==================================================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_006/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 10 items test_chunk.py . [hook] pytest_runtest_teardown:test_chunk_special_values[inf-pynative] tests/st/mint/test_chunk.py::test_chunk_special_values[inf-pynative],max_mem:2.0M TotalTime = 7.6792, [33] [bootstrap]: 0.00068083 [type_inference]: 0.581481 [event_method]: 1.497e-05 [auto_monad]: 0.00015875 [graph_reusing]: 6.14001e-06 [pre_auto_parallel]: 1.364e-05 [py_interpret_to_execute]: 0.00010329 [rewriter_before_opt_a]: 6.061e-05 [expand_dump_flag]: 3.71999e-06 [jit_opt_a]: 0.167528, [2] [Cycle 1]: 0.00244024, [27] [switch_simplify]: 5.735e-05 [loop_unroll]: 1.834e-05 [a_1]: 0.00043774 [with_stream_mark]: 3.101e-05 [recompute_prepare]: 1.173e-05 [updatestate_depend_eliminate]: 7.04001e-06 [updatestate_assign_eliminate]: 9.56e-06 [updatestate_loads_eliminate]: 5.67999e-06 [parameter_eliminate]: 1.82999e-06 [specialize_transform]: 9.05999e-06 [updatestate_useless_node_eliminater]: 1.131e-05 [accelerated_algorithm]: 8.84e-06 [meta_shard_fg_expand]: 2.98e-06 [get_grad_eliminate_]: 9.05001e-06 [merge_forward]: 5.84999e-06 [cell_reuse_recompute_pass]: 1.10001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.259e-05 [j_node_and_user_rematch]: 1.355e-05 [meta_fg_expand]: 3.81999e-06 [replace_old_param]: 1.248e-05 [inline_without_move]: 7.63999e-06 [renormalize]: 0.00139619 [add_forward_monad_depend]: 1.494e-05 [auto_monad_grad]: 3.12002e-06 [auto_monad_eliminator]: 2.466e-05 [cse]: 6.392e-05 [replace_applicator]: 1.928e-05 [Cycle 2]: 0.00052937, [27] [switch_simplify]: 8.80999e-06 [loop_unroll]: 7.65e-06 [a_1]: 0.00016571 [with_stream_mark]: 1.563e-05 [recompute_prepare]: 7.66999e-06 [updatestate_depend_eliminate]: 5.14998e-06 [updatestate_assign_eliminate]: 4.64998e-06 [updatestate_loads_eliminate]: 8.10999e-06 [parameter_eliminate]: 1.20001e-06 [specialize_transform]: 8.49002e-06 [updatestate_useless_node_eliminater]: 1.075e-05 [accelerated_algorithm]: 7.46999e-06 [meta_shard_fg_expand]: 2.05002e-06 [get_grad_eliminate_]: 7.45998e-06 [merge_forward]: 5.35001e-06 [cell_reuse_recompute_pass]: 2.28998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.828e-05 [j_node_and_user_rematch]: 1.225e-05 [meta_fg_expand]: 2.597e-05 [replace_old_param]: 1.489e-05 [inline_without_move]: 7.85998e-06 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 1.62999e-06 [auto_monad_grad]: 1.45001e-06 [auto_monad_eliminator]: 1.252e-05 [cse]: 2.704e-05 [replace_applicator]: 8.46002e-06 [py_interpret_to_execute_after_opt_a]: 1.861e-05 [rewriter_after_opt_a]: 0.0003136 [convert_after_rewriter]: 1.405e-05 [order_py_execute_after_rewriter]: 7.95e-06 [mutable_eliminate]: 0.00075417 [jit_opt_b]: 7.291e-05, [1] [Cycle 1]: 6.382e-05, [2] [frontend_op_eliminate]: 2.537e-05 [inline_after_opt_a]: 2.443e-05 [cconv]: 3.626e-05 [loop_unroll]: 0.00050071 [jit_opt_after_cconv]: 0.00025839, [1] [Cycle 1]: 0.00025044, [11] [c_1]: 5.283e-05 [parameter_eliminate]: 5.04e-06 [updatestate_depend_eliminate]: 1.085e-05 [updatestate_assign_eliminate]: 4.89e-06 [updatestate_loads_eliminate]: 4.72e-06 [cse]: 4.088e-05 [call_graph_tuple_transform]: 2.402e-05 [tuple_list_get_item_eliminator]: 8.32e-06 [none_parameter_eliminate]: 1.59998e-06 [renormalize]: 9.00007e-07 [switch_simplify]: 1.142e-05 [remove_dup_value]: 2.359e-05 [partial_unused_args_eliminate]: 2.89999e-06 [environ_conv]: 2.818e-05 [add_recomputation]: 8.454e-05 [cse_after_recomputation]: 3.767e-05, [1] [Cycle 1]: 3.061e-05, [1] [cse]: 2.269e-05 [auto_monad_reorder]: 3.909e-05 [get_jit_bprop_graph]: 2.71999e-06 [rewriter_after_jit_bprop_graph]: 0.00015662 [opt_after_jit_grad]: 0.00063682 [symbol_engine_optimizer]: 0.00011369, [1] [Cycle 1]: 0.00010559, [6] [build]: 1.709e-05 [elim_shapecalc]: 1.341e-05 [elim_not_effective]: 1.825e-05 [opt_reshape]: 8.62e-06 [fold_const_symbol]: 1.364e-05 [renormalize]: 9.70002e-07 [validate]: 0.00011915 [backend_pass]: 1.07e-06 [task_emit]: 6.92551 [execute]: 1.121e-05 Sums bootstrap : 0.000681s : 0.01% type_inference : 0.581481s : 7.74% event_method : 0.000015s : 0.00% auto_monad : 0.000159s : 0.00% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000014s : 0.00% py_interpret_to_execute : 0.000103s : 0.00% rewriter_before_opt_a : 0.000061s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000066s : 0.00% jit_opt_a.loop_unroll : 0.000026s : 0.00% jit_opt_a.a_1 : 0.000603s : 0.01% jit_opt_a.with_stream_mark : 0.000047s : 0.00% jit_opt_a.recompute_prepare : 0.000019s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000014s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000018s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000022s : 0.00% jit_opt_a.accelerated_algorithm : 0.000016s : 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 : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000041s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.00% jit_opt_a.meta_fg_expand : 0.000030s : 0.00% jit_opt_a.replace_old_param : 0.000027s : 0.00% jit_opt_a.inline_without_move : 0.000015s : 0.00% jit_opt_a.renormalize : 0.001396s : 0.02% jit_opt_a.add_forward_monad_depend : 0.000017s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000037s : 0.00% jit_opt_a.cse : 0.000091s : 0.00% jit_opt_a.replace_applicator : 0.000028s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000314s : 0.00% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000754s : 0.01% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.00% jit_opt_b.inline_after_opt_a : 0.000024s : 0.00% cconv : 0.000036s : 0.00% loop_unroll : 0.000501s : 0.01% jit_opt_after_cconv.c_1 : 0.000053s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 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 : 0.000041s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 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 : 0.000011s : 0.00% remove_dup_value : 0.000024s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000028s : 0.00% add_recomputation : 0.000085s : 0.00% cse_after_recomputation.cse : 0.000023s : 0.00% auto_monad_reorder : 0.000039s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000157s : 0.00% opt_after_jit_grad : 0.000637s : 0.01% symbol_engine_optimizer.build : 0.000017s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000018s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000119s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 6.925513s : 92.17% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000221 43 4.17% : 0.000009s : 2: substitution.depend_value_elim 1.26% : 0.000003s : 4: substitution.elim_not_effective 1.00% : 0.000002s : 4: substitution.fold_const_symbol 3.47% : 0.000008s : 5: substitution.graph_param_transform 71.17% : 0.000157s : 2: substitution.inline 1.93% : 0.000004s : 8: substitution.j_node_and_user_rematch 3.16% : 0.000007s : 8: substitution.remove_not_recompute_node 2.87% : 0.000006s : 2: substitution.replace_old_param 5.78% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 5.19% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.581398 2 99.81% : 0.580289s : 1: type_inference.infer 0.19% : 0.001109s : 1: type_inference.specialize ------[replace.] 0.000029 2 100.00% : 0.000029s : 2: replace.inline ------[match.] 0.000156 2 100.00% : 0.000156s : 2: match.inline ------[predicate.] 