==================================================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/ops/ascend/test_aclnn_ops, configfile: ../../../../../../../../sault/virtual_test/virtualenv_003/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 4 items test_dequant_swiglu_quant.py [WARNING] ME(166930:281473228386096,MainProcess):2026-01-29-17:39:43.398.579 [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 = 0.687298, [21] [bootstrap]: 0.00099095 [type_inference]: 0.23903 [event_method]: 1.879e-05 [auto_monad]: 0.00010671 [graph_reusing]: 6.52001e-06 [inline]: 3.06999e-06 [add_attr]: 0.231094, [1] [add_attr_with_inline]: 0.231078, [1] [Cycle 1]: 0.00010868, [2] [tag_attr]: 2.53e-05 [meta_addattr_fg_expand]: 5.67001e-06 [parallel-infer-symbol]: 3.63e-06 [pre_auto_parallel]: 5.378e-05 [insert-virtual-dataset]: 7.51999e-06 [parallel-infer-symbol-second]: 9.39996e-07 [dataset_repeat_opt]: 1.87999e-06 [pipeline_split]: 1.72999e-06 [optimize]: 0.0088421, [53] [py_interpret_to_execute]: 4.582e-05 [rewriter_before_opt_a]: 0.00010415 [opt_a]: 0.0049715, [2] [Cycle 1]: 0.00345686, [45] [expand_dump_flag]: 3.43e-06 [switch_simplify]: 4.105e-05 [loop_unroll]: 2.488e-05 [a_1]: 0.00066835 [with_stream_mark]: 2.431e-05 [recompute_prepare]: 1.449e-05 [updatestate_depend_eliminate]: 7.18e-06 [updatestate_assign_eliminate]: 6.81001e-06 [updatestate_loads_eliminate]: 5.92999e-06 [parameter_eliminate]: 2.33002e-06 [a_2]: 0.00020233 [accelerated_algorithm]: 2.875e-05 [shard]: 2.68e-06 [meta_shard_fg_expand]: 2.78e-06 [shard_inline]: 1.16e-05 [merge_send_recv]: 3.218e-05 [auto_parallel]: 1.058e-05 [parallel]: 5.15e-05 [flash_sp]: 2.091e-05 [merge_comm]: 8.15999e-06 [allreduce_fusion]: 6.68e-06 [matmul_add_comm_reduction]: 1.578e-05 [allreduce_slice_to_reducescatter]: 1.18001e-06 [virtual_shard_identity]: 1.626e-05 [virtual_dataset]: 1.248e-05 [get_grad_eliminate_]: 1.191e-05 [virtual_output]: 1.19e-05 [merge_forward]: 7.17997e-06 [cell_reuse_recompute_pass]: 1.86e-06 [offload_activation]: 1.552e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.112e-05 [merge_recompute_call_nodes]: 1.86e-06 [before_grad]: 1.862e-05 [set_forward_comm_id_for_comm_node_pass]: 7.71999e-06 [meta_fg_expand]: 5.12999e-06 [flash_sp_send_recv_attached]: 5.44998e-06 [receive_attached]: 1.171e-05 [after_resolve]: 2.099e-05 [a_after_grad]: 0.00024137 [renormalize]: 0.00125819 [add_forward_monad_depend]: 1.761e-05 [auto_monad_grad]: 3.08e-06 [auto_monad_eliminator]: 2.469e-05 [cse]: 0.00013476 [a_3]: 0.00010195 [Cycle 2]: 0.00149855, [45] [expand_dump_flag]: 3.01999e-06 [switch_simplify]: 1.576e-05 [loop_unroll]: 1.223e-05 [a_1]: 0.00047639 [with_stream_mark]: 2.143e-05 [recompute_prepare]: 1.295e-05 [updatestate_depend_eliminate]: 8.27e-06 [updatestate_assign_eliminate]: 6.58e-06 [updatestate_loads_eliminate]: 5.81003e-06 [parameter_eliminate]: 2.34999e-06 [a_2]: 0.00016514 [accelerated_algorithm]: 1.631e-05 [shard]: 2.39999e-06 [meta_shard_fg_expand]: 3.36001e-06 [shard_inline]: 1.224e-05 [merge_send_recv]: 1.26e-05 [auto_parallel]: 1.318e-05 [parallel]: 9.69e-06 [flash_sp]: 4.27998e-06 [merge_comm]: 6.98e-06 [allreduce_fusion]: 7.3e-06 [matmul_add_comm_reduction]: 1.397e-05 [allreduce_slice_to_reducescatter]: 6.50005e-07 [virtual_shard_identity]: 1.353e-05 [virtual_dataset]: 1.198e-05 [get_grad_eliminate_]: 1.165e-05 [virtual_output]: 1.22e-05 [merge_forward]: 7.00998e-06 [cell_reuse_recompute_pass]: 3.37002e-06 [offload_activation]: 1.453e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.064e-05 [merge_recompute_call_nodes]: 1.81e-06 [before_grad]: 1.774e-05 [set_forward_comm_id_for_comm_node_pass]: 6.83e-06 [meta_fg_expand]: 4.37e-06 [flash_sp_send_recv_attached]: 1.56002e-06 [receive_attached]: 2.79999e-06 [after_resolve]: 1.88e-05 [a_after_grad]: 1.721e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.85001e-06 [auto_monad_grad]: 1.81e-06 [auto_monad_eliminator]: 1.609e-05 [cse]: 4.293e-05 [a_3]: 7.352e-05 [py_interpret_to_execute_after_opt_a]: 2.668e-05 [slice_cell_reuse_recomputed_activation]: 2.71999e-06 [rewriter_after_opt_a]: 0.00033789 [convert_after_rewriter]: 3.19e-05 [order_py_execute_after_rewriter]: 9.30001e-06 [mutable_eliminate]: 0.00089114 [opt_b]: 0.000453, [1] [Cycle 1]: 0.00044278, [7] [b_1]: 0.00029973 [b_2]: 1.411e-05 [updatestate_depend_eliminate]: 1.305e-05 [updatestate_assign_eliminate]: 6.28998e-06 [updatestate_loads_eliminate]: 5.89999e-06 [renormalize]: 5.69999e-07 [cse]: 5.997e-05 [optimize_parallel_all_gather_comm]: 2.972e-05 [overlap_param_gather]: 1.87001e-06 [cconv]: 3.825e-05 [loop_unroll]: 0.00060203 [opt_after_cconv]: 0.00017342, [1] [Cycle 1]: 0.00016494, [7] [c_1]: 5.761e-05 [parameter_eliminate]: 4.75999e-06 [updatestate_depend_eliminate]: 9.53002e-06 [updatestate_assign_eliminate]: 5.48002e-06 [updatestate_loads_eliminate]: 5.18002e-06 [cse]: 4.538e-05 [renormalize]: 5.69999e-07 [remove_dup_value]: 7.568e-05 [tuple_transform]: 0.00015725, [1] [Cycle 1]: 0.00015156, [4] [d_1]: 0.00011358 [none_parameter_eliminate]: 2.19001e-06 [renormalize]: 4.19997e-07 [switch_simplify]: 1.276e-05 [partial_unused_args_eliminate]: 1.99e-06 [add_recomputation]: 0.00012449 [cse_after_recomputation]: 5.294e-05, [1] [Cycle 1]: 4.413e-05, [1] [cse]: 3.438e-05 [environ_conv]: 2.847e-05 [swap_dp_allreduce_reducescatter]: 