==================================================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/infer/ops/test_internal_ops, configfile: ../../../../../../../../sault/virtual_test/virtualenv_004/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 4 items test_qbmm_split.py [WARNING] ME(164923:281473602678576,MainProcess):2026-01-29-17:37:25.867.264 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 1.14991, [21] [bootstrap]: 0.00067741 [type_inference]: 1.06685 [event_method]: 1.965e-05 [auto_monad]: 0.0016483 [graph_reusing]: 7.25003e-06 [inline]: 3.25998e-06 [add_attr]: 0.0208128, [1] [add_attr_with_inline]: 0.0207966, [1] [Cycle 1]: 0.00011489, [2] [tag_attr]: 2.69e-05 [meta_addattr_fg_expand]: 5.17e-06 [parallel-infer-symbol]: 4.00998e-06 [pre_auto_parallel]: 5.21e-05 [insert-virtual-dataset]: 2.62001e-06 [parallel-infer-symbol-second]: 9.09989e-07 [dataset_repeat_opt]: 1.99e-06 [pipeline_split]: 1.88002e-06 [optimize]: 0.0182789, [53] [py_interpret_to_execute]: 3.583e-05 [rewriter_before_opt_a]: 0.00011093 [opt_a]: 0.0136307, [2] [Cycle 1]: 0.0115025, [45] [expand_dump_flag]: 2.60997e-06 [switch_simplify]: 4.012e-05 [loop_unroll]: 2.71e-05 [a_1]: 0.00081162 [with_stream_mark]: 2.525e-05 [recompute_prepare]: 2.196e-05 [updatestate_depend_eliminate]: 1.162e-05 [updatestate_assign_eliminate]: 1.398e-05 [updatestate_loads_eliminate]: 1.765e-05 [parameter_eliminate]: 2.34001e-06 [a_2]: 0.00029916 [accelerated_algorithm]: 4.487e-05 [shard]: 2.49001e-06 [meta_shard_fg_expand]: 4.39998e-06 [shard_inline]: 2.027e-05 [merge_send_recv]: 1.525e-05 [auto_parallel]: 1.579e-05 [parallel]: 4.477e-05 [flash_sp]: 2.351e-05 [merge_comm]: 1.193e-05 [allreduce_fusion]: 1.053e-05 [matmul_add_comm_reduction]: 1.906e-05 [allreduce_slice_to_reducescatter]: 7.89994e-07 [virtual_shard_identity]: 2.425e-05 [virtual_dataset]: 2.15e-05 [get_grad_eliminate_]: 2.038e-05 [virtual_output]: 2.037e-05 [merge_forward]: 1.043e-05 [cell_reuse_recompute_pass]: 1.85001e-06 [offload_activation]: 2.11e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.734e-05 [merge_recompute_call_nodes]: 1.79e-06 [before_grad]: 3.265e-05 [set_forward_comm_id_for_comm_node_pass]: 1.126e-05 [meta_fg_expand]: 8.30999e-06 [flash_sp_send_recv_attached]: 5.17e-06 [receive_attached]: 1.196e-05 [after_resolve]: 2.986e-05 [a_after_grad]: 3.222e-05 [renormalize]: 0.0086331 [add_forward_monad_depend]: 1.219e-05 [auto_monad_grad]: 3.09001e-06 [auto_monad_eliminator]: 7.711e-05 [cse]: 0.00050915 [a_3]: 0.00016958 [Cycle 2]: 0.00211236, [45] [expand_dump_flag]: 3.69002e-06 [switch_simplify]: 2.415e-05 [loop_unroll]: 2.107e-05 [a_1]: 0.00060345 [with_stream_mark]: 3.527e-05 [recompute_prepare]: 2.651e-05 [updatestate_depend_eliminate]: 1.394e-05 [updatestate_assign_eliminate]: 1.144e-05 [updatestate_loads_eliminate]: 1.745e-05 [parameter_eliminate]: 2.61e-06 [a_2]: 0.00030565 [accelerated_algorithm]: 3.095e-05 [shard]: 2.68e-06 [meta_shard_fg_expand]: 7.85e-06 [shard_inline]: 2.15e-05 [merge_send_recv]: 1.939e-05 [auto_parallel]: 1.759e-05 [parallel]: 1.064e-05 [flash_sp]: 4.94e-06 [merge_comm]: 1.057e-05 [allreduce_fusion]: 9.91998e-06 [matmul_add_comm_reduction]: 2.083e-05 [allreduce_slice_to_reducescatter]: 1.22999e-06 [virtual_shard_identity]: 2.578e-05 [virtual_dataset]: 2.043e-05 [get_grad_eliminate_]: 1.979e-05 [virtual_output]: 1.978e-05 [merge_forward]: 1.16e-05 [cell_reuse_recompute_pass]: 3.18e-06 [offload_activation]: 2.099e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.278e-05 [merge_recompute_call_nodes]: 2.11e-06 [before_grad]: 3.346e-05 [set_forward_comm_id_for_comm_node_pass]: 1.427e-05 [meta_fg_expand]: 8.63001e-06 [flash_sp_send_recv_attached]: 1.79e-06 [receive_attached]: 2.46998e-06 [after_resolve]: 3.156e-05 [a_after_grad]: 3.126e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 6.38998e-06 [auto_monad_grad]: 3.66999e-06 [auto_monad_eliminator]: 7.326e-05 [cse]: 8.549e-05 [a_3]: 0.00013983 [py_interpret_to_execute_after_opt_a]: 3.723e-05 [slice_cell_reuse_recomputed_activation]: 2.34001e-06 [rewriter_after_opt_a]: 0.00028002 [convert_after_rewriter]: 2.344e-05 [order_py_execute_after_rewriter]: 1.179e-05 [mutable_eliminate]: 0.00088922 [opt_b]: 0.00077517, [1] [Cycle 1]: 0.00076536, [7] [b_1]: 0.00050216 [b_2]: 2.539e-05 [updatestate_depend_eliminate]: 2.225e-05 [updatestate_assign_eliminate]: 1.1e-05 [updatestate_loads_eliminate]: 1.813e-05 [renormalize]: 1.09e-06 [cse]: 0.00012481 [optimize_parallel_all_gather_comm]: 4.348e-05 [overlap_param_gather]: 2.00002e-06 [cconv]: 4.534e-05 [loop_unroll]: 0.0007049 [opt_after_cconv]: 0.00036617, [1] [Cycle 1]: 0.00035558, [7] [c_1]: 0.0001563 [parameter_eliminate]: 6.82002e-06 [updatestate_depend_eliminate]: 1.959e-05 [updatestate_assign_eliminate]: 1.08e-05 [updatestate_loads_eliminate]: 1.663e-05 [cse]: 9.524e-05 [renormalize]: 8.80013e-07 [remove_dup_value]: 9.671e-05 [tuple_transform]: 0.00021476, [1] [Cycle 1]: 0.00020679, [4] [d_1]: 0.00015399 [none_parameter_eliminate]: 3.3e-06 [renormalize]: 3.69997e-07 [switch_simplify]: 2.48e-05 [partial_unused_args_eliminate]: 2.43998e-06 [add_recomputation]: 0.00014697 [cse_after_recomputation]: 7.683e-05, [1] [Cycle 1]: 6.898e-05, [1] [cse]: 5.751e-05 [environ_conv]: 3.892e-05 [swap_dp_allreduce_reducescatter]: 1.749e-05 [bias_add_comm_swap]: 3.39001e-06 [label_micro_interleaved_index]: 8.27998e-06 [label_fine_grained_interleaved_index]: 2.69999e-06 [merge_cast_opt]: 1.58002e-06 [slice_recompute_activation]: 2.19001e-06 [micro_interleaved_order_control]: 2.72001e-06 [assign_add_opt]: 1.29998e-06 [ForceFp32Comm]: 1.15001e-06 [remove_cast_before_assign_add]: 1.05999e-06 [full_micro_interleaved_order_control]: 2.44999e-06 [reorder_send_recv_between_fp_bp]: 2.74999e-06 [comm_op_add_attrs]: 1.46998e-06 [add_comm_op_reuse_tag]: 1.22e-06 [interleave_split_concat_branches]: 1.20999e-06 [interleave_parallel_branches]: 1.06002e-06 [overlap_opt_shard_in_pipeline]: 2.529e-05 [overlap_opt_shard_grad_in_pipeline]: 1.82999e-06 [control_data_broadcast_order]: 3.615e-05 [grouped_pairwise_exchange_alltoall]: 1.91003e-06 [offloading_packed_experts]: 1e-05 [overlap_recompute_and_grad_model_parallel]: 1.012e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.25999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.50999e-06 [overlap_recompute_comm]: 2.68e-06 [overlap_grad_ring_attention]: 9.39e-06 [overlap_grad_flash_sp]: 6.598e-05 [begin_end_overlap_inline]: 8.00006e-07 [split_matmul_comm_elemetwise]: 2.21e-06 [split_layernorm_comm]: 2.02001e-06 [handle_group_info]: 1.22e-06 [symbol_engine_optimizer]: 0.00021292, [1] [Cycle 1]: 0.0002056, [6] [build]: 2.135e-05 [elim_shapecalc]: 3.813e-05 [elim_not_effective]: 4.066e-05 [opt_reshape]: 2.803e-05 [fold_const_symbol]: 3.368e-05 [renormalize]: 2.00002e-07 [detach_backward]: 2.81999e-06 [pipeline_parallel_scheduler]: 1.62999e-06 [auto_monad_reorder]: 0.0402112 [get_jit_bprop_graph]: 3.84002e-06 [rewriter_after_jit_bprop_graph]: 1.005e-05 [opt_after_jit_grad]: 0.00088062 [validate]: 0.00013045 Sums bootstrap : 0.000677s : 0.06% type_inference : 1.066855s : 94.61% event_method : 0.000020s : 0.00% auto_monad : 0.001648s : 0.15% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000027s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000052s : 0.00% 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 : 0.000036s : 0.00% optimize.rewriter_before_opt_a : 0.000111s : 0.01% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000064s : 0.01% optimize.opt_a.loop_unroll : 0.000048s : 0.00% optimize.opt_a.a_1 : 0.001415s : 0.13% optimize.opt_a.with_stream_mark : 0.000061s : 0.01% optimize.opt_a.recompute_prepare : 0.000048s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000026s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000025s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000035s : 0.00% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000605s : 0.05% optimize.opt_a.accelerated_algorithm : 0.000076s : 0.01% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000012s : 0.00% optimize.opt_a.shard_inline : 0.000042s : 0.00% optimize.opt_a.merge_send_recv : 0.000035s : 0.00% optimize.opt_a.auto_parallel : 0.000033s : 0.00% optimize.opt_a.parallel : 0.000055s : 0.00% optimize.opt_a.flash_sp : 0.000028s : 0.00% optimize.opt_a.merge_comm : 0.000022s : 0.00% optimize.opt_a.allreduce_fusion : 0.000020s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000040s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000050s : 0.00% optimize.opt_a.virtual_dataset : 0.000042s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000040s : 0.00% optimize.opt_a.virtual_output : 0.000040s : 0.00% optimize.opt_a.merge_forward : 0.000022s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000042s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000080s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000066s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000026s : 0.00% optimize.opt_a.meta_fg_expand : 0.000017s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000014s : 0.00% optimize.opt_a.after_resolve : 0.000061s : 0.01% optimize.opt_a.a_after_grad : 0.000063s : 0.01% optimize.opt_a.renormalize : 0.008633s : 0.77% optimize.opt_a.add_forward_monad_depend : 0.000019s : 0.00% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000150s : 0.01% optimize.opt_a.cse : 0.000595s : 0.05% optimize.opt_a.a_3 : 0.000309s : 0.03% optimize.py_interpret_to_execute_after_opt_a : 0.000037s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000280s : 0.02% optimize.convert_after_rewriter : 0.000023s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000889s : 0.08% optimize.opt_b.b_1 : 0.000502s : 0.04% optimize.opt_b.b_2 : 0.000025s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000022s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000018s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000125s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000043s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000045s : 0.00% optimize.loop_unroll : 0.000705s : 0.06% optimize.opt_after_cconv.c_1 : 0.000156s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000020s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.cse : 0.000095s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000097s : 0.01% optimize.tuple_transform.d_1 : 0.000154s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000025s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000147s : 0.01% optimize.cse_after_recomputation.cse : 0.000058s : 0.01% optimize.environ_conv : 0.000039s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000017s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000008s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000025s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000036s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000010s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000066s : 0.01% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000021s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000038s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000041s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000028s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000034s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.040211s : 3.57% get_jit_bprop_graph : 0.000004s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000881s : 0.08% validate : 0.000130s : 0.01% Time group info: ------[substitution.] 