==================================================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_005/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_qbmm_split.py [WARNING] ME(169412:281473043910448,MainProcess):2026-01-29-17:37:34.535.72 [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 = 1.69585, [21] [bootstrap]: 0.00070872 [type_inference]: 1.48596 [event_method]: 0.00021619 [auto_monad]: 0.00086988 [graph_reusing]: 5.108e-05 [inline]: 3.59002e-06 [add_attr]: 0.00868476, [1] [add_attr_with_inline]: 0.0086508, [1] [Cycle 1]: 0.00036511, [2] [tag_attr]: 0.00018754 [meta_addattr_fg_expand]: 6.074e-05 [parallel-infer-symbol]: 4.05e-06 [pre_auto_parallel]: 0.00026416 [insert-virtual-dataset]: 2.78e-06 [parallel-infer-symbol-second]: 1.07e-06 [dataset_repeat_opt]: 2.63e-06 [pipeline_split]: 1.87001e-06 [optimize]: 0.197812, [53] [py_interpret_to_execute]: 0.00019991 [rewriter_before_opt_a]: 0.0691458 [opt_a]: 0.122433, [2] [Cycle 1]: 0.11958, [45] [expand_dump_flag]: 3.569e-05 [switch_simplify]: 0.00084228 [loop_unroll]: 0.00030531 [a_1]: 0.0084541 [with_stream_mark]: 9.774e-05 [recompute_prepare]: 5.014e-05 [updatestate_depend_eliminate]: 2.381e-05 [updatestate_assign_eliminate]: 2.517e-05 [updatestate_loads_eliminate]: 5.451e-05 [parameter_eliminate]: 2.97002e-06 [a_2]: 0.00108856 [accelerated_algorithm]: 8.514e-05 [shard]: 2.46e-06 [meta_shard_fg_expand]: 2.263e-05 [shard_inline]: 3.205e-05 [merge_send_recv]: 2.398e-05 [auto_parallel]: 2.41e-05 [parallel]: 9.42e-05 [flash_sp]: 1.741e-05 [merge_comm]: 1.853e-05 [allreduce_fusion]: 1.608e-05 [matmul_add_comm_reduction]: 2.695e-05 [allreduce_slice_to_reducescatter]: 1.17e-06 [virtual_shard_identity]: 3.37e-05 [virtual_dataset]: 2.883e-05 [get_grad_eliminate_]: 2.836e-05 [virtual_output]: 2.828e-05 [merge_forward]: 1.546e-05 [cell_reuse_recompute_pass]: 2.48002e-06 [offload_activation]: 2.688e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.838e-05 [merge_recompute_call_nodes]: 1.50001e-06 [before_grad]: 5.22e-05 [set_forward_comm_id_for_comm_node_pass]: 1.798e-05 [meta_fg_expand]: 2.2e-05 [flash_sp_send_recv_attached]: 5.67999e-06 [receive_attached]: 1.633e-05 [after_resolve]: 4.145e-05 [a_after_grad]: 4.729e-05 [renormalize]: 0.0103415 [add_forward_monad_depend]: 1.418e-05 [auto_monad_grad]: 3.69002e-06 [auto_monad_eliminator]: 0.00010287 [cse]: 0.00042095 [a_3]: 0.096437 [Cycle 2]: 0.0028274, [45] [expand_dump_flag]: 5.32001e-06 [switch_simplify]: 3.95e-05 [loop_unroll]: 2.929e-05 [a_1]: 0.00093362 [with_stream_mark]: 4.72e-05 [recompute_prepare]: 3.075e-05 [updatestate_depend_eliminate]: 1.804e-05 [updatestate_assign_eliminate]: 1.562e-05 [updatestate_loads_eliminate]: 2.3e-05 [parameter_eliminate]: 3.36999e-06 [a_2]: 0.00044062 [accelerated_algorithm]: 3.997e-05 [shard]: 3.18e-06 [meta_shard_fg_expand]: 1.2e-05 [shard_inline]: 2.869e-05 [merge_send_recv]: 2.597e-05 [auto_parallel]: 2.304e-05 [parallel]: 1.087e-05 [flash_sp]: 4.15999e-06 [merge_comm]: 1.76e-05 [allreduce_fusion]: 1.555e-05 [matmul_add_comm_reduction]: 2.687e-05 [allreduce_slice_to_reducescatter]: 8.89995e-07 [virtual_shard_identity]: 3.026e-05 [virtual_dataset]: 2.786e-05 [get_grad_eliminate_]: 2.65e-05 [virtual_output]: 2.65e-05 [merge_forward]: 1.485e-05 [cell_reuse_recompute_pass]: 3.04999e-06 [offload_activation]: 2.678e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.293e-05 [merge_recompute_call_nodes]: 1.59998e-06 [before_grad]: 4.777e-05 [set_forward_comm_id_for_comm_node_pass]: 1.856e-05 [meta_fg_expand]: 1.312e-05 [flash_sp_send_recv_attached]: 1.99e-06 [receive_attached]: 2.60002e-06 [after_resolve]: 3.962e-05 [a_after_grad]: 4.398e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 3.07002e-06 [auto_monad_grad]: 3.53999e-06 [auto_monad_eliminator]: 7.725e-05 [cse]: 0.00011757 [a_3]: 0.00018875 [py_interpret_to_execute_after_opt_a]: 3.685e-05 [slice_cell_reuse_recomputed_activation]: 2.86e-06 [rewriter_after_opt_a]: 0.00096926 [convert_after_rewriter]: 5.312e-05 [order_py_execute_after_rewriter]: 1.739e-05 [mutable_eliminate]: 0.00080693 [opt_b]: 0.00097455, [1] [Cycle 1]: 0.00096559, [7] [b_1]: 0.0007177 [b_2]: 3.058e-05 [updatestate_depend_eliminate]: 1.936e-05 [updatestate_assign_eliminate]: 1.415e-05 [updatestate_loads_eliminate]: 2.05e-05 [renormalize]: 1.00001e-06 [cse]: 0.00011863 [optimize_parallel_all_gather_comm]: 4.157e-05 [overlap_param_gather]: 6.64001e-06 [cconv]: 4.264e-05 [loop_unroll]: 0.00052686 [opt_after_cconv]: 0.00035515, [1] [Cycle 1]: 0.00034892, [7] [c_1]: 0.00017586 [parameter_eliminate]: 3.76999e-06 [updatestate_depend_eliminate]: 1.798e-05 [updatestate_assign_eliminate]: 1.38e-05 [updatestate_loads_eliminate]: 1.671e-05 [cse]: 8.283e-05 [renormalize]: 3.59985e-07 [remove_dup_value]: 0.00012675 [tuple_transform]: 0.00032775, [1] [Cycle 1]: 0.00032178, [4] [d_1]: 0.00026421 [none_parameter_eliminate]: 2.36e-06 [renormalize]: 2.30008e-07 [switch_simplify]: 3.233e-05 [partial_unused_args_eliminate]: 2.22001e-06 [add_recomputation]: 0.0001771 [cse_after_recomputation]: 8.014e-05, [1] [Cycle 1]: 7.467e-05, [1] [cse]: 6.758e-05 [environ_conv]: 3.897e-05 [swap_dp_allreduce_reducescatter]: 2.136e-05 [bias_add_comm_swap]: 3.6e-06 [label_micro_interleaved_index]: 5.47999e-06 [label_fine_grained_interleaved_index]: 2.89001e-06 [merge_cast_opt]: 1.57999e-06 [slice_recompute_activation]: 2.32001e-06 [micro_interleaved_order_control]: 2.53e-06 [assign_add_opt]: 1.37e-06 [ForceFp32Comm]: 9.50007e-07 [remove_cast_before_assign_add]: 1.17e-06 [full_micro_interleaved_order_control]: 