==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/mint, configfile: ../../../../../../sault/virtual_test/virtualenv_008/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_chunk.py . [hook] pytest_runtest_teardown:test_chunk_empty_tensor[pynative] tests/st/mint/test_chunk.py::test_chunk_empty_tensor[pynative],max_mem:2.0M TotalTime = 0.664512, [30] [bootstrap]: 0.00064171 [type_inference]: 0.520905 [event_method]: 1.789e-05 [auto_monad]: 0.00015508 [graph_reusing]: 6.43e-06 [pre_auto_parallel]: 3.054e-05 [py_interpret_to_execute]: 0.00012933 [rewriter_before_opt_a]: 7.634e-05 [expand_dump_flag]: 3.86999e-06 [jit_opt_a]: 0.139656, [2] [Cycle 1]: 0.00206027, [27] [switch_simplify]: 5.595e-05 [loop_unroll]: 2.062e-05 [a_1]: 0.00043688 [with_stream_mark]: 2.952e-05 [recompute_prepare]: 1.25e-05 [updatestate_depend_eliminate]: 7.36999e-06 [updatestate_assign_eliminate]: 8.99e-06 [updatestate_loads_eliminate]: 5.57001e-06 [parameter_eliminate]: 1.89999e-06 [specialize_transform]: 1.035e-05 [updatestate_useless_node_eliminater]: 1.282e-05 [accelerated_algorithm]: 9.45001e-06 [meta_shard_fg_expand]: 2.87002e-06 [get_grad_eliminate_]: 9.66e-06 [merge_forward]: 6.32001e-06 [cell_reuse_recompute_pass]: 1.29e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.446e-05 [j_node_and_user_rematch]: 1.563e-05 [meta_fg_expand]: 4.51002e-06 [replace_old_param]: 1.335e-05 [inline_without_move]: 8.79998e-06 [renormalize]: 0.00105043 [add_forward_monad_depend]: 5.09998e-06 [auto_monad_grad]: 2.32999e-06 [auto_monad_eliminator]: 2.113e-05 [cse]: 5.222e-05 [replace_applicator]: 1.65e-05 [Cycle 2]: 0.00051012, [27] [switch_simplify]: 9.82001e-06 [loop_unroll]: 8.48999e-06 [a_1]: 0.00018161 [with_stream_mark]: 1.181e-05 [recompute_prepare]: 9.15999e-06 [updatestate_depend_eliminate]: 5.46998e-06 [updatestate_assign_eliminate]: 7.63001e-06 [updatestate_loads_eliminate]: 4.66002e-06 [parameter_eliminate]: 1.27999e-06 [specialize_transform]: 9.32999e-06 [updatestate_useless_node_eliminater]: 1.18e-05 [accelerated_algorithm]: 8.84e-06 [meta_shard_fg_expand]: 1.84998e-06 [get_grad_eliminate_]: 8.18999e-06 [merge_forward]: 5.17999e-06 [cell_reuse_recompute_pass]: 1.60999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.786e-05 [j_node_and_user_rematch]: 1.363e-05 [meta_fg_expand]: 2.96999e-06 [replace_old_param]: 1.078e-05 [inline_without_move]: 8.31002e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.34998e-06 [auto_monad_grad]: 7.90023e-07 [auto_monad_eliminator]: 1.125e-05 [cse]: 2.09e-05 [replace_applicator]: 8.90001e-06 [py_interpret_to_execute_after_opt_a]: 3.231e-05 [rewriter_after_opt_a]: 0.00030305 [convert_after_rewriter]: 1.335e-05 [order_py_execute_after_rewriter]: 7.35e-06 [mutable_eliminate]: 0.00057337 [jit_opt_b]: 7.243e-05, [1] [Cycle 1]: 6.485e-05, [2] [frontend_op_eliminate]: 2.614e-05 [inline_after_opt_a]: 2.574e-05 [cconv]: 2.809e-05 [loop_unroll]: 0.00045717 [jit_opt_after_cconv]: 0.00020784, [1] [Cycle 1]: 0.00020158, [11] [c_1]: 4.975e-05 [parameter_eliminate]: 2.46e-06 [updatestate_depend_eliminate]: 9.04e-06 [updatestate_assign_eliminate]: 5.08002e-06 [updatestate_loads_eliminate]: 4.15e-06 [cse]: 3.062e-05 [call_graph_tuple_transform]: 2.354e-05 [tuple_list_get_item_eliminator]: 9.88002e-06 [none_parameter_eliminate]: 1.55999e-06 [renormalize]: 3.00002e-07 [switch_simplify]: 9.27001e-06 [remove_dup_value]: 2.136e-05 [partial_unused_args_eliminate]: 2.24999e-06 [environ_conv]: 2.302e-05 [add_recomputation]: 7.391e-05 [cse_after_recomputation]: 3.276e-05, [1] [Cycle 1]: 2.688e-05, [1] [cse]: 1.993e-05 [auto_monad_reorder]: 3.358e-05 [get_jit_bprop_graph]: 1.97001e-06 [rewriter_after_jit_bprop_graph]: 3.33998e-06 [opt_after_jit_grad]: 0.00051211 [symbol_engine_optimizer]: 0.00010878, [1] [Cycle 1]: 0.00010244, [6] [build]: 1.326e-05 [elim_shapecalc]: 1.344e-05 [elim_not_effective]: 1.977e-05 [opt_reshape]: 9.62999e-06 [fold_const_symbol]: 1.468e-05 [renormalize]: 4.09986e-07 [validate]: 7.477e-05 Sums bootstrap : 0.000642s : 0.12% type_inference : 0.520905s : 98.91% event_method : 0.000018s : 0.00% auto_monad : 0.000155s : 0.03% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000031s : 0.01% py_interpret_to_execute : 0.000129s : 0.02% rewriter_before_opt_a : 0.000076s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000066s : 0.01% jit_opt_a.loop_unroll : 0.000029s : 0.01% jit_opt_a.a_1 : 0.000618s : 0.12% jit_opt_a.with_stream_mark : 0.000041s : 0.01% jit_opt_a.recompute_prepare : 0.000022s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000017s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.00% jit_opt_a.accelerated_algorithm : 0.000018s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000018s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000042s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000029s : 0.01% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.001050s : 0.20% jit_opt_a.add_forward_monad_depend : 0.000006s : 0.00% jit_opt_a.auto_monad_grad : 0.000003s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000032s : 0.01% jit_opt_a.cse : 0.000073s : 0.01% jit_opt_a.replace_applicator : 0.000025s : 0.00% py_interpret_to_execute_after_opt_a : 0.000032s : 0.01% rewriter_after_opt_a : 0.000303s : 0.06% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000573s : 0.11% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.00% jit_opt_b.inline_after_opt_a : 0.000026s : 0.00% cconv : 0.000028s : 0.01% loop_unroll : 0.000457s : 0.09% jit_opt_after_cconv.c_1 : 0.000050s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000031s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 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 : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000021s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000023s : 0.00% add_recomputation : 0.000074s : 0.01% cse_after_recomputation.cse : 0.000020s : 0.00% auto_monad_reorder : 0.000034s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000003s : 0.00% opt_after_jit_grad : 0.000512s : 0.10% symbol_engine_optimizer.build : 0.000013s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000075s : 0.01% Time group info: ------[substitution.] 0.000200 43 4.27% : 0.000009s : 2: substitution.depend_value_elim 1.60% : 0.000003s : 4: substitution.elim_not_effective 1.10% : 0.000002s : 4: substitution.fold_const_symbol 3.40% : 0.000007s : 5: substitution.graph_param_transform 71.23% : 0.000143s : 2: substitution.inline 2.57% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.92% : 0.000008s : 8: substitution.remove_not_recompute_node 2.37% : 0.000005s : 2: substitution.replace_old_param 4.69% : 0.000009s : 3: substitution.updatestate_pure_node_eliminater 4.84% : 0.000010s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.520811 2 99.78% : 0.519649s : 1: type_inference.infer 0.22% : 0.001162s : 1: type_inference.specialize ------[replace.] 0.000029 2 100.00% : 0.000029s : 2: replace.inline ------[match.] 0.000141 2 100.00% : 0.000141s : 2: match.inline ------[predicate.] 0.000152 767 1.19% : 0.000002s : 11: predicate.accumulaten_eliminater 1.51% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.09% : 0.000002s : 11: predicate.addn_check_dump 1.29% : 0.000002s : 11: predicate.addn_zero_filter 2.03% : 0.000003s : 11: predicate.arithmetic_simplify 1.22% : 0.000002s : 11: predicate.cast_eliminate 0.55% : 0.000001s : 5: predicate.check_bprop_eliminate 1.13% : 0.000002s : 11: predicate.compare_switch_simplify 1.34% : 0.000002s : 11: predicate.depend_value_elim 1.11% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.20% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.16% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.15% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.41% : 0.000001s : 5: predicate.elim_not_effective 0.86% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.26% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.17% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.15% : 0.000002s : 11: predicate.environ_get_depend_swap 1.19% : 0.000002s : 11: predicate.environ_get_eliminate 1.11% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.36% : 0.000001s : 5: predicate.fold_const_symbol 1.36% : 0.000002s : 10: predicate.get_grad_eliminate 0.36% : 0.000001s : 5: predicate.graph_param_transform 5.90% : 0.000009s : 23: predicate.inline 1.51% : 0.000002s : 10: predicate.inline_without_move 0.63% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.46% : 0.000002s : 10: predicate.less_batch_normalization 1.17% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.94% : 0.000003s : 16: predicate.load_eliminater 1.86% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.44% : 0.000004s : 20: predicate.loop_unroll_before_grad 2.03% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.11% : 0.000002s : 11: predicate.merge_addn 1.11% : 0.000002s : 11: predicate.minmaximum_grad 1.96% : 0.000003s : 5: predicate.mutable_eliminate 0.78% : 0.000001s : 5: predicate.opt_reshape 2.42% : 0.000004s : 16: predicate.partial_eliminate 1.15% : 0.000002s : 11: predicate.print_const_string_wrapper 1.49% : 0.000002s : 11: predicate.reduce_eliminate 1.21% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.90% : 0.000001s : 10: predicate.remove_not_recompute_node 1.76% : 0.000003s : 21: predicate.replace_applicator 1.09% : 0.000002s : 10: predicate.replace_old_param 0.48% : 0.000001s : 5: predicate.reset_defer_inline 1.19% : 0.000002s : 11: predicate.reshape_eliminate 1.20% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.84% : 0.000001s : 5: predicate.row_tensor_eliminate 1.36% : 0.000002s : 11: predicate.same_eliminate 0.73% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.39% : 0.000002s : 10: predicate.special_op_eliminate 1.58% : 0.000002s : 10: predicate.specialize_transform 1.38% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.22% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.72% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.63% : 0.000002s : 13: predicate.switch_defer_inline 1.55% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.81% : 0.000009s : 38: predicate.switch_simplify 1.36% : 0.000002s : 11: predicate.tile_eliminate 1.35% : 0.000002s : 11: predicate.transpose_eliminate 1.41% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.29% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.40% : 0.000005s : 21: predicate.tuple_list_get_item_eliminator 1.49% : 0.000002s : 11: predicate.tuple_list_set_item_eliminator 1.23% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.84% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.53% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.51% : 0.000002s : 11: predicate.value_based_eliminate 0.58% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.80% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000487 6 32.84% : 0.000160s : 2: func_graph_cloner_run.FuncGraphClonerGraph 67.16% : 0.000327s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.666485 72 0.01% : 0.000077s : 1: add_recomputation 0.02% : 0.000161s : 1: auto_monad 0.01% : 0.000037s : 1: auto_monad_reorder 0.10% : 0.000663s : 1: bootstrap 0.00% : 0.000031s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.01% : 0.000035s : 1: cse_after_recomputation 0.00% : 0.000026s : 1: environ_conv 0.00% : 0.000023s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 20.95% : 0.139660s : 1: jit_opt_a 0.03% : 0.000211s : 1: jit_opt_after_cconv 0.01% : 0.000076s : 1: jit_opt_b 0.07% : 0.000465s : 1: loop_unroll 0.09% : 0.000580s : 1: mutable_eliminate 0.14% : 0.000912s : 26: opt.transform.jit_opt_a 0.01% : 0.000088s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000019s : 1: opt.transform.mutable_eliminate 0.00% : 0.000032s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000054s : 4: opt.transform.symbol_engine_opt 0.08% : 0.000520s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.01% : 0.000034s : 1: pre_auto_parallel 0.02% : 0.000133s : 1: py_interpret_to_execute 0.01% : 0.000036s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000024s : 1: remove_dup_value 0.10% : 0.000688s : 1: renormalize.infer 0.05% : 0.000355s : 1: renormalize.specialize 0.00% : 0.000005s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000308s : 1: rewriter_after_opt_a 0.01% : 0.000080s : 1: rewriter_before_opt_a 0.02% : 0.000112s : 1: symbol_engine_optimizer 78.16% : 0.520928s : 1: type_inference TotalTime = 0.0861303, [30] [bootstrap]: 0.00052968 [type_inference]: 0.0751938 [event_method]: 1.482e-05 [auto_monad]: 0.00014224 [graph_reusing]: 6.53e-06 [pre_auto_parallel]: 2.62001e-06 [py_interpret_to_execute]: 9.505e-05 [rewriter_before_opt_a]: 6.319e-05 [expand_dump_flag]: 2.92002e-06 [jit_opt_a]: 0.00685055, [2] [Cycle 1]: 0.00228227, [27] [switch_simplify]: 5.175e-05 [loop_unroll]: 2.277e-05 [a_1]: 0.00047939 [with_stream_mark]: 3.101e-05 [recompute_prepare]: 1.659e-05 [updatestate_depend_eliminate]: 7.71001e-06 [updatestate_assign_eliminate]: 8.2e-06 [updatestate_loads_eliminate]: 5.39998e-06 [parameter_eliminate]: 1.97001e-06 [specialize_transform]: 1.165e-05 [updatestate_useless_node_eliminater]: 1.549e-05 [accelerated_algorithm]: 1.009e-05 [meta_shard_fg_expand]: 3.18e-06 [get_grad_eliminate_]: 9.57001e-06 [merge_forward]: 6.06e-06 [cell_reuse_recompute_pass]: 1.41002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.494e-05 [j_node_and_user_rematch]: 1.802e-05 [meta_fg_expand]: 5.06002e-06 [replace_old_param]: 1.546e-05 [inline_without_move]: 1.038e-05 [renormalize]: 0.00120039 [add_forward_monad_depend]: 7.2e-06 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 2.693e-05 [cse]: 4.378e-05 [replace_applicator]: 2.342e-05 [Cycle 2]: 0.0006122, [27] [switch_simplify]: 1.146e-05 [loop_unroll]: 9.37001e-06 [a_1]: 0.00021323 [with_stream_mark]: 1.917e-05 [recompute_prepare]: 1.154e-05 [updatestate_depend_eliminate]: 7.62002e-06 [updatestate_assign_eliminate]: 5.75001e-06 [updatestate_loads_eliminate]: 5.97999e-06 [parameter_eliminate]: 1.56998e-06 [specialize_transform]: 1.044e-05 [updatestate_useless_node_eliminater]: 1.384e-05 [accelerated_algorithm]: 9.77999e-06 [meta_shard_fg_expand]: 2.49999e-06 [get_grad_eliminate_]: 1.038e-05 [merge_forward]: 6.21e-06 [cell_reuse_recompute_pass]: 2.89001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.154e-05 [j_node_and_user_rematch]: 1.706e-05 [meta_fg_expand]: 4.22003e-06 [replace_old_param]: 1.32e-05 [inline_without_move]: 9.14e-06 [renormalize]: 1.19995e-07 [add_forward_monad_depend]: 2.40002e-06 [auto_monad_grad]: 1.36998e-06 [auto_monad_eliminator]: 1.475e-05 [cse]: 2.597e-05 [replace_applicator]: 1.113e-05 [py_interpret_to_execute_after_opt_a]: 1.816e-05 [rewriter_after_opt_a]: 