==================================================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_chunk.py . [hook] pytest_runtest_teardown:test_chunk_zero_bias[pynative] tests/st/mint/test_chunk.py::test_chunk_zero_bias[pynative],max_mem:2.0M TotalTime = 3.38288, [33] [bootstrap]: 0.00110001 [type_inference]: 0.448897 [event_method]: 1.718e-05 [auto_monad]: 0.00017721 [graph_reusing]: 7.2e-06 [pre_auto_parallel]: 1.163e-05 [py_interpret_to_execute]: 0.00011558 [rewriter_before_opt_a]: 7.773e-05 [expand_dump_flag]: 3.529e-05 [jit_opt_a]: 0.141047, [2] [Cycle 1]: 0.00221408, [27] [switch_simplify]: 5.888e-05 [loop_unroll]: 1.86e-05 [a_1]: 0.00045135 [with_stream_mark]: 3.106e-05 [recompute_prepare]: 1.057e-05 [updatestate_depend_eliminate]: 7.53999e-06 [updatestate_assign_eliminate]: 7.71999e-06 [updatestate_loads_eliminate]: 5.02999e-06 [parameter_eliminate]: 2.47001e-06 [specialize_transform]: 9.47001e-06 [updatestate_useless_node_eliminater]: 1.229e-05 [accelerated_algorithm]: 8.75999e-06 [meta_shard_fg_expand]: 2.89001e-06 [get_grad_eliminate_]: 7.98999e-06 [merge_forward]: 6.43998e-06 [cell_reuse_recompute_pass]: 1.15001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.357e-05 [j_node_and_user_rematch]: 1.402e-05 [meta_fg_expand]: 3.75e-06 [replace_old_param]: 1.273e-05 [inline_without_move]: 8.23999e-06 [renormalize]: 0.00116578 [add_forward_monad_depend]: 1.199e-05 [auto_monad_grad]: 2.91e-06 [auto_monad_eliminator]: 2.693e-05 [cse]: 4.629e-05 [replace_applicator]: 2.189e-05 [Cycle 2]: 0.00064516, [27] [switch_simplify]: 9.52999e-06 [loop_unroll]: 9.22001e-06 [a_1]: 0.00025244 [with_stream_mark]: 2.166e-05 [recompute_prepare]: 1.002e-05 [updatestate_depend_eliminate]: 7.36001e-06 [updatestate_assign_eliminate]: 5.42001e-06 [updatestate_loads_eliminate]: 4.42e-06 [parameter_eliminate]: 2.07999e-06 [specialize_transform]: 1.546e-05 [updatestate_useless_node_eliminater]: 1.428e-05 [accelerated_algorithm]: 8.57e-06 [meta_shard_fg_expand]: 2.01998e-06 [get_grad_eliminate_]: 8.66002e-06 [merge_forward]: 5.92001e-06 [cell_reuse_recompute_pass]: 2.48e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.967e-05 [j_node_and_user_rematch]: 1.335e-05 [meta_fg_expand]: 3.28998e-06 [replace_old_param]: 1.155e-05 [inline_without_move]: 8.40999e-06 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 2.98998e-06 [auto_monad_grad]: 1.64e-06 [auto_monad_eliminator]: 1.632e-05 [cse]: 3.248e-05 [replace_applicator]: 1.055e-05 [py_interpret_to_execute_after_opt_a]: 1.834e-05 [rewriter_after_opt_a]: 0.00033413 [convert_after_rewriter]: 2.864e-05 [order_py_execute_after_rewriter]: 7.1e-06 [mutable_eliminate]: 0.00090307 [jit_opt_b]: 7.893e-05, [1] [Cycle 1]: 6.837e-05, [2] [frontend_op_eliminate]: 2.561e-05 [inline_after_opt_a]: 2.756e-05 [cconv]: 4.417e-05 [loop_unroll]: 0.00061221 [jit_opt_after_cconv]: 0.00025292, [1] [Cycle 1]: 0.00024386, [11] [c_1]: 5.909e-05 [parameter_eliminate]: 7.19001e-06 [updatestate_depend_eliminate]: 1.361e-05 [updatestate_assign_eliminate]: 5.30999e-06 [updatestate_loads_eliminate]: 5.26002e-06 [cse]: 4.914e-05 [call_graph_tuple_transform]: 2.557e-05 [tuple_list_get_item_eliminator]: 9.38002e-06 [none_parameter_eliminate]: 1.72001e-06 [renormalize]: 8.30012e-07 [switch_simplify]: 8.67e-06 [remove_dup_value]: 2.496e-05 [partial_unused_args_eliminate]: 2.69999e-06 [environ_conv]: 3.248e-05 [add_recomputation]: 8.667e-05 [cse_after_recomputation]: 3.48e-05, [1] [Cycle 1]: 2.801e-05, [1] [cse]: 2.055e-05 [auto_monad_reorder]: 0.00022403 [get_jit_bprop_graph]: 2.86e-06 [rewriter_after_jit_bprop_graph]: 0.00031537 [opt_after_jit_grad]: 0.00072722 [symbol_engine_optimizer]: 0.00013821, [1] [Cycle 1]: 0.00013023, [6] [build]: 3.404e-05 [elim_shapecalc]: 1.468e-05 [elim_not_effective]: 