==================================================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 3 items test_qbmm_split.py [WARNING] ME(160491:281473110478640,MainProcess):2026-01-29-17:37:42.107.798 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 2.65644, [21] [bootstrap]: 0.0407493 [type_inference]: 2.33684 [event_method]: 0.00021037 [auto_monad]: 0.0008009 [graph_reusing]: 4.947e-05 [inline]: 5.85002e-06 [add_attr]: 0.00879156, [1] [add_attr_with_inline]: 0.00877619, [1] [Cycle 1]: 0.00032888, [2] [tag_attr]: 0.00019129 [meta_addattr_fg_expand]: 4.957e-05 [parallel-infer-symbol]: 3.85e-06 [pre_auto_parallel]: 0.00025247 [insert-virtual-dataset]: 2.84001e-06 [parallel-infer-symbol-second]: 1.27999e-06 [dataset_repeat_opt]: 2.17999e-06 [pipeline_split]: 1.97001e-06 [optimize]: 0.267418, [53] [py_interpret_to_execute]: 0.00018408 [rewriter_before_opt_a]: 0.00077587 [opt_a]: 0.260242, [2] [Cycle 1]: 0.157449, [45] [expand_dump_flag]: 2.058e-05 [switch_simplify]: 0.0006956 [loop_unroll]: 0.00025464 [a_1]: 0.143654 [with_stream_mark]: 0.00010625 [recompute_prepare]: 4.845e-05 [updatestate_depend_eliminate]: 2.541e-05 [updatestate_assign_eliminate]: 2.28e-05 [updatestate_loads_eliminate]: 2.857e-05 [parameter_eliminate]: 3.14001e-06 [a_2]: 0.000968 [accelerated_algorithm]: 7.156e-05 [shard]: 2.63998e-06 [meta_shard_fg_expand]: 2.249e-05 [shard_inline]: 2.729e-05 [merge_send_recv]: 2.215e-05 [auto_parallel]: 2.274e-05 [parallel]: 6.081e-05 [flash_sp]: 1.665e-05 [merge_comm]: 1.712e-05 [allreduce_fusion]: 1.523e-05 [matmul_add_comm_reduction]: 2.46e-05 [allreduce_slice_to_reducescatter]: 8.09989e-07 [virtual_shard_identity]: 3.2e-05 [virtual_dataset]: 2.622e-05 [get_grad_eliminate_]: 2.529e-05 [virtual_output]: 2.552e-05 [merge_forward]: 1.551e-05 [cell_reuse_recompute_pass]: 2.26e-06 [offload_activation]: 2.746e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.201e-05 [merge_recompute_call_nodes]: 1.59998e-06 [before_grad]: 4.64e-05 [set_forward_comm_id_for_comm_node_pass]: 1.709e-05 [meta_fg_expand]: 1.707e-05 [flash_sp_send_recv_attached]: 5.32001e-06 [receive_attached]: 2.79001e-06 [after_resolve]: 3.55e-05 [a_after_grad]: 4.197e-05 [renormalize]: 0.0097946 [add_forward_monad_depend]: 1.394e-05 [auto_monad_grad]: 3.76999e-06 [auto_monad_eliminator]: 0.00010331 [cse]: 0.00037816 [a_3]: 0.00020439 [Cycle 2]: 0.102774, [45] [expand_dump_flag]: 2.79999e-06 [switch_simplify]: 2.921e-05 [loop_unroll]: 2.499e-05 [a_1]: 0.00078148 [with_stream_mark]: 3.193e-05 [recompute_prepare]: 2.776e-05 [updatestate_depend_eliminate]: 1.672e-05 [updatestate_assign_eliminate]: 1.485e-05 [updatestate_loads_eliminate]: 2.067e-05 [parameter_eliminate]: 2.29999e-06 [a_2]: 0.00039123 [accelerated_algorithm]: 3.604e-05 [shard]: 2.14999e-06 [meta_shard_fg_expand]: 8.64e-06 [shard_inline]: 2.547e-05 [merge_send_recv]: 2.37e-05 [auto_parallel]: 2.352e-05 [parallel]: 9.54999e-06 [flash_sp]: 4.65001e-06 [merge_comm]: 1.623e-05 [allreduce_fusion]: 1.464e-05 [matmul_add_comm_reduction]: 2.347e-05 [allreduce_slice_to_reducescatter]: 6.89994e-07 [virtual_shard_identity]: 2.893e-05 [virtual_dataset]: 2.499e-05 [get_grad_eliminate_]: 2.329e-05 [virtual_output]: 2.366e-05 [merge_forward]: 1.493e-05 [cell_reuse_recompute_pass]: 3.88999e-06 [offload_activation]: 2.663e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.699e-05 [merge_recompute_call_nodes]: 1.77001e-06 [before_grad]: 0.100169 [set_forward_comm_id_for_comm_node_pass]: 4.389e-05 [meta_fg_expand]: 1.869e-05 [flash_sp_send_recv_attached]: 2.59001e-06 [receive_attached]: 2.66e-06 [after_resolve]: 5.143e-05 [a_after_grad]: 4.111e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 7.56001e-06 [auto_monad_grad]: 2.78e-06 [auto_monad_eliminator]: 8.564e-05 [cse]: 0.00011979 [a_3]: 0.00017803 [py_interpret_to_execute_after_opt_a]: 4.034e-05 [slice_cell_reuse_recomputed_activation]: 2.65002e-06 [rewriter_after_opt_a]: 0.00093918 [convert_after_rewriter]: 3.287e-05 [order_py_execute_after_rewriter]: 1.64e-05 [mutable_eliminate]: 0.00083619 [opt_b]: 0.00099249, [1] [Cycle 1]: 0.00098211, [7] [b_1]: 0.00068138 [b_2]: 2.791e-05 [updatestate_depend_eliminate]: 2.414e-05 [updatestate_assign_eliminate]: 1.513e-05 [updatestate_loads_eliminate]: 2.18e-05 [renormalize]: 1.22999e-06 [cse]: 0.00015212 [optimize_parallel_all_gather_comm]: 5.033e-05 [overlap_param_gather]: 7.13998e-06 [cconv]: 4.271e-05 [loop_unroll]: 0.00074038 [opt_after_cconv]: 0.00043702, [1] [Cycle 1]: 0.00042782, [7] [c_1]: 0.00017895 [parameter_eliminate]: 6.59001e-06 [updatestate_depend_eliminate]: 2.787e-05 [updatestate_assign_eliminate]: 1.998e-05 [updatestate_loads_eliminate]: 2.302e-05 [cse]: 0.0001145 [renormalize]: 9.30013e-07 [remove_dup_value]: 0.00013216 [tuple_transform]: 0.00034313, [1] [Cycle 1]: 0.00033556, [4] [d_1]: 0.00026769 [none_parameter_eliminate]: 3.63e-06 [renormalize]: 4.00003e-07 [switch_simplify]: 3.181e-05 [partial_unused_args_eliminate]: 2.59001e-06 [add_recomputation]: 0.00019356 [cse_after_recomputation]: 0.00010029, [1] [Cycle 1]: 9.283e-05, [1] [cse]: 8.247e-05 [environ_conv]: 4.369e-05 [swap_dp_allreduce_reducescatter]: 2.459e-05 [bias_add_comm_swap]: 4.01001e-06 [label_micro_interleaved_index]: 8.67e-06 [label_fine_grained_interleaved_index]: 3.25e-06 [merge_cast_opt]: 1.81e-06 [slice_recompute_activation]: 2.03997e-06 [micro_interleaved_order_control]: 3.06999e-06 [assign_add_opt]: 1.52001e-06 [ForceFp32Comm]: 1.22e-06 [remove_cast_before_assign_add]: 1.25999e-06 [full_micro_interleaved_order_control]: 2.81e-06 [reorder_send_recv_between_fp_bp]: 2.81e-06 [comm_op_add_attrs]: 1.22999e-06 [add_comm_op_reuse_tag]: 1.18001e-06 [interleave_split_concat_branches]: 1.25001e-06 [interleave_parallel_branches]: 1.14e-06 [overlap_opt_shard_in_pipeline]: 2.534e-05 [overlap_opt_shard_grad_in_pipeline]: 2.32999e-06 [control_data_broadcast_order]: 5.447e-05 [grouped_pairwise_exchange_alltoall]: 1.74e-06 [offloading_packed_experts]: 1.337e-05 [overlap_recompute_and_grad_model_parallel]: 1.268e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.44e-06 [overlap_recompute_allgather_and_fa_grad]: 1.55999e-06 [overlap_recompute_comm]: 2.19999e-06 [overlap_grad_ring_attention]: 1.154e-05 [overlap_grad_flash_sp]: 7.817e-05 [begin_end_overlap_inline]: 6.09987e-07 [split_matmul_comm_elemetwise]: 2.85002e-06 [split_layernorm_comm]: 1.75001e-06 [handle_group_info]: 1.05001e-06 [symbol_engine_optimizer]: 0.00065298, [1] [Cycle 1]: 0.00064383, [6] [build]: 0.00033321 [elim_shapecalc]: 4.919e-05 [elim_not_effective]: 7.54e-05 [opt_reshape]: 4.294e-05 [fold_const_symbol]: 7.433e-05 [renormalize]: 4.7998e-07 [detach_backward]: 3.12002e-06 [pipeline_parallel_scheduler]: 1.79e-06 [auto_monad_reorder]: 9.883e-05 [get_jit_bprop_graph]: 2.04e-06 [rewriter_after_jit_bprop_graph]: 7.38e-06 [opt_after_jit_grad]: 0.00077974 [validate]: 0.00014951 Sums bootstrap : 0.040749s : 1.54% type_inference : 2.336842s : 88.31% event_method : 0.000210s : 0.01% auto_monad : 0.000801s : 0.03% graph_reusing : 0.000049s : 0.00% inline : 0.000006s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000191s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000050s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000252s : 0.01% 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 : 0.000184s : 0.01% optimize.rewriter_before_opt_a : 0.000776s : 0.03% optimize.opt_a.expand_dump_flag : 0.000023s : 0.00% optimize.opt_a.switch_simplify : 0.000725s : 0.03% optimize.opt_a.loop_unroll : 0.000280s : 0.01% optimize.opt_a.a_1 : 0.144435s : 5.46% optimize.opt_a.with_stream_mark : 0.000138s : 0.01% optimize.opt_a.recompute_prepare : 0.000076s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000042s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000049s : 0.00% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.001359s : 0.05% optimize.opt_a.accelerated_algorithm : 0.000108s : 0.00% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000031s : 0.00% optimize.opt_a.shard_inline : 0.000053s : 0.00% optimize.opt_a.merge_send_recv : 0.000046s : 0.00% optimize.opt_a.auto_parallel : 0.000046s : 0.00% optimize.opt_a.parallel : 0.000070s : 