2.41998e-06 [reorder_send_recv_between_fp_bp]: 3.16001e-06 [comm_op_add_attrs]: 1.27999e-06 [add_comm_op_reuse_tag]: 1.43002e-06 [interleave_split_concat_branches]: 1.19e-06 [interleave_parallel_branches]: 1.15001e-06 [overlap_opt_shard_in_pipeline]: 4.654e-05 [overlap_opt_shard_grad_in_pipeline]: 1.91998e-06 [control_data_broadcast_order]: 4.662e-05 [grouped_pairwise_exchange_alltoall]: 2.21e-06 [offloading_packed_experts]: 1.208e-05 [overlap_recompute_and_grad_model_parallel]: 1.311e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.24e-06 [overlap_recompute_allgather_and_fa_grad]: 1.49e-06 [overlap_recompute_comm]: 2.46998e-06 [overlap_grad_ring_attention]: 1.112e-05 [overlap_grad_flash_sp]: 7.923e-05 [begin_end_overlap_inline]: 5.8001e-07 [split_matmul_comm_elemetwise]: 2.62001e-06 [split_layernorm_comm]: 2.19001e-06 [handle_group_info]: 1.37999e-06 [symbol_engine_optimizer]: 0.00077411, [1] [Cycle 1]: 0.00076695, [6] [build]: 0.00047173 [elim_shapecalc]: 4.138e-05 [elim_not_effective]: 8.71e-05 [opt_reshape]: 4.182e-05 [fold_const_symbol]: 7.269e-05 [renormalize]: 3.20026e-07 [detach_backward]: 3.13e-06 [pipeline_parallel_scheduler]: 1.86998e-06 [auto_monad_reorder]: 9.525e-05 [get_jit_bprop_graph]: 1.78002e-06 [rewriter_after_jit_bprop_graph]: 6.08998e-06 [opt_after_jit_grad]: 0.00077769 [validate]: 0.00013844 Sums bootstrap : 0.000709s : 0.04% type_inference : 1.485959s : 88.15% event_method : 0.000216s : 0.01% auto_monad : 0.000870s : 0.05% graph_reusing : 0.000051s : 0.00% inline : 0.000004s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000188s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000061s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000264s : 0.02% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000200s : 0.01% optimize.rewriter_before_opt_a : 0.069146s : 4.10% optimize.opt_a.expand_dump_flag : 0.000041s : 0.00% optimize.opt_a.switch_simplify : 0.000882s : 0.05% optimize.opt_a.loop_unroll : 0.000335s : 0.02% optimize.opt_a.a_1 : 0.009388s : 0.56% optimize.opt_a.with_stream_mark : 0.000145s : 0.01% optimize.opt_a.recompute_prepare : 0.000081s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000042s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000041s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000078s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.001529s : 0.09% optimize.opt_a.accelerated_algorithm : 0.000125s : 0.01% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000035s : 0.00% optimize.opt_a.shard_inline : 0.000061s : 0.00% optimize.opt_a.merge_send_recv : 0.000050s : 0.00% optimize.opt_a.auto_parallel : 0.000047s : 0.00% optimize.opt_a.parallel : 0.000105s : 0.01% optimize.opt_a.flash_sp : 0.000022s : 0.00% optimize.opt_a.merge_comm : 0.000036s : 0.00% optimize.opt_a.allreduce_fusion : 0.000032s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000054s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000064s : 0.00% optimize.opt_a.virtual_dataset : 0.000057s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000055s : 0.00% optimize.opt_a.virtual_output : 0.000055s : 0.00% optimize.opt_a.merge_forward : 0.000030s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000054s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000111s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000100s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000037s : 0.00% optimize.opt_a.meta_fg_expand : 0.000035s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000019s : 0.00% optimize.opt_a.after_resolve : 0.000081s : 0.00% optimize.opt_a.a_after_grad : 0.000091s : 0.01% optimize.opt_a.renormalize : 0.010342s : 0.61% optimize.opt_a.add_forward_monad_depend : 0.000017s : 0.00% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000180s : 0.01% optimize.opt_a.cse : 0.000539s : 0.03% optimize.opt_a.a_3 : 0.096626s : 5.73% optimize.py_interpret_to_execute_after_opt_a : 0.000037s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000969s : 0.06% optimize.convert_after_rewriter : 0.000053s : 0.00% optimize.order_py_execute_after_rewriter : 0.000017s : 0.00% optimize.mutable_eliminate : 0.000807s : 0.05% optimize.opt_b.b_1 : 0.000718s : 0.04% optimize.opt_b.b_2 : 0.000031s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000019s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000021s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000119s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000042s : 0.00% optimize.overlap_param_gather : 0.000007s : 0.00% optimize.cconv : 0.000043s : 0.00% optimize.loop_unroll : 0.000527s : 0.03% optimize.opt_after_cconv.c_1 : 0.000176s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000018s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.cse : 0.000083s : 0.00% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000127s : 0.01% optimize.tuple_transform.d_1 : 0.000264s : 0.02% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000032s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000177s : 0.01% optimize.cse_after_recomputation.cse : 0.000068s : 0.00% optimize.environ_conv : 0.000039s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000021s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 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 : 0.000047s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000047s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000012s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000013s : 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 : 0.000011s : 0.00% optimize.overlap_grad_flash_sp : 0.000079s : 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 : 0.000472s : 0.03% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000041s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000087s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000042s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000073s : 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 : 0.000095s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000778s : 0.05% validate : 0.000138s : 0.01% Time group info: ------[substitution.] 