[WARNING] ME(171330:281473562074928,MainProcess):2026-01-29-17:37:47.309.382 [mindspore/context.py:1334] For 'context.set_context', the parameter 'max_call_depth' will be deprecated and removed in a future version. Please use the api mindspore.set_recursion_limit() instead. ==================================================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/runtime/parallel_dispatch, 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 1 item test_parallel_dispatch.py TotalTime = 25.673, [21] [bootstrap]: 0.0507839 [type_inference]: 17.922 [event_method]: 0.00485266 [auto_monad]: 0.00593049 [graph_reusing]: 0.00033665 [inline]: 3.42002e-06 [add_attr]: 0.224345, [1] [add_attr_with_inline]: 0.22432, [1] [Cycle 1]: 0.093509, [2] [tag_attr]: 0.0920736 [meta_addattr_fg_expand]: 0.0012885 [parallel-infer-symbol]: 5.67001e-06 [pre_auto_parallel]: 0.00311787 [insert-virtual-dataset]: 3.91001e-06 [parallel-infer-symbol-second]: 5.66e-06 [dataset_repeat_opt]: 3.65e-06 [pipeline_split]: 2.18002e-06 [optimize]: 7.2476, [53] [py_interpret_to_execute]: 0.00360196 [rewriter_before_opt_a]: 0.00847914 [opt_a]: 5.37391, [2] [Cycle 1]: 3.99504, [45] [expand_dump_flag]: 0.00311561 [switch_simplify]: 0.134056 [loop_unroll]: 0.00288101 [a_1]: 0.379133 [with_stream_mark]: 0.00248393 [recompute_prepare]: 0.00164707 [updatestate_depend_eliminate]: 0.120052 [updatestate_assign_eliminate]: 0.00151509 [updatestate_loads_eliminate]: 0.00105654 [parameter_eliminate]: 9.09e-06 [a_2]: 0.505008 [accelerated_algorithm]: 0.00273089 [shard]: 3.23e-06 [meta_shard_fg_expand]: 0.00082644 [shard_inline]: 0.00113156 [merge_send_recv]: 0.00145177 [auto_parallel]: 0.00101063 [parallel]: 6.489e-05 [flash_sp]: 0.00064601 [merge_comm]: 0.0011156 [allreduce_fusion]: 0.00106845 [matmul_add_comm_reduction]: 0.00134847 [allreduce_slice_to_reducescatter]: 9.70002e-07 [virtual_shard_identity]: 0.00140287 [virtual_dataset]: 0.149183 [get_grad_eliminate_]: 0.00164758 [virtual_output]: 0.00124295 [merge_forward]: 0.00137458 [cell_reuse_recompute_pass]: 5.37001e-06 [offload_activation]: 0.00138591 [cell_reuse_handle_not_recompute_node_pass]: 0.00216054 [merge_recompute_call_nodes]: 4.05998e-06 [before_grad]: 0.0020737 [set_forward_comm_id_for_comm_node_pass]: 0.142693 [meta_fg_expand]: 0.00347713 [flash_sp_send_recv_attached]: 1.959e-05 [receive_attached]: 2.81e-06 [after_resolve]: 0.00175089 [a_after_grad]: 0.00248663 [renormalize]: 2.32075 [add_forward_monad_depend]: 1.598e-05 [auto_monad_grad]: 3.27002e-06 [auto_monad_eliminator]: 0.00312028 [cse]: 0.00909812 [a_3]: 0.187177 [Cycle 2]: 1.37884, [45] [expand_dump_flag]: 5.51e-06 [switch_simplify]: 0.00099323 [loop_unroll]: 0.00099238 [a_1]: 0.33159 [with_stream_mark]: 0.00195275 [recompute_prepare]: 0.00115494 [updatestate_depend_eliminate]: 0.00144478 [updatestate_assign_eliminate]: 0.00129573 [updatestate_loads_eliminate]: 0.00110939 [parameter_eliminate]: 5.83002e-06 [a_2]: 0.225316 [accelerated_algorithm]: 0.173074 [shard]: 4.15e-06 [meta_shard_fg_expand]: 0.00099365 [shard_inline]: 0.00129113 [merge_send_recv]: 0.00187991 [auto_parallel]: 0.00150301 [parallel]: 1.526e-05 [flash_sp]: 7.5e-06 [merge_comm]: 0.00151312 [allreduce_fusion]: 0.00121084 [matmul_add_comm_reduction]: 0.00140069 [allreduce_slice_to_reducescatter]: 1.54e-06 [virtual_shard_identity]: 0.00121726 [virtual_dataset]: 0.00116826 [get_grad_eliminate_]: 