==================================================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_007/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_gated_ffn.py [WARNING] ME(168808:281473662574384,MainProcess):2026-01-29-17:37:34.861.422 [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 = 2.71883, [21] [bootstrap]: 0.00066332 [type_inference]: 2.53981 [event_method]: 3.01e-05 [auto_monad]: 0.00153609 [graph_reusing]: 1.091e-05 [inline]: 3.41999e-06 [add_attr]: 0.157295, [1] [add_attr_with_inline]: 0.157277, [1] [Cycle 1]: 0.00012583, [2] [tag_attr]: 4.519e-05 [meta_addattr_fg_expand]: 9.12999e-06 [parallel-infer-symbol]: 3.32997e-06 [pre_auto_parallel]: 7.538e-05 [insert-virtual-dataset]: 3.31999e-06 [parallel-infer-symbol-second]: 8.70001e-07 [dataset_repeat_opt]: 1.99e-06 [pipeline_split]: 1.86e-06 [optimize]: 0.0183991, [53] [py_interpret_to_execute]: 5.168e-05 [rewriter_before_opt_a]: 0.00016699 [opt_a]: 0.0140754, [2] [Cycle 1]: 0.0120325, [45] [expand_dump_flag]: 3.51999e-06 [switch_simplify]: 6.332e-05 [loop_unroll]: 4.53e-05 [a_1]: 0.00155707 [with_stream_mark]: 3.971e-05 [recompute_prepare]: 3.319e-05 [updatestate_depend_eliminate]: 7.709e-05 [updatestate_assign_eliminate]: 1.551e-05 [updatestate_loads_eliminate]: 1.357e-05 [parameter_eliminate]: 3.26001e-06 [a_2]: 0.00041659 [accelerated_algorithm]: 6.181e-05 [shard]: 3.13e-06 [meta_shard_fg_expand]: 7.1e-06 [shard_inline]: 2.227e-05 [merge_send_recv]: 1.893e-05 [auto_parallel]: 2.075e-05 [parallel]: 4.849e-05 [flash_sp]: 1.602e-05 [merge_comm]: 1.341e-05 [allreduce_fusion]: 1.075e-05 [matmul_add_comm_reduction]: 2.003e-05 [allreduce_slice_to_reducescatter]: 1.06997e-06 [virtual_shard_identity]: 2.734e-05 [virtual_dataset]: 1.999e-05 [get_grad_eliminate_]: 1.976e-05 [virtual_output]: 2.028e-05 [merge_forward]: 1.192e-05 [cell_reuse_recompute_pass]: 2.10002e-06 [offload_activation]: 2.228e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.238e-05 [merge_recompute_call_nodes]: 1.87001e-06 [before_grad]: 3.525e-05 [set_forward_comm_id_for_comm_node_pass]: 1.386e-05 [meta_fg_expand]: 9.09998e-06 [flash_sp_send_recv_attached]: 5.27001e-06 [receive_attached]: 1.375e-05 [after_resolve]: 2.945e-05 [a_after_grad]: 3.299e-05 [renormalize]: 0.00834515 [add_forward_monad_depend]: 1.188e-05 [auto_monad_grad]: 2.67001e-06 [auto_monad_eliminator]: 7.066e-05 [cse]: 0.00024535 [a_3]: 0.00016377 [Cycle 2]: 0.00202711, [45] [expand_dump_flag]: 3.34001e-06 [switch_simplify]: 2.24e-05 [loop_unroll]: 1.969e-05 [a_1]: 0.00064397 [with_stream_mark]: 3.191e-05 [recompute_prepare]: 2.302e-05 [updatestate_depend_eliminate]: 1.413e-05 [updatestate_assign_eliminate]: 1.05e-05 [updatestate_loads_eliminate]: 1.35e-05 [parameter_eliminate]: 2.17999e-06 [a_2]: 0.00029716 [accelerated_algorithm]: 2.704e-05 [shard]: 2.40002e-06 [meta_shard_fg_expand]: 5.54e-06 [shard_inline]: 2.093e-05 [merge_send_recv]: 1.824e-05 [auto_parallel]: 1.892e-05 [parallel]: 9.50001e-06 [flash_sp]: 4.26001e-06 [merge_comm]: 1.205e-05 [allreduce_fusion]: 1.043e-05 [matmul_add_comm_reduction]: 1.927e-05 [allreduce_slice_to_reducescatter]: 7.7e-07 [virtual_shard_identity]: 2.369e-05 [virtual_dataset]: 1.871e-05 [get_grad_eliminate_]: 1.884e-05 [virtual_output]: 1.955e-05 [merge_forward]: 1.077e-05 [cell_reuse_recompute_pass]: 2.68e-06 [offload_activation]: 2.14e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.883e-05 [merge_recompute_call_nodes]: 1.41998e-06 [before_grad]: 3.306e-05 [set_forward_comm_id_for_comm_node_pass]: 1.17e-05 [meta_fg_expand]: 8.77e-06 [flash_sp_send_recv_attached]: 1.92001e-06 [receive_attached]: 2.48e-06 [after_resolve]: 2.622e-05 [a_after_grad]: 3.109e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.48e-06 [auto_monad_grad]: 2.31e-06 [auto_monad_eliminator]: 5.341e-05 [cse]: 8.55e-05 [a_3]: 0.00013286 [py_interpret_to_execute_after_opt_a]: 3.418e-05 [slice_cell_reuse_recomputed_activation]: 2.71e-06 [rewriter_after_opt_a]: 0.00041344 [convert_after_rewriter]: 2.787e-05 [order_py_execute_after_rewriter]: 1.253e-05 [mutable_eliminate]: 0.00080101 [opt_b]: 0.00068991, [1] [Cycle 1]: 0.00068139, [7] [b_1]: 0.00048956 [b_2]: 2.415e-05 [updatestate_depend_eliminate]: 1.805e-05 [updatestate_assign_eliminate]: 9.86998e-06 [updatestate_loads_eliminate]: 1.266e-05 [renormalize]: 7.09988e-07 [cse]: 8.192e-05 [optimize_parallel_all_gather_comm]: 3.989e-05 [overlap_param_gather]: 5.15001e-06 [cconv]: 3.74e-05 [loop_unroll]: 0.00052226 [opt_after_cconv]: 0.00028935, [1] [Cycle 1]: 0.00028216, [7] [c_1]: 0.0001301 [parameter_eliminate]: 4.09002e-06 [updatestate_depend_eliminate]: 1.574e-05 [updatestate_assign_eliminate]: 9.40001e-06 [updatestate_loads_eliminate]: 1.156e-05 [cse]: 7.306e-05 [renormalize]: 5.60016e-07 [remove_dup_value]: 7.753e-05 [tuple_transform]: 0.00023463, [1] [Cycle 1]: 0.00022935, [4] [d_1]: 0.00018255 [none_parameter_eliminate]: 2.41e-06 [renormalize]: 1.59984e-07 [switch_simplify]: 2.328e-05 [partial_unused_args_eliminate]: 2.01e-06 [add_recomputation]: 0.00014345 [cse_after_recomputation]: 6.736e-05, [1] [Cycle 1]: 6.171e-05, [1] [cse]: 5.345e-05 [environ_conv]: 2.79e-05 [swap_dp_allreduce_reducescatter]: 1.603e-05 [bias_add_comm_swap]: 2.68e-06 [label_micro_interleaved_index]: 5.32999e-06 [label_fine_grained_interleaved_index]: 