==================================================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(167021:281473591054128,MainProcess):2026-01-29-17:38:02.837.936 [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(167021:281473591054128,MainProcess):2026-01-29-17:38:02.838.541 [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 = 0.688867, [21] [bootstrap]: 0.00077315 [type_inference]: 0.522253 [event_method]: 0.00013234 [auto_monad]: 0.00016897 [graph_reusing]: 1.039e-05 [inline]: 2.89001e-06 [add_attr]: 0.00833306, [1] [add_attr_with_inline]: 0.00831604, [1] [Cycle 1]: 0.00014, [2] [tag_attr]: 4.72e-05 [meta_addattr_fg_expand]: 1.103e-05 [parallel-infer-symbol]: 3.76999e-06 [pre_auto_parallel]: 8.31e-05 [insert-virtual-dataset]: 2.58e-06 [parallel-infer-symbol-second]: 7.60017e-07 [dataset_repeat_opt]: 2.32001e-06 [pipeline_split]: 1.55001e-06 [optimize]: 0.155373, [53] [py_interpret_to_execute]: 4.899e-05 [rewriter_before_opt_a]: 0.00019285 [opt_a]: 0.0111035, [3] [Cycle 1]: 0.00703159, [45] [expand_dump_flag]: 4.56002e-06 [switch_simplify]: 0.00013769 [loop_unroll]: 6.405e-05 [a_1]: 0.00193658 [with_stream_mark]: 0.0001633 [recompute_prepare]: 5.687e-05 [updatestate_depend_eliminate]: 1.606e-05 [updatestate_assign_eliminate]: 1.431e-05 [updatestate_loads_eliminate]: 1.356e-05 [parameter_eliminate]: 4.52e-06 [a_2]: 0.00085436 [accelerated_algorithm]: 4.963e-05 [shard]: 1.44e-06 [meta_shard_fg_expand]: 6.14001e-06 [shard_inline]: 1.954e-05 [merge_send_recv]: 1.668e-05 [auto_parallel]: 1.527e-05 [parallel]: 3.886e-05 [flash_sp]: 1.184e-05 [merge_comm]: 1.321e-05 [allreduce_fusion]: 1.262e-05 [matmul_add_comm_reduction]: 1.94e-05 [allreduce_slice_to_reducescatter]: 4.99975e-07 [virtual_shard_identity]: 2.201e-05 [virtual_dataset]: 1.867e-05 [get_grad_eliminate_]: 1.735e-05 [virtual_output]: 1.752e-05 [merge_forward]: 1.103e-05 [cell_reuse_recompute_pass]: 1.17e-06 [offload_activation]: 2.023e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.133e-05 [merge_recompute_call_nodes]: 8.30012e-07 [before_grad]: 3.304e-05 [set_forward_comm_id_for_comm_node_pass]: 1.287e-05 [meta_fg_expand]: 9.44e-06 [flash_sp_send_recv_attached]: 5.15001e-06 [receive_attached]: 1.27999e-06 [after_resolve]: 2.114e-05 [a_after_grad]: 2.894e-05 [renormalize]: 0.00230535 [add_forward_monad_depend]: 7.98999e-06 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 3.253e-05 [cse]: 0.00021826 [a_3]: 0.00012678 [Cycle 2]: 0.00261334, [45] [expand_dump_flag]: 2.58e-06 [switch_simplify]: 1.646e-05 [loop_unroll]: 1.407e-05 [a_1]: 0.0004184 [with_stream_mark]: 2.159e-05 [recompute_prepare]: 1.465e-05 [updatestate_depend_eliminate]: 9.34e-06 [updatestate_assign_eliminate]: 8.37e-06 [updatestate_loads_eliminate]: 7.95998e-06 [parameter_eliminate]: 2.04e-06 [a_2]: 0.0004613 [accelerated_algorithm]: 1.907e-05 [shard]: 2.13002e-06 [meta_shard_fg_expand]: 3.03998e-06 [shard_inline]: 1.083e-05 [merge_send_recv]: 1.393e-05 [auto_parallel]: 1.332e-05 [parallel]: 8.97e-06 [flash_sp]: 4.73001e-06 [merge_comm]: 6.89999e-06 [allreduce_fusion]: 6.06998e-06 [matmul_add_comm_reduction]: 1.445e-05 [allreduce_slice_to_reducescatter]: 7.89994e-07 [virtual_shard_identity]: 1.296e-05 [virtual_dataset]: 1.101e-05 [get_grad_eliminate_]: 1.001e-05 [virtual_output]: 9.56e-06 [merge_forward]: 7.01001e-06 [cell_reuse_recompute_pass]: 2.46998e-06 [offload_activation]: 1.517e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.504e-05 [merge_recompute_call_nodes]: 1.44998e-06 [before_grad]: 1.935e-05 [set_forward_comm_id_for_comm_node_pass]: 7.78001e-06 [meta_fg_expand]: 4.50001e-06 [flash_sp_send_recv_attached]: 1.84e-06 [receive_attached]: 2.47001e-06 [after_resolve]: 1.598e-05 [a_after_grad]: 1.737e-05 [renormalize]: 0.00072364 [add_forward_monad_depend]: 6.79001e-06 [auto_monad_grad]: 2.15002e-06 [auto_monad_eliminator]: 2.261e-05 [cse]: 0.00011032 [a_3]: 0.00010395 [Cycle 3]: 0.00143564, [45] [expand_dump_flag]: 2.27999e-06 [switch_simplify]: 1.33e-05 [loop_unroll]: 1.108e-05 [a_1]: 0.00033294 [with_stream_mark]: 2.151e-05 [recompute_prepare]: 1.258e-05 [updatestate_depend_eliminate]: 7.63001e-06 [updatestate_assign_eliminate]: 6.41998e-06 [updatestate_loads_eliminate]: 5.72999e-06 [parameter_eliminate]: 2.02999e-06 [a_2]: 0.00019684 [accelerated_algorithm]: 1.857e-05 [shard]: 2.61999e-06 [meta_shard_fg_expand]: 2.98e-06 [shard_inline]: 1.219e-05 [merge_send_recv]: 1.193e-05 [auto_parallel]: 1.454e-05 [parallel]: 9.08002e-06 [flash_sp]: 1.74e-06 [merge_comm]: 6.89999e-06 [allreduce_fusion]: 6.64001e-06 [matmul_add_comm_reduction]: 1.417e-05 [allreduce_slice_to_reducescatter]: 4.40021e-07 [virtual_shard_identity]: 1.37e-05 [virtual_dataset]: 1.081e-05 [get_grad_eliminate_]: 1.149e-05 [virtual_output]: 1.114e-05 [merge_forward]: 7.21999e-06 [cell_reuse_recompute_pass]: 2.51998e-06 [offload_activation]: 1.41e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.9e-05 [merge_recompute_call_nodes]: 1.67001e-06 [before_grad]: 1.93e-05 [set_forward_comm_id_for_comm_node_pass]: 7.55e-06 [meta_fg_expand]: 4.65001e-06 [flash_sp_send_recv_attached]: 2.37001e-06 [receive_attached]: 2.27001e-06 [after_resolve]: 1.58e-05 [a_after_grad]: 1.772e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.74999e-06 [auto_monad_grad]: 2.51e-06 [auto_monad_eliminator]: 1.859e-05 [cse]: 4.957e-05 [a_3]: 8.938e-05 [py_interpret_to_execute_after_opt_a]: 2.587e-05 [slice_cell_reuse_recomputed_activation]: 5.29e-06 [rewriter_after_opt_a]: 9.709e-05 [convert_after_rewriter]: 1.648e-05 [order_py_execute_after_rewriter]: 1.14e-05 [mutable_eliminate]: 0.00085656 [opt_b]: 0.140751, [1] [Cycle 1]: 0.140731, [7] [b_1]: 0.00028616 [b_2]: 5.378e-05 [updatestate_depend_eliminate]: 2.135e-05 [updatestate_assign_eliminate]: 6.08002e-06 [updatestate_loads_eliminate]: 6.07999e-06 [renormalize]: 1.10001e-06 [cse]: 8.489e-05 [optimize_parallel_all_gather_comm]: 3.92e-05 [overlap_param_gather]: 5.35999e-06 [cconv]: 4.588e-05 [loop_unroll]: 0.00083033 [opt_after_cconv]: 0.0002258, [1] [Cycle 1]: 0.00021233, [7] [c_1]: 6.335e-05 [parameter_eliminate]: 6.94001e-06 [updatestate_depend_eliminate]: 1.314e-05 [updatestate_assign_eliminate]: 5.72999e-06 [updatestate_loads_eliminate]: 5.88002e-06 [cse]: 5.614e-05 [renormalize]: 4.39992e-07 [remove_dup_value]: 0.00010106 [tuple_transform]: 0.00014377, [1] [Cycle 1]: 0.00013539, [4] [d_1]: 8.704e-05 [none_parameter_eliminate]: 2.49001e-06 [renormalize]: 1.60013e-07 [switch_simplify]: 1.177e-05 [partial_unused_args_eliminate]: 5.25999e-06 [add_recomputation]: 0.00010174 [cse_after_recomputation]: 5.44e-05, [1] [Cycle 1]: 4.619e-05, [1] [cse]: 3.447e-05 [environ_conv]: 3.04e-05 [swap_dp_allreduce_reducescatter]: 1.268e-05 [bias_add_comm_swap]: 6.59999e-06 [label_micro_interleaved_index]: 1.049e-05 [label_fine_grained_interleaved_index]: 5.69999e-06 [merge_cast_opt]: 4.19002e-06 [slice_recompute_activation]: 5.13002e-06 [micro_interleaved_order_control]: 4.97e-06 [assign_add_opt]: 4.01001e-06 [ForceFp32Comm]: 3.43e-06 [remove_cast_before_assign_add]: 3.90998e-06 [full_micro_interleaved_order_control]: 5.01002e-06 [reorder_send_recv_between_fp_bp]: 5.37001e-06 [comm_op_add_attrs]: 3.83999e-06 [add_comm_op_reuse_tag]: 3.48e-06 [interleave_split_concat_branches]: 3.75998e-06 [interleave_parallel_branches]: 3.79002e-06 [overlap_opt_shard_in_pipeline]: 3.218e-05 [overlap_opt_shard_grad_in_pipeline]: 4.67e-06 [control_data_broadcast_order]: 2.82e-05 [grouped_pairwise_exchange_alltoall]: 3.71001e-06 [offloading_packed_experts]: 1.089e-05 [overlap_recompute_and_grad_model_parallel]: 1.004e-05 [overlap_grad_matmul_and_grad_allreduce]: 4.06001e-06 [overlap_recompute_allgather_and_fa_grad]: 4.00998e-06 [overlap_recompute_comm]: 5.39e-06 [overlap_grad_ring_attention]: 1.062e-05 [overlap_grad_flash_sp]: 5.847e-05 [begin_end_overlap_inline]: 3.41999e-06 [split_matmul_comm_elemetwise]: 5.04e-06 [split_layernorm_comm]: 4.07e-06 [handle_group_info]: 3.7e-06 [symbol_engine_optimizer]: 0.00014807, [1] [Cycle 1]: 0.00013949, [6] [build]: 6.44999e-06 [elim_shapecalc]: 1.902e-05 [elim_not_effective]: 2.833e-05 [opt_reshape]: 1.371e-05 [fold_const_symbol]: 2.017e-05 [renormalize]: 3.9002e-07 [detach_backward]: 4.22998e-06 [pipeline_parallel_scheduler]: 1.87001e-06 [auto_monad_reorder]: 4.82e-05 [get_jit_bprop_graph]: 2.76e-06 [rewriter_after_jit_bprop_graph]: 5.84e-06 [opt_after_jit_grad]: 0.00080892 [validate]: 7.924e-05 Sums bootstrap : 0.000773s : 0.14% type_inference : 0.522253s : 97.13% event_method : 0.000132s : 0.02% auto_monad : 0.000169s : 0.03% graph_reusing : 0.000010s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000047s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000011s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000083s : 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 : 0.000049s : 0.01% optimize.rewriter_before_opt_a : 0.000193s : 0.04% optimize.opt_a.expand_dump_flag : 0.000009s : 0.00% optimize.opt_a.switch_simplify : 0.000167s : 0.03% optimize.opt_a.loop_unroll : 0.000089s : 0.02% optimize.opt_a.a_1 : 0.002688s : 0.50% optimize.opt_a.with_stream_mark : 0.000206s : 0.04% optimize.opt_a.recompute_prepare : 0.000084s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000033s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000029s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000027s : 0.01% optimize.opt_a.parameter_eliminate : 0.000009s : 0.00% optimize.opt_a.a_2 : 0.001513s : 0.28% optimize.opt_a.accelerated_algorithm : 0.000087s : 0.02% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000012s : 0.00% optimize.opt_a.shard_inline : 0.000043s : 0.01% optimize.opt_a.merge_send_recv : 0.000043s : 0.01% optimize.opt_a.auto_parallel : 0.000043s : 0.01% optimize.opt_a.parallel : 0.000057s : 0.01% optimize.opt_a.flash_sp : 0.000018s : 0.00% optimize.opt_a.merge_comm : 0.000027s : 0.01% optimize.opt_a.allreduce_fusion : 0.000025s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000048s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000049s : 0.01% optimize.opt_a.virtual_dataset : 