0.00027936 [convert_after_rewriter]: 1.724e-05 [order_py_execute_after_rewriter]: 7.71999e-06 [mutable_eliminate]: 0.00076786 [jit_opt_b]: 8.884e-05, [1] [Cycle 1]: 7.866e-05, [2] [frontend_op_eliminate]: 3.129e-05 [inline_after_opt_a]: 3.11e-05 [cconv]: 3.434e-05 [loop_unroll]: 0.0005625 [jit_opt_after_cconv]: 0.00025721, [1] [Cycle 1]: 0.0002475, [11] [c_1]: 6.133e-05 [parameter_eliminate]: 4.75001e-06 [updatestate_depend_eliminate]: 1.179e-05 [updatestate_assign_eliminate]: 5.57001e-06 [updatestate_loads_eliminate]: 5.42999e-06 [cse]: 3.92e-05 [call_graph_tuple_transform]: 2.906e-05 [tuple_list_get_item_eliminator]: 1.165e-05 [none_parameter_eliminate]: 1.40001e-06 [renormalize]: 7.09988e-07 [switch_simplify]: 1.126e-05 [remove_dup_value]: 2.275e-05 [partial_unused_args_eliminate]: 2.90002e-06 [environ_conv]: 1.489e-05 [add_recomputation]: 8.085e-05 [cse_after_recomputation]: 3.641e-05, [1] [Cycle 1]: 2.916e-05, [1] [cse]: 2.095e-05 [auto_monad_reorder]: 2.845e-05 [get_jit_bprop_graph]: 2.49999e-06 [rewriter_after_jit_bprop_graph]: 5.64e-06 [opt_after_jit_grad]: 0.00059787 [symbol_engine_optimizer]: 0.00011725, [1] [Cycle 1]: 0.00010973, [6] [build]: 1.568e-05 [elim_shapecalc]: 1.313e-05 [elim_not_effective]: 2.22e-05 [opt_reshape]: 1.016e-05 [fold_const_symbol]: 1.658e-05 [renormalize]: 4.60015e-07 [validate]: 6.628e-05 Sums bootstrap : 0.000530s : 0.65% type_inference : 0.075194s : 92.34% event_method : 0.000015s : 0.02% auto_monad : 0.000142s : 0.17% graph_reusing : 0.000007s : 0.01% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000095s : 0.12% rewriter_before_opt_a : 0.000063s : 0.08% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000063s : 0.08% jit_opt_a.loop_unroll : 0.000032s : 0.04% jit_opt_a.a_1 : 0.000693s : 0.85% jit_opt_a.with_stream_mark : 0.000050s : 0.06% jit_opt_a.recompute_prepare : 0.000028s : 0.03% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.02% jit_opt_a.updatestate_assign_eliminate : 0.000014s : 0.02% jit_opt_a.updatestate_loads_eliminate : 0.000011s : 0.01% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000022s : 0.03% jit_opt_a.updatestate_useless_node_eliminater : 0.000029s : 0.04% jit_opt_a.accelerated_algorithm : 0.000020s : 0.02% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.01% jit_opt_a.get_grad_eliminate_ : 0.000020s : 0.02% jit_opt_a.merge_forward : 0.000012s : 0.02% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.01% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000046s : 0.06% jit_opt_a.j_node_and_user_rematch : 0.000035s : 0.04% jit_opt_a.meta_fg_expand : 0.000009s : 0.01% jit_opt_a.replace_old_param : 0.000029s : 0.04% jit_opt_a.inline_without_move : 0.000020s : 0.02% jit_opt_a.renormalize : 0.001201s : 1.47% jit_opt_a.add_forward_monad_depend : 0.000010s : 0.01% jit_opt_a.auto_monad_grad : 0.000004s : 0.01% jit_opt_a.auto_monad_eliminator : 0.000042s : 0.05% jit_opt_a.cse : 0.000070s : 0.09% jit_opt_a.replace_applicator : 0.000035s : 0.04% py_interpret_to_execute_after_opt_a : 0.000018s : 0.02% rewriter_after_opt_a : 0.000279s : 0.34% convert_after_rewriter : 0.000017s : 0.02% order_py_execute_after_rewriter : 0.000008s : 0.01% mutable_eliminate : 0.000768s : 0.94% jit_opt_b.frontend_op_eliminate : 0.000031s : 0.04% jit_opt_b.inline_after_opt_a : 0.000031s : 0.04% cconv : 0.000034s : 0.04% loop_unroll : 0.000563s : 0.69% jit_opt_after_cconv.c_1 : 0.000061s : 0.08% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.01% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.01% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.01% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.01% jit_opt_after_cconv.cse : 0.000039s : 0.05% jit_opt_after_cconv.call_graph_tuple_transform : 0.000029s : 0.04% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 0.01% jit_opt_after_cconv.none_parameter_eliminate : 0.000001s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000011s : 0.01% remove_dup_value : 0.000023s : 0.03% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000015s : 0.02% add_recomputation : 0.000081s : 0.10% cse_after_recomputation.cse : 0.000021s : 0.03% auto_monad_reorder : 0.000028s : 0.03% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.01% opt_after_jit_grad : 0.000598s : 0.73% symbol_engine_optimizer.build : 0.000016s : 0.02% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.02% symbol_engine_optimizer.elim_not_effective : 0.000022s : 0.03% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.02% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000066s : 0.08% Time group info: ------[substitution.] 