0.000144 767 1.20% : 0.000002s : 11: predicate.accumulaten_eliminater 1.96% : 0.000003s : 5: predicate.ad_related_special_op_eliminate 1.13% : 0.000002s : 11: predicate.addn_check_dump 1.15% : 0.000002s : 11: predicate.addn_zero_filter 2.00% : 0.000003s : 11: predicate.arithmetic_simplify 1.40% : 0.000002s : 11: predicate.cast_eliminate 1.03% : 0.000001s : 5: predicate.check_bprop_eliminate 0.99% : 0.000001s : 11: predicate.compare_switch_simplify 1.19% : 0.000002s : 11: predicate.depend_value_elim 1.01% : 0.000001s : 11: predicate.dict_get_item_const_eliminator 1.56% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.12% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.65% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.51% : 0.000001s : 5: predicate.elim_not_effective 0.90% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.09% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.04% : 0.000001s : 11: predicate.environ_get_add_eliminate 1.15% : 0.000002s : 11: predicate.environ_get_depend_swap 1.21% : 0.000002s : 11: predicate.environ_get_eliminate 1.02% : 0.000001s : 11: predicate.environ_get_set_eliminate 0.30% : 0.000000s : 5: predicate.fold_const_symbol 1.36% : 0.000002s : 10: predicate.get_grad_eliminate 0.44% : 0.000001s : 5: predicate.graph_param_transform 4.86% : 0.000007s : 23: predicate.inline 1.22% : 0.000002s : 10: predicate.inline_without_move 0.51% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.38% : 0.000002s : 10: predicate.less_batch_normalization 1.26% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.82% : 0.000003s : 16: predicate.load_eliminater 1.91% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.40% : 0.000003s : 20: predicate.loop_unroll_before_grad 1.92% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.16% : 0.000002s : 11: predicate.merge_addn 1.07% : 0.000002s : 11: predicate.minmaximum_grad 2.50% : 0.000004s : 5: predicate.mutable_eliminate 0.74% : 0.000001s : 5: predicate.opt_reshape 2.13% : 0.000003s : 16: predicate.partial_eliminate 1.10% : 0.000002s : 11: predicate.print_const_string_wrapper 1.77% : 0.000003s : 11: predicate.reduce_eliminate 1.24% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.99% : 0.000001s : 10: predicate.remove_not_recompute_node 1.67% : 0.000002s : 21: predicate.replace_applicator 0.92% : 0.000001s : 10: predicate.replace_old_param 0.56% : 0.000001s : 5: predicate.reset_defer_inline 1.17% : 0.000002s : 11: predicate.reshape_eliminate 1.14% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.90% : 0.000001s : 5: predicate.row_tensor_eliminate 1.26% : 0.000002s : 11: predicate.same_eliminate 0.65% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.35% : 0.000002s : 10: predicate.special_op_eliminate 1.24% : 0.000002s : 10: predicate.specialize_transform 1.43% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.13% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.76% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.61% : 0.000002s : 13: predicate.switch_defer_inline 1.58% : 0.000002s : 13: predicate.switch_layer_defer_inline 6.42% : 0.000009s : 38: predicate.switch_simplify 1.24% : 0.000002s : 11: predicate.tile_eliminate 1.22% : 0.000002s : 11: predicate.transpose_eliminate 1.31% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.19% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.64% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.41% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.08% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.87% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.81% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.58% : 0.000002s : 11: predicate.value_based_eliminate 0.53% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.97% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000770 6 19.38% : 0.000149s : 2: func_graph_cloner_run.FuncGraphClonerGraph 80.62% : 0.000621s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 7.681575 76 0.00% : 0.000088s : 1: add_recomputation 0.00% : 0.000165s : 1: auto_monad 0.00% : 0.000043s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.01% : 0.000707s : 1: bootstrap 0.00% : 0.000039s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.00% : 0.000040s : 1: cse_after_recomputation 0.00% : 0.000031s : 1: environ_conv 0.00% : 0.000020s : 1: event_method 0.00% : 0.000017s : 1: execute 