==================================================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_paged_attention.py [WARNING] ME(163654:281473352806192,MainProcess):2026-01-29-17:39:39.640.6 [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 = 0.450033, [21] [bootstrap]: 0.00076038 [type_inference]: 0.433169 [event_method]: 2.266e-05 [auto_monad]: 0.00012382 [graph_reusing]: 5.89e-06 [inline]: 3.63e-06 [add_attr]: 0.00871513, [1] [add_attr_with_inline]: 0.0086993, [1] [Cycle 1]: 0.00010044, [2] [tag_attr]: 2.274e-05 [meta_addattr_fg_expand]: 3.7e-06 [parallel-infer-symbol]: 3.48e-06 [pre_auto_parallel]: 5.05e-05 [insert-virtual-dataset]: 2.41e-06 [parallel-infer-symbol-second]: 7.59988e-07 [dataset_repeat_opt]: 2.04e-06 [pipeline_split]: 1.77001e-06 [optimize]: 0.00631372, [53] [py_interpret_to_execute]: 2.925e-05 [rewriter_before_opt_a]: 8.408e-05 [opt_a]: 0.00339061, [2] [Cycle 1]: 0.00229545, [45] [expand_dump_flag]: 3.14001e-06 [switch_simplify]: 3.45e-05 [loop_unroll]: 1.871e-05 [a_1]: 0.00045017 [with_stream_mark]: 2.561e-05 [recompute_prepare]: 1.377e-05 [updatestate_depend_eliminate]: 6.45002e-06 [updatestate_assign_eliminate]: 5.15999e-06 [updatestate_loads_eliminate]: 4.73001e-06 [parameter_eliminate]: 1.84998e-06 [a_2]: 0.00014163 [accelerated_algorithm]: 1.099e-05 [shard]: 3.07002e-06 [meta_shard_fg_expand]: 2.47001e-06 [shard_inline]: 1.028e-05 [merge_send_recv]: 2.019e-05 [auto_parallel]: 9.30001e-06 [parallel]: 4.678e-05 [flash_sp]: 2.28e-05 [merge_comm]: 6.24999e-06 [allreduce_fusion]: 5.00001e-06 [matmul_add_comm_reduction]: 1.226e-05 [allreduce_slice_to_reducescatter]: 7.50006e-07 [virtual_shard_identity]: 1.335e-05 [virtual_dataset]: 1.076e-05 [get_grad_eliminate_]: 9.94999e-06 [virtual_output]: 9.94001e-06 [merge_forward]: 5.34998e-06 [cell_reuse_recompute_pass]: 2.04999e-06 [offload_activation]: 1.335e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.776e-05 [merge_recompute_call_nodes]: 1.42999e-06 [before_grad]: 1.472e-05 [set_forward_comm_id_for_comm_node_pass]: 5.14998e-06 [meta_fg_expand]: 3.63e-06 [flash_sp_send_recv_attached]: 3.66001e-06 [receive_attached]: 1.094e-05 [after_resolve]: 2.124e-05 [a_after_grad]: 1.696e-05 [renormalize]: 0.00081068 [add_forward_monad_depend]: 7.13998e-06 [auto_monad_grad]: 2.81e-06 [auto_monad_eliminator]: 1.867e-05 [cse]: 8.669e-05 [a_3]: 8.233e-05 [Cycle 2]: 0.00108198, [45] [expand_dump_flag]: 2.63e-06 [switch_simplify]: 1.435e-05 [loop_unroll]: 1.068e-05 [a_1]: 0.00028871 [with_stream_mark]: 2.283e-05 [recompute_prepare]: 1.403e-05 [updatestate_depend_eliminate]: 5.99999e-06 [updatestate_assign_eliminate]: 4.68001e-06 [updatestate_loads_eliminate]: 5.15001e-06 [parameter_eliminate]: 2.41e-06 [a_2]: 0.00013156 [accelerated_algorithm]: 1.161e-05 [shard]: 2.41e-06 [meta_shard_fg_expand]: 2.66999e-06 [shard_inline]: 1.017e-05 [merge_send_recv]: 1.033e-05 [auto_parallel]: 1.068e-05 [parallel]: 7.41999e-06 [flash_sp]: 4.18001e-06 [merge_comm]: 5.37999e-06 [allreduce_fusion]: 5.02999e-06 [matmul_add_comm_reduction]: 1.057e-05 [allreduce_slice_to_reducescatter]: 5.29981e-07 [virtual_shard_identity]: 1.434e-05 [virtual_dataset]: 1.158e-05 [get_grad_eliminate_]: 9.84001e-06 [virtual_output]: 9.56e-06 [merge_forward]: 6.15002e-06 [cell_reuse_recompute_pass]: 2.02001e-06 [offload_activation]: 1.166e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.272e-05 [merge_recompute_call_nodes]: 9.39996e-07 [before_grad]: 1.549e-05 [set_forward_comm_id_for_comm_node_pass]: 5.54e-06 [meta_fg_expand]: 3.53999e-06 [flash_sp_send_recv_attached]: 1.45999e-06 [receive_attached]: 1.71e-06 [after_resolve]: 2.066e-05 [a_after_grad]: 1.606e-05 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 3.02002e-06 [auto_monad_grad]: 2.02001e-06 [auto_monad_eliminator]: 1.391e-05 [cse]: 3.594e-05 [a_3]: 6.725e-05 [py_interpret_to_execute_after_opt_a]: 2.088e-05 [slice_cell_reuse_recomputed_activation]: 2.63e-06 [rewriter_after_opt_a]: 8.042e-05 [convert_after_rewriter]: 2.416e-05 [order_py_execute_after_rewriter]: 7.11001e-06 [mutable_eliminate]: 0.00073813 [opt_b]: 0.00034323, [1] [Cycle 1]: 0.00033385, [7] [b_1]: 0.00021366 [b_2]: 1.332e-05 [updatestate_depend_eliminate]: 1.244e-05 [updatestate_assign_eliminate]: 4.77e-06 [updatestate_loads_eliminate]: 4.47998e-06 [renormalize]: 5.59987e-07 [cse]: 4.507e-05 [optimize_parallel_all_gather_comm]: 2.435e-05 [overlap_param_gather]: 4.97999e-06 [cconv]: 3.848e-05 [loop_unroll]: 0.00046033 [opt_after_cconv]: 0.00014996, [1] [Cycle 1]: 0.000143, [7] [c_1]: 5.171e-05 [parameter_eliminate]: 4.68001e-06 [updatestate_depend_eliminate]: 8.23999e-06 [updatestate_assign_eliminate]: 4.09997e-06 [updatestate_loads_eliminate]: 4.05e-06 [cse]: 3.468e-05 [renormalize]: 3.80009e-07 [remove_dup_value]: 7.447e-05 [tuple_transform]: 0.00011425, [1] [Cycle 1]: 0.00010893, [4] [d_1]: 7.668e-05 [none_parameter_eliminate]: 2.08998e-06 [renormalize]: 1.80007e-07 [switch_simplify]: 1.15e-05 [partial_unused_args_eliminate]: 1.98997e-06 [add_recomputation]: 7.246e-05 [cse_after_recomputation]: 3.402e-05, [1] [Cycle 1]: 2.902e-05, [1] [cse]: 2.264e-05 [environ_conv]: 1.983e-05 [swap_dp_allreduce_reducescatter]: 7.31001e-06 [bias_add_comm_swap]: 3.5e-06 [label_micro_interleaved_index]: 5.19e-06 [label_fine_grained_interleaved_index]: 2.89999e-06 [merge_cast_opt]: 1.44998e-06 [slice_recompute_activation]: 