==================================================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_002/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(171560:281472843685680,MainProcess):2026-01-29-17:37:55.886.713 [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 = 1.85249, [21] [bootstrap]: 0.00073516 [type_inference]: 1.68508 [event_method]: 0.00050994 [auto_monad]: 0.00092892 [graph_reusing]: 5.797e-05 [inline]: 3.4e-06 [add_attr]: 0.00997733, [1] [add_attr_with_inline]: 0.00995828, [1] [Cycle 1]: 0.00040316, [2] [tag_attr]: 0.00024948 [meta_addattr_fg_expand]: 5.926e-05 [parallel-infer-symbol]: 4.40999e-06 [pre_auto_parallel]: 0.00028658 [insert-virtual-dataset]: 5.49e-06 [parallel-infer-symbol-second]: 1.49e-06 [dataset_repeat_opt]: 2.93998e-06 [pipeline_split]: 1.78002e-06 [optimize]: 0.153424, [53] [py_interpret_to_execute]: 0.00023774 [rewriter_before_opt_a]: 0.00101973 [opt_a]: 0.145315, [2] [Cycle 1]: 0.142433, [45] [expand_dump_flag]: 2.456e-05 [switch_simplify]: 0.00087227 [loop_unroll]: 0.0002861 [a_1]: 0.0678278 [with_stream_mark]: 0.00013114 [recompute_prepare]: 5.058e-05 [updatestate_depend_eliminate]: 2.767e-05 [updatestate_assign_eliminate]: 2.394e-05 [updatestate_loads_eliminate]: 2.814e-05 [parameter_eliminate]: 3.18e-06 [a_2]: 0.00114812 [accelerated_algorithm]: 7.582e-05 [shard]: 2.78e-06 [meta_shard_fg_expand]: 3.316e-05 [shard_inline]: 3.074e-05 [merge_send_recv]: 2.574e-05 [auto_parallel]: 2.484e-05 [parallel]: 5.95e-05 [flash_sp]: 1.827e-05 [merge_comm]: 1.684e-05 [allreduce_fusion]: 1.562e-05 [matmul_add_comm_reduction]: 2.777e-05 [allreduce_slice_to_reducescatter]: 9.49978e-07 [virtual_shard_identity]: 3.524e-05 [virtual_dataset]: 2.779e-05 [get_grad_eliminate_]: 2.65e-05 [virtual_output]: 2.646e-05 [merge_forward]: 1.625e-05 [cell_reuse_recompute_pass]: 2.34001e-06 [offload_activation]: 2.566e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.74e-05 [merge_recompute_call_nodes]: 1.84e-06 [before_grad]: 4.803e-05 [set_forward_comm_id_for_comm_node_pass]: 1.81e-05 [meta_fg_expand]: 6.615e-05 [flash_sp_send_recv_attached]: 7.03998e-06 [receive_attached]: 1.354e-05 [after_resolve]: 4.672e-05 [a_after_grad]: 4.615e-05 [renormalize]: 0.0699824 [add_forward_monad_depend]: 1.764e-05 [auto_monad_grad]: 4.02e-06 [auto_monad_eliminator]: 0.00011595 [cse]: 0.00039737 [a_3]: 0.00021476 [Cycle 2]: 0.00286056, [45] [expand_dump_flag]: 3.23e-06 [switch_simplify]: 3e-05 [loop_unroll]: 2.533e-05 [a_1]: 0.00081706 [with_stream_mark]: 3.481e-05 [recompute_prepare]: 2.729e-05 [updatestate_depend_eliminate]: 1.812e-05 [updatestate_assign_eliminate]: 1.534e-05 [updatestate_loads_eliminate]: 2.133e-05 [parameter_eliminate]: 3.18e-06 [a_2]: 0.0005554 [accelerated_algorithm]: 4.062e-05 [shard]: 2.83e-06 [meta_shard_fg_expand]: 1.051e-05 [shard_inline]: 2.783e-05 [merge_send_recv]: 2.506e-05 [auto_parallel]: 2.311e-05 [parallel]: 1.092e-05 [flash_sp]: 5.89e-06 [merge_comm]: 1.729e-05 [allreduce_fusion]: 1.467e-05 [matmul_add_comm_reduction]: 2.579e-05 [allreduce_slice_to_reducescatter]: 9.00007e-07 [virtual_shard_identity]: 2.846e-05 [virtual_dataset]: 2.606e-05 [get_grad_eliminate_]: 2.495e-05 [virtual_output]: 2.511e-05 [merge_forward]: 1.547e-05 [cell_reuse_recompute_pass]: 3.61999e-06 [offload_activation]: 2.713e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.962e-05 [merge_recompute_call_nodes]: 1.53002e-06 [before_grad]: 4.336e-05 [set_forward_comm_id_for_comm_node_pass]: 1.744e-05 [meta_fg_expand]: 1.201e-05 [flash_sp_send_recv_attached]: 2.54001e-06 [receive_attached]: 3.03e-06 [after_resolve]: 3.827e-05 [a_after_grad]: 0.00010088 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 4.85001e-06 [auto_monad_grad]: 5.058e-05 [auto_monad_eliminator]: 7.068e-05 [cse]: 0.00011157 [a_3]: 0.0001805 [py_interpret_to_execute_after_opt_a]: 4.476e-05 [slice_cell_reuse_recomputed_activation]: 2.65997e-06 [rewriter_after_opt_a]: 0.00103337 [convert_after_rewriter]: 3.778e-05 [order_py_execute_after_rewriter]: 1.661e-05 [mutable_eliminate]: 0.00095216 [opt_b]: 0.00107015, [1] [Cycle 1]: 0.00105889, [7] [b_1]: 0.00074326 [b_2]: 3.162e-05 [updatestate_depend_eliminate]: 2.692e-05 [updatestate_assign_eliminate]: 1.552e-05 [updatestate_loads_eliminate]: 2.344e-05 [renormalize]: 6.50005e-07 [cse]: 0.00016332 [optimize_parallel_all_gather_comm]: 5.174e-05 [overlap_param_gather]: 7.83001e-06 [cconv]: 5.209e-05 [loop_unroll]: 0.0008903 [opt_after_cconv]: 0.00044006, [1] [Cycle 1]: 0.00042907, [7] [c_1]: 0.00019784 [parameter_eliminate]: 5.77999e-06 [updatestate_depend_eliminate]: 2.991e-05 [updatestate_assign_eliminate]: 1.487e-05 [updatestate_loads_eliminate]: 1.949e-05 [cse]: 0.0001141 [renormalize]: 7.39994e-07 [remove_dup_value]: 0.00019975 [tuple_transform]: 0.00032007, [1] [Cycle 1]: 0.00031118, [4] [d_1]: 0.00024944 [none_parameter_eliminate]: 3.26999e-06 [renormalize]: 2.9002e-07 [switch_simplify]: 2.959e-05 [partial_unused_args_eliminate]: 2.26998e-06 [add_recomputation]: 0.00020662 [cse_after_recomputation]: 9.586e-05, [1] [Cycle 1]: 8.898e-05, [1] [cse]: 7.953e-05 [environ_conv]: 4.577e-05 [swap_dp_allreduce_reducescatter]: 2.457e-05 [bias_add_comm_swap]: 3.61999e-06 [label_micro_interleaved_index]: 7.86001e-06 [label_fine_grained_interleaved_index]: 3.07002e-06 [merge_cast_opt]: 1.79998e-06 [slice_recompute_activation]: 2.39001e-06 [micro_interleaved_order_control]: 2.51e-06 [assign_add_opt]: 1.69e-06 [ForceFp32Comm]: 9.29984e-07 [remove_cast_before_assign_add]: 