==================================================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/ops, 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 3 items test_ops_square.py . [hook] pytest_runtest_teardown:test_square_normal[pynative] tests/st/ops/test_ops_square.py::test_square_normal[pynative],max_mem:2.0M TotalTime = 0.315112, [30] [bootstrap]: 0.00068559 [type_inference]: 0.0385393 [event_method]: 1.732e-05 [auto_monad]: 0.00011866 [graph_reusing]: 6.59999e-06 [pre_auto_parallel]: 1.149e-05 [py_interpret_to_execute]: 2.702e-05 [rewriter_before_opt_a]: 6.822e-05 [expand_dump_flag]: 3.27997e-06 [jit_opt_a]: 0.273025, [2] [Cycle 1]: 0.00155821, [27] [switch_simplify]: 5.494e-05 [loop_unroll]: 2.138e-05 [a_1]: 0.00041339 [with_stream_mark]: 2.732e-05 [recompute_prepare]: 7.05e-06 [updatestate_depend_eliminate]: 4.04002e-06 [updatestate_assign_eliminate]: 3.29001e-06 [updatestate_loads_eliminate]: 2.71e-06 [parameter_eliminate]: 1.94999e-06 [specialize_transform]: 5.59e-06 [updatestate_useless_node_eliminater]: 4.90999e-06 [accelerated_algorithm]: 8.57998e-06 [meta_shard_fg_expand]: 2.26998e-06 [get_grad_eliminate_]: 5.65001e-06 [merge_forward]: 3.93999e-06 [cell_reuse_recompute_pass]: 1.04998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.844e-05 [j_node_and_user_rematch]: 9.46e-06 [meta_fg_expand]: 2.18002e-06 [replace_old_param]: 9.13002e-06 [inline_without_move]: 5.14e-06 [renormalize]: 0.00066915 [add_forward_monad_depend]: 1.006e-05 [auto_monad_grad]: 3.56001e-06 [auto_monad_eliminator]: 1.402e-05 [cse]: 3.31e-05 [replace_applicator]: 1.303e-05 [Cycle 2]: 0.00032117, [27] [switch_simplify]: 5.84e-06 [loop_unroll]: 4.97e-06 [a_1]: 8.852e-05 [with_stream_mark]: 9.17001e-06 [recompute_prepare]: 4.90999e-06 [updatestate_depend_eliminate]: 3.01001e-06 [updatestate_assign_eliminate]: 2.06e-06 [updatestate_loads_eliminate]: 1.90001e-06 [parameter_eliminate]: 1.00999e-06 [specialize_transform]: 4.82e-06 [updatestate_useless_node_eliminater]: 4.69002e-06 [accelerated_algorithm]: 5.60001e-06 [meta_shard_fg_expand]: 1.10999e-06 [get_grad_eliminate_]: 4.60001e-06 [merge_forward]: 2.54001e-06 [cell_reuse_recompute_pass]: 1.15999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.295e-05 [j_node_and_user_rematch]: 8.60001e-06 [meta_fg_expand]: 2.02999e-06 [replace_old_param]: 8.23999e-06 [inline_without_move]: 4.83001e-06 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 1.31998e-06 [auto_monad_grad]: 1.29e-06 [auto_monad_eliminator]: 5.14e-06 [cse]: 1.255e-05 [replace_applicator]: 4.89e-06 [py_interpret_to_execute_after_opt_a]: 1.192e-05 [rewriter_after_opt_a]: 6.693e-05 [convert_after_rewriter]: 2.085e-05 [order_py_execute_after_rewriter]: 5.52001e-06 [mutable_eliminate]: 0.00061602 [jit_opt_b]: 4.996e-05, [1] [Cycle 1]: 4.189e-05, [2] [frontend_op_eliminate]: 1.556e-05 [inline_after_opt_a]: 1.479e-05 [cconv]: 3.013e-05 [loop_unroll]: 0.00041938 [jit_opt_after_cconv]: 0.00015139, [1] [Cycle 1]: 0.0001446, [11] [c_1]: 2.13e-05 [parameter_eliminate]: 3.3e-06 [updatestate_depend_eliminate]: 7.64002e-06 [updatestate_assign_eliminate]: 2.71999e-06 [updatestate_loads_eliminate]: 2.26e-06 [cse]: 2.435e-05 [call_graph_tuple_transform]: 1.996e-05 [tuple_list_get_item_eliminator]: 5.14e-06 [none_parameter_eliminate]: 1.57999e-06 [renormalize]: 4.99975e-07 [switch_simplify]: 5.64e-06 [remove_dup_value]: 1.418e-05 [partial_unused_args_eliminate]: 2.22999e-06 [environ_conv]: 1.759e-05 [add_recomputation]: 5.976e-05 [cse_after_recomputation]: 2.284e-05, [1] [Cycle 1]: 1.697e-05, [1] [cse]: 1.129e-05 [auto_monad_reorder]: 2.535e-05 [get_jit_bprop_graph]: 2.12999e-06 [rewriter_after_jit_bprop_graph]: 0.00015247 [opt_after_jit_grad]: 0.000471 [symbol_engine_optimizer]: 7.19e-05, [1] [Cycle 1]: 6.608e-05, [6] [build]: 4.74e-06 [elim_shapecalc]: 7.31001e-06 [elim_not_effective]: 1.273e-05 [opt_reshape]: 5.43002e-06 [fold_const_symbol]: 8.17998e-06 [renormalize]: 4.69998e-07 [validate]: 6.029e-05 Sums bootstrap : 0.000686s : 1.59% type_inference : 0.038539s : 89.23% event_method : 0.000017s : 0.04% auto_monad : 0.000119s : 0.27% graph_reusing : 0.000007s : 0.02% pre_auto_parallel : 0.000011s : 0.03% py_interpret_to_execute : 0.000027s : 0.06% rewriter_before_opt_a : 0.000068s : 0.16% expand_dump_flag : 0.000003s : 0.01% jit_opt_a.switch_simplify : 0.000061s : 0.14% jit_opt_a.loop_unroll : 0.000026s : 0.06% jit_opt_a.a_1 : 0.000502s : 1.16% jit_opt_a.with_stream_mark : 0.000036s : 0.08% jit_opt_a.recompute_prepare : 0.000012s : 0.03% jit_opt_a.updatestate_depend_eliminate : 0.000007s : 0.02% jit_opt_a.updatestate_assign_eliminate : 0.000005s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000005s : 0.01% jit_opt_a.parameter_eliminate : 0.000003s : 0.01% jit_opt_a.specialize_transform : 0.000010s : 0.02% jit_opt_a.updatestate_useless_node_eliminater : 0.000010s : 0.02% jit_opt_a.accelerated_algorithm : 0.000014s : 0.03% jit_opt_a.meta_shard_fg_expand : 0.000003s : 0.01% jit_opt_a.get_grad_eliminate_ : 0.000010s : 0.02% jit_opt_a.merge_forward : 0.000006s : 0.02% jit_opt_a.cell_reuse_recompute_pass : 0.000002s : 0.01% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000031s : 0.07% jit_opt_a.j_node_and_user_rematch : 0.000018s : 0.04% jit_opt_a.meta_fg_expand : 0.000004s : 0.01% jit_opt_a.replace_old_param : 0.000017s : 0.04% jit_opt_a.inline_without_move : 0.000010s : 0.02% jit_opt_a.renormalize : 0.000669s : 1.55% jit_opt_a.add_forward_monad_depend : 0.000011s : 0.03% jit_opt_a.auto_monad_grad : 0.000005s : 0.01% jit_opt_a.auto_monad_eliminator : 0.000019s : 0.04% jit_opt_a.cse : 0.000046s : 0.11% jit_opt_a.replace_applicator : 0.000018s : 0.04% py_interpret_to_execute_after_opt_a : 0.000012s : 0.03% rewriter_after_opt_a : 0.000067s : 0.15% convert_after_rewriter : 0.000021s : 0.05% order_py_execute_after_rewriter : 0.000006s : 0.01% mutable_eliminate : 0.000616s : 1.43% jit_opt_b.frontend_op_eliminate : 0.000016s : 0.04% jit_opt_b.inline_after_opt_a : 0.000015s : 0.03% cconv : 0.000030s : 0.07% loop_unroll : 0.000419s : 0.97% jit_opt_after_cconv.c_1 : 0.000021s : 0.05% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 0.01% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.02% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.01% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000002s : 0.01% jit_opt_after_cconv.cse : 0.000024s : 0.06% jit_opt_after_cconv.call_graph_tuple_transform : 0.000020s : 0.05% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000005s : 0.01% 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 : 0.000006s : 0.01% remove_dup_value : 0.000014s : 0.03% partial_unused_args_eliminate : 0.000002s : 0.01% environ_conv : 0.000018s : 0.04% add_recomputation : 0.000060s : 0.14% cse_after_recomputation.cse : 0.000011s : 0.03% auto_monad_reorder : 0.000025s : 0.06% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000152s : 0.35% opt_after_jit_grad : 0.000471s : 1.09% symbol_engine_optimizer.build : 0.000005s : 0.01% symbol_engine_optimizer.elim_shapecalc : 0.000007s : 0.02% symbol_engine_optimizer.elim_not_effective : 0.000013s : 0.03% symbol_engine_optimizer.opt_reshape : 0.000005s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000008s : 0.02% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000060s : 0.14% Time group info: ------[substitution.] 