==================================================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/compiler/stream_event, configfile: ../../../../../../../sault/virtual_test/virtualenv_007/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_with_stream.py [WARNING] ME(169308:281472985550640,MainProcess):2026-01-29-17:38:01.230.727 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS instead. [WARNING] ME(169308:281472985550640,MainProcess):2026-01-29-17:38:01.231.315 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs_path' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS_PATH instead. TotalTime = 0.34554, [21] [bootstrap]: 0.00075744 [type_inference]: 0.226758 [event_method]: 0.00011639 [auto_monad]: 0.00020045 [graph_reusing]: 1.025e-05 [inline]: 3.71001e-06 [add_attr]: 0.0218308, [1] [add_attr_with_inline]: 0.0218139, [1] [Cycle 1]: 0.00015439, [2] [tag_attr]: 5.218e-05 [meta_addattr_fg_expand]: 1.032e-05 [parallel-infer-symbol]: 3.48e-06 [pre_auto_parallel]: 7.536e-05 [insert-virtual-dataset]: 2.75002e-06 [parallel-infer-symbol-second]: 1.07e-06 [dataset_repeat_opt]: 2.12999e-06 [pipeline_split]: 1.74e-06 [optimize]: 0.0945157, [53] [py_interpret_to_execute]: 7.094e-05 [rewriter_before_opt_a]: 0.0002004 [opt_a]: 0.0915345, [3] [Cycle 1]: 0.0885077, [45] [expand_dump_flag]: 6.71e-06 [switch_simplify]: 0.00018699 [loop_unroll]: 5.901e-05 [a_1]: 0.00199681 [with_stream_mark]: 0.00018678 [recompute_prepare]: 5.06e-05 [updatestate_depend_eliminate]: 1.482e-05 [updatestate_assign_eliminate]: 1.301e-05 [updatestate_loads_eliminate]: 1.312e-05 [parameter_eliminate]: 6.07001e-06 [a_2]: 0.00073305 [accelerated_algorithm]: 3.704e-05 [shard]: 2.49999e-06 [meta_shard_fg_expand]: 6.21998e-06 [shard_inline]: 1.552e-05 [merge_send_recv]: 1.921e-05 [auto_parallel]: 1.795e-05 [parallel]: 5.536e-05 [flash_sp]: 2.361e-05 [merge_comm]: 1.194e-05 [allreduce_fusion]: 9.41e-06 [matmul_add_comm_reduction]: 1.946e-05 [allreduce_slice_to_reducescatter]: 9.50007e-07 [virtual_shard_identity]: 2.018e-05 [virtual_dataset]: 1.653e-05 [get_grad_eliminate_]: 1.409e-05 [virtual_output]: 1.467e-05 [merge_forward]: 9.14e-06 [cell_reuse_recompute_pass]: 1.84e-06 [offload_activation]: 1.911e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.528e-05 [merge_recompute_call_nodes]: 1.62001e-06 [before_grad]: 2.721e-05 [set_forward_comm_id_for_comm_node_pass]: 1.049e-05 [meta_fg_expand]: 7.83999e-06 [flash_sp_send_recv_attached]: 4.89e-06 [receive_attached]: 2.21e-06 [after_resolve]: 1.965e-05 [a_after_grad]: 2.773e-05 [renormalize]: 0.00229286 [add_forward_monad_depend]: 1.066e-05 [auto_monad_grad]: 2.56e-06 [auto_monad_eliminator]: 3.583e-05 [cse]: 0.0681629 [a_3]: 0.00012556 [Cycle 2]: 0.00219704, [45] [expand_dump_flag]: 3.78001e-06 [switch_simplify]: 1.545e-05 [loop_unroll]: 1.254e-05 [a_1]: 0.00026749 [with_stream_mark]: 3.63e-05 [recompute_prepare]: 1.218e-05 [updatestate_depend_eliminate]: 8.08999e-06 [updatestate_assign_eliminate]: 6.86001e-06 [updatestate_loads_eliminate]: 6.17999e-06 [parameter_eliminate]: 2.94001e-06 [a_2]: 0.00034021 [accelerated_algorithm]: 1.072e-05 [shard]: 3.28e-06 [meta_shard_fg_expand]: 2.31998e-06 [shard_inline]: 6.96999e-06 [merge_send_recv]: 1.195e-05 [auto_parallel]: 1.225e-05 [parallel]: 1.01e-05 [flash_sp]: 4.28999e-06 [merge_comm]: 4.19002e-06 [allreduce_fusion]: 3.58999e-06 [matmul_add_comm_reduction]: 1.029e-05 [allreduce_slice_to_reducescatter]: 6.09987e-07 [virtual_shard_identity]: 8.3e-06 [virtual_dataset]: 6.56999e-06 [get_grad_eliminate_]: 7.64002e-06 [virtual_output]: 6.21e-06 [merge_forward]: 5.16002e-06 [cell_reuse_recompute_pass]: 