==================================================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_003/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(166838:281473094930224,MainProcess):2026-01-29-17:37:52.116.516 [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 = 0.445582, [21] [bootstrap]: 0.00075856 [type_inference]: 0.11557 [event_method]: 2.104e-05 [auto_monad]: 0.00010434 [graph_reusing]: 5.26998e-06 [inline]: 2.76e-06 [add_attr]: 0.199488, [1] [add_attr_with_inline]: 0.199472, [1] [Cycle 1]: 0.00011345, [2] [tag_attr]: 2.595e-05 [meta_addattr_fg_expand]: 5.54e-06 [parallel-infer-symbol]: 3.97998e-06 [pre_auto_parallel]: 4.747e-05 [insert-virtual-dataset]: 3.3e-06 [parallel-infer-symbol-second]: 9.70002e-07 [dataset_repeat_opt]: 2.13998e-06 [pipeline_split]: 1.96998e-06 [optimize]: 0.128534, [53] [py_interpret_to_execute]: 3.71e-05 [rewriter_before_opt_a]: 9.623e-05 [opt_a]: 0.0036946, [2] [Cycle 1]: 0.00264544, [45] [expand_dump_flag]: 3.02002e-06 [switch_simplify]: 3.335e-05 [loop_unroll]: 1.773e-05 [a_1]: 0.00045993 [with_stream_mark]: 3.095e-05 [recompute_prepare]: 1.419e-05 [updatestate_depend_eliminate]: 6.34001e-06 [updatestate_assign_eliminate]: 5.15999e-06 [updatestate_loads_eliminate]: 5.04998e-06 [parameter_eliminate]: 1.269e-05 [a_2]: 0.00014499 [accelerated_algorithm]: 1.306e-05 [shard]: 2.83e-06 [meta_shard_fg_expand]: 3.6e-06 [shard_inline]: 1.092e-05 [merge_send_recv]: 1.229e-05 [auto_parallel]: 1.066e-05 [parallel]: 7.203e-05 [flash_sp]: 2.512e-05 [merge_comm]: 6.48e-06 [allreduce_fusion]: 4.561e-05 [matmul_add_comm_reduction]: 1.506e-05 [allreduce_slice_to_reducescatter]: 8.50006e-07 [virtual_shard_identity]: 1.794e-05 [virtual_dataset]: 1.14e-05 [get_grad_eliminate_]: 1.06e-05 [virtual_output]: 1.059e-05 [merge_forward]: 6.46e-06 [cell_reuse_recompute_pass]: 1.45999e-06 [offload_activation]: 1.261e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.943e-05 [merge_recompute_call_nodes]: 1.94999e-06 [before_grad]: 1.59e-05 [set_forward_comm_id_for_comm_node_pass]: 5.78002e-06 [meta_fg_expand]: 6.08002e-06 [flash_sp_send_recv_attached]: 4.84998e-06 [receive_attached]: 3.22002e-06 [after_resolve]: 2.299e-05 [a_after_grad]: 1.697e-05 [renormalize]: 0.00099403 [add_forward_monad_depend]: 8.3e-06 [auto_monad_grad]: 4.18001e-06 [auto_monad_eliminator]: 2.208e-05 [cse]: 0.00010375 [a_3]: 8.735e-05 [Cycle 2]: 0.0010334, [45] [expand_dump_flag]: 2.29001e-06 [switch_simplify]: 1.478e-05 [loop_unroll]: 1.004e-05 [a_1]: 0.00024279 [with_stream_mark]: 2.271e-05 [recompute_prepare]: 1.224e-05 [updatestate_depend_eliminate]: 7.26001e-06 [updatestate_assign_eliminate]: 5.22999e-06 [updatestate_loads_eliminate]: 4.78001e-06 [parameter_eliminate]: 1.61998e-06 [a_2]: 0.00012932 [accelerated_algorithm]: 1.073e-05 [shard]: 2.26998e-06 [meta_shard_fg_expand]: 4.05998e-06 [shard_inline]: 1.048e-05 [merge_send_recv]: 8.75999e-06 [auto_parallel]: 1.094e-05 [parallel]: 7.4e-06 [flash_sp]: 4.57e-06 [merge_comm]: 5.66e-06 [allreduce_fusion]: 4.84003e-06 [matmul_add_comm_reduction]: 1.121e-05 [allreduce_slice_to_reducescatter]: 7.50006e-07 [virtual_shard_identity]: 1.163e-05 [virtual_dataset]: 1.055e-05 [get_grad_eliminate_]: 9.46e-06 [virtual_output]: 1.057e-05 [merge_forward]: 6.16e-06 [cell_reuse_recompute_pass]: 1.76e-06 [offload_activation]: 1.204e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.995e-05 [merge_recompute_call_nodes]: 1.86998e-06 [before_grad]: 1.373e-05 [set_forward_comm_id_for_comm_node_pass]: 5.47999e-06 [meta_fg_expand]: 4.45e-06 [flash_sp_send_recv_attached]: 1.44e-06 [receive_attached]: 1.83002e-06 [after_resolve]: 2.149e-05 [a_after_grad]: 1.538e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 2.01e-06 [auto_monad_grad]: 1.62999e-06 [auto_monad_eliminator]: 1.298e-05 [cse]: 4.262e-05 [a_3]: 6.615e-05 [py_interpret_to_execute_after_opt_a]: 2.089e-05 [slice_cell_reuse_recomputed_activation]: 1.285e-05 [rewriter_after_opt_a]: 9.37e-05 [convert_after_rewriter]: 1.101e-05 [order_py_execute_after_rewriter]: 7.36001e-06 [mutable_eliminate]: 0.00075562 [opt_b]: 0.00035854, [1] [Cycle 1]: 0.00034917, [7] [b_1]: 0.00021421 [b_2]: 1.478e-05 [updatestate_depend_eliminate]: 1.246e-05 [updatestate_assign_eliminate]: 5.94999e-06 [updatestate_loads_eliminate]: 4.55001e-06 [renormalize]: 1.22e-06 [cse]: 5.52e-05 [optimize_parallel_all_gather_comm]: 0.121225 [overlap_param_gather]: 1.277e-05 [cconv]: 5.089e-05 [loop_unroll]: 0.00085933 [opt_after_cconv]: 0.00022048, [1] [Cycle 1]: 0.0002089, [7] [c_1]: 5.845e-05 [parameter_eliminate]: 7.01999e-06 [updatestate_depend_eliminate]: 1.312e-05 [updatestate_assign_eliminate]: 5.42999e-06 [updatestate_loads_eliminate]: 5.34e-06 [cse]: 8.019e-05 [renormalize]: 6.50005e-07 [remove_dup_value]: 8.415e-05 [tuple_transform]: 0.00012643, [1] [Cycle 1]: 0.00012071, [4] [d_1]: 8.618e-05 [none_parameter_eliminate]: 2.49999e-06 [renormalize]: 2.20025e-07 [switch_simplify]: 1.126e-05 [partial_unused_args_eliminate]: 2.36998e-06 [add_recomputation]: 7.496e-05 [cse_after_recomputation]: 3.812e-05, [1] [Cycle 1]: 3.219e-05, [1] [cse]: 2.456e-05 [environ_conv]: 2.593e-05 [swap_dp_allreduce_reducescatter]: 8.80001e-06 [bias_add_comm_swap]: 4.03001e-06 [label_micro_interleaved_index]: 6.37001e-06 [label_fine_grained_interleaved_index]: 2.84001e-06 [merge_cast_opt]: 1.67001e-06 [slice_recompute_activation]: 2.45997e-06 [micro_interleaved_order_control]: 2.66e-06 [assign_add_opt]: 1.47999e-06 [ForceFp32Comm]: 9.50007e-07 [remove_cast_before_assign_add]: 1.47999e-06 [full_micro_interleaved_order_control]: 2.21e-06 [reorder_send_recv_between_fp_bp]: 2.79999e-06 [comm_op_add_attrs]: 1.24e-06 [add_comm_op_reuse_tag]: 1.22999e-06 [interleave_split_concat_branches]: 1.17999e-06 [interleave_parallel_branches]: 1.19e-06 [overlap_opt_shard_in_pipeline]: 2.924e-05 [overlap_opt_shard_grad_in_pipeline]: 2.22999e-06 [control_data_broadcast_order]: 2.044e-05 [grouped_pairwise_exchange_alltoall]: 2.28998e-06 [offloading_packed_experts]: 7.03e-06 [overlap_recompute_and_grad_model_parallel]: 6.78e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.27999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.91e-06 [overlap_recompute_comm]: 2.52001e-06 [overlap_grad_ring_attention]: 5.87999e-06 [overlap_grad_flash_sp]: 3.905e-05 [begin_end_overlap_inline]: 5.50004e-07 [split_matmul_comm_elemetwise]: 2.78e-06 [split_layernorm_comm]: 1.84e-06 [handle_group_info]: 1.17999e-06 [symbol_engine_optimizer]: 0.00021892, [1] [Cycle 1]: 0.00021288, [6] [build]: 9.951e-05 [elim_shapecalc]: 1.704e-05 [elim_not_effective]: 2.896e-05 [opt_reshape]: 1.212e-05 [fold_const_symbol]: 2.122e-05 [renormalize]: 3.00002e-07 [detach_backward]: 2.83e-06 [pipeline_parallel_scheduler]: 1.67001e-06 [auto_monad_reorder]: 3.256e-05 [get_jit_bprop_graph]: 2.61e-06 [rewriter_after_jit_bprop_graph]: 6.43e-06 [opt_after_jit_grad]: 0.00070177 [validate]: 8.391e-05 Sums bootstrap : 0.000759s : 0.31% type_inference : 0.115570s : 47.20% event_method : 0.000021s : 0.01% auto_monad : 0.000104s : 0.04% graph_reusing : 0.000005s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000026s : 0.01% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000006s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000047s : 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 : 0.000037s : 0.02% optimize.rewriter_before_opt_a : 0.000096s : 0.04% optimize.opt_a.expand_dump_flag : 0.000005s : 0.00% optimize.opt_a.switch_simplify : 0.000048s : 0.02% optimize.opt_a.loop_unroll : 0.000028s : 0.01% optimize.opt_a.a_1 : 0.000703s : 0.29% optimize.opt_a.with_stream_mark : 0.000054s : 0.02% optimize.opt_a.recompute_prepare : 0.000026s : 0.01% optimize.opt_a.updatestate_depend_eliminate : 0.000014s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% optimize.opt_a.parameter_eliminate : 0.000014s : 0.01% optimize.opt_a.a_2 : 0.000274s : 0.11% optimize.opt_a.accelerated_algorithm : 0.000024s : 0.01% optimize.opt_a.shard : 0.000005s : 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 : 0.000021s : 0.01% optimize.opt_a.auto_parallel : 0.000022s : 0.01% optimize.opt_a.parallel : 0.000079s : 0.03% optimize.opt_a.flash_sp : 0.000030s : 0.01% optimize.opt_a.merge_comm : 0.000012s : 0.00% optimize.opt_a.allreduce_fusion : 0.000050s : 0.02% optimize.opt_a.matmul_add_comm_reduction : 0.000026s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000030s : 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 : 0.000021s : 0.01% optimize.opt_a.merge_forward : 0.000013s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% optimize.opt_a.offload_activation : 0.000025s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000049s : 0.02% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000030s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000011s : 0.00% optimize.opt_a.meta_fg_expand : 0.000011s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000006s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000044s : 0.02% optimize.opt_a.a_after_grad : 0.000032s : 0.01% optimize.opt_a.renormalize : 0.000994s : 0.41% optimize.opt_a.add_forward_monad_depend : 0.000010s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000035s : 0.01% optimize.opt_a.cse : 0.000146s : 0.06% optimize.opt_a.a_3 : 0.000154s : 0.06% optimize.py_interpret_to_execute_after_opt_a : 0.000021s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000013s : 0.01% optimize.rewriter_after_opt_a : 0.000094s : 0.04% optimize.convert_after_rewriter : 0.000011s : 0.00% optimize.order_py_execute_after_rewriter : 0.000007s : 0.00% optimize.mutable_eliminate : 0.000756s : 0.31% optimize.opt_b.b_1 : 0.000214s : 0.09% optimize.opt_b.b_2 : 0.000015s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000012s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000055s : 0.02% optimize.optimize_parallel_all_gather_comm : 0.121225s : 49.51% optimize.overlap_param_gather : 0.000013s : 0.01% optimize.cconv : 0.000051s : 0.02% optimize.loop_unroll : 0.000859s : 0.35% optimize.opt_after_cconv.c_1 : 0.000058s : 0.02% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.cse : 0.000080s : 0.03% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000084s : 0.03% optimize.tuple_transform.d_1 : 0.000086s : 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 : 0.000011s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000075s : 0.03% optimize.cse_after_recomputation.cse : 0.000025s : 0.01% optimize.environ_conv : 0.000026s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000009s : 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 : 0.000002s : 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 : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000029s : 0.01% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000020s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000007s : 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 : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000006s : 0.00% optimize.overlap_grad_flash_sp : 0.000039s : 0.02% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000100s : 0.04% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000029s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000021s : 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 : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000702s : 0.29% validate : 0.000084s : 0.03% Time group info: ------[substitution.] 0.000184 33 6.37% : 0.000012s : 2: substitution.elim_not_effective 4.45% : 0.000008s : 2: substitution.fold_const_symbol 4.67% : 0.000009s : 8: substitution.graph_param_transform 68.96% : 0.000127s : 1: substitution.inline 2.31% : 0.000004s : 4: substitution.j_node_and_user_rematch 8.20% : 0.000015s : 4: substitution.remove_not_recompute_node 5.04% : 0.000009s : 12: substitution.replace_old_param ------[type_inference.] 0.115420 2 99.27% : 0.114575s : 1: type_inference.infer 0.73% : 0.000844s : 1: type_inference.specialize ------[replace.] 0.000024 1 100.00% : 0.000024s : 1: replace.inline ------[match.] 0.000126 1 100.00% : 0.000126s : 1: match.inline ------[predicate.] 0.000247 1879 0.67% : 0.000002s : 17: predicate.accumulaten_eliminater 1.19% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 0.74% : 0.000002s : 16: predicate.addn_check_dump 0.83% : 0.000002s : 17: predicate.addn_zero_filter 0.77% : 0.000002s : 17: predicate.adjust_all_reduce_mul_add 1.93% : 0.000005s : 33: predicate.arithmetic_simplify 0.79% : 0.000002s : 17: predicate.cast_eliminate 0.67% : 0.000002s : 16: predicate.check_bprop_eliminate 0.71% : 0.000002s : 16: predicate.compare_switch_simplify 0.24% : 0.000001s : 8: predicate.const_output_eliminate 0.86% : 0.000002s : 16: predicate.depend_value_elim 0.74% : 0.000002s : 17: predicate.dict_get_item_const_eliminator 0.86% : 0.000002s : 17: predicate.dict_get_item_eliminator 0.82% : 0.000002s : 17: predicate.dict_set_item_eliminator 1.25% : 0.000003s : 16: predicate.dumpgradient_eliminate 0.38% : 0.000001s : 8: predicate.elim_not_effective 0.53% : 0.000001s : 8: predicate.elim_shapecalc_of_broadcastargs 1.11% : 0.000003s : 25: predicate.environ_add_const_eliminate 1.08% : 0.000003s : 25: predicate.environ_get_add_eliminate 1.01% : 0.000003s : 25: predicate.environ_get_depend_swap 1.88% : 0.000005s : 41: predicate.environ_get_eliminate 1.17% : 0.000003s : 25: predicate.environ_get_set_eliminate 0.90% : 0.000002s : 18: predicate.exchange_switch_depend_value 1.58% : 0.000004s : 18: predicate.float_depend_g_call 0.60% : 0.000001s : 16: predicate.float_environ_get_switch 1.06% : 0.000003s : 24: predicate.float_tuple_getitem_switch 0.26% : 0.000001s : 8: predicate.fold_const_symbol 0.81% : 0.000002s : 16: predicate.get_grad_eliminate 0.45% : 0.000001s : 8: predicate.graph_param_transform 0.78% : 0.000002s : 16: predicate.incorporate_call 0.60% : 0.000001s : 16: predicate.incorporate_call_switch 5.53% : 0.000014s : 83: predicate.inline 0.97% : 0.000002s : 16: predicate.inline_without_move 0.47% : 0.000001s : 16: predicate.j_node_and_user_rematch 0.94% : 0.000002s : 16: predicate.less_batch_normalization 1.76% : 0.000004s : 33: predicate.list_to_tuple_eliminator_ 2.24% : 0.000006s : 50: predicate.load_eliminater 1.17% : 0.000003s : 8: predicate.loop_unroll_after_grad 1.29% : 0.000003s : 25: predicate.loop_unroll_before_grad 2.14% : 0.000005s : 33: predicate.make_slice_get_slice_eliminator 0.80% : 0.000002s : 16: predicate.merge_addn 0.79% : 0.000002s : 16: predicate.micro_step_allgather_replace 0.72% : 0.000002s : 16: predicate.mini_step_allgather_replace 0.72% : 0.000002s : 17: predicate.minmaximum_grad 1.57% : 0.000004s : 8: predicate.mutable_eliminate 0.67% : 0.000002s : 8: predicate.opt_reshape 0.43% : 0.000001s : 8: predicate.parallel_virtual_node 0.99% : 0.000002s : 18: predicate.partial_defer_inline 1.15% : 0.000003s : 25: predicate.partial_eliminate 0.84% : 0.000002s : 17: predicate.print_const_string_wrapper 0.81% : 0.000002s : 16: predicate.reduce_all_const_elim 0.99% : 0.000002s : 17: predicate.reduce_eliminate 2.20% : 0.000005s : 50: predicate.redundant_stop_gradient_eliminater 0.71% : 0.000002s : 16: predicate.remove_not_recompute_node 1.23% : 0.000003s : 33: predicate.replace_applicator 0.69% : 0.000002s : 16: predicate.replace_old_param 0.42% : 0.000001s : 8: predicate.reset_defer_inline 0.67% : 0.000002s : 17: predicate.reshape_eliminate 1.11% : 0.000003s : 16: predicate.row_tensor_add_zeros_like 0.46% : 0.000001s : 8: predicate.row_tensor_eliminate 1.16% : 0.000003s : 16: predicate.same_eliminate 0.65% : 0.000002s : 16: predicate.set_cell_output_no_recompute 1.35% : 0.000003s : 16: predicate.shard_identity_eliminate 1.09% : 0.000003s : 16: predicate.special_op_eliminate 0.85% : 0.000002s : 16: predicate.specialize_transform 1.23% : 0.000003s : 16: predicate.split_environ_get_set_with_tuple_value 1.12% : 0.000003s : 16: predicate.stack_unstack_eliminate 0.45% : 0.000001s : 8: predicate.switch_call_monad_eliminater 0.86% : 0.000002s : 18: predicate.switch_defer_inline 2.20% : 0.000005s : 34: predicate.switch_layer_defer_inline 3.69% : 0.000009s : 67: predicate.switch_simplify 0.74% : 0.000002s : 17: predicate.tile_eliminate 0.74% : 0.000002s : 17: predicate.transpose_eliminate 2.06% : 0.000005s : 33: predicate.tuple_list_convert_item_index_to_positive 1.57% : 0.000004s : 33: predicate.tuple_list_get_item_const_eliminator 1.68% : 0.000004s : 33: predicate.tuple_list_get_item_depend_reorder 2.94% : 0.000007s : 49: predicate.tuple_list_get_item_eliminator 1.54% : 0.000004s : 33: predicate.tuple_list_get_set_item_eliminator 2.55% : 0.000006s : 49: predicate.tuple_list_set_item_eliminator 1.67% : 0.000004s : 33: predicate.tuple_to_list_eliminator_ 2.18% : 0.000005s : 50: predicate.updatestate_pure_node_eliminater 2.81% : 0.000007s : 66: predicate.updatestate_useless_node_eliminater 0.46% : 0.000001s : 8: predicate.value_based_eliminate 1.07% : 0.000003s : 16: predicate.virtual_dataset_eliminate 0.72% : 0.000002s : 16: predicate.virtual_output_eliminate 0.38% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.50% : 0.000001s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000807 6 51.62% : 0.000416s : 3: func_graph_cloner_run.FuncGraphClonerGraph 48.38% : 0.000390s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.776328 192 0.00% : 0.000004s : 1: ForceFp32Comm 25.70% : 0.199497s : 1: add_attr 25.69% : 0.199476s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000080s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.01% : 0.000111s : 1: auto_monad 0.00% : 0.000038s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.10% : 0.000796s : 1: bootstrap 0.01% : 0.000055s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000024s : 1: control_data_broadcast_order 0.00% : 0.000015s : 1: convert_after_rewriter 0.01% : 0.000041s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000030s : 1: environ_conv 0.00% : 0.000029s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 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% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000010s : 1: label_micro_interleaved_index 0.11% : 0.000871s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.10% : 0.000773s : 1: mutable_eliminate 0.00% : 0.000010s : 1: offloading_packed_experts 0.00% : 0.000031s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 0.18% : 0.001421s : 78: opt.transform.opt_a 0.01% : 0.000057s : 1: opt.transform.opt_after_cconv 0.01% : 0.000045s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000199s : 28: opt.transform.opt_b 0.01% : 0.000095s : 2: opt.transform.opt_trans_graph 0.01% : 0.000075s : 4: opt.transform.symbol_engine_opt 0.48% : 0.003700s : 1: opt_a 0.03% : 0.000224s : 1: opt_after_cconv 0.09% : 0.000719s : 1: opt_after_jit_grad 0.05% : 0.000362s : 1: opt_b 16.56% : 0.128540s : 1: optimize 15.62% : 0.121269s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.01% : 0.000043s : 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 0.00% : 0.000033s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000022s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000010s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000008s : 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% : 0.000053s : 1: pre_auto_parallel 0.01% : 0.000043s : 1: py_interpret_to_execute 0.00% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000089s : 1: remove_dup_value 0.07% : 0.000510s : 1: renormalize.infer 0.06% : 0.000471s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000101s : 1: rewriter_after_opt_a 0.01% : 0.000102s : 1: rewriter_before_opt_a 0.00% : 0.000016s : 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% : 0.000012s : 1: swap_dp_allreduce_reducescatter 0.03% : 0.000222s : 1: symbol_engine_optimizer 0.02% : 0.000130s : 1: tuple_transform 14.89% : 0.115603s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_quant_no_quant_jiutian[0] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_quant_no_quant_jiutian[0],max_mem:792.0M [WARNING] ME(166838:281473094930224,MainProcess):2026-01-29-17:39:18.661.431 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 2.81016, [21] [bootstrap]: 0.0150724 [type_inference]: 0.991471 [event_method]: 0.23615 [auto_monad]: 0.00033555 [graph_reusing]: 6.07999e-06 [inline]: 3.45e-06 [add_attr]: 1.31334, [1] [add_attr_with_inline]: 1.31322, [1] [Cycle 1]: 0.00014646, [2] [tag_attr]: 2.979e-05 [meta_addattr_fg_expand]: 5.64e-06 [parallel-infer-symbol]: 3.86999e-06 [pre_auto_parallel]: 0.00014934 [insert-virtual-dataset]: 4e-06 [parallel-infer-symbol-second]: 7.7e-07 [dataset_repeat_opt]: 2.38002e-06 [pipeline_split]: 1.66998e-06 [optimize]: 0.250349, [53] [py_interpret_to_execute]: 4.816e-05 [rewriter_before_opt_a]: 0.00012346 [opt_a]: 0.240795, [2] [Cycle 1]: 0.0170933, [45] [expand_dump_flag]: 3.98001e-06 [switch_simplify]: 3.373e-05 [loop_unroll]: 1.745e-05 [a_1]: 0.00068121 [with_stream_mark]: 4.401e-05 [recompute_prepare]: 1.351e-05 [updatestate_depend_eliminate]: 6.84999e-06 [updatestate_assign_eliminate]: 5.49998e-06 [updatestate_loads_eliminate]: 5.00001e-06 [parameter_eliminate]: 2.12001e-06 [a_2]: 0.00014268 [accelerated_algorithm]: 7.291e-05 [shard]: 2.24999e-06 [meta_shard_fg_expand]: 2.99999e-06 [shard_inline]: 1.059e-05 [merge_send_recv]: 1.155e-05 [auto_parallel]: 9.61998e-06 [parallel]: 0.00029046 [flash_sp]: 1.092e-05 [merge_comm]: 5.84e-06 [allreduce_fusion]: 6.47001e-06 [matmul_add_comm_reduction]: 1.326e-05 [allreduce_slice_to_reducescatter]: 1.20999e-06 [virtual_shard_identity]: 1.523e-05 [virtual_dataset]: 6.209e-05 [get_grad_eliminate_]: 1.428e-05 [virtual_output]: 5.264e-05 [merge_forward]: 6.78e-06 [cell_reuse_recompute_pass]: 1.37e-06 [offload_activation]: 1.554e-05 [cell_reuse_handle_not_recompute_node_pass]: 0.00010049 [merge_recompute_call_nodes]: 1.60001e-06 [before_grad]: 0.00175371 [set_forward_comm_id_for_comm_node_pass]: 1.473e-05 [meta_fg_expand]: 9.12001e-06 [flash_sp_send_recv_attached]: 5.49e-06 [receive_attached]: 2.87002e-06 [after_resolve]: 9.102e-05 [a_after_grad]: 9.453e-05 [renormalize]: 0.0122797 [add_forward_monad_depend]: 1.479e-05 [auto_monad_grad]: 2.89001e-06 [auto_monad_eliminator]: 2.956e-05 [cse]: 6.94e-05 [a_3]: 0.00012147 [Cycle 2]: 0.223682, [45] [expand_dump_flag]: 2.91e-06 [switch_simplify]: 1.609e-05 [loop_unroll]: 1.201e-05 [a_1]: 0.220635 [with_stream_mark]: 5.018e-05 [recompute_prepare]: 2.522e-05 [updatestate_depend_eliminate]: 7.80998e-06 [updatestate_assign_eliminate]: 5.67999e-06 [updatestate_loads_eliminate]: 6.32001e-06 [parameter_eliminate]: 2.48e-06 [a_2]: 0.00018775 [accelerated_algorithm]: 0.00017411 [shard]: 5.05999e-06 [meta_shard_fg_expand]: 9.55001e-06 [shard_inline]: 1.167e-05 [merge_send_recv]: 1.319e-05 [auto_parallel]: 1.378e-05 [parallel]: 6.338e-05 [flash_sp]: 4.94e-06 [merge_comm]: 6.28e-06 [allreduce_fusion]: 5.59e-06 [matmul_add_comm_reduction]: 1.695e-05 [allreduce_slice_to_reducescatter]: 1.42999e-06 [virtual_shard_identity]: 1.482e-05 [virtual_dataset]: 9.109e-05 [get_grad_eliminate_]: 1.063e-05 [virtual_output]: 4.94e-05 [merge_forward]: 7.24001e-06 [cell_reuse_recompute_pass]: 2.89999e-06 [offload_activation]: 0.00017859 [cell_reuse_handle_not_recompute_node_pass]: 3.259e-05 [merge_recompute_call_nodes]: 1.79998e-06 [before_grad]: 1.793e-05 [set_forward_comm_id_for_comm_node_pass]: 7.29001e-06 [meta_fg_expand]: 6.66e-06 [flash_sp_send_recv_attached]: 2.50002e-06 [receive_attached]: 3.80998e-06 [after_resolve]: 3.067e-05 [a_after_grad]: 1.957e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 5.28002e-06 [auto_monad_grad]: 3.28e-06 [auto_monad_eliminator]: 2.317e-05 [cse]: 0.00011111 [a_3]: 7.438e-05 [py_interpret_to_execute_after_opt_a]: 0.00010404 [slice_cell_reuse_recomputed_activation]: 3.25998e-06 [rewriter_after_opt_a]: 0.00017889 [convert_after_rewriter]: 1.163e-05 [order_py_execute_after_rewriter]: 8.27998e-06 [mutable_eliminate]: 0.00139126 [opt_b]: 0.00063247, [1] [Cycle 1]: 0.00056689, [7] [b_1]: 0.00022575 [b_2]: 1.387e-05 [updatestate_depend_eliminate]: 1.338e-05 [updatestate_assign_eliminate]: 5.91e-06 [updatestate_loads_eliminate]: 5.69999e-06 [renormalize]: 5.89993e-07 [cse]: 0.00014686 [optimize_parallel_all_gather_comm]: 0.000113 [overlap_param_gather]: 1.554e-05 [cconv]: 4.619e-05 [loop_unroll]: 0.00111249 [opt_after_cconv]: 0.0004757, [1] [Cycle 1]: 0.000466, [7] [c_1]: 5.602e-05 [parameter_eliminate]: 6.59001e-06 [updatestate_depend_eliminate]: 1.15e-05 [updatestate_assign_eliminate]: 5.15999e-06 [updatestate_loads_eliminate]: 5.55001e-06 [cse]: 0.00011292 [renormalize]: 4.99975e-07 [remove_dup_value]: 0.00023494 [tuple_transform]: 0.00029344, [1] [Cycle 1]: 0.00028607, [4] [d_1]: 0.00019347 [none_parameter_eliminate]: 2.19999e-06 [renormalize]: 2.50002e-07 [switch_simplify]: 1.169e-05 [partial_unused_args_eliminate]: 2.09e-06 [add_recomputation]: 0.00015418 [cse_after_recomputation]: 0.00011733, [1] [Cycle 1]: 0.00011002, [1] [cse]: 3.326e-05 [environ_conv]: 1.011e-05 [swap_dp_allreduce_reducescatter]: 8.53001e-06 [bias_add_comm_swap]: 3.35e-06 [label_micro_interleaved_index]: 6.51e-06 [label_fine_grained_interleaved_index]: 6.097e-05 [merge_cast_opt]: 1.92999e-06 [slice_recompute_activation]: 2.07001e-06 [micro_interleaved_order_control]: 3.10998e-06 [assign_add_opt]: 1.52999e-06 [ForceFp32Comm]: 8.70001e-07 [remove_cast_before_assign_add]: 1.20999e-06 [full_micro_interleaved_order_control]: 3.65e-06 [reorder_send_recv_between_fp_bp]: 3.12002e-06 [comm_op_add_attrs]: 1.12e-06 [add_comm_op_reuse_tag]: 9.99979e-07 [interleave_split_concat_branches]: 1.53002e-06 [interleave_parallel_branches]: 1.82001e-06 [overlap_opt_shard_in_pipeline]: 2.909e-05 [overlap_opt_shard_grad_in_pipeline]: 1.98997e-06 [control_data_broadcast_order]: 