==================================================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_002/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_tensor[pynative] tests/st/mint/test_addmm.py::test_addmm_tensor[pynative],max_mem:2.0M TotalTime = 6.58414, [33] [bootstrap]: 0.00076029 [type_inference]: 1.06164 [event_method]: 0.00025255 [auto_monad]: 0.00020958 [graph_reusing]: 1.077e-05 [pre_auto_parallel]: 1.501e-05 [py_interpret_to_execute]: 6.613e-05 [rewriter_before_opt_a]: 0.00022404 [expand_dump_flag]: 4.42e-06 [jit_opt_a]: 0.253894, [2] [Cycle 1]: 0.00511908, [27] [switch_simplify]: 0.00029098 [loop_unroll]: 7.284e-05 [a_1]: 0.00180079 [with_stream_mark]: 3.092e-05 [recompute_prepare]: 1.459e-05 [updatestate_depend_eliminate]: 6.59001e-06 [updatestate_assign_eliminate]: 5.40001e-06 [updatestate_loads_eliminate]: 4.94e-06 [parameter_eliminate]: 9.77001e-06 [specialize_transform]: 1.401e-05 [updatestate_useless_node_eliminater]: 9.59e-06 [accelerated_algorithm]: 2.896e-05 [meta_shard_fg_expand]: 3.48e-06 [get_grad_eliminate_]: 9.55001e-06 [merge_forward]: 6.04001e-06 [cell_reuse_recompute_pass]: 2.94001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.964e-05 [j_node_and_user_rematch]: 1.475e-05 [meta_fg_expand]: 4.4e-06 [replace_old_param]: 1.883e-05 [inline_without_move]: 9.57999e-06 [renormalize]: 0.00227141 [add_forward_monad_depend]: 2.295e-05 [auto_monad_grad]: 3.38e-06 [auto_monad_eliminator]: 2.753e-05 [cse]: 7.253e-05 [replace_applicator]: 2.804e-05 [Cycle 2]: 0.00056629, [27] [switch_simplify]: 1.031e-05 [loop_unroll]: 8.59998e-06 [a_1]: 0.00021525 [with_stream_mark]: 1.725e-05 [recompute_prepare]: 1.048e-05 [updatestate_depend_eliminate]: 5.04998e-06 [updatestate_assign_eliminate]: 4.89e-06 [updatestate_loads_eliminate]: 3.85e-06 [parameter_eliminate]: 2.33002e-06 [specialize_transform]: 9.25001e-06 [updatestate_useless_node_eliminater]: 8.40001e-06 [accelerated_algorithm]: 1.424e-05 [meta_shard_fg_expand]: 2.73e-06 [get_grad_eliminate_]: 8.17e-06 [merge_forward]: 5.40001e-06 [cell_reuse_recompute_pass]: 3.75e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.927e-05 [j_node_and_user_rematch]: 1.323e-05 [meta_fg_expand]: 3.22002e-06 [replace_old_param]: 1.544e-05 [inline_without_move]: 8.14997e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.02001e-06 [auto_monad_grad]: 1.32999e-06 [auto_monad_eliminator]: 9.72001e-06 [cse]: 2.327e-05 [replace_applicator]: 9.44998e-06 [py_interpret_to_execute_after_opt_a]: 2.014e-05 [rewriter_after_opt_a]: 7.596e-05 [convert_after_rewriter]: 1.121e-05 [order_py_execute_after_rewriter]: 6.33998e-06 [mutable_eliminate]: 0.00079063 [jit_opt_b]: 7.507e-05, [1] [Cycle 1]: 6.541e-05, [2] [frontend_op_eliminate]: 2.675e-05 [inline_after_opt_a]: 2.514e-05 [cconv]: 3.797e-05 [loop_unroll]: 0.00048584 [jit_opt_after_cconv]: 0.00022389, [1] [Cycle 1]: 0.00021664, [11] [c_1]: 3.871e-05 [parameter_eliminate]: 5.26002e-06 [updatestate_depend_eliminate]: 1.175e-05 [updatestate_assign_eliminate]: 4.14002e-06 [updatestate_loads_eliminate]: 3.5e-06 [cse]: 4.452e-05 [call_graph_tuple_transform]: 3.151e-05 [tuple_list_get_item_eliminator]: 9.24998e-06 [none_parameter_eliminate]: 1.55999e-06 [renormalize]: 7.30011e-07 [switch_simplify]: 9.15999e-06 [remove_dup_value]: 5.543e-05 [partial_unused_args_eliminate]: 2.37999e-06 [environ_conv]: 2.055e-05 [add_recomputation]: 7.611e-05 [cse_after_recomputation]: 3.437e-05, [1] [Cycle 1]: 2.701e-05, [1] [cse]: 1.86e-05 [auto_monad_reorder]: 3.056e-05 [get_jit_bprop_graph]: 2.53e-06 [rewriter_after_jit_bprop_graph]: 0.00031082 [opt_after_jit_grad]: 0.00064722 [symbol_engine_optimizer]: 9.96e-05, [1] [Cycle 1]: 9.255e-05, [6] [build]: 6.04999e-06 [elim_shapecalc]: 1.264e-05 [elim_not_effective]: 1.898e-05 [opt_reshape]: 8.59e-06 [fold_const_symbol]: 1.365e-05 [renormalize]: 6.19999e-07 [validate]: 7.78e-05 [backend_pass]: 1.32999e-06 [task_emit]: 5.26348 [execute]: 1.149e-05 Sums bootstrap : 0.000760s : 0.01% type_inference : 1.061639s : 16.76% event_method : 0.000253s : 0.00% auto_monad : 0.000210s : 0.00% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000015s : 0.00% py_interpret_to_execute : 0.000066s : 0.00% rewriter_before_opt_a : 0.000224s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000301s : 0.00% jit_opt_a.loop_unroll : 0.000081s : 0.00% jit_opt_a.a_1 : 0.002016s : 0.03% jit_opt_a.with_stream_mark : 0.000048s : 0.00% jit_opt_a.recompute_prepare : 0.000025s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000012s : 0.00% jit_opt_a.specialize_transform : 0.000023s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000018s : 0.00% jit_opt_a.accelerated_algorithm : 0.000043s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000018s : 0.00% jit_opt_a.merge_forward : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000059s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000034s : 0.00% jit_opt_a.inline_without_move : 0.000018s : 0.00% jit_opt_a.renormalize : 0.002271s : 0.04% jit_opt_a.add_forward_monad_depend : 0.000025s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000037s : 0.00% jit_opt_a.cse : 0.000096s : 0.00% jit_opt_a.replace_applicator : 0.000037s : 0.00% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000076s : 0.00% convert_after_rewriter : 0.000011s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000791s : 0.01% jit_opt_b.frontend_op_eliminate : 0.000027s : 0.00% jit_opt_b.inline_after_opt_a : 0.000025s : 0.00% cconv : 0.000038s : 0.00% loop_unroll : 0.000486s : 0.01% jit_opt_after_cconv.c_1 : 0.000039s : 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 : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000045s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000032s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000055s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000021s : 0.00% add_recomputation : 0.000076s : 0.00% cse_after_recomputation.cse : 0.000019s : 0.00% auto_monad_reorder : 0.000031s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000311s : 0.00% opt_after_jit_grad : 0.000647s : 0.01% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000078s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 5.263478s : 83.09% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000660 64 8.84% : 0.000058s : 9: substitution.arithmetic_simplify 0.36% : 0.000002s : 3: substitution.elim_not_effective 0.29% : 0.000002s : 3: substitution.fold_const_symbol 1.22% : 0.000008s : 6: substitution.graph_param_transform 75.40% : 0.000498s : 14: substitution.inline 0.88% : 0.000006s : 6: substitution.j_node_and_user_rematch 2.50% : 0.000017s : 4: substitution.less_batch_normalization 3.20% : 0.000021s : 6: substitution.remove_not_recompute_node 1.66% : 0.000011s : 6: substitution.replace_old_param 2.26% : 0.000015s : 2: substitution.switch_simplify 3.40% : 0.000022s : 5: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.061488 2 99.64% : 1.057629s : 1: type_inference.infer 0.36% : 0.003859s : 1: type_inference.specialize ------[replace.] 