==================================================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_001/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_addmm.py . [hook] pytest_runtest_teardown:test_addmm_normal[pynative] tests/st/mint/test_addmm.py::test_addmm_normal[pynative],max_mem:2.0M TotalTime = 0.45087, [30] [bootstrap]: 0.00086315 [type_inference]: 0.325605 [event_method]: 2.519e-05 [auto_monad]: 0.00011205 [graph_reusing]: 6.33e-06 [pre_auto_parallel]: 1.201e-05 [py_interpret_to_execute]: 0.00015505 [rewriter_before_opt_a]: 9.584e-05 [expand_dump_flag]: 3.68e-06 [jit_opt_a]: 0.121033, [2] [Cycle 1]: 0.00260924, [27] [switch_simplify]: 7.473e-05 [loop_unroll]: 2.93e-05 [a_1]: 0.00060695 [with_stream_mark]: 3.174e-05 [recompute_prepare]: 1.051e-05 [updatestate_depend_eliminate]: 5.20001e-06 [updatestate_assign_eliminate]: 3.83999e-06 [updatestate_loads_eliminate]: 3.69002e-06 [parameter_eliminate]: 2.49001e-06 [specialize_transform]: 8.95001e-06 [updatestate_useless_node_eliminater]: 7.06001e-06 [accelerated_algorithm]: 7.58001e-06 [meta_shard_fg_expand]: 2.84001e-06 [get_grad_eliminate_]: 6.97002e-06 [merge_forward]: 4.18999e-06 [cell_reuse_recompute_pass]: 1.59e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.232e-05 [j_node_and_user_rematch]: 1.287e-05 [meta_fg_expand]: 3.18e-06 [replace_old_param]: 1.484e-05 [inline_without_move]: 7.78001e-06 [renormalize]: 0.00125654 [add_forward_monad_depend]: 8.276e-05 [auto_monad_grad]: 3.03998e-06 [auto_monad_eliminator]: 1.899e-05 [cse]: 0.00012931 [replace_applicator]: 1.983e-05 [Cycle 2]: 0.00043289, [27] [switch_simplify]: 8.52e-06 [loop_unroll]: 6.78e-06 [a_1]: 0.00014516 [with_stream_mark]: 1.458e-05 [recompute_prepare]: 7.16001e-06 [updatestate_depend_eliminate]: 4.55999e-06 [updatestate_assign_eliminate]: 3.19001e-06 [updatestate_loads_eliminate]: 3.05002e-06 [parameter_eliminate]: 1.34998e-06 [specialize_transform]: 7.38999e-06 [updatestate_useless_node_eliminater]: 7.01001e-06 [accelerated_algorithm]: 6.91999e-06 [meta_shard_fg_expand]: 1.91e-06 [get_grad_eliminate_]: 6.65002e-06 [merge_forward]: 4.15e-06 [cell_reuse_recompute_pass]: 1.94e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.742e-05 [j_node_and_user_rematch]: 1.038e-05 [meta_fg_expand]: 2.46998e-06 [replace_old_param]: 1.225e-05 [inline_without_move]: 6.46999e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.30999e-06 [auto_monad_grad]: 1.04e-06 [auto_monad_eliminator]: 8.50999e-06 [cse]: 1.704e-05 [replace_applicator]: 7.09001e-06 [py_interpret_to_execute_after_opt_a]: 1.708e-05 [rewriter_after_opt_a]: 0.00012233 [convert_after_rewriter]: 1.17e-05 [order_py_execute_after_rewriter]: 6.43e-06 [mutable_eliminate]: 0.00068273 [jit_opt_b]: 6.49e-05, [1] [Cycle 1]: 5.627e-05, [2] [frontend_op_eliminate]: 2.23e-05 [inline_after_opt_a]: 2.155e-05 [cconv]: 3.19e-05 [loop_unroll]: 0.00044825 [jit_opt_after_cconv]: 0.00019008, [1] [Cycle 1]: 0.00018272, [11] [c_1]: 3.077e-05 [parameter_eliminate]: 3.38e-06 [updatestate_depend_eliminate]: 9.96e-06 [updatestate_assign_eliminate]: 3.38e-06 [updatestate_loads_eliminate]: 2.93e-06 [cse]: 3.464e-05 [call_graph_tuple_transform]: 2.641e-05 [tuple_list_get_item_eliminator]: 7.71999e-06 [none_parameter_eliminate]: 1.91e-06 [renormalize]: 5.40022e-07 [switch_simplify]: 7.2e-06 [remove_dup_value]: 4.78e-05 [partial_unused_args_eliminate]: 3.22002e-06 [environ_conv]: 2.33e-05 [add_recomputation]: 6.481e-05 [cse_after_recomputation]: 3.043e-05, [1] [Cycle 1]: 2.353e-05, [1] [cse]: 1.67e-05 [auto_monad_reorder]: 2.819e-05 [get_jit_bprop_graph]: 2.51e-06 [rewriter_after_jit_bprop_graph]: 0.0001246 [opt_after_jit_grad]: 0.00051353 [symbol_engine_optimizer]: 8.937e-05, [1] [Cycle 1]: 8.19e-05, [6] [build]: 5.09e-06 [elim_shapecalc]: 1.014e-05 [elim_not_effective]: 1.545e-05 [opt_reshape]: 8.26002e-06 [fold_const_symbol]: 1.133e-05 [renormalize]: 5.19998e-07 [validate]: 6.536e-05 Sums bootstrap : 0.000863s : 0.26% type_inference : 0.325605s : 98.07% event_method : 0.000025s : 0.01% auto_monad : 0.000112s : 0.03% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000155s : 0.05% rewriter_before_opt_a : 0.000096s : 0.03% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000083s : 0.03% jit_opt_a.loop_unroll : 0.000036s : 0.01% jit_opt_a.a_1 : 0.000752s : 0.23% jit_opt_a.with_stream_mark : 0.000046s : 0.01% jit_opt_a.recompute_prepare : 0.000018s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000016s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000014s : 0.00% jit_opt_a.accelerated_algorithm : 0.000014s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000014s : 0.00% jit_opt_a.merge_forward : 0.000008s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000040s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000023s : 0.01% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000027s : 0.01% jit_opt_a.inline_without_move : 0.000014s : 0.00% jit_opt_a.renormalize : 0.001257s : 0.38% jit_opt_a.add_forward_monad_depend : 0.000084s : 0.03% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000028s : 0.01% jit_opt_a.cse : 0.000146s : 0.04% jit_opt_a.replace_applicator : 0.000027s : 0.01% py_interpret_to_execute_after_opt_a : 0.000017s : 0.01% rewriter_after_opt_a : 0.000122s : 0.04% convert_after_rewriter : 0.000012s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000683s : 0.21% jit_opt_b.frontend_op_eliminate : 0.000022s : 0.01% jit_opt_b.inline_after_opt_a : 0.000022s : 0.01% cconv : 0.000032s : 0.01% loop_unroll : 0.000448s : 0.14% jit_opt_after_cconv.c_1 : 0.000031s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 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 : 0.000035s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000007s : 0.00% remove_dup_value : 0.000048s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000023s : 0.01% add_recomputation : 0.000065s : 0.02% cse_after_recomputation.cse : 0.000017s : 0.01% auto_monad_reorder : 0.000028s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000125s : 0.04% opt_after_jit_grad : 0.000514s : 0.15% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000015s : 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 : 0.000065s : 0.02% Time group info: ------[substitution.] 0.000244 29 0.97% : 0.000002s : 2: substitution.elim_not_effective 0.63% : 0.000002s : 2: substitution.fold_const_symbol 3.17% : 0.000008s : 5: substitution.graph_param_transform 80.71% : 0.000197s : 3: substitution.inline 1.96% : 0.000005s : 4: substitution.j_node_and_user_rematch 2.19% : 0.000005s : 4: substitution.remove_not_recompute_node 3.57% : 0.000009s : 6: substitution.replace_old_param 6.80% : 0.000017s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.325495 2 99.44% : 0.323664s : 1: type_inference.infer 0.56% : 0.001831s : 1: type_inference.specialize ------[replace.] 