==================================================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_006/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_asd_paged_attention.py [WARNING] ME(161347:281473000189744,MainProcess):2026-01-29-17:37:37.901.586 [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 = 0.269393, [21] [bootstrap]: 0.00071256 [type_inference]: 0.135321 [event_method]: 1.871e-05 [auto_monad]: 9.757e-05 [graph_reusing]: 5.57999e-06 [inline]: 3.03e-06 [add_attr]: 0.010514, [1] [add_attr_with_inline]: 0.0104976, [1] [Cycle 1]: 0.00010343, [2] [tag_attr]: 2.463e-05 [meta_addattr_fg_expand]: 4.30999e-06 [parallel-infer-symbol]: 4.12e-06 [pre_auto_parallel]: 5.325e-05 [insert-virtual-dataset]: 3.09999e-06 [parallel-infer-symbol-second]: 8.29983e-07 [dataset_repeat_opt]: 2.00002e-06 [pipeline_split]: 1.97999e-06 [optimize]: 0.12156, [53] [py_interpret_to_execute]: 3.256e-05 [rewriter_before_opt_a]: 9.377e-05 [opt_a]: 0.11811, [2] [Cycle 1]: 0.116909, [45] [expand_dump_flag]: 2.76999e-06 [switch_simplify]: 6e-05 [loop_unroll]: 2.125e-05 [a_1]: 0.00048107 [with_stream_mark]: 2.892e-05 [recompute_prepare]: 1.61e-05 [updatestate_depend_eliminate]: 6.54999e-06 [updatestate_assign_eliminate]: 5.04e-06 [updatestate_loads_eliminate]: 5.39998e-06 [parameter_eliminate]: 1.99e-06 [a_2]: 0.00015215 [accelerated_algorithm]: 1.306e-05 [shard]: 3.17002e-06 [meta_shard_fg_expand]: 4.68001e-06 [shard_inline]: 1.208e-05 [merge_send_recv]: 1.153e-05 [auto_parallel]: 1.113e-05 [parallel]: 6.225e-05 [flash_sp]: 1.535e-05 [merge_comm]: 7.31999e-06 [allreduce_fusion]: 4.84e-06 [matmul_add_comm_reduction]: 1.385e-05 [allreduce_slice_to_reducescatter]: 8.89995e-07 [virtual_shard_identity]: 4.878e-05 [virtual_dataset]: 1.83e-05 [get_grad_eliminate_]: 1.11e-05 [virtual_output]: 1.02e-05 [merge_forward]: 8.32e-06 [cell_reuse_recompute_pass]: 2.12001e-06 [offload_activation]: 1.418e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.519e-05 [merge_recompute_call_nodes]: 2.39001e-06 [before_grad]: 1.673e-05 [set_forward_comm_id_for_comm_node_pass]: 6.39001e-06 [meta_fg_expand]: 5.12e-06 [flash_sp_send_recv_attached]: 3.89002e-06 [receive_attached]: 1.26e-05 [after_resolve]: 2.51e-05 [a_after_grad]: 1.769e-05 [renormalize]: 0.115128 [add_forward_monad_depend]: 1.585e-05 [auto_monad_grad]: 3.03998e-06 [auto_monad_eliminator]: 3.094e-05 [cse]: 0.00011255 [a_3]: 0.00010535 [Cycle 2]: 0.0011844, [45] [expand_dump_flag]: 2.88e-06 [switch_simplify]: 1.727e-05 [loop_unroll]: 1.109e-05 [a_1]: 0.0002789 [with_stream_mark]: 2.983e-05 [recompute_prepare]: 1.586e-05 [updatestate_depend_eliminate]: 7.05e-06 [updatestate_assign_eliminate]: 5.69999e-06 [updatestate_loads_eliminate]: 5.42999e-06 [parameter_eliminate]: 4.16001e-06 [a_2]: 0.00013903 [accelerated_algorithm]: 1.182e-05 [shard]: 3.89002e-06 [meta_shard_fg_expand]: 4.32998e-06 [shard_inline]: 1.164e-05 [merge_send_recv]: 1.3e-05 [auto_parallel]: 1.228e-05 [parallel]: 1.057e-05 [flash_sp]: 5.00001e-06 [merge_comm]: 4.82e-06 [allreduce_fusion]: 4.80001e-06 [matmul_add_comm_reduction]: 1.369e-05 [allreduce_slice_to_reducescatter]: 1.09e-06 [virtual_shard_identity]: 1.569e-05 [virtual_dataset]: 1.184e-05 [get_grad_eliminate_]: 9.92001e-06 [virtual_output]: 1.06e-05 [merge_forward]: 5.91998e-06 [cell_reuse_recompute_pass]: 3.81001e-06 [offload_activation]: 1.42e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.567e-05 [merge_recompute_call_nodes]: 1.58002e-06 [before_grad]: 1.476e-05 [set_forward_comm_id_for_comm_node_pass]: 5.45001e-06 [meta_fg_expand]: 4.12e-06 [flash_sp_send_recv_attached]: 2.98998e-06 [receive_attached]: 3.18e-06 [after_resolve]: 2.575e-05 [a_after_grad]: 1.78e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 4.25999e-06 [auto_monad_grad]: 1.69e-06 [auto_monad_eliminator]: 1.613e-05 [cse]: 4.989e-05 [a_3]: 7.237e-05 [py_interpret_to_execute_after_opt_a]: 3.085e-05 [slice_cell_reuse_recomputed_activation]: 2.51e-06 [rewriter_after_opt_a]: 0.00011542 [convert_after_rewriter]: 1.123e-05 [order_py_execute_after_rewriter]: 8.00999e-06 [mutable_eliminate]: 0.00092771 [opt_b]: 0.00036644, [1] [Cycle 1]: 0.00035731, [7] [b_1]: 0.0002255 [b_2]: 1.36e-05 [updatestate_depend_eliminate]: 1.107e-05 [updatestate_assign_eliminate]: 4.94998e-06 [updatestate_loads_eliminate]: 4.99e-06 [renormalize]: 7.2e-07 [cse]: 5.644e-05 [optimize_parallel_all_gather_comm]: 2.548e-05 [overlap_param_gather]: 6.11e-06 [cconv]: 4.137e-05 [loop_unroll]: 0.00059351 [opt_after_cconv]: 0.00017347, [1] [Cycle 1]: 0.00016612, [7] [c_1]: 5.821e-05 [parameter_eliminate]: 5.85002e-06 [updatestate_depend_eliminate]: 9.32999e-06 [updatestate_assign_eliminate]: 4.27e-06 [updatestate_loads_eliminate]: 4.03001e-06 [cse]: 4.826e-05 [renormalize]: 5.60016e-07 [remove_dup_value]: 7.831e-05 [tuple_transform]: 0.00013953, [1] [Cycle 1]: 0.00013294, [4] [d_1]: 9.905e-05 [none_parameter_eliminate]: 2.06e-06 [renormalize]: 4.19997e-07 [switch_simplify]: 1.194e-05 [partial_unused_args_eliminate]: 2.69001e-06 [add_recomputation]: 7.653e-05 [cse_after_recomputation]: 4.043e-05, [1] [Cycle 1]: 3.464e-05, [1] [cse]: 2.782e-05 [environ_conv]: 2.058e-05 [swap_dp_allreduce_reducescatter]: 7.65998e-06 [bias_add_comm_swap]: 3.83001e-06 [label_micro_interleaved_index]: 6.37001e-06 [label_fine_grained_interleaved_index]: 2.89001e-06 [merge_cast_opt]: 2.04e-06 [slice_recompute_activation]: 2.81999e-06 [micro_interleaved_order_control]: 3.01001e-06 [assign_add_opt]: 1.71e-06 [ForceFp32Comm]: 1.20999e-06 [remove_cast_before_assign_add]: 1.12e-06 [full_micro_interleaved_order_control]: 2.43e-06 [reorder_send_recv_between_fp_bp]: 3.14001e-06 [comm_op_add_attrs]: 1.24003e-06 [add_comm_op_reuse_tag]: 1.19e-06 [interleave_split_concat_branches]: 2.19001e-06 [interleave_parallel_branches]: 1.20999e-06 [overlap_opt_shard_in_pipeline]: 2.547e-05 [overlap_opt_shard_grad_in_pipeline]: 2.48e-06 [control_data_broadcast_order]: 1.921e-05 [grouped_pairwise_exchange_alltoall]: 1.74e-06 [offloading_packed_experts]: 5.02e-06 [overlap_recompute_and_grad_model_parallel]: 6.84999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.35999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.31002e-06 [overlap_recompute_comm]: 2.91999e-06 [overlap_grad_ring_attention]: 5.89e-06 [overlap_grad_flash_sp]: 4.156e-05 [begin_end_overlap_inline]: 5.8001e-07 [split_matmul_comm_elemetwise]: 2.21e-06 [split_layernorm_comm]: 2.51e-06 [handle_group_info]: 1.27e-06 [symbol_engine_optimizer]: 0.00023132, [1] [Cycle 1]: 0.00022557, [6] [build]: 0.00010466 [elim_shapecalc]: 2.097e-05 [elim_not_effective]: 3.01e-05 [opt_reshape]: 1.204e-05 [fold_const_symbol]: 2.04e-05 [renormalize]: 2.59985e-07 [detach_backward]: 3.35e-06 [pipeline_parallel_scheduler]: 1.72001e-06 [auto_monad_reorder]: 3.285e-05 [get_jit_bprop_graph]: 1.94999e-06 [rewriter_after_jit_bprop_graph]: 4.81002e-06 [opt_after_jit_grad]: 0.00077966 [validate]: 8.586e-05 Sums bootstrap : 0.000713s : 0.28% type_inference : 0.135321s : 52.52% event_method : 0.000019s : 0.01% auto_monad : 0.000098s : 0.04% graph_reusing : 0.000006s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000025s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000053s : 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 : 0.000033s : 0.01% optimize.rewriter_before_opt_a : 0.000094s : 0.04% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000077s : 0.03% optimize.opt_a.loop_unroll : 0.000032s : 0.01% optimize.opt_a.a_1 : 0.000760s : 0.29% optimize.opt_a.with_stream_mark : 0.000059s : 0.02% optimize.opt_a.recompute_prepare : 0.000032s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000014s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000011s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000291s : 0.11% optimize.opt_a.accelerated_algorithm : 0.000025s : 0.01% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000009s : 0.00% optimize.opt_a.shard_inline : 0.000024s : 0.01% optimize.opt_a.merge_send_recv : 0.000025s : 0.01% optimize.opt_a.auto_parallel : 0.000023s : 0.01% optimize.opt_a.parallel : 0.000073s : 0.03% optimize.opt_a.flash_sp : 0.000020s : 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 : 0.000028s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000064s : 0.03% optimize.opt_a.virtual_dataset : 0.000030s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000021s : 0.01% optimize.opt_a.virtual_output : 0.000021s : 0.01% optimize.opt_a.merge_forward : 0.000014s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000028s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000051s : 0.02% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000031s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000012s : 0.00% optimize.opt_a.meta_fg_expand : 0.000009s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000016s : 0.01% optimize.opt_a.after_resolve : 0.000051s : 0.02% optimize.opt_a.a_after_grad : 0.000035s : 0.01% optimize.opt_a.renormalize : 0.115128s : 44.68% optimize.opt_a.add_forward_monad_depend : 0.000020s : 0.01% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000047s : 0.02% optimize.opt_a.cse : 0.000162s : 0.06% optimize.opt_a.a_3 : 0.000178s : 0.07% optimize.py_interpret_to_execute_after_opt_a : 0.000031s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000115s : 0.04% optimize.convert_after_rewriter : 0.000011s : 0.00% optimize.order_py_execute_after_rewriter : 0.000008s : 0.00% optimize.mutable_eliminate : 0.000928s : 0.36% optimize.opt_b.b_1 : 0.000225s : 0.09% optimize.opt_b.b_2 : 0.000014s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000011s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000056s : 0.02% optimize.optimize_parallel_all_gather_comm : 0.000025s : 0.01% optimize.overlap_param_gather : 0.000006s : 0.00% optimize.cconv : 0.000041s : 0.02% optimize.loop_unroll : 0.000594s : 0.23% optimize.opt_after_cconv.c_1 : 0.000058s : 0.02% 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 : 0.000048s : 0.02% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000078s : 0.03% optimize.tuple_transform.d_1 : 0.000099s : 0.04% 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 : 0.000003s : 0.00% optimize.add_recomputation : 0.000077s : 0.03% optimize.cse_after_recomputation.cse : 0.000028s : 0.01% optimize.environ_conv : 0.000021s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000008s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000002s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000025s : 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 : 0.000007s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000006s : 0.00% optimize.overlap_grad_flash_sp : 0.000042s : 0.02% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000003s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000105s : 0.04% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000021s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000030s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000033s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000780s : 0.30% validate : 0.000086s : 0.03% Time group info: ------[substitution.] 