2.29001e-06 [micro_interleaved_order_control]: 2.81999e-06 [assign_add_opt]: 1.47001e-06 [ForceFp32Comm]: 8.79983e-07 [remove_cast_before_assign_add]: 1.40001e-06 [full_micro_interleaved_order_control]: 3.55998e-06 [reorder_send_recv_between_fp_bp]: 2.76e-06 [comm_op_add_attrs]: 1.34998e-06 [add_comm_op_reuse_tag]: 1.07e-06 [interleave_split_concat_branches]: 1.24e-06 [interleave_parallel_branches]: 1.19e-06 [overlap_opt_shard_in_pipeline]: 2.418e-05 [overlap_opt_shard_grad_in_pipeline]: 1.93002e-06 [control_data_broadcast_order]: 1.924e-05 [grouped_pairwise_exchange_alltoall]: 2.36998e-06 [offloading_packed_experts]: 5.90002e-06 [overlap_recompute_and_grad_model_parallel]: 6.06e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.30001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.44e-06 [overlap_recompute_comm]: 2.43e-06 [overlap_grad_ring_attention]: 5.22999e-06 [overlap_grad_flash_sp]: 2.908e-05 [begin_end_overlap_inline]: 5.39992e-07 [split_matmul_comm_elemetwise]: 2.20002e-06 [split_layernorm_comm]: 2.98e-06 [handle_group_info]: 1.08001e-06 [symbol_engine_optimizer]: 0.00020395, [1] [Cycle 1]: 0.00019888, [6] [build]: 8.991e-05 [elim_shapecalc]: 1.698e-05 [elim_not_effective]: 2.682e-05 [opt_reshape]: 1.211e-05 [fold_const_symbol]: 1.95e-05 [renormalize]: 2.00002e-07 [detach_backward]: 3.32002e-06 [pipeline_parallel_scheduler]: 1.71002e-06 [auto_monad_reorder]: 3.099e-05 [get_jit_bprop_graph]: 2.63e-06 [rewriter_after_jit_bprop_graph]: 6.36e-06 [opt_after_jit_grad]: 0.00054444 [validate]: 7.078e-05 Sums bootstrap : 0.000760s : 0.17% type_inference : 0.433169s : 98.39% event_method : 0.000023s : 0.01% auto_monad : 0.000124s : 0.03% graph_reusing : 0.000006s : 0.00% inline : 0.000004s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000023s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.00% parallel-infer-symbol : 0.000003s : 0.00% pre_auto_parallel : 0.000051s : 0.01% 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 : 0.000029s : 0.01% optimize.rewriter_before_opt_a : 0.000084s : 0.02% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000049s : 0.01% optimize.opt_a.loop_unroll : 0.000029s : 0.01% optimize.opt_a.a_1 : 0.000739s : 0.17% optimize.opt_a.with_stream_mark : 0.000048s : 0.01% optimize.opt_a.recompute_prepare : 0.000028s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% optimize.opt_a.parameter_eliminate : 0.000004s : 0.00% optimize.opt_a.a_2 : 0.000273s : 0.06% optimize.opt_a.accelerated_algorithm : 0.000023s : 0.01% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000005s : 0.00% optimize.opt_a.shard_inline : 0.000020s : 0.00% optimize.opt_a.merge_send_recv : 0.000031s : 0.01% optimize.opt_a.auto_parallel : 0.000020s : 0.00% optimize.opt_a.parallel : 0.000054s : 0.01% optimize.opt_a.flash_sp : 0.000027s : 0.01% optimize.opt_a.merge_comm : 0.000012s : 0.00% optimize.opt_a.allreduce_fusion : 0.000010s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000023s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000028s : 0.01% optimize.opt_a.virtual_dataset : 0.000022s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000020s : 0.00% optimize.opt_a.virtual_output : 0.000020s : 0.00% optimize.opt_a.merge_forward : 0.000012s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% optimize.opt_a.offload_activation : 0.000025s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000050s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000002s : 0.00% optimize.opt_a.before_grad : 0.000030s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000011s : 0.00% optimize.opt_a.meta_fg_expand : 0.000007s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000005s : 0.00% optimize.opt_a.receive_attached : 0.000013s : 0.00% optimize.opt_a.after_resolve : 0.000042s : 0.01% optimize.opt_a.a_after_grad : 0.000033s : 0.01% optimize.opt_a.renormalize : 0.000811s : 0.18% optimize.opt_a.add_forward_monad_depend : 0.000010s : 0.00% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000033s : 0.01% optimize.opt_a.cse : 0.000123s : 0.03% optimize.opt_a.a_3 : 0.000150s : 0.03% optimize.py_interpret_to_execute_after_opt_a : 0.000021s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000080s : 0.02% optimize.convert_after_rewriter : 0.000024s : 0.01% optimize.order_py_execute_after_rewriter : 0.000007s : 0.00% optimize.mutable_eliminate : 0.000738s : 0.17% optimize.opt_b.b_1 : 0.000214s : 0.05% optimize.opt_b.b_2 : 0.000013s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000012s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000004s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000045s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000024s : 0.01% optimize.overlap_param_gather : 0.000005s : 0.00% optimize.cconv : 0.000038s : 0.01% optimize.loop_unroll : 0.000460s : 0.10% optimize.opt_after_cconv.c_1 : 0.000052s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 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 : 0.01% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000074s : 0.02% optimize.tuple_transform.d_1 : 0.000077s : 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 : 0.000012s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000072s : 0.02% optimize.cse_after_recomputation.cse : 0.000023s : 0.01% optimize.environ_conv : 0.000020s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000007s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 