0.000064 6 69.43% : 0.000044s : 3: replace.inline 30.57% : 0.000019s : 3: replace.tuple_list_get_item_eliminator ------[match.] 0.000210 6 92.89% : 0.000195s : 3: match.inline 7.11% : 0.000015s : 3: match.tuple_list_get_item_eliminator ------[predicate.] 0.000147 922 1.19% : 0.000002s : 13: predicate.accumulaten_eliminater 1.16% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.07% : 0.000002s : 13: predicate.addn_check_dump 1.21% : 0.000002s : 13: predicate.addn_zero_filter 2.44% : 0.000004s : 13: predicate.arithmetic_simplify 1.10% : 0.000002s : 13: predicate.cast_eliminate 0.55% : 0.000001s : 5: predicate.check_bprop_eliminate 1.06% : 0.000002s : 13: predicate.compare_switch_simplify 1.13% : 0.000002s : 13: predicate.depend_value_elim 1.07% : 0.000002s : 13: predicate.dict_get_item_const_eliminator 1.75% : 0.000003s : 13: predicate.dict_get_item_eliminator 1.25% : 0.000002s : 13: predicate.dict_set_item_eliminator 0.97% : 0.000001s : 5: predicate.dumpgradient_eliminate 0.53% : 0.000001s : 5: predicate.elim_not_effective 0.59% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.11% : 0.000002s : 13: predicate.environ_add_const_eliminate 1.05% : 0.000002s : 13: predicate.environ_get_add_eliminate 0.99% : 0.000001s : 13: predicate.environ_get_depend_swap 1.11% : 0.000002s : 13: predicate.environ_get_eliminate 1.09% : 0.000002s : 13: predicate.environ_get_set_eliminate 0.30% : 0.000000s : 5: predicate.fold_const_symbol 1.32% : 0.000002s : 10: predicate.get_grad_eliminate 0.31% : 0.000000s : 5: predicate.graph_param_transform 6.01% : 0.000009s : 29: predicate.inline 0.99% : 0.000001s : 10: predicate.inline_without_move 0.50% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.25% : 0.000002s : 10: predicate.less_batch_normalization 1.43% : 0.000002s : 16: predicate.list_to_tuple_eliminator_ 1.92% : 0.000003s : 21: predicate.load_eliminater 1.42% : 0.000002s : 5: predicate.loop_unroll_after_grad 3.17% : 0.000005s : 32: predicate.loop_unroll_before_grad 1.86% : 0.000003s : 18: predicate.make_slice_get_slice_eliminator 1.06% : 0.000002s : 13: predicate.merge_addn 1.56% : 0.000002s : 13: predicate.minmaximum_grad 1.75% : 0.000003s : 5: predicate.mutable_eliminate 1.04% : 0.000002s : 5: predicate.opt_reshape 2.53% : 0.000004s : 21: predicate.partial_eliminate 1.11% : 0.000002s : 13: predicate.print_const_string_wrapper 1.45% : 0.000002s : 13: predicate.reduce_eliminate 1.37% : 0.000002s : 16: predicate.redundant_stop_gradient_eliminater 0.90% : 0.000001s : 10: predicate.remove_not_recompute_node 1.91% : 0.000003s : 26: predicate.replace_applicator 0.83% : 0.000001s : 10: predicate.replace_old_param 0.35% : 0.000001s : 5: predicate.reset_defer_inline 1.13% : 0.000002s : 13: predicate.reshape_eliminate 1.25% : 0.000002s : 13: predicate.row_tensor_add_zeros_like 0.78% : 0.000001s : 5: predicate.row_tensor_eliminate 1.09% : 0.000002s : 13: predicate.same_eliminate 0.67% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.21% : 0.000002s : 10: predicate.special_op_eliminate 1.21% : 0.000002s : 10: predicate.specialize_transform 1.23% : 0.000002s : 13: predicate.split_environ_get_set_with_tuple_value 1.13% : 0.000002s : 13: predicate.stack_unstack_eliminate 0.48% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.29% : 0.000003s : 19: predicate.switch_defer_inline 1.90% : 0.000003s : 19: predicate.switch_layer_defer_inline 7.42% : 0.000011s : 56: predicate.switch_simplify 1.15% : 0.000002s : 13: predicate.tile_eliminate 1.17% : 0.000002s : 13: predicate.transpose_eliminate 1.39% : 0.000002s : 13: predicate.tuple_list_convert_item_index_to_positive 1.20% : 0.000002s : 13: predicate.tuple_list_get_item_depend_reorder 4.23% : 0.000006s : 26: predicate.tuple_list_get_item_eliminator 1.49% : 0.000002s : 13: predicate.tuple_list_set_item_eliminator 1.57% : 0.000002s : 16: predicate.tuple_to_list_eliminator_ 1.66% : 0.000002s : 21: predicate.updatestate_pure_node_eliminater 3.09% : 0.000005s : 31: predicate.updatestate_useless_node_eliminater 1.36% : 0.000002s : 13: predicate.value_based_eliminate 0.45% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.65% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001043 10 54.36% : 0.000567s : 5: func_graph_cloner_run.FuncGraphClonerGraph 45.64% : 0.000476s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.453061 72 0.02% : 0.000068s : 1: add_recomputation 0.03% : 0.000117s : 1: auto_monad 0.01% : 0.000031s : 1: auto_monad_reorder 0.20% : 0.000889s : 1: bootstrap 0.01% : 0.000035s : 1: cconv 0.00% : 0.000014s : 1: convert_after_rewriter 0.01% : 0.000033s : 1: cse_after_recomputation 0.01% : 0.000026s : 1: environ_conv 0.01% : 0.000031s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 26.72% : 0.121038s : 1: jit_opt_a 0.04% : 0.000193s : 1: jit_opt_after_cconv 0.01% : 0.000068s : 1: jit_opt_b 0.10% : 0.000456s : 1: loop_unroll 0.15% : 0.000693s : 1: mutable_eliminate 0.23% : 0.001035s : 26: opt.transform.jit_opt_a 0.02% : 0.000068s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000036s : 4: opt.transform.jit_opt_b 0.00% : 0.000014s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000016s : 1: opt.transform.mutable_eliminate 0.01% : 0.000030s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000042s : 4: opt.transform.symbol_engine_opt 0.12% : 0.000524s : 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% : 0.000014s : 1: pre_auto_parallel 0.04% : 0.000159s : 1: py_interpret_to_execute 0.00% : 0.000019s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000051s : 1: remove_dup_value 0.15% : 0.000699s : 1: renormalize.infer 0.12% : 0.000546s : 1: renormalize.specialize 0.03% : 0.000128s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000127s : 1: rewriter_after_opt_a 0.02% : 0.000101s : 1: rewriter_before_opt_a 0.02% : 0.000092s : 1: symbol_engine_optimizer 71.87% : 0.325631s : 1: type_inference [WARNING] ME(159823:281473136459568,MainProcess):2026-01-29-17:41:16.501.928 [mindspore/graph/api.py:128] The function "addmm_forward_func" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/mint/test_addmm.py", line 51 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 = 0.314017, [30] [bootstrap]: 0.00058042 [type_inference]: 0.218354 [event_method]: 1.956e-05 [auto_monad]: 7.088e-05 [graph_reusing]: 6.44999e-06 [pre_auto_parallel]: 2.46e-06 [py_interpret_to_execute]: 0.00011731 [rewriter_before_opt_a]: 7.868e-05 [expand_dump_flag]: 3.38999e-06 [jit_opt_a]: 0.0918857, [2] [Cycle 1]: 0.00221279, [27] [switch_simplify]: 6.141e-05 [loop_unroll]: 3.022e-05 [a_1]: 0.00057127 [with_stream_mark]: 2.486e-05 [recompute_prepare]: 1.15e-05 [updatestate_depend_eliminate]: 5.66e-06 [updatestate_assign_eliminate]: 3.88999e-06 [updatestate_loads_eliminate]: 3.38999e-06 [parameter_eliminate]: 2.16e-06 [specialize_transform]: 