0.000218 43 4.79% : 0.000010s : 2: substitution.depend_value_elim 1.53% : 0.000003s : 4: substitution.elim_not_effective 1.38% : 0.000003s : 4: substitution.fold_const_symbol 3.91% : 0.000009s : 5: substitution.graph_param_transform 68.01% : 0.000148s : 2: substitution.inline 2.47% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.95% : 0.000009s : 8: substitution.remove_not_recompute_node 3.05% : 0.000007s : 2: substitution.replace_old_param 5.87% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 5.04% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.075125 2 98.71% : 0.074152s : 1: type_inference.infer 1.29% : 0.000973s : 1: type_inference.specialize ------[replace.] 0.000031 2 100.00% : 0.000031s : 2: replace.inline ------[match.] 0.000146 2 100.00% : 0.000146s : 2: match.inline ------[predicate.] 0.000181 767 1.31% : 0.000002s : 11: predicate.accumulaten_eliminater 1.30% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.11% : 0.000002s : 11: predicate.addn_check_dump 1.16% : 0.000002s : 11: predicate.addn_zero_filter 1.84% : 0.000003s : 11: predicate.arithmetic_simplify 1.33% : 0.000002s : 11: predicate.cast_eliminate 0.68% : 0.000001s : 5: predicate.check_bprop_eliminate 1.09% : 0.000002s : 11: predicate.compare_switch_simplify 1.43% : 0.000003s : 11: predicate.depend_value_elim 1.18% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.06% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.12% : 0.000002s : 11: predicate.dict_set_item_eliminator 1.10% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.55% : 0.000001s : 5: predicate.elim_not_effective 0.74% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.26% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.12% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.51% : 0.000003s : 11: predicate.environ_get_depend_swap 1.17% : 0.000002s : 11: predicate.environ_get_eliminate 1.13% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.38% : 0.000001s : 5: predicate.fold_const_symbol 1.60% : 0.000003s : 10: predicate.get_grad_eliminate 0.38% : 0.000001s : 5: predicate.graph_param_transform 5.27% : 0.000010s : 23: predicate.inline 1.56% : 0.000003s : 10: predicate.inline_without_move 0.54% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.52% : 0.000003s : 10: predicate.less_batch_normalization 1.24% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.99% : 0.000004s : 16: predicate.load_eliminater 2.08% : 0.000004s : 5: predicate.loop_unroll_after_grad 2.35% : 0.000004s : 20: predicate.loop_unroll_before_grad 1.99% : 0.000004s : 16: predicate.make_slice_get_slice_eliminator 1.13% : 0.000002s : 11: predicate.merge_addn 1.09% : 0.000002s : 11: predicate.minmaximum_grad 2.44% : 0.000004s : 5: predicate.mutable_eliminate 0.56% : 0.000001s : 5: predicate.opt_reshape 2.20% : 0.000004s : 16: predicate.partial_eliminate 1.07% : 0.000002s : 11: predicate.print_const_string_wrapper 1.46% : 0.000003s : 11: predicate.reduce_eliminate 1.19% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 0.79% : 0.000001s : 10: predicate.remove_not_recompute_node 1.57% : 0.000003s : 21: predicate.replace_applicator 0.96% : 0.000002s : 10: predicate.replace_old_param 0.88% : 0.000002s : 5: predicate.reset_defer_inline 1.17% : 0.000002s : 11: predicate.reshape_eliminate 1.24% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 1.06% : 0.000002s : 5: predicate.row_tensor_eliminate 1.29% : 0.000002s : 11: predicate.same_eliminate 0.64% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.35% : 0.000002s : 10: predicate.special_op_eliminate 1.45% : 0.000003s : 10: predicate.specialize_transform 1.25% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.14% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.70% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.70% : 0.000003s : 13: predicate.switch_defer_inline 1.50% : 0.000003s : 13: predicate.switch_layer_defer_inline 5.86% : 0.000011s : 38: predicate.switch_simplify 1.20% : 0.000002s : 11: predicate.tile_eliminate 1.28% : 0.000002s : 11: predicate.transpose_eliminate 1.52% : 0.000003s : 11: predicate.tuple_list_convert_item_index_to_positive 1.29% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 3.39% : 0.000006s : 21: predicate.tuple_list_get_item_eliminator 1.67% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.21% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.94% : 0.000004s : 16: predicate.updatestate_pure_node_eliminater 3.74% : 0.000007s : 26: predicate.updatestate_useless_node_eliminater 1.69% : 0.000003s : 11: predicate.value_based_eliminate 0.46% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.88% : 0.000002s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000424 6 29.14% : 0.000124s : 2: func_graph_cloner_run.FuncGraphClonerGraph 70.86% : 0.000301s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.088516 72 0.10% : 0.000085s : 1: add_recomputation 0.17% : 0.000147s : 1: auto_monad 0.04% : 0.000031s : 1: auto_monad_reorder 0.63% : 0.000555s : 1: bootstrap 0.04% : 0.000037s : 1: cconv 0.02% : 0.000021s : 1: convert_after_rewriter 0.04% : 0.000039s : 1: cse_after_recomputation 0.02% : 0.000018s : 1: environ_conv 0.02% : 0.000020s : 1: event_method 0.01% : 0.000005s : 1: expand_dump_flag 0.01% : 0.000005s : 1: get_jit_bprop_graph 0.01% : 0.000009s : 1: graph_reusing 7.74% : 0.006855s : 1: jit_opt_a 0.30% : 0.000261s : 1: jit_opt_after_cconv 0.10% : 0.000092s : 1: jit_opt_b 0.65% : 0.000571s : 1: loop_unroll 0.88% : 0.000778s : 1: mutable_eliminate 1.16% : 0.001030s : 26: opt.transform.jit_opt_a 0.12% : 0.000108s : 4: opt.transform.jit_opt_after_cconv 0.06% : 0.000054s : 4: opt.transform.jit_opt_b 0.03% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.03% : 0.000029s : 1: opt.transform.mutable_eliminate 0.04% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.07% : 0.000058s : 4: opt.transform.symbol_engine_opt 0.68% : 0.000606s : 1: opt_after_jit_grad 0.01% : 0.000010s : 1: order_py_execute_after_rewriter 0.01% : 0.000005s : 1: partial_unused_args_eliminate 0.01% : 0.000005s : 1: pre_auto_parallel 0.11% : 0.000098s : 1: py_interpret_to_execute 0.02% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.03% : 0.000026s : 1: remove_dup_value 0.86% : 0.000763s : 1: renormalize.infer 0.48% : 0.000425s : 1: renormalize.specialize 0.01% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.32% : 0.000284s : 1: rewriter_after_opt_a 0.08% : 0.000067s : 1: rewriter_before_opt_a 0.14% : 0.000121s : 1: symbol_engine_optimizer 84.97% : 0.075209s : 1: type_inference TotalTime = 0.0994156, [30] [bootstrap]: 0.00032417 [type_inference]: 0.0770047 [event_method]: 1.619e-05 [auto_monad]: 0.00014808 [graph_reusing]: 6.26e-06 [pre_auto_parallel]: 2.56e-06 [py_interpret_to_execute]: 9.69e-05 [rewriter_before_opt_a]: 6.147e-05 [expand_dump_flag]: 3.03998e-06 [jit_opt_a]: 0.0187713, [2] [Cycle 1]: 0.014391, [27] [switch_simplify]: 5.407e-05 [loop_unroll]: 2.025e-05 [a_1]: 0.00046379 [with_stream_mark]: 3.223e-05 [recompute_prepare]: 1.262e-05 [updatestate_depend_eliminate]: 7.43999e-06 [updatestate_assign_eliminate]: 6.17999e-06 [updatestate_loads_eliminate]: 4.65999e-06 [parameter_eliminate]: 2.40002e-06 [specialize_transform]: 1.041e-05 [updatestate_useless_node_eliminater]: 1.241e-05 [accelerated_algorithm]: 9.44998e-06 [meta_shard_fg_expand]: 2.91e-06 [get_grad_eliminate_]: 8.60001e-06 [merge_forward]: 5.85002e-06 [cell_reuse_recompute_pass]: 1.19e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.327e-05 [j_node_and_user_rematch]: 1.555e-05 [meta_fg_expand]: 4.1e-06 [replace_old_param]: 1.447e-05 [inline_without_move]: 9.22001e-06 [renormalize]: 0.0132728 [add_forward_monad_depend]: 1.571e-05 [auto_monad_grad]: 4.02998e-06 [auto_monad_eliminator]: 4.006e-05 [cse]: 5.262e-05 [replace_applicator]: 3.5e-05 [Cycle 2]: 0.00058666, [27] [switch_simplify]: 1.02e-05 [loop_unroll]: 8.77e-06 [a_1]: 0.00021283 [with_stream_mark]: 2.543e-05 [recompute_prepare]: 9.49e-06 [updatestate_depend_eliminate]: 6.63e-06 [updatestate_assign_eliminate]: 5.91e-06 [updatestate_loads_eliminate]: 5.02999e-06 [parameter_eliminate]: 2.49999e-06 [specialize_transform]: 8.95001e-06 [updatestate_useless_node_eliminater]: 1.266e-05 [accelerated_algorithm]: 9.17999e-06 [meta_shard_fg_expand]: 2.71e-06 [get_grad_eliminate_]: 9.58997e-06 [merge_forward]: 6.01e-06 [cell_reuse_recompute_pass]: 2.77002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.353e-05 [j_node_and_user_rematch]: 1.506e-05 [meta_fg_expand]: 3.58999e-06 [replace_old_param]: 1.322e-05 [inline_without_move]: 8.59e-06 [renormalize]: 5.9983e-08 [add_forward_monad_depend]: 1.54e-06 [auto_monad_grad]: 1.17e-06 [auto_monad_eliminator]: 1.141e-05 [cse]: 2.358e-05 [replace_applicator]: 8.84998e-06 [py_interpret_to_execute_after_opt_a]: 2.311e-05 [rewriter_after_opt_a]: 0.0002828 [convert_after_rewriter]: 1.16e-05 [order_py_execute_after_rewriter]: 7.34002e-06 [mutable_eliminate]: 0.00077571 [jit_opt_b]: 7.843e-05, [1] [Cycle 1]: 6.916e-05, [2] [frontend_op_eliminate]: 2.725e-05 [inline_after_opt_a]: 2.789e-05 [cconv]: 3.736e-05 [loop_unroll]: 0.0004493 [jit_opt_after_cconv]: 0.00022553, [1] [Cycle 1]: 0.00021875, [11] [c_1]: 5.244e-05 [parameter_eliminate]: 4.27998e-06 [updatestate_depend_eliminate]: 1.057e-05 [updatestate_assign_eliminate]: 5.57001e-06 [updatestate_loads_eliminate]: 4.75001e-06 [cse]: 3.595e-05 [call_graph_tuple_transform]: 2.633e-05 [tuple_list_get_item_eliminator]: 9.06998e-06 [none_parameter_eliminate]: 1.57001e-06 [renormalize]: 8.39995e-07 [switch_simplify]: 9.56e-06 [remove_dup_value]: 2.293e-05 [partial_unused_args_eliminate]: 2.44999e-06 [environ_conv]: 1.395e-05 [add_recomputation]: 7.647e-05 [cse_after_recomputation]: 3.198e-05, [1] [Cycle 1]: 2.545e-05, [1] [cse]: 1.835e-05 [auto_monad_reorder]: 2.614e-05 [get_jit_bprop_graph]: 2.09e-06 [rewriter_after_jit_bprop_graph]: 5.86e-06 [opt_after_jit_grad]: 0.00051411 [symbol_engine_optimizer]: 0.00011867, [1] [Cycle 1]: 0.00011125, [6] [build]: 1.716e-05 [elim_shapecalc]: 1.334e-05 [elim_not_effective]: 2.07e-05 [opt_reshape]: 9.96e-06 [fold_const_symbol]: 1.582e-05 [renormalize]: 