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 : 0.000004s : 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 : 0.000024s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000019s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000006s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000006s : 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 : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000005s : 0.00% optimize.overlap_grad_flash_sp : 0.000029s : 0.01% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000003s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000090s : 0.02% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000031s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000544s : 0.12% validate : 0.000071s : 0.02% Time group info: ------[substitution.] 0.000173 36 6.35% : 0.000011s : 2: substitution.elim_not_effective 4.10% : 0.000007s : 2: substitution.fold_const_symbol 4.73% : 0.000008s : 9: substitution.graph_param_transform 67.85% : 0.000118s : 1: substitution.inline 2.54% : 0.000004s : 4: substitution.j_node_and_user_rematch 8.72% : 0.000015s : 4: substitution.remove_not_recompute_node 5.70% : 0.000010s : 14: substitution.replace_old_param ------[type_inference.] 0.433013 2 52.73% : 0.228319s : 1: type_inference.infer 47.27% : 0.204694s : 1: type_inference.specialize ------[replace.] 0.000022 1 100.00% : 0.000022s : 1: replace.inline ------[match.] 0.000117 1 100.00% : 0.000117s : 1: match.inline ------[predicate.] 0.000237 2107 0.85% : 0.000002s : 19: predicate.accumulaten_eliminater 1.18% : 0.000003s : 9: predicate.ad_related_special_op_eliminate 0.89% : 0.000002s : 18: predicate.addn_check_dump 0.84% : 0.000002s : 19: predicate.addn_zero_filter 0.72% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 2.10% : 0.000005s : 37: predicate.arithmetic_simplify 0.83% : 0.000002s : 19: predicate.cast_eliminate 0.84% : 0.000002s : 18: predicate.check_bprop_eliminate 0.70% : 0.000002s : 18: predicate.compare_switch_simplify 0.30% : 0.000001s : 9: predicate.const_output_eliminate 0.81% : 0.000002s : 18: predicate.depend_value_elim 0.82% : 0.000002s : 19: predicate.dict_get_item_const_eliminator 0.89% : 0.000002s : 19: predicate.dict_get_item_eliminator 0.81% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.48% : 0.000004s : 18: predicate.dumpgradient_eliminate 0.40% : 0.000001s : 9: predicate.elim_not_effective 0.57% : 0.000001s : 9: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000003s : 28: predicate.environ_add_const_eliminate 1.05% : 0.000003s : 28: predicate.environ_get_add_eliminate 1.08% : 0.000003s : 28: predicate.environ_get_depend_swap 1.84% : 0.000004s : 46: predicate.environ_get_eliminate 1.13% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.83% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.46% : 0.000003s : 20: predicate.float_depend_g_call 0.76% : 0.000002s : 18: predicate.float_environ_get_switch 1.05% : 0.000002s : 27: predicate.float_tuple_getitem_switch 0.29% : 0.000001s : 9: predicate.fold_const_symbol 0.91% : 0.000002s : 18: predicate.get_grad_eliminate 0.42% : 0.000001s : 9: predicate.graph_param_transform 0.79% : 0.000002s : 18: predicate.incorporate_call 0.66% : 0.000002s : 18: predicate.incorporate_call_switch 5.39% : 0.000013s : 93: predicate.inline 1.13% : 0.000003s : 18: predicate.inline_without_move 0.53% : 0.000001s : 18: predicate.j_node_and_user_rematch 1.03% : 0.000002s : 18: predicate.less_batch_normalization 1.66% : 0.000004s : 37: predicate.list_to_tuple_eliminator_ 2.22% : 0.000005s : 56: predicate.load_eliminater 1.25% : 0.000003s : 9: predicate.loop_unroll_after_grad 1.45% : 0.000003s : 28: predicate.loop_unroll_before_grad 1.75% : 0.000004s : 37: predicate.make_slice_get_slice_eliminator 0.79% : 0.000002s : 18: predicate.merge_addn 0.81% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.76% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.75% : 0.000002s : 19: predicate.minmaximum_grad 1.33% : 0.000003s : 9: predicate.mutable_eliminate 0.43% : 0.000001s : 9: predicate.opt_reshape 0.54% : 0.000001s : 9: predicate.parallel_virtual_node 1.09% : 0.000003s : 20: predicate.partial_defer_inline 1.30% : 0.000003s : 28: predicate.partial_eliminate 0.89% : 0.000002s : 19: predicate.print_const_string_wrapper 0.75% : 0.000002s : 18: predicate.reduce_all_const_elim 1.13% : 0.000003s : 19: predicate.reduce_eliminate 2.23% : 0.000005s : 56: predicate.redundant_stop_gradient_eliminater 1.02% : 0.000002s : 18: predicate.remove_not_recompute_node 1.53% : 0.000004s : 37: predicate.replace_applicator 0.71% : 0.000002s : 18: predicate.replace_old_param 0.44% : 0.000001s : 9: predicate.reset_defer_inline 0.78% : 0.000002s : 19: predicate.reshape_eliminate 0.83% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.45% : 0.000001s : 9: predicate.row_tensor_eliminate 1.09% : 0.000003s : 18: predicate.same_eliminate 0.63% : 0.000001s : 18: predicate.set_cell_output_no_recompute 1.00% : 0.000002s : 18: predicate.shard_identity_eliminate 0.81% : 0.000002s : 18: predicate.special_op_eliminate 0.85% : 0.000002s : 18: predicate.specialize_transform 1.21% : 0.000003s : 18: predicate.split_environ_get_set_with_tuple_value 0.96% : 0.000002s : 18: predicate.stack_unstack_eliminate 0.43% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.84% : 