==================================================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_001/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(160809:281473230462768,MainProcess):2026-01-29-17:37:32.572.081 [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 = 0.0485579, [21] [bootstrap]: 0.00074529 [type_inference]: 0.0209114 [event_method]: 1.559e-05 [auto_monad]: 8.167e-05 [graph_reusing]: 5.25001e-06 [inline]: 2.37001e-06 [add_attr]: 0.0198293, [1] [add_attr_with_inline]: 0.019816, [1] [Cycle 1]: 9.743e-05, [2] [tag_attr]: 2.197e-05 [meta_addattr_fg_expand]: 3.66999e-06 [parallel-infer-symbol]: 3.54002e-06 [pre_auto_parallel]: 4.241e-05 [insert-virtual-dataset]: 2.37999e-06 [parallel-infer-symbol-second]: 8.10018e-07 [dataset_repeat_opt]: 2.14999e-06 [pipeline_split]: 1.60999e-06 [optimize]: 0.00602617, [53] [py_interpret_to_execute]: 3.022e-05 [rewriter_before_opt_a]: 7.866e-05 [opt_a]: 0.00326924, [2] [Cycle 1]: 0.00219623, [45] [expand_dump_flag]: 3.14999e-06 [switch_simplify]: 3.293e-05 [loop_unroll]: 1.921e-05 [a_1]: 0.00046846 [with_stream_mark]: 2.324e-05 [recompute_prepare]: 1.418e-05 [updatestate_depend_eliminate]: 5.32001e-06 [updatestate_assign_eliminate]: 4.76002e-06 [updatestate_loads_eliminate]: 4.65001e-06 [parameter_eliminate]: 1.79998e-06 [a_2]: 0.00014584 [accelerated_algorithm]: 1.147e-05 [shard]: 2.36998e-06 [meta_shard_fg_expand]: 1.97999e-06 [shard_inline]: 1.089e-05 [merge_send_recv]: 1.074e-05 [auto_parallel]: 8.59998e-06 [parallel]: 5.313e-05 [flash_sp]: 1.993e-05 [merge_comm]: 6.24001e-06 [allreduce_fusion]: 4.92e-06 [matmul_add_comm_reduction]: 1.106e-05 [allreduce_slice_to_reducescatter]: 6.49976e-07 [virtual_shard_identity]: 1.396e-05 [virtual_dataset]: 1.094e-05 [get_grad_eliminate_]: 1.012e-05 [virtual_output]: 1.085e-05 [merge_forward]: 5.66e-06 [cell_reuse_recompute_pass]: 1.34998e-06 [offload_activation]: 1.123e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.858e-05 [merge_recompute_call_nodes]: 1.84e-06 [before_grad]: 1.497e-05 [set_forward_comm_id_for_comm_node_pass]: 5.16002e-06 [meta_fg_expand]: 3.26001e-06 [flash_sp_send_recv_attached]: 2.76e-06 [receive_attached]: 2.13002e-06 [after_resolve]: 2.267e-05 [a_after_grad]: 1.772e-05 [renormalize]: 0.00075289 [add_forward_monad_depend]: 1.079e-05 [auto_monad_grad]: 2.39001e-06 [auto_monad_eliminator]: 1.698e-05 [cse]: 7.026e-05 [a_3]: 8.215e-05 [Cycle 2]: 0.00106128, [45] [expand_dump_flag]: 1.63002e-06 [switch_simplify]: 1.299e-05 [loop_unroll]: 1.066e-05 [a_1]: 0.00031072 [with_stream_mark]: 1.898e-05 [recompute_prepare]: 1.142e-05 [updatestate_depend_eliminate]: 4.95001e-06 [updatestate_assign_eliminate]: 4.1e-06 [updatestate_loads_eliminate]: 3.94997e-06 [parameter_eliminate]: 1.15001e-06 [a_2]: 0.00013535 [accelerated_algorithm]: 1.092e-05 [shard]: 1.82001e-06 [meta_shard_fg_expand]: 2.37999e-06 [shard_inline]: 1.088e-05 [merge_send_recv]: 7.84002e-06 [auto_parallel]: 9.52001e-06 [parallel]: 6.86999e-06 [flash_sp]: 3.83001e-06 [merge_comm]: 5.13002e-06 [allreduce_fusion]: 4.85999e-06 [matmul_add_comm_reduction]: 9.20001e-06 [allreduce_slice_to_reducescatter]: 5.8001e-07 [virtual_shard_identity]: 1.171e-05 [virtual_dataset]: 1.139e-05 [get_grad_eliminate_]: 9.98002e-06 [virtual_output]: 9.83002e-06 [merge_forward]: 5.69e-06 [cell_reuse_recompute_pass]: 1.71e-06 [offload_activation]: 1.04e-05 [cell_reuse_handle_not_recompute_node_pass]: 1.975e-05 [merge_recompute_call_nodes]: 1.09e-06 [before_grad]: 1.449e-05 [set_forward_comm_id_for_comm_node_pass]: 5.34e-06 [meta_fg_expand]: 2.93998e-06 [flash_sp_send_recv_attached]: 1.25001e-06 [receive_attached]: 1.59e-06 [after_resolve]: 2.201e-05 [a_after_grad]: 1.661e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.16e-06 [auto_monad_grad]: 1.54998e-06 [auto_monad_eliminator]: 1.22e-05 [cse]: 3.361e-05 [a_3]: 6.857e-05 [py_interpret_to_execute_after_opt_a]: 1.675e-05 [slice_cell_reuse_recomputed_activation]: 2.06e-06 [rewriter_after_opt_a]: 7.815e-05 [convert_after_rewriter]: 1.03e-05 [order_py_execute_after_rewriter]: 8.00999e-06 [mutable_eliminate]: 0.00062011 [opt_b]: 0.00034286, [1] [Cycle 1]: 0.00033483, [7] [b_1]: 0.00022164 [b_2]: 1.272e-05 [updatestate_depend_eliminate]: 1.095e-05 [updatestate_assign_eliminate]: 4.34002e-06 [updatestate_loads_eliminate]: 4.17e-06 [renormalize]: 8.70001e-07 [cse]: 4.413e-05 [optimize_parallel_all_gather_comm]: 2.211e-05 [overlap_param_gather]: 1.99e-06 [cconv]: 3.3e-05 [loop_unroll]: 0.00046776 [opt_after_cconv]: 0.00016089, [1] [Cycle 1]: 0.00015385, [7] [c_1]: 5.741e-05 [parameter_eliminate]: 5.79e-06 [updatestate_depend_eliminate]: 8.38001e-06 [updatestate_assign_eliminate]: 4.03999e-06 [updatestate_loads_eliminate]: 3.85e-06 [cse]: 3.775e-05 [renormalize]: 7.09988e-07 [remove_dup_value]: 5.784e-05 [tuple_transform]: 0.0001208, [1] [Cycle 1]: 0.00011601, [4] [d_1]: 8.219e-05 [none_parameter_eliminate]: 2.11e-06 [renormalize]: 3.4002e-07 [switch_simplify]: 1.19e-05 [partial_unused_args_eliminate]: 1.81998e-06 [add_recomputation]: 6.615e-05 [cse_after_recomputation]: 3.599e-05, [1] [Cycle 1]: 3.111e-05, [1] [cse]: 2.512e-05 [environ_conv]: 1.783e-05 [swap_dp_allreduce_reducescatter]: 7.65e-06 [bias_add_comm_swap]: 3.13e-06 [label_micro_interleaved_index]: 5.41998e-06 [label_fine_grained_interleaved_index]: 2.59001e-06 [merge_cast_opt]: 1.50999e-06 [slice_recompute_activation]: 2.24001e-06 [micro_interleaved_order_control]: 2.46998e-06 [assign_add_opt]: 1.22999e-06 [ForceFp32Comm]: 9.80013e-07 [remove_cast_before_assign_add]: 