==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/infer/ops/test_internal_ops, configfile: ../../../../../../../../sault/virtual_test/virtualenv_005/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_paged_attention.py [WARNING] ME(167157:281472908701488,MainProcess):2026-01-29-17:37:56.147.945 [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 = 0.305842, [21] [bootstrap]: 0.00074543 [type_inference]: 0.202342 [event_method]: 1.657e-05 [auto_monad]: 9.09e-05 [graph_reusing]: 5.12e-06 [inline]: 2.89999e-06 [add_attr]: 0.095519, [1] [add_attr_with_inline]: 0.0955036, [1] [Cycle 1]: 9.257e-05, [2] [tag_attr]: 1.928e-05 [meta_addattr_fg_expand]: 3.43e-06 [parallel-infer-symbol]: 3.53e-06 [pre_auto_parallel]: 4.441e-05 [insert-virtual-dataset]: 2.50002e-06 [parallel-infer-symbol-second]: 7.89994e-07 [dataset_repeat_opt]: 1.71e-06 [pipeline_split]: 1.84e-06 [optimize]: 0.00620569, [53] [py_interpret_to_execute]: 2.582e-05 [rewriter_before_opt_a]: 7.571e-05 [opt_a]: 0.00324565, [2] [Cycle 1]: 0.00212442, [45] [expand_dump_flag]: 2.86e-06 [switch_simplify]: 3.261e-05 [loop_unroll]: 1.883e-05 [a_1]: 0.00045224 [with_stream_mark]: 2.184e-05 [recompute_prepare]: 1.194e-05 [updatestate_depend_eliminate]: 5.83002e-06 [updatestate_assign_eliminate]: 4.79e-06 [updatestate_loads_eliminate]: 4.94998e-06 [parameter_eliminate]: 1.87001e-06 [a_2]: 0.00016716 [accelerated_algorithm]: 1.127e-05 [shard]: 2.31e-06 [meta_shard_fg_expand]: 1.97001e-06 [shard_inline]: 1.034e-05 [merge_send_recv]: 9.22999e-06 [auto_parallel]: 7.31001e-06 [parallel]: 5.305e-05 [flash_sp]: 1.156e-05 [merge_comm]: 5.69999e-06 [allreduce_fusion]: 4.79e-06 [matmul_add_comm_reduction]: 1.187e-05 [allreduce_slice_to_reducescatter]: 9.5999e-07 [virtual_shard_identity]: 1.318e-05 [virtual_dataset]: 1.129e-05 [get_grad_eliminate_]: 1.033e-05 [virtual_output]: 1.059e-05 [merge_forward]: 5.49e-06 [cell_reuse_recompute_pass]: 1.27999e-06 [offload_activation]: 1.21e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.055e-05 [merge_recompute_call_nodes]: 1.72999e-06 [before_grad]: 1.663e-05 [set_forward_comm_id_for_comm_node_pass]: 6.16998e-06 [meta_fg_expand]: 3.26001e-06 [flash_sp_send_recv_attached]: 2.98998e-06 [receive_attached]: 1.277e-05 [after_resolve]: 2.355e-05 [a_after_grad]: 1.752e-05 [renormalize]: 0.00063715 [add_forward_monad_depend]: 1.147e-05 [auto_monad_grad]: 2.27999e-06 [auto_monad_eliminator]: 1.862e-05 [cse]: 8.025e-05 [a_3]: 7.754e-05 [Cycle 2]: 0.0011069, [45] [expand_dump_flag]: 2.17001e-06 [switch_simplify]: 1.254e-05 [loop_unroll]: 1.361e-05 [a_1]: 0.00027417 [with_stream_mark]: 2.199e-05 [recompute_prepare]: 1.276e-05 [updatestate_depend_eliminate]: 5.76e-06 [updatestate_assign_eliminate]: 4.58999e-06 [updatestate_loads_eliminate]: 3.91999e-06 [parameter_eliminate]: 1.37999e-06 [a_2]: 0.00013517 [accelerated_algorithm]: 1.176e-05 [shard]: 2.13998e-06 [meta_shard_fg_expand]: 2.94001e-06 [shard_inline]: 1.014e-05 [merge_send_recv]: 9.16998e-06 [auto_parallel]: 9.36e-06 [parallel]: 8.30999e-06 [flash_sp]: 3.97e-06 [merge_comm]: 4.80001e-06 [allreduce_fusion]: 4.94e-06 [matmul_add_comm_reduction]: 9.00999e-06 [allreduce_slice_to_reducescatter]: 5.50004e-07 [virtual_shard_identity]: 1.319e-05 [virtual_dataset]: 1.022e-05 [get_grad_eliminate_]: 1.013e-05 [virtual_output]: 9.82999e-06 [merge_forward]: 6.16e-06 [cell_reuse_recompute_pass]: 1.72001e-06 [offload_activation]: 1.132e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.139e-05 [merge_recompute_call_nodes]: 1.35999e-06 [before_grad]: 1.432e-05 [set_forward_comm_id_for_comm_node_pass]: 5.24e-06 [meta_fg_expand]: 3.13998e-06 [flash_sp_send_recv_attached]: 1.69e-06 [receive_attached]: 1.92999e-06 [after_resolve]: 2.109e-05 [a_after_grad]: 1.719e-05 [renormalize]: 5.9983e-08 [add_forward_monad_depend]: 2.39999e-06 [auto_monad_grad]: 1.52999e-06 [auto_monad_eliminator]: 1.282e-05 [cse]: 3.865e-05 [a_3]: 6.984e-05 [py_interpret_to_execute_after_opt_a]: 2.117e-05 [slice_cell_reuse_recomputed_activation]: 2.22999e-06 [rewriter_after_opt_a]: 8.762e-05 [convert_after_rewriter]: 1.085e-05 [order_py_execute_after_rewriter]: 7.33999e-06 [mutable_eliminate]: 0.0006531 [opt_b]: 0.00037935, [1] [Cycle 1]: 0.00036944, [7] [b_1]: 0.00024922 [b_2]: 1.261e-05 [updatestate_depend_eliminate]: 1.105e-05 [updatestate_assign_eliminate]: 4.27e-06 [updatestate_loads_eliminate]: 4.29002e-06 [renormalize]: 4.60015e-07 [cse]: 4.575e-05 [optimize_parallel_all_gather_comm]: 2.369e-05 [overlap_param_gather]: 3.56001e-06 [cconv]: 3.626e-05 [loop_unroll]: 0.000509 [opt_after_cconv]: 0.00015895, [1] [Cycle 1]: 0.00015132, [7] [c_1]: 5.729e-05 [parameter_eliminate]: 5.68997e-06 [updatestate_depend_eliminate]: 8.70001e-06 [updatestate_assign_eliminate]: 4.13999e-06 [updatestate_loads_eliminate]: 3.57997e-06 [cse]: 3.797e-05 [renormalize]: 3.29979e-07 [remove_dup_value]: 6.303e-05 [tuple_transform]: 0.00016449, [1] [Cycle 1]: 0.00015959, [4] [d_1]: 0.00012015 [none_parameter_eliminate]: 2.16e-06 [renormalize]: 2.50002e-07 [switch_simplify]: 1.278e-05 [partial_unused_args_eliminate]: 2.21e-06 [add_recomputation]: 6.813e-05 [cse_after_recomputation]: 3.551e-05, [1] [Cycle 1]: 2.994e-05, [1] [cse]: 2.336e-05 [environ_conv]: 1.915e-05 [swap_dp_allreduce_reducescatter]: 6.81001e-06 [bias_add_comm_swap]: 3.86999e-06 [label_micro_interleaved_index]: 5.30001e-06 [label_fine_grained_interleaved_index]: 3.21001e-06 [merge_cast_opt]: 1.48002e-06 [slice_recompute_activation]: 2.16e-06 [micro_interleaved_order_control]: 2.62001e-06 [assign_add_opt]: 1.52001e-06 [ForceFp32Comm]: 8.79983e-07 [remove_cast_before_assign_add]: 1.22999e-06 [full_micro_interleaved_order_control]: 2.62001e-06 [reorder_send_recv_between_fp_bp]: 2.86999e-06 [comm_op_add_attrs]: 1.20001e-06 [add_comm_op_reuse_tag]: 1.40999e-06 [interleave_split_concat_branches]: 1.14e-06 [interleave_parallel_branches]: 1.05999e-06 [overlap_opt_shard_in_pipeline]: 2.134e-05 [overlap_opt_shard_grad_in_pipeline]: 1.83002e-06 [control_data_broadcast_order]: 1.923e-05 [grouped_pairwise_exchange_alltoall]: 1.69e-06 [offloading_packed_experts]: 5.16002e-06 [overlap_recompute_and_grad_model_parallel]: 5.84e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.22999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.46002e-06 [overlap_recompute_comm]: 3.04999e-06 [overlap_grad_ring_attention]: 5.35999e-06 [overlap_grad_flash_sp]: 3.624e-05 [begin_end_overlap_inline]: 5.40022e-07 [split_matmul_comm_elemetwise]: 2.26e-06 [split_layernorm_comm]: 1.82001e-06 [handle_group_info]: 9.80013e-07 [symbol_engine_optimizer]: 0.00020887, [1] [Cycle 1]: 0.0002035, [6] [build]: 9.116e-05 [elim_shapecalc]: 1.843e-05 [elim_not_effective]: 2.562e-05 [opt_reshape]: 1.19e-05 [fold_const_symbol]: 1.892e-05 [renormalize]: 1.69995e-07 [detach_backward]: 2.53e-06 [pipeline_parallel_scheduler]: 1.50999e-06 [auto_monad_reorder]: 3.155e-05 [get_jit_bprop_graph]: 1.92001e-06 [rewriter_after_jit_bprop_graph]: 4.92999e-06 [opt_after_jit_grad]: 0.00057994 [validate]: 6.7e-05 Sums bootstrap : 0.000745s : 0.36% type_inference : 0.202342s : 96.71% event_method : 0.000017s : 0.01% auto_monad : 0.000091s : 0.04% graph_reusing : 0.000005s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000019s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000003s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000044s : 0.02% 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 : 0.01% optimize.rewriter_before_opt_a : 0.000076s : 0.04% optimize.opt_a.expand_dump_flag : 0.000005s : 0.00% optimize.opt_a.switch_simplify : 0.000045s : 0.02% optimize.opt_a.loop_unroll : 0.000032s : 0.02% optimize.opt_a.a_1 : 0.000726s : 0.35% optimize.opt_a.with_stream_mark : 0.000044s : 0.02% optimize.opt_a.recompute_prepare : 0.000025s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000012s : 0.01% 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 : 0.000302s : 0.14% optimize.opt_a.accelerated_algorithm : 0.000023s : 0.01% optimize.opt_a.shard : 0.000004s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000005s : 0.00% optimize.opt_a.shard_inline : 0.000020s : 0.01% optimize.opt_a.merge_send_recv : 0.000018s : 0.01% optimize.opt_a.auto_parallel : 0.000017s : 0.01% optimize.opt_a.parallel : 0.000061s : 0.03% optimize.opt_a.flash_sp : 0.000016s : 0.01% optimize.opt_a.merge_comm : 0.000010s : 0.01% optimize.opt_a.allreduce_fusion : 0.000010s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000021s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000026s : 0.01% optimize.opt_a.virtual_dataset : 0.000022s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000020s : 0.01% optimize.opt_a.virtual_output : 0.000020s : 0.01% optimize.opt_a.merge_forward : 0.000012s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% optimize.opt_a.offload_activation : 0.000023s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000072s : 0.03% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000031s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000011s : 0.01% optimize.opt_a.meta_fg_expand : 0.000006s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000005s : 0.00% optimize.opt_a.receive_attached : 0.000015s : 0.01% optimize.opt_a.after_resolve : 0.000045s : 0.02% optimize.opt_a.a_after_grad : 0.000035s : 0.02% optimize.opt_a.renormalize : 0.000637s : 0.30% optimize.opt_a.add_forward_monad_depend : 0.000014s : 0.01% optimize.opt_a.auto_monad_grad : 0.000004s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000031s : 0.02% optimize.opt_a.cse : 0.000119s : 0.06% optimize.opt_a.a_3 : 0.000147s : 0.07% optimize.py_interpret_to_execute_after_opt_a : 0.000021s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000088s : 0.04% optimize.convert_after_rewriter : 0.000011s : 0.01% optimize.order_py_execute_after_rewriter : 0.000007s : 0.00% optimize.mutable_eliminate : 0.000653s : 0.31% optimize.opt_b.b_1 : 0.000249s : 0.12% optimize.opt_b.b_2 : 0.000013s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000011s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000004s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000004s : 0.00% optimize.opt_b.renormalize : 0.000000s : 0.00% optimize.opt_b.cse : 0.000046s : 0.02% optimize.optimize_parallel_all_gather_comm : 0.000024s : 0.01% optimize.overlap_param_gather : 0.000004s : 0.00% optimize.cconv : 0.000036s : 0.02% optimize.loop_unroll : 0.000509s : 0.24% optimize.opt_after_cconv.c_1 : 0.000057s : 0.03% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 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 : 0.000038s : 0.02% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000063s : 0.03% optimize.tuple_transform.d_1 : 0.000120s : 0.06% 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 : 0.000068s : 0.03% optimize.cse_after_recomputation.cse : 0.000023s : 0.01% optimize.environ_conv : 0.000019s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000007s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000021s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000019s : 0.01% 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 : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000005s : 0.00% optimize.overlap_grad_flash_sp : 0.000036s : 0.02% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000091s : 0.04% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000018s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000012s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000032s : 0.02% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000580s : 0.28% validate : 0.000067s : 0.03% Time group info: ------[substitution.] 0.000191 39 5.14% : 0.000010s : 2: substitution.elim_not_effective 3.35% : 0.000006s : 2: substitution.fold_const_symbol 11.72% : 0.000022s : 10: substitution.graph_param_transform 53.42% : 0.000102s : 1: substitution.inline 2.27% : 0.000004s : 4: substitution.j_node_and_user_rematch 19.08% : 0.000036s : 4: substitution.remove_not_recompute_node 5.02% : 0.000010s : 16: substitution.replace_old_param ------[type_inference.] 0.202245 2 99.74% : 0.201714s : 1: type_inference.infer 0.26% : 0.000531s : 1: type_inference.specialize ------[replace.] 0.000017 1 100.00% : 0.000017s : 1: replace.inline ------[match.] 0.000101 1 100.00% : 0.000101s : 1: match.inline ------[predicate.] 0.000249 2335 0.76% : 0.000002s : 21: predicate.accumulaten_eliminater 0.91% : 0.000002s : 10: predicate.ad_related_special_op_eliminate 0.78% : 0.000002s : 20: predicate.addn_check_dump 0.80% : 0.000002s : 21: predicate.addn_zero_filter 0.71% : 0.000002s : 21: predicate.adjust_all_reduce_mul_add 1.89% : 0.000005s : 41: predicate.arithmetic_simplify 0.78% : 0.000002s : 21: predicate.cast_eliminate 0.81% : 0.000002s : 20: predicate.check_bprop_eliminate 0.71% : 0.000002s : 20: predicate.compare_switch_simplify 0.45% : 0.000001s : 10: predicate.const_output_eliminate 0.77% : 0.000002s : 20: predicate.depend_value_elim 0.83% : 0.000002s : 21: predicate.dict_get_item_const_eliminator 1.01% : 0.000003s : 21: predicate.dict_get_item_eliminator 0.77% : 0.000002s : 21: predicate.dict_set_item_eliminator 1.42% : 0.000004s : 20: predicate.dumpgradient_eliminate 0.42% : 0.000001s : 10: predicate.elim_not_effective 0.97% : 0.000002s : 10: predicate.elim_shapecalc_of_broadcastargs 1.12% : 0.000003s : 31: predicate.environ_add_const_eliminate 1.07% : 0.000003s : 31: predicate.environ_get_add_eliminate 1.06% : 0.000003s : 31: predicate.environ_get_depend_swap 1.93% : 0.000005s : 51: predicate.environ_get_eliminate 1.07% : 0.000003s : 31: predicate.environ_get_set_eliminate 0.79% : 0.000002s : 22: predicate.exchange_switch_depend_value 1.44% : 0.000004s : 22: predicate.float_depend_g_call 0.73% : 0.000002s : 20: predicate.float_environ_get_switch 1.09% : 0.000003s : 30: predicate.float_tuple_getitem_switch 0.32% : 0.000001s : 10: predicate.fold_const_symbol 0.83% : 0.000002s : 20: predicate.get_grad_eliminate 0.43% : 0.000001s : 10: predicate.graph_param_transform 0.85% : 0.000002s : 20: predicate.incorporate_call 0.69% : 0.000002s : 20: predicate.incorporate_call_switch 5.54% : 0.000014s : 103: predicate.inline 1.21% : 0.000003s : 20: predicate.inline_without_move 0.55% : 0.000001s : 20: predicate.j_node_and_user_rematch 0.91% : 0.000002s : 20: predicate.less_batch_normalization 1.67% : 0.000004s : 41: predicate.list_to_tuple_eliminator_ 2.41% : 0.000006s : 62: predicate.load_eliminater 1.24% : 0.000003s : 10: predicate.loop_unroll_after_grad 1.39% : 0.000003s : 31: predicate.loop_unroll_before_grad 1.86% : 0.000005s : 41: predicate.make_slice_get_slice_eliminator 0.82% : 0.000002s : 20: predicate.merge_addn 0.74% : 0.000002s : 20: predicate.micro_step_allgather_replace 0.75% : 0.000002s : 20: predicate.mini_step_allgather_replace 0.71% : 0.000002s : 21: predicate.minmaximum_grad 1.34% : 0.000003s : 10: predicate.mutable_eliminate 0.52% : 0.000001s : 10: predicate.opt_reshape 0.43% : 0.000001s : 10: predicate.parallel_virtual_node 1.01% : 0.000003s : 22: predicate.partial_defer_inline 1.32% : 0.000003s : 31: predicate.partial_eliminate 0.77% : 0.000002s : 21: predicate.print_const_string_wrapper 0.79% : 0.000002s : 20: predicate.reduce_all_const_elim 0.92% : 0.000002s : 21: predicate.reduce_eliminate 2.33% : 0.000006s : 62: predicate.redundant_stop_gradient_eliminater 0.83% : 0.000002s : 20: predicate.remove_not_recompute_node 1.58% : 0.000004s : 41: predicate.replace_applicator 0.75% : 0.000002s : 20: predicate.replace_old_param 0.59% : 0.000001s : 10: predicate.reset_defer_inline 0.75% : 0.000002s : 21: predicate.reshape_eliminate 0.77% : 0.000002s : 20: predicate.row_tensor_add_zeros_like 