0.000002s : 20: predicate.switch_defer_inline 1.73% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.93% : 0.000009s : 75: predicate.switch_simplify 0.76% : 0.000002s : 19: predicate.tile_eliminate 0.75% : 0.000002s : 19: predicate.transpose_eliminate 1.53% : 0.000004s : 37: predicate.tuple_list_convert_item_index_to_positive 1.58% : 0.000004s : 37: predicate.tuple_list_get_item_const_eliminator 1.43% : 0.000003s : 37: predicate.tuple_list_get_item_depend_reorder 3.09% : 0.000007s : 55: predicate.tuple_list_get_item_eliminator 1.40% : 0.000003s : 37: predicate.tuple_list_get_set_item_eliminator 2.39% : 0.000006s : 55: predicate.tuple_list_set_item_eliminator 1.56% : 0.000004s : 37: predicate.tuple_to_list_eliminator_ 2.20% : 0.000005s : 56: predicate.updatestate_pure_node_eliminater 3.17% : 0.000008s : 74: predicate.updatestate_useless_node_eliminater 0.45% : 0.000001s : 9: predicate.value_based_eliminate 1.03% : 0.000002s : 18: predicate.virtual_dataset_eliminate 0.84% : 0.000002s : 18: predicate.virtual_output_eliminate 0.37% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.54% : 0.000001s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000522 6 54.88% : 0.000287s : 3: func_graph_cloner_run.FuncGraphClonerGraph 45.12% : 0.000236s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.467646 192 0.00% : 0.000004s : 1: ForceFp32Comm 1.87% : 0.008722s : 1: add_attr 1.86% : 0.008704s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000077s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.03% : 0.000130s : 1: auto_monad 0.01% : 0.000036s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.17% : 0.000799s : 1: bootstrap 0.01% : 0.000043s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000023s : 1: control_data_broadcast_order 0.01% : 0.000028s : 1: convert_after_rewriter 0.01% : 0.000037s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.01% : 0.000024s : 1: environ_conv 0.01% : 0.000033s : 1: event_method 0.00% : 0.000007s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 0.00% : 0.000005s : 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 0.00% : 0.000008s : 1: label_micro_interleaved_index 0.10% : 0.000468s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.16% : 0.000752s : 1: mutable_eliminate 0.00% : 0.000009s : 1: offloading_packed_experts 0.00% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000029s : 1: opt.transform.mutable_eliminate 0.31% : 0.001462s : 78: opt.transform.opt_a 0.01% : 0.000051s : 1: opt.transform.opt_after_cconv 0.01% : 0.000039s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000199s : 28: opt.transform.opt_b 0.02% : 0.000086s : 2: opt.transform.opt_trans_graph 0.02% : 0.000071s : 4: opt.transform.symbol_engine_opt 0.73% : 0.003394s : 1: opt_a 0.03% : 0.000153s : 1: opt_after_cconv 0.12% : 0.000556s : 1: opt_after_jit_grad 0.07% : 0.000348s : 1: opt_b 1.35% : 0.006319s : 1: optimize 0.01% : 0.000028s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.01% : 0.000032s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000009s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.01% : 0.000028s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000009s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000007s : 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 0.01% : 0.000056s : 1: pre_auto_parallel 0.01% : 0.000034s : 1: py_interpret_to_execute 0.01% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.02% : 0.000079s : 1: remove_dup_value 0.09% : 0.000426s : 1: renormalize.infer 0.08% : 0.000375s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000086s : 1: rewriter_after_opt_a 0.02% : 0.000088s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000010s : 1: swap_dp_allreduce_reducescatter 0.04% : 0.000207s : 1: symbol_engine_optimizer 0.03% : 0.000117s : 1: tuple_transform 92.64% : 0.433206s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_lookahead1[0] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_lookahead1[0],max_mem:492.0M [WARNING] ME(163654:281473352806192,MainProcess):2026-01-29-17:42:05.518.949 [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 = 0.134065, [21] [bootstrap]: 0.00131276 [type_inference]: 0.00816127 [event_method]: 1.974e-05 [auto_monad]: 9.72e-05 [graph_reusing]: 4.82998e-06 [inline]: 3.26001e-06 [add_attr]: 0.113311, [1] [add_attr_with_inline]: 0.113292, [1] [Cycle 1]: 0.00011131, [2] [tag_attr]: 2.368e-05 [meta_addattr_fg_expand]: 4.12e-06 [parallel-infer-symbol]: 3.83999e-06 [pre_auto_parallel]: 4.946e-05 [insert-virtual-dataset]: 2.86e-06 [parallel-infer-symbol-second]: 8.39995e-07 [dataset_repeat_opt]: 2.29001e-06 [pipeline_split]: 1.54998e-06 [optimize]: 0.00961271, [53] [py_interpret_to_execute]: 0.00010325 [rewriter_before_opt_a]: 0.0001864 [opt_a]: 0.00483504, [2] [Cycle 1]: 0.00329555, [45] [expand_dump_flag]: 3.3e-06 [switch_simplify]: 3.525e-05 [loop_unroll]: 1.918e-05 [a_1]: 0.00053949 [with_stream_mark]: 7.436e-05 [recompute_prepare]: 2.256e-05 [updatestate_depend_eliminate]: 7.68999e-06 [updatestate_assign_eliminate]: 5.52001e-06 [updatestate_loads_eliminate]: 6.01e-06 [parameter_eliminate]: 2.30002e-06 [a_2]: 0.00014766 [accelerated_algorithm]: 1.278e-05 [shard]: 2.94999e-06 [meta_shard_fg_expand]: 3.31999e-06 [shard_inline]: 1.133e-05 [merge_send_recv]: 1.228e-05 [auto_parallel]: 1.344e-05 [parallel]: 0.000143 [flash_sp]: 1.845e-05 [merge_comm]: 8.84e-06 [allreduce_fusion]: 5.43002e-06 [matmul_add_comm_reduction]: 1.346e-05 [allreduce_slice_to_reducescatter]: 1.22e-06 [virtual_shard_identity]: 2.225e-05 [virtual_dataset]: 1.154e-05 [get_grad_eliminate_]: 1.079e-05 [virtual_output]: 1.104e-05 [merge_forward]: 6.59001e-06 [cell_reuse_recompute_pass]: 2.71999e-06 [offload_activation]: 1.412e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.597e-05 [merge_recompute_call_nodes]: 1.54e-06 [before_grad]: 1.755e-05 [set_forward_comm_id_for_comm_node_pass]: 7.09001e-06 [meta_fg_expand]: 4.72e-06 [flash_sp_send_recv_attached]: 3.63999e-06 [receive_attached]: 3.46001e-06 [after_resolve]: 2.513e-05 [a_after_grad]: 1.781e-05 [renormalize]: 0.00139304 [add_forward_monad_depend]: 1.062e-05 [auto_monad_grad]: 2.60002e-06 [auto_monad_eliminator]: 2.778e-05 [cse]: 6.334e-05 [a_3]: 9.638e-05 [Cycle 2]: 0.00152088, [45] [expand_dump_flag]: 3.27997e-06 [switch_simplify]: 8.157e-05 [loop_unroll]: 1.339e-05 [a_1]: 0.00027371 [with_stream_mark]: 2.691e-05 [recompute_prepare]: 1.219e-05 [updatestate_depend_eliminate]: 6.55997e-06 [updatestate_assign_eliminate]: 5.32999e-06 [updatestate_loads_eliminate]: 5.49e-06 [parameter_eliminate]: 2.20002e-06 [a_2]: 0.00013586 [accelerated_algorithm]: 1.231e-05 [shard]: 2.93e-06 [meta_shard_fg_expand]: 4.47998e-06 [shard_inline]: 1.074e-05 [merge_send_recv]: 1.163e-05 [auto_parallel]: 1.217e-05 [parallel]: 9.76e-06 [flash_sp]: 4.1e-06 [merge_comm]: 5.86e-06 [allreduce_fusion]: 4.93001e-06 [matmul_add_comm_reduction]: 1.267e-05 [allreduce_slice_to_reducescatter]: 8.60018e-07 [virtual_shard_identity]: 1.422e-05 [virtual_dataset]: 1.141e-05 [get_grad_eliminate_]: 1.12e-05 [virtual_output]: 1.165e-05 [merge_forward]: 6.11998e-06 [cell_reuse_recompute_pass]: 3.7e-06 [offload_activation]: 1.341e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.779e-05 [merge_recompute_call_nodes]: 1.62001e-06 [before_grad]: 1.667e-05 [set_forward_comm_id_for_comm_node_pass]: 5.83002e-06 [meta_fg_expand]: 4.60999e-06 [flash_sp_send_recv_attached]: 2.09e-06 [receive_attached]: 3.08998e-06 [after_resolve]: 2.483e-05 [a_after_grad]: 1.752e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.99001e-06 [auto_monad_grad]: 2.41e-06 [auto_monad_eliminator]: 0.00021817 [cse]: 7.895e-05 [a_3]: 8.291e-05 [py_interpret_to_execute_after_opt_a]: 2.873e-05 [slice_cell_reuse_recomputed_activation]: 2.71999e-06 [rewriter_after_opt_a]: 0.00016222 [convert_after_rewriter]: 4.947e-05 [order_py_execute_after_rewriter]: 8.45001e-06 [mutable_eliminate]: 0.00102472 [opt_b]: 0.00050041, [1] [Cycle 1]: 0.00045833, [7] [b_1]: 0.00023321 [b_2]: 1.295e-05 [updatestate_depend_eliminate]: 1.558e-05 [updatestate_assign_eliminate]: 5.09e-06 [updatestate_loads_eliminate]: 4.89003e-06 [renormalize]: 1.07e-06 [cse]: 0.00013396 [optimize_parallel_all_gather_comm]: 7.9e-05 [overlap_param_gather]: 5.47999e-06 [cconv]: 4.409e-05 [loop_unroll]: 0.00077542 [opt_after_cconv]: 0.00030929, [1] [Cycle 1]: 0.00029846, [7] [c_1]: 0.00013792 [parameter_eliminate]: 7.11999e-06 [updatestate_depend_eliminate]: 1.36e-05 [updatestate_assign_eliminate]: 4.82998e-06 [updatestate_loads_eliminate]: 4.68001e-06 [cse]: 7.453e-05 [renormalize]: 1.13001e-06 [remove_dup_value]: 7.844e-05 [tuple_transform]: 0.0001412, [1] [Cycle 1]: 0.00013382, [4] [d_1]: 9.526e-05 [none_parameter_eliminate]: 2.56e-06 [renormalize]: 3.9002e-07 [switch_simplify]: 1.199e-05 [partial_unused_args_eliminate]: 2.51e-06 [add_recomputation]: 0.00013337 [cse_after_recomputation]: 4.451e-05, [1] [Cycle 1]: 3.791e-05, [1] [cse]: 3.078e-05 [environ_conv]: 1.021e-05 [swap_dp_allreduce_reducescatter]: 8.05e-06 [bias_add_comm_swap]: 2.439e-05 [label_micro_interleaved_index]: 8.54e-06 [label_fine_grained_interleaved_index]: 3.08e-06 [merge_cast_opt]: 1.72999e-06 [slice_recompute_activation]: 2.24001e-06 [micro_interleaved_order_control]: 2.74999e-06 [assign_add_opt]: 1.50001e-06 [ForceFp32Comm]: 1.30001e-06 [remove_cast_before_assign_add]: 1.15001e-06 [full_micro_interleaved_order_control]: 2.66e-06 [reorder_send_recv_between_fp_bp]: 3.02002e-06 [comm_op_add_attrs]: 1.42999e-06 [add_comm_op_reuse_tag]: 1.27e-06 [interleave_split_concat_branches]: 1.38002e-06 [interleave_parallel_branches]: 1.72001e-06 [overlap_opt_shard_in_pipeline]: 3.748e-05 [overlap_opt_shard_grad_in_pipeline]: 1.87999e-06 [control_data_broadcast_order]: 2.284e-05 [grouped_pairwise_exchange_alltoall]: 1.74e-06 [offloading_packed_experts]: 5.26998e-06 [overlap_recompute_and_grad_model_parallel]: 6.51e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.80001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.54e-06 [overlap_recompute_comm]: 2.73998e-06 [overlap_grad_ring_attention]: 5.31998e-06 [overlap_grad_flash_sp]: 8.24e-05 [begin_end_overlap_inline]: 9.00007e-07 [split_matmul_comm_elemetwise]: 2.91e-06 [split_layernorm_comm]: 1.78002e-06 [handle_group_info]: 1.03001e-06 [symbol_engine_optimizer]: 0.00041928, [1] [Cycle 1]: 0.00041146, [6] [build]: 0.00023315 [elim_shapecalc]: 3.109e-05 [elim_not_effective]: 5.374e-05 [opt_reshape]: 1.379e-05 [fold_const_symbol]: 2.275e-05 [renormalize]: 3.50003e-07 [detach_backward]: 3.01001e-06 [pipeline_parallel_scheduler]: 1.38002e-06 [auto_monad_reorder]: 4.076e-05 [get_jit_bprop_graph]: 2.32999e-06 [rewriter_after_jit_bprop_graph]: 