0.000196 36 5.23% : 0.000010s : 2: substitution.elim_not_effective 3.81% : 0.000007s : 2: substitution.fold_const_symbol 11.53% : 0.000023s : 9: substitution.graph_param_transform 66.92% : 0.000131s : 1: substitution.inline 2.96% : 0.000006s : 4: substitution.j_node_and_user_rematch 3.34% : 0.000007s : 4: substitution.remove_not_recompute_node 6.22% : 0.000012s : 14: substitution.replace_old_param ------[type_inference.] 0.135200 2 99.50% : 0.134530s : 1: type_inference.infer 0.50% : 0.000670s : 1: type_inference.specialize ------[replace.] 0.000026 1 100.00% : 0.000026s : 1: replace.inline ------[match.] 0.000130 1 100.00% : 0.000130s : 1: match.inline ------[predicate.] 0.000270 2107 0.81% : 0.000002s : 19: predicate.accumulaten_eliminater 1.04% : 0.000003s : 9: predicate.ad_related_special_op_eliminate 0.76% : 0.000002s : 18: predicate.addn_check_dump 0.74% : 0.000002s : 19: predicate.addn_zero_filter 0.73% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 1.98% : 0.000005s : 37: predicate.arithmetic_simplify 0.94% : 0.000003s : 19: predicate.cast_eliminate 0.92% : 0.000002s : 18: predicate.check_bprop_eliminate 0.77% : 0.000002s : 18: predicate.compare_switch_simplify 0.27% : 0.000001s : 9: predicate.const_output_eliminate 0.83% : 0.000002s : 18: predicate.depend_value_elim 1.22% : 0.000003s : 19: predicate.dict_get_item_const_eliminator 0.94% : 0.000003s : 19: predicate.dict_get_item_eliminator 0.76% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.14% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.39% : 0.000001s : 9: predicate.elim_not_effective 0.50% : 0.000001s : 9: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000003s : 28: predicate.environ_add_const_eliminate 1.12% : 0.000003s : 28: predicate.environ_get_add_eliminate 1.05% : 0.000003s : 28: predicate.environ_get_depend_swap 1.85% : 0.000005s : 46: predicate.environ_get_eliminate 1.22% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.78% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.54% : 0.000004s : 20: predicate.float_depend_g_call 0.74% : 0.000002s : 18: predicate.float_environ_get_switch 1.00% : 0.000003s : 27: predicate.float_tuple_getitem_switch 0.27% : 0.000001s : 9: predicate.fold_const_symbol 0.73% : 0.000002s : 18: predicate.get_grad_eliminate 0.39% : 0.000001s : 9: predicate.graph_param_transform 0.74% : 0.000002s : 18: predicate.incorporate_call 0.60% : 0.000002s : 18: predicate.incorporate_call_switch 5.07% : 0.000014s : 93: predicate.inline 1.03% : 0.000003s : 18: predicate.inline_without_move 0.46% : 0.000001s : 18: predicate.j_node_and_user_rematch 1.20% : 0.000003s : 18: predicate.less_batch_normalization 1.73% : 0.000005s : 37: predicate.list_to_tuple_eliminator_ 2.18% : 0.000006s : 56: predicate.load_eliminater 1.14% : 0.000003s : 9: predicate.loop_unroll_after_grad 1.26% : 0.000003s : 28: predicate.loop_unroll_before_grad 2.21% : 0.000006s : 37: predicate.make_slice_get_slice_eliminator 0.69% : 0.000002s : 18: predicate.merge_addn 0.63% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.70% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.79% : 0.000002s : 19: predicate.minmaximum_grad 1.40% : 0.000004s : 9: predicate.mutable_eliminate 0.43% : 0.000001s : 9: predicate.opt_reshape 0.50% : 0.000001s : 9: predicate.parallel_virtual_node 1.07% : 0.000003s : 20: predicate.partial_defer_inline 1.18% : 0.000003s : 28: predicate.partial_eliminate 0.81% : 0.000002s : 19: predicate.print_const_string_wrapper 0.78% : 0.000002s : 18: predicate.reduce_all_const_elim 1.15% : 0.000003s : 19: predicate.reduce_eliminate 2.44% : 0.000007s : 56: predicate.redundant_stop_gradient_eliminater 0.82% : 0.000002s : 18: predicate.remove_not_recompute_node 1.54% : 0.000004s : 37: predicate.replace_applicator 0.60% : 0.000002s : 18: predicate.replace_old_param 0.31% : 0.000001s : 9: predicate.reset_defer_inline 0.97% : 0.000003s : 19: predicate.reshape_eliminate 0.80% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.54% : 0.000001s : 9: predicate.row_tensor_eliminate 1.10% : 0.000003s : 18: predicate.same_eliminate 0.80% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.46% : 0.000004s : 18: predicate.shard_identity_eliminate 0.87% : 0.000002s : 18: predicate.special_op_eliminate 0.97% : 0.000003s : 18: predicate.specialize_transform 0.97% : 0.000003s : 18: predicate.split_environ_get_set_with_tuple_value 1.27% : 0.000003s : 18: predicate.stack_unstack_eliminate 0.48% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.81% : 0.000002s : 20: predicate.switch_defer_inline 1.63% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.75% : 