0.000161 21 1.31% : 0.000002s : 2: substitution.elim_not_effective 0.76% : 0.000001s : 2: substitution.fold_const_symbol 3.62% : 0.000006s : 3: substitution.graph_param_transform 79.36% : 0.000128s : 3: substitution.inline 2.52% : 0.000004s : 4: substitution.j_node_and_user_rematch 3.06% : 0.000005s : 4: substitution.remove_not_recompute_node 2.66% : 0.000004s : 2: substitution.replace_old_param 6.72% : 0.000011s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.038452 2 98.08% : 0.037713s : 1: type_inference.infer 1.92% : 0.000738s : 1: type_inference.specialize ------[replace.] 0.000041 4 83.14% : 0.000034s : 3: replace.inline 16.86% : 0.000007s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000136 4 92.57% : 0.000126s : 3: match.inline 7.43% : 0.000010s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000106 606 1.08% : 0.000001s : 9: predicate.accumulaten_eliminater 1.60% : 0.000002s : 3: predicate.ad_related_special_op_eliminate 1.06% : 0.000001s : 9: predicate.addn_check_dump 1.13% : 0.000001s : 9: predicate.addn_zero_filter 2.03% : 0.000002s : 9: predicate.arithmetic_simplify 1.14% : 0.000001s : 9: predicate.cast_eliminate 0.56% : 0.000001s : 3: predicate.check_bprop_eliminate 1.04% : 0.000001s : 9: predicate.compare_switch_simplify 1.18% : 0.000001s : 9: predicate.depend_value_elim 1.07% : 0.000001s : 9: predicate.dict_get_item_const_eliminator 1.46% : 0.000002s : 9: predicate.dict_get_item_eliminator 1.06% : 0.000001s : 9: predicate.dict_set_item_eliminator 1.43% : 0.000002s : 3: predicate.dumpgradient_eliminate 0.41% : 0.000000s : 3: predicate.elim_not_effective 0.63% : 0.000001s : 3: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000001s : 9: predicate.environ_add_const_eliminate 1.05% : 0.000001s : 9: predicate.environ_get_add_eliminate 1.02% : 0.000001s : 9: predicate.environ_get_depend_swap 1.15% : 0.000001s : 9: predicate.environ_get_eliminate 1.06% : 0.000001s : 9: predicate.environ_get_set_eliminate 0.27% : 0.000000s : 3: predicate.fold_const_symbol 1.09% : 0.000001s : 6: predicate.get_grad_eliminate 0.29% : 0.000000s : 3: predicate.graph_param_transform 5.51% : 0.000006s : 19: predicate.inline 1.12% : 0.000001s : 6: predicate.inline_without_move 0.45% : 0.000000s : 6: predicate.j_node_and_user_rematch 1.71% : 0.000002s : 6: predicate.less_batch_normalization 1.38% : 0.000001s : 10: predicate.list_to_tuple_eliminator_ 1.70% : 0.000002s : 13: predicate.load_eliminater 1.47% : 0.000002s : 3: predicate.loop_unroll_after_grad 3.11% : 0.000003s : 22: predicate.loop_unroll_before_grad 1.97% : 0.000002s : 12: predicate.make_slice_get_slice_eliminator 1.02% : 0.000001s : 9: predicate.merge_addn 1.03% : 0.000001s : 9: predicate.minmaximum_grad 3.15% : 0.000003s : 3: predicate.mutable_eliminate 0.59% : 0.000001s : 3: predicate.opt_reshape 2.29% : 0.000002s : 13: predicate.partial_eliminate 1.15% : 0.000001s : 9: predicate.print_const_string_wrapper 1.65% : 0.000002s : 9: predicate.reduce_eliminate 1.32% : 0.000001s : 10: predicate.redundant_stop_gradient_eliminater 0.56% : 0.000001s : 6: predicate.remove_not_recompute_node 1.83% : 0.000002s : 16: predicate.replace_applicator 1.07% : 0.000001s : 6: predicate.replace_old_param 0.35% : 0.000000s : 3: predicate.reset_defer_inline 1.21% : 0.000001s : 9: predicate.reshape_eliminate 1.15% : 0.000001s : 9: predicate.row_tensor_add_zeros_like 0.87% : 0.000001s : 3: predicate.row_tensor_eliminate 1.19% : 0.000001s : 9: predicate.same_eliminate 0.78% : 0.000001s : 6: predicate.set_cell_output_no_recompute 1.16% : 0.000001s : 6: predicate.special_op_eliminate 1.10% : 0.000001s : 6: predicate.specialize_transform 1.43% : 0.000002s : 9: predicate.split_environ_get_set_with_tuple_value 1.16% : 0.000001s : 9: predicate.stack_unstack_eliminate 0.59% : 0.000001s : 3: predicate.switch_call_monad_eliminater 1.97% : 0.000002s : 13: predicate.switch_defer_inline 1.82% : 0.000002s : 13: predicate.switch_layer_defer_inline 7.42% : 0.000008s : 38: predicate.switch_simplify 1.17% : 0.000001s : 9: predicate.tile_eliminate 1.19% : 0.000001s : 9: predicate.transpose_eliminate 1.66% : 0.000002s : 9: predicate.tuple_list_convert_item_index_to_positive 1.52% : 0.000002s : 9: predicate.tuple_list_get_item_depend_reorder 3.96% : 0.000004s : 16: predicate.tuple_list_get_item_eliminator 1.76% : 0.000002s : 9: predicate.tuple_list_set_item_eliminator 1.29% : 0.000001s : 10: predicate.tuple_to_list_eliminator_ 1.57% : 0.000002s : 13: predicate.updatestate_pure_node_eliminater 2.92% : 0.000003s : 19: predicate.updatestate_useless_node_eliminater 1.61% : 0.000002s : 9: predicate.value_based_eliminate 0.39% : 0.000000s : 3: predicate.virtual_view_grad_eliminate 0.75% : 0.000001s : 3: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000471 8 46.31% : 0.000218s : 3: func_graph_cloner_run.FuncGraphClonerGraph 53.69% : 0.000253s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.316398 72 0.02% : 0.000063s : 1: add_recomputation 0.04% : 0.000123s : 1: auto_monad 0.01% : 0.000044s : 1: auto_monad_reorder 0.22% : 0.000712s : 1: bootstrap 0.01% : 0.000033s : 1: cconv 0.01% : 0.000024s : 1: convert_after_rewriter 0.01% : 0.000025s : 1: cse_after_recomputation 0.01% : 0.000020s : 1: environ_conv 0.01% : 0.000023s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 86.29% : 0.273029s : 1: jit_opt_a 0.05% : 0.000155s : 1: jit_opt_after_cconv 0.02% : 0.000053s : 1: jit_opt_b 0.14% : 0.000428s : 1: loop_unroll 0.20% : 0.000626s : 1: mutable_eliminate 0.22% : 0.000701s : 26: opt.transform.jit_opt_a 0.02% : 0.000049s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000024s : 4: opt.transform.jit_opt_b 0.00% : 0.000013s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000015s : 1: opt.transform.mutable_eliminate 0.01% : 0.000022s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000030s : 4: opt.transform.symbol_engine_opt 0.15% : 0.000481s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000014s : 1: pre_auto_parallel 0.01% : 0.000029s : 1: py_interpret_to_execute 0.00% : 0.000014s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000017s : 1: remove_dup_value 0.12% : 0.000381s : 1: renormalize.infer 0.09% : 0.000280s : 1: renormalize.specialize 0.05% : 0.000157s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000071s : 1: rewriter_after_opt_a 0.02% : 0.000071s : 1: rewriter_before_opt_a 0.02% : 0.000074s : 1: symbol_engine_optimizer 12.19% : 0.038568s : 1: type_inference TotalTime = 0.77736, [30] [bootstrap]: 0.0005986 [type_inference]: 0.549128 [event_method]: 0.00012286 [auto_monad]: 0.00015205 [graph_reusing]: 9.66e-06 [pre_auto_parallel]: 3.48e-06 [py_interpret_to_execute]: 3.971e-05 [rewriter_before_opt_a]: 0.00013864 [expand_dump_flag]: 3.98001e-06 [jit_opt_a]: 0.224018, [3] [Cycle 1]: 0.0068654, [27] [switch_simplify]: 0.00019309 [loop_unroll]: 5.742e-05 [a_1]: 0.00108042 [with_stream_mark]: 2.843e-05 [recompute_prepare]: 2.038e-05 [updatestate_depend_eliminate]: 9.46998e-06 [updatestate_assign_eliminate]: 6.74001e-06 [updatestate_loads_eliminate]: 7.21999e-06 [parameter_eliminate]: 