CONF] config: aclnn_cache_queue_length:0 TotalTime = 0.209338, [30] [bootstrap]: 0.00058402 [type_inference]: 0.118868 [event_method]: 0.080728 [auto_monad]: 0.00013796 [graph_reusing]: 7e-06 [pre_auto_parallel]: 3.31001e-06 [py_interpret_to_execute]: 0.0002416 [rewriter_before_opt_a]: 8.704e-05 [expand_dump_flag]: 3.63e-06 [jit_opt_a]: 0.00632514, [2] [Cycle 1]: 0.00184183, [27] [switch_simplify]: 0.00010628 [loop_unroll]: 2.239e-05 [a_1]: 0.00043988 [with_stream_mark]: 2.223e-05 [recompute_prepare]: 6.94001e-06 [updatestate_depend_eliminate]: 4.22998e-06 [updatestate_assign_eliminate]: 3.14999e-06 [updatestate_loads_eliminate]: 2.96999e-06 [parameter_eliminate]: 1.94999e-06 [specialize_transform]: 6.14999e-06 [updatestate_useless_node_eliminater]: 5.24e-06 [accelerated_algorithm]: 5.28002e-06 [meta_shard_fg_expand]: 2.06998e-06 [get_grad_eliminate_]: 5.30999e-06 [merge_forward]: 3.60998e-06 [cell_reuse_recompute_pass]: 1.10999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.462e-05 [j_node_and_user_rematch]: 1.01e-05 [meta_fg_expand]: 2.53e-06 [replace_old_param]: 9.71e-06 [inline_without_move]: 5.29e-06 [renormalize]: 0.00092719 [add_forward_monad_depend]: 1.109e-05 [auto_monad_grad]: 2.64999e-06 [auto_monad_eliminator]: 1.453e-05 [cse]: 2.297e-05 [replace_applicator]: 1.223e-05 [Cycle 2]: 0.0003241, [27] [switch_simplify]: 5.54e-06 [loop_unroll]: 4.77e-06 [a_1]: 9.206e-05 [with_stream_mark]: 1.037e-05 [recompute_prepare]: 4.67e-06 [updatestate_depend_eliminate]: 2.83e-06 [updatestate_assign_eliminate]: 2.34001e-06 [updatestate_loads_eliminate]: 2.03002e-06 [parameter_eliminate]: 1.10999e-06 [specialize_transform]: 5.16002e-06 [updatestate_useless_node_eliminater]: 5.05999e-06 [accelerated_algorithm]: 4.53999e-06 [meta_shard_fg_expand]: 1.45999e-06 [get_grad_eliminate_]: 4.63999e-06 [merge_forward]: 2.70002e-06 [cell_reuse_recompute_pass]: 1.29998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.369e-05 [j_node_and_user_rematch]: 8.62998e-06 [meta_fg_expand]: 1.87999e-06 [replace_old_param]: 7.6e-06 [inline_without_move]: 4.64002e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.02998e-06 [auto_monad_grad]: 8.09989e-07 [auto_monad_eliminator]: 5.42001e-06 [cse]: 1.122e-05 [replace_applicator]: 4.95999e-06 [py_interpret_to_execute_after_opt_a]: 1.268e-05 [rewriter_after_opt_a]: 3.534e-05 [convert_after_rewriter]: 6.94001e-06 [order_py_execute_after_rewriter]: 5.71998e-06 [mutable_eliminate]: 0.00057858 [jit_opt_b]: 5.229e-05, [1] [Cycle 1]: 4.463e-05, [2] [frontend_op_eliminate]: 1.657e-05 [inline_after_opt_a]: 1.553e-05 [cconv]: 2.623e-05 [loop_unroll]: 0.00041655 [jit_opt_after_cconv]: 0.00014517, [1] [Cycle 1]: 0.00013845, [11] [c_1]: 2.068e-05 [parameter_eliminate]: 3.06999e-06 [updatestate_depend_eliminate]: 5.84999e-06 [updatestate_assign_eliminate]: 2.63998e-06 [updatestate_loads_eliminate]: 2.25002e-06 [cse]: 1.883e-05 [call_graph_tuple_transform]: 1.952e-05 [tuple_list_get_item_eliminator]: 5.51e-06 [none_parameter_eliminate]: 1.50999e-06 [renormalize]: 7.49977e-07 [switch_simplify]: 5.37001e-06 [remove_dup_value]: 1.359e-05 [partial_unused_args_eliminate]: 2.07001e-06 [environ_conv]: 4.87998e-06 [add_recomputation]: 5.048e-05 [cse_after_recomputation]: 2.199e-05, [1] [Cycle 1]: 1.646e-05, [1] [cse]: 1.046e-05 [auto_monad_reorder]: 1.516e-05 [get_jit_bprop_graph]: 2.31998e-06 [rewriter_after_jit_bprop_graph]: 4.70001e-06 [opt_after_jit_grad]: 0.00044906 [symbol_engine_optimizer]: 0.00015761, [1] [Cycle 1]: 0.00015116, [6] [build]: 7.277e-05 [elim_shapecalc]: 9.54999e-06 [elim_not_effective]: 1.643e-05 [opt_reshape]: 5.65001e-06 [fold_const_symbol]: 1.328e-05 [renormalize]: 6.89994e-07 [validate]: 3.672e-05 Sums bootstrap : 0.000584s : 0.29% type_inference : 0.118868s : 58.14% event_method : 0.080728s : 39.49% auto_monad : 0.000138s : 0.07% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000242s : 0.12% rewriter_before_opt_a : 0.000087s : 0.04% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000112s : 0.05% jit_opt_a.loop_unroll : 0.000027s : 0.01% jit_opt_a.a_1 : 0.000532s : 0.26% jit_opt_a.with_stream_mark : 0.000033s : 0.02% jit_opt_a.recompute_prepare : 0.000012s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000007s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000011s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000010s : 