1.18001e-06 [full_micro_interleaved_order_control]: 2.39999e-06 [reorder_send_recv_between_fp_bp]: 3.25e-06 [comm_op_add_attrs]: 1.34e-06 [add_comm_op_reuse_tag]: 1.15001e-06 [interleave_split_concat_branches]: 1.30999e-06 [interleave_parallel_branches]: 1.10999e-06 [overlap_opt_shard_in_pipeline]: 2.702e-05 [overlap_opt_shard_grad_in_pipeline]: 2.14e-06 [control_data_broadcast_order]: 5.176e-05 [grouped_pairwise_exchange_alltoall]: 1.77999e-06 [offloading_packed_experts]: 1.269e-05 [overlap_recompute_and_grad_model_parallel]: 1.329e-05 [overlap_grad_matmul_and_grad_allreduce]: 3.65e-06 [overlap_recompute_allgather_and_fa_grad]: 1.87001e-06 [overlap_recompute_comm]: 2.64001e-06 [overlap_grad_ring_attention]: 1.762e-05 [overlap_grad_flash_sp]: 8.304e-05 [begin_end_overlap_inline]: 6.29982e-07 [split_matmul_comm_elemetwise]: 2.83e-06 [split_layernorm_comm]: 2.31e-06 [handle_group_info]: 1.15999e-06 [symbol_engine_optimizer]: 0.00062622, [1] [Cycle 1]: 0.00061828, [6] [build]: 0.00032969 [elim_shapecalc]: 4.755e-05 [elim_not_effective]: 7.669e-05 [opt_reshape]: 4.211e-05 [fold_const_symbol]: 7.136e-05 [renormalize]: 6.59988e-07 [detach_backward]: 2.99999e-06 [pipeline_parallel_scheduler]: 2.39999e-06 [auto_monad_reorder]: 9.89e-05 [get_jit_bprop_graph]: 2.32001e-06 [rewriter_after_jit_bprop_graph]: 7.08e-06 [opt_after_jit_grad]: 0.00090639 [validate]: 0.00014212 Sums bootstrap : 0.000735s : 0.04% type_inference : 1.685075s : 91.53% event_method : 0.000510s : 0.03% auto_monad : 0.000929s : 0.05% graph_reusing : 0.000058s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000249s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000059s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000287s : 0.02% insert-virtual-dataset : 0.000005s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000238s : 0.01% optimize.rewriter_before_opt_a : 0.001020s : 0.06% optimize.opt_a.expand_dump_flag : 0.000028s : 0.00% optimize.opt_a.switch_simplify : 0.000902s : 0.05% optimize.opt_a.loop_unroll : 0.000311s : 0.02% optimize.opt_a.a_1 : 0.068645s : 3.73% optimize.opt_a.with_stream_mark : 0.000166s : 0.01% optimize.opt_a.recompute_prepare : 0.000078s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000046s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000039s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000049s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.001704s : 0.09% optimize.opt_a.accelerated_algorithm : 0.000116s : 0.01% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000044s : 0.00% optimize.opt_a.shard_inline : 0.000059s : 0.00% optimize.opt_a.merge_send_recv : 0.000051s : 0.00% optimize.opt_a.auto_parallel : 0.000048s : 0.00% optimize.opt_a.parallel : 0.000070s : 0.00% optimize.opt_a.flash_sp : 0.000024s : 0.00% optimize.opt_a.merge_comm : 0.000034s : 0.00% optimize.opt_a.allreduce_fusion : 0.000030s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000054s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000064s : 0.00% optimize.opt_a.virtual_dataset : 0.000054s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000051s : 0.00% optimize.opt_a.virtual_output : 0.000052s : 0.00% optimize.opt_a.merge_forward : 0.000032s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000053s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000107s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000091s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000036s : 0.00% optimize.opt_a.meta_fg_expand : 0.000078s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000010s : 0.00% optimize.opt_a.receive_attached : 0.000017s : 0.00% optimize.opt_a.after_resolve : 0.000085s : 0.00% optimize.opt_a.a_after_grad : 0.000147s : 0.01% optimize.opt_a.renormalize : 0.069982s : 3.80% optimize.opt_a.add_forward_monad_depend : 0.000022s : 0.00% optimize.opt_a.auto_monad_grad : 0.000055s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000187s : 0.01% optimize.opt_a.cse : 0.000509s : 0.03% optimize.opt_a.a_3 : 0.000395s : 0.02% optimize.py_interpret_to_execute_after_opt_a : 0.000045s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.001033s : 0.06% optimize.convert_after_rewriter : 0.000038s : 0.00% optimize.order_py_execute_after_rewriter : 0.000017s : 0.00% optimize.mutable_eliminate : 0.000952s : 0.05% optimize.opt_b.b_1 : 0.000743s : 0.04% optimize.opt_b.b_2 : 0.000032s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000027s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000016s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000023s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000163s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000052s : 0.00% optimize.overlap_param_gather : 0.000008s : 0.00% optimize.cconv : 0.000052s : 0.00% optimize.loop_unroll : 0.000890s : 0.05% optimize.opt_after_cconv.c_1 : 0.000198s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000030s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000015s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000019s : 0.00% optimize.opt_after_cconv.cse : 0.000114s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000200s : 0.01% optimize.tuple_transform.d_1 : 0.000249s : 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 : 0.000030s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000207s : 0.01% optimize.cse_after_recomputation.cse : 0.000080s : 0.00% optimize.environ_conv : 0.000046s : 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 : 