2.93e-06 [specialize_transform]: 1.314e-05 [updatestate_useless_node_eliminater]: 1.219e-05 [accelerated_algorithm]: 1.203e-05 [meta_shard_fg_expand]: 3.97002e-06 [get_grad_eliminate_]: 1.248e-05 [merge_forward]: 8.88002e-06 [cell_reuse_recompute_pass]: 1.00999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.798e-05 [j_node_and_user_rematch]: 2.327e-05 [meta_fg_expand]: 0.00163987 [replace_old_param]: 5.908e-05 [inline_without_move]: 5.521e-05 [renormalize]: 0.00295533 [add_forward_monad_depend]: 2.151e-05 [auto_monad_grad]: 7.60998e-06 [auto_monad_eliminator]: 5.85e-05 [cse]: 0.00020693 [replace_applicator]: 8.623e-05 [Cycle 2]: 0.212154, [27] [switch_simplify]: 3.939e-05 [loop_unroll]: 3.618e-05 [a_1]: 0.210558 [with_stream_mark]: 3.065e-05 [recompute_prepare]: 1.501e-05 [updatestate_depend_eliminate]: 6.06e-06 [updatestate_assign_eliminate]: 5.40999e-06 [updatestate_loads_eliminate]: 3.64002e-06 [parameter_eliminate]: 2.80002e-06 [specialize_transform]: 7.95e-06 [updatestate_useless_node_eliminater]: 7.18e-06 [accelerated_algorithm]: 8.28999e-06 [meta_shard_fg_expand]: 4.84e-06 [get_grad_eliminate_]: 6.41998e-06 [merge_forward]: 6.96999e-06 [cell_reuse_recompute_pass]: 2.21e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.23e-05 [j_node_and_user_rematch]: 1.305e-05 [meta_fg_expand]: 9.068e-05 [replace_old_param]: 1.394e-05 [inline_without_move]: 6.65998e-06 [renormalize]: 0.00093113 [add_forward_monad_depend]: 8.99e-06 [auto_monad_grad]: 2.78998e-06 [auto_monad_eliminator]: 2.548e-05 [cse]: 4.551e-05 [replace_applicator]: 2.271e-05 [Cycle 3]: 0.00046892, [27] [switch_simplify]: 7.95998e-06 [loop_unroll]: 6.58998e-06 [a_1]: 0.00015228 [with_stream_mark]: 1.69e-05 [recompute_prepare]: 7.22002e-06 [updatestate_depend_eliminate]: 5.86e-06 [updatestate_assign_eliminate]: 3.53999e-06 [updatestate_loads_eliminate]: 3.78001e-06 [parameter_eliminate]: 1.52001e-06 [specialize_transform]: 6.52001e-06 [updatestate_useless_node_eliminater]: 5.99e-06 [accelerated_algorithm]: 6.73998e-06 [meta_shard_fg_expand]: 1.87001e-06 [get_grad_eliminate_]: 5.96998e-06 [merge_forward]: 4.75001e-06 [cell_reuse_recompute_pass]: 2.44001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.83e-05 [j_node_and_user_rematch]: 1.099e-05 [meta_fg_expand]: 3.75e-06 [replace_old_param]: 9.94999e-06 [inline_without_move]: 6.06e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 3.76999e-06 [auto_monad_grad]: 1.23002e-06 [auto_monad_eliminator]: 1.144e-05 [cse]: 2.497e-05 [replace_applicator]: 8.64e-06 [py_interpret_to_execute_after_opt_a]: 2.051e-05 [rewriter_after_opt_a]: 5.642e-05 [convert_after_rewriter]: 9.07999e-06 [order_py_execute_after_rewriter]: 6.35002e-06 [mutable_eliminate]: 0.00079856 [jit_opt_b]: 8.611e-05, [1] [Cycle 1]: 7.595e-05, [2] [frontend_op_eliminate]: 3.842e-05 [inline_after_opt_a]: 2.329e-05 [cconv]: 3.797e-05 [loop_unroll]: 0.00061356 [jit_opt_after_cconv]: 0.00021159, [1] [Cycle 1]: 0.0002032, [11] [c_1]: 2.92e-05 [parameter_eliminate]: 5.19998e-06 [updatestate_depend_eliminate]: 1.24e-05 [updatestate_assign_eliminate]: 3.46999e-06 [updatestate_loads_eliminate]: 4.04002e-06 [cse]: 4.658e-05 [call_graph_tuple_transform]: 3.021e-05 [tuple_list_get_item_eliminator]: 7e-06 [none_parameter_eliminate]: 1.70001e-06 [renormalize]: 5.60016e-07 [switch_simplify]: 6.99001e-06 [remove_dup_value]: 2.014e-05 [partial_unused_args_eliminate]: 2.46998e-06 [environ_conv]: 8.72e-06 [add_recomputation]: 7.114e-05 [cse_after_recomputation]: 3.287e-05, [1] [Cycle 1]: 2.58e-05, [1] [cse]: 1.838e-05 [auto_monad_reorder]: 2.166e-05 [get_jit_bprop_graph]: 2.12999e-06 [rewriter_after_jit_bprop_graph]: 9.04e-06 [opt_after_jit_grad]: 0.00060515 [symbol_engine_optimizer]: 9.625e-05, [1] [Cycle 1]: 8.768e-05, [6] [build]: 6.04999e-06 [elim_shapecalc]: 1.106e-05 [elim_not_effective]: 1.974e-05 [opt_reshape]: 7.55e-06 [fold_const_symbol]: 1.138e-05 [renormalize]: 5.19998e-07 [validate]: 6.094e-05 Sums bootstrap : 0.000599s : 0.08% type_inference : 0.549128s : 71.16% event_method : 0.000123s : 0.02% auto_monad : 0.000152s : 0.02% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000040s : 0.01% rewriter_before_opt_a : 0.000139s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000240s : 0.03% jit_opt_a.loop_unroll : 0.000100s : 0.01% jit_opt_a.a_1 : 0.211790s : 27.44% jit_opt_a.with_stream_mark : 0.000076s : 0.01% jit_opt_a.recompute_prepare : 0.000043s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000021s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000016s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000015s : 0.00% jit_opt_a.parameter_eliminate : 0.000007s : 0.00% jit_opt_a.specialize_transform : 0.000028s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.00% jit_opt_a.accelerated_algorithm : 0.000027s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000011s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000025s : 0.00% jit_opt_a.merge_forward : 0.000021s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000069s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000047s : 0.01% jit_opt_a.meta_fg_expand : 0.001734s : 0.22% jit_opt_a.replace_old_param : 0.000083s : 0.01% jit_opt_a.inline_without_move : 0.000068s : 0.01% jit_opt_a.renormalize : 0.003887s : 0.50% jit_opt_a.add_forward_monad_depend : 0.000034s : 0.00% jit_opt_a.auto_monad_grad : 0.000012s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000095s : 0.01% jit_opt_a.cse : 0.000277s : 0.04% jit_opt_a.replace_applicator : 0.000118s : 0.02% py_interpret_to_execute_after_opt_a : 0.000021s : 0.00% rewriter_after_opt_a : 0.000056s : 0.01% convert_after_rewriter : 0.000009s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000799s : 0.10% jit_opt_b.frontend_op_eliminate : 0.000038s : 0.00% jit_opt_b.inline_after_opt_a : 0.000023s : 0.00% cconv : 0.000038s : 0.00% loop_unroll : 0.000614s : 0.08% jit_opt_after_cconv.c_1 : 0.000029s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000047s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000007s : 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 : 0.000007s : 0.00% remove_dup_value : 0.000020s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000009s : 0.00% add_recomputation : 0.000071s : 0.01% cse_after_recomputation.cse : 0.000018s : 0.00% auto_monad_reorder : 0.000022s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000605s : 0.08% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000061s : 0.01% Time group info: ------[substitution.] 0.000904 125 12.27% : 0.000111s : 3: substitution.arithmetic_simplify 0.39% : 0.000004s : 3: substitution.elim_not_effective 0.23% : 0.000002s : 3: substitution.fold_const_symbol 0.76% : 0.000007s : 4: substitution.graph_param_transform 59.16% : 0.000535s : 18: substitution.inline 2.17% : 0.000020s : 2: substitution.inline_without_move 1.20% : 0.000011s : 14: substitution.j_node_and_user_rematch 1.45% : 0.000013s : 7: substitution.minmaximum_grad 1.15% : 0.000010s : 10: substitution.partial_eliminate 1.46% : 0.000013s : 14: substitution.remove_not_recompute_node 5.24% : 0.000047s : 9: substitution.replace_applicator 1.23% : 0.000011s : 7: substitution.replace_old_param 0.29% : 0.000003s : 1: substitution.set_cell_output_no_recompute 1.59% : 0.000014s : 3: substitution.switch_simplify 3.07% : 0.000028s : 7: substitution.tuple_list_convert_item_index_to_positive 2.22% : 0.000020s : 7: substitution.tuple_list_get_item_depend_reorder 6.13% : 0.000055s : 13: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.549022 2 99.60% : 0.546831s : 1: type_inference.infer 0.40% : 0.002190s : 1: type_inference.specialize ------[replace.] 