==================================================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_008/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_select.py . [hook] pytest_runtest_teardown:test_select_non_contiguous[pynative] tests/st/mint/test_select.py::test_select_non_contiguous[pynative],max_mem:2.0M TotalTime = 0.830328, [30] [bootstrap]: 0.00103579 [type_inference]: 0.702508 [event_method]: 1.264e-05 [auto_monad]: 0.00014594 [graph_reusing]: 6.19001e-06 [pre_auto_parallel]: 1.212e-05 [py_interpret_to_execute]: 0.00020599 [rewriter_before_opt_a]: 6.885e-05 [expand_dump_flag]: 3.38999e-06 [jit_opt_a]: 0.123129, [2] [Cycle 1]: 0.00202789, [27] [switch_simplify]: 6.974e-05 [loop_unroll]: 1.957e-05 [a_1]: 0.0004502 [with_stream_mark]: 3.141e-05 [recompute_prepare]: 9.20001e-06 [updatestate_depend_eliminate]: 6.96001e-06 [updatestate_assign_eliminate]: 1.055e-05 [updatestate_loads_eliminate]: 4.99998e-06 [parameter_eliminate]: 1.89999e-06 [specialize_transform]: 8.72998e-06 [updatestate_useless_node_eliminater]: 1.099e-05 [accelerated_algorithm]: 9.02e-06 [meta_shard_fg_expand]: 2.70002e-06 [get_grad_eliminate_]: 8.00999e-06 [merge_forward]: 5.25999e-06 [cell_reuse_recompute_pass]: 1.07e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.996e-05 [j_node_and_user_rematch]: 1.359e-05 [meta_fg_expand]: 4.13999e-06 [replace_old_param]: 1.256e-05 [inline_without_move]: 7.82e-06 [renormalize]: 0.00099216 [add_forward_monad_depend]: 1.215e-05 [auto_monad_grad]: 2.68e-06 [auto_monad_eliminator]: 1.987e-05 [cse]: 4.939e-05 [replace_applicator]: 1.525e-05 [Cycle 2]: 0.00047339, [27] [switch_simplify]: 8.60999e-06 [loop_unroll]: 8.15e-06 [a_1]: 0.00016728 [with_stream_mark]: 9.94001e-06 [recompute_prepare]: 8.44002e-06 [updatestate_depend_eliminate]: 4.97e-06 [updatestate_assign_eliminate]: 4.34002e-06 [updatestate_loads_eliminate]: 3.82998e-06 [parameter_eliminate]: 1.07e-06 [specialize_transform]: 9.85002e-06 [updatestate_useless_node_eliminater]: 1.039e-05 [accelerated_algorithm]: 7.48999e-06 [meta_shard_fg_expand]: 1.76e-06 [get_grad_eliminate_]: 7.84002e-06 [merge_forward]: 4.2e-06 [cell_reuse_recompute_pass]: 1.30999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.698e-05 [j_node_and_user_rematch]: 1.21e-05 [meta_fg_expand]: 2.75997e-06 [replace_old_param]: 9.60001e-06 [inline_without_move]: 7.90998e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.44e-06 [auto_monad_grad]: 8.70001e-07 [auto_monad_eliminator]: 9.04e-06 [cse]: 1.834e-05 [replace_applicator]: 8.52e-06 [py_interpret_to_execute_after_opt_a]: 1.516e-05 [rewriter_after_opt_a]: 0.00043221 [convert_after_rewriter]: 1.311e-05 [order_py_execute_after_rewriter]: 7.28999e-06 [mutable_eliminate]: 0.00070987 [jit_opt_b]: 6.722e-05, [1] [Cycle 1]: 6.02e-05, [2] [frontend_op_eliminate]: 2.465e-05 [inline_after_opt_a]: 2.292e-05 [cconv]: 2.787e-05 [loop_unroll]: 0.00042694 [jit_opt_after_cconv]: 0.00019816, [1] [Cycle 1]: 0.0001912, [11] [c_1]: 4.68e-05 [parameter_eliminate]: 3.26001e-06 [updatestate_depend_eliminate]: 8.50001e-06 [updatestate_assign_eliminate]: 4.67e-06 [updatestate_loads_eliminate]: 4.05e-06 [cse]: 2.768e-05 [call_graph_tuple_transform]: 2.206e-05 [tuple_list_get_item_eliminator]: 8.26002e-06 [none_parameter_eliminate]: 1.54e-06 [renormalize]: 3.30008e-07 [switch_simplify]: 8.43001e-06 [remove_dup_value]: 2.004e-05 [partial_unused_args_eliminate]: 2.82002e-06 [environ_conv]: 1.961e-05 [add_recomputation]: 7.459e-05 [cse_after_recomputation]: 2.738e-05, [1] [Cycle 1]: 2.105e-05, [1] [cse]: 1.49e-05 [auto_monad_reorder]: 3.345e-05 [get_jit_bprop_graph]: 2.34999e-06 [rewriter_after_jit_bprop_graph]: 0.00011985 [opt_after_jit_grad]: 0.00048747 [symbol_engine_optimizer]: 0.00010192, [1] [Cycle 1]: 9.504e-05, [6] [build]: 5.53002e-06 [elim_shapecalc]: 1.238e-05 [elim_not_effective]: 1.944e-05 [opt_reshape]: 9.42999e-06 [fold_const_symbol]: 1.561e-05 [renormalize]: 6.39993e-07 [validate]: 7.125e-05 Sums bootstrap : 0.001036s : 0.15% type_inference : 0.702508s : 99.10% event_method : 0.000013s : 0.00% auto_monad : 0.000146s : 0.02% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000206s : 0.03% rewriter_before_opt_a : 0.000069s : 0.01% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000078s : 0.01% jit_opt_a.loop_unroll : 0.000028s : 0.00% jit_opt_a.a_1 : 0.000617s : 0.09% jit_opt_a.with_stream_mark : 0.000041s : 0.01% jit_opt_a.recompute_prepare : 0.000018s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000019s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000021s : 0.00% jit_opt_a.accelerated_algorithm : 0.000017s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000016s : 0.00% jit_opt_a.merge_forward : 0.000009s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000002s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000022s : 0.00% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.000992s : 0.14% jit_opt_a.add_forward_monad_depend : 0.000014s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000029s : 0.00% jit_opt_a.cse : 0.000068s : 0.01% jit_opt_a.replace_applicator : 0.000024s : 0.00% py_interpret_to_execute_after_opt_a : 0.000015s : 0.00% rewriter_after_opt_a : 0.000432s : 0.06% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000710s : 0.10% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.00% jit_opt_b.inline_after_opt_a : 0.000023s : 0.00% cconv : 0.000028s : 0.00% loop_unroll : 0.000427s : 0.06% jit_opt_after_cconv.c_1 : 0.000047s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000028s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000022s : 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 : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000008s : 0.00% remove_dup_value : 0.000020s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000020s : 0.00% add_recomputation : 0.000075s : 0.01% cse_after_recomputation.cse : 0.000015s : 0.00% auto_monad_reorder : 0.000033s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000120s : 0.02% opt_after_jit_grad : 0.000487s : 0.07% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000071s : 0.01% Time group info: ------[substitution.] 0.000213 43 4.37% : 0.000009s : 2: substitution.depend_value_elim 1.24% : 0.000003s : 4: substitution.elim_not_effective 1.04% : 0.000002s : 4: substitution.fold_const_symbol 2.99% : 0.000006s : 5: substitution.graph_param_transform 73.10% : 0.000156s : 2: substitution.inline 2.13% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.74% : 0.000008s : 8: substitution.remove_not_recompute_node 2.40% : 0.000005s : 2: substitution.replace_old_param 4.45% : 0.000009s : 3: substitution.updatestate_pure_node_eliminater 4.55% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.702427 2 99.88% : 0.701563s : 1: type_inference.infer 0.12% : 0.000864s : 1: type_inference.specialize ------[replace.] 0.000031 2 100.00% : 0.000031s : 2: replace.inline ------[match.] 0.000154 2 100.00% : 0.000154s : 2: match.inline ------[predicate.] 