0.000040s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000039s : 0.01% optimize.opt_a.virtual_output : 0.000038s : 0.01% optimize.opt_a.merge_forward : 0.000025s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000050s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000095s : 0.02% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000072s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000028s : 0.01% optimize.opt_a.meta_fg_expand : 0.000019s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000009s : 0.00% optimize.opt_a.receive_attached : 0.000006s : 0.00% optimize.opt_a.after_resolve : 0.000053s : 0.01% optimize.opt_a.a_after_grad : 0.000064s : 0.01% optimize.opt_a.renormalize : 0.003029s : 0.56% optimize.opt_a.add_forward_monad_depend : 0.000018s : 0.00% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000074s : 0.01% optimize.opt_a.cse : 0.000378s : 0.07% optimize.opt_a.a_3 : 0.000320s : 0.06% optimize.py_interpret_to_execute_after_opt_a : 0.000026s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000005s : 0.00% optimize.rewriter_after_opt_a : 0.000097s : 0.02% optimize.convert_after_rewriter : 0.000016s : 0.00% optimize.order_py_execute_after_rewriter : 0.000011s : 0.00% optimize.mutable_eliminate : 0.000857s : 0.16% optimize.opt_b.b_1 : 0.000286s : 0.05% optimize.opt_b.b_2 : 0.000054s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000021s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000085s : 0.02% optimize.optimize_parallel_all_gather_comm : 0.000039s : 0.01% optimize.overlap_param_gather : 0.000005s : 0.00% optimize.cconv : 0.000046s : 0.01% optimize.loop_unroll : 0.000830s : 0.15% optimize.opt_after_cconv.c_1 : 0.000063s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.cse : 0.000056s : 0.01% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000101s : 0.02% optimize.tuple_transform.d_1 : 0.000087s : 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 : 0.000012s : 0.00% optimize.partial_unused_args_eliminate : 0.000005s : 0.00% optimize.add_recomputation : 0.000102s : 0.02% optimize.cse_after_recomputation.cse : 0.000034s : 0.01% optimize.environ_conv : 0.000030s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000013s : 0.00% optimize.bias_add_comm_swap : 0.000007s : 0.00% optimize.label_micro_interleaved_index : 0.000010s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000006s : 0.00% optimize.merge_cast_opt : 0.000004s : 0.00% optimize.slice_recompute_activation : 0.000005s : 0.00% optimize.micro_interleaved_order_control : 0.000005s : 0.00% optimize.assign_add_opt : 0.000004s : 0.00% optimize.ForceFp32Comm : 0.000003s : 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 : 0.000005s : 0.00% optimize.comm_op_add_attrs : 0.000004s : 0.00% optimize.add_comm_op_reuse_tag : 0.000003s : 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 : 0.000032s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000005s : 0.00% optimize.control_data_broadcast_order : 0.000028s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000004s : 0.00% optimize.offloading_packed_experts : 0.000011s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 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 : 0.000005s : 0.00% optimize.overlap_grad_ring_attention : 0.000011s : 0.00% optimize.overlap_grad_flash_sp : 0.000058s : 0.01% optimize.begin_end_overlap_inline : 0.000003s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000005s : 0.00% optimize.split_layernorm_comm : 0.000004s : 0.00% optimize.handle_group_info : 0.000004s : 0.00% optimize.symbol_engine_optimizer.build : 0.000006s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000019s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000028s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000014s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000020s : 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 : 0.000048s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000809s : 0.15% validate : 0.000079s : 0.01% Time group info: ------[substitution.] 0.000785 163 27.76% : 0.000218s : 18: substitution.arithmetic_simplify 2.12% : 0.000017s : 12: substitution.depend_value_elim 0.53% : 0.000004s : 7: substitution.elim_not_effective 0.40% : 0.000003s : 7: substitution.fold_const_symbol 1.28% : 0.000010s : 8: substitution.graph_param_transform 52.51% : 0.000412s : 23: substitution.inline 1.85% : 0.000015s : 29: substitution.j_node_and_user_rematch 3.76% : 0.000029s : 6: substitution.less_batch_normalization 0.72% : 0.000006s : 8: substitution.redundant_stop_gradient_eliminater 2.49% : 0.000020s : 29: substitution.remove_not_recompute_node 0.52% : 0.000004s : 4: substitution.replace_applicator 0.99% : 0.000008s : 3: substitution.replace_old_param 2.41% : 0.000019s : 4: substitution.set_cell_output_no_recompute 1.73% : 0.000014s : 4: substitution.specialize_transform 0.93% : 0.000007s : 1: substitution.switch_simplify ------[type_inference.] 0.522161 2 91.79% : 0.479317s : 1: type_inference.infer 8.21% : 0.042844s : 1: type_inference.specialize ------[replace.] 