6.13998e-06 [opt_after_jit_grad]: 0.00106178 [validate]: 0.00013745 Sums bootstrap : 0.001313s : 6.86% type_inference : 0.008161s : 42.65% event_method : 0.000020s : 0.10% auto_monad : 0.000097s : 0.51% graph_reusing : 0.000005s : 0.03% inline : 0.000003s : 0.02% add_attr.add_attr_with_inline.tag_attr : 0.000024s : 0.12% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.02% parallel-infer-symbol : 0.000004s : 0.02% pre_auto_parallel : 0.000049s : 0.26% insert-virtual-dataset : 0.000003s : 0.01% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.01% pipeline_split : 0.000002s : 0.01% optimize.py_interpret_to_execute : 0.000103s : 0.54% optimize.rewriter_before_opt_a : 0.000186s : 0.97% optimize.opt_a.expand_dump_flag : 0.000007s : 0.03% optimize.opt_a.switch_simplify : 0.000117s : 0.61% optimize.opt_a.loop_unroll : 0.000033s : 0.17% optimize.opt_a.a_1 : 0.000813s : 4.25% optimize.opt_a.with_stream_mark : 0.000101s : 0.53% optimize.opt_a.recompute_prepare : 0.000035s : 0.18% optimize.opt_a.updatestate_depend_eliminate : 0.000014s : 0.07% optimize.opt_a.updatestate_assign_eliminate : 0.000011s : 0.06% optimize.opt_a.updatestate_loads_eliminate : 0.000012s : 0.06% optimize.opt_a.parameter_eliminate : 0.000005s : 0.02% optimize.opt_a.a_2 : 0.000284s : 1.48% optimize.opt_a.accelerated_algorithm : 0.000025s : 0.13% optimize.opt_a.shard : 0.000006s : 0.03% optimize.opt_a.meta_shard_fg_expand : 0.000008s : 0.04% optimize.opt_a.shard_inline : 0.000022s : 0.12% optimize.opt_a.merge_send_recv : 0.000024s : 0.12% optimize.opt_a.auto_parallel : 0.000026s : 0.13% optimize.opt_a.parallel : 0.000153s : 0.80% optimize.opt_a.flash_sp : 0.000023s : 0.12% optimize.opt_a.merge_comm : 0.000015s : 0.08% optimize.opt_a.allreduce_fusion : 0.000010s : 0.05% optimize.opt_a.matmul_add_comm_reduction : 0.000026s : 0.14% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.01% optimize.opt_a.virtual_shard_identity : 0.000036s : 0.19% optimize.opt_a.virtual_dataset : 0.000023s : 0.12% optimize.opt_a.get_grad_eliminate_ : 0.000022s : 0.11% optimize.opt_a.virtual_output : 0.000023s : 0.12% optimize.opt_a.merge_forward : 0.000013s : 0.07% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.03% optimize.opt_a.offload_activation : 0.000028s : 0.14% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000054s : 0.28% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.02% optimize.opt_a.before_grad : 0.000034s : 0.18% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000013s : 0.07% optimize.opt_a.meta_fg_expand : 0.000009s : 0.05% optimize.opt_a.flash_sp_send_recv_attached : 0.000006s : 0.03% optimize.opt_a.receive_attached : 0.000007s : 0.03% optimize.opt_a.after_resolve : 0.000050s : 0.26% optimize.opt_a.a_after_grad : 0.000035s : 0.18% optimize.opt_a.renormalize : 0.001393s : 7.28% optimize.opt_a.add_forward_monad_depend : 0.000014s : 0.07% optimize.opt_a.auto_monad_grad : 0.000005s : 0.03% optimize.opt_a.auto_monad_eliminator : 0.000246s : 1.29% optimize.opt_a.cse : 0.000142s : 0.74% optimize.opt_a.a_3 : 0.000179s : 0.94% optimize.py_interpret_to_execute_after_opt_a : 0.000029s : 0.15% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.01% optimize.rewriter_after_opt_a : 0.000162s : 0.85% optimize.convert_after_rewriter : 0.000049s : 0.26% optimize.order_py_execute_after_rewriter : 0.000008s : 0.04% optimize.mutable_eliminate : 0.001025s : 5.36% optimize.opt_b.b_1 : 0.000233s : 1.22% optimize.opt_b.b_2 : 0.000013s : 0.07% optimize.opt_b.updatestate_depend_eliminate : 0.000016s : 0.08% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.03% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.03% optimize.opt_b.renormalize : 0.000001s : 0.01% optimize.opt_b.cse : 0.000134s : 0.70% optimize.optimize_parallel_all_gather_comm : 0.000079s : 0.41% optimize.overlap_param_gather : 0.000005s : 0.03% optimize.cconv : 0.000044s : 0.23% optimize.loop_unroll : 0.000775s : 4.05% optimize.opt_after_cconv.c_1 : 0.000138s : 0.72% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.04% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.07% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.03% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.02% optimize.opt_after_cconv.cse : 0.000075s : 0.39% optimize.opt_after_cconv.renormalize : 0.000001s : 0.01% optimize.remove_dup_value : 0.000078s : 0.41% optimize.tuple_transform.d_1 : 0.000095s : 0.50% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.01% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000012s : 0.06% optimize.partial_unused_args_eliminate : 0.000003s : 0.01% optimize.add_recomputation : 0.000133s : 0.70% optimize.cse_after_recomputation.cse : 0.000031s : 0.16% optimize.environ_conv : 0.000010s : 0.05% optimize.swap_dp_allreduce_reducescatter : 0.000008s : 0.04% optimize.bias_add_comm_swap : 0.000024s : 0.13% optimize.label_micro_interleaved_index : 0.000009s : 0.04% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.02% optimize.merge_cast_opt : 0.000002s : 0.01% optimize.slice_recompute_activation : 0.000002s : 0.01% optimize.micro_interleaved_order_control : 0.000003s : 0.01% optimize.assign_add_opt : 0.000002s : 0.01% optimize.ForceFp32Comm : 0.000001s : 0.01% optimize.remove_cast_before_assign_add : 0.000001s : 0.01% optimize.full_micro_interleaved_order_control : 0.000003s : 