8.48001e-06 [updatestate_useless_node_eliminater]: 7.21999e-06 [accelerated_algorithm]: 8.55001e-06 [meta_shard_fg_expand]: 2.35002e-06 [get_grad_eliminate_]: 7.56999e-06 [merge_forward]: 4.87998e-06 [cell_reuse_recompute_pass]: 1.18001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.872e-05 [j_node_and_user_rematch]: 1.153e-05 [meta_fg_expand]: 3.06999e-06 [replace_old_param]: 1.517e-05 [inline_without_move]: 7.88001e-06 [renormalize]: 0.00109851 [add_forward_monad_depend]: 1.507e-05 [auto_monad_grad]: 3.35998e-06 [auto_monad_eliminator]: 1.916e-05 [cse]: 4.182e-05 [replace_applicator]: 2.068e-05 [Cycle 2]: 0.084895, [27] [switch_simplify]: 8.27e-06 [loop_unroll]: 6.98998e-06 [a_1]: 0.0844086 [with_stream_mark]: 4.139e-05 [recompute_prepare]: 1.711e-05 [updatestate_depend_eliminate]: 5.89e-06 [updatestate_assign_eliminate]: 4.2e-06 [updatestate_loads_eliminate]: 3.52002e-06 [parameter_eliminate]: 3.14999e-06 [specialize_transform]: 8.48999e-06 [updatestate_useless_node_eliminater]: 8.1e-06 [accelerated_algorithm]: 7.86001e-06 [meta_shard_fg_expand]: 3.83001e-06 [get_grad_eliminate_]: 6.31e-06 [merge_forward]: 5.07e-06 [cell_reuse_recompute_pass]: 3.61001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.761e-05 [j_node_and_user_rematch]: 1.185e-05 [meta_fg_expand]: 3.17002e-06 [replace_old_param]: 1.663e-05 [inline_without_move]: 6.54999e-06 [renormalize]: 1.69995e-07 [add_forward_monad_depend]: 4.52e-06 [auto_monad_grad]: 3.95e-06 [auto_monad_eliminator]: 2.103e-05 [cse]: 5.123e-05 [replace_applicator]: 7.51999e-06 [py_interpret_to_execute_after_opt_a]: 2.355e-05 [rewriter_after_opt_a]: 4.8e-05 [convert_after_rewriter]: 9.17999e-06 [order_py_execute_after_rewriter]: 5.52999e-06 [mutable_eliminate]: 0.00082501 [jit_opt_b]: 0.00011898, [1] [Cycle 1]: 0.00010784, [2] [frontend_op_eliminate]: 6.905e-05 [inline_after_opt_a]: 2.374e-05 [cconv]: 4.272e-05 [loop_unroll]: 0.00052909 [jit_opt_after_cconv]: 0.00021292, [1] [Cycle 1]: 0.00020356, [11] [c_1]: 3.399e-05 [parameter_eliminate]: 5.00999e-06 [updatestate_depend_eliminate]: 1.093e-05 [updatestate_assign_eliminate]: 3.61999e-06 [updatestate_loads_eliminate]: 3.34001e-06 [cse]: 4.368e-05 [call_graph_tuple_transform]: 2.959e-05 [tuple_list_get_item_eliminator]: 7.53999e-06 [none_parameter_eliminate]: 1.96998e-06 [renormalize]: 5.79981e-07 [switch_simplify]: 8.42e-06 [remove_dup_value]: 1.964e-05 [partial_unused_args_eliminate]: 2.59999e-06 [environ_conv]: 8.88002e-06 [add_recomputation]: 6.478e-05 [cse_after_recomputation]: 2.994e-05, [1] [Cycle 1]: 2.351e-05, [1] [cse]: 1.696e-05 [auto_monad_reorder]: 1.917e-05 [get_jit_bprop_graph]: 2.00002e-06 [rewriter_after_jit_bprop_graph]: 9.34998e-06 [opt_after_jit_grad]: 0.00055338 [symbol_engine_optimizer]: 9.289e-05, [1] [Cycle 1]: 8.542e-05, [6] [build]: 5.00999e-06 [elim_shapecalc]: 1.134e-05 [elim_not_effective]: 1.749e-05 [opt_reshape]: 7.58001e-06 [fold_const_symbol]: 1.147e-05 [renormalize]: 7.50006e-07 [validate]: 5.1e-05 Sums bootstrap : 0.000580s : 0.19% type_inference : 0.218354s : 70.79% event_method : 0.000020s : 0.01% auto_monad : 0.000071s : 0.02% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000002s : 0.00% py_interpret_to_execute : 0.000117s : 0.04% rewriter_before_opt_a : 0.000079s : 0.03% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000070s : 0.02% jit_opt_a.loop_unroll : 0.000037s : 0.01% jit_opt_a.a_1 : 0.084980s : 27.55% jit_opt_a.with_stream_mark : 0.000066s : 0.02% jit_opt_a.recompute_prepare : 0.000029s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000017s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000015s : 0.00% jit_opt_a.accelerated_algorithm : 0.000016s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000014s : 0.00% jit_opt_a.merge_forward : 0.000010s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000046s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000023s : 0.01% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000032s : 0.01% jit_opt_a.inline_without_move : 0.000014s : 0.00% jit_opt_a.renormalize : 0.001099s : 0.36% jit_opt_a.add_forward_monad_depend : 0.000020s : 0.01% jit_opt_a.auto_monad_grad : 0.000007s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000040s : 0.01% jit_opt_a.cse : 0.000093s : 0.03% jit_opt_a.replace_applicator : 0.000028s : 0.01% py_interpret_to_execute_after_opt_a : 0.000024s : 0.01% rewriter_after_opt_a : 0.000048s : 0.02% convert_after_rewriter : 0.000009s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000825s : 0.27% jit_opt_b.frontend_op_eliminate : 0.000069s : 0.02% jit_opt_b.inline_after_opt_a : 0.000024s : 0.01% cconv : 0.000043s : 0.01% loop_unroll : 0.000529s : 0.17% jit_opt_after_cconv.c_1 : 0.000034s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000044s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000008s : 0.00% remove_dup_value : 0.000020s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000009s : 0.00% add_recomputation : 0.000065s : 0.02% cse_after_recomputation.cse : 0.000017s : 0.01% auto_monad_reorder : 0.000019s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000553s : 0.18% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000017s : 0.01% 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 : 0.000051s : 0.02% Time group info: ------[substitution.] 0.000210 29 1.13% : 0.000002s : 2: substitution.elim_not_effective 0.75% : 0.000002s : 2: substitution.fold_const_symbol 3.46% : 0.000007s : 5: substitution.graph_param_transform 77.04% : 0.000162s : 3: substitution.inline 2.09% : 0.000004s : 4: substitution.j_node_and_user_rematch 2.58% : 0.000005s : 4: substitution.remove_not_recompute_node 5.36% : 0.000011s : 6: substitution.replace_old_param 7.59% : 0.000016s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.218250 2 99.32% : 0.216764s : 1: type_inference.infer 0.68% : 0.001485s : 1: type_inference.specialize ------[replace.] 0.000059 6 69.28% : 0.000041s : 3: replace.inline 30.72% : 0.000018s : 3: replace.tuple_list_get_item_eliminator ------[match.] 0.000173 6 91.76% : 0.000159s : 3: match.inline 8.24% : 0.000014s : 3: match.tuple_list_get_item_eliminator ------[predicate.] 