==================================================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 2 items test_select.py . [hook] pytest_runtest_teardown:test_select_zero_bias[pynative] tests/st/mint/test_select.py::test_select_zero_bias[pynative],max_mem:2.0M TotalTime = 0.992613, [30] [bootstrap]: 0.00119907 [type_inference]: 0.858292 [event_method]: 1.367e-05 [auto_monad]: 0.00020509 [graph_reusing]: 6.16998e-06 [pre_auto_parallel]: 1.207e-05 [py_interpret_to_execute]: 8.854e-05 [rewriter_before_opt_a]: 0.00017701 [expand_dump_flag]: 3.45e-06 [jit_opt_a]: 0.128247, [2] [Cycle 1]: 0.00239864, [27] [switch_simplify]: 9.835e-05 [loop_unroll]: 2.289e-05 [a_1]: 0.00047802 [with_stream_mark]: 3.207e-05 [recompute_prepare]: 1.098e-05 [updatestate_depend_eliminate]: 7.01001e-06 [updatestate_assign_eliminate]: 6.46e-06 [updatestate_loads_eliminate]: 5.22e-06 [parameter_eliminate]: 1.90001e-06 [specialize_transform]: 9.60001e-06 [updatestate_useless_node_eliminater]: 1.297e-05 [accelerated_algorithm]: 1.015e-05 [meta_shard_fg_expand]: 3.57002e-06 [get_grad_eliminate_]: 8.43001e-06 [merge_forward]: 5.96e-06 [cell_reuse_recompute_pass]: 1.33002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.756e-05 [j_node_and_user_rematch]: 1.657e-05 [meta_fg_expand]: 3.88001e-06 [replace_old_param]: 1.377e-05 [inline_without_move]: 8.52e-06 [renormalize]: 0.00124253 [add_forward_monad_depend]: 1.298e-05 [auto_monad_grad]: 2.86999e-06 [auto_monad_eliminator]: 2.601e-05 [cse]: 4.246e-05 [replace_applicator]: 2.275e-05 [Cycle 2]: 0.00058678, [27] [switch_simplify]: 9.47999e-06 [loop_unroll]: 8.16002e-06 [a_1]: 0.00018914 [with_stream_mark]: 1.691e-05 [recompute_prepare]: 8.85001e-06 [updatestate_depend_eliminate]: 3.618e-05 [updatestate_assign_eliminate]: 4.87e-06 [updatestate_loads_eliminate]: 4.74998e-06 [parameter_eliminate]: 1.69e-06 [specialize_transform]: 8.74998e-06 [updatestate_useless_node_eliminater]: 1.245e-05 [accelerated_algorithm]: 9.16002e-06 [meta_shard_fg_expand]: 2.99001e-06 [get_grad_eliminate_]: 8.72e-06 [merge_forward]: 5.44998e-06 [cell_reuse_recompute_pass]: 3.16001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.179e-05 [j_node_and_user_rematch]: 1.496e-05 [meta_fg_expand]: 3.28e-06 [replace_old_param]: 1.394e-05 [inline_without_move]: 9.64e-06 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 1.76e-06 [auto_monad_grad]: 2.15002e-06 [auto_monad_eliminator]: 1.422e-05 [cse]: 2.317e-05 [replace_applicator]: 1.024e-05 [py_interpret_to_execute_after_opt_a]: 2.047e-05 [rewriter_after_opt_a]: 0.00055866 [convert_after_rewriter]: 7.05e-05 [order_py_execute_after_rewriter]: 8.48001e-06 [mutable_eliminate]: 0.00084482 [jit_opt_b]: 8.008e-05, [1] [Cycle 1]: 6.895e-05, [2] [frontend_op_eliminate]: 2.691e-05 [inline_after_opt_a]: 2.748e-05 [cconv]: 4.212e-05 [loop_unroll]: 0.00064478 [jit_opt_after_cconv]: 0.00025506, [1] [Cycle 1]: 0.00024727, [11] [c_1]: 6.002e-05 [parameter_eliminate]: 6.56999e-06 [updatestate_depend_eliminate]: 1.454e-05 [updatestate_assign_eliminate]: 6.34999e-06 [updatestate_loads_eliminate]: 5.14e-06 [cse]: 5.069e-05 [call_graph_tuple_transform]: 2.391e-05 [tuple_list_get_item_eliminator]: 9.20999e-06 [none_parameter_eliminate]: 2.39001e-06 [renormalize]: 1.17e-06 [switch_simplify]: 8.97999e-06 [remove_dup_value]: 2.517e-05 [partial_unused_args_eliminate]: 2.57001e-06 [environ_conv]: 2.574e-05 [add_recomputation]: 0.00014154 [cse_after_recomputation]: 3.568e-05, [1] [Cycle 1]: 2.775e-05, [1] [cse]: 1.97e-05 [auto_monad_reorder]: 4.07e-05 [get_jit_bprop_graph]: 2.69001e-06 [rewriter_after_jit_bprop_graph]: 0.00017498 [opt_after_jit_grad]: 0.00079378 [symbol_engine_optimizer]: 0.00011367, [1] [Cycle 1]: 0.00010426, [6] [build]: 1.039e-05 [elim_shapecalc]: 1.238e-05 [elim_not_effective]: 2.322e-05 [opt_reshape]: 9.69999e-06 [fold_const_symbol]: 1.439e-05 [renormalize]: 1.04e-06 [validate]: 8.152e-05 Sums bootstrap : 0.001199s : 0.14% type_inference : 0.858292s : 99.06% event_method : 0.000014s : 0.00% auto_monad : 0.000205s : 0.02% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000089s : 0.01% rewriter_before_opt_a : 0.000177s : 0.02% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000108s : 0.01% jit_opt_a.loop_unroll : 0.000031s : 0.00% jit_opt_a.a_1 : 0.000667s : 0.08% jit_opt_a.with_stream_mark : 0.000049s : 0.01% jit_opt_a.recompute_prepare : 0.000020s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000043s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000018s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.00% jit_opt_a.accelerated_algorithm : 0.000019s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000007s : 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 : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000059s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000032s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000028s : 0.00% jit_opt_a.inline_without_move : 0.000018s : 0.00% jit_opt_a.renormalize : 0.001243s : 0.14% 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 : 0.000040s : 0.00% jit_opt_a.cse : 0.000066s : 0.01% jit_opt_a.replace_applicator : 0.000033s : 0.00% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000559s : 0.06% convert_after_rewriter : 0.000070s : 0.01% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000845s : 0.10% jit_opt_b.frontend_op_eliminate : 0.000027s : 0.00% jit_opt_b.inline_after_opt_a : 0.000027s : 0.00% cconv : 0.000042s : 0.00% loop_unroll : 0.000645s : 0.07% jit_opt_after_cconv.c_1 : 0.000060s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000051s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 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 : 0.000026s : 0.00% add_recomputation : 0.000142s : 0.02% cse_after_recomputation.cse : 0.000020s : 0.00% auto_monad_reorder : 0.000041s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000175s : 0.02% opt_after_jit_grad : 0.000794s : 0.09% symbol_engine_optimizer.build : 0.000010s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000023s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000082s : 0.01% Time group info: ------[substitution.] 0.000247 43 4.19% : 0.000010s : 2: substitution.depend_value_elim 1.51% : 0.000004s : 4: substitution.elim_not_effective 0.83% : 0.000002s : 4: substitution.fold_const_symbol 3.08% : 0.000008s : 5: substitution.graph_param_transform 64.32% : 0.000159s : 2: substitution.inline 2.61% : 0.000006s : 8: substitution.j_node_and_user_rematch 8.19% : 0.000020s : 8: substitution.remove_not_recompute_node 3.17% : 0.000008s : 2: substitution.replace_old_param 6.29% : 0.000016s : 3: substitution.updatestate_pure_node_eliminater 5.80% : 0.000014s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.858224 2 99.89% : 0.857311s : 1: type_inference.infer 0.11% : 0.000912s : 1: type_inference.specialize ------[replace.] 0.000033 2 100.00% : 0.000033s : 2: replace.inline ------[match.] 0.000157 2 100.00% : 0.000157s : 2: match.inline ------[predicate.] 