0.01% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.02% optimize.comm_op_add_attrs : 0.000001s : 0.01% optimize.add_comm_op_reuse_tag : 0.000001s : 0.01% optimize.interleave_split_concat_branches : 0.000001s : 0.01% optimize.interleave_parallel_branches : 0.000002s : 0.01% optimize.overlap_opt_shard_in_pipeline : 0.000037s : 0.20% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.01% optimize.control_data_broadcast_order : 0.000023s : 0.12% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.01% optimize.offloading_packed_experts : 0.000005s : 0.03% optimize.overlap_recompute_and_grad_model_parallel : 0.000007s : 0.03% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000002s : 0.01% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.01% optimize.overlap_recompute_comm : 0.000003s : 0.01% optimize.overlap_grad_ring_attention : 0.000005s : 0.03% optimize.overlap_grad_flash_sp : 0.000082s : 0.43% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.02% optimize.split_layernorm_comm : 0.000002s : 0.01% optimize.handle_group_info : 0.000001s : 0.01% optimize.symbol_engine_optimizer.build : 0.000233s : 1.22% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000031s : 0.16% optimize.symbol_engine_optimizer.elim_not_effective : 0.000054s : 0.28% optimize.symbol_engine_optimizer.opt_reshape : 0.000014s : 0.07% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000023s : 0.12% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.02% pipeline_parallel_scheduler : 0.000001s : 0.01% auto_monad_reorder : 0.000041s : 0.21% get_jit_bprop_graph : 0.000002s : 0.01% rewriter_after_jit_bprop_graph : 0.000006s : 0.03% opt_after_jit_grad : 0.001062s : 5.55% validate : 0.000137s : 0.72% Time group info: ------[substitution.] 0.000231 36 13.12% : 0.000030s : 2: substitution.elim_not_effective 3.99% : 0.000009s : 2: substitution.fold_const_symbol 3.67% : 0.000008s : 9: substitution.graph_param_transform 69.45% : 0.000160s : 1: substitution.inline 2.08% : 0.000005s : 4: substitution.j_node_and_user_rematch 2.75% : 0.000006s : 4: substitution.remove_not_recompute_node 4.94% : 0.000011s : 14: substitution.replace_old_param ------[type_inference.] 0.008039 2 90.05% : 0.007239s : 1: type_inference.infer 9.95% : 0.000800s : 1: type_inference.specialize ------[replace.] 0.000025 1 100.00% : 0.000025s : 1: replace.inline ------[match.] 0.000158 1 100.00% : 0.000158s : 1: match.inline ------[predicate.] 0.000325 2107 0.75% : 0.000002s : 19: predicate.accumulaten_eliminater 1.22% : 0.000004s : 9: predicate.ad_related_special_op_eliminate 0.57% : 0.000002s : 18: predicate.addn_check_dump 0.62% : 0.000002s : 19: predicate.addn_zero_filter 0.56% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 2.00% : 0.000006s : 37: predicate.arithmetic_simplify 0.63% : 0.000002s : 19: predicate.cast_eliminate 0.61% : 0.000002s : 18: predicate.check_bprop_eliminate 0.59% : 0.000002s : 18: predicate.compare_switch_simplify 0.23% : 0.000001s : 9: predicate.const_output_eliminate 0.65% : 0.000002s : 18: predicate.depend_value_elim 0.74% : 0.000002s : 19: predicate.dict_get_item_const_eliminator 0.73% : 0.000002s : 19: predicate.dict_get_item_eliminator 0.71% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.28% : 0.000004s : 18: predicate.dumpgradient_eliminate 0.46% : 0.000002s : 9: predicate.elim_not_effective 0.63% : 0.000002s : 9: predicate.elim_shapecalc_of_broadcastargs 1.03% : 0.000003s : 28: predicate.environ_add_const_eliminate 0.86% : 0.000003s : 28: predicate.environ_get_add_eliminate 0.84% : 0.000003s : 28: predicate.environ_get_depend_swap 1.50% : 0.000005s : 46: predicate.environ_get_eliminate 0.88% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.61% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.18% : 0.000004s : 20: predicate.float_depend_g_call 0.60% : 0.000002s : 18: predicate.float_environ_get_switch 0.88% : 0.000003s : 27: predicate.float_tuple_getitem_switch 0.21% : 0.000001s : 9: predicate.fold_const_symbol 0.72% : 0.000002s : 18: predicate.get_grad_eliminate 0.32% : 0.000001s : 9: predicate.graph_param_transform 0.55% : 0.000002s : 18: predicate.incorporate_call 0.52% : 0.000002s : 18: predicate.incorporate_call_switch 4.48% : 0.000015s : 93: predicate.inline 0.94% : 0.000003s : 18: predicate.inline_without_move 0.40% : 0.000001s : 18: predicate.j_node_and_user_rematch 0.95% : 0.000003s : 18: predicate.less_batch_normalization 1.51% : 0.000005s : 37: predicate.list_to_tuple_eliminator_ 1.80% : 0.000006s : 56: predicate.load_eliminater 1.35% : 0.000004s : 9: predicate.loop_unroll_after_grad 1.00% : 0.000003s : 28: predicate.loop_unroll_before_grad 16.74% : 0.000054s : 37: predicate.make_slice_get_slice_eliminator 0.61% : 0.000002s : 18: predicate.merge_addn 0.64% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.59% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.56% : 0.000002s : 19: predicate.minmaximum_grad 1.65% : 0.000005s : 9: predicate.mutable_eliminate 0.44% : 0.000001s : 9: predicate.opt_reshape 0.40% : 0.000001s : 9: predicate.parallel_virtual_node 0.77% : 0.000003s : 20: predicate.partial_defer_inline 0.99% : 0.000003s : 28: predicate.partial_eliminate 0.64% : 0.000002s : 19: predicate.print_const_string_wrapper 0.66% : 0.000002s : 18: predicate.reduce_all_const_elim 0.86% : 0.000003s : 19: predicate.reduce_eliminate 1.92% : 0.000006s : 56: predicate.redundant_stop_gradient_eliminater 