2.64999e-06 [merge_cast_opt]: 1.67001e-06 [slice_recompute_activation]: 2.14999e-06 [micro_interleaved_order_control]: 2.15002e-06 [assign_add_opt]: 1.22e-06 [ForceFp32Comm]: 8.50006e-07 [remove_cast_before_assign_add]: 9.50007e-07 [full_micro_interleaved_order_control]: 2.11e-06 [reorder_send_recv_between_fp_bp]: 3.05998e-06 [comm_op_add_attrs]: 1.03001e-06 [add_comm_op_reuse_tag]: 9.89996e-07 [interleave_split_concat_branches]: 1.14e-06 [interleave_parallel_branches]: 1.29e-06 [overlap_opt_shard_in_pipeline]: 2.319e-05 [overlap_opt_shard_grad_in_pipeline]: 1.69e-06 [control_data_broadcast_order]: 3.481e-05 [grouped_pairwise_exchange_alltoall]: 1.47001e-06 [offloading_packed_experts]: 8.90999e-06 [overlap_recompute_and_grad_model_parallel]: 9.72001e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.45999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.19e-06 [overlap_recompute_comm]: 2.26998e-06 [overlap_grad_ring_attention]: 8.95001e-06 [overlap_grad_flash_sp]: 8.726e-05 [begin_end_overlap_inline]: 7.80012e-07 [split_matmul_comm_elemetwise]: 2.20002e-06 [split_layernorm_comm]: 1.70001e-06 [handle_group_info]: 1.07e-06 [symbol_engine_optimizer]: 0.00018144, [1] [Cycle 1]: 0.00017506, [6] [build]: 1.552e-05 [elim_shapecalc]: 2.991e-05 [elim_not_effective]: 3.766e-05 [opt_reshape]: 2.541e-05 [fold_const_symbol]: 3.157e-05 [renormalize]: 2.19996e-07 [detach_backward]: 2.19001e-06 [pipeline_parallel_scheduler]: 1.48002e-06 [auto_monad_reorder]: 6.021e-05 [get_jit_bprop_graph]: 2.07001e-06 [rewriter_after_jit_bprop_graph]: 6.04001e-06 [opt_after_jit_grad]: 0.00059287 [validate]: 0.00011642 Sums bootstrap : 0.000663s : 0.03% type_inference : 2.539810s : 99.20% event_method : 0.000030s : 0.00% auto_monad : 0.001536s : 0.06% graph_reusing : 0.000011s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000045s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000009s : 0.00% parallel-infer-symbol : 0.000003s : 0.00% pre_auto_parallel : 0.000075s : 0.00% 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 : 0.000052s : 0.00% optimize.rewriter_before_opt_a : 0.000167s : 0.01% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000086s : 0.00% optimize.opt_a.loop_unroll : 0.000065s : 0.00% optimize.opt_a.a_1 : 0.002201s : 0.09% optimize.opt_a.with_stream_mark : 0.000072s : 0.00% optimize.opt_a.recompute_prepare : 0.000056s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000091s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000026s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000027s : 0.00% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000714s : 0.03% optimize.opt_a.accelerated_algorithm : 0.000089s : 0.00% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.00% optimize.opt_a.shard_inline : 0.000043s : 0.00% optimize.opt_a.merge_send_recv : 0.000037s : 0.00% optimize.opt_a.auto_parallel : 0.000040s : 0.00% optimize.opt_a.parallel : 0.000058s : 0.00% optimize.opt_a.flash_sp : 0.000020s : 0.00% optimize.opt_a.merge_comm : 0.000025s : 0.00% optimize.opt_a.allreduce_fusion : 0.000021s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000039s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000051s : 0.00% optimize.opt_a.virtual_dataset : 0.000039s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000039s : 0.00% optimize.opt_a.virtual_output : 0.000040s : 0.00% optimize.opt_a.merge_forward : 0.000023s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000044s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000081s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000068s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000026s : 0.00% optimize.opt_a.meta_fg_expand : 0.000018s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000016s : 0.00% optimize.opt_a.after_resolve : 0.000056s : 0.00% optimize.opt_a.a_after_grad : 0.000064s : 0.00% optimize.opt_a.renormalize : 0.008345s : 0.33% optimize.opt_a.add_forward_monad_depend : 0.000014s : 0.00% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000124s : 0.00% optimize.opt_a.cse : 0.000331s : 0.01% optimize.opt_a.a_3 : 0.000297s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000034s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000413s : 0.02% optimize.convert_after_rewriter : 0.000028s : 0.00% optimize.order_py_execute_after_rewriter : 0.000013s : 0.00% optimize.mutable_eliminate : 0.000801s : 0.03% optimize.opt_b.b_1 : 0.000490s : 0.02% optimize.opt_b.b_2 : 0.000024s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000018s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000013s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000082s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000040s : 0.00% optimize.overlap_param_gather : 0.000005s : 0.00% optimize.cconv : 0.000037s : 0.00% optimize.loop_unroll : 0.000522s : 0.02% optimize.opt_after_cconv.c_1 : 0.000130s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000009s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000012s : 0.00% optimize.opt_after_cconv.cse : 0.000073s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000078s : 0.00% optimize.tuple_transform.d_1 : 0.000183s : 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 : 0.000023s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000143s : 