1.095e-05 [bias_add_comm_swap]: 3.65998e-06 [label_micro_interleaved_index]: 6.22001e-06 [label_fine_grained_interleaved_index]: 2.67001e-06 [merge_cast_opt]: 1.50001e-06 [slice_recompute_activation]: 2.44001e-06 [micro_interleaved_order_control]: 3.33e-06 [assign_add_opt]: 1.44e-06 [ForceFp32Comm]: 1.56002e-06 [remove_cast_before_assign_add]: 1.18001e-06 [full_micro_interleaved_order_control]: 2.47001e-06 [reorder_send_recv_between_fp_bp]: 2.61e-06 [comm_op_add_attrs]: 1.25999e-06 [add_comm_op_reuse_tag]: 1.02998e-06 [interleave_split_concat_branches]: 1.22e-06 [interleave_parallel_branches]: 1.09998e-06 [overlap_opt_shard_in_pipeline]: 2.633e-05 [overlap_opt_shard_grad_in_pipeline]: 2.06998e-06 [control_data_broadcast_order]: 2.452e-05 [grouped_pairwise_exchange_alltoall]: 1.75001e-06 [offloading_packed_experts]: 7.37002e-06 [overlap_recompute_and_grad_model_parallel]: 7.02002e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.43002e-06 [overlap_recompute_allgather_and_fa_grad]: 1.42e-06 [overlap_recompute_comm]: 2.65997e-06 [overlap_grad_ring_attention]: 6.49999e-06 [overlap_grad_flash_sp]: 4.828e-05 [begin_end_overlap_inline]: 6.19999e-07 [split_matmul_comm_elemetwise]: 3.35e-06 [split_layernorm_comm]: 1.99e-06 [handle_group_info]: 1.19e-06 [symbol_engine_optimizer]: 0.00013729, [1] [Cycle 1]: 0.00013188, [6] [build]: 2.552e-05 [elim_shapecalc]: 2.103e-05 [elim_not_effective]: 2.26e-05 [opt_reshape]: 1.266e-05 [fold_const_symbol]: 1.72e-05 [renormalize]: 2.49973e-07 [detach_backward]: 2.70002e-06 [pipeline_parallel_scheduler]: 1.40001e-06 [auto_monad_reorder]: 3.695e-05 [get_jit_bprop_graph]: 2.16998e-06 [rewriter_after_jit_bprop_graph]: 5.81998e-06 [opt_after_jit_grad]: 0.206772 [validate]: 0.00010607 Sums bootstrap : 0.000991s : 0.22% type_inference : 0.239030s : 52.56% event_method : 0.000019s : 0.00% auto_monad : 0.000107s : 0.02% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000025s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000006s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000054s : 0.01% insert-virtual-dataset : 0.000008s : 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 : 0.000046s : 0.01% optimize.rewriter_before_opt_a : 0.000104s : 0.02% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000057s : 0.01% optimize.opt_a.loop_unroll : 0.000037s : 0.01% optimize.opt_a.a_1 : 0.001145s : 0.25% optimize.opt_a.with_stream_mark : 0.000046s : 0.01% optimize.opt_a.recompute_prepare : 0.000027s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000013s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000012s : 0.00% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000367s : 0.08% optimize.opt_a.accelerated_algorithm : 0.000045s : 0.01% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000006s : 0.00% optimize.opt_a.shard_inline : 0.000024s : 0.01% optimize.opt_a.merge_send_recv : 0.000045s : 0.01% optimize.opt_a.auto_parallel : 0.000024s : 0.01% optimize.opt_a.parallel : 0.000061s : 0.01% optimize.opt_a.flash_sp : 0.000025s : 0.01% optimize.opt_a.merge_comm : 0.000015s : 0.00% optimize.opt_a.allreduce_fusion : 0.000014s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000030s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000030s : 0.01% optimize.opt_a.virtual_dataset : 0.000024s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000024s : 0.01% optimize.opt_a.virtual_output : 0.000024s : 0.01% optimize.opt_a.merge_forward : 0.000014s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000030s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000042s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000036s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000015s : 0.00% optimize.opt_a.meta_fg_expand : 0.000009s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000015s : 0.00% optimize.opt_a.after_resolve : 0.000040s : 0.01% optimize.opt_a.a_after_grad : 0.000259s : 0.06% optimize.opt_a.renormalize : 0.001258s : 0.28% optimize.opt_a.add_forward_monad_depend : 0.000019s : 0.00% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000041s : 0.01% optimize.opt_a.cse : 0.000178s : 0.04% optimize.opt_a.a_3 : 0.000175s : 0.04% optimize.py_interpret_to_execute_after_opt_a : 0.000027s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000338s : 0.07% optimize.convert_after_rewriter : 0.000032s : 0.01% optimize.order_py_execute_after_rewriter : 0.000009s : 0.00% optimize.mutable_eliminate : 0.000891s : 0.20% optimize.opt_b.b_1 : 0.000300s : 0.07% optimize.opt_b.b_2 : 0.000014s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000013s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000060s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000030s : 0.01% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000038s : 0.01% optimize.loop_unroll : 0.000602s : 0.13% optimize.opt_after_cconv.c_1 : 0.000058s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.cse : 0.000045s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000076s : 0.02% optimize.tuple_transform.d_1 : 0.000114s : 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 : 0.000013s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000124s : 0.03% optimize.cse_after_recomputation.cse : 0.000034s : 0.01% optimize.environ_conv : 0.000028s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000011s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000002s : 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 : 0.000026s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000025s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000007s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000007s : 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 : 0.000006s : 0.00% optimize.overlap_grad_flash_sp : 0.000048s : 0.01% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000026s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000021s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000023s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000001s : 0.00% auto_monad_reorder : 0.000037s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.206772s : 45.47% validate : 0.000106s : 0.02% Time group info: ------[substitution.] 0.000405 106 0.75% : 0.000003s : 5: substitution.elim_not_effective 7.47% : 0.000030s : 6: substitution.float_tuple_getitem_switch 0.62% : 0.000003s : 5: substitution.fold_const_symbol 2.37% : 0.000010s : 9: substitution.graph_param_transform 44.64% : 0.000181s : 3: substitution.inline 1.64% : 0.000007s : 10: substitution.j_node_and_user_rematch 4.12% : 0.000017s : 2: substitution.less_batch_normalization 2.63% : 0.000011s : 4: substitution.minmaximum_grad 2.09% : 0.000008s : 10: substitution.remove_not_recompute_node 2.11% : 0.000009s : 8: substitution.replace_old_param 7.75% : 0.000031s : 8: substitution.tuple_list_convert_item_index_to_positive 3.20% : 0.000013s : 8: substitution.tuple_list_get_item_const_eliminator 4.45% : 0.000018s : 8: substitution.tuple_list_get_item_depend_reorder 11.65% : 0.000047s : 12: substitution.tuple_list_get_item_eliminator 4.51% : 0.000018s : 8: substitution.tuple_list_get_set_item_eliminator ------[type_inference.] 0.238924 2 99.62% : 0.238019s : 1: type_inference.infer 0.38% : 0.000905s : 1: type_inference.specialize ------[replace.] 0.000041 3 100.00% : 0.000041s : 3: replace.inline ------[match.] 0.000179 3 100.00% : 0.000179s : 3: match.inline ------[predicate.] 0.000448 2177 0.62% : 0.000003s : 20: predicate.accumulaten_eliminater 1.66% : 0.000007s : 9: predicate.ad_related_special_op_eliminate 0.53% : 0.000002s : 18: predicate.addn_check_dump 0.65% : 0.000003s : 20: predicate.addn_zero_filter 0.56% : 0.000003s : 20: predicate.adjust_all_reduce_mul_add 1.47% : 0.000007s : 38: predicate.arithmetic_simplify 0.58% : 0.000003s : 20: predicate.cast_eliminate 0.58% : 0.000003s : 18: predicate.check_bprop_eliminate 0.51% : 0.000002s : 18: predicate.compare_switch_simplify 0.17% : 0.000001s : 9: predicate.const_output_eliminate 0.55% : 0.000002s : 18: predicate.depend_value_elim 0.58% : 0.000003s : 20: predicate.dict_get_item_const_eliminator 0.69% : 0.000003s : 20: predicate.dict_get_item_eliminator 0.59% : 0.000003s : 20: predicate.dict_set_item_eliminator 1.38% : 0.000006s : 18: predicate.dumpgradient_eliminate 0.24% : 0.000001s : 9: predicate.elim_not_effective 0.45% : 0.000002s : 9: predicate.elim_shapecalc_of_broadcastargs 0.86% : 0.000004s : 29: predicate.environ_add_const_eliminate 0.76% : 0.000003s : 29: predicate.environ_get_add_eliminate 0.78% : 0.000003s : 29: predicate.environ_get_depend_swap 1.31% : 0.000006s : 47: predicate.environ_get_eliminate 0.80% : 0.000004s : 29: predicate.environ_get_set_eliminate 0.64% : 0.000003s : 23: predicate.exchange_switch_depend_value 1.19% : 0.000005s : 23: predicate.float_depend_g_call 0.54% : 0.000002s : 18: predicate.float_environ_get_switch 0.93% : 0.000004s : 27: predicate.float_tuple_getitem_switch 0.17% : 0.000001s : 9: predicate.fold_const_symbol 0.63% : 0.000003s : 18: predicate.get_grad_eliminate 0.17% : 0.000001s : 9: predicate.graph_param_transform 0.55% : 0.000002s : 18: predicate.incorporate_call 0.49% : 0.000002s : 18: predicate.incorporate_call_switch 4.04% : 0.000018s : 97: predicate.inline 1.46% : 0.000007s : 18: predicate.inline_without_move 0.32% : 0.000001s : 18: predicate.j_node_and_user_rematch 0.82% : 0.000004s : 18: predicate.less_batch_normalization 1.15% : 0.000005s : 38: predicate.list_to_tuple_eliminator_ 1.62% : 0.000007s : 58: predicate.load_eliminater 0.87% : 0.000004s : 9: predicate.loop_unroll_after_grad 1.06% : 0.000005s : 33: predicate.loop_unroll_before_grad 1.19% : 0.000005s : 38: predicate.make_slice_get_slice_eliminator 0.56% : 0.000002s : 18: predicate.merge_addn 0.54% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.61% : 0.000003s : 18: predicate.mini_step_allgather_replace 0.55% : 0.000002s : 20: predicate.minmaximum_grad 0.90% : 0.000004s : 9: predicate.mutable_eliminate 0.42% : 0.000002s : 9: predicate.opt_reshape 0.36% : 0.000002s : 9: predicate.parallel_virtual_node 0.81% : 0.000004s : 23: predicate.partial_defer_inline 0.83% : 0.000004s : 29: predicate.partial_eliminate 0.56% : 0.000002s : 20: predicate.print_const_string_wrapper 0.55% : 0.000002s : 18: predicate.reduce_all_const_elim 0.81% : 0.000004s : 20: predicate.reduce_eliminate 1.58% : 0.000007s : 58: predicate.redundant_stop_gradient_eliminater 0.32% : 0.000001s : 18: predicate.remove_not_recompute_node 0.91% : 0.000004s : 38: predicate.replace_applicator 0.40% : 0.000002s : 18: predicate.replace_old_param 0.23% : 0.000001s : 9: predicate.reset_defer_inline 0.56% : 0.000002s : 20: predicate.reshape_eliminate 0.60% : 0.000003s : 18: predicate.row_tensor_add_zeros_like 0.36% : 0.000002s : 9: predicate.row_tensor_eliminate 0.68% : 0.000003s : 18: predicate.same_eliminate 0.42% : 0.000002s : 18: predicate.set_cell_output_no_recompute 0.73% : 0.000003s : 18: predicate.shard_identity_eliminate 0.61% : 0.000003s : 18: predicate.special_op_eliminate 0.61% : 0.000003s : 18: predicate.specialize_transform 0.82% : 0.000004s : 18: predicate.split_environ_get_set_with_tuple_value 0.96% : 0.000004s : 18: predicate.stack_unstack_eliminate 0.28% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.69% : 0.000003s : 23: predicate.switch_defer_inline 27.36% : 0.000122s : 41: predicate.switch_layer_defer_inline 2.75% : 0.000012s : 83: predicate.switch_simplify 0.63% : 0.000003s : 20: predicate.tile_eliminate 0.57% : 0.000003s : 20: predicate.transpose_eliminate 1.28% : 0.000006s : 38: predicate.tuple_list_convert_item_index_to_positive 1.23% : 0.000006s : 38: predicate.tuple_list_get_item_const_eliminator 1.10% : 0.000005s : 38: predicate.tuple_list_get_item_depend_reorder 2.42% : 0.000011s : 56: predicate.tuple_list_get_item_eliminator 1.11% : 0.000005s : 38: predicate.tuple_list_get_set_item_eliminator 1.77% : 0.000008s : 56: predicate.tuple_list_set_item_eliminator 1.23% : 0.000006s : 38: predicate.tuple_to_list_eliminator_ 1.58% : 0.000007s : 58: predicate.updatestate_pure_node_eliminater 2.25% : 0.000010s : 76: predicate.updatestate_useless_node_eliminater 0.29% : 0.000001s : 9: predicate.value_based_eliminate 0.63% : 0.000003s : 18: predicate.virtual_dataset_eliminate 0.76% : 0.000003s : 18: predicate.virtual_output_eliminate 0.26% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.37% : 0.000002s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000895 10 60.15% : 0.000538s : 5: func_graph_cloner_run.FuncGraphClonerGraph 39.85% : 0.000356s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.931174 192 0.00% : 0.000004s : 1: ForceFp32Comm 24.82% : 0.231101s : 1: add_attr 24.82% : 0.231083s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000132s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.01% : 0.000113s : 1: auto_monad 0.00% : 0.000041s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.11% : 0.001039s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000028s : 1: control_data_broadcast_order 0.00% : 0.000039s : 1: convert_after_rewriter 0.01% : 0.000076s : 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 0.00% : 0.000025s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 0.00% : 0.000004s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000006s : 1: inline 0.00% : 0.000011s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000009s : 1: label_micro_interleaved_index 0.07% : 0.000615s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.10% : 0.000909s : 1: mutable_eliminate 0.00% : 0.000011s : 1: offloading_packed_experts 0.00% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.24% : 0.002255s : 78: opt.transform.opt_a 0.01% : 0.000056s : 1: opt.transform.opt_after_cconv 0.01% : 0.000075s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000283s : 28: opt.transform.opt_b 0.01% : 0.000124s : 2: opt.transform.opt_trans_graph 0.01% : 0.000068s : 4: opt.transform.symbol_engine_opt 0.53% : 0.004975s : 1: opt_a 0.02% : 0.000177s : 1: opt_after_cconv 22.21% : 0.206799s : 1: opt_after_jit_grad 0.05% : 0.000457s : 1: opt_b 0.95% : 0.008848s : 1: optimize 0.00% : 0.000033s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000013s : 1: order_py_execute_after_rewriter 0.01% : 0.000053s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000010s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000030s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000010s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000058s : 1: pre_auto_parallel 0.01% : 0.000050s : 1: py_interpret_to_execute 0.00% : 0.000031s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000081s : 1: remove_dup_value 0.07% : 0.000630s : 1: renormalize.infer 0.07% : 0.000615s : 1: renormalize.specialize 0.00% : 0.000005s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000409s : 1: rewriter_after_opt_a 0.01% : 0.000109s : 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% : 0.000007s : 1: split_matmul_comm_elemetwise 0.00% : 0.000014s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000140s : 1: symbol_engine_optimizer 0.02% : 0.000160s : 1: tuple_transform 25.67% : 0.239054s : 1: type_inference [SUCCESS] err_cnt = 0 / 18 . [hook] pytest_runtest_teardown:test_dequant_swiglu_quant_non_group_index[0-True] tests/st/ops/ascend/test_aclnn_ops/test_dequant_swiglu_quant.py::test_dequant_swiglu_quant_non_group_index[0-True],max_mem:60.0M [WARNING] ME(166930:281473228386096,MainProcess):2026-01-29-17:41:05.866.149 [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 = 0.137721, [21] [bootstrap]: 0.0009931 [type_inference]: 0.120852 [event_method]: 1.877e-05 [auto_monad]: 8.078e-05 [graph_reusing]: 6.61e-06 [inline]: 3.14001e-06 [add_attr]: 0.00497293, [1] [add_attr_with_inline]: 0.0049575, [1] [Cycle 1]: 8.063e-05, [2] [tag_attr]: 2.618e-05 [meta_addattr_fg_expand]: 5.47999e-06 [parallel-infer-symbol]: 3.98999e-06 [pre_auto_parallel]: 4.107e-05 [insert-virtual-dataset]: 2.73e-06 [parallel-infer-symbol-second]: 8.89995e-07 [dataset_repeat_opt]: 2.28998e-06 [pipeline_split]: 2.47001e-06 [optimize]: 0.00975908, [53] [py_interpret_to_execute]: 3.393e-05 [rewriter_before_opt_a]: 0.00010047 [opt_a]: 0.00591835, [2] [Cycle 1]: 0.00455654, [45] [expand_dump_flag]: 3.97998e-06 [switch_simplify]: 3.997e-05 [loop_unroll]: 2.567e-05 [a_1]: 0.00076361 [with_stream_mark]: 2.868e-05 [recompute_prepare]: 1.778e-05 [updatestate_depend_eliminate]: 8.34002e-06 [updatestate_assign_eliminate]: 6.96001e-06 [updatestate_loads_eliminate]: 6.93e-06 [parameter_eliminate]: 2.22001e-06 [a_2]: 0.00018856 [accelerated_algorithm]: 3.091e-05 [shard]: 2.59999e-06 [meta_shard_fg_expand]: 4.70999e-06 [shard_inline]: 1.186e-05 [merge_send_recv]: 1.435e-05 [auto_parallel]: 1.119e-05 [parallel]: 4.686e-05 [flash_sp]: 1.049e-05 [merge_comm]: 8.07998e-06 [allreduce_fusion]: 7.02002e-06 [matmul_add_comm_reduction]: 2.655e-05 [allreduce_slice_to_reducescatter]: 8.40024e-07 [virtual_shard_identity]: 3.043e-05 [virtual_dataset]: 1.88e-05 [get_grad_eliminate_]: 1.219e-05 [virtual_output]: 1.19e-05 [merge_forward]: 9.69999e-06 [cell_reuse_recompute_pass]: 2.41998e-06 [offload_activation]: 1.729e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.695e-05 [merge_recompute_call_nodes]: 2.81e-06 [before_grad]: 2.575e-05 [set_forward_comm_id_for_comm_node_pass]: 9.51e-06 [meta_fg_expand]: 7.3e-06 [flash_sp_send_recv_attached]: 7.18e-06 [receive_attached]: 3.05002e-06 [after_resolve]: 2.075e-05 [a_after_grad]: 1.92e-05 [renormalize]: 0.00123456 [add_forward_monad_depend]: 1.718e-05 [auto_monad_grad]: 2.64001e-06 [auto_monad_eliminator]: 3.841e-05 [cse]: 6.43e-05 [a_3]: 9.413e-05 [Cycle 2]: 0.0013472, [45] [expand_dump_flag]: 1.78002e-06 [switch_simplify]: 1.409e-05 [loop_unroll]: 1.157e-05 [a_1]: 0.00033658 [with_stream_mark]: 1.85e-05 [recompute_prepare]: 1.311e-05 [updatestate_depend_eliminate]: 6.81001e-06 [updatestate_assign_eliminate]: 5.94e-06 [updatestate_loads_eliminate]: 5.94e-06 [parameter_eliminate]: 2.14e-06 [a_2]: 0.00016692 [accelerated_algorithm]: 2.104e-05 [shard]: 2.42001e-06 [meta_shard_fg_expand]: 2.71999e-06 [shard_inline]: 1.182e-05 [merge_send_recv]: 1.036e-05 [auto_parallel]: 1.363e-05 [parallel]: 1e-05 [flash_sp]: 4.65001e-06 [merge_comm]: 7.05998e-06 [allreduce_fusion]: 6.83998e-06 [matmul_add_comm_reduction]: 1.416e-05 [allreduce_slice_to_reducescatter]: 6.49976e-07 [virtual_shard_identity]: 1.307e-05 [virtual_dataset]: 1.237e-05 [get_grad_eliminate_]: 1.217e-05 [virtual_output]: 1.136e-05 [merge_forward]: 6.74999e-06 [cell_reuse_recompute_pass]: 2.88e-06 [offload_activation]: 2.523e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.344e-05 [merge_recompute_call_nodes]: 1.35001e-06 [before_grad]: 1.865e-05 [set_forward_comm_id_for_comm_node_pass]: 7.51001e-06 [meta_fg_expand]: 4.63001e-06 [flash_sp_send_recv_attached]: 1.58002e-06 [receive_attached]: 2.82002e-06 [after_resolve]: 2.186e-05 [a_after_grad]: 1.826e-05 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 3.26999e-06 [auto_monad_grad]: 1.72001e-06 [auto_monad_eliminator]: 1.888e-05 [cse]: 6.038e-05 [a_3]: 7.802e-05 [py_interpret_to_execute_after_opt_a]: 2.974e-05 [slice_cell_reuse_recomputed_activation]: 2.49001e-06 [rewriter_after_opt_a]: 0.00033577 [convert_after_rewriter]: 1.773e-05 [order_py_execute_after_rewriter]: 8.78001e-06 [mutable_eliminate]: 0.00090962 [opt_b]: 0.00050388, [1] [Cycle 1]: 0.00049306, [7] [b_1]: 0.00031171 [b_2]: 1.394e-05 [updatestate_depend_eliminate]: 1.404e-05 [updatestate_assign_eliminate]: 5.93002e-06 [updatestate_loads_eliminate]: 6.14001e-06 [renormalize]: 1.04e-06 [cse]: 7.952e-05 [optimize_parallel_all_gather_comm]: 3.029e-05 [overlap_param_gather]: 3.86001e-06 [cconv]: 4.028e-05 [loop_unroll]: 0.00060616 [opt_after_cconv]: 0.00020098, [1] [Cycle 1]: 0.00019163, [7] [c_1]: 5.81e-05 [parameter_eliminate]: 5.82999e-06 [updatestate_depend_eliminate]: 1.182e-05 [updatestate_assign_eliminate]: 5.91e-06 [updatestate_loads_eliminate]: 5.78997e-06 [cse]: 6.091e-05 [renormalize]: 3.49974e-07 [remove_dup_value]: 9.064e-05 [tuple_transform]: 0.00016883, [1] [Cycle 1]: 0.00016253, [4] [d_1]: 0.00012442 [none_parameter_eliminate]: 2.25002e-06 [renormalize]: 2.49973e-07 [switch_simplify]: 1.295e-05 [partial_unused_args_eliminate]: 1.91e-06 [add_recomputation]: 0.00010611 [cse_after_recomputation]: 4.49e-05, [1] [Cycle 1]: 3.832e-05, [1] [cse]: 3.123e-05 [environ_conv]: 1.829e-05 [swap_dp_allreduce_reducescatter]: 9.51e-06 [bias_add_comm_swap]: 3.85e-06 [label_micro_interleaved_index]: 6.33998e-06 [label_fine_grained_interleaved_index]: 2.80002e-06 [merge_cast_opt]: 1.44e-06 [slice_recompute_activation]: 2.69001e-06 [micro_interleaved_order_control]: 2.98e-06 [assign_add_opt]: 1.34e-06 [ForceFp32Comm]: 1.10999e-06 [remove_cast_before_assign_add]: 1.15999e-06 [full_micro_interleaved_order_control]: 2.86e-06 [reorder_send_recv_between_fp_bp]: 2.89999e-06 [comm_op_add_attrs]: 1.21002e-06 [add_comm_op_reuse_tag]: 1.25999e-06 [interleave_split_concat_branches]: 1.39e-06 [interleave_parallel_branches]: 1.20999e-06 [overlap_opt_shard_in_pipeline]: 3.74002e-06 [overlap_opt_shard_grad_in_pipeline]: 1.74998e-06 [control_data_broadcast_order]: 2.294e-05 [grouped_pairwise_exchange_alltoall]: 2.02999e-06 [offloading_packed_experts]: 7.51999e-06 [overlap_recompute_and_grad_model_parallel]: 