0.000145 767 1.24% : 0.000002s : 11: predicate.accumulaten_eliminater 1.36% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.49% : 0.000002s : 11: predicate.addn_check_dump 1.26% : 0.000002s : 11: predicate.addn_zero_filter 2.07% : 0.000003s : 11: predicate.arithmetic_simplify 1.32% : 0.000002s : 11: predicate.cast_eliminate 0.61% : 0.000001s : 5: predicate.check_bprop_eliminate 1.20% : 0.000002s : 11: predicate.compare_switch_simplify 1.49% : 0.000002s : 11: predicate.depend_value_elim 1.19% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.13% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.13% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.08% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.66% : 0.000001s : 5: predicate.elim_not_effective 0.86% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.19% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.13% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.16% : 0.000002s : 11: predicate.environ_get_depend_swap 1.53% : 0.000002s : 11: predicate.environ_get_eliminate 1.16% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.34% : 0.000000s : 5: predicate.fold_const_symbol 1.26% : 0.000002s : 10: predicate.get_grad_eliminate 0.31% : 0.000000s : 5: predicate.graph_param_transform 5.13% : 0.000007s : 23: predicate.inline 1.25% : 0.000002s : 10: predicate.inline_without_move 0.51% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.58% : 0.000002s : 10: predicate.less_batch_normalization 1.14% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.85% : 0.000003s : 16: predicate.load_eliminater 1.32% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.30% : 0.000003s : 20: predicate.loop_unroll_before_grad 2.02% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.12% : 0.000002s : 11: predicate.merge_addn 1.42% : 0.000002s : 11: predicate.minmaximum_grad 1.69% : 0.000002s : 5: predicate.mutable_eliminate 0.98% : 0.000001s : 5: predicate.opt_reshape 2.04% : 0.000003s : 16: predicate.partial_eliminate 1.24% : 0.000002s : 11: predicate.print_const_string_wrapper 1.68% : 0.000002s : 11: predicate.reduce_eliminate 1.24% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 1.16% : 0.000002s : 10: predicate.remove_not_recompute_node 1.58% : 0.000002s : 21: predicate.replace_applicator 0.84% : 0.000001s : 10: predicate.replace_old_param 0.41% : 0.000001s : 5: predicate.reset_defer_inline 1.47% : 0.000002s : 11: predicate.reshape_eliminate 1.30% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.87% : 0.000001s : 5: predicate.row_tensor_eliminate 1.24% : 0.000002s : 11: predicate.same_eliminate 0.72% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.20% : 0.000002s : 10: predicate.special_op_eliminate 1.36% : 0.000002s : 10: predicate.specialize_transform 1.55% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.18% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.59% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.89% : 0.000003s : 13: predicate.switch_defer_inline 1.71% : 0.000002s : 13: predicate.switch_layer_defer_inline 6.01% : 0.000009s : 38: predicate.switch_simplify 1.27% : 0.000002s : 11: predicate.tile_eliminate 1.16% : 0.000002s : 11: predicate.transpose_eliminate 1.70% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.29% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.54% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.81% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.31% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.66% : 0.000002s : 16: predicate.updatestate_pure_node_eliminater 3.54% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.46% : 0.000002s : 11: predicate.value_based_eliminate 0.56% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.95% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000300 