==================================================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_005/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(160037:281473276727088,MainProcess):2026-01-29-17:37:55.672.647 [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(160037:281473276727088,MainProcess):2026-01-29-17:37:55.673.330 [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 = 0.56605, [21] [bootstrap]: 0.00057198 [type_inference]: 0.412826 [event_method]: 5.008e-05 [auto_monad]: 0.00013624 [graph_reusing]: 7.83999e-06 [inline]: 2.37999e-06 [add_attr]: 0.056338, [1] [add_attr_with_inline]: 0.0563249, [1] [Cycle 1]: 0.00010259, [2] [tag_attr]: 3.22e-05 [meta_addattr_fg_expand]: 7.22997e-06 [parallel-infer-symbol]: 3.79002e-06 [pre_auto_parallel]: 4.882e-05 [insert-virtual-dataset]: 2.40002e-06 [parallel-infer-symbol-second]: 7.00005e-07 [dataset_repeat_opt]: 1.89999e-06 [pipeline_split]: 1.89999e-06 [optimize]: 0.0942254, [53] [py_interpret_to_execute]: 3.661e-05 [rewriter_before_opt_a]: 0.00012124 [opt_a]: 0.00704027, [3] [Cycle 1]: 0.00409498, [45] [expand_dump_flag]: 2.19999e-06 [switch_simplify]: 4.653e-05 [loop_unroll]: 3.853e-05 [a_1]: 0.00105039 [with_stream_mark]: 9.549e-05 [recompute_prepare]: 2.808e-05 [updatestate_depend_eliminate]: 1.046e-05 [updatestate_assign_eliminate]: 8.45999e-06 [updatestate_loads_eliminate]: 8.18999e-06 [parameter_eliminate]: 4.90999e-06 [a_2]: 0.00055587 [accelerated_algorithm]: 3.823e-05 [shard]: 1.77999e-06 [meta_shard_fg_expand]: 4.02998e-06 [shard_inline]: 1.443e-05 [merge_send_recv]: 1.283e-05 [auto_parallel]: 1.258e-05 [parallel]: 4.876e-05 [flash_sp]: 1.988e-05 [merge_comm]: 1.026e-05 [allreduce_fusion]: 8.22e-06 [matmul_add_comm_reduction]: 1.562e-05 [allreduce_slice_to_reducescatter]: 5.40022e-07 [virtual_shard_identity]: 1.726e-05 [virtual_dataset]: 1.305e-05 [get_grad_eliminate_]: 1.2e-05 [virtual_output]: 1.248e-05 [merge_forward]: 7.85998e-06 [cell_reuse_recompute_pass]: 1.32999e-06 [offload_activation]: 1.53e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.83e-05 [merge_recompute_call_nodes]: 9.60019e-07 [before_grad]: 2.377e-05 [set_forward_comm_id_for_comm_node_pass]: 8.75001e-06 [meta_fg_expand]: 5.77999e-06 [flash_sp_send_recv_attached]: 4.95001e-06 [receive_attached]: 1.89999e-06 [after_resolve]: 1.668e-05 [a_after_grad]: 1.947e-05 [renormalize]: 0.00115883 [add_forward_monad_depend]: 7.58001e-06 [auto_monad_grad]: 2.49999e-06 [auto_monad_eliminator]: 2.594e-05 [cse]: 0.00012273 [a_3]: 9.612e-05 [Cycle 2]: 0.00197313, [45] [expand_dump_flag]: 2.32999e-06 [switch_simplify]: 1.284e-05 [loop_unroll]: 1.011e-05 [a_1]: 0.00025921 [with_stream_mark]: 1.873e-05 [recompute_prepare]: 1.134e-05 [updatestate_depend_eliminate]: 7.25e-06 [updatestate_assign_eliminate]: 6.72002e-06 [updatestate_loads_eliminate]: 5.47999e-06 [parameter_eliminate]: 1.87999e-06 [a_2]: 0.00033508 [accelerated_algorithm]: 4.28e-05 [shard]: 2.22001e-06 [meta_shard_fg_expand]: 2.83e-06 [shard_inline]: 8.38999e-06 [merge_send_recv]: 1.066e-05 [auto_parallel]: 1.086e-05 [parallel]: 8.82e-06 [flash_sp]: 4.15999e-06 [merge_comm]: 4.97999e-06 [allreduce_fusion]: 4.53001e-06 [matmul_add_comm_reduction]: 1.224e-05 [allreduce_slice_to_reducescatter]: 4.59986e-07 [virtual_shard_identity]: 9.49999e-06 [virtual_dataset]: 7.55e-06 [get_grad_eliminate_]: 7.41999e-06 [virtual_output]: 7.21999e-06 [merge_forward]: 4.85001e-06 [cell_reuse_recompute_pass]: 2.87002e-06 [offload_activation]: 1.158e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.765e-05 [merge_recompute_call_nodes]: 1.43002e-06 [before_grad]: 1.352e-05 [set_forward_comm_id_for_comm_node_pass]: 4.68999e-06 [meta_fg_expand]: 3.64002e-06 [flash_sp_send_recv_attached]: 1.60001e-06 [receive_attached]: 1.99e-06 [after_resolve]: 1.286e-05 [a_after_grad]: 1.077e-05 [renormalize]: 0.00056839 [add_forward_monad_depend]: 5.56e-06 [auto_monad_grad]: 2.21e-06 [auto_monad_eliminator]: 1.596e-05 [cse]: 3.246e-05 [a_3]: 6.907e-05 [Cycle 3]: 0.00095075, [45] [expand_dump_flag]: 1.32999e-06 [switch_simplify]: 9.17999e-06 [loop_unroll]: 7.58001e-06 [a_1]: 0.00017989 [with_stream_mark]: 1.144e-05 [recompute_prepare]: 7.97998e-06 [updatestate_depend_eliminate]: 4.47e-06 [updatestate_assign_eliminate]: 3.55e-06 [updatestate_loads_eliminate]: 3.48999e-06 [parameter_eliminate]: 1.30999e-06 [a_2]: 0.00013127 [accelerated_algorithm]: 1.055e-05 [shard]: 1.14998e-06 [meta_shard_fg_expand]: 2.06e-06 [shard_inline]: 7.66999e-06 [merge_send_recv]: 6.49999e-06 [auto_parallel]: 7.32002e-06 [parallel]: 5.61998e-06 [flash_sp]: 9.39996e-07 [merge_comm]: 4.67e-06 [allreduce_fusion]: 6.88998e-06 [matmul_add_comm_reduction]: 8.32e-06 [allreduce_slice_to_reducescatter]: 2.19996e-07 [virtual_shard_identity]: 8.45999e-06 [virtual_dataset]: 7.03e-06 [get_grad_eliminate_]: 7.10002e-06 [virtual_output]: 7.11001e-06 [merge_forward]: 4.79e-06 [cell_reuse_recompute_pass]: 1.34e-06 [offload_activation]: 8.62e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.709e-05 [merge_recompute_call_nodes]: 