0.00011366 [grouped_pairwise_exchange_alltoall]: 1.99e-06 [offloading_packed_experts]: 7.97e-06 [overlap_recompute_and_grad_model_parallel]: 7.36999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.76e-06 [overlap_recompute_allgather_and_fa_grad]: 1.71e-06 [overlap_recompute_comm]: 3.01001e-06 [overlap_grad_ring_attention]: 6.34001e-06 [overlap_grad_flash_sp]: 0.00012529 [begin_end_overlap_inline]: 5.19998e-07 [split_matmul_comm_elemetwise]: 2.63e-06 [split_layernorm_comm]: 2.07001e-06 [handle_group_info]: 1.12e-06 [symbol_engine_optimizer]: 0.00275439, [1] [Cycle 1]: 0.00268486, [6] [build]: 0.00199509 [elim_shapecalc]: 0.00037735 [elim_not_effective]: 5.097e-05 [opt_reshape]: 1.872e-05 [fold_const_symbol]: 0.00011824 [renormalize]: 2.70025e-07 [detach_backward]: 3.08e-06 [pipeline_parallel_scheduler]: 1.79e-06 [auto_monad_reorder]: 5.393e-05 [get_jit_bprop_graph]: 2.46998e-06 [rewriter_after_jit_bprop_graph]: 5.30001e-06 [opt_after_jit_grad]: 0.00219226 [validate]: 0.00010546 Sums bootstrap : 0.015072s : 1.01% type_inference : 0.991471s : 66.49% event_method : 0.236150s : 15.84% auto_monad : 0.000336s : 0.02% graph_reusing : 0.000006s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000030s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000006s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000149s : 0.01% insert-virtual-dataset : 0.000004s : 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 : 0.000048s : 0.00% optimize.rewriter_before_opt_a : 0.000123s : 0.01% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000050s : 0.00% optimize.opt_a.loop_unroll : 0.000029s : 0.00% optimize.opt_a.a_1 : 0.221316s : 14.84% optimize.opt_a.with_stream_mark : 0.000094s : 0.01% optimize.opt_a.recompute_prepare : 0.000039s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% 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 : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000330s : 0.02% optimize.opt_a.accelerated_algorithm : 0.000247s : 0.02% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.00% optimize.opt_a.shard_inline : 0.000022s : 0.00% optimize.opt_a.merge_send_recv : 0.000025s : 0.00% optimize.opt_a.auto_parallel : 0.000023s : 0.00% optimize.opt_a.parallel : 0.000354s : 0.02% optimize.opt_a.flash_sp : 0.000016s : 0.00% optimize.opt_a.merge_comm : 0.000012s : 0.00% optimize.opt_a.allreduce_fusion : 0.000012s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000030s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000003s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000030s : 0.00% optimize.opt_a.virtual_dataset : 0.000153s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000025s : 0.00% optimize.opt_a.virtual_output : 0.000102s : 0.01% optimize.opt_a.merge_forward : 0.000014s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% optimize.opt_a.offload_activation : 0.000194s : 0.01% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000133s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.001772s : 0.12% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000022s : 0.00% optimize.opt_a.meta_fg_expand : 0.000016s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000007s : 0.00% optimize.opt_a.after_resolve : 0.000122s : 0.01% optimize.opt_a.a_after_grad : 0.000114s : 0.01% optimize.opt_a.renormalize : 0.012280s : 0.82% optimize.opt_a.add_forward_monad_depend : 0.000020s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000053s : 0.00% optimize.opt_a.cse : 0.000181s : 0.01% optimize.opt_a.a_3 : 0.000196s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000104s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000179s : 0.01% optimize.convert_after_rewriter : 0.000012s : 0.00% optimize.order_py_execute_after_rewriter : 0.000008s : 0.00% optimize.mutable_eliminate : 0.001391s : 0.09% optimize.opt_b.b_1 : 0.000226s : 0.02% optimize.opt_b.b_2 : 0.000014s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000013s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000147s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000113s : 0.01% optimize.overlap_param_gather : 0.000016s : 0.00% optimize.cconv : 0.000046s : 0.00% optimize.loop_unroll : 0.001112s : 0.07% optimize.opt_after_cconv.c_1 : 0.000056s : 0.00% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.cse : 0.000113s : 0.01% optimize.opt_after_cconv.renormalize : 0.000000s : 0.00% optimize.remove_dup_value : 0.000235s : 0.02% optimize.tuple_transform.d_1 : 0.000193s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000012s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000154s : 0.01% optimize.cse_after_recomputation.cse : 0.000033s : 0.00% optimize.environ_conv : 0.000010s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000009s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000007s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000061s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000004s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000002s : 0.00% optimize.interleave_parallel_branches : 