==================================================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_008/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_asd_paged_attention.py [WARNING] ME(170484:281473336930096,MainProcess):2026-01-29-17:41:40.465.870 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 2.19463, [21] [bootstrap]: 0.00089979 [type_inference]: 0.883118 [event_method]: 1.752e-05 [auto_monad]: 0.00011084 [graph_reusing]: 5.91e-06 [inline]: 7.08e-06 [add_attr]: 0.00936796, [1] [add_attr_with_inline]: 0.00935254, [1] [Cycle 1]: 9.392e-05, [2] [tag_attr]: 2.123e-05 [meta_addattr_fg_expand]: 4.24002e-06 [parallel-infer-symbol]: 5.56e-06 [pre_auto_parallel]: 4.841e-05 [insert-virtual-dataset]: 3.41999e-06 [parallel-infer-symbol-second]: 8.30012e-07 [dataset_repeat_opt]: 1.89e-06 [pipeline_split]: 2.00002e-06 [optimize]: 1.30021, [53] [py_interpret_to_execute]: 2.555e-05 [rewriter_before_opt_a]: 7.787e-05 [opt_a]: 1.29729, [2] [Cycle 1]: 0.00211632, [45] [expand_dump_flag]: 2.74999e-06 [switch_simplify]: 3.267e-05 [loop_unroll]: 1.889e-05 [a_1]: 0.00042961 [with_stream_mark]: 2.039e-05 [recompute_prepare]: 1.166e-05 [updatestate_depend_eliminate]: 5.82001e-06 [updatestate_assign_eliminate]: 4.77e-06 [updatestate_loads_eliminate]: 4.75999e-06 [parameter_eliminate]: 1.94e-06 [a_2]: 0.00014131 [accelerated_algorithm]: 1.036e-05 [shard]: 2.55002e-06 [meta_shard_fg_expand]: 2.11e-06 [shard_inline]: 1.028e-05 [merge_send_recv]: 1.022e-05 [auto_parallel]: 7.8e-06 [parallel]: 6.752e-05 [flash_sp]: 1.949e-05 [merge_comm]: 6.02001e-06 [allreduce_fusion]: 4.81002e-06 [matmul_add_comm_reduction]: 1.161e-05 [allreduce_slice_to_reducescatter]: 6.10016e-07 [virtual_shard_identity]: 1.263e-05 [virtual_dataset]: 1.04e-05 [get_grad_eliminate_]: 9.62001e-06 [virtual_output]: 1.222e-05 [merge_forward]: 6.19001e-06 [cell_reuse_recompute_pass]: 1.56002e-06 [offload_activation]: 1.185e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.787e-05 [merge_recompute_call_nodes]: 1.64e-06 [before_grad]: 1.491e-05 [set_forward_comm_id_for_comm_node_pass]: 5.34998e-06 [meta_fg_expand]: 3.64002e-06 [flash_sp_send_recv_attached]: 2.73998e-06 [receive_attached]: 1.103e-05 [after_resolve]: 2.073e-05 [a_after_grad]: 1.652e-05 [renormalize]: 0.00071279 [add_forward_monad_depend]: 6.71e-06 [auto_monad_grad]: 3.01001e-06 [auto_monad_eliminator]: 1.605e-05 [cse]: 8.997e-05 [a_3]: 7.356e-05 [Cycle 2]: 1.29516, [45] [expand_dump_flag]: 9.79984e-07 [switch_simplify]: 1.24e-05 [loop_unroll]: 1.002e-05 [a_1]: 0.00025027 [with_stream_mark]: 1.323e-05 [recompute_prepare]: 9.92999e-06 [updatestate_depend_eliminate]: 4.94e-06 [updatestate_assign_eliminate]: 3.97e-06 [updatestate_loads_eliminate]: 4.13001e-06 [parameter_eliminate]: 9.70002e-07 [a_2]: 0.00012661 [accelerated_algorithm]: 9.75002e-06 [shard]: 1.32e-06 [meta_shard_fg_expand]: 1.64e-06 [shard_inline]: 9.84999e-06 [merge_send_recv]: 6.51999e-06 [auto_parallel]: 7.18998e-06 [parallel]: 4.24002e-06 [flash_sp]: 3.4e-06 [merge_comm]: 4.60001e-06 [allreduce_fusion]: 4.32e-06 [matmul_add_comm_reduction]: 6.84999e-06 [allreduce_slice_to_reducescatter]: 3.09985e-07 [virtual_shard_identity]: 1.115e-05 [virtual_dataset]: 9.69e-06 [get_grad_eliminate_]: 9.50001e-06 [virtual_output]: 9.79e-06 [merge_forward]: 4.38999e-06 [cell_reuse_recompute_pass]: 1.52001e-06 [offload_activation]: 7.94002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.578e-05 [merge_recompute_call_nodes]: 8.59989e-07 [before_grad]: 1.286e-05 [set_forward_comm_id_for_comm_node_pass]: 4.87998e-06 [meta_fg_expand]: 3.70003e-06 [flash_sp_send_recv_attached]: 8.50006e-07 [receive_attached]: 1.00001e-06 [after_resolve]: 1.923e-05 [a_after_grad]: 1.549e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.67999e-06 [auto_monad_grad]: 8.59989e-07 [auto_monad_eliminator]: 8.00999e-06 [cse]: 1.29416 [a_3]: 0.00010732 [py_interpret_to_execute_after_opt_a]: 3.052e-05 [slice_cell_reuse_recomputed_activation]: 3.94002e-06 [rewriter_after_opt_a]: 0.00011278 [convert_after_rewriter]: 1.135e-05 [order_py_execute_after_rewriter]: 7.70998e-06 [mutable_eliminate]: 0.00072517 [opt_b]: 0.00033596, [1] [Cycle 1]: 0.00032605, [7] [b_1]: 0.00021616 [b_2]: 1.279e-05 [updatestate_depend_eliminate]: 9.07001e-06 [updatestate_assign_eliminate]: 5.12e-06 [updatestate_loads_eliminate]: 5.00001e-06 [renormalize]: 8.00006e-07 [cse]: 4.177e-05 [optimize_parallel_all_gather_comm]: 2.415e-05 [overlap_param_gather]: 5.85002e-06 [cconv]: 3.735e-05 [loop_unroll]: 0.00045612 [opt_after_cconv]: 0.00015274, [1] [Cycle 1]: 0.00014584, [7] [c_1]: 5.53e-05 [parameter_eliminate]: 3.63e-06 [updatestate_depend_eliminate]: 7.85998e-06 [updatestate_assign_eliminate]: 4.11001e-06 [updatestate_loads_eliminate]: 3.93001e-06 [cse]: 3.453e-05 [renormalize]: 5.50004e-07 [remove_dup_value]: 7.043e-05 [tuple_transform]: 0.00011715, [1] [Cycle 1]: 0.00011168, [4] [d_1]: 7.895e-05 [none_parameter_eliminate]: 1.67999e-06 [renormalize]: 2.00002e-07 [switch_simplify]: 1.132e-05 [partial_unused_args_eliminate]: 1.87999e-06 [add_recomputation]: 6.797e-05 [cse_after_recomputation]: 3.471e-05, [1] [Cycle 1]: 2.9e-05, [1] [cse]: 2.344e-05 [environ_conv]: 2.139e-05 [swap_dp_allreduce_reducescatter]: 7.51001e-06 [bias_add_comm_swap]: 2.99999e-06 [label_micro_interleaved_index]: 5.10001e-06 [label_fine_grained_interleaved_index]: 3.50998e-06 [merge_cast_opt]: 1.45999e-06 [slice_recompute_activation]: 2.14999e-06 [micro_interleaved_order_control]: 2.58e-06 [assign_add_opt]: 1.26002e-06 [ForceFp32Comm]: 9.20001e-07 [remove_cast_before_assign_add]: 1.43002e-06 [full_micro_interleaved_order_control]: 2.16e-06 [reorder_send_recv_between_fp_bp]: 3.28998e-06 [comm_op_add_attrs]: 1.82001e-06 [add_comm_op_reuse_tag]: 1.19e-06 [interleave_split_concat_branches]: 1.25999e-06 [interleave_parallel_branches]: 1.13001e-06 [overlap_opt_shard_in_pipeline]: 2.456e-05 [overlap_opt_shard_grad_in_pipeline]: 1.91e-06 [control_data_broadcast_order]: 1.75e-05 [grouped_pairwise_exchange_alltoall]: 1.98002e-06 [offloading_packed_experts]: 5.00999e-06 [overlap_recompute_and_grad_model_parallel]: 6.49001e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.62999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.45001e-06 [overlap_recompute_comm]: 2.30002e-06 [overlap_grad_ring_attention]: 5.90002e-06 [overlap_grad_flash_sp]: 4.168e-05 [begin_end_overlap_inline]: 5.50004e-07 [split_matmul_comm_elemetwise]: 2.56e-06 [split_layernorm_comm]: 2.09e-06 [handle_group_info]: 1.52999e-06 [symbol_engine_optimizer]: 0.00020607, [1] [Cycle 1]: 0.00020094, [6] [build]: 9.389e-05 [elim_shapecalc]: 1.679e-05 [elim_not_effective]: 2.527e-05 [opt_reshape]: 1.129e-05 [fold_const_symbol]: 2.197e-05 [renormalize]: 2.89991e-07 [detach_backward]: 2.46998e-06 [pipeline_parallel_scheduler]: 1.42e-06 [auto_monad_reorder]: 2.983e-05 [get_jit_bprop_graph]: 1.98002e-06 [rewriter_after_jit_bprop_graph]: 3.95e-06 [opt_after_jit_grad]: 0.00051505 [validate]: 7.151e-05 Sums bootstrap : 0.000900s : 0.04% type_inference : 0.883118s : 40.43% event_method : 0.000018s : 0.00% auto_monad : 0.000111s : 0.01% graph_reusing : 0.000006s : 0.00% inline : 0.000007s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000021s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.00% parallel-infer-symbol : 0.000006s : 0.00% pre_auto_parallel : 0.000048s : 0.00% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000026s : 0.00% optimize.rewriter_before_opt_a : 0.000078s : 0.00% optimize.opt_a.expand_dump_flag : 0.000004s : 0.00% optimize.opt_a.switch_simplify : 0.000045s : 0.00% optimize.opt_a.loop_unroll : 0.000029s : 0.00% optimize.opt_a.a_1 : 0.000680s : 0.03% optimize.opt_a.with_stream_mark : 0.000034s : 0.00% optimize.opt_a.recompute_prepare : 0.000022s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000011s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000009s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% optimize.opt_a.parameter_eliminate : 0.000003s : 0.00% optimize.opt_a.a_2 : 0.000268s : 0.01% optimize.opt_a.accelerated_algorithm : 0.000020s : 0.00% optimize.opt_a.shard : 0.000004s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000004s : 0.00% optimize.opt_a.shard_inline : 0.000020s : 0.00% optimize.opt_a.merge_send_recv : 0.000017s : 0.00% optimize.opt_a.auto_parallel : 0.000015s : 0.00% optimize.opt_a.parallel : 0.000072s : 0.00% optimize.opt_a.flash_sp : 0.000023s : 0.00% optimize.opt_a.merge_comm : 0.000011s : 0.00% optimize.opt_a.allreduce_fusion : 0.000009s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000018s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000024s : 0.00% optimize.opt_a.virtual_dataset : 0.000020s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000019s : 0.00% optimize.opt_a.virtual_output : 0.000022s : 0.00% optimize.opt_a.merge_forward : 0.000011s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% optimize.opt_a.offload_activation : 0.000020s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000034s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000002s : 0.00% optimize.opt_a.before_grad : 0.000028s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000010s : 0.00% optimize.opt_a.meta_fg_expand : 0.000007s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000004s : 0.00% optimize.opt_a.receive_attached : 0.000012s : 0.00% optimize.opt_a.after_resolve : 0.000040s : 0.00% optimize.opt_a.a_after_grad : 0.000032s : 0.00% optimize.opt_a.renormalize : 0.000713s : 0.03% optimize.opt_a.add_forward_monad_depend : 0.000008s : 0.00% optimize.opt_a.auto_monad_grad : 0.000004s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000024s : 0.00% optimize.opt_a.cse : 1.294248s : 59.26% optimize.opt_a.a_3 : 0.000181s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000031s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000004s : 0.00% optimize.rewriter_after_opt_a : 0.000113s : 0.01% optimize.convert_after_rewriter : 0.000011s : 0.00% optimize.order_py_execute_after_rewriter : 0.000008s : 0.00% optimize.mutable_eliminate : 0.000725s : 0.03% optimize.opt_b.b_1 : 0.000216s : 0.01% optimize.opt_b.b_2 : 0.000013s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000009s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000042s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000024s : 