0.000397 135 2.65% : 0.000011s : 2: substitution.depend_value_elim 1.34% : 0.000005s : 11: substitution.elim_not_effective 1.05% : 0.000004s : 11: substitution.fold_const_symbol 3.81% : 0.000015s : 18: substitution.graph_param_transform 32.97% : 0.000131s : 1: substitution.inline 2.73% : 0.000011s : 22: substitution.j_node_and_user_rematch 6.15% : 0.000024s : 2: substitution.less_batch_normalization 3.14% : 0.000012s : 18: substitution.load_eliminater 0.52% : 0.000002s : 2: substitution.opt_reshape 4.20% : 0.000017s : 22: substitution.remove_not_recompute_node 2.64% : 0.000010s : 8: substitution.replace_old_param 7.41% : 0.000029s : 4: substitution.reshape_eliminate 2.67% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 28.72% : 0.000114s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.066725 2 95.07% : 1.014090s : 1: type_inference.infer 4.93% : 0.052635s : 1: type_inference.specialize ------[replace.] 0.000021 1 100.00% : 0.000021s : 1: replace.inline ------[match.] 0.000130 1 100.00% : 0.000130s : 1: match.inline ------[predicate.] 0.000570 4131 0.78% : 0.000004s : 37: predicate.accumulaten_eliminater 0.99% : 0.000006s : 18: predicate.ad_related_special_op_eliminate 0.78% : 0.000004s : 36: predicate.addn_check_dump 0.79% : 0.000005s : 37: predicate.addn_zero_filter 0.74% : 0.000004s : 37: predicate.adjust_all_reduce_mul_add 2.19% : 0.000012s : 73: predicate.arithmetic_simplify 0.81% : 0.000005s : 37: predicate.cast_eliminate 0.81% : 0.000005s : 36: predicate.check_bprop_eliminate 0.80% : 0.000005s : 36: predicate.compare_switch_simplify 0.27% : 0.000002s : 18: predicate.const_output_eliminate 0.82% : 0.000005s : 36: predicate.depend_value_elim 0.87% : 0.000005s : 37: predicate.dict_get_item_const_eliminator 0.97% : 0.000006s : 37: predicate.dict_get_item_eliminator 0.83% : 0.000005s : 37: predicate.dict_set_item_eliminator 1.01% : 0.000006s : 36: predicate.dumpgradient_eliminate 0.31% : 0.000002s : 18: predicate.elim_not_effective 0.58% : 0.000003s : 18: predicate.elim_shapecalc_of_broadcastargs 1.18% : 0.000007s : 55: predicate.environ_add_const_eliminate 1.13% : 0.000006s : 55: predicate.environ_get_add_eliminate 1.12% : 0.000006s : 55: predicate.environ_get_depend_swap 1.99% : 0.000011s : 91: predicate.environ_get_eliminate 1.12% : 0.000006s : 55: predicate.environ_get_set_eliminate 0.78% : 0.000004s : 38: predicate.exchange_switch_depend_value 1.20% : 0.000007s : 38: predicate.float_depend_g_call 0.79% : 0.000005s : 36: predicate.float_environ_get_switch 1.19% : 0.000007s : 54: predicate.float_tuple_getitem_switch 0.23% : 0.000001s : 18: predicate.fold_const_symbol 0.87% : 0.000005s : 36: predicate.get_grad_eliminate 0.29% : 0.000002s : 18: predicate.graph_param_transform 0.87% : 0.000005s : 36: predicate.incorporate_call 0.74% : 0.000004s : 36: predicate.incorporate_call_switch 5.36% : 0.000031s : 183: predicate.inline 1.09% : 0.000006s : 36: predicate.inline_without_move 0.47% : 0.000003s : 36: predicate.j_node_and_user_rematch 1.10% : 0.000006s : 36: predicate.less_batch_normalization 1.68% : 0.000010s : 73: predicate.list_to_tuple_eliminator_ 2.37% : 0.000013s : 110: predicate.load_eliminater 1.03% : 0.000006s : 18: predicate.loop_unroll_after_grad 1.00% : 0.000006s : 41: predicate.loop_unroll_before_grad 1.79% : 0.000010s : 73: predicate.make_slice_get_slice_eliminator 0.83% : 0.000005s : 36: predicate.merge_addn 0.87% : 0.000005s : 36: predicate.micro_step_allgather_replace 0.93% : 0.000005s : 36: predicate.mini_step_allgather_replace 0.80% : 0.000005s : 37: predicate.minmaximum_grad 1.06% : 0.000006s : 18: predicate.mutable_eliminate 0.60% : 0.000003s : 18: predicate.opt_reshape 0.46% : 0.000003s : 18: predicate.parallel_virtual_node 1.03% : 0.000006s : 38: predicate.partial_defer_inline 1.32% : 0.000008s : 55: predicate.partial_eliminate 0.89% : 0.000005s : 37: predicate.print_const_string_wrapper 0.81% : 0.000005s : 36: predicate.reduce_all_const_elim 1.01% : 0.000006s : 37: predicate.reduce_eliminate 2.35% : 0.000013s : 110: predicate.redundant_stop_gradient_eliminater 0.51% : 0.000003s : 36: predicate.remove_not_recompute_node 1.40% : 0.000008s : 73: predicate.replace_applicator 0.56% : 0.000003s : 36: predicate.replace_old_param 0.34% : 0.000002s : 18: predicate.reset_defer_inline 0.87% : 0.000005s : 37: predicate.reshape_eliminate 0.96% : 0.000005s : 36: predicate.row_tensor_add_zeros_like 0.49% : 0.000003s : 18: predicate.row_tensor_eliminate 1.08% : 0.000006s : 36: predicate.same_eliminate 0.58% : 0.000003s : 36: predicate.set_cell_output_no_recompute 1.03% : 0.000006s : 36: predicate.shard_identity_eliminate 0.92% : 0.000005s : 36: predicate.special_op_eliminate 0.93% : 0.000005s : 36: predicate.specialize_transform 1.10% : 0.000006s : 36: predicate.split_environ_get_set_with_tuple_value 1.00% : 0.000006s : 36: predicate.stack_unstack_eliminate 0.47% : 0.000003s : 18: predicate.switch_call_monad_eliminater 0.95% : 0.000005s : 38: predicate.switch_defer_inline 1.71% : 0.000010s : 74: predicate.switch_layer_defer_inline 3.42% : 0.000019s : 133: predicate.switch_simplify 0.82% : 0.000005s : 37: predicate.tile_eliminate 0.80% : 0.000005s : 37: predicate.transpose_eliminate 1.87% : 0.000011s : 73: predicate.tuple_list_convert_item_index_to_positive 1.74% : 0.000010s : 73: predicate.tuple_list_get_item_const_eliminator 1.65% : 0.000009s : 73: predicate.tuple_list_get_item_depend_reorder 2.88% : 0.000016s : 109: predicate.tuple_list_get_item_eliminator 1.85% : 0.000011s : 73: predicate.tuple_list_get_set_item_eliminator 2.80% : 0.000016s : 109: predicate.tuple_list_set_item_eliminator 1.58% : 0.000009s : 73: predicate.tuple_to_list_eliminator_ 2.31% : 0.000013s : 110: predicate.updatestate_pure_node_eliminater 3.36% : 0.000019s : 146: predicate.updatestate_useless_node_eliminater 0.52% : 0.000003s : 18: predicate.value_based_eliminate 0.94% : 0.000005s : 36: predicate.virtual_dataset_eliminate 0.89% : 0.000005s : 36: predicate.virtual_output_eliminate 0.44% : 0.000003s : 18: predicate.virtual_view_grad_eliminate 0.50% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.010431 58 78.91% : 0.008231s : 55: func_graph_cloner_run.FuncGraphClonerGraph 21.09% : 0.002200s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.201408 192 0.00% : 0.000004s : 1: ForceFp32Comm 1.73% : 0.020819s : 1: add_attr 1.73% : 0.020801s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000155s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.14% : 0.001681s : 1: auto_monad 3.35% : 0.040250s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.06% : 0.000724s : 1: bootstrap 0.00% : 0.000051s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000042s : 1: control_data_broadcast_order 0.00% : 0.000030s : 1: convert_after_rewriter 0.01% : 0.000080s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000045s : 1: environ_conv 0.00% : 0.000028s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000012s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000012s : 1: label_micro_interleaved_index 0.06% : 0.000720s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.08% : 0.000903s : 1: mutable_eliminate 0.00% : 0.000014s : 1: offloading_packed_experts 0.00% : 0.000042s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000047s : 1: opt.transform.mutable_eliminate 0.24% : 0.002927s : 78: opt.transform.opt_a 0.01% : 0.000154s : 1: opt.transform.opt_after_cconv 0.01% : 0.000087s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000488s : 28: opt.transform.opt_b 0.01% : 0.000175s : 2: opt.transform.opt_trans_graph 0.01% : 0.000135s : 4: opt.transform.symbol_engine_opt 1.13% : 0.013635s : 1: opt_a 0.03% : 0.000370s : 1: opt_after_cconv 0.07% : 0.000892s : 1: opt_after_jit_grad 0.07% : 0.000781s : 1: opt_b 1.52% : 0.018287s : 1: optimize 0.00% : 0.000049s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.01% : 0.000071s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000031s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000057s : 1: pre_auto_parallel 0.00% : 0.000040s : 1: py_interpret_to_execute 0.00% : 0.000044s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000103s : 1: remove_dup_value 0.49% : 0.005869s : 1: renormalize.infer 0.23% : 0.002747s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000014s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000294s : 1: rewriter_after_opt_a 0.01% : 0.000116s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000021s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000216s : 1: symbol_engine_optimizer 0.02% : 0.000218s : 1: tuple_transform 88.80% : 1.066902s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_0[False-k_n_shape0-1] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_0[False-k_n_shape0-1],max_mem:110.0M [WARNING] ME(164923:281473602678576,MainProcess):2026-01-29-17:37:57.654.917 