0.084347 922 0.00% : 0.000002s : 13: predicate.accumulaten_eliminater 0.00% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 0.00% : 0.000002s : 13: predicate.addn_check_dump 0.00% : 0.000002s : 13: predicate.addn_zero_filter 0.00% : 0.000003s : 13: predicate.arithmetic_simplify 0.00% : 0.000002s : 13: predicate.cast_eliminate 0.00% : 0.000001s : 5: predicate.check_bprop_eliminate 0.00% : 0.000002s : 13: predicate.compare_switch_simplify 0.00% : 0.000002s : 13: predicate.depend_value_elim 0.00% : 0.000002s : 13: predicate.dict_get_item_const_eliminator 0.00% : 0.000002s : 13: predicate.dict_get_item_eliminator 0.00% : 0.000002s : 13: predicate.dict_set_item_eliminator 0.00% : 0.000001s : 5: predicate.dumpgradient_eliminate 0.00% : 0.000001s : 5: predicate.elim_not_effective 0.00% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 0.00% : 0.000002s : 13: predicate.environ_add_const_eliminate 0.01% : 0.000006s : 13: predicate.environ_get_add_eliminate 0.00% : 0.000002s : 13: predicate.environ_get_depend_swap 99.80% : 0.084180s : 13: predicate.environ_get_eliminate 0.00% : 0.000002s : 13: predicate.environ_get_set_eliminate 0.00% : 0.000000s : 5: predicate.fold_const_symbol 0.00% : 0.000002s : 10: predicate.get_grad_eliminate 0.00% : 0.000000s : 5: predicate.graph_param_transform 0.01% : 0.000011s : 29: predicate.inline 0.00% : 0.000002s : 10: predicate.inline_without_move 0.00% : 0.000001s : 10: predicate.j_node_and_user_rematch 0.00% : 0.000003s : 10: predicate.less_batch_normalization 0.00% : 0.000003s : 16: predicate.list_to_tuple_eliminator_ 0.00% : 0.000003s : 21: predicate.load_eliminater 0.00% : 0.000002s : 5: predicate.loop_unroll_after_grad 0.01% : 0.000005s : 32: predicate.loop_unroll_before_grad 0.00% : 0.000003s : 18: predicate.make_slice_get_slice_eliminator 0.00% : 0.000002s : 13: predicate.merge_addn 0.00% : 0.000002s : 13: predicate.minmaximum_grad 0.00% : 0.000003s : 5: predicate.mutable_eliminate 0.00% : 0.000001s : 5: predicate.opt_reshape 0.00% : 0.000004s : 21: predicate.partial_eliminate 0.00% : 0.000002s : 13: predicate.print_const_string_wrapper 0.00% : 0.000003s : 13: predicate.reduce_eliminate 0.00% : 0.000003s : 16: predicate.redundant_stop_gradient_eliminater 0.00% : 0.000002s : 10: predicate.remove_not_recompute_node 0.00% : 0.000003s : 26: predicate.replace_applicator 0.00% : 0.000001s : 10: predicate.replace_old_param 0.00% : 0.000001s : 5: predicate.reset_defer_inline 0.00% : 0.000003s : 13: predicate.reshape_eliminate 0.00% : 0.000002s : 13: predicate.row_tensor_add_zeros_like 0.00% : 0.000002s : 5: predicate.row_tensor_eliminate 0.00% : 0.000002s : 13: predicate.same_eliminate 0.00% : 0.000001s : 10: predicate.set_cell_output_no_recompute 0.00% : 0.000001s : 10: predicate.special_op_eliminate 0.00% : 0.000002s : 10: predicate.specialize_transform 0.00% : 0.000002s : 13: predicate.split_environ_get_set_with_tuple_value 0.00% : 0.000002s : 13: predicate.stack_unstack_eliminate 0.00% : 0.000001s : 5: predicate.switch_call_monad_eliminater 0.00% : 0.000004s : 19: predicate.switch_defer_inline 0.00% : 0.000003s : 19: predicate.switch_layer_defer_inline 0.01% : 0.000011s : 56: predicate.switch_simplify 0.00% : 0.000002s : 13: predicate.tile_eliminate 0.00% : 0.000002s : 13: predicate.transpose_eliminate 0.00% : 0.000002s : 13: predicate.tuple_list_convert_item_index_to_positive 0.00% : 0.000002s : 13: predicate.tuple_list_get_item_depend_reorder 0.01% : 0.000006s : 26: predicate.tuple_list_get_item_eliminator 0.00% : 0.000003s : 13: predicate.tuple_list_set_item_eliminator 0.00% : 0.000003s : 16: predicate.tuple_to_list_eliminator_ 0.00% : 0.000003s : 21: predicate.updatestate_pure_node_eliminater 0.01% : 0.000005s : 31: predicate.updatestate_useless_node_eliminater 0.00% : 0.000004s : 13: predicate.value_based_eliminate 0.00% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.00% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000933 10 55.47% : 0.000517s : 5: func_graph_cloner_run.FuncGraphClonerGraph 44.53% : 0.000415s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.400537 72 0.02% : 0.000068s : 1: add_recomputation 0.02% : 0.000075s : 1: auto_monad 0.01% : 0.000022s : 1: auto_monad_reorder 0.15% : 0.000607s : 1: bootstrap 0.01% : 0.000046s : 1: cconv 0.00% : 0.000012s : 1: convert_after_rewriter 0.01% : 0.000032s : 1: cse_after_recomputation 0.00% : 0.000011s : 1: environ_conv 0.01% : 0.000024s : 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 22.94% : 0.091891s : 1: jit_opt_a 0.05% : 0.000216s : 1: jit_opt_after_cconv 0.03% : 0.000123s : 1: jit_opt_b 0.13% : 0.000540s : 1: loop_unroll 0.21% : 0.000839s : 1: mutable_eliminate 21.29% : 0.085281s : 26: opt.transform.jit_opt_a 0.02% : 0.000075s : 4: opt.transform.jit_opt_after_cconv 0.02% : 0.000084s : 4: opt.transform.jit_opt_b 0.00% : 0.000019s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000020s : 1: opt.transform.mutable_eliminate 0.01% : 0.000029s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000044s : 4: opt.transform.symbol_engine_opt 0.14% : 0.000563s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pre_auto_parallel 0.03% : 0.000121s : 1: py_interpret_to_execute 0.01% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000022s : 1: remove_dup_value 0.15% : 0.000584s : 1: renormalize.infer 0.13% : 0.000504s : 1: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000052s : 1: rewriter_after_opt_a 0.02% : 0.000083s : 1: rewriter_before_opt_a 0.02% : 0.000096s : 1: symbol_engine_optimizer 54.52% : 0.218379s : 1: type_inference TotalTime = 0.759796, [30] [bootstrap]: 0.00038036 [type_inference]: 0.491151 [event_method]: 0.00011893 [auto_monad]: 0.00018521 [graph_reusing]: 1.111e-05 [pre_auto_parallel]: 4.08999e-06 [py_interpret_to_execute]: 6.534e-05 [rewriter_before_opt_a]: 0.00022298 [expand_dump_flag]: 4.68001e-06 [jit_opt_a]: 0.263943, [3] [Cycle 1]: 0.254149, [27] [switch_simplify]: 0.00029881 [loop_unroll]: 8.536e-05 [a_1]: 0.00221761 [with_stream_mark]: 4.837e-05 [recompute_prepare]: 3.516e-05 [updatestate_depend_eliminate]: 1.36e-05 [updatestate_assign_eliminate]: 9.97001e-06 [updatestate_loads_eliminate]: 9.79e-06 [parameter_eliminate]: 4.23999e-06 [specialize_transform]: 2.33e-05 [updatestate_useless_node_eliminater]: 2.206e-05 [accelerated_algorithm]: 4.197e-05 [meta_shard_fg_expand]: 9.39e-06 [get_grad_eliminate_]: 1.985e-05 [merge_forward]: 1.187e-05 [cell_reuse_recompute_pass]: 1.35001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.856e-05 [j_node_and_user_rematch]: 3.426e-05 [meta_fg_expand]: 0.136005 [replace_old_param]: 0.00013652 [inline_without_move]: 8.77e-05 [renormalize]: 0.113961 [add_forward_monad_depend]: 2.408e-05 [auto_monad_grad]: 8.89998e-06 [auto_monad_eliminator]: 8.503e-05 [cse]: 0.00043006 [replace_applicator]: 0.00011659 [Cycle 2]: 0.00500213, [27] [switch_simplify]: 5.301e-05 [loop_unroll]: 5.083e-05 [a_1]: 0.00175561 [with_stream_mark]: 3.245e-05 [recompute_prepare]: 1.663e-05 [updatestate_depend_eliminate]: 7.53e-06 [updatestate_assign_eliminate]: 5.27001e-06 [updatestate_loads_eliminate]: 4.75999e-06 [parameter_eliminate]: 2.44999e-06 [specialize_transform]: 1.19e-05 [updatestate_useless_node_eliminater]: 9.52999e-06 [accelerated_algorithm]: 1.9e-05 [meta_shard_fg_expand]: 4.22e-06 [get_grad_eliminate_]: 1.29e-05 [merge_forward]: 6.58e-06 [cell_reuse_recompute_pass]: 1.40001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.253e-05 [j_node_and_user_rematch]: 1.571e-05 [meta_fg_expand]: 0.00033048 [replace_old_param]: 2.822e-05 [inline_without_move]: 1.013e-05 [renormalize]: 0.00210332 [add_forward_monad_depend]: 1.318e-05 [auto_monad_grad]: 2.55002e-06 [auto_monad_eliminator]: 2.687e-05 [cse]: 0.00017179 [replace_applicator]: 3.374e-05 [Cycle 3]: 0.00060849, [27] [switch_simplify]: 1.191e-05 [loop_unroll]: 9.68002e-06 [a_1]: 0.00020003 [with_stream_mark]: 2.222e-05 [recompute_prepare]: 9.97001e-06 [updatestate_depend_eliminate]: 6.43e-06 [updatestate_assign_eliminate]: 4.99e-06 [updatestate_loads_eliminate]: 4.70001e-06 [parameter_eliminate]: 2.49999e-06 [specialize_transform]: 8.94998e-06 [updatestate_useless_node_eliminater]: 8.77999e-06 [accelerated_algorithm]: 2.565e-05 [meta_shard_fg_expand]: 3.01001e-06 [get_grad_eliminate_]: 9.72001e-06 [merge_forward]: 6.04001e-06 [cell_reuse_recompute_pass]: 4.72e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.275e-05 [j_node_and_user_rematch]: 1.618e-05 [meta_fg_expand]: 4.14002e-06 [replace_old_param]: 1.415e-05 [inline_without_move]: 8.79998e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.69999e-06 [auto_monad_grad]: 1.69e-06 [auto_monad_eliminator]: 1.371e-05 [cse]: 4.022e-05 [replace_applicator]: 1.037e-05 [py_interpret_to_execute_after_opt_a]: 2.491e-05 [rewriter_after_opt_a]: 0.00026298 [convert_after_rewriter]: 1.183e-05 [order_py_execute_after_rewriter]: 7.61999e-06 [mutable_eliminate]: 0.00089493 [jit_opt_b]: 8.578e-05, [1] [Cycle 1]: 7.655e-05, [2] [frontend_op_eliminate]: 3.288e-05 [inline_after_opt_a]: 2.968e-05 [cconv]: 3.987e-05 [loop_unroll]: 0.00054968 [jit_opt_after_cconv]: 0.00027429, [1] [Cycle 1]: 0.00026623, [11] [c_1]: 4.608e-05 [parameter_eliminate]: 6.18998e-06 [updatestate_depend_eliminate]: 1.37e-05 [updatestate_assign_eliminate]: 6.01e-06 [updatestate_loads_eliminate]: 5.59e-06 [cse]: 6.33e-05 [call_graph_tuple_transform]: 3.879e-05 [tuple_list_get_item_eliminator]: 1.046e-05 [none_parameter_eliminate]: 1.73002e-06 [renormalize]: 7.59988e-07 [switch_simplify]: 1.076e-05 [remove_dup_value]: 6.862e-05 [partial_unused_args_eliminate]: 2.82002e-06 [environ_conv]: 1.444e-05 [add_recomputation]: 8.033e-05 [cse_after_recomputation]: 4.149e-05, [1] [Cycle 1]: 3.347e-05, [1] [cse]: 2.437e-05 [auto_monad_reorder]: 2.431e-05 [get_jit_bprop_graph]: 2.70002e-06 [rewriter_after_jit_bprop_graph]: 9.08002e-06 [opt_after_jit_grad]: 0.00085331 [symbol_engine_optimizer]: 0.00012271, [1] [Cycle 1]: 0.00011506, [6] [build]: 1.579e-05 [elim_shapecalc]: 1.518e-05 [elim_not_effective]: 2.24e-05 [opt_reshape]: 1.077e-05 [fold_const_symbol]: 1.589e-05 [renormalize]: 7.29982e-07 [validate]: 6.828e-05 Sums bootstrap : 0.000380s : 0.05% type_inference : 0.491151s : 65.10% event_method : 0.000119s : 0.02% auto_monad : 0.000185s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000065s : 0.01% rewriter_before_opt_a : 0.000223s : 0.03% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000364s : 0.05% jit_opt_a.loop_unroll : 0.000146s : 0.02% jit_opt_a.a_1 : 0.004173s : 0.55% jit_opt_a.with_stream_mark : 0.000103s : 0.01% jit_opt_a.recompute_prepare : 0.000062s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000028s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000020s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000019s : 0.00% jit_opt_a.parameter_eliminate : 0.000009s : 0.00% jit_opt_a.specialize_transform : 0.000044s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000040s : 0.01% jit_opt_a.accelerated_algorithm : 0.000087s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000017s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000042s : 0.01% jit_opt_a.merge_forward : 0.000024s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000084s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000066s : 0.01% jit_opt_a.meta_fg_expand : 0.136339s : 18.07% jit_opt_a.replace_old_param : 0.000179s : 0.02% jit_opt_a.inline_without_move : 0.000107s : 0.01% jit_opt_a.renormalize : 0.116064s : 15.38% jit_opt_a.add_forward_monad_depend : 0.000040s : 0.01% jit_opt_a.auto_monad_grad : 0.000013s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000126s : 0.02% jit_opt_a.cse : 0.000642s : 0.09% jit_opt_a.replace_applicator : 0.000161s : 0.02% py_interpret_to_execute_after_opt_a : 0.000025s : 0.00% rewriter_after_opt_a : 0.000263s : 0.03% convert_after_rewriter : 0.000012s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000895s : 0.12% jit_opt_b.frontend_op_eliminate : 0.000033s : 0.00% jit_opt_b.inline_after_opt_a : 0.000030s : 0.00% cconv : 0.000040s : 0.01% loop_unroll : 0.000550s : 0.07% jit_opt_after_cconv.c_1 : 0.000046s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000063s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000039s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000010s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000011s : 0.00% remove_dup_value : 0.000069s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000014s : 0.00% add_recomputation : 0.000080s : 0.01% cse_after_recomputation.cse : 0.000024s : 0.00% auto_monad_reorder : 0.000024s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000853s : 0.11% symbol_engine_optimizer.build : 0.000016s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000022s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000068s : 0.01% Time group info: ------[substitution.] 0.001259 198 0.28% : 0.000003s : 4: substitution.elim_not_effective 0.19% : 0.000002s : 4: substitution.fold_const_symbol 0.73% : 0.000009s : 6: substitution.graph_param_transform 69.02% : 0.000869s : 21: substitution.inline 2.50% : 0.000032s : 2: substitution.inline_without_move 1.12% : 0.000014s : 19: substitution.j_node_and_user_rematch 2.09% : 0.000026s : 7: substitution.less_batch_normalization 1.80% : 0.000023s : 15: substitution.minmaximum_grad 0.89% : 0.000011s : 10: substitution.partial_eliminate 1.17% : 0.000015s : 19: substitution.remove_not_recompute_node 2.87% : 0.000036s : 9: substitution.replace_applicator 1.54% : 0.000019s : 19: substitution.replace_old_param 0.38% : 0.000005s : 1: substitution.set_cell_output_no_recompute 1.39% : 0.000018s : 3: substitution.switch_simplify 3.64% : 0.000046s : 15: substitution.tuple_list_convert_item_index_to_positive 3.69% : 0.000046s : 15: substitution.tuple_list_get_item_depend_reorder 6.69% : 0.000084s : 29: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.490871 2 98.87% : 0.485346s : 1: type_inference.infer 1.13% : 0.005525s : 1: type_inference.specialize ------[replace.] 0.000451 38 51.87% : 0.000234s : 21: replace.inline 19.89% : 0.000090s : 3: replace.switch_simplify 28.24% : 0.000127s : 14: replace.tuple_list_get_item_eliminator ------[match.] 0.000908 38 94.29% : 0.000856s : 21: match.inline 1.70% : 0.000015s : 3: match.switch_simplify 4.00% : 0.000036s : 14: match.tuple_list_get_item_eliminator ------[predicate.] 