0.000002s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000029s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000114s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000008s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000007s : 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 : 0.000006s : 0.00% optimize.overlap_grad_flash_sp : 0.000125s : 0.01% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.001995s : 0.13% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000377s : 0.03% optimize.symbol_engine_optimizer.elim_not_effective : 0.000051s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000019s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000118s : 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 : 0.000054s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.002192s : 0.15% validate : 0.000105s : 0.01% Time group info: ------[substitution.] 0.000359 33 7.60% : 0.000027s : 2: substitution.elim_not_effective 2.74% : 0.000010s : 2: substitution.fold_const_symbol 2.65% : 0.000010s : 8: substitution.graph_param_transform 80.35% : 0.000288s : 1: substitution.inline 1.38% : 0.000005s : 4: substitution.j_node_and_user_rematch 1.76% : 0.000006s : 4: substitution.remove_not_recompute_node 3.51% : 0.000013s : 12: substitution.replace_old_param ------[type_inference.] 0.990895 2 98.32% : 0.974262s : 1: type_inference.infer 1.68% : 0.016633s : 1: type_inference.specialize ------[replace.] 0.000027 1 100.00% : 0.000027s : 1: replace.inline ------[match.] 0.000287 1 100.00% : 0.000287s : 1: match.inline ------[predicate.] 0.000305 1879 0.78% : 0.000002s : 17: predicate.accumulaten_eliminater 1.40% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 0.62% : 0.000002s : 16: predicate.addn_check_dump 0.80% : 0.000002s : 17: predicate.addn_zero_filter 0.76% : 0.000002s : 17: predicate.adjust_all_reduce_mul_add 1.73% : 0.000005s : 33: predicate.arithmetic_simplify 0.73% : 0.000002s : 17: predicate.cast_eliminate 0.64% : 0.000002s : 16: predicate.check_bprop_eliminate 0.58% : 0.000002s : 16: predicate.compare_switch_simplify 0.21% : 0.000001s : 8: predicate.const_output_eliminate 0.71% : 0.000002s : 16: predicate.depend_value_elim 0.82% : 0.000003s : 17: predicate.dict_get_item_const_eliminator 0.80% : 0.000002s : 17: predicate.dict_get_item_eliminator 0.91% : 0.000003s : 17: predicate.dict_set_item_eliminator 1.28% : 0.000004s : 16: predicate.dumpgradient_eliminate 0.33% : 0.000001s : 8: predicate.elim_not_effective 1.13% : 0.000003s : 8: predicate.elim_shapecalc_of_broadcastargs 1.07% : 0.000003s : 25: predicate.environ_add_const_eliminate 1.01% : 0.000003s : 25: predicate.environ_get_add_eliminate 0.99% : 0.000003s : 25: predicate.environ_get_depend_swap 1.87% : 0.000006s : 41: predicate.environ_get_eliminate 1.04% : 0.000003s : 25: predicate.environ_get_set_eliminate 0.77% : 0.000002s : 18: predicate.exchange_switch_depend_value 2.08% : 0.000006s : 18: predicate.float_depend_g_call 0.62% : 0.000002s : 16: predicate.float_environ_get_switch 0.84% : 0.000003s : 24: predicate.float_tuple_getitem_switch 0.21% : 0.000001s : 8: predicate.fold_const_symbol 0.78% : 0.000002s : 16: predicate.get_grad_eliminate 0.31% : 0.000001s : 8: predicate.graph_param_transform 0.66% : 0.000002s : 16: predicate.incorporate_call 0.46% : 0.000001s : 16: predicate.incorporate_call_switch 4.40% : 0.000013s : 83: predicate.inline 1.01% : 0.000003s : 16: predicate.inline_without_move 0.66% : 0.000002s : 16: predicate.j_node_and_user_rematch 0.96% : 0.000003s : 16: predicate.less_batch_normalization 1.59% : 0.000005s : 33: predicate.list_to_tuple_eliminator_ 2.05% : 0.000006s : 50: predicate.load_eliminater 1.42% : 0.000004s : 8: predicate.loop_unroll_after_grad 1.01% : 0.000003s : 25: predicate.loop_unroll_before_grad 1.53% : 0.000005s : 33: predicate.make_slice_get_slice_eliminator 0.63% : 0.000002s : 16: predicate.merge_addn 0.67% : 0.000002s : 16: predicate.micro_step_allgather_replace 0.63% : 0.000002s : 16: predicate.mini_step_allgather_replace 0.50% : 0.000002s : 17: predicate.minmaximum_grad 1.63% : 0.000005s : 8: predicate.mutable_eliminate 0.51% : 0.000002s : 8: predicate.opt_reshape 0.40% : 0.000001s : 8: predicate.parallel_virtual_node 4.50% : 0.000014s : 18: predicate.partial_defer_inline 0.90% : 0.000003s : 25: predicate.partial_eliminate 0.69% : 0.000002s : 17: predicate.print_const_string_wrapper 0.76% : 0.000002s : 16: predicate.reduce_all_const_elim 1.07% : 0.000003s : 17: predicate.reduce_eliminate 1.86% : 0.000006s : 50: predicate.redundant_stop_gradient_eliminater 0.58% : 0.000002s : 16: predicate.remove_not_recompute_node 1.19% : 0.000004s : 33: predicate.replace_applicator 0.64% : 0.000002s : 16: predicate.replace_old_param 0.22% : 0.000001s : 8: predicate.reset_defer_inline 0.98% : 0.000003s : 17: predicate.reshape_eliminate 7.06% : 0.000022s : 16: predicate.row_tensor_add_zeros_like 0.40% : 0.000001s : 8: predicate.row_tensor_eliminate 1.10% : 0.000003s : 16: predicate.same_eliminate 0.53% : 0.000002s : 16: predicate.set_cell_output_no_recompute 0.85% : 0.000003s : 16: predicate.shard_identity_eliminate 0.91% : 0.000003s : 16: predicate.special_op_eliminate 0.63% : 0.000002s : 16: predicate.specialize_transform 