0.01% jit_opt_a.accelerated_algorithm : 0.000010s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000010s : 0.00% jit_opt_a.merge_forward : 0.000006s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000002s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000028s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000019s : 0.01% jit_opt_a.meta_fg_expand : 0.000004s : 0.00% jit_opt_a.replace_old_param : 0.000017s : 0.01% jit_opt_a.inline_without_move : 0.000010s : 0.00% jit_opt_a.renormalize : 0.000927s : 0.45% jit_opt_a.add_forward_monad_depend : 0.000012s : 0.01% jit_opt_a.auto_monad_grad : 0.000003s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000020s : 0.01% jit_opt_a.cse : 0.000034s : 0.02% jit_opt_a.replace_applicator : 0.000017s : 0.01% py_interpret_to_execute_after_opt_a : 0.000013s : 0.01% rewriter_after_opt_a : 0.000035s : 0.02% convert_after_rewriter : 0.000007s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000579s : 0.28% jit_opt_b.frontend_op_eliminate : 0.000017s : 0.01% jit_opt_b.inline_after_opt_a : 0.000016s : 0.01% cconv : 0.000026s : 0.01% loop_unroll : 0.000417s : 0.20% jit_opt_after_cconv.c_1 : 0.000021s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000006s : 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 : 0.000019s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000020s : 0.01% 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 : 0.000005s : 0.00% remove_dup_value : 0.000014s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000005s : 0.00% add_recomputation : 0.000050s : 0.02% cse_after_recomputation.cse : 0.000010s : 0.01% auto_monad_reorder : 0.000015s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000449s : 0.22% symbol_engine_optimizer.build : 0.000073s : 0.04% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000016s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000006s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000013s : 0.01% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000037s : 0.02% Time group info: ------[substitution.] 0.000154 25 3.47% : 0.000005s : 2: substitution.elim_not_effective 3.81% : 0.000006s : 2: substitution.fold_const_symbol 4.06% : 0.000006s : 3: substitution.graph_param_transform 73.11% : 0.000113s : 6: substitution.inline 2.56% : 0.000004s : 4: substitution.j_node_and_user_rematch 3.02% : 0.000005s : 4: substitution.remove_not_recompute_node 3.16% : 0.000005s : 2: substitution.replace_old_param 6.81% : 0.000010s : 2: substitution.switch_simplify ------[type_inference.] 0.118804 2 98.88% : 0.117473s : 1: type_inference.infer 1.12% : 0.001332s : 1: type_inference.specialize ------[replace.] 0.000069 8 48.80% : 0.000034s : 6: replace.inline 51.20% : 0.000036s : 2: replace.switch_simplify ------[match.] 0.000119 8 92.14% : 0.000109s : 6: match.inline 7.86% : 0.000009s : 2: match.switch_simplify ------[predicate.] 0.000122 705 1.60% : 0.000002s : 11: predicate.accumulaten_eliminater 1.29% : 0.000002s : 3: predicate.ad_related_special_op_eliminate 1.18% : 0.000001s : 11: predicate.addn_check_dump 1.30% : 0.000002s : 11: predicate.addn_zero_filter 2.16% : 0.000003s : 11: predicate.arithmetic_simplify 1.38% : 0.000002s : 11: predicate.cast_eliminate 0.47% : 0.000001s : 3: predicate.check_bprop_eliminate 1.11% : 0.000001s : 11: predicate.compare_switch_simplify 1.22% : 0.000001s : 11: predicate.depend_value_elim 1.20% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.33% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.35% : 0.000002s : 11: predicate.dict_set_item_eliminator 0.96% : 0.000001s : 3: predicate.dumpgradient_eliminate 0.34% : 0.000000s : 3: predicate.elim_not_effective 0.71% : 0.000001s : 3: predicate.elim_shapecalc_of_broadcastargs 1.23% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.14% : 0.000001s : 11: predicate.environ_get_add_eliminate 1.13% : 0.000001s : 11: predicate.environ_get_depend_swap 1.23% : 0.000001s : 11: predicate.environ_get_eliminate 1.17% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.23% : 0.000000s : 3: predicate.fold_const_symbol 1.19% : 0.000001s : 6: predicate.get_grad_eliminate 0.23% : 0.000000s : 3: predicate.graph_param_transform 5.22% : 0.000006s : 23: predicate.inline 0.89% : 0.000001s : 6: predicate.inline_without_move 0.41% : 0.000001s : 6: predicate.j_node_and_user_rematch 1.22% : 0.000001s : 6: predicate.less_batch_normalization 