0.000010s : 75: predicate.switch_simplify 0.77% : 0.000002s : 19: predicate.tile_eliminate 0.68% : 0.000002s : 19: predicate.transpose_eliminate 1.60% : 0.000004s : 37: predicate.tuple_list_convert_item_index_to_positive 1.50% : 0.000004s : 37: predicate.tuple_list_get_item_const_eliminator 1.73% : 0.000005s : 37: predicate.tuple_list_get_item_depend_reorder 3.13% : 0.000008s : 55: predicate.tuple_list_get_item_eliminator 1.29% : 0.000003s : 37: predicate.tuple_list_get_set_item_eliminator 2.75% : 0.000007s : 55: predicate.tuple_list_set_item_eliminator 1.74% : 0.000005s : 37: predicate.tuple_to_list_eliminator_ 1.98% : 0.000005s : 56: predicate.updatestate_pure_node_eliminater 2.98% : 0.000008s : 74: predicate.updatestate_useless_node_eliminater 0.45% : 0.000001s : 9: predicate.value_based_eliminate 1.21% : 0.000003s : 18: predicate.virtual_dataset_eliminate 0.79% : 0.000002s : 18: predicate.virtual_output_eliminate 0.35% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.57% : 0.000002s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000607 6 50.13% : 0.000304s : 3: func_graph_cloner_run.FuncGraphClonerGraph 49.87% : 0.000303s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.518532 192 0.00% : 0.000004s : 1: ForceFp32Comm 2.03% : 0.010521s : 1: add_attr 2.03% : 0.010503s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000081s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.02% : 0.000104s : 1: auto_monad 0.01% : 0.000037s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.14% : 0.000744s : 1: bootstrap 0.01% : 0.000045s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000023s : 1: control_data_broadcast_order 0.00% : 0.000016s : 1: convert_after_rewriter 0.01% : 0.000043s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000025s : 1: environ_conv 0.01% : 0.000026s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 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% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000009s : 1: label_micro_interleaved_index 0.12% : 0.000603s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.18% : 0.000942s : 1: mutable_eliminate 0.00% : 0.000008s : 1: offloading_packed_experts 0.00% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000031s : 1: opt.transform.mutable_eliminate 0.31% : 0.001597s : 78: opt.transform.opt_a 0.01% : 0.000057s : 1: opt.transform.opt_after_cconv 0.01% : 0.000049s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000206s : 28: opt.transform.opt_b 0.02% : 0.000109s : 2: opt.transform.opt_trans_graph 0.01% : 0.000078s : 4: opt.transform.symbol_engine_opt 22.78% : 0.118114s : 1: opt_a 0.03% : 0.000177s : 1: opt_after_cconv 0.15% : 0.000797s : 1: opt_after_jit_grad 0.07% : 0.000370s : 1: opt_b 23.44% : 0.121566s : 1: optimize 0.01% : 0.000030s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.01% : 0.000046s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000010s : 1: overlap_grad_ring_attention 0.00% : 0.000007s : 1: overlap_opt_shard_grad_in_pipeline 0.01% : 0.000030s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000010s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000010s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000007s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000058s : 1: pre_auto_parallel 0.01% : 0.000038s : 1: py_interpret_to_execute 0.01% : 0.000036s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.02% : 0.000083s : 1: remove_dup_value 0.10% : 0.000519s : 1: renormalize.infer 22.10% : 0.114588s : 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% : 0.000123s : 1: rewriter_after_opt_a 0.02% : 0.000098s : 1: rewriter_before_opt_a 0.00% : 0.000007s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.05% : 0.000234s : 1: symbol_engine_optimizer 0.03% : 0.000143s : 1: tuple_transform 26.10% : 0.135347s : 1: type_inference mki_log delete old file:/home/jenkins/ascend/log/atb/atb_70508_20260129172110.log . [hook] pytest_runtest_teardown:test_paged_attention_asd_mla_fp16[1] tests/st/infer/ops/test_internal_ops/test_asd_paged_attention.py::test_paged_attention_asd_mla_fp16[1],max_mem:272.0M [WARNING] ME(161347:281473000189744,MainProcess):2026-01-29-17:39:00.726.662 [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 = 0.201522, [21] [bootstrap]: 0.00087064 [type_inference]: 0.00920492 [event_method]: 1.871e-05 [auto_monad]: 7.346e-05 [graph_reusing]: 5.92001e-06 [inline]: 3.4e-06 [add_attr]: 0.182817, [1] [add_attr_with_inline]: 0.1828, [1] [Cycle 1]: 8.806e-05, [2] [tag_attr]: 2.497e-05 [meta_addattr_fg_expand]: 4.53999e-06 [parallel-infer-symbol]: 3.98001e-06 [pre_auto_parallel]: 5.19e-05 [insert-virtual-dataset]: 2.91e-06 [parallel-infer-symbol-second]: 9.20001e-07 [dataset_repeat_opt]: 1.98002e-06 [pipeline_split]: 1.76998e-06 [optimize]: 0.0075396, [53] [py_interpret_to_execute]: 5.266e-05 [rewriter_before_opt_a]: 0.00011969 [opt_a]: 0.00412997, [2] [Cycle 1]: 0.00293067, [45] [expand_dump_flag]: 3.64002e-06 [switch_simplify]: 3.455e-05 [loop_unroll]: 1.897e-05 [a_1]: 0.00051346 [with_stream_mark]: 2.884e-05 [recompute_prepare]: 1.658e-05 [updatestate_depend_eliminate]: 9.69999e-06 [updatestate_assign_eliminate]: 5.21002e-06 [updatestate_loads_eliminate]: 5.14e-06 [parameter_eliminate]: 