1.04e-06 [full_micro_interleaved_order_control]: 2.04999e-06 [reorder_send_recv_between_fp_bp]: 3.08e-06 [comm_op_add_attrs]: 1.04e-06 [add_comm_op_reuse_tag]: 9.89996e-07 [interleave_split_concat_branches]: 1.14998e-06 [interleave_parallel_branches]: 1.12e-06 [overlap_opt_shard_in_pipeline]: 2.267e-05 [overlap_opt_shard_grad_in_pipeline]: 2.12999e-06 [control_data_broadcast_order]: 1.763e-05 [grouped_pairwise_exchange_alltoall]: 1.69e-06 [offloading_packed_experts]: 4.84998e-06 [overlap_recompute_and_grad_model_parallel]: 5.46e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.17e-06 [overlap_recompute_allgather_and_fa_grad]: 1.40001e-06 [overlap_recompute_comm]: 2.37999e-06 [overlap_grad_ring_attention]: 5.14e-06 [overlap_grad_flash_sp]: 3.583e-05 [begin_end_overlap_inline]: 5.19998e-07 [split_matmul_comm_elemetwise]: 2.37999e-06 [split_layernorm_comm]: 2.24999e-06 [handle_group_info]: 1.00001e-06 [symbol_engine_optimizer]: 0.00020002, [1] [Cycle 1]: 0.00019438, [6] [build]: 8.512e-05 [elim_shapecalc]: 1.708e-05 [elim_not_effective]: 2.545e-05 [opt_reshape]: 1.137e-05 [fold_const_symbol]: 1.962e-05 [renormalize]: 3.00002e-07 [detach_backward]: 2.21998e-06 [pipeline_parallel_scheduler]: 1.78002e-06 [auto_monad_reorder]: 3.069e-05 [get_jit_bprop_graph]: 2.02999e-06 [rewriter_after_jit_bprop_graph]: 5.49998e-06 [opt_after_jit_grad]: 0.00060317 [validate]: 6.864e-05 Sums bootstrap : 0.000745s : 2.69% type_inference : 0.020911s : 75.45% event_method : 0.000016s : 0.06% auto_monad : 0.000082s : 0.29% graph_reusing : 0.000005s : 0.02% inline : 0.000002s : 0.01% add_attr.add_attr_with_inline.tag_attr : 0.000022s : 0.08% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.01% parallel-infer-symbol : 0.000004s : 0.01% pre_auto_parallel : 0.000042s : 0.15% insert-virtual-dataset : 0.000002s : 0.01% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.01% pipeline_split : 0.000002s : 0.01% optimize.py_interpret_to_execute : 0.000030s : 0.11% optimize.rewriter_before_opt_a : 0.000079s : 0.28% optimize.opt_a.expand_dump_flag : 0.000005s : 0.02% optimize.opt_a.switch_simplify : 0.000046s : 0.17% optimize.opt_a.loop_unroll : 0.000030s : 0.11% optimize.opt_a.a_1 : 0.000779s : 2.81% optimize.opt_a.with_stream_mark : 0.000042s : 0.15% optimize.opt_a.recompute_prepare : 0.000026s : 0.09% optimize.opt_a.updatestate_depend_eliminate : 0.000010s : 0.04% optimize.opt_a.updatestate_assign_eliminate : 0.000009s : 0.03% optimize.opt_a.updatestate_loads_eliminate : 0.000009s : 0.03% optimize.opt_a.parameter_eliminate : 0.000003s : 0.01% optimize.opt_a.a_2 : 0.000281s : 1.01% optimize.opt_a.accelerated_algorithm : 0.000022s : 0.08% optimize.opt_a.shard : 0.000004s : 0.02% optimize.opt_a.meta_shard_fg_expand : 0.000004s : 0.02% optimize.opt_a.shard_inline : 0.000022s : 0.08% optimize.opt_a.merge_send_recv : 0.000019s : 0.07% optimize.opt_a.auto_parallel : 0.000018s : 0.07% optimize.opt_a.parallel : 0.000060s : 0.22% optimize.opt_a.flash_sp : 0.000024s : 0.09% optimize.opt_a.merge_comm : 0.000011s : 0.04% optimize.opt_a.allreduce_fusion : 0.000010s : 0.04% optimize.opt_a.matmul_add_comm_reduction : 0.000020s : 0.07% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000026s : 0.09% optimize.opt_a.virtual_dataset : 0.000022s : 0.08% optimize.opt_a.get_grad_eliminate_ : 0.000020s : 0.07% optimize.opt_a.virtual_output : 0.000021s : 0.07% optimize.opt_a.merge_forward : 0.000011s : 0.04% optimize.opt_a.cell_reuse_recompute_pass : 0.000003s : 0.01% optimize.opt_a.offload_activation : 0.000022s : 0.08% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000038s : 0.14% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.01% optimize.opt_a.before_grad : 0.000029s : 0.11% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000011s : 0.04% optimize.opt_a.meta_fg_expand : 0.000006s : 0.02% optimize.opt_a.flash_sp_send_recv_attached : 0.000004s : 0.01% optimize.opt_a.receive_attached : 0.000004s : 0.01% optimize.opt_a.after_resolve : 0.000045s : 0.16% optimize.opt_a.a_after_grad : 0.000034s : 0.12% optimize.opt_a.renormalize : 0.000753s : 2.72% optimize.opt_a.add_forward_monad_depend : 0.000013s : 0.05% optimize.opt_a.auto_monad_grad : 0.000004s : 0.01% optimize.opt_a.auto_monad_eliminator : 0.000029s : 0.11% optimize.opt_a.cse : 0.000104s : 0.37% optimize.opt_a.a_3 : 0.000151s : 0.54% optimize.py_interpret_to_execute_after_opt_a : 0.000017s : 0.06% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.01% optimize.rewriter_after_opt_a : 0.000078s : 0.28% optimize.convert_after_rewriter : 0.000010s : 0.04% optimize.order_py_execute_after_rewriter : 0.000008s : 0.03% optimize.mutable_eliminate : 0.000620s : 2.24% optimize.opt_b.b_1 : 0.000222s : 0.80% optimize.opt_b.b_2 : 0.000013s : 0.05% optimize.opt_b.updatestate_depend_eliminate : 0.000011s : 0.04% optimize.opt_b.updatestate_assign_eliminate : 0.000004s : 0.02% optimize.opt_b.updatestate_loads_eliminate : 0.000004s : 0.02% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000044s : 0.16% optimize.optimize_parallel_all_gather_comm : 0.000022s : 0.08% optimize.overlap_param_gather : 0.000002s : 0.01% optimize.cconv : 0.000033s : 0.12% optimize.loop_unroll : 0.000468s : 1.69% optimize.opt_after_cconv.c_1 : 0.000057s : 0.21% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.02% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.03% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.01% optimize.opt_after_cconv.cse : 0.000038s : 0.14% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000058s : 0.21% optimize.tuple_transform.d_1 : 0.000082s : 0.30% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.01% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000012s : 0.04% optimize.partial_unused_args_eliminate : 0.000002s : 0.01% optimize.add_recomputation : 0.000066s : 0.24% optimize.cse_after_recomputation.cse : 0.000025s : 0.09% optimize.environ_conv : 0.000018s : 0.06% optimize.swap_dp_allreduce_reducescatter : 0.000008s : 0.03% optimize.bias_add_comm_swap : 0.000003s : 0.01% optimize.label_micro_interleaved_index : 0.000005s : 0.02% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.01% optimize.merge_cast_opt : 0.000002s : 0.01% optimize.slice_recompute_activation : 0.000002s : 0.01% optimize.micro_interleaved_order_control : 0.000002s : 0.01% 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 : 0.01% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.01% 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 : 0.08% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.01% optimize.control_data_broadcast_order : 0.000018s : 0.06% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.01% optimize.offloading_packed_experts : 0.000005s : 0.02% optimize.overlap_recompute_and_grad_model_parallel : 0.000005s : 0.02% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.01% optimize.overlap_recompute_comm : 0.000002s : 0.01% optimize.overlap_grad_ring_attention : 0.000005s : 0.02% optimize.overlap_grad_flash_sp : 0.000036s : 0.13% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.01% optimize.split_layernorm_comm : 0.000002s : 0.01% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000085s : 0.31% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.06% optimize.symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.09% optimize.symbol_engine_optimizer.opt_reshape : 0.000011s : 0.04% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.07% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.01% pipeline_parallel_scheduler : 0.000002s : 0.01% auto_monad_reorder : 0.000031s : 0.11% get_jit_bprop_graph : 0.000002s : 0.01% rewriter_after_jit_bprop_graph : 0.000005s : 0.02% opt_after_jit_grad : 0.000603s : 2.18% validate : 0.000069s : 0.25% Time group info: ------[substitution.] 0.000154 39 5.75% : 0.000009s : 2: substitution.elim_not_effective 4.33% : 0.000007s : 2: substitution.fold_const_symbol 5.32% : 0.000008s : 10: substitution.graph_param_transform 71.33% : 0.000110s : 1: substitution.inline 3.01% : 0.000005s : 4: substitution.j_node_and_user_rematch 3.67% : 0.000006s : 4: substitution.remove_not_recompute_node 6.59% : 0.000010s : 16: substitution.replace_old_param ------[type_inference.] 0.020815 2 97.58% : 0.020312s : 1: type_inference.infer 2.42% : 0.000503s : 1: type_inference.specialize ------[replace.] 0.000020 1 100.00% : 0.000020s : 1: replace.inline ------[match.] 0.000108 1 100.00% : 0.000108s : 1: match.inline ------[predicate.] 0.000250 2335 0.87% : 0.000002s : 21: predicate.accumulaten_eliminater 0.94% : 0.000002s : 10: predicate.ad_related_special_op_eliminate 0.74% : 0.000002s : 20: predicate.addn_check_dump 0.88% : 0.000002s : 21: predicate.addn_zero_filter 0.74% : 0.000002s : 21: predicate.adjust_all_reduce_mul_add 1.97% : 0.000005s : 41: predicate.arithmetic_simplify 0.82% : 0.000002s : 21: predicate.cast_eliminate 0.86% : 0.000002s : 20: predicate.check_bprop_eliminate 0.74% : 0.000002s : 20: predicate.compare_switch_simplify 0.30% : 0.000001s : 10: predicate.const_output_eliminate 0.72% : 0.000002s : 20: predicate.depend_value_elim 0.85% : 0.000002s : 21: predicate.dict_get_item_const_eliminator 0.97% : 0.000002s : 21: predicate.dict_get_item_eliminator 0.83% : 0.000002s : 21: predicate.dict_set_item_eliminator 1.27% : 0.000003s : 20: predicate.dumpgradient_eliminate 0.42% : 0.000001s : 10: predicate.elim_not_effective 0.52% : 0.000001s : 10: predicate.elim_shapecalc_of_broadcastargs 1.20% : 0.000003s : 31: predicate.environ_add_const_eliminate 1.12% : 0.000003s : 31: predicate.environ_get_add_eliminate 1.13% : 0.000003s : 31: predicate.environ_get_depend_swap 2.03% : 0.000005s : 51: predicate.environ_get_eliminate 1.10% : 0.000003s : 31: predicate.environ_get_set_eliminate 0.82% : 0.000002s : 22: predicate.exchange_switch_depend_value 1.65% : 0.000004s : 22: predicate.float_depend_g_call 0.73% : 0.000002s : 20: predicate.float_environ_get_switch 1.15% : 0.000003s : 30: predicate.float_tuple_getitem_switch 0.32% : 0.000001s : 10: predicate.fold_const_symbol 0.84% : 0.000002s : 20: predicate.get_grad_eliminate 0.38% : 0.000001s : 10: predicate.graph_param_transform 0.75% : 0.000002s : 20: predicate.incorporate_call 0.70% : 0.000002s : 20: predicate.incorporate_call_switch 5.73% : 0.000014s : 103: predicate.inline 1.09% : 0.000003s : 20: predicate.inline_without_move 0.56% : 0.000001s : 20: predicate.j_node_and_user_rematch 0.92% : 0.000002s : 20: predicate.less_batch_normalization 1.60% : 0.000004s : 41: predicate.list_to_tuple_eliminator_ 2.25% : 0.000006s : 62: predicate.load_eliminater 1.11% : 0.000003s : 10: predicate.loop_unroll_after_grad 1.28% : 0.000003s : 31: predicate.loop_unroll_before_grad 1.93% : 0.000005s : 41: predicate.make_slice_get_slice_eliminator 0.78% : 0.000002s : 20: predicate.merge_addn 0.84% : 0.000002s : 20: predicate.micro_step_allgather_replace 0.80% : 0.000002s : 20: predicate.mini_step_allgather_replace 0.76% : 0.000002s : 21: predicate.minmaximum_grad 1.27% : 0.000003s : 10: predicate.mutable_eliminate 0.43% : 0.000001s : 