0.000162 767 1.39% : 0.000002s : 11: predicate.accumulaten_eliminater 2.01% : 0.000003s : 5: predicate.ad_related_special_op_eliminate 0.90% : 0.000001s : 11: predicate.addn_check_dump 1.14% : 0.000002s : 11: predicate.addn_zero_filter 1.95% : 0.000003s : 11: predicate.arithmetic_simplify 1.35% : 0.000002s : 11: predicate.cast_eliminate 0.56% : 0.000001s : 5: predicate.check_bprop_eliminate 0.97% : 0.000002s : 11: predicate.compare_switch_simplify 1.46% : 0.000002s : 11: predicate.depend_value_elim 1.11% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.30% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.20% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.51% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.42% : 0.000001s : 5: predicate.elim_not_effective 0.73% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.04% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.03% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.13% : 0.000002s : 11: predicate.environ_get_depend_swap 1.30% : 0.000002s : 11: predicate.environ_get_eliminate 1.10% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.27% : 0.000000s : 5: predicate.fold_const_symbol 1.25% : 0.000002s : 10: predicate.get_grad_eliminate 0.30% : 0.000000s : 5: predicate.graph_param_transform 4.94% : 0.000008s : 23: predicate.inline 1.14% : 0.000002s : 10: predicate.inline_without_move 0.49% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.49% : 0.000002s : 10: predicate.less_batch_normalization 1.21% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.91% : 0.000003s : 16: predicate.load_eliminater 2.49% : 0.000004s : 5: predicate.loop_unroll_after_grad 2.68% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.65% : 0.000004s : 16: predicate.make_slice_get_slice_eliminator 1.02% : 0.000002s : 11: predicate.merge_addn 1.22% : 0.000002s : 11: predicate.minmaximum_grad 2.78% : 0.000004s : 5: predicate.mutable_eliminate 0.65% : 0.000001s : 5: predicate.opt_reshape 2.08% : 0.000003s : 16: predicate.partial_eliminate 1.24% : 0.000002s : 11: predicate.print_const_string_wrapper 1.74% : 0.000003s : 11: predicate.reduce_eliminate 1.38% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.83% : 0.000001s : 10: predicate.remove_not_recompute_node 1.47% : 0.000002s : 21: predicate.replace_applicator 0.74% : 0.000001s : 10: predicate.replace_old_param 0.48% : 0.000001s : 5: predicate.reset_defer_inline 1.07% : 0.000002s : 11: predicate.reshape_eliminate 1.08% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.30% : 0.000002s : 5: predicate.row_tensor_eliminate 1.26% : 0.000002s : 11: predicate.same_eliminate 0.75% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.53% : 0.000002s : 10: predicate.special_op_eliminate 1.20% : 0.000002s : 10: predicate.specialize_transform 1.41% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.11% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.69% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.49% : 0.000002s : 13: predicate.switch_defer_inline 1.54% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.82% : 0.000009s : 38: predicate.switch_simplify 1.43% : 0.000002s : 11: predicate.tile_eliminate 1.22% : 0.000002s : 11: predicate.transpose_eliminate 1.22% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.12% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.57% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.78% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.38% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.84% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.34% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.65% : 0.000003s : 11: predicate.value_based_eliminate 0.50% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.67% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000439 