0.000631 4248 1.49% : 0.000009s : 71: predicate.accumulaten_eliminater 0.52% : 0.000003s : 6: predicate.ad_related_special_op_eliminate 1.50% : 0.000009s : 71: predicate.addn_check_dump 1.53% : 0.000010s : 71: predicate.addn_zero_filter 1.97% : 0.000012s : 71: predicate.arithmetic_simplify 1.53% : 0.000010s : 71: predicate.cast_eliminate 0.20% : 0.000001s : 6: predicate.check_bprop_eliminate 1.34% : 0.000008s : 71: predicate.compare_switch_simplify 1.45% : 0.000009s : 71: predicate.depend_value_elim 1.37% : 0.000009s : 71: predicate.dict_get_item_const_eliminator 1.55% : 0.000010s : 71: predicate.dict_get_item_eliminator 1.52% : 0.000010s : 71: predicate.dict_set_item_eliminator 0.33% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 6: predicate.elim_not_effective 0.24% : 0.000002s : 6: predicate.elim_shapecalc_of_broadcastargs 1.52% : 0.000010s : 71: predicate.environ_add_const_eliminate 1.41% : 0.000009s : 71: predicate.environ_get_add_eliminate 1.40% : 0.000009s : 71: predicate.environ_get_depend_swap 1.47% : 0.000009s : 71: predicate.environ_get_eliminate 1.35% : 0.000009s : 71: predicate.environ_get_set_eliminate 0.08% : 0.000000s : 6: predicate.fold_const_symbol 0.88% : 0.000006s : 30: predicate.get_grad_eliminate 0.09% : 0.000001s : 6: predicate.graph_param_transform 4.51% : 0.000028s : 118: predicate.inline 1.75% : 0.000011s : 61: predicate.inline_without_move 0.34% : 0.000002s : 30: predicate.j_node_and_user_rematch 1.18% : 0.000007s : 30: predicate.less_batch_normalization 2.03% : 0.000013s : 85: predicate.list_to_tuple_eliminator_ 1.89% : 0.000012s : 91: predicate.load_eliminater 0.48% : 0.000003s : 6: predicate.loop_unroll_after_grad 3.35% : 0.000021s : 148: predicate.loop_unroll_before_grad 1.71% : 0.000011s : 77: predicate.make_slice_get_slice_eliminator 1.36% : 0.000009s : 71: predicate.merge_addn 1.63% : 0.000010s : 71: predicate.minmaximum_grad 0.72% : 0.000005s : 6: predicate.mutable_eliminate 0.18% : 0.000001s : 6: predicate.opt_reshape 2.39% : 0.000015s : 91: predicate.partial_eliminate 1.42% : 0.000009s : 71: predicate.print_const_string_wrapper 2.00% : 0.000013s : 71: predicate.reduce_eliminate 1.89% : 0.000012s : 85: predicate.redundant_stop_gradient_eliminater 0.45% : 0.000003s : 30: predicate.remove_not_recompute_node 2.46% : 0.000016s : 147: predicate.replace_applicator 1.02% : 0.000006s : 61: predicate.replace_old_param 0.12% : 0.000001s : 6: predicate.reset_defer_inline 1.62% : 0.000010s : 71: predicate.reshape_eliminate 1.42% : 0.000009s : 71: predicate.row_tensor_add_zeros_like 0.39% : 0.000002s : 6: predicate.row_tensor_eliminate 1.42% : 0.000009s : 71: predicate.same_eliminate 0.46% : 0.000003s : 30: predicate.set_cell_output_no_recompute 0.36% : 0.000002s : 12: predicate.special_op_eliminate 0.81% : 0.000005s : 30: predicate.specialize_transform 1.68% : 0.000011s : 71: predicate.split_environ_get_set_with_tuple_value 1.44% : 0.000009s : 71: predicate.stack_unstack_eliminate 0.15% : 0.000001s : 6: predicate.switch_call_monad_eliminater 2.84% : 0.000018s : 106: predicate.switch_defer_inline 2.61% : 0.000016s : 106: predicate.switch_layer_defer_inline 6.57% : 0.000041s : 266: predicate.switch_simplify 1.41% : 0.000009s : 71: predicate.tile_eliminate 1.45% : 0.000009s : 71: predicate.transpose_eliminate 1.85% : 0.000012s : 71: predicate.tuple_list_convert_item_index_to_positive 1.66% : 0.000010s : 71: predicate.tuple_list_get_item_depend_reorder 3.52% : 0.000022s : 97: predicate.tuple_list_get_item_eliminator 1.96% : 0.000012s : 71: predicate.tuple_list_set_item_eliminator 1.74% : 0.000011s : 85: predicate.tuple_to_list_eliminator_ 1.92% : 0.000012s : 91: predicate.updatestate_pure_node_eliminater 2.78% : 0.000018s : 121: predicate.updatestate_useless_node_eliminater 1.84% : 0.000012s : 71: predicate.value_based_eliminate 0.16% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.20% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004768 47 62.90% : 0.002999s : 22: func_graph_cloner_run.FuncGraphClonerGraph 37.10% : 0.001769s : 25: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.881465 87 0.01% : 0.000084s : 1: add_recomputation 0.02% : 0.000192s : 1: auto_monad 0.00% : 0.000028s : 1: auto_monad_reorder 0.05% : 0.000407s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000015s : 1: convert_after_rewriter 0.01% : 0.000044s : 1: cse_after_recomputation 0.00% : 0.000017s : 1: environ_conv 0.01% : 0.000127s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 29.94% : 0.263947s : 1: jit_opt_a 0.03% : 0.000278s : 1: jit_opt_after_cconv 0.01% : 0.000089s : 1: jit_opt_b 0.06% : 0.000561s : 1: loop_unroll 0.10% : 0.000913s : 1: mutable_eliminate 0.62% : 0.005480s : 39: opt.transform.jit_opt_a 0.01% : 0.000102s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000054s : 4: opt.transform.jit_opt_b 0.00% : 0.000021s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000033s : 1: opt.transform.mutable_eliminate 0.00% : 0.000042s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000060s : 4: opt.transform.symbol_engine_opt 0.10% : 0.000867s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000069s : 1: py_interpret_to_execute 0.00% : 0.000028s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000072s : 1: remove_dup_value 1.62% : 0.014255s : 2: renormalize.infer 11.55% : 0.101775s : 2: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000271s : 1: rewriter_after_opt_a 0.03% : 0.000226s : 1: rewriter_before_opt_a 0.01% : 0.000126s : 1: symbol_engine_optimizer 55.72% : 0.491180s : 1: type_inference [WARNING] ME(159823:281473136459568,MainProcess):2026-01-29-17:41:18.734.482 [mindspore/graph/api.py:128] The function "addmm_backward_func" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/mint/test_addmm.py", line 55 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 = 0.886333, [30] [bootstrap]: 0.00040968 [type_inference]: 0.40649 [event_method]: 0.00011977 [auto_monad]: 0.00019074 [graph_reusing]: 1.126e-05 [pre_auto_parallel]: 4.57e-06 [py_interpret_to_execute]: 6.844e-05 [rewriter_before_opt_a]: 0.00022362 [expand_dump_flag]: 4.81002e-06 [jit_opt_a]: 0.473502, [3] [Cycle 1]: 0.277174, [27] [switch_simplify]: 0.00025289 [loop_unroll]: 8.314e-05 [a_1]: 0.256508 [with_stream_mark]: 5.277e-05 [recompute_prepare]: 3.526e-05 [updatestate_depend_eliminate]: 1.415e-05 [updatestate_assign_eliminate]: 1.024e-05 [updatestate_loads_eliminate]: 9.77001e-06 [parameter_eliminate]: 4.30999e-06 [specialize_transform]: 2.35e-05 [updatestate_useless_node_eliminater]: 2.068e-05 [accelerated_algorithm]: 4.309e-05 [meta_shard_fg_expand]: 1.019e-05 [get_grad_eliminate_]: 2.12e-05 [merge_forward]: 1.276e-05 [cell_reuse_recompute_pass]: 1.86998e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.019e-05 [j_node_and_user_rematch]: 