0.000282 23 4.06% : 0.000011s : 2: replace.arithmetic_simplify 43.51% : 0.000123s : 14: replace.inline 40.18% : 0.000113s : 2: replace.switch_simplify 12.24% : 0.000035s : 5: replace.tuple_list_get_item_eliminator ------[match.] 0.000534 23 2.19% : 0.000012s : 2: match.arithmetic_simplify 91.64% : 0.000490s : 14: match.inline 2.52% : 0.000013s : 2: match.switch_simplify 3.64% : 0.000019s : 5: match.tuple_list_get_item_eliminator ------[predicate.] 0.000324 1863 2.02% : 0.000007s : 28: predicate.accumulaten_eliminater 0.88% : 0.000003s : 6: predicate.ad_related_special_op_eliminate 1.18% : 0.000004s : 28: predicate.addn_check_dump 1.24% : 0.000004s : 28: predicate.addn_zero_filter 2.53% : 0.000008s : 30: predicate.arithmetic_simplify 1.33% : 0.000004s : 30: predicate.cast_eliminate 0.27% : 0.000001s : 6: predicate.check_bprop_eliminate 1.17% : 0.000004s : 28: predicate.compare_switch_simplify 1.21% : 0.000004s : 28: predicate.depend_value_elim 1.24% : 0.000004s : 30: predicate.dict_get_item_const_eliminator 1.35% : 0.000004s : 30: predicate.dict_get_item_eliminator 1.29% : 0.000004s : 30: predicate.dict_set_item_eliminator 0.60% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.22% : 0.000001s : 6: predicate.elim_not_effective 0.34% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.33% : 0.000004s : 30: predicate.environ_add_const_eliminate 1.23% : 0.000004s : 30: predicate.environ_get_add_eliminate 1.42% : 0.000005s : 30: predicate.environ_get_depend_swap 1.29% : 0.000004s : 30: predicate.environ_get_eliminate 1.31% : 0.000004s : 30: predicate.environ_get_set_eliminate 0.18% : 0.000001s : 6: predicate.fold_const_symbol 0.71% : 0.000002s : 12: predicate.get_grad_eliminate 0.22% : 0.000001s : 6: predicate.graph_param_transform 5.83% : 0.000019s : 61: predicate.inline 0.81% : 0.000003s : 12: predicate.inline_without_move 0.31% : 0.000001s : 12: predicate.j_node_and_user_rematch 0.90% : 0.000003s : 12: predicate.less_batch_normalization 1.62% : 0.000005s : 35: predicate.list_to_tuple_eliminator_ 1.91% : 0.000006s : 41: predicate.load_eliminater 0.84% : 0.000003s : 6: predicate.loop_unroll_after_grad 3.76% : 0.000012s : 80: predicate.loop_unroll_before_grad 1.71% : 0.000006s : 36: predicate.make_slice_get_slice_eliminator 1.28% : 0.000004s : 28: predicate.merge_addn 1.24% : 0.000004s : 30: predicate.minmaximum_grad 1.44% : 0.000005s : 6: predicate.mutable_eliminate 0.32% : 0.000001s : 6: predicate.opt_reshape 2.39% : 0.000008s : 41: predicate.partial_eliminate 1.17% : 0.000004s : 28: predicate.print_const_string_wrapper 1.85% : 0.000006s : 30: predicate.reduce_eliminate 1.70% : 0.000005s : 35: predicate.redundant_stop_gradient_eliminater 0.40% : 0.000001s : 12: predicate.remove_not_recompute_node 1.80% : 0.000006s : 47: predicate.replace_applicator 0.45% : 0.000001s : 12: predicate.replace_old_param 0.27% : 0.000001s : 6: predicate.reset_defer_inline 1.29% : 0.000004s : 30: predicate.reshape_eliminate 1.21% : 0.000004s : 28: predicate.row_tensor_add_zeros_like 0.41% : 0.000001s : 6: predicate.row_tensor_eliminate 1.19% : 0.000004s : 28: predicate.same_eliminate 0.46% : 0.000001s : 12: predicate.set_cell_output_no_recompute 0.88% : 0.000003s : 12: predicate.special_op_eliminate 1.09% : 0.000004s : 12: predicate.specialize_transform 1.54% : 0.000005s : 28: predicate.split_environ_get_set_with_tuple_value 1.34% : 0.000004s : 28: predicate.stack_unstack_eliminate 0.30% : 0.000001s : 6: predicate.switch_call_monad_eliminater 3.08% : 0.000010s : 49: predicate.switch_defer_inline 2.47% : 0.000008s : 49: predicate.switch_layer_defer_inline 7.86% : 0.000026s : 139: predicate.switch_simplify 1.31% : 0.000004s : 30: predicate.tile_eliminate 1.44% : 0.000005s : 30: predicate.transpose_eliminate 1.71% : 0.000006s : 30: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000005s : 30: predicate.tuple_list_get_item_depend_reorder 3.96% : 0.000013s : 47: predicate.tuple_list_get_item_eliminator 1.76% : 0.000006s : 30: predicate.tuple_list_set_item_eliminator 1.55% : 0.000005s : 35: predicate.tuple_to_list_eliminator_ 1.79% : 0.000006s : 41: predicate.updatestate_pure_node_eliminater 2.73% : 0.000009s : 53: predicate.updatestate_useless_node_eliminater 1.81% : 0.000006s : 28: predicate.value_based_eliminate 0.27% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.38% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003058 27 61.91% : 0.001893s : 11: func_graph_cloner_run.FuncGraphClonerGraph 2.14% : 0.000065s : 1: func_graph_cloner_run.FuncGraphClonerNode 35.95% : 0.001100s : 15: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 6.589137 76 0.00% : 0.000079s : 1: add_recomputation 0.00% : 0.000219s : 1: auto_monad 0.00% : 0.000033s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.01% : 0.000787s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000014s : 1: convert_after_rewriter 0.00% : 0.000036s : 1: cse_after_recomputation 0.00% : 0.000024s : 1: environ_conv 0.00% : 0.000265s : 1: event_method 0.00% : 0.000017s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 3.85% : 0.253898s : 1: jit_opt_a 0.00% : 0.000227s : 1: jit_opt_after_cconv 0.00% : 0.000078s : 1: jit_opt_b 0.01% : 0.000495s : 1: loop_unroll 0.01% : 0.000805s : 1: mutable_eliminate 0.04% : 0.002646s : 26: opt.transform.jit_opt_a 0.00% : 0.000084s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000023s : 1: opt.transform.mutable_eliminate 0.00% : 0.000041s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000049s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000661s : 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% : 0.000017s : 1: pre_auto_parallel 0.00% : 0.000070s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000059s : 1: remove_dup_value 0.02% : 0.001175s : 1: renormalize.infer 0.02% : 0.001080s : 1: renormalize.specialize 0.00% : 0.000318s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000080s : 1: rewriter_after_opt_a 0.00% : 0.000230s : 1: rewriter_before_opt_a 0.00% : 0.000103s : 1: symbol_engine_optimizer 79.88% : 5.263499s : 1: task_emit 16.11% : 1.061663s : 1: type_inference 0.00% : 0.000191s : 1: validate [WARNING] ME(169024:281473628827440,MainProcess):2026-01-29-17:40:10.633.309 [mindspore/graph/api.py:128] The function "addmm_forward_func_tensor" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/mint/test_addmm.py", line 61 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 = 0.202898, [33] [bootstrap]: 0.0005228 [type_inference]: 0.154767 [event_method]: 0.00022978 [auto_monad]: 0.00014834 [graph_reusing]: 9.77999e-06 [pre_auto_parallel]: 4.07e-06 [py_interpret_to_execute]: 5.164e-05 [rewriter_before_opt_a]: 0.00018666 [expand_dump_flag]: 3.88001e-06 [jit_opt_a]: 0.0220794, [2] [Cycle 1]: 0.0164147, [27] [switch_simplify]: 0.00023396 [loop_unroll]: 7.532e-05 [a_1]: 0.00149587 [with_stream_mark]: 3.311e-05 [recompute_prepare]: 1.609e-05 [updatestate_depend_eliminate]: 7.11999e-06 [updatestate_assign_eliminate]: 5.39e-06 [updatestate_loads_eliminate]: 4.85999e-06 [parameter_eliminate]: 2.31e-06 [specialize_transform]: 1.148e-05 [updatestate_useless_node_eliminater]: 9.96998e-06 [accelerated_algorithm]: 2.826e-05 [meta_shard_fg_expand]: 4.41002e-06 [get_grad_eliminate_]: 1.062e-05 [merge_forward]: 