0.000211 20 15.70% : 0.000033s : 4: replace.depend_value_elim 65.41% : 0.000138s : 15: replace.inline 18.89% : 0.000040s : 1: replace.switch_simplify ------[match.] 0.000407 20 1.07% : 0.000004s : 4: match.depend_value_elim 97.39% : 0.000396s : 15: match.inline 1.54% : 0.000006s : 1: match.switch_simplify ------[predicate.] 0.000840 5290 1.05% : 0.000009s : 62: predicate.accumulaten_eliminater 0.46% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.21% : 0.000010s : 72: predicate.addn_check_dump 1.05% : 0.000009s : 62: predicate.addn_zero_filter 0.99% : 0.000008s : 62: predicate.adjust_all_reduce_mul_add 2.76% : 0.000023s : 122: predicate.arithmetic_simplify 1.13% : 0.000010s : 62: predicate.cast_eliminate 0.56% : 0.000005s : 28: predicate.check_bprop_eliminate 1.28% : 0.000011s : 72: predicate.compare_switch_simplify 0.09% : 0.000001s : 8: predicate.const_output_eliminate 1.18% : 0.000010s : 63: predicate.depend_value_elim 1.13% : 0.000009s : 62: predicate.dict_get_item_const_eliminator 1.16% : 0.000010s : 62: predicate.dict_get_item_eliminator 1.08% : 0.000009s : 62: predicate.dict_set_item_eliminator 0.52% : 0.000004s : 16: predicate.dumpgradient_eliminate 0.12% : 0.000001s : 8: predicate.elim_not_effective 0.22% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.25% : 0.000010s : 70: predicate.environ_add_const_eliminate 1.14% : 0.000010s : 70: predicate.environ_get_add_eliminate 1.16% : 0.000010s : 70: predicate.environ_get_depend_swap 2.29% : 0.000019s : 130: predicate.environ_get_eliminate 1.18% : 0.000010s : 70: predicate.environ_get_set_eliminate 1.21% : 0.000010s : 73: predicate.exchange_switch_depend_value 1.76% : 0.000015s : 73: predicate.float_depend_g_call 1.21% : 0.000010s : 72: predicate.float_environ_get_switch 1.33% : 0.000011s : 80: predicate.float_tuple_getitem_switch 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.64% : 0.000005s : 32: predicate.get_grad_eliminate 0.12% : 0.000001s : 8: predicate.graph_param_transform 1.03% : 0.000009s : 60: predicate.incorporate_call 0.96% : 0.000008s : 60: predicate.incorporate_call_switch 5.94% : 0.000050s : 251: predicate.inline 0.76% : 0.000006s : 32: predicate.inline_without_move 0.26% : 0.000002s : 32: predicate.j_node_and_user_rematch 0.87% : 0.000007s : 32: predicate.less_batch_normalization 1.35% : 0.000011s : 78: predicate.list_to_tuple_eliminator_ 2.33% : 0.000020s : 140: predicate.load_eliminater 0.72% : 0.000006s : 8: predicate.loop_unroll_after_grad 1.65% : 0.000014s : 88: predicate.loop_unroll_before_grad 1.50% : 0.000013s : 78: predicate.make_slice_get_slice_eliminator 1.27% : 0.000011s : 72: predicate.merge_addn 0.55% : 0.000005s : 28: predicate.micro_step_allgather_replace 0.52% : 0.000004s : 28: predicate.mini_step_allgather_replace 0.98% : 0.000008s : 62: predicate.minmaximum_grad 0.45% : 0.000004s : 8: predicate.mutable_eliminate 0.20% : 0.000002s : 8: predicate.opt_reshape 0.20% : 0.000002s : 8: predicate.parallel_virtual_node 1.44% : 0.000012s : 73: predicate.partial_defer_inline 1.32% : 0.000011s : 70: predicate.partial_eliminate 1.02% : 0.000009s : 62: predicate.print_const_string_wrapper 1.02% : 0.000009s : 56: predicate.reduce_all_const_elim 1.35% : 0.000011s : 62: predicate.reduce_eliminate 2.45% : 0.000021s : 140: predicate.redundant_stop_gradient_eliminater 0.42% : 0.000004s : 32: predicate.remove_not_recompute_node 1.13% : 0.000009s : 90: predicate.replace_applicator 0.36% : 0.000003s : 32: predicate.replace_old_param 0.13% : 0.000001s : 8: predicate.reset_defer_inline 1.06% : 0.000009s : 62: predicate.reshape_eliminate 0.59% : 0.000005s : 28: predicate.row_tensor_add_zeros_like 0.92% : 0.000008s : 8: predicate.row_tensor_eliminate 0.74% : 0.000006s : 28: predicate.same_eliminate 0.55% : 0.000005s : 48: predicate.set_cell_output_no_recompute 0.70% : 0.000006s : 32: predicate.shard_identity_eliminate 0.37% : 0.000003s : 16: predicate.special_op_eliminate 1.51% : 0.000013s : 72: predicate.specialize_transform 0.76% : 0.000006s : 28: predicate.split_environ_get_set_with_tuple_value 0.77% : 0.000006s : 32: predicate.stack_unstack_eliminate 0.18% : 0.000002s : 8: predicate.switch_call_monad_eliminater 1.30% : 0.000011s : 73: predicate.switch_defer_inline 1.83% : 0.000015s : 101: predicate.switch_layer_defer_inline 4.67% : 0.000039s : 243: predicate.switch_simplify 1.07% : 0.000009s : 62: predicate.tile_eliminate 1.11% : 0.000009s : 62: predicate.transpose_eliminate 1.40% : 0.000012s : 78: predicate.tuple_list_convert_item_index_to_positive 1.53% : 0.000013s : 78: predicate.tuple_list_get_item_const_eliminator 1.37% : 0.000012s : 78: predicate.tuple_list_get_item_depend_reorder 2.85% : 0.000024s : 138: predicate.tuple_list_get_item_eliminator 1.40% : 0.000012s : 78: predicate.tuple_list_get_set_item_eliminator 2.62% : 0.000022s : 138: predicate.tuple_list_set_item_eliminator 1.50% : 0.000013s : 78: predicate.tuple_to_list_eliminator_ 2.26% : 0.000019s : 140: predicate.updatestate_pure_node_eliminater 3.42% : 0.000029s : 200: predicate.updatestate_useless_node_eliminater 0.23% : 0.000002s : 8: predicate.value_based_eliminate 0.63% : 0.000005s : 32: predicate.virtual_dataset_eliminate 0.65% : 0.000005s : 32: predicate.virtual_output_eliminate 0.15% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.34% : 0.000003s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001879 26 44.18% : 0.000830s : 8: func_graph_cloner_run.FuncGraphClonerGraph 3.74% : 0.000070s : 2: func_graph_cloner_run.FuncGraphClonerNode 52.08% : 0.000979s : 16: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.861035 267 0.00% : 0.000006s : 1: ForceFp32Comm 0.97% : 0.008344s : 1: add_attr 0.97% : 0.008321s : 1: add_attr_with_inline 0.00% : 0.000006s : 1: add_comm_op_reuse_tag 0.01% : 0.000106s : 1: add_recomputation 0.00% : 0.000007s : 1: assign_add_opt 0.02% : 0.000183s : 1: auto_monad 0.01% : 0.000057s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: begin_end_overlap_inline 0.00% : 0.000010s : 1: bias_add_comm_swap 0.10% : 0.000860s : 1: bootstrap 0.01% : 0.000050s : 1: cconv 0.00% : 0.000007s : 1: comm_op_add_attrs 0.00% : 0.000032s : 1: control_data_broadcast_order 0.00% : 0.000020s : 1: convert_after_rewriter 0.01% : 0.000058s : 1: cse_after_recomputation 0.00% : 0.000009s : 1: dataset_repeat_opt 0.00% : 0.000029s : 1: detach_backward 0.00% : 0.000034s : 1: environ_conv 0.02% : 0.000149s : 1: event_method 0.00% : 0.000009s : 1: full_micro_interleaved_order_control 0.00% : 0.000009s : 1: get_jit_bprop_graph 0.00% : 0.000018s : 1: graph_reusing 0.00% : 0.000006s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000006s : 1: handle_group_info 0.00% : 0.000009s : 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% : 0.000013s : 1: label_micro_interleaved_index 0.10% : 0.000840s : 1: loop_unroll 0.00% : 0.000007s : 1: merge_cast_opt 0.00% : 0.000008s : 1: micro_interleaved_order_control 0.10% : 0.000865s : 1: mutable_eliminate 0.00% : 0.000014s : 1: offloading_packed_experts 0.00% : 0.000032s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000027s : 1: opt.transform.mutable_eliminate 0.59% : 0.005053s : 151: opt.transform.opt_a 0.01% : 0.000062s : 1: opt.transform.opt_after_cconv 0.01% : 0.000046s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000254s : 28: opt.transform.opt_b 0.01% : 0.000096s : 2: opt.transform.opt_trans_graph 0.01% : 0.000076s : 4: opt.transform.symbol_engine_opt 1.29% : 0.011108s : 1: opt_a 0.03% : 0.000230s : 1: opt_after_cconv 0.10% : 0.000822s : 1: opt_after_jit_grad 16.35% : 0.140756s : 1: opt_b 18.10% : 0.155817s : 1: optimize 0.01% : 0.000043s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.01% : 0.000063s : 1: overlap_grad_flash_sp 0.00% : 0.000007s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000014s : 1: overlap_grad_ring_attention 0.00% : 0.000008s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000036s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000007s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 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% : 0.000007s : 1: parallel-infer-symbol-second 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000009s : 1: pipeline_parallel_scheduler 0.00% : 0.000008s : 1: pipeline_split 0.01% : 0.000091s : 1: pre_auto_parallel 0.01% : 0.000053s : 1: py_interpret_to_execute 0.00% : 0.000030s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000006s : 1: remove_cast_before_assign_add 0.01% : 0.000107s : 1: remove_dup_value 0.19% : 0.001679s : 2: renormalize.infer 0.16% : 0.001335s : 2: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000103s : 1: rewriter_after_opt_a 0.02% : 0.000197s : 1: rewriter_before_opt_a 0.00% : 0.000008s : 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% : 0.000016s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000151s : 1: symbol_engine_optimizer 0.02% : 0.000147s : 1: tuple_transform 60.66% : 0.522296s : 1: type_inference [WARNING] ME(167021:281473591054128,MainProcess):2026-01-29-17:38:20.393.543 [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. TotalTime = 1.74242, [30] [bootstrap]: 0.00052463 [type_inference]: 0.810184 [event_method]: 5.59e-05 [auto_monad]: 0.00019794 [graph_reusing]: 1.156e-05 [pre_auto_parallel]: 4.22e-06 [py_interpret_to_execute]: 6.739e-05 [rewriter_before_opt_a]: 0.0002218 [expand_dump_flag]: 4.94e-06 [jit_opt_a]: 0.927423, [3] [Cycle 1]: 0.693327, [27] [switch_simplify]: 0.00023065 [loop_unroll]: 9.363e-05 [a_1]: 0.0026089 [with_stream_mark]: 0.00018705 [recompute_prepare]: 5.595e-05 [updatestate_depend_eliminate]: 4.139e-05 [updatestate_assign_eliminate]: 2.003e-05 [updatestate_loads_eliminate]: 2.018e-05 [parameter_eliminate]: 6.19999e-06 [specialize_transform]: 6.018e-05 [updatestate_useless_node_eliminater]: 3.552e-05 [accelerated_algorithm]: 8.846e-05 [meta_shard_fg_expand]: 9.34e-06 [get_grad_eliminate_]: 3.49e-05 [merge_forward]: 2.4e-05 [cell_reuse_recompute_pass]: 1.26002e-06 [cell_reuse_handle_not_recompute_node_pass]: 7.176e-05 [j_node_and_user_rematch]: 7.744e-05 [meta_fg_expand]: 