==================================================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_paged_attention.py [WARNING] ME(168514:281473890443056,MainProcess):2026-01-29-17:37:33.911.619 [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 = 0.131689, [21] [bootstrap]: 0.00078335 [type_inference]: 0.0518549 [event_method]: 1.642e-05 [auto_monad]: 9.592e-05 [graph_reusing]: 5.14998e-06 [inline]: 2.79001e-06 [add_attr]: 0.0442535, [1] [add_attr_with_inline]: 0.0442011, [1] [Cycle 1]: 0.00042763, [2] [tag_attr]: 8.073e-05 [meta_addattr_fg_expand]: 2.177e-05 [parallel-infer-symbol]: 1.402e-05 [pre_auto_parallel]: 0.00015901 [insert-virtual-dataset]: 8.54e-06 [parallel-infer-symbol-second]: 4.74e-06 [dataset_repeat_opt]: 8.3e-06 [pipeline_split]: 7.62998e-06 [optimize]: 0.0332945, [53] [py_interpret_to_execute]: 0.00011853 [rewriter_before_opt_a]: 0.00043205 [opt_a]: 0.0202366, [2] [Cycle 1]: 0.0128239, [45] [expand_dump_flag]: 1.292e-05 [switch_simplify]: 0.00016412 [loop_unroll]: 9.586e-05 [a_1]: 0.00219533 [with_stream_mark]: 0.00014999 [recompute_prepare]: 0.00010745 [updatestate_depend_eliminate]: 3.099e-05 [updatestate_assign_eliminate]: 2.264e-05 [updatestate_loads_eliminate]: 2.268e-05 [parameter_eliminate]: 1.207e-05 [a_2]: 0.00096077 [accelerated_algorithm]: 8.178e-05 [shard]: 1.414e-05 [meta_shard_fg_expand]: 1.594e-05 [shard_inline]: 8.411e-05 [merge_send_recv]: 7.295e-05 [auto_parallel]: 6.782e-05 [parallel]: 0.00015763 [flash_sp]: 0.00020071 [merge_comm]: 4.406e-05 [allreduce_fusion]: 3.024e-05 [matmul_add_comm_reduction]: 6.538e-05 [allreduce_slice_to_reducescatter]: 4.2e-06 [virtual_shard_identity]: 0.00012944 [virtual_dataset]: 6.949e-05 [get_grad_eliminate_]: 5.282e-05 [virtual_output]: 5.926e-05 [merge_forward]: 3.708e-05 [cell_reuse_recompute_pass]: 1.527e-05 [offload_activation]: 6.784e-05 [cell_reuse_handle_not_recompute_node_pass]: 0.00014181 [merge_recompute_call_nodes]: 9.67001e-06 [before_grad]: 0.00010227 [set_forward_comm_id_for_comm_node_pass]: 4.653e-05 [meta_fg_expand]: 2.236e-05 [flash_sp_send_recv_attached]: 2.75e-05 [receive_attached]: 2.755e-05 [after_resolve]: 0.00016717 [a_after_grad]: 9.52e-05 [renormalize]: 0.00387601 [add_forward_monad_depend]: 5.06e-05 [auto_monad_grad]: 1.256e-05 [auto_monad_eliminator]: 0.00019843 [cse]: 0.00035634 [a_3]: 0.00050811 [Cycle 2]: 0.00732455, [45] [expand_dump_flag]: 1.303e-05 [switch_simplify]: 0.00010609 [loop_unroll]: 7.073e-05 [a_1]: 0.00159889 [with_stream_mark]: 0.00014993 [recompute_prepare]: 0.0001024 [updatestate_depend_eliminate]: 3.662e-05 [updatestate_assign_eliminate]: 2.121e-05 [updatestate_loads_eliminate]: 2.359e-05 [parameter_eliminate]: 1.258e-05 [a_2]: 0.00075173 [accelerated_algorithm]: 7.015e-05 [shard]: 1.261e-05 [meta_shard_fg_expand]: 1.931e-05 [shard_inline]: 6.701e-05 [merge_send_recv]: 5.535e-05 [auto_parallel]: 6.427e-05 [parallel]: 4.849e-05 [flash_sp]: 4.51e-05 [merge_comm]: 3.403e-05 [allreduce_fusion]: 2.792e-05 [matmul_add_comm_reduction]: 7.072e-05 [allreduce_slice_to_reducescatter]: 8.3e-06 [virtual_shard_identity]: 0.00011158 [virtual_dataset]: 0.0001666 [get_grad_eliminate_]: 7.991e-05 [virtual_output]: 5.26e-05 [merge_forward]: 3.517e-05 [cell_reuse_recompute_pass]: 3.506e-05 [offload_activation]: 7.671e-05 [cell_reuse_handle_not_recompute_node_pass]: 0.0001374 [merge_recompute_call_nodes]: 8.90001e-06 [before_grad]: 8.796e-05 [set_forward_comm_id_for_comm_node_pass]: 3.068e-05 [meta_fg_expand]: 2.096e-05 [flash_sp_send_recv_attached]: 8.23999e-06 [receive_attached]: 1.033e-05 [after_resolve]: 0.00014397 [a_after_grad]: 0.00011139 [renormalize]: 2.00002e-07 [add_forward_monad_depend]: 2.402e-05 [auto_monad_grad]: 1.773e-05 [auto_monad_eliminator]: 9.894e-05 [cse]: 0.00026011 [a_3]: 0.00049048 [py_interpret_to_execute_after_opt_a]: 0.00012068 [slice_cell_reuse_recomputed_activation]: 1.373e-05 [rewriter_after_opt_a]: 0.00088108 [convert_after_rewriter]: 6.781e-05 [order_py_execute_after_rewriter]: 3.797e-05 [mutable_eliminate]: 0.00846892 [opt_b]: 0.00043061, [1] [Cycle 1]: 0.00041548, [7] [b_1]: 0.00024342 [b_2]: 1.422e-05 [updatestate_depend_eliminate]: 1.823e-05 [updatestate_assign_eliminate]: 4.87998e-06 [updatestate_loads_eliminate]: 4.68999e-06 [renormalize]: 1.25001e-06 [cse]: 7.725e-05 [optimize_parallel_all_gather_comm]: 3.102e-05 [overlap_param_gather]: 7.09001e-06 [cconv]: 4.622e-05 [loop_unroll]: 0.00081789 [opt_after_cconv]: 0.00019059, [1] [Cycle 1]: 0.00018069, [7] [c_1]: 5.648e-05 [parameter_eliminate]: 6.69001e-06 [updatestate_depend_eliminate]: 1.258e-05 [updatestate_assign_eliminate]: 4.84e-06 [updatestate_loads_eliminate]: 4.16001e-06 [cse]: 5.673e-05 [renormalize]: 1.03001e-06 [remove_dup_value]: 0.00012306 [tuple_transform]: 0.0001311, [1] [Cycle 1]: 0.00012508, [4] [d_1]: 8.906e-05 [none_parameter_eliminate]: 2.84999e-06 [renormalize]: 2.10013e-07 [switch_simplify]: 1.169e-05 [partial_unused_args_eliminate]: 2.49999e-06 [add_recomputation]: 7.955e-05 [cse_after_recomputation]: 3.714e-05, [1] [Cycle 1]: 3.251e-05, [1] [cse]: 2.505e-05 [environ_conv]: 2.354e-05 [swap_dp_allreduce_reducescatter]: 8.54e-06 [bias_add_comm_swap]: 