3.17002e-06 [offload_activation]: 1.136e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.742e-05 [merge_recompute_call_nodes]: 1.76003e-06 [before_grad]: 1.2e-05 [set_forward_comm_id_for_comm_node_pass]: 4.3e-06 [meta_fg_expand]: 3.17002e-06 [flash_sp_send_recv_attached]: 1.87999e-06 [receive_attached]: 2.32001e-06 [after_resolve]: 1.267e-05 [a_after_grad]: 1.04e-05 [renormalize]: 0.00076125 [add_forward_monad_depend]: 6.92002e-06 [auto_monad_grad]: 3.21999e-06 [auto_monad_eliminator]: 1.793e-05 [cse]: 4.719e-05 [a_3]: 6.359e-05 [Cycle 3]: 0.00080669, [45] [expand_dump_flag]: 1.66e-06 [switch_simplify]: 8.67e-06 [loop_unroll]: 6.61999e-06 [a_1]: 0.00012527 [with_stream_mark]: 1.108e-05 [recompute_prepare]: 6.53e-06 [updatestate_depend_eliminate]: 3.98001e-06 [updatestate_assign_eliminate]: 3.08e-06 [updatestate_loads_eliminate]: 2.68e-06 [parameter_eliminate]: 1.02e-06 [a_2]: 9.948e-05 [accelerated_algorithm]: 6.41998e-06 [shard]: 1.45999e-06 [meta_shard_fg_expand]: 1.72001e-06 [shard_inline]: 6.33998e-06 [merge_send_recv]: 5.07e-06 [auto_parallel]: 7.53e-06 [parallel]: 5.93002e-06 [flash_sp]: 8.70001e-07 [merge_comm]: 3.41999e-06 [allreduce_fusion]: 3.45e-06 [matmul_add_comm_reduction]: 6.64999e-06 [allreduce_slice_to_reducescatter]: 4.30009e-07 [virtual_shard_identity]: 7.68999e-06 [virtual_dataset]: 6.21e-06 [get_grad_eliminate_]: 5.77999e-06 [virtual_output]: 6.76e-06 [merge_forward]: 3.57997e-06 [cell_reuse_recompute_pass]: 1.42999e-06 [offload_activation]: 9.08002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.819e-05 [merge_recompute_call_nodes]: 1.06997e-06 [before_grad]: 1.035e-05 [set_forward_comm_id_for_comm_node_pass]: 4.18999e-06 [meta_fg_expand]: 2.17999e-06 [flash_sp_send_recv_attached]: 9.00007e-07 [receive_attached]: 1.22999e-06 [after_resolve]: 9.32001e-06 [a_after_grad]: 9.32001e-06 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 1.81998e-06 [auto_monad_grad]: 1.05999e-06 [auto_monad_eliminator]: 7.45e-06 [cse]: 1.54e-05 [a_3]: 4.952e-05 [py_interpret_to_execute_after_opt_a]: 1.458e-05 [slice_cell_reuse_recomputed_activation]: 4.67998e-06 [rewriter_after_opt_a]: 8.389e-05 [convert_after_rewriter]: 1.099e-05 [order_py_execute_after_rewriter]: 8.45999e-06 [mutable_eliminate]: 0.00075406 [opt_b]: 0.00032951, [1] [Cycle 1]: 0.00031777, [7] [b_1]: 0.00020217 [b_2]: 9.20001e-06 [updatestate_depend_eliminate]: 7.43999e-06 [updatestate_assign_eliminate]: 3.21001e-06 [updatestate_loads_eliminate]: 2.81e-06 [renormalize]: 8.59989e-07 [cse]: 2.147e-05 [optimize_parallel_all_gather_comm]: 2.29e-05 [overlap_param_gather]: 5.52001e-06 [cconv]: 3.619e-05 [loop_unroll]: 0.00045839 [opt_after_cconv]: 0.00013363, [1] [Cycle 1]: 0.00012379, [7] [c_1]: 3.557e-05 [parameter_eliminate]: 3.11001e-06 [updatestate_depend_eliminate]: 6.07999e-06 [updatestate_assign_eliminate]: 2.96999e-06 [updatestate_loads_eliminate]: 3.03e-06 [cse]: 1.79e-05 [renormalize]: 3.50003e-07 [remove_dup_value]: 1.713e-05 [tuple_transform]: 9.666e-05, [1] [Cycle 1]: 8.952e-05, [4] [d_1]: 4.985e-05 [none_parameter_eliminate]: 1.50001e-06 [renormalize]: 1.80007e-07 [switch_simplify]: 7.03e-06 [partial_unused_args_eliminate]: 5.57001e-06 [add_recomputation]: 6.054e-05 [cse_after_recomputation]: 2.888e-05, [1] [Cycle 1]: 2.163e-05, [1] [cse]: 1.237e-05 [environ_conv]: 5.195e-05 [swap_dp_allreduce_reducescatter]: 9.84001e-06 [bias_add_comm_swap]: 5.51e-06 [label_micro_interleaved_index]: 7.77998e-06 [label_fine_grained_interleaved_index]: 5.12999e-06 [merge_cast_opt]: 3.81999e-06 [slice_recompute_activation]: 5.53002e-06 [micro_interleaved_order_control]: 1.656e-05 [assign_add_opt]: 