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 1.74059, [21] [bootstrap]: 0.00058842 [type_inference]: 1.54899 [event_method]: 1.966e-05 [auto_monad]: 0.00034453 [graph_reusing]: 7.45998e-06 [inline]: 2.85002e-06 [add_attr]: 0.00637379, [1] [add_attr_with_inline]: 0.00635778, [1] [Cycle 1]: 8.107e-05, [2] [tag_attr]: 2.416e-05 [meta_addattr_fg_expand]: 5.14e-06 [parallel-infer-symbol]: 4.09002e-06 [pre_auto_parallel]: 3.831e-05 [insert-virtual-dataset]: 2.78e-06 [parallel-infer-symbol-second]: 6.69999e-07 [dataset_repeat_opt]: 1.84e-06 [pipeline_split]: 1.91e-06 [optimize]: 0.183033, [53] [py_interpret_to_execute]: 3.302e-05 [rewriter_before_opt_a]: 0.0001015 [opt_a]: 0.178927, [2] [Cycle 1]: 0.176867, [45] [expand_dump_flag]: 2.97002e-06 [switch_simplify]: 3.982e-05 [loop_unroll]: 2.512e-05 [a_1]: 0.165104 [with_stream_mark]: 6.533e-05 [recompute_prepare]: 5.201e-05 [updatestate_depend_eliminate]: 1.542e-05 [updatestate_assign_eliminate]: 1.334e-05 [updatestate_loads_eliminate]: 2.176e-05 [parameter_eliminate]: 2.79999e-06 [a_2]: 0.00046532 [accelerated_algorithm]: 5.522e-05 [shard]: 2.65002e-06 [meta_shard_fg_expand]: 8.27e-06 [shard_inline]: 2.132e-05 [merge_send_recv]: 1.842e-05 [auto_parallel]: 1.815e-05 [parallel]: 4.289e-05 [flash_sp]: 1.606e-05 [merge_comm]: 1.169e-05 [allreduce_fusion]: 1.138e-05 [matmul_add_comm_reduction]: 2.163e-05 [allreduce_slice_to_reducescatter]: 9.5999e-07 [virtual_shard_identity]: 2.601e-05 [virtual_dataset]: 2.417e-05 [get_grad_eliminate_]: 2.384e-05 [virtual_output]: 2.385e-05 [merge_forward]: 1.314e-05 [cell_reuse_recompute_pass]: 2.66e-06 [offload_activation]: 2.176e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.302e-05 [merge_recompute_call_nodes]: 1.52999e-06 [before_grad]: 3.895e-05 [set_forward_comm_id_for_comm_node_pass]: 1.191e-05 [meta_fg_expand]: 7.62998e-06 [flash_sp_send_recv_attached]: 4.90999e-06 [receive_attached]: 2.62001e-06 [after_resolve]: 3.286e-05 [a_after_grad]: 3.918e-05 [renormalize]: 0.00920513 [add_forward_monad_depend]: 1.158e-05 [auto_monad_grad]: 2.83e-06 [auto_monad_eliminator]: 6.33e-05 [cse]: 0.00067226 [a_3]: 0.00017265 [Cycle 2]: 0.00204663, [45] [expand_dump_flag]: 2.65002e-06 [switch_simplify]: 2.354e-05 [loop_unroll]: 2.153e-05 [a_1]: 0.00061927 [with_stream_mark]: 2.659e-05 [recompute_prepare]: 2.217e-05 [updatestate_depend_eliminate]: 1.227e-05 [updatestate_assign_eliminate]: 1.135e-05 [updatestate_loads_eliminate]: 6.67e-05 [parameter_eliminate]: 2.76e-06 [a_2]: 0.00030079 [accelerated_algorithm]: 2.844e-05 [shard]: 2.21e-06 [meta_shard_fg_expand]: 5.09e-06 [shard_inline]: 2.022e-05 [merge_send_recv]: 1.833e-05 [auto_parallel]: 1.78e-05 [parallel]: 1.221e-05 [flash_sp]: 5.02999e-06 [merge_comm]: 1.05e-05 [allreduce_fusion]: 1.018e-05 [matmul_add_comm_reduction]: 1.979e-05 [allreduce_slice_to_reducescatter]: 7.89994e-07 [virtual_shard_identity]: 2.38e-05 [virtual_dataset]: 1.968e-05 [get_grad_eliminate_]: 1.997e-05 [virtual_output]: 2.027e-05 [merge_forward]: 1.072e-05 [cell_reuse_recompute_pass]: 3.14001e-06 [offload_activation]: 1.911e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.791e-05 [merge_recompute_call_nodes]: 1.69998e-06 [before_grad]: 3.278e-05 [set_forward_comm_id_for_comm_node_pass]: 1.13e-05 [meta_fg_expand]: 7.23999e-06 [flash_sp_send_recv_attached]: 1.87001e-06 [receive_attached]: 2.58998e-06 [after_resolve]: 3.007e-05 [a_after_grad]: 3.314e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 3.82002e-06 [auto_monad_grad]: 2.56e-06 [auto_monad_eliminator]: 5.461e-05 [cse]: 7.07e-05 [a_3]: 0.00013789 [py_interpret_to_execute_after_opt_a]: 3.205e-05 [slice_cell_reuse_recomputed_activation]: 2.26e-06 [rewriter_after_opt_a]: 0.00021702 [convert_after_rewriter]: 2.12e-05 [order_py_execute_after_rewriter]: 1.251e-05 [mutable_eliminate]: 0.00080366 [opt_b]: 0.00068497, [1] [Cycle 1]: 0.00067495, [7] [b_1]: 0.00048232 [b_2]: 2.479e-05 [updatestate_depend_eliminate]: 1.675e-05 [updatestate_assign_eliminate]: 1.033e-05 [updatestate_loads_eliminate]: 1.599e-05 [renormalize]: 5.40022e-07 [cse]: 8.154e-05 [optimize_parallel_all_gather_comm]: 3.39e-05 [overlap_param_gather]: 1.85001e-06 [cconv]: 3.853e-05 [loop_unroll]: 0.00051123 [opt_after_cconv]: 0.00029359, [1] [Cycle 1]: 0.00028695, [7] [c_1]: 0.00013625 [parameter_eliminate]: 4.43001e-06 [updatestate_depend_eliminate]: 1.452e-05 [updatestate_assign_eliminate]: 1.004e-05 [updatestate_loads_eliminate]: 1.411e-05 [cse]: 6.774e-05 [renormalize]: 1.19e-06 [remove_dup_value]: 0.00013589 [tuple_transform]: 0.00026959, [1] [Cycle 1]: 0.00026314, [4] [d_1]: 0.00016162 [none_parameter_eliminate]: 2.74999e-06 [renormalize]: 5.50004e-07 [switch_simplify]: 2.582e-05 [partial_unused_args_eliminate]: 2.20002e-06 [add_recomputation]: 0.00013457 [cse_after_recomputation]: 7.606e-05, [1] [Cycle 1]: 6.788e-05, [1] [cse]: 5.775e-05 [environ_conv]: 2.093e-05 [swap_dp_allreduce_reducescatter]: 1.634e-05 [bias_add_comm_swap]: 2.98e-06 [label_micro_interleaved_index]: 6.21e-06 [label_fine_grained_interleaved_index]: 2.86999e-06 [merge_cast_opt]: 1.35999e-06 [slice_recompute_activation]: 2.13002e-06 [micro_interleaved_order_control]: 2.48e-06 [assign_add_opt]: 1.50999e-06 [ForceFp32Comm]: 1.22e-06 [remove_cast_before_assign_add]: 1.30001e-06 [full_micro_interleaved_order_control]: 2.51e-06 [reorder_send_recv_between_fp_bp]: 3.04001e-06 [comm_op_add_attrs]: 1.09e-06 [add_comm_op_reuse_tag]: 1.29e-06 [interleave_split_concat_branches]: 1.18001e-06 [interleave_parallel_branches]: 1.04998e-06 [overlap_opt_shard_in_pipeline]: 4.00998e-06 [overlap_opt_shard_grad_in_pipeline]: 1.65001e-06 [control_data_broadcast_order]: 3.514e-05 [grouped_pairwise_exchange_alltoall]: 1.97001e-06 [offloading_packed_experts]: 9.28002e-06 [overlap_recompute_and_grad_model_parallel]: 9.71003e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.35001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.49e-06 [overlap_recompute_comm]: 2.09e-06 [overlap_grad_ring_attention]: 1.018e-05 [overlap_grad_flash_sp]: 4.863e-05 [begin_end_overlap_inline]: 5.50004e-07 [split_matmul_comm_elemetwise]: 2.65002e-06 [split_layernorm_comm]: 1.80001e-06 [handle_group_info]: 1.86e-06 [symbol_engine_optimizer]: 0.00021153, [1] [Cycle 1]: 0.000204, [6] [build]: 1.8e-05 [elim_shapecalc]: 3.381e-05 [elim_not_effective]: 4.518e-05 [opt_reshape]: 3.064e-05 [fold_const_symbol]: 3.542e-05 [renormalize]: 2.29978e-07 [detach_backward]: 2.24001e-06 [pipeline_parallel_scheduler]: 1.91e-06 [auto_monad_reorder]: 6.825e-05 [get_jit_bprop_graph]: 1.92999e-06 [rewriter_after_jit_bprop_graph]: 7.55e-06 [opt_after_jit_grad]: 0.00076296 [validate]: 0.00011187 Sums bootstrap : 0.000588s : 0.03% type_inference : 1.548991s : 89.39% event_method : 0.000020s : 0.00% auto_monad : 0.000345s : 0.02% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000024s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000038s : 0.00% 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 : 0.000033s : 0.00% optimize.rewriter_before_opt_a : 0.000101s : 0.01% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000063s : 0.00% optimize.opt_a.loop_unroll : 0.000047s : 0.00% optimize.opt_a.a_1 : 0.165723s : 9.56% optimize.opt_a.with_stream_mark : 0.000092s : 0.01% optimize.opt_a.recompute_prepare : 0.000074s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000028s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000025s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000088s : 0.01% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000766s : 0.04% optimize.opt_a.accelerated_algorithm : 0.000084s : 0.00% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.00% optimize.opt_a.shard_inline : 0.000042s : 0.00% optimize.opt_a.merge_send_recv : 0.000037s : 0.00% optimize.opt_a.auto_parallel : 0.000036s : 0.00% optimize.opt_a.parallel : 0.000055s : 0.00% optimize.opt_a.flash_sp : 0.000021s : 0.00% optimize.opt_a.merge_comm : 0.000022s : 0.00% optimize.opt_a.allreduce_fusion : 0.000022s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000041s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000050s : 0.00% optimize.opt_a.virtual_dataset : 0.000044s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000044s : 0.00% optimize.opt_a.virtual_output : 0.000044s : 0.00% optimize.opt_a.merge_forward : 0.000024s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000041s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000081s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000072s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000023s : 0.00% optimize.opt_a.meta_fg_expand : 0.000015s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000063s : 0.00% optimize.opt_a.a_after_grad : 0.000072s : 0.00% optimize.opt_a.renormalize : 0.009205s : 0.53% optimize.opt_a.add_forward_monad_depend : 0.000015s : 0.00% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000118s : 0.01% optimize.opt_a.cse : 0.000743s : 0.04% optimize.opt_a.a_3 : 0.000311s : 0.02% optimize.py_interpret_to_execute_after_opt_a : 0.000032s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000217s : 0.01% optimize.convert_after_rewriter : 0.000021s : 0.00% optimize.order_py_execute_after_rewriter : 0.000013s : 0.00% optimize.mutable_eliminate : 0.000804s : 0.05% optimize.opt_b.b_1 : 0.000482s : 0.03% optimize.opt_b.b_2 : 0.000025s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000017s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000016s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000082s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000034s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000039s : 0.00% optimize.loop_unroll : 0.000511s : 0.03% optimize.opt_after_cconv.c_1 : 0.000136s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000015s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000014s : 0.00% optimize.opt_after_cconv.cse : 0.000068s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000136s : 0.01% optimize.tuple_transform.d_1 : 0.000162s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000001s : 0.00% optimize.tuple_transform.switch_simplify : 0.000026s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000135s : 0.01% optimize.cse_after_recomputation.cse : 0.000058s : 0.00% optimize.environ_conv : 0.000021s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000016s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000002s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000004s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000035s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000009s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000010s : 0.00% optimize.overlap_grad_flash_sp : 0.000049s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000002s : 0.00% optimize.symbol_engine_optimizer.build : 0.000018s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000034s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000045s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000031s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000035s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000068s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000763s : 0.04% validate : 0.000112s : 0.01% Time group info: ------[substitution.] 