6.41e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.71e-06 [overlap_recompute_allgather_and_fa_grad]: 1.52999e-06 [overlap_recompute_comm]: 3.17002e-06 [overlap_grad_ring_attention]: 6.57002e-06 [overlap_grad_flash_sp]: 3.259e-05 [begin_end_overlap_inline]: 5.59987e-07 [split_matmul_comm_elemetwise]: 2.81e-06 [split_layernorm_comm]: 2.21e-06 [handle_group_info]: 1.18001e-06 [symbol_engine_optimizer]: 0.00012248, [1] [Cycle 1]: 0.00011687, [6] [build]: 1.403e-05 [elim_shapecalc]: 1.78e-05 [elim_not_effective]: 2.078e-05 [opt_reshape]: 1.224e-05 [fold_const_symbol]: 1.681e-05 [renormalize]: 2.69996e-07 [detach_backward]: 2.78e-06 [pipeline_parallel_scheduler]: 1.92999e-06 [auto_monad_reorder]: 3.313e-05 [get_jit_bprop_graph]: 2.34999e-06 [rewriter_after_jit_bprop_graph]: 6.47001e-06 [opt_after_jit_grad]: 0.00063726 [validate]: 7.982e-05 Sums bootstrap : 0.000993s : 0.76% type_inference : 0.120852s : 92.90% event_method : 0.000019s : 0.01% auto_monad : 0.000081s : 0.06% graph_reusing : 0.000007s : 0.01% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000026s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000041s : 0.03% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000034s : 0.03% optimize.rewriter_before_opt_a : 0.000100s : 0.08% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000054s : 0.04% optimize.opt_a.loop_unroll : 0.000037s : 0.03% optimize.opt_a.a_1 : 0.001100s : 0.85% optimize.opt_a.with_stream_mark : 0.000047s : 0.04% optimize.opt_a.recompute_prepare : 0.000031s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000015s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000013s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000013s : 0.01% optimize.opt_a.parameter_eliminate : 0.000004s : 0.00% optimize.opt_a.a_2 : 0.000355s : 0.27% optimize.opt_a.accelerated_algorithm : 0.000052s : 0.04% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000007s : 0.01% optimize.opt_a.shard_inline : 0.000024s : 0.02% optimize.opt_a.merge_send_recv : 0.000025s : 0.02% optimize.opt_a.auto_parallel : 0.000025s : 0.02% optimize.opt_a.parallel : 0.000057s : 0.04% optimize.opt_a.flash_sp : 0.000015s : 0.01% optimize.opt_a.merge_comm : 0.000015s : 0.01% optimize.opt_a.allreduce_fusion : 0.000014s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000041s : 0.03% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000044s : 0.03% optimize.opt_a.virtual_dataset : 0.000031s : 0.02% optimize.opt_a.get_grad_eliminate_ : 0.000024s : 0.02% optimize.opt_a.virtual_output : 0.000023s : 0.02% optimize.opt_a.merge_forward : 0.000016s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000043s : 0.03% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000050s : 0.04% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000044s : 0.03% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000017s : 0.01% optimize.opt_a.meta_fg_expand : 0.000012s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000009s : 0.01% optimize.opt_a.receive_attached : 0.000006s : 0.00% optimize.opt_a.after_resolve : 0.000043s : 0.03% optimize.opt_a.a_after_grad : 0.000037s : 0.03% optimize.opt_a.renormalize : 0.001235s : 0.95% optimize.opt_a.add_forward_monad_depend : 0.000020s : 0.02% optimize.opt_a.auto_monad_grad : 0.000004s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000057s : 0.04% optimize.opt_a.cse : 0.000125s : 0.10% optimize.opt_a.a_3 : 0.000172s : 0.13% optimize.py_interpret_to_execute_after_opt_a : 0.000030s : 0.02% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000336s : 0.26% optimize.convert_after_rewriter : 0.000018s : 0.01% optimize.order_py_execute_after_rewriter : 0.000009s : 0.01% optimize.mutable_eliminate : 0.000910s : 0.70% optimize.opt_b.b_1 : 0.000312s : 0.24% optimize.opt_b.b_2 : 0.000014s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000014s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000080s : 0.06% optimize.optimize_parallel_all_gather_comm : 0.000030s : 0.02% optimize.overlap_param_gather : 0.000004s : 0.00% optimize.cconv : 0.000040s : 0.03% optimize.loop_unroll : 0.000606s : 0.47% optimize.opt_after_cconv.c_1 : 0.000058s : 0.04% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.cse : 0.000061s : 0.05% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000091s : 0.07% optimize.tuple_transform.d_1 : 0.000124s : 0.10% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000013s : 0.01% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000106s : 0.08% optimize.cse_after_recomputation.cse : 0.000031s : 0.02% optimize.environ_conv : 0.000018s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000010s : 0.01% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000003s : 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 : 0.000004s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000023s : 0.02% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000008s : 0.01% optimize.overlap_recompute_and_grad_model_parallel : 0.000006s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000002s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000007s : 0.01% optimize.overlap_grad_flash_sp : 0.000033s : 0.03% 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 : 0.000014s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000018s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.02% optimize.symbol_engine_optimizer.opt_reshape : 0.000012s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.01% 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 : 0.000033s : 0.03% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000637s : 0.49% validate : 0.000080s : 0.06% Time group info: ------[substitution.] 