10: predicate.opt_reshape 0.59% : 0.000001s : 10: predicate.parallel_virtual_node 0.97% : 0.000002s : 22: predicate.partial_defer_inline 1.31% : 0.000003s : 31: predicate.partial_eliminate 0.76% : 0.000002s : 21: predicate.print_const_string_wrapper 0.81% : 0.000002s : 20: predicate.reduce_all_const_elim 1.17% : 0.000003s : 21: predicate.reduce_eliminate 2.25% : 0.000006s : 62: predicate.redundant_stop_gradient_eliminater 0.78% : 0.000002s : 20: predicate.remove_not_recompute_node 1.70% : 0.000004s : 41: predicate.replace_applicator 0.92% : 0.000002s : 20: predicate.replace_old_param 0.52% : 0.000001s : 10: predicate.reset_defer_inline 0.82% : 0.000002s : 21: predicate.reshape_eliminate 0.85% : 0.000002s : 20: predicate.row_tensor_add_zeros_like 0.44% : 0.000001s : 10: predicate.row_tensor_eliminate 0.90% : 0.000002s : 20: predicate.same_eliminate 0.81% : 0.000002s : 20: predicate.set_cell_output_no_recompute 0.95% : 0.000002s : 20: predicate.shard_identity_eliminate 0.81% : 0.000002s : 20: predicate.special_op_eliminate 0.86% : 0.000002s : 20: predicate.specialize_transform 1.06% : 0.000003s : 20: predicate.split_environ_get_set_with_tuple_value 1.01% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.50% : 0.000001s : 10: predicate.switch_call_monad_eliminater 0.85% : 0.000002s : 22: predicate.switch_defer_inline 1.62% : 0.000004s : 42: predicate.switch_layer_defer_inline 3.70% : 0.000009s : 83: predicate.switch_simplify 0.76% : 0.000002s : 21: predicate.tile_eliminate 0.79% : 0.000002s : 21: predicate.transpose_eliminate 1.55% : 0.000004s : 41: predicate.tuple_list_convert_item_index_to_positive 1.56% : 0.000004s : 41: predicate.tuple_list_get_item_const_eliminator 1.50% : 0.000004s : 41: predicate.tuple_list_get_item_depend_reorder 2.85% : 0.000007s : 61: predicate.tuple_list_get_item_eliminator 1.58% : 0.000004s : 41: predicate.tuple_list_get_set_item_eliminator 2.47% : 0.000006s : 61: predicate.tuple_list_set_item_eliminator 1.66% : 0.000004s : 41: predicate.tuple_to_list_eliminator_ 2.16% : 0.000005s : 62: predicate.updatestate_pure_node_eliminater 3.30% : 0.000008s : 82: predicate.updatestate_useless_node_eliminater 0.42% : 0.000001s : 10: predicate.value_based_eliminate 0.90% : 0.000002s : 20: predicate.virtual_dataset_eliminate 0.83% : 0.000002s : 20: predicate.virtual_output_eliminate 0.39% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.60% : 0.000002s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000498 6 54.43% : 0.000271s : 3: func_graph_cloner_run.FuncGraphClonerGraph 45.57% : 0.000227s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.077008 192 0.00% : 0.000004s : 1: ForceFp32Comm 25.76% : 0.019836s : 1: add_attr 25.74% : 0.019820s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.09% : 0.000071s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.11% : 0.000087s : 1: auto_monad 0.05% : 0.000037s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.01% : 0.000006s : 1: bias_add_comm_swap 1.02% : 0.000783s : 1: bootstrap 0.05% : 0.000037s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.03% : 0.000021s : 1: control_data_broadcast_order 0.02% : 0.000014s : 1: convert_after_rewriter 0.05% : 0.000039s : 1: cse_after_recomputation 0.01% : 0.000005s : 1: dataset_repeat_opt 0.01% : 0.000006s : 1: detach_backward 0.03% : 0.000021s : 1: environ_conv 0.03% : 0.000023s : 1: event_method 0.01% : 0.000005s : 1: full_micro_interleaved_order_control 0.01% : 0.000006s : 1: get_jit_bprop_graph 0.01% : 0.000009s : 1: graph_reusing 0.01% : 0.000004s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.01% : 0.000005s : 1: inline 0.01% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.01% : 0.000004s : 1: interleave_split_concat_branches 0.01% : 0.000006s : 1: label_fine_grained_interleaved_index 0.01% : 0.000008s : 1: label_micro_interleaved_index 0.62% : 0.000478s : 1: loop_unroll 0.01% : 0.000004s : 1: merge_cast_opt 0.01% : 0.000005s : 1: micro_interleaved_order_control 0.82% : 0.000634s : 1: mutable_eliminate 0.01% : 0.000008s : 1: offloading_packed_experts 0.03% : 0.000021s : 1: opt.transform.loop_unroll_optimizer 0.03% : 0.000026s : 1: opt.transform.mutable_eliminate 1.95% : 0.001499s : 78: opt.transform.opt_a 0.07% : 0.000056s : 1: opt.transform.opt_after_cconv 0.06% : 0.000043s : 1: opt.transform.opt_after_jit_grad 0.27% : 0.000206s : 28: opt.transform.opt_b 0.12% : 0.000092s : 2: opt.transform.opt_trans_graph 0.09% : 0.000069s : 4: opt.transform.symbol_engine_opt 4.25% : 0.003273s : 1: opt_a 0.21% : 0.000164s : 1: opt_after_cconv 0.80% : 0.000616s : 1: opt_after_jit_grad 0.45% : 0.000347s : 1: opt_b 7.83% : 0.006031s : 1: optimize 0.03% : 0.000026s : 1: optimize_parallel_all_gather_comm 0.01% : 0.000011s : 1: order_py_execute_after_rewriter 0.05% : 0.000040s : 1: overlap_grad_flash_sp 0.01% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000008s : 1: overlap_grad_ring_attention 0.01% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.03% : 0.000026s : 1: overlap_opt_shard_in_pipeline 0.01% : 0.000005s : 1: overlap_param_gather 0.01% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000008s : 1: overlap_recompute_and_grad_model_parallel 0.01% : 0.000005s : 1: overlap_recompute_comm 0.01% : 0.000007s : 1: parallel-infer-symbol 0.01% : 0.000004s : 1: parallel-infer-symbol-second 0.01% : 0.000005s : 1: partial_unused_args_eliminate 0.01% : 0.000005s : 1: pipeline_parallel_scheduler 0.01% : 0.000004s : 1: pipeline_split 0.06% : 0.000047s : 1: pre_auto_parallel 0.04% : 0.000035s : 1: py_interpret_to_execute 0.03% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.08% : 0.000063s : 1: remove_dup_value 0.52% : 0.000399s : 1: renormalize.infer 0.45% : 0.000345s : 1: renormalize.specialize 0.01% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.01% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.11% : 0.000084s : 1: rewriter_after_opt_a 0.11% : 0.000083s : 1: rewriter_before_opt_a 0.01% : 0.000005s : 1: slice_cell_reuse_recomputed_activation 0.01% : 0.000005s : 1: slice_recompute_activation 0.01% : 0.000005s : 1: split_layernorm_comm 0.01% : 0.000005s : 1: split_matmul_comm_elemetwise 0.01% : 0.000011s : 1: swap_dp_allreduce_reducescatter 0.26% : 0.000203s : 1: symbol_engine_optimizer 0.16% : 0.000124s : 1: tuple_transform 27.18% : 0.020932s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_quant0[0] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_quant0[0],max_mem:484.0M [WARNING] ME(160809:281473230462768,MainProcess):2026-01-29-17:38:12.901.123 [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 = 0.218645, [21] [bootstrap]: 0.00089652 [type_inference]: 0.114851 [event_method]: 2.015e-05 [auto_monad]: 9.403e-05 [graph_reusing]: 6.11e-06 [inline]: 3.11001e-06 [add_attr]: 0.00712975, [1] [add_attr_with_inline]: 0.00710728, [1] [Cycle 1]: 0.0001089, [2] [tag_attr]: 3.48e-05 [meta_addattr_fg_expand]: 7.68001e-06 [parallel-infer-symbol]: 4.72e-06 [pre_auto_parallel]: 5.942e-05 [insert-virtual-dataset]: 2.97002e-06 [parallel-infer-symbol-second]: 7.30011e-07 [dataset_repeat_opt]: 3.38e-06 [pipeline_split]: 1.86e-06 [optimize]: 0.0942972, [53] [py_interpret_to_execute]: 9.928e-05 [rewriter_before_opt_a]: 0.0001255 [opt_a]: 0.0902386, [2] [Cycle 1]: 0.0887068, [45] [expand_dump_flag]: 4.48001e-06 [switch_simplify]: 3.804e-05 [loop_unroll]: 2.252e-05 [a_1]: 0.00061786 [with_stream_mark]: 3.6e-05 [recompute_prepare]: 2e-05 [updatestate_depend_eliminate]: 7.58999e-06 [updatestate_assign_eliminate]: 6.19001e-06 [updatestate_loads_eliminate]: 5.32999e-06 [parameter_eliminate]: 2.61e-06 [a_2]: 0.00016109 [accelerated_algorithm]: 1.73e-05 [shard]: 3.50998e-06 [meta_shard_fg_expand]: 8.3e-06 [shard_inline]: 1.335e-05 [merge_send_recv]: 1.245e-05 [auto_parallel]: 1.465e-05 [parallel]: 3.766e-05 [flash_sp]: 1.693e-05 [merge_comm]: 7.77e-06 [allreduce_fusion]: 5.46002e-06 [matmul_add_comm_reduction]: 1.619e-05 [allreduce_slice_to_reducescatter]: 9.20001e-07 [virtual_shard_identity]: 3.665e-05 [virtual_dataset]: 1.741e-05 [get_grad_eliminate_]: 1.986e-05 [virtual_output]: 2.075e-05 [merge_forward]: 7.80998e-06 [cell_reuse_recompute_pass]: 3.01001e-06 [offload_activation]: 1.884e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.215e-05 [merge_recompute_call_nodes]: 2.02001e-06 [before_grad]: 2.942e-05 [set_forward_comm_id_for_comm_node_pass]: 7.55e-06 [meta_fg_expand]: 7.66001e-06 [flash_sp_send_recv_attached]: 3.94002e-06 [receive_attached]: 3.13e-06 [after_resolve]: 4.784e-05 [a_after_grad]: 3.775e-05 [renormalize]: 0.0865643 [add_forward_monad_depend]: 1.959e-05 [auto_monad_grad]: 2.93e-06 [auto_monad_eliminator]: 2.794e-05 [cse]: 0.00010819 [a_3]: 0.00011305 [Cycle 2]: 0.00150867, [45] [expand_dump_flag]: 2.61e-06 [switch_simplify]: 1.58e-05 [loop_unroll]: 1.272e-05 [a_1]: 0.00032067 [with_stream_mark]: 3.126e-05 [recompute_prepare]: 1.413e-05 [updatestate_depend_eliminate]: 6.55002e-06 [updatestate_assign_eliminate]: 5.94999e-06 [updatestate_loads_eliminate]: 6.01e-06 [parameter_eliminate]: 2.61e-06 [a_2]: 0.00015083 [accelerated_algorithm]: 1.346e-05 [shard]: 3.4e-06 [meta_shard_fg_expand]: 3.91001e-06 [shard_inline]: 1.407e-05 [merge_send_recv]: 1.484e-05 [auto_parallel]: 1.379e-05 [parallel]: 1.207e-05 [flash_sp]: 4.60001e-06 [merge_comm]: 6.44001e-06 [allreduce_fusion]: 5.20001e-06 [matmul_add_comm_reduction]: 1.373e-05 [allreduce_slice_to_reducescatter]: 7.39994e-07 [virtual_shard_identity]: 2.125e-05 [virtual_dataset]: 1.225e-05 [get_grad_eliminate_]: 1.369e-05 [virtual_output]: 1.3e-05 [merge_forward]: 1.083e-05 [cell_reuse_recompute_pass]: 2.99999e-06 [offload_activation]: 1.703e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.116e-05 [merge_recompute_call_nodes]: 2.37999e-06 [before_grad]: 2.098e-05 [set_forward_comm_id_for_comm_node_pass]: 7.25998e-06 [meta_fg_expand]: 5.83997e-06 [flash_sp_send_recv_attached]: 2.66e-06 [receive_attached]: 2.86999e-06 [after_resolve]: 3.787e-05 [a_after_grad]: 2.038e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 4.57998e-06 [auto_monad_grad]: 2.63e-06 [auto_monad_eliminator]: 1.858e-05 [cse]: 7.283e-05 [a_3]: 8.071e-05 [py_interpret_to_execute_after_opt_a]: 3.362e-05 [slice_cell_reuse_recomputed_activation]: 2.81999e-06 [rewriter_after_opt_a]: 7.652e-05 [convert_after_rewriter]: 1.108e-05 [order_py_execute_after_rewriter]: 7.34002e-06 [mutable_eliminate]: 0.00102496 [opt_b]: 0.00045447, [1] [Cycle 1]: 0.00044321, [7] [b_1]: 0.00025168 [b_2]: 1.393e-05 [updatestate_depend_eliminate]: 1.409e-05 [updatestate_assign_eliminate]: 8.52e-06 [updatestate_loads_eliminate]: 4.79e-06 [renormalize]: 1.07998e-06 [cse]: 8.829e-05 [optimize_parallel_all_gather_comm]: 2.735e-05 [overlap_param_gather]: 2.34001e-06 [cconv]: 4.607e-05 [loop_unroll]: 0.00063047 [opt_after_cconv]: 0.00022945, [1] [Cycle 1]: 0.00021609, [7] [c_1]: 6.634e-05 [parameter_eliminate]: 7.1e-06 [updatestate_depend_eliminate]: 1.071e-05 [updatestate_assign_eliminate]: 4.31002e-06 [updatestate_loads_eliminate]: 4.32e-06 [cse]: 6.689e-05 [renormalize]: 8.59989e-07 [remove_dup_value]: 8.202e-05 [tuple_transform]: 0.00016698, [1] [Cycle 1]: 0.00015864, [4] [d_1]: 0.00010874 [none_parameter_eliminate]: 2.46e-06 [renormalize]: 2.30008e-07 [switch_simplify]: 1.409e-05 [partial_unused_args_eliminate]: 2.41998e-06 [add_recomputation]: 8.09e-05 [cse_after_recomputation]: 5.116e-05, [1] [Cycle 1]: 4.284e-05, [1] [cse]: 3.329e-05 [environ_conv]: 1.154e-05 [swap_dp_allreduce_reducescatter]: 8.61997e-06 [bias_add_comm_swap]: 3.76999e-06 [label_micro_interleaved_index]: 6.93e-06 [label_fine_grained_interleaved_index]: 3.63e-06 [merge_cast_opt]: 1.64e-06 [slice_recompute_activation]: 2.56e-06 [micro_interleaved_order_control]: 2.93e-06 [assign_add_opt]: 1.74e-06 [ForceFp32Comm]: 9.20001e-07 [remove_cast_before_assign_add]: 1.44998e-06 [full_micro_interleaved_order_control]: 3.12002e-06 [reorder_send_recv_between_fp_bp]: 4.18999e-06 [comm_op_add_attrs]: 1.24e-06 [add_comm_op_reuse_tag]: 1.20999e-06 [interleave_split_concat_branches]: 1.96998e-06 [interleave_parallel_branches]: 1.81e-06 [overlap_opt_shard_in_pipeline]: 1.35999e-06 [overlap_opt_shard_grad_in_pipeline]: 2.41998e-06 [control_data_broadcast_order]: 2.834e-05 [grouped_pairwise_exchange_alltoall]: 1.81e-06 [offloading_packed_experts]: 6.47001e-06 [overlap_recompute_and_grad_model_parallel]: 9.56998e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.52999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.59e-06 [overlap_recompute_comm]: 2.92002e-06 [overlap_grad_ring_attention]: 8.84e-06 [overlap_grad_flash_sp]: 2.88e-05 [begin_end_overlap_inline]: 7.7e-07 [split_matmul_comm_elemetwise]: 2.62001e-06 [split_layernorm_comm]: 2.38998e-06 [handle_group_info]: 1.32999e-06 [symbol_engine_optimizer]: 0.00033018, [1] [Cycle 1]: 0.00031616, [6] [build]: 0.00013273 [elim_shapecalc]: 3.838e-05 [elim_not_effective]: 2.955e-05 [opt_reshape]: 2.104e-05 [fold_const_symbol]: 2.57e-05 [renormalize]: 3.89991e-07 [detach_backward]: 2.94999e-06 [pipeline_parallel_scheduler]: 1.73002e-06 [auto_monad_reorder]: 4.848e-05 [get_jit_bprop_graph]: 2.45002e-06 [rewriter_after_jit_bprop_graph]: 7.78999e-06 [opt_after_jit_grad]: 0.00088481 [validate]: 8.642e-05 Sums bootstrap : 0.000897s : 0.43% type_inference : 0.114851s : 54.77% event_method : 0.000020s : 0.01% auto_monad : 0.000094s : 0.04% graph_reusing : 0.000006s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000035s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000008s : 0.00% parallel-infer-symbol : 0.000005s : 0.00% pre_auto_parallel : 0.000059s : 0.03% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000099s : 0.05% optimize.rewriter_before_opt_a : 0.000125s : 0.06% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000054s : 0.03% optimize.opt_a.loop_unroll : 0.000035s : 0.02% optimize.opt_a.a_1 : 0.000939s : 0.45% optimize.opt_a.with_stream_mark : 0.000067s : 0.03% optimize.opt_a.recompute_prepare : 0.000034s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000014s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000012s : 0.01% optimize.opt_a.updatestate_loads_eliminate : 0.000011s : 0.01% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000312s : 0.15% optimize.opt_a.accelerated_algorithm : 0.000031s : 0.01% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000012s : 0.01% optimize.opt_a.shard_inline : 0.000027s : 0.01% optimize.opt_a.merge_send_recv : 0.000027s : 0.01% optimize.opt_a.auto_parallel : 0.000028s : 0.01% optimize.opt_a.parallel : 0.000050s : 0.02% optimize.opt_a.flash_sp : 0.000022s : 0.01% optimize.opt_a.merge_comm : 0.000014s : 0.01% optimize.opt_a.allreduce_fusion : 0.000011s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000030s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000058s : 0.03% optimize.opt_a.virtual_dataset : 0.000030s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000034s : 0.02% optimize.opt_a.virtual_output : 0.000034s : 0.02% optimize.opt_a.merge_forward : 0.000019s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000036s : 0.02% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000073s : 0.03% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000050s : 0.02% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000015s : 0.01% optimize.opt_a.meta_fg_expand : 0.000013s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000006s : 0.00% optimize.opt_a.after_resolve : 0.000086s : 0.04% optimize.opt_a.a_after_grad : 0.000058s : 0.03% optimize.opt_a.renormalize : 0.086564s : 41.28% optimize.opt_a.add_forward_monad_depend : 0.000024s : 0.01% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000047s : 0.02% optimize.opt_a.cse : 0.000181s : 0.09% optimize.opt_a.a_3 : 0.000194s : 0.09% optimize.py_interpret_to_execute_after_opt_a : 0.000034s : 0.02% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000077s : 0.04% optimize.convert_after_rewriter : 0.000011s : 0.01% optimize.order_py_execute_after_rewriter : 0.000007s : 0.00% optimize.mutable_eliminate : 0.001025s : 0.49% optimize.opt_b.b_1 : 0.000252s : 0.12% optimize.opt_b.b_2 : 0.000014s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000014s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000009s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000005s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000088s : 0.04% optimize.optimize_parallel_all_gather_comm : 0.000027s : 0.01% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000046s : 0.02% optimize.loop_unroll : 0.000630s : 0.30% optimize.opt_after_cconv.c_1 : 0.000066s : 