0.000299 28 2.99% : 0.000009s : 1: replace.arithmetic_simplify 57.58% : 0.000172s : 18: replace.inline 20.81% : 0.000062s : 3: replace.switch_simplify 18.62% : 0.000056s : 6: replace.tuple_list_get_item_eliminator ------[match.] 0.000649 28 12.62% : 0.000082s : 1: match.arithmetic_simplify 80.87% : 0.000525s : 18: match.inline 1.95% : 0.000013s : 3: match.switch_simplify 4.56% : 0.000030s : 6: match.tuple_list_get_item_eliminator ------[predicate.] 0.209449 2877 0.00% : 0.000007s : 48: predicate.accumulaten_eliminater 0.00% : 0.000003s : 4: predicate.ad_related_special_op_eliminate 0.00% : 0.000007s : 48: predicate.addn_check_dump 0.00% : 0.000007s : 48: predicate.addn_zero_filter 0.01% : 0.000012s : 49: predicate.arithmetic_simplify 0.00% : 0.000008s : 49: predicate.cast_eliminate 0.00% : 0.000001s : 4: predicate.check_bprop_eliminate 0.00% : 0.000006s : 48: predicate.compare_switch_simplify 0.00% : 0.000006s : 48: predicate.depend_value_elim 0.00% : 0.000006s : 49: predicate.dict_get_item_const_eliminator 0.00% : 0.000008s : 49: predicate.dict_get_item_eliminator 0.00% : 0.000006s : 49: predicate.dict_set_item_eliminator 0.00% : 0.000003s : 4: predicate.dumpgradient_eliminate 0.00% : 0.000001s : 4: predicate.elim_not_effective 0.00% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 0.00% : 0.000007s : 49: predicate.environ_add_const_eliminate 0.00% : 0.000006s : 49: predicate.environ_get_add_eliminate 0.00% : 0.000006s : 49: predicate.environ_get_depend_swap 0.00% : 0.000006s : 49: predicate.environ_get_eliminate 0.00% : 0.000006s : 49: predicate.environ_get_set_eliminate 0.00% : 0.000000s : 4: predicate.fold_const_symbol 0.00% : 0.000004s : 19: predicate.get_grad_eliminate 0.00% : 0.000001s : 4: predicate.graph_param_transform 0.01% : 0.000021s : 81: predicate.inline 0.00% : 0.000007s : 40: predicate.inline_without_move 0.00% : 0.000002s : 19: predicate.j_node_and_user_rematch 0.00% : 0.000004s : 19: predicate.less_batch_normalization 0.00% : 0.000008s : 55: predicate.list_to_tuple_eliminator_ 0.00% : 0.000008s : 59: predicate.load_eliminater 0.00% : 0.000004s : 4: predicate.loop_unroll_after_grad 0.01% : 0.000015s : 104: predicate.loop_unroll_before_grad 0.00% : 0.000008s : 53: predicate.make_slice_get_slice_eliminator 0.00% : 0.000006s : 48: predicate.merge_addn 0.00% : 0.000006s : 49: predicate.minmaximum_grad 0.00% : 0.000005s : 4: predicate.mutable_eliminate 0.00% : 0.000001s : 4: predicate.opt_reshape 0.01% : 0.000011s : 59: predicate.partial_eliminate 0.00% : 0.000006s : 48: predicate.print_const_string_wrapper 0.00% : 0.000009s : 49: predicate.reduce_eliminate 0.00% : 0.000008s : 55: predicate.redundant_stop_gradient_eliminater 0.00% : 0.000002s : 19: predicate.remove_not_recompute_node 0.01% : 0.000011s : 103: predicate.replace_applicator 0.00% : 0.000004s : 40: predicate.replace_old_param 0.00% : 0.000001s : 4: predicate.reset_defer_inline 0.00% : 0.000007s : 49: predicate.reshape_eliminate 0.00% : 0.000006s : 48: predicate.row_tensor_add_zeros_like 0.00% : 0.000001s : 4: predicate.row_tensor_eliminate 0.00% : 0.000006s : 48: predicate.same_eliminate 0.00% : 0.000002s : 19: predicate.set_cell_output_no_recompute 0.00% : 0.000001s : 8: predicate.special_op_eliminate 0.00% : 0.000004s : 19: predicate.specialize_transform 0.00% : 0.000007s : 48: predicate.split_environ_get_set_with_tuple_value 0.00% : 0.000006s : 48: predicate.stack_unstack_eliminate 0.00% : 0.000001s : 4: predicate.switch_call_monad_eliminater 0.01% : 0.000014s : 73: predicate.switch_defer_inline 0.01% : 0.000011s : 73: predicate.switch_layer_defer_inline 0.01% : 0.000030s : 187: predicate.switch_simplify 99.78% : 0.208998s : 49: predicate.tile_eliminate 0.01% : 0.000011s : 49: predicate.transpose_eliminate 0.00% : 0.000008s : 49: predicate.tuple_list_convert_item_index_to_positive 0.00% : 0.000007s : 49: predicate.tuple_list_get_item_depend_reorder 0.01% : 0.000015s : 63: predicate.tuple_list_get_item_eliminator 0.00% : 0.000009s : 49: predicate.tuple_list_set_item_eliminator 0.00% : 0.000008s : 55: predicate.tuple_to_list_eliminator_ 0.00% : 0.000008s : 59: predicate.updatestate_pure_node_eliminater 0.01% : 0.000012s : 78: predicate.updatestate_useless_node_eliminater 0.00% : 0.000008s : 48: predicate.value_based_eliminate 0.00% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.00% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.002234 34 63.45% : 0.001417s : 12: func_graph_cloner_run.FuncGraphClonerGraph 36.55% : 0.000817s : 22: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.993828 87 0.01% : 0.000075s : 1: add_recomputation 0.02% : 0.000158s : 1: auto_monad 0.00% : 0.000025s : 1: auto_monad_reorder 0.06% : 0.000632s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000011s : 1: convert_after_rewriter 0.00% : 0.000035s : 1: cse_after_recomputation 0.00% : 0.000011s : 1: environ_conv 0.01% : 0.000131s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 22.54% : 0.224022s : 1: jit_opt_a 0.02% : 0.000215s : 1: jit_opt_after_cconv 0.01% : 0.000089s : 1: jit_opt_b 0.06% : 0.000626s : 1: loop_unroll 0.08% : 0.000815s : 1: mutable_eliminate 21.39% : 0.212601s : 39: opt.transform.jit_opt_a 0.01% : 0.000070s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000053s : 4: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000026s : 1: opt.transform.mutable_eliminate 0.00% : 0.000036s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000046s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000618s : 1: opt_after_jit_grad 0.00% : 0.000009s : 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% : 0.000043s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000023s : 1: remove_dup_value 0.21% : 0.002068s : 2: renormalize.infer 0.18% : 0.001798s : 2: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000060s : 1: rewriter_after_opt_a 0.01% : 0.000143s : 1: rewriter_before_opt_a 0.01% : 0.000099s : 1: symbol_engine_optimizer 55.26% : 0.549156s : 1: type_inference . [hook] pytest_runtest_teardown:test_square_normal[KBK] tests/st/ops/test_ops_square.py::test_square_normal[KBK],max_mem:4.0M [WARNING] ME(170331:281473334710064,MainProcess):2026-01-29-17:39:11.642.973 [mindspore/graph/api.py:128] The function "square_forward_func" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/utils/test_utils.py", line 49 has been compiled again. Try to reuse the function object decorated by @jit to reduce the compile time. For more details, get instructions about `jit` at https://www.mindspore.cn/search?inputValue=jit. TotalTime = 0.0164763, [30] [bootstrap]: 0.00052791 [type_inference]: 0.00728655 [event_method]: 1.77e-05 [auto_monad]: 6.667e-05 [graph_reusing]: 6.11e-06 [pre_auto_parallel]: 2.42001e-06 [py_interpret_to_execute]: 2.764e-05 [rewriter_before_opt_a]: 