0.003007 608 0.64% : 0.000019s : 8: substitution.depend_value_elim 1.24% : 0.000037s : 17: substitution.elim_not_effective 0.62% : 0.000019s : 12: substitution.float_tuple_getitem_switch 1.02% : 0.000031s : 17: substitution.fold_const_symbol 0.75% : 0.000022s : 22: substitution.graph_param_transform 61.51% : 0.001849s : 71: substitution.inline 0.60% : 0.000018s : 35: substitution.j_node_and_user_rematch 1.33% : 0.000040s : 6: substitution.less_batch_normalization 1.97% : 0.000059s : 2: substitution.list_to_tuple_eliminator_ 0.41% : 0.000012s : 18: substitution.load_eliminater 0.98% : 0.000029s : 21: substitution.minmaximum_grad 0.26% : 0.000008s : 2: substitution.opt_reshape 0.82% : 0.000025s : 35: substitution.remove_not_recompute_node 0.42% : 0.000013s : 8: substitution.replace_old_param 1.71% : 0.000051s : 18: substitution.reshape_eliminate 2.00% : 0.000060s : 24: substitution.switch_simplify 4.58% : 0.000138s : 51: substitution.tuple_list_convert_item_index_to_positive 2.32% : 0.000070s : 51: substitution.tuple_list_get_item_const_eliminator 3.18% : 0.000096s : 51: substitution.tuple_list_get_item_depend_reorder 6.00% : 0.000180s : 73: substitution.tuple_list_get_item_eliminator 3.02% : 0.000091s : 51: substitution.tuple_list_get_set_item_eliminator 0.36% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 4.28% : 0.000129s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.485544 2 93.18% : 1.384276s : 1: type_inference.infer 6.82% : 0.101268s : 1: type_inference.specialize ------[replace.] 0.001061 115 4.44% : 0.000047s : 5: replace.depend_value_elim 54.31% : 0.000576s : 71: replace.inline 3.65% : 0.000039s : 2: replace.list_to_tuple_eliminator_ 28.79% : 0.000305s : 24: replace.switch_simplify 8.81% : 0.000093s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.001939 115 0.14% : 0.000003s : 5: match.depend_value_elim 93.16% : 0.001806s : 71: match.inline 2.91% : 0.000056s : 2: match.list_to_tuple_eliminator_ 2.31% : 0.000045s : 24: match.switch_simplify 1.48% : 0.000029s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.002032 10915 3.14% : 0.000064s : 133: predicate.accumulaten_eliminater 0.36% : 0.000007s : 22: predicate.ad_related_special_op_eliminate 0.58% : 0.000012s : 73: predicate.addn_check_dump 1.05% : 0.000021s : 133: predicate.addn_zero_filter 1.01% : 0.000021s : 133: predicate.adjust_all_reduce_mul_add 2.04% : 0.000041s : 206: predicate.arithmetic_simplify 1.07% : 0.000022s : 133: predicate.cast_eliminate 1.23% : 0.000025s : 44: predicate.check_bprop_eliminate 0.58% : 0.000012s : 73: predicate.compare_switch_simplify 0.10% : 0.000002s : 22: predicate.const_output_eliminate 0.65% : 0.000013s : 76: predicate.depend_value_elim 1.12% : 0.000023s : 133: predicate.dict_get_item_const_eliminator 1.15% : 0.000023s : 133: predicate.dict_get_item_eliminator 1.06% : 0.000022s : 133: predicate.dict_set_item_eliminator 0.40% : 0.000008s : 44: predicate.dumpgradient_eliminate 0.11% : 0.000002s : 22: predicate.elim_not_effective 0.22% : 0.000004s : 22: predicate.elim_shapecalc_of_broadcastargs 1.21% : 0.000025s : 155: predicate.environ_add_const_eliminate 1.23% : 0.000025s : 155: predicate.environ_get_add_eliminate 1.19% : 0.000024s : 155: predicate.environ_get_depend_swap 1.87% : 0.000038s : 228: predicate.environ_get_eliminate 1.19% : 0.000024s : 155: predicate.environ_get_set_eliminate 1.86% : 0.000038s : 219: predicate.exchange_switch_depend_value 2.57% : 0.000052s : 219: predicate.float_depend_g_call 0.61% : 0.000012s : 73: predicate.float_environ_get_switch 0.81% : 0.000016s : 95: predicate.float_tuple_getitem_switch 0.10% : 0.000002s : 22: predicate.fold_const_symbol 0.39% : 0.000008s : 45: predicate.get_grad_eliminate 0.12% : 0.000002s : 22: predicate.graph_param_transform 0.60% : 0.000012s : 73: predicate.incorporate_call 0.57% : 0.000012s : 73: predicate.incorporate_call_switch 6.17% : 0.000125s : 514: predicate.inline 0.52% : 0.000011s : 45: predicate.inline_without_move 0.20% : 0.000004s : 45: predicate.j_node_and_user_rematch 0.50% : 0.000010s : 45: predicate.less_batch_normalization 1.56% : 0.000032s : 192: predicate.list_to_tuple_eliminator_ 2.67% : 0.000054s : 325: predicate.load_eliminater 0.30% : 0.000006s : 22: predicate.loop_unroll_after_grad 2.91% : 0.000059s : 324: predicate.loop_unroll_before_grad 1.48% : 0.000030s : 177: predicate.make_slice_get_slice_eliminator 0.60% : 0.000012s : 73: predicate.merge_addn 0.36% : 0.000007s : 44: predicate.micro_step_allgather_replace 0.35% : 0.000007s : 44: predicate.mini_step_allgather_replace 1.08% : 0.000022s : 133: predicate.minmaximum_grad 0.32% : 0.000006s : 22: predicate.mutable_eliminate 0.22% : 0.000005s : 22: predicate.opt_reshape 0.18% : 0.000004s : 22: predicate.parallel_virtual_node 2.59% : 0.000053s : 219: predicate.partial_defer_inline 1.58% : 0.000032s : 170: predicate.partial_eliminate 1.08% : 0.000022s : 133: predicate.print_const_string_wrapper 0.57% : 0.000012s : 68: predicate.reduce_all_const_elim 