0.341524, [1] [partial_eliminate_before_grad]: 0.00042501, [1] [Cycle 1]: 0.00040541, [1] [partial_eliminate_]: 0.00035573 [replace_old_param]: 0.00037089 [inline_without_move]: 0.00043241 [renormalize]: 0.3454 [add_forward_monad_depend]: 7.195e-05 [auto_monad_grad]: 3.374e-05 [auto_monad_eliminator]: 0.00029525 [cse]: 0.00076254 [replace_applicator]: 0.00038221 [Cycle 2]: 0.22881, [27] [switch_simplify]: 0.00022748 [loop_unroll]: 0.00022086 [a_1]: 0.223408 [with_stream_mark]: 4.372e-05 [recompute_prepare]: 2.271e-05 [updatestate_depend_eliminate]: 1.169e-05 [updatestate_assign_eliminate]: 8.37e-06 [updatestate_loads_eliminate]: 8.12998e-06 [parameter_eliminate]: 2.87002e-06 [specialize_transform]: 1.802e-05 [updatestate_useless_node_eliminater]: 1.57e-05 [accelerated_algorithm]: 4.539e-05 [meta_shard_fg_expand]: 1.268e-05 [get_grad_eliminate_]: 1.503e-05 [merge_forward]: 9.99001e-06 [cell_reuse_recompute_pass]: 1.33002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.782e-05 [j_node_and_user_rematch]: 2.757e-05 [meta_fg_expand]: 0.00011543 [replace_old_param]: 2.215e-05 [inline_without_move]: 1.621e-05 [renormalize]: 0.00380572 [add_forward_monad_depend]: 1.234e-05 [auto_monad_grad]: 3.5e-06 [auto_monad_eliminator]: 4.2e-05 [cse]: 0.00034649 [replace_applicator]: 3.821e-05 [Cycle 3]: 0.00102649, [27] [switch_simplify]: 1.761e-05 [loop_unroll]: 1.545e-05 [a_1]: 0.00048293 [with_stream_mark]: 2.783e-05 [recompute_prepare]: 1.597e-05 [updatestate_depend_eliminate]: 1.064e-05 [updatestate_assign_eliminate]: 9.55001e-06 [updatestate_loads_eliminate]: 8.08999e-06 [parameter_eliminate]: 2.27999e-06 [specialize_transform]: 1.579e-05 [updatestate_useless_node_eliminater]: 1.45e-05 [accelerated_algorithm]: 2.476e-05 [meta_shard_fg_expand]: 4.26001e-06 [get_grad_eliminate_]: 1.506e-05 [merge_forward]: 9.64e-06 [cell_reuse_recompute_pass]: 3.18998e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.775e-05 [j_node_and_user_rematch]: 3.135e-05 [meta_fg_expand]: 7.28e-06 [replace_old_param]: 2.178e-05 [inline_without_move]: 1.61e-05 [renormalize]: 1.19995e-07 [add_forward_monad_depend]: 3.16999e-06 [auto_monad_grad]: 2.30002e-06 [auto_monad_eliminator]: 2.504e-05 [cse]: 5.035e-05 [replace_applicator]: 1.563e-05 [py_interpret_to_execute_after_opt_a]: 2.611e-05 [rewriter_after_opt_a]: 7.823e-05 [convert_after_rewriter]: 1.458e-05 [order_py_execute_after_rewriter]: 1.234e-05 [mutable_eliminate]: 0.00080001 [jit_opt_b]: 0.00011417, [1] [Cycle 1]: 0.00010439, [2] [frontend_op_eliminate]: 4.761e-05 [inline_after_opt_a]: 4.398e-05 [cconv]: 3.759e-05 [loop_unroll]: 0.00052022 [jit_opt_after_cconv]: 0.0003102, [1] [Cycle 1]: 0.00030293, [11] [c_1]: 7.036e-05 [parameter_eliminate]: 4.20999e-06 [updatestate_depend_eliminate]: 1.537e-05 [updatestate_assign_eliminate]: 8.17e-06 [updatestate_loads_eliminate]: 6.92002e-06 [cse]: 5.856e-05 [call_graph_tuple_transform]: 5.088e-05 [tuple_list_get_item_eliminator]: 1.537e-05 [none_parameter_eliminate]: 1.82999e-06 [renormalize]: 6.80011e-07 [switch_simplify]: 1.574e-05 [remove_dup_value]: 9.083e-05 [partial_unused_args_eliminate]: 2.59001e-06 [environ_conv]: 1.039e-05 [add_recomputation]: 0.00012513 [cse_after_recomputation]: 5e-05, [1] [Cycle 1]: 4.347e-05, [1] [cse]: 3.573e-05 [auto_monad_reorder]: 3.281e-05 [get_jit_bprop_graph]: 2.14e-06 [rewriter_after_jit_bprop_graph]: 0.00021557 [opt_after_jit_grad]: 0.00053703 [symbol_engine_optimizer]: 0.00014656, [1] [Cycle 1]: 0.00013973, [6] [build]: 9.49e-06 [elim_shapecalc]: 1.843e-05 [elim_not_effective]: 3.21e-05 [opt_reshape]: 1.508e-05 [fold_const_symbol]: 3.362e-05 [renormalize]: 4.09986e-07 [validate]: 6.384e-05 Sums bootstrap : 0.000525s : 0.04% type_inference : 0.810184s : 58.06% event_method : 0.000056s : 0.00% auto_monad : 0.000198s : 0.01% graph_reusing : 0.000012s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000067s : 0.00% rewriter_before_opt_a : 0.000222s : 0.02% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000476s : 0.03% jit_opt_a.loop_unroll : 0.000330s : 0.02% jit_opt_a.a_1 : 0.226500s : 16.23% jit_opt_a.with_stream_mark : 0.000259s : 0.02% jit_opt_a.recompute_prepare : 0.000095s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000064s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000036s : 0.00% jit_opt_a.parameter_eliminate : 0.000011s : 0.00% jit_opt_a.specialize_transform : 0.000094s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000066s : 0.00% jit_opt_a.accelerated_algorithm : 0.000159s : 0.01% jit_opt_a.meta_shard_fg_expand : 0.000026s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000065s : 0.00% jit_opt_a.merge_forward : 0.000044s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000147s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000136s : 0.01% jit_opt_a.meta_fg_expand : 0.000123s : 0.01% jit_opt_a.meta_fg_expand.partial_eliminate_before_grad.partial_eliminate_ : 0.000356s : 0.03% jit_opt_a.replace_old_param : 0.000415s : 0.03% jit_opt_a.inline_without_move : 0.000465s : 0.03% jit_opt_a.renormalize : 