0.00% optimize.opt_a.flash_sp : 0.000021s : 0.00% optimize.opt_a.merge_comm : 0.000033s : 0.00% optimize.opt_a.allreduce_fusion : 0.000030s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000048s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000061s : 0.00% optimize.opt_a.virtual_dataset : 0.000051s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000049s : 0.00% optimize.opt_a.virtual_output : 0.000049s : 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 : 0.000099s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.100215s : 3.79% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000061s : 0.00% optimize.opt_a.meta_fg_expand : 0.000036s : 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 : 0.000087s : 0.00% optimize.opt_a.a_after_grad : 0.000083s : 0.00% optimize.opt_a.renormalize : 0.009795s : 0.37% optimize.opt_a.add_forward_monad_depend : 0.000021s : 0.00% optimize.opt_a.auto_monad_grad : 0.000007s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000189s : 0.01% optimize.opt_a.cse : 0.000498s : 0.02% optimize.opt_a.a_3 : 0.000382s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000040s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000939s : 0.04% optimize.convert_after_rewriter : 0.000033s : 0.00% optimize.order_py_execute_after_rewriter : 0.000016s : 0.00% optimize.mutable_eliminate : 0.000836s : 0.03% optimize.opt_b.b_1 : 0.000681s : 0.03% optimize.opt_b.b_2 : 0.000028s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000024s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000015s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000022s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000152s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000050s : 0.00% optimize.overlap_param_gather : 0.000007s : 0.00% optimize.cconv : 0.000043s : 0.00% optimize.loop_unroll : 0.000740s : 0.03% optimize.opt_after_cconv.c_1 : 0.000179s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000028s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000020s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000023s : 0.00% optimize.opt_after_cconv.cse : 0.000114s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000132s : 0.00% optimize.tuple_transform.d_1 : 0.000268s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000004s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000032s : 0.00% optimize.partial_unused_args_eliminate : 0.000003s : 0.00% optimize.add_recomputation : 0.000194s : 0.01% optimize.cse_after_recomputation.cse : 0.000082s : 0.00% optimize.environ_conv : 0.000044s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000025s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000009s : 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 : 0.000025s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000054s : 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 : 0.000013s : 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 : 0.000078s : 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 : 0.000333s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000049s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000075s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000043s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000074s : 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 : 0.000099s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000780s : 0.03% validate : 0.000150s : 0.01% Time group info: ------[substitution.] 0.002979 608 0.51% : 0.000015s : 8: substitution.depend_value_elim 0.82% : 0.000024s : 17: substitution.elim_not_effective 0.61% : 0.000018s : 12: substitution.float_tuple_getitem_switch 1.06% : 0.000032s : 17: substitution.fold_const_symbol 0.70% : 0.000021s : 22: substitution.graph_param_transform 63.34% : 0.001887s : 71: substitution.inline 1.02% : 0.000031s : 35: substitution.j_node_and_user_rematch 1.25% : 0.000037s : 6: substitution.less_batch_normalization 1.56% : 0.000046s : 2: substitution.list_to_tuple_eliminator_ 0.39% : 0.000012s : 18: substitution.load_eliminater 1.02% : 0.000030s : 21: substitution.minmaximum_grad 0.26% : 0.000008s : 2: substitution.opt_reshape 0.75% : 0.000022s : 35: substitution.remove_not_recompute_node 0.42% : 0.000013s : 8: substitution.replace_old_param 1.73% : 0.000051s : 18: substitution.reshape_eliminate 1.53% : 0.000046s : 24: substitution.switch_simplify 4.30% : 0.000128s : 51: substitution.tuple_list_convert_item_index_to_positive 2.45% : 0.000073s : 51: substitution.tuple_list_get_item_const_eliminator 2.90% : 0.000086s : 51: substitution.tuple_list_get_item_depend_reorder 6.01% : 0.000179s : 73: substitution.tuple_list_get_item_eliminator 2.86% : 0.000085s : 51: substitution.tuple_list_get_set_item_eliminator 0.34% : 0.000010s : 6: substitution.updatestate_pure_node_eliminater 4.16% : 0.000124s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.336487 2 92.64% : 2.164558s : 1: type_inference.infer 7.36% : 0.171929s : 1: type_inference.specialize ------[replace.] 0.001047 115 4.77% : 0.000050s : 5: replace.depend_value_elim 57.08% : 0.000598s : 71: replace.inline 3.58% : 0.000038s : 2: replace.list_to_tuple_eliminator_ 25.60% : 0.000268s : 24: replace.switch_simplify 8.96% : 0.000094s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.001959 115 0.11% : 0.000002s : 5: match.depend_value_elim 94.45% : 0.001850s : 71: match.inline 2.26% : 0.000044s : 2: match.list_to_tuple_eliminator_ 1.81% : 0.000036s : 24: match.switch_simplify 1.36% : 0.000027s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.001656 10915 1.11% : 0.000018s : 133: predicate.accumulaten_eliminater 0.39% : 0.000006s : 22: predicate.ad_related_special_op_eliminate 0.58% : 0.000010s : 73: predicate.addn_check_dump 1.11% : 0.000018s : 133: predicate.addn_zero_filter 1.05% : 0.000017s : 133: predicate.adjust_all_reduce_mul_add 2.20% : 0.000036s : 206: predicate.arithmetic_simplify 1.17% : 0.000019s : 133: predicate.cast_eliminate 0.39% : 0.000006s : 44: predicate.check_bprop_eliminate 0.58% : 0.000010s : 73: predicate.compare_switch_simplify 0.10% : 0.000002s : 22: predicate.const_output_eliminate 0.66% : 0.000011s : 76: predicate.depend_value_elim 1.16% : 0.000019s : 133: predicate.dict_get_item_const_eliminator 1.19% : 0.000020s : 133: predicate.dict_get_item_eliminator 1.18% : 0.000020s : 133: predicate.dict_set_item_eliminator 0.47% : 0.000008s : 44: predicate.dumpgradient_eliminate 0.12% : 0.000002s : 22: predicate.elim_not_effective 0.32% : 0.000005s : 22: predicate.elim_shapecalc_of_broadcastargs 1.27% : 0.000021s : 155: predicate.environ_add_const_eliminate 1.25% : 0.000021s : 155: predicate.environ_get_add_eliminate 1.23% : 0.000020s : 155: predicate.environ_get_depend_swap 1.88% : 0.000031s : 228: predicate.environ_get_eliminate 1.24% : 0.000020s : 155: predicate.environ_get_set_eliminate 1.88% : 0.000031s : 219: predicate.exchange_switch_depend_value 2.49% : 0.000041s : 219: predicate.float_depend_g_call 0.60% : 0.000010s : 73: predicate.float_environ_get_switch 0.79% : 0.000013s : 95: predicate.float_tuple_getitem_switch 0.11% : 0.000002s : 22: predicate.fold_const_symbol 0.39% : 0.000006s : 45: predicate.get_grad_eliminate 0.14% : 0.000002s : 22: predicate.graph_param_transform 0.61% : 0.000010s : 73: predicate.incorporate_call 0.56% : 0.000009s : 73: predicate.incorporate_call_switch 6.04% : 0.000100s : 514: predicate.inline 0.50% : 0.000008s : 45: predicate.inline_without_move 0.24% : 0.000004s : 45: predicate.j_node_and_user_rematch 0.51% : 0.000008s : 45: predicate.less_batch_normalization 1.68% : 0.000028s : 192: predicate.list_to_tuple_eliminator_ 2.62% : 0.000043s : 325: predicate.load_eliminater 0.47% : 0.000008s : 22: predicate.loop_unroll_after_grad 2.90% : 0.000048s : 324: predicate.loop_unroll_before_grad 1.67% : 0.000028s : 177: predicate.make_slice_get_slice_eliminator 0.63% : 0.000010s : 73: predicate.merge_addn 0.37% : 0.000006s : 44: predicate.micro_step_allgather_replace 0.35% : 0.000006s : 44: predicate.mini_step_allgather_replace 1.09% : 0.000018s : 133: predicate.minmaximum_grad 0.45% : 0.000007s : 22: predicate.mutable_eliminate 0.30% : 0.000005s : 22: predicate.opt_reshape 