0.000008s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 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 : 0.000027s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000052s : 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 : 0.000004s : 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 : 0.000018s : 0.00% optimize.overlap_grad_flash_sp : 0.000083s : 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 : 0.000330s : 0.02% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000048s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000077s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000042s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000071s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000099s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000906s : 0.05% validate : 0.000142s : 0.01% Time group info: ------[substitution.] 0.062524 608 0.03% : 0.000020s : 8: substitution.depend_value_elim 0.04% : 0.000025s : 17: substitution.elim_not_effective 0.03% : 0.000019s : 12: substitution.float_tuple_getitem_switch 0.05% : 0.000032s : 17: substitution.fold_const_symbol 0.03% : 0.000019s : 22: substitution.graph_param_transform 98.04% : 0.061300s : 71: substitution.inline 0.03% : 0.000017s : 35: substitution.j_node_and_user_rematch 0.07% : 0.000041s : 6: substitution.less_batch_normalization 0.10% : 0.000063s : 2: substitution.list_to_tuple_eliminator_ 0.02% : 0.000011s : 18: substitution.load_eliminater 0.06% : 0.000038s : 21: substitution.minmaximum_grad 0.01% : 0.000009s : 2: substitution.opt_reshape 0.04% : 0.000023s : 35: substitution.remove_not_recompute_node 0.02% : 0.000012s : 8: substitution.replace_old_param 0.09% : 0.000057s : 18: substitution.reshape_eliminate 0.09% : 0.000057s : 24: substitution.switch_simplify 0.25% : 0.000156s : 51: substitution.tuple_list_convert_item_index_to_positive 0.11% : 0.000066s : 51: substitution.tuple_list_get_item_const_eliminator 0.15% : 0.000095s : 51: substitution.tuple_list_get_item_depend_reorder 0.34% : 0.000212s : 73: substitution.tuple_list_get_item_eliminator 0.15% : 0.000094s : 51: substitution.tuple_list_get_set_item_eliminator 0.02% : 0.000012s : 6: substitution.updatestate_pure_node_eliminater 0.23% : 0.000146s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.684637 2 95.03% : 1.600974s : 1: type_inference.infer 4.97% : 0.083663s : 1: type_inference.specialize ------[replace.] 0.001259 115 4.50% : 0.000057s : 5: replace.depend_value_elim 55.67% : 0.000701s : 71: replace.inline 3.50% : 0.000044s : 2: replace.list_to_tuple_eliminator_ 26.68% : 0.000336s : 24: replace.switch_simplify 9.64% : 0.000121s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.061392 115 0.00% : 0.000002s : 5: match.depend_value_elim 99.78% : 0.061254s : 71: match.inline 0.10% : 0.000060s : 2: match.list_to_tuple_eliminator_ 0.07% : 0.000046s : 24: match.switch_simplify 0.05% : 0.000030s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.001941 10915 1.08% : 0.000021s : 133: predicate.accumulaten_eliminater 0.36% : 0.000007s : 22: predicate.ad_related_special_op_eliminate 0.52% : 0.000010s : 73: predicate.addn_check_dump 0.96% : 0.000019s : 133: predicate.addn_zero_filter 0.92% : 0.000018s : 133: predicate.adjust_all_reduce_mul_add 2.18% : 0.000042s : 206: predicate.arithmetic_simplify 1.84% : 0.000036s : 133: predicate.cast_eliminate 0.33% : 0.000006s : 44: predicate.check_bprop_eliminate 0.52% : 0.000010s : 73: predicate.compare_switch_simplify 0.09% : 0.000002s : 22: predicate.const_output_eliminate 0.58% : 0.000011s : 76: predicate.depend_value_elim 1.04% : 0.000020s : 133: predicate.dict_get_item_const_eliminator 1.04% : 0.000020s : 133: predicate.dict_get_item_eliminator 1.09% : 0.000021s : 133: predicate.dict_set_item_eliminator 2.55% : 0.000049s : 44: predicate.dumpgradient_eliminate 0.15% : 0.000003s : 22: predicate.elim_not_effective 0.20% : 0.000004s : 22: predicate.elim_shapecalc_of_broadcastargs 1.10% : 0.000021s : 155: predicate.environ_add_const_eliminate 1.06% : 0.000021s : 155: predicate.environ_get_add_eliminate 1.08% : 0.000021s : 155: predicate.environ_get_depend_swap 1.68% : 0.000033s : 228: predicate.environ_get_eliminate 1.08% : 0.000021s : 155: predicate.environ_get_set_eliminate 3.69% : 0.000072s : 219: predicate.exchange_switch_depend_value 2.31% : 0.000045s : 219: predicate.float_depend_g_call 0.51% : 0.000010s : 73: predicate.float_environ_get_switch 0.72% : 0.000014s : 95: predicate.float_tuple_getitem_switch 0.09% : 0.000002s : 22: predicate.fold_const_symbol 0.35% : 0.000007s : 45: predicate.get_grad_eliminate 0.11% : 0.000002s : 22: predicate.graph_param_transform 0.53% : 0.000010s : 73: predicate.incorporate_call 0.50% : 0.000010s : 73: predicate.incorporate_call_switch 5.51% : 0.000107s : 514: predicate.inline 0.52% : 0.000010s : 45: predicate.inline_without_move 0.16% : 0.000003s : 45: predicate.j_node_and_user_rematch 0.49% : 0.000009s : 45: predicate.less_batch_normalization 1.38% : 0.000027s : 192: predicate.list_to_tuple_eliminator_ 2.28% : 0.000044s : 325: predicate.load_eliminater 0.43% : 0.000008s : 22: predicate.loop_unroll_after_grad 3.09% : 0.000060s : 324: predicate.loop_unroll_before_grad 1.35% : 0.000026s : 177: predicate.make_slice_get_slice_eliminator 0.52% : 0.000010s : 73: predicate.merge_addn 0.31% : 0.000006s : 44: predicate.micro_step_allgather_replace 0.30% : 0.000006s : 44: predicate.mini_step_allgather_replace 1.03% : 0.000020s : 133: predicate.minmaximum_grad 0.39% : 0.000008s : 22: predicate.mutable_eliminate 0.22% : 0.000004s : 22: predicate.opt_reshape 0.19% : 0.000004s : 22: predicate.parallel_virtual_node 2.90% : 0.000056s : 219: predicate.partial_defer_inline 1.35% : 0.000026s : 170: predicate.partial_eliminate 1.04% : 0.000020s : 133: predicate.print_const_string_wrapper 0.52% : 0.000010s : 68: predicate.reduce_all_const_elim 1.29% : 0.000025s : 133: predicate.reduce_eliminate 2.36% : 0.000046s : 325: predicate.redundant_stop_gradient_eliminater 0.18% : 0.000004s : 45: predicate.remove_not_recompute_node 1.04% : 0.000020s : 192: predicate.replace_applicator 0.20% : 0.000004s : 45: predicate.replace_old_param 0.11% : 0.000002s : 22: predicate.reset_defer_inline 1.06% : 0.000021s : 133: predicate.reshape_eliminate 0.32% : 0.000006s : 44: predicate.row_tensor_add_zeros_like 0.20% : 0.000004s : 22: predicate.row_tensor_eliminate 0.40% : 0.000008s : 44: predicate.same_eliminate 0.21% : 0.000004s : 50: predicate.set_cell_output_no_recompute 0.40% : 0.000008s : 45: predicate.shard_identity_eliminate 0.35% : 0.000007s : 44: predicate.special_op_eliminate 0.64% : 0.000012s : 73: predicate.specialize_transform 0.43% : 0.000008s : 44: predicate.split_environ_get_set_with_tuple_value 0.40% : 0.000008s : 45: predicate.stack_unstack_eliminate 0.18% : 0.000004s : 22: predicate.switch_call_monad_eliminater 1.78% : 0.000035s : 219: predicate.switch_defer_inline 2.07% : 0.000040s : 263: predicate.switch_layer_defer_inline 6.61% : 0.000128s : 686: predicate.switch_simplify 1.00% : 0.000019s : 133: predicate.tile_eliminate 1.05% : 0.000020s : 133: predicate.transpose_eliminate 1.63% : 0.000032s : 177: predicate.tuple_list_convert_item_index_to_positive 1.56% : 0.000030s : 177: predicate.tuple_list_get_item_const_eliminator 1.37% : 0.000027s : 177: predicate.tuple_list_get_item_depend_reorder 2.82% : 0.000055s : 263: predicate.tuple_list_get_item_eliminator 1.46% : 0.000028s : 177: predicate.tuple_list_get_set_item_eliminator 2.14% : 0.000041s : 250: predicate.tuple_list_set_item_eliminator 1.40% : 0.000027s : 190: predicate.tuple_to_list_eliminator_ 2.34% : 0.000045s : 325: predicate.updatestate_pure_node_eliminater 7.51% : 0.000146s : 398: predicate.updatestate_useless_node_eliminater 0.21% : 0.000004s : 22: predicate.value_based_eliminate 0.34% : 0.000007s : 45: predicate.virtual_dataset_eliminate 0.33% : 0.000006s : 45: predicate.virtual_output_eliminate 0.17% : 0.000003s : 22: predicate.virtual_view_grad_eliminate 0.18% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.014623 133 59.18% : 0.008653s : 53: func_graph_cloner_run.FuncGraphClonerGraph 40.82% : 0.005970s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.159862 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.46% : 0.009984s : 1: add_attr 0.46% : 0.009964s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000214s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.04% : 0.000951s : 1: auto_monad 0.00% : 0.000105s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.04% : 0.000778s : 1: bootstrap 0.00% : 0.000057s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000056s : 1: control_data_broadcast_order 0.00% : 0.000045s : 1: convert_after_rewriter 0.00% : 0.000100s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000052s : 1: environ_conv 0.02% : 0.000533s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000067s : 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% : 0.000053s : 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 0.04% : 0.000907s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.04% : 0.000968s : 1: mutable_eliminate 0.00% : 0.000016s : 1: offloading_packed_experts 0.00% : 0.000054s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000050s : 1: opt.transform.mutable_eliminate 3.36% : 0.072670s : 95: opt.transform.opt_a 0.01% : 0.000196s : 1: opt.transform.opt_after_cconv 0.00% : 0.000096s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000729s : 28: opt.transform.opt_b 0.01% : 0.000274s : 2: opt.transform.opt_trans_graph 0.01% : 0.000230s : 4: opt.transform.symbol_engine_opt 6.73% : 0.145321s : 1: opt_a 0.02% : 0.000444s : 1: opt_after_cconv 0.04% : 0.000922s : 1: opt_after_jit_grad 0.05% : 0.001075s : 1: opt_b 7.10% : 0.153432s : 1: optimize 0.00% : 0.000057s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000022s : 1: order_py_execute_after_rewriter 0.00% : 0.000088s : 1: overlap_grad_flash_sp 0.00% : 0.000009s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000021s : 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% : 0.000011s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000126s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000006s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000296s : 1: pre_auto_parallel 0.01% : 0.000246s : 1: py_interpret_to_execute 0.00% : 0.000050s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000211s : 1: remove_dup_value 0.57% : 0.012333s : 1: renormalize.infer 2.67% : 0.057626s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.001052s : 1: rewriter_after_opt_a 0.05% : 0.001044s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000029s : 1: swap_dp_allreduce_reducescatter 0.03% : 0.000630s : 1: symbol_engine_optimizer 0.01% : 0.000324s : 1: tuple_transform 78.02% : 1.685120s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_ffn_0[True-k_n_shape0-256] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_ffn_0[True-k_n_shape0-256],max_mem:196.0M [WARNING] ME(171560:281472843685680,MainProcess):2026-01-29-17:40:17.928.355 [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 = 1.41525, [21] [bootstrap]: 0.00058224 [type_inference]: 1.25154 [event_method]: 0.00019911 [auto_monad]: 0.00072987 [graph_reusing]: 3.919e-05 [inline]: 6.16998e-06 [add_attr]: 0.00756845, [1] [add_attr_with_inline]: 0.00755483, [1] [Cycle 1]: 0.00027704, [2] [tag_attr]: 0.00019154 [meta_addattr_fg_expand]: 4.603e-05 [parallel-infer-symbol]: 3.68999e-06 [pre_auto_parallel]: 0.00022434 [insert-virtual-dataset]: 3.7e-06 [parallel-infer-symbol-second]: 1.02e-06 [dataset_repeat_opt]: 2.51998e-06 [pipeline_split]: 2.47001e-06 [optimize]: 0.153189, [53] [py_interpret_to_execute]: 0.00021674 [rewriter_before_opt_a]: 0.00075609 [opt_a]: 0.0773786, [2] [Cycle 1]: 0.0746004, [45] [expand_dump_flag]: 2.834e-05 [switch_simplify]: 0.0007116 [loop_unroll]: 0.00028818 [a_1]: 0.0547747 [with_stream_mark]: 0.00013963 [recompute_prepare]: 4.731e-05 [updatestate_depend_eliminate]: 2.822e-05 [updatestate_assign_eliminate]: 2.338e-05 [updatestate_loads_eliminate]: 2.777e-05 [parameter_eliminate]: 3.01001e-06 [a_2]: 0.00098169 [accelerated_algorithm]: 8.138e-05 [shard]: 2.59001e-06 [meta_shard_fg_expand]: 2.332e-05 [shard_inline]: 3.084e-05 [merge_send_recv]: 2.437e-05 [auto_parallel]: 2.412e-05 [parallel]: 4.316e-05 [flash_sp]: 1.617e-05 [merge_comm]: 1.703e-05 [allreduce_fusion]: 1.767e-05 [matmul_add_comm_reduction]: 2.632e-05 [allreduce_slice_to_reducescatter]: 7.80012e-07 [virtual_shard_identity]: 3.432e-05 [virtual_dataset]: 3.039e-05 [get_grad_eliminate_]: 2.939e-05 [virtual_output]: 2.878e-05 [merge_forward]: 1.603e-05 [cell_reuse_recompute_pass]: 2.07001e-06 [offload_activation]: 2.893e-05 [cell_reuse_handle_not_recompute_node_pass]: 6.33e-05 [merge_recompute_call_nodes]: 1.54998e-06 [before_grad]: 5.45e-05 [set_forward_comm_id_for_comm_node_pass]: 1.993e-05 [meta_fg_expand]: 1.754e-05 [flash_sp_send_recv_attached]: 5.34e-06 [receive_attached]: 2.66e-06 [after_resolve]: 4.072e-05 [a_after_grad]: 5.773e-05 [renormalize]: 0.0155167 [add_forward_monad_depend]: 1.895e-05 [auto_monad_grad]: 2.91999e-06 [auto_monad_eliminator]: 9.618e-05 [cse]: 0.00055852 [a_3]: 0.00020683 [Cycle 2]: 0.00276042, [45] [expand_dump_flag]: 2.54001e-06 [switch_simplify]: 2.98e-05 [loop_unroll]: 2.678e-05 [a_1]: 0.00094676 [with_stream_mark]: 3.173e-05 [recompute_prepare]: 2.823e-05 [updatestate_depend_eliminate]: 2.996e-05 [updatestate_assign_eliminate]: 1.516e-05 [updatestate_loads_eliminate]: 2.104e-05 [parameter_eliminate]: 2.72001e-06 [a_2]: 0.00042283 [accelerated_algorithm]: 4.082e-05 [shard]: 2.48998e-06 [meta_shard_fg_expand]: 7.13998e-06 [shard_inline]: 2.959e-05 [merge_send_recv]: 2.271e-05 [auto_parallel]: 2.095e-05 [parallel]: 1.078e-05 [flash_sp]: 5.24998e-06 [merge_comm]: 1.514e-05 [allreduce_fusion]: 1.627e-05 [matmul_add_comm_reduction]: 2.477e-05 [allreduce_slice_to_reducescatter]: 7.09988e-07 [virtual_shard_identity]: 2.902e-05 [virtual_dataset]: 2.724e-05 [get_grad_eliminate_]: 2.87e-05 [virtual_output]: 2.676e-05 [merge_forward]: 1.556e-05 [cell_reuse_recompute_pass]: 3.83999e-06 [offload_activation]: 2.677e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.172e-05 [merge_recompute_call_nodes]: 1.67999e-06 [before_grad]: 4.965e-05 [set_forward_comm_id_for_comm_node_pass]: 1.696e-05 [meta_fg_expand]: 1.104e-05 [flash_sp_send_recv_attached]: 2.35002e-06 [receive_attached]: 2.61e-06 [after_resolve]: 3.786e-05 [a_after_grad]: 4.93e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 3.04001e-06 [auto_monad_grad]: 2.79999e-06 [auto_monad_eliminator]: 6.425e-05 [cse]: 9.999e-05 [a_3]: 0.00019123 [py_interpret_to_execute_after_opt_a]: 3.348e-05 [slice_cell_reuse_recomputed_activation]: 2.46998e-06 [rewriter_after_opt_a]: 0.00090759 [convert_after_rewriter]: 3.24e-05 [order_py_execute_after_rewriter]: 1.632e-05 [mutable_eliminate]: 0.00082757 [opt_b]: 0.0699446, [1] [Cycle 1]: 0.069934, [7] [b_1]: 0.069624 [b_2]: 3.857e-05 [updatestate_depend_eliminate]: 2.642e-05 [updatestate_assign_eliminate]: 1.586e-05 [updatestate_loads_eliminate]: 2.273e-05 [renormalize]: 7.80012e-07 [cse]: 0.00012508 [optimize_parallel_all_gather_comm]: 5.247e-05 [overlap_param_gather]: 3.06999e-06 [cconv]: 4.026e-05 [loop_unroll]: 0.00077844 [opt_after_cconv]: 0.0003791, [1] [Cycle 1]: 0.00036899, [7] [c_1]: 0.00018042 [parameter_eliminate]: 4.33001e-06 [updatestate_depend_eliminate]: 1.836e-05 [updatestate_assign_eliminate]: 1.353e-05 [updatestate_loads_eliminate]: 1.73e-05 [cse]: 9.461e-05 [renormalize]: 1.20999e-06 [remove_dup_value]: 0.00011819 [tuple_transform]: 0.00030618, [1] [Cycle 1]: 0.00030019, [4] [d_1]: 0.00024801 [none_parameter_eliminate]: 2.22001e-06 [renormalize]: 2.69996e-07 [switch_simplify]: 2.679e-05 [partial_unused_args_eliminate]: 1.96e-06 [add_recomputation]: 0.00018267 [cse_after_recomputation]: 8.05e-05, [1] [Cycle 1]: 7.503e-05, [1] [cse]: 6.739e-05 [environ_conv]: 2.879e-05 [swap_dp_allreduce_reducescatter]: 1.968e-05 [bias_add_comm_swap]: 3.58e-06 [label_micro_interleaved_index]: 5.42001e-06 [label_fine_grained_interleaved_index]: 3.07002e-06 [merge_cast_opt]: 1.46998e-06 [slice_recompute_activation]: 2.64001e-06 [micro_interleaved_order_control]: 2.32999e-06 [assign_add_opt]: 1.33002e-06 [ForceFp32Comm]: 1.22e-06 [remove_cast_before_assign_add]: 1.46998e-06 [full_micro_interleaved_order_control]: 2.56998e-06 [reorder_send_recv_between_fp_bp]: 3.08998e-06 [comm_op_add_attrs]: 1.44e-06 [add_comm_op_reuse_tag]: 1.02e-06 [interleave_split_concat_branches]: 1.32999e-06 [interleave_parallel_branches]: 1.09003e-06 [overlap_opt_shard_in_pipeline]: 2.36998e-06 [overlap_opt_shard_grad_in_pipeline]: 2.00002e-06 [control_data_broadcast_order]: 4.372e-05 [grouped_pairwise_exchange_alltoall]: 1.69e-06 [offloading_packed_experts]: 1.19e-05 [overlap_recompute_and_grad_model_parallel]: 1.21e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.30001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.44e-06 [overlap_recompute_comm]: 2.53e-06 [overlap_grad_ring_attention]: 1.069e-05 [overlap_grad_flash_sp]: 6.127e-05 [begin_end_overlap_inline]: 5.89993e-07 [split_matmul_comm_elemetwise]: 2.33998e-06 [split_layernorm_comm]: 1.94e-06 [handle_group_info]: 1.04998e-06 [symbol_engine_optimizer]: 0.00060068, [1] [Cycle 1]: 0.0005948, [6] [build]: 0.00034553 [elim_shapecalc]: 4.021e-05 [elim_not_effective]: 6.035e-05 [opt_reshape]: 3.647e-05 [fold_const_symbol]: 6.611e-05 [renormalize]: 2.50002e-07 [detach_backward]: 2.88e-06 [pipeline_parallel_scheduler]: 1.59e-06 [auto_monad_reorder]: 8.038e-05 [get_jit_bprop_graph]: 1.68002e-06 [rewriter_after_jit_bprop_graph]: 4.47e-06 [opt_after_jit_grad]: 0.00072914 [validate]: 0.00010923 Sums bootstrap : 0.000582s : 0.04% type_inference : 1.251544s : 88.98% event_method : 0.000199s : 0.01% auto_monad : 0.000730s : 0.05% graph_reusing : 0.000039s : 0.00% inline : 0.000006s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000192s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000046s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000224s : 0.02% insert-virtual-dataset : 0.000004s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000217s : 0.02% optimize.rewriter_before_opt_a : 0.000756s : 0.05% optimize.opt_a.expand_dump_flag : 0.000031s : 0.00% optimize.opt_a.switch_simplify : 0.000741s : 0.05% optimize.opt_a.loop_unroll : 0.000315s : 0.02% optimize.opt_a.a_1 : 0.055721s : 3.96% optimize.opt_a.with_stream_mark : 0.000171s : 0.01% optimize.opt_a.recompute_prepare : 0.000076s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000058s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000039s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000049s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.001405s : 0.10% optimize.opt_a.accelerated_algorithm : 0.000122s : 0.01% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000030s : 0.00% optimize.opt_a.shard_inline : 0.000060s : 0.00% optimize.opt_a.merge_send_recv : 0.000047s : 0.00% optimize.opt_a.auto_parallel : 0.000045s : 0.00% optimize.opt_a.parallel : 0.000054s : 0.00% optimize.opt_a.flash_sp : 0.000021s : 0.00% optimize.opt_a.merge_comm : 0.000032s : 0.00% optimize.opt_a.allreduce_fusion : 0.000034s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000051s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000063s : 0.00% optimize.opt_a.virtual_dataset : 0.000058s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000058s : 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 : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000056s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000115s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000104s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000037s : 0.00% optimize.opt_a.meta_fg_expand : 0.000029s : 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 : 0.000079s : 0.01% optimize.opt_a.a_after_grad : 0.000107s : 0.01% optimize.opt_a.renormalize : 0.015517s : 1.10% optimize.opt_a.add_forward_monad_depend : 0.000022s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000160s : 0.01% optimize.opt_a.cse : 0.000659s : 0.05% optimize.opt_a.a_3 : 0.000398s : 0.03% optimize.py_interpret_to_execute_after_opt_a : 0.000033s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000908s : 0.06% optimize.convert_after_rewriter : 0.000032s : 0.00% optimize.order_py_execute_after_rewriter : 0.000016s : 0.00% optimize.mutable_eliminate : 0.000828s : 0.06% optimize.opt_b.b_1 : 0.069624s : 4.95% optimize.opt_b.b_2 : 0.000039s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000026s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000016s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000023s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000125s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000052s : 0.00% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000040s : 0.00% optimize.loop_unroll : 0.000778s : 0.06% optimize.opt_after_cconv.c_1 : 0.000180s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000018s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.cse : 0.000095s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000118s : 0.01% optimize.tuple_transform.d_1 : 0.000248s : 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 : 0.000027s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000183s : 0.01% optimize.cse_after_recomputation.cse : 0.000067s : 0.00% optimize.environ_conv : 0.000029s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000020s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000002s : 0.00% optimize.assign_add_opt : 0.000001s : 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 : 0.000002s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000044s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000012s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000012s : 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 : 0.000061s : 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 : 0.000346s : 0.02% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000040s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000060s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000036s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000066s : 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 : 0.000080s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000004s : 0.00% opt_after_jit_grad : 0.000729s : 0.05% validate : 0.000109s : 0.01% Time group info: ------[substitution.] 