3.55998e-06 [label_micro_interleaved_index]: 8.38001e-06 [label_fine_grained_interleaved_index]: 2.71e-06 [merge_cast_opt]: 1.80001e-06 [slice_recompute_activation]: 2.68e-06 [micro_interleaved_order_control]: 2.96001e-06 [assign_add_opt]: 1.87001e-06 [ForceFp32Comm]: 1.00999e-06 [remove_cast_before_assign_add]: 1.05001e-06 [full_micro_interleaved_order_control]: 2.41e-06 [reorder_send_recv_between_fp_bp]: 3.04999e-06 [comm_op_add_attrs]: 1.07e-06 [add_comm_op_reuse_tag]: 9.90025e-07 [interleave_split_concat_branches]: 1.17999e-06 [interleave_parallel_branches]: 1.14e-06 [overlap_opt_shard_in_pipeline]: 2.342e-05 [overlap_opt_shard_grad_in_pipeline]: 1.84998e-06 [control_data_broadcast_order]: 1.981e-05 [grouped_pairwise_exchange_alltoall]: 1.92999e-06 [offloading_packed_experts]: 5.46e-06 [overlap_recompute_and_grad_model_parallel]: 6.06e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.47999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.45999e-06 [overlap_recompute_comm]: 2.49999e-06 [overlap_grad_ring_attention]: 5.71e-06 [overlap_grad_flash_sp]: 5.351e-05 [begin_end_overlap_inline]: 5.40022e-07 [split_matmul_comm_elemetwise]: 2.45002e-06 [split_layernorm_comm]: 1.89e-06 [handle_group_info]: 1.19e-06 [symbol_engine_optimizer]: 0.00023436, [1] [Cycle 1]: 0.00022899, [6] [build]: 0.00010613 [elim_shapecalc]: 1.892e-05 [elim_not_effective]: 2.944e-05 [opt_reshape]: 1.146e-05 [fold_const_symbol]: 2.323e-05 [renormalize]: 5.19998e-07 [detach_backward]: 2.55002e-06 [pipeline_parallel_scheduler]: 1.55001e-06 [auto_monad_reorder]: 3.144e-05 [get_jit_bprop_graph]: 2.56998e-06 [rewriter_after_jit_bprop_graph]: 6.22001e-06 [opt_after_jit_grad]: 0.0007257 [validate]: 7.721e-05 Sums bootstrap : 0.000783s : 0.95% type_inference : 0.051855s : 63.02% event_method : 0.000016s : 0.02% auto_monad : 0.000096s : 0.12% graph_reusing : 0.000005s : 0.01% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000081s : 0.10% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000022s : 0.03% parallel-infer-symbol : 0.000014s : 0.02% pre_auto_parallel : 0.000159s : 0.19% insert-virtual-dataset : 0.000009s : 0.01% parallel-infer-symbol-second : 0.000005s : 0.01% dataset_repeat_opt : 0.000008s : 0.01% pipeline_split : 0.000008s : 0.01% optimize.py_interpret_to_execute : 0.000119s : 0.14% optimize.rewriter_before_opt_a : 0.000432s : 0.53% optimize.opt_a.expand_dump_flag : 0.000026s : 0.03% optimize.opt_a.switch_simplify : 0.000270s : 0.33% optimize.opt_a.loop_unroll : 0.000167s : 0.20% optimize.opt_a.a_1 : 0.003794s : 4.61% optimize.opt_a.with_stream_mark : 0.000300s : 0.36% optimize.opt_a.recompute_prepare : 0.000210s : 0.26% optimize.opt_a.updatestate_depend_eliminate : 0.000068s : 0.08% optimize.opt_a.updatestate_assign_eliminate : 0.000044s : 0.05% optimize.opt_a.updatestate_loads_eliminate : 0.000046s : 0.06% optimize.opt_a.parameter_eliminate : 0.000025s : 0.03% optimize.opt_a.a_2 : 0.001713s : 2.08% optimize.opt_a.accelerated_algorithm : 0.000152s : 0.18% optimize.opt_a.shard : 0.000027s : 0.03% optimize.opt_a.meta_shard_fg_expand : 0.000035s : 0.04% optimize.opt_a.shard_inline : 0.000151s : 0.18% optimize.opt_a.merge_send_recv : 0.000128s : 0.16% optimize.opt_a.auto_parallel : 0.000132s : 0.16% optimize.opt_a.parallel : 0.000206s : 0.25% optimize.opt_a.flash_sp : 0.000246s : 0.30% optimize.opt_a.merge_comm : 0.000078s : 0.09% optimize.opt_a.allreduce_fusion : 0.000058s : 0.07% optimize.opt_a.matmul_add_comm_reduction : 0.000136s : 0.17% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000013s : 0.02% optimize.opt_a.virtual_shard_identity : 0.000241s : 0.29% optimize.opt_a.virtual_dataset : 0.000236s : 0.29% optimize.opt_a.get_grad_eliminate_ : 0.000133s : 0.16% optimize.opt_a.virtual_output : 0.000112s : 0.14% optimize.opt_a.merge_forward : 0.000072s : 0.09% optimize.opt_a.cell_reuse_recompute_pass : 0.000050s : 0.06% optimize.opt_a.offload_activation : 0.000145s : 0.18% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000279s : 0.34% optimize.opt_a.merge_recompute_call_nodes : 0.000019s : 0.02% optimize.opt_a.before_grad : 0.000190s : 0.23% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000077s : 0.09% optimize.opt_a.meta_fg_expand : 0.000043s : 0.05% optimize.opt_a.flash_sp_send_recv_attached : 0.000036s : 0.04% optimize.opt_a.receive_attached : 0.000038s : 0.05% optimize.opt_a.after_resolve : 0.000311s : 0.38% optimize.opt_a.a_after_grad : 0.000207s : 0.25% optimize.opt_a.renormalize : 0.003876s : 4.71% optimize.opt_a.add_forward_monad_depend : 0.000075s : 0.09% optimize.opt_a.auto_monad_grad : 0.000030s : 0.04% optimize.opt_a.auto_monad_eliminator : 0.000297s : 0.36% optimize.opt_a.cse : 0.000616s : 0.75% optimize.opt_a.a_3 : 0.000999s : 1.21% optimize.py_interpret_to_execute_after_opt_a : 0.000121s : 0.15% optimize.slice_cell_reuse_recomputed_activation : 0.000014s : 0.02% optimize.rewriter_after_opt_a : 0.000881s : 1.07% optimize.convert_after_rewriter : 0.000068s : 0.08% optimize.order_py_execute_after_rewriter : 0.000038s : 0.05% optimize.mutable_eliminate : 0.008469s : 10.29% optimize.opt_b.b_1 : 0.000243s : 0.30% optimize.opt_b.b_2 : 0.000014s : 0.02% optimize.opt_b.updatestate_depend_eliminate : 0.000018s : 0.02% optimize.opt_b.updatestate_assign_eliminate : 0.000005s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000077s : 0.09% optimize.optimize_parallel_all_gather_comm : 0.000031s : 0.04% optimize.overlap_param_gather : 0.000007s : 0.01% optimize.cconv : 0.000046s : 0.06% optimize.loop_unroll : 0.000818s : 0.99% optimize.opt_after_cconv.c_1 : 0.000056s : 0.07% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.01% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.02% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.01% optimize.opt_after_cconv.cse : 0.000057s : 0.07% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000123s : 0.15% optimize.tuple_transform.d_1 : 0.000089s : 0.11% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000012s : 0.01% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000080s : 0.10% optimize.cse_after_recomputation.cse : 0.000025s : 0.03% optimize.environ_conv : 0.000024s : 0.03% optimize.swap_dp_allreduce_reducescatter : 0.000009s : 0.01% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000008s : 0.01% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000023s : 0.03% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000020s : 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 : 0.000006s : 0.01% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000006s : 0.01% optimize.overlap_grad_flash_sp : 0.000054s : 0.07% 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 : 0.000106s : 0.13% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000019s : 0.02% optimize.symbol_engine_optimizer.elim_not_effective : 0.000029s : 0.04% optimize.symbol_engine_optimizer.opt_reshape : 0.000011s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000023s : 0.03% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000031s : 0.04% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.01% opt_after_jit_grad : 0.000726s : 0.88% validate : 0.000077s : 0.09% Time group info: ------[substitution.] 0.000704 36 1.56% : 0.000011s : 2: substitution.elim_not_effective 1.40% : 0.000010s : 2: substitution.fold_const_symbol 1.28% : 0.000009s : 9: substitution.graph_param_transform 75.76% : 0.000534s : 1: substitution.inline 4.93% : 0.000035s : 4: substitution.j_node_and_user_rematch 5.06% : 0.000036s : 4: substitution.remove_not_recompute_node 10.03% : 0.000071s : 14: substitution.replace_old_param ------[type_inference.] 0.051755 2 98.93% : 0.051201s : 1: type_inference.infer 1.07% : 0.000553s : 1: type_inference.specialize ------[replace.] 0.000105 1 100.00% : 0.000105s : 1: replace.inline ------[match.] 0.000526 1 100.00% : 0.000526s : 1: match.inline ------[predicate.] 0.001227 2107 0.77% : 0.000009s : 19: predicate.accumulaten_eliminater 0.21% : 0.000003s : 9: predicate.ad_related_special_op_eliminate 0.39% : 0.000005s : 18: predicate.addn_check_dump 1.61% : 0.000020s : 19: predicate.addn_zero_filter 1.02% : 0.000013s : 19: predicate.adjust_all_reduce_mul_add 2.63% : 0.000032s : 37: predicate.arithmetic_simplify 0.75% : 0.000009s : 19: predicate.cast_eliminate 1.78% : 0.000022s : 18: predicate.check_bprop_eliminate 0.68% : 0.000008s : 18: predicate.compare_switch_simplify 0.06% : 0.000001s : 9: predicate.const_output_eliminate 1.22% : 0.000015s : 18: predicate.depend_value_elim 0.98% : 0.000012s : 19: predicate.dict_get_item_const_eliminator 1.25% : 0.000015s : 19: predicate.dict_get_item_eliminator 1.74% : 0.000021s : 19: predicate.dict_set_item_eliminator 0.28% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.08% : 0.000001s : 9: predicate.elim_not_effective 0.15% : 0.000002s : 9: predicate.elim_shapecalc_of_broadcastargs 1.38% : 0.000017s : 28: predicate.environ_add_const_eliminate 0.83% : 0.000010s : 28: predicate.environ_get_add_eliminate 0.53% : 0.000006s : 28: predicate.environ_get_depend_swap 2.57% : 0.000032s : 46: predicate.environ_get_eliminate 0.84% : 0.000010s : 28: predicate.environ_get_set_eliminate 0.23% : 0.000003s : 20: predicate.exchange_switch_depend_value 1.62% : 0.000020s : 20: predicate.float_depend_g_call 1.00% : 0.000012s : 18: predicate.float_environ_get_switch 0.56% : 0.000007s : 27: predicate.float_tuple_getitem_switch 0.05% : 0.000001s : 9: predicate.fold_const_symbol 0.93% : 0.000011s : 18: predicate.get_grad_eliminate 0.08% : 0.000001s : 9: predicate.graph_param_transform 1.00% : 0.000012s : 18: predicate.incorporate_call 0.40% : 0.000005s : 18: predicate.incorporate_call_switch 4.76% : 0.000058s : 93: predicate.inline 1.15% : 0.000014s : 18: predicate.inline_without_move 0.41% : 0.000005s : 18: predicate.j_node_and_user_rematch 1.27% : 0.000016s : 18: predicate.less_batch_normalization 1.15% : 0.000014s : 37: predicate.list_to_tuple_eliminator_ 2.25% : 0.000028s : 56: predicate.load_eliminater 0.33% : 0.000004s : 9: predicate.loop_unroll_after_grad 1.90% : 0.000023s : 28: predicate.loop_unroll_before_grad 1.05% : 0.000013s : 37: predicate.make_slice_get_slice_eliminator 1.69% : 0.000021s : 18: predicate.merge_addn 0.83% : 0.000010s : 18: predicate.micro_step_allgather_replace 0.73% : 0.000009s : 18: predicate.mini_step_allgather_replace 