0.01% optimize.cse_after_recomputation.cse : 0.000053s : 0.00% optimize.environ_conv : 0.000028s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000016s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000002s : 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 : 0.000023s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000035s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000001s : 0.00% optimize.offloading_packed_experts : 0.000009s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000087s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000016s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000030s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000038s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000025s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000032s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000001s : 0.00% auto_monad_reorder : 0.000060s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000593s : 0.02% validate : 0.000116s : 0.00% Time group info: ------[substitution.] 0.000741 201 6.37% : 0.000047s : 5: substitution.arithmetic_simplify 1.51% : 0.000011s : 2: substitution.depend_value_elim 0.73% : 0.000005s : 12: substitution.elim_not_effective 1.88% : 0.000014s : 6: substitution.float_tuple_getitem_switch 0.59% : 0.000004s : 12: substitution.fold_const_symbol 2.12% : 0.000016s : 17: substitution.graph_param_transform 45.44% : 0.000337s : 7: substitution.inline 1.56% : 0.000012s : 24: substitution.j_node_and_user_rematch 4.03% : 0.000030s : 2: substitution.less_batch_normalization 0.88% : 0.000007s : 6: substitution.load_eliminater 1.79% : 0.000013s : 4: substitution.minmaximum_grad 0.32% : 0.000002s : 2: substitution.opt_reshape 2.25% : 0.000017s : 24: substitution.remove_not_recompute_node 1.14% : 0.000008s : 4: substitution.replace_old_param 3.41% : 0.000025s : 4: substitution.reshape_eliminate 4.54% : 0.000034s : 8: substitution.tuple_list_convert_item_index_to_positive 1.85% : 0.000014s : 8: substitution.tuple_list_get_item_const_eliminator 2.76% : 0.000020s : 8: substitution.tuple_list_get_item_depend_reorder 7.34% : 0.000054s : 12: substitution.tuple_list_get_item_eliminator 2.75% : 0.000020s : 8: substitution.tuple_list_get_set_item_eliminator 3.47% : 0.000026s : 12: substitution.updatestate_pure_node_eliminater 3.27% : 0.000024s : 14: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.539687 2 99.80% : 2.534680s : 1: type_inference.infer 0.20% : 0.005007s : 1: type_inference.specialize ------[replace.] 0.000070 7 100.00% : 0.000070s : 7: replace.inline ------[match.] 0.000332 7 100.00% : 0.000332s : 7: match.inline ------[predicate.] 0.000671 4469 0.87% : 0.000006s : 45: predicate.accumulaten_eliminater 0.83% : 0.000006s : 17: predicate.ad_related_special_op_eliminate 0.68% : 0.000005s : 34: predicate.addn_check_dump 0.99% : 0.000007s : 45: predicate.addn_zero_filter 0.85% : 0.000006s : 45: predicate.adjust_all_reduce_mul_add 2.58% : 0.000017s : 79: predicate.arithmetic_simplify 0.92% : 0.000006s : 45: predicate.cast_eliminate 0.73% : 0.000005s : 34: predicate.check_bprop_eliminate 0.69% : 0.000005s : 34: predicate.compare_switch_simplify 0.22% : 0.000001s : 17: predicate.const_output_eliminate 0.71% : 0.000005s : 34: predicate.depend_value_elim 0.94% : 0.000006s : 45: predicate.dict_get_item_const_eliminator 0.99% : 0.000007s : 45: predicate.dict_get_item_eliminator 0.85% : 0.000006s : 45: predicate.dict_set_item_eliminator 0.87% : 0.000006s : 34: predicate.dumpgradient_eliminate 0.22% : 0.000001s : 17: predicate.elim_not_effective 0.47% : 0.000003s : 17: predicate.elim_shapecalc_of_broadcastargs 1.20% : 0.000008s : 62: predicate.environ_add_const_eliminate 1.16% : 0.000008s : 62: predicate.environ_get_add_eliminate 1.23% : 0.000008s : 62: predicate.environ_get_depend_swap 1.92% : 0.000013s : 96: predicate.environ_get_eliminate 1.15% : 0.000008s : 62: predicate.environ_get_set_eliminate 1.04% : 0.000007s : 52: predicate.exchange_switch_depend_value 1.66% : 0.000011s : 52: predicate.float_depend_g_call 0.65% : 0.000004s : 34: predicate.float_environ_get_switch 1.24% : 0.000008s : 51: predicate.float_tuple_getitem_switch 0.19% : 0.000001s : 17: predicate.fold_const_symbol 0.76% : 0.000005s : 34: predicate.get_grad_eliminate 0.21% : 0.000001s : 17: predicate.graph_param_transform 0.78% : 0.000005s : 34: predicate.incorporate_call 0.66% : 0.000004s : 34: predicate.incorporate_call_switch 5.85% : 0.000039s : 199: predicate.inline 1.02% : 0.000007s : 34: predicate.inline_without_move 0.37% : 0.000002s : 34: predicate.j_node_and_user_rematch 1.24% : 0.000008s : 36: predicate.less_batch_normalization 1.64% : 0.000011s : 79: predicate.list_to_tuple_eliminator_ 2.37% : 0.000016s : 124: predicate.load_eliminater 0.79% : 0.000005s : 17: predicate.loop_unroll_after_grad 1.41% : 0.000009s : 67: predicate.loop_unroll_before_grad 1.70% : 0.000011s : 79: predicate.make_slice_get_slice_eliminator 0.69% : 0.000005s : 34: predicate.merge_addn 0.66% : 0.000004s : 34: predicate.micro_step_allgather_replace 0.69% : 0.000005s : 34: predicate.mini_step_allgather_replace 0.85% : 0.000006s : 45: predicate.minmaximum_grad 0.91% : 0.000006s : 17: predicate.mutable_eliminate 0.44% : 0.000003s : 17: predicate.opt_reshape 0.48% : 0.000003s : 17: predicate.parallel_virtual_node 