9.50007e-07 [before_grad]: 1.276e-05 [set_forward_comm_id_for_comm_node_pass]: 4.68001e-06 [meta_fg_expand]: 2.91e-06 [flash_sp_send_recv_attached]: 1.14e-06 [receive_attached]: 1.41002e-06 [after_resolve]: 1.026e-05 [a_after_grad]: 1.177e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.82001e-06 [auto_monad_grad]: 1.49e-06 [auto_monad_eliminator]: 9.64e-06 [cse]: 2.246e-05 [a_3]: 5.989e-05 [py_interpret_to_execute_after_opt_a]: 1.789e-05 [slice_cell_reuse_recomputed_activation]: 5.18002e-06 [rewriter_after_opt_a]: 8.706e-05 [convert_after_rewriter]: 1.326e-05 [order_py_execute_after_rewriter]: 9.08002e-06 [mutable_eliminate]: 0.00069446 [opt_b]: 0.00032031, [1] [Cycle 1]: 0.00030953, [7] [b_1]: 0.00019929 [b_2]: 9.46e-06 [updatestate_depend_eliminate]: 8.22998e-06 [updatestate_assign_eliminate]: 4.02e-06 [updatestate_loads_eliminate]: 3.63e-06 [renormalize]: 5.40022e-07 [cse]: 2.898e-05 [optimize_parallel_all_gather_comm]: 2.387e-05 [overlap_param_gather]: 8.07003e-06 [cconv]: 3.429e-05 [loop_unroll]: 0.00046802 [opt_after_cconv]: 0.0843811, [1] [Cycle 1]: 0.084364, [7] [c_1]: 3.577e-05 [parameter_eliminate]: 3.66999e-06 [updatestate_depend_eliminate]: 6.76e-06 [updatestate_assign_eliminate]: 3.9e-06 [updatestate_loads_eliminate]: 3.40998e-06 [cse]: 7.96e-05 [renormalize]: 9.30013e-07 [remove_dup_value]: 3.1e-05 [tuple_transform]: 0.00014738, [1] [Cycle 1]: 0.00013484, [4] [d_1]: 8.626e-05 [none_parameter_eliminate]: 5.84e-06 [renormalize]: 2.3999e-07 [switch_simplify]: 1.028e-05 [partial_unused_args_eliminate]: 5.61003e-06 [add_recomputation]: 8.651e-05 [cse_after_recomputation]: 3.83e-05, [1] [Cycle 1]: 3.033e-05, [1] [cse]: 2.047e-05 [environ_conv]: 2.501e-05 [swap_dp_allreduce_reducescatter]: 1.048e-05 [bias_add_comm_swap]: 7e-06 [label_micro_interleaved_index]: 1.126e-05 [label_fine_grained_interleaved_index]: 5.30001e-06 [merge_cast_opt]: 3.93999e-06 [slice_recompute_activation]: 4.67998e-06 [micro_interleaved_order_control]: 5.74999e-06 [assign_add_opt]: 4.80999e-06 [ForceFp32Comm]: 4e-06 [remove_cast_before_assign_add]: 3.80998e-06 [full_micro_interleaved_order_control]: 5.63002e-06 [reorder_send_recv_between_fp_bp]: 5.53002e-06 [comm_op_add_attrs]: 4.60999e-06 [add_comm_op_reuse_tag]: 3.73001e-06 [interleave_split_concat_branches]: 4.02002e-06 [interleave_parallel_branches]: 3.74002e-06 [overlap_opt_shard_in_pipeline]: 2.77e-05 [overlap_opt_shard_grad_in_pipeline]: 4.90001e-06 [control_data_broadcast_order]: 2.828e-05 [grouped_pairwise_exchange_alltoall]: 4.18001e-06 [offloading_packed_experts]: 8.42e-06 [overlap_recompute_and_grad_model_parallel]: 8.89e-06 [overlap_grad_matmul_and_grad_allreduce]: 3.69002e-06 [overlap_recompute_allgather_and_fa_grad]: 3.83999e-06 [overlap_recompute_comm]: 4.90001e-06 [overlap_grad_ring_attention]: 9.61998e-06 [overlap_grad_flash_sp]: 4.95e-05 [begin_end_overlap_inline]: 3.09999e-06 [split_matmul_comm_elemetwise]: 4.94e-06 [split_layernorm_comm]: 4.50999e-06 [handle_group_info]: 4.3e-06 [symbol_engine_optimizer]: 0.00013305, [1] [Cycle 1]: 0.00012395, [6] [build]: 5.31002e-06 [elim_shapecalc]: 1.76e-05 [elim_not_effective]: 2.006e-05 [opt_reshape]: 1.039e-05 [fold_const_symbol]: 1.506e-05 [renormalize]: 2.50002e-07 [detach_backward]: 6.53998e-06 [pipeline_parallel_scheduler]: 2.01998e-06 [auto_monad_reorder]: 3.915e-05 [get_jit_bprop_graph]: 2.01e-06 [rewriter_after_jit_bprop_graph]: 6.56e-06 [opt_after_jit_grad]: 0.00087597 [validate]: 7.39e-05 Sums bootstrap : 0.000572s : 0.14% type_inference : 0.412826s : 97.58% event_method : 0.000050s : 0.01% auto_monad : 0.000136s : 0.03% graph_reusing : 0.000008s : 0.00% inline : 0.000002s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000032s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000007s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000049s : 0.01% insert-virtual-dataset : 0.000002s : 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 : 0.000037s : 0.01% optimize.rewriter_before_opt_a : 0.000121s : 0.03% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000069s : 0.02% optimize.opt_a.loop_unroll : 0.000056s : 0.01% optimize.opt_a.a_1 : 0.001489s : 0.35% optimize.opt_a.with_stream_mark : 0.000126s : 0.03% optimize.opt_a.recompute_prepare : 0.000047s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000022s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000019s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000017s : 0.00% optimize.opt_a.parameter_eliminate : 0.000008s : 0.00% optimize.opt_a.a_2 : 0.001022s : 0.24% optimize.opt_a.accelerated_algorithm : 0.000092s : 0.02% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000009s : 0.00% optimize.opt_a.shard_inline : 0.000030s : 0.01% optimize.opt_a.merge_send_recv : 0.000030s : 0.01% optimize.opt_a.auto_parallel : 0.000031s : 0.01% optimize.opt_a.parallel : 0.000063s : 0.01% optimize.opt_a.flash_sp : 0.000025s : 0.01% optimize.opt_a.merge_comm : 0.000020s : 0.00% optimize.opt_a.allreduce_fusion : 