0.000389 135 2.70% : 0.000010s : 2: substitution.depend_value_elim 1.32% : 0.000005s : 11: substitution.elim_not_effective 1.06% : 0.000004s : 11: substitution.fold_const_symbol 4.05% : 0.000016s : 18: substitution.graph_param_transform 32.36% : 0.000126s : 1: substitution.inline 2.91% : 0.000011s : 22: substitution.j_node_and_user_rematch 7.50% : 0.000029s : 2: substitution.less_batch_normalization 2.65% : 0.000010s : 18: substitution.load_eliminater 0.89% : 0.000003s : 2: substitution.opt_reshape 4.49% : 0.000017s : 22: substitution.remove_not_recompute_node 2.52% : 0.000010s : 8: substitution.replace_old_param 7.35% : 0.000029s : 4: substitution.reshape_eliminate 2.67% : 0.000010s : 6: substitution.updatestate_pure_node_eliminater 27.53% : 0.000107s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.548880 2 99.72% : 1.544527s : 1: type_inference.infer 0.28% : 0.004353s : 1: type_inference.specialize ------[replace.] 0.000019 1 100.00% : 0.000019s : 1: replace.inline ------[match.] 0.000125 1 100.00% : 0.000125s : 1: match.inline ------[predicate.] 0.000578 4131 0.78% : 0.000005s : 37: predicate.accumulaten_eliminater 0.91% : 0.000005s : 18: predicate.ad_related_special_op_eliminate 0.89% : 0.000005s : 36: predicate.addn_check_dump 0.83% : 0.000005s : 37: predicate.addn_zero_filter 0.72% : 0.000004s : 37: predicate.adjust_all_reduce_mul_add 2.21% : 0.000013s : 73: predicate.arithmetic_simplify 0.84% : 0.000005s : 37: predicate.cast_eliminate 0.82% : 0.000005s : 36: predicate.check_bprop_eliminate 0.80% : 0.000005s : 36: predicate.compare_switch_simplify 0.24% : 0.000001s : 18: predicate.const_output_eliminate 0.86% : 0.000005s : 36: predicate.depend_value_elim 0.89% : 0.000005s : 37: predicate.dict_get_item_const_eliminator 1.01% : 0.000006s : 37: predicate.dict_get_item_eliminator 0.76% : 0.000004s : 37: predicate.dict_set_item_eliminator 1.16% : 0.000007s : 36: predicate.dumpgradient_eliminate 0.42% : 0.000002s : 18: predicate.elim_not_effective 0.63% : 0.000004s : 18: predicate.elim_shapecalc_of_broadcastargs 1.18% : 0.000007s : 55: predicate.environ_add_const_eliminate 1.15% : 0.000007s : 55: predicate.environ_get_add_eliminate 1.10% : 0.000006s : 55: predicate.environ_get_depend_swap 1.98% : 0.000011s : 91: predicate.environ_get_eliminate 1.11% : 0.000006s : 55: predicate.environ_get_set_eliminate 0.81% : 0.000005s : 38: predicate.exchange_switch_depend_value 1.25% : 0.000007s : 38: predicate.float_depend_g_call 0.82% : 0.000005s : 36: predicate.float_environ_get_switch 1.18% : 0.000007s : 54: predicate.float_tuple_getitem_switch 0.27% : 0.000002s : 18: predicate.fold_const_symbol 0.86% : 0.000005s : 36: predicate.get_grad_eliminate 0.28% : 0.000002s : 18: predicate.graph_param_transform 0.82% : 0.000005s : 36: predicate.incorporate_call 0.76% : 0.000004s : 36: predicate.incorporate_call_switch 5.26% : 0.000030s : 183: predicate.inline 1.01% : 0.000006s : 36: predicate.inline_without_move 0.46% : 0.000003s : 36: predicate.j_node_and_user_rematch 1.01% : 0.000006s : 36: predicate.less_batch_normalization 1.72% : 0.000010s : 73: predicate.list_to_tuple_eliminator_ 2.40% : 0.000014s : 110: predicate.load_eliminater 0.89% : 0.000005s : 18: predicate.loop_unroll_after_grad 0.96% : 0.000006s : 41: predicate.loop_unroll_before_grad 1.72% : 0.000010s : 73: predicate.make_slice_get_slice_eliminator 0.94% : 0.000005s : 36: predicate.merge_addn 0.80% : 0.000005s : 36: predicate.micro_step_allgather_replace 0.81% : 0.000005s : 36: predicate.mini_step_allgather_replace 0.75% : 0.000004s : 37: predicate.minmaximum_grad 1.09% : 0.000006s : 18: predicate.mutable_eliminate 0.54% : 0.000003s : 18: predicate.opt_reshape 0.46% : 0.000003s : 18: predicate.parallel_virtual_node 0.97% : 0.000006s : 38: predicate.partial_defer_inline 1.50% : 0.000009s : 55: predicate.partial_eliminate 0.76% : 0.000004s : 37: predicate.print_const_string_wrapper 0.83% : 0.000005s : 36: predicate.reduce_all_const_elim 1.04% : 0.000006s : 37: predicate.reduce_eliminate 2.89% : 0.000017s : 110: predicate.redundant_stop_gradient_eliminater 0.58% : 0.000003s : 36: predicate.remove_not_recompute_node 1.46% : 0.000008s : 73: predicate.replace_applicator 0.56% : 0.000003s : 36: predicate.replace_old_param 0.33% : 0.000002s : 18: predicate.reset_defer_inline 0.91% : 0.000005s : 37: predicate.reshape_eliminate 0.84% : 0.000005s : 36: predicate.row_tensor_add_zeros_like 0.56% : 0.000003s : 18: predicate.row_tensor_eliminate 1.09% : 0.000006s : 36: predicate.same_eliminate 0.53% : 0.000003s : 36: predicate.set_cell_output_no_recompute 0.96% : 0.000006s : 36: predicate.shard_identity_eliminate 0.91% : 0.000005s : 36: predicate.special_op_eliminate 0.95% : 0.000006s : 36: predicate.specialize_transform 1.08% : 0.000006s : 36: predicate.split_environ_get_set_with_tuple_value 1.07% : 0.000006s : 36: predicate.stack_unstack_eliminate 0.45% : 0.000003s : 18: predicate.switch_call_monad_eliminater 0.82% : 0.000005s : 38: predicate.switch_defer_inline 1.62% : 0.000009s : 74: predicate.switch_layer_defer_inline 3.34% : 0.000019s : 133: predicate.switch_simplify 0.79% : 0.000005s : 37: predicate.tile_eliminate 0.77% : 0.000004s : 37: predicate.transpose_eliminate 1.76% : 0.000010s : 73: predicate.tuple_list_convert_item_index_to_positive 1.67% : 0.000010s : 73: predicate.tuple_list_get_item_const_eliminator 1.63% : 0.000009s : 73: predicate.tuple_list_get_item_depend_reorder 3.16% : 0.000018s : 109: predicate.tuple_list_get_item_eliminator 1.83% : 0.000011s : 73: predicate.tuple_list_get_set_item_eliminator 2.78% : 0.000016s : 109: predicate.tuple_list_set_item_eliminator 1.63% : 0.000009s : 73: predicate.tuple_to_list_eliminator_ 2.27% : 0.000013s : 110: predicate.updatestate_pure_node_eliminater 3.39% : 0.000020s : 146: predicate.updatestate_useless_node_eliminater 0.45% : 0.000003s : 18: predicate.value_based_eliminate 0.87% : 0.000005s : 36: predicate.virtual_dataset_eliminate 0.89% : 0.000005s : 36: predicate.virtual_output_eliminate 0.47% : 0.000003s : 18: predicate.virtual_view_grad_eliminate 0.46% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.090960 58 97.04% : 0.088270s : 55: func_graph_cloner_run.FuncGraphClonerGraph 2.96% : 0.002689s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.107489 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.30% : 0.006381s : 1: add_attr 0.30% : 0.006362s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000141s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.02% : 0.000358s : 1: auto_monad 0.00% : 0.000076s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.03% : 0.000626s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000039s : 1: control_data_broadcast_order 0.00% : 0.000027s : 1: convert_after_rewriter 0.00% : 0.000080s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000026s : 1: environ_conv 0.00% : 0.000029s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000006s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000005s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000010s : 1: label_micro_interleaved_index 0.02% : 0.000521s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.04% : 0.000818s : 1: mutable_eliminate 0.00% : 0.000013s : 1: offloading_packed_experts 0.00% : 0.000035s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000042s : 1: opt.transform.mutable_eliminate 7.95% : 0.167452s : 78: opt.transform.opt_a 0.01% : 0.000135s : 1: opt.transform.opt_after_cconv 0.00% : 0.000085s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000475s : 28: opt.transform.opt_b 0.01% : 0.000183s : 2: opt.transform.opt_trans_graph 0.01% : 0.000140s : 4: opt.transform.symbol_engine_opt 8.49% : 0.178931s : 1: opt_a 0.01% : 0.000297s : 1: opt_after_cconv 0.04% : 0.000783s : 1: opt_after_jit_grad 0.03% : 0.000689s : 1: opt_b 8.69% : 0.183039s : 1: optimize 0.00% : 0.000038s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000054s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 1: overlap_grad_ring_attention 0.00% : 0.000004s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000007s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000043s : 1: pre_auto_parallel 0.00% : 0.000037s : 1: py_interpret_to_execute 0.00% : 0.000036s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000143s : 1: remove_dup_value 0.29% : 0.006065s : 1: renormalize.infer 0.15% : 0.003119s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000227s : 1: rewriter_after_opt_a 0.01% : 0.000106s : 1: rewriter_before_opt_a 0.00% : 0.000005s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000020s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000215s : 1: symbol_engine_optimizer 0.01% : 0.000273s : 1: tuple_transform 73.50% : 1.549022s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_0[False-k_n_shape0-16] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_0[False-k_n_shape0-16],max_mem:110.0M [WARNING] ME(164923:281473602678576,MainProcess):2026-01-29-17:38:04.311.200 