6.86999e-06 [cell_reuse_recompute_pass]: 1.52001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.357e-05 [j_node_and_user_rematch]: 1.776e-05 [meta_fg_expand]: 5.20999e-06 [replace_old_param]: 1.754e-05 [inline_without_move]: 1.024e-05 [renormalize]: 0.0137746 [add_forward_monad_depend]: 2.126e-05 [auto_monad_grad]: 3.61999e-06 [auto_monad_eliminator]: 5.672e-05 [cse]: 0.00022159 [replace_applicator]: 3.953e-05 [Cycle 2]: 0.00070788, [27] [switch_simplify]: 1.304e-05 [loop_unroll]: 9.89001e-06 [a_1]: 0.00029584 [with_stream_mark]: 2.269e-05 [recompute_prepare]: 1.076e-05 [updatestate_depend_eliminate]: 6.89001e-06 [updatestate_assign_eliminate]: 5.94999e-06 [updatestate_loads_eliminate]: 4.65001e-06 [parameter_eliminate]: 2.76e-06 [specialize_transform]: 9.91e-06 [updatestate_useless_node_eliminater]: 9.52001e-06 [accelerated_algorithm]: 1.825e-05 [meta_shard_fg_expand]: 3.44001e-06 [get_grad_eliminate_]: 9.12001e-06 [merge_forward]: 6.38e-06 [cell_reuse_recompute_pass]: 4.02e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.305e-05 [j_node_and_user_rematch]: 1.658e-05 [meta_fg_expand]: 4.16001e-06 [replace_old_param]: 1.728e-05 [inline_without_move]: 9.47001e-06 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 1.96e-06 [auto_monad_grad]: 1.81e-06 [auto_monad_eliminator]: 1.24e-05 [cse]: 3.658e-05 [replace_applicator]: 1.116e-05 [py_interpret_to_execute_after_opt_a]: 2.731e-05 [rewriter_after_opt_a]: 5.832e-05 [convert_after_rewriter]: 1.058e-05 [order_py_execute_after_rewriter]: 7.42998e-06 [mutable_eliminate]: 0.000888 [jit_opt_b]: 0.00011084, [1] [Cycle 1]: 0.00010131, [2] [frontend_op_eliminate]: 3.124e-05 [inline_after_opt_a]: 5.282e-05 [cconv]: 4.28e-05 [loop_unroll]: 0.00051596 [jit_opt_after_cconv]: 0.00024038, [1] [Cycle 1]: 0.00023307, [11] [c_1]: 4.521e-05 [parameter_eliminate]: 4.28999e-06 [updatestate_depend_eliminate]: 9.61998e-06 [updatestate_assign_eliminate]: 4.37e-06 [updatestate_loads_eliminate]: 3.97e-06 [cse]: 4.694e-05 [call_graph_tuple_transform]: 3.458e-05 [tuple_list_get_item_eliminator]: 1.043e-05 [none_parameter_eliminate]: 2.44001e-06 [renormalize]: 6.20028e-07 [switch_simplify]: 1.04e-05 [remove_dup_value]: 6.07e-05 [partial_unused_args_eliminate]: 2.26998e-06 [environ_conv]: 8.05e-06 [add_recomputation]: 8.126e-05 [cse_after_recomputation]: 3.916e-05, [1] [Cycle 1]: 3.213e-05, [1] [cse]: 2.52e-05 [auto_monad_reorder]: 2.614e-05 [get_jit_bprop_graph]: 2.41e-06 [rewriter_after_jit_bprop_graph]: 8.51002e-06 [opt_after_jit_grad]: 0.00054709 [symbol_engine_optimizer]: 0.00010487, [1] [Cycle 1]: 9.813e-05, [6] [build]: 5.35001e-06 [elim_shapecalc]: 1.336e-05 [elim_not_effective]: 2.057e-05 [opt_reshape]: 1.014e-05 [fold_const_symbol]: 1.577e-05 [renormalize]: 1.22e-06 [validate]: 5.86e-05 [backend_pass]: 1.20001e-06 [task_emit]: 0.0216441 [execute]: 1.262e-05 Sums bootstrap : 0.000523s : 0.27% type_inference : 0.154767s : 78.57% event_method : 0.000230s : 0.12% auto_monad : 0.000148s : 0.08% graph_reusing : 0.000010s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000052s : 0.03% rewriter_before_opt_a : 0.000187s : 0.09% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000247s : 0.13% jit_opt_a.loop_unroll : 0.000085s : 0.04% jit_opt_a.a_1 : 0.001792s : 0.91% jit_opt_a.with_stream_mark : 0.000056s : 0.03% jit_opt_a.recompute_prepare : 0.000027s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000019s : 0.01% jit_opt_a.accelerated_algorithm : 0.000047s : 0.02% jit_opt_a.meta_shard_fg_expand : 0.000008s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000020s : 0.01% jit_opt_a.merge_forward : 0.000013s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000034s : 0.02% jit_opt_a.meta_fg_expand : 0.000009s : 0.00% jit_opt_a.replace_old_param : 0.000035s : 0.02% jit_opt_a.inline_without_move : 0.000020s : 0.01% jit_opt_a.renormalize : 0.013775s : 6.99% jit_opt_a.add_forward_monad_depend : 0.000023s : 0.01% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000069s : 0.04% jit_opt_a.cse : 0.000258s : 0.13% jit_opt_a.replace_applicator : 0.000051s : 0.03% py_interpret_to_execute_after_opt_a : 0.000027s : 0.01% rewriter_after_opt_a : 0.000058s : 0.03% convert_after_rewriter : 0.000011s : 0.01% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000888s : 0.45% jit_opt_b.frontend_op_eliminate : 0.000031s : 0.02% jit_opt_b.inline_after_opt_a : 0.000053s : 0.03% cconv : 0.000043s : 0.02% loop_unroll : 0.000516s : 0.26% jit_opt_after_cconv.c_1 : 0.000045s : 0.02% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000047s : 0.02% jit_opt_after_cconv.call_graph_tuple_transform : 0.000035s : 0.02% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000010s : 0.01% 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 : 0.000010s : 0.01% remove_dup_value : 0.000061s : 0.03% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000008s : 0.00% add_recomputation : 0.000081s : 0.04% cse_after_recomputation.cse : 0.000025s : 0.01% auto_monad_reorder : 0.000026s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000547s : 0.28% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.01% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.01% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000059s : 0.03% backend_pass : 0.000001s : 0.00% task_emit : 0.021644s : 10.99% execute : 0.000013s : 0.01% Time group info: ------[substitution.] 0.000560 71 14.67% : 0.000082s : 9: substitution.arithmetic_simplify 0.55% : 0.000003s : 4: substitution.elim_not_effective 0.44% : 0.000002s : 4: substitution.fold_const_symbol 1.74% : 0.000010s : 7: substitution.graph_param_transform 68.60% : 0.000384s : 14: substitution.inline 1.34% : 0.000007s : 8: substitution.j_node_and_user_rematch 3.15% : 0.000018s : 4: substitution.less_batch_normalization 1.50% : 0.000008s : 8: substitution.remove_not_recompute_node 1.78% : 0.000010s : 6: substitution.replace_old_param 2.41% : 0.000014s : 2: substitution.switch_simplify 3.83% : 0.000021s : 5: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.154615 2 76.84% : 0.118811s : 1: type_inference.infer 23.16% : 0.035804s : 1: type_inference.specialize ------[replace.] 0.000205 22 2.58% : 0.000005s : 1: replace.arithmetic_simplify 49.85% : 0.000102s : 14: replace.inline 32.47% : 0.000066s : 2: replace.switch_simplify 15.11% : 0.000031s : 5: replace.tuple_list_get_item_eliminator ------[match.] 0.000415 22 2.00% : 0.000008s : 1: match.arithmetic_simplify 90.51% : 0.000376s : 14: match.inline 2.96% : 0.000012s : 2: match.switch_simplify 4.53% : 0.000019s : 5: match.tuple_list_get_item_eliminator ------[predicate.] 