0.000020s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000036s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000035s : 0.01% optimize.opt_a.virtual_dataset : 0.000028s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000027s : 0.01% optimize.opt_a.virtual_output : 0.000027s : 0.01% optimize.opt_a.merge_forward : 0.000017s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000036s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000073s : 0.02% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000050s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000018s : 0.00% optimize.opt_a.meta_fg_expand : 0.000012s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000040s : 0.01% optimize.opt_a.a_after_grad : 0.000042s : 0.01% optimize.opt_a.renormalize : 0.001727s : 0.41% optimize.opt_a.add_forward_monad_depend : 0.000015s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000052s : 0.01% optimize.opt_a.cse : 0.000178s : 0.04% optimize.opt_a.a_3 : 0.000225s : 0.05% optimize.py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000005s : 0.00% optimize.rewriter_after_opt_a : 0.000087s : 0.02% optimize.convert_after_rewriter : 0.000013s : 0.00% optimize.order_py_execute_after_rewriter : 0.000009s : 0.00% optimize.mutable_eliminate : 0.000694s : 0.16% optimize.opt_b.b_1 : 0.000199s : 0.05% optimize.opt_b.b_2 : 0.000009s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000008s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000004s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000004s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000029s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000024s : 0.01% optimize.overlap_param_gather : 0.000008s : 0.00% optimize.cconv : 0.000034s : 0.01% optimize.loop_unroll : 0.000468s : 0.11% optimize.opt_after_cconv.c_1 : 0.000036s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% optimize.opt_after_cconv.cse : 0.000080s : 0.02% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000031s : 0.01% optimize.tuple_transform.d_1 : 0.000086s : 0.02% optimize.tuple_transform.none_parameter_eliminate : 0.000006s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000010s : 0.00% optimize.partial_unused_args_eliminate : 0.000006s : 0.00% optimize.add_recomputation : 0.000087s : 0.02% optimize.cse_after_recomputation.cse : 0.000020s : 0.00% optimize.environ_conv : 0.000025s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000010s : 0.00% optimize.bias_add_comm_swap : 0.000007s : 0.00% optimize.label_micro_interleaved_index : 0.000011s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000005s : 0.00% optimize.merge_cast_opt : 0.000004s : 0.00% optimize.slice_recompute_activation : 0.000005s : 0.00% optimize.micro_interleaved_order_control : 0.000006s : 0.00% optimize.assign_add_opt : 0.000005s : 0.00% optimize.ForceFp32Comm : 0.000004s : 0.00% optimize.remove_cast_before_assign_add : 0.000004s : 0.00% optimize.full_micro_interleaved_order_control : 0.000006s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000006s : 0.00% optimize.comm_op_add_attrs : 0.000005s : 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 : 0.000028s : 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 : 0.000008s : 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 : 0.000005s : 0.00% optimize.overlap_grad_ring_attention : 0.000010s : 0.00% optimize.overlap_grad_flash_sp : 0.000049s : 0.01% optimize.begin_end_overlap_inline : 0.000003s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000005s : 0.00% optimize.split_layernorm_comm : 0.000005s : 0.00% optimize.handle_group_info : 0.000004s : 0.00% optimize.symbol_engine_optimizer.build : 0.000005s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000018s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000020s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000007s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000039s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000876s : 0.21% validate : 0.000074s : 0.02% Time group info: ------[substitution.] 0.000536 95 24.90% : 0.000134s : 16: substitution.arithmetic_simplify 2.40% : 0.000013s : 6: substitution.depend_value_elim 0.61% : 0.000003s : 4: substitution.elim_not_effective 0.38% : 0.000002s : 4: substitution.fold_const_symbol 1.55% : 0.000008s : 5: substitution.graph_param_transform 54.78% : 0.000294s : 12: substitution.inline 1.97% : 0.000011s : 16: substitution.j_node_and_user_rematch 4.61% : 0.000025s : 3: substitution.less_batch_normalization 0.54% : 0.000003s : 4: substitution.redundant_stop_gradient_eliminater 4.05% : 0.000022s : 16: substitution.remove_not_recompute_node 0.46% : 0.000002s : 2: substitution.replace_applicator 1.16% : 0.000006s : 3: substitution.replace_old_param 0.94% : 0.000005s : 2: substitution.set_cell_output_no_recompute 1.66% : 0.000009s : 2: substitution.specialize_transform ------[type_inference.] 0.412755 2 99.71% : 0.411555s : 1: type_inference.infer 0.29% : 0.001200s : 1: type_inference.specialize ------[replace.] 0.000105 10 32.37% : 0.000034s : 2: replace.depend_value_elim 67.63% : 0.000071s : 8: replace.inline ------[match.] 