0.175729 [virtual_output]: 0.00213458 [merge_forward]: 0.00246043 [cell_reuse_recompute_pass]: 7.78001e-06 [offload_activation]: 0.00240492 [cell_reuse_handle_not_recompute_node_pass]: 0.00302947 [merge_recompute_call_nodes]: 8.72e-06 [before_grad]: 0.0159932 [set_forward_comm_id_for_comm_node_pass]: 0.201961 [meta_fg_expand]: 0.00176916 [flash_sp_send_recv_attached]: 6.86999e-06 [receive_attached]: 2.64999e-06 [after_resolve]: 0.00123092 [a_after_grad]: 0.00152958 [renormalize]: 3.39991e-07 [add_forward_monad_depend]: 1.371e-05 [auto_monad_grad]: 4.33999e-06 [auto_monad_eliminator]: 0.00219102 [cse]: 0.00487722 [a_3]: 0.210622 [py_interpret_to_execute_after_opt_a]: 0.00235366 [slice_cell_reuse_recomputed_activation]: 6.33e-06 [rewriter_after_opt_a]: 0.00572591 [convert_after_rewriter]: 0.180934 [order_py_execute_after_rewriter]: 0.00204197 [mutable_eliminate]: 0.0031281 [opt_b]: 0.469296, [1] [Cycle 1]: 0.46925, [7] [b_1]: 0.45923 [b_2]: 0.00107708 [updatestate_depend_eliminate]: 0.00167991 [updatestate_assign_eliminate]: 0.00103135 [updatestate_loads_eliminate]: 0.00112983 [renormalize]: 1.52001e-06 [cse]: 0.00483019 [optimize_parallel_all_gather_comm]: 0.245075 [overlap_param_gather]: 1.61e-05 [cconv]: 0.0008455 [loop_unroll]: 0.00262207 [opt_after_cconv]: 0.248893, [1] [Cycle 1]: 0.248854, [7] [c_1]: 0.00531521 [parameter_eliminate]: 8.87999e-06 [updatestate_depend_eliminate]: 0.00226051 [updatestate_assign_eliminate]: 0.00119494 [updatestate_loads_eliminate]: 0.234342 [cse]: 0.00542215 [renormalize]: 1.97001e-06 [remove_dup_value]: 0.229866 [tuple_transform]: 0.00708865, [1] [Cycle 1]: 0.00706729, [4] [d_1]: 0.00587718 [none_parameter_eliminate]: 7.13998e-06 [renormalize]: 1.68002e-06 [switch_simplify]: 0.00108418 [partial_unused_args_eliminate]: 6.48998e-06 [add_recomputation]: 0.00734663 [cse_after_recomputation]: 0.218382, [1] [Cycle 1]: 0.218357, [1] [cse]: 0.218292 [environ_conv]: 0.00069111 [swap_dp_allreduce_reducescatter]: 0.00148365 [bias_add_comm_swap]: 6.76e-06 [label_micro_interleaved_index]: 9.47999e-06 [label_fine_grained_interleaved_index]: 2.96999e-06 [merge_cast_opt]: 1.69e-06 [slice_recompute_activation]: 2.29001e-06 [micro_interleaved_order_control]: 2.76e-06 [assign_add_opt]: 1.72001e-06 [ForceFp32Comm]: 1.15999e-06 [remove_cast_before_assign_add]: 1.10001e-06 [full_micro_interleaved_order_control]: 2.37001e-06 [reorder_send_recv_between_fp_bp]: 3.24001e-06 [comm_op_add_attrs]: 1.33002e-06 [add_comm_op_reuse_tag]: 1.04003e-06 [interleave_split_concat_branches]: 1.54998e-06 [interleave_parallel_branches]: 1.13001e-06 [overlap_opt_shard_in_pipeline]: 3.287e-05 [overlap_opt_shard_grad_in_pipeline]: 2.88998e-06 [control_data_broadcast_order]: 0.00220892 [grouped_pairwise_exchange_alltoall]: 2.91999e-06 [offloading_packed_experts]: 0.00042238 [overlap_recompute_and_grad_model_parallel]: 0.00041483 [overlap_grad_matmul_and_grad_allreduce]: 3.06001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.55999e-06 [overlap_recompute_comm]: 3.50998e-06 [overlap_grad_ring_attention]: 0.00040494 [overlap_grad_flash_sp]: 0.00250786 [begin_end_overlap_inline]: 2.27999e-06 [split_matmul_comm_elemetwise]: 4.10998e-06 [split_layernorm_comm]: 1.91e-06 [handle_group_info]: 1.71998e-06 [symbol_engine_optimizer]: 0.228396, [1] [Cycle 1]: 0.228377, [6] [build]: 0.22112 [elim_shapecalc]: 0.00113621 [elim_not_effective]: 0.00217169 [opt_reshape]: 0.00136041 [fold_const_symbol]: 0.00233648 [renormalize]: 1.09e-06 [detach_backward]: 5.54998e-06 [pipeline_parallel_scheduler]: 2.26e-06 [auto_monad_reorder]: 0.00224479 [get_jit_bprop_graph]: 3.31001e-06 [rewriter_after_jit_bprop_graph]: 1.242e-05 [opt_after_jit_grad]: 0.00469704 [validate]: 0.206549 Sums bootstrap : 0.050784s : 0.20% type_inference : 17.922034s : 70.18% event_method : 0.004853s : 0.02% auto_monad : 0.005930s : 0.02% graph_reusing : 0.000337s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.092074s : 0.36% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.001288s : 0.01% parallel-infer-symbol : 0.000006s : 0.00% pre_auto_parallel : 0.003118s : 0.01% insert-virtual-dataset : 0.000004s : 0.00% parallel-infer-symbol-second : 0.000006s : 0.00% dataset_repeat_opt : 0.000004s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.003602s : 0.01% optimize.rewriter_before_opt_a : 0.008479s : 0.03% optimize.opt_a.expand_dump_flag : 0.003121s : 0.01% optimize.opt_a.switch_simplify : 0.135049s : 0.53% optimize.opt_a.loop_unroll : 0.003873s : 0.02% optimize.opt_a.a_1 : 0.710723s : 2.78% optimize.opt_a.with_stream_mark : 0.004437s : 0.02% optimize.opt_a.recompute_prepare : 0.002802s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.121497s : 0.48% optimize.opt_a.updatestate_assign_eliminate : 0.002811s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.002166s : 0.01% optimize.opt_a.parameter_eliminate : 0.000015s : 0.00% optimize.opt_a.a_2 : 0.730324s : 2.86% optimize.opt_a.accelerated_algorithm : 0.175805s : 0.69% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.001820s : 0.01% optimize.opt_a.shard_inline : 0.002423s : 0.01% optimize.opt_a.merge_send_recv : 0.003332s : 0.01% optimize.opt_a.auto_parallel : 0.002514s : 0.01% optimize.opt_a.parallel : 0.000080s : 0.00% optimize.opt_a.flash_sp : 0.000654s : 0.00% optimize.opt_a.merge_comm : 0.002629s : 0.01% optimize.opt_a.allreduce_fusion : 0.002279s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.002749s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000003s : 0.00% optimize.opt_a.virtual_shard_identity : 0.002620s : 0.01% optimize.opt_a.virtual_dataset : 0.150351s : 0.59% optimize.opt_a.get_grad_eliminate_ : 0.177377s : 0.69% optimize.opt_a.virtual_output : 0.003378s : 0.01% optimize.opt_a.merge_forward : 0.003835s : 0.02% optimize.opt_a.cell_reuse_recompute_pass : 0.000013s : 0.00% optimize.opt_a.offload_activation : 0.003791s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.005190s : 0.02% optimize.opt_a.merge_recompute_call_nodes : 0.000013s : 0.00% optimize.opt_a.before_grad : 0.018067s : 0.07% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.344654s : 1.35% optimize.opt_a.meta_fg_expand : 0.005246s : 0.02% optimize.opt_a.flash_sp_send_recv_attached : 0.000026s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.002982s : 0.01% optimize.opt_a.a_after_grad : 0.004016s : 0.02% optimize.opt_a.renormalize : 2.320751s : 9.09% optimize.opt_a.add_forward_monad_depend : 0.000030s : 0.00% optimize.opt_a.auto_monad_grad : 0.000008s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.005311s : 0.02% optimize.opt_a.cse : 0.013975s : 0.05% optimize.opt_a.a_3 : 0.397800s : 1.56% optimize.py_interpret_to_execute_after_opt_a : 0.002354s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000006s : 0.00% optimize.rewriter_after_opt_a : 0.005726s : 0.02% optimize.convert_after_rewriter : 0.180934s : 0.71% optimize.order_py_execute_after_rewriter : 0.002042s : 0.01% optimize.mutable_eliminate : 0.003128s : 0.01% optimize.opt_b.b_1 : 0.459230s : 1.80% optimize.opt_b.b_2 : 0.001077s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.001680s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.001031s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.001130s : 0.00% optimize.opt_b.renormalize : 0.000002s : 0.00% optimize.opt_b.cse : 0.004830s : 0.02% optimize.optimize_parallel_all_gather_comm : 0.245075s : 0.96% optimize.overlap_param_gather : 0.000016s : 0.00% optimize.cconv : 0.000845s : 0.00% optimize.loop_unroll : 0.002622s : 0.01% optimize.opt_after_cconv.c_1 : 0.005315s : 0.02% optimize.opt_after_cconv.parameter_eliminate : 0.000009s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.002261s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.001195s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.234342s : 0.92% optimize.opt_after_cconv.cse : 0.005422s : 0.02% optimize.opt_after_cconv.renormalize : 0.000002s : 0.00% optimize.remove_dup_value : 0.229866s : 0.90% optimize.tuple_transform.d_1 : 0.005877s : 0.02% optimize.tuple_transform.none_parameter_eliminate : 0.000007s : 0.00% optimize.tuple_transform.renormalize : 0.000002s : 0.00% optimize.tuple_transform.switch_simplify : 0.001084s : 0.00% optimize.partial_unused_args_eliminate : 0.000006s : 0.00% optimize.add_recomputation : 0.007347s : 0.03% optimize.cse_after_recomputation.cse : 0.218292s : 0.85% optimize.environ_conv : 0.000691s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.001484s : 0.01% optimize.bias_add_comm_swap : 0.000007s : 0.00% optimize.label_micro_interleaved_index : 0.000009s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000002s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000033s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000003s : 0.00% optimize.control_data_broadcast_order : 0.002209s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000003s : 0.00% optimize.offloading_packed_experts : 0.000422s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000415s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000003s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000004s : 0.00% optimize.overlap_grad_ring_attention : 0.000405s : 0.00% optimize.overlap_grad_flash_sp : 0.002508s : 0.01% optimize.begin_end_overlap_inline : 0.000002s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000004s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000002s : 0.00% optimize.symbol_engine_optimizer.build : 0.221120s : 0.87% optimize.symbol_engine_optimizer.elim_shapecalc : 0.001136s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.002172s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.001360s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.002336s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000006s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.002245s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000012s : 0.00% opt_after_jit_grad : 0.004697s : 0.02% validate : 0.206549s : 0.81% Time group info: ------[substitution.] 