4.09002e-06 [ForceFp32Comm]: 3.78001e-06 [remove_cast_before_assign_add]: 3.71001e-06 [full_micro_interleaved_order_control]: 4.56002e-06 [reorder_send_recv_between_fp_bp]: 5.61e-06 [comm_op_add_attrs]: 3.97e-06 [add_comm_op_reuse_tag]: 4.08001e-06 [interleave_split_concat_branches]: 4e-06 [interleave_parallel_branches]: 3.9e-06 [overlap_opt_shard_in_pipeline]: 2.508e-05 [overlap_opt_shard_grad_in_pipeline]: 4.52e-06 [control_data_broadcast_order]: 1.828e-05 [grouped_pairwise_exchange_alltoall]: 4.72e-06 [offloading_packed_experts]: 7.51001e-06 [overlap_recompute_and_grad_model_parallel]: 8.62e-06 [overlap_grad_matmul_and_grad_allreduce]: 4.45999e-06 [overlap_recompute_allgather_and_fa_grad]: 3.9e-06 [overlap_recompute_comm]: 5.99999e-06 [overlap_grad_ring_attention]: 8.29002e-06 [overlap_grad_flash_sp]: 3.972e-05 [begin_end_overlap_inline]: 3.38999e-06 [split_matmul_comm_elemetwise]: 5.59e-06 [split_layernorm_comm]: 4.25e-06 [handle_group_info]: 3.74002e-06 [symbol_engine_optimizer]: 0.00011414, [1] [Cycle 1]: 0.00010525, [6] [build]: 3.13e-06 [elim_shapecalc]: 1.203e-05 [elim_not_effective]: 1.534e-05 [opt_reshape]: 7.55e-06 [fold_const_symbol]: 1.126e-05 [renormalize]: 2.40019e-07 [detach_backward]: 3.83001e-06 [pipeline_parallel_scheduler]: 2.02001e-06 [auto_monad_reorder]: 2.673e-05 [get_jit_bprop_graph]: 1.76003e-06 [rewriter_after_jit_bprop_graph]: 4.37e-06 [opt_after_jit_grad]: 0.00049733 [validate]: 5.449e-05 Sums bootstrap : 0.000757s : 0.25% type_inference : 0.226758s : 73.69% event_method : 0.000116s : 0.04% auto_monad : 0.000200s : 0.07% graph_reusing : 0.000010s : 0.00% inline : 0.000004s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000052s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000010s : 0.00% parallel-infer-symbol : 0.000003s : 0.00% pre_auto_parallel : 0.000075s : 0.02% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000071s : 0.02% optimize.rewriter_before_opt_a : 0.000200s : 0.07% optimize.opt_a.expand_dump_flag : 0.000012s : 0.00% optimize.opt_a.switch_simplify : 0.000211s : 0.07% optimize.opt_a.loop_unroll : 0.000078s : 0.03% optimize.opt_a.a_1 : 0.002390s : 0.78% optimize.opt_a.with_stream_mark : 0.000234s : 0.08% optimize.opt_a.recompute_prepare : 0.000069s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000027s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000023s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000022s : 0.01% optimize.opt_a.parameter_eliminate : 0.000010s : 0.00% optimize.opt_a.a_2 : 0.001173s : 0.38% optimize.opt_a.accelerated_algorithm : 0.000054s : 0.02% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000010s : 0.00% optimize.opt_a.shard_inline : 0.000029s : 0.01% optimize.opt_a.merge_send_recv : 0.000036s : 0.01% optimize.opt_a.auto_parallel : 0.000038s : 0.01% optimize.opt_a.parallel : 0.000071s : 0.02% optimize.opt_a.flash_sp : 0.000029s : 0.01% optimize.opt_a.merge_comm : 0.000020s : 0.01% optimize.opt_a.allreduce_fusion : 0.000016s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000036s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000036s : 0.01% optimize.opt_a.virtual_dataset : 0.000029s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000028s : 0.01% optimize.opt_a.virtual_output : 0.000028s : 0.01% optimize.opt_a.merge_forward : 0.000018s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000040s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000081s : 0.03% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000050s : 0.02% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000019s : 0.01% optimize.opt_a.meta_fg_expand : 