6.30011e-07 [validate]: 7e-05 Sums bootstrap : 0.000324s : 0.34% type_inference : 0.077005s : 81.15% event_method : 0.000016s : 0.02% auto_monad : 0.000148s : 0.16% graph_reusing : 0.000006s : 0.01% pre_auto_parallel : 0.000003s : 0.00% py_interpret_to_execute : 0.000097s : 0.10% rewriter_before_opt_a : 0.000061s : 0.06% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000064s : 0.07% jit_opt_a.loop_unroll : 0.000029s : 0.03% jit_opt_a.a_1 : 0.000677s : 0.71% jit_opt_a.with_stream_mark : 0.000058s : 0.06% jit_opt_a.recompute_prepare : 0.000022s : 0.02% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000012s : 0.01% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.01% jit_opt_a.parameter_eliminate : 0.000005s : 0.01% jit_opt_a.specialize_transform : 0.000019s : 0.02% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.03% jit_opt_a.accelerated_algorithm : 0.000019s : 0.02% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.01% jit_opt_a.get_grad_eliminate_ : 0.000018s : 0.02% jit_opt_a.merge_forward : 0.000012s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 0.05% jit_opt_a.j_node_and_user_rematch : 0.000031s : 0.03% jit_opt_a.meta_fg_expand : 0.000008s : 0.01% jit_opt_a.replace_old_param : 0.000028s : 0.03% jit_opt_a.inline_without_move : 0.000018s : 0.02% jit_opt_a.renormalize : 0.013273s : 13.99% jit_opt_a.add_forward_monad_depend : 0.000017s : 0.02% jit_opt_a.auto_monad_grad : 0.000005s : 0.01% jit_opt_a.auto_monad_eliminator : 0.000051s : 0.05% jit_opt_a.cse : 0.000076s : 0.08% jit_opt_a.replace_applicator : 0.000044s : 0.05% py_interpret_to_execute_after_opt_a : 0.000023s : 0.02% rewriter_after_opt_a : 0.000283s : 0.30% convert_after_rewriter : 0.000012s : 0.01% order_py_execute_after_rewriter : 0.000007s : 0.01% mutable_eliminate : 0.000776s : 0.82% jit_opt_b.frontend_op_eliminate : 0.000027s : 0.03% jit_opt_b.inline_after_opt_a : 0.000028s : 0.03% cconv : 0.000037s : 0.04% loop_unroll : 0.000449s : 0.47% jit_opt_after_cconv.c_1 : 0.000052s : 0.06% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 0.01% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.01% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.01% jit_opt_after_cconv.cse : 0.000036s : 0.04% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.03% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 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 : 0.000023s : 0.02% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000014s : 0.01% add_recomputation : 0.000076s : 0.08% cse_after_recomputation.cse : 0.000018s : 0.02% auto_monad_reorder : 0.000026s : 0.03% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.01% opt_after_jit_grad : 0.000514s : 0.54% symbol_engine_optimizer.build : 0.000017s : 0.02% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.01% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.02% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.01% symbol_engine_optimizer.fold_const_symbol : 0.000016s : 0.02% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000070s : 0.07% Time group info: ------[substitution.] 0.000232 43 5.26% : 0.000012s : 2: substitution.depend_value_elim 1.32% : 0.000003s : 4: substitution.elim_not_effective 1.22% : 0.000003s : 4: substitution.fold_const_symbol 3.70% : 0.000009s : 5: substitution.graph_param_transform 68.52% : 0.000159s : 2: substitution.inline 2.48% : 0.000006s : 8: substitution.j_node_and_user_rematch 3.82% : 0.000009s : 8: substitution.remove_not_recompute_node 3.40% : 0.000008s : 2: substitution.replace_old_param 4.85% : 0.000011s : 3: substitution.updatestate_pure_node_eliminater 5.42% : 0.000013s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.076932 2 98.70% : 0.075931s : 1: type_inference.infer 1.30% : 0.001002s : 1: type_inference.specialize ------[replace.] 0.000033 2 100.00% : 0.000033s : 2: replace.inline ------[match.] 0.000157 2 100.00% : 0.000157s : 2: match.inline ------[predicate.] 0.000166 767 1.28% : 0.000002s : 11: predicate.accumulaten_eliminater 1.18% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.08% : 0.000002s : 11: predicate.addn_check_dump 1.26% : 0.000002s : 11: predicate.addn_zero_filter 1.86% : 0.000003s : 11: predicate.arithmetic_simplify 1.25% : 0.000002s : 11: predicate.cast_eliminate 0.67% : 0.000001s : 5: predicate.check_bprop_eliminate 1.09% : 0.000002s : 11: predicate.compare_switch_simplify 1.35% : 0.000002s : 11: predicate.depend_value_elim 1.36% : 0.000002s : 11: predicate.dict_get_item_const_eliminator 1.17% : 0.000002s : 11: predicate.dict_get_item_eliminator 1.15% : 0.000002s : 11: predicate.dict_set_item_eliminator 0.95% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.38% : 0.000001s : 5: predicate.elim_not_effective 0.82% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.24% : 0.000002s : 11: predicate.environ_add_const_eliminate 1.03% : 0.000002s : 11: predicate.environ_get_add_eliminate 