2.171e-05 [opt_reshape]: 9.39998e-06 [fold_const_symbol]: 1.445e-05 [renormalize]: 2.00002e-07 [validate]: 9.109e-05 [backend_pass]: 9.70002e-07 [task_emit]: 2.78701 [execute]: 1.056e-05 Sums bootstrap : 0.001100s : 0.03% type_inference : 0.448897s : 13.84% event_method : 0.000017s : 0.00% auto_monad : 0.000177s : 0.01% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000116s : 0.00% rewriter_before_opt_a : 0.000078s : 0.00% expand_dump_flag : 0.000035s : 0.00% jit_opt_a.switch_simplify : 0.000068s : 0.00% jit_opt_a.loop_unroll : 0.000028s : 0.00% jit_opt_a.a_1 : 0.000704s : 0.02% jit_opt_a.with_stream_mark : 0.000053s : 0.00% jit_opt_a.recompute_prepare : 0.000021s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000025s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000027s : 0.00% jit_opt_a.accelerated_algorithm : 0.000017s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 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 : 0.000043s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000027s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.001166s : 0.04% jit_opt_a.add_forward_monad_depend : 0.000015s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000043s : 0.00% jit_opt_a.cse : 0.000079s : 0.00% jit_opt_a.replace_applicator : 0.000032s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000334s : 0.01% convert_after_rewriter : 0.000029s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000903s : 0.03% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.00% jit_opt_b.inline_after_opt_a : 0.000028s : 0.00% cconv : 0.000044s : 0.00% loop_unroll : 0.000612s : 0.02% jit_opt_after_cconv.c_1 : 0.000059s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 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 : 0.000049s : 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 : 0.000025s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000032s : 0.00% add_recomputation : 0.000087s : 0.00% cse_after_recomputation.cse : 0.000021s : 0.00% auto_monad_reorder : 0.000224s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000315s : 0.01% opt_after_jit_grad : 0.000727s : 0.02% symbol_engine_optimizer.build : 0.000034s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 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 : 0.000000s : 0.00% validate : 0.000091s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 2.787008s : 85.92% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000233 43 4.48% : 0.000010s : 2: substitution.depend_value_elim 1.15% : 0.000003s : 4: substitution.elim_not_effective 0.83% : 0.000002s : 4: substitution.fold_const_symbol 3.32% : 0.000008s : 5: substitution.graph_param_transform 70.46% : 0.000164s : 2: substitution.inline 2.16% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.31% : 0.000008s : 8: substitution.remove_not_recompute_node 2.57% : 0.000006s : 2: substitution.replace_old_param 6.64% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 5.09% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.448809 2 99.77% : 0.447768s : 1: type_inference.infer 0.23% : 0.001041s : 1: type_inference.specialize ------[replace.] 0.000033 2 100.00% : 0.000033s : 2: replace.inline ------[match.] 0.000163 2 100.00% : 0.000163s : 2: match.inline ------[predicate.] 