3.375e-05 [meta_fg_expand]: 0.00251626 [replace_old_param]: 9.94e-05 [inline_without_move]: 8.015e-05 [renormalize]: 0.0164596 [add_forward_monad_depend]: 2.341e-05 [auto_monad_grad]: 8.88002e-06 [auto_monad_eliminator]: 9.754e-05 [cse]: 0.00026551 [replace_applicator]: 0.0001063 [Cycle 2]: 0.191441, [27] [switch_simplify]: 5.404e-05 [loop_unroll]: 5.209e-05 [a_1]: 0.188189 [with_stream_mark]: 3.436e-05 [recompute_prepare]: 2.068e-05 [updatestate_depend_eliminate]: 8.83001e-06 [updatestate_assign_eliminate]: 6.94999e-06 [updatestate_loads_eliminate]: 6.66e-06 [parameter_eliminate]: 2.72001e-06 [specialize_transform]: 1.449e-05 [updatestate_useless_node_eliminater]: 1.1e-05 [accelerated_algorithm]: 2.061e-05 [meta_shard_fg_expand]: 8.13001e-06 [get_grad_eliminate_]: 1.137e-05 [merge_forward]: 8.19002e-06 [cell_reuse_recompute_pass]: 1.94e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.472e-05 [j_node_and_user_rematch]: 1.881e-05 [meta_fg_expand]: 0.00032271 [replace_old_param]: 2.653e-05 [inline_without_move]: 1.18e-05 [renormalize]: 0.0020878 [add_forward_monad_depend]: 9.37001e-06 [auto_monad_grad]: 2.81999e-06 [auto_monad_eliminator]: 2.999e-05 [cse]: 0.00016274 [replace_applicator]: 3.001e-05 [Cycle 3]: 0.00071525, [27] [switch_simplify]: 1.256e-05 [loop_unroll]: 1.116e-05 [a_1]: 0.00027668 [with_stream_mark]: 2.076e-05 [recompute_prepare]: 1.252e-05 [updatestate_depend_eliminate]: 7.49002e-06 [updatestate_assign_eliminate]: 6.63e-06 [updatestate_loads_eliminate]: 5.44e-06 [parameter_eliminate]: 1.98997e-06 [specialize_transform]: 1.138e-05 [updatestate_useless_node_eliminater]: 1.072e-05 [accelerated_algorithm]: 1.846e-05 [meta_shard_fg_expand]: 3.2e-06 [get_grad_eliminate_]: 1.13e-05 [merge_forward]: 7.06999e-06 [cell_reuse_recompute_pass]: 3.65e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.519e-05 [j_node_and_user_rematch]: 1.837e-05 [meta_fg_expand]: 4.50001e-06 [replace_old_param]: 1.57e-05 [inline_without_move]: 1.045e-05 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 2.69001e-06 [auto_monad_grad]: 1.86003e-06 [auto_monad_eliminator]: 1.706e-05 [cse]: 4.638e-05 [replace_applicator]: 1.368e-05 [py_interpret_to_execute_after_opt_a]: 2.457e-05 [rewriter_after_opt_a]: 0.00025734 [convert_after_rewriter]: 1.503e-05 [order_py_execute_after_rewriter]: 8.85999e-06 [mutable_eliminate]: 0.00082377 [jit_opt_b]: 0.00111096, [1] [Cycle 1]: 0.00109912, [2] [frontend_op_eliminate]: 3.47e-05 [inline_after_opt_a]: 0.00103031 [cconv]: 4.822e-05 [loop_unroll]: 0.00065896 [jit_opt_after_cconv]: 0.00032825, [1] [Cycle 1]: 0.0003177, [11] [c_1]: 5.561e-05 [parameter_eliminate]: 5.64e-06 [updatestate_depend_eliminate]: 1.85e-05 [updatestate_assign_eliminate]: 8.91002e-06 [updatestate_loads_eliminate]: 7.55998e-06 [cse]: 8.797e-05 [call_graph_tuple_transform]: 4.33e-05 [tuple_list_get_item_eliminator]: 1.217e-05 [none_parameter_eliminate]: 1.77001e-06 [renormalize]: 1.24e-06 [switch_simplify]: 1.312e-05 [remove_dup_value]: 7.96e-05 [partial_unused_args_eliminate]: 2.88e-06 [environ_conv]: 1.664e-05 [add_recomputation]: 9.726e-05 [cse_after_recomputation]: 5.231e-05, [1] [Cycle 1]: 4.386e-05, [1] [cse]: 3.496e-05 [auto_monad_reorder]: 2.988e-05 [get_jit_bprop_graph]: 2.34999e-06 [rewriter_after_jit_bprop_graph]: 9.64e-06 [opt_after_jit_grad]: 0.00125812 [symbol_engine_optimizer]: 0.00013751, [1] [Cycle 1]: 0.00012864, [6] [build]: 1.708e-05 [elim_shapecalc]: 1.613e-05 [elim_not_effective]: 3.002e-05 [opt_reshape]: 1.304e-05 [fold_const_symbol]: 1.888e-05 [renormalize]: 8.50006e-07 [validate]: 7.44e-05 Sums bootstrap : 0.000410s : 0.05% type_inference : 0.406490s : 46.14% event_method : 0.000120s : 0.01% auto_monad : 0.000191s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000068s : 0.01% rewriter_before_opt_a : 0.000224s : 0.03% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000319s : 0.04% jit_opt_a.loop_unroll : 0.000146s : 0.02% jit_opt_a.a_1 : 0.444974s : 50.51% jit_opt_a.with_stream_mark : 0.000108s : 0.01% jit_opt_a.recompute_prepare : 0.000068s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000030s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000024s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000022s : 0.00% jit_opt_a.parameter_eliminate : 0.000009s : 0.00% jit_opt_a.specialize_transform : 0.000049s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000042s : 0.00% jit_opt_a.accelerated_algorithm : 0.000082s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000022s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000044s : 0.00% jit_opt_a.merge_forward : 0.000028s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000090s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000071s : 0.01% jit_opt_a.meta_fg_expand : 0.002843s : 0.32% jit_opt_a.replace_old_param : 0.000142s : 0.02% jit_opt_a.inline_without_move : 0.000102s : 0.01% jit_opt_a.renormalize : 0.018547s : 2.11% jit_opt_a.add_forward_monad_depend : 0.000035s : 0.00% jit_opt_a.auto_monad_grad : 0.000014s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000145s : 0.02% jit_opt_a.cse : 0.000475s : 0.05% jit_opt_a.replace_applicator : 0.000150s : 0.02% py_interpret_to_execute_after_opt_a : 0.000025s : 0.00% rewriter_after_opt_a : 0.000257s : 0.03% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000824s : 0.09% jit_opt_b.frontend_op_eliminate : 0.000035s : 0.00% jit_opt_b.inline_after_opt_a : 0.001030s : 0.12% cconv : 0.000048s : 0.01% loop_unroll : 0.000659s : 0.07% jit_opt_after_cconv.c_1 : 0.000056s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000018s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.cse : 0.000088s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000043s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000013s : 0.00% remove_dup_value : 0.000080s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000017s : 0.00% add_recomputation : 0.000097s : 0.01% cse_after_recomputation.cse : 0.000035s : 0.00% auto_monad_reorder : 0.000030s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.001258s : 0.14% symbol_engine_optimizer.build : 0.000017s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000016s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000030s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000074s : 0.01% Time group info: ------[substitution.] 