==================================================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_006/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(168097:281473552867120,MainProcess):2026-01-29-17:37:54.857.652 [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 = 3.39217, [21] [bootstrap]: 0.00063403 [type_inference]: 3.09705 [event_method]: 2.12e-05 [auto_monad]: 0.00258584 [graph_reusing]: 7.91001e-06 [inline]: 2.96999e-06 [add_attr]: 0.136969, [1] [add_attr_with_inline]: 0.136917, [1] [Cycle 1]: 0.00011026, [2] [tag_attr]: 2.805e-05 [meta_addattr_fg_expand]: 5.53002e-06 [parallel-infer-symbol]: 4.60001e-06 [pre_auto_parallel]: 5.2e-05 [insert-virtual-dataset]: 2.91e-06 [parallel-infer-symbol-second]: 1.22999e-06 [dataset_repeat_opt]: 2.43002e-06 [pipeline_split]: 2.12001e-06 [optimize]: 0.153492, [53] [py_interpret_to_execute]: 3.429e-05 [rewriter_before_opt_a]: 0.00012337 [opt_a]: 0.148502, [2] [Cycle 1]: 0.0785613, [45] [expand_dump_flag]: 3.53e-06 [switch_simplify]: 4.344e-05 [loop_unroll]: 3.345e-05 [a_1]: 0.00085212 [with_stream_mark]: 2.485e-05 [recompute_prepare]: 2.292e-05 [updatestate_depend_eliminate]: 1.168e-05 [updatestate_assign_eliminate]: 1.422e-05 [updatestate_loads_eliminate]: 1.788e-05 [parameter_eliminate]: 2.41e-06 [a_2]: 0.00031459 [accelerated_algorithm]: 4.842e-05 [shard]: 2.04e-06 [meta_shard_fg_expand]: 4.71002e-06 [shard_inline]: 2.144e-05 [merge_send_recv]: 1.759e-05 [auto_parallel]: 1.518e-05 [parallel]: 4.404e-05 [flash_sp]: 1.298e-05 [merge_comm]: 1.22e-05 [allreduce_fusion]: 1.021e-05 [matmul_add_comm_reduction]: 2.071e-05 [allreduce_slice_to_reducescatter]: 7.7e-07 [virtual_shard_identity]: 2.484e-05 [virtual_dataset]: 2.119e-05 [get_grad_eliminate_]: 2.119e-05 [virtual_output]: 2.055e-05 [merge_forward]: 1.149e-05 [cell_reuse_recompute_pass]: 1.42e-06 [offload_activation]: 2.175e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.791e-05 [merge_recompute_call_nodes]: 1.95001e-06 [before_grad]: 3.585e-05 [set_forward_comm_id_for_comm_node_pass]: 1.147e-05 [meta_fg_expand]: 8.72e-06 [flash_sp_send_recv_attached]: 5.02999e-06 [receive_attached]: 1.287e-05 [after_resolve]: 3.281e-05 [a_after_grad]: 3.572e-05 [renormalize]: 0.0758369 [add_forward_monad_depend]: 1.249e-05 [auto_monad_grad]: 3.03e-06 [auto_monad_eliminator]: 6.663e-05 [cse]: 0.00028917 [a_3]: 0.00017393 [Cycle 2]: 0.0699238, [45] [expand_dump_flag]: 2.74001e-06 [switch_simplify]: 2.444e-05 [loop_unroll]: 2.304e-05 [a_1]: 0.00062195 [with_stream_mark]: 0.0674918 [recompute_prepare]: 7.557e-05 [updatestate_depend_eliminate]: 2.2e-05 [updatestate_assign_eliminate]: 1.315e-05 [updatestate_loads_eliminate]: 2.649e-05 [parameter_eliminate]: 3.43999e-06 [a_2]: 0.00039686 [accelerated_algorithm]: 3.406e-05 [shard]: 4.07e-06 [meta_shard_fg_expand]: 1.194e-05 [shard_inline]: 2.195e-05 [merge_send_recv]: 2.216e-05 [auto_parallel]: 2.518e-05 [parallel]: 1.388e-05 [flash_sp]: 5.45001e-06 [merge_comm]: 1.166e-05 [allreduce_fusion]: 1.058e-05 [matmul_add_comm_reduction]: 2.37e-05 [allreduce_slice_to_reducescatter]: 1.37e-06 [virtual_shard_identity]: 3.204e-05 [virtual_dataset]: 2.333e-05 [get_grad_eliminate_]: 3.026e-05 [virtual_output]: 2.333e-05 [merge_forward]: 1.236e-05 [cell_reuse_recompute_pass]: 3.35e-06 [offload_activation]: 2.353e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.599e-05 [merge_recompute_call_nodes]: 1.54e-06 [before_grad]: 3.564e-05 [set_forward_comm_id_for_comm_node_pass]: 1.235e-05 [meta_fg_expand]: 1.082e-05 [flash_sp_send_recv_attached]: 2.53e-06 [receive_attached]: 2.46e-06 [after_resolve]: 3.293e-05 [a_after_grad]: 3.531e-05 [renormalize]: 1.50001e-07 [add_forward_monad_depend]: 4.37998e-06 [auto_monad_grad]: 3.68e-06 [auto_monad_eliminator]: 7.911e-05 [cse]: 0.00011263 [a_3]: 0.00014807 [py_interpret_to_execute_after_opt_a]: 4.445e-05 [slice_cell_reuse_recomputed_activation]: 2.61e-06 [rewriter_after_opt_a]: 0.00030701 [convert_after_rewriter]: 2.202e-05 [order_py_execute_after_rewriter]: 1.211e-05 [mutable_eliminate]: 0.00092128 [opt_b]: 0.00084666, [1] [Cycle 1]: 0.00083428, [7] [b_1]: 0.00055251 [b_2]: 3.095e-05 [updatestate_depend_eliminate]: 2.156e-05 [updatestate_assign_eliminate]: 1.155e-05 [updatestate_loads_eliminate]: 1.935e-05 [renormalize]: 8.30012e-07 [cse]: 0.0001384 [optimize_parallel_all_gather_comm]: 4.51e-05 [overlap_param_gather]: 2.33002e-06 [cconv]: 4.683e-05 [loop_unroll]: 0.00070589 [opt_after_cconv]: 0.00036877, [1] [Cycle 1]: 0.00035847, [7] [c_1]: 0.00017041 [parameter_eliminate]: 7e-06 [updatestate_depend_eliminate]: 1.854e-05 [updatestate_assign_eliminate]: 1.09e-05 [updatestate_loads_eliminate]: 1.564e-05 [cse]: 8.941e-05 [renormalize]: 4.90021e-07 [remove_dup_value]: 0.00011588 [tuple_transform]: 0.00027311, [1] [Cycle 1]: 0.00026599, [4] [d_1]: 0.00020615 [none_parameter_eliminate]: 3.11999e-06 [renormalize]: 2.09984e-07 [switch_simplify]: 2.806e-05 [partial_unused_args_eliminate]: 2.56e-06 [add_recomputation]: 0.00016222 [cse_after_recomputation]: 8.199e-05, [1] [Cycle 1]: 7.519e-05, [1] [cse]: 