0.46% : 0.000006s : 19: predicate.minmaximum_grad 2.11% : 0.000026s : 9: predicate.mutable_eliminate 0.08% : 0.000001s : 9: predicate.opt_reshape 0.10% : 0.000001s : 9: predicate.parallel_virtual_node 2.60% : 0.000032s : 20: predicate.partial_defer_inline 1.16% : 0.000014s : 28: predicate.partial_eliminate 0.45% : 0.000005s : 19: predicate.print_const_string_wrapper 0.19% : 0.000002s : 18: predicate.reduce_all_const_elim 0.30% : 0.000004s : 19: predicate.reduce_eliminate 2.78% : 0.000034s : 56: predicate.redundant_stop_gradient_eliminater 1.04% : 0.000013s : 18: predicate.remove_not_recompute_node 2.17% : 0.000027s : 37: predicate.replace_applicator 1.32% : 0.000016s : 18: predicate.replace_old_param 0.13% : 0.000002s : 9: predicate.reset_defer_inline 0.79% : 0.000010s : 19: predicate.reshape_eliminate 1.29% : 0.000016s : 18: predicate.row_tensor_add_zeros_like 0.09% : 0.000001s : 9: predicate.row_tensor_eliminate 1.57% : 0.000019s : 18: predicate.same_eliminate 1.04% : 0.000013s : 18: predicate.set_cell_output_no_recompute 1.45% : 0.000018s : 18: predicate.shard_identity_eliminate 0.19% : 0.000002s : 18: predicate.special_op_eliminate 2.78% : 0.000034s : 18: predicate.specialize_transform 1.93% : 0.000024s : 18: predicate.split_environ_get_set_with_tuple_value 1.34% : 0.000017s : 18: predicate.stack_unstack_eliminate 0.11% : 0.000001s : 9: predicate.switch_call_monad_eliminater 1.52% : 0.000019s : 20: predicate.switch_defer_inline 2.38% : 0.000029s : 38: predicate.switch_layer_defer_inline 3.42% : 0.000042s : 75: predicate.switch_simplify 0.44% : 0.000005s : 19: predicate.tile_eliminate 0.76% : 0.000009s : 19: predicate.transpose_eliminate 1.21% : 0.000015s : 37: predicate.tuple_list_convert_item_index_to_positive 1.24% : 0.000015s : 37: predicate.tuple_list_get_item_const_eliminator 0.82% : 0.000010s : 37: predicate.tuple_list_get_item_depend_reorder 2.40% : 0.000029s : 55: predicate.tuple_list_get_item_eliminator 1.18% : 0.000015s : 37: predicate.tuple_list_get_set_item_eliminator 1.13% : 0.000014s : 55: predicate.tuple_list_set_item_eliminator 0.64% : 0.000008s : 37: predicate.tuple_to_list_eliminator_ 1.30% : 0.000016s : 56: predicate.updatestate_pure_node_eliminater 6.09% : 0.000075s : 74: predicate.updatestate_useless_node_eliminater 0.10% : 0.000001s : 9: predicate.value_based_eliminate 1.15% : 0.000014s : 18: predicate.virtual_dataset_eliminate 1.03% : 0.000013s : 18: predicate.virtual_output_eliminate 0.07% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.45% : 0.000006s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001050 6 29.93% : 0.000314s : 3: func_graph_cloner_run.FuncGraphClonerGraph 70.07% : 0.000736s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.226751 192 0.00% : 0.000004s : 1: ForceFp32Comm 19.53% : 0.044284s : 1: add_attr 19.50% : 0.044227s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.04% : 0.000085s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.04% : 0.000102s : 1: auto_monad 0.02% : 0.000037s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.36% : 0.000826s : 1: bootstrap 0.02% : 0.000050s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.01% : 0.000023s : 1: control_data_broadcast_order 0.04% : 0.000094s : 1: convert_after_rewriter 0.02% : 0.000040s : 1: cse_after_recomputation 0.01% : 0.000024s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.01% : 0.000028s : 1: environ_conv 0.01% : 0.000023s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 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 0.01% : 0.000028s : 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% : 0.000011s : 1: label_micro_interleaved_index 0.37% : 0.000835s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 3.75% : 0.008500s : 1: mutable_eliminate 0.00% : 0.000008s : 1: offloading_packed_experts 0.01% : 0.000032s : 1: opt.transform.loop_unroll_optimizer 2.25% : 0.005104s : 1: opt.transform.mutable_eliminate 3.70% : 0.008382s : 78: opt.transform.opt_a 0.02% : 0.000055s : 1: opt.transform.opt_after_cconv 0.02% : 0.000046s : 1: opt.transform.opt_after_jit_grad 0.10% : 0.000219s : 28: opt.transform.opt_b 0.04% : 0.000097s : 2: opt.transform.opt_trans_graph 0.03% : 0.000079s : 4: opt.transform.symbol_engine_opt 8.93% : 0.020255s : 1: opt_a 0.09% : 0.000195s : 1: opt_after_cconv 0.33% : 0.000740s : 1: opt_after_jit_grad 0.19% : 0.000437s : 1: opt_b 14.69% : 0.033304s : 1: optimize 0.02% : 0.000035s : 1: optimize_parallel_all_gather_comm 0.03% : 0.000059s : 1: order_py_execute_after_rewriter 0.03% : 0.000058s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000010s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.01% : 0.000027s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000011s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000009s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.02% : 0.000039s : 1: parallel-infer-symbol 0.01% : 0.000017s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.01% : 0.000021s : 1: pipeline_split 0.08% : 0.000184s : 1: pre_auto_parallel 0.06% : 0.000140s : 1: py_interpret_to_execute 0.07% : 0.000153s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.06% : 