0.000338 1930 1.42% : 0.000005s : 29: predicate.accumulaten_eliminater 0.68% : 0.000002s : 7: predicate.ad_related_special_op_eliminate 1.19% : 0.000004s : 29: predicate.addn_check_dump 1.47% : 0.000005s : 29: predicate.addn_zero_filter 2.65% : 0.000009s : 30: predicate.arithmetic_simplify 1.33% : 0.000004s : 30: predicate.cast_eliminate 0.33% : 0.000001s : 7: predicate.check_bprop_eliminate 1.24% : 0.000004s : 29: predicate.compare_switch_simplify 1.27% : 0.000004s : 29: predicate.depend_value_elim 1.28% : 0.000004s : 30: predicate.dict_get_item_const_eliminator 1.30% : 0.000004s : 30: predicate.dict_get_item_eliminator 1.29% : 0.000004s : 30: predicate.dict_set_item_eliminator 0.48% : 0.000002s : 7: predicate.dumpgradient_eliminate 0.25% : 0.000001s : 7: predicate.elim_not_effective 0.43% : 0.000001s : 7: predicate.elim_shapecalc_of_broadcastargs 1.42% : 0.000005s : 30: predicate.environ_add_const_eliminate 1.23% : 0.000004s : 30: predicate.environ_get_add_eliminate 1.29% : 0.000004s : 30: predicate.environ_get_depend_swap 1.25% : 0.000004s : 30: predicate.environ_get_eliminate 1.50% : 0.000005s : 30: predicate.environ_get_set_eliminate 0.21% : 0.000001s : 7: predicate.fold_const_symbol 0.75% : 0.000003s : 14: predicate.get_grad_eliminate 0.17% : 0.000001s : 7: predicate.graph_param_transform 5.33% : 0.000018s : 63: predicate.inline 0.74% : 0.000003s : 14: predicate.inline_without_move 0.36% : 0.000001s : 14: predicate.j_node_and_user_rematch 1.08% : 0.000004s : 14: predicate.less_batch_normalization 1.58% : 0.000005s : 35: predicate.list_to_tuple_eliminator_ 1.85% : 0.000006s : 42: predicate.load_eliminater 0.78% : 0.000003s : 7: predicate.loop_unroll_after_grad 3.85% : 0.000013s : 84: predicate.loop_unroll_before_grad 1.77% : 0.000006s : 37: predicate.make_slice_get_slice_eliminator 1.29% : 0.000004s : 29: predicate.merge_addn 1.23% : 0.000004s : 30: predicate.minmaximum_grad 0.73% : 0.000002s : 7: predicate.mutable_eliminate 0.32% : 0.000001s : 7: predicate.opt_reshape 2.47% : 0.000008s : 42: predicate.partial_eliminate 1.41% : 0.000005s : 29: predicate.print_const_string_wrapper 1.60% : 0.000005s : 30: predicate.reduce_eliminate 1.61% : 0.000005s : 35: predicate.redundant_stop_gradient_eliminater 0.46% : 0.000002s : 14: predicate.remove_not_recompute_node 1.74% : 0.000006s : 49: predicate.replace_applicator 0.48% : 0.000002s : 14: predicate.replace_old_param 0.30% : 0.000001s : 7: predicate.reset_defer_inline 1.36% : 0.000005s : 30: predicate.reshape_eliminate 1.21% : 0.000004s : 29: predicate.row_tensor_add_zeros_like 0.58% : 0.000002s : 7: predicate.row_tensor_eliminate 1.41% : 0.000005s : 29: predicate.same_eliminate 0.44% : 0.000001s : 14: predicate.set_cell_output_no_recompute 0.70% : 0.000002s : 14: predicate.special_op_eliminate 0.76% : 0.000003s : 14: predicate.specialize_transform 1.55% : 0.000005s : 29: predicate.split_environ_get_set_with_tuple_value 1.41% : 0.000005s : 29: predicate.stack_unstack_eliminate 0.35% : 0.000001s : 7: predicate.switch_call_monad_eliminater 2.72% : 0.000009s : 49: predicate.switch_defer_inline 2.41% : 0.000008s : 49: predicate.switch_layer_defer_inline 7.52% : 0.000025s : 144: predicate.switch_simplify 1.31% : 0.000004s : 30: predicate.tile_eliminate 1.30% : 0.000004s : 30: predicate.transpose_eliminate 4.28% : 0.000014s : 30: predicate.tuple_list_convert_item_index_to_positive 1.64% : 0.000006s : 30: predicate.tuple_list_get_item_depend_reorder 3.48% : 0.000012s : 49: predicate.tuple_list_get_item_eliminator 1.66% : 0.000006s : 30: predicate.tuple_list_set_item_eliminator 1.62% : 0.000005s : 35: predicate.tuple_to_list_eliminator_ 1.90% : 0.000006s : 42: predicate.updatestate_pure_node_eliminater 2.68% : 0.000009s : 56: predicate.updatestate_useless_node_eliminater 1.68% : 0.000006s : 29: predicate.value_based_eliminate 0.27% : 0.000001s : 7: predicate.virtual_view_grad_eliminate 0.35% : 0.000001s : 7: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003022 27 54.57% : 0.001649s : 11: func_graph_cloner_run.FuncGraphClonerGraph 45.43% : 0.001373s : 16: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.219279 76 0.04% : 0.000084s : 1: add_recomputation 0.07% : 0.000156s : 1: auto_monad 0.01% : 0.000029s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.25% : 0.000550s : 1: bootstrap 0.02% : 0.000046s : 1: cconv 0.01% : 0.000013s : 1: convert_after_rewriter 0.02% : 0.000041s : 1: cse_after_recomputation 0.00% : 0.000010s : 1: environ_conv 0.11% : 0.000240s : 1: event_method 0.01% : 0.000021s : 1: execute 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.01% : 0.000012s : 1: graph_reusing 10.07% : 0.022084s : 1: jit_opt_a 0.11% : 0.000243s : 1: jit_opt_after_cconv 0.05% : 0.000114s : 1: jit_opt_b 0.24% : 0.000527s : 1: loop_unroll 0.41% : 0.000899s : 1: mutable_eliminate 1.09% : 0.002400s : 26: opt.transform.jit_opt_a 0.04% : 0.000097s : 4: opt.transform.jit_opt_after_cconv 0.02% : 0.000053s : 4: opt.transform.jit_opt_b 0.01% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000021s : 1: opt.transform.mutable_eliminate 0.02% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000056s : 4: opt.transform.symbol_engine_opt 0.25% : 0.000557s : 1: opt_after_jit_grad 0.00% : 0.000009s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.02% : 0.000054s : 1: py_interpret_to_execute 0.01% : 0.000030s : 1: py_interpret_to_execute_after_opt_a 0.03% : 0.000064s : 1: remove_dup_value 5.61% : 0.012300s : 1: renormalize.infer 0.66% : 0.001452s : 1: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000061s : 1: rewriter_after_opt_a 0.09% : 0.000190s : 1: rewriter_before_opt_a 0.05% : 0.000108s : 1: symbol_engine_optimizer 9.89% : 0.021689s : 1: task_emit 70.59% : 0.154794s : 1: type_inference 0.08% : 0.000180s : 1: validate TotalTime = 0.668901, [33] [bootstrap]: 0.00054356 [type_inference]: 0.445562 [event_method]: 7.031e-05 [auto_monad]: 0.00025626 [graph_reusing]: 1.684e-05 [pre_auto_parallel]: 5.37001e-06 [py_interpret_to_execute]: 8.577e-05 [rewriter_before_opt_a]: 0.00035446 [expand_dump_flag]: 7.13e-06 [jit_opt_a]: 0.143751, [3] [Cycle 1]: 0.0995832, [27] [switch_simplify]: 0.00126143 [loop_unroll]: 0.00016296 [a_1]: 0.00324138 [with_stream_mark]: 4.481e-05 [recompute_prepare]: 3.375e-05 [updatestate_depend_eliminate]: 1.491e-05 [updatestate_assign_eliminate]: 9.96e-06 [updatestate_loads_eliminate]: 9.79e-06 [parameter_eliminate]: 3.63e-06 [specialize_transform]: 2.452e-05 [updatestate_useless_node_eliminater]: 2.276e-05 [accelerated_algorithm]: 6.455e-05 [meta_shard_fg_expand]: 9.18002e-06 [get_grad_eliminate_]: 2.226e-05 [merge_forward]: 1.272e-05 [cell_reuse_recompute_pass]: 1.14998e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.599e-05 [j_node_and_user_rematch]: 4.613e-05 [meta_fg_expand]: 0.00339991 [replace_old_param]: 0.00013538 [inline_without_move]: 0.00013986 [renormalize]: 0.089848 [add_forward_monad_depend]: 1.831e-05 [auto_monad_grad]: 8.62e-06 [auto_monad_eliminator]: 7.376e-05 [cse]: 0.00043527 [replace_applicator]: 0.00011767 [Cycle 2]: 0.00530427, [27] [switch_simplify]: 5.443e-05 [loop_unroll]: 7.842e-05 [a_1]: 0.00192795 [with_stream_mark]: 3.091e-05 [recompute_prepare]: 1.682e-05 [updatestate_depend_eliminate]: 7.09001e-06 [updatestate_assign_eliminate]: 5.40001e-06 [updatestate_loads_eliminate]: 4.92e-06 [parameter_eliminate]: 2.93e-06 [specialize_transform]: 1.216e-05 [updatestate_useless_node_eliminater]: 1.288e-05 [accelerated_algorithm]: 2.268e-05 [meta_shard_fg_expand]: 5.59e-06 [get_grad_eliminate_]: 1.013e-05 [merge_forward]: 7.04001e-06 [cell_reuse_recompute_pass]: 1.45999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.34e-05 [j_node_and_user_rematch]: 1.687e-05 [meta_fg_expand]: 0.00059657 [replace_old_param]: 3.647e-05 [inline_without_move]: 1.13e-05 [renormalize]: 0.00192456 [add_forward_monad_depend]: 1.077e-05 [auto_monad_grad]: 2.75997e-06 [auto_monad_eliminator]: 2.743e-05 [cse]: 0.00016014 [replace_applicator]: 2.954e-05 [Cycle 3]: 0.00074424, [27] [switch_simplify]: 1.252e-05 [loop_unroll]: 1.048e-05 [a_1]: 0.00024228 [with_stream_mark]: 2.248e-05 [recompute_prepare]: 1.095e-05 [updatestate_depend_eliminate]: 7.90998e-06 [updatestate_assign_eliminate]: 5.34e-06 [updatestate_loads_eliminate]: 4.92999e-06 [parameter_eliminate]: 2.59001e-06 [specialize_transform]: 1.064e-05 [updatestate_useless_node_eliminater]: 1.045e-05 [accelerated_algorithm]: 2.598e-05 [meta_shard_fg_expand]: 3.14999e-06 [get_grad_eliminate_]: 9.27999e-06 [merge_forward]: 7.01999e-06 [cell_reuse_recompute_pass]: 4.75001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.257e-05 [j_node_and_user_rematch]: 1.666e-05 [meta_fg_expand]: 3.95998e-06 [replace_old_param]: 1.543e-05 [inline_without_move]: 1.309e-05 [renormalize]: 1.29978e-07 [add_forward_monad_depend]: 3.31001e-06 [auto_monad_grad]: 3.04999e-06 [auto_monad_eliminator]: 1.531e-05 [cse]: 5.064e-05 [replace_applicator]: 1.119e-05 [py_interpret_to_execute_after_opt_a]: 2.329e-05 [rewriter_after_opt_a]: 0.0002543 [convert_after_rewriter]: 1.278e-05 [order_py_execute_after_rewriter]: 8.26002e-06 [mutable_eliminate]: 0.00091115 [jit_opt_b]: 8.926e-05, [1] [Cycle 1]: 7.915e-05, [2] [frontend_op_eliminate]: 3.325e-05 [inline_after_opt_a]: 3.146e-05 [cconv]: 4.482e-05 [loop_unroll]: 0.0653759 [jit_opt_after_cconv]: 0.0003217, [1] [Cycle 1]: 0.00030909, [11] [c_1]: 5.076e-05 [parameter_eliminate]: 9.49e-06 [updatestate_depend_eliminate]: 1.74e-05 [updatestate_assign_eliminate]: 5.46e-06 [updatestate_loads_eliminate]: 5.30001e-06 [cse]: 8.531e-05 [call_graph_tuple_transform]: 4.502e-05 [tuple_list_get_item_eliminator]: 1.113e-05 [none_parameter_eliminate]: 1.84e-06 [renormalize]: 9.00007e-07 [switch_simplify]: 1.172e-05 [remove_dup_value]: 7.947e-05 [partial_unused_args_eliminate]: 2.96999e-06 [environ_conv]: 1.643e-05 [add_recomputation]: 9.184e-05 [cse_after_recomputation]: 0.00011899, [1] [Cycle 1]: 0.00011086, [1] [cse]: 0.00010067 [auto_monad_reorder]: 2.634e-05 [get_jit_bprop_graph]: 3.27997e-06 [rewriter_after_jit_bprop_graph]: 1.211e-05 [opt_after_jit_grad]: 0.00066517 [symbol_engine_optimizer]: 0.00012775, [1] [Cycle 1]: 0.00012083, [6] [build]: 1.645e-05 [elim_shapecalc]: 1.427e-05 [elim_not_effective]: 2.575e-05 [opt_reshape]: 1.158e-05 [fold_const_symbol]: 1.795e-05 [renormalize]: 6.00005e-07 [validate]: 7.402e-05 [backend_pass]: 1.42e-06 [task_emit]: 0.00953151 [execute]: 1.074e-05 Sums bootstrap : 0.000544s : 0.09% type_inference : 0.445562s : 70.80% event_method : 0.000070s : 0.01% auto_monad : 0.000256s : 0.04% graph_reusing : 0.000017s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000086s : 0.01% rewriter_before_opt_a : 0.000354s : 0.06% expand_dump_flag : 0.000007s : 0.00% jit_opt_a.switch_simplify : 0.001328s : 0.21% jit_opt_a.loop_unroll : 0.000252s : 0.04% jit_opt_a.a_1 : 0.005412s : 0.86% jit_opt_a.with_stream_mark : 0.000098s : 0.02% jit_opt_a.recompute_prepare : 0.000062s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000030s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000021s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000020s : 0.00% jit_opt_a.parameter_eliminate : 0.000009s : 0.00% jit_opt_a.specialize_transform : 0.000047s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000046s : 0.01% jit_opt_a.accelerated_algorithm : 0.000113s : 0.02% jit_opt_a.meta_shard_fg_expand : 0.000018s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000042s : 0.01% jit_opt_a.merge_forward : 0.000027s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000092s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000080s : 0.01% jit_opt_a.meta_fg_expand : 0.004000s : 0.64% jit_opt_a.replace_old_param : 0.000187s : 0.03% jit_opt_a.inline_without_move : 0.000164s : 0.03% jit_opt_a.renormalize : 0.091773s : 14.58% jit_opt_a.add_forward_monad_depend : 0.000032s : 0.01% jit_opt_a.auto_monad_grad : 0.000014s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000116s : 0.02% jit_opt_a.cse : 0.000646s : 0.10% jit_opt_a.replace_applicator : 0.000158s : 0.03% py_interpret_to_execute_after_opt_a : 0.000023s : 0.00% rewriter_after_opt_a : 0.000254s : 0.04% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000911s : 0.14% jit_opt_b.frontend_op_eliminate : 0.000033s : 0.01% jit_opt_b.inline_after_opt_a : 0.000031s : 0.00% cconv : 0.000045s : 0.01% loop_unroll : 0.065376s : 10.39% jit_opt_after_cconv.c_1 : 0.000051s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000085s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000045s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000011s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000012s : 0.00% remove_dup_value : 0.000079s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000016s : 0.00% add_recomputation : 0.000092s : 0.01% cse_after_recomputation.cse : 0.000101s : 0.02% auto_monad_reorder : 0.000026s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000012s : 0.00% opt_after_jit_grad : 0.000665s : 0.11% symbol_engine_optimizer.build : 0.000016s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000018s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000074s : 0.01% backend_pass : 0.000001s : 0.00% task_emit : 0.009532s : 1.51% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.001552 228 2.89% : 0.000045s : 8: substitution.arithmetic_simplify 0.28% : 0.000004s : 4: substitution.elim_not_effective 0.19% : 0.000003s : 4: substitution.fold_const_symbol 0.59% : 0.000009s : 6: substitution.graph_param_transform 70.59% : 0.001095s : 32: substitution.inline 2.28% : 0.000035s : 3: substitution.inline_without_move 1.00% : 0.000015s : 20: substitution.j_node_and_user_rematch 2.02% : 0.000031s : 9: substitution.less_batch_normalization 1.53% : 0.000024s : 15: substitution.minmaximum_grad 0.76% : 0.000012s : 10: substitution.partial_eliminate 1.10% : 0.000017s : 20: substitution.remove_not_recompute_node 2.47% : 0.000038s : 9: substitution.replace_applicator 1.50% : 0.000023s : 21: substitution.replace_old_param 0.22% : 0.000003s : 1: substitution.set_cell_output_no_recompute 1.29% : 0.000020s : 5: substitution.switch_simplify 3.07% : 0.000048s : 15: substitution.tuple_list_convert_item_index_to_positive 2.02% : 0.000031s : 15: substitution.tuple_list_get_item_depend_reorder 6.20% : 0.000096s : 31: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.445028 2 87.69% : 0.390230s : 1: type_inference.infer 12.31% : 0.054798s : 1: type_inference.specialize ------[replace.] 0.000658 55 1.33% : 0.000009s : 2: replace.arithmetic_simplify 57.84% : 0.000381s : 32: replace.inline 15.27% : 0.000101s : 5: replace.switch_simplify 25.56% : 0.000168s : 16: replace.tuple_list_get_item_eliminator ------[match.] 0.001149 55 1.06% : 0.000012s : 2: match.arithmetic_simplify 93.68% : 0.001076s : 32: match.inline 1.46% : 0.000017s : 5: match.switch_simplify 3.79% : 0.000044s : 16: match.tuple_list_get_item_eliminator ------[predicate.] 