5 5.74% : 0.000025s : 1: func_graph_cloner_run.FuncGraphClonerGraph 94.26% : 0.000413s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.994844 72 0.01% : 0.000146s : 1: add_recomputation 0.02% : 0.000211s : 1: auto_monad 0.00% : 0.000044s : 1: auto_monad_reorder 0.12% : 0.001227s : 1: bootstrap 0.00% : 0.000045s : 1: cconv 0.01% : 0.000076s : 1: convert_after_rewriter 0.00% : 0.000039s : 1: cse_after_recomputation 0.00% : 0.000029s : 1: environ_conv 0.00% : 0.000020s : 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 12.89% : 0.128252s : 1: jit_opt_a 0.03% : 0.000259s : 1: jit_opt_after_cconv 0.01% : 0.000083s : 1: jit_opt_b 0.07% : 0.000658s : 1: loop_unroll 0.09% : 0.000862s : 1: mutable_eliminate 0.10% : 0.000995s : 26: opt.transform.jit_opt_a 0.01% : 0.000098s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000046s : 4: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000032s : 1: opt.transform.mutable_eliminate 0.00% : 0.000043s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000056s : 4: opt.transform.symbol_engine_opt 0.08% : 0.000815s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000092s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000028s : 1: remove_dup_value 0.07% : 0.000712s : 1: renormalize.infer 0.05% : 0.000519s : 1: renormalize.specialize 0.02% : 0.000180s : 1: rewriter_after_jit_bprop_graph 0.06% : 0.000567s : 1: rewriter_after_opt_a 0.02% : 0.000183s : 1: rewriter_before_opt_a 0.01% : 0.000117s : 1: symbol_engine_optimizer 86.28% : 0.858312s : 1: type_inference TotalTime = 1.09479, [30] [bootstrap]: 0.00060197 [type_inference]: 0.558088 [event_method]: 0.0002156 [auto_monad]: 0.00033575 [graph_reusing]: 1.112e-05 [pre_auto_parallel]: 3.85998e-06 [py_interpret_to_execute]: 5.233e-05 [rewriter_before_opt_a]: 0.000161 [expand_dump_flag]: 4.42e-06 [jit_opt_a]: 0.531889, [4] [Cycle 1]: 0.421914, [27] [switch_simplify]: 0.00022543 [loop_unroll]: 0.0010626 [a_1]: 0.00161364 [with_stream_mark]: 3.812e-05 [recompute_prepare]: 3.179e-05 [updatestate_depend_eliminate]: 1.293e-05 [updatestate_assign_eliminate]: 1.162e-05 [updatestate_loads_eliminate]: 1.002e-05 [parameter_eliminate]: 3.04999e-06 [specialize_transform]: 2.167e-05 [updatestate_useless_node_eliminater]: 2.574e-05 [accelerated_algorithm]: 2.025e-05 [meta_shard_fg_expand]: 7.34002e-06 [get_grad_eliminate_]: 1.991e-05 [merge_forward]: 1.173e-05 [cell_reuse_recompute_pass]: 1.42e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.99e-05 [j_node_and_user_rematch]: 3.607e-05 [meta_fg_expand]: 0.213705 [replace_old_param]: 0.0001476 [inline_without_move]: 0.00013876 [renormalize]: 0.203453 [add_forward_monad_depend]: 3.633e-05 [auto_monad_grad]: 1.334e-05 [auto_monad_eliminator]: 0.00013687 [cse]: 0.00035883 [replace_applicator]: 0.00027911 [Cycle 2]: 0.10234, [27] [switch_simplify]: 0.00011241 [loop_unroll]: 9.725e-05 [a_1]: 0.0987331 [with_stream_mark]: 4.334e-05 [recompute_prepare]: 3.812e-05 [updatestate_depend_eliminate]: 1.612e-05 [updatestate_assign_eliminate]: 1.609e-05 [updatestate_loads_eliminate]: 1.55e-05 [parameter_eliminate]: 4.98001e-06 [specialize_transform]: 2.6e-05 [updatestate_useless_node_eliminater]: 9.057e-05 [accelerated_algorithm]: 3.776e-05 [meta_shard_fg_expand]: 5.74999e-06 [get_grad_eliminate_]: 1.46e-05 [merge_forward]: 8.91002e-06 [cell_reuse_recompute_pass]: 2.18002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.328e-05 [j_node_and_user_rematch]: 2.583e-05 [meta_fg_expand]: 0.00012668 [replace_old_param]: 2.234e-05 [inline_without_move]: 1.472e-05 [renormalize]: 0.00233282 [add_forward_monad_depend]: 8.22e-06 [auto_monad_grad]: 2.91999e-06 [auto_monad_eliminator]: 3.783e-05 [cse]: 0.00016141 [replace_applicator]: 3.702e-05 [Cycle 3]: 0.00191793, [27] [switch_simplify]: 1.74e-05 [loop_unroll]: 1.643e-05 [a_1]: 0.00036175 [with_stream_mark]: 2.242e-05 [recompute_prepare]: 1.467e-05 [updatestate_depend_eliminate]: 3.694e-05 [updatestate_assign_eliminate]: 8.51002e-06 [updatestate_loads_eliminate]: 7.23999e-06 [parameter_eliminate]: 2.06003e-06 [specialize_transform]: 1.477e-05 [updatestate_useless_node_eliminater]: 1.63e-05 [accelerated_algorithm]: 1.867e-05 [meta_shard_fg_expand]: 3.61999e-06 [get_grad_eliminate_]: 1.205e-05 [merge_forward]: 7.52002e-06 [cell_reuse_recompute_pass]: 3.81999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.938e-05 [j_node_and_user_rematch]: 2.086e-05 [meta_fg_expand]: 4.72e-06 [replace_old_param]: 1.782e-05 [inline_without_move]: 1.182e-05 [renormalize]: 0.00095473 [add_forward_monad_depend]: 5.96998e-06 [auto_monad_grad]: 1.92001e-06 [auto_monad_eliminator]: 2.403e-05 [cse]: 8.965e-05 [replace_applicator]: 2.383e-05 [Cycle 4]: 0.00073318, [27] [switch_simplify]: 1.31e-05 [loop_unroll]: 1.231e-05 [a_1]: 0.00028026 [with_stream_mark]: 1.621e-05 [recompute_prepare]: 1.179e-05 [updatestate_depend_eliminate]: 7.44002e-06 [updatestate_assign_eliminate]: 6.72002e-06 [updatestate_loads_eliminate]: 6.86001e-06 [parameter_eliminate]: 1.16002e-06 [specialize_transform]: 1.348e-05 [updatestate_useless_node_eliminater]: 1.542e-05 [accelerated_algorithm]: 1.703e-05 [meta_shard_fg_expand]: 2.76e-06 [get_grad_eliminate_]: 2.606e-05 [merge_forward]: 7.97998e-06 [cell_reuse_recompute_pass]: 2.93e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.707e-05 [j_node_and_user_rematch]: 2.073e-05 [meta_fg_expand]: 4.71002e-06 [replace_old_param]: 1.625e-05 [inline_without_move]: 1.255e-05 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 2.01e-06 [auto_monad_grad]: 1.13001e-06 [auto_monad_eliminator]: 1.898e-05 [cse]: 3.999e-05 [replace_applicator]: 1.271e-05 [py_interpret_to_execute_after_opt_a]: 2.092e-05 [rewriter_after_opt_a]: 0.00023253 [convert_after_rewriter]: 1.385e-05 [order_py_execute_after_rewriter]: 9.12999e-06 [mutable_eliminate]: 0.0008487 [jit_opt_b]: 0.00010213, [1] [Cycle 1]: 9.125e-05, [2] [frontend_op_eliminate]: 3.951e-05 [inline_after_opt_a]: 3.677e-05 [cconv]: 4.223e-05 [loop_unroll]: 0.00050866 [jit_opt_after_cconv]: 0.00031327, [1] [Cycle 1]: 0.00030511, [11] [c_1]: 7.526e-05 [parameter_eliminate]: 6.79001e-06 [updatestate_depend_eliminate]: 1.409e-05 [updatestate_assign_eliminate]: 7.55e-06 [updatestate_loads_eliminate]: 6.81001e-06 [cse]: 7.021e-05 [call_graph_tuple_transform]: 3.472e-05 [tuple_list_get_item_eliminator]: 1.315e-05 [none_parameter_eliminate]: 1.89e-06 [renormalize]: 1.10001e-06 [switch_simplify]: 1.339e-05 [remove_dup_value]: 3.511e-05 [partial_unused_args_eliminate]: 2.98e-06 [environ_conv]: 1.593e-05 [add_recomputation]: 0.00010554 [cse_after_recomputation]: 5.036e-05, [1] [Cycle 1]: 4.297e-05, [1] [cse]: 3.462e-05 [auto_monad_reorder]: 3.543e-05 [get_jit_bprop_graph]: 2.79999e-06 [rewriter_after_jit_bprop_graph]: 8.55999e-06 [opt_after_jit_grad]: 0.00058826 [symbol_engine_optimizer]: 0.00013921, [1] [Cycle 1]: 0.00013207, [6] [build]: 1.949e-05 [elim_shapecalc]: 1.717e-05 [elim_not_effective]: 2.698e-05 [opt_reshape]: 1.391e-05 [fold_const_symbol]: 2.084e-05 [renormalize]: 7.2e-07 [validate]: 7.37e-05 Sums bootstrap : 0.000602s : 0.06% type_inference : 0.558088s : 