0.22% : 0.000004s : 22: predicate.parallel_virtual_node 2.88% : 0.000048s : 219: predicate.partial_defer_inline 1.54% : 0.000026s : 170: predicate.partial_eliminate 1.08% : 0.000018s : 133: predicate.print_const_string_wrapper 0.55% : 0.000009s : 68: predicate.reduce_all_const_elim 1.47% : 0.000024s : 133: predicate.reduce_eliminate 2.61% : 0.000043s : 325: predicate.redundant_stop_gradient_eliminater 0.23% : 0.000004s : 45: predicate.remove_not_recompute_node 1.13% : 0.000019s : 192: predicate.replace_applicator 0.23% : 0.000004s : 45: predicate.replace_old_param 0.14% : 0.000002s : 22: predicate.reset_defer_inline 1.23% : 0.000020s : 133: predicate.reshape_eliminate 0.40% : 0.000007s : 44: predicate.row_tensor_add_zeros_like 0.21% : 0.000003s : 22: predicate.row_tensor_eliminate 0.51% : 0.000008s : 44: predicate.same_eliminate 0.27% : 0.000004s : 50: predicate.set_cell_output_no_recompute 0.45% : 0.000007s : 45: predicate.shard_identity_eliminate 0.44% : 0.000007s : 44: predicate.special_op_eliminate 0.70% : 0.000012s : 73: predicate.specialize_transform 0.54% : 0.000009s : 44: predicate.split_environ_get_set_with_tuple_value 0.50% : 0.000008s : 45: predicate.stack_unstack_eliminate 0.22% : 0.000004s : 22: predicate.switch_call_monad_eliminater 2.09% : 0.000035s : 219: predicate.switch_defer_inline 2.34% : 0.000039s : 263: predicate.switch_layer_defer_inline 6.46% : 0.000107s : 686: predicate.switch_simplify 1.07% : 0.000018s : 133: predicate.tile_eliminate 1.11% : 0.000018s : 133: predicate.transpose_eliminate 1.73% : 0.000029s : 177: predicate.tuple_list_convert_item_index_to_positive 1.73% : 0.000029s : 177: predicate.tuple_list_get_item_const_eliminator 1.61% : 0.000027s : 177: predicate.tuple_list_get_item_depend_reorder 3.26% : 0.000054s : 263: predicate.tuple_list_get_item_eliminator 1.67% : 0.000028s : 177: predicate.tuple_list_get_set_item_eliminator 2.28% : 0.000038s : 250: predicate.tuple_list_set_item_eliminator 1.58% : 0.000026s : 190: predicate.tuple_to_list_eliminator_ 2.61% : 0.000043s : 325: predicate.updatestate_pure_node_eliminater 3.34% : 0.000055s : 398: predicate.updatestate_useless_node_eliminater 0.29% : 0.000005s : 22: predicate.value_based_eliminate 0.39% : 0.000007s : 45: predicate.virtual_dataset_eliminate 0.39% : 0.000006s : 45: predicate.virtual_output_eliminate 0.25% : 0.000004s : 22: predicate.virtual_view_grad_eliminate 0.24% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.135559 135 96.74% : 0.131144s : 55: func_graph_cloner_run.FuncGraphClonerGraph 3.26% : 0.004415s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.191661 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.28% : 0.008798s : 1: add_attr 0.28% : 0.008782s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000204s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.03% : 0.000821s : 1: auto_monad 0.00% : 0.000109s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 1.28% : 0.040795s : 1: bootstrap 0.00% : 0.000047s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000060s : 1: control_data_broadcast_order 0.00% : 0.000040s : 1: convert_after_rewriter 0.00% : 0.000104s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000050s : 1: environ_conv 0.01% : 0.000225s : 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% : 0.000009s : 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% : 0.000007s : 1: label_fine_grained_interleaved_index 0.00% : 0.000012s : 1: label_micro_interleaved_index 0.02% : 0.000753s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.03% : 0.000848s : 1: mutable_eliminate 0.00% : 0.000017s : 1: offloading_packed_experts 0.00% : 0.000048s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000051s : 1: opt.transform.mutable_eliminate 7.77% : 0.247951s : 95: opt.transform.opt_a 0.01% : 0.000177s : 1: opt.transform.opt_after_cconv 0.00% : 0.000100s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000670s : 28: opt.transform.opt_b 0.01% : 0.000296s : 2: opt.transform.opt_trans_graph 0.01% : 0.000234s : 4: opt.transform.symbol_engine_opt 8.15% : 0.260246s : 1: opt_a 0.01% : 0.000442s : 1: opt_after_cconv 0.02% : 0.000793s : 1: opt_after_jit_grad 0.03% : 0.000997s : 1: opt_b 8.38% : 0.267424s : 1: optimize 0.00% : 0.000055s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000020s : 1: order_py_execute_after_rewriter 0.00% : 0.000084s : 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% : 0.000031s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000011s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000016s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000262s : 1: pre_auto_parallel 0.01% : 0.000193s : 1: py_interpret_to_execute 0.00% : 0.000045s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000141s : 1: remove_dup_value 0.16% : 0.005227s : 1: renormalize.infer 0.14% : 0.004547s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000955s : 1: rewriter_after_opt_a 0.02% : 0.000791s : 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% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000029s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000657s : 1: symbol_engine_optimizer 0.01% : 0.000347s : 1: tuple_transform 73.22% : 2.336885s : 1: type_inference . [hook] pytest_runtest_teardown:test_dynamic_shape[input_shape0] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_dynamic_shape[input_shape0],max_mem:110.0M [WARNING] ME(160491:281473110478640,MainProcess):2026-01-29-17:38:22.929.816 [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 = 3.39889, [21] [bootstrap]: 0.00224889 [type_inference]: 2.8583 [event_method]: 0.00022005 [auto_monad]: 0.00092189 [graph_reusing]: 4.896e-05 [inline]: 3.21001e-06 [add_attr]: 0.219373, [1] [add_attr_with_inline]: 0.219357, [1] [Cycle 1]: 0.00038325, [2] [tag_attr]: 0.00021395 [meta_addattr_fg_expand]: 6.04e-05 [parallel-infer-symbol]: 4.42e-06 [pre_auto_parallel]: 0.00025201 [insert-virtual-dataset]: 3.61999e-06 [parallel-infer-symbol-second]: 1.29e-06 [dataset_repeat_opt]: 2.02999e-06 [pipeline_split]: 3.08e-06 [optimize]: 0.316177, [53] [py_interpret_to_execute]: 0.00026921 [rewriter_before_opt_a]: 0.0008407 [opt_a]: 0.309133, [2] [Cycle 1]: 0.306362, [45] [expand_dump_flag]: 3.127e-05 [switch_simplify]: 0.11941 [loop_unroll]: 0.00045393 [a_1]: 0.0088862 [with_stream_mark]: 0.00013557 [recompute_prepare]: 4.756e-05 [updatestate_depend_eliminate]: 2.696e-05 [updatestate_assign_eliminate]: 2.096e-05 [updatestate_loads_eliminate]: 2.96e-05 [parameter_eliminate]: 3.43e-06 [a_2]: 0.00099443 [accelerated_algorithm]: 7.839e-05 [shard]: 3.03e-06 [meta_shard_fg_expand]: 3.364e-05 [shard_inline]: 2.974e-05 [merge_send_recv]: 2.657e-05 [auto_parallel]: 2.713e-05 [parallel]: 0.00018062 [flash_sp]: 1.865e-05 [merge_comm]: 1.926e-05 [allreduce_fusion]: 1.787e-05 [matmul_add_comm_reduction]: 2.908e-05 [allreduce_slice_to_reducescatter]: 1.27e-06 [virtual_shard_identity]: 3.959e-05 [virtual_dataset]: 3.265e-05 [get_grad_eliminate_]: 3.204e-05 [virtual_output]: 3.131e-05 [merge_forward]: 1.727e-05 [cell_reuse_recompute_pass]: 2.89001e-06 [offload_activation]: 3.257e-05 [cell_reuse_handle_not_recompute_node_pass]: 6.408e-05 [merge_recompute_call_nodes]: 1.74e-06 [before_grad]: 5.571e-05 [set_forward_comm_id_for_comm_node_pass]: 2.002e-05 [meta_fg_expand]: 2.509e-05 [flash_sp_send_recv_attached]: 6.63e-06 [receive_attached]: 2.61999e-06 [after_resolve]: 4.457e-05 [a_after_grad]: 5.143e-05 [renormalize]: 0.173902 [add_forward_monad_depend]: 1.459e-05 [auto_monad_grad]: 3.97e-06 [auto_monad_eliminator]: 0.00010546 [cse]: 0.00065068 [a_3]: 0.0002131 [Cycle 2]: 0.00275076, [45] [expand_dump_flag]: 3.58999e-06 [switch_simplify]: 3.089e-05 [loop_unroll]: 3.632e-05 [a_1]: 0.00082175 [with_stream_mark]: 3.658e-05 [recompute_prepare]: 2.655e-05 [updatestate_depend_eliminate]: 1.767e-05 [updatestate_assign_eliminate]: 1.658e-05 [updatestate_loads_eliminate]: 2.195e-05 [parameter_eliminate]: 3.09001e-06 [a_2]: 0.00039536 [accelerated_algorithm]: 3.526e-05 [shard]: 2.86e-06 [meta_shard_fg_expand]: 8.27e-06 [shard_inline]: 2.598e-05 [merge_send_recv]: 2.307e-05 [auto_parallel]: 2.279e-05 [parallel]: 1.114e-05 [flash_sp]: 4.81002e-06 [merge_comm]: 1.609e-05 [allreduce_fusion]: 1.61e-05 [matmul_add_comm_reduction]: 2.456e-05 [allreduce_slice_to_reducescatter]: 9.89996e-07 [virtual_shard_identity]: 2.769e-05 [virtual_dataset]: 2.574e-05 [get_grad_eliminate_]: 2.455e-05 [virtual_output]: 2.489e-05 [merge_forward]: 1.486e-05 [cell_reuse_recompute_pass]: 3.97e-06 [offload_activation]: 2.802e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.711e-05 [merge_recompute_call_nodes]: 1.50999e-06 [before_grad]: 4.329e-05 [set_forward_comm_id_for_comm_node_pass]: 1.636e-05 [meta_fg_expand]: 1.232e-05 [flash_sp_send_recv_attached]: 2.16e-06 [receive_attached]: 2.57001e-06 [after_resolve]: 3.511e-05 [a_after_grad]: 4.122e-05 [renormalize]: 1.59984e-07 [add_forward_monad_depend]: 2.51e-06 [auto_monad_grad]: 2.49999e-06 [auto_monad_eliminator]: 5.563e-05 [cse]: 0.00015985 [a_3]: 0.00017491 [py_interpret_to_execute_after_opt_a]: 4.01e-05 [slice_cell_reuse_recomputed_activation]: 2.56998e-06 [rewriter_after_opt_a]: 0.00087712 [convert_after_rewriter]: 3.129e-05 [order_py_execute_after_rewriter]: 1.61e-05 [mutable_eliminate]: 0.00084317 [opt_b]: 0.00090637, [1] [Cycle 1]: 0.00089715, [7] [b_1]: 0.00066323 [b_2]: 2.904e-05 [updatestate_depend_eliminate]: 2.07e-05 [updatestate_assign_eliminate]: 1.447e-05 [updatestate_loads_eliminate]: 2.063e-05 [renormalize]: 8.80013e-07 [cse]: 0.00010355 [optimize_parallel_all_gather_comm]: 4.474e-05 [overlap_param_gather]: 3.985e-05 [cconv]: 4.764e-05 [loop_unroll]: 0.00056142 [opt_after_cconv]: 0.0003709, [1] [Cycle 1]: 0.00036392, [7] [c_1]: 0.00016327 [parameter_eliminate]: 5.10001e-06 [updatestate_depend_eliminate]: 1.901e-05 [updatestate_assign_eliminate]: 1.372e-05 [updatestate_loads_eliminate]: 1.842e-05 [cse]: 9.037e-05 [renormalize]: 4.39992e-07 [remove_dup_value]: 0.00012492 [tuple_transform]: 0.0002926, [1] [Cycle 1]: 0.00028671, [4] [d_1]: 0.00023068 [none_parameter_eliminate]: 3.3e-06 [renormalize]: 1.90019e-07 [switch_simplify]: 2.871e-05 [partial_unused_args_eliminate]: 2.24001e-06 [add_recomputation]: 0.00029455 [cse_after_recomputation]: 8.647e-05, [1] [Cycle 1]: 8.062e-05, [1] [cse]: 7.197e-05 [environ_conv]: 6.478e-05 [swap_dp_allreduce_reducescatter]: 2.193e-05 [bias_add_comm_swap]: 3.96001e-06 [label_micro_interleaved_index]: 7.94997e-06 [label_fine_grained_interleaved_index]: 2.88e-06 [merge_cast_opt]: 1.57999e-06 [slice_recompute_activation]: 2.51998e-06 [micro_interleaved_order_control]: 3.49001e-06 [assign_add_opt]: 1.47001e-06 [ForceFp32Comm]: 1.35999e-06 [remove_cast_before_assign_add]: 1.26002e-06 [full_micro_interleaved_order_control]: 3.13e-06 [reorder_send_recv_between_fp_bp]: 2.93998e-06 [comm_op_add_attrs]: 1.22e-06 [add_comm_op_reuse_tag]: 1.05001e-06 [interleave_split_concat_branches]: 1.29998e-06 [interleave_parallel_branches]: 1.15999e-06 [overlap_opt_shard_in_pipeline]: 3.623e-05 [overlap_opt_shard_grad_in_pipeline]: 1.97999e-06 [control_data_broadcast_order]: 4.689e-05 [grouped_pairwise_exchange_alltoall]: 1.74998e-06 [offloading_packed_experts]: 1.332e-05 [overlap_recompute_and_grad_model_parallel]: 1.193e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.66e-06 [overlap_recompute_allgather_and_fa_grad]: 1.46002e-06 [overlap_recompute_comm]: 2.39999e-06 [overlap_grad_ring_attention]: 1.128e-05 [overlap_grad_flash_sp]: 6.443e-05 [begin_end_overlap_inline]: 5.99975e-07 [split_matmul_comm_elemetwise]: 2.28002e-06 [split_layernorm_comm]: 2.07999e-06 [handle_group_info]: 1.24e-06 [symbol_engine_optimizer]: 0.0007188, [1] [Cycle 1]: 0.00071232, [6] [build]: 0.00038405 [elim_shapecalc]: 4.494e-05 [elim_not_effective]: 0.00012181 [opt_reshape]: 4.248e-05 [fold_const_symbol]: 6.802e-05 [renormalize]: 2.50002e-07 [detach_backward]: 2.81999e-06 [pipeline_parallel_scheduler]: 2.37001e-06 [auto_monad_reorder]: 8.798e-05 [get_jit_bprop_graph]: 2.80002e-06 [rewriter_after_jit_bprop_graph]: 7.01001e-06 [opt_after_jit_grad]: 0.0007546 [validate]: 0.00015207 Sums bootstrap : 0.002249s : 0.07% type_inference : 2.858299s : 89.94% event_method : 0.000220s : 0.01% auto_monad : 0.000922s : 0.03% graph_reusing : 0.000049s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000214s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000060s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000252s : 0.01% insert-virtual-dataset : 0.000004s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000003s : 0.00% optimize.py_interpret_to_execute : 0.000269s : 0.01% optimize.rewriter_before_opt_a : 0.000841s : 0.03% optimize.opt_a.expand_dump_flag : 0.000035s : 0.00% optimize.opt_a.switch_simplify : 0.119441s : 3.76% optimize.opt_a.loop_unroll : 0.000490s : 0.02% optimize.opt_a.a_1 : 0.009708s : 0.31% optimize.opt_a.with_stream_mark : 0.000172s : 0.01% optimize.opt_a.recompute_prepare : 0.000074s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000045s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000052s : 0.00% optimize.opt_a.parameter_eliminate : 0.000007s : 0.00% optimize.opt_a.a_2 : 0.001390s : 0.04% optimize.opt_a.accelerated_algorithm : 0.000114s : 0.00% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000042s : 0.00% optimize.opt_a.shard_inline : 0.000056s : 0.00% optimize.opt_a.merge_send_recv : 0.000050s : 0.00% optimize.opt_a.auto_parallel : 0.000050s : 0.00% optimize.opt_a.parallel : 0.000192s : 0.01% optimize.opt_a.flash_sp : 0.000023s : 0.00% optimize.opt_a.merge_comm : 0.000035s : 0.00% optimize.opt_a.allreduce_fusion : 0.000034s : 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 : 0.000067s : 0.00% optimize.opt_a.virtual_dataset : 0.000058s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000057s : 0.00% optimize.opt_a.virtual_output : 0.000056s : 0.00% optimize.opt_a.merge_forward : 0.000032s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% optimize.opt_a.offload_activation : 0.000061s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000111s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000099s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000036s : 0.00% optimize.opt_a.meta_fg_expand : 0.000037s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000009s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000080s : 0.00% optimize.opt_a.a_after_grad : 0.000093s : 0.00% optimize.opt_a.renormalize : 0.173903s : 5.47% optimize.opt_a.add_forward_monad_depend : 0.000017s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000161s : 0.01% optimize.opt_a.cse : 0.000811s : 0.03% optimize.opt_a.a_3 : 0.000388s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000040s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000877s : 0.03% optimize.convert_after_rewriter : 0.000031s : 0.00% optimize.order_py_execute_after_rewriter : 0.000016s : 0.00% optimize.mutable_eliminate : 0.000843s : 0.03% optimize.opt_b.b_1 : 0.000663s : 0.02% optimize.opt_b.b_2 : 0.000029s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000021s : 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 : 0.000104s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000045s : 0.00% optimize.overlap_param_gather : 0.000040s : 0.00% optimize.cconv : 0.000048s : 0.00% optimize.loop_unroll : 0.000561s : 0.02% optimize.opt_after_cconv.c_1 : 0.000163s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000019s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000018s : 0.00% optimize.opt_after_cconv.cse : 0.000090s : 0.00% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000125s : 0.00% optimize.tuple_transform.d_1 : 0.000231s : 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 : 0.000029s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000295s : 0.01% optimize.cse_after_recomputation.cse : 0.000072s : 0.00% optimize.environ_conv : 0.000065s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000022s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000008s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 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 : 0.000003s : 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 : 0.000036s : 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 : 0.000002s : 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 : 0.000064s : 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 : 0.000384s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000045s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000122s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000042s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000068s : 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 : 0.000088s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000755s : 0.02% validate : 0.000152s : 0.00% Time group info: ------[substitution.] 