1.05% : 0.000002s : 11: predicate.environ_get_depend_swap 1.29% : 0.000002s : 11: predicate.environ_get_eliminate 1.09% : 0.000002s : 11: predicate.environ_get_set_eliminate 0.34% : 0.000001s : 5: predicate.fold_const_symbol 1.35% : 0.000002s : 10: predicate.get_grad_eliminate 0.46% : 0.000001s : 5: predicate.graph_param_transform 5.59% : 0.000009s : 23: predicate.inline 1.47% : 0.000002s : 10: predicate.inline_without_move 0.69% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.54% : 0.000003s : 10: predicate.less_batch_normalization 1.22% : 0.000002s : 11: predicate.list_to_tuple_eliminator_ 1.91% : 0.000003s : 16: predicate.load_eliminater 1.52% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.48% : 0.000004s : 20: predicate.loop_unroll_before_grad 1.99% : 0.000003s : 16: predicate.make_slice_get_slice_eliminator 1.03% : 0.000002s : 11: predicate.merge_addn 1.05% : 0.000002s : 11: predicate.minmaximum_grad 1.68% : 0.000003s : 5: predicate.mutable_eliminate 0.92% : 0.000002s : 5: predicate.opt_reshape 2.12% : 0.000004s : 16: predicate.partial_eliminate 1.32% : 0.000002s : 11: predicate.print_const_string_wrapper 1.71% : 0.000003s : 11: predicate.reduce_eliminate 1.21% : 0.000002s : 11: predicate.redundant_stop_gradient_eliminater 1.00% : 0.000002s : 10: predicate.remove_not_recompute_node 2.00% : 0.000003s : 21: predicate.replace_applicator 0.93% : 0.000002s : 10: predicate.replace_old_param 0.36% : 0.000001s : 5: predicate.reset_defer_inline 1.80% : 0.000003s : 11: predicate.reshape_eliminate 1.30% : 0.000002s : 11: predicate.row_tensor_add_zeros_like 0.97% : 0.000002s : 5: predicate.row_tensor_eliminate 1.27% : 0.000002s : 11: predicate.same_eliminate 0.72% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.36% : 0.000002s : 10: predicate.special_op_eliminate 1.39% : 0.000002s : 10: predicate.specialize_transform 1.33% : 0.000002s : 11: predicate.split_environ_get_set_with_tuple_value 1.32% : 0.000002s : 11: predicate.stack_unstack_eliminate 0.61% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.53% : 0.000003s : 13: predicate.switch_defer_inline 1.47% : 0.000002s : 13: predicate.switch_layer_defer_inline 5.64% : 0.000009s : 38: predicate.switch_simplify 1.25% : 0.000002s : 11: predicate.tile_eliminate 1.16% : 0.000002s : 11: predicate.transpose_eliminate 1.47% : 0.000002s : 11: predicate.tuple_list_convert_item_index_to_positive 1.21% : 0.000002s : 11: predicate.tuple_list_get_item_depend_reorder 4.26% : 0.000007s : 21: predicate.tuple_list_get_item_eliminator 1.59% : 0.000003s : 11: predicate.tuple_list_set_item_eliminator 1.30% : 0.000002s : 11: predicate.tuple_to_list_eliminator_ 1.89% : 0.000003s : 16: predicate.updatestate_pure_node_eliminater 3.30% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 2.01% : 0.000003s : 11: predicate.value_based_eliminate 0.52% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.90% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000417 6 29.34% : 0.000122s : 2: func_graph_cloner_run.FuncGraphClonerGraph 70.66% : 0.000294s : 4: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.113800 72 0.07% : 0.000080s : 1: add_recomputation 0.13% : 0.000153s : 1: auto_monad 0.03% : 0.000029s : 1: auto_monad_reorder 0.30% : 0.000347s : 1: bootstrap 0.04% : 0.000040s : 1: cconv 0.01% : 0.000015s : 1: convert_after_rewriter 0.03% : 0.000035s : 1: cse_after_recomputation 0.01% : 0.000017s : 1: environ_conv 0.02% : 0.000022s : 1: event_method 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.01% : 0.000009s : 1: graph_reusing 16.50% : 0.018775s : 1: jit_opt_a 0.20% : 0.000229s : 1: jit_opt_after_cconv 0.07% : 0.000082s : 1: jit_opt_b 0.40% : 0.000456s : 1: loop_unroll 0.69% : 0.000784s : 1: mutable_eliminate 0.88% : 0.001000s : 26: opt.transform.jit_opt_a 0.08% : 0.000093s : 4: opt.transform.jit_opt_after_cconv 0.04% : 0.000048s : 4: opt.transform.jit_opt_b 0.02% : 0.000017s : 1: opt.transform.loop_unroll_optimizer 0.02% : 0.000020s : 1: opt.transform.mutable_eliminate 0.03% : 0.000032s : 1: opt.transform.opt_after_jit_grad 0.05% : 0.000055s : 4: opt.transform.symbol_engine_opt 0.46% : 0.000522s : 1: opt_after_jit_grad 0.01% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pre_auto_parallel 0.09% : 0.000100s : 1: py_interpret_to_execute 0.02% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.02% : 0.000026s : 1: remove_dup_value 0.64% : 0.000727s : 1: renormalize.infer 11.01% : 0.012530s : 1: renormalize.specialize 0.01% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.25% : 0.000287s : 1: rewriter_after_opt_a 0.06% : 0.000065s : 1: rewriter_before_opt_a 0.11% : 0.000121s : 1: symbol_engine_optimizer 67.68% : 0.077022s : 1: type_inference . [hook] pytest_runtest_teardown:test_chunk_empty_tensor[KBK] tests/st/mint/test_chunk.py::test_chunk_empty_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 80.36s (0:01:20) ===================