5.573e-05 [expand_dump_flag]: 3.36001e-06 [jit_opt_a]: 0.00618399, [2] [Cycle 1]: 0.00163875, [27] [switch_simplify]: 4.98e-05 [loop_unroll]: 1.968e-05 [a_1]: 0.00041863 [with_stream_mark]: 3.03e-05 [recompute_prepare]: 6.78998e-06 [updatestate_depend_eliminate]: 4.52998e-06 [updatestate_assign_eliminate]: 3.33e-06 [updatestate_loads_eliminate]: 3.33998e-06 [parameter_eliminate]: 2.01998e-06 [specialize_transform]: 5.64e-06 [updatestate_useless_node_eliminater]: 4.90001e-06 [accelerated_algorithm]: 5.62999e-06 [meta_shard_fg_expand]: 2.37999e-06 [get_grad_eliminate_]: 4.75001e-06 [merge_forward]: 3.8e-06 [cell_reuse_recompute_pass]: 1.28002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.4e-05 [j_node_and_user_rematch]: 8.92999e-06 [meta_fg_expand]: 2.31e-06 [replace_old_param]: 9.14e-06 [inline_without_move]: 5.12999e-06 [renormalize]: 0.00076423 [add_forward_monad_depend]: 1.228e-05 [auto_monad_grad]: 2.71e-06 [auto_monad_eliminator]: 1.694e-05 [cse]: 3.357e-05 [replace_applicator]: 1.461e-05 [Cycle 2]: 0.0003242, [27] [switch_simplify]: 5.55001e-06 [loop_unroll]: 4.72998e-06 [a_1]: 8.984e-05 [with_stream_mark]: 1.211e-05 [recompute_prepare]: 4.59998e-06 [updatestate_depend_eliminate]: 3.25e-06 [updatestate_assign_eliminate]: 2.69001e-06 [updatestate_loads_eliminate]: 1.94e-06 [parameter_eliminate]: 1.29e-06 [specialize_transform]: 4.82e-06 [updatestate_useless_node_eliminater]: 4.61002e-06 [accelerated_algorithm]: 4.43001e-06 [meta_shard_fg_expand]: 1.46998e-06 [get_grad_eliminate_]: 4.34997e-06 [merge_forward]: 2.79999e-06 [cell_reuse_recompute_pass]: 2.24001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.455e-05 [j_node_and_user_rematch]: 8.48999e-06 [meta_fg_expand]: 1.71e-06 [replace_old_param]: 8.1e-06 [inline_without_move]: 4.82e-06 [renormalize]: 1.09983e-07 [add_forward_monad_depend]: 9.89996e-07 [auto_monad_grad]: 1.43002e-06 [auto_monad_eliminator]: 5.59e-06 [cse]: 1.096e-05 [replace_applicator]: 4.88001e-06 [py_interpret_to_execute_after_opt_a]: 1.394e-05 [rewriter_after_opt_a]: 3.699e-05 [convert_after_rewriter]: 8.61002e-06 [order_py_execute_after_rewriter]: 5.63002e-06 [mutable_eliminate]: 0.00062067 [jit_opt_b]: 5.096e-05, [1] [Cycle 1]: 4.343e-05, [2] [frontend_op_eliminate]: 1.661e-05 [inline_after_opt_a]: 1.518e-05 [cconv]: 3.456e-05 [loop_unroll]: 0.00043706 [jit_opt_after_cconv]: 0.00015224, [1] [Cycle 1]: 0.00014624, [11] [c_1]: 2.045e-05 [parameter_eliminate]: 3.97998e-06 [updatestate_depend_eliminate]: 7.88001e-06 [updatestate_assign_eliminate]: 3.18998e-06 [updatestate_loads_eliminate]: 2.10002e-06 [cse]: 2.33e-05 [call_graph_tuple_transform]: 2.152e-05 [tuple_list_get_item_eliminator]: 5.29998e-06 [none_parameter_eliminate]: 1.76e-06 [renormalize]: 8.50006e-07 [switch_simplify]: 5.27001e-06 [remove_dup_value]: 1.494e-05 [partial_unused_args_eliminate]: 2.24999e-06 [environ_conv]: 7.1e-06 [add_recomputation]: 5.654e-05 [cse_after_recomputation]: 2.226e-05, [1] [Cycle 1]: 1.615e-05, [1] [cse]: 1.047e-05 [auto_monad_reorder]: 1.562e-05 [get_jit_bprop_graph]: 2.36998e-06 [rewriter_after_jit_bprop_graph]: 5.27999e-06 [opt_after_jit_grad]: 0.00047406 [symbol_engine_optimizer]: 7.352e-05, [1] [Cycle 1]: 6.641e-05, [6] [build]: 4.22e-06 [elim_shapecalc]: 7.41001e-06 [elim_not_effective]: 1.247e-05 [opt_reshape]: 5.40001e-06 [fold_const_symbol]: 8.90001e-06 [renormalize]: 7.39994e-07 [validate]: 4.085e-05 Sums bootstrap : 0.000528s : 4.55% type_inference : 0.007287s : 62.76% event_method : 0.000018s : 0.15% auto_monad : 0.000067s : 0.57% graph_reusing : 0.000006s : 0.05% pre_auto_parallel : 0.000002s : 0.02% py_interpret_to_execute : 0.000028s : 0.24% rewriter_before_opt_a : 0.000056s : 0.48% expand_dump_flag : 0.000003s : 0.03% jit_opt_a.switch_simplify : 0.000055s : 0.48% jit_opt_a.loop_unroll : 0.000024s : 0.21% jit_opt_a.a_1 : 0.000508s : 4.38% jit_opt_a.with_stream_mark : 0.000042s : 0.37% jit_opt_a.recompute_prepare : 0.000011s : 0.10% jit_opt_a.updatestate_depend_eliminate : 0.000008s : 0.07% jit_opt_a.updatestate_assign_eliminate : 0.000006s : 0.05% jit_opt_a.updatestate_loads_eliminate : 0.000005s : 0.05% jit_opt_a.parameter_eliminate : 0.000003s : 0.03% jit_opt_a.specialize_transform : 0.000010s : 0.09% jit_opt_a.updatestate_useless_node_eliminater : 0.000010s : 0.08% jit_opt_a.accelerated_algorithm : 0.000010s : 0.09% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.03% jit_opt_a.get_grad_eliminate_ : 0.000009s : 0.08% jit_opt_a.merge_forward : 0.000007s : 0.06% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.03% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000029s : 0.25% jit_opt_a.j_node_and_user_rematch : 0.000017s : 0.15% jit_opt_a.meta_fg_expand : 0.000004s : 0.03% jit_opt_a.replace_old_param : 0.000017s : 0.15% jit_opt_a.inline_without_move : 0.000010s : 0.09% jit_opt_a.renormalize : 0.000764s : 6.58% jit_opt_a.add_forward_monad_depend : 0.000013s : 0.11% jit_opt_a.auto_monad_grad : 0.000004s : 0.04% jit_opt_a.auto_monad_eliminator : 0.000023s : 0.19% jit_opt_a.cse : 0.000045s : 0.38% jit_opt_a.replace_applicator : 0.000019s : 0.17% py_interpret_to_execute_after_opt_a : 0.000014s : 0.12% rewriter_after_opt_a : 0.000037s : 0.32% convert_after_rewriter : 0.000009s : 0.07% order_py_execute_after_rewriter : 0.000006s : 0.05% mutable_eliminate : 0.000621s : 5.35% jit_opt_b.frontend_op_eliminate : 0.000017s : 0.14% jit_opt_b.inline_after_opt_a : 0.000015s : 0.13% cconv : 0.000035s : 0.30% loop_unroll : 0.000437s : 3.76% jit_opt_after_cconv.c_1 : 0.000020s : 0.18% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.03% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.07% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.03% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000002s : 0.02% jit_opt_after_cconv.cse : 0.000023s : 0.20% jit_opt_after_cconv.call_graph_tuple_transform : 0.000022s : 0.19% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000005s : 0.05% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.02% jit_opt_after_cconv.renormalize : 0.000001s : 0.01% jit_opt_after_cconv.switch_simplify : 0.000005s : 0.05% remove_dup_value : 0.000015s : 0.13% partial_unused_args_eliminate : 0.000002s : 0.02% environ_conv : 0.000007s : 0.06% add_recomputation : 0.000057s : 0.49% cse_after_recomputation.cse : 0.000010s : 0.09% auto_monad_reorder : 0.000016s : 0.13% get_jit_bprop_graph : 0.000002s : 0.02% rewriter_after_jit_bprop_graph : 0.000005s : 0.05% opt_after_jit_grad : 0.000474s : 4.08% symbol_engine_optimizer.build : 0.000004s : 0.04% symbol_engine_optimizer.elim_shapecalc : 0.000007s : 0.06% symbol_engine_optimizer.elim_not_effective : 0.000012s : 0.11% symbol_engine_optimizer.opt_reshape : 0.000005s : 0.05% symbol_engine_optimizer.fold_const_symbol : 0.000009s : 0.08% symbol_engine_optimizer.renormalize : 0.000001s : 0.01% validate : 0.000041s : 0.35% Time group info: ------[substitution.] 0.000166 21 1.20% : 0.000002s : 2: substitution.elim_not_effective 0.80% : 0.000001s : 2: substitution.fold_const_symbol 3.87% : 0.000006s : 3: substitution.graph_param_transform 80.44% : 0.000134s : 3: substitution.inline 2.22% : 0.000004s : 4: substitution.j_node_and_user_rematch 2.52% : 0.000004s : 4: substitution.remove_not_recompute_node 2.96% : 0.000005s : 2: substitution.replace_old_param 6.00% : 0.000010s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.007201 2 90.51% : 0.006518s : 1: type_inference.infer 9.49% : 0.000683s : 1: type_inference.specialize ------[replace.] 