0.003679 608 0.47% : 0.000017s : 8: substitution.depend_value_elim 2.05% : 0.000075s : 17: substitution.elim_not_effective 0.51% : 0.000019s : 12: substitution.float_tuple_getitem_switch 0.82% : 0.000030s : 17: substitution.fold_const_symbol 0.47% : 0.000017s : 22: substitution.graph_param_transform 65.22% : 0.002400s : 71: substitution.inline 0.45% : 0.000017s : 35: substitution.j_node_and_user_rematch 1.12% : 0.000041s : 6: substitution.less_batch_normalization 1.77% : 0.000065s : 2: substitution.list_to_tuple_eliminator_ 0.31% : 0.000011s : 18: substitution.load_eliminater 0.94% : 0.000035s : 21: substitution.minmaximum_grad 0.20% : 0.000008s : 2: substitution.opt_reshape 0.63% : 0.000023s : 35: substitution.remove_not_recompute_node 0.30% : 0.000011s : 8: substitution.replace_old_param 1.70% : 0.000063s : 18: substitution.reshape_eliminate 1.77% : 0.000065s : 24: substitution.switch_simplify 4.92% : 0.000181s : 51: substitution.tuple_list_convert_item_index_to_positive 1.96% : 0.000072s : 51: substitution.tuple_list_get_item_const_eliminator 2.69% : 0.000099s : 51: substitution.tuple_list_get_item_depend_reorder 5.48% : 0.000202s : 73: substitution.tuple_list_get_item_eliminator 2.62% : 0.000096s : 51: substitution.tuple_list_get_set_item_eliminator 0.30% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 3.32% : 0.000122s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.857814 2 95.31% : 2.723835s : 1: type_inference.infer 4.69% : 0.133979s : 1: type_inference.specialize ------[replace.] 0.001273 115 4.06% : 0.000052s : 5: replace.depend_value_elim 53.83% : 0.000685s : 71: replace.inline 4.13% : 0.000053s : 2: replace.list_to_tuple_eliminator_ 29.51% : 0.000376s : 24: replace.switch_simplify 8.46% : 0.000108s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.002505 115 0.09% : 0.000002s : 5: match.depend_value_elim 94.07% : 0.002357s : 71: match.inline 2.46% : 0.000062s : 2: match.list_to_tuple_eliminator_ 2.14% : 0.000054s : 24: match.switch_simplify 1.25% : 0.000031s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.120372 10915 0.02% : 0.000018s : 133: predicate.accumulaten_eliminater 0.01% : 0.000007s : 22: predicate.ad_related_special_op_eliminate 0.01% : 0.000010s : 73: predicate.addn_check_dump 0.02% : 0.000020s : 133: predicate.addn_zero_filter 0.01% : 0.000018s : 133: predicate.adjust_all_reduce_mul_add 0.03% : 0.000038s : 206: predicate.arithmetic_simplify 0.02% : 0.000019s : 133: predicate.cast_eliminate 0.01% : 0.000006s : 44: predicate.check_bprop_eliminate 0.01% : 0.000010s : 73: predicate.compare_switch_simplify 0.00% : 0.000002s : 22: predicate.const_output_eliminate 0.01% : 0.000012s : 76: predicate.depend_value_elim 0.02% : 0.000020s : 133: predicate.dict_get_item_const_eliminator 0.02% : 0.000021s : 133: predicate.dict_get_item_eliminator 0.02% : 0.000019s : 133: predicate.dict_set_item_eliminator 0.01% : 0.000008s : 44: predicate.dumpgradient_eliminate 0.00% : 0.000002s : 22: predicate.elim_not_effective 0.00% : 0.000005s : 22: predicate.elim_shapecalc_of_broadcastargs 0.02% : 0.000021s : 155: predicate.environ_add_const_eliminate 0.02% : 0.000021s : 155: predicate.environ_get_add_eliminate 0.02% : 0.000021s : 155: predicate.environ_get_depend_swap 0.03% : 0.000032s : 228: predicate.environ_get_eliminate 0.02% : 0.000021s : 155: predicate.environ_get_set_eliminate 0.03% : 0.000031s : 219: predicate.exchange_switch_depend_value 0.04% : 0.000045s : 219: predicate.float_depend_g_call 0.01% : 0.000010s : 73: predicate.float_environ_get_switch 0.01% : 0.000014s : 95: predicate.float_tuple_getitem_switch 0.00% : 0.000002s : 22: predicate.fold_const_symbol 0.01% : 0.000007s : 45: predicate.get_grad_eliminate 0.00% : 0.000002s : 22: predicate.graph_param_transform 0.01% : 0.000010s : 73: predicate.incorporate_call 0.01% : 0.000010s : 73: predicate.incorporate_call_switch 0.08% : 0.000101s : 514: predicate.inline 0.01% : 0.000008s : 45: predicate.inline_without_move 0.00% : 0.000003s : 45: predicate.j_node_and_user_rematch 0.01% : 0.000009s : 45: predicate.less_batch_normalization 0.02% : 0.000030s : 192: predicate.list_to_tuple_eliminator_ 0.04% : 0.000046s : 325: predicate.load_eliminater 0.01% : 0.000007s : 22: predicate.loop_unroll_after_grad 0.11% : 0.000127s : 324: predicate.loop_unroll_before_grad 0.02% : 0.000027s : 177: predicate.make_slice_get_slice_eliminator 0.01% : 0.000011s : 73: predicate.merge_addn 0.00% : 0.000006s : 44: predicate.micro_step_allgather_replace 0.01% : 0.000006s : 44: predicate.mini_step_allgather_replace 0.02% : 0.000019s : 133: predicate.minmaximum_grad 0.01% : 0.000008s : 22: predicate.mutable_eliminate 0.00% : 0.000004s : 22: predicate.opt_reshape 0.00% : 0.000004s : 22: predicate.parallel_virtual_node 0.05% : 0.000062s : 219: predicate.partial_defer_inline 0.02% : 0.000026s : 170: predicate.partial_eliminate 0.02% : 0.000018s : 133: predicate.print_const_string_wrapper 0.01% : 0.000010s : 68: predicate.reduce_all_const_elim 0.13% : 0.000157s : 133: predicate.reduce_eliminate 0.04% : 0.000044s : 325: predicate.redundant_stop_gradient_eliminater 0.00% : 0.000003s : 45: predicate.remove_not_recompute_node 0.02% : 0.000019s : 192: predicate.replace_applicator 0.00% : 0.000004s : 45: predicate.replace_old_param 0.00% : 0.000002s : 22: predicate.reset_defer_inline 0.02% : 0.000021s : 133: predicate.reshape_eliminate 0.01% : 0.000007s : 44: predicate.row_tensor_add_zeros_like 0.00% : 0.000004s : 22: predicate.row_tensor_eliminate 0.01% : 0.000009s : 44: predicate.same_eliminate 0.00% : 0.000004s : 50: predicate.set_cell_output_no_recompute 0.01% : 0.000008s : 45: predicate.shard_identity_eliminate 0.01% : 0.000007s : 44: predicate.special_op_eliminate 0.01% : 0.000012s : 73: predicate.specialize_transform 0.01% : 0.000008s : 44: predicate.split_environ_get_set_with_tuple_value 0.01% : 0.000008s : 45: predicate.stack_unstack_eliminate 0.00% : 0.000004s : 22: predicate.switch_call_monad_eliminater 0.03% : 0.000034s : 219: predicate.switch_defer_inline 0.03% : 0.000039s : 263: predicate.switch_layer_defer_inline 98.49% : 0.118560s : 686: predicate.switch_simplify 0.02% : 0.000021s : 133: predicate.tile_eliminate 0.02% : 0.000018s : 133: predicate.transpose_eliminate 0.03% : 0.000030s : 177: predicate.tuple_list_convert_item_index_to_positive 0.03% : 0.000031s : 177: predicate.tuple_list_get_item_const_eliminator 0.02% : 0.000028s : 177: predicate.tuple_list_get_item_depend_reorder 0.04% : 0.000053s : 263: predicate.tuple_list_get_item_eliminator 0.02% : 0.000029s : 177: predicate.tuple_list_get_set_item_eliminator 0.03% : 0.000041s : 250: predicate.tuple_list_set_item_eliminator 0.02% : 0.000027s : 190: predicate.tuple_to_list_eliminator_ 0.04% : 0.000044s : 325: predicate.updatestate_pure_node_eliminater 0.05% : 0.000056s : 398: predicate.updatestate_useless_node_eliminater 0.00% : 0.000004s : 22: predicate.value_based_eliminate 0.01% : 0.000007s : 45: predicate.virtual_dataset_eliminate 0.01% : 0.000007s : 45: predicate.virtual_output_eliminate 0.00% : 0.000003s : 22: predicate.virtual_view_grad_eliminate 0.00% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.246857 135 51.16% : 0.126298s : 55: func_graph_cloner_run.FuncGraphClonerGraph 48.84% : 0.120559s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.241667 209 0.00% : 0.000004s : 1: ForceFp32Comm 5.17% : 0.219382s : 1: add_attr 5.17% : 0.219361s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000304s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.02% : 0.000941s : 1: auto_monad 0.00% : 0.000093s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.06% : 0.002366s : 1: bootstrap 0.00% : 