0.349205s : 25.02% jit_opt_a.add_forward_monad_depend : 0.000087s : 0.01% jit_opt_a.auto_monad_grad : 0.000040s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000362s : 0.03% jit_opt_a.cse : 0.001159s : 0.08% jit_opt_a.replace_applicator : 0.000436s : 0.03% py_interpret_to_execute_after_opt_a : 0.000026s : 0.00% rewriter_after_opt_a : 0.000078s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000012s : 0.00% mutable_eliminate : 0.000800s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000048s : 0.00% jit_opt_b.inline_after_opt_a : 0.000044s : 0.00% cconv : 0.000038s : 0.00% loop_unroll : 0.000520s : 0.04% jit_opt_after_cconv.c_1 : 0.000070s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000059s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000051s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000015s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000016s : 0.00% remove_dup_value : 0.000091s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000010s : 0.00% add_recomputation : 0.000125s : 0.01% cse_after_recomputation.cse : 0.000036s : 0.00% auto_monad_reorder : 0.000033s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000216s : 0.02% opt_after_jit_grad : 0.000537s : 0.04% symbol_engine_optimizer.build : 0.000009s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000018s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000032s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000015s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000034s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000064s : 0.00% Time group info: ------[substitution.] 0.004630 528 8.07% : 0.000373s : 25: substitution.arithmetic_simplify 0.21% : 0.000010s : 5: substitution.depend_value_elim 0.13% : 0.000006s : 12: substitution.elim_not_effective 0.13% : 0.000006s : 12: substitution.fold_const_symbol 18.59% : 0.000861s : 4: substitution.getattr_setattr_resolve 0.28% : 0.000013s : 13: substitution.graph_param_transform 50.88% : 0.002356s : 54: substitution.inline 3.19% : 0.000148s : 19: substitution.inline_without_move 0.80% : 0.000037s : 53: substitution.j_node_and_user_rematch 1.52% : 0.000070s : 7: substitution.less_batch_normalization 0.89% : 0.000041s : 27: substitution.minmaximum_grad 2.04% : 0.000094s : 18: substitution.partial_eliminate 0.08% : 0.000004s : 4: substitution.redundant_stop_gradient_eliminater 0.71% : 0.000033s : 53: substitution.remove_not_recompute_node 3.80% : 0.000176s : 57: substitution.replace_applicator 0.65% : 0.000030s : 39: substitution.replace_old_param 0.18% : 0.000008s : 5: substitution.set_cell_output_no_recompute 0.33% : 0.000015s : 4: substitution.specialize_transform 0.22% : 0.000010s : 1: substitution.switch_simplify 1.80% : 0.000083s : 27: substitution.tuple_list_convert_item_index_to_positive 1.33% : 0.000062s : 27: substitution.tuple_list_get_item_depend_reorder 4.21% : 0.000195s : 62: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.809869 2 71.12% : 0.576005s : 1: type_inference.infer 28.88% : 0.233864s : 1: type_inference.specialize ------[replace.] 0.001491 94 0.46% : 0.000007s : 1: replace.arithmetic_simplify 4.58% : 0.000068s : 3: replace.getattr_setattr_resolve 43.53% : 0.000649s : 50: replace.inline 7.01% : 0.000105s : 4: replace.partial_eliminate 3.26% : 0.000049s : 1: replace.switch_simplify 41.16% : 0.000614s : 35: replace.tuple_list_get_item_eliminator ------[match.] 0.003326 94 0.68% : 0.000023s : 1: match.arithmetic_simplify 24.27% : 0.000807s : 3: match.getattr_setattr_resolve 69.63% : 0.002316s : 50: match.inline 1.64% : 0.000054s : 4: match.partial_eliminate 0.28% : 0.000009s : 1: match.switch_simplify 3.50% : 0.000116s : 35: match.tuple_list_get_item_eliminator ------[predicate.] 0.001676 11078 1.45% : 0.000024s : 178: predicate.accumulaten_eliminater 0.25% : 0.000004s : 13: predicate.ad_related_special_op_eliminate 1.36% : 0.000023s : 178: predicate.addn_check_dump 1.48% : 0.000025s : 178: predicate.addn_zero_filter 2.33% : 0.000039s : 179: predicate.arithmetic_simplify 1.46% : 0.000024s : 179: predicate.cast_eliminate 0.13% : 0.000002s : 13: predicate.check_bprop_eliminate 1.36% : 0.000023s : 178: predicate.compare_switch_simplify 1.44% : 0.000024s : 178: predicate.depend_value_elim 1.44% : 0.000024s : 179: predicate.dict_get_item_const_eliminator 1.53% : 0.000026s : 179: predicate.dict_get_item_eliminator 1.45% : 0.000024s : 179: predicate.dict_set_item_eliminator 0.18% : 0.000003s : 13: predicate.dumpgradient_eliminate 0.07% : 0.000001s : 13: predicate.elim_not_effective 0.14% : 0.000002s : 13: predicate.elim_shapecalc_of_broadcastargs 0.28% : 0.000005s : 36: predicate.eliminate_switch_conditional_partial_ 0.28% : 0.000005s : 36: predicate.eliminate_switch_layer_partial_ 0.29% : 0.000005s : 36: predicate.eliminate_switch_partial_ 1.38% : 0.000023s : 179: predicate.environ_add_const_eliminate 1.39% : 0.000023s : 179: predicate.environ_get_add_eliminate 1.39% : 0.000023s : 179: predicate.environ_get_depend_swap 1.41% : 0.000024s : 179: predicate.environ_get_eliminate 