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 2.18% : 0.167531s : 1: jit_opt_a 0.00% : 0.000262s : 1: jit_opt_after_cconv 0.00% : 0.000076s : 1: jit_opt_b 0.01% : 0.000512s : 1: loop_unroll 0.01% : 0.000766s : 1: mutable_eliminate 0.01% : 0.000879s : 26: opt.transform.jit_opt_a 0.00% : 0.000092s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000043s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000021s : 1: opt.transform.mutable_eliminate 0.00% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000050s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000652s : 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% : 0.000016s : 1: pre_auto_parallel 0.00% : 0.000107s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000026s : 1: remove_dup_value 0.01% : 0.000693s : 1: renormalize.infer 0.01% : 0.000693s : 1: renormalize.specialize 0.00% : 0.000160s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000318s : 1: rewriter_after_opt_a 0.00% : 0.000068s : 1: rewriter_before_opt_a 0.00% : 0.000117s : 1: symbol_engine_optimizer 90.16% : 6.925546s : 1: task_emit 7.57% : 0.581511s : 1: type_inference 0.00% : 0.000151s : 1: validate TotalTime = 4.40855, [33] [bootstrap]: 0.00076908 [type_inference]: 0.738155 [event_method]: 0.00044388 [auto_monad]: 0.00041329 [graph_reusing]: 1.265e-05 [pre_auto_parallel]: 4.33999e-06 [py_interpret_to_execute]: 5.692e-05 [rewriter_before_opt_a]: 0.00018071 [expand_dump_flag]: 4.32e-06 [jit_opt_a]: 1.03081, [4] [Cycle 1]: 1.01351, [27] [switch_simplify]: 0.00185873 [loop_unroll]: 0.118588 [a_1]: 0.00205734 [with_stream_mark]: 5.065e-05 [recompute_prepare]: 4.329e-05 [updatestate_depend_eliminate]: 5.391e-05 [updatestate_assign_eliminate]: 1.121e-05 [updatestate_loads_eliminate]: 1.04e-05 [parameter_eliminate]: 4.53001e-06 [specialize_transform]: 2.317e-05 [updatestate_useless_node_eliminater]: 2.559e-05 [accelerated_algorithm]: 2.054e-05 [meta_shard_fg_expand]: 7.36999e-06 [get_grad_eliminate_]: 1.929e-05 [merge_forward]: 1.312e-05 [cell_reuse_recompute_pass]: 1.63002e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.292e-05 [j_node_and_user_rematch]: 3.432e-05 [meta_fg_expand]: 0.31239 [replace_old_param]: 0.00016222 [inline_without_move]: 0.00015178 [renormalize]: 0.576388 [add_forward_monad_depend]: 3.563e-05 [auto_monad_grad]: 1.931e-05 [auto_monad_eliminator]: 0.00015624 [cse]: 0.00046291 [replace_applicator]: 0.00041352 [Cycle 2]: 0.00881387, [27] [switch_simplify]: 0.0001174 [loop_unroll]: 0.00020639 [a_1]: 0.00498911 [with_stream_mark]: 5.145e-05 [recompute_prepare]: 4.009e-05 [updatestate_depend_eliminate]: 1.78e-05 [updatestate_assign_eliminate]: 1.81e-05 [updatestate_loads_eliminate]: 1.733e-05 [parameter_eliminate]: 6.28e-06 [specialize_transform]: 2.609e-05 [updatestate_useless_node_eliminater]: 9.225e-05 [accelerated_algorithm]: 4.159e-05 [meta_shard_fg_expand]: 7.46001e-06 [get_grad_eliminate_]: 1.684e-05 [merge_forward]: 1.147e-05 [cell_reuse_recompute_pass]: 1.34998e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.961e-05 [j_node_and_user_rematch]: 2.897e-05 [meta_fg_expand]: 0.00016191 [replace_old_param]: 2.714e-05 [inline_without_move]: 1.731e-05 [renormalize]: 0.00235774 [add_forward_monad_depend]: 9.92999e-06 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 3.618e-05 [cse]: 0.00016652 [replace_applicator]: 3.315e-05 [Cycle 3]: 0.00290015, [27] [switch_simplify]: 1.751e-05 [loop_unroll]: 1.529e-05 [a_1]: 0.00046664 [with_stream_mark]: 2.907e-05 [recompute_prepare]: 1.888e-05 [updatestate_depend_eliminate]: 4.929e-05 [updatestate_assign_eliminate]: 8.28999e-06 [updatestate_loads_eliminate]: 6.86001e-06 [parameter_eliminate]: 2.21e-06 [specialize_transform]: 1.504e-05 [updatestate_useless_node_eliminater]: 1.698e-05 [accelerated_algorithm]: 1.829e-05 [meta_shard_fg_expand]: 3.42997e-06 [get_grad_eliminate_]: 1.198e-05 [merge_forward]: 7.73999e-06 [cell_reuse_recompute_pass]: 