0.00% optimize.overlap_param_gather : 0.000006s : 0.00% optimize.cconv : 0.000037s : 0.00% optimize.loop_unroll : 0.000456s : 0.02% optimize.opt_after_cconv.c_1 : 0.000055s : 0.00% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.cse : 0.000035s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000070s : 0.00% optimize.tuple_transform.d_1 : 0.000079s : 0.00% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000011s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000068s : 0.00% optimize.cse_after_recomputation.cse : 0.000023s : 0.00% optimize.environ_conv : 0.000021s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000008s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000004s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000002s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000025s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000017s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000005s : 0.00% 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 : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000006s : 0.00% optimize.overlap_grad_flash_sp : 0.000042s : 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 : 0.000002s : 0.00% optimize.symbol_engine_optimizer.build : 0.000094s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000022s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000001s : 0.00% auto_monad_reorder : 0.000030s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000004s : 0.00% opt_after_jit_grad : 0.000515s : 0.02% validate : 0.000072s : 0.00% Time group info: ------[substitution.] 0.000143 36 6.34% : 0.000009s : 2: substitution.elim_not_effective 6.43% : 0.000009s : 2: substitution.fold_const_symbol 6.17% : 0.000009s : 9: substitution.graph_param_transform 68.74% : 0.000098s : 1: substitution.inline 2.41% : 0.000003s : 4: substitution.j_node_and_user_rematch 3.83% : 0.000005s : 4: substitution.remove_not_recompute_node 6.08% : 0.000009s : 14: substitution.replace_old_param ------[type_inference.] 0.882878 2 99.93% : 0.882255s : 1: type_inference.infer 0.07% : 0.000623s : 1: type_inference.specialize ------[replace.] 0.000019 1 100.00% : 0.000019s : 1: replace.inline ------[match.] 0.000097 1 100.00% : 0.000097s : 1: match.inline ------[predicate.] 0.000234 2107 0.79% : 0.000002s : 19: predicate.accumulaten_eliminater 1.03% : 0.000002s : 9: predicate.ad_related_special_op_eliminate 0.71% : 0.000002s : 18: predicate.addn_check_dump 0.79% : 0.000002s : 19: predicate.addn_zero_filter 0.71% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 1.88% : 0.000004s : 37: predicate.arithmetic_simplify 0.79% : 0.000002s : 19: predicate.cast_eliminate 0.91% : 0.000002s : 18: predicate.check_bprop_eliminate 0.72% : 0.000002s : 18: predicate.compare_switch_simplify 0.31% : 0.000001s : 9: predicate.const_output_eliminate 0.75% : 0.000002s : 18: predicate.depend_value_elim 0.87% : 0.000002s : 19: predicate.dict_get_item_const_eliminator 0.94% : 0.000002s : 19: predicate.dict_get_item_eliminator 0.82% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.20% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.42% : 0.000001s : 9: predicate.elim_not_effective 0.48% : 0.000001s : 9: predicate.elim_shapecalc_of_broadcastargs 1.15% : 0.000003s : 28: predicate.environ_add_const_eliminate 1.12% : 0.000003s : 28: predicate.environ_get_add_eliminate 1.11% : 0.000003s : 28: predicate.environ_get_depend_swap 1.91% : 0.000004s : 46: predicate.environ_get_eliminate 1.09% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.79% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.47% : 0.000003s : 20: predicate.float_depend_g_call 0.70% : 0.000002s : 18: predicate.float_environ_get_switch 1.10% : 0.000003s : 27: predicate.float_tuple_getitem_switch 0.32% : 0.000001s : 9: predicate.fold_const_symbol 0.78% : 0.000002s : 18: predicate.get_grad_eliminate 0.36% : 0.000001s : 9: predicate.graph_param_transform 0.78% : 0.000002s : 18: predicate.incorporate_call 0.68% : 0.000002s : 18: predicate.incorporate_call_switch 5.55% : 0.000013s : 93: predicate.inline 0.97% : 0.000002s : 18: predicate.inline_without_move 0.55% : 0.000001s : 18: predicate.j_node_and_user_rematch 0.87% : 0.000002s : 18: predicate.less_batch_normalization 1.62% : 0.000004s : 37: predicate.list_to_tuple_eliminator_ 2.33% : 0.000005s : 56: predicate.load_eliminater 0.91% : 0.000002s : 9: predicate.loop_unroll_after_grad 1.30% : 0.000003s : 28: predicate.loop_unroll_before_grad 1.98% : 0.000005s : 37: predicate.make_slice_get_slice_eliminator 0.73% : 0.000002s : 18: predicate.merge_addn 0.80% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.82% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.71% : 0.000002s : 19: predicate.minmaximum_grad 0.96% : 0.000002s : 9: predicate.mutable_eliminate 0.48% : 0.000001s : 9: predicate.opt_reshape 0.44% : 0.000001s : 9: predicate.parallel_virtual_node 1.03% : 0.000002s : 20: predicate.partial_defer_inline 1.31% : 0.000003s : 28: predicate.partial_eliminate 0.82% : 0.000002s : 19: predicate.print_const_string_wrapper 0.75% : 0.000002s : 18: predicate.reduce_all_const_elim 1.08% : 0.000003s : 19: predicate.reduce_eliminate 2.32% : 