1.35% : 0.000027s : 133: predicate.reduce_eliminate 2.62% : 0.000053s : 325: predicate.redundant_stop_gradient_eliminater 0.21% : 0.000004s : 45: predicate.remove_not_recompute_node 1.16% : 0.000024s : 192: predicate.replace_applicator 0.23% : 0.000005s : 45: predicate.replace_old_param 0.11% : 0.000002s : 22: predicate.reset_defer_inline 1.14% : 0.000023s : 133: predicate.reshape_eliminate 0.36% : 0.000007s : 44: predicate.row_tensor_add_zeros_like 0.20% : 0.000004s : 22: predicate.row_tensor_eliminate 0.49% : 0.000010s : 44: predicate.same_eliminate 0.26% : 0.000005s : 50: predicate.set_cell_output_no_recompute 0.40% : 0.000008s : 45: predicate.shard_identity_eliminate 0.37% : 0.000007s : 44: predicate.special_op_eliminate 0.74% : 0.000015s : 73: predicate.specialize_transform 0.45% : 0.000009s : 44: predicate.split_environ_get_set_with_tuple_value 0.42% : 0.000009s : 45: predicate.stack_unstack_eliminate 0.20% : 0.000004s : 22: predicate.switch_call_monad_eliminater 1.94% : 0.000040s : 219: predicate.switch_defer_inline 2.24% : 0.000046s : 263: predicate.switch_layer_defer_inline 7.30% : 0.000148s : 686: predicate.switch_simplify 1.02% : 0.000021s : 133: predicate.tile_eliminate 1.04% : 0.000021s : 133: predicate.transpose_eliminate 1.68% : 0.000034s : 177: predicate.tuple_list_convert_item_index_to_positive 1.70% : 0.000035s : 177: predicate.tuple_list_get_item_const_eliminator 1.64% : 0.000033s : 177: predicate.tuple_list_get_item_depend_reorder 2.81% : 0.000057s : 263: predicate.tuple_list_get_item_eliminator 1.61% : 0.000033s : 177: predicate.tuple_list_get_set_item_eliminator 2.24% : 0.000045s : 250: predicate.tuple_list_set_item_eliminator 1.53% : 0.000031s : 190: predicate.tuple_to_list_eliminator_ 2.53% : 0.000051s : 325: predicate.updatestate_pure_node_eliminater 3.23% : 0.000066s : 398: predicate.updatestate_useless_node_eliminater 0.20% : 0.000004s : 22: predicate.value_based_eliminate 0.39% : 0.000008s : 45: predicate.virtual_dataset_eliminate 0.39% : 0.000008s : 45: predicate.virtual_output_eliminate 0.17% : 0.000004s : 22: predicate.virtual_view_grad_eliminate 0.20% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.061078 135 92.32% : 0.056390s : 55: func_graph_cloner_run.FuncGraphClonerGraph 7.68% : 0.004688s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.927279 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.45% : 0.008692s : 1: add_attr 0.45% : 0.008656s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000183s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.05% : 0.000887s : 1: auto_monad 0.01% : 0.000101s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000063s : 1: bias_add_comm_swap 0.04% : 0.000748s : 1: bootstrap 0.00% : 0.000047s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000050s : 1: control_data_broadcast_order 0.00% : 0.000059s : 1: convert_after_rewriter 0.00% : 0.000083s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000043s : 1: environ_conv 0.01% : 0.000231s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000058s : 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% : 0.000007s : 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% : 0.000009s : 1: label_micro_interleaved_index 0.03% : 0.000537s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.04% : 0.000817s : 1: mutable_eliminate 0.00% : 0.000015s : 1: offloading_packed_experts 0.00% : 0.000040s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000045s : 1: opt.transform.mutable_eliminate 0.69% : 0.013326s : 95: opt.transform.opt_a 0.01% : 0.000174s : 1: opt.transform.opt_after_cconv 0.01% : 0.000097s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000712s : 28: opt.transform.opt_b 0.02% : 0.000293s : 2: opt.transform.opt_trans_graph 0.01% : 0.000237s : 4: opt.transform.symbol_engine_opt 6.35% : 0.122439s : 1: opt_a 0.02% : 0.000359s : 1: opt_after_cconv 0.04% : 0.000790s : 1: opt_after_jit_grad 0.05% : 0.000978s : 1: opt_b 10.26% : 0.197818s : 1: optimize 0.00% : 0.000046s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000021s : 1: order_py_execute_after_rewriter 0.00% : 0.000083s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000014s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000051s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000010s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000016s : 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 0.01% : 0.000273s : 1: pre_auto_parallel 0.01% : 0.000209s : 1: py_interpret_to_execute 0.00% : 0.000041s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000133s : 1: remove_dup_value 0.27% : 0.005260s : 1: renormalize.infer 0.26% : 0.005061s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000980s : 1: rewriter_after_opt_a 3.59% : 0.069182s : 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% : 0.000025s : 1: swap_dp_allreduce_reducescatter 0.04% : 0.000778s : 1: symbol_engine_optimizer 0.02% : 0.000331s : 1: tuple_transform 77.10% : 1.485998s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_11008_4096_4096_0[True-4096-16] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_11008_4096_4096_0[True-4096-16],max_mem:174.0M [WARNING] ME(169412:281473043910448,MainProcess):2026-01-29-17:38:19.335.021 [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 = 1.0287, [21] [bootstrap]: 0.00066761 [type_inference]: 0.939357 [event_method]: 0.00024139 [auto_monad]: 0.00094489 [graph_reusing]: 4.93e-05 [inline]: 3.16999e-06 [add_attr]: 0.00712782, [1] [add_attr_with_inline]: 0.00710731, [1] [Cycle 1]: 