3.33e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.884e-05 [j_node_and_user_rematch]: 2.146e-05 [meta_fg_expand]: 5.27999e-06 [replace_old_param]: 1.707e-05 [inline_without_move]: 1.192e-05 [renormalize]: 0.00112575 [add_forward_monad_depend]: 7.14001e-06 [auto_monad_grad]: 2.58e-06 [auto_monad_eliminator]: 2.663e-05 [cse]: 0.00012595 [replace_applicator]: 2.408e-05 [Cycle 4]: 0.00077082, [27] [switch_simplify]: 1.309e-05 [loop_unroll]: 1.22e-05 [a_1]: 0.00031846 [with_stream_mark]: 1.699e-05 [recompute_prepare]: 1.382e-05 [updatestate_depend_eliminate]: 8.2e-06 [updatestate_assign_eliminate]: 7.4e-06 [updatestate_loads_eliminate]: 6.51e-06 [parameter_eliminate]: 1.42999e-06 [specialize_transform]: 1.302e-05 [updatestate_useless_node_eliminater]: 1.563e-05 [accelerated_algorithm]: 1.707e-05 [meta_shard_fg_expand]: 2.96999e-06 [get_grad_eliminate_]: 1.236e-05 [merge_forward]: 6.76e-06 [cell_reuse_recompute_pass]: 1.95001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.654e-05 [j_node_and_user_rematch]: 2.086e-05 [meta_fg_expand]: 4.87998e-06 [replace_old_param]: 1.637e-05 [inline_without_move]: 1.186e-05 [renormalize]: 1.10012e-07 [add_forward_monad_depend]: 1.78002e-06 [auto_monad_grad]: 1.62999e-06 [auto_monad_eliminator]: 1.92e-05 [cse]: 4.12e-05 [replace_applicator]: 1.59e-05 [py_interpret_to_execute_after_opt_a]: 2.179e-05 [rewriter_after_opt_a]: 0.00034189 [convert_after_rewriter]: 1.645e-05 [order_py_execute_after_rewriter]: 9.20999e-06 [mutable_eliminate]: 0.00081308 [jit_opt_b]: 0.00025108, [2] [Cycle 1]: 0.00017969, [2] [frontend_op_eliminate]: 0.00012895 [inline_after_opt_a]: 3.168e-05 [Cycle 2]: 5.831e-05, [2] [frontend_op_eliminate]: 2.437e-05 [inline_after_opt_a]: 2.454e-05 [cconv]: 3.862e-05 [loop_unroll]: 0.00050458 [jit_opt_after_cconv]: 0.00026858, [1] [Cycle 1]: 0.0002609, [11] [c_1]: 5.708e-05 [parameter_eliminate]: 4.51002e-06 [updatestate_depend_eliminate]: 1.401e-05 [updatestate_assign_eliminate]: 6.02999e-06 [updatestate_loads_eliminate]: 6.48e-06 [cse]: 6.085e-05 [call_graph_tuple_transform]: 3.011e-05 [tuple_list_get_item_eliminator]: 1.089e-05 [none_parameter_eliminate]: 1.69e-06 [renormalize]: 9.00007e-07 [switch_simplify]: 1.155e-05 [remove_dup_value]: 4.977e-05 [partial_unused_args_eliminate]: 2.43998e-06 [environ_conv]: 1.3e-05 [add_recomputation]: 9.023e-05 [cse_after_recomputation]: 4.461e-05, [1] [Cycle 1]: 3.759e-05, [1] [cse]: 3.041e-05 [auto_monad_reorder]: 3.26e-05 [get_jit_bprop_graph]: 2.74001e-06 [rewriter_after_jit_bprop_graph]: 7.55998e-06 [opt_after_jit_grad]: 0.00055658 [symbol_engine_optimizer]: 0.00012502, [1] [Cycle 1]: 0.00011697, [6] [build]: 1.741e-05 [elim_shapecalc]: 1.542e-05 [elim_not_effective]: 2.376e-05 [opt_reshape]: 1.073e-05 [fold_const_symbol]: 1.853e-05 [renormalize]: 6.39993e-07 [validate]: 6.206e-05 [backend_pass]: 1.14e-06 [task_emit]: 2.62197 [execute]: 1.021e-05 Sums bootstrap : 0.000769s : 0.02% type_inference : 0.738155s : 16.82% event_method : 0.000444s : 0.01% auto_monad : 0.000413s : 0.01% graph_reusing : 0.000013s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000057s : 0.00% rewriter_before_opt_a : 0.000181s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.002007s : 0.05% jit_opt_a.loop_unroll : 0.118822s : 2.71% jit_opt_a.a_1 : 0.007832s : 0.18% jit_opt_a.with_stream_mark : 0.000148s : 0.00% jit_opt_a.recompute_prepare : 0.000116s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000129s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000045s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000041s : 0.00% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000077s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000150s : 0.00% jit_opt_a.accelerated_algorithm : 0.000097s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000021s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000060s : 0.00% jit_opt_a.merge_forward : 