1.47% : 0.000010s : 52: predicate.partial_defer_inline 1.36% : 0.000009s : 62: predicate.partial_eliminate 0.99% : 0.000007s : 45: predicate.print_const_string_wrapper 0.76% : 0.000005s : 34: predicate.reduce_all_const_elim 1.22% : 0.000008s : 45: predicate.reduce_eliminate 2.41% : 0.000016s : 124: predicate.redundant_stop_gradient_eliminater 0.50% : 0.000003s : 34: predicate.remove_not_recompute_node 1.36% : 0.000009s : 79: predicate.replace_applicator 0.45% : 0.000003s : 34: predicate.replace_old_param 0.27% : 0.000002s : 17: predicate.reset_defer_inline 1.05% : 0.000007s : 45: predicate.reshape_eliminate 0.76% : 0.000005s : 34: predicate.row_tensor_add_zeros_like 0.47% : 0.000003s : 17: predicate.row_tensor_eliminate 1.06% : 0.000007s : 34: predicate.same_eliminate 0.52% : 0.000003s : 38: predicate.set_cell_output_no_recompute 0.85% : 0.000006s : 34: predicate.shard_identity_eliminate 0.82% : 0.000005s : 34: predicate.special_op_eliminate 0.83% : 0.000006s : 34: predicate.specialize_transform 1.03% : 0.000007s : 34: predicate.split_environ_get_set_with_tuple_value 0.82% : 0.000006s : 34: predicate.stack_unstack_eliminate 0.42% : 0.000003s : 17: predicate.switch_call_monad_eliminater 1.09% : 0.000007s : 52: predicate.switch_defer_inline 1.74% : 0.000012s : 86: predicate.switch_layer_defer_inline 3.83% : 0.000026s : 170: predicate.switch_simplify 0.87% : 0.000006s : 45: predicate.tile_eliminate 0.89% : 0.000006s : 45: predicate.transpose_eliminate 1.75% : 0.000012s : 79: predicate.tuple_list_convert_item_index_to_positive 1.85% : 0.000012s : 79: predicate.tuple_list_get_item_const_eliminator 1.68% : 0.000011s : 79: predicate.tuple_list_get_item_depend_reorder 3.08% : 0.000021s : 113: predicate.tuple_list_get_item_eliminator 1.64% : 0.000011s : 79: predicate.tuple_list_get_set_item_eliminator 2.53% : 0.000017s : 113: predicate.tuple_list_set_item_eliminator 1.63% : 0.000011s : 79: predicate.tuple_to_list_eliminator_ 2.36% : 0.000016s : 124: predicate.updatestate_pure_node_eliminater 3.46% : 0.000023s : 158: predicate.updatestate_useless_node_eliminater 0.43% : 0.000003s : 17: predicate.value_based_eliminate 0.76% : 0.000005s : 34: predicate.virtual_dataset_eliminate 0.74% : 0.000005s : 34: predicate.virtual_output_eliminate 0.39% : 0.000003s : 17: predicate.virtual_view_grad_eliminate 0.48% : 0.000003s : 17: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.159489 64 98.57% : 0.157203s : 55: func_graph_cloner_run.FuncGraphClonerGraph 1.43% : 0.002285s : 9: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.907558 192 0.00% : 0.000003s : 1: ForceFp32Comm 5.41% : 0.157301s : 1: add_attr 5.41% : 0.157282s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000149s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.05% : 0.001562s : 1: auto_monad 0.00% : 0.000066s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.02% : 0.000698s : 1: bootstrap 0.00% : 0.000041s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000038s : 1: control_data_broadcast_order 0.00% : 0.000033s : 1: convert_after_rewriter 0.00% : 0.000071s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000005s : 1: detach_backward 0.00% : 0.000032s : 1: environ_conv 0.00% : 0.000039s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000017s : 1: graph_reusing 0.00% : 0.000004s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000008s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000008s : 1: label_micro_interleaved_index 0.02% : 0.000532s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.03% : 0.000812s : 1: mutable_eliminate 0.00% : 0.000012s : 1: offloading_packed_experts 0.00% : 0.000035s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000039s : 1: opt.transform.mutable_eliminate 0.13% : 0.003857s : 78: opt.transform.opt_a 0.00% : 0.000129s : 1: opt.transform.opt_after_cconv 0.00% : 0.000072s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000481s : 28: opt.transform.opt_b 0.01% : 0.000202s : 2: opt.transform.opt_trans_graph 0.00% : 0.000120s : 4: opt.transform.symbol_engine_opt 0.48% : 0.014080s : 1: opt_a 0.01% : 0.000294s : 1: opt_after_cconv 0.02% : 0.000604s : 1: opt_after_jit_grad 0.02% : 0.000694s : 1: opt_b 0.63% : 0.018405s : 1: optimize 0.00% : 0.000044s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000093s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000012s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000027s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000006s : 1: overlap_recompute_comm 0.00% : 0.000007s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000081s : 1: pre_auto_parallel 0.00% : 0.000057s : 1: py_interpret_to_execute 0.00% : 0.000038s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000083s : 1: remove_dup_value 0.20% : 0.005674s : 1: renormalize.infer 0.09% : 0.002652s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000423s : 1: rewriter_after_opt_a 0.01% : 0.000173s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000020s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000184s : 1: symbol_engine_optimizer 0.01% : 0.000238s : 1: tuple_transform 87.35% : 2.539841s : 1: type_inference mki_log delete old file:/home/jenkins/ascend/log/atb/atb_65631_20260129171956.log . [hook] pytest_runtest_teardown:test_gated_ffn_split2_float16_310P_0[4096-1] tests/st/infer/ops/test_internal_ops/test_gated_ffn.py::test_gated_ffn_split2_float16_310P_0[4096-1],max_mem:156.0M [WARNING] ME(168808:281473662574384,MainProcess):2026-01-29-17:38:29.921.651 [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 = 2.4071, [21] [bootstrap]: 0.0007463 [type_inference]: 2.1872 [event_method]: 3.244e-05 [auto_monad]: 0.00038742 [graph_reusing]: 9.15999e-06 [inline]: 3.24001e-06 [add_attr]: 0.00653698, [1] [add_attr_with_inline]: 0.00651872, [1] [Cycle 1]: 0.00010381, [2] [tag_attr]: 4.458e-05 [meta_addattr_fg_expand]: 8.80001e-06 [parallel-infer-symbol]: 4.11001e-06 [pre_auto_parallel]: 6.116e-05 [insert-virtual-dataset]: 2.49001e-06 [parallel-infer-symbol-second]: 9.60019e-07 [dataset_repeat_opt]: 2.28998e-06 [pipeline_split]: 1.67999e-06 [optimize]: 0.210945, [53] [py_interpret_to_execute]: 4.967e-05 [rewriter_before_opt_a]: 0.00014898 [opt_a]: 0.206489, [2] [Cycle 1]: 0.204281, [45] [expand_dump_flag]: 3.88001e-06 [switch_simplify]: 5.933e-05 [loop_unroll]: 4.639e-05 [a_1]: 0.077755 [with_stream_mark]: 6.034e-05 [recompute_prepare]: 4.082e-05 [updatestate_depend_eliminate]: 8.801e-05 [updatestate_assign_eliminate]: 1.586e-05 [updatestate_loads_eliminate]: 1.336e-05 [parameter_eliminate]: 3.35e-06 [a_2]: 0.00033777 [accelerated_algorithm]: 5.237e-05 [shard]: 2.81999e-06 [meta_shard_fg_expand]: 1.087e-05 [shard_inline]: 2.03e-05 [merge_send_recv]: 1.839e-05 [auto_parallel]: 1.964e-05 [parallel]: 3.079e-05 [flash_sp]: 1.316e-05 [merge_comm]: 1.257e-05 [allreduce_fusion]: 1.056e-05 [matmul_add_comm_reduction]: 2.133e-05 [allreduce_slice_to_reducescatter]: 9.40025e-07 [virtual_shard_identity]: 2.354e-05 [virtual_dataset]: 2.036e-05 [get_grad_eliminate_]: 2.02e-05 [virtual_output]: 2.069e-05 [merge_forward]: 1.113e-05 [cell_reuse_recompute_pass]: 3.65003e-06 [offload_activation]: 2.121e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.943e-05 [merge_recompute_call_nodes]: 1.84e-06 [before_grad]: 3.441e-05 [set_forward_comm_id_for_comm_node_pass]: 1.247e-05 [meta_fg_expand]: 1.035e-05 [flash_sp_send_recv_attached]: 5.44998e-06 [receive_attached]: 2.06e-06 [after_resolve]: 2.685e-05 [a_after_grad]: 3.423e-05 [renormalize]: 0.0772113 [add_forward_monad_depend]: 1.301e-05 [auto_monad_grad]: 2.73998e-06 [auto_monad_eliminator]: 7.18e-05 [cse]: 0.00085445 [a_3]: 0.0462713 [Cycle 2]: 0.00218925, [45] [expand_dump_flag]: 5.56e-06 [switch_simplify]: 3.641e-05 [loop_unroll]: 2.214e-05 [a_1]: 0.00067324 [with_stream_mark]: 4.162e-05 [recompute_prepare]: 2.474e-05 [updatestate_depend_eliminate]: 1.388e-05 [updatestate_assign_eliminate]: 1.136e-05 [updatestate_loads_eliminate]: 1.324e-05 [parameter_eliminate]: 2.94001e-06 [a_2]: 0.00032222 [accelerated_algorithm]: 2.722e-05 [shard]: 2.36e-06 [meta_shard_fg_expand]: 1.033e-05 [shard_inline]: 2.11e-05 [merge_send_recv]: 2.036e-05 [auto_parallel]: 1.915e-05 [parallel]: 1.055e-05 [flash_sp]: 4.60999e-06 [merge_comm]: 1.169e-05 [allreduce_fusion]: 1.143e-05 [matmul_add_comm_reduction]: 2.118e-05 [allreduce_slice_to_reducescatter]: 1.19003e-06 [virtual_shard_identity]: 2.378e-05 [virtual_dataset]: 1.979e-05 [get_grad_eliminate_]: 1.849e-05 [virtual_output]: 1.913e-05 [merge_forward]: 1.366e-05 [cell_reuse_recompute_pass]: 3.33e-06 [offload_activation]: 2.107e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.695e-05 [merge_recompute_call_nodes]: 2.02001e-06 [before_grad]: 3.321e-05 [set_forward_comm_id_for_comm_node_pass]: 1.204e-05 [meta_fg_expand]: 1e-05 [flash_sp_send_recv_attached]: 1.93002e-06 [receive_attached]: 2.10002e-06 [after_resolve]: 2.637e-05 [a_after_grad]: 3.173e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 3.48e-06 [auto_monad_grad]: 3.02002e-06 [auto_monad_eliminator]: 7.122e-05 [cse]: 9.689e-05 [a_3]: 0.00013286 [py_interpret_to_execute_after_opt_a]: 3.908e-05 [slice_cell_reuse_recomputed_activation]: 3.13998e-06 [rewriter_after_opt_a]: 0.00039275 [convert_after_rewriter]: 2.743e-05 [order_py_execute_after_rewriter]: 1.271e-05 [mutable_eliminate]: 0.00081695 [opt_b]: 0.00071738, [1] [Cycle 1]: 0.00070823, [7] [b_1]: 0.00050388 [b_2]: 2.604e-05 [updatestate_depend_eliminate]: 1.867e-05 [updatestate_assign_eliminate]: 1.016e-05 [updatestate_loads_eliminate]: 1.372e-05 [renormalize]: 6.90023e-07 [cse]: 8.768e-05 [optimize_parallel_all_gather_comm]: 3.98e-05 [overlap_param_gather]: 2.14999e-06 [cconv]: 4.27e-05 [loop_unroll]: 0.00055862 [opt_after_cconv]: 0.00031735, [1] [Cycle 1]: 0.00030974, [7] [c_1]: 0.00012629 [parameter_eliminate]: 4.93001e-06 [updatestate_depend_eliminate]: 1.611e-05 [updatestate_assign_eliminate]: 1.039e-05 [updatestate_loads_eliminate]: 1.24e-05 [cse]: 7.487e-05 [renormalize]: 8.39995e-07 [remove_dup_value]: 9.157e-05 [tuple_transform]: 0.00024391, [1] [Cycle 1]: 0.00023665, [4] [d_1]: 0.00018845 [none_parameter_eliminate]: 2.70997e-06 [renormalize]: 2.19996e-07 [switch_simplify]: 2.168e-05 [partial_unused_args_eliminate]: 1.87999e-06 [add_recomputation]: 0.0001522 [cse_after_recomputation]: 7.017e-05, [1] [Cycle 1]: 6.462e-05, [1] [cse]: 5.708e-05 [environ_conv]: 1.929e-05 [swap_dp_allreduce_reducescatter]: 1.671e-05 [bias_add_comm_swap]: 2.88998e-06 [label_micro_interleaved_index]: 6.32001e-06 [label_fine_grained_interleaved_index]: 2.69999e-06 [merge_cast_opt]: 