0.272414 7288 3.59% : 0.009786s : 1750: substitution.arithmetic_simplify 0.02% : 0.000052s : 50: substitution.depend_value_elim 0.27% : 0.000738s : 653: substitution.elim_not_effective 0.39% : 0.001052s : 653: substitution.fold_const_symbol 0.24% : 0.000645s : 658: substitution.graph_param_transform 46.02% : 0.125361s : 103: substitution.inline 0.41% : 0.001127s : 1306: substitution.j_node_and_user_rematch 0.53% : 0.001439s : 300: substitution.less_batch_normalization 0.06% : 0.000171s : 152: substitution.opt_reshape 0.27% : 0.000748s : 1306: substitution.remove_not_recompute_node 0.01% : 0.000014s : 2: substitution.replace_old_param 0.69% : 0.001873s : 304: substitution.reshape_eliminate 47.50% : 0.129409s : 51: substitution.switch_simplify ------[type_inference.] 17.829076 2 79.86% : 14.238586s : 1: type_inference.infer 20.14% : 3.590489s : 1: type_inference.specialize ------[replace.] 0.003059 204 17.21% : 0.000526s : 50: replace.depend_value_elim 45.20% : 0.001383s : 103: replace.inline 37.59% : 0.001150s : 51: replace.switch_simplify ------[match.] 0.254666 204 0.01% : 0.000032s : 50: match.depend_value_elim 49.19% : 0.125273s : 103: match.inline 50.80% : 0.129361s : 51: match.switch_simplify ------[predicate.] 0.763346184242 1.93% : 0.014701s : 1616: predicate.accumulaten_eliminater 0.04% : 0.000332s : 658: predicate.ad_related_special_op_eliminate 23.66% : 0.180593s : 2370: predicate.addn_check_dump 0.03% : 0.000244s : 1616: predicate.addn_zero_filter 0.03% : 0.000222s : 1616: predicate.adjust_all_reduce_mul_add 9.23% : 0.070440s : 3986: predicate.arithmetic_simplify 0.03% : 0.000259s : 1616: predicate.cast_eliminate 0.11% : 0.000857s : 1316: predicate.check_bprop_eliminate 1.87% : 0.014246s : 2370: predicate.compare_switch_simplify 0.01% : 0.000046s : 658: predicate.const_output_eliminate 0.17% : 0.001331s : 2369: predicate.depend_value_elim 0.03% : 0.000242s : 1616: predicate.dict_get_item_const_eliminator 0.03% : 0.000262s : 1616: predicate.dict_get_item_eliminator 0.03% : 0.000218s : 1616: predicate.dict_set_item_eliminator 0.05% : 0.000410s : 1316: predicate.dumpgradient_eliminate 0.01% : 0.000047s : 658: predicate.elim_not_effective 0.05% : 0.000359s : 658: predicate.elim_shapecalc_of_broadcastargs 0.07% : 0.000555s : 2274: predicate.environ_add_const_eliminate 0.12% : 0.000886s : 2274: predicate.environ_get_add_eliminate 0.08% : 0.000598s : 2274: predicate.environ_get_depend_swap 0.24% : 0.001837s : 4644: predicate.environ_get_eliminate 0.09% : 0.000703s : 2274: predicate.environ_get_set_eliminate 0.03% : 0.000248s : 1719: predicate.exchange_switch_depend_value 0.05% : 0.000399s : 1719: predicate.float_depend_g_call 0.13% : 0.001024s : 2370: predicate.float_environ_get_switch 0.20% : 0.001524s : 3028: predicate.float_tuple_getitem_switch 0.01% : 0.000047s : 658: predicate.fold_const_symbol 22.98% : 0.175400s : 1464: predicate.get_grad_eliminate 0.01% : 0.000054s : 658: predicate.graph_param_transform 0.14% : 0.001052s : 2370: predicate.incorporate_call 0.11% : 0.000835s : 2370: predicate.incorporate_call_switch 0.41% : 0.003152s : 8485: predicate.inline 0.13% : 0.000994s : 1464: predicate.inline_without_move 0.01% : 0.000112s : 1464: predicate.j_node_and_user_rematch 0.15% : 0.001170s : 1464: predicate.less_batch_normalization 0.12% : 0.000932s : 2932: predicate.list_to_tuple_eliminator_ 0.10% : 0.000746s : 4548: predicate.load_eliminater 0.08% : 0.000583s : 658: predicate.loop_unroll_after_grad 0.16% : 0.001232s : 1925: predicate.loop_unroll_before_grad 0.10% : 0.000726s : 2932: predicate.make_slice_get_slice_eliminator 0.15% : 0.001150s : 2370: predicate.merge_addn 0.08% : 0.000578s : 1316: predicate.micro_step_allgather_replace 0.09% : 0.000724s : 1316: predicate.mini_step_allgather_replace 0.03% : 0.000223s : 1616: predicate.minmaximum_grad 0.09% : 0.000709s : 658: predicate.mutable_eliminate 0.04% : 0.000285s : 658: predicate.opt_reshape 0.04% : 0.000277s : 658: predicate.parallel_virtual_node 0.13% : 0.000991s : 1719: predicate.partial_defer_inline 0.05% : 0.000354s : 2274: predicate.partial_eliminate 0.03% : 0.000224s : 1616: predicate.print_const_string_wrapper 0.12% : 0.000891s : 2270: predicate.reduce_all_const_elim 0.04% : 0.000330s : 1616: predicate.reduce_eliminate 0.10% : 0.000740s : 4548: predicate.redundant_stop_gradient_eliminater 0.01% : 0.000100s : 1464: predicate.remove_not_recompute_node 0.03% : 0.000260s : 2932: predicate.replace_applicator 0.01% : 0.000106s : 1464: predicate.replace_old_param 0.01% : 0.000047s : 658: predicate.reset_defer_inline 0.04% : 0.000280s : 1616: predicate.reshape_eliminate 0.13% : 0.001008s : 1316: predicate.row_tensor_add_zeros_like 0.04% : 0.000331s : 658: predicate.row_tensor_eliminate 0.13% : 0.000977s : 1316: predicate.same_eliminate 0.02% : 0.000124s : 1564: predicate.set_cell_output_no_recompute 0.08% : 0.000635s : 1464: predicate.shard_identity_eliminate 0.05% : 0.000398s : 1316: predicate.special_op_eliminate 0.15% : 0.001149s : 2370: predicate.specialize_transform 0.07% : 0.000544s : 1316: predicate.split_environ_get_set_with_tuple_value 0.03% : 0.000247s : 1464: predicate.stack_unstack_eliminate 0.02% : 0.000116s : 658: predicate.switch_call_monad_eliminater 0.04% : 0.000270s : 1719: predicate.switch_defer_inline 0.15% : 0.001164s : 3035: predicate.switch_layer_defer_inline 0.34% : 0.002618s : 6774: predicate.switch_simplify 0.03% : 0.000228s : 1616: predicate.tile_eliminate 0.03% : 0.000256s : 1616: predicate.transpose_eliminate 0.14% : 0.001057s : 2932: predicate.tuple_list_convert_item_index_to_positive 0.12% : 0.000914s : 2932: predicate.tuple_list_get_item_const_eliminator 32.78% : 0.250254s : 2932: predicate.tuple_list_get_item_depend_reorder 0.35% : 0.002642s : 5302: predicate.tuple_list_get_item_eliminator 0.12% : 0.000939s : 2932: predicate.tuple_list_get_set_item_eliminator 0.41% : 0.003128s : 5302: predicate.tuple_list_set_item_eliminator 0.11% : 0.000846s : 2932: predicate.tuple_to_list_eliminator_ 0.10% : 0.000777s : 4548: predicate.updatestate_pure_node_eliminater 0.21% : 0.001641s : 6918: predicate.updatestate_useless_node_eliminater 0.04% : 0.000329s : 658: predicate.value_based_eliminate 0.12% : 0.000905s : 1464: predicate.virtual_dataset_eliminate 0.17% : 0.001268s : 1464: predicate.virtual_output_eliminate 0.01% : 0.000091s : 658: predicate.virtual_view_grad_eliminate 0.08% : 0.000598s : 658: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.731268 483 15.30% : 0.111850s : 376: func_graph_cloner_run.FuncGraphClonerGraph 84.70% : 0.619417s : 107: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 38.265626 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.59% : 0.224353s : 1: add_attr 0.59% : 0.224327s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.007380s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.02% : 0.005971s : 1: auto_monad 0.01% : 0.002288s : 1: auto_monad_reorder 0.00% : 0.000013s : 1: begin_end_overlap_inline 0.00% : 0.000023s : 1: bias_add_comm_swap 0.13% : 