0.000156 767 1.31% : 0.000002s : 11: predicate.accumulaten_eliminater 2.07% : 0.000003s : 5: predicate.ad_related_special_op_eliminate 1.02% : 0.000002s : 11: predicate.addn_check_dump 1.63% : 0.000003s : 11: predicate.addn_zero_filter 2.17% : 0.000003s : 11: predicate.arithmetic_simplify 1.11% : 0.000002s : 11: predicate.cast_eliminate 0.59% : 0.000001s : 5: predicate.check_bprop_eliminate 1.06% : 0.000002s : 11: predicate.compare_switch_simplify 1.34% : 0.000002s : 11: predicate.depend_value_elim 1.10% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.04% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.17% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.13% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.65% : 0.000001s : 5: predicate.elim_not_effective 1.06% : 0.000002s : 5: predicate.elim_shapecalc_of_broadcastargs 1.09% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.04% : 0.000002s : 11: predicate.environ_get_add_eliminate 0.98% : 0.000002s : 11: predicate.environ_get_depend_swap 1.17% : 0.000002s : 11: predicate.environ_get_eliminate 0.98% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.28% : 0.000000s : 5: predicate.fold_const_symbol 1.27% : 0.000002s : 10: predicate.get_grad_eliminate 0.31% : 0.000000s : 5: predicate.graph_param_transform 6.25% : 0.000010s : 23: predicate.inline 1.50% : 0.000002s : 10: predicate.inline_without_move 0.62% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.54% : 0.000002s : 10: predicate.less_batch_normalization 1.49% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.84% : 0.000003s : 16: predicate.load_eliminater 1.79% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.52% : 0.000004s : 20: predicate.loop_unroll_before_grad 1.91% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 0.98% : 0.000002s : 11: predicate.merge_addn 0.96% : 0.000002s : 11: predicate.minmaximum_grad 2.98% : 0.000005s : 5: predicate.mutable_eliminate 0.69% : 0.000001s : 5: predicate.opt_reshape 2.00% : 0.000003s : 16: predicate.partial_eliminate 1.34% : 0.000002s : 11: predicate.print_const_string_wrapper 1.76% : 0.000003s : 11: predicate.reduce_eliminate 1.10% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.81% : 0.000001s : 10: predicate.remove_not_recompute_node 1.54% : 0.000002s : 21: predicate.replace_applicator 0.76% : 0.000001s : 10: predicate.replace_old_param 0.65% : 0.000001s : 5: predicate.reset_defer_inline 1.35% : 0.000002s : 11: predicate.reshape_eliminate 1.11% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.11% : 0.000002s : 5: predicate.row_tensor_eliminate 1.18% : 0.000002s : 11: predicate.same_eliminate 0.63% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.40% : 0.000002s : 10: predicate.special_op_eliminate 1.81% : 0.000003s : 10: predicate.specialize_transform 1.54% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.14% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.65% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.30% : 0.000002s : 13: predicate.switch_defer_inline 1.34% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.42% : 0.000008s : 38: predicate.switch_simplify 0.99% : 0.000002s : 11: predicate.tile_eliminate 0.96% : 0.000002s : 11: predicate.transpose_eliminate 1.26% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.09% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.56% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.47% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.08% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.79% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 4.47% : 0.000007s : 26: predicate.updatestate_useless_node_eliminater 1.48% : 0.000002s : 11: predicate.value_based_eliminate 0.53% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.74% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000470 6 30.29% : 0.000142s : 2: func_graph_cloner_run.FuncGraphClonerGraph 69.71% : 0.000328s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.385163 76 0.00% : 0.000090s : 1: add_recomputation 0.01% : 0.000182s : 1: auto_monad 0.01% : 0.000232s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.03% : 0.001124s : 1: bootstrap 0.00% : 0.000047s : 1: cconv 0.00% : 0.000034s : 1: convert_after_rewriter 0.00% : 0.000037s : 1: cse_after_recomputation 0.00% : 0.000035s : 1: environ_conv 0.00% : 0.000022s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000041s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 4.17% : 0.141052s : 1: jit_opt_a 0.01% : 0.000257s : 1: jit_opt_after_cconv 0.00% : 0.000082s : 1: jit_opt_b 0.02% : 0.000626s : 1: loop_unroll 0.03% : 0.000916s : 1: mutable_eliminate 0.03% : 0.001001s : 26: opt.transform.jit_opt_a 0.00% : 0.000099s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000030s : 1: opt.transform.mutable_eliminate 0.00% : 0.000039s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000056s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000739s : 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% : 0.000014s : 1: pre_auto_parallel 0.00% : 0.000120s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000028s : 1: remove_dup_value 0.02% : 0.000733s : 1: renormalize.infer 0.01% : 0.000422s : 1: renormalize.specialize 0.01% : 0.000323s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000343s : 1: rewriter_after_opt_a 0.00% : 0.000082s : 1: rewriter_before_opt_a 0.00% : 0.000141s : 1: symbol_engine_optimizer 82.33% : 2.787037s : 1: task_emit 13.26% : 0.448917s : 1: type_inference 0.00% : 0.000123s : 1: validate TotalTime = 4.41, [33] [bootstrap]: 0.0005438 [type_inference]: 0.757359 [event_method]: 0.0002977 [auto_monad]: 0.00048154 [graph_reusing]: 1.439e-05 [pre_auto_parallel]: 4.18001e-06 [py_interpret_to_execute]: 8.199e-05 [rewriter_before_opt_a]: 0.00018105 [expand_dump_flag]: 6.06e-06 [jit_opt_a]: 1.07704, [4] [Cycle 1]: 0.909466, [27] [switch_simplify]: 0.00023715 [loop_unroll]: 6.586e-05 [a_1]: 0.00196602 [with_stream_mark]: 4.817e-05 [recompute_prepare]: 4.216e-05 [updatestate_depend_eliminate]: 5.526e-05 [updatestate_assign_eliminate]: 1.338e-05 [updatestate_loads_eliminate]: 1.054e-05 [parameter_eliminate]: 4.03999e-06 [specialize_transform]: 2.567e-05 [updatestate_useless_node_eliminater]: 2.693e-05 [accelerated_algorithm]: 2.07e-05 [meta_shard_fg_expand]: 1.081e-05 [get_grad_eliminate_]: 2.003e-05 [merge_forward]: 1.322e-05 [cell_reuse_recompute_pass]: 1.37e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.289e-05 [j_node_and_user_rematch]: 3.706e-05 [meta_fg_expand]: 0.542413 [replace_old_param]: 0.00019187 [inline_without_move]: 0.00017547 [renormalize]: 0.362564 [add_forward_monad_depend]: 3.82e-05 [auto_monad_grad]: 2.344e-05 [auto_monad_eliminator]: 0.00016731 [cse]: 0.00050531 [replace_applicator]: 0.00038219 [Cycle 2]: 0.160065, [27] [switch_simplify]: 0.00011687 [loop_unroll]: 0.00010869 [a_1]: 0.155525 [with_stream_mark]: 6.109e-05 [recompute_prepare]: 4.605e-05 [updatestate_depend_eliminate]: 1.954e-05 [updatestate_assign_eliminate]: 2.089e-05 [updatestate_loads_eliminate]: 1.846e-05 [parameter_eliminate]: 5.76998e-06 [specialize_transform]: 3.092e-05 [updatestate_useless_node_eliminater]: 0.00010948 [accelerated_algorithm]: 4.476e-05 [meta_shard_fg_expand]: 1.157e-05 [get_grad_eliminate_]: 1.838e-05 [merge_forward]: 1.209e-05 [cell_reuse_recompute_pass]: 1.37999e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.618e-05 [j_node_and_user_rematch]: 3.247e-05 [meta_fg_expand]: 0.00023696 [replace_old_param]: 2.875e-05 [inline_without_move]: 1.893e-05 [renormalize]: 0.00297175 [add_forward_monad_depend]: 1.315e-05 [auto_monad_grad]: 2.86999e-06 [auto_monad_eliminator]: 4.544e-05 [cse]: 0.00020674 [replace_applicator]: 4.279e-05 [Cycle 3]: 0.00250764, [27] [switch_simplify]: 2.033e-05 [loop_unroll]: 1.874e-05 [a_1]: 0.00051625 [with_stream_mark]: 2.775e-05 [recompute_prepare]: 2.819e-05 [updatestate_depend_eliminate]: 4.645e-05 [updatestate_assign_eliminate]: 9.54999e-06 [updatestate_loads_eliminate]: 8.15e-06 [parameter_eliminate]: 2.82002e-06 [specialize_transform]: 1.596e-05 [updatestate_useless_node_eliminater]: 1.829e-05 [accelerated_algorithm]: 2.032e-05 [meta_shard_fg_expand]: 3.88999e-06 [get_grad_eliminate_]: 1.519e-05 [merge_forward]: 9.15001e-06 [cell_reuse_recompute_pass]: 2.98e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.363e-05 [j_node_and_user_rematch]: 2.512e-05 [meta_fg_expand]: 6.68e-06 [replace_old_param]: 1.768e-05 [inline_without_move]: 1.345e-05 [renormalize]: 0.00127861 [add_forward_monad_depend]: 7.68999e-06 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 3.11e-05 [cse]: 0.00012286 [replace_applicator]: 2.704e-05 [Cycle 4]: 0.00087921, [27] [switch_simplify]: 1.503e-05 [loop_unroll]: 1.404e-05 [a_1]: 0.00039103 [with_stream_mark]: 2.001e-05 [recompute_prepare]: 1.603e-05 [updatestate_depend_eliminate]: 9.22999e-06 [updatestate_assign_eliminate]: 8.2e-06 [updatestate_loads_eliminate]: 7.68999e-06 [parameter_eliminate]: 1.76998e-06 [specialize_transform]: 1.474e-05 [updatestate_useless_node_eliminater]: 1.762e-05 [accelerated_algorithm]: 1.887e-05 [meta_shard_fg_expand]: 4.15e-06 [get_grad_eliminate_]: 1.369e-05 [merge_forward]: 9.10001e-06 [cell_reuse_recompute_pass]: 2.18002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.24e-05 [j_node_and_user_rematch]: 2.476e-05 [meta_fg_expand]: 5.84999e-06 [replace_old_param]: 1.63e-05 [inline_without_move]: 1.366e-05 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 1.78002e-06 [auto_monad_grad]: 1.64e-06 [auto_monad_eliminator]: 2.22e-05 [cse]: 4.991e-05 [replace_applicator]: 1.419e-05 [py_interpret_to_execute_after_opt_a]: 2.462e-05 [rewriter_after_opt_a]: 0.0151586 [convert_after_rewriter]: 4.412e-05 [order_py_execute_after_rewriter]: 1.608e-05 [mutable_eliminate]: 0.00093684 [jit_opt_b]: 0.0003444, [2] [Cycle 1]: 0.00026547, [2] [frontend_op_eliminate]: 0.00020325 [inline_after_opt_a]: 3.83e-05 [Cycle 2]: 6.455e-05, [2] [frontend_op_eliminate]: 2.585e-05 [inline_after_opt_a]: 2.625e-05 [cconv]: 3.995e-05 [loop_unroll]: 0.00058602 [jit_opt_after_cconv]: 0.00031706, [1] [Cycle 1]: 0.00030928, [11] [c_1]: 6.735e-05 [parameter_eliminate]: 6.48e-06 [updatestate_depend_eliminate]: 1.711e-05 [updatestate_assign_eliminate]: 7.51999e-06 [updatestate_loads_eliminate]: 7.1e-06 [cse]: 8.117e-05 [call_graph_tuple_transform]: 3.367e-05 [tuple_list_get_item_eliminator]: 1.174e-05 [none_parameter_eliminate]: 1.69e-06 [renormalize]: 1.27999e-06 [switch_simplify]: 1.231e-05 [remove_dup_value]: 7.85e-05 [partial_unused_args_eliminate]: 2.90002e-06 [environ_conv]: 1.857e-05 [add_recomputation]: 0.00010259 [cse_after_recomputation]: 5.317e-05, [1] [Cycle 1]: 4.537e-05, [1] [cse]: 3.599e-05 [auto_monad_reorder]: 3.384e-05 [get_jit_bprop_graph]: 2.26998e-06 [rewriter_after_jit_bprop_graph]: 1.066e-05 [opt_after_jit_grad]: 0.00064833 [symbol_engine_optimizer]: 0.00020276, [1] [Cycle 1]: 0.00013869, [6] [build]: 1.819e-05 [elim_shapecalc]: 1.982e-05 [elim_not_effective]: 2.848e-05 [opt_reshape]: 1.321e-05 [fold_const_symbol]: 2.013e-05 [renormalize]: 6.69999e-07 [validate]: 7.229e-05 [backend_pass]: 1.00999e-06 [task_emit]: 2.55494 [execute]: 1.074e-05 Sums bootstrap : 0.000544s : 0.01% type_inference : 0.757359s : 17.20% event_method : 0.000298s : 0.01% auto_monad : 0.000482s : 0.01% graph_reusing : 0.000014s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000082s : 0.00% rewriter_before_opt_a : 0.000181s : 0.00% expand_dump_flag : 0.000006s : 0.00% jit_opt_a.switch_simplify : 0.000389s : 0.01% jit_opt_a.loop_unroll : 0.000207s : 0.00% jit_opt_a.a_1 : 0.158399s : 3.60% jit_opt_a.with_stream_mark : 0.000157s : 0.00% jit_opt_a.recompute_prepare : 0.000132s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000130s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000052s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000045s : 0.00% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000087s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000172s : 0.00% jit_opt_a.accelerated_algorithm : 0.000105s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000030s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000067s : 0.00% jit_opt_a.merge_forward : 0.000044s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000008s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000155s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000119s : 0.00% jit_opt_a.meta_fg_expand : 0.542663s : 12.32% jit_opt_a.replace_old_param : 0.000255s : 0.01% jit_opt_a.inline_without_move : 0.000222s : 0.01% jit_opt_a.renormalize : 0.366815s : 8.33% jit_opt_a.add_forward_monad_depend : 0.000061s : 0.00% jit_opt_a.auto_monad_grad : 0.000031s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000266s : 0.01% jit_opt_a.cse : 0.000885s : 0.02% jit_opt_a.replace_applicator : 0.000466s : 0.01% py_interpret_to_execute_after_opt_a : 0.000025s : 0.00% rewriter_after_opt_a : 0.015159s : 0.34% convert_after_rewriter : 0.000044s : 0.00% order_py_execute_after_rewriter : 0.000016s : 0.00% mutable_eliminate : 0.000937s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000229s : 0.01% jit_opt_b.inline_after_opt_a : 0.000065s : 0.00% cconv : 0.000040s : 0.00% loop_unroll : 0.000586s : 0.01% jit_opt_after_cconv.c_1 : 0.000067s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 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 : 0.000081s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000034s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000012s : 0.00% remove_dup_value : 0.000079s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000019s : 0.00% add_recomputation : 0.000103s : 0.00% cse_after_recomputation.cse : 0.000036s : 0.00% auto_monad_reorder : 0.000034s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000011s : 0.00% opt_after_jit_grad : 0.000648s : 0.01% symbol_engine_optimizer.build : 0.000018s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000020s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000028s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000072s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 2.554941s : 58.01% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.004571 395 0.82% : 0.000037s : 4: substitution.cast_eliminate 1.15% : 0.000053s : 15: substitution.depend_value_elim 0.08% : 0.000004s : 6: substitution.elim_not_effective 0.06% : 0.000003s : 6: substitution.fold_const_symbol 33.48% : 0.001530s : 9: substitution.getattr_setattr_resolve 0.18% : 0.000008s : 7: substitution.graph_param_transform 45.15% : 0.002064s : 34: substitution.inline 1.24% : 0.000057s : 5: substitution.inline_without_move 0.52% : 0.000024s : 46: substitution.j_node_and_user_rematch 0.59% : 0.000027s : 3: substitution.less_batch_normalization 1.00% : 0.000046s : 24: substitution.minmaximum_grad 0.35% : 0.000016s : 14: substitution.partial_eliminate 0.74% : 0.000034s : 46: substitution.remove_not_recompute_node 2.39% : 0.000109s : 26: substitution.replace_applicator 0.50% : 0.000023s : 20: substitution.replace_old_param 0.16% : 0.000007s : 2: substitution.set_cell_output_no_recompute 0.37% : 0.000017s : 3: substitution.switch_simplify 1.87% : 0.000086s : 24: substitution.tuple_list_convert_item_index_to_positive 1.64% : 0.000075s : 25: substitution.tuple_list_get_item_depend_reorder 3.15% : 0.000144s : 43: substitution.tuple_list_get_item_eliminator 0.78% : 0.000036s : 2: substitution.tuple_list_set_item_eliminator 0.65% : 0.000030s : 11: substitution.updatestate_pure_node_eliminater 1.53% : 0.000070s : 18: substitution.updatestate_useless_node_eliminater 1.60% : 0.000073s : 2: substitution.zero_like_fill_zero ------[type_inference.] 