0.000857 5087 1.62% : 0.000014s : 84: predicate.accumulaten_eliminater 0.27% : 0.000002s : 6: predicate.ad_related_special_op_eliminate 1.42% : 0.000012s : 84: predicate.addn_check_dump 1.35% : 0.000012s : 84: predicate.addn_zero_filter 2.15% : 0.000018s : 86: predicate.arithmetic_simplify 1.41% : 0.000012s : 86: predicate.cast_eliminate 0.13% : 0.000001s : 6: predicate.check_bprop_eliminate 1.40% : 0.000012s : 84: predicate.compare_switch_simplify 1.33% : 0.000011s : 84: predicate.depend_value_elim 1.50% : 0.000013s : 86: predicate.dict_get_item_const_eliminator 1.52% : 0.000013s : 86: predicate.dict_get_item_eliminator 1.37% : 0.000012s : 86: predicate.dict_set_item_eliminator 0.22% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.11% : 0.000001s : 6: predicate.elim_not_effective 0.14% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.42% : 0.000012s : 86: predicate.environ_add_const_eliminate 1.34% : 0.000011s : 86: predicate.environ_get_add_eliminate 4.63% : 0.000040s : 86: predicate.environ_get_depend_swap 1.44% : 0.000012s : 86: predicate.environ_get_eliminate 1.45% : 0.000012s : 86: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 6: predicate.fold_const_symbol 0.69% : 0.000006s : 31: predicate.get_grad_eliminate 0.09% : 0.000001s : 6: predicate.graph_param_transform 5.09% : 0.000044s : 146: predicate.inline 1.98% : 0.000017s : 78: predicate.inline_without_move 0.29% : 0.000002s : 31: predicate.j_node_and_user_rematch 0.92% : 0.000008s : 31: predicate.less_batch_normalization 1.71% : 0.000015s : 102: predicate.list_to_tuple_eliminator_ 1.84% : 0.000016s : 108: predicate.load_eliminater 0.91% : 0.000008s : 6: predicate.loop_unroll_after_grad 3.71% : 0.000032s : 193: predicate.loop_unroll_before_grad 1.72% : 0.000015s : 92: predicate.make_slice_get_slice_eliminator 1.39% : 0.000012s : 84: predicate.merge_addn 1.36% : 0.000012s : 86: predicate.minmaximum_grad 0.40% : 0.000003s : 6: predicate.mutable_eliminate 0.13% : 0.000001s : 6: predicate.opt_reshape 2.33% : 0.000020s : 108: predicate.partial_eliminate 1.39% : 0.000012s : 84: predicate.print_const_string_wrapper 1.74% : 0.000015s : 86: predicate.reduce_eliminate 1.80% : 0.000015s : 102: predicate.redundant_stop_gradient_eliminater 0.37% : 0.000003s : 31: predicate.remove_not_recompute_node 2.10% : 0.000018s : 162: predicate.replace_applicator 0.89% : 0.000008s : 78: predicate.replace_old_param 0.08% : 0.000001s : 6: predicate.reset_defer_inline 1.40% : 0.000012s : 86: predicate.reshape_eliminate 1.39% : 0.000012s : 84: predicate.row_tensor_add_zeros_like 0.26% : 0.000002s : 6: predicate.row_tensor_eliminate 1.31% : 0.000011s : 84: predicate.same_eliminate 0.34% : 0.000003s : 31: predicate.set_cell_output_no_recompute 0.27% : 0.000002s : 12: predicate.special_op_eliminate 0.77% : 0.000007s : 31: predicate.specialize_transform 1.55% : 0.000013s : 84: predicate.split_environ_get_set_with_tuple_value 1.32% : 0.000011s : 84: predicate.stack_unstack_eliminate 0.14% : 0.000001s : 6: predicate.switch_call_monad_eliminater 3.18% : 0.000027s : 134: predicate.switch_defer_inline 2.55% : 0.000022s : 134: predicate.switch_layer_defer_inline 6.82% : 0.000058s : 343: predicate.switch_simplify 1.40% : 0.000012s : 86: predicate.tile_eliminate 1.40% : 0.000012s : 86: predicate.transpose_eliminate 1.90% : 0.000016s : 86: predicate.tuple_list_convert_item_index_to_positive 1.69% : 0.000014s : 86: predicate.tuple_list_get_item_depend_reorder 3.15% : 0.000027s : 114: predicate.tuple_list_get_item_eliminator 1.89% : 0.000016s : 86: predicate.tuple_list_set_item_eliminator 1.70% : 0.000015s : 102: predicate.tuple_to_list_eliminator_ 1.74% : 0.000015s : 108: predicate.updatestate_pure_node_eliminater 2.62% : 0.000022s : 139: predicate.updatestate_useless_node_eliminater 1.71% : 0.000015s : 84: predicate.value_based_eliminate 0.09% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.17% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.007856 71 67.16% : 0.005276s : 32: func_graph_cloner_run.FuncGraphClonerGraph 0.86% : 0.000068s : 1: func_graph_cloner_run.FuncGraphClonerNode 31.98% : 0.002512s : 38: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.768832 91 0.01% : 0.000096s : 1: add_recomputation 0.03% : 0.000263s : 1: auto_monad 0.00% : 0.000029s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.07% : 0.000571s : 1: bootstrap 0.01% : 0.000048s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.02% : 0.000121s : 1: cse_after_recomputation 0.00% : 0.000019s : 1: environ_conv 0.01% : 0.000078s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000020s : 1: graph_reusing 18.70% : 0.143755s : 1: jit_opt_a 0.04% : 0.000327s : 1: jit_opt_after_cconv 0.01% : 0.000092s : 1: jit_opt_b 8.51% : 0.065407s : 1: loop_unroll 0.12% : 0.000924s : 1: mutable_eliminate 1.03% : 0.007902s : 39: opt.transform.jit_opt_a 0.01% : 0.000114s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000056s : 4: opt.transform.jit_opt_b 0.01% : 0.000046s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000030s : 1: opt.transform.mutable_eliminate 0.01% : 0.000042s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000066s : 4: opt.transform.symbol_engine_opt 0.09% : 0.000675s : 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% : 0.000008s : 1: pre_auto_parallel 0.01% : 0.000089s : 1: py_interpret_to_execute 0.00% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000084s : 1: remove_dup_value 11.38% : 0.087455s : 2: renormalize.infer 0.56% : 0.004286s : 2: renormalize.specialize 0.00% : 0.000014s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000260s : 1: rewriter_after_opt_a 0.05% : 0.000360s : 1: rewriter_before_opt_a 0.02% : 0.000130s : 1: symbol_engine_optimizer 1.24% : 0.009550s : 1: task_emit 57.96% : 0.445623s : 1: type_inference 0.03% : 0.000199s : 1: validate [WARNING] ME(169024:281473628827440,MainProcess):2026-01-29-17:40:12.459.656 [mindspore/graph/api.py:128] The function "addmm_backward_func_tensor" at the file "/home/jenkins/mindspore/testcases/testcases/tests/st/mint/test_addmm.py", line 65 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 = 1.71871, [33] [bootstrap]: 0.00048002 [type_inference]: 0.957633 [event_method]: 6.844e-05 [auto_monad]: 0.00024308 [graph_reusing]: 1.773e-05 [pre_auto_parallel]: 4.73001e-06 [py_interpret_to_execute]: 8.267e-05 [rewriter_before_opt_a]: 0.00033625 [expand_dump_flag]: 5.69999e-06 [jit_opt_a]: 0.61139, [3] [Cycle 1]: 0.231675, [27] [switch_simplify]: 0.00035364 [loop_unroll]: 0.00014391 [a_1]: 0.00355651 [with_stream_mark]: 4.889e-05 [recompute_prepare]: 4.023e-05 [updatestate_depend_eliminate]: 1.6e-05 [updatestate_assign_eliminate]: 1.139e-05 [updatestate_loads_eliminate]: 1.063e-05 [parameter_eliminate]: 4.21001e-06 [specialize_transform]: 2.639e-05 [updatestate_useless_node_eliminater]: 2.308e-05 [accelerated_algorithm]: 5.544e-05 [meta_shard_fg_expand]: 7.20998e-06 [get_grad_eliminate_]: 2.314e-05 [merge_forward]: 1.25e-05 [cell_reuse_recompute_pass]: 1.09998e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.696e-05 [j_node_and_user_rematch]: 