2.12001e-06 [slice_recompute_activation]: 2.11e-06 [micro_interleaved_order_control]: 2.79001e-06 [assign_add_opt]: 1.10999e-06 [ForceFp32Comm]: 9.20001e-07 [remove_cast_before_assign_add]: 1.07998e-06 [full_micro_interleaved_order_control]: 2.31e-06 [reorder_send_recv_between_fp_bp]: 3.01001e-06 [comm_op_add_attrs]: 1.32e-06 [add_comm_op_reuse_tag]: 9.70002e-07 [interleave_split_concat_branches]: 1.18001e-06 [interleave_parallel_branches]: 1.11002e-06 [overlap_opt_shard_in_pipeline]: 1.35999e-06 [overlap_opt_shard_grad_in_pipeline]: 1.80001e-06 [control_data_broadcast_order]: 5.138e-05 [grouped_pairwise_exchange_alltoall]: 1.58002e-06 [offloading_packed_experts]: 1.232e-05 [overlap_recompute_and_grad_model_parallel]: 1.255e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.29e-06 [overlap_recompute_allgather_and_fa_grad]: 1.40999e-06 [overlap_recompute_comm]: 2.32001e-06 [overlap_grad_ring_attention]: 1.216e-05 [overlap_grad_flash_sp]: 6.109e-05 [begin_end_overlap_inline]: 6.49976e-07 [split_matmul_comm_elemetwise]: 2.43e-06 [split_layernorm_comm]: 1.79e-06 [handle_group_info]: 1.30999e-06 [symbol_engine_optimizer]: 0.00020941, [1] [Cycle 1]: 0.00020224, [6] [build]: 1.859e-05 [elim_shapecalc]: 3.594e-05 [elim_not_effective]: 4.341e-05 [opt_reshape]: 2.856e-05 [fold_const_symbol]: 3.369e-05 [renormalize]: 6.50005e-07 [detach_backward]: 3.04001e-06 [pipeline_parallel_scheduler]: 1.78002e-06 [auto_monad_reorder]: 7.929e-05 [get_jit_bprop_graph]: 2.00002e-06 [rewriter_after_jit_bprop_graph]: 7.61001e-06 [opt_after_jit_grad]: 0.00073283 [validate]: 0.00012374 Sums bootstrap : 0.000746s : 0.03% type_inference : 2.187200s : 91.18% event_method : 0.000032s : 0.00% auto_monad : 0.000387s : 0.02% graph_reusing : 0.000009s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000045s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000009s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000061s : 0.00% insert-virtual-dataset : 0.000002s : 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 : 0.000050s : 0.00% optimize.rewriter_before_opt_a : 0.000149s : 0.01% optimize.opt_a.expand_dump_flag : 0.000009s : 0.00% optimize.opt_a.switch_simplify : 0.000096s : 0.00% optimize.opt_a.loop_unroll : 0.000069s : 0.00% optimize.opt_a.a_1 : 0.078428s : 3.27% optimize.opt_a.with_stream_mark : 0.000102s : 0.00% optimize.opt_a.recompute_prepare : 0.000066s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000102s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000027s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000027s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000660s : 0.03% optimize.opt_a.accelerated_algorithm : 0.000080s : 0.00% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000021s : 0.00% optimize.opt_a.shard_inline : 0.000041s : 0.00% optimize.opt_a.merge_send_recv : 0.000039s : 0.00% optimize.opt_a.auto_parallel : 0.000039s : 0.00% optimize.opt_a.parallel : 0.000041s : 0.00% optimize.opt_a.flash_sp : 0.000018s : 0.00% optimize.opt_a.merge_comm : 0.000024s : 0.00% optimize.opt_a.allreduce_fusion : 0.000022s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000043s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000047s : 0.00% optimize.opt_a.virtual_dataset : 0.000040s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000039s : 0.00% optimize.opt_a.virtual_output : 0.000040s : 0.00% optimize.opt_a.merge_forward : 0.000025s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% optimize.opt_a.offload_activation : 0.000042s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000076s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000068s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000025s : 0.00% optimize.opt_a.meta_fg_expand : 0.000020s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000004s : 0.00% optimize.opt_a.after_resolve : 0.000053s : 0.00% optimize.opt_a.a_after_grad : 0.000066s : 0.00% optimize.opt_a.renormalize : 0.077211s : 3.22% optimize.opt_a.add_forward_monad_depend : 0.000016s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000143s : 0.01% optimize.opt_a.cse : 0.000951s : 0.04% optimize.opt_a.a_3 : 0.046404s : 1.93% optimize.py_interpret_to_execute_after_opt_a : 0.000039s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000393s : 0.02% optimize.convert_after_rewriter : 0.000027s : 0.00% optimize.order_py_execute_after_rewriter : 0.000013s : 0.00% optimize.mutable_eliminate : 0.000817s : 0.03% optimize.opt_b.b_1 : 0.000504s : 0.02% optimize.opt_b.b_2 : 0.000026s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000019s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000014s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000088s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000040s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000043s : 0.00% optimize.loop_unroll : 0.000559s : 0.02% optimize.opt_after_cconv.c_1 : 0.000126s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000012s : 0.00% optimize.opt_after_cconv.cse : 0.000075s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000092s : 0.00% optimize.tuple_transform.d_1 : 0.000188s : 0.01% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000022s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000152s : 0.01% optimize.cse_after_recomputation.cse : 