0.000130s : 1: remove_dup_value 0.86% : 0.001942s : 1: renormalize.infer 0.83% : 0.001876s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.42% : 0.000950s : 1: rewriter_after_opt_a 0.21% : 0.000474s : 1: rewriter_before_opt_a 0.01% : 0.000032s : 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 0.01% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.10% : 0.000237s : 1: symbol_engine_optimizer 0.06% : 0.000134s : 1: tuple_transform 22.88% : 0.051878s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_lookahead0[0] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_lookahead0[0],max_mem:936.0M [WARNING] ME(168514:281473890443056,MainProcess):2026-01-29-17:38:29.419.078 [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 = 0.193935, [21] [bootstrap]: 0.00068331 [type_inference]: 0.0843635 [event_method]: 1.978e-05 [auto_monad]: 7.769e-05 [graph_reusing]: 5.91e-06 [inline]: 3.28e-06 [add_attr]: 0.0272638, [1] [add_attr_with_inline]: 0.0272453, [1] [Cycle 1]: 8.25e-05, [2] [tag_attr]: 2.397e-05 [meta_addattr_fg_expand]: 4.18999e-06 [parallel-infer-symbol]: 4.07998e-06 [pre_auto_parallel]: 3.947e-05 [insert-virtual-dataset]: 2.65997e-06 [parallel-infer-symbol-second]: 8.10018e-07 [dataset_repeat_opt]: 2.27999e-06 [pipeline_split]: 1.69998e-06 [optimize]: 0.0806112, [53] [py_interpret_to_execute]: 3.573e-05 [rewriter_before_opt_a]: 8.158e-05 [opt_a]: 0.0776484, [2] [Cycle 1]: 0.0765571, [45] [expand_dump_flag]: 3.33e-06 [switch_simplify]: 3.188e-05 [loop_unroll]: 1.838e-05 [a_1]: 0.0712891 [with_stream_mark]: 4.715e-05 [recompute_prepare]: 2.501e-05 [updatestate_depend_eliminate]: 8.45001e-06 [updatestate_assign_eliminate]: 5.34e-06 [updatestate_loads_eliminate]: 5.10999e-06 [parameter_eliminate]: 2.66999e-06 [a_2]: 0.0001482 [accelerated_algorithm]: 1.204e-05 [shard]: 3.07002e-06 [meta_shard_fg_expand]: 5.19998e-06 [shard_inline]: 1.069e-05 [merge_send_recv]: 1.218e-05 [auto_parallel]: 1.285e-05 [parallel]: 4.258e-05 [flash_sp]: 1.633e-05 [merge_comm]: 5.27999e-06 [allreduce_fusion]: 4.75001e-06 [matmul_add_comm_reduction]: 1.446e-05 [allreduce_slice_to_reducescatter]: 9.09989e-07 [virtual_shard_identity]: 1.32e-05 [virtual_dataset]: 1.12e-05 [get_grad_eliminate_]: 1.016e-05 [virtual_output]: 1.016e-05 [merge_forward]: 5.91998e-06 [cell_reuse_recompute_pass]: 3.66001e-06 [offload_activation]: 1.391e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.722e-05 [merge_recompute_call_nodes]: 1.54e-06 [before_grad]: 1.568e-05 [set_forward_comm_id_for_comm_node_pass]: 5.98998e-06 [meta_fg_expand]: 4.32998e-06 [flash_sp_send_recv_attached]: 2.57001e-06 [receive_attached]: 3.32002e-06 [after_resolve]: 2.215e-05 [a_after_grad]: 1.598e-05 [renormalize]: 0.00409557 [add_forward_monad_depend]: 1.124e-05 [auto_monad_grad]: 2.98e-06 [auto_monad_eliminator]: 2.474e-05 [cse]: 8.016e-05 [a_3]: 9.145e-05 [Cycle 2]: 0.00107533, [45] [expand_dump_flag]: 2.66e-06 [switch_simplify]: 1.431e-05 [loop_unroll]: 1.07e-05 [a_1]: 0.00026972 [with_stream_mark]: 2.186e-05 [recompute_prepare]: 1.178e-05 [updatestate_depend_eliminate]: 6.22001e-06 [updatestate_assign_eliminate]: 5.05001e-06 [updatestate_loads_eliminate]: 5.50001e-06 [parameter_eliminate]: 1.65001e-06 [a_2]: 0.00013018 [accelerated_algorithm]: 1.112e-05 [shard]: 2.79999e-06 [meta_shard_fg_expand]: 2.93e-06 [shard_inline]: 1.018e-05 [merge_send_recv]: 1.032e-05 [auto_parallel]: 1.068e-05 [parallel]: 9.06002e-06 [flash_sp]: 3.93001e-06 [merge_comm]: 5.02e-06 [allreduce_fusion]: 4.87998e-06 [matmul_add_comm_reduction]: 1.194e-05 [allreduce_slice_to_reducescatter]: 9.40025e-07 [virtual_shard_identity]: 1.136e-05 [virtual_dataset]: 1.069e-05 [get_grad_eliminate_]: 1.02e-05 [virtual_output]: 9.69999e-06 [merge_forward]: 6.02999e-06 [cell_reuse_recompute_pass]: 2.37999e-06 [offload_activation]: 1.331e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.018e-05 [merge_recompute_call_nodes]: 1.82001e-06 [before_grad]: 1.516e-05 [set_forward_comm_id_for_comm_node_pass]: 5.73002e-06 [meta_fg_expand]: 3.03e-06 [flash_sp_send_recv_attached]: 1.57999e-06 [receive_attached]: 2.32999e-06 [after_resolve]: 2.27e-05 [a_after_grad]: 1.592e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 2.21003e-06 [auto_monad_grad]: 2.01e-06 [auto_monad_eliminator]: 1.186e-05 [cse]: 4.633e-05 [a_3]: 6.533e-05 [py_interpret_to_execute_after_opt_a]: 2.485e-05 [slice_cell_reuse_recomputed_activation]: 1.98002e-06 [rewriter_after_opt_a]: 6.284e-05 [convert_after_rewriter]: 1.015e-05 [order_py_execute_after_rewriter]: 7.98001e-06 [mutable_eliminate]: 0.00077952 [opt_b]: 0.00034949, [1] [Cycle 1]: 0.00033983, [7] [b_1]: 0.00021362 [b_2]: 1.181e-05 [updatestate_depend_eliminate]: 8.92e-06 [updatestate_assign_eliminate]: 4.37e-06 [updatestate_loads_eliminate]: 4.3e-06 [renormalize]: 5.69999e-07 [cse]: 5.685e-05 [optimize_parallel_all_gather_comm]: 2.446e-05 [overlap_param_gather]: 3.48e-06 [cconv]: 3.367e-05 [loop_unroll]: 0.00048003 [opt_after_cconv]: 0.00016429, [1] [Cycle 1]: 0.00015723, [7] [c_1]: 5.212e-05 [parameter_eliminate]: 4.90999e-06 [updatestate_depend_eliminate]: 8.11002e-06 [updatestate_assign_eliminate]: 4.50001e-06 [updatestate_loads_eliminate]: 4.32e-06 [cse]: 4.293e-05 [renormalize]: 1.37e-06 [remove_dup_value]: 6.981e-05 [tuple_transform]: 0.00011706, [1] [Cycle 1]: 0.00011186, [4] [d_1]: 7.697e-05 [none_parameter_eliminate]: 1.94999e-06 [renormalize]: 1.8999e-07 [switch_simplify]: 1.193e-05 [partial_unused_args_eliminate]: 1.90001e-06 [add_recomputation]: 7.159e-05 [cse_after_recomputation]: 3.551e-05, [1] [Cycle 1]: 3.052e-05, [1] [cse]: 2.353e-05 [environ_conv]: 7.39002e-06 [swap_dp_allreduce_reducescatter]: 7.77998e-06 [bias_add_comm_swap]: 3.54002e-06 [label_micro_interleaved_index]: 7.06001e-06 [label_fine_grained_interleaved_index]: 3.71001e-06 [merge_cast_opt]: 1.44e-06 [slice_recompute_activation]: 2.26e-06 [micro_interleaved_order_control]: 2.82002e-06 [assign_add_opt]: 1.32e-06 [ForceFp32Comm]: 8.70001e-07 [remove_cast_before_assign_add]: 1.37e-06 [full_micro_interleaved_order_control]: 2.44999e-06 [reorder_send_recv_between_fp_bp]: 2.91999e-06 [comm_op_add_attrs]: 1.09998e-06 [add_comm_op_reuse_tag]: 1.17999e-06 [interleave_split_concat_branches]: 1.52999e-06 [interleave_parallel_branches]: 1.18001e-06 [overlap_opt_shard_in_pipeline]: 3.11999e-06 [overlap_opt_shard_grad_in_pipeline]: 2.27001e-06 [control_data_broadcast_order]: 1.706e-05 [grouped_pairwise_exchange_alltoall]: 2.21e-06 [offloading_packed_experts]: 5.90002e-06 [overlap_recompute_and_grad_model_parallel]: 5.71003e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.79998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.63002e-06 [overlap_recompute_comm]: 2.85998e-06 [overlap_grad_ring_attention]: 5.17e-06 [overlap_grad_flash_sp]: 2.681e-05 [begin_end_overlap_inline]: 5.39992e-07 [split_matmul_comm_elemetwise]: 2.32999e-06 [split_layernorm_comm]: 2.04e-06 [handle_group_info]: 1.09003e-06 [symbol_engine_optimizer]: 0.00020967, [1] [Cycle 1]: 0.00020394, [6] [build]: 9.743e-05 [elim_shapecalc]: 1.718e-05 [elim_not_effective]: 2.074e-05 [opt_reshape]: 1.094e-05 [fold_const_symbol]: 2.068e-05 [renormalize]: 2.50002e-07 [detach_backward]: 2.31998e-06 [pipeline_parallel_scheduler]: 1.89e-06 [auto_monad_reorder]: 2.965e-05 [get_jit_bprop_graph]: 1.84e-06 [rewriter_after_jit_bprop_graph]: 6.78e-06 [opt_after_jit_grad]: 0.00055219 [validate]: 6.149e-05 Sums bootstrap : 0.000683s : 0.41% type_inference : 0.084363s : 50.99% event_method : 0.000020s : 0.01% auto_monad : 0.000078s : 0.05% graph_reusing : 0.000006s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000024s : 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 : 0.000039s : 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 : 0.000036s : 0.02% optimize.rewriter_before_opt_a : 0.000082s : 0.05% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000046s : 0.03% optimize.opt_a.loop_unroll : 0.000029s : 0.02% optimize.opt_a.a_1 : 0.071559s : 43.25% optimize.opt_a.with_stream_mark : 0.000069s : 0.04% optimize.opt_a.recompute_prepare : 0.000037s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000015s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000010s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000011s : 0.01% optimize.opt_a.parameter_eliminate : 0.000004s : 0.00% optimize.opt_a.a_2 : 0.000278s : 0.17% optimize.opt_a.accelerated_algorithm : 0.000023s : 0.01% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000008s : 0.00% optimize.opt_a.shard_inline : 0.000021s : 0.01% optimize.opt_a.merge_send_recv : 0.000022s : 0.01% optimize.opt_a.auto_parallel : 0.000024s : 0.01% optimize.opt_a.parallel : 0.000052s : 0.03% optimize.opt_a.flash_sp : 0.000020s : 0.01% optimize.opt_a.merge_comm : 0.000010s : 0.01% optimize.opt_a.allreduce_fusion : 0.000010s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000026s : 0.02% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000025s : 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 : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000027s : 0.02% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 0.03% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000031s : 0.02% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000012s : 0.01% optimize.opt_a.meta_fg_expand : 0.000007s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000004s : 0.00% optimize.opt_a.receive_attached : 0.000006s : 0.00% optimize.opt_a.after_resolve : 0.000045s : 0.03% optimize.opt_a.a_after_grad : 0.000032s : 0.02% optimize.opt_a.renormalize : 0.004096s : 2.48% optimize.opt_a.add_forward_monad_depend : 0.000013s : 0.01% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000037s : 0.02% optimize.opt_a.cse : 0.000126s : 0.08% optimize.opt_a.a_3 : 0.000157s : 0.09% optimize.py_interpret_to_execute_after_opt_a : 0.000025s : 0.02% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000063s : 0.04% optimize.convert_after_rewriter : 0.000010s : 0.01% optimize.order_py_execute_after_rewriter : 0.000008s : 0.00% optimize.mutable_eliminate : 0.000780s : 0.47% optimize.opt_b.b_1 : 0.000214s : 0.13% optimize.opt_b.b_2 : 0.000012s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000009s : 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 : 0.000001s : 0.00% optimize.opt_b.cse : 0.000057s : 