0.757202 2 99.49% : 0.753336s : 1: type_inference.infer 0.51% : 0.003866s : 1: type_inference.specialize ------[replace.] 0.001387 77 1.71% : 0.000024s : 4: replace.cast_eliminate 12.66% : 0.000176s : 7: replace.getattr_setattr_resolve 42.39% : 0.000588s : 34: replace.inline 6.85% : 0.000095s : 5: replace.replace_applicator 5.41% : 0.000075s : 3: replace.switch_simplify 1.23% : 0.000017s : 1: replace.tuple_list_get_item_depend_reorder 18.05% : 0.000250s : 18: replace.tuple_list_get_item_eliminator 2.96% : 0.000041s : 2: replace.tuple_list_set_item_eliminator 4.22% : 0.000059s : 1: replace.updatestate_useless_node_eliminater 4.51% : 0.000063s : 2: replace.zero_like_fill_zero ------[match.] 0.003721 77 0.92% : 0.000034s : 4: match.cast_eliminate 38.26% : 0.001423s : 7: match.getattr_setattr_resolve 54.75% : 0.002037s : 34: match.inline 0.98% : 0.000036s : 5: match.replace_applicator 0.40% : 0.000015s : 3: match.switch_simplify 0.34% : 0.000013s : 1: match.tuple_list_get_item_depend_reorder 1.16% : 0.000043s : 18: match.tuple_list_get_item_eliminator 0.88% : 0.000033s : 2: match.tuple_list_set_item_eliminator 0.39% : 0.000015s : 1: match.updatestate_useless_node_eliminater 1.92% : 0.000071s : 2: match.zero_like_fill_zero ------[predicate.] 0.001241 7808 1.45% : 0.000018s : 130: predicate.accumulaten_eliminater 0.26% : 0.000003s : 7: predicate.ad_related_special_op_eliminate 1.39% : 0.000017s : 130: predicate.addn_check_dump 1.52% : 0.000019s : 130: predicate.addn_zero_filter 2.10% : 0.000026s : 130: predicate.arithmetic_simplify 1.72% : 0.000021s : 134: predicate.cast_eliminate 0.19% : 0.000002s : 15: predicate.check_bprop_eliminate 1.35% : 0.000017s : 130: predicate.compare_switch_simplify 1.63% : 0.000020s : 130: predicate.depend_value_elim 1.47% : 0.000018s : 134: predicate.dict_get_item_const_eliminator 1.52% : 0.000019s : 134: predicate.dict_get_item_eliminator 1.47% : 0.000018s : 134: predicate.dict_set_item_eliminator 0.19% : 0.000002s : 7: predicate.dumpgradient_eliminate 0.07% : 0.000001s : 7: predicate.elim_not_effective 0.19% : 0.000002s : 7: predicate.elim_shapecalc_of_broadcastargs 1.49% : 0.000019s : 134: predicate.environ_add_const_eliminate 1.49% : 0.000018s : 134: predicate.environ_get_add_eliminate 1.45% : 0.000018s : 134: predicate.environ_get_depend_swap 1.51% : 0.000019s : 134: predicate.environ_get_eliminate 1.44% : 0.000018s : 134: predicate.environ_get_set_eliminate 0.05% : 0.000001s : 7: predicate.fold_const_symbol 0.75% : 0.000009s : 53: predicate.get_grad_eliminate 1.23% : 0.000015s : 51: predicate.getattr_setattr_resolve 0.05% : 0.000001s : 7: predicate.graph_param_transform 4.75% : 0.000059s : 210: predicate.inline 2.11% : 0.000026s : 136: predicate.inline_without_move 0.30% : 0.000004s : 53: predicate.j_node_and_user_rematch 0.85% : 0.000011s : 53: predicate.less_batch_normalization 1.93% : 0.000024s : 155: predicate.list_to_tuple_eliminator_ 1.84% : 0.000023s : 162: predicate.load_eliminater 0.26% : 0.000003s : 7: predicate.loop_unroll_after_grad 2.59% : 0.000032s : 214: predicate.loop_unroll_before_grad 1.62% : 0.000020s : 142: predicate.make_slice_get_slice_eliminator 1.41% : 0.000017s : 130: predicate.merge_addn 1.48% : 0.000018s : 130: predicate.minmaximum_grad 0.56% : 0.000007s : 11: predicate.mutable_eliminate 0.11% : 0.000001s : 7: predicate.opt_reshape 2.31% : 0.000029s : 162: predicate.partial_eliminate 1.44% : 0.000018s : 130: predicate.print_const_string_wrapper 2.02% : 0.000025s : 130: predicate.reduce_eliminate 1.81% : 0.000022s : 155: predicate.redundant_stop_gradient_eliminater 0.36% : 0.000004s : 53: predicate.remove_not_recompute_node 2.59% : 0.000032s : 322: predicate.replace_applicator 