0.000013s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000006s : 0.00% optimize.opt_a.after_resolve : 0.000042s : 0.01% optimize.opt_a.a_after_grad : 0.000047s : 0.02% optimize.opt_a.renormalize : 0.003054s : 0.99% optimize.opt_a.add_forward_monad_depend : 0.000019s : 0.01% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000061s : 0.02% optimize.opt_a.cse : 0.068225s : 22.17% optimize.opt_a.a_3 : 0.000239s : 0.08% optimize.py_interpret_to_execute_after_opt_a : 0.000015s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000005s : 0.00% optimize.rewriter_after_opt_a : 0.000084s : 0.03% optimize.convert_after_rewriter : 0.000011s : 0.00% optimize.order_py_execute_after_rewriter : 0.000008s : 0.00% optimize.mutable_eliminate : 0.000754s : 0.25% optimize.opt_b.b_1 : 0.000202s : 0.07% optimize.opt_b.b_2 : 0.000009s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000007s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000003s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000003s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000021s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000023s : 0.01% optimize.overlap_param_gather : 0.000006s : 0.00% optimize.cconv : 0.000036s : 0.01% optimize.loop_unroll : 0.000458s : 0.15% optimize.opt_after_cconv.c_1 : 0.000036s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000003s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% optimize.opt_after_cconv.cse : 0.000018s : 0.01% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000017s : 0.01% optimize.tuple_transform.d_1 : 0.000050s : 0.02% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000007s : 0.00% optimize.partial_unused_args_eliminate : 0.000006s : 0.00% optimize.add_recomputation : 0.000061s : 0.02% optimize.cse_after_recomputation.cse : 0.000012s : 0.00% optimize.environ_conv : 0.000052s : 0.02% optimize.swap_dp_allreduce_reducescatter : 0.000010s : 0.00% optimize.bias_add_comm_swap : 0.000006s : 0.00% optimize.label_micro_interleaved_index : 0.000008s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000005s : 0.00% optimize.merge_cast_opt : 0.000004s : 0.00% optimize.slice_recompute_activation : 0.000006s : 0.00% optimize.micro_interleaved_order_control : 0.000017s : 0.01% optimize.assign_add_opt : 0.000004s : 0.00% optimize.ForceFp32Comm : 0.000004s : 0.00% optimize.remove_cast_before_assign_add : 0.000004s : 0.00% optimize.full_micro_interleaved_order_control : 0.000005s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000006s : 0.00% optimize.comm_op_add_attrs : 0.000004s : 0.00% optimize.add_comm_op_reuse_tag : 0.000004s : 0.00% optimize.interleave_split_concat_branches : 0.000004s : 0.00% optimize.interleave_parallel_branches : 0.000004s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000025s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000005s : 0.00% optimize.control_data_broadcast_order : 0.000018s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000005s : 0.00% optimize.offloading_packed_experts : 0.000008s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000009s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000004s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000004s : 0.00% optimize.overlap_recompute_comm : 0.000006s : 0.00% optimize.overlap_grad_ring_attention : 0.000008s : 0.00% optimize.overlap_grad_flash_sp : 0.000040s : 0.01% optimize.begin_end_overlap_inline : 0.000003s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000006s : 0.00% optimize.split_layernorm_comm : 0.000004s : 0.00% optimize.handle_group_info : 0.000004s : 0.00% optimize.symbol_engine_optimizer.build : 0.000003s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000015s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000004s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000027s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000004s : 0.00% opt_after_jit_grad : 0.000497s : 0.16% validate : 0.000054s : 0.02% Time group info: ------[substitution.] 