0.000005s : 56: predicate.redundant_stop_gradient_eliminater 0.72% : 0.000002s : 18: predicate.remove_not_recompute_node 1.86% : 0.000004s : 37: predicate.replace_applicator 0.79% : 0.000002s : 18: predicate.replace_old_param 0.39% : 0.000001s : 9: predicate.reset_defer_inline 0.74% : 0.000002s : 19: predicate.reshape_eliminate 1.03% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.47% : 0.000001s : 9: predicate.row_tensor_eliminate 1.47% : 0.000003s : 18: predicate.same_eliminate 0.68% : 0.000002s : 18: predicate.set_cell_output_no_recompute 0.94% : 0.000002s : 18: predicate.shard_identity_eliminate 0.95% : 0.000002s : 18: predicate.special_op_eliminate 0.92% : 0.000002s : 18: predicate.specialize_transform 1.58% : 0.000004s : 18: predicate.split_environ_get_set_with_tuple_value 0.93% : 0.000002s : 18: predicate.stack_unstack_eliminate 0.50% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.85% : 0.000002s : 20: predicate.switch_defer_inline 1.69% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.78% : 0.000009s : 75: predicate.switch_simplify 0.77% : 0.000002s : 19: predicate.tile_eliminate 0.81% : 0.000002s : 19: predicate.transpose_eliminate 1.58% : 0.000004s : 37: predicate.tuple_list_convert_item_index_to_positive 1.80% : 0.000004s : 37: predicate.tuple_list_get_item_const_eliminator 1.59% : 0.000004s : 37: predicate.tuple_list_get_item_depend_reorder 3.04% : 0.000007s : 55: predicate.tuple_list_get_item_eliminator 1.63% : 0.000004s : 37: predicate.tuple_list_get_set_item_eliminator 2.53% : 0.000006s : 55: predicate.tuple_list_set_item_eliminator 1.62% : 0.000004s : 37: predicate.tuple_to_list_eliminator_ 2.20% : 0.000005s : 56: predicate.updatestate_pure_node_eliminater 3.18% : 0.000007s : 74: predicate.updatestate_useless_node_eliminater 0.44% : 0.000001s : 9: predicate.value_based_eliminate 0.86% : 0.000002s : 18: predicate.virtual_dataset_eliminate 0.84% : 0.000002s : 18: predicate.virtual_output_eliminate 0.42% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.53% : 0.000001s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000564 6 58.33% : 0.000329s : 3: func_graph_cloner_run.FuncGraphClonerGraph 41.67% : 0.000235s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.506610 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.27% : 0.009374s : 1: add_attr 0.27% : 0.009357s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000072s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.00% : 0.000118s : 1: auto_monad 0.00% : 0.000034s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.03% : 0.000938s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000021s : 1: control_data_broadcast_order 0.00% : 0.000015s : 1: convert_after_rewriter 0.00% : 0.000038s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000025s : 1: environ_conv 0.00% : 0.000026s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 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% : 0.000007s : 1: label_fine_grained_interleaved_index 0.00% : 0.000008s : 1: label_micro_interleaved_index 0.01% : 0.000465s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.02% : 0.000734s : 1: mutable_eliminate 0.00% : 0.000008s : 1: offloading_packed_experts 0.00% : 0.000019s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000022s : 1: opt.transform.mutable_eliminate 0.04% : 0.001376s : 78: opt.transform.opt_a 0.00% : 0.000054s : 1: opt.transform.opt_after_cconv 0.00% : 0.000038s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000201s : 28: opt.transform.opt_b 0.00% : 0.000088s : 2: opt.transform.opt_trans_graph 0.00% : 0.000070s : 4: opt.transform.symbol_engine_opt 37.00% : 1.297290s : 1: opt_a 0.00% : 0.000156s : 1: opt_after_cconv 0.01% : 0.000525s : 1: opt_after_jit_grad 0.01% : 0.000340s : 1: opt_b 37.08% : 1.300217s : 1: optimize 0.00% : 0.000028s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000045s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 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% : 0.000028s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000009s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000053s : 1: pre_auto_parallel 0.00% : 0.000030s : 1: py_interpret_to_execute 0.00% : 0.000034s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000075s : 1: remove_dup_value 0.01% : 0.000380s : 1: renormalize.infer 0.01% : 0.000325s : 1: renormalize.specialize 0.00% : 0.000007s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000118s : 1: rewriter_after_opt_a 0.00% : 0.000082s : 1: rewriter_before_opt_a 0.00% : 0.000007s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000209s : 1: symbol_engine_optimizer 0.00% : 0.000120s : 1: tuple_transform 25.19% : 0.883164s : 1: type_inference mki_log delete old file:/home/jenkins/ascend/log/atb/atb_75218_20260129172214.log . [hook] pytest_runtest_teardown:test_paged_attention_asd_mla_fp32[1] tests/st/infer/ops/test_internal_ops/test_asd_paged_attention.py::test_paged_attention_asd_mla_fp32[1],max_mem:272.0M [WARNING] ME(170484:281473336930096,MainProcess):2026-01-29-17:43:16.918.116 [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 = 0.0951198, [21] [bootstrap]: 0.00096143 [type_inference]: 