6.026e-05 [meta_fg_expand]: 0.00386202 [replace_old_param]: 0.00018499 [inline_without_move]: 0.00013625 [renormalize]: 0.221907 [add_forward_monad_depend]: 2.021e-05 [auto_monad_grad]: 9.66998e-06 [auto_monad_eliminator]: 9.613e-05 [cse]: 0.00045596 [replace_applicator]: 0.00018882 [Cycle 2]: 0.0176101, [27] [switch_simplify]: 8.052e-05 [loop_unroll]: 7.616e-05 [a_1]: 0.0136384 [with_stream_mark]: 3.558e-05 [recompute_prepare]: 2.028e-05 [updatestate_depend_eliminate]: 8.35001e-06 [updatestate_assign_eliminate]: 6.58e-06 [updatestate_loads_eliminate]: 5.62999e-06 [parameter_eliminate]: 2.46e-06 [specialize_transform]: 1.313e-05 [updatestate_useless_node_eliminater]: 1.505e-05 [accelerated_algorithm]: 2.421e-05 [meta_shard_fg_expand]: 5.10001e-06 [get_grad_eliminate_]: 1.084e-05 [merge_forward]: 8.52998e-06 [cell_reuse_recompute_pass]: 1.61002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.413e-05 [j_node_and_user_rematch]: 1.859e-05 [meta_fg_expand]: 0.00064462 [replace_old_param]: 4.208e-05 [inline_without_move]: 1.275e-05 [renormalize]: 0.00239179 [add_forward_monad_depend]: 1.182e-05 [auto_monad_grad]: 2.98e-06 [auto_monad_eliminator]: 2.611e-05 [cse]: 0.00014561 [replace_applicator]: 3.132e-05 [Cycle 3]: 0.00060632, [27] [switch_simplify]: 1.17e-05 [loop_unroll]: 9.84999e-06 [a_1]: 0.0002002 [with_stream_mark]: 2.279e-05 [recompute_prepare]: 9.96998e-06 [updatestate_depend_eliminate]: 6.41e-06 [updatestate_assign_eliminate]: 5.41002e-06 [updatestate_loads_eliminate]: 4.90001e-06 [parameter_eliminate]: 2.07001e-06 [specialize_transform]: 9.52999e-06 [updatestate_useless_node_eliminater]: 9.41e-06 [accelerated_algorithm]: 2.442e-05 [meta_shard_fg_expand]: 3.08e-06 [get_grad_eliminate_]: 9.47999e-06 [merge_forward]: 6.36e-06 [cell_reuse_recompute_pass]: 3.65e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.454e-05 [j_node_and_user_rematch]: 1.618e-05 [meta_fg_expand]: 4.57998e-06 [replace_old_param]: 1.622e-05 [inline_without_move]: 9.01998e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.09e-06 [auto_monad_grad]: 1.85001e-06 [auto_monad_eliminator]: 1.206e-05 [cse]: 3.494e-05 [replace_applicator]: 1.181e-05 [py_interpret_to_execute_after_opt_a]: 4.001e-05 [rewriter_after_opt_a]: 0.0002498 [convert_after_rewriter]: 1.242e-05 [order_py_execute_after_rewriter]: 7.13e-06 [mutable_eliminate]: 0.00085445 [jit_opt_b]: 8.241e-05, [1] [Cycle 1]: 7.4e-05, [2] [frontend_op_eliminate]: 2.835e-05 [inline_after_opt_a]: 3.2e-05 [cconv]: 4.07e-05 [loop_unroll]: 0.00048514 [jit_opt_after_cconv]: 0.00023835, [1] [Cycle 1]: 0.00023116, [11] [c_1]: 4.163e-05 [parameter_eliminate]: 4.96997e-06 [updatestate_depend_eliminate]: 1.22e-05 [updatestate_assign_eliminate]: 5.15001e-06 [updatestate_loads_eliminate]: 4.57e-06 [cse]: 5.078e-05 [call_graph_tuple_transform]: 3.301e-05 [tuple_list_get_item_eliminator]: 1.025e-05 [none_parameter_eliminate]: 1.94e-06 [renormalize]: 8.80013e-07 [switch_simplify]: 1.055e-05 [remove_dup_value]: 0.00011208 [partial_unused_args_eliminate]: 4.01001e-06 [environ_conv]: 1.343e-05 [add_recomputation]: 8.269e-05 [cse_after_recomputation]: 4.417e-05, [1] [Cycle 1]: 3.691e-05, [1] [cse]: 2.84e-05 [auto_monad_reorder]: 2.757e-05 [get_jit_bprop_graph]: 3.33998e-06 [rewriter_after_jit_bprop_graph]: 7.55998e-06 [opt_after_jit_grad]: 0.00123342 [symbol_engine_optimizer]: 0.000127, [1] [Cycle 1]: 0.00011888, [6] [build]: 1.631e-05 [elim_shapecalc]: 1.414e-05 [elim_not_effective]: 2.428e-05 [opt_reshape]: 1.058e-05 [fold_const_symbol]: 1.964e-05 [renormalize]: 8.80013e-07 [validate]: 7.147e-05 [backend_pass]: 1.86998e-06 [task_emit]: 0.144256 [execute]: 1.099e-05 Sums bootstrap : 0.000480s : 0.04% type_inference : 0.957633s : 70.63% event_method : 0.000068s : 0.01% auto_monad : 0.000243s : 0.02% graph_reusing : 0.000018s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000083s : 0.01% rewriter_before_opt_a : 0.000336s : 0.02% expand_dump_flag : 0.000006s : 0.00% jit_opt_a.switch_simplify : 0.000446s : 0.03% jit_opt_a.loop_unroll : 0.000230s : 0.02% jit_opt_a.a_1 : 0.017395s : 1.28% jit_opt_a.with_stream_mark : 0.000107s : 0.01% jit_opt_a.recompute_prepare : 0.000070s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000031s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000023s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000021s : 0.00% jit_opt_a.parameter_eliminate : 0.000009s : 0.00% jit_opt_a.specialize_transform : 0.000049s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000048s : 0.00% jit_opt_a.accelerated_algorithm : 0.000104s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000015s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000043s : 0.00% jit_opt_a.merge_forward : 0.000027s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000096s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000095s : 0.01% jit_opt_a.meta_fg_expand : 0.004511s : 0.33% jit_opt_a.replace_old_param : 0.000243s : 0.02% jit_opt_a.inline_without_move : 0.000158s : 0.01% jit_opt_a.renormalize : 0.224299s : 16.54% jit_opt_a.add_forward_monad_depend : 0.000034s : 0.00% jit_opt_a.auto_monad_grad : 0.000014s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000134s : 0.01% jit_opt_a.cse : 0.000637s : 0.05% jit_opt_a.replace_applicator : 0.000232s : 0.02% py_interpret_to_execute_after_opt_a : 0.000040s : 0.00% rewriter_after_opt_a : 0.000250s : 0.02% convert_after_rewriter : 0.000012s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000854s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000028s : 0.00% jit_opt_b.inline_after_opt_a : 0.000032s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000485s : 0.04% jit_opt_after_cconv.c_1 : 0.000042s : 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 : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000051s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000033s : 0.00% 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 : 0.000112s : 0.01% partial_unused_args_eliminate : 0.000004s : 0.00% environ_conv : 0.000013s : 0.00% add_recomputation : 0.000083s : 0.01% cse_after_recomputation.cse : 0.000028s : 0.00% auto_monad_reorder : 0.000028s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.001233s : 0.09% symbol_engine_optimizer.build : 0.000016s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000014s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000024s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000071s : 0.01% backend_pass : 0.000002s : 0.00% task_emit : 0.144256s : 10.64% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.001900 259 4.44% : 0.000084s : 9: substitution.arithmetic_simplify 0.15% : 0.000003s : 4: substitution.elim_not_effective 0.16% : 0.000003s : 4: substitution.fold_const_symbol 0.41% : 0.000008s : 6: substitution.graph_param_transform 64.51% : 0.001225s : 36: substitution.inline 1.99% : 0.000038s : 4: substitution.inline_without_move 1.59% : 0.000030s : 22: substitution.j_node_and_user_rematch 1.73% : 0.000033s : 9: substitution.less_batch_normalization 4.85% : 0.000092s : 17: substitution.minmaximum_grad 0.63% : 0.000012s : 11: substitution.partial_eliminate 0.95% : 0.000018s : 22: substitution.remove_not_recompute_node 2.76% : 0.000052s : 14: substitution.replace_applicator 3.11% : 0.000059s : 24: substitution.replace_old_param 0.23% : 0.000004s : 1: substitution.set_cell_output_no_recompute 1.10% : 0.000021s : 5: substitution.switch_simplify 3.00% : 0.000057s : 17: substitution.tuple_list_convert_item_index_to_positive 2.09% : 0.000040s : 17: substitution.tuple_list_get_item_depend_reorder 6.31% : 0.000120s : 37: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.957088 2 99.37% : 0.951031s : 1: type_inference.infer 0.63% : 0.006057s : 1: type_inference.specialize ------[replace.] 