5 6.71% : 0.000020s : 1: func_graph_cloner_run.FuncGraphClonerGraph 93.29% : 0.000280s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.832167 72 0.01% : 0.000078s : 1: add_recomputation 0.02% : 0.000151s : 1: auto_monad 0.00% : 0.000036s : 1: auto_monad_reorder 0.13% : 0.001058s : 1: bootstrap 0.00% : 0.000030s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.00% : 0.000030s : 1: cse_after_recomputation 0.00% : 0.000022s : 1: environ_conv 0.00% : 0.000018s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 14.80% : 0.123133s : 1: jit_opt_a 0.02% : 0.000201s : 1: jit_opt_after_cconv 0.01% : 0.000070s : 1: jit_opt_b 0.05% : 0.000434s : 1: loop_unroll 0.09% : 0.000718s : 1: mutable_eliminate 0.11% : 0.000892s : 26: opt.transform.jit_opt_a 0.01% : 0.000081s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000041s : 4: opt.transform.jit_opt_b 0.00% : 0.000015s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.00% : 0.000032s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000053s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000495s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.03% : 0.000211s : 1: py_interpret_to_execute 0.00% : 0.000018s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000023s : 1: remove_dup_value 0.08% : 0.000633s : 1: renormalize.infer 0.04% : 0.000350s : 1: renormalize.specialize 0.01% : 0.000123s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000436s : 1: rewriter_after_opt_a 0.01% : 0.000073s : 1: rewriter_before_opt_a 0.01% : 0.000105s : 1: symbol_engine_optimizer 84.42% : 0.702523s : 1: type_inference TotalTime = 1.23006, [30] [bootstrap]: 0.00052175 [type_inference]: 0.64559 [event_method]: 0.00017987 [auto_monad]: 0.00027408 [graph_reusing]: 9.37999e-06 [pre_auto_parallel]: 3.5e-06 [py_interpret_to_execute]: 5.125e-05 [rewriter_before_opt_a]: 0.0001429 [expand_dump_flag]: 4.41002e-06 [jit_opt_a]: 0.57967, [4] [Cycle 1]: 0.566508, [27] [switch_simplify]: 0.00019327 [loop_unroll]: 5.611e-05 [a_1]: 0.00134105 [with_stream_mark]: 3.456e-05 [recompute_prepare]: 2.587e-05 [updatestate_depend_eliminate]: 1.238e-05 [updatestate_assign_eliminate]: 1.034e-05 [updatestate_loads_eliminate]: 1.005e-05 [parameter_eliminate]: 3.31001e-06 [specialize_transform]: 1.879e-05 [updatestate_useless_node_eliminater]: 2.284e-05 [accelerated_algorithm]: 1.767e-05 [meta_shard_fg_expand]: 5.36002e-06 [get_grad_eliminate_]: 1.791e-05 [merge_forward]: 1.17e-05 [cell_reuse_recompute_pass]: 1.29e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.84e-05 [j_node_and_user_rematch]: 4.424e-05 [meta_fg_expand]: 0.3272 [replace_old_param]: 0.00011779 [inline_without_move]: 0.00011849 [renormalize]: 0.236216 [add_forward_monad_depend]: 2.651e-05 [auto_monad_grad]: 1.001e-05 [auto_monad_eliminator]: 0.00011942 [cse]: 0.00034288 [replace_applicator]: 0.00021045 [Cycle 2]: 0.00646251, [27] [switch_simplify]: 9.047e-05 [loop_unroll]: 8.565e-05 [a_1]: 0.0033997 [with_stream_mark]: 0.00013607 [recompute_prepare]: 3.703e-05 [updatestate_depend_eliminate]: 1.727e-05 [updatestate_assign_eliminate]: 1.563e-05 [updatestate_loads_eliminate]: 1.455e-05 [parameter_eliminate]: 5.03002e-06 [specialize_transform]: 2.294e-05 [updatestate_useless_node_eliminater]: 9.351e-05 [accelerated_algorithm]: 3.581e-05 [meta_shard_fg_expand]: 5.87999e-06 [get_grad_eliminate_]: 1.402e-05 [merge_forward]: 9.77001e-06 [cell_reuse_recompute_pass]: 1.37e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.375e-05 [j_node_and_user_rematch]: 2.369e-05 [meta_fg_expand]: 0.00010269 [replace_old_param]: 