0.00802387 [event_method]: 2.083e-05 [auto_monad]: 7.001e-05 [graph_reusing]: 5.12e-06 [inline]: 2.72001e-06 [add_attr]: 0.00533433, [1] [add_attr_with_inline]: 0.00532204, [1] [Cycle 1]: 6.665e-05, [2] [tag_attr]: 2.109e-05 [meta_addattr_fg_expand]: 4.16001e-06 [parallel-infer-symbol]: 3.96001e-06 [pre_auto_parallel]: 3.446e-05 [insert-virtual-dataset]: 2.34001e-06 [parallel-infer-symbol-second]: 8.99978e-07 [dataset_repeat_opt]: 1.96e-06 [pipeline_split]: 1.61998e-06 [optimize]: 0.0795988, [53] [py_interpret_to_execute]: 4.053e-05 [rewriter_before_opt_a]: 0.00015131 [opt_a]: 0.0751002, [2] [Cycle 1]: 0.0734128, [45] [expand_dump_flag]: 6.06998e-06 [switch_simplify]: 3.34e-05 [loop_unroll]: 1.903e-05 [a_1]: 0.00077294 [with_stream_mark]: 2.38e-05 [recompute_prepare]: 1.904e-05 [updatestate_depend_eliminate]: 6.34001e-06 [updatestate_assign_eliminate]: 5.44e-06 [updatestate_loads_eliminate]: 5.30999e-06 [parameter_eliminate]: 1.99e-06 [a_2]: 0.00018772 [accelerated_algorithm]: 1.779e-05 [shard]: 2.47001e-06 [meta_shard_fg_expand]: 2.93998e-06 [shard_inline]: 1.113e-05 [merge_send_recv]: 1.201e-05 [auto_parallel]: 1.415e-05 [parallel]: 3.671e-05 [flash_sp]: 1.071e-05 [merge_comm]: 9.98002e-06 [allreduce_fusion]: 5.10001e-06 [matmul_add_comm_reduction]: 1.507e-05 [allreduce_slice_to_reducescatter]: 9.5999e-07 [virtual_shard_identity]: 1.717e-05 [virtual_dataset]: 1.591e-05 [get_grad_eliminate_]: 1.385e-05 [virtual_output]: 1.752e-05 [merge_forward]: 6.56e-06 [cell_reuse_recompute_pass]: 1.77001e-06 [offload_activation]: 1.916e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.733e-05 [merge_recompute_call_nodes]: 1.64e-06 [before_grad]: 2.227e-05 [set_forward_comm_id_for_comm_node_pass]: 5.37001e-06 [meta_fg_expand]: 4.12e-06 [flash_sp_send_recv_attached]: 2.61e-06 [receive_attached]: 3.34001e-06 [after_resolve]: 2.66e-05 [a_after_grad]: 2.399e-05 [renormalize]: 0.0712896 [add_forward_monad_depend]: 1.425e-05 [auto_monad_grad]: 2.54001e-06 [auto_monad_eliminator]: 2.934e-05 [cse]: 9.019e-05 [a_3]: 0.00012018 [Cycle 2]: 0.00167239, [45] [expand_dump_flag]: 3.03998e-06 [switch_simplify]: 2.563e-05 [loop_unroll]: 1.984e-05 [a_1]: 0.0004351 [with_stream_mark]: 2.681e-05 [recompute_prepare]: 2.18e-05 [updatestate_depend_eliminate]: 6.48e-06 [updatestate_assign_eliminate]: 5.81e-06 [updatestate_loads_eliminate]: 9.09998e-06 [parameter_eliminate]: 2.47001e-06 [a_2]: 0.00019618 [accelerated_algorithm]: 1.957e-05 [shard]: 3.38e-06 [meta_shard_fg_expand]: 3.36001e-06 [shard_inline]: 1.11e-05 [merge_send_recv]: 1.138e-05 [auto_parallel]: 1.292e-05 [parallel]: 1.072e-05 [flash_sp]: 5.06997e-06 [merge_comm]: 7.85998e-06 [allreduce_fusion]: 6.02999e-06 [matmul_add_comm_reduction]: 1.809e-05 [allreduce_slice_to_reducescatter]: 1.28002e-06 [virtual_shard_identity]: 1.63e-05 [virtual_dataset]: 2.029e-05 [get_grad_eliminate_]: 1.48e-05 [virtual_output]: 1.858e-05 [merge_forward]: 6.81001e-06 [cell_reuse_recompute_pass]: 3.33998e-06 [offload_activation]: 1.448e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.464e-05 [merge_recompute_call_nodes]: 1.74e-06 [before_grad]: 1.904e-05 [set_forward_comm_id_for_comm_node_pass]: 5.60001e-06 [meta_fg_expand]: 4.03001e-06 [flash_sp_send_recv_attached]: 1.57001e-06 [receive_attached]: 2.95002e-06 [after_resolve]: 3.478e-05 [a_after_grad]: 3.216e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.39e-06 [auto_monad_grad]: 1.37999e-06 [auto_monad_eliminator]: 1.215e-05 [cse]: 8.953e-05 [a_3]: 8.79e-05 [py_interpret_to_execute_after_opt_a]: 3.598e-05 [slice_cell_reuse_recomputed_activation]: 2.12999e-06 [rewriter_after_opt_a]: 0.00012299 [convert_after_rewriter]: 3.034e-05 [order_py_execute_after_rewriter]: 7.93999e-06 [mutable_eliminate]: 0.00089199 [opt_b]: 0.00057612, [1] [Cycle 1]: 0.0005654, [7] [b_1]: 0.0003705 [b_2]: 1.946e-05 [updatestate_depend_eliminate]: 9.62999e-06 [updatestate_assign_eliminate]: 5.14998e-06 [updatestate_loads_eliminate]: 5.15999e-06 [renormalize]: 8.39995e-07 [cse]: 8.322e-05 [optimize_parallel_all_gather_comm]: 2.766e-05 [overlap_param_gather]: 4.15999e-06 [cconv]: 3.346e-05 [loop_unroll]: 0.00060898 [opt_after_cconv]: 0.00024185, [1] [Cycle 1]: 0.00023449, [7] [c_1]: 7.391e-05 [parameter_eliminate]: 3.18e-06 [updatestate_depend_eliminate]: 1.374e-05 [updatestate_assign_eliminate]: 8.23999e-06 [updatestate_loads_eliminate]: 4.97999e-06 [cse]: 7.185e-05 [renormalize]: 4.69998e-07 [remove_dup_value]: 7.754e-05 [tuple_transform]: 0.00018438, [1] [Cycle 1]: 0.00017838, [4] [d_1]: 0.00013063 [none_parameter_eliminate]: 2.12999e-06 [renormalize]: 1.80007e-07 [switch_simplify]: 1.257e-05 [partial_unused_args_eliminate]: 2.09e-06 [add_recomputation]: 8.308e-05 [cse_after_recomputation]: 5.082e-05, [1] [Cycle 1]: 4.59e-05, [1] [cse]: 3.411e-05 [environ_conv]: 8.66002e-06 [swap_dp_allreduce_reducescatter]: 7.78001e-06 [bias_add_comm_swap]: 3.48e-06 [label_micro_interleaved_index]: 5.92999e-06 [label_fine_grained_interleaved_index]: 2.95002e-06 [merge_cast_opt]: 1.81e-06 [slice_recompute_activation]: 2.66e-06 [micro_interleaved_order_control]: 2.53e-06 [assign_add_opt]: 1.85001e-06 [ForceFp32Comm]: 9.70002e-07 [remove_cast_before_assign_add]: 1.37e-06 [full_micro_interleaved_order_control]: 2.29001e-06 [reorder_send_recv_between_fp_bp]: 2.87002e-06 [comm_op_add_attrs]: 1.13001e-06 [add_comm_op_reuse_tag]: 1.13001e-06 [interleave_split_concat_branches]: 1.34e-06 [interleave_parallel_branches]: 1.07e-06 [overlap_opt_shard_in_pipeline]: 2.84001e-06 [overlap_opt_shard_grad_in_pipeline]: 2.23998e-06 [control_data_broadcast_order]: 1.864e-05 [grouped_pairwise_exchange_alltoall]: 1.72999e-06 [offloading_packed_experts]: 5.19998e-06 [overlap_recompute_and_grad_model_parallel]: 9.53002e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.35001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.77001e-06 [overlap_recompute_comm]: 2.67001e-06 [overlap_grad_ring_attention]: 7.75e-06 [overlap_grad_flash_sp]: 3.429e-05 [begin_end_overlap_inline]: 8.2e-07 [split_matmul_comm_elemetwise]: 2.93e-06 [split_layernorm_comm]: 1.81998e-06 [handle_group_info]: 9.40025e-07 [symbol_engine_optimizer]: 0.00035414, [1] [Cycle 1]: 0.00034904, [6] [build]: 0.00019495 [elim_shapecalc]: 3.297e-05 [elim_not_effective]: 2.774e-05 [opt_reshape]: 1.452e-05 [fold_const_symbol]: 2.382e-05 [renormalize]: 1.80007e-07 [detach_backward]: 2.61e-06 [pipeline_parallel_scheduler]: 1.50001e-06 [auto_monad_reorder]: 3.2e-05 [get_jit_bprop_graph]: 1.68002e-06 [rewriter_after_jit_bprop_graph]: 4.60001e-06 [opt_after_jit_grad]: 0.00075447 [validate]: 6.959e-05 Sums bootstrap : 0.000961s : 1.10% type_inference : 0.008024s : 9.15% event_method : 0.000021s : 0.02% auto_monad : 0.000070s : 0.08% graph_reusing : 0.000005s : 0.01% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000021s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000034s : 0.04% insert-virtual-dataset : 0.000002s : 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 : 0.000041s : 0.05% optimize.rewriter_before_opt_a : 0.000151s : 0.17% optimize.opt_a.expand_dump_flag : 0.000009s : 0.01% optimize.opt_a.switch_simplify : 0.000059s : 0.07% optimize.opt_a.loop_unroll : 0.000039s : 0.04% optimize.opt_a.a_1 : 0.001208s : 1.38% optimize.opt_a.with_stream_mark : 0.000051s : 0.06% optimize.opt_a.recompute_prepare : 0.000041s : 0.05% optimize.opt_a.updatestate_depend_eliminate : 0.000013s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000011s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000014s : 0.02% optimize.opt_a.parameter_eliminate : 0.000004s : 0.01% optimize.opt_a.a_2 : 0.000384s : 0.44% optimize.opt_a.accelerated_algorithm : 0.000037s : 0.04% optimize.opt_a.shard : 0.000006s : 0.01% optimize.opt_a.meta_shard_fg_expand : 0.000006s : 0.01% optimize.opt_a.shard_inline : 0.000022s : 0.03% optimize.opt_a.merge_send_recv : 0.000023s : 0.03% optimize.opt_a.auto_parallel : 0.000027s : 0.03% optimize.opt_a.parallel : 0.000047s : 0.05% optimize.opt_a.flash_sp : 0.000016s : 0.02% optimize.opt_a.merge_comm : 0.000018s : 0.02% optimize.opt_a.allreduce_fusion : 0.000011s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000033s : 0.04% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000033s : 0.04% optimize.opt_a.virtual_dataset : 0.000036s : 0.04% optimize.opt_a.get_grad_eliminate_ : 0.000029s : 0.03% optimize.opt_a.virtual_output : 0.000036s : 0.04% optimize.opt_a.merge_forward : 0.000013s : 0.02% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.01% optimize.opt_a.offload_activation : 0.000034s : 0.04% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000062s : 0.07% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000041s : 0.05% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000011s : 0.01% optimize.opt_a.meta_fg_expand : 0.000008s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000004s : 0.00% optimize.opt_a.receive_attached : 0.000006s : 0.01% optimize.opt_a.after_resolve : 0.000061s : 0.07% optimize.opt_a.a_after_grad : 0.000056s : 0.06% optimize.opt_a.renormalize : 0.071290s : 81.30% optimize.opt_a.add_forward_monad_depend : 0.000016s : 0.02% optimize.opt_a.auto_monad_grad : 0.000004s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000041s : 0.05% optimize.opt_a.cse : 0.000180s : 0.20% optimize.opt_a.a_3 : 0.000208s : 0.24% optimize.py_interpret_to_execute_after_opt_a : 0.000036s : 0.04% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000123s : 0.14% optimize.convert_after_rewriter : 0.000030s : 0.03% optimize.order_py_execute_after_rewriter : 0.000008s : 0.01% optimize.mutable_eliminate : 0.000892s : 1.02% optimize.opt_b.b_1 : 0.000370s : 0.42% optimize.opt_b.b_2 : 0.000019s : 0.02% optimize.opt_b.updatestate_depend_eliminate : 0.000010s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000083s : 0.09% optimize.optimize_parallel_all_gather_comm : 0.000028s : 0.03% optimize.overlap_param_gather : 0.000004s : 0.00% optimize.cconv : 0.000033s : 0.04% optimize.loop_unroll : 0.000609s : 0.69% optimize.opt_after_cconv.c_1 : 0.000074s : 0.08% optimize.opt_after_cconv.parameter_eliminate : 0.000003s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.02% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.01% optimize.opt_after_cconv.cse : 0.000072s : 0.08% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000078s : 