1.39% : 0.000023s : 179: predicate.environ_get_set_eliminate 0.06% : 0.000001s : 13: predicate.fold_const_symbol 0.58% : 0.000010s : 62: predicate.get_grad_eliminate 0.42% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000001s : 13: predicate.graph_param_transform 5.17% : 0.000087s : 290: predicate.inline 3.10% : 0.000052s : 303: predicate.inline_without_move 0.27% : 0.000004s : 62: predicate.j_node_and_user_rematch 0.74% : 0.000012s : 65: predicate.less_batch_normalization 1.81% : 0.000030s : 214: predicate.list_to_tuple_eliminator_ 1.93% : 0.000032s : 227: predicate.load_eliminater 0.33% : 0.000006s : 13: predicate.loop_unroll_after_grad 3.17% : 0.000053s : 362: predicate.loop_unroll_before_grad 1.61% : 0.000027s : 192: predicate.make_slice_get_slice_eliminator 1.40% : 0.000023s : 178: predicate.merge_addn 1.48% : 0.000025s : 179: predicate.minmaximum_grad 0.36% : 0.000006s : 13: predicate.mutable_eliminate 0.15% : 0.000002s : 13: predicate.opt_reshape 3.33% : 0.000056s : 267: predicate.partial_eliminate 1.43% : 0.000024s : 178: predicate.print_const_string_wrapper 1.87% : 0.000031s : 179: predicate.reduce_eliminate 1.75% : 0.000029s : 214: predicate.redundant_stop_gradient_eliminater 0.30% : 0.000005s : 62: predicate.remove_not_recompute_node 2.76% : 0.000046s : 485: predicate.replace_applicator 1.39% : 0.000023s : 303: predicate.replace_old_param 0.08% : 0.000001s : 13: predicate.reset_defer_inline 1.51% : 0.000025s : 179: predicate.reshape_eliminate 1.41% : 0.000024s : 178: predicate.row_tensor_add_zeros_like 0.16% : 0.000003s : 13: predicate.row_tensor_eliminate 1.44% : 0.000024s : 178: predicate.same_eliminate 0.34% : 0.000006s : 62: predicate.set_cell_output_no_recompute 0.25% : 0.000004s : 26: predicate.special_op_eliminate 0.64% : 0.000011s : 62: predicate.specialize_transform 1.68% : 0.000028s : 178: predicate.split_environ_get_set_with_tuple_value 1.39% : 0.000023s : 178: predicate.stack_unstack_eliminate 0.15% : 0.000002s : 13: predicate.switch_call_monad_eliminater 3.35% : 0.000056s : 264: predicate.switch_defer_inline 2.46% : 0.000041s : 264: predicate.switch_layer_defer_inline 5.86% : 0.000098s : 641: predicate.switch_simplify 1.45% : 0.000024s : 179: predicate.tile_eliminate 1.49% : 0.000025s : 179: predicate.transpose_eliminate 1.88% : 0.000031s : 179: predicate.tuple_list_convert_item_index_to_positive 1.74% : 0.000029s : 179: predicate.tuple_list_get_item_depend_reorder 3.21% : 0.000054s : 240: predicate.tuple_list_get_item_eliminator 1.80% : 0.000030s : 179: predicate.tuple_list_set_item_eliminator 1.75% : 0.000029s : 214: predicate.tuple_to_list_eliminator_ 1.80% : 0.000030s : 227: predicate.updatestate_pure_node_eliminater 2.75% : 0.000046s : 289: predicate.updatestate_useless_node_eliminater 1.82% : 0.000030s : 178: predicate.value_based_eliminate 0.11% : 0.000002s : 13: predicate.virtual_view_grad_eliminate 0.15% : 0.000002s : 13: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.013547 130 44.02% : 0.005964s : 62: func_graph_cloner_run.FuncGraphClonerGraph 4.48% : 0.000607s : 8: func_graph_cloner_run.FuncGraphClonerNode 51.49% : 0.006976s : 60: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.322239 90 0.01% : 0.000129s : 1: add_recomputation 0.01% : 0.000203s : 1: auto_monad 0.00% : 0.000035s : 1: auto_monad_reorder 0.02% : 0.000554s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.00% : 0.000052s : 1: cse_after_recomputation 0.00% : 0.000013s : 1: environ_conv 0.00% : 0.000062s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 39.94% : 0.927428s : 1: jit_opt_a 0.01% : 0.000313s : 1: jit_opt_after_cconv 0.01% : 0.000117s : 1: jit_opt_b 0.02% : 0.000528s : 1: loop_unroll 0.03% : 0.000809s : 1: mutable_eliminate 9.87% : 0.229303s : 39: opt.transform.jit_opt_a 0.01% : 0.000148s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000083s : 4: opt.transform.jit_opt_b 0.00% : 0.000027s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.00% : 0.000057s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000999s : 2: opt.transform.opt_resolve 0.02% : 0.000349s : 1: opt.transform.partial_eliminate 0.00% : 0.000096s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000546s : 1: opt_after_jit_grad 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000071s : 1: py_interpret_to_execute 0.00% : 0.000029s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000095s : 1: remove_dup_value 14.56% : 0.338124s : 2: renormalize.infer 0.48% : 0.011045s : 2: renormalize.specialize 0.01% : 0.000219s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000082s : 1: rewriter_after_opt_a 0.01% : 0.000225s : 1: rewriter_before_opt_a 0.01% : 0.000150s : 1: symbol_engine_optimizer 34.89% : 0.810207s : 1: type_inference . [hook] pytest_runtest_teardown:test_basic_stream_block_annotation_2 tests/st/compiler/stream_event/test_with_stream.py::test_basic_stream_block_annotation_2,max_mem:12.0M =============================== 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 92.78s (0:01:32) ===================