1.967e-05 [inline_without_move]: 1.381e-05 [renormalize]: 0.00167985 [add_forward_monad_depend]: 6.18002e-06 [auto_monad_grad]: 2.36e-06 [auto_monad_eliminator]: 2.809e-05 [cse]: 0.00013169 [replace_applicator]: 2.386e-05 [Cycle 3]: 0.00160484, [27] [switch_simplify]: 1.642e-05 [loop_unroll]: 1.537e-05 [a_1]: 0.00033417 [with_stream_mark]: 1.697e-05 [recompute_prepare]: 1.386e-05 [updatestate_depend_eliminate]: 3.214e-05 [updatestate_assign_eliminate]: 7.19001e-06 [updatestate_loads_eliminate]: 6.79001e-06 [parameter_eliminate]: 1.44e-06 [specialize_transform]: 1.254e-05 [updatestate_useless_node_eliminater]: 1.458e-05 [accelerated_algorithm]: 1.747e-05 [meta_shard_fg_expand]: 2.46e-06 [get_grad_eliminate_]: 1.232e-05 [merge_forward]: 6.69999e-06 [cell_reuse_recompute_pass]: 2.17999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.575e-05 [j_node_and_user_rematch]: 2.041e-05 [meta_fg_expand]: 4.22e-06 [replace_old_param]: 1.464e-05 [inline_without_move]: 1.163e-05 [renormalize]: 0.00074366 [add_forward_monad_depend]: 4.27e-06 [auto_monad_grad]: 1.40999e-06 [auto_monad_eliminator]: 1.977e-05 [cse]: 7.11e-05 [replace_applicator]: 2.036e-05 [Cycle 4]: 0.00068249, [27] [switch_simplify]: 1.33e-05 [loop_unroll]: 1.24e-05 [a_1]: 0.00027572 [with_stream_mark]: 1.394e-05 [recompute_prepare]: 1.236e-05 [updatestate_depend_eliminate]: 6.84999e-06 [updatestate_assign_eliminate]: 6.53e-06 [updatestate_loads_eliminate]: 6.45002e-06 [parameter_eliminate]: 8.80013e-07 [specialize_transform]: 1.207e-05 [updatestate_useless_node_eliminater]: 1.407e-05 [accelerated_algorithm]: 1.48e-05 [meta_shard_fg_expand]: 2.54001e-06 [get_grad_eliminate_]: 1.105e-05 [merge_forward]: 6.17999e-06 [cell_reuse_recompute_pass]: 1.59e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.526e-05 [j_node_and_user_rematch]: 2.04e-05 [meta_fg_expand]: 4.82e-06 [replace_old_param]: 1.416e-05 [inline_without_move]: 1.397e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.52999e-06 [auto_monad_grad]: 9.60019e-07 [auto_monad_eliminator]: 1.691e-05 [cse]: 3.468e-05 [replace_applicator]: 1.324e-05 [py_interpret_to_execute_after_opt_a]: 1.661e-05 [rewriter_after_opt_a]: 0.00022025 [convert_after_rewriter]: 1.388e-05 [order_py_execute_after_rewriter]: 9.74999e-06 [mutable_eliminate]: 0.00078068 [jit_opt_b]: 8.896e-05, [1] [Cycle 1]: 8.098e-05, [2] [frontend_op_eliminate]: 3.443e-05 [inline_after_opt_a]: 3.327e-05 [cconv]: 2.915e-05 [loop_unroll]: 0.00045191 [jit_opt_after_cconv]: 0.00024844, [1] [Cycle 1]: 0.00024146, [11] [c_1]: 5.914e-05 [parameter_eliminate]: 2.40002e-06 [updatestate_depend_eliminate]: 1.033e-05 [updatestate_assign_eliminate]: 6.41998e-06 [updatestate_loads_eliminate]: 5.97999e-06 [cse]: 4.312e-05 [call_graph_tuple_transform]: 3.078e-05 [tuple_list_get_item_eliminator]: 1.257e-05 [none_parameter_eliminate]: 1.77001e-06 [renormalize]: 4.89992e-07 [switch_simplify]: 1.214e-05 [remove_dup_value]: 3.063e-05 [partial_unused_args_eliminate]: 2.17999e-06 [environ_conv]: 1.193e-05 [add_recomputation]: 8.981e-05 [cse_after_recomputation]: 4.506e-05, [1] [Cycle 1]: 3.861e-05, [1] [cse]: 3.134e-05 [auto_monad_reorder]: 3.339e-05 [get_jit_bprop_graph]: 2.06e-06 [rewriter_after_jit_bprop_graph]: 5.06997e-06 [opt_after_jit_grad]: 0.00051328 [symbol_engine_optimizer]: 0.00012192, [1] [Cycle 1]: 0.00011478, [6] [build]: 1.163e-05 [elim_shapecalc]: 1.595e-05 [elim_not_effective]: 2.455e-05 [opt_reshape]: 1.273e-05 [fold_const_symbol]: 1.923e-05 [renormalize]: 3.30008e-07 [validate]: 0.00066465 Sums bootstrap : 0.000522s : 0.04% type_inference : 0.645590s : 52.73% event_method : 0.000180s : 0.01% auto_monad : 0.000274s : 0.02% graph_reusing : 0.000009s : 0.00% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000051s : 0.00% rewriter_before_opt_a : 0.000143s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000313s : 0.03% jit_opt_a.loop_unroll : 0.000170s : 0.01% jit_opt_a.a_1 : 0.005351s : 0.44% jit_opt_a.with_stream_mark : 0.000202s : 0.02% jit_opt_a.recompute_prepare : 0.000089s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000069s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000040s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000038s : 0.00% jit_opt_a.parameter_eliminate : 0.000011s : 0.00% jit_opt_a.specialize_transform : 0.000066s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000145s : 0.01% jit_opt_a.accelerated_algorithm : 0.000086s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000016s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000055s : 0.00% jit_opt_a.merge_forward : 0.000034s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000123s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000109s : 0.01% jit_opt_a.meta_fg_expand : 0.327312s : 26.73% jit_opt_a.replace_old_param : 0.000166s : 0.01% jit_opt_a.inline_without_move : 0.000158s : 0.01% jit_opt_a.renormalize : 0.238639s : 19.49% jit_opt_a.add_forward_monad_depend : 0.000038s : 0.00% jit_opt_a.auto_monad_grad : 0.000015s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000184s : 0.02% jit_opt_a.cse : 0.000580s : 0.05% jit_opt_a.replace_applicator : 0.000268s : 0.02% py_interpret_to_execute_after_opt_a : 0.000017s : 0.00% rewriter_after_opt_a : 0.000220s : 0.02% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000781s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000034s : 0.00% jit_opt_b.inline_after_opt_a : 0.000033s : 0.00% cconv : 0.000029s : 0.00% loop_unroll : 0.000452s : 0.04% jit_opt_after_cconv.c_1 : 0.000059s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 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 : 0.000043s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000031s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000013s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000012s : 0.00% remove_dup_value : 0.000031s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000012s : 0.00% add_recomputation : 0.000090s : 0.01% cse_after_recomputation.cse : 0.000031s : 0.00% auto_monad_reorder : 0.000033s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000513s : 0.04% symbol_engine_optimizer.build : 0.000012s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000016s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000665s : 0.05% Time group info: ------[substitution.] 0.003301 291 1.07% : 0.000035s : 12: substitution.depend_value_elim 0.12% : 0.000004s : 7: substitution.elim_not_effective 0.09% : 0.000003s : 7: substitution.fold_const_symbol 52.94% : 0.001748s : 4: substitution.getattr_setattr_resolve 0.26% : 0.000008s : 8: substitution.graph_param_transform 31.59% : 0.001043s : 28: substitution.inline 1.07% : 0.000035s : 4: substitution.inline_without_move 0.84% : 0.000028s : 35: substitution.j_node_and_user_rematch 0.65% : 0.000021s : 3: substitution.less_batch_normalization 0.54% : 0.000018s : 13: substitution.minmaximum_grad 0.80% : 0.000026s : 14: substitution.partial_eliminate 0.78% : 0.000026s : 35: substitution.remove_not_recompute_node 1.64% : 0.000054s : 16: substitution.replace_applicator 0.55% : 0.000018s : 19: substitution.replace_old_param 0.20% : 0.000007s : 2: substitution.set_cell_output_no_recompute 