0.53% : 0.000001s : 10: predicate.row_tensor_eliminate 1.09% : 0.000003s : 20: predicate.same_eliminate 0.87% : 0.000002s : 20: predicate.set_cell_output_no_recompute 1.07% : 0.000003s : 20: predicate.shard_identity_eliminate 0.78% : 0.000002s : 20: predicate.special_op_eliminate 0.93% : 0.000002s : 20: predicate.specialize_transform 1.14% : 0.000003s : 20: predicate.split_environ_get_set_with_tuple_value 1.14% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.51% : 0.000001s : 10: predicate.switch_call_monad_eliminater 0.84% : 0.000002s : 22: predicate.switch_defer_inline 1.57% : 0.000004s : 42: predicate.switch_layer_defer_inline 3.63% : 0.000009s : 83: predicate.switch_simplify 0.77% : 0.000002s : 21: predicate.tile_eliminate 0.78% : 0.000002s : 21: predicate.transpose_eliminate 1.61% : 0.000004s : 41: predicate.tuple_list_convert_item_index_to_positive 1.52% : 0.000004s : 41: predicate.tuple_list_get_item_const_eliminator 1.50% : 0.000004s : 41: predicate.tuple_list_get_item_depend_reorder 3.21% : 0.000008s : 61: predicate.tuple_list_get_item_eliminator 1.49% : 0.000004s : 41: predicate.tuple_list_get_set_item_eliminator 2.35% : 0.000006s : 61: predicate.tuple_list_set_item_eliminator 1.57% : 0.000004s : 41: predicate.tuple_to_list_eliminator_ 2.15% : 0.000005s : 62: predicate.updatestate_pure_node_eliminater 3.09% : 0.000008s : 82: predicate.updatestate_useless_node_eliminater 0.47% : 0.000001s : 10: predicate.value_based_eliminate 0.88% : 0.000002s : 20: predicate.virtual_dataset_eliminate 0.84% : 0.000002s : 20: predicate.virtual_output_eliminate 0.40% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.56% : 0.000001s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000519 6 56.07% : 0.000291s : 3: func_graph_cloner_run.FuncGraphClonerGraph 43.93% : 0.000228s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.410062 192 0.00% : 0.000004s : 1: ForceFp32Comm 23.30% : 0.095525s : 1: add_attr 23.29% : 0.095508s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000073s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.02% : 0.000096s : 1: auto_monad 0.01% : 0.000036s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.19% : 0.000783s : 1: bootstrap 0.01% : 0.000041s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.01% : 0.000023s : 1: control_data_broadcast_order 0.00% : 0.000015s : 1: convert_after_rewriter 0.01% : 0.000039s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.01% : 0.000023s : 1: environ_conv 0.01% : 0.000024s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 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% : 0.000008s : 1: label_micro_interleaved_index 0.13% : 0.000520s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.16% : 0.000669s : 1: mutable_eliminate 0.00% : 0.000008s : 1: offloading_packed_experts 0.01% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000027s : 1: opt.transform.mutable_eliminate 0.36% : 0.001478s : 78: opt.transform.opt_a 0.01% : 0.000056s : 1: opt.transform.opt_after_cconv 0.01% : 0.000040s : 1: opt.transform.opt_after_jit_grad 0.05% : 0.000209s : 28: opt.transform.opt_b 0.03% : 0.000130s : 2: opt.transform.opt_trans_graph 0.02% : 0.000071s : 4: opt.transform.symbol_engine_opt 0.79% : 0.003249s : 1: opt_a 0.04% : 0.000162s : 1: opt_after_cconv 0.14% : 0.000590s : 1: opt_after_jit_grad 0.09% : 0.000383s : 1: opt_b 1.51% : 0.006211s : 1: optimize 0.01% : 0.000028s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.01% : 0.000040s : 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% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.01% : 0.000025s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 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% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000007s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000049s : 1: pre_auto_parallel 0.01% : 0.000030s : 1: py_interpret_to_execute 0.01% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.02% : 0.000067s : 1: remove_dup_value 0.07% : 0.000283s : 1: renormalize.infer 0.08% : 0.000346s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000097s : 1: rewriter_after_opt_a 0.02% : 0.000080s : 1: rewriter_before_opt_a 0.00% : 0.000005s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000010s : 1: swap_dp_allreduce_reducescatter 0.05% : 0.000212s : 1: symbol_engine_optimizer 0.04% : 0.000167s : 1: tuple_transform 49.35% : 0.202364s : 1: type_inference .[WARNING] PRE_ACT(167157,ffff84bcaf30,python3.9):2026-01-29-17:39:19.438.572 [mindspore/ccsrc/runtime/memory/mem_pool/abstract_dynamic_mem_pool.cc:1109] FreeIdleMemsByEagerFree] Eager free count : 1, free memory : 1582359040, real free : 1585446912, not free : 0. [hook] pytest_runtest_teardown:test_paged_attention_quant_pertoken[0] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_quant_pertoken[0],max_mem:1608.0M [WARNING] ME(167157:281472908701488,MainProcess):2026-01-29-17:39:20.736.689 [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 = 0.143005, [21] [bootstrap]: 0.00101104 [type_inference]: 0.0700519 [event_method]: 2.251e-05 [auto_monad]: 7.219e-05 [graph_reusing]: 5.31002e-06 [inline]: 3.23e-06 [add_attr]: 0.0589097, [1] [add_attr_with_inline]: 0.0588908, [1] [Cycle 