0.000042 4 82.46% : 0.000034s : 3: replace.inline 17.54% : 0.000007s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000141 4 93.41% : 0.000131s : 3: match.inline 6.59% : 0.000009s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000105 606 1.40% : 0.000001s : 9: predicate.accumulaten_eliminater 1.46% : 0.000002s : 3: predicate.ad_related_special_op_eliminate 1.04% : 0.000001s : 9: predicate.addn_check_dump 1.23% : 0.000001s : 9: predicate.addn_zero_filter 1.88% : 0.000002s : 9: predicate.arithmetic_simplify 1.19% : 0.000001s : 9: predicate.cast_eliminate 0.55% : 0.000001s : 3: predicate.check_bprop_eliminate 1.02% : 0.000001s : 9: predicate.compare_switch_simplify 1.16% : 0.000001s : 9: predicate.depend_value_elim 1.06% : 0.000001s : 9: predicate.dict_get_item_const_eliminator 1.65% : 0.000002s : 9: predicate.dict_get_item_eliminator 1.22% : 0.000001s : 9: predicate.dict_set_item_eliminator 1.04% : 0.000001s : 3: predicate.dumpgradient_eliminate 0.37% : 0.000000s : 3: predicate.elim_not_effective 0.58% : 0.000001s : 3: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000001s : 9: predicate.environ_add_const_eliminate 1.11% : 0.000001s : 9: predicate.environ_get_add_eliminate 1.03% : 0.000001s : 9: predicate.environ_get_depend_swap 1.11% : 0.000001s : 9: predicate.environ_get_eliminate 1.12% : 0.000001s : 9: predicate.environ_get_set_eliminate 0.28% : 0.000000s : 3: predicate.fold_const_symbol 0.82% : 0.000001s : 6: predicate.get_grad_eliminate 0.27% : 0.000000s : 3: predicate.graph_param_transform 6.66% : 0.000007s : 19: predicate.inline 1.13% : 0.000001s : 6: predicate.inline_without_move 0.42% : 0.000000s : 6: predicate.j_node_and_user_rematch 1.19% : 0.000001s : 6: predicate.less_batch_normalization 1.33% : 0.000001s : 10: predicate.list_to_tuple_eliminator_ 1.81% : 0.000002s : 13: predicate.load_eliminater 2.23% : 0.000002s : 3: predicate.loop_unroll_after_grad 3.25% : 0.000003s : 22: predicate.loop_unroll_before_grad 1.87% : 0.000002s : 12: predicate.make_slice_get_slice_eliminator 1.09% : 0.000001s : 9: predicate.merge_addn 1.00% : 0.000001s : 9: predicate.minmaximum_grad 2.68% : 0.000003s : 3: predicate.mutable_eliminate 0.49% : 0.000001s : 3: predicate.opt_reshape 2.35% : 0.000002s : 13: predicate.partial_eliminate 1.21% : 0.000001s : 9: predicate.print_const_string_wrapper 1.56% : 0.000002s : 9: predicate.reduce_eliminate 1.31% : 0.000001s : 10: predicate.redundant_stop_gradient_eliminater 0.58% : 0.000001s : 6: predicate.remove_not_recompute_node 1.91% : 0.000002s : 16: predicate.replace_applicator 0.80% : 0.000001s : 6: predicate.replace_old_param 0.38% : 0.000000s : 3: predicate.reset_defer_inline 1.14% : 0.000001s : 9: predicate.reshape_eliminate 1.21% : 0.000001s : 9: predicate.row_tensor_add_zeros_like 0.88% : 0.000001s : 3: predicate.row_tensor_eliminate 1.06% : 0.000001s : 9: predicate.same_eliminate 0.57% : 0.000001s : 6: predicate.set_cell_output_no_recompute 1.54% : 0.000002s : 6: predicate.special_op_eliminate 1.06% : 0.000001s : 6: predicate.specialize_transform 1.34% : 0.000001s : 9: predicate.split_environ_get_set_with_tuple_value 1.17% : 0.000001s : 9: predicate.stack_unstack_eliminate 0.58% : 0.000001s : 3: predicate.switch_call_monad_eliminater 2.28% : 0.000002s : 13: predicate.switch_defer_inline 1.80% : 0.000002s : 13: predicate.switch_layer_defer_inline 7.24% : 0.000008s : 38: predicate.switch_simplify 1.27% : 0.000001s : 9: predicate.tile_eliminate 1.13% : 0.000001s : 9: predicate.transpose_eliminate 1.32% : 0.000001s : 9: predicate.tuple_list_convert_item_index_to_positive 1.24% : 0.000001s : 9: predicate.tuple_list_get_item_depend_reorder 4.59% : 0.000005s : 16: predicate.tuple_list_get_item_eliminator 1.43% : 0.000002s : 9: predicate.tuple_list_set_item_eliminator 1.39% : 0.000001s : 10: predicate.tuple_to_list_eliminator_ 1.57% : 0.000002s : 13: predicate.updatestate_pure_node_eliminater 2.67% : 0.000003s : 19: predicate.updatestate_useless_node_eliminater 1.37% : 0.000001s : 9: predicate.value_based_eliminate 0.37% : 0.000000s : 3: predicate.virtual_view_grad_eliminate 0.78% : 0.000001s : 3: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000548 8 44.35% : 0.000243s : 3: func_graph_cloner_run.FuncGraphClonerGraph 55.65% : 0.000305s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.017995 72 0.33% : 0.000060s : 1: add_recomputation 0.39% : 0.000071s : 1: auto_monad 0.10% : 0.000018s : 1: auto_monad_reorder 3.17% : 0.000570s : 1: bootstrap 0.21% : 0.000037s : 1: cconv 0.06% : 0.000011s : 1: convert_after_rewriter 0.14% : 0.000024s : 1: cse_after_recomputation 0.05% : 0.000009s : 1: environ_conv 0.13% : 0.000023s : 1: event_method 0.03% : 0.000006s : 1: expand_dump_flag 0.02% : 0.000004s : 1: get_jit_bprop_graph 0.05% : 0.000009s : 1: graph_reusing 34.39% : 0.006188s : 1: jit_opt_a 0.86% : 0.000155s : 1: jit_opt_after_cconv 0.30% : 0.000054s : 1: jit_opt_b 2.48% : 0.000446s : 1: loop_unroll 3.50% : 0.000630s : 1: mutable_eliminate 3.91% : 0.000703s : 26: opt.transform.jit_opt_a 0.27% : 0.000049s : 4: opt.transform.jit_opt_after_cconv 0.14% : 0.000025s : 4: opt.transform.jit_opt_b 0.08% : 0.000014s : 1: opt.transform.loop_unroll_optimizer 0.10% : 0.000017s : 1: opt.transform.mutable_eliminate 0.12% : 0.000022s : 1: opt.transform.opt_after_jit_grad 0.17% : 0.000031s : 4: opt.transform.symbol_engine_opt 2.68% : 0.000483s : 1: opt_after_jit_grad 0.04% : 0.000008s : 1: order_py_execute_after_rewriter 0.02% : 0.000004s : 1: partial_unused_args_eliminate 0.02% : 0.000004s : 1: pre_auto_parallel 0.17% : 0.000030s : 1: py_interpret_to_execute 0.09% : 0.000017s : 1: py_interpret_to_execute_after_opt_a 0.10% : 0.000017s : 1: remove_dup_value 2.19% : 0.000395s : 1: renormalize.infer 2.01% : 0.000361s : 1: renormalize.specialize 0.04% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.24% : 0.000044s : 1: rewriter_after_opt_a 0.33% : 0.000059s : 1: rewriter_before_opt_a 0.42% : 0.000076s : 1: symbol_engine_optimizer 40.63% : 0.007312s : 1: type_inference ........