0.000660 62 0.88% : 0.000006s : 1: replace.arithmetic_simplify 55.64% : 0.000367s : 36: replace.inline 15.14% : 0.000100s : 5: replace.switch_simplify 28.33% : 0.000187s : 20: replace.tuple_list_get_item_eliminator ------[match.] 0.001291 62 0.81% : 0.000010s : 1: match.arithmetic_simplify 93.19% : 0.001203s : 36: match.inline 1.33% : 0.000017s : 5: match.switch_simplify 4.67% : 0.000060s : 20: match.tuple_list_get_item_eliminator ------[predicate.] 0.011952 5834 0.13% : 0.000015s : 97: predicate.accumulaten_eliminater 0.03% : 0.000004s : 6: predicate.ad_related_special_op_eliminate 0.11% : 0.000013s : 97: predicate.addn_check_dump 0.12% : 0.000015s : 97: predicate.addn_zero_filter 0.18% : 0.000022s : 98: predicate.arithmetic_simplify 0.11% : 0.000014s : 98: predicate.cast_eliminate 0.01% : 0.000001s : 6: predicate.check_bprop_eliminate 0.11% : 0.000013s : 97: predicate.compare_switch_simplify 0.12% : 0.000014s : 97: predicate.depend_value_elim 0.11% : 0.000013s : 98: predicate.dict_get_item_const_eliminator 0.12% : 0.000015s : 98: predicate.dict_get_item_eliminator 0.12% : 0.000014s : 98: predicate.dict_set_item_eliminator 0.02% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.01% : 0.000001s : 6: predicate.elim_not_effective 0.01% : 0.000002s : 6: predicate.elim_shapecalc_of_broadcastargs 0.12% : 0.000015s : 98: predicate.environ_add_const_eliminate 0.11% : 0.000013s : 98: predicate.environ_get_add_eliminate 0.12% : 0.000014s : 98: predicate.environ_get_depend_swap 0.12% : 0.000014s : 98: predicate.environ_get_eliminate 0.12% : 0.000014s : 98: predicate.environ_get_set_eliminate 0.00% : 0.000001s : 6: predicate.fold_const_symbol 0.05% : 0.000006s : 33: predicate.get_grad_eliminate 0.01% : 0.000001s : 6: predicate.graph_param_transform 92.29% : 0.011031s : 166: predicate.inline 0.17% : 0.000020s : 97: predicate.inline_without_move 0.02% : 0.000003s : 33: predicate.j_node_and_user_rematch 0.07% : 0.000008s : 33: predicate.less_batch_normalization 0.15% : 0.000018s : 118: predicate.list_to_tuple_eliminator_ 0.15% : 0.000018s : 124: predicate.load_eliminater 0.02% : 0.000003s : 6: predicate.loop_unroll_after_grad 0.28% : 0.000033s : 223: predicate.loop_unroll_before_grad 0.13% : 0.000015s : 104: predicate.make_slice_get_slice_eliminator 0.12% : 0.000014s : 97: predicate.merge_addn 0.12% : 0.000014s : 98: predicate.minmaximum_grad 0.03% : 0.000003s : 6: predicate.mutable_eliminate 0.01% : 0.000001s : 6: predicate.opt_reshape 0.20% : 0.000024s : 124: predicate.partial_eliminate 0.13% : 0.000015s : 97: predicate.print_const_string_wrapper 0.15% : 0.000018s : 98: predicate.reduce_eliminate 0.15% : 0.000018s : 118: predicate.redundant_stop_gradient_eliminater 0.03% : 0.000003s : 33: predicate.remove_not_recompute_node 0.19% : 0.000022s : 205: predicate.replace_applicator 0.08% : 0.000010s : 97: predicate.replace_old_param 0.01% : 0.000001s : 6: predicate.reset_defer_inline 0.12% : 0.000014s : 98: predicate.reshape_eliminate 0.12% : 0.000014s : 97: predicate.row_tensor_add_zeros_like 0.01% : 0.000001s : 6: predicate.row_tensor_eliminate 0.12% : 0.000014s : 97: predicate.same_eliminate 0.03% : 0.000003s : 33: predicate.set_cell_output_no_recompute 0.02% : 0.000002s : 12: predicate.special_op_eliminate 0.05% : 0.000006s : 33: predicate.specialize_transform 0.13% : 0.000016s : 97: predicate.split_environ_get_set_with_tuple_value 0.11% : 0.000014s : 97: predicate.stack_unstack_eliminate 0.01% : 0.000001s : 6: predicate.switch_call_monad_eliminater 0.26% : 0.000031s : 154: predicate.switch_defer_inline 0.21% : 0.000025s : 154: predicate.switch_layer_defer_inline 0.54% : 0.000064s : 393: predicate.switch_simplify 0.30% : 0.000036s : 98: predicate.tile_eliminate 0.12% : 0.000014s : 98: predicate.transpose_eliminate 0.15% : 0.000018s : 98: predicate.tuple_list_convert_item_index_to_positive 0.14% : 0.000017s : 98: predicate.tuple_list_get_item_depend_reorder 0.27% : 0.000032s : 130: predicate.tuple_list_get_item_eliminator 0.17% : 0.000020s : 98: predicate.tuple_list_set_item_eliminator 0.14% : 0.000017s : 118: predicate.tuple_to_list_eliminator_ 0.15% : 0.000018s : 124: predicate.updatestate_pure_node_eliminater 0.22% : 0.000026s : 157: predicate.updatestate_useless_node_eliminater 0.14% : 0.000017s : 97: predicate.value_based_eliminate 0.01% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.01% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.006871 79 65.34% : 0.004490s : 36: func_graph_cloner_run.FuncGraphClonerGraph 34.66% : 0.002382s : 43: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.962347 91 0.00% : 0.000086s : 1: add_recomputation 0.01% : 0.000250s : 1: auto_monad 0.00% : 0.000031s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: backend_pass 0.03% : 0.000505s : 1: bootstrap 0.00% : 0.000044s : 1: cconv 0.00% : 0.000015s : 1: convert_after_rewriter 0.00% : 0.000046s : 1: cse_after_recomputation 0.00% : 0.000017s : 1: environ_conv 0.00% : 0.000075s : 1: event_method 0.00% : 0.000017s : 1: execute 0.00% : 0.000055s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000021s : 1: graph_reusing 31.16% : 0.611395s : 1: jit_opt_a 0.01% : 0.000242s : 1: jit_opt_after_cconv 0.00% : 0.000085s : 1: jit_opt_b 0.03% : 0.000494s : 1: loop_unroll 0.04% : 0.000868s : 1: mutable_eliminate 0.97% : 0.019128s : 39: opt.transform.jit_opt_a 0.00% : 0.000092s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000052s : 4: opt.transform.jit_opt_b 0.00% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000026s : 1: opt.transform.mutable_eliminate 0.00% : 0.000046s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000065s : 4: opt.transform.symbol_engine_opt 0.06% : 0.001250s : 1: opt_after_jit_grad 0.00% : 0.000009s : 1: order_py_execute_after_rewriter 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000086s : 1: py_interpret_to_execute 0.00% : 0.000046s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000117s : 1: remove_dup_value 11.19% : 0.219682s : 2: renormalize.infer 0.23% : 0.004586s : 2: renormalize.specialize 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000256s : 1: rewriter_after_opt_a 0.02% : 0.000341s : 1: rewriter_before_opt_a 0.01% : 0.000130s : 1: symbol_engine_optimizer 7.35% : 0.144277s : 1: task_emit 48.80% : 0.957657s : 1: type_inference 0.01% : 0.000201s : 1: validate . [hook] pytest_runtest_teardown:test_addmm_tensor[KBK] tests/st/mint/test_addmm.py::test_addmm_tensor[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 206.88s (0:03:26) ==================