0.00035404, [2] [tag_attr]: 0.00021703 [meta_addattr_fg_expand]: 6.656e-05 [parallel-infer-symbol]: 4.25e-06 [pre_auto_parallel]: 0.00026548 [insert-virtual-dataset]: 3.60998e-06 [parallel-infer-symbol-second]: 1.52001e-06 [dataset_repeat_opt]: 2.67001e-06 [pipeline_split]: 2.96001e-06 [optimize]: 0.0786854, [53] [py_interpret_to_execute]: 0.00027605 [rewriter_before_opt_a]: 0.00089172 [opt_a]: 0.0703092, [2] [Cycle 1]: 0.0287468, [45] [expand_dump_flag]: 4.4e-05 [switch_simplify]: 0.00086769 [loop_unroll]: 0.00033606 [a_1]: 0.00955501 [with_stream_mark]: 0.00016873 [recompute_prepare]: 5.582e-05 [updatestate_depend_eliminate]: 2.937e-05 [updatestate_assign_eliminate]: 2.287e-05 [updatestate_loads_eliminate]: 2.896e-05 [parameter_eliminate]: 3.31001e-06 [a_2]: 0.00110379 [accelerated_algorithm]: 7.592e-05 [shard]: 2.64001e-06 [meta_shard_fg_expand]: 2.602e-05 [shard_inline]: 3.118e-05 [merge_send_recv]: 2.481e-05 [auto_parallel]: 2.553e-05 [parallel]: 3.748e-05 [flash_sp]: 1.606e-05 [merge_comm]: 1.714e-05 [allreduce_fusion]: 1.741e-05 [matmul_add_comm_reduction]: 2.526e-05 [allreduce_slice_to_reducescatter]: 1.00001e-06 [virtual_shard_identity]: 3.451e-05 [virtual_dataset]: 3.189e-05 [get_grad_eliminate_]: 2.961e-05 [virtual_output]: 3.056e-05 [merge_forward]: 1.529e-05 [cell_reuse_recompute_pass]: 2.26998e-06 [offload_activation]: 2.693e-05 [cell_reuse_handle_not_recompute_node_pass]: 6.243e-05 [merge_recompute_call_nodes]: 1.55999e-06 [before_grad]: 5.315e-05 [set_forward_comm_id_for_comm_node_pass]: 1.824e-05 [meta_fg_expand]: 2.333e-05 [flash_sp_send_recv_attached]: 6.17999e-06 [receive_attached]: 2.16e-06 [after_resolve]: 4.098e-05 [a_after_grad]: 5.126e-05 [renormalize]: 0.0142283 [add_forward_monad_depend]: 1.212e-05 [auto_monad_grad]: 2.98e-06 [auto_monad_eliminator]: 9.029e-05 [cse]: 0.00076934 [a_3]: 0.00023209 [Cycle 2]: 0.0415417, [45] [expand_dump_flag]: 2.98998e-06 [switch_simplify]: 3.419e-05 [loop_unroll]: 2.925e-05 [a_1]: 0.00091169 [with_stream_mark]: 3.036e-05 [recompute_prepare]: 0.0384725 [updatestate_depend_eliminate]: 4.474e-05 [updatestate_assign_eliminate]: 1.773e-05 [updatestate_loads_eliminate]: 2.62e-05 [parameter_eliminate]: 9.14e-06 [a_2]: 0.00051733 [accelerated_algorithm]: 4.695e-05 [shard]: 3.97998e-06 [meta_shard_fg_expand]: 1.464e-05 [shard_inline]: 3.218e-05 [merge_send_recv]: 2.738e-05 [auto_parallel]: 2.666e-05 [parallel]: 1.103e-05 [flash_sp]: 6.26e-06 [merge_comm]: 1.719e-05 [allreduce_fusion]: 1.701e-05 [matmul_add_comm_reduction]: 2.892e-05 [allreduce_slice_to_reducescatter]: 9.00007e-07 [virtual_shard_identity]: 3.33e-05 [virtual_dataset]: 2.886e-05 [get_grad_eliminate_]: 2.779e-05 [virtual_output]: 2.846e-05 [merge_forward]: 1.685e-05 [cell_reuse_recompute_pass]: 3.8e-06 [offload_activation]: 2.791e-05 [cell_reuse_handle_not_recompute_node_pass]: 6.086e-05 [merge_recompute_call_nodes]: 2.11e-06 [before_grad]: 5.099e-05 [set_forward_comm_id_for_comm_node_pass]: 1.872e-05 [meta_fg_expand]: 1.485e-05 [flash_sp_send_recv_attached]: 2.22999e-06 [receive_attached]: 2.68e-06 [after_resolve]: 4.26e-05 [a_after_grad]: 4.805e-05 [renormalize]: 5.9983e-08 [add_forward_monad_depend]: 6.04999e-06 [auto_monad_grad]: 3.59002e-06 [auto_monad_eliminator]: 8.701e-05 [cse]: 0.00012166 [a_3]: 0.00020433 [py_interpret_to_execute_after_opt_a]: 4.255e-05 [slice_cell_reuse_recomputed_activation]: 3.50998e-06 [rewriter_after_opt_a]: 0.00107183 [convert_after_rewriter]: 3.746e-05 [order_py_execute_after_rewriter]: 1.678e-05 [mutable_eliminate]: 0.0013731 [opt_b]: 0.00102613, [1] [Cycle 1]: 0.00101555, [7] [b_1]: 0.00074911 [b_2]: 3.06e-05 [updatestate_depend_eliminate]: 2.636e-05 [updatestate_assign_eliminate]: 1.579e-05 [updatestate_loads_eliminate]: 2.167e-05 [renormalize]: 9.50007e-07 [cse]: 0.00012291 [optimize_parallel_all_gather_comm]: 5.145e-05 [overlap_param_gather]: 3.58e-06 [cconv]: 4.089e-05 [loop_unroll]: 0.00066226 [opt_after_cconv]: 0.00039704, [1] [Cycle 1]: 0.00038828, [7] [c_1]: 0.00019216 [parameter_eliminate]: 4.80001e-06 [updatestate_depend_eliminate]: 2.117e-05 [updatestate_assign_eliminate]: 1.457e-05 [updatestate_loads_eliminate]: 1.962e-05 [cse]: 9.328e-05 [renormalize]: 6.00005e-07 [remove_dup_value]: 0.0001266 [tuple_transform]: 0.00032565, [1] [Cycle 1]: 0.0003192, [4] [d_1]: 0.0002632 [none_parameter_eliminate]: 2.41e-06 [renormalize]: 2.30008e-07 [switch_simplify]: 2.973e-05 [partial_unused_args_eliminate]: 2.02001e-06 [add_recomputation]: 0.00018441 [cse_after_recomputation]: 7.867e-05, [1] [Cycle 1]: 7.299e-05, [1] [cse]: 6.5e-05 [environ_conv]: 3.027e-05 [swap_dp_allreduce_reducescatter]: 2.068e-05 [bias_add_comm_swap]: 3.45003e-06 [label_micro_interleaved_index]: 6.48998e-06 [label_fine_grained_interleaved_index]: 2.86e-06 [merge_cast_opt]: 1.55001e-06 [slice_recompute_activation]: 2.42001e-06 [micro_interleaved_order_control]: 2.84999e-06 [assign_add_opt]: 1.90001e-06 [ForceFp32Comm]: 9.20001e-07 [remove_cast_before_assign_add]: 1.37999e-06 [full_micro_interleaved_order_control]: 3.17002e-06 [reorder_send_recv_between_fp_bp]: 3.04001e-06 [comm_op_add_attrs]: 1.12e-06 [add_comm_op_reuse_tag]: 1.18001e-06 [interleave_split_concat_branches]: 1.29998e-06 [interleave_parallel_branches]: 1.13001e-06 [overlap_opt_shard_in_pipeline]: 3.08e-06 [overlap_opt_shard_grad_in_pipeline]: 2.02001e-06 [control_data_broadcast_order]: 4.704e-05 [grouped_pairwise_exchange_alltoall]: 1.67001e-06 [offloading_packed_experts]: 1.309e-05 [overlap_recompute_and_grad_model_parallel]: 