0.002773 608 0.57% : 0.000016s : 8: substitution.depend_value_elim 0.61% : 0.000017s : 17: substitution.elim_not_effective 0.62% : 0.000017s : 12: substitution.float_tuple_getitem_switch 1.00% : 0.000028s : 17: substitution.fold_const_symbol 0.64% : 0.000018s : 22: substitution.graph_param_transform 59.97% : 0.001663s : 71: substitution.inline 0.61% : 0.000017s : 35: substitution.j_node_and_user_rematch 1.40% : 0.000039s : 6: substitution.less_batch_normalization 1.54% : 0.000043s : 2: substitution.list_to_tuple_eliminator_ 0.41% : 0.000011s : 18: substitution.load_eliminater 1.22% : 0.000034s : 21: substitution.minmaximum_grad 0.23% : 0.000006s : 2: substitution.opt_reshape 0.88% : 0.000025s : 35: substitution.remove_not_recompute_node 0.37% : 0.000010s : 8: substitution.replace_old_param 1.68% : 0.000047s : 18: substitution.reshape_eliminate 1.42% : 0.000039s : 24: substitution.switch_simplify 6.47% : 0.000179s : 51: substitution.tuple_list_convert_item_index_to_positive 2.42% : 0.000067s : 51: substitution.tuple_list_get_item_const_eliminator 3.40% : 0.000094s : 51: substitution.tuple_list_get_item_depend_reorder 6.97% : 0.000193s : 73: substitution.tuple_list_get_item_eliminator 3.30% : 0.000092s : 51: substitution.tuple_list_get_set_item_eliminator 0.39% : 0.000011s : 6: substitution.updatestate_pure_node_eliminater 3.90% : 0.000108s : 9: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.251176 2 91.96% : 1.150552s : 1: type_inference.infer 8.04% : 0.100624s : 1: type_inference.specialize ------[replace.] 0.000976 115 4.78% : 0.000047s : 5: replace.depend_value_elim 53.44% : 0.000521s : 71: replace.inline 3.09% : 0.000030s : 2: replace.list_to_tuple_eliminator_ 26.16% : 0.000255s : 24: replace.switch_simplify 12.54% : 0.000122s : 13: replace.tuple_list_get_item_eliminator ------[match.] 0.001735 115 0.13% : 0.000002s : 5: match.depend_value_elim 93.61% : 0.001625s : 71: match.inline 2.33% : 0.000040s : 2: match.list_to_tuple_eliminator_ 1.75% : 0.000030s : 24: match.switch_simplify 2.18% : 0.000038s : 13: match.tuple_list_get_item_eliminator ------[predicate.] 0.001716 10915 1.09% : 0.000019s : 133: predicate.accumulaten_eliminater 0.38% : 0.000006s : 22: predicate.ad_related_special_op_eliminate 0.59% : 0.000010s : 73: predicate.addn_check_dump 1.10% : 0.000019s : 133: predicate.addn_zero_filter 1.02% : 0.000018s : 133: predicate.adjust_all_reduce_mul_add 2.22% : 0.000038s : 206: predicate.arithmetic_simplify 1.10% : 0.000019s : 133: predicate.cast_eliminate 0.37% : 0.000006s : 44: predicate.check_bprop_eliminate 0.58% : 0.000010s : 73: predicate.compare_switch_simplify 0.13% : 0.000002s : 22: predicate.const_output_eliminate 0.68% : 0.000012s : 76: predicate.depend_value_elim 1.18% : 0.000020s : 133: predicate.dict_get_item_const_eliminator 1.28% : 0.000022s : 133: predicate.dict_get_item_eliminator 1.08% : 0.000019s : 133: predicate.dict_set_item_eliminator 0.43% : 0.000007s : 44: predicate.dumpgradient_eliminate 0.12% : 0.000002s : 22: predicate.elim_not_effective 0.21% : 0.000004s : 22: predicate.elim_shapecalc_of_broadcastargs 1.24% : 0.000021s : 155: predicate.environ_add_const_eliminate 1.22% : 0.000021s : 155: predicate.environ_get_add_eliminate 1.22% : 0.000021s : 155: predicate.environ_get_depend_swap 1.93% : 0.000033s : 228: predicate.environ_get_eliminate 2.44% : 0.000042s : 155: predicate.environ_get_set_eliminate 1.83% : 0.000031s : 219: predicate.exchange_switch_depend_value 2.38% : 0.000041s : 219: predicate.float_depend_g_call 0.60% : 0.000010s : 73: predicate.float_environ_get_switch 0.79% : 0.000014s : 95: predicate.float_tuple_getitem_switch 0.10% : 0.000002s : 22: predicate.fold_const_symbol 0.45% : 0.000008s : 45: predicate.get_grad_eliminate 0.12% : 0.000002s : 22: predicate.graph_param_transform 0.59% : 0.000010s : 73: predicate.incorporate_call 0.55% : 0.000009s : 73: predicate.incorporate_call_switch 5.87% : 0.000101s : 514: predicate.inline 0.53% : 0.000009s : 45: predicate.inline_without_move 0.20% : 0.000004s : 45: predicate.j_node_and_user_rematch 0.55% : 0.000009s : 45: predicate.less_batch_normalization 1.60% : 0.000027s : 192: predicate.list_to_tuple_eliminator_ 2.57% : 0.000044s : 325: predicate.load_eliminater 0.41% : 0.000007s : 22: predicate.loop_unroll_after_grad 2.91% : 0.000050s : 324: predicate.loop_unroll_before_grad 1.52% : 0.000026s : 177: predicate.make_slice_get_slice_eliminator 0.62% : 0.000011s : 73: predicate.merge_addn 0.36% : 0.000006s : 44: predicate.micro_step_allgather_replace 0.40% : 0.000007s : 44: predicate.mini_step_allgather_replace 1.10% : 0.000019s : 133: predicate.minmaximum_grad 0.43% : 0.000007s : 22: predicate.mutable_eliminate 0.22% : 0.000004s : 22: predicate.opt_reshape 0.79% : 0.000014s : 22: predicate.parallel_virtual_node 2.45% : 0.000042s : 219: predicate.partial_defer_inline 1.57% : 0.000027s : 170: predicate.partial_eliminate 