0.09% optimize.tuple_transform.d_1 : 0.000131s : 0.15% 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 : 0.000083s : 0.09% optimize.cse_after_recomputation.cse : 0.000034s : 0.04% optimize.environ_conv : 0.000009s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000008s : 0.01% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.01% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000003s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000019s : 0.02% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000005s : 0.01% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.01% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000008s : 0.01% optimize.overlap_grad_flash_sp : 0.000034s : 0.04% 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 : 0.000195s : 0.22% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000033s : 0.04% optimize.symbol_engine_optimizer.elim_not_effective : 0.000028s : 0.03% optimize.symbol_engine_optimizer.opt_reshape : 0.000015s : 0.02% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000024s : 0.03% 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 : 0.000032s : 0.04% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.01% opt_after_jit_grad : 0.000754s : 0.86% validate : 0.000070s : 0.08% Time group info: ------[substitution.] 0.000190 36 2.90% : 0.000006s : 2: substitution.elim_not_effective 4.42% : 0.000008s : 2: substitution.fold_const_symbol 4.40% : 0.000008s : 9: substitution.graph_param_transform 77.91% : 0.000148s : 1: substitution.inline 2.19% : 0.000004s : 4: substitution.j_node_and_user_rematch 2.73% : 0.000005s : 4: substitution.remove_not_recompute_node 5.45% : 0.000010s : 14: substitution.replace_old_param ------[type_inference.] 0.007913 2 88.70% : 0.007019s : 1: type_inference.infer 11.30% : 0.000894s : 1: type_inference.specialize ------[replace.] 0.000020 1 100.00% : 0.000020s : 1: replace.inline ------[match.] 0.000147 1 100.00% : 0.000147s : 1: match.inline ------[predicate.] 0.000256 2107 0.83% : 0.000002s : 19: predicate.accumulaten_eliminater 0.94% : 0.000002s : 9: predicate.ad_related_special_op_eliminate 0.69% : 0.000002s : 18: predicate.addn_check_dump 0.83% : 0.000002s : 19: predicate.addn_zero_filter 0.70% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 2.07% : 0.000005s : 37: predicate.arithmetic_simplify 0.93% : 0.000002s : 19: predicate.cast_eliminate 0.86% : 0.000002s : 18: predicate.check_bprop_eliminate 0.70% : 0.000002s : 18: predicate.compare_switch_simplify 0.28% : 0.000001s : 9: predicate.const_output_eliminate 0.75% : 0.000002s : 18: predicate.depend_value_elim 0.83% : 0.000002s : 19: predicate.dict_get_item_const_eliminator 1.08% : 0.000003s : 19: predicate.dict_get_item_eliminator 0.86% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.29% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.42% : 0.000001s : 9: predicate.elim_not_effective 0.50% : 0.000001s : 9: predicate.elim_shapecalc_of_broadcastargs 1.16% : 0.000003s : 28: predicate.environ_add_const_eliminate 1.05% : 0.000003s : 28: predicate.environ_get_add_eliminate 1.07% : 0.000003s : 28: predicate.environ_get_depend_swap 1.90% : 0.000005s : 46: predicate.environ_get_eliminate 1.07% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.74% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.50% : 0.000004s : 20: predicate.float_depend_g_call 0.66% : 0.000002s : 18: predicate.float_environ_get_switch 1.02% : 0.000003s : 27: predicate.float_tuple_getitem_switch 0.33% : 0.000001s : 9: predicate.fold_const_symbol 0.94% : 0.000002s : 18: predicate.get_grad_eliminate 0.44% : 0.000001s : 9: predicate.graph_param_transform 0.71% : 0.000002s : 18: predicate.incorporate_call 0.63% : 0.000002s : 18: predicate.incorporate_call_switch 5.21% : 0.000013s : 93: predicate.inline 0.92% : 0.000002s : 18: predicate.inline_without_move 0.53% : 0.000001s : 18: predicate.j_node_and_user_rematch 1.07% : 0.000003s : 18: predicate.less_batch_normalization 1.77% : 0.000005s : 37: predicate.list_to_tuple_eliminator_ 2.34% : 0.000006s : 56: predicate.load_eliminater 1.33% : 0.000003s : 9: predicate.loop_unroll_after_grad 1.25% : 0.000003s : 28: predicate.loop_unroll_before_grad 1.85% : 0.000005s : 37: predicate.make_slice_get_slice_eliminator 0.76% : 0.000002s : 18: predicate.merge_addn 0.76% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.79% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.75% : 0.000002s : 19: predicate.minmaximum_grad 1.22% : 0.000003s : 9: predicate.mutable_eliminate 0.62% : 0.000002s : 9: predicate.opt_reshape 0.50% : 0.000001s : 9: predicate.parallel_virtual_node 1.21% : 0.000003s : 20: predicate.partial_defer_inline 1.22% : 0.000003s : 28: predicate.partial_eliminate 0.80% : 0.000002s : 19: predicate.print_const_string_wrapper 0.72% : 0.000002s : 18: predicate.reduce_all_const_elim 1.23% : 0.000003s : 19: predicate.reduce_eliminate 2.35% : 0.000006s : 56: predicate.redundant_stop_gradient_eliminater 0.81% : 0.000002s : 18: predicate.remove_not_recompute_node 1.62% : 0.000004s : 37: predicate.replace_applicator 0.80% : 0.000002s : 18: predicate.replace_old_param 0.42% : 0.000001s : 9: predicate.reset_defer_inline 