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 1.71116, [21] [bootstrap]: 0.00062921 [type_inference]: 1.5941 [event_method]: 2.004e-05 [auto_monad]: 0.00041365 [graph_reusing]: 7.48999e-06 [inline]: 3.46001e-06 [add_attr]: 0.00721963, [1] [add_attr_with_inline]: 0.00719727, [1] [Cycle 1]: 7.948e-05, [2] [tag_attr]: 2.691e-05 [meta_addattr_fg_expand]: 4.82e-06 [parallel-infer-symbol]: 3.50998e-06 [pre_auto_parallel]: 4.059e-05 [insert-virtual-dataset]: 2.46998e-06 [parallel-infer-symbol-second]: 6.50005e-07 [dataset_repeat_opt]: 2.09e-06 [pipeline_split]: 1.75001e-06 [optimize]: 0.107592, [53] [py_interpret_to_execute]: 5.493e-05 [rewriter_before_opt_a]: 0.00011516 [opt_a]: 0.103274, [2] [Cycle 1]: 0.101089, [45] [expand_dump_flag]: 3.22002e-06 [switch_simplify]: 4.527e-05 [loop_unroll]: 2.828e-05 [a_1]: 0.0010357 [with_stream_mark]: 3.768e-05 [recompute_prepare]: 3.797e-05 [updatestate_depend_eliminate]: 1.512e-05 [updatestate_assign_eliminate]: 1.444e-05 [updatestate_loads_eliminate]: 1.92e-05 [parameter_eliminate]: 2.39001e-06 [a_2]: 0.0003498 [accelerated_algorithm]: 5.471e-05 [shard]: 2.99999e-06 [meta_shard_fg_expand]: 4.71002e-06 [shard_inline]: 2.311e-05 [merge_send_recv]: 1.864e-05 [auto_parallel]: 1.87e-05 [parallel]: 3.873e-05 [flash_sp]: 1.539e-05 [merge_comm]: 1.273e-05 [allreduce_fusion]: 1.082e-05 [matmul_add_comm_reduction]: 2.168e-05 [allreduce_slice_to_reducescatter]: 8.2e-07 [virtual_shard_identity]: 2.991e-05 [virtual_dataset]: 2.372e-05 [get_grad_eliminate_]: 2.42e-05 [virtual_output]: 2.309e-05 [merge_forward]: 1.389e-05 [cell_reuse_recompute_pass]: 2.69001e-06 [offload_activation]: 2.375e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.575e-05 [merge_recompute_call_nodes]: 2.17999e-06 [before_grad]: 3.835e-05 [set_forward_comm_id_for_comm_node_pass]: 1.275e-05 [meta_fg_expand]: 7.82998e-06 [flash_sp_send_recv_attached]: 6.81001e-06 [receive_attached]: 2.71e-06 [after_resolve]: 3.518e-05 [a_after_grad]: 4.077e-05 [renormalize]: 0.0968699 [add_forward_monad_depend]: 1.227e-05 [auto_monad_grad]: 3.14999e-06 [auto_monad_eliminator]: 7.302e-05 [cse]: 0.0013938 [a_3]: 0.00018219 [Cycle 2]: 0.00216755, [45] [expand_dump_flag]: 4.08001e-06 [switch_simplify]: 2.703e-05 [loop_unroll]: 2.592e-05 [a_1]: 0.00064852 [with_stream_mark]: 3.892e-05 [recompute_prepare]: 2.57e-05 [updatestate_depend_eliminate]: 1.59e-05 [updatestate_assign_eliminate]: 1.129e-05 [updatestate_loads_eliminate]: 1.894e-05 [parameter_eliminate]: 3.30998e-06 [a_2]: 0.00030489 [accelerated_algorithm]: 3.039e-05 [shard]: 2.41998e-06 [meta_shard_fg_expand]: 8.22998e-06 [shard_inline]: 2.174e-05 [merge_send_recv]: 1.886e-05 [auto_parallel]: 1.835e-05 [parallel]: 1.352e-05 [flash_sp]: 5.45001e-06 [merge_comm]: 1.126e-05 [allreduce_fusion]: 1.033e-05 [matmul_add_comm_reduction]: 2.253e-05 [allreduce_slice_to_reducescatter]: 9.20001e-07 [virtual_shard_identity]: 2.73e-05 [virtual_dataset]: 2.052e-05 [get_grad_eliminate_]: 2.072e-05 [virtual_output]: 2.237e-05 [merge_forward]: 1.248e-05 [cell_reuse_recompute_pass]: 3.10998e-06 [offload_activation]: 2.066e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.395e-05 [merge_recompute_call_nodes]: 1.90001e-06 [before_grad]: 3.393e-05 [set_forward_comm_id_for_comm_node_pass]: 1.17e-05 [meta_fg_expand]: 9.37001e-06 [flash_sp_send_recv_attached]: 1.99e-06 [receive_attached]: 2.59999e-06 [after_resolve]: 3.136e-05 [a_after_grad]: 3.31e-05 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 4.95999e-06 [auto_monad_grad]: 2.94999e-06 [auto_monad_eliminator]: 7.42e-05 [cse]: 8.944e-05 [a_3]: 0.00014027 [py_interpret_to_execute_after_opt_a]: 3.762e-05 [slice_cell_reuse_recomputed_activation]: 2.93e-06 [rewriter_after_opt_a]: 0.00024987 [convert_after_rewriter]: 2.118e-05 [order_py_execute_after_rewriter]: 1.153e-05 [mutable_eliminate]: 0.00087664 [opt_b]: 0.00081474, [1] [Cycle 1]: 0.00080522, [7] [b_1]: 0.00057828 [b_2]: 2.706e-05 [updatestate_depend_eliminate]: 2.071e-05 [updatestate_assign_eliminate]: 1.107e-05 [updatestate_loads_eliminate]: 1.581e-05 [renormalize]: 5.00004e-07 [cse]: 0.00010242 [optimize_parallel_all_gather_comm]: 4.093e-05 [overlap_param_gather]: 2.80002e-06 [cconv]: 4.136e-05 [loop_unroll]: 0.00058345 [opt_after_cconv]: 0.00029783, [1] [Cycle 1]: 0.00029157, [7] [c_1]: 0.00013894 [parameter_eliminate]: 5.16998e-06 [updatestate_depend_eliminate]: 1.478e-05 [updatestate_assign_eliminate]: 9.62999e-06 [updatestate_loads_eliminate]: 1.318e-05 [cse]: 7.163e-05 [renormalize]: 3.39991e-07 [remove_dup_value]: 9.353e-05 [tuple_transform]: 0.00020405, [1] [Cycle 1]: 0.00019868, [4] [d_1]: 0.00015238 [none_parameter_eliminate]: 2.31998e-06 [renormalize]: 1.50001e-07 [switch_simplify]: 2.178e-05 [partial_unused_args_eliminate]: 2.11e-06 [add_recomputation]: 0.00013427 [cse_after_recomputation]: 6.568e-05, [1] [Cycle 1]: 5.951e-05, [1] [cse]: 5.173e-05 [environ_conv]: 2.121e-05 [swap_dp_allreduce_reducescatter]: 1.449e-05 [bias_add_comm_swap]: 3.83999e-06 [label_micro_interleaved_index]: 5.77001e-06 [label_fine_grained_interleaved_index]: 2.89999e-06 [merge_cast_opt]: 1.47001e-06 [slice_recompute_activation]: 2.12001e-06 [micro_interleaved_order_control]: 2.29999e-06 [assign_add_opt]: 1.91998e-06 [ForceFp32Comm]: 9.20001e-07 [remove_cast_before_assign_add]: 1.07e-06 [full_micro_interleaved_order_control]: 2.91999e-06 [reorder_send_recv_between_fp_bp]: 3.04999e-06 [comm_op_add_attrs]: 1.17999e-06 [add_comm_op_reuse_tag]: 9.79984e-07 [interleave_split_concat_branches]: 1.32e-06 [interleave_parallel_branches]: 1.47999e-06 [overlap_opt_shard_in_pipeline]: 1.59e-06 [overlap_opt_shard_grad_in_pipeline]: 2.32999e-06 [control_data_broadcast_order]: 3.375e-05 [grouped_pairwise_exchange_alltoall]: 2.26e-06 [offloading_packed_experts]: 8.83001e-06 [overlap_recompute_and_grad_model_parallel]: 9.57999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.28002e-06 [overlap_recompute_allgather_and_fa_grad]: 1.44003e-06 [overlap_recompute_comm]: 2.24001e-06 [overlap_grad_ring_attention]: 9.22001e-06 [overlap_grad_flash_sp]: 5.017e-05 [begin_end_overlap_inline]: 5.49975e-07 [split_matmul_comm_elemetwise]: 2.22999e-06 [split_layernorm_comm]: 1.86e-06 [handle_group_info]: 9.79984e-07 [symbol_engine_optimizer]: 0.00018382, [1] [Cycle 1]: 0.00017722, [6] [build]: 1.804e-05 [elim_shapecalc]: 2.918e-05 [elim_not_effective]: 3.7e-05 [opt_reshape]: 2.671e-05 [fold_const_symbol]: 3.267e-05 [renormalize]: 2.10013e-07 [detach_backward]: 2.21998e-06 [pipeline_parallel_scheduler]: 1.40001e-06 [auto_monad_reorder]: 6.979e-05 [get_jit_bprop_graph]: 2.00002e-06 [rewriter_after_jit_bprop_graph]: 7.59002e-06 [opt_after_jit_grad]: 0.00072244 [validate]: 0.00010546 Sums bootstrap : 0.000629s : 0.04% type_inference : 1.594097s : 93.63% event_method : 0.000020s : 0.00% auto_monad : 0.000414s : 0.02% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000027s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000041s : 0.00% 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 : 0.000055s : 0.00% optimize.rewriter_before_opt_a : 0.000115s : 0.01% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000072s : 0.00% optimize.opt_a.loop_unroll : 0.000054s : 0.00% optimize.opt_a.a_1 : 0.001684s : 0.10% optimize.opt_a.with_stream_mark : 0.000077s : 0.00% optimize.opt_a.recompute_prepare : 0.000064s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000031s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000026s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000038s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000655s : 0.04% optimize.opt_a.accelerated_algorithm : 0.000085s : 0.00% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.00% optimize.opt_a.shard_inline : 0.000045s : 0.00% optimize.opt_a.merge_send_recv : 0.000037s : 0.00% optimize.opt_a.auto_parallel : 0.000037s : 0.00% optimize.opt_a.parallel : 0.000052s : 0.00% optimize.opt_a.flash_sp : 0.000021s : 0.00% optimize.opt_a.merge_comm : 0.000024s : 0.00% optimize.opt_a.allreduce_fusion : 0.000021s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000044s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000057s : 0.00% optimize.opt_a.virtual_dataset : 0.000044s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000045s : 0.00% optimize.opt_a.virtual_output : 0.000045s : 0.00% optimize.opt_a.merge_forward : 0.000026s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000044s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000090s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000072s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000024s : 0.00% optimize.opt_a.meta_fg_expand : 0.000017s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000009s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000067s : 0.00% optimize.opt_a.a_after_grad : 0.000074s : 0.00% optimize.opt_a.renormalize : 0.096870s : 5.69% optimize.opt_a.add_forward_monad_depend : 0.000017s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000147s : 0.01% optimize.opt_a.cse : 0.001483s : 0.09% optimize.opt_a.a_3 : 0.000322s : 0.02% optimize.py_interpret_to_execute_after_opt_a : 0.000038s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000250s : 0.01% optimize.convert_after_rewriter : 0.000021s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000877s : 0.05% optimize.opt_b.b_1 : 0.000578s : 0.03% optimize.opt_b.b_2 : 0.000027s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000021s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000016s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000102s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000041s : 0.00% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000041s : 0.00% optimize.loop_unroll : 0.000583s : 0.03% optimize.opt_after_cconv.c_1 : 0.000139s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000015s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000013s : 0.00% optimize.opt_after_cconv.cse : 0.000072s : 0.00% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000094s : 0.01% optimize.tuple_transform.d_1 : 0.000152s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000022s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000134s : 0.01% optimize.cse_after_recomputation.cse : 0.000052s : 0.00% optimize.environ_conv : 0.000021s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000014s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000002s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000002s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000034s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000009s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000050s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000018s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000029s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000037s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000027s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000033s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000001s : 0.00% auto_monad_reorder : 0.000070s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000722s : 0.04% validate : 0.000105s : 0.01% Time group info: ------[substitution.] 