0.255691 216 0.02% : 0.000043s : 4: substitution.arithmetic_simplify 0.00% : 0.000004s : 6: substitution.elim_not_effective 0.00% : 0.000003s : 6: substitution.fold_const_symbol 0.00% : 0.000011s : 8: substitution.graph_param_transform 99.83% : 0.255256s : 21: substitution.inline 0.01% : 0.000025s : 2: substitution.inline_without_move 0.01% : 0.000014s : 23: substitution.j_node_and_user_rematch 0.01% : 0.000025s : 7: substitution.less_batch_normalization 0.01% : 0.000027s : 15: substitution.minmaximum_grad 0.01% : 0.000014s : 10: substitution.partial_eliminate 0.01% : 0.000017s : 23: substitution.remove_not_recompute_node 0.01% : 0.000031s : 9: substitution.replace_applicator 0.01% : 0.000018s : 19: substitution.replace_old_param 0.00% : 0.000004s : 1: substitution.set_cell_output_no_recompute 0.01% : 0.000016s : 3: substitution.switch_simplify 0.02% : 0.000052s : 15: substitution.tuple_list_convert_item_index_to_positive 0.02% : 0.000046s : 15: substitution.tuple_list_get_item_depend_reorder 0.03% : 0.000086s : 29: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.406308 2 98.62% : 0.400705s : 1: type_inference.infer 1.38% : 0.005603s : 1: type_inference.specialize ------[replace.] 0.000472 38 58.45% : 0.000276s : 21: replace.inline 16.21% : 0.000077s : 3: replace.switch_simplify 25.34% : 0.000120s : 14: replace.tuple_list_get_item_eliminator ------[match.] 0.255290 38 99.98% : 0.255238s : 21: match.inline 0.01% : 0.000014s : 3: match.switch_simplify 0.01% : 0.000038s : 14: match.tuple_list_get_item_eliminator ------[predicate.] 0.000707 4528 1.55% : 0.000011s : 75: predicate.accumulaten_eliminater 0.56% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.43% : 0.000010s : 75: predicate.addn_check_dump 1.53% : 0.000011s : 75: predicate.addn_zero_filter 2.09% : 0.000015s : 75: predicate.arithmetic_simplify 1.58% : 0.000011s : 75: predicate.cast_eliminate 0.18% : 0.000001s : 8: predicate.check_bprop_eliminate 1.38% : 0.000010s : 75: predicate.compare_switch_simplify 1.32% : 0.000009s : 75: predicate.depend_value_elim 1.34% : 0.000009s : 75: predicate.dict_get_item_const_eliminator 1.43% : 0.000010s : 75: predicate.dict_get_item_eliminator 1.38% : 0.000010s : 75: predicate.dict_set_item_eliminator 0.38% : 0.000003s : 8: predicate.dumpgradient_eliminate 0.18% : 0.000001s : 8: predicate.elim_not_effective 0.26% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.52% : 0.000011s : 75: predicate.environ_add_const_eliminate 1.40% : 0.000010s : 75: predicate.environ_get_add_eliminate 1.30% : 0.000009s : 75: predicate.environ_get_depend_swap 1.46% : 0.000010s : 75: predicate.environ_get_eliminate 1.46% : 0.000010s : 75: predicate.environ_get_set_eliminate 0.09% : 0.000001s : 8: predicate.fold_const_symbol 0.81% : 0.000006s : 34: predicate.get_grad_eliminate 0.11% : 0.000001s : 8: predicate.graph_param_transform 4.73% : 0.000033s : 126: predicate.inline 1.61% : 0.000011s : 65: predicate.inline_without_move 0.37% : 0.000003s : 34: predicate.j_node_and_user_rematch 1.18% : 0.000008s : 34: predicate.less_batch_normalization 1.88% : 0.000013s : 89: predicate.list_to_tuple_eliminator_ 1.77% : 0.000013s : 97: predicate.load_eliminater 0.48% : 0.000003s : 8: predicate.loop_unroll_after_grad 3.10% : 0.000022s : 152: predicate.loop_unroll_before_grad 2.17% : 0.000015s : 83: predicate.make_slice_get_slice_eliminator 1.34% : 0.000009s : 75: predicate.merge_addn 1.38% : 0.000010s : 75: predicate.minmaximum_grad 0.61% : 0.000004s : 8: predicate.mutable_eliminate 0.19% : 0.000001s : 8: predicate.opt_reshape 2.32% : 0.000016s : 97: predicate.partial_eliminate 1.48% : 0.000010s : 75: predicate.print_const_string_wrapper 1.85% : 0.000013s : 75: predicate.reduce_eliminate 1.74% : 0.000012s : 89: predicate.redundant_stop_gradient_eliminater 0.45% : 0.000003s : 34: predicate.remove_not_recompute_node 2.23% : 0.000016s : 157: predicate.replace_applicator 0.87% : 0.000006s : 65: predicate.replace_old_param 0.16% : 0.000001s : 8: predicate.reset_defer_inline 1.55% : 0.000011s : 75: predicate.reshape_eliminate 1.46% : 0.000010s : 75: predicate.row_tensor_add_zeros_like 0.26% : 0.000002s : 8: predicate.row_tensor_eliminate 1.34% : 0.000009s : 75: predicate.same_eliminate 0.46% : 0.000003s : 34: predicate.set_cell_output_no_recompute 0.35% : 0.000002s : 16: predicate.special_op_eliminate 0.86% : 0.000006s : 34: predicate.specialize_transform 1.72% : 0.000012s : 75: predicate.split_environ_get_set_with_tuple_value 1.35% : 0.000010s : 75: predicate.stack_unstack_eliminate 0.18% : 0.000001s : 8: predicate.switch_call_monad_eliminater 3.57% : 0.000025s : 110: predicate.switch_defer_inline 2.46% : 0.000017s : 110: predicate.switch_layer_defer_inline 5.99% : 0.000042s : 276: predicate.switch_simplify 1.48% : 0.000010s : 75: predicate.tile_eliminate 1.48% : 0.000010s : 75: predicate.transpose_eliminate 1.84% : 0.000013s : 75: predicate.tuple_list_convert_item_index_to_positive 1.87% : 0.000013s : 75: predicate.tuple_list_get_item_depend_reorder 3.88% : 0.000027s : 105: predicate.tuple_list_get_item_eliminator 2.45% : 0.000017s : 75: predicate.tuple_list_set_item_eliminator 1.82% : 0.000013s : 89: predicate.tuple_to_list_eliminator_ 1.90% : 0.000013s : 97: predicate.updatestate_pure_node_eliminater 2.84% : 0.000020s : 131: predicate.updatestate_useless_node_eliminater 1.73% : 0.000012s : 75: predicate.value_based_eliminate 0.22% : 0.000002s : 8: predicate.virtual_view_grad_eliminate 0.26% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004775 47 63.84% : 0.003048s : 22: func_graph_cloner_run.FuncGraphClonerGraph 36.16% : 0.001727s : 25: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.352244 87 0.01% : 0.000101s : 1: add_recomputation 0.01% : 0.000198s : 1: auto_monad 0.00% : 0.000033s : 1: auto_monad_reorder 0.03% : 0.000433s : 1: bootstrap 0.00% : 0.000052s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000055s : 1: cse_after_recomputation 0.00% : 0.000019s : 1: environ_conv 0.01% : 0.000128s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 35.02% : 0.473507s : 1: jit_opt_a 0.02% : 0.000332s : 1: jit_opt_after_cconv 0.08% : 0.001116s : 1: jit_opt_b 0.05% : 0.000670s : 1: loop_unroll 0.06% : 0.000841s : 1: mutable_eliminate 33.00% : 0.446207s : 39: opt.transform.jit_opt_a 0.01% : 0.000119s : 4: opt.transform.jit_opt_after_cconv 0.08% : 0.001046s : 4: opt.transform.jit_opt_b 0.00% : 0.000022s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.00% : 0.000054s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000073s : 4: opt.transform.symbol_engine_opt 0.09% : 0.001273s : 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% : 0.000007s : 1: pre_auto_parallel 0.01% : 0.000072s : 1: py_interpret_to_execute 0.00% : 0.000028s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000084s : 1: remove_dup_value 1.09% : 0.014781s : 2: renormalize.infer 0.28% : 0.003736s : 2: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000265s : 1: rewriter_after_opt_a 0.02% : 0.000228s : 1: rewriter_before_opt_a 0.01% : 0.000141s : 1: symbol_engine_optimizer 30.06% : 0.406521s : 1: type_inference . [hook] pytest_runtest_teardown:test_addmm_normal[KBK] tests/st/mint/test_addmm.py::test_addmm_normal[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 277.31s (0:04:37) ==================