1.10% : 0.000019s : 133: predicate.print_const_string_wrapper 0.58% : 0.000010s : 68: predicate.reduce_all_const_elim 1.45% : 0.000025s : 133: predicate.reduce_eliminate 2.54% : 0.000044s : 325: predicate.redundant_stop_gradient_eliminater 0.22% : 0.000004s : 45: predicate.remove_not_recompute_node 1.19% : 0.000020s : 192: predicate.replace_applicator 0.25% : 0.000004s : 45: predicate.replace_old_param 0.12% : 0.000002s : 22: predicate.reset_defer_inline 1.21% : 0.000021s : 133: predicate.reshape_eliminate 0.39% : 0.000007s : 44: predicate.row_tensor_add_zeros_like 0.24% : 0.000004s : 22: predicate.row_tensor_eliminate 0.51% : 0.000009s : 44: predicate.same_eliminate 0.25% : 0.000004s : 50: predicate.set_cell_output_no_recompute 0.44% : 0.000008s : 45: predicate.shard_identity_eliminate 0.42% : 0.000007s : 44: predicate.special_op_eliminate 0.69% : 0.000012s : 73: predicate.specialize_transform 0.46% : 0.000008s : 44: predicate.split_environ_get_set_with_tuple_value 0.48% : 0.000008s : 45: predicate.stack_unstack_eliminate 0.21% : 0.000004s : 22: predicate.switch_call_monad_eliminater 1.98% : 0.000034s : 219: predicate.switch_defer_inline 2.31% : 0.000040s : 263: predicate.switch_layer_defer_inline 6.21% : 0.000107s : 686: predicate.switch_simplify 1.08% : 0.000019s : 133: predicate.tile_eliminate 1.16% : 0.000020s : 133: predicate.transpose_eliminate 1.73% : 0.000030s : 177: predicate.tuple_list_convert_item_index_to_positive 1.74% : 0.000030s : 177: predicate.tuple_list_get_item_const_eliminator 1.65% : 0.000028s : 177: predicate.tuple_list_get_item_depend_reorder 3.19% : 0.000055s : 263: predicate.tuple_list_get_item_eliminator 1.64% : 0.000028s : 177: predicate.tuple_list_get_set_item_eliminator 2.36% : 0.000041s : 250: predicate.tuple_list_set_item_eliminator 1.83% : 0.000031s : 190: predicate.tuple_to_list_eliminator_ 2.55% : 0.000044s : 325: predicate.updatestate_pure_node_eliminater 3.29% : 0.000057s : 398: predicate.updatestate_useless_node_eliminater 0.20% : 0.000003s : 22: predicate.value_based_eliminate 0.40% : 0.000007s : 45: predicate.virtual_dataset_eliminate 0.41% : 0.000007s : 45: predicate.virtual_output_eliminate 0.20% : 0.000003s : 22: predicate.virtual_view_grad_eliminate 0.22% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.016864 133 67.52% : 0.011386s : 53: func_graph_cloner_run.FuncGraphClonerGraph 32.48% : 0.005478s : 80: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.721020 209 0.00% : 0.000004s : 1: ForceFp32Comm 0.44% : 0.007575s : 1: add_attr 0.44% : 0.007559s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000189s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.04% : 0.000746s : 1: auto_monad 0.01% : 0.000087s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.04% : 0.000621s : 1: bootstrap 0.00% : 0.000044s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000047s : 1: control_data_broadcast_order 0.00% : 0.000039s : 1: convert_after_rewriter 0.00% : 0.000084s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000033s : 1: environ_conv 0.01% : 0.000210s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000045s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000010s : 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% : 0.000008s : 1: label_micro_interleaved_index 0.05% : 0.000789s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.05% : 0.000839s : 1: mutable_eliminate 0.00% : 0.000015s : 1: offloading_packed_experts 0.00% : 0.000042s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000049s : 1: opt.transform.mutable_eliminate 3.45% : 0.059324s : 95: opt.transform.opt_a 0.01% : 0.000179s : 1: opt.transform.opt_after_cconv 0.01% : 0.000089s : 1: opt.transform.opt_after_jit_grad 4.04% : 0.069605s : 28: opt.transform.opt_b 0.02% : 0.000271s : 2: opt.transform.opt_trans_graph 0.01% : 0.000198s : 4: opt.transform.symbol_engine_opt 4.50% : 0.077383s : 1: opt_a 0.02% : 0.000383s : 1: opt_after_cconv 0.04% : 0.000744s : 1: opt_after_jit_grad 4.06% : 0.069950s : 1: opt_b 8.90% : 0.153195s : 1: optimize 0.00% : 0.000057s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000020s : 1: order_py_execute_after_rewriter 0.00% : 0.000065s : 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% : 0.000005s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000007s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000015s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000232s : 1: pre_auto_parallel 0.01% : 0.000224s : 1: py_interpret_to_execute 0.00% : 0.000040s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000124s : 1: remove_dup_value 0.52% : 0.008941s : 1: renormalize.infer 0.38% : 0.006556s : 1: renormalize.specialize 0.00% : 0.000007s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000921s : 1: rewriter_after_opt_a 0.04% : 0.000766s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000023s : 1: swap_dp_allreduce_reducescatter 0.04% : 0.000604s : 1: symbol_engine_optimizer 0.02% : 0.000309s : 1: tuple_transform 72.72% : 1.251570s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_ffn_0[True-k_n_shape0-1024] tests/st/infer/ops/test_internal_ops/test_qbmm_split.py::test_qbmm_ffn_0[True-k_n_shape0-1024],max_mem:232.0M =============================== 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_ffn_0[True-k_n_shape0-256] test_qbmm_split.py::test_qbmm_ffn_0[True-k_n_shape0-1024] /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, 27 warnings in 484.90s (0:08:04) ==================