0.000692 105 2.99% : 0.000021s : 12: substitution.depend_value_elim 0.30% : 0.000002s : 3: substitution.elim_not_effective 0.23% : 0.000002s : 3: substitution.fold_const_symbol 1.00% : 0.000007s : 4: substitution.graph_param_transform 82.86% : 0.000574s : 23: substitution.inline 1.43% : 0.000010s : 17: substitution.j_node_and_user_rematch 1.04% : 0.000007s : 8: substitution.redundant_stop_gradient_eliminater 3.44% : 0.000024s : 17: substitution.remove_not_recompute_node 0.53% : 0.000004s : 4: substitution.replace_applicator 1.14% : 0.000008s : 3: substitution.replace_old_param 1.15% : 0.000008s : 4: substitution.set_cell_output_no_recompute 1.93% : 0.000013s : 4: substitution.specialize_transform 1.96% : 0.000014s : 3: substitution.switch_simplify ------[type_inference.] 0.226646 2 92.36% : 0.209339s : 1: type_inference.infer 7.64% : 0.017306s : 1: type_inference.specialize ------[replace.] 0.000271 22 14.85% : 0.000040s : 4: replace.depend_value_elim 58.28% : 0.000158s : 15: replace.inline 26.87% : 0.000073s : 3: replace.switch_simplify ------[match.] 0.000571 22 0.86% : 0.000005s : 4: match.depend_value_elim 97.04% : 0.000554s : 15: match.inline 2.10% : 0.000012s : 3: match.switch_simplify ------[predicate.] 0.000606 3776 1.14% : 0.000007s : 47: predicate.accumulaten_eliminater 0.27% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 1.20% : 0.000007s : 52: predicate.addn_check_dump 1.05% : 0.000006s : 47: predicate.addn_zero_filter 1.00% : 0.000006s : 47: predicate.adjust_all_reduce_mul_add 2.78% : 0.000017s : 87: predicate.arithmetic_simplify 1.13% : 0.000007s : 47: predicate.cast_eliminate 0.43% : 0.000003s : 16: predicate.check_bprop_eliminate 2.58% : 0.000016s : 52: predicate.compare_switch_simplify 0.09% : 0.000001s : 4: predicate.const_output_eliminate 1.14% : 0.000007s : 43: predicate.depend_value_elim 1.10% : 0.000007s : 47: predicate.dict_get_item_const_eliminator 1.16% : 0.000007s : 47: predicate.dict_get_item_eliminator 1.05% : 0.000006s : 47: predicate.dict_set_item_eliminator 0.37% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.07% : 0.000000s : 4: predicate.elim_not_effective 0.14% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.17% : 0.000007s : 51: predicate.environ_add_const_eliminate 1.11% : 0.000007s : 51: predicate.environ_get_add_eliminate 1.10% : 0.000007s : 51: predicate.environ_get_depend_swap 2.28% : 0.000014s : 91: predicate.environ_get_eliminate 1.13% : 0.000007s : 51: predicate.environ_get_set_eliminate 1.38% : 0.000008s : 58: predicate.exchange_switch_depend_value 2.16% : 0.000013s : 58: predicate.float_depend_g_call 1.19% : 0.000007s : 52: predicate.float_environ_get_switch 1.25% : 0.000008s : 56: predicate.float_tuple_getitem_switch 0.07% : 0.000000s : 4: predicate.fold_const_symbol 0.58% : 0.000004s : 20: predicate.get_grad_eliminate 0.10% : 0.000001s : 4: predicate.graph_param_transform 1.01% : 0.000006s : 40: predicate.incorporate_call 0.98% : 0.000006s : 40: predicate.incorporate_call_switch 5.84% : 0.000035s : 181: predicate.inline 0.70% : 0.000004s : 20: predicate.inline_without_move 0.23% : 0.000001s : 20: predicate.j_node_and_user_rematch 0.79% : 0.000005s : 20: predicate.less_batch_normalization 1.31% : 0.000008s : 55: predicate.list_to_tuple_eliminator_ 2.30% : 0.000014s : 102: predicate.load_eliminater 0.33% : 0.000002s : 4: predicate.loop_unroll_after_grad 1.87% : 0.000011s : 76: predicate.loop_unroll_before_grad 1.36% : 0.000008s : 55: predicate.make_slice_get_slice_eliminator 1.25% : 0.000008s : 52: predicate.merge_addn 0.37% : 0.000002s : 16: predicate.micro_step_allgather_replace 0.40% : 0.000002s : 16: predicate.mini_step_allgather_replace 1.05% : 0.000006s : 47: predicate.minmaximum_grad 0.32% : 0.000002s : 4: predicate.mutable_eliminate 0.17% : 0.000001s : 4: predicate.opt_reshape 0.15% : 0.000001s : 4: predicate.parallel_virtual_node 4.11% : 0.000025s : 58: predicate.partial_defer_inline 1.27% : 0.000008s : 51: predicate.partial_eliminate 1.05% : 0.000006s : 47: predicate.print_const_string_wrapper 0.87% : 0.000005s : 36: predicate.reduce_all_const_elim 1.37% : 0.000008s : 47: predicate.reduce_eliminate 2.39% : 0.000015s : 102: predicate.redundant_stop_gradient_eliminater 0.38% : 0.000002s : 20: predicate.remove_not_recompute_node 1.17% : 0.000007s : 63: predicate.replace_applicator 0.35% : 0.000002s : 20: predicate.replace_old_param 0.11% : 0.000001s : 4: predicate.reset_defer_inline 1.13% : 0.000007s : 47: predicate.reshape_eliminate 0.46% : 0.000003s : 16: predicate.row_tensor_add_zeros_like 0.14% : 0.000001s : 4: predicate.row_tensor_eliminate 0.75% : 0.000005s : 16: predicate.same_eliminate 0.63% : 0.000004s : 36: predicate.set_cell_output_no_recompute 0.77% : 0.000005s : 20: predicate.shard_identity_eliminate 0.29% : 0.000002s : 8: predicate.special_op_eliminate 1.45% : 0.000009s : 52: predicate.specialize_transform 0.66% : 0.000004s : 16: predicate.split_environ_get_set_with_tuple_value 0.62% : 0.000004s : 20: predicate.stack_unstack_eliminate 0.14% : 0.000001s : 4: predicate.switch_call_monad_eliminater 1.45% : 0.000009s : 58: predicate.switch_defer_inline 1.78% : 0.000011s : 74: predicate.switch_layer_defer_inline 5.03% : 0.000030s : 196: predicate.switch_simplify 1.10% : 0.000007s : 47: predicate.tile_eliminate 1.07% : 0.000007s : 47: predicate.transpose_eliminate 1.38% : 0.000008s : 55: predicate.tuple_list_convert_item_index_to_positive 1.38% : 0.000008s : 55: predicate.tuple_list_get_item_const_eliminator 1.25% : 0.000008s : 55: predicate.tuple_list_get_item_depend_reorder 2.71% : 0.000016s : 95: predicate.tuple_list_get_item_eliminator 1.43% : 0.000009s : 55: predicate.tuple_list_get_set_item_eliminator 2.48% : 0.000015s : 95: predicate.tuple_list_set_item_eliminator 1.27% : 0.000008s : 55: predicate.tuple_to_list_eliminator_ 2.18% : 0.000013s : 102: predicate.updatestate_pure_node_eliminater 3.27% : 0.000020s : 142: predicate.updatestate_useless_node_eliminater 0.14% : 0.000001s : 4: predicate.value_based_eliminate 0.54% : 0.000003s : 20: predicate.virtual_dataset_eliminate 0.53% : 0.000003s : 20: predicate.virtual_output_eliminate 0.09% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.17% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.002512 28 35.55% : 0.000893s : 8: func_graph_cloner_run.FuncGraphClonerGraph 4.26% : 0.000107s : 2: func_graph_cloner_run.FuncGraphClonerNode 60.19% : 0.001512s : 18: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.469235 267 0.00% : 0.000006s : 1: ForceFp32Comm 4.66% : 0.021844s : 1: add_attr 4.65% : 0.021818s : 1: add_attr_with_inline 0.00% : 0.000007s : 1: add_comm_op_reuse_tag 0.01% : 0.000064s : 1: add_recomputation 0.00% : 0.000007s : 1: assign_add_opt 0.05% : 0.000215s : 1: auto_monad 0.01% : 0.000034s : 1: auto_monad_reorder 0.00% : 0.000007s : 1: begin_end_overlap_inline 0.00% : 0.000008s : 1: bias_add_comm_swap 0.18% : 0.000841s : 1: bootstrap 