1]: 9.511e-05, [2] [tag_attr]: 3.613e-05 [meta_addattr_fg_expand]: 1.004e-05 [parallel-infer-symbol]: 4.06001e-06 [pre_auto_parallel]: 3.677e-05 [insert-virtual-dataset]: 2.58e-06 [parallel-infer-symbol-second]: 6.60017e-07 [dataset_repeat_opt]: 2.43998e-06 [pipeline_split]: 1.84e-06 [optimize]: 0.0115162, [53] [py_interpret_to_execute]: 6.469e-05 [rewriter_before_opt_a]: 8.501e-05 [opt_a]: 0.00723474, [2] [Cycle 1]: 0.00515502, [45] [expand_dump_flag]: 3.28e-06 [switch_simplify]: 3.272e-05 [loop_unroll]: 1.974e-05 [a_1]: 0.00107342 [with_stream_mark]: 3.257e-05 [recompute_prepare]: 2.867e-05 [updatestate_depend_eliminate]: 6.81001e-06 [updatestate_assign_eliminate]: 5.32999e-06 [updatestate_loads_eliminate]: 5.10001e-06 [parameter_eliminate]: 3.13998e-06 [a_2]: 0.00022092 [accelerated_algorithm]: 2.594e-05 [shard]: 3.53999e-06 [meta_shard_fg_expand]: 3.4e-06 [shard_inline]: 1.353e-05 [merge_send_recv]: 1.291e-05 [auto_parallel]: 1.169e-05 [parallel]: 3.708e-05 [flash_sp]: 1.37e-05 [merge_comm]: 5.98002e-06 [allreduce_fusion]: 5.28002e-06 [matmul_add_comm_reduction]: 1.662e-05 [allreduce_slice_to_reducescatter]: 1.05999e-06 [virtual_shard_identity]: 2.627e-05 [virtual_dataset]: 2.112e-05 [get_grad_eliminate_]: 1.852e-05 [virtual_output]: 2.494e-05 [merge_forward]: 6.39001e-06 [cell_reuse_recompute_pass]: 2.01e-06 [offload_activation]: 1.739e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.383e-05 [merge_recompute_call_nodes]: 1.34e-06 [before_grad]: 2.75e-05 [set_forward_comm_id_for_comm_node_pass]: 5.76e-06 [meta_fg_expand]: 4.80999e-06 [flash_sp_send_recv_attached]: 2.88e-06 [receive_attached]: 3.05002e-06 [after_resolve]: 3.979e-05 [a_after_grad]: 3.706e-05 [renormalize]: 0.00260569 [add_forward_monad_depend]: 1.521e-05 [auto_monad_grad]: 3.23e-06 [auto_monad_eliminator]: 2.728e-05 [cse]: 8.823e-05 [a_3]: 0.00011065 [Cycle 2]: 0.00205591, [45] [expand_dump_flag]: 2.63e-06 [switch_simplify]: 2.558e-05 [loop_unroll]: 2.595e-05 [a_1]: 0.00051047 [with_stream_mark]: 2.806e-05 [recompute_prepare]: 2.707e-05 [updatestate_depend_eliminate]: 1.11e-05 [updatestate_assign_eliminate]: 5.24998e-06 [updatestate_loads_eliminate]: 4.72998e-06 [parameter_eliminate]: 2.61e-06 [a_2]: 0.00020348 [accelerated_algorithm]: 2.146e-05 [shard]: 3.13e-06 [meta_shard_fg_expand]: 2.86e-06 [shard_inline]: 1.538e-05 [merge_send_recv]: 1.109e-05 [auto_parallel]: 1.102e-05 [parallel]: 9.47001e-06 [flash_sp]: 4.05e-06 [merge_comm]: 5.32001e-06 [allreduce_fusion]: 8.37e-06 [matmul_add_comm_reduction]: 1.23e-05 [allreduce_slice_to_reducescatter]: 9.00007e-07 [virtual_shard_identity]: 1.753e-05 [virtual_dataset]: 2.034e-05 [get_grad_eliminate_]: 1.842e-05 [virtual_output]: 2.564e-05 [merge_forward]: 6.73998e-06 [cell_reuse_recompute_pass]: 3.4e-06 [offload_activation]: 1.909e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.068e-05 [merge_recompute_call_nodes]: 1.45001e-06 [before_grad]: 2.022e-05 [set_forward_comm_id_for_comm_node_pass]: 5.69999e-06 [meta_fg_expand]: 1.975e-05 [flash_sp_send_recv_attached]: 1.84998e-06 [receive_attached]: 6.10002e-06 [after_resolve]: 0.00010509 [a_after_grad]: 3.494e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 4.21001e-06 [auto_monad_grad]: 2.32001e-06 [auto_monad_eliminator]: 1.635e-05 [cse]: 0.00011459 [a_3]: 0.00022285 [py_interpret_to_execute_after_opt_a]: 3.43e-05 [slice_cell_reuse_recomputed_activation]: 2.76e-06 [rewriter_after_opt_a]: 7.818e-05 [convert_after_rewriter]: 9.29e-06 [order_py_execute_after_rewriter]: 8.02e-06 [mutable_eliminate]: 0.00098927 [opt_b]: 0.00064134, [1] [Cycle 1]: 0.0006236, [7] [b_1]: 0.00040389 [b_2]: 1.921e-05 [updatestate_depend_eliminate]: 1.237e-05 [updatestate_assign_eliminate]: 5.54e-06 [updatestate_loads_eliminate]: 4.74e-06 [renormalize]: 1.27e-06 [cse]: 0.00011123 [optimize_parallel_all_gather_comm]: 3.2e-05 [overlap_param_gather]: 5.07e-06 [cconv]: 4.348e-05 [loop_unroll]: 0.00068568 [opt_after_cconv]: 0.00025444, [1] [Cycle 1]: 0.00024527, [7] [c_1]: 8.654e-05 [parameter_eliminate]: 6.46999e-06 [updatestate_depend_eliminate]: 9.49e-06 [updatestate_assign_eliminate]: 4.25999e-06 [updatestate_loads_eliminate]: 7.83001e-06 [cse]: 7.74e-05 [renormalize]: 7.09988e-07 [remove_dup_value]: 8.618e-05 [tuple_transform]: 0.0002165, [1] [Cycle 1]: 0.00020728, [4] [d_1]: 0.00015819 [none_parameter_eliminate]: 2.86e-06 [renormalize]: 1.50001e-07 [switch_simplify]: 1.364e-05 [partial_unused_args_eliminate]: 2.24001e-06 [add_recomputation]: 9.405e-05 [cse_after_recomputation]: 5.489e-05, [1] [Cycle 1]: 4.998e-05, [1] [cse]: 3.935e-05 [environ_conv]: 9.31e-06 [swap_dp_allreduce_reducescatter]: 1.094e-05 [bias_add_comm_swap]: 3.29001e-06 [label_micro_interleaved_index]: 6.54999e-06 [label_fine_grained_interleaved_index]: 3.14999e-06 [merge_cast_opt]: 1.82999e-06 [slice_recompute_activation]: 2.16998e-06 [micro_interleaved_order_control]: 3.21001e-06 [assign_add_opt]: 1.44e-06 [ForceFp32Comm]: 1.55999e-06 [remove_cast_before_assign_add]: 1.12e-06 [full_micro_interleaved_order_control]: 2.64999e-06 [reorder_send_recv_between_fp_bp]: 2.61e-06 [comm_op_add_attrs]: 1.20001e-06 [add_comm_op_reuse_tag]: 1.26997e-06 [interleave_split_concat_branches]: 1.23002e-06 [interleave_parallel_branches]: 1.14e-06 [overlap_opt_shard_in_pipeline]: 2.56998e-06 [overlap_opt_shard_grad_in_pipeline]: 2.59001e-06 [control_data_broadcast_order]: 1.888e-05 [grouped_pairwise_exchange_alltoall]: 2.15002e-06 [offloading_packed_experts]: 5.24998e-06 [overlap_recompute_and_grad_model_parallel]: 9.46e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.22e-06 [overlap_recompute_allgather_and_fa_grad]: 1.84e-06 [overlap_recompute_comm]: 2.46e-06 [overlap_grad_ring_attention]: 9.441e-05 [overlap_grad_flash_sp]: 3.606e-05 [begin_end_overlap_inline]: 6.09987e-07 [split_matmul_comm_elemetwise]: 2.63e-06 [split_layernorm_comm]: 2.81e-06 [handle_group_info]: 1.04e-06 [symbol_engine_optimizer]: 0.00030073, [1] [Cycle 1]: 0.00029325, [6] [build]: 0.00011479 [elim_shapecalc]: 3.186e-05 [elim_not_effective]: 3.562e-05 [opt_reshape]: 2.084e-05 [fold_const_symbol]: 2.678e-05 [renormalize]: 1.8999e-07 [detach_backward]: 3.08e-06 [pipeline_parallel_scheduler]: 1.72999e-06 [auto_monad_reorder]: 3.587e-05 [get_jit_bprop_graph]: 2.84001e-06 [rewriter_after_jit_bprop_graph]: 8.1e-06 [opt_after_jit_grad]: 0.00098888 [validate]: 9.33e-05 Sums bootstrap : 0.001011s : 1.23% type_inference : 0.070052s : 85.01% event_method : 0.000023s : 0.03% auto_monad : 0.000072s : 0.09% graph_reusing : 0.000005s : 0.01% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000036s : 0.04% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000010s : 0.01% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000037s : 0.04% 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 : 0.000065s : 0.08% optimize.rewriter_before_opt_a : 0.000085s : 0.10% optimize.opt_a.expand_dump_flag : 0.000006s : 0.01% optimize.opt_a.switch_simplify : 0.000058s : 0.07% optimize.opt_a.loop_unroll : 0.000046s : 0.06% optimize.opt_a.a_1 : 0.001584s : 1.92% optimize.opt_a.with_stream_mark : 0.000061s : 0.07% optimize.opt_a.recompute_prepare : 0.000056s : 0.07% optimize.opt_a.updatestate_depend_eliminate : 0.000018s : 0.02% optimize.opt_a.updatestate_assign_eliminate : 0.000011s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000010s : 0.01% optimize.opt_a.parameter_eliminate : 0.000006s : 0.01% optimize.opt_a.a_2 : 0.000424s : 0.52% optimize.opt_a.accelerated_algorithm : 0.000047s : 0.06% optimize.opt_a.shard : 0.000007s : 0.01% optimize.opt_a.meta_shard_fg_expand : 0.000006s : 0.01% optimize.opt_a.shard_inline : 0.000029s : 0.04% optimize.opt_a.merge_send_recv : 0.000024s : 0.03% optimize.opt_a.auto_parallel : 0.000023s : 0.03% optimize.opt_a.parallel : 0.000047s : 0.06% optimize.opt_a.flash_sp : 0.000018s : 0.02% optimize.opt_a.merge_comm : 0.000011s : 0.01% optimize.opt_a.allreduce_fusion : 0.000014s : 0.02% optimize.opt_a.matmul_add_comm_reduction : 0.000029s : 0.04% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000044s : 0.05% optimize.opt_a.virtual_dataset : 0.000041s : 0.05% optimize.opt_a.get_grad_eliminate_ : 0.000037s : 0.04% optimize.opt_a.virtual_output : 0.000051s : 0.06% 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 : 0.000036s : 0.04% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000065s : 0.08% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000048s : 0.06% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000011s : 0.01% optimize.opt_a.meta_fg_expand : 0.000025s : 0.03% optimize.opt_a.flash_sp_send_recv_attached : 0.000005s : 0.01% optimize.opt_a.receive_attached : 0.000009s : 0.01% optimize.opt_a.after_resolve : 0.000145s : 0.18% optimize.opt_a.a_after_grad : 0.000072s : 0.09% optimize.opt_a.renormalize : 0.002606s : 3.16% optimize.opt_a.add_forward_monad_depend : 0.000019s : 0.02% optimize.opt_a.auto_monad_grad : 0.000006s : 0.01% optimize.opt_a.auto_monad_eliminator : 0.000044s : 0.05% optimize.opt_a.cse : 0.000203s : 0.25% optimize.opt_a.a_3 : 0.000333s : 0.40% optimize.py_interpret_to_execute_after_opt_a : 0.000034s : 0.04% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000078s : 0.09% optimize.convert_after_rewriter : 0.000009s : 0.01% optimize.order_py_execute_after_rewriter : 0.000008s : 0.01% optimize.mutable_eliminate : 0.000989s : 1.20% optimize.opt_b.b_1 : 0.000404s : 0.49% optimize.opt_b.b_2 : 0.000019s : 0.02% optimize.opt_b.updatestate_depend_eliminate : 0.000012s : 0.02% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000111s : 0.13% optimize.optimize_parallel_all_gather_comm : 0.000032s : 0.04% optimize.overlap_param_gather : 0.000005s : 0.01% optimize.cconv : 0.000043s : 0.05% optimize.loop_unroll : 0.000686s : 0.83% optimize.opt_after_cconv.c_1 : 0.000087s : 0.11% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.01% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000008s : 0.01% optimize.opt_after_cconv.cse : 0.000077s : 0.09% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000086s : 0.10% optimize.tuple_transform.d_1 : 0.000158s : 0.19% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000014s : 0.02% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000094s : 0.11% optimize.cse_after_recomputation.cse : 0.000039s : 0.05% optimize.environ_conv : 0.000009s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000011s : 0.01% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000007s : 0.01% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000002s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000003s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000003s : 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 : 0.000009s : 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 : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000094s : 0.11% optimize.overlap_grad_flash_sp : 0.000036s : 0.04% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000003s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000115s : 0.14% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000032s : 0.04% optimize.symbol_engine_optimizer.elim_not_effective : 0.000036s : 0.04% optimize.symbol_engine_optimizer.opt_reshape : 0.000021s : 0.03% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000027s : 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 : 0.000036s : 0.04% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.01% opt_after_jit_grad : 0.000989s : 1.20% validate : 0.000093s : 0.11% Time group info: ------[substitution.] 0.000241 39 5.49% : 0.000013s : 2: substitution.elim_not_effective 4.88% : 0.000012s : 2: substitution.fold_const_symbol 4.01% : 0.000010s : 10: substitution.graph_param_transform 76.76% : 0.000185s : 1: substitution.inline 1.81% : 0.000004s : 4: substitution.j_node_and_user_rematch 2.14% : 0.000005s : 4: substitution.remove_not_recompute_node 4.91% : 0.000012s : 16: substitution.replace_old_param ------[type_inference.] 0.069905 2 98.42% : 0.068798s : 1: type_inference.infer 1.58% : 0.001107s : 1: type_inference.specialize ------[replace.] 0.000030 1 100.00% : 0.000030s : 1: replace.inline ------[match.] 0.000184 1 100.00% : 0.000184s : 1: match.inline ------[predicate.] 0.000302 2335 0.76% : 0.000002s : 21: predicate.accumulaten_eliminater 1.23% : 0.000004s : 10: predicate.ad_related_special_op_eliminate 0.67% : 0.000002s : 20: predicate.addn_check_dump 0.80% : 0.000002s : 21: predicate.addn_zero_filter 0.69% : 0.000002s : 21: predicate.adjust_all_reduce_mul_add 2.11% : 0.000006s : 41: predicate.arithmetic_simplify 0.75% : 0.000002s : 21: predicate.cast_eliminate 0.70% : 0.000002s : 20: predicate.check_bprop_eliminate 0.65% : 0.000002s : 20: predicate.compare_switch_simplify 0.26% : 0.000001s : 10: predicate.const_output_eliminate 0.82% : 0.000002s : 20: predicate.depend_value_elim 0.77% : 0.000002s : 21: predicate.dict_get_item_const_eliminator 0.98% : 0.000003s : 21: predicate.dict_get_item_eliminator 0.75% : 0.000002s : 21: predicate.dict_set_item_eliminator 1.24% : 0.000004s : 20: predicate.dumpgradient_eliminate 0.35% : 0.000001s : 10: predicate.elim_not_effective 0.47% : 0.000001s : 10: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000003s : 31: predicate.environ_add_const_eliminate 0.95% : 0.000003s : 31: predicate.environ_get_add_eliminate 1.00% : 0.000003s : 31: predicate.environ_get_depend_swap 1.82% : 0.000006s : 51: predicate.environ_get_eliminate 7.20% : 0.000022s : 31: predicate.environ_get_set_eliminate 0.69% : 0.000002s : 22: predicate.exchange_switch_depend_value 1.24% : 0.000004s : 22: predicate.float_depend_g_call 0.75% : 0.000002s : 20: predicate.float_environ_get_switch 0.97% : 0.000003s : 30: predicate.float_tuple_getitem_switch 0.26% : 0.000001s : 10: predicate.fold_const_symbol 0.84% : 0.000003s : 20: predicate.get_grad_eliminate 0.30% : 0.000001s : 10: predicate.graph_param_transform 0.71% : 0.000002s : 20: predicate.incorporate_call 0.60% : 0.000002s : 20: predicate.incorporate_call_switch 5.00% : 0.000015s : 103: predicate.inline 1.05% : 0.000003s : 20: predicate.inline_without_move 0.46% : 0.000001s : 20: predicate.j_node_and_user_rematch 1.18% : 0.000004s : 20: predicate.less_batch_normalization 1.51% : 0.000005s : 41: predicate.list_to_tuple_eliminator_ 2.04% : 0.000006s : 62: predicate.load_eliminater 1.01% : 0.000003s : 10: predicate.loop_unroll_after_grad 1.17% : 0.000004s : 31: predicate.loop_unroll_before_grad 1.80% : 0.000005s : 41: predicate.make_slice_get_slice_eliminator 0.71% : 0.000002s : 20: predicate.merge_addn 0.75% : 0.000002s : 20: predicate.micro_step_allgather_replace 0.72% : 0.000002s : 20: predicate.mini_step_allgather_replace 0.62% : 0.000002s : 21: predicate.minmaximum_grad 1.40% : 0.000004s : 10: predicate.mutable_eliminate 0.44% : 0.000001s : 10: predicate.opt_reshape 0.42% : 0.000001s : 10: predicate.parallel_virtual_node 1.03% : 0.000003s : 22: predicate.partial_defer_inline 1.08% : 0.000003s : 31: predicate.partial_eliminate 0.91% : 0.000003s : 21: predicate.print_const_string_wrapper 0.79% : 0.000002s : 20: predicate.reduce_all_const_elim 1.06% : 0.000003s : 21: predicate.reduce_eliminate 2.27% : 0.000007s : 62: predicate.redundant_stop_gradient_eliminater 0.67% : 0.000002s : 20: predicate.remove_not_recompute_node 1.44% : 0.000004s : 41: predicate.replace_applicator 0.67% : 0.000002s : 20: predicate.replace_old_param 0.38% : 0.000001s : 10: predicate.reset_defer_inline 0.90% : 0.000003s : 21: predicate.reshape_eliminate 0.81% : 0.000002s : 20: predicate.row_tensor_add_zeros_like 0.42% : 0.000001s : 10: predicate.row_tensor_eliminate 0.97% : 0.000003s : 20: predicate.same_eliminate 0.57% : 