0.000039s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000008s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000138s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000106s : 0.00% jit_opt_a.meta_fg_expand : 0.312562s : 7.12% jit_opt_a.replace_old_param : 0.000223s : 0.01% jit_opt_a.inline_without_move : 0.000193s : 0.00% jit_opt_a.renormalize : 0.579872s : 13.21% jit_opt_a.add_forward_monad_depend : 0.000054s : 0.00% jit_opt_a.auto_monad_grad : 0.000026s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000238s : 0.01% jit_opt_a.cse : 0.000797s : 0.02% jit_opt_a.replace_applicator : 0.000487s : 0.01% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.000342s : 0.01% convert_after_rewriter : 0.000016s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000813s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000153s : 0.00% jit_opt_b.inline_after_opt_a : 0.000056s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000505s : 0.01% jit_opt_after_cconv.c_1 : 0.000057s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000061s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000011s : 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 : 0.000050s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000013s : 0.00% add_recomputation : 0.000090s : 0.00% cse_after_recomputation.cse : 0.000030s : 0.00% auto_monad_reorder : 0.000033s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000557s : 0.01% symbol_engine_optimizer.build : 0.000017s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000024s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000062s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 2.621974s : 59.73% execute : 0.000010s : 0.00% Time group info: ------[substitution.] 0.152356 361 0.01% : 0.000019s : 2: substitution.cast_eliminate 0.03% : 0.000049s : 15: substitution.depend_value_elim 0.00% : 0.000004s : 6: substitution.elim_not_effective 0.00% : 0.000003s : 6: substitution.fold_const_symbol 98.28% : 0.149731s : 9: substitution.getattr_setattr_resolve 0.01% : 0.000009s : 7: substitution.graph_param_transform 1.15% : 0.001750s : 32: substitution.inline 0.03% : 0.000047s : 5: substitution.inline_without_move 0.01% : 0.000020s : 40: substitution.j_node_and_user_rematch 0.02% : 0.000023s : 3: substitution.less_batch_normalization 0.03% : 0.000038s : 20: substitution.minmaximum_grad 0.01% : 0.000016s : 14: substitution.partial_eliminate 0.02% : 0.000030s : 40: substitution.remove_not_recompute_node 0.07% : 0.000113s : 25: substitution.replace_applicator 0.02% : 0.000025s : 20: substitution.replace_old_param 0.01% : 0.000009s : 2: substitution.set_cell_output_no_recompute 0.02% : 0.000024s : 3: substitution.switch_simplify 0.05% : 0.000073s : 20: substitution.tuple_list_convert_item_index_to_positive 0.05% : 0.000069s : 21: substitution.tuple_list_get_item_depend_reorder 0.09% : 0.000137s : 39: substitution.tuple_list_get_item_eliminator 0.02% : 0.000031s : 2: substitution.tuple_list_set_item_eliminator 0.02% : 0.000027s : 11: substitution.updatestate_pure_node_eliminater 0.04% : 0.000061s : 18: substitution.updatestate_useless_node_eliminater 0.03% : 0.000047s : 1: substitution.zero_like_fill_zero ------[type_inference.] 0.738005 2 99.55% : 0.734681s : 1: type_inference.infer 0.45% : 0.003325s : 1: type_inference.specialize ------[replace.] 0.002786 71 0.55% : 0.000015s : 2: replace.cast_eliminate 6.46% : 0.000180s : 7: replace.getattr_setattr_resolve 17.09% : 0.000476s : 32: replace.inline 3.48% : 0.000097s : 4: replace.replace_applicator 58.34% : 0.001625s : 3: replace.switch_simplify 0.45% : 0.000013s : 1: replace.tuple_list_get_item_depend_reorder 9.30% : 0.000259s : 18: replace.tuple_list_get_item_eliminator 1.45% : 0.000040s : 2: replace.tuple_list_set_item_eliminator 1.69% : 0.000047s : 1: replace.updatestate_useless_node_eliminater 1.19% : 0.000033s : 1: replace.zero_like_fill_zero ------[match.] 