0.01% : 0.000040s : 1: cconv 0.00% : 0.000007s : 1: comm_op_add_attrs 0.00% : 0.000021s : 1: control_data_broadcast_order 0.00% : 0.000014s : 1: convert_after_rewriter 0.01% : 0.000032s : 1: cse_after_recomputation 0.00% : 0.000008s : 1: dataset_repeat_opt 0.00% : 0.000020s : 1: detach_backward 0.01% : 0.000055s : 1: environ_conv 0.03% : 0.000131s : 1: event_method 0.00% : 0.000007s : 1: full_micro_interleaved_order_control 0.00% : 0.000009s : 1: get_jit_bprop_graph 0.00% : 0.000017s : 1: graph_reusing 0.00% : 0.000008s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000006s : 1: handle_group_info 0.00% : 0.000010s : 1: inline 0.00% : 0.000009s : 1: insert-virtual-dataset 0.00% : 0.000007s : 1: interleave_parallel_branches 0.00% : 0.000007s : 1: interleave_split_concat_branches 0.00% : 0.000009s : 1: label_fine_grained_interleaved_index 0.00% : 0.000011s : 1: label_micro_interleaved_index 0.10% : 0.000464s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000020s : 1: micro_interleaved_order_control 0.16% : 0.000760s : 1: mutable_eliminate 0.00% : 0.000010s : 1: offloading_packed_experts 0.00% : 0.000015s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000016s : 1: opt.transform.mutable_eliminate 0.89% : 0.004171s : 151: opt.transform.opt_a 0.01% : 0.000034s : 1: opt.transform.opt_after_cconv 0.01% : 0.000027s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000121s : 28: opt.transform.opt_b 0.01% : 0.000055s : 2: opt.transform.opt_trans_graph 0.01% : 0.000043s : 4: opt.transform.symbol_engine_opt 19.51% : 0.091538s : 1: opt_a 0.03% : 0.000137s : 1: opt_after_cconv 0.11% : 0.000508s : 1: opt_after_jit_grad 0.07% : 0.000333s : 1: opt_b 20.22% : 0.094860s : 1: optimize 0.01% : 0.000026s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.01% : 0.000043s : 1: overlap_grad_flash_sp 0.00% : 0.000007s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000011s : 1: overlap_grad_ring_attention 0.00% : 0.000007s : 1: overlap_opt_shard_grad_in_pipeline 0.01% : 0.000028s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 1: overlap_param_gather 0.00% : 0.000007s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000012s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000009s : 1: overlap_recompute_comm 0.00% : 0.000011s : 1: parallel-infer-symbol 0.00% : 0.000008s : 1: parallel-infer-symbol-second 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000010s : 1: pipeline_parallel_scheduler 0.00% : 0.000007s : 1: pipeline_split 0.02% : 0.000085s : 1: pre_auto_parallel 0.02% : 0.000075s : 1: py_interpret_to_execute 0.00% : 0.000017s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000006s : 1: remove_cast_before_assign_add 0.00% : 0.000020s : 1: remove_dup_value 0.34% : 0.001597s : 2: renormalize.infer 0.31% : 0.001436s : 2: renormalize.specialize 0.00% : 0.000010s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000088s : 1: rewriter_after_opt_a 0.04% : 0.000206s : 1: rewriter_before_opt_a 0.00% : 0.000007s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000008s : 1: slice_recompute_activation 0.00% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000008s : 1: split_matmul_comm_elemetwise 0.00% : 0.000013s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000117s : 1: symbol_engine_optimizer 0.02% : 0.000100s : 1: tuple_transform 48.34% : 0.226809s : 1: type_inference . [hook] pytest_runtest_teardown:test_with_stream_while_loop tests/st/compiler/stream_event/test_with_stream.py::test_with_stream_while_loop,max_mem:814.0M =============================== 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 84.75s (0:01:24) ===================