0.000411 135 2.63% : 0.000011s : 2: substitution.depend_value_elim 1.19% : 0.000005s : 11: substitution.elim_not_effective 0.96% : 0.000004s : 11: substitution.fold_const_symbol 3.61% : 0.000015s : 18: substitution.graph_param_transform 34.68% : 0.000143s : 1: substitution.inline 2.88% : 0.000012s : 22: substitution.j_node_and_user_rematch 6.57% : 0.000027s : 2: substitution.less_batch_normalization 2.66% : 0.000011s : 18: substitution.load_eliminater 0.63% : 0.000003s : 2: substitution.opt_reshape 4.28% : 0.000018s : 22: substitution.remove_not_recompute_node 2.36% : 0.000010s : 8: substitution.replace_old_param 7.77% : 0.000032s : 4: substitution.reshape_eliminate 2.63% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 27.15% : 0.000112s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.593974 2 99.69% : 1.589086s : 1: type_inference.infer 0.31% : 0.004888s : 1: type_inference.specialize ------[replace.] 0.000021 1 100.00% : 0.000021s : 1: replace.inline ------[match.] 0.000141 1 100.00% : 0.000141s : 1: match.inline ------[predicate.] 0.000660 4131 0.87% : 0.000006s : 37: predicate.accumulaten_eliminater 0.71% : 0.000005s : 18: predicate.ad_related_special_op_eliminate 0.70% : 0.000005s : 36: predicate.addn_check_dump 0.70% : 0.000005s : 37: predicate.addn_zero_filter 0.72% : 0.000005s : 37: predicate.adjust_all_reduce_mul_add 1.99% : 0.000013s : 73: predicate.arithmetic_simplify 0.87% : 0.000006s : 37: predicate.cast_eliminate 0.71% : 0.000005s : 36: predicate.check_bprop_eliminate 0.72% : 0.000005s : 36: predicate.compare_switch_simplify 0.23% : 0.000001s : 18: predicate.const_output_eliminate 0.81% : 0.000005s : 36: predicate.depend_value_elim 0.91% : 0.000006s : 37: predicate.dict_get_item_const_eliminator 0.95% : 0.000006s : 37: predicate.dict_get_item_eliminator 0.78% : 0.000005s : 37: predicate.dict_set_item_eliminator 0.89% : 0.000006s : 36: predicate.dumpgradient_eliminate 0.25% : 0.000002s : 18: predicate.elim_not_effective 0.46% : 0.000003s : 18: predicate.elim_shapecalc_of_broadcastargs 1.15% : 0.000008s : 55: predicate.environ_add_const_eliminate 1.08% : 0.000007s : 55: predicate.environ_get_add_eliminate 1.13% : 0.000007s : 55: predicate.environ_get_depend_swap 1.83% : 0.000012s : 91: predicate.environ_get_eliminate 9.82% : 0.000065s : 55: predicate.environ_get_set_eliminate 0.74% : 0.000005s : 38: predicate.exchange_switch_depend_value 1.08% : 0.000007s : 38: predicate.float_depend_g_call 0.70% : 0.000005s : 36: predicate.float_environ_get_switch 1.07% : 0.000007s : 54: predicate.float_tuple_getitem_switch 0.20% : 0.000001s : 18: predicate.fold_const_symbol 0.90% : 0.000006s : 36: predicate.get_grad_eliminate 0.23% : 0.000001s : 18: predicate.graph_param_transform 0.75% : 0.000005s : 36: predicate.incorporate_call 0.65% : 0.000004s : 36: predicate.incorporate_call_switch 4.97% : 0.000033s : 183: predicate.inline 0.94% : 0.000006s : 36: predicate.inline_without_move 0.42% : 0.000003s : 36: predicate.j_node_and_user_rematch 1.08% : 0.000007s : 36: predicate.less_batch_normalization 1.50% : 0.000010s : 73: predicate.list_to_tuple_eliminator_ 2.23% : 0.000015s : 110: predicate.load_eliminater 0.69% : 0.000005s : 18: predicate.loop_unroll_after_grad 0.93% : 0.000006s : 41: predicate.loop_unroll_before_grad 1.65% : 0.000011s : 73: predicate.make_slice_get_slice_eliminator 0.69% : 0.000005s : 36: predicate.merge_addn 0.71% : 0.000005s : 36: predicate.micro_step_allgather_replace 0.69% : 0.000005s : 36: predicate.mini_step_allgather_replace 0.73% : 0.000005s : 37: predicate.minmaximum_grad 1.17% : 0.000008s : 18: predicate.mutable_eliminate 0.45% : 0.000003s : 18: predicate.opt_reshape 0.40% : 0.000003s : 18: predicate.parallel_virtual_node 1.01% : 0.000007s : 38: predicate.partial_defer_inline 1.20% : 0.000008s : 55: predicate.partial_eliminate 0.86% : 0.000006s : 37: predicate.print_const_string_wrapper 0.71% : 0.000005s : 36: predicate.reduce_all_const_elim 1.07% : 0.000007s : 37: predicate.reduce_eliminate 2.10% : 0.000014s : 110: predicate.redundant_stop_gradient_eliminater 0.48% : 0.000003s : 36: predicate.remove_not_recompute_node 1.30% : 0.000009s : 73: predicate.replace_applicator 0.54% : 0.000004s : 36: predicate.replace_old_param 0.32% : 0.000002s : 18: predicate.reset_defer_inline 0.84% : 0.000006s : 37: predicate.reshape_eliminate 0.77% : 0.000005s : 36: predicate.row_tensor_add_zeros_like 0.43% : 0.000003s : 18: predicate.row_tensor_eliminate 1.12% : 0.000007s : 36: predicate.same_eliminate 0.49% : 0.000003s : 36: predicate.set_cell_output_no_recompute 0.83% : 0.000005s : 36: predicate.shard_identity_eliminate 0.83% : 0.000006s : 36: predicate.special_op_eliminate 0.88% : 0.000006s : 36: predicate.specialize_transform 1.13% : 0.000007s : 36: predicate.split_environ_get_set_with_tuple_value 0.88% : 0.000006s : 36: predicate.stack_unstack_eliminate 0.40% : 0.000003s : 18: predicate.switch_call_monad_eliminater 0.78% : 0.000005s : 38: predicate.switch_defer_inline 1.49% : 0.000010s : 74: predicate.switch_layer_defer_inline 3.01% : 0.000020s : 133: predicate.switch_simplify 0.74% : 0.000005s : 37: predicate.tile_eliminate 0.79% : 0.000005s : 37: predicate.transpose_eliminate 1.72% : 0.000011s : 73: predicate.tuple_list_convert_item_index_to_positive 1.55% : 0.000010s : 73: predicate.tuple_list_get_item_const_eliminator 1.55% : 0.000010s : 73: predicate.tuple_list_get_item_depend_reorder 2.62% : 0.000017s : 109: predicate.tuple_list_get_item_eliminator 1.66% : 0.000011s : 73: predicate.tuple_list_get_set_item_eliminator 2.48% : 0.000016s : 109: predicate.tuple_list_set_item_eliminator 1.51% : 0.000010s : 73: predicate.tuple_to_list_eliminator_ 2.13% : 0.000014s : 110: predicate.updatestate_pure_node_eliminater 3.08% : 0.000020s : 146: predicate.updatestate_useless_node_eliminater 0.44% : 0.000003s : 18: predicate.value_based_eliminate 0.87% : 0.000006s : 36: predicate.virtual_dataset_eliminate 0.78% : 0.000005s : 36: predicate.virtual_output_eliminate 0.38% : 0.000002s : 18: predicate.virtual_view_grad_eliminate 0.43% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.013059 58 70.93% : 0.009263s : 55: func_graph_cloner_run.FuncGraphClonerGraph 29.07% : 0.003796s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.927074 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.38% : 0.007228s : 1: add_attr 0.37% : 0.007202s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000139s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.02% : 0.000427s : 1: auto_monad 0.00% : 0.000076s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.03% : 0.000664s : 1: bootstrap 0.00% : 0.000045s : 1: cconv 0.00% : 0.000006s : 1: comm_op_add_attrs 0.00% : 0.000038s : 1: control_data_broadcast_order 0.00% : 0.000026s : 1: convert_after_rewriter 0.00% : 0.000069s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000026s : 1: environ_conv 0.00% : 0.000029s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000006s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000009s : 1: label_micro_interleaved_index 0.03% : 0.000593s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.05% : 0.000893s : 1: mutable_eliminate 0.00% : 0.000012s : 1: offloading_packed_experts 0.00% : 0.000035s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000046s : 1: opt.transform.mutable_eliminate 0.17% : 0.003344s : 78: opt.transform.opt_a 0.01% : 0.000137s : 1: opt.transform.opt_after_cconv 0.00% : 0.000078s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000564s : 28: opt.transform.opt_b 0.01% : 0.000171s : 2: opt.transform.opt_trans_graph 0.01% : 0.000121s : 4: opt.transform.symbol_engine_opt 5.36% : 0.103279s : 1: opt_a 0.02% : 0.000302s : 1: opt_after_cconv 0.04% : 0.000738s : 1: opt_after_jit_grad 0.04% : 0.000819s : 1: opt_b 5.58% : 0.107598s : 1: optimize 0.00% : 0.000045s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.00% : 0.000054s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000012s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000004s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000006s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000007s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000045s : 1: pre_auto_parallel 0.00% : 0.000061s : 1: py_interpret_to_execute 0.00% : 0.000043s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000098s : 1: remove_dup_value 4.80% : 0.092502s : 1: renormalize.infer 0.23% : 0.004346s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000261s : 1: rewriter_after_opt_a 0.01% : 0.000121s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000018s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000187s : 1: symbol_engine_optimizer 0.01% : 0.000207s : 1: tuple_transform 82.72% : 1.594130s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_0[False-k_n_shape1-1] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_0[False-k_n_shape1-1],max_mem:120.0M [WARNING] ME(164923:281473602678576,MainProcess):2026-01-29-17:38:10.968.651 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 2.92304, [21] [bootstrap]: 0.00061843 [type_inference]: 2.74704 [event_method]: 2.319e-05 [auto_monad]: 0.00040056 [graph_reusing]: 7.16999e-06 [inline]: 3.13998e-06 [add_attr]: 0.00666498, [1] [add_attr_with_inline]: 0.00664653, [1] [Cycle 1]: 8.103e-05, [2] [tag_attr]: 2.602e-05 [meta_addattr_fg_expand]: 4.94e-06 [parallel-infer-symbol]: 3.68e-06 [pre_auto_parallel]: 4.037e-05 [insert-virtual-dataset]: 2.96999e-06 [parallel-infer-symbol-second]: 9.39996e-07 [dataset_repeat_opt]: 1.67001e-06 [pipeline_split]: 1.97001e-06 [optimize]: 0.167068, [53] [py_interpret_to_execute]: 3.408e-05 [rewriter_before_opt_a]: 0.00010046 [opt_a]: 0.162706, [2] [Cycle 1]: 0.146763, [45] [expand_dump_flag]: 2.74999e-06 [switch_simplify]: 4.085e-05 [loop_unroll]: 2.473e-05 [a_1]: 0.00100297 [with_stream_mark]: 3.223e-05 [recompute_prepare]: 3.298e-05 [updatestate_depend_eliminate]: 1.32e-05 [updatestate_assign_eliminate]: 1.166e-05 [updatestate_loads_eliminate]: 1.901e-05 [parameter_eliminate]: 2.79999e-06 [a_2]: 0.00035627 [accelerated_algorithm]: 6.587e-05 [shard]: 2.47001e-06 [meta_shard_fg_expand]: 4.86002e-06 [shard_inline]: 2.493e-05 [merge_send_recv]: 1.817e-05 [auto_parallel]: 1.838e-05 [parallel]: 3.558e-05 [flash_sp]: 1.495e-05 [merge_comm]: 1.322e-05 [allreduce_fusion]: 1.132e-05 [matmul_add_comm_reduction]: 2.409e-05 [allreduce_slice_to_reducescatter]: 6.89994e-07 [virtual_shard_identity]: 3.064e-05 [virtual_dataset]: 2.67e-05 [get_grad_eliminate_]: 2.292e-05 [virtual_output]: 2.34e-05 [merge_forward]: 1.336e-05 [cell_reuse_recompute_pass]: 2.53e-06 [offload_activation]: 2.362e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.11e-05 [merge_recompute_call_nodes]: 1.55999e-06 [before_grad]: 3.942e-05 [set_forward_comm_id_for_comm_node_pass]: 1.359e-05 [meta_fg_expand]: 7.30998e-06 [flash_sp_send_recv_attached]: 6.71e-06 [receive_attached]: 2.44999e-06 [after_resolve]: 3.592e-05 [a_after_grad]: 3.903e-05 [renormalize]: 0.142927 [add_forward_monad_depend]: 1.354e-05 [auto_monad_grad]: 3.25e-06 [auto_monad_eliminator]: 7.264e-05 [cse]: 0.00107899 [a_3]: 0.0001838 [Cycle 2]: 0.0159253, [45] [expand_dump_flag]: 3.48999e-06 [switch_simplify]: 2.568e-05 [loop_unroll]: 2.325e-05 [a_1]: 0.0006371 [with_stream_mark]: 3.518e-05 [recompute_prepare]: 0.00095949 [updatestate_depend_eliminate]: 0.0001571 [updatestate_assign_eliminate]: 8.682e-05 [updatestate_loads_eliminate]: 0.00015211 [parameter_eliminate]: 2.565e-05 [a_2]: 0.00305682 [accelerated_algorithm]: 0.00840107 [shard]: 5.82999e-06 [meta_shard_fg_expand]: 1.419e-05 [shard_inline]: 3.706e-05 [merge_send_recv]: 3.096e-05 [auto_parallel]: 2.269e-05 [parallel]: 1.151e-05 [flash_sp]: 6.69999e-06 [merge_comm]: 1.153e-05 [allreduce_fusion]: 1.036e-05 [matmul_add_comm_reduction]: 2.406e-05 [allreduce_slice_to_reducescatter]: 8.70001e-07 [virtual_shard_identity]: 2.661e-05 [virtual_dataset]: 2.351e-05 [get_grad_eliminate_]: 2.18e-05 [virtual_output]: 2.47e-05 [merge_forward]: 1.251e-05 [cell_reuse_recompute_pass]: 3.55e-06 [offload_activation]: 2.27e-05 [cell_reuse_handle_not_recompute_node_pass]: 0.00053527 [merge_recompute_call_nodes]: 2.93e-06 [before_grad]: 4.515e-05 [set_forward_comm_id_for_comm_node_pass]: 1.964e-05 [meta_fg_expand]: 1.054e-05 [flash_sp_send_recv_attached]: 2.18002e-06 [receive_attached]: 3.11999e-06 [after_resolve]: 4.01e-05 [a_after_grad]: 3.574e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 7.6e-06 [auto_monad_grad]: 3.31001e-06 [auto_monad_eliminator]: 8.641e-05 [cse]: 0.00010399 [a_3]: 0.00014628 [py_interpret_to_execute_after_opt_a]: 3.717e-05 [slice_cell_reuse_recomputed_activation]: 2.26e-06 [rewriter_after_opt_a]: 0.00023331 [convert_after_rewriter]: 1.977e-05 [order_py_execute_after_rewriter]: 1.214e-05 [mutable_eliminate]: 0.00082436 [opt_b]: 0.00078675, [1] [Cycle 1]: 0.00077623, [7] [b_1]: 0.00055538 [b_2]: 2.628e-05 [updatestate_depend_eliminate]: 1.983e-05 [updatestate_assign_eliminate]: 1.16e-05 [updatestate_loads_eliminate]: 1.786e-05 [renormalize]: 7.7e-07 [cse]: 9.612e-05 [optimize_parallel_all_gather_comm]: 4.222e-05 [overlap_param_gather]: 2.12001e-06 [cconv]: 4.624e-05 [loop_unroll]: 0.00063798 [opt_after_cconv]: 0.00039388, [1] [Cycle 1]: 0.00038428, [7] [c_1]: 0.00014781 [parameter_eliminate]: 5.71003e-06 [updatestate_depend_eliminate]: 1.641e-05 [updatestate_assign_eliminate]: 1.048e-05 [updatestate_loads_eliminate]: 1.59e-05 [cse]: 0.00014288 [renormalize]: 7.29982e-07 [remove_dup_value]: 9.45e-05 [tuple_transform]: 0.00021146, [1] [Cycle 1]: 0.00020514, [4] [d_1]: 0.00015792 [none_parameter_eliminate]: 2.49001e-06 [renormalize]: 2.79979e-07 [switch_simplify]: 2.26e-05 [partial_unused_args_eliminate]: 2.39001e-06 [add_recomputation]: 0.00013424 [cse_after_recomputation]: 6.986e-05, [1] [Cycle 1]: 6.283e-05, [1] [cse]: 5.481e-05 [environ_conv]: 2.206e-05 [swap_dp_allreduce_reducescatter]: 1.539e-05 [bias_add_comm_swap]: 3.36999e-06 [label_micro_interleaved_index]: 6.49999e-06 [label_fine_grained_interleaved_index]: 3.04001e-06 [merge_cast_opt]: 1.52999e-06 [slice_recompute_activation]: 2.53003e-06 [micro_interleaved_order_control]: 2.58e-06 [assign_add_opt]: 1.84e-06 [ForceFp32Comm]: 9.30013e-07 [remove_cast_before_assign_add]: 1.11002e-06 [full_micro_interleaved_order_control]: 2.76999e-06 [reorder_send_recv_between_fp_bp]: 2.99001e-06 [comm_op_add_attrs]: 1.20999e-06 [add_comm_op_reuse_tag]: 1.08001e-06 [interleave_split_concat_branches]: 1.35999e-06 [interleave_parallel_branches]: 1.13001e-06 [overlap_opt_shard_in_pipeline]: 1.66e-06 [overlap_opt_shard_grad_in_pipeline]: 1.97001e-06 [control_data_broadcast_order]: 3.611e-05 [grouped_pairwise_exchange_alltoall]: 1.76e-06 [offloading_packed_experts]: 9.41003e-06 [overlap_recompute_and_grad_model_parallel]: 9.94999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.34998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.40999e-06 [overlap_recompute_comm]: 2.48e-06 [overlap_grad_ring_attention]: 9.37001e-06 [overlap_grad_flash_sp]: 4.697e-05 [begin_end_overlap_inline]: 5.39992e-07 [split_matmul_comm_elemetwise]: 2.89999e-06 [split_layernorm_comm]: 1.74e-06 [handle_group_info]: 1.04e-06 [symbol_engine_optimizer]: 0.00018996, [1] [Cycle 1]: 0.00018388, [6] [build]: 2.08e-05 [elim_shapecalc]: 2.93e-05 [elim_not_effective]: 3.756e-05 [opt_reshape]: 2.762e-05 [fold_const_symbol]: 3.195e-05 [renormalize]: 1.80007e-07 [detach_backward]: 2.62001e-06 [pipeline_parallel_scheduler]: 1.51998e-06 [auto_monad_reorder]: 7.077e-05 [get_jit_bprop_graph]: 2.26e-06 [rewriter_after_jit_bprop_graph]: 6.63003e-06 [opt_after_jit_grad]: 0.00072649 [validate]: 0.00010937 Sums bootstrap : 0.000618s : 0.02% type_inference : 2.747041s : 94.26% event_method : 0.000023s : 0.00% auto_monad : 0.000401s : 0.01% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000026s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000040s : 0.00% 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 : 0.000034s : 0.00% optimize.rewriter_before_opt_a : 0.000100s : 0.00% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000067s : 0.00% optimize.opt_a.loop_unroll : 0.000048s : 0.00% optimize.opt_a.a_1 : 0.001640s : 0.06% optimize.opt_a.with_stream_mark : 0.000067s : 0.00% optimize.opt_a.recompute_prepare : 0.000992s : 0.03% optimize.opt_a.updatestate_depend_eliminate : 0.000170s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000098s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000171s : 0.01% optimize.opt_a.parameter_eliminate : 0.000028s : 0.00% optimize.opt_a.a_2 : 0.003413s : 0.12% optimize.opt_a.accelerated_algorithm : 0.008467s : 0.29% optimize.opt_a.shard : 0.000008s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000019s : 0.00% optimize.opt_a.shard_inline : 0.000062s : 0.00% optimize.opt_a.merge_send_recv : 0.000049s : 0.00% optimize.opt_a.auto_parallel : 0.000041s : 0.00% optimize.opt_a.parallel : 0.000047s : 0.00% optimize.opt_a.flash_sp : 0.000022s : 0.00% optimize.opt_a.merge_comm : 0.000025s : 0.00% optimize.opt_a.allreduce_fusion : 0.000022s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000048s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000057s : 0.00% optimize.opt_a.virtual_dataset : 0.000050s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000045s : 0.00% optimize.opt_a.virtual_output : 0.000048s : 0.00% optimize.opt_a.merge_forward : 0.000026s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000046s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000586s : 0.02% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000085s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000033s : 0.00% optimize.opt_a.meta_fg_expand : 0.000018s : 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 : 0.000076s : 0.00% optimize.opt_a.a_after_grad : 0.000075s : 0.00% optimize.opt_a.renormalize : 0.142927s : 4.90% optimize.opt_a.add_forward_monad_depend : 0.000021s : 0.00% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000159s : 0.01% optimize.opt_a.cse : 0.001183s : 0.04% optimize.opt_a.a_3 : 0.000330s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000037s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000233s : 0.01% optimize.convert_after_rewriter : 0.000020s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000824s : 0.03% optimize.opt_b.b_1 : 0.000555s : 0.02% optimize.opt_b.b_2 : 0.000026s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000020s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000012s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000018s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000096s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000042s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000046s : 0.00% optimize.loop_unroll : 0.000638s : 0.02% optimize.opt_after_cconv.c_1 : 0.000148s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000016s : 0.00% optimize.opt_after_cconv.cse : 0.000143s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000095s : 0.00% optimize.tuple_transform.d_1 : 0.000158s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000023s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000134s : 0.00% optimize.cse_after_recomputation.cse : 0.000055s : 0.00% optimize.environ_conv : 0.000022s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000015s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000002s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000036s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000009s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000047s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000021s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000029s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000038s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000028s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000032s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000071s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000726s : 0.02% validate : 0.000109s : 0.00% Time group info: ------[substitution.] 