0.000057s : 0.00% optimize.environ_conv : 0.000019s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000017s : 0.00% optimize.bias_add_comm_swap : 0.000003s : 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 : 0.000001s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000051s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000012s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000013s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000012s : 0.00% optimize.overlap_grad_flash_sp : 0.000061s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000019s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000036s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000043s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000029s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000034s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000079s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000733s : 0.03% validate : 0.000124s : 0.01% Time group info: ------[substitution.] 0.000742 201 6.92% : 0.000051s : 5: substitution.arithmetic_simplify 1.39% : 0.000010s : 2: substitution.depend_value_elim 0.87% : 0.000006s : 12: substitution.elim_not_effective 1.78% : 0.000013s : 6: substitution.float_tuple_getitem_switch 0.64% : 0.000005s : 12: substitution.fold_const_symbol 2.23% : 0.000017s : 17: substitution.graph_param_transform 42.84% : 0.000318s : 7: substitution.inline 1.64% : 0.000012s : 24: substitution.j_node_and_user_rematch 3.76% : 0.000028s : 2: substitution.less_batch_normalization 0.82% : 0.000006s : 6: substitution.load_eliminater 1.12% : 0.000008s : 4: substitution.minmaximum_grad 0.30% : 0.000002s : 2: substitution.opt_reshape 2.30% : 0.000017s : 24: substitution.remove_not_recompute_node 1.09% : 0.000008s : 4: substitution.replace_old_param 5.57% : 0.000041s : 4: substitution.reshape_eliminate 4.68% : 0.000035s : 8: substitution.tuple_list_convert_item_index_to_positive 1.80% : 0.000013s : 8: substitution.tuple_list_get_item_const_eliminator 2.83% : 0.000021s : 8: substitution.tuple_list_get_item_depend_reorder 7.55% : 0.000056s : 12: substitution.tuple_list_get_item_eliminator 2.75% : 0.000020s : 8: substitution.tuple_list_get_set_item_eliminator 3.76% : 0.000028s : 12: substitution.updatestate_pure_node_eliminater 3.36% : 0.000025s : 14: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.187075 2 98.78% : 2.160389s : 1: type_inference.infer 1.22% : 0.026687s : 1: type_inference.specialize ------[replace.] 0.000063 7 100.00% : 0.000063s : 7: replace.inline ------[match.] 0.000312 7 100.00% : 0.000312s : 7: match.inline ------[predicate.] 0.000712 4469 0.91% : 0.000006s : 45: predicate.accumulaten_eliminater 0.81% : 0.000006s : 17: predicate.ad_related_special_op_eliminate 0.63% : 0.000004s : 34: predicate.addn_check_dump 0.92% : 0.000007s : 45: predicate.addn_zero_filter 0.82% : 0.000006s : 45: predicate.adjust_all_reduce_mul_add 2.30% : 0.000016s : 79: predicate.arithmetic_simplify 0.93% : 0.000007s : 45: predicate.cast_eliminate 1.57% : 0.000011s : 34: predicate.check_bprop_eliminate 0.63% : 0.000004s : 34: predicate.compare_switch_simplify 0.21% : 0.000001s : 17: predicate.const_output_eliminate 0.72% : 0.000005s : 34: predicate.depend_value_elim 0.96% : 0.000007s : 45: predicate.dict_get_item_const_eliminator 1.12% : 0.000008s : 45: predicate.dict_get_item_eliminator 0.86% : 0.000006s : 45: predicate.dict_set_item_eliminator 0.90% : 0.000006s : 34: predicate.dumpgradient_eliminate 0.26% : 0.000002s : 17: predicate.elim_not_effective 0.48% : 0.000003s : 17: predicate.elim_shapecalc_of_broadcastargs 1.22% : 0.000009s : 62: predicate.environ_add_const_eliminate 1.12% : 0.000008s : 62: predicate.environ_get_add_eliminate 1.10% : 0.000008s : 62: predicate.environ_get_depend_swap 1.85% : 0.000013s : 96: predicate.environ_get_eliminate 1.11% : 0.000008s : 62: predicate.environ_get_set_eliminate 1.06% : 0.000008s : 52: predicate.exchange_switch_depend_value 1.73% : 0.000012s : 52: predicate.float_depend_g_call 0.68% : 0.000005s : 34: predicate.float_environ_get_switch 1.03% : 0.000007s : 51: predicate.float_tuple_getitem_switch 0.18% : 0.000001s : 17: predicate.fold_const_symbol 0.75% : 0.000005s : 34: predicate.get_grad_eliminate 0.21% : 0.000002s : 17: predicate.graph_param_transform 0.66% : 0.000005s : 34: predicate.incorporate_call 0.60% : 0.000004s : 34: predicate.incorporate_call_switch 5.57% : 0.000040s : 199: predicate.inline 0.89% : 0.000006s : 34: predicate.inline_without_move 0.34% : 0.000002s : 34: predicate.j_node_and_user_rematch 1.05% : 0.000007s : 36: predicate.less_batch_normalization 1.74% : 0.000012s : 79: predicate.list_to_tuple_eliminator_ 2.29% : 0.000016s : 124: predicate.load_eliminater 0.85% : 0.000006s : 17: predicate.loop_unroll_after_grad 1.34% : 0.000010s : 67: predicate.loop_unroll_before_grad 1.78% : 0.000013s : 79: predicate.make_slice_get_slice_eliminator 0.66% : 0.000005s : 34: predicate.merge_addn 0.69% : 0.000005s : 34: predicate.micro_step_allgather_replace 0.68% : 0.000005s : 34: predicate.mini_step_allgather_replace 0.85% : 0.000006s : 45: predicate.minmaximum_grad 0.87% : 0.000006s : 17: predicate.mutable_eliminate 0.45% : 0.000003s : 17: predicate.opt_reshape 0.38% : 0.000003s : 17: predicate.parallel_virtual_node 2.00% : 