0.050829s : 1: bootstrap 0.00% : 0.000867s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.01% : 0.002240s : 1: control_data_broadcast_order 0.47% : 0.180992s : 1: convert_after_rewriter 0.57% : 0.218396s : 1: cse_after_recomputation 0.00% : 0.000007s : 1: dataset_repeat_opt 0.00% : 0.000010s : 1: detach_backward 0.00% : 0.000709s : 1: environ_conv 0.01% : 0.004899s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000013s : 1: get_jit_bprop_graph 0.00% : 0.000359s : 1: graph_reusing 0.00% : 0.000012s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000009s : 1: inline 0.00% : 0.000011s : 1: insert-virtual-dataset 0.00% : 0.000005s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000009s : 1: label_fine_grained_interleaved_index 0.00% : 0.000014s : 1: label_micro_interleaved_index 0.01% : 0.002648s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.01% : 0.003161s : 1: mutable_eliminate 0.00% : 0.000435s : 1: offloading_packed_experts 0.00% : 0.001648s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.001992s : 1: opt.transform.mutable_eliminate 6.59% : 2.521683s : 95: opt.transform.opt_a 0.01% : 0.005307s : 1: opt.transform.opt_after_cconv 0.01% : 0.002543s : 1: opt.transform.opt_after_jit_grad 1.20% : 0.459999s : 28: opt.transform.opt_b 0.02% : 0.006939s : 2: opt.transform.opt_trans_graph 0.02% : 0.006972s : 4: opt.transform.symbol_engine_opt 14.04% : 5.373920s : 1: opt_a 0.65% : 0.248904s : 1: opt_after_cconv 0.01% : 0.004728s : 1: opt_after_jit_grad 1.23% : 0.469307s : 1: opt_b 18.94% : 7.247608s : 1: optimize 0.64% : 0.245120s : 1: optimize_parallel_all_gather_comm 0.01% : 0.002083s : 1: order_py_execute_after_rewriter 0.01% : 0.002546s : 1: overlap_grad_flash_sp 0.00% : 0.000008s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000415s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000037s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000028s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000428s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000008s : 1: overlap_recompute_comm 0.00% : 0.000011s : 1: parallel-infer-symbol 0.00% : 0.000009s : 1: parallel-infer-symbol-second 0.00% : 0.000014s : 1: partial_unused_args_eliminate 0.00% : 0.000008s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.003160s : 1: pre_auto_parallel 0.01% : 0.003632s : 1: py_interpret_to_execute 0.01% : 0.002397s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.60% : 0.229963s : 1: remove_dup_value 3.70% : 1.414938s : 1: renormalize.infer 2.37% : 0.905779s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000016s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.005776s : 1: rewriter_after_opt_a 0.02% : 0.008514s : 1: rewriter_before_opt_a 0.00% : 0.000016s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000009s : 1: split_matmul_comm_elemetwise 0.00% : 0.001508s : 1: swap_dp_allreduce_reducescatter 0.60% : 0.228406s : 1: symbol_engine_optimizer 0.02% : 0.007099s : 1: tuple_transform 46.84% : 17.922081s : 1: type_inference [[-0.06835746 -0.06835746 -0.06835746] [-0.06835746 -0.06835746 -0.06835746]] . [hook] pytest_runtest_teardown:test_host_bound_for_parallel_dispatch tests/st/runtime/parallel_dispatch/test_parallel_dispatch.py::test_host_bound_for_parallel_dispatch,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 ================== 1 passed, 25 warnings in 151.92s (0:02:31) ==================