0.000288 10 1.16% : 0.000003s : 2: match.depend_value_elim 98.84% : 0.000284s : 8: match.inline ------[predicate.] 0.000466 3006 1.01% : 0.000005s : 34: predicate.accumulaten_eliminater 0.70% : 0.000003s : 5: predicate.ad_related_special_op_eliminate 1.21% : 0.000006s : 41: predicate.addn_check_dump 1.02% : 0.000005s : 34: predicate.addn_zero_filter 0.94% : 0.000004s : 34: predicate.adjust_all_reduce_mul_add 3.13% : 0.000015s : 69: predicate.arithmetic_simplify 1.14% : 0.000005s : 34: predicate.cast_eliminate 0.62% : 0.000003s : 17: predicate.check_bprop_eliminate 1.24% : 0.000006s : 41: predicate.compare_switch_simplify 0.09% : 0.000000s : 5: predicate.const_output_eliminate 1.22% : 0.000006s : 36: predicate.depend_value_elim 1.07% : 0.000005s : 34: predicate.dict_get_item_const_eliminator 1.12% : 0.000005s : 34: predicate.dict_get_item_eliminator 1.04% : 0.000005s : 34: predicate.dict_set_item_eliminator 0.71% : 0.000003s : 10: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 5: predicate.elim_not_effective 0.26% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.16% : 0.000005s : 39: predicate.environ_add_const_eliminate 1.08% : 0.000005s : 39: predicate.environ_get_add_eliminate 1.11% : 0.000005s : 39: predicate.environ_get_depend_swap 2.27% : 0.000011s : 74: predicate.environ_get_eliminate 1.09% : 0.000005s : 39: predicate.environ_get_set_eliminate 1.20% : 0.000006s : 40: predicate.exchange_switch_depend_value 1.91% : 0.000009s : 40: predicate.float_depend_g_call 1.26% : 0.000006s : 41: predicate.float_environ_get_switch 1.35% : 0.000006s : 46: predicate.float_tuple_getitem_switch 0.10% : 0.000000s : 5: predicate.fold_const_symbol 0.67% : 0.000003s : 19: predicate.get_grad_eliminate 0.21% : 0.000001s : 5: predicate.graph_param_transform 1.08% : 0.000005s : 35: predicate.incorporate_call 0.98% : 0.000005s : 35: predicate.incorporate_call_switch 5.86% : 0.000027s : 142: predicate.inline 0.83% : 0.000004s : 19: predicate.inline_without_move 0.35% : 0.000002s : 19: predicate.j_node_and_user_rematch 0.97% : 0.000005s : 19: predicate.less_batch_normalization 1.47% : 0.000007s : 44: predicate.list_to_tuple_eliminator_ 2.26% : 0.000011s : 78: predicate.load_eliminater 0.49% : 0.000002s : 5: predicate.loop_unroll_after_grad 1.66% : 0.000008s : 54: predicate.loop_unroll_before_grad 1.49% : 0.000007s : 44: predicate.make_slice_get_slice_eliminator 1.34% : 0.000006s : 41: predicate.merge_addn 0.54% : 0.000003s : 17: predicate.micro_step_allgather_replace 0.56% : 0.000003s : 17: predicate.mini_step_allgather_replace 0.92% : 0.000004s : 34: predicate.minmaximum_grad 0.48% : 0.000002s : 5: predicate.mutable_eliminate 0.22% : 0.000001s : 5: predicate.opt_reshape 0.19% : 0.000001s : 5: predicate.parallel_virtual_node 1.37% : 0.000006s : 40: predicate.partial_defer_inline 1.27% : 0.000006s : 39: predicate.partial_eliminate 1.01% : 0.000005s : 34: predicate.print_const_string_wrapper 1.06% : 0.000005s : 33: predicate.reduce_all_const_elim 1.31% : 0.000006s : 34: predicate.reduce_eliminate 2.28% : 0.000011s : 78: predicate.redundant_stop_gradient_eliminater 0.45% : 0.000002s : 19: predicate.remove_not_recompute_node 1.15% : 0.000005s : 51: predicate.replace_applicator 0.49% : 0.000002s : 19: predicate.replace_old_param 0.12% : 0.000001s : 5: predicate.reset_defer_inline 1.02% : 0.000005s : 34: predicate.reshape_eliminate 0.73% : 0.000003s : 17: predicate.row_tensor_add_zeros_like 0.21% : 0.000001s : 5: predicate.row_tensor_eliminate 0.77% : 0.000004s : 17: predicate.same_eliminate 0.52% : 0.000002s : 27: predicate.set_cell_output_no_recompute 0.95% : 0.000004s : 19: predicate.shard_identity_eliminate 0.43% : 0.000002s : 10: predicate.special_op_eliminate 1.57% : 0.000007s : 41: predicate.specialize_transform 0.75% : 0.000004s : 17: predicate.split_environ_get_set_with_tuple_value 0.85% : 0.000004s : 19: predicate.stack_unstack_eliminate 0.18% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.28% : 0.000006s : 40: predicate.switch_defer_inline 1.82% : 0.000008s : 57: predicate.switch_layer_defer_inline 4.65% : 0.000022s : 140: predicate.switch_simplify 1.03% : 0.000005s : 34: predicate.tile_eliminate 1.01% : 0.000005s : 34: predicate.transpose_eliminate 1.45% : 0.000007s : 44: predicate.tuple_list_convert_item_index_to_positive 1.38% : 0.000006s : 44: predicate.tuple_list_get_item_const_eliminator 1.33% : 0.000006s : 44: predicate.tuple_list_get_item_depend_reorder 2.99% : 0.000014s : 79: predicate.tuple_list_get_item_eliminator 1.43% : 0.000007s : 44: predicate.tuple_list_get_set_item_eliminator 2.56% : 0.000012s : 79: predicate.tuple_list_set_item_eliminator 1.48% : 0.000007s : 44: predicate.tuple_to_list_eliminator_ 2.15% : 0.000010s : 78: predicate.updatestate_pure_node_eliminater 3.28% : 0.000015s : 113: predicate.updatestate_useless_node_eliminater 0.19% : 0.000001s : 5: predicate.value_based_eliminate 0.67% : 0.000003s : 19: predicate.virtual_dataset_eliminate 0.68% : 0.000003s : 19: predicate.virtual_output_eliminate 