[WARNING] ME(170331:281473334710064,MainProcess):2026-01-29-17:43:37.812.364 [mindspore/graph/api.py:128] The function "square_backward_func" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/utils/test_utils.py", line 49 has been compiled again. Try to reuse the function object decorated by @jit to reduce the compile time. For more details, get instructions about `jit` at https://www.mindspore.cn/search?inputValue=jit. TotalTime = 0.343253, [30] [bootstrap]: 0.00057542 [type_inference]: 0.285731 [event_method]: 0.00017675 [auto_monad]: 0.00020287 [graph_reusing]: 1.03e-05 [pre_auto_parallel]: 3.99002e-06 [py_interpret_to_execute]: 5.092e-05 [rewriter_before_opt_a]: 0.00014911 [expand_dump_flag]: 4.1e-06 [jit_opt_a]: 0.0536091, [3] [Cycle 1]: 0.0419049, [27] [switch_simplify]: 0.00023889 [loop_unroll]: 6.507e-05 [a_1]: 0.0336641 [with_stream_mark]: 4.566e-05 [recompute_prepare]: 3.045e-05 [updatestate_depend_eliminate]: 9.72999e-06 [updatestate_assign_eliminate]: 7.18e-06 [updatestate_loads_eliminate]: 6.83e-06 [parameter_eliminate]: 4.07998e-06 [specialize_transform]: 1.608e-05 [updatestate_useless_node_eliminater]: 1.5e-05 [accelerated_algorithm]: 1.522e-05 [meta_shard_fg_expand]: 9.67999e-06 [get_grad_eliminate_]: 1.544e-05 [merge_forward]: 9.86e-06 [cell_reuse_recompute_pass]: 1.46002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.448e-05 [j_node_and_user_rematch]: 2.812e-05 [meta_fg_expand]: 0.00244027 [replace_old_param]: 7.906e-05 [inline_without_move]: 7.166e-05 [renormalize]: 0.0041972 [add_forward_monad_depend]: 1.77e-05 [auto_monad_grad]: 7.5e-06 [auto_monad_eliminator]: 6.796e-05 [cse]: 0.000288 [replace_applicator]: 9.922e-05 [Cycle 2]: 0.00328806, [27] [switch_simplify]: 4.117e-05 [loop_unroll]: 3.941e-05 [a_1]: 0.0016746 [with_stream_mark]: 2.674e-05 [recompute_prepare]: 1.365e-05 [updatestate_depend_eliminate]: 6.17999e-06 [updatestate_assign_eliminate]: 4.15e-06 [updatestate_loads_eliminate]: 3.57002e-06 [parameter_eliminate]: 3.16001e-06 [specialize_transform]: 7.41999e-06 [updatestate_useless_node_eliminater]: 7.41001e-06 [accelerated_algorithm]: 7.77e-06 [meta_shard_fg_expand]: 3.38e-06 [get_grad_eliminate_]: 7.29001e-06 [merge_forward]: 4.33001e-06 [cell_reuse_recompute_pass]: 2.06e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.847e-05 [j_node_and_user_rematch]: 1.189e-05 [meta_fg_expand]: 0.00010348 [replace_old_param]: 1.388e-05 [inline_without_move]: 6.93998e-06 [renormalize]: 0.00100463 [add_forward_monad_depend]: 7.58001e-06 [auto_monad_grad]: 2.24001e-06 [auto_monad_eliminator]: 1.992e-05 [cse]: 3.597e-05 [replace_applicator]: 1.745e-05 [Cycle 3]: 0.00048712, [27] [switch_simplify]: 8.15999e-06 [loop_unroll]: 6.48e-06 [a_1]: 0.00014532 [with_stream_mark]: 5.683e-05 [recompute_prepare]: 7.2e-06 [updatestate_depend_eliminate]: 4.55001e-06 [updatestate_assign_eliminate]: 3.24001e-06 [updatestate_loads_eliminate]: 2.78998e-06 [parameter_eliminate]: 1.77999e-06 [specialize_transform]: 7.88001e-06 [updatestate_useless_node_eliminater]: 6.65998e-06 [accelerated_algorithm]: 6.76999e-06 [meta_shard_fg_expand]: 2.37999e-06 [get_grad_eliminate_]: 6.35002e-06 [merge_forward]: 3.66999e-06 [cell_reuse_recompute_pass]: 2.58e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.739e-05 [j_node_and_user_rematch]: 1.181e-05 [meta_fg_expand]: 2.73998e-06 [replace_old_param]: 9.17999e-06 [inline_without_move]: 6.98998e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.15002e-06 [auto_monad_grad]: 1.02998e-06 [auto_monad_eliminator]: 9.17001e-06 [cse]: 2.227e-05 [replace_applicator]: 7.34002e-06 [py_interpret_to_execute_after_opt_a]: 1.874e-05 [rewriter_after_opt_a]: 4.843e-05 [convert_after_rewriter]: 9.14e-06 [order_py_execute_after_rewriter]: 5.99e-06 [mutable_eliminate]: 0.00080431 [jit_opt_b]: 6.367e-05, [1] [Cycle 1]: 5.465e-05, [2] [frontend_op_eliminate]: 2.138e-05 [inline_after_opt_a]: 2.114e-05 [cconv]: 3.246e-05 [loop_unroll]: 0.00045898 [jit_opt_after_cconv]: 0.00019153, [1] [Cycle 1]: 0.00018418, [11] [c_1]: 3.047e-05 [parameter_eliminate]: 4e-06 [updatestate_depend_eliminate]: 8.78001e-06 [updatestate_assign_eliminate]: 3.48e-06 [updatestate_loads_eliminate]: 2.91e-06 [cse]: 3.321e-05 [call_graph_tuple_transform]: 2.749e-05 [tuple_list_get_item_eliminator]: 7.47002e-06 [none_parameter_eliminate]: 1.62001e-06 [renormalize]: 5.3001e-07 [switch_simplify]: 7.79002e-06 [remove_dup_value]: 2.027e-05 [partial_unused_args_eliminate]: 2.23998e-06 [environ_conv]: 7.93999e-06 [add_recomputation]: 6.371e-05 [cse_after_recomputation]: 5.031e-05, [1] [Cycle 1]: 2.353e-05, [1] [cse]: 1.65e-05 [auto_monad_reorder]: 2.266e-05 [get_jit_bprop_graph]: 2.17999e-06 [rewriter_after_jit_bprop_graph]: 8.64e-06 [opt_after_jit_grad]: 0.00054384 [symbol_engine_optimizer]: 9.56e-05, [1] [Cycle 1]: 8.793e-05, [6] [build]: 5.96e-06 [elim_shapecalc]: 1.099e-05 [elim_not_effective]: 1.84e-05 [opt_reshape]: 8.27998e-06 [fold_const_symbol]: 1.232e-05 [renormalize]: 4.89992e-07 [validate]: 5.1e-05 Sums bootstrap : 0.000575s : 0.17% type_inference : 0.285731s : 85.50% event_method : 0.000177s : 0.05% auto_monad : 0.000203s : 0.06% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000051s : 0.02% rewriter_before_opt_a : 0.000149s : 0.04% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000288s : 0.09% jit_opt_a.loop_unroll : 0.000111s : 0.03% jit_opt_a.a_1 : 0.035484s : 10.62% jit_opt_a.with_stream_mark : 0.000129s : 0.04% jit_opt_a.recompute_prepare : 0.000051s : 0.02% jit_opt_a.updatestate_depend_eliminate : 0.000020s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000013s : 0.00% jit_opt_a.parameter_eliminate : 0.000009s : 0.00% jit_opt_a.specialize_transform : 0.000031s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000029s : 0.01% jit_opt_a.accelerated_algorithm : 0.000030s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000015s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000029s : 0.01% jit_opt_a.merge_forward : 0.000018s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000070s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000052s : 0.02% jit_opt_a.meta_fg_expand : 0.002546s : 0.76% jit_opt_a.replace_old_param : 0.000102s : 0.03% jit_opt_a.inline_without_move : 0.000086s : 0.03% jit_opt_a.renormalize : 0.005202s : 1.56% jit_opt_a.add_forward_monad_depend : 0.000027s : 0.01% jit_opt_a.auto_monad_grad : 0.000011s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000097s : 0.03% jit_opt_a.cse : 0.000346s : 0.10% jit_opt_a.replace_applicator : 0.000124s : 0.04% py_interpret_to_execute_after_opt_a : 0.000019s : 0.01% rewriter_after_opt_a : 0.000048s : 0.01% convert_after_rewriter : 0.000009s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000804s : 0.24% jit_opt_b.frontend_op_eliminate : 0.000021s : 0.01% jit_opt_b.inline_after_opt_a : 0.000021s : 0.01% cconv : 0.000032s : 0.01% loop_unroll : 0.000459s : 0.14% jit_opt_after_cconv.c_1 : 0.000030s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000033s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000027s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000007s : 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 : 0.000008s : 0.00% remove_dup_value : 0.000020s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000008s : 0.00% add_recomputation : 0.000064s : 0.02% cse_after_recomputation.cse : 0.000017s : 0.00% auto_monad_reorder : 0.000023s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000544s : 0.16% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000018s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000012s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000051s : 0.02% Time group info: ------[substitution.] 