0.000002s : 20: predicate.set_cell_output_no_recompute 0.92% : 0.000003s : 20: predicate.shard_identity_eliminate 0.89% : 0.000003s : 20: predicate.special_op_eliminate 0.94% : 0.000003s : 20: predicate.specialize_transform 1.32% : 0.000004s : 20: predicate.split_environ_get_set_with_tuple_value 0.96% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.44% : 0.000001s : 10: predicate.switch_call_monad_eliminater 0.78% : 0.000002s : 22: predicate.switch_defer_inline 1.57% : 0.000005s : 42: predicate.switch_layer_defer_inline 3.25% : 0.000010s : 83: predicate.switch_simplify 0.73% : 0.000002s : 21: predicate.tile_eliminate 0.71% : 0.000002s : 21: predicate.transpose_eliminate 1.74% : 0.000005s : 41: predicate.tuple_list_convert_item_index_to_positive 1.65% : 0.000005s : 41: predicate.tuple_list_get_item_const_eliminator 1.44% : 0.000004s : 41: predicate.tuple_list_get_item_depend_reorder 2.75% : 0.000008s : 61: predicate.tuple_list_get_item_eliminator 1.39% : 0.000004s : 41: predicate.tuple_list_get_set_item_eliminator 2.28% : 0.000007s : 61: predicate.tuple_list_set_item_eliminator 1.89% : 0.000006s : 41: predicate.tuple_to_list_eliminator_ 1.83% : 0.000006s : 62: predicate.updatestate_pure_node_eliminater 2.69% : 0.000008s : 82: predicate.updatestate_useless_node_eliminater 0.47% : 0.000001s : 10: predicate.value_based_eliminate 0.75% : 0.000002s : 20: predicate.virtual_dataset_eliminate 0.96% : 0.000003s : 20: predicate.virtual_output_eliminate 0.45% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.48% : 0.000001s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001396 6 44.50% : 0.000621s : 3: func_graph_cloner_run.FuncGraphClonerGraph 55.50% : 0.000775s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.219599 192 0.00% : 0.000004s : 1: ForceFp32Comm 26.83% : 0.058918s : 1: add_attr 26.82% : 0.058896s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.04% : 0.000099s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.04% : 0.000078s : 1: auto_monad 0.02% : 0.000041s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.48% : 0.001058s : 1: bootstrap 0.02% : 0.000048s : 1: cconv 0.00% : 0.000008s : 1: comm_op_add_attrs 0.01% : 0.000022s : 1: control_data_broadcast_order 0.01% : 0.000013s : 1: convert_after_rewriter 0.03% : 0.000058s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.01% : 0.000012s : 1: environ_conv 0.01% : 0.000030s : 1: event_method 0.01% : 0.000013s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.01% : 0.000014s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.01% : 0.000011s : 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% : 0.000010s : 1: label_micro_interleaved_index 0.32% : 0.000698s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000008s : 1: micro_interleaved_order_control 0.46% : 0.001003s : 1: mutable_eliminate 0.00% : 0.000008s : 1: offloading_packed_experts 0.02% : 0.000048s : 1: opt.transform.loop_unroll_optimizer 0.02% : 0.000034s : 1: opt.transform.mutable_eliminate 1.34% : 0.002940s : 78: opt.transform.opt_a 0.04% : 0.000084s : 1: opt.transform.opt_after_cconv 0.04% : 0.000085s : 1: opt.transform.opt_after_jit_grad 0.17% : 0.000378s : 28: opt.transform.opt_b 0.08% : 0.000169s : 2: opt.transform.opt_trans_graph 0.05% : 0.000110s : 4: opt.transform.symbol_engine_opt 3.30% : 0.007239s : 1: opt_a 0.12% : 0.000258s : 1: opt_after_cconv 0.46% : 0.001003s : 1: opt_after_jit_grad 0.29% : 0.000646s : 1: opt_b 5.25% : 0.011524s : 1: optimize 0.02% : 0.000039s : 1: optimize_parallel_all_gather_comm 0.01% : 0.000011s : 1: order_py_execute_after_rewriter 0.02% : 0.000040s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.05% : 0.000116s : 1: overlap_grad_ring_attention 0.01% : 0.000015s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000006s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 1: overlap_param_gather 0.00% : 0.000009s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000012s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.01% : 0.000012s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.02% : 0.000041s : 1: pre_auto_parallel 0.03% : 0.000069s : 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 0.04% : 0.000091s : 1: remove_dup_value 0.31% : 0.000684s : 1: renormalize.infer 0.87% : 0.001906s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.01% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000083s : 1: rewriter_after_opt_a 0.04% : 0.000089s : 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 0.01% : 0.000014s : 1: swap_dp_allreduce_reducescatter 0.14% : 0.000304s : 1: symbol_engine_optimizer 0.10% : 0.000220s : 1: tuple_transform 31.91% : 0.070079s : 1: type_inference .[WARNING] PRE_ACT(167157,ffff84bcaf30,python3.9):2026-01-29-17:40:21.456.312 [mindspore/ccsrc/runtime/memory/mem_pool/abstract_dynamic_mem_pool.cc:1109] FreeIdleMemsByEagerFree] Eager free count : 2, free memory : 1582359040, real free : 1585446912, not free : 0. [hook] pytest_runtest_teardown:test_paged_attention_quant_pertoken[1] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_quant_pertoken[1],max_mem:1608.0M =============================== 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 208.75s (0:03:28) ==================