2.17999e-06 [a_2]: 0.00016799 [accelerated_algorithm]: 1.72e-05 [shard]: 3.07002e-06 [meta_shard_fg_expand]: 2.23002e-06 [shard_inline]: 1.076e-05 [merge_send_recv]: 1.085e-05 [auto_parallel]: 8.35001e-06 [parallel]: 3.213e-05 [flash_sp]: 1.127e-05 [merge_comm]: 8.45999e-06 [allreduce_fusion]: 5.38002e-06 [matmul_add_comm_reduction]: 1.374e-05 [allreduce_slice_to_reducescatter]: 8.2e-07 [virtual_shard_identity]: 1.622e-05 [virtual_dataset]: 1.202e-05 [get_grad_eliminate_]: 1.169e-05 [virtual_output]: 1.84e-05 [merge_forward]: 6.36e-06 [cell_reuse_recompute_pass]: 1.87001e-06 [offload_activation]: 1.376e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.449e-05 [merge_recompute_call_nodes]: 1.59e-06 [before_grad]: 2.4e-05 [set_forward_comm_id_for_comm_node_pass]: 6.21e-06 [meta_fg_expand]: 4.15e-06 [flash_sp_send_recv_attached]: 3.13998e-06 [receive_attached]: 2.69001e-06 [after_resolve]: 2.466e-05 [a_after_grad]: 2.949e-05 [renormalize]: 0.00128234 [add_forward_monad_depend]: 1.06e-05 [auto_monad_grad]: 2.92002e-06 [auto_monad_eliminator]: 1.775e-05 [cse]: 7.963e-05 [a_3]: 8.214e-05 [Cycle 2]: 0.00118389, [45] [expand_dump_flag]: 1.54e-06 [switch_simplify]: 5.022e-05 [loop_unroll]: 1.408e-05 [a_1]: 0.00026604 [with_stream_mark]: 1.72e-05 [recompute_prepare]: 1.119e-05 [updatestate_depend_eliminate]: 5.48002e-06 [updatestate_assign_eliminate]: 4.68001e-06 [updatestate_loads_eliminate]: 4.4e-06 [parameter_eliminate]: 1.65001e-06 [a_2]: 0.00013435 [accelerated_algorithm]: 1.074e-05 [shard]: 1.28002e-06 [meta_shard_fg_expand]: 2.22001e-06 [shard_inline]: 1.019e-05 [merge_send_recv]: 7.57998e-06 [auto_parallel]: 8.82e-06 [parallel]: 5.76998e-06 [flash_sp]: 3.78999e-06 [merge_comm]: 5.13002e-06 [allreduce_fusion]: 5.14e-06 [matmul_add_comm_reduction]: 1.179e-05 [allreduce_slice_to_reducescatter]: 5.39992e-07 [virtual_shard_identity]: 1.178e-05 [virtual_dataset]: 1.095e-05 [get_grad_eliminate_]: 1.012e-05 [virtual_output]: 1.009e-05 [merge_forward]: 5.24e-06 [cell_reuse_recompute_pass]: 1.94e-06 [offload_activation]: 1.459e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.855e-05 [merge_recompute_call_nodes]: 7.10017e-07 [before_grad]: 1.483e-05 [set_forward_comm_id_for_comm_node_pass]: 5.46e-06 [meta_fg_expand]: 3.09001e-06 [flash_sp_send_recv_attached]: 1.25001e-06 [receive_attached]: 1.89e-06 [after_resolve]: 2.565e-05 [a_after_grad]: 1.96e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.54e-06 [auto_monad_grad]: 1.67999e-06 [auto_monad_eliminator]: 1.087e-05 [cse]: 5.54e-05 [a_3]: 0.00010581 [py_interpret_to_execute_after_opt_a]: 2.382e-05 [slice_cell_reuse_recomputed_activation]: 1.14e-05 [rewriter_after_opt_a]: 6.966e-05 [convert_after_rewriter]: 1.02e-05 [order_py_execute_after_rewriter]: 7e-06 [mutable_eliminate]: 0.00086072 [opt_b]: 0.00038785, [1] [Cycle 1]: 0.00037426, [7] [b_1]: 0.00023034 [b_2]: 1.248e-05 [updatestate_depend_eliminate]: 9.49999e-06 [updatestate_assign_eliminate]: 4.83001e-06 [updatestate_loads_eliminate]: 4.46002e-06 [renormalize]: 5.60016e-07 [cse]: 6.395e-05 [optimize_parallel_all_gather_comm]: 2.377e-05 [overlap_param_gather]: 3.03e-06 [cconv]: 3.557e-05 [loop_unroll]: 0.00058215 [opt_after_cconv]: 0.00018862, [1] [Cycle 1]: 0.00017399, [7] [c_1]: 5.877e-05 [parameter_eliminate]: 4.60999e-06 [updatestate_depend_eliminate]: 8.41002e-06 [updatestate_assign_eliminate]: 7.84002e-06 [updatestate_loads_eliminate]: 3.96001e-06 [cse]: 4.574e-05 [renormalize]: 2.29978e-07 [remove_dup_value]: 7.32e-05 [tuple_transform]: 0.0001358, [1] [Cycle 1]: 0.00012714, [4] [d_1]: 8.499e-05 [none_parameter_eliminate]: 2.06e-06 [renormalize]: 3.50003e-07 [switch_simplify]: 1.201e-05 [partial_unused_args_eliminate]: 2.21998e-06 [add_recomputation]: 7.532e-05 [cse_after_recomputation]: 4.124e-05, [1] [Cycle 1]: 3.614e-05, [1] [cse]: 2.956e-05 [environ_conv]: 8.03999e-06 [swap_dp_allreduce_reducescatter]: 7.21999e-06 [bias_add_comm_swap]: 3.33e-06 [label_micro_interleaved_index]: 5.40999e-06 [label_fine_grained_interleaved_index]: 2.76999e-06 [merge_cast_opt]: 1.62001e-06 [slice_recompute_activation]: 2.63e-06 [micro_interleaved_order_control]: 2.79001e-06 [assign_add_opt]: 1.86e-06 [ForceFp32Comm]: 9.29984e-07 [remove_cast_before_assign_add]: 1.08001e-06 [full_micro_interleaved_order_control]: 2.64001e-06 [reorder_send_recv_between_fp_bp]: 3.08e-06 [comm_op_add_attrs]: 1.22e-06 [add_comm_op_reuse_tag]: 1.02998e-06 [interleave_split_concat_branches]: 1.67001e-06 [interleave_parallel_branches]: 1.42999e-06 [overlap_opt_shard_in_pipeline]: 2.36e-06 [overlap_opt_shard_grad_in_pipeline]: 2.04999e-06 [control_data_broadcast_order]: 1.984e-05 [grouped_pairwise_exchange_alltoall]: 1.67001e-06 [offloading_packed_experts]: 5.31002e-06 [overlap_recompute_and_grad_model_parallel]: 9.69e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.47001e-06 [overlap_recompute_allgather_and_fa_grad]: 1.69e-06 [overlap_recompute_comm]: 2.53e-06 [overlap_grad_ring_attention]: 7.98999e-06 [overlap_grad_flash_sp]: 2.658e-05 [begin_end_overlap_inline]: 5.50004e-07 [split_matmul_comm_elemetwise]: 2.68998e-06 [split_layernorm_comm]: 1.89e-06 [handle_group_info]: 1.02998e-06 [symbol_engine_optimizer]: 0.00026892, [1] [Cycle 1]: 0.00026381, [6] [build]: 9.44e-05 [elim_shapecalc]: 2.197e-05 [elim_not_effective]: 2.43e-05 [opt_reshape]: 4.749e-05 [fold_const_symbol]: 2.342e-05 [renormalize]: 6.89994e-07 [detach_backward]: 2.53e-06 [pipeline_parallel_scheduler]: 1.70001e-06 [auto_monad_reorder]: 3.428e-05 [get_jit_bprop_graph]: 2.16998e-06 [rewriter_after_jit_bprop_graph]: 9.72001e-06 [opt_after_jit_grad]: 0.00060138 [validate]: 6.358e-05 Sums bootstrap : 0.000871s : 5.01% type_inference : 0.009205s : 52.93% event_method : 0.000019s : 0.11% auto_monad : 0.000073s : 0.42% graph_reusing : 0.000006s : 0.03% inline : 0.000003s : 0.02% add_attr.add_attr_with_inline.tag_attr : 0.000025s : 0.14% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.03% parallel-infer-symbol : 0.000004s : 0.02% pre_auto_parallel : 0.000052s : 0.30% insert-virtual-dataset : 0.000003s : 0.02% parallel-infer-symbol-second : 0.000001s : 0.01% dataset_repeat_opt : 0.000002s : 0.01% pipeline_split : 0.000002s : 0.01% optimize.py_interpret_to_execute : 0.000053s : 0.30% optimize.rewriter_before_opt_a : 0.000120s : 0.69% optimize.opt_a.expand_dump_flag : 0.000005s : 0.03% optimize.opt_a.switch_simplify : 0.000085s : 0.49% optimize.opt_a.loop_unroll : 0.000033s : 0.19% optimize.opt_a.a_1 : 0.000779s : 4.48% optimize.opt_a.with_stream_mark : 0.000046s : 0.26% optimize.opt_a.recompute_prepare : 0.000028s : 0.16% optimize.opt_a.updatestate_depend_eliminate : 0.000015s : 0.09% optimize.opt_a.updatestate_assign_eliminate : 0.000010s : 0.06% optimize.opt_a.updatestate_loads_eliminate : 0.000010s : 0.05% optimize.opt_a.parameter_eliminate : 0.000004s : 0.02% optimize.opt_a.a_2 : 0.000302s : 1.74% optimize.opt_a.accelerated_algorithm : 0.000028s : 0.16% optimize.opt_a.shard : 0.000004s : 0.03% optimize.opt_a.meta_shard_fg_expand : 0.000004s : 0.03% optimize.opt_a.shard_inline : 0.000021s : 0.12% optimize.opt_a.merge_send_recv : 0.000018s : 0.11% optimize.opt_a.auto_parallel : 0.000017s : 0.10% optimize.opt_a.parallel : 0.000038s : 0.22% optimize.opt_a.flash_sp : 0.000015s : 0.09% optimize.opt_a.merge_comm : 0.000014s : 0.08% optimize.opt_a.allreduce_fusion : 0.000011s : 0.06% optimize.opt_a.matmul_add_comm_reduction : 0.000026s : 0.15% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.01% optimize.opt_a.virtual_shard_identity : 0.000028s : 0.16% optimize.opt_a.virtual_dataset : 0.000023s : 0.13% optimize.opt_a.get_grad_eliminate_ : 0.000022s : 0.13% optimize.opt_a.virtual_output : 0.000028s : 0.16% optimize.opt_a.merge_forward : 0.000012s : 0.07% optimize.opt_a.cell_reuse_recompute_pass : 0.000004s : 0.02% optimize.opt_a.offload_activation : 0.000028s : 0.16% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000043s : 0.25% optimize.opt_a.merge_recompute_call_nodes : 0.000002s : 0.01% optimize.opt_a.before_grad : 0.000039s : 0.22% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000012s : 0.07% optimize.opt_a.meta_fg_expand : 0.000007s : 0.04% optimize.opt_a.flash_sp_send_recv_attached : 0.000004s : 0.03% optimize.opt_a.receive_attached : 0.000005s : 0.03% optimize.opt_a.after_resolve : 0.000050s : 0.29% optimize.opt_a.a_after_grad : 0.000049s : 0.28% optimize.opt_a.renormalize : 0.001282s : 7.37% optimize.opt_a.add_forward_monad_depend : 0.000012s : 0.07% optimize.opt_a.auto_monad_grad : 0.000005s : 0.03% optimize.opt_a.auto_monad_eliminator : 0.000029s : 0.16% optimize.opt_a.cse : 0.000135s : 0.78% optimize.opt_a.a_3 : 0.000188s : 1.08% optimize.py_interpret_to_execute_after_opt_a : 0.000024s : 0.14% optimize.slice_cell_reuse_recomputed_activation : 0.000011s : 0.07% optimize.rewriter_after_opt_a : 0.000070s : 0.40% optimize.convert_after_rewriter : 0.000010s : 0.06% optimize.order_py_execute_after_rewriter : 0.000007s : 0.04% optimize.mutable_eliminate : 0.000861s : 4.95% optimize.opt_b.b_1 : 0.000230s : 1.32% optimize.opt_b.b_2 : 0.000012s : 0.07% optimize.opt_b.updatestate_depend_eliminate : 0.000009s : 0.05% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.03% optimize.opt_b.updatestate_loads_eliminate : 0.000004s : 0.03% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000064s : 0.37% optimize.optimize_parallel_all_gather_comm : 0.000024s : 0.14% optimize.overlap_param_gather : 0.000003s : 0.02% optimize.cconv : 0.000036s : 0.20% optimize.loop_unroll : 0.000582s : 3.35% optimize.opt_after_cconv.c_1 : 0.000059s : 0.34% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.03% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.05% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.05% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.02% optimize.opt_after_cconv.cse : 0.000046s : 0.26% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000073s : 0.42% optimize.tuple_transform.d_1 : 0.000085s : 0.49% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.01% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000012s : 0.07% optimize.partial_unused_args_eliminate : 0.000002s : 0.01% optimize.add_recomputation : 0.000075s : 0.43% optimize.cse_after_recomputation.cse : 0.000030s : 0.17% optimize.environ_conv : 0.000008s : 0.05% optimize.swap_dp_allreduce_reducescatter : 0.000007s : 0.04% optimize.bias_add_comm_swap : 0.000003s : 0.02% optimize.label_micro_interleaved_index : 0.000005s : 