0.17% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.21% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000956 16 42.49% : 0.000406s : 5: func_graph_cloner_run.FuncGraphClonerGraph 57.51% : 0.000550s : 11: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.721529 267 0.00% : 0.000007s : 1: ForceFp32Comm 7.81% : 0.056350s : 1: add_attr 7.81% : 0.056329s : 1: add_attr_with_inline 0.00% : 0.000006s : 1: add_comm_op_reuse_tag 0.01% : 0.000090s : 1: add_recomputation 0.00% : 0.000007s : 1: assign_add_opt 0.02% : 0.000147s : 1: auto_monad 0.01% : 0.000050s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: begin_end_overlap_inline 0.00% : 0.000010s : 1: bias_add_comm_swap 0.09% : 0.000644s : 1: bootstrap 0.01% : 0.000037s : 1: cconv 0.00% : 0.000008s : 1: comm_op_add_attrs 0.00% : 0.000032s : 1: control_data_broadcast_order 0.00% : 0.000017s : 1: convert_after_rewriter 0.01% : 0.000042s : 1: cse_after_recomputation 0.00% : 0.000007s : 1: dataset_repeat_opt 0.00% : 0.000035s : 1: detach_backward 0.00% : 0.000029s : 1: environ_conv 0.01% : 0.000063s : 1: event_method 0.00% : 0.000009s : 1: full_micro_interleaved_order_control 0.00% : 0.000009s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 0.00% : 0.000007s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000007s : 1: handle_group_info 0.00% : 0.000008s : 1: inline 0.00% : 0.000009s : 1: insert-virtual-dataset 0.00% : 0.000006s : 1: interleave_parallel_branches 0.00% : 0.000007s : 1: interleave_split_concat_branches 0.00% : 0.000008s : 1: label_fine_grained_interleaved_index 0.00% : 0.000014s : 1: label_micro_interleaved_index 0.07% : 0.000473s : 1: loop_unroll 0.00% : 0.000007s : 1: merge_cast_opt 0.00% : 0.000008s : 1: micro_interleaved_order_control 0.10% : 0.000701s : 1: mutable_eliminate 0.00% : 0.000012s : 1: offloading_packed_experts 0.00% : 0.000017s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.41% : 0.002992s : 151: opt.transform.opt_a 0.00% : 0.000034s : 1: opt.transform.opt_after_cconv 0.01% : 0.000041s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000138s : 28: opt.transform.opt_b 0.01% : 0.000091s : 2: opt.transform.opt_trans_graph 0.01% : 0.000059s : 4: opt.transform.symbol_engine_opt 0.98% : 0.007044s : 1: opt_a 11.70% : 0.084387s : 1: opt_after_cconv 0.12% : 0.000893s : 1: opt_after_jit_grad 0.04% : 0.000324s : 1: opt_b 13.13% : 0.094726s : 1: optimize 0.00% : 0.000027s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.01% : 0.000054s : 1: overlap_grad_flash_sp 0.00% : 0.000006s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 1: overlap_grad_ring_attention 0.00% : 0.000008s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000032s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000011s : 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% : 0.000008s : 1: overlap_recompute_comm 0.00% : 0.000011s : 1: parallel-infer-symbol 0.00% : 0.000006s : 1: parallel-infer-symbol-second 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000013s : 1: pipeline_parallel_scheduler 0.00% : 0.000007s : 1: pipeline_split 0.01% : 0.000057s : 1: pre_auto_parallel 0.01% : 0.000040s : 1: py_interpret_to_execute 0.00% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000006s : 1: remove_cast_before_assign_add 0.00% : 0.000035s : 1: remove_dup_value 0.13% : 0.000956s : 2: renormalize.infer 0.10% : 0.000754s : 2: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000015s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000091s : 1: rewriter_after_opt_a 0.02% : 0.000126s : 1: rewriter_before_opt_a 0.00% : 0.000008s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000007s : 1: slice_recompute_activation 0.00% : 0.000008s : 1: split_layernorm_comm 0.00% : 0.000008s : 1: split_matmul_comm_elemetwise 0.00% : 0.000013s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000136s : 1: symbol_engine_optimizer 0.02% : 0.000150s : 1: tuple_transform 57.22% : 0.412871s : 1: type_inference [WARNING] ME(160037:281473276727088,MainProcess):2026-01-29-17:38:09.559.007 [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 = 0.821694, [30] [bootstrap]: 0.00047909 [type_inference]: 0.22098 [event_method]: 4.15e-05 [auto_monad]: 0.00016986 [graph_reusing]: 1.133e-05 [pre_auto_parallel]: 4.50001e-06 [py_interpret_to_execute]: 5.811e-05 [rewriter_before_opt_a]: 0.00017334 [expand_dump_flag]: 4.50001e-06 [jit_opt_a]: 0.595855, [3] [Cycle 1]: 0.346878, [27] [switch_simplify]: 0.0001307 [loop_unroll]: 6.905e-05 [a_1]: 0.00174841 [with_stream_mark]: 0.00012156 [recompute_prepare]: 4.516e-05 [updatestate_depend_eliminate]: 1.427e-05 [updatestate_assign_eliminate]: 1.267e-05 [updatestate_loads_eliminate]: 1.207e-05 [parameter_eliminate]: 5.01002e-06 [specialize_transform]: 4.097e-05 [updatestate_useless_node_eliminater]: 2.438e-05 [accelerated_algorithm]: 6.813e-05 [meta_shard_fg_expand]: 6.83e-06 [get_grad_eliminate_]: 2.893e-05 [merge_forward]: 1.53e-05 [cell_reuse_recompute_pass]: 1.45001e-06 [cell_reuse_handle_not_recompute_node_pass]: 5.036e-05 [j_node_and_user_rematch]: 