1.193e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.29998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.77999e-06 [overlap_recompute_comm]: 2.06998e-06 [overlap_grad_ring_attention]: 1.155e-05 [overlap_grad_flash_sp]: 6.469e-05 [begin_end_overlap_inline]: 6.00005e-07 [split_matmul_comm_elemetwise]: 2.21e-06 [split_layernorm_comm]: 1.89e-06 [handle_group_info]: 1.17e-06 [symbol_engine_optimizer]: 0.00116066, [1] [Cycle 1]: 0.00115219, [6] [build]: 0.00085338 [elim_shapecalc]: 5.057e-05 [elim_not_effective]: 7.179e-05 [opt_reshape]: 4.578e-05 [fold_const_symbol]: 7.189e-05 [renormalize]: 4.2998e-07 [detach_backward]: 3.31999e-06 [pipeline_parallel_scheduler]: 2.66e-06 [auto_monad_reorder]: 9.113e-05 [get_jit_bprop_graph]: 2.57001e-06 [rewriter_after_jit_bprop_graph]: 6.63998e-06 [opt_after_jit_grad]: 0.00083171 [validate]: 0.00012416 Sums bootstrap : 0.000668s : 0.07% type_inference : 0.939357s : 92.08% event_method : 0.000241s : 0.02% auto_monad : 0.000945s : 0.09% graph_reusing : 0.000049s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000217s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000067s : 0.01% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000265s : 0.03% insert-virtual-dataset : 0.000004s : 0.00% parallel-infer-symbol-second : 0.000002s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000003s : 0.00% optimize.py_interpret_to_execute : 0.000276s : 0.03% optimize.rewriter_before_opt_a : 0.000892s : 0.09% optimize.opt_a.expand_dump_flag : 0.000047s : 0.00% optimize.opt_a.switch_simplify : 0.000902s : 0.09% optimize.opt_a.loop_unroll : 0.000365s : 0.04% optimize.opt_a.a_1 : 0.010467s : 1.03% optimize.opt_a.with_stream_mark : 0.000199s : 0.02% optimize.opt_a.recompute_prepare : 0.038528s : 3.78% optimize.opt_a.updatestate_depend_eliminate : 0.000074s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000041s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000055s : 0.01% optimize.opt_a.parameter_eliminate : 0.000012s : 0.00% optimize.opt_a.a_2 : 0.001621s : 0.16% optimize.opt_a.accelerated_algorithm : 0.000123s : 0.01% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000041s : 0.00% optimize.opt_a.shard_inline : 0.000063s : 0.01% optimize.opt_a.merge_send_recv : 0.000052s : 0.01% optimize.opt_a.auto_parallel : 0.000052s : 0.01% optimize.opt_a.parallel : 0.000049s : 0.00% optimize.opt_a.flash_sp : 0.000022s : 0.00% optimize.opt_a.merge_comm : 0.000034s : 0.00% optimize.opt_a.allreduce_fusion : 0.000034s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000054s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000068s : 0.01% optimize.opt_a.virtual_dataset : 0.000061s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000057s : 0.01% optimize.opt_a.virtual_output : 0.000059s : 0.01% optimize.opt_a.merge_forward : 0.000032s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000055s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000123s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000104s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000037s : 0.00% optimize.opt_a.meta_fg_expand : 0.000038s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000084s : 0.01% optimize.opt_a.a_after_grad : 0.000099s : 0.01% optimize.opt_a.renormalize : 0.014228s : 1.39% optimize.opt_a.add_forward_monad_depend : 0.000018s : 0.00% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000177s : 0.02% optimize.opt_a.cse : 0.000891s : 0.09% optimize.opt_a.a_3 : 0.000436s : 0.04% optimize.py_interpret_to_execute_after_opt_a : 0.000043s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000004s : 0.00% optimize.rewriter_after_opt_a : 0.001072s : 0.11% optimize.convert_after_rewriter : 0.000037s : 0.00% optimize.order_py_execute_after_rewriter : 0.000017s : 0.00% optimize.mutable_eliminate : 0.001373s : 0.13% optimize.opt_b.b_1 : 0.000749s : 0.07% optimize.opt_b.b_2 : 0.000031s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000026s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000016s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000022s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000123s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000051s : 0.01% optimize.overlap_param_gather : 0.000004s : 0.00% optimize.cconv : 0.000041s : 0.00% optimize.loop_unroll : 0.000662s : 0.06% optimize.opt_after_cconv.c_1 : 0.000192s : 0.02% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000021s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000015s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000020s : 0.00% optimize.opt_after_cconv.cse : 0.000093s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000127s : 0.01% optimize.tuple_transform.d_1 : 0.000263s : 0.03% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000030s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000184s : 0.02% optimize.cse_after_recomputation.cse : 0.000065s : 0.01% optimize.environ_conv : 0.000030s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000021s : 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 : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 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 : 0.000003s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000047s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000013s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000012s : 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 : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000012s : 0.00% optimize.overlap_grad_flash_sp : 0.000065s : 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 : 0.000853s : 0.08% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000051s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000072s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000046s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000072s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000003s : 0.00% auto_monad_reorder : 0.000091s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000832s : 0.08% validate : 0.000124s : 0.01% Time group info: ------[substitution.] 