1.23% : 0.000004s : 16: predicate.split_environ_get_set_with_tuple_value 1.09% : 0.000003s : 16: predicate.stack_unstack_eliminate 0.36% : 0.000001s : 8: predicate.switch_call_monad_eliminater 0.77% : 0.000002s : 18: predicate.switch_defer_inline 1.61% : 0.000005s : 34: predicate.switch_layer_defer_inline 2.86% : 0.000009s : 67: predicate.switch_simplify 0.73% : 0.000002s : 17: predicate.tile_eliminate 0.59% : 0.000002s : 17: predicate.transpose_eliminate 1.62% : 0.000005s : 33: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000005s : 33: predicate.tuple_list_get_item_const_eliminator 1.60% : 0.000005s : 33: predicate.tuple_list_get_item_depend_reorder 2.78% : 0.000008s : 49: predicate.tuple_list_get_item_eliminator 1.54% : 0.000005s : 33: predicate.tuple_list_get_set_item_eliminator 2.03% : 0.000006s : 49: predicate.tuple_list_set_item_eliminator 1.39% : 0.000004s : 33: predicate.tuple_to_list_eliminator_ 1.74% : 0.000005s : 50: predicate.updatestate_pure_node_eliminater 2.37% : 0.000007s : 66: predicate.updatestate_useless_node_eliminater 0.39% : 0.000001s : 8: predicate.value_based_eliminate 0.79% : 0.000002s : 16: predicate.virtual_dataset_eliminate 0.75% : 0.000002s : 16: predicate.virtual_output_eliminate 0.30% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.46% : 0.000001s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.288996 6 96.24% : 0.278135s : 3: func_graph_cloner_run.FuncGraphClonerGraph 3.76% : 0.010861s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.610956 192 0.00% : 0.000005s : 1: ForceFp32Comm 28.48% : 1.313348s : 1: add_attr 28.48% : 1.313227s : 1: add_attr_with_inline 0.00% : 0.000005s : 1: add_comm_op_reuse_tag 0.00% : 0.000161s : 1: add_recomputation 0.00% : 0.000006s : 1: assign_add_opt 0.01% : 0.000348s : 1: auto_monad 0.00% : 0.000059s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.33% : 0.015334s : 1: bootstrap 0.00% : 0.000052s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000119s : 1: control_data_broadcast_order 0.00% : 0.000071s : 1: convert_after_rewriter 0.00% : 0.000122s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000015s : 1: environ_conv 5.12% : 0.236289s : 1: event_method 0.00% : 0.000009s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 0.00% : 0.000080s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000080s : 1: inline 0.00% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000006s : 1: interleave_parallel_branches 0.00% : 0.000006s : 1: interleave_split_concat_branches 0.00% : 0.000149s : 1: label_fine_grained_interleaved_index 0.00% : 0.000011s : 1: label_micro_interleaved_index 0.02% : 0.001128s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000053s : 1: micro_interleaved_order_control 0.03% : 0.001412s : 1: mutable_eliminate 0.00% : 0.000013s : 1: offloading_packed_experts 0.00% : 0.000026s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000031s : 1: opt.transform.mutable_eliminate 4.87% : 0.224503s : 78: opt.transform.opt_a 0.00% : 0.000054s : 1: opt.transform.opt_after_cconv 0.00% : 0.000068s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000203s : 28: opt.transform.opt_b 0.00% : 0.000202s : 2: opt.transform.opt_trans_graph 0.01% : 0.000557s : 4: opt.transform.symbol_engine_opt 5.22% : 0.240801s : 1: opt_a 0.01% : 0.000481s : 1: opt_after_cconv 0.05% : 0.002211s : 1: opt_after_jit_grad 0.01% : 0.000638s : 1: opt_b 5.43% : 0.250358s : 1: optimize 0.00% : 0.000118s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000013s : 1: order_py_execute_after_rewriter 0.00% : 0.000131s : 1: overlap_grad_flash_sp 0.00% : 0.000006s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000010s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000100s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000051s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000012s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000007s : 1: overlap_recompute_comm 0.00% : 0.000041s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000099s : 1: partial_unused_args_eliminate 0.00% : 0.000058s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000154s : 1: pre_auto_parallel 0.00% : 0.000054s : 1: py_interpret_to_execute 0.00% : 0.000109s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000065s : 1: remove_cast_before_assign_add 0.01% : 0.000242s : 1: remove_dup_value 0.05% : 0.002492s : 1: renormalize.infer 0.21% : 0.009771s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000187s : 1: rewriter_after_opt_a 0.00% : 0.000128s : 1: rewriter_before_opt_a 0.00% : 0.000008s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000059s : 1: split_layernorm_comm 0.00% : 0.000007s : 1: split_matmul_comm_elemetwise 0.00% : 0.000073s : 1: swap_dp_allreduce_reducescatter 0.06% : 0.002759s : 1: symbol_engine_optimizer 0.01% : 0.000298s : 1: tuple_transform 21.50% : 0.991552s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_quant_no_quant_jiutian[1] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_quant_no_quant_jiutian[1],max_mem:792.0M =============================== 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 240.47s (0:04:00) ==================