0.03% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.cse : 0.000067s : 0.03% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000082s : 0.04% optimize.tuple_transform.d_1 : 0.000109s : 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 : 0.000014s : 0.01% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000081s : 0.04% optimize.cse_after_recomputation.cse : 0.000033s : 0.02% optimize.environ_conv : 0.000012s : 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 : 0.000007s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000004s : 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 : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000004s : 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 : 0.000001s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000028s : 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 : 0.000010s : 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 : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000029s : 0.01% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000133s : 0.06% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000038s : 0.02% optimize.symbol_engine_optimizer.elim_not_effective : 0.000030s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000021s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000026s : 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 : 0.000048s : 0.02% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000885s : 0.42% validate : 0.000086s : 0.04% Time group info: ------[substitution.] 0.000247 39 2.00% : 0.000005s : 2: substitution.elim_not_effective 3.37% : 0.000008s : 2: substitution.fold_const_symbol 3.46% : 0.000009s : 10: substitution.graph_param_transform 80.12% : 0.000198s : 1: substitution.inline 2.11% : 0.000005s : 4: substitution.j_node_and_user_rematch 2.76% : 0.000007s : 4: substitution.remove_not_recompute_node 6.18% : 0.000015s : 16: substitution.replace_old_param ------[type_inference.] 0.114659 2 98.69% : 0.113156s : 1: type_inference.infer 1.31% : 0.001503s : 1: type_inference.specialize ------[replace.] 0.000028 1 100.00% : 0.000028s : 1: replace.inline ------[match.] 0.000196 1 100.00% : 0.000196s : 1: match.inline ------[predicate.] 0.000282 2335 0.77% : 0.000002s : 21: predicate.accumulaten_eliminater 1.23% : 0.000003s : 10: predicate.ad_related_special_op_eliminate 0.64% : 0.000002s : 20: predicate.addn_check_dump 0.78% : 0.000002s : 21: predicate.addn_zero_filter 0.69% : 0.000002s : 21: predicate.adjust_all_reduce_mul_add 2.19% : 0.000006s : 41: predicate.arithmetic_simplify 0.84% : 0.000002s : 21: predicate.cast_eliminate 0.80% : 0.000002s : 20: predicate.check_bprop_eliminate 0.69% : 0.000002s : 20: predicate.compare_switch_simplify 0.26% : 0.000001s : 10: predicate.const_output_eliminate 0.79% : 0.000002s : 20: predicate.depend_value_elim 0.87% : 0.000002s : 21: predicate.dict_get_item_const_eliminator 0.96% : 0.000003s : 21: predicate.dict_get_item_eliminator 0.86% : 0.000002s : 21: predicate.dict_set_item_eliminator 1.35% : 0.000004s : 20: predicate.dumpgradient_eliminate 0.32% : 0.000001s : 10: predicate.elim_not_effective 0.90% : 0.000003s : 10: predicate.elim_shapecalc_of_broadcastargs 1.13% : 0.000003s : 31: predicate.environ_add_const_eliminate 1.01% : 0.000003s : 31: predicate.environ_get_add_eliminate 1.03% : 0.000003s : 31: predicate.environ_get_depend_swap 1.89% : 0.000005s : 51: predicate.environ_get_eliminate 1.00% : 0.000003s : 31: predicate.environ_get_set_eliminate 0.75% : 0.000002s : 22: predicate.exchange_switch_depend_value 1.86% : 0.000005s : 22: predicate.float_depend_g_call 0.76% : 0.000002s : 20: predicate.float_environ_get_switch 1.03% : 0.000003s : 30: predicate.float_tuple_getitem_switch 0.28% : 0.000001s : 10: predicate.fold_const_symbol 0.89% : 0.000003s : 20: predicate.get_grad_eliminate 0.39% : 0.000001s : 10: predicate.graph_param_transform 0.64% : 0.000002s : 20: predicate.incorporate_call 0.61% : 0.000002s : 20: predicate.incorporate_call_switch 5.18% : 0.000015s : 103: predicate.inline 1.30% : 0.000004s : 20: predicate.inline_without_move 0.51% : 0.000001s : 20: predicate.j_node_and_user_rematch 1.08% : 0.000003s : 20: predicate.less_batch_normalization 1.76% : 0.000005s : 41: predicate.list_to_tuple_eliminator_ 2.07% : 0.000006s : 62: predicate.load_eliminater 0.99% : 0.000003s : 10: predicate.loop_unroll_after_grad 1.21% : 0.000003s : 31: predicate.loop_unroll_before_grad 1.75% : 0.000005s : 41: predicate.make_slice_get_slice_eliminator 0.71% : 0.000002s : 20: predicate.merge_addn 0.75% : 0.000002s : 20: predicate.micro_step_allgather_replace 0.67% : 0.000002s : 20: predicate.mini_step_allgather_replace 0.66% : 0.000002s : 21: predicate.minmaximum_grad 1.28% : 0.000004s : 10: predicate.mutable_eliminate 0.43% : 0.000001s : 10: predicate.opt_reshape 0.42% : 0.000001s : 10: predicate.parallel_virtual_node 1.01% : 0.000003s : 22: predicate.partial_defer_inline 1.20% : 0.000003s : 31: predicate.partial_eliminate 0.76% : 0.000002s : 21: predicate.print_const_string_wrapper 0.71% : 0.000002s : 20: predicate.reduce_all_const_elim 1.27% : 0.000004s : 21: predicate.reduce_eliminate 2.26% : 0.000006s : 62: predicate.redundant_stop_gradient_eliminater 0.91% : 0.000003s : 20: predicate.remove_not_recompute_node 1.50% : 0.000004s : 41: predicate.replace_applicator 0.78% : 0.000002s : 20: predicate.replace_old_param 0.41% : 0.000001s : 10: predicate.reset_defer_inline 0.79% : 0.000002s : 21: predicate.reshape_eliminate 0.90% : 0.000003s : 20: predicate.row_tensor_add_zeros_like 