0.03% optimize.optimize_parallel_all_gather_comm : 0.000024s : 0.01% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000034s : 0.02% optimize.loop_unroll : 0.000480s : 0.29% optimize.opt_after_cconv.c_1 : 0.000052s : 0.03% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.cse : 0.000043s : 0.03% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000070s : 0.04% optimize.tuple_transform.d_1 : 0.000077s : 0.05% 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 : 0.01% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000072s : 0.04% optimize.cse_after_recomputation.cse : 0.000024s : 0.01% optimize.environ_conv : 0.000007s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000008s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000007s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000004s : 0.00% optimize.merge_cast_opt : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 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 : 0.000003s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000017s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000006s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000006s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000002s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000005s : 0.00% optimize.overlap_grad_flash_sp : 0.000027s : 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 : 0.000097s : 0.06% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000011s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000021s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000030s : 0.02% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000552s : 0.33% validate : 0.000061s : 0.04% Time group info: ------[substitution.] 0.000176 36 2.43% : 0.000004s : 2: substitution.elim_not_effective 4.40% : 0.000008s : 2: substitution.fold_const_symbol 4.51% : 0.000008s : 9: substitution.graph_param_transform 76.32% : 0.000135s : 1: substitution.inline 2.62% : 0.000005s : 4: substitution.j_node_and_user_rematch 3.37% : 0.000006s : 4: substitution.remove_not_recompute_node 6.34% : 0.000011s : 14: substitution.replace_old_param ------[type_inference.] 0.084238 2 98.90% : 0.083314s : 1: type_inference.infer 1.10% : 0.000923s : 1: type_inference.specialize ------[replace.] 0.000023 1 100.00% : 0.000023s : 1: replace.inline ------[match.] 0.000132 1 100.00% : 0.000132s : 1: match.inline ------[predicate.] 0.000257 2107 0.81% : 0.000002s : 19: predicate.accumulaten_eliminater 0.81% : 0.000002s : 9: predicate.ad_related_special_op_eliminate 0.83% : 0.000002s : 18: predicate.addn_check_dump 1.06% : 0.000003s : 19: predicate.addn_zero_filter 0.72% : 0.000002s : 19: predicate.adjust_all_reduce_mul_add 2.25% : 0.000006s : 37: predicate.arithmetic_simplify 0.85% : 0.000002s : 19: predicate.cast_eliminate 0.82% : 0.000002s : 18: predicate.check_bprop_eliminate 0.73% : 0.000002s : 18: predicate.compare_switch_simplify 0.29% : 0.000001s : 9: predicate.const_output_eliminate 0.80% : 0.000002s : 18: predicate.depend_value_elim 0.92% : 0.000002s : 19: predicate.dict_get_item_const_eliminator 0.92% : 0.000002s : 19: predicate.dict_get_item_eliminator 0.82% : 0.000002s : 19: predicate.dict_set_item_eliminator 1.23% : 0.000003s : 18: predicate.dumpgradient_eliminate 0.34% : 0.000001s : 9: predicate.elim_not_effective 0.50% : 0.000001s : 9: predicate.elim_shapecalc_of_broadcastargs 1.12% : 0.000003s : 28: predicate.environ_add_const_eliminate 1.03% : 0.000003s : 28: predicate.environ_get_add_eliminate 1.06% : 0.000003s : 28: predicate.environ_get_depend_swap 2.00% : 0.000005s : 46: predicate.environ_get_eliminate 1.06% : 0.000003s : 28: predicate.environ_get_set_eliminate 0.87% : 0.000002s : 20: predicate.exchange_switch_depend_value 1.44% : 0.000004s : 20: predicate.float_depend_g_call 0.80% : 0.000002s : 18: predicate.float_environ_get_switch 1.05% : 0.000003s : 27: predicate.float_tuple_getitem_switch 0.31% : 0.000001s : 9: predicate.fold_const_symbol 0.82% : 0.000002s : 18: predicate.get_grad_eliminate 0.35% : 0.000001s : 9: predicate.graph_param_transform 0.75% : 0.000002s : 18: predicate.incorporate_call 0.65% : 0.000002s : 18: predicate.incorporate_call_switch 5.49% : 0.000014s : 93: predicate.inline 0.84% : 0.000002s : 18: predicate.inline_without_move 0.55% : 0.000001s : 18: predicate.j_node_and_user_rematch 1.04% : 0.000003s : 18: predicate.less_batch_normalization 2.03% : 0.000005s : 37: predicate.list_to_tuple_eliminator_ 2.09% : 0.000005s : 56: predicate.load_eliminater 0.89% : 0.000002s : 9: predicate.loop_unroll_after_grad 1.23% : 0.000003s : 28: predicate.loop_unroll_before_grad 1.82% : 0.000005s : 37: predicate.make_slice_get_slice_eliminator 0.99% : 0.000003s : 18: predicate.merge_addn 0.74% : 0.000002s : 18: predicate.micro_step_allgather_replace 0.74% : 0.000002s : 18: predicate.mini_step_allgather_replace 0.71% : 0.000002s : 19: predicate.minmaximum_grad 1.22% : 0.000003s : 9: predicate.mutable_eliminate 0.47% : 0.000001s : 9: predicate.opt_reshape 0.44% : 0.000001s : 9: predicate.parallel_virtual_node 1.10% : 0.000003s : 20: predicate.partial_defer_inline 1.94% : 0.000005s : 28: predicate.partial_eliminate 