4.656e-05 [meta_fg_expand]: 0.191221, [1] [partial_eliminate_before_grad]: 0.00020423, [1] [Cycle 1]: 0.00019272, [1] [partial_eliminate_]: 0.00016813 [replace_old_param]: 0.00026926 [inline_without_move]: 0.00028929 [renormalize]: 0.151216 [add_forward_monad_depend]: 5.302e-05 [auto_monad_grad]: 2.828e-05 [auto_monad_eliminator]: 0.00019715 [cse]: 0.00047192 [replace_applicator]: 0.00033264 [Cycle 2]: 0.0796233, [27] [switch_simplify]: 0.00013983 [loop_unroll]: 0.00013155 [a_1]: 0.0749664 [with_stream_mark]: 3.577e-05 [recompute_prepare]: 1.826e-05 [updatestate_depend_eliminate]: 7.35e-06 [updatestate_assign_eliminate]: 5.47999e-06 [updatestate_loads_eliminate]: 4.89e-06 [parameter_eliminate]: 3.50003e-06 [specialize_transform]: 9.34998e-06 [updatestate_useless_node_eliminater]: 8.69e-06 [accelerated_algorithm]: 2.788e-05 [meta_shard_fg_expand]: 6.98998e-06 [get_grad_eliminate_]: 8.90999e-06 [merge_forward]: 5.82001e-06 [cell_reuse_recompute_pass]: 1.55001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.216e-05 [j_node_and_user_rematch]: 1.608e-05 [meta_fg_expand]: 0.00010731 [replace_old_param]: 1.101e-05 [inline_without_move]: 9.05999e-06 [renormalize]: 0.00368855 [add_forward_monad_depend]: 1.441e-05 [auto_monad_grad]: 3.14999e-06 [auto_monad_eliminator]: 2.711e-05 [cse]: 5.006e-05 [replace_applicator]: 2.784e-05 [Cycle 3]: 0.00049417, [27] [switch_simplify]: 9.04e-06 [loop_unroll]: 7.63999e-06 [a_1]: 0.00018496 [with_stream_mark]: 2.01e-05 [recompute_prepare]: 7.56999e-06 [updatestate_depend_eliminate]: 5.19e-06 [updatestate_assign_eliminate]: 3.39001e-06 [updatestate_loads_eliminate]: 4.1e-06 [parameter_eliminate]: 2.01e-06 [specialize_transform]: 6.34999e-06 [updatestate_useless_node_eliminater]: 6.94999e-06 [accelerated_algorithm]: 7.87998e-06 [meta_shard_fg_expand]: 2.75002e-06 [get_grad_eliminate_]: 6.53003e-06 [merge_forward]: 4.4e-06 [cell_reuse_recompute_pass]: 2.98e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.867e-05 [j_node_and_user_rematch]: 1.151e-05 [meta_fg_expand]: 3.35e-06 [replace_old_param]: 6.02001e-06 [inline_without_move]: 6.05002e-06 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 2.27999e-06 [auto_monad_grad]: 1.25001e-06 [auto_monad_eliminator]: 7.84002e-06 [cse]: 1.657e-05 [replace_applicator]: 6.09999e-06 [py_interpret_to_execute_after_opt_a]: 2.302e-05 [rewriter_after_opt_a]: 5.349e-05 [convert_after_rewriter]: 9.81e-06 [order_py_execute_after_rewriter]: 5.87999e-06 [mutable_eliminate]: 0.00100793 [jit_opt_b]: 6.63e-05, [1] [Cycle 1]: 5.648e-05, [2] [frontend_op_eliminate]: 2.136e-05 [inline_after_opt_a]: 2.079e-05 [cconv]: 3.419e-05 [loop_unroll]: 0.00057139 [jit_opt_after_cconv]: 0.00019942, [1] [Cycle 1]: 0.00019176, [11] [c_1]: 2.591e-05 [parameter_eliminate]: 4.74998e-06 [updatestate_depend_eliminate]: 9.25999e-06 [updatestate_assign_eliminate]: 3.66999e-06 [updatestate_loads_eliminate]: 2.63e-06 [cse]: 4.105e-05 [call_graph_tuple_transform]: 2.624e-05 [tuple_list_get_item_eliminator]: 7.70998e-06 [none_parameter_eliminate]: 1.77999e-06 [renormalize]: 5.79981e-07 [switch_simplify]: 6.76e-06 [remove_dup_value]: 2.246e-05 [partial_unused_args_eliminate]: 2.26e-06 [environ_conv]: 1.144e-05 [add_recomputation]: 6.019e-05 [cse_after_recomputation]: 2.884e-05, [1] [Cycle 1]: 2.214e-05, [1] [cse]: 1.346e-05 [auto_monad_reorder]: 1.763e-05 [get_jit_bprop_graph]: 3.08e-06 [rewriter_after_jit_bprop_graph]: 0.00054393 [opt_after_jit_grad]: 0.00071754 [symbol_engine_optimizer]: 9.492e-05, [1] [Cycle 1]: 8.607e-05, [6] [build]: 6.83e-06 [elim_shapecalc]: 1.126e-05 [elim_not_effective]: 1.887e-05 [opt_reshape]: 6.52001e-06 [fold_const_symbol]: 1.053e-05 [renormalize]: 5.8001e-07 [validate]: 5.607e-05 Sums bootstrap : 0.000479s : 0.10% type_inference : 0.220980s : 47.99% event_method : 0.000041s : 0.01% auto_monad : 0.000170s : 0.04% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000058s : 0.01% rewriter_before_opt_a : 0.000173s : 0.04% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000280s : 0.06% jit_opt_a.loop_unroll : 0.000208s : 0.05% jit_opt_a.a_1 : 0.076900s : 16.70% jit_opt_a.with_stream_mark : 0.000177s : 0.04% jit_opt_a.recompute_prepare : 0.000071s : 0.02% jit_opt_a.updatestate_depend_eliminate : 0.000027s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000022s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000021s : 0.00% jit_opt_a.parameter_eliminate : 0.000011s : 0.00% jit_opt_a.specialize_transform : 0.000057s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000040s : 0.01% jit_opt_a.accelerated_algorithm : 0.000104s : 0.02% jit_opt_a.meta_shard_fg_expand : 0.000017s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000044s : 0.01% jit_opt_a.merge_forward : 0.000026s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000091s : 0.02% jit_opt_a.j_node_and_user_rematch : 0.000074s : 0.02% jit_opt_a.meta_fg_expand : 0.000111s : 0.02% jit_opt_a.meta_fg_expand.partial_eliminate_before_grad.partial_eliminate_ : 0.000168s : 0.04% jit_opt_a.replace_old_param : 