0.86% : 0.000002s : 19: predicate.reshape_eliminate 0.95% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.52% : 0.000001s : 9: predicate.row_tensor_eliminate 1.17% : 0.000003s : 18: predicate.same_eliminate 0.61% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.11% : 0.000003s : 18: predicate.shard_identity_eliminate 1.06% : 0.000003s : 18: predicate.special_op_eliminate 0.82% : 0.000002s : 18: predicate.specialize_transform 1.36% : 0.000003s : 18: predicate.split_environ_get_set_with_tuple_value 0.92% : 0.000002s : 18: predicate.stack_unstack_eliminate 0.55% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.82% : 0.000002s : 20: predicate.switch_defer_inline 1.50% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.85% : 0.000010s : 75: predicate.switch_simplify 0.80% : 0.000002s : 19: predicate.tile_eliminate 0.76% : 0.000002s : 19: predicate.transpose_eliminate 1.56% : 0.000004s : 37: predicate.tuple_list_convert_item_index_to_positive 1.82% : 0.000005s : 37: predicate.tuple_list_get_item_const_eliminator 1.50% : 0.000004s : 37: predicate.tuple_list_get_item_depend_reorder 2.91% : 0.000007s : 55: predicate.tuple_list_get_item_eliminator 1.64% : 0.000004s : 37: predicate.tuple_list_get_set_item_eliminator 2.44% : 0.000006s : 55: predicate.tuple_list_set_item_eliminator 1.71% : 0.000004s : 37: predicate.tuple_to_list_eliminator_ 2.07% : 0.000005s : 56: predicate.updatestate_pure_node_eliminater 2.94% : 0.000008s : 74: predicate.updatestate_useless_node_eliminater 0.46% : 0.000001s : 9: predicate.value_based_eliminate 0.83% : 0.000002s : 18: predicate.virtual_dataset_eliminate 0.93% : 0.000002s : 18: predicate.virtual_output_eliminate 0.44% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.50% : 0.000001s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001161 6 40.54% : 0.000471s : 3: func_graph_cloner_run.FuncGraphClonerGraph 59.46% : 0.000690s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.254145 192 0.00% : 0.000004s : 1: ForceFp32Comm 2.10% : 0.005340s : 1: add_attr 2.10% : 0.005326s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.03% : 0.000087s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.03% : 0.000076s : 1: auto_monad 0.01% : 0.000036s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.39% : 0.001001s : 1: bootstrap 0.02% : 0.000038s : 1: cconv 0.00% : 0.000007s : 1: comm_op_add_attrs 0.01% : 0.000022s : 1: control_data_broadcast_order 0.01% : 0.000035s : 1: convert_after_rewriter 0.02% : 0.000054s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000012s : 1: environ_conv 0.01% : 0.000028s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000009s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000006s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000004s : 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% : 0.000012s : 1: label_micro_interleaved_index 0.24% : 0.000618s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.36% : 0.000906s : 1: mutable_eliminate 0.00% : 0.000008s : 1: offloading_packed_experts 0.01% : 0.000032s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000026s : 1: opt.transform.mutable_eliminate 0.88% : 0.002233s : 78: opt.transform.opt_a 0.03% : 0.000073s : 1: opt.transform.opt_after_cconv 0.03% : 0.000064s : 1: opt.transform.opt_after_jit_grad 0.14% : 0.000347s : 28: opt.transform.opt_b 0.06% : 0.000140s : 2: opt.transform.opt_trans_graph 0.04% : 0.000094s : 4: opt.transform.symbol_engine_opt 29.55% : 0.075104s : 1: opt_a 0.10% : 0.000246s : 1: opt_after_cconv 0.30% : 0.000772s : 1: opt_after_jit_grad 0.23% : 0.000580s : 1: opt_b 31.32% : 0.079606s : 1: optimize 0.01% : 0.000032s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.01% : 0.000038s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000018s : 1: overlap_grad_ring_attention 0.00% : 0.000010s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000006s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000010s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000007s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000009s : 1: pipeline_parallel_scheduler 0.00% : 0.000004s : 1: pipeline_split 0.02% : 0.000039s : 1: pre_auto_parallel 0.02% : 0.000044s : 1: py_interpret_to_execute 0.02% : 0.000040s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.03% : 0.000082s : 1: remove_dup_value 27.67% : 0.070322s : 1: renormalize.infer 0.37% : 0.000947s : 1: renormalize.specialize 0.00% : 0.000009s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.05% : 0.000132s : 1: rewriter_after_opt_a 0.06% : 0.000157s : 1: rewriter_before_opt_a 0.21% : 0.000527s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000010s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.14% : 0.000357s : 1: symbol_engine_optimizer 0.07% : 0.000188s : 1: tuple_transform 3.17% : 0.008044s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_asd_mla_fp32[2] tests/st/infer/ops/test_internal_ops/test_asd_paged_attention.py::test_paged_attention_asd_mla_fp32[2],max_mem:272.0M =============================== 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 ================== 2 passed, 25 warnings in 385.80s (0:06:25) ==================