6.595e-05 [environ_conv]: 4.455e-05 [swap_dp_allreduce_reducescatter]: 2.052e-05 [bias_add_comm_swap]: 4.12e-06 [label_micro_interleaved_index]: 5.52001e-06 [label_fine_grained_interleaved_index]: 2.85002e-06 [merge_cast_opt]: 1.44e-06 [slice_recompute_activation]: 2.33998e-06 [micro_interleaved_order_control]: 3.11999e-06 [assign_add_opt]: 1.59e-06 [ForceFp32Comm]: 9.50007e-07 [remove_cast_before_assign_add]: 1.65001e-06 [full_micro_interleaved_order_control]: 3.11001e-06 [reorder_send_recv_between_fp_bp]: 3.11001e-06 [comm_op_add_attrs]: 1.14e-06 [add_comm_op_reuse_tag]: 1.22999e-06 [interleave_split_concat_branches]: 1.49e-06 [interleave_parallel_branches]: 1.19998e-06 [overlap_opt_shard_in_pipeline]: 2.831e-05 [overlap_opt_shard_grad_in_pipeline]: 2.36e-06 [control_data_broadcast_order]: 3.668e-05 [grouped_pairwise_exchange_alltoall]: 1.86e-06 [offloading_packed_experts]: 1.069e-05 [overlap_recompute_and_grad_model_parallel]: 1.102e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.61998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.87001e-06 [overlap_recompute_comm]: 2.78998e-06 [overlap_grad_ring_attention]: 9.87999e-06 [overlap_grad_flash_sp]: 7.746e-05 [begin_end_overlap_inline]: 6.80011e-07 [split_matmul_comm_elemetwise]: 2.44999e-06 [split_layernorm_comm]: 2.10002e-06 [handle_group_info]: 1.40001e-06 [symbol_engine_optimizer]: 0.00026329, [1] [Cycle 1]: 0.00025591, [6] [build]: 2.492e-05 [elim_shapecalc]: 3.707e-05 [elim_not_effective]: 4.447e-05 [opt_reshape]: 5.864e-05 [fold_const_symbol]: 4.06e-05 [renormalize]: 2.3999e-07 [detach_backward]: 2.99999e-06 [pipeline_parallel_scheduler]: 1.77999e-06 [auto_monad_reorder]: 9.017e-05 [get_jit_bprop_graph]: 1.96e-06 [rewriter_after_jit_bprop_graph]: 6.80002e-06 [opt_after_jit_grad]: 0.00085475 [validate]: 0.00014814 Sums bootstrap : 0.000634s : 0.02% type_inference : 3.097053s : 95.18% event_method : 0.000021s : 0.00% auto_monad : 0.002586s : 0.08% graph_reusing : 0.000008s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000028s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000006s : 0.00% parallel-infer-symbol : 0.000005s : 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 : 0.000034s : 0.00% optimize.rewriter_before_opt_a : 0.000123s : 0.00% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000068s : 0.00% optimize.opt_a.loop_unroll : 0.000056s : 0.00% optimize.opt_a.a_1 : 0.001474s : 0.05% optimize.opt_a.with_stream_mark : 0.067517s : 2.08% optimize.opt_a.recompute_prepare : 0.000098s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000034s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000027s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000044s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000711s : 0.02% optimize.opt_a.accelerated_algorithm : 0.000082s : 0.00% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000017s : 0.00% optimize.opt_a.shard_inline : 0.000043s : 0.00% optimize.opt_a.merge_send_recv : 0.000040s : 0.00% optimize.opt_a.auto_parallel : 0.000040s : 0.00% optimize.opt_a.parallel : 0.000058s : 0.00% optimize.opt_a.flash_sp : 0.000018s : 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 : 0.000045s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000051s : 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 : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000045s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000084s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000071s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000024s : 0.00% optimize.opt_a.meta_fg_expand : 0.000020s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000015s : 0.00% optimize.opt_a.after_resolve : 0.000066s : 0.00% optimize.opt_a.a_after_grad : 0.000071s : 0.00% optimize.opt_a.renormalize : 0.075837s : 2.33% 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 : 0.000146s : 0.00% optimize.opt_a.cse : 0.000402s : 0.01% optimize.opt_a.a_3 : 0.000322s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000044s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000307s : 0.01% optimize.convert_after_rewriter : 0.000022s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000921s : 0.03% optimize.opt_b.b_1 : 0.000553s : 0.02% optimize.opt_b.b_2 : 0.000031s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000022s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000012s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000019s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000138s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000045s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000047s : 0.00% optimize.loop_unroll : 0.000706s : 0.02% optimize.opt_after_cconv.c_1 : 0.000170s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000019s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000016s : 0.00% optimize.opt_after_cconv.cse : 0.000089s : 0.00% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000116s : 0.00% optimize.tuple_transform.d_1 : 0.000206s : 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 : 0.000028s : 0.00% optimize.partial_unused_args_eliminate : 0.000003s : 0.00% optimize.add_recomputation : 0.000162s : 0.00% optimize.cse_after_recomputation.cse : 0.000066s : 0.00% optimize.environ_conv : 0.000045s : 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 : 0.000006s : 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 : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000002s : 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 : 0.000028s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000037s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000011s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000011s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000002s : 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 : 0.000010s : 0.00% optimize.overlap_grad_flash_sp : 0.000077s : 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 : 0.000025s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000037s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000044s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000059s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000041s : 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 : 0.000090s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000855s : 0.03% validate : 0.000148s : 0.00% Time group info: ------[substitution.] 0.000410 135 2.79% : 0.000011s : 2: substitution.depend_value_elim 1.41% : 0.000006s : 11: substitution.elim_not_effective 1.27% : 0.000005s : 11: substitution.fold_const_symbol 4.69% : 0.000019s : 18: substitution.graph_param_transform 32.38% : 0.000133s : 1: substitution.inline 2.92% : 0.000012s : 22: substitution.j_node_and_user_rematch 6.26% : 0.000026s : 2: substitution.less_batch_normalization 2.97% : 0.000012s : 18: substitution.load_eliminater 0.63% : 0.000003s : 2: substitution.opt_reshape 4.46% : 0.000018s : 22: substitution.remove_not_recompute_node 2.78% : 0.000011s : 8: substitution.replace_old_param 6.78% : 0.000028s : 4: substitution.reshape_eliminate 2.72% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 27.94% : 0.000115s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 3.096832 2 99.79% : 3.090187s : 1: type_inference.infer 0.21% : 0.006645s : 1: type_inference.specialize ------[replace.] 0.000020 1 100.00% : 0.000020s : 1: replace.inline ------[match.] 0.000132 1 100.00% : 0.000132s : 1: match.inline ------[predicate.] 0.000603 4131 0.74% : 0.000004s : 37: predicate.accumulaten_eliminater 1.13% : 0.000007s : 18: predicate.ad_related_special_op_eliminate 0.76% : 0.000005s : 36: predicate.addn_check_dump 0.75% : 0.000005s : 37: predicate.addn_zero_filter 0.70% : 0.000004s : 37: predicate.adjust_all_reduce_mul_add 2.17% : 0.000013s : 73: predicate.arithmetic_simplify 0.78% : 0.000005s : 37: predicate.cast_eliminate 0.83% : 0.000005s : 36: predicate.check_bprop_eliminate 0.74% : 0.000004s : 36: predicate.compare_switch_simplify 0.26% : 0.000002s : 18: predicate.const_output_eliminate 0.86% : 0.000005s : 36: predicate.depend_value_elim 0.81% : 0.000005s : 37: predicate.dict_get_item_const_eliminator 0.88% : 0.000005s : 37: predicate.dict_get_item_eliminator 0.73% : 0.000004s : 37: predicate.dict_set_item_eliminator 1.19% : 0.000007s : 36: predicate.dumpgradient_eliminate 0.32% : 0.000002s : 18: predicate.elim_not_effective 0.65% : 0.000004s : 18: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000007s : 55: predicate.environ_add_const_eliminate 1.09% : 0.000007s : 55: predicate.environ_get_add_eliminate 1.11% : 0.000007s : 55: predicate.environ_get_depend_swap 2.10% : 0.000013s : 91: predicate.environ_get_eliminate 1.12% : 0.000007s : 55: predicate.environ_get_set_eliminate 0.73% : 0.000004s : 38: predicate.exchange_switch_depend_value 1.19% : 0.000007s : 38: predicate.float_depend_g_call 0.83% : 0.000005s : 36: predicate.float_environ_get_switch 1.26% : 0.000008s : 54: predicate.float_tuple_getitem_switch 0.25% : 0.000002s : 18: predicate.fold_const_symbol 0.91% : 0.000006s : 36: predicate.get_grad_eliminate 0.31% : 0.000002s : 18: predicate.graph_param_transform 0.86% : 0.000005s : 36: predicate.incorporate_call 0.71% : 0.000004s : 36: predicate.incorporate_call_switch 5.21% : 0.000031s : 183: predicate.inline 1.05% : 0.000006s : 36: predicate.inline_without_move 0.46% : 0.000003s : 36: predicate.j_node_and_user_rematch 1.13% : 0.000007s : 36: predicate.less_batch_normalization 1.78% : 0.000011s : 73: predicate.list_to_tuple_eliminator_ 2.42% : 0.000015s : 110: predicate.load_eliminater 1.27% : 0.000008s : 18: predicate.loop_unroll_after_grad 0.98% : 0.000006s : 41: predicate.loop_unroll_before_grad 1.76% : 0.000011s : 73: predicate.make_slice_get_slice_eliminator 0.79% : 0.000005s : 36: predicate.merge_addn 0.80% : 0.000005s : 36: predicate.micro_step_allgather_replace 0.84% : 0.000005s : 36: predicate.mini_step_allgather_replace 0.75% : 0.000004s : 37: predicate.minmaximum_grad 1.43% : 0.000009s : 18: predicate.mutable_eliminate 0.73% : 0.000004s : 18: predicate.opt_reshape 0.49% : 0.000003s : 18: predicate.parallel_virtual_node 