0.001169 125 9.04% : 0.000106s : 3: substitution.arithmetic_simplify 0.23% : 0.000003s : 3: substitution.elim_not_effective 0.15% : 0.000002s : 3: substitution.fold_const_symbol 0.60% : 0.000007s : 4: substitution.graph_param_transform 65.08% : 0.000760s : 18: substitution.inline 2.56% : 0.000030s : 2: substitution.inline_without_move 1.03% : 0.000012s : 14: substitution.j_node_and_user_rematch 1.33% : 0.000016s : 7: substitution.minmaximum_grad 1.27% : 0.000015s : 10: substitution.partial_eliminate 1.19% : 0.000014s : 14: substitution.remove_not_recompute_node 3.26% : 0.000038s : 9: substitution.replace_applicator 0.87% : 0.000010s : 7: substitution.replace_old_param 0.29% : 0.000003s : 1: substitution.set_cell_output_no_recompute 1.32% : 0.000015s : 3: substitution.switch_simplify 4.38% : 0.000051s : 7: substitution.tuple_list_convert_item_index_to_positive 2.04% : 0.000024s : 7: substitution.tuple_list_get_item_depend_reorder 5.39% : 0.000063s : 13: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.285594 2 44.28% : 0.126465s : 1: type_inference.infer 55.72% : 0.159129s : 1: type_inference.specialize ------[replace.] 0.000391 28 1.84% : 0.000007s : 1: replace.arithmetic_simplify 60.52% : 0.000236s : 18: replace.inline 21.00% : 0.000082s : 3: replace.switch_simplify 16.64% : 0.000065s : 6: replace.tuple_list_get_item_eliminator ------[match.] 0.000868 28 9.38% : 0.000081s : 1: match.arithmetic_simplify 85.99% : 0.000746s : 18: match.inline 1.58% : 0.000014s : 3: match.switch_simplify 3.06% : 0.000027s : 6: match.tuple_list_get_item_eliminator ------[predicate.] 0.000512 2877 1.40% : 0.000007s : 48: predicate.accumulaten_eliminater 0.46% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 1.26% : 0.000006s : 48: predicate.addn_check_dump 1.36% : 0.000007s : 48: predicate.addn_zero_filter 2.39% : 0.000012s : 49: predicate.arithmetic_simplify 1.40% : 0.000007s : 49: predicate.cast_eliminate 0.14% : 0.000001s : 4: predicate.check_bprop_eliminate 1.35% : 0.000007s : 48: predicate.compare_switch_simplify 1.26% : 0.000006s : 48: predicate.depend_value_elim 1.41% : 0.000007s : 49: predicate.dict_get_item_const_eliminator 1.62% : 0.000008s : 49: predicate.dict_get_item_eliminator 1.39% : 0.000007s : 49: predicate.dict_set_item_eliminator 0.31% : 0.000002s : 4: predicate.dumpgradient_eliminate 0.10% : 0.000001s : 4: predicate.elim_not_effective 0.23% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.33% : 0.000007s : 49: predicate.environ_add_const_eliminate 1.34% : 0.000007s : 49: predicate.environ_get_add_eliminate 1.22% : 0.000006s : 49: predicate.environ_get_depend_swap 1.46% : 0.000007s : 49: predicate.environ_get_eliminate 1.25% : 0.000006s : 49: predicate.environ_get_set_eliminate 0.07% : 0.000000s : 4: predicate.fold_const_symbol 0.78% : 0.000004s : 19: predicate.get_grad_eliminate 0.08% : 0.000000s : 4: predicate.graph_param_transform 4.99% : 0.000026s : 81: predicate.inline 1.74% : 0.000009s : 40: predicate.inline_without_move 0.27% : 0.000001s : 19: predicate.j_node_and_user_rematch 0.99% : 0.000005s : 19: predicate.less_batch_normalization 1.65% : 0.000008s : 55: predicate.list_to_tuple_eliminator_ 1.93% : 0.000010s : 59: predicate.load_eliminater 0.44% : 0.000002s : 4: predicate.loop_unroll_after_grad 3.53% : 0.000018s : 104: predicate.loop_unroll_before_grad 6.26% : 0.000032s : 53: predicate.make_slice_get_slice_eliminator 1.26% : 0.000006s : 48: predicate.merge_addn 1.33% : 0.000007s : 49: predicate.minmaximum_grad 0.53% : 0.000003s : 4: predicate.mutable_eliminate 0.12% : 0.000001s : 4: predicate.opt_reshape 2.22% : 0.000011s : 59: predicate.partial_eliminate 1.25% : 0.000006s : 48: predicate.print_const_string_wrapper 1.92% : 0.000010s : 49: predicate.reduce_eliminate 1.55% : 0.000008s : 55: predicate.redundant_stop_gradient_eliminater 0.37% : 0.000002s : 19: predicate.remove_not_recompute_node 2.15% : 0.000011s : 103: predicate.replace_applicator 0.82% : 0.000004s : 40: predicate.replace_old_param 0.10% : 0.000000s : 4: predicate.reset_defer_inline 1.33% : 0.000007s : 49: predicate.reshape_eliminate 1.51% : 0.000008s : 48: predicate.row_tensor_add_zeros_like 0.21% : 0.000001s : 4: predicate.row_tensor_eliminate 1.36% : 0.000007s : 48: predicate.same_eliminate 0.46% : 0.000002s : 19: predicate.set_cell_output_no_recompute 0.32% : 0.000002s : 8: predicate.special_op_eliminate 0.81% : 0.000004s : 19: predicate.specialize_transform 1.62% : 0.000008s : 48: predicate.split_environ_get_set_with_tuple_value 1.36% : 0.000007s : 48: predicate.stack_unstack_eliminate 0.16% : 0.000001s : 4: predicate.switch_call_monad_eliminater 3.48% : 0.000018s : 73: predicate.switch_defer_inline 2.54% : 0.000013s : 73: predicate.switch_layer_defer_inline 6.57% : 0.000034s : 187: predicate.switch_simplify 1.39% : 0.000007s : 49: predicate.tile_eliminate 1.46% : 0.000007s : 49: predicate.transpose_eliminate 2.56% : 0.000013s : 49: predicate.tuple_list_convert_item_index_to_positive 1.51% : 0.000008s : 49: predicate.tuple_list_get_item_depend_reorder 3.06% : 0.000016s : 63: predicate.tuple_list_get_item_eliminator 1.75% : 0.000009s : 49: predicate.tuple_list_set_item_eliminator 1.56% : 0.000008s : 55: predicate.tuple_to_list_eliminator_ 1.49% : 0.000008s : 59: predicate.updatestate_pure_node_eliminater 2.47% : 0.000013s : 78: predicate.updatestate_useless_node_eliminater 1.65% : 0.000008s : 48: predicate.value_based_eliminate 0.12% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.19% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.158949 34 1.03% : 0.001637s : 12: func_graph_cloner_run.FuncGraphClonerGraph 98.97% : 0.157312s : 22: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.384945 87 0.02% : 0.000067s : 1: add_recomputation 0.06% : 0.000212s : 1: auto_monad 0.01% : 0.000026s : 1: auto_monad_reorder 0.16% : 0.000606s : 1: bootstrap 0.01% : 0.000035s : 1: cconv 0.00% : 0.000012s : 1: convert_after_rewriter 0.01% : 0.000053s : 1: cse_after_recomputation 0.00% : 0.000010s : 1: environ_conv 0.05% : 0.000186s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000013s : 1: graph_reusing 13.93% : 0.053613s : 1: jit_opt_a 0.05% : 0.000194s : 1: jit_opt_after_cconv 0.02% : 0.000066s : 1: jit_opt_b 0.12% : 0.000469s : 1: loop_unroll 0.21% : 0.000815s : 1: mutable_eliminate 9.46% : 0.036418s : 39: opt.transform.jit_opt_a 0.02% : 0.000069s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000036s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.01% : 0.000030s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000045s : 4: opt.transform.symbol_engine_opt 0.14% : 0.000555s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000054s : 1: py_interpret_to_execute 0.01% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000023s : 1: remove_dup_value 0.76% : 0.002917s : 2: renormalize.infer 0.59% : 0.002260s : 2: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000052s : 1: rewriter_after_opt_a 0.04% : 0.000153s : 1: rewriter_before_opt_a 0.03% : 0.000099s : 1: symbol_engine_optimizer 74.23% : 0.285761s : 1: type_inference ........ [hook] pytest_runtest_teardown:test_square_normal[GE] tests/st/ops/test_ops_square.py::test_square_normal[GE],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") test_ops_square.py::test_square_normal[GE] /usr/local/Ascend/cann-8.5.0/python/site-packages/asc_op_compile_base/asc_op_compiler/ascendc_compile_gen_code.py:161: DeprecationWarning: invalid escape sequence \w match = re.search(f'{option}=(\w+)', ' '.join(compile_options)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 3 passed, 26 warnings in 472.26s (0:07:52) ==================