0.000051s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000051s : 1: control_data_broadcast_order 0.00% : 0.000037s : 1: convert_after_rewriter 0.00% : 0.000090s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000071s : 1: environ_conv 0.01% : 0.000233s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000056s : 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% : 0.000011s : 1: label_micro_interleaved_index 0.01% : 0.000572s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.02% : 0.000856s : 1: mutable_eliminate 0.00% : 0.000017s : 1: offloading_packed_experts 0.00% : 0.000041s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000047s : 1: opt.transform.mutable_eliminate 3.11% : 0.132116s : 95: opt.transform.opt_a 0.00% : 0.000162s : 1: opt.transform.opt_after_cconv 0.00% : 0.000093s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000656s : 28: opt.transform.opt_b 0.01% : 0.000255s : 2: opt.transform.opt_trans_graph 0.01% : 0.000272s : 4: opt.transform.symbol_engine_opt 7.29% : 0.309138s : 1: opt_a 0.01% : 0.000375s : 1: opt_after_cconv 0.02% : 0.000767s : 1: opt_after_jit_grad 0.02% : 0.000911s : 1: opt_b 7.45% : 0.316184s : 1: optimize 0.00% : 0.000049s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000020s : 1: order_py_execute_after_rewriter 0.00% : 0.000068s : 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% : 0.000040s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000045s : 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% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000006s : 1: pipeline_split 0.01% : 0.000260s : 1: pre_auto_parallel 0.01% : 0.000278s : 1: py_interpret_to_execute 0.00% : 0.000044s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000130s : 1: remove_dup_value 3.90% : 0.165542s : 1: renormalize.infer 0.20% : 0.008328s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000888s : 1: rewriter_after_opt_a 0.02% : 0.000855s : 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% : 0.000026s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000722s : 1: symbol_engine_optimizer 0.01% : 0.000296s : 1: tuple_transform 67.39% : 2.858342s : 1: type_inference . [hook] pytest_runtest_teardown:test_dynamic_shape[input_shape1] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_dynamic_shape[input_shape1],max_mem:148.0M [WARNING] ME(160491:281473110478640,MainProcess):2026-01-29-17:38:56.968.667 [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 = 3.16954, [21] [bootstrap]: 0.00130038 [type_inference]: 2.75373 [event_method]: 0.0002163 [auto_monad]: 0.0007409 [graph_reusing]: 4.207e-05 [inline]: 3.25e-06 [add_attr]: 0.00544121, [1] [add_attr_with_inline]: 0.00542174, [1] [Cycle 1]: 0.00037223, [2] [tag_attr]: 0.00025746 [meta_addattr_fg_expand]: 5.755e-05 [parallel-infer-symbol]: 4.07e-06 [pre_auto_parallel]: 0.0002589 [insert-virtual-dataset]: 3.94002e-06 [parallel-infer-symbol-second]: 1.30999e-06 [dataset_repeat_opt]: 2.36e-06 [pipeline_split]: 2.68003e-06 [optimize]: 0.406309, [53] [py_interpret_to_execute]: 0.00025941 [rewriter_before_opt_a]: 0.00081674 [opt_a]: 0.285373, [2] [Cycle 1]: 0.282715, [45] [expand_dump_flag]: 3.778e-05 [switch_simplify]: 0.00087227 [loop_unroll]: 0.0003346 [a_1]: 0.202991 [with_stream_mark]: 0.00048772 [recompute_prepare]: 5.748e-05 [updatestate_depend_eliminate]: 3.129e-05 [updatestate_assign_eliminate]: 2.259e-05 [updatestate_loads_eliminate]: 2.865e-05 [parameter_eliminate]: 3.45e-06 [a_2]: 0.00106598 [accelerated_algorithm]: 7.552e-05 [shard]: 2.98e-06 [meta_shard_fg_expand]: 2.842e-05 [shard_inline]: 2.83e-05 [merge_send_recv]: 2.515e-05 [auto_parallel]: 2.538e-05 [parallel]: 4.1e-05 [flash_sp]: 1.731e-05 [merge_comm]: 1.648e-05 [allreduce_fusion]: 1.594e-05 [matmul_add_comm_reduction]: 2.68e-05 [allreduce_slice_to_reducescatter]: 1.20001e-06 [virtual_shard_identity]: 3.545e-05 [virtual_dataset]: 2.959e-05 [get_grad_eliminate_]: 2.978e-05 [virtual_output]: 2.967e-05 [merge_forward]: 1.871e-05 [cell_reuse_recompute_pass]: 3.5e-06 [offload_activation]: 3.08e-05 [cell_reuse_handle_not_recompute_node_pass]: 6.671e-05 [merge_recompute_call_nodes]: 1.66e-06 [before_grad]: 5.929e-05 [set_forward_comm_id_for_comm_node_pass]: 2.076e-05 [meta_fg_expand]: 2.159e-05 [flash_sp_send_recv_attached]: 6.88e-06 [receive_attached]: 2.78e-06 [after_resolve]: 4.316e-05 [a_after_grad]: 5.546e-05 [renormalize]: 0.0747258 [add_forward_monad_depend]: 1.298e-05 [auto_monad_grad]: 3.9e-06 [auto_monad_eliminator]: 9.336e-05 [cse]: 0.00048791 [a_3]: 0.00021272 [Cycle 2]: 0.00263967, [45] [expand_dump_flag]: 2.88003e-06 [switch_simplify]: 3.237e-05 [loop_unroll]: 2.614e-05 [a_1]: 0.00082489 [with_stream_mark]: 3.479e-05 [recompute_prepare]: 2.753e-05 [updatestate_depend_eliminate]: 1.821e-05 [updatestate_assign_eliminate]: 1.541e-05 [updatestate_loads_eliminate]: 2.116e-05 [parameter_eliminate]: 2.42001e-06 [a_2]: 0.00042556 [accelerated_algorithm]: 4.059e-05 [shard]: 2.48e-06 [meta_shard_fg_expand]: 8.69e-06 [shard_inline]: 2.531e-05 [merge_send_recv]: 2.568e-05 [auto_parallel]: 2.419e-05 [parallel]: 1.113e-05 [flash_sp]: 5.04e-06 [merge_comm]: 1.662e-05 [allreduce_fusion]: 1.588e-05 [matmul_add_comm_reduction]: 2.585e-05 [allreduce_slice_to_reducescatter]: 7.50006e-07 [virtual_shard_identity]: 3.031e-05 [virtual_dataset]: 2.892e-05 [get_grad_eliminate_]: 2.47e-05 [virtual_output]: 2.609e-05 [merge_forward]: 1.592e-05 [cell_reuse_recompute_pass]: 4.16001e-06 [offload_activation]: 2.656e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.029e-05 [merge_recompute_call_nodes]: 2.18998e-06 [before_grad]: 4.623e-05 [set_forward_comm_id_for_comm_node_pass]: 1.756e-05 [meta_fg_expand]: 1.187e-05 [flash_sp_send_recv_attached]: 2.39001e-06 [receive_attached]: 2.94999e-06 [after_resolve]: 4.057e-05 [a_after_grad]: 4.236e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 4.08999e-06 [auto_monad_grad]: 2.48998e-06 [auto_monad_eliminator]: 6.99e-05 [cse]: 0.00010557 [a_3]: 0.00018052 [py_interpret_to_execute_after_opt_a]: 4.012e-05 [slice_cell_reuse_recomputed_activation]: 3.02002e-06 [rewriter_after_opt_a]: 0.00091778 [convert_after_rewriter]: 3.362e-05 [order_py_execute_after_rewriter]: 1.882e-05 [mutable_eliminate]: 0.00084556 [opt_b]: 0.00105482, [1] [Cycle 1]: 0.00104413, [7] [b_1]: 0.00079131 [b_2]: 2.942e-05 [updatestate_depend_eliminate]: 1.995e-05 [updatestate_assign_eliminate]: 1.534e-05 [updatestate_loads_eliminate]: 2.224e-05 [renormalize]: 7.80012e-07 [cse]: 0.00011435 [optimize_parallel_all_gather_comm]: 5.233e-05 [overlap_param_gather]: 2.22001e-06 [cconv]: 3.637e-05 [loop_unroll]: 0.00060323 [opt_after_cconv]: 0.00037705, [1] [Cycle 1]: 0.00036819, [7] [c_1]: 0.0001766 [parameter_eliminate]: 4.22e-06 [updatestate_depend_eliminate]: 2.071e-05 [updatestate_assign_eliminate]: 1.387e-05 [updatestate_loads_eliminate]: 1.918e-05 [cse]: 9.144e-05 [renormalize]: 8.09989e-07 [remove_dup_value]: 0.00013758 [tuple_transform]: 0.0003132, [1] [Cycle 1]: 0.00030695, [4] [d_1]: 0.0002525 [none_parameter_eliminate]: 2.22999e-06 [renormalize]: 4.00003e-07 [switch_simplify]: 2.815e-05 [partial_unused_args_eliminate]: 2.18998e-06 [add_recomputation]: 0.00016854 [cse_after_recomputation]: 0.113912, [1] [Cycle 1]: 0.113901, [1] [cse]: 0.113844 [environ_conv]: 4.988e-05 [swap_dp_allreduce_reducescatter]: 4.842e-05 [bias_add_comm_swap]: 4.27003e-06 [label_micro_interleaved_index]: 9.95002e-06 [label_fine_grained_interleaved_index]: 3.25e-06 [merge_cast_opt]: 1.90001e-06 [slice_recompute_activation]: 2.37999e-06 [micro_interleaved_order_control]: 2.32001e-06 [assign_add_opt]: 1.99999e-06 [ForceFp32Comm]: 8.70001e-07 [remove_cast_before_assign_add]: 1.59e-06 [full_micro_interleaved_order_control]: 2.31e-06 [reorder_send_recv_between_fp_bp]: 3.13e-06 [comm_op_add_attrs]: 1.47001e-06 [add_comm_op_reuse_tag]: 1.10001e-06 [interleave_split_concat_branches]: 1.28002e-06 [interleave_parallel_branches]: 1.45999e-06 [overlap_opt_shard_in_pipeline]: 1.32e-06 [overlap_opt_shard_grad_in_pipeline]: 1.98997e-06 [control_data_broadcast_order]: 5.083e-05 [grouped_pairwise_exchange_alltoall]: 1.71e-06 [offloading_packed_experts]: 1.462e-05 [overlap_recompute_and_grad_model_parallel]: 