0.000555 135 5.00% : 0.000028s : 2: substitution.depend_value_elim 0.85% : 0.000005s : 11: substitution.elim_not_effective 0.77% : 0.000004s : 11: substitution.fold_const_symbol 2.70% : 0.000015s : 18: substitution.graph_param_transform 23.13% : 0.000128s : 1: substitution.inline 2.27% : 0.000013s : 22: substitution.j_node_and_user_rematch 9.48% : 0.000053s : 2: substitution.less_batch_normalization 2.01% : 0.000011s : 18: substitution.load_eliminater 0.55% : 0.000003s : 2: substitution.opt_reshape 4.30% : 0.000024s : 22: substitution.remove_not_recompute_node 2.26% : 0.000013s : 8: substitution.replace_old_param 5.80% : 0.000032s : 4: substitution.reshape_eliminate 1.97% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 38.91% : 0.000216s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.746907 2 99.83% : 2.742163s : 1: type_inference.infer 0.17% : 0.004744s : 1: type_inference.specialize ------[replace.] 0.000019 1 100.00% : 0.000019s : 1: replace.inline ------[match.] 0.000127 1 100.00% : 0.000127s : 1: match.inline ------[predicate.] 0.000921 4131 0.53% : 0.000005s : 37: predicate.accumulaten_eliminater 0.64% : 0.000006s : 18: predicate.ad_related_special_op_eliminate 2.39% : 0.000022s : 36: predicate.addn_check_dump 0.52% : 0.000005s : 37: predicate.addn_zero_filter 0.48% : 0.000004s : 37: predicate.adjust_all_reduce_mul_add 3.64% : 0.000034s : 73: predicate.arithmetic_simplify 0.57% : 0.000005s : 37: predicate.cast_eliminate 0.55% : 0.000005s : 36: predicate.check_bprop_eliminate 1.47% : 0.000014s : 36: predicate.compare_switch_simplify 0.16% : 0.000001s : 18: predicate.const_output_eliminate 4.45% : 0.000041s : 36: predicate.depend_value_elim 0.59% : 0.000005s : 37: predicate.dict_get_item_const_eliminator 0.64% : 0.000006s : 37: predicate.dict_get_item_eliminator 0.52% : 0.000005s : 37: predicate.dict_set_item_eliminator 0.63% : 0.000006s : 36: predicate.dumpgradient_eliminate 0.17% : 0.000002s : 18: predicate.elim_not_effective 0.32% : 0.000003s : 18: predicate.elim_shapecalc_of_broadcastargs 0.76% : 0.000007s : 55: predicate.environ_add_const_eliminate 0.71% : 0.000007s : 55: predicate.environ_get_add_eliminate 0.75% : 0.000007s : 55: predicate.environ_get_depend_swap 2.25% : 0.000021s : 91: predicate.environ_get_eliminate 0.75% : 0.000007s : 55: predicate.environ_get_set_eliminate 0.50% : 0.000005s : 38: predicate.exchange_switch_depend_value 0.83% : 0.000008s : 38: predicate.float_depend_g_call 1.41% : 0.000013s : 36: predicate.float_environ_get_switch 1.88% : 0.000017s : 54: predicate.float_tuple_getitem_switch 0.15% : 0.000001s : 18: predicate.fold_const_symbol 0.59% : 0.000005s : 36: predicate.get_grad_eliminate 0.18% : 0.000002s : 18: predicate.graph_param_transform 1.52% : 0.000014s : 36: predicate.incorporate_call 2.28% : 0.000021s : 36: predicate.incorporate_call_switch 4.12% : 0.000038s : 183: predicate.inline 0.73% : 0.000007s : 36: predicate.inline_without_move 0.29% : 0.000003s : 36: predicate.j_node_and_user_rematch 3.25% : 0.000030s : 36: predicate.less_batch_normalization 1.11% : 0.000010s : 73: predicate.list_to_tuple_eliminator_ 1.51% : 0.000014s : 110: predicate.load_eliminater 0.50% : 0.000005s : 18: predicate.loop_unroll_after_grad 0.61% : 0.000006s : 41: predicate.loop_unroll_before_grad 1.08% : 0.000010s : 73: predicate.make_slice_get_slice_eliminator 1.43% : 0.000013s : 36: predicate.merge_addn 0.53% : 0.000005s : 36: predicate.micro_step_allgather_replace 0.56% : 0.000005s : 36: predicate.mini_step_allgather_replace 0.48% : 0.000004s : 37: predicate.minmaximum_grad 0.65% : 0.000006s : 18: predicate.mutable_eliminate 0.35% : 0.000003s : 18: predicate.opt_reshape 0.28% : 0.000003s : 18: predicate.parallel_virtual_node 0.62% : 0.000006s : 38: predicate.partial_defer_inline 0.83% : 0.000008s : 55: predicate.partial_eliminate 0.51% : 0.000005s : 37: predicate.print_const_string_wrapper 3.19% : 0.000029s : 36: predicate.reduce_all_const_elim 0.76% : 0.000007s : 37: predicate.reduce_eliminate 1.47% : 0.000014s : 110: predicate.redundant_stop_gradient_eliminater 0.36% : 0.000003s : 36: predicate.remove_not_recompute_node 0.85% : 0.000008s : 73: predicate.replace_applicator 0.37% : 0.000003s : 36: predicate.replace_old_param 0.21% : 0.000002s : 18: predicate.reset_defer_inline 0.57% : 0.000005s : 37: predicate.reshape_eliminate 0.55% : 0.000005s : 36: predicate.row_tensor_add_zeros_like 0.29% : 0.000003s : 18: predicate.row_tensor_eliminate 0.73% : 0.000007s : 36: predicate.same_eliminate 3.75% : 0.000035s : 36: predicate.set_cell_output_no_recompute 0.62% : 0.000006s : 36: predicate.shard_identity_eliminate 0.61% : 0.000006s : 36: predicate.special_op_eliminate 1.58% : 0.000015s : 36: predicate.specialize_transform 0.87% : 0.000008s : 36: predicate.split_environ_get_set_with_tuple_value 0.69% : 0.000006s : 36: predicate.stack_unstack_eliminate 0.31% : 0.000003s : 18: predicate.switch_call_monad_eliminater 0.52% : 0.000005s : 38: predicate.switch_defer_inline 1.06% : 0.000010s : 74: predicate.switch_layer_defer_inline 3.42% : 0.000032s : 133: predicate.switch_simplify 0.56% : 0.000005s : 37: predicate.tile_eliminate 0.50% : 0.000005s : 37: predicate.transpose_eliminate 1.08% : 0.000010s : 73: predicate.tuple_list_convert_item_index_to_positive 1.14% : 0.000010s : 73: predicate.tuple_list_get_item_const_eliminator 1.06% : 0.000010s : 73: predicate.tuple_list_get_item_depend_reorder 5.18% : 0.000048s : 109: predicate.tuple_list_get_item_eliminator 1.12% : 0.000010s : 73: predicate.tuple_list_get_set_item_eliminator 3.48% : 0.000032s : 109: predicate.tuple_list_set_item_eliminator 1.09% : 0.000010s : 73: predicate.tuple_to_list_eliminator_ 1.46% : 0.000013s : 110: predicate.updatestate_pure_node_eliminater 6.21% : 0.000057s : 146: predicate.updatestate_useless_node_eliminater 0.36% : 0.000003s : 18: predicate.value_based_eliminate 0.58% : 0.000005s : 36: predicate.virtual_dataset_eliminate 0.57% : 0.000005s : 36: predicate.virtual_output_eliminate 0.26% : 0.000002s : 18: predicate.virtual_view_grad_eliminate 0.30% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.276330 58 98.84% : 0.273116s : 55: func_graph_cloner_run.FuncGraphClonerGraph 1.16% : 0.003214s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.255553 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.20% : 0.006673s : 1: add_attr 0.20% : 0.006651s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000140s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.01% : 0.000414s : 1: auto_monad 0.00% : 0.000078s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.02% : 0.000670s : 1: bootstrap 0.00% : 0.000050s : 1: cconv 0.00% : 0.000006s : 1: comm_op_add_attrs 0.00% : 0.000040s : 1: control_data_broadcast_order 0.00% : 0.000025s : 1: convert_after_rewriter 0.00% : 0.000073s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000027s : 1: environ_conv 0.00% : 0.000032s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000006s : 1: inline 0.00% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000005s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000010s : 1: label_micro_interleaved_index 0.02% : 0.000651s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.03% : 0.000838s : 1: mutable_eliminate 0.00% : 0.000013s : 1: offloading_packed_experts 0.00% : 0.000040s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000043s : 1: opt.transform.mutable_eliminate 0.46% : 0.014968s : 78: opt.transform.opt_a 0.00% : 0.000146s : 1: opt.transform.opt_after_cconv 0.00% : 0.000079s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000544s : 28: opt.transform.opt_b 0.01% : 0.000177s : 2: opt.transform.opt_trans_graph 0.00% : 0.000121s : 4: opt.transform.symbol_engine_opt 5.00% : 0.162710s : 1: opt_a 0.01% : 0.000398s : 1: opt_after_cconv 0.02% : 0.000743s : 1: opt_after_jit_grad 0.02% : 0.000792s : 1: opt_b 5.13% : 0.167074s : 1: optimize 0.00% : 0.000047s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000051s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000004s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000014s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000046s : 1: pre_auto_parallel 0.00% : 0.000039s : 1: py_interpret_to_execute 0.00% : 0.000042s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000099s : 1: remove_dup_value 4.28% : 0.139273s : 1: renormalize.infer 0.11% : 0.003634s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000241s : 1: rewriter_after_opt_a 0.00% : 0.000106s : 1: rewriter_before_opt_a 0.00% : 0.000005s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000019s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000193s : 1: symbol_engine_optimizer 0.01% : 0.000214s : 1: tuple_transform 84.38% : 2.747080s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_0[False-k_n_shape1-16] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_0[False-k_n_shape1-16],max_mem:120.0M =============================== 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_qbmm_split.py::test_qbmm_qkv_0[False-k_n_shape0-16] /home/jenkins/mindspore/testcases/testcases/tests/st/infer/ops/test_internal_ops/st_utils.py:39: RuntimeWarning: invalid value encountered in divide err_cnt = np.sum(np.abs(out_flatten - expect_flatten) / -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 4 passed, 26 warnings in 93.27s (0:01:33) ===================