0.47% : 0.000001s : 10: predicate.row_tensor_eliminate 0.95% : 0.000003s : 20: predicate.same_eliminate 0.69% : 0.000002s : 20: predicate.set_cell_output_no_recompute 1.32% : 0.000004s : 20: predicate.shard_identity_eliminate 0.95% : 0.000003s : 20: predicate.special_op_eliminate 0.86% : 0.000002s : 20: predicate.specialize_transform 1.53% : 0.000004s : 20: predicate.split_environ_get_set_with_tuple_value 1.02% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.47% : 0.000001s : 10: predicate.switch_call_monad_eliminater 0.81% : 0.000002s : 22: predicate.switch_defer_inline 1.71% : 0.000005s : 42: predicate.switch_layer_defer_inline 3.66% : 0.000010s : 83: predicate.switch_simplify 0.80% : 0.000002s : 21: predicate.tile_eliminate 0.88% : 0.000002s : 21: predicate.transpose_eliminate 1.78% : 0.000005s : 41: predicate.tuple_list_convert_item_index_to_positive 2.00% : 0.000006s : 41: predicate.tuple_list_get_item_const_eliminator 1.45% : 0.000004s : 41: predicate.tuple_list_get_item_depend_reorder 3.13% : 0.000009s : 61: predicate.tuple_list_get_item_eliminator 1.73% : 0.000005s : 41: predicate.tuple_list_get_set_item_eliminator 2.85% : 0.000008s : 61: predicate.tuple_list_set_item_eliminator 1.55% : 0.000004s : 41: predicate.tuple_to_list_eliminator_ 1.96% : 0.000006s : 62: predicate.updatestate_pure_node_eliminater 2.78% : 0.000008s : 82: predicate.updatestate_useless_node_eliminater 0.39% : 0.000001s : 10: predicate.value_based_eliminate 0.88% : 0.000002s : 20: predicate.virtual_dataset_eliminate 0.82% : 0.000002s : 20: predicate.virtual_output_eliminate 0.37% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.71% : 0.000002s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001628 6 40.43% : 0.000658s : 3: func_graph_cloner_run.FuncGraphClonerGraph 59.57% : 0.000970s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.324163 192 0.00% : 0.000006s : 1: ForceFp32Comm 2.20% : 0.007140s : 1: add_attr 2.19% : 0.007112s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.03% : 0.000089s : 1: add_recomputation 0.00% : 0.000009s : 1: assign_add_opt 0.03% : 0.000102s : 1: auto_monad 0.02% : 0.000054s : 1: auto_monad_reorder 0.00% : 0.000008s : 1: begin_end_overlap_inline 0.00% : 0.000011s : 1: bias_add_comm_swap 0.29% : 0.000932s : 1: bootstrap 0.02% : 0.000054s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.01% : 0.000034s : 1: control_data_broadcast_order 0.00% : 0.000016s : 1: convert_after_rewriter 0.02% : 0.000055s : 1: cse_after_recomputation 0.00% : 0.000007s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.01% : 0.000016s : 1: environ_conv 0.01% : 0.000028s : 1: event_method 0.00% : 0.000008s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000011s : 1: graph_reusing 0.00% : 0.000006s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000013s : 1: inline 0.00% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000006s : 1: interleave_parallel_branches 0.00% : 0.000009s : 1: interleave_split_concat_branches 0.00% : 0.000008s : 1: label_fine_grained_interleaved_index 0.00% : 0.000011s : 1: label_micro_interleaved_index 0.20% : 0.000649s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000008s : 1: micro_interleaved_order_control 0.32% : 0.001042s : 1: mutable_eliminate 0.00% : 0.000011s : 1: offloading_packed_experts 0.01% : 0.000028s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000040s : 1: opt.transform.mutable_eliminate 0.59% : 0.001905s : 78: opt.transform.opt_a 0.02% : 0.000064s : 1: opt.transform.opt_after_cconv 0.02% : 0.000075s : 1: opt.transform.opt_after_jit_grad 0.07% : 0.000231s : 28: opt.transform.opt_b 0.04% : 0.000119s : 2: opt.transform.opt_trans_graph 0.03% : 0.000108s : 4: opt.transform.symbol_engine_opt 27.84% : 0.090245s : 1: opt_a 0.07% : 0.000234s : 1: opt_after_cconv 0.28% : 0.000907s : 1: opt_after_jit_grad 0.14% : 0.000463s : 1: opt_b 29.09% : 0.094306s : 1: optimize 0.01% : 0.000032s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.01% : 0.000035s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000019s : 1: overlap_grad_ring_attention 0.00% : 0.000009s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000005s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000006s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000014s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000010s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pipeline_parallel_scheduler 0.00% : 0.000006s : 1: pipeline_split 0.02% : 0.000065s : 1: pre_auto_parallel 0.03% : 0.000105s : 1: py_interpret_to_execute 0.01% : 0.000040s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000005s : 1: remove_cast_before_assign_add 0.03% : 0.000089s : 1: remove_dup_value 0.25% : 0.000816s : 1: renormalize.infer 0.30% : 0.000960s : 1: renormalize.specialize 0.00% : 0.000014s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000083s : 1: rewriter_after_opt_a 0.04% : 0.000133s : 1: rewriter_before_opt_a 0.00% : 0.000007s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000007s : 1: split_matmul_comm_elemetwise 0.00% : 0.000013s : 1: swap_dp_allreduce_reducescatter 0.10% : 0.000335s : 1: symbol_engine_optimizer 0.05% : 0.000176s : 1: tuple_transform 35.44% : 0.114881s : 1: type_inference . [hook] pytest_runtest_teardown:test_paged_attention_quant0[1] tests/st/infer/ops/test_internal_ops/test_paged_attention.py::test_paged_attention_quant0[1],max_mem:484.0M =============================== 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 100.50s (0:01:40) ==================