0.43% : 0.000014s : 3: substitution.switch_simplify 1.13% : 0.000037s : 13: substitution.tuple_list_convert_item_index_to_positive 0.84% : 0.000028s : 13: substitution.tuple_list_get_item_depend_reorder 2.40% : 0.000079s : 30: substitution.tuple_list_get_item_eliminator 0.55% : 0.000018s : 9: substitution.updatestate_pure_node_eliminater 1.51% : 0.000050s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.645490 2 99.61% : 0.642949s : 1: type_inference.infer 0.39% : 0.002541s : 1: type_inference.specialize ------[replace.] 0.000692 53 9.40% : 0.000065s : 3: replace.getattr_setattr_resolve 47.58% : 0.000329s : 28: replace.inline 4.99% : 0.000034s : 1: replace.replace_applicator 8.19% : 0.000057s : 3: replace.switch_simplify 23.05% : 0.000159s : 17: replace.tuple_list_get_item_eliminator 6.80% : 0.000047s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002786 53 60.74% : 0.001692s : 3: match.getattr_setattr_resolve 36.83% : 0.001026s : 28: match.inline 0.37% : 0.000010s : 1: match.replace_applicator 0.45% : 0.000012s : 3: match.switch_simplify 1.16% : 0.000032s : 17: match.tuple_list_get_item_eliminator 0.45% : 0.000013s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000902 5919 1.58% : 0.000014s : 99: predicate.accumulaten_eliminater 0.31% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.46% : 0.000013s : 99: predicate.addn_check_dump 1.61% : 0.000015s : 99: predicate.addn_zero_filter 1.99% : 0.000018s : 99: predicate.arithmetic_simplify 1.60% : 0.000014s : 99: predicate.cast_eliminate 0.15% : 0.000001s : 8: predicate.check_bprop_eliminate 1.51% : 0.000014s : 99: predicate.compare_switch_simplify 1.78% : 0.000016s : 99: predicate.depend_value_elim 1.43% : 0.000013s : 99: predicate.dict_get_item_const_eliminator 1.50% : 0.000013s : 99: predicate.dict_get_item_eliminator 1.49% : 0.000013s : 99: predicate.dict_set_item_eliminator 0.22% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.09% : 0.000001s : 8: predicate.elim_not_effective 0.20% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.55% : 0.000014s : 99: predicate.environ_add_const_eliminate 1.44% : 0.000013s : 99: predicate.environ_get_add_eliminate 1.42% : 0.000013s : 99: predicate.environ_get_depend_swap 1.58% : 0.000014s : 99: predicate.environ_get_eliminate 1.51% : 0.000014s : 99: predicate.environ_get_set_eliminate 0.08% : 0.000001s : 8: predicate.fold_const_symbol 0.82% : 0.000007s : 42: predicate.get_grad_eliminate 0.74% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.07% : 0.000001s : 8: predicate.graph_param_transform 4.08% : 0.000037s : 160: predicate.inline 1.93% : 0.000017s : 106: predicate.inline_without_move 0.38% : 0.000003s : 42: predicate.j_node_and_user_rematch 0.99% : 0.000009s : 42: predicate.less_batch_normalization 1.81% : 0.000016s : 116: predicate.list_to_tuple_eliminator_ 1.92% : 0.000017s : 124: predicate.load_eliminater 0.30% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.80% : 0.000025s : 171: predicate.loop_unroll_before_grad 1.78% : 0.000016s : 107: predicate.make_slice_get_slice_eliminator 1.46% : 0.000013s : 99: predicate.merge_addn 1.50% : 0.000014s : 99: predicate.minmaximum_grad 0.34% : 0.000003s : 8: predicate.mutable_eliminate 0.17% : 0.000002s : 8: predicate.opt_reshape 2.41% : 0.000022s : 124: predicate.partial_eliminate 1.53% : 0.000014s : 99: predicate.print_const_string_wrapper 1.91% : 0.000017s : 99: predicate.reduce_eliminate 1.93% : 0.000017s : 116: predicate.redundant_stop_gradient_eliminater 0.46% : 0.000004s : 42: predicate.remove_not_recompute_node 2.51% : 0.000023s : 236: predicate.replace_applicator 0.98% : 0.000009s : 106: predicate.replace_old_param 0.09% : 0.000001s : 8: predicate.reset_defer_inline 1.67% : 0.000015s : 99: predicate.reshape_eliminate 1.62% : 0.000015s : 99: predicate.row_tensor_add_zeros_like 0.19% : 0.000002s : 8: predicate.row_tensor_eliminate 1.66% : 0.000015s : 99: predicate.same_eliminate 0.51% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.35% : 0.000003s : 16: predicate.special_op_eliminate 0.91% : 0.000008s : 50: predicate.specialize_transform 1.71% : 0.000015s : 99: predicate.split_environ_get_set_with_tuple_value 1.49% : 0.000013s : 99: predicate.stack_unstack_eliminate 0.14% : 0.000001s : 8: predicate.switch_call_monad_eliminater 2.94% : 0.000026s : 144: predicate.switch_defer_inline 2.59% : 0.000023s : 144: predicate.switch_layer_defer_inline 5.79% : 0.000052s : 329: predicate.switch_simplify 1.56% : 0.000014s : 99: predicate.tile_eliminate 1.48% : 0.000013s : 99: predicate.transpose_eliminate 1.92% : 0.000017s : 99: predicate.tuple_list_convert_item_index_to_positive 1.79% : 0.000016s : 99: predicate.tuple_list_get_item_depend_reorder 3.10% : 0.000028s : 132: predicate.tuple_list_get_item_eliminator 1.96% : 0.000018s : 99: predicate.tuple_list_set_item_eliminator 1.81% : 0.000016s : 116: predicate.tuple_to_list_eliminator_ 1.96% : 0.000018s : 124: predicate.updatestate_pure_node_eliminater 3.13% : 0.000028s : 168: predicate.updatestate_useless_node_eliminater 1.94% : 0.000018s : 99: predicate.value_based_eliminate 0.15% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.20% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004414 58 58.48% : 0.002581s : 22: func_graph_cloner_run.FuncGraphClonerGraph 6.57% : 0.000290s : 7: func_graph_cloner_run.FuncGraphClonerNode 34.95% : 0.001543s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.477149 104 0.01% : 0.000093s : 1: add_recomputation 0.02% : 0.000282s : 1: auto_monad 0.00% : 0.000036s : 1: auto_monad_reorder 0.04% : 0.000550s : 1: bootstrap 0.00% : 0.000032s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.00% : 0.000047s : 1: cse_after_recomputation 0.00% : 0.000014s : 1: environ_conv 0.01% : 0.000188s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000013s : 1: graph_reusing 39.24% : 0.579674s : 1: jit_opt_a 0.02% : 0.000252s : 1: jit_opt_after_cconv 0.01% : 0.000092s : 1: jit_opt_b 0.03% : 0.000459s : 1: loop_unroll 0.05% : 0.000789s : 1: mutable_eliminate 0.48% : 0.007024s : 52: opt.transform.jit_opt_a 0.01% : 0.000111s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000061s : 4: opt.transform.jit_opt_b 0.00% : 0.000021s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000022s : 1: opt.transform.mutable_eliminate 0.00% : 0.000047s : 1: opt.transform.opt_after_jit_grad 0.13% : 0.001873s : 2: opt.transform.opt_resolve 0.00% : 0.000069s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000523s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000055s : 1: py_interpret_to_execute 0.00% : 0.000020s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000033s : 1: remove_dup_value 15.86% : 0.234218s : 3: renormalize.infer 0.30% : 0.004386s : 3: renormalize.specialize 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000225s : 1: rewriter_after_opt_a 0.01% : 0.000146s : 1: rewriter_before_opt_a 0.01% : 0.000125s : 1: symbol_engine_optimizer 43.71% : 0.645611s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_non_contiguous[KBK] tests/st/mint/test_select.py::test_select_non_contiguous[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 315.89s (0:05:15) ==================