1.31e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.49998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.42999e-06 [overlap_recompute_comm]: 2.65002e-06 [overlap_grad_ring_attention]: 1.105e-05 [overlap_grad_flash_sp]: 7.156e-05 [begin_end_overlap_inline]: 6.10016e-07 [split_matmul_comm_elemetwise]: 2.52001e-06 [split_layernorm_comm]: 2.12001e-06 [handle_group_info]: 1.45001e-06 [symbol_engine_optimizer]: 0.00066977, [1] [Cycle 1]: 0.00065456, [6] [build]: 0.00034019 [elim_shapecalc]: 6.068e-05 [elim_not_effective]: 7.227e-05 [opt_reshape]: 4.304e-05 [fold_const_symbol]: 7.323e-05 [renormalize]: 1.24998e-06 [detach_backward]: 3.59002e-06 [pipeline_parallel_scheduler]: 3.11001e-06 [auto_monad_reorder]: 0.00010625 [get_jit_bprop_graph]: 2.81e-06 [rewriter_after_jit_bprop_graph]: 9.65002e-06 [opt_after_jit_grad]: 0.0009817 [validate]: 0.00013422 Sums bootstrap : 0.001300s : 0.04% type_inference : 2.753732s : 87.07% event_method : 0.000216s : 0.01% auto_monad : 0.000741s : 0.02% graph_reusing : 0.000042s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000257s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000058s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000259s : 0.01% insert-virtual-dataset : 0.000004s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000003s : 0.00% optimize.py_interpret_to_execute : 0.000259s : 0.01% optimize.rewriter_before_opt_a : 0.000817s : 0.03% optimize.opt_a.expand_dump_flag : 0.000041s : 0.00% optimize.opt_a.switch_simplify : 0.000905s : 0.03% optimize.opt_a.loop_unroll : 0.000361s : 0.01% optimize.opt_a.a_1 : 0.203816s : 6.44% optimize.opt_a.with_stream_mark : 0.000523s : 0.02% optimize.opt_a.recompute_prepare : 0.000085s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000049s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000050s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.001492s : 0.05% optimize.opt_a.accelerated_algorithm : 0.000116s : 0.00% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000037s : 0.00% optimize.opt_a.shard_inline : 0.000054s : 0.00% optimize.opt_a.merge_send_recv : 0.000051s : 0.00% optimize.opt_a.auto_parallel : 0.000050s : 0.00% optimize.opt_a.parallel : 0.000052s : 0.00% optimize.opt_a.flash_sp : 0.000022s : 0.00% optimize.opt_a.merge_comm : 0.000033s : 0.00% optimize.opt_a.allreduce_fusion : 0.000032s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000053s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000066s : 0.00% optimize.opt_a.virtual_dataset : 0.000059s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000054s : 0.00% optimize.opt_a.virtual_output : 0.000056s : 0.00% optimize.opt_a.merge_forward : 0.000035s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000008s : 0.00% optimize.opt_a.offload_activation : 0.000057s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000117s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000106s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000038s : 0.00% optimize.opt_a.meta_fg_expand : 0.000033s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000009s : 0.00% optimize.opt_a.receive_attached : 0.000006s : 0.00% optimize.opt_a.after_resolve : 0.000084s : 0.00% optimize.opt_a.a_after_grad : 0.000098s : 0.00% optimize.opt_a.renormalize : 0.074726s : 2.36% optimize.opt_a.add_forward_monad_depend : 0.000017s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000163s : 0.01% optimize.opt_a.cse : 0.000593s : 0.02% optimize.opt_a.a_3 : 0.000393s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000040s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000918s : 0.03% optimize.convert_after_rewriter : 0.000034s : 0.00% optimize.order_py_execute_after_rewriter : 0.000019s : 0.00% optimize.mutable_eliminate : 0.000846s : 0.03% optimize.opt_b.b_1 : 0.000791s : 0.03% optimize.opt_b.b_2 : 0.000029s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000020s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000015s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000022s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000114s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000052s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000036s : 0.00% optimize.loop_unroll : 0.000603s : 0.02% optimize.opt_after_cconv.c_1 : 0.000177s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000021s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000019s : 0.00% optimize.opt_after_cconv.cse : 0.000091s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000138s : 0.00% optimize.tuple_transform.d_1 : 0.000253s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000028s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000169s : 0.01% optimize.cse_after_recomputation.cse : 0.113844s : 3.60% optimize.environ_conv : 0.000050s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000048s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000010s : 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 : 0.000002s : 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 : 0.000002s : 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 : 0.000001s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000051s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000015s : 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 : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000011s : 0.00% optimize.overlap_grad_flash_sp : 0.000072s : 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 : 0.000340s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000061s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000072s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000043s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000073s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000004s : 0.00% pipeline_parallel_scheduler : 0.000003s : 0.00% auto_monad_reorder : 0.000106s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000982s : 0.03% validate : 0.000134s : 0.00% Time group info: ------[substitution.] 0.004338 608 0.40% : 0.000017s : 8: substitution.depend_value_elim 0.39% : 0.000017s : 17: substitution.elim_not_effective 0.45% : 0.000020s : 12: substitution.float_tuple_getitem_switch 0.77% : 0.000034s : 17: substitution.fold_const_symbol 0.42% : 0.000018s : 22: substitution.graph_param_transform 68.96% : 0.002991s : 71: substitution.inline 0.39% : 0.000017s : 35: substitution.j_node_and_user_rematch 0.91% : 0.000039s : 6: substitution.less_batch_normalization 1.52% : 0.000066s : 2: substitution.list_to_tuple_eliminator_ 0.28% : 0.000012s : 18: substitution.load_eliminater 0.99% : 0.000043s : 21: substitution.minmaximum_grad 0.19% : 0.000008s : 2: substitution.opt_reshape 0.55% : 0.000024s : 35: substitution.remove_not_recompute_node 0.31% : 0.000014s : 8: substitution.replace_old_param 1.57% : 0.000068s : 18: substitution.reshape_eliminate 1.10% : 0.000048s : 24: substitution.switch_simplify 4.01% : 0.000174s : 51: substitution.tuple_list_convert_item_index_to_positive 2.26% : 0.000098s : 51: substitution.tuple_list_get_item_const_eliminator 2.91% : 0.000126s : 51: substitution.tuple_list_get_item_depend_reorder 5.78% : 0.000251s : 73: substitution.tuple_list_get_item_eliminator 2.84% : 0.000123s : 51: substitution.tuple_list_get_set_item_eliminator 0.24% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 2.75% : 0.000119s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.753327 2 94.97% : 2.614892s : 1: type_inference.infer 5.03% : 0.138435s : 1: type_inference.specialize ------[replace.] 