0.03% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.02% optimize.merge_cast_opt : 0.000002s : 0.01% optimize.slice_recompute_activation : 0.000003s : 0.02% optimize.micro_interleaved_order_control : 0.000003s : 0.02% 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 : 0.02% 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 : 0.000002s : 0.01% optimize.interleave_parallel_branches : 0.000001s : 0.01% optimize.overlap_opt_shard_in_pipeline : 0.000002s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.01% optimize.control_data_broadcast_order : 0.000020s : 0.11% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.01% optimize.offloading_packed_experts : 0.000005s : 0.03% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.06% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 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 : 0.000008s : 0.05% optimize.overlap_grad_flash_sp : 0.000027s : 0.15% 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 : 0.000094s : 0.54% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000022s : 0.13% optimize.symbol_engine_optimizer.elim_not_effective : 0.000024s : 0.14% optimize.symbol_engine_optimizer.opt_reshape : 0.000047s : 0.27% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000023s : 0.13% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000003s : 0.01% pipeline_parallel_scheduler : 0.000002s : 0.01% auto_monad_reorder : 0.000034s : 0.20% get_jit_bprop_graph : 0.000002s : 0.01% rewriter_after_jit_bprop_graph : 0.000010s : 0.06% opt_after_jit_grad : 0.000601s : 3.46% validate : 0.000064s : 0.37% Time group info: ------[substitution.] 0.000193 36 3.46% : 0.000007s : 2: substitution.elim_not_effective 4.20% : 0.000008s : 2: substitution.fold_const_symbol 4.40% : 0.000008s : 9: substitution.graph_param_transform 78.18% : 0.000151s : 1: substitution.inline 2.24% : 0.000004s : 4: substitution.j_node_and_user_rematch 2.53% : 0.000005s : 4: substitution.remove_not_recompute_node 4.99% : 0.000010s : 14: substitution.replace_old_param ------[type_inference.] 0.009064 2 87.33% : 0.007916s : 1: type_inference.infer 12.67% : 0.001148s : 1: type_inference.specialize ------[replace.] 0.000023 1 100.00% : 0.000023s : 1: replace.inline ------[match.] 0.000150 1 100.00% : 0.000150s : 1: match.inline ------[predicate.] 0.000252 2107 0.88% : 0.000002s : 19: predicate.accumulaten_eliminater 0.86% : 0.000002s : 9: predicate.ad_related_special_op_eliminate 0.73% : 0.000002s : 18: predicate.addn_check_dump 0.89% : 0.000002s : 19: predicate.addn_zero_filter 0.76% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 1.94% : 0.000005s : 37: predicate.arithmetic_simplify 0.74% : 0.000002s : 19: predicate.cast_eliminate 0.75% : 0.000002s : 18: predicate.check_bprop_eliminate 0.80% : 0.000002s : 18: predicate.compare_switch_simplify 0.28% : 0.000001s : 9: predicate.const_output_eliminate 0.79% : 0.000002s : 18: predicate.depend_value_elim 0.87% : 0.000002s : 19: predicate.dict_get_item_const_eliminator 0.84% : 0.000002s : 19: predicate.dict_get_item_eliminator 0.75% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.24% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.34% : 0.000001s : 9: predicate.elim_not_effective 0.46% : 0.000001s : 9: predicate.elim_shapecalc_of_broadcastargs 1.28% : 0.000003s : 28: predicate.environ_add_const_eliminate 1.09% : 0.000003s : 28: predicate.environ_get_add_eliminate 1.11% : 0.000003s : 28: predicate.environ_get_depend_swap 1.94% : 0.000005s : 46: predicate.environ_get_eliminate 1.25% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.85% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.55% : 0.000004s : 20: predicate.float_depend_g_call 0.76% : 0.000002s : 18: predicate.float_environ_get_switch 1.11% : 0.000003s : 27: predicate.float_tuple_getitem_switch 0.28% : 0.000001s : 9: predicate.fold_const_symbol 0.87% : 0.000002s : 18: predicate.get_grad_eliminate 0.34% : 0.000001s : 9: predicate.graph_param_transform 0.67% : 0.000002s : 18: predicate.incorporate_call 0.64% : 0.000002s : 18: predicate.incorporate_call_switch 5.23% : 0.000013s : 93: predicate.inline 0.95% : 0.000002s : 18: predicate.inline_without_move 0.52% : 0.000001s : 18: predicate.j_node_and_user_rematch 1.13% : 0.000003s : 18: predicate.less_batch_normalization 1.65% : 0.000004s : 37: predicate.list_to_tuple_eliminator_ 2.28% : 0.000006s : 56: predicate.load_eliminater 1.32% : 0.000003s : 9: predicate.loop_unroll_after_grad 1.54% : 0.000004s : 28: predicate.loop_unroll_before_grad 2.00% : 0.000005s : 37: predicate.make_slice_get_slice_eliminator 0.77% : 0.000002s : 18: predicate.merge_addn 0.75% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.80% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.78% : 0.000002s : 19: predicate.minmaximum_grad 1.19% : 0.000003s : 9: predicate.mutable_eliminate 0.54% : 0.000001s : 9: predicate.opt_reshape 0.49% : 0.000001s : 9: predicate.parallel_virtual_node 1.05% : 0.000003s : 20: predicate.partial_defer_inline 1.22% : 0.000003s : 28: predicate.partial_eliminate 0.82% : 0.000002s : 19: predicate.print_const_string_wrapper 0.80% : 0.000002s : 18: predicate.reduce_all_const_elim 1.06% : 0.000003s : 19: predicate.reduce_eliminate 2.35% : 0.000006s : 56: predicate.redundant_stop_gradient_eliminater 