0.70% : 0.000002s : 18: predicate.remove_not_recompute_node 1.33% : 0.000004s : 37: predicate.replace_applicator 0.59% : 0.000002s : 18: predicate.replace_old_param 0.32% : 0.000001s : 9: predicate.reset_defer_inline 0.67% : 0.000002s : 19: predicate.reshape_eliminate 0.70% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.40% : 0.000001s : 9: predicate.row_tensor_eliminate 1.29% : 0.000004s : 18: predicate.same_eliminate 0.50% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.17% : 0.000004s : 18: predicate.shard_identity_eliminate 0.77% : 0.000003s : 18: predicate.special_op_eliminate 0.80% : 0.000003s : 18: predicate.specialize_transform 1.16% : 0.000004s : 18: predicate.split_environ_get_set_with_tuple_value 0.91% : 0.000003s : 18: predicate.stack_unstack_eliminate 0.46% : 0.000002s : 9: predicate.switch_call_monad_eliminater 0.68% : 0.000002s : 20: predicate.switch_defer_inline 1.24% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.11% : 0.000010s : 75: predicate.switch_simplify 0.66% : 0.000002s : 19: predicate.tile_eliminate 0.63% : 0.000002s : 19: predicate.transpose_eliminate 1.37% : 0.000004s : 37: predicate.tuple_list_convert_item_index_to_positive 1.36% : 0.000004s : 37: predicate.tuple_list_get_item_const_eliminator 1.31% : 0.000004s : 37: predicate.tuple_list_get_item_depend_reorder 2.49% : 0.000008s : 55: predicate.tuple_list_get_item_eliminator 1.22% : 0.000004s : 37: predicate.tuple_list_get_set_item_eliminator 2.04% : 0.000007s : 55: predicate.tuple_list_set_item_eliminator 1.34% : 0.000004s : 37: predicate.tuple_to_list_eliminator_ 1.79% : 0.000006s : 56: predicate.updatestate_pure_node_eliminater 2.58% : 0.000008s : 74: predicate.updatestate_useless_node_eliminater 0.43% : 0.000001s : 9: predicate.value_based_eliminate 0.89% : 0.000003s : 18: predicate.virtual_dataset_eliminate 0.69% : 0.000002s : 18: predicate.virtual_output_eliminate 0.39% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.41% : 0.000001s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000792 6 47.29% : 0.000375s : 3: func_graph_cloner_run.FuncGraphClonerGraph 52.71% : 0.000417s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.260456 192 0.00% : 0.000004s : 1: ForceFp32Comm 43.51% : 0.113318s : 1: add_attr 43.50% : 0.113297s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.05% : 0.000141s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.04% : 0.000105s : 1: auto_monad 0.02% : 0.000046s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: begin_end_overlap_inline 0.01% : 0.000029s : 1: bias_add_comm_swap 0.52% : 0.001354s : 1: bootstrap 0.02% : 0.000049s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.01% : 0.000027s : 1: control_data_broadcast_order 0.02% : 0.000055s : 1: convert_after_rewriter 0.02% : 0.000048s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.01% : 0.000014s : 1: environ_conv 0.01% : 0.000027s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 0.00% : 0.000006s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000008s : 1: inline 0.00% : 0.000010s : 1: insert-virtual-dataset 0.00% : 0.000005s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000008s : 1: label_fine_grained_interleaved_index 0.00% : 0.000012s : 1: label_micro_interleaved_index 0.30% : 0.000792s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000007s : 1: micro_interleaved_order_control 0.40% : 0.001045s : 1: mutable_eliminate 0.00% : 0.000009s : 1: offloading_packed_experts 0.01% : 0.000036s : 1: opt.transform.loop_unroll_optimizer 0.02% : 0.000040s : 1: opt.transform.mutable_eliminate 0.64% : 0.001667s : 78: opt.transform.opt_a 0.05% : 0.000136s : 1: opt.transform.opt_after_cconv 0.02% : 0.000060s : 1: opt.transform.opt_after_jit_grad 0.08% : 0.000211s : 28: opt.transform.opt_b 0.04% : 0.000104s : 2: opt.transform.opt_trans_graph 0.04% : 0.000113s : 4: opt.transform.symbol_engine_opt 1.86% : 0.004844s : 1: opt_a 0.12% : 0.000314s : 1: opt_after_cconv 0.42% : 0.001084s : 1: opt_after_jit_grad 0.20% : 0.000511s : 1: opt_b 3.69% : 0.009620s : 1: optimize 0.03% : 0.000086s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.06% : 0.000153s : 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% : 0.000008s : 1: overlap_opt_shard_grad_in_pipeline 0.02% : 0.000043s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000005s : 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% : 0.000012s : 1: parallel-infer-symbol 0.00% : 0.000007s : 1: parallel-infer-symbol-second 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000008s : 1: pipeline_split 0.02% : 0.000054s : 1: pre_auto_parallel 0.04% : 0.000112s : 1: py_interpret_to_execute 0.01% : 0.000034s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.03% : 0.000084s : 1: remove_dup_value 0.29% : 0.000761s : 1: renormalize.infer 0.24% : 0.000614s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.07% : 0.000171s : 1: rewriter_after_opt_a 0.08% : 0.000209s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.16% : 0.000424s : 1: symbol_engine_optimizer 0.06% : 0.000144s : 1: tuple_transform 3.14% : 0.008188s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_lookahead1[1] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_lookahead1[1],max_mem:492.0M =============================== 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 373.83s (0:06:13) ==================