0.193396 115 0.03% : 0.000058s : 5: replace.depend_value_elim 99.72% : 0.192852s : 71: replace.inline 0.02% : 0.000047s : 2: replace.list_to_tuple_eliminator_ 0.17% : 0.000321s : 24: replace.switch_simplify 0.06% : 0.000118s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.003080 115 0.07% : 0.000002s : 5: match.depend_value_elim 95.48% : 0.002941s : 71: match.inline 2.02% : 0.000062s : 2: match.list_to_tuple_eliminator_ 1.19% : 0.000037s : 24: match.switch_simplify 1.24% : 0.000038s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.001809 10915 1.07% : 0.000019s : 133: predicate.accumulaten_eliminater 0.44% : 0.000008s : 22: predicate.ad_related_special_op_eliminate 0.55% : 0.000010s : 73: predicate.addn_check_dump 1.07% : 0.000019s : 133: predicate.addn_zero_filter 1.03% : 0.000019s : 133: predicate.adjust_all_reduce_mul_add 2.41% : 0.000044s : 206: predicate.arithmetic_simplify 1.09% : 0.000020s : 133: predicate.cast_eliminate 0.37% : 0.000007s : 44: predicate.check_bprop_eliminate 0.56% : 0.000010s : 73: predicate.compare_switch_simplify 0.10% : 0.000002s : 22: predicate.const_output_eliminate 0.74% : 0.000013s : 76: predicate.depend_value_elim 1.19% : 0.000022s : 133: predicate.dict_get_item_const_eliminator 1.29% : 0.000023s : 133: predicate.dict_get_item_eliminator 1.17% : 0.000021s : 133: predicate.dict_set_item_eliminator 0.43% : 0.000008s : 44: predicate.dumpgradient_eliminate 0.14% : 0.000003s : 22: predicate.elim_not_effective 0.22% : 0.000004s : 22: predicate.elim_shapecalc_of_broadcastargs 1.22% : 0.000022s : 155: predicate.environ_add_const_eliminate 1.20% : 0.000022s : 155: predicate.environ_get_add_eliminate 1.26% : 0.000023s : 155: predicate.environ_get_depend_swap 1.82% : 0.000033s : 228: predicate.environ_get_eliminate 1.24% : 0.000023s : 155: predicate.environ_get_set_eliminate 1.74% : 0.000031s : 219: predicate.exchange_switch_depend_value 2.52% : 0.000046s : 219: predicate.float_depend_g_call 0.56% : 0.000010s : 73: predicate.float_environ_get_switch 0.78% : 0.000014s : 95: predicate.float_tuple_getitem_switch 0.09% : 0.000002s : 22: predicate.fold_const_symbol 0.40% : 0.000007s : 45: predicate.get_grad_eliminate 0.12% : 0.000002s : 22: predicate.graph_param_transform 0.56% : 0.000010s : 73: predicate.incorporate_call 0.54% : 0.000010s : 73: predicate.incorporate_call_switch 5.76% : 0.000104s : 514: predicate.inline 0.54% : 0.000010s : 45: predicate.inline_without_move 0.19% : 0.000003s : 45: predicate.j_node_and_user_rematch 0.49% : 0.000009s : 45: predicate.less_batch_normalization 1.65% : 0.000030s : 192: predicate.list_to_tuple_eliminator_ 2.61% : 0.000047s : 325: predicate.load_eliminater 0.35% : 0.000006s : 22: predicate.loop_unroll_after_grad 3.16% : 0.000057s : 324: predicate.loop_unroll_before_grad 1.60% : 0.000029s : 177: predicate.make_slice_get_slice_eliminator 0.58% : 0.000011s : 73: predicate.merge_addn 0.34% : 0.000006s : 44: predicate.micro_step_allgather_replace 0.33% : 0.000006s : 44: predicate.mini_step_allgather_replace 1.19% : 0.000022s : 133: predicate.minmaximum_grad 0.43% : 0.000008s : 22: predicate.mutable_eliminate 0.22% : 0.000004s : 22: predicate.opt_reshape 0.21% : 0.000004s : 22: predicate.parallel_virtual_node 3.42% : 0.000062s : 219: predicate.partial_defer_inline 1.45% : 0.000026s : 170: predicate.partial_eliminate 1.08% : 0.000020s : 133: predicate.print_const_string_wrapper 0.53% : 0.000010s : 68: predicate.reduce_all_const_elim 1.47% : 0.000027s : 133: predicate.reduce_eliminate 2.57% : 0.000046s : 325: predicate.redundant_stop_gradient_eliminater 0.20% : 0.000004s : 45: predicate.remove_not_recompute_node 1.05% : 0.000019s : 192: predicate.replace_applicator 0.22% : 0.000004s : 45: predicate.replace_old_param 0.11% : 0.000002s : 22: predicate.reset_defer_inline 1.22% : 0.000022s : 133: predicate.reshape_eliminate 0.35% : 0.000006s : 44: predicate.row_tensor_add_zeros_like 0.20% : 0.000004s : 22: predicate.row_tensor_eliminate 0.44% : 0.000008s : 44: predicate.same_eliminate 0.24% : 0.000004s : 50: predicate.set_cell_output_no_recompute 0.41% : 0.000007s : 45: predicate.shard_identity_eliminate 0.38% : 0.000007s : 44: predicate.special_op_eliminate 0.68% : 0.000012s : 73: predicate.specialize_transform 0.47% : 0.000009s : 44: predicate.split_environ_get_set_with_tuple_value 0.46% : 0.000008s : 45: predicate.stack_unstack_eliminate 0.19% : 0.000003s : 22: predicate.switch_call_monad_eliminater 1.98% : 0.000036s : 219: predicate.switch_defer_inline 2.26% : 0.000041s : 263: predicate.switch_layer_defer_inline 6.86% : 0.000124s : 686: predicate.switch_simplify 1.03% : 0.000019s : 133: predicate.tile_eliminate 1.10% : 0.000020s : 133: predicate.transpose_eliminate 1.71% : 0.000031s : 177: predicate.tuple_list_convert_item_index_to_positive 1.77% : 0.000032s : 177: predicate.tuple_list_get_item_const_eliminator 2.37% : 0.000043s : 177: predicate.tuple_list_get_item_depend_reorder 3.19% : 0.000058s : 263: predicate.tuple_list_get_item_eliminator 1.81% : 0.000033s : 177: predicate.tuple_list_get_set_item_eliminator 2.35% : 0.000043s : 250: predicate.tuple_list_set_item_eliminator 1.63% : 0.000030s : 190: predicate.tuple_to_list_eliminator_ 2.52% : 0.000046s : 325: predicate.updatestate_pure_node_eliminater 3.32% : 0.000060s : 398: predicate.updatestate_useless_node_eliminater 0.22% : 0.000004s : 22: predicate.value_based_eliminate 0.39% : 0.000007s : 45: predicate.virtual_dataset_eliminate 0.40% : 0.000007s : 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.] 0.277146 135 54.40% : 0.150773s : 55: func_graph_cloner_run.FuncGraphClonerGraph 45.60% : 0.126373s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.865030 209 0.00% : 0.000003s : 1: ForceFp32Comm 0.14% : 0.005449s : 1: add_attr 0.14% : 0.005426s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000174s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.02% : 0.000757s : 1: auto_monad 0.00% : 0.000114s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.03% : 0.001335s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000006s : 1: comm_op_add_attrs 0.00% : 0.000055s : 1: control_data_broadcast_order 0.00% : 0.000041s : 1: convert_after_rewriter 2.95% : 0.113922s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000008s : 1: detach_backward 0.00% : 0.000060s : 1: environ_conv 0.01% : 0.000229s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000009s : 1: get_jit_bprop_graph 0.00% : 0.000049s : 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% : 0.000013s : 1: label_micro_interleaved_index 0.02% : 0.000614s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.02% : 0.000856s : 1: mutable_eliminate 0.00% : 0.000018s : 1: offloading_packed_experts 0.00% : 0.000044s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000052s : 1: opt.transform.mutable_eliminate 5.37% : 0.207673s : 95: opt.transform.opt_a 0.00% : 0.000175s : 1: opt.transform.opt_after_cconv 0.00% : 0.000104s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000777s : 28: opt.transform.opt_b 0.01% : 0.000277s : 2: opt.transform.opt_trans_graph 0.01% : 0.000239s : 4: opt.transform.symbol_engine_opt 7.38% : 0.285378s : 1: opt_a 0.01% : 0.000381s : 1: opt_after_cconv 0.03% : 0.000998s : 1: opt_after_jit_grad 0.03% : 0.001059s : 1: opt_b 10.51% : 0.406318s : 1: optimize 0.00% : 0.000057s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000023s : 1: order_py_execute_after_rewriter 0.00% : 0.000076s : 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% : 0.000004s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000016s : 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% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pipeline_parallel_scheduler 0.00% : 0.000006s : 1: pipeline_split 0.01% : 0.000268s : 1: pre_auto_parallel 0.01% : 0.000269s : 1: py_interpret_to_execute 0.00% : 0.000045s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000144s : 1: remove_dup_value 1.72% : 0.066658s : 1: renormalize.infer 0.21% : 0.008044s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000934s : 1: rewriter_after_opt_a 0.02% : 0.000833s : 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% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000053s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000674s : 1: symbol_engine_optimizer 0.01% : 0.000317s : 1: tuple_transform 71.25% : 2.753765s : 1: type_inference . [hook] pytest_runtest_teardown:test_dynamic_shape[input_shape2] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_dynamic_shape[input_shape2],max_mem:154.0M =============================== 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_dynamic_shape[input_shape1] test_qbmm_split.py::test_dynamic_shape[input_shape2] /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 ================== 3 passed, 27 warnings in 159.28s (0:02:39) ==================