0.71% : 0.000002s : 18: predicate.remove_not_recompute_node 1.34% : 0.000003s : 37: predicate.replace_applicator 0.70% : 0.000002s : 18: predicate.replace_old_param 0.34% : 0.000001s : 9: predicate.reset_defer_inline 0.83% : 0.000002s : 19: predicate.reshape_eliminate 0.80% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.42% : 0.000001s : 9: predicate.row_tensor_eliminate 1.09% : 0.000003s : 18: predicate.same_eliminate 0.65% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.02% : 0.000003s : 18: predicate.shard_identity_eliminate 0.93% : 0.000002s : 18: predicate.special_op_eliminate 0.80% : 0.000002s : 18: predicate.specialize_transform 1.16% : 0.000003s : 18: predicate.split_environ_get_set_with_tuple_value 0.96% : 0.000002s : 18: predicate.stack_unstack_eliminate 0.40% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.82% : 0.000002s : 20: predicate.switch_defer_inline 1.69% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.81% : 0.000010s : 75: predicate.switch_simplify 0.84% : 0.000002s : 19: predicate.tile_eliminate 0.92% : 0.000002s : 19: predicate.transpose_eliminate 1.81% : 0.000005s : 37: predicate.tuple_list_convert_item_index_to_positive 1.63% : 0.000004s : 37: predicate.tuple_list_get_item_const_eliminator 1.80% : 0.000005s : 37: predicate.tuple_list_get_item_depend_reorder 3.30% : 0.000008s : 55: predicate.tuple_list_get_item_eliminator 1.59% : 0.000004s : 37: predicate.tuple_list_get_set_item_eliminator 2.52% : 0.000006s : 55: predicate.tuple_list_set_item_eliminator 1.57% : 0.000004s : 37: predicate.tuple_to_list_eliminator_ 2.07% : 0.000005s : 56: predicate.updatestate_pure_node_eliminater 3.09% : 0.000008s : 74: predicate.updatestate_useless_node_eliminater 0.58% : 0.000001s : 9: predicate.value_based_eliminate 0.97% : 0.000002s : 18: predicate.virtual_dataset_eliminate 0.97% : 0.000002s : 18: predicate.virtual_output_eliminate 0.35% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.65% : 0.000002s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001178 6 48.09% : 0.000566s : 3: func_graph_cloner_run.FuncGraphClonerGraph 51.91% : 0.000611s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.395178 192 0.00% : 0.000004s : 1: ForceFp32Comm 46.26% : 0.182824s : 1: add_attr 46.26% : 0.182805s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000083s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.02% : 0.000080s : 1: auto_monad 0.01% : 0.000038s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000009s : 1: bias_add_comm_swap 0.23% : 0.000921s : 1: bootstrap 0.01% : 0.000040s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.01% : 0.000024s : 1: control_data_broadcast_order 0.00% : 0.000014s : 1: convert_after_rewriter 0.01% : 0.000045s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000015s : 1: environ_conv 0.01% : 0.000027s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000011s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000005s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000009s : 1: label_micro_interleaved_index 0.15% : 0.000597s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.22% : 0.000874s : 1: mutable_eliminate 0.00% : 0.000009s : 1: offloading_packed_experts 0.01% : 0.000057s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000025s : 1: opt.transform.mutable_eliminate 0.41% : 0.001621s : 78: opt.transform.opt_a 0.01% : 0.000057s : 1: opt.transform.opt_after_cconv 0.01% : 0.000052s : 1: opt.transform.opt_after_jit_grad 0.05% : 0.000212s : 28: opt.transform.opt_b 0.02% : 0.000094s : 2: opt.transform.opt_trans_graph 0.02% : 0.000081s : 4: opt.transform.symbol_engine_opt 1.05% : 0.004138s : 1: opt_a 0.05% : 0.000193s : 1: opt_after_cconv 0.16% : 0.000613s : 1: opt_after_jit_grad 0.10% : 0.000392s : 1: opt_b 1.91% : 0.007547s : 1: optimize 0.01% : 0.000028s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000014s : 1: order_py_execute_after_rewriter 0.01% : 0.000031s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000016s : 1: overlap_grad_ring_attention 0.00% : 0.000012s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000006s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000007s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000009s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000057s : 1: pre_auto_parallel 0.01% : 0.000057s : 1: py_interpret_to_execute 0.01% : 0.000028s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.02% : 0.000078s : 1: remove_dup_value 0.16% : 0.000625s : 1: renormalize.infer 0.16% : 0.000645s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000074s : 1: rewriter_after_opt_a 0.03% : 0.000128s : 1: rewriter_before_opt_a 0.00% : 0.000015s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000012s : 1: swap_dp_allreduce_reducescatter 0.07% : 0.000272s : 1: symbol_engine_optimizer 0.04% : 0.000139s : 1: tuple_transform 2.34% : 0.009233s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_asd_mla_fp16[2] tests/st/infer/ops/test_internal_ops/test_asd_paged_attention.py::test_paged_attention_asd_mla_fp16[2],max_mem:272.0M =============================== warnings summary =============================== ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 181.49s (0:03:01) ==================