0.003539 608 0.52% : 0.000018s : 8: substitution.depend_value_elim 0.52% : 0.000018s : 17: substitution.elim_not_effective 0.53% : 0.000019s : 12: substitution.float_tuple_getitem_switch 0.83% : 0.000029s : 17: substitution.fold_const_symbol 0.56% : 0.000020s : 22: substitution.graph_param_transform 62.82% : 0.002223s : 71: substitution.inline 0.53% : 0.000019s : 35: substitution.j_node_and_user_rematch 1.12% : 0.000039s : 6: substitution.less_batch_normalization 1.74% : 0.000062s : 2: substitution.list_to_tuple_eliminator_ 0.37% : 0.000013s : 18: substitution.load_eliminater 0.97% : 0.000035s : 21: substitution.minmaximum_grad 0.22% : 0.000008s : 2: substitution.opt_reshape 0.70% : 0.000025s : 35: substitution.remove_not_recompute_node 0.31% : 0.000011s : 8: substitution.replace_old_param 1.59% : 0.000056s : 18: substitution.reshape_eliminate 1.42% : 0.000050s : 24: substitution.switch_simplify 5.41% : 0.000191s : 51: substitution.tuple_list_convert_item_index_to_positive 2.16% : 0.000077s : 51: substitution.tuple_list_get_item_const_eliminator 3.32% : 0.000117s : 51: substitution.tuple_list_get_item_depend_reorder 6.96% : 0.000246s : 73: substitution.tuple_list_get_item_eliminator 3.32% : 0.000118s : 51: substitution.tuple_list_get_set_item_eliminator 0.30% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 3.77% : 0.000133s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.938855 2 93.66% : 0.879377s : 1: type_inference.infer 6.34% : 0.059478s : 1: type_inference.specialize ------[replace.] 0.001238 115 4.11% : 0.000051s : 5: replace.depend_value_elim 58.41% : 0.000723s : 71: replace.inline 3.60% : 0.000045s : 2: replace.list_to_tuple_eliminator_ 25.17% : 0.000312s : 24: replace.switch_simplify 8.72% : 0.000108s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.002315 115 0.11% : 0.000003s : 5: match.depend_value_elim 93.88% : 0.002173s : 71: match.inline 2.51% : 0.000058s : 2: match.list_to_tuple_eliminator_ 1.69% : 0.000039s : 24: match.switch_simplify 1.81% : 0.000042s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.002009 10915 1.10% : 0.000022s : 133: predicate.accumulaten_eliminater 0.35% : 0.000007s : 22: predicate.ad_related_special_op_eliminate 0.59% : 0.000012s : 73: predicate.addn_check_dump 1.18% : 0.000024s : 133: predicate.addn_zero_filter 1.05% : 0.000021s : 133: predicate.adjust_all_reduce_mul_add 2.14% : 0.000043s : 206: predicate.arithmetic_simplify 1.10% : 0.000022s : 133: predicate.cast_eliminate 0.38% : 0.000008s : 44: predicate.check_bprop_eliminate 0.60% : 0.000012s : 73: predicate.compare_switch_simplify 0.10% : 0.000002s : 22: predicate.const_output_eliminate 0.69% : 0.000014s : 76: predicate.depend_value_elim 1.14% : 0.000023s : 133: predicate.dict_get_item_const_eliminator 1.21% : 0.000024s : 133: predicate.dict_get_item_eliminator 1.07% : 0.000022s : 133: predicate.dict_set_item_eliminator 0.40% : 0.000008s : 44: predicate.dumpgradient_eliminate 0.13% : 0.000003s : 22: predicate.elim_not_effective 0.22% : 0.000004s : 22: predicate.elim_shapecalc_of_broadcastargs 1.23% : 0.000025s : 155: predicate.environ_add_const_eliminate 1.25% : 0.000025s : 155: predicate.environ_get_add_eliminate 1.21% : 0.000024s : 155: predicate.environ_get_depend_swap 1.82% : 0.000037s : 228: predicate.environ_get_eliminate 1.20% : 0.000024s : 155: predicate.environ_get_set_eliminate 1.87% : 0.000038s : 219: predicate.exchange_switch_depend_value 2.96% : 0.000060s : 219: predicate.float_depend_g_call 0.59% : 0.000012s : 73: predicate.float_environ_get_switch 0.83% : 0.000017s : 95: predicate.float_tuple_getitem_switch 0.11% : 0.000002s : 22: predicate.fold_const_symbol 0.40% : 0.000008s : 45: predicate.get_grad_eliminate 0.12% : 0.000002s : 22: predicate.graph_param_transform 0.61% : 0.000012s : 73: predicate.incorporate_call 0.57% : 0.000012s : 73: predicate.incorporate_call_switch 6.40% : 0.000129s : 514: predicate.inline 0.48% : 0.000010s : 45: predicate.inline_without_move 0.20% : 0.000004s : 45: predicate.j_node_and_user_rematch 0.54% : 0.000011s : 45: predicate.less_batch_normalization 1.69% : 0.000034s : 192: predicate.list_to_tuple_eliminator_ 2.59% : 0.000052s : 325: predicate.load_eliminater 0.36% : 0.000007s : 22: predicate.loop_unroll_after_grad 3.12% : 0.000063s : 324: predicate.loop_unroll_before_grad 1.52% : 0.000030s : 177: predicate.make_slice_get_slice_eliminator 0.60% : 0.000012s : 73: predicate.merge_addn 0.37% : 0.000007s : 44: predicate.micro_step_allgather_replace 0.36% : 0.000007s : 44: predicate.mini_step_allgather_replace 1.08% : 0.000022s : 133: predicate.minmaximum_grad 0.47% : 0.000009s : 22: predicate.mutable_eliminate 0.20% : 0.000004s : 22: predicate.opt_reshape 0.22% : 0.000004s : 22: predicate.parallel_virtual_node 3.05% : 0.000061s : 219: predicate.partial_defer_inline 1.60% : 0.000032s : 170: predicate.partial_eliminate 1.10% : 0.000022s : 133: predicate.print_const_string_wrapper 0.80% : 0.000016s : 68: predicate.reduce_all_const_elim 1.38% : 0.000028s : 133: predicate.reduce_eliminate 2.71% : 