1.31% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.57% : 0.000002s : 14: predicate.load_eliminater 1.34% : 0.000002s : 3: predicate.loop_unroll_after_grad 3.29% : 0.000004s : 26: predicate.loop_unroll_before_grad 1.98% : 0.000002s : 14: predicate.make_slice_get_slice_eliminator 1.13% : 0.000001s : 11: predicate.merge_addn 1.13% : 0.000001s : 11: predicate.minmaximum_grad 1.65% : 0.000002s : 3: predicate.mutable_eliminate 0.50% : 0.000001s : 3: predicate.opt_reshape 2.16% : 0.000003s : 14: predicate.partial_eliminate 1.34% : 0.000002s : 11: predicate.print_const_string_wrapper 1.84% : 0.000002s : 11: predicate.reduce_eliminate 1.30% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.63% : 0.000001s : 6: predicate.remove_not_recompute_node 1.63% : 0.000002s : 17: predicate.replace_applicator 0.76% : 0.000001s : 6: predicate.replace_old_param 0.35% : 0.000000s : 3: predicate.reset_defer_inline 1.30% : 0.000002s : 11: predicate.reshape_eliminate 1.40% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.72% : 0.000001s : 3: predicate.row_tensor_eliminate 1.25% : 0.000002s : 11: predicate.same_eliminate 0.52% : 0.000001s : 6: predicate.set_cell_output_no_recompute 0.98% : 0.000001s : 6: predicate.special_op_eliminate 1.03% : 0.000001s : 6: predicate.specialize_transform 1.47% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.26% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.44% : 0.000001s : 3: predicate.switch_call_monad_eliminater 2.37% : 0.000003s : 17: predicate.switch_defer_inline 2.27% : 0.000003s : 17: predicate.switch_layer_defer_inline 8.20% : 0.000010s : 50: predicate.switch_simplify 1.26% : 0.000002s : 11: predicate.tile_eliminate 1.33% : 0.000002s : 11: predicate.transpose_eliminate 1.75% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.69% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.11% : 0.000004s : 17: predicate.tuple_list_get_item_eliminator 2.20% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.32% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.54% : 0.000002s : 14: predicate.updatestate_pure_node_eliminater 2.86% : 0.000003s : 20: predicate.updatestate_useless_node_eliminater 1.75% : 0.000002s : 11: predicate.value_based_eliminate 0.38% : 0.000000s : 3: predicate.virtual_view_grad_eliminate 0.78% : 0.000001s : 3: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.085967 11 99.61% : 0.085632s : 3: func_graph_cloner_run.FuncGraphClonerGraph 0.39% : 0.000334s : 8: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.211010 72 0.03% : 0.000054s : 1: add_recomputation 0.07% : 0.000146s : 1: auto_monad 0.01% : 0.000018s : 1: auto_monad_reorder 0.29% : 0.000606s : 1: bootstrap 0.01% : 0.000029s : 1: cconv 0.00% : 0.000010s : 1: convert_after_rewriter 0.01% : 0.000024s : 1: cse_after_recomputation 0.00% : 0.000007s : 1: environ_conv 38.27% : 0.080757s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 3.00% : 0.006329s : 1: jit_opt_a 0.07% : 0.000148s : 1: jit_opt_after_cconv 0.03% : 0.000055s : 1: jit_opt_b 0.20% : 0.000424s : 1: loop_unroll 0.28% : 0.000588s : 1: mutable_eliminate 0.37% : 0.000784s : 26: opt.transform.jit_opt_a 0.02% : 0.000048s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000025s : 4: opt.transform.jit_opt_b 0.01% : 0.000011s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000014s : 1: opt.transform.mutable_eliminate 0.01% : 0.000020s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000041s : 4: opt.transform.symbol_engine_opt 0.22% : 0.000457s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pre_auto_parallel 0.12% : 0.000246s : 1: py_interpret_to_execute 0.01% : 0.000015s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000016s : 1: remove_dup_value 0.26% : 0.000543s : 1: renormalize.infer 0.18% : 0.000375s : 1: renormalize.specialize 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000038s : 1: rewriter_after_opt_a 0.04% : 0.000092s : 1: rewriter_before_opt_a 0.08% : 0.000161s : 1: symbol_engine_optimizer 56.34% : 0.118884s : 1: type_inference [] [] . [hook] pytest_runtest_teardown:test_sync_aclnn_op_kbyk tests/st/hardware/ascend/aclnn/test_aclnn_cache.py::test_sync_aclnn_op_kbyk,max_mem:6.0M =============================== warnings summary =============================== ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 1 passed, 25 warnings in 78.06s (0:01:18) ===================