0.83% : 0.000002s : 19: predicate.print_const_string_wrapper 0.78% : 0.000002s : 18: predicate.reduce_all_const_elim 0.97% : 0.000002s : 19: predicate.reduce_eliminate 2.17% : 0.000006s : 56: predicate.redundant_stop_gradient_eliminater 0.82% : 0.000002s : 18: predicate.remove_not_recompute_node 1.67% : 0.000004s : 37: predicate.replace_applicator 0.80% : 0.000002s : 18: predicate.replace_old_param 0.34% : 0.000001s : 9: predicate.reset_defer_inline 0.84% : 0.000002s : 19: predicate.reshape_eliminate 0.82% : 0.000002s : 18: predicate.row_tensor_add_zeros_like 0.45% : 0.000001s : 9: predicate.row_tensor_eliminate 1.07% : 0.000003s : 18: predicate.same_eliminate 0.67% : 0.000002s : 18: predicate.set_cell_output_no_recompute 1.02% : 0.000003s : 18: predicate.shard_identity_eliminate 0.84% : 0.000002s : 18: predicate.special_op_eliminate 0.96% : 0.000002s : 18: predicate.specialize_transform 1.33% : 0.000003s : 18: predicate.split_environ_get_set_with_tuple_value 1.00% : 0.000003s : 18: predicate.stack_unstack_eliminate 0.39% : 0.000001s : 9: predicate.switch_call_monad_eliminater 0.79% : 0.000002s : 20: predicate.switch_defer_inline 1.55% : 0.000004s : 38: predicate.switch_layer_defer_inline 3.57% : 0.000009s : 75: predicate.switch_simplify 0.77% : 0.000002s : 19: predicate.tile_eliminate 0.79% : 0.000002s : 19: predicate.transpose_eliminate 1.57% : 0.000004s : 37: predicate.tuple_list_convert_item_index_to_positive 1.65% : 0.000004s : 37: predicate.tuple_list_get_item_const_eliminator 1.48% : 0.000004s : 37: predicate.tuple_list_get_item_depend_reorder 3.33% : 0.000009s : 55: predicate.tuple_list_get_item_eliminator 1.48% : 0.000004s : 37: predicate.tuple_list_get_set_item_eliminator 3.17% : 0.000008s : 55: predicate.tuple_list_set_item_eliminator 1.52% : 0.000004s : 37: predicate.tuple_to_list_eliminator_ 2.06% : 0.000005s : 56: predicate.updatestate_pure_node_eliminater 3.19% : 0.000008s : 74: predicate.updatestate_useless_node_eliminater 0.39% : 0.000001s : 9: predicate.value_based_eliminate 0.91% : 0.000002s : 18: predicate.virtual_dataset_eliminate 0.78% : 0.000002s : 18: predicate.virtual_output_eliminate 0.38% : 0.000001s : 9: predicate.virtual_view_grad_eliminate 0.53% : 0.000001s : 9: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000826 6 43.84% : 0.000362s : 3: func_graph_cloner_run.FuncGraphClonerGraph 56.16% : 0.000464s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.378495 192 0.00% : 0.000004s : 1: ForceFp32Comm 7.21% : 0.027271s : 1: add_attr 7.20% : 0.027253s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000077s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.02% : 0.000084s : 1: auto_monad 0.01% : 0.000034s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.19% : 0.000720s : 1: bootstrap 0.01% : 0.000038s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.01% : 0.000021s : 1: control_data_broadcast_order 0.00% : 0.000014s : 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 0.00% : 0.000011s : 1: environ_conv 0.01% : 0.000028s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000008s : 1: label_fine_grained_interleaved_index 0.00% : 0.000011s : 1: label_micro_interleaved_index 0.13% : 0.000490s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.21% : 0.000791s : 1: mutable_eliminate 0.00% : 0.000009s : 1: offloading_packed_experts 0.01% : 0.000020s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000024s : 1: opt.transform.mutable_eliminate 19.10% : 0.072292s : 78: opt.transform.opt_a 0.01% : 0.000051s : 1: opt.transform.opt_after_cconv 0.01% : 0.000041s : 1: opt.transform.opt_after_jit_grad 0.05% : 0.000198s : 28: opt.transform.opt_b 0.02% : 0.000086s : 2: opt.transform.opt_trans_graph 0.02% : 0.000066s : 4: opt.transform.symbol_engine_opt 20.52% : 0.077652s : 1: opt_a 0.04% : 0.000168s : 1: opt_after_cconv 0.15% : 0.000565s : 1: opt_after_jit_grad 0.09% : 0.000353s : 1: opt_b 21.30% : 0.080618s : 1: optimize 0.01% : 0.000029s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000011s : 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% : 0.000009s : 1: overlap_grad_ring_attention 0.00% : 0.000007s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000007s : 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% : 0.000009s : 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% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.01% : 0.000044s : 1: pre_auto_parallel 0.01% : 0.000041s : 1: py_interpret_to_execute 0.01% : 0.000030s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.02% : 0.000074s : 1: remove_dup_value 0.94% : 0.003539s : 1: renormalize.infer 0.14% : 0.000538s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000069s : 1: rewriter_after_opt_a 0.02% : 0.000088s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.06% : 0.000213s : 1: symbol_engine_optimizer 0.03% : 0.000120s : 1: tuple_transform 22.30% : 0.084397s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_lookahead0[1] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_lookahead0[1],max_mem:936.0M =============================== 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 156.65s (0:02:36) ==================