0.000054s : 325: predicate.redundant_stop_gradient_eliminater 0.21% : 0.000004s : 45: predicate.remove_not_recompute_node 1.18% : 0.000024s : 192: predicate.replace_applicator 0.25% : 0.000005s : 45: predicate.replace_old_param 0.11% : 0.000002s : 22: predicate.reset_defer_inline 1.17% : 0.000024s : 133: predicate.reshape_eliminate 0.38% : 0.000008s : 44: predicate.row_tensor_add_zeros_like 0.20% : 0.000004s : 22: predicate.row_tensor_eliminate 0.53% : 0.000011s : 44: predicate.same_eliminate 0.39% : 0.000008s : 50: predicate.set_cell_output_no_recompute 0.42% : 0.000008s : 45: predicate.shard_identity_eliminate 0.40% : 0.000008s : 44: predicate.special_op_eliminate 0.79% : 0.000016s : 73: predicate.specialize_transform 0.46% : 0.000009s : 44: predicate.split_environ_get_set_with_tuple_value 0.45% : 0.000009s : 45: predicate.stack_unstack_eliminate 0.21% : 0.000004s : 22: predicate.switch_call_monad_eliminater 2.00% : 0.000040s : 219: predicate.switch_defer_inline 2.32% : 0.000047s : 263: predicate.switch_layer_defer_inline 6.52% : 0.000131s : 686: predicate.switch_simplify 1.08% : 0.000022s : 133: predicate.tile_eliminate 1.05% : 0.000021s : 133: predicate.transpose_eliminate 1.70% : 0.000034s : 177: predicate.tuple_list_convert_item_index_to_positive 1.80% : 0.000036s : 177: predicate.tuple_list_get_item_const_eliminator 1.65% : 0.000033s : 177: predicate.tuple_list_get_item_depend_reorder 2.89% : 0.000058s : 263: predicate.tuple_list_get_item_eliminator 1.67% : 0.000034s : 177: predicate.tuple_list_get_set_item_eliminator 2.30% : 0.000046s : 250: predicate.tuple_list_set_item_eliminator 1.53% : 0.000031s : 190: predicate.tuple_to_list_eliminator_ 2.61% : 0.000052s : 325: predicate.updatestate_pure_node_eliminater 3.28% : 0.000066s : 398: predicate.updatestate_useless_node_eliminater 0.19% : 0.000004s : 22: predicate.value_based_eliminate 0.42% : 0.000008s : 45: predicate.virtual_dataset_eliminate 0.41% : 0.000008s : 45: predicate.virtual_output_eliminate 0.17% : 0.000003s : 22: predicate.virtual_view_grad_eliminate 0.22% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.119095 135 94.21% : 0.112200s : 55: func_graph_cloner_run.FuncGraphClonerGraph 5.79% : 0.006895s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.183048 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.60% : 0.007136s : 1: add_attr 0.60% : 0.007112s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000191s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.08% : 0.000968s : 1: auto_monad 0.01% : 0.000097s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.06% : 0.000731s : 1: bootstrap 0.00% : 0.000045s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000051s : 1: control_data_broadcast_order 0.00% : 0.000045s : 1: convert_after_rewriter 0.01% : 0.000082s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000035s : 1: environ_conv 0.02% : 0.000257s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000057s : 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% : 0.000008s : 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% : 0.000009s : 1: label_micro_interleaved_index 0.06% : 0.000674s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.12% : 0.001392s : 1: mutable_eliminate 0.00% : 0.000016s : 1: offloading_packed_experts 0.00% : 0.000045s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000058s : 1: opt.transform.mutable_eliminate 4.48% : 0.052961s : 95: opt.transform.opt_a 0.02% : 0.000191s : 1: opt.transform.opt_after_cconv 0.01% : 0.000098s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.000735s : 28: opt.transform.opt_b 0.02% : 0.000289s : 2: opt.transform.opt_trans_graph 0.02% : 0.000233s : 4: opt.transform.symbol_engine_opt 5.94% : 0.070315s : 1: opt_a 0.03% : 0.000401s : 1: opt_after_cconv 0.07% : 0.000843s : 1: opt_after_jit_grad 0.09% : 0.001030s : 1: opt_b 6.65% : 0.078693s : 1: optimize 0.00% : 0.000056s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000021s : 1: order_py_execute_after_rewriter 0.01% : 0.000069s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000015s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000006s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000007s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000015s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000010s : 1: parallel-infer-symbol 0.00% : 0.000005s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000006s : 1: pipeline_split 0.02% : 0.000278s : 1: pre_auto_parallel 0.02% : 0.000287s : 1: py_interpret_to_execute 0.00% : 0.000049s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.01% : 0.000132s : 1: remove_dup_value 0.54% : 0.006388s : 1: renormalize.infer 0.66% : 0.007821s : 1: renormalize.specialize 0.00% : 0.000007s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.09% : 0.001089s : 1: rewriter_after_opt_a 0.08% : 0.000910s : 1: rewriter_before_opt_a 0.00% : 0.000007s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000024s : 1: swap_dp_allreduce_reducescatter 0.10% : 0.001166s : 1: symbol_engine_optimizer 0.03% : 0.000329s : 1: tuple_transform 79.41% : 0.939400s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_11008_4096_4096_0[True-4096-1024] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_11008_4096_4096_0[True-4096-1024],max_mem:214.0M =============================== 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_11008_4096_4096_0[True-4096-1024] /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 ================== 2 passed, 26 warnings in 445.67s (0:07:25) ==================