0.151564 71 0.01% : 0.000017s : 2: match.cast_eliminate 98.71% : 0.149612s : 7: match.getattr_setattr_resolve 1.14% : 0.001728s : 32: match.inline 0.02% : 0.000037s : 4: match.replace_applicator 0.01% : 0.000022s : 3: match.switch_simplify 0.01% : 0.000017s : 1: match.tuple_list_get_item_depend_reorder 0.03% : 0.000044s : 18: match.tuple_list_get_item_eliminator 0.02% : 0.000028s : 2: match.tuple_list_set_item_eliminator 0.01% : 0.000012s : 1: match.updatestate_useless_node_eliminater 0.03% : 0.000046s : 1: match.zero_like_fill_zero ------[predicate.] 0.001194 7225 1.54% : 0.000018s : 120: predicate.accumulaten_eliminater 0.24% : 0.000003s : 7: predicate.ad_related_special_op_eliminate 1.35% : 0.000016s : 120: predicate.addn_check_dump 1.52% : 0.000018s : 120: predicate.addn_zero_filter 1.97% : 0.000023s : 120: predicate.arithmetic_simplify 1.73% : 0.000021s : 122: predicate.cast_eliminate 0.23% : 0.000003s : 15: predicate.check_bprop_eliminate 1.36% : 0.000016s : 120: predicate.compare_switch_simplify 1.55% : 0.000019s : 120: predicate.depend_value_elim 1.52% : 0.000018s : 122: predicate.dict_get_item_const_eliminator 1.48% : 0.000018s : 122: predicate.dict_get_item_eliminator 1.53% : 0.000018s : 122: predicate.dict_set_item_eliminator 0.17% : 0.000002s : 7: predicate.dumpgradient_eliminate 0.08% : 0.000001s : 7: predicate.elim_not_effective 0.16% : 0.000002s : 7: predicate.elim_shapecalc_of_broadcastargs 1.53% : 0.000018s : 122: predicate.environ_add_const_eliminate 1.42% : 0.000017s : 122: predicate.environ_get_add_eliminate 1.44% : 0.000017s : 122: predicate.environ_get_depend_swap 1.47% : 0.000018s : 122: predicate.environ_get_eliminate 1.46% : 0.000017s : 122: predicate.environ_get_set_eliminate 0.05% : 0.000001s : 7: predicate.fold_const_symbol 0.69% : 0.000008s : 47: predicate.get_grad_eliminate 1.54% : 0.000018s : 51: predicate.getattr_setattr_resolve 0.05% : 0.000001s : 7: predicate.graph_param_transform 4.14% : 0.000049s : 196: predicate.inline 1.90% : 0.000023s : 130: predicate.inline_without_move 0.28% : 0.000003s : 47: predicate.j_node_and_user_rematch 0.95% : 0.000011s : 47: predicate.less_batch_normalization 1.77% : 0.000021s : 143: predicate.list_to_tuple_eliminator_ 1.90% : 0.000023s : 150: predicate.load_eliminater 0.28% : 0.000003s : 7: predicate.loop_unroll_after_grad 4.53% : 0.000054s : 208: predicate.loop_unroll_before_grad 1.63% : 0.000020s : 130: predicate.make_slice_get_slice_eliminator 1.38% : 0.000016s : 120: predicate.merge_addn 1.51% : 0.000018s : 120: predicate.minmaximum_grad 0.35% : 0.000004s : 9: predicate.mutable_eliminate 0.11% : 0.000001s : 7: predicate.opt_reshape 2.16% : 0.000026s : 150: predicate.partial_eliminate 1.41% : 0.000017s : 120: predicate.print_const_string_wrapper 1.83% : 0.000022s : 120: predicate.reduce_eliminate 1.82% : 0.000022s : 143: predicate.redundant_stop_gradient_eliminater 0.37% : 0.000004s : 47: predicate.remove_not_recompute_node 2.55% : 0.000030s : 300: predicate.replace_applicator 1.03% : 0.000012s : 130: predicate.replace_old_param 0.13% : 0.000002s : 14: predicate.reset_defer_inline 1.49% : 0.000018s : 120: predicate.reshape_eliminate 1.48% : 0.000018s : 120: predicate.row_tensor_add_zeros_like 0.26% : 0.000003s : 15: predicate.row_tensor_eliminate 1.46% : 0.000017s : 120: predicate.same_eliminate 0.46% : 0.000006s : 60: predicate.set_cell_output_no_recompute 0.29% : 0.000004s : 22: predicate.special_op_eliminate 0.83% : 0.000010s : 55: predicate.specialize_transform 1.62% : 0.000019s : 120: predicate.split_environ_get_set_with_tuple_value 1.40% : 0.000017s : 120: predicate.stack_unstack_eliminate 0.10% : 0.000001s : 7: predicate.switch_call_monad_eliminater 3.51% : 0.000042s : 175: predicate.switch_defer_inline 2.39% : 0.000028s : 175: predicate.switch_layer_defer_inline 6.02% : 0.000072s : 396: predicate.switch_simplify 1.58% : 0.000019s : 120: predicate.tile_eliminate 