0.000434 106 0.69% : 0.000003s : 5: substitution.elim_not_effective 4.21% : 0.000018s : 6: substitution.float_tuple_getitem_switch 0.47% : 0.000002s : 5: substitution.fold_const_symbol 2.18% : 0.000009s : 9: substitution.graph_param_transform 49.72% : 0.000216s : 3: substitution.inline 1.43% : 0.000006s : 10: substitution.j_node_and_user_rematch 3.81% : 0.000017s : 2: substitution.less_batch_normalization 2.04% : 0.000009s : 4: substitution.minmaximum_grad 2.12% : 0.000009s : 10: substitution.remove_not_recompute_node 2.07% : 0.000009s : 8: substitution.replace_old_param 7.36% : 0.000032s : 8: substitution.tuple_list_convert_item_index_to_positive 2.95% : 0.000013s : 8: substitution.tuple_list_get_item_const_eliminator 4.55% : 0.000020s : 8: substitution.tuple_list_get_item_depend_reorder 11.99% : 0.000052s : 12: substitution.tuple_list_get_item_eliminator 4.41% : 0.000019s : 8: substitution.tuple_list_get_set_item_eliminator ------[type_inference.] 0.120732 2 98.70% : 0.119165s : 1: type_inference.infer 1.30% : 0.001567s : 1: type_inference.specialize ------[replace.] 0.000043 3 100.00% : 0.000043s : 3: replace.inline ------[match.] 0.000213 3 100.00% : 0.000213s : 3: match.inline ------[predicate.] 0.000326 2177 0.75% : 0.000002s : 20: predicate.accumulaten_eliminater 0.87% : 0.000003s : 9: predicate.ad_related_special_op_eliminate 0.73% : 0.000002s : 18: predicate.addn_check_dump 0.76% : 0.000002s : 20: predicate.addn_zero_filter 0.70% : 0.000002s : 20: predicate.adjust_all_reduce_mul_add 1.97% : 0.000006s : 38: predicate.arithmetic_simplify 0.79% : 0.000003s : 20: predicate.cast_eliminate 0.75% : 0.000002s : 18: predicate.check_bprop_eliminate 0.73% : 0.000002s : 18: predicate.compare_switch_simplify 0.25% : 0.000001s : 9: predicate.const_output_eliminate 0.79% : 0.000003s : 18: predicate.depend_value_elim 0.91% : 0.000003s : 20: predicate.dict_get_item_const_eliminator 0.88% : 0.000003s : 20: predicate.dict_get_item_eliminator 0.83% : 0.000003s : 20: predicate.dict_set_item_eliminator 1.23% : 0.000004s : 18: predicate.dumpgradient_eliminate 0.24% : 0.000001s : 9: predicate.elim_not_effective 0.65% : 0.000002s : 9: predicate.elim_shapecalc_of_broadcastargs 1.17% : 0.000004s : 29: predicate.environ_add_const_eliminate 1.08% : 0.000004s : 29: predicate.environ_get_add_eliminate 1.09% : 0.000004s : 29: predicate.environ_get_depend_swap 2.05% : 0.000007s : 47: predicate.environ_get_eliminate 1.15% : 0.000004s : 29: predicate.environ_get_set_eliminate 0.86% : 0.000003s : 23: predicate.exchange_switch_depend_value 1.43% : 0.000005s : 23: predicate.float_depend_g_call 0.73% : 0.000002s : 18: predicate.float_environ_get_switch 1.18% : 0.000004s : 27: predicate.float_tuple_getitem_switch 0.23% : 0.000001s : 9: predicate.fold_const_symbol 1.02% : 0.000003s : 18: predicate.get_grad_eliminate 0.25% : 0.000001s : 9: predicate.graph_param_transform 0.77% : 0.000003s : 18: predicate.incorporate_call 0.66% : 0.000002s : 18: predicate.incorporate_call_switch 5.49% : 0.000018s : 97: predicate.inline 1.16% : 0.000004s : 18: predicate.inline_without_move 0.43% : 0.000001s : 18: predicate.j_node_and_user_rematch 1.20% : 0.000004s : 18: predicate.less_batch_normalization 1.73% : 0.000006s : 38: predicate.list_to_tuple_eliminator_ 2.14% : 0.000007s : 58: predicate.load_eliminater 1.20% : 0.000004s : 9: predicate.loop_unroll_after_grad 1.47% : 0.000005s : 33: predicate.loop_unroll_before_grad 1.85% : 0.000006s : 38: predicate.make_slice_get_slice_eliminator 0.81% : 0.000003s : 18: predicate.merge_addn 0.78% : 0.000003s : 18: predicate.micro_step_allgather_replace 0.77% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.79% : 0.000003s : 20: predicate.minmaximum_grad 1.55% : 0.000005s : 9: predicate.mutable_eliminate 0.48% : 0.000002s : 9: predicate.opt_reshape 0.51% : 0.000002s : 9: predicate.parallel_virtual_node 1.16% : 0.000004s : 23: predicate.partial_defer_inline 1.16% : 0.000004s : 29: predicate.partial_eliminate 0.72% : 0.000002s : 20: predicate.print_const_string_wrapper 0.73% : 0.000002s : 18: predicate.reduce_all_const_elim 1.16% : 0.000004s : 20: predicate.reduce_eliminate 2.11% : 0.000007s : 58: predicate.redundant_stop_gradient_eliminater 0.47% : 0.000002s : 18: predicate.remove_not_recompute_node 1.12% : 0.000004s : 38: predicate.replace_applicator 0.59% : 0.000002s : 18: predicate.replace_old_param 0.25% : 0.000001s : 9: predicate.reset_defer_inline 0.89% : 0.000003s : 20: predicate.reshape_eliminate 0.80% : 0.000003s : 18: predicate.row_tensor_add_zeros_like 0.48% : 0.000002s : 9: predicate.row_tensor_eliminate 1.08% : 0.000004s : 18: predicate.same_eliminate 0.55% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.23% : 0.000004s : 18: predicate.shard_identity_eliminate 0.88% : 0.000003s : 18: predicate.special_op_eliminate 0.82% : 0.000003s : 18: predicate.specialize_transform 1.27% : 0.000004s : 18: predicate.split_environ_get_set_with_tuple_value 1.15% : 0.000004s : 18: predicate.stack_unstack_eliminate 0.37% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.97% : 0.000003s : 23: predicate.switch_defer_inline 1.67% : 0.000005s : 41: predicate.switch_layer_defer_inline 3.85% : 0.000013s : 83: predicate.switch_simplify 0.81% : 0.000003s : 20: predicate.tile_eliminate 0.82% : 0.000003s : 20: predicate.transpose_eliminate 1.71% : 0.000006s : 38: predicate.tuple_list_convert_item_index_to_positive 1.83% : 0.000006s : 38: predicate.tuple_list_get_item_const_eliminator 1.63% : 0.000005s : 38: predicate.tuple_list_get_item_depend_reorder 3.79% : 0.000012s : 56: predicate.tuple_list_get_item_eliminator 1.95% : 0.000006s : 38: predicate.tuple_list_get_set_item_eliminator 2.46% : 0.000008s : 56: predicate.tuple_list_set_item_eliminator 1.61% : 0.000005s : 38: predicate.tuple_to_list_eliminator_ 2.09% : 0.000007s : 58: predicate.updatestate_pure_node_eliminater 3.04% : 0.000010s : 76: predicate.updatestate_useless_node_eliminater 0.39% : 0.000001s : 9: predicate.value_based_eliminate 0.93% : 0.000003s : 18: predicate.virtual_dataset_eliminate 0.82% : 0.000003s : 18: predicate.virtual_output_eliminate 0.33% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.47% : 0.000002s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001691 10 60.92% : 0.001030s : 5: func_graph_cloner_run.FuncGraphClonerGraph 39.08% : 0.000661s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.156158 192 0.00% : 0.000004s : 1: ForceFp32Comm 3.19% : 0.004980s : 1: add_attr 3.18% : 0.004962s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.07% : 0.000113s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.06% : 0.000086s : 1: auto_monad 0.03% : 0.000039s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.67% : 0.001047s : 1: bootstrap 0.03% : 0.000045s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.02% : 0.000027s : 1: control_data_broadcast_order 0.02% : 0.000025s : 1: convert_after_rewriter 0.03% : 0.000049s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.01% : 0.000022s : 1: environ_conv 0.02% : 0.000027s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.01% : 0.000011s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.01% : 0.000010s : 1: label_micro_interleaved_index 0.40% : 0.000622s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.60% : 0.000931s : 1: mutable_eliminate 0.01% : 0.000011s : 1: offloading_packed_experts 0.02% : 0.000028s : 1: opt.transform.loop_unroll_optimizer 0.02% : 0.000034s : 1: opt.transform.mutable_eliminate 1.29% : 0.002019s : 78: opt.transform.opt_a 0.04% : 0.000057s : 1: opt.transform.opt_after_cconv 0.03% : 0.000048s : 1: opt.transform.opt_after_jit_grad 0.19% : 0.000292s : 28: opt.transform.opt_b 0.09% : 0.000135s : 2: opt.transform.opt_trans_graph 0.04% : 0.000064s : 4: opt.transform.symbol_engine_opt 3.79% : 0.005924s : 1: opt_a 0.13% : 0.000206s : 1: opt_after_cconv 0.42% : 0.000654s : 1: opt_after_jit_grad 0.33% : 0.000509s : 1: opt_b 6.25% : 0.009766s : 1: optimize 0.02% : 0.000036s : 1: optimize_parallel_all_gather_comm 0.01% : 0.000013s : 1: order_py_execute_after_rewriter 0.02% : 0.000037s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000015s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000008s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000010s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.01% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.03% : 0.000046s : 1: pre_auto_parallel 0.03% : 0.000039s : 1: py_interpret_to_execute 0.02% : 0.000035s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.06% : 0.000096s : 1: remove_dup_value 0.36% : 0.000559s : 1: renormalize.infer 0.43% : 0.000665s : 1: renormalize.specialize 0.01% : 0.000009s : 1: reorder_send_recv_between_fp_bp 0.01% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.22% : 0.000350s : 1: rewriter_after_opt_a 0.07% : 0.000106s : 1: rewriter_before_opt_a 0.01% : 0.000012s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.01% : 0.000013s : 1: swap_dp_allreduce_reducescatter 0.08% : 0.000131s : 1: symbol_engine_optimizer 0.11% : 0.000172s : 1: tuple_transform 77.41% : 0.120876s : 1: type_inference [SUCCESS] err_cnt = 0 / 18 . [hook] pytest_runtest_teardown:test_dequant_swiglu_quant_non_group_index[0-False] tests/st/ops/ascend/test_aclnn_ops/test_dequant_swiglu_quant.py::test_dequant_swiglu_quant_non_group_index[0-False],max_mem:60.0M [WARNING] ME(166930:281473228386096,MainProcess):2026-01-29-17:41:22.873.986 [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. [SUCCESS] err_cnt = 0 / 18 . [hook] pytest_runtest_teardown:test_dequant_swiglu_quant_non_group_index[1-True] tests/st/ops/ascend/test_aclnn_ops/test_dequant_swiglu_quant.py::test_dequant_swiglu_quant_non_group_index[1-True],max_mem:60.0M [WARNING] ME(166930:281473228386096,MainProcess):2026-01-29-17:41:26.782.179 [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. [SUCCESS] err_cnt = 0 / 18 . [hook] pytest_runtest_teardown:test_dequant_swiglu_quant_non_group_index[1-False] tests/st/ops/ascend/test_aclnn_ops/test_dequant_swiglu_quant.py::test_dequant_swiglu_quant_non_group_index[1-False],max_mem:58.0M =============================== 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") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 4 passed, 25 warnings in 277.74s (0:04:37) ==================