51.28% event_method : 0.000216s : 0.02% auto_monad : 0.000336s : 0.03% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000052s : 0.00% rewriter_before_opt_a : 0.000161s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000368s : 0.03% jit_opt_a.loop_unroll : 0.001189s : 0.11% jit_opt_a.a_1 : 0.100989s : 9.28% jit_opt_a.with_stream_mark : 0.000120s : 0.01% jit_opt_a.recompute_prepare : 0.000096s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000073s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000043s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000040s : 0.00% jit_opt_a.parameter_eliminate : 0.000011s : 0.00% jit_opt_a.specialize_transform : 0.000076s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000148s : 0.01% jit_opt_a.accelerated_algorithm : 0.000094s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000019s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000073s : 0.01% jit_opt_a.merge_forward : 0.000036s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000010s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000130s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000103s : 0.01% jit_opt_a.meta_fg_expand : 0.213841s : 19.65% jit_opt_a.replace_old_param : 0.000204s : 0.02% jit_opt_a.inline_without_move : 0.000178s : 0.02% jit_opt_a.renormalize : 0.206741s : 19.00% jit_opt_a.add_forward_monad_depend : 0.000053s : 0.00% jit_opt_a.auto_monad_grad : 0.000019s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000218s : 0.02% jit_opt_a.cse : 0.000650s : 0.06% jit_opt_a.replace_applicator : 0.000353s : 0.03% py_interpret_to_execute_after_opt_a : 0.000021s : 0.00% rewriter_after_opt_a : 0.000233s : 0.02% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000849s : 0.08% jit_opt_b.frontend_op_eliminate : 0.000040s : 0.00% jit_opt_b.inline_after_opt_a : 0.000037s : 0.00% cconv : 0.000042s : 0.00% loop_unroll : 0.000509s : 0.05% jit_opt_after_cconv.c_1 : 0.000075s : 0.01% 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 : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000070s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000035s : 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 : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000013s : 0.00% remove_dup_value : 0.000035s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000016s : 0.00% add_recomputation : 0.000106s : 0.01% cse_after_recomputation.cse : 0.000035s : 0.00% auto_monad_reorder : 0.000035s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000588s : 0.05% symbol_engine_optimizer.build : 0.000019s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000014s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000021s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000074s : 0.01% Time group info: ------[substitution.] 0.003093 291 1.62% : 0.000050s : 12: substitution.depend_value_elim 0.12% : 0.000004s : 7: substitution.elim_not_effective 0.10% : 0.000003s : 7: substitution.fold_const_symbol 31.85% : 0.000985s : 4: substitution.getattr_setattr_resolve 0.31% : 0.000009s : 8: substitution.graph_param_transform 46.69% : 0.001444s : 28: substitution.inline 1.50% : 0.000046s : 4: substitution.inline_without_move 0.67% : 0.000021s : 35: substitution.j_node_and_user_rematch 0.75% : 0.000023s : 3: substitution.less_batch_normalization 1.02% : 0.000032s : 13: substitution.minmaximum_grad 0.62% : 0.000019s : 14: substitution.partial_eliminate 0.84% : 0.000026s : 35: substitution.remove_not_recompute_node 3.13% : 0.000097s : 16: substitution.replace_applicator 0.70% : 0.000022s : 19: substitution.replace_old_param 0.24% : 0.000007s : 2: substitution.set_cell_output_no_recompute 0.52% : 0.000016s : 3: substitution.switch_simplify 1.64% : 0.000051s : 13: substitution.tuple_list_convert_item_index_to_positive 1.13% : 0.000035s : 13: substitution.tuple_list_get_item_depend_reorder 3.55% : 0.000110s : 30: substitution.tuple_list_get_item_eliminator 0.89% : 0.000027s : 9: substitution.updatestate_pure_node_eliminater 2.11% : 0.000065s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.557940 2 99.41% : 0.554675s : 1: type_inference.infer 0.59% : 0.003265s : 1: type_inference.specialize ------[replace.] 0.000948 53 13.79% : 0.000131s : 3: replace.getattr_setattr_resolve 48.32% : 0.000458s : 28: replace.inline 4.93% : 0.000047s : 1: replace.replace_applicator 7.59% : 0.000072s : 3: replace.switch_simplify 20.46% : 0.000194s : 17: replace.tuple_list_get_item_eliminator 4.91% : 0.000047s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002425 53 37.55% : 0.000911s : 3: match.getattr_setattr_resolve 58.74% : 0.001424s : 28: match.inline 0.88% : 0.000021s : 1: match.replace_applicator 0.59% : 0.000014s : 3: match.switch_simplify 1.76% : 0.000043s : 17: match.tuple_list_get_item_eliminator 0.49% : 0.000012s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001009 5919 2.94% : 0.000030s : 99: predicate.accumulaten_eliminater 0.28% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.42% : 0.000014s : 99: predicate.addn_check_dump 1.67% : 0.000017s : 99: predicate.addn_zero_filter 2.47% : 0.000025s : 99: predicate.arithmetic_simplify 2.70% : 0.000027s : 99: predicate.cast_eliminate 0.14% : 0.000001s : 8: predicate.check_bprop_eliminate 1.39% : 0.000014s : 99: predicate.compare_switch_simplify 1.65% : 0.000017s : 99: predicate.depend_value_elim 1.32% : 0.000013s : 99: predicate.dict_get_item_const_eliminator 1.34% : 0.000014s : 99: predicate.dict_get_item_eliminator 1.57% : 0.000016s : 99: predicate.dict_set_item_eliminator 0.20% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.08% : 0.000001s : 8: predicate.elim_not_effective 0.18% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.43% : 0.000014s : 99: predicate.environ_add_const_eliminate 1.34% : 0.000014s : 99: predicate.environ_get_add_eliminate 1.36% : 0.000014s : 99: predicate.environ_get_depend_swap 1.43% : 0.000014s : 99: predicate.environ_get_eliminate 1.34% : 0.000014s : 99: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.78% : 0.000008s : 42: predicate.get_grad_eliminate 0.76% : 0.000008s : 20: predicate.getattr_setattr_resolve 0.07% : 0.000001s : 8: predicate.graph_param_transform 4.44% : 0.000045s : 160: predicate.inline 1.91% : 0.000019s : 106: predicate.inline_without_move 0.30% : 0.000003s : 42: predicate.j_node_and_user_rematch 1.03% : 0.000010s : 42: predicate.less_batch_normalization 1.78% : 0.000018s : 116: predicate.list_to_tuple_eliminator_ 1.83% : 0.000018s : 124: predicate.load_eliminater 0.38% : 0.000004s : 8: predicate.loop_unroll_after_grad 3.16% : 0.000032s : 171: predicate.loop_unroll_before_grad 1.71% : 0.000017s : 107: predicate.make_slice_get_slice_eliminator 1.33% : 0.000013s : 99: predicate.merge_addn 1.44% : 0.000015s : 99: predicate.minmaximum_grad 0.43% : 0.000004s : 8: predicate.mutable_eliminate 0.19% : 0.000002s : 8: predicate.opt_reshape 2.36% : 0.000024s : 124: predicate.partial_eliminate 1.41% : 0.000014s : 99: predicate.print_const_string_wrapper 1.90% : 0.000019s : 99: predicate.reduce_eliminate 1.86% : 0.000019s : 116: predicate.redundant_stop_gradient_eliminater 0.40% : 0.000004s : 42: predicate.remove_not_recompute_node 2.49% : 0.000025s : 236: predicate.replace_applicator 1.00% : 0.000010s : 106: predicate.replace_old_param 0.07% : 0.000001s : 8: predicate.reset_defer_inline 1.52% : 0.000015s : 99: predicate.reshape_eliminate 1.62% : 0.000016s : 99: predicate.row_tensor_add_zeros_like 0.26% : 0.000003s : 8: predicate.row_tensor_eliminate 1.58% : 0.000016s : 99: predicate.same_eliminate 0.54% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.32% : 0.000003s : 16: predicate.special_op_eliminate 0.86% : 0.000009s : 50: predicate.specialize_transform 1.81% : 0.000018s : 99: predicate.split_environ_get_set_with_tuple_value 1.39% : 0.000014s : 99: predicate.stack_unstack_eliminate 0.16% : 0.000002s : 8: predicate.switch_call_monad_eliminater 3.12% : 0.000031s : 144: predicate.switch_defer_inline 2.39% : 0.000024s : 144: predicate.switch_layer_defer_inline 5.41% : 0.000055s : 329: predicate.switch_simplify 1.42% : 0.000014s : 99: predicate.tile_eliminate 1.40% : 0.000014s : 99: predicate.transpose_eliminate 1.81% : 0.000018s : 99: predicate.tuple_list_convert_item_index_to_positive 1.60% : 0.000016s : 99: predicate.tuple_list_get_item_depend_reorder 2.96% : 0.000030s : 132: predicate.tuple_list_get_item_eliminator 1.97% : 0.000020s : 99: predicate.tuple_list_set_item_eliminator 1.80% : 0.000018s : 116: predicate.tuple_to_list_eliminator_ 1.87% : 0.000019s : 124: predicate.updatestate_pure_node_eliminater 2.78% : 0.000028s : 168: predicate.updatestate_useless_node_eliminater 1.78% : 0.000018s : 99: predicate.value_based_eliminate 0.11% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.17% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.185472 58 98.79% : 0.183229s : 22: func_graph_cloner_run.FuncGraphClonerGraph 0.22% : 0.000404s : 7: func_graph_cloner_run.FuncGraphClonerNode 0.99% : 0.001839s : 29: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.406811 104 0.01% : 0.000109s : 1: add_recomputation 0.02% : 0.000348s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 0.04% : 0.000629s : 1: bootstrap 0.00% : 0.000045s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.00% : 0.000053s : 1: cse_after_recomputation 0.00% : 0.000018s : 1: environ_conv 0.02% : 0.000227s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 37.81% : 0.531893s : 1: jit_opt_a 0.02% : 0.000317s : 1: jit_opt_after_cconv 0.01% : 0.000105s : 1: jit_opt_b 0.04% : 0.000519s : 1: loop_unroll 0.06% : 0.000864s : 1: mutable_eliminate 7.39% : 0.103909s : 52: opt.transform.jit_opt_a 0.01% : 0.000132s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000068s : 4: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000033s : 1: opt.transform.mutable_eliminate 0.00% : 0.000047s : 1: opt.transform.opt_after_jit_grad 0.08% : 0.001193s : 2: opt.transform.opt_resolve 0.01% : 0.000075s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000601s : 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% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000055s : 1: py_interpret_to_execute 0.00% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000038s : 1: remove_dup_value 14.34% : 0.201791s : 3: renormalize.infer 0.35% : 0.004908s : 3: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000239s : 1: rewriter_after_opt_a 0.01% : 0.000165s : 1: rewriter_before_opt_a 0.01% : 0.000142s : 1: symbol_engine_optimizer 39.67% : 0.558123s : 1: type_inference . [hook] pytest_runtest_teardown:test_select_zero_bias[KBK] tests/st/mint/test_select.py::test_select_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 317.21s (0:05:17) ==================