1.46% : 0.000017s : 120: predicate.transpose_eliminate 1.90% : 0.000023s : 122: predicate.tuple_list_convert_item_index_to_positive 1.81% : 0.000022s : 123: predicate.tuple_list_get_item_depend_reorder 3.20% : 0.000038s : 164: predicate.tuple_list_get_item_eliminator 2.00% : 0.000024s : 125: predicate.tuple_list_set_item_eliminator 1.74% : 0.000021s : 143: predicate.tuple_to_list_eliminator_ 1.86% : 0.000022s : 150: predicate.updatestate_pure_node_eliminater 2.76% : 0.000033s : 199: predicate.updatestate_useless_node_eliminater 1.88% : 0.000022s : 120: predicate.value_based_eliminate 0.09% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 0.32% : 0.000004s : 16: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.006503 75 60.38% : 0.003927s : 31: func_graph_cloner_run.FuncGraphClonerGraph 6.66% : 0.000433s : 7: func_graph_cloner_run.FuncGraphClonerNode 32.96% : 0.002144s : 37: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 5.269038 114 0.00% : 0.000093s : 1: add_recomputation 0.01% : 0.000426s : 1: auto_monad 0.00% : 0.000035s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.02% : 0.000791s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000021s : 1: convert_after_rewriter 0.00% : 0.000047s : 1: cse_after_recomputation 0.00% : 0.000015s : 1: environ_conv 0.01% : 0.000470s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000017s : 1: graph_reusing 19.56% : 1.030819s : 1: jit_opt_a 0.01% : 0.000272s : 1: jit_opt_after_cconv 0.00% : 0.000254s : 1: jit_opt_b 0.01% : 0.000515s : 1: loop_unroll 0.02% : 0.000827s : 1: mutable_eliminate 2.47% : 0.130196s : 52: opt.transform.jit_opt_a 0.00% : 0.000106s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000198s : 8: opt.transform.jit_opt_b 0.00% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000029s : 1: opt.transform.mutable_eliminate 0.00% : 0.000040s : 1: opt.transform.opt_after_jit_grad 2.85% : 0.150065s : 4: opt.transform.opt_resolve 0.00% : 0.000064s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000568s : 1: opt_after_jit_grad 0.00% : 0.000012s : 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% : 0.000060s : 1: py_interpret_to_execute 0.00% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000053s : 1: remove_dup_value 10.88% : 0.573407s : 3: renormalize.infer 0.12% : 0.006426s : 3: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000348s : 1: rewriter_after_opt_a 0.00% : 0.000185s : 1: rewriter_before_opt_a 0.00% : 0.000128s : 1: symbol_engine_optimizer 49.76% : 2.621993s : 1: task_emit 14.24% : 0.750319s : 1: type_inference 0.00% : 0.000102s : 1: validate . [hook] pytest_runtest_teardown:test_chunk_special_values[inf-KBK] tests/st/mint/test_chunk.py::test_chunk_special_values[inf-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[nan-pynative] tests/st/mint/test_chunk.py::test_chunk_special_values[nan-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[nan-KBK] tests/st/mint/test_chunk.py::test_chunk_special_values[nan-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[zero-pynative] tests/st/mint/test_chunk.py::test_chunk_special_values[zero-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[zero-KBK] tests/st/mint/test_chunk.py::test_chunk_special_values[zero-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[large-pynative] tests/st/mint/test_chunk.py::test_chunk_special_values[large-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[large-KBK] tests/st/mint/test_chunk.py::test_chunk_special_values[large-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[small-pynative] tests/st/mint/test_chunk.py::test_chunk_special_values[small-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_chunk_special_values[small-KBK] tests/st/mint/test_chunk.py::test_chunk_special_values[small-KBK],max_mem:4.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================= 10 passed, 25 warnings in 223.60s (0:03:43) ==================