1.00% : 0.000006s : 38: predicate.partial_defer_inline 1.37% : 0.000008s : 55: predicate.partial_eliminate 0.74% : 0.000004s : 37: predicate.print_const_string_wrapper 0.82% : 0.000005s : 36: predicate.reduce_all_const_elim 0.97% : 0.000006s : 37: predicate.reduce_eliminate 2.36% : 0.000014s : 110: predicate.redundant_stop_gradient_eliminater 0.52% : 0.000003s : 36: predicate.remove_not_recompute_node 1.20% : 0.000007s : 73: predicate.replace_applicator 0.57% : 0.000003s : 36: predicate.replace_old_param 0.30% : 0.000002s : 18: predicate.reset_defer_inline 0.96% : 0.000006s : 37: predicate.reshape_eliminate 0.81% : 0.000005s : 36: predicate.row_tensor_add_zeros_like 0.70% : 0.000004s : 18: predicate.row_tensor_eliminate 1.16% : 0.000007s : 36: predicate.same_eliminate 0.77% : 0.000005s : 36: predicate.set_cell_output_no_recompute 0.92% : 0.000006s : 36: predicate.shard_identity_eliminate 0.98% : 0.000006s : 36: predicate.special_op_eliminate 0.94% : 0.000006s : 36: predicate.specialize_transform 1.17% : 0.000007s : 36: predicate.split_environ_get_set_with_tuple_value 0.99% : 0.000006s : 36: predicate.stack_unstack_eliminate 0.48% : 0.000003s : 18: predicate.switch_call_monad_eliminater 0.81% : 0.000005s : 38: predicate.switch_defer_inline 1.57% : 0.000009s : 74: predicate.switch_layer_defer_inline 3.30% : 0.000020s : 133: predicate.switch_simplify 0.75% : 0.000005s : 37: predicate.tile_eliminate 0.76% : 0.000005s : 37: predicate.transpose_eliminate 1.71% : 0.000010s : 73: predicate.tuple_list_convert_item_index_to_positive 1.71% : 0.000010s : 73: predicate.tuple_list_get_item_const_eliminator 1.74% : 0.000010s : 73: predicate.tuple_list_get_item_depend_reorder 3.05% : 0.000018s : 109: predicate.tuple_list_get_item_eliminator 1.64% : 0.000010s : 73: predicate.tuple_list_get_set_item_eliminator 2.64% : 0.000016s : 109: predicate.tuple_list_set_item_eliminator 1.85% : 0.000011s : 73: predicate.tuple_to_list_eliminator_ 2.34% : 0.000014s : 110: predicate.updatestate_pure_node_eliminater 3.35% : 0.000020s : 146: predicate.updatestate_useless_node_eliminater 0.48% : 0.000003s : 18: predicate.value_based_eliminate 0.89% : 0.000005s : 36: predicate.virtual_dataset_eliminate 0.90% : 0.000005s : 36: predicate.virtual_output_eliminate 0.45% : 0.000003s : 18: predicate.virtual_view_grad_eliminate 0.57% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.036100 58 92.70% : 0.033463s : 55: func_graph_cloner_run.FuncGraphClonerGraph 7.30% : 0.002636s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.762617 192 0.00% : 0.000004s : 1: ForceFp32Comm 3.64% : 0.136976s : 1: add_attr 3.64% : 0.136923s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000168s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.07% : 0.002607s : 1: auto_monad 0.00% : 0.000097s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.02% : 0.000672s : 1: bootstrap 0.00% : 0.000052s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000041s : 1: control_data_broadcast_order 0.00% : 0.000027s : 1: convert_after_rewriter 0.00% : 0.000086s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000049s : 1: environ_conv 0.00% : 0.000030s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 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% : 0.000006s : 1: inline 0.00% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000008s : 1: label_micro_interleaved_index 0.02% : 0.000721s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.02% : 0.000939s : 1: mutable_eliminate 0.00% : 0.000014s : 1: offloading_packed_experts 0.00% : 0.000042s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000060s : 1: opt.transform.mutable_eliminate 0.08% : 0.003194s : 78: opt.transform.opt_a 0.00% : 0.000168s : 1: opt.transform.opt_after_cconv 0.00% : 0.000089s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000535s : 28: opt.transform.opt_b 0.01% : 0.000230s : 2: opt.transform.opt_trans_graph 0.00% : 0.000174s : 4: opt.transform.symbol_engine_opt 3.95% : 0.148508s : 1: opt_a 0.01% : 0.000373s : 1: opt_after_cconv 0.02% : 0.000872s : 1: opt_after_jit_grad 0.02% : 0.000852s : 1: opt_b 4.08% : 0.153500s : 1: optimize 0.00% : 0.000050s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000082s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 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% : 0.000032s : 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% : 0.000014s : 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% : 0.000007s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000057s : 1: pre_auto_parallel 0.00% : 0.000039s : 1: py_interpret_to_execute 0.00% : 0.000050s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.00% : 0.000122s : 1: remove_dup_value 1.94% : 0.073075s : 1: renormalize.infer 0.07% : 0.002743s : 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% : 0.000320s : 1: rewriter_after_opt_a 0.00% : 0.000128s : 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% : 0.000025s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000267s : 1: symbol_engine_optimizer 0.01% : 0.000277s : 1: tuple_transform 82.31% : 3.097085s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_11008_4096_4096_1[False-4096-16] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_11008_4096_4096_1[False-4096-16],max_mem:174.0M [WARNING] ME(168097:281473552867120,MainProcess):2026-01-29-17:38:50.377.733 [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 = 1.00203, [21] [bootstrap]: 0.00075501 [type_inference]: 0.898944 [event_method]: 2.159e-05 [auto_monad]: 0.00041959 [graph_reusing]: 6.96001e-06 [inline]: 2.81999e-06 [add_attr]: 0.0793933, [1] [add_attr_with_inline]: 0.0793706, [1] [Cycle 1]: 8.289e-05, [2] [tag_attr]: 2.527e-05 [meta_addattr_fg_expand]: 5.17e-06 [parallel-infer-symbol]: 4.33001e-06 [pre_auto_parallel]: 4.356e-05 [insert-virtual-dataset]: 2.54001e-06 [parallel-infer-symbol-second]: 7.7e-07 [dataset_repeat_opt]: 2.27999e-06 [pipeline_split]: 2.05002e-06 [optimize]: 0.0213483, [53] [py_interpret_to_execute]: 3.613e-05 [rewriter_before_opt_a]: 0.00010665 [opt_a]: 0.0171604, [2] [Cycle 1]: 0.0150837, [45] [expand_dump_flag]: 2.71999e-06 [switch_simplify]: 4.049e-05 [loop_unroll]: 2.509e-05 [a_1]: 0.00104356 [with_stream_mark]: 3.483e-05 [recompute_prepare]: 3.077e-05 [updatestate_depend_eliminate]: 1.396e-05 [updatestate_assign_eliminate]: 1.506e-05 [updatestate_loads_eliminate]: 2.001e-05 [parameter_eliminate]: 2.39001e-06 [a_2]: 0.00035398 [accelerated_algorithm]: 5.044e-05 [shard]: 2.51e-06 [meta_shard_fg_expand]: 6.13002e-06 [shard_inline]: 2.303e-05 [merge_send_recv]: 1.831e-05 [auto_parallel]: 1.597e-05 [parallel]: 6.716e-05 [flash_sp]: 1.494e-05 [merge_comm]: 1.356e-05 [allreduce_fusion]: 1.185e-05 [matmul_add_comm_reduction]: 2.343e-05 [allreduce_slice_to_reducescatter]: 9.39996e-07 [virtual_shard_identity]: 2.93e-05 [virtual_dataset]: 2.402e-05 [get_grad_eliminate_]: 2.354e-05 [virtual_output]: 2.412e-05 [merge_forward]: 1.35e-05 [cell_reuse_recompute_pass]: 2.82002e-06 [offload_activation]: 2.305e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.035e-05 [merge_recompute_call_nodes]: 1.69e-06 [before_grad]: 3.972e-05 [set_forward_comm_id_for_comm_node_pass]: 1.337e-05 [meta_fg_expand]: 9.52999e-06 [flash_sp_send_recv_attached]: 6.24999e-06 [receive_attached]: 2.34999e-06 [after_resolve]: 3.542e-05 [a_after_grad]: 4.025e-05 [renormalize]: 0.0109815 [add_forward_monad_depend]: 8.82e-06 [auto_monad_grad]: 2.84999e-06 [auto_monad_eliminator]: 6.3e-05 [cse]: 0.00131244 [a_3]: 0.00017962 [Cycle 2]: 0.00205989, [45] [expand_dump_flag]: 3.23e-06 [switch_simplify]: 2.567e-05 [loop_unroll]: 2.354e-05 [a_1]: 0.00064802 [with_stream_mark]: 2.805e-05 [recompute_prepare]: 2.324e-05 [updatestate_depend_eliminate]: 1.251e-05 [updatestate_assign_eliminate]: 1.119e-05 [updatestate_loads_eliminate]: 1.805e-05 [parameter_eliminate]: 2.16e-06 [a_2]: 0.00030631 [accelerated_algorithm]: 2.899e-05 [shard]: 2.16e-06 [meta_shard_fg_expand]: 7.00002e-06 [shard_inline]: 2.108e-05 [merge_send_recv]: 1.784e-05 [auto_parallel]: 1.729e-05 [parallel]: 1.217e-05 [flash_sp]: 4.74e-06 [merge_comm]: 1.078e-05 [allreduce_fusion]: 1.057e-05 [matmul_add_comm_reduction]: 1.971e-05 [allreduce_slice_to_reducescatter]: 1.03001e-06 [virtual_shard_identity]: 2.346e-05 [virtual_dataset]: 2.097e-05 [get_grad_eliminate_]: 1.952e-05 [virtual_output]: 2.142e-05 [merge_forward]: 1.132e-05 [cell_reuse_recompute_pass]: 3.25e-06 [offload_activation]: 1.987e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.029e-05 [merge_recompute_call_nodes]: 1.76003e-06 [before_grad]: 3.271e-05 [set_forward_comm_id_for_comm_node_pass]: 1.136e-05 [meta_fg_expand]: 9.38002e-06 [flash_sp_send_recv_attached]: 2.09e-06 [receive_attached]: 2.39999e-06 [after_resolve]: 2.905e-05 [a_after_grad]: 3.363e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 3.14001e-06 [auto_monad_grad]: 2.51e-06 [auto_monad_eliminator]: 5.575e-05 [cse]: 7.731e-05 [a_3]: 0.0001396 [py_interpret_to_execute_after_opt_a]: 3.177e-05 [slice_cell_reuse_recomputed_activation]: 2.19001e-06 [rewriter_after_opt_a]: 0.00022766 [convert_after_rewriter]: 1.895e-05 [order_py_execute_after_rewriter]: 1.183e-05 [mutable_eliminate]: 0.00080784 [opt_b]: 0.00071194, [1] [Cycle 1]: 0.00070265, [7] [b_1]: 0.00050436 [b_2]: 2.532e-05 [updatestate_depend_eliminate]: 1.687e-05 [updatestate_assign_eliminate]: 1.081e-05 [updatestate_loads_eliminate]: 1.514e-05 [renormalize]: 7.40023e-07 [cse]: 8.622e-05 [optimize_parallel_all_gather_comm]: 3.672e-05 [overlap_param_gather]: 3.36999e-06 [cconv]: 4.093e-05 [loop_unroll]: 0.00056998 [opt_after_cconv]: 0.00029871, [1] [Cycle 1]: 0.00029214, [7] [c_1]: 0.00014067 [parameter_eliminate]: 5.71e-06 [updatestate_depend_eliminate]: 1.467e-05 [updatestate_assign_eliminate]: 9.66e-06 [updatestate_loads_eliminate]: 1.264e-05 [cse]: 6.997e-05 [renormalize]: 5.89993e-07 [remove_dup_value]: 9.431e-05 [tuple_transform]: 0.00020511, [1] [Cycle 1]: 0.00019888, [4] [d_1]: 0.00015251 [none_parameter_eliminate]: 2.34999e-06 [renormalize]: 2.30008e-07 [switch_simplify]: 2.292e-05 [partial_unused_args_eliminate]: 2.24001e-06 [add_recomputation]: 0.00022816 [cse_after_recomputation]: 6.602e-05, [1] [Cycle 1]: 5.957e-05, [1] [cse]: 5.235e-05 [environ_conv]: 4.405e-05 [swap_dp_allreduce_reducescatter]: 1.492e-05 [bias_add_comm_swap]: 2.98998e-06 [label_micro_interleaved_index]: 4.75001e-06 [label_fine_grained_interleaved_index]: 3.5e-06 [merge_cast_opt]: 1.40001e-06 [slice_recompute_activation]: 2.56998e-06 [micro_interleaved_order_control]: 2.25002e-06 [assign_add_opt]: 1.79998e-06 [ForceFp32Comm]: 8.89995e-07 [remove_cast_before_assign_add]: 1.30001e-06 [full_micro_interleaved_order_control]: 2.26998e-06 [reorder_send_recv_between_fp_bp]: 2.75997e-06 [comm_op_add_attrs]: 1.08001e-06 [add_comm_op_reuse_tag]: 1.05001e-06 [interleave_split_concat_branches]: 1.23002e-06 [interleave_parallel_branches]: 1.37999e-06 [overlap_opt_shard_in_pipeline]: 2.71999e-06 [overlap_opt_shard_grad_in_pipeline]: 2.15002e-06 [control_data_broadcast_order]: 3.394e-05 [grouped_pairwise_exchange_alltoall]: 1.51002e-06 [offloading_packed_experts]: 8.92e-06 [overlap_recompute_and_grad_model_parallel]: 9.52001e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.20001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.27e-06 [overlap_recompute_comm]: 2.80002e-06 [overlap_grad_ring_attention]: 9.70002e-06 [overlap_grad_flash_sp]: 4.773e-05 [begin_end_overlap_inline]: 5.69999e-07 [split_matmul_comm_elemetwise]: 2.17001e-06 [split_layernorm_comm]: 2.12001e-06 [handle_group_info]: 1.17e-06 [symbol_engine_optimizer]: 0.00019031, [1] [Cycle 1]: 0.00018364, [6] [build]: 1.855e-05 [elim_shapecalc]: 3.064e-05 [elim_not_effective]: 3.823e-05 [opt_reshape]: 2.748e-05 [fold_const_symbol]: 3.209e-05 [renormalize]: 3.89991e-07 [detach_backward]: 2.51e-06 [pipeline_parallel_scheduler]: 1.77001e-06 [auto_monad_reorder]: 6.526e-05 [get_jit_bprop_graph]: 2.18998e-06 [rewriter_after_jit_bprop_graph]: 5.15999e-06 [opt_after_jit_grad]: 0.00061178 [validate]: 0.00015082 Sums bootstrap : 0.000755s : 0.08% type_inference : 0.898944s : 97.57% event_method : 0.000022s : 0.00% auto_monad : 0.000420s : 0.05% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000025s : 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 : 0.000044s : 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 : 0.000107s : 0.01% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000066s : 0.01% optimize.opt_a.loop_unroll : 0.000049s : 0.01% optimize.opt_a.a_1 : 0.001692s : 0.18% optimize.opt_a.with_stream_mark : 0.000063s : 0.01% optimize.opt_a.recompute_prepare : 0.000054s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000026s : 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 : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000660s : 0.07% optimize.opt_a.accelerated_algorithm : 0.000079s : 0.01% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.00% optimize.opt_a.shard_inline : 0.000044s : 0.00% optimize.opt_a.merge_send_recv : 0.000036s : 0.00% optimize.opt_a.auto_parallel : 0.000033s : 0.00% optimize.opt_a.parallel : 0.000079s : 0.01% optimize.opt_a.flash_sp : 0.000020s : 0.00% optimize.opt_a.merge_comm : 0.000024s : 0.00% optimize.opt_a.allreduce_fusion : 0.000022s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000043s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000053s : 0.01% optimize.opt_a.virtual_dataset : 0.000045s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000043s : 0.00% optimize.opt_a.virtual_output : 0.000046s : 0.00% optimize.opt_a.merge_forward : 0.000025s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000043s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000091s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000072s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000025s : 0.00% optimize.opt_a.meta_fg_expand : 0.000019s : 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 : 0.000064s : 0.01% optimize.opt_a.a_after_grad : 0.000074s : 0.01% optimize.opt_a.renormalize : 0.010982s : 1.19% optimize.opt_a.add_forward_monad_depend : 0.000012s : 0.00% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000119s : 0.01% optimize.opt_a.cse : 0.001390s : 0.15% optimize.opt_a.a_3 : 0.000319s : 0.03% 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 : 0.000228s : 0.02% optimize.convert_after_rewriter : 0.000019s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000808s : 0.09% optimize.opt_b.b_1 : 0.000504s : 0.05% 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 : 0.000011s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000015s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000086s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000037s : 0.00% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000041s : 0.00% optimize.loop_unroll : 0.000570s : 0.06% optimize.opt_after_cconv.c_1 : 0.000141s : 0.02% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 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 : 0.000070s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000094s : 0.01% optimize.tuple_transform.d_1 : 0.000153s : 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 : 0.000023s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000228s : 0.02% optimize.cse_after_recomputation.cse : 0.000052s : 0.01% optimize.environ_conv : 0.000044s : 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 : 0.000005s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000003s : 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 : 0.000002s : 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 : 0.000003s : 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 : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000010s : 0.00% optimize.overlap_grad_flash_sp : 0.000048s : 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 : 0.000019s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000031s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000038s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000027s : 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 : 0.000065s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000612s : 0.07% validate : 0.000151s : 0.02% Time group info: ------[substitution.] 0.000372 135 2.91% : 0.000011s : 2: substitution.depend_value_elim 1.26% : 0.000005s : 11: substitution.elim_not_effective 1.07% : 0.000004s : 11: substitution.fold_const_symbol 3.94% : 0.000015s : 18: substitution.graph_param_transform 33.75% : 0.000125s : 1: substitution.inline 2.89% : 0.000011s : 22: substitution.j_node_and_user_rematch 6.82% : 0.000025s : 2: substitution.less_batch_normalization 2.92% : 0.000011s : 18: substitution.load_eliminater 0.74% : 0.000003s : 2: substitution.opt_reshape 4.98% : 0.000018s : 22: substitution.remove_not_recompute_node 2.58% : 0.000010s : 8: substitution.replace_old_param 7.75% : 0.000029s : 4: substitution.reshape_eliminate 2.73% : 0.000010s : 6: substitution.updatestate_pure_node_eliminater 25.65% : 0.000095s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.898826 2 99.39% : 0.893328s : 1: type_inference.infer 0.61% : 0.005498s : 1: type_inference.specialize ------[replace.] 0.000017 1 100.00% : 0.000017s : 1: replace.inline ------[match.] 0.000124 1 100.00% : 0.000124s : 1: match.inline ------[predicate.] 0.000593 4131 0.79% : 0.000005s : 37: predicate.accumulaten_eliminater 0.81% : 0.000005s : 18: predicate.ad_related_special_op_eliminate 0.81% : 0.000005s : 36: predicate.addn_check_dump 0.88% : 0.000005s : 37: predicate.addn_zero_filter 0.74% : 0.000004s : 37: predicate.adjust_all_reduce_mul_add 2.13% : 0.000013s : 73: predicate.arithmetic_simplify 0.85% : 0.000005s : 37: predicate.cast_eliminate 0.82% : 0.000005s : 36: predicate.check_bprop_eliminate 0.82% : 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 0.94% : 0.000006s : 37: predicate.dict_get_item_const_eliminator 0.91% : 0.000005s : 37: predicate.dict_get_item_eliminator 0.77% : 0.000005s : 37: predicate.dict_set_item_eliminator 0.98% : 0.000006s : 36: predicate.dumpgradient_eliminate 0.29% : 0.000002s : 18: predicate.elim_not_effective 0.48% : 0.000003s : 18: predicate.elim_shapecalc_of_broadcastargs 1.23% : 0.000007s : 55: predicate.environ_add_const_eliminate 1.21% : 0.000007s : 55: predicate.environ_get_add_eliminate 1.11% : 0.000007s : 55: predicate.environ_get_depend_swap 1.95% : 0.000012s : 91: predicate.environ_get_eliminate 1.12% : 0.000007s : 55: predicate.environ_get_set_eliminate 0.82% : 0.000005s : 38: predicate.exchange_switch_depend_value 1.44% : 0.000009s : 38: predicate.float_depend_g_call 0.83% : 0.000005s : 36: predicate.float_environ_get_switch 1.29% : 0.000008s : 54: predicate.float_tuple_getitem_switch 0.26% : 0.000002s : 18: predicate.fold_const_symbol 0.87% : 0.000005s : 36: predicate.get_grad_eliminate 0.32% : 0.000002s : 18: predicate.graph_param_transform 0.85% : 0.000005s : 36: predicate.incorporate_call 0.80% : 0.000005s : 36: predicate.incorporate_call_switch 5.64% : 0.000033s : 183: predicate.inline 1.09% : 0.000006s : 36: predicate.inline_without_move 0.52% : 0.000003s : 36: predicate.j_node_and_user_rematch 1.20% : 0.000007s : 36: predicate.less_batch_normalization 1.76% : 0.000010s : 73: predicate.list_to_tuple_eliminator_ 2.41% : 0.000014s : 110: predicate.load_eliminater 0.95% : 0.000006s : 18: predicate.loop_unroll_after_grad 0.99% : 0.000006s : 41: predicate.loop_unroll_before_grad 1.71% : 0.000010s : 73: predicate.make_slice_get_slice_eliminator 0.88% : 0.000005s : 36: predicate.merge_addn 0.80% : 0.000005s : 36: predicate.micro_step_allgather_replace 0.78% : 0.000005s : 36: predicate.mini_step_allgather_replace 0.73% : 0.000004s : 37: predicate.minmaximum_grad 0.87% : 0.000005s : 18: predicate.mutable_eliminate 0.51% : 0.000003s : 18: predicate.opt_reshape 0.48% : 0.000003s : 18: predicate.parallel_virtual_node 1.10% : 0.000007s : 38: predicate.partial_defer_inline 1.49% : 0.000009s : 55: predicate.partial_eliminate 0.78% : 0.000005s : 37: predicate.print_const_string_wrapper 0.82% : 0.000005s : 36: predicate.reduce_all_const_elim 1.12% : 0.000007s : 37: predicate.reduce_eliminate 2.36% : 0.000014s : 110: predicate.redundant_stop_gradient_eliminater 0.55% : 0.000003s : 36: predicate.remove_not_recompute_node 1.36% : 0.000008s : 73: predicate.replace_applicator 0.57% : 0.000003s : 36: predicate.replace_old_param 0.34% : 0.000002s : 18: predicate.reset_defer_inline 0.89% : 0.000005s : 37: predicate.reshape_eliminate 0.84% : 0.000005s : 36: predicate.row_tensor_add_zeros_like 0.54% : 0.000003s : 18: predicate.row_tensor_eliminate 1.16% : 0.000007s : 36: predicate.same_eliminate 0.61% : 0.000004s : 36: predicate.set_cell_output_no_recompute 0.96% : 0.000006s : 36: predicate.shard_identity_eliminate 0.86% : 0.000005s : 36: predicate.special_op_eliminate 1.00% : 0.000006s : 36: predicate.specialize_transform 1.02% : 0.000006s : 36: predicate.split_environ_get_set_with_tuple_value 1.04% : 0.000006s : 36: predicate.stack_unstack_eliminate 0.58% : 0.000003s : 18: predicate.switch_call_monad_eliminater 0.89% : 0.000005s : 38: predicate.switch_defer_inline 1.71% : 0.000010s : 74: predicate.switch_layer_defer_inline 3.18% : 0.000019s : 133: predicate.switch_simplify 0.77% : 0.000005s : 37: predicate.tile_eliminate 0.78% : 0.000005s : 37: predicate.transpose_eliminate 1.70% : 0.000010s : 73: predicate.tuple_list_convert_item_index_to_positive 1.68% : 0.000010s : 73: predicate.tuple_list_get_item_const_eliminator 1.72% : 0.000010s : 73: predicate.tuple_list_get_item_depend_reorder 2.98% : 0.000018s : 109: predicate.tuple_list_get_item_eliminator 1.84% : 0.000011s : 73: predicate.tuple_list_get_set_item_eliminator 2.65% : 0.000016s : 109: predicate.tuple_list_set_item_eliminator 1.63% : 0.000010s : 73: predicate.tuple_to_list_eliminator_ 2.38% : 0.000014s : 110: predicate.updatestate_pure_node_eliminater 3.45% : 0.000020s : 146: predicate.updatestate_useless_node_eliminater 0.44% : 0.000003s : 18: predicate.value_based_eliminate 0.89% : 0.000005s : 36: predicate.virtual_dataset_eliminate 0.88% : 0.000005s : 36: predicate.virtual_output_eliminate 0.40% : 0.000002s : 18: predicate.virtual_view_grad_eliminate 0.46% : 0.000003s : 18: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.065405 58 94.41% : 0.061746s : 55: func_graph_cloner_run.FuncGraphClonerGraph 5.59% : 0.003659s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.117842 192 0.00% : 0.000003s : 1: ForceFp32Comm 7.10% : 0.079402s : 1: add_attr 7.10% : 0.079376s : 1: add_attr_with_inline 0.00% : 0.000003s : 1: add_comm_op_reuse_tag 0.02% : 0.000236s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.04% : 0.000434s : 1: auto_monad 0.01% : 0.000071s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.07% : 0.000807s : 1: bootstrap 0.00% : 0.000044s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000038s : 1: control_data_broadcast_order 0.00% : 0.000024s : 1: convert_after_rewriter 0.01% : 0.000069s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000050s : 1: environ_conv 0.00% : 0.000031s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 0.00% : 0.000004s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 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% : 0.000007s : 1: label_fine_grained_interleaved_index 0.00% : 0.000008s : 1: label_micro_interleaved_index 0.05% : 0.000582s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.07% : 0.000823s : 1: mutable_eliminate 0.00% : 0.000012s : 1: offloading_packed_experts 0.00% : 0.000035s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000039s : 1: opt.transform.mutable_eliminate 0.30% : 0.003319s : 78: opt.transform.opt_a 0.01% : 0.000139s : 1: opt.transform.opt_after_cconv 0.01% : 0.000074s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000493s : 28: opt.transform.opt_b 0.02% : 0.000172s : 2: opt.transform.opt_trans_graph 0.01% : 0.000124s : 4: opt.transform.symbol_engine_opt 1.54% : 0.017165s : 1: opt_a 0.03% : 0.000303s : 1: opt_after_cconv 0.06% : 0.000625s : 1: opt_after_jit_grad 0.06% : 0.000716s : 1: opt_b 1.91% : 0.021354s : 1: optimize 0.00% : 0.000041s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.00% : 0.000052s : 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% : 0.000006s : 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% : 0.000009s : 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% : 0.000049s : 1: pre_auto_parallel 0.00% : 0.000040s : 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% : 0.000100s : 1: remove_dup_value 0.62% : 0.006939s : 1: renormalize.infer 0.36% : 0.004022s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000237s : 1: rewriter_after_opt_a 0.01% : 0.000111s : 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% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000018s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000193s : 1: symbol_engine_optimizer 0.02% : 0.000208s : 1: tuple_transform 80.42% : 0.898988s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_qkv_11008_4096_4096_1[False-4096-1024] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_qkv_11008_4096_4096_1[False-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_1[False-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 482.01s (0:08:02) ==================