0.000286s : 0.06% jit_opt_a.inline_without_move : 0.000304s : 0.07% jit_opt_a.renormalize : 0.154905s : 33.64% jit_opt_a.add_forward_monad_depend : 0.000070s : 0.02% jit_opt_a.auto_monad_grad : 0.000033s : 0.01% jit_opt_a.auto_monad_eliminator : 0.000232s : 0.05% jit_opt_a.cse : 0.000539s : 0.12% jit_opt_a.replace_applicator : 0.000367s : 0.08% py_interpret_to_execute_after_opt_a : 0.000023s : 0.00% rewriter_after_opt_a : 0.000053s : 0.01% convert_after_rewriter : 0.000010s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.001008s : 0.22% jit_opt_b.frontend_op_eliminate : 0.000021s : 0.00% jit_opt_b.inline_after_opt_a : 0.000021s : 0.00% cconv : 0.000034s : 0.01% loop_unroll : 0.000571s : 0.12% jit_opt_after_cconv.c_1 : 0.000026s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000041s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 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 : 0.000007s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000011s : 0.00% add_recomputation : 0.000060s : 0.01% cse_after_recomputation.cse : 0.000013s : 0.00% auto_monad_reorder : 0.000018s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000544s : 0.12% opt_after_jit_grad : 0.000718s : 0.16% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000007s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000056s : 0.01% Time group info: ------[substitution.] 0.002908 270 0.26% : 0.000008s : 2: substitution.addn_check_dump 0.67% : 0.000019s : 2: substitution.addn_zero_filter 3.55% : 0.000103s : 9: substitution.arithmetic_simplify 0.27% : 0.000008s : 3: substitution.depend_value_elim 0.09% : 0.000003s : 2: substitution.elim_not_effective 0.05% : 0.000001s : 2: substitution.fold_const_symbol 33.94% : 0.000987s : 4: substitution.getattr_setattr_resolve 0.22% : 0.000006s : 3: substitution.graph_param_transform 40.18% : 0.001169s : 29: substitution.inline 2.83% : 0.000082s : 10: substitution.inline_without_move 0.54% : 0.000016s : 25: substitution.j_node_and_user_rematch 1.77% : 0.000051s : 2: substitution.less_batch_normalization 1.27% : 0.000037s : 2: substitution.merge_addn 0.79% : 0.000023s : 14: substitution.minmaximum_grad 1.33% : 0.000039s : 10: substitution.partial_eliminate 0.08% : 0.000002s : 2: substitution.redundant_stop_gradient_eliminater 0.60% : 0.000018s : 25: substitution.remove_not_recompute_node 3.75% : 0.000109s : 35: substitution.replace_applicator 0.64% : 0.000019s : 26: substitution.replace_old_param 0.22% : 0.000006s : 3: substitution.set_cell_output_no_recompute 0.29% : 0.000008s : 2: substitution.specialize_transform 1.67% : 0.000049s : 14: substitution.tuple_list_convert_item_index_to_positive 1.23% : 0.000036s : 14: substitution.tuple_list_get_item_depend_reorder 3.77% : 0.000110s : 30: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.220761 2 98.75% : 0.217996s : 1: type_inference.infer 1.25% : 0.002766s : 1: type_inference.specialize ------[replace.] 0.000873 50 8.16% : 0.000071s : 3: replace.getattr_setattr_resolve 34.90% : 0.000305s : 27: replace.inline 4.94% : 0.000043s : 2: replace.partial_eliminate 5.52% : 0.000048s : 2: replace.replace_applicator 46.49% : 0.000406s : 16: replace.tuple_list_get_item_eliminator ------[match.] 0.002178 50 42.61% : 0.000928s : 3: match.getattr_setattr_resolve 52.60% : 0.001146s : 27: match.inline 1.08% : 0.000024s : 2: match.partial_eliminate 0.90% : 0.000020s : 2: match.replace_applicator 2.80% : 0.000061s : 16: match.tuple_list_get_item_eliminator ------[predicate.] 0.000914 5640 1.42% : 0.000013s : 90: predicate.accumulaten_eliminater 0.27% : 0.000002s : 3: predicate.ad_related_special_op_eliminate 1.42% : 0.000013s : 90: predicate.addn_check_dump 1.52% : 0.000014s : 90: predicate.addn_zero_filter 2.35% : 0.000021s : 90: predicate.arithmetic_simplify 1.42% : 0.000013s : 90: predicate.cast_eliminate 0.07% : 0.000001s : 3: predicate.check_bprop_eliminate 1.33% : 0.000012s : 90: predicate.compare_switch_simplify 1.41% : 0.000013s : 90: predicate.depend_value_elim 1.29% : 0.000012s : 90: predicate.dict_get_item_const_eliminator 1.41% : 0.000013s : 90: predicate.dict_get_item_eliminator 1.40% : 0.000013s : 90: predicate.dict_set_item_eliminator 0.23% : 0.000002s : 3: predicate.dumpgradient_eliminate 0.06% : 0.000001s : 3: predicate.elim_not_effective 0.09% : 0.000001s : 3: predicate.elim_shapecalc_of_broadcastargs 0.29% : 0.000003s : 21: predicate.eliminate_switch_conditional_partial_ 0.28% : 0.000003s : 21: predicate.eliminate_switch_layer_partial_ 0.29% : 0.000003s : 21: predicate.eliminate_switch_partial_ 1.32% : 0.000012s : 90: predicate.environ_add_const_eliminate 1.28% : 0.000012s : 90: predicate.environ_get_add_eliminate 1.30% : 0.000012s : 90: predicate.environ_get_depend_swap 1.34% : 0.000012s : 90: predicate.environ_get_eliminate 1.32% : 0.000012s : 90: predicate.environ_get_set_eliminate 0.03% : 0.000000s : 3: predicate.fold_const_symbol 0.57% : 0.000005s : 31: predicate.get_grad_eliminate 0.76% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.04% : 0.000000s : 3: predicate.graph_param_transform 4.37% : 0.000040s : 139: predicate.inline 4.12% : 0.000038s : 175: predicate.inline_without_move 0.24% : 0.000002s : 31: predicate.j_node_and_user_rematch 0.72% : 0.000007s : 31: predicate.less_batch_normalization 1.75% : 0.000016s : 106: predicate.list_to_tuple_eliminator_ 1.84% : 0.000017s : 109: predicate.load_eliminater 0.20% : 0.000002s : 3: predicate.loop_unroll_after_grad 3.53% : 0.000032s : 227: predicate.loop_unroll_before_grad 1.51% : 0.000014s : 93: predicate.make_slice_get_slice_eliminator 1.31% : 0.000012s : 90: predicate.merge_addn 1.37% : 0.000013s : 90: predicate.minmaximum_grad 0.33% : 0.000003s : 3: predicate.mutable_eliminate 0.07% : 0.000001s : 3: predicate.opt_reshape 2.67% : 0.000024s : 132: predicate.partial_eliminate 1.38% : 0.000013s : 90: predicate.print_const_string_wrapper 1.81% : 0.000017s : 90: predicate.reduce_eliminate 1.88% : 0.000017s : 106: predicate.redundant_stop_gradient_eliminater 0.29% : 0.000003s : 31: predicate.remove_not_recompute_node 2.81% : 0.000026s : 262: predicate.replace_applicator 1.54% : 0.000014s : 175: predicate.replace_old_param 0.05% : 0.000000s : 3: predicate.reset_defer_inline 1.43% : 0.000013s : 90: predicate.reshape_eliminate 1.48% : 0.000014s : 90: predicate.row_tensor_add_zeros_like 0.13% : 0.000001s : 3: predicate.row_tensor_eliminate 1.42% : 0.000013s : 90: predicate.same_eliminate 0.37% : 0.000003s : 31: predicate.set_cell_output_no_recompute 0.16% : 0.000001s : 6: predicate.special_op_eliminate 0.67% : 0.000006s : 31: predicate.specialize_transform 1.65% : 0.000015s : 90: predicate.split_environ_get_set_with_tuple_value 1.42% : 0.000013s : 90: predicate.stack_unstack_eliminate 0.08% : 0.000001s : 3: predicate.switch_call_monad_eliminater 4.26% : 0.000039s : 133: predicate.switch_defer_inline 2.30% : 0.000021s : 133: predicate.switch_layer_defer_inline 6.74% : 0.000062s : 363: predicate.switch_simplify 1.42% : 0.000013s : 90: predicate.tile_eliminate 2.38% : 0.000022s : 90: predicate.transpose_eliminate 1.80% : 0.000016s : 90: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000015s : 90: predicate.tuple_list_get_item_depend_reorder 3.03% : 0.000028s : 112: predicate.tuple_list_get_item_eliminator 1.74% : 0.000016s : 90: predicate.tuple_list_set_item_eliminator 1.63% : 0.000015s : 106: predicate.tuple_to_list_eliminator_ 1.66% : 0.000015s : 109: predicate.updatestate_pure_node_eliminater 2.46% : 0.000022s : 140: predicate.updatestate_useless_node_eliminater 1.70% : 0.000016s : 90: predicate.value_based_eliminate 0.07% : 0.000001s : 3: predicate.virtual_view_grad_eliminate 0.11% : 0.000001s : 3: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.007460 85 60.66% : 0.004526s : 42: func_graph_cloner_run.FuncGraphClonerGraph 39.34% : 0.002935s : 43: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.056535 90 0.01% : 0.000063s : 1: add_recomputation 0.02% : 0.000176s : 1: auto_monad 0.00% : 0.000020s : 1: auto_monad_reorder 0.05% : 0.000508s : 1: bootstrap 0.00% : 0.000037s : 1: cconv 0.00% : 0.000012s : 1: convert_after_rewriter 0.00% : 0.000031s : 1: cse_after_recomputation 0.00% : 0.000014s : 1: environ_conv 0.00% : 0.000048s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 56.40% : 0.595860s : 1: jit_opt_a 0.02% : 0.000203s : 1: jit_opt_after_cconv 0.01% : 0.000069s : 1: jit_opt_b 0.06% : 0.000582s : 1: loop_unroll 0.10% : 0.001024s : 1: mutable_eliminate 7.45% : 0.078744s : 39: opt.transform.jit_opt_a 0.01% : 0.000061s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000033s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000022s : 1: opt.transform.mutable_eliminate 0.00% : 0.000031s : 1: opt.transform.opt_after_jit_grad 0.11% : 0.001129s : 2: opt.transform.opt_resolve 0.02% : 0.000164s : 1: opt.transform.partial_eliminate 0.00% : 0.000042s : 4: opt.transform.symbol_engine_opt 0.07% : 0.000730s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.01% : 0.000061s : 1: py_interpret_to_execute 0.00% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000025s : 1: remove_dup_value 13.87% : 0.146544s : 2: renormalize.infer 0.79% : 0.008328s : 2: renormalize.specialize 0.05% : 0.000551s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000058s : 1: rewriter_after_opt_a 0.02% : 0.000177s : 1: rewriter_before_opt_a 0.01% : 0.000098s : 1: symbol_engine_optimizer 20.92% : 0.221002s : 1: type_inference . [hook] pytest_runtest_teardown:test_my_ms_jit_stream_ctx_runtime tests/st/compiler/stream_event/test_with_stream.py::test_my_ms_jit_stream_ctx_runtime,max_mem:8.0M =============================== 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") test_with_stream.py::test_my_ms_jit_stream_ctx_runtime /usr/local/Ascend/cann-8.5.0/python/site-packages/asc_op_compile_base/asc_op_compiler/ascendc_compile_gen_code.py:161: DeprecationWarning: invalid escape sequence \w match = re.search(f'{option}=(\w+)', ' '.join(compile_options)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 1 passed, 26 warnings in 233.88s (0:03:53) ==================