0.94% : 0.000012s : 136: predicate.replace_old_param 0.14% : 0.000002s : 14: predicate.reset_defer_inline 1.66% : 0.000021s : 130: predicate.reshape_eliminate 1.42% : 0.000018s : 130: predicate.row_tensor_add_zeros_like 0.32% : 0.000004s : 15: predicate.row_tensor_eliminate 1.53% : 0.000019s : 130: predicate.same_eliminate 0.48% : 0.000006s : 68: predicate.set_cell_output_no_recompute 0.35% : 0.000004s : 22: predicate.special_op_eliminate 0.90% : 0.000011s : 63: predicate.specialize_transform 1.75% : 0.000022s : 130: predicate.split_environ_get_set_with_tuple_value 1.48% : 0.000018s : 130: predicate.stack_unstack_eliminate 0.10% : 0.000001s : 7: predicate.switch_call_monad_eliminater 3.20% : 0.000040s : 189: predicate.switch_defer_inline 2.47% : 0.000031s : 189: predicate.switch_layer_defer_inline 5.95% : 0.000074s : 416: predicate.switch_simplify 1.52% : 0.000019s : 130: predicate.tile_eliminate 1.48% : 0.000018s : 130: predicate.transpose_eliminate 1.95% : 0.000024s : 134: predicate.tuple_list_convert_item_index_to_positive 1.74% : 0.000022s : 135: predicate.tuple_list_get_item_depend_reorder 3.30% : 0.000041s : 176: predicate.tuple_list_get_item_eliminator 2.04% : 0.000025s : 137: predicate.tuple_list_set_item_eliminator 1.84% : 0.000023s : 155: predicate.tuple_to_list_eliminator_ 1.87% : 0.000023s : 162: predicate.updatestate_pure_node_eliminater 2.86% : 0.000036s : 217: predicate.updatestate_useless_node_eliminater 1.98% : 0.000025s : 130: predicate.value_based_eliminate 0.08% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 0.33% : 0.000004s : 17: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.007335 77 56.60% : 0.004151s : 31: func_graph_cloner_run.FuncGraphClonerGraph 8.88% : 0.000651s : 9: func_graph_cloner_run.FuncGraphClonerNode 34.53% : 0.002533s : 37: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.939806 114 0.00% : 0.000106s : 1: add_recomputation 0.01% : 0.000492s : 1: auto_monad 0.00% : 0.000037s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.01% : 0.000568s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000051s : 1: convert_after_rewriter 0.00% : 0.000056s : 1: cse_after_recomputation 0.00% : 0.000022s : 1: environ_conv 0.01% : 0.000308s : 1: event_method 0.00% : 0.000017s : 1: execute 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000018s : 1: graph_reusing 21.80% : 1.077043s : 1: jit_opt_a 0.01% : 0.000321s : 1: jit_opt_after_cconv 0.01% : 0.000348s : 1: jit_opt_b 0.01% : 0.000596s : 1: loop_unroll 0.02% : 0.000949s : 1: mutable_eliminate 3.25% : 0.160673s : 52: opt.transform.jit_opt_a 0.00% : 0.000120s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000278s : 8: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000045s : 1: opt.transform.mutable_eliminate 0.00% : 0.000048s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.001856s : 4: opt.transform.opt_resolve 0.00% : 0.000076s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000658s : 1: opt_after_jit_grad 0.00% : 0.000019s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000086s : 1: py_interpret_to_execute 0.00% : 0.000028s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000083s : 1: remove_dup_value 7.26% : 0.358835s : 3: renormalize.infer 0.16% : 0.007924s : 3: renormalize.specialize 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.31% : 0.015192s : 1: rewriter_after_opt_a 0.00% : 0.000185s : 1: rewriter_before_opt_a 0.00% : 0.000207s : 1: symbol_engine_optimizer 51.72% : 2.554961s : 1: task_emit 15.33% : 0.757383s : 1: type_inference 0.00% : 0.000109s : 1: validate . [hook] pytest_runtest_teardown:test_chunk_zero_bias[KBK] tests/st/mint/test_chunk.py::test_chunk_zero_bias[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 213.40s (0:03:33) ==================