0.000014s : 52: predicate.partial_defer_inline 1.39% : 0.000010s : 62: predicate.partial_eliminate 0.93% : 0.000007s : 45: predicate.print_const_string_wrapper 0.71% : 0.000005s : 34: predicate.reduce_all_const_elim 1.25% : 0.000009s : 45: predicate.reduce_eliminate 2.43% : 0.000017s : 124: predicate.redundant_stop_gradient_eliminater 0.36% : 0.000003s : 34: predicate.remove_not_recompute_node 1.26% : 0.000009s : 79: predicate.replace_applicator 0.41% : 0.000003s : 34: predicate.replace_old_param 0.28% : 0.000002s : 17: predicate.reset_defer_inline 1.17% : 0.000008s : 45: predicate.reshape_eliminate 0.73% : 0.000005s : 34: predicate.row_tensor_add_zeros_like 0.46% : 0.000003s : 17: predicate.row_tensor_eliminate 1.08% : 0.000008s : 34: predicate.same_eliminate 0.52% : 0.000004s : 38: predicate.set_cell_output_no_recompute 0.80% : 0.000006s : 34: predicate.shard_identity_eliminate 0.74% : 0.000005s : 34: predicate.special_op_eliminate 0.76% : 0.000005s : 34: predicate.specialize_transform 1.08% : 0.000008s : 34: predicate.split_environ_get_set_with_tuple_value 0.87% : 0.000006s : 34: predicate.stack_unstack_eliminate 0.38% : 0.000003s : 17: predicate.switch_call_monad_eliminater 1.13% : 0.000008s : 52: predicate.switch_defer_inline 2.49% : 0.000018s : 86: predicate.switch_layer_defer_inline 3.91% : 0.000028s : 170: predicate.switch_simplify 0.89% : 0.000006s : 45: predicate.tile_eliminate 0.87% : 0.000006s : 45: predicate.transpose_eliminate 1.70% : 0.000012s : 79: predicate.tuple_list_convert_item_index_to_positive 1.80% : 0.000013s : 79: predicate.tuple_list_get_item_const_eliminator 1.90% : 0.000014s : 79: predicate.tuple_list_get_item_depend_reorder 3.05% : 0.000022s : 113: predicate.tuple_list_get_item_eliminator 1.69% : 0.000012s : 79: predicate.tuple_list_get_set_item_eliminator 2.55% : 0.000018s : 113: predicate.tuple_list_set_item_eliminator 1.62% : 0.000012s : 79: predicate.tuple_to_list_eliminator_ 2.34% : 0.000017s : 124: predicate.updatestate_pure_node_eliminater 3.09% : 0.000022s : 158: predicate.updatestate_useless_node_eliminater 0.39% : 0.000003s : 17: predicate.value_based_eliminate 0.70% : 0.000005s : 34: predicate.virtual_dataset_eliminate 0.70% : 0.000005s : 34: predicate.virtual_output_eliminate 0.35% : 0.000003s : 17: predicate.virtual_view_grad_eliminate 0.43% : 0.000003s : 17: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.025019 64 35.34% : 0.008841s : 55: func_graph_cloner_run.FuncGraphClonerGraph 64.66% : 0.016177s : 9: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.828752 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.23% : 0.006544s : 1: add_attr 0.23% : 0.006524s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000159s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.01% : 0.000400s : 1: auto_monad 0.00% : 0.000087s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000006s : 1: bias_add_comm_swap 0.03% : 0.000786s : 1: bootstrap 0.00% : 0.000047s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000055s : 1: control_data_broadcast_order 0.00% : 0.000032s : 1: convert_after_rewriter 0.00% : 0.000074s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000007s : 1: detach_backward 0.00% : 0.000024s : 1: environ_conv 0.00% : 0.000041s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000008s : 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% : 0.000009s : 1: label_micro_interleaved_index 0.02% : 0.000570s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.03% : 0.000828s : 1: mutable_eliminate 0.00% : 0.000016s : 1: offloading_packed_experts 0.00% : 0.000036s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000040s : 1: opt.transform.mutable_eliminate 4.46% : 0.126116s : 78: opt.transform.opt_a 0.00% : 0.000124s : 1: opt.transform.opt_after_cconv 0.00% : 0.000081s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000493s : 28: opt.transform.opt_b 0.01% : 0.000207s : 2: opt.transform.opt_trans_graph 0.00% : 0.000135s : 4: opt.transform.symbol_engine_opt 7.30% : 0.206494s : 1: opt_a 0.01% : 0.000322s : 1: opt_after_cconv 0.03% : 0.000748s : 1: opt_after_jit_grad 0.03% : 0.000721s : 1: opt_b 7.46% : 0.210951s : 1: optimize 0.00% : 0.000044s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000068s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000016s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000004s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000016s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000004s : 1: pipeline_split 0.00% : 0.000066s : 1: pre_auto_parallel 0.00% : 0.000056s : 1: py_interpret_to_execute 0.00% : 0.000043s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000097s : 1: remove_dup_value 2.14% : 0.060555s : 1: renormalize.infer 0.59% : 0.016629s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000403s : 1: rewriter_after_opt_a 0.01% : 0.000154s : 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% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000020s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000213s : 1: symbol_engine_optimizer 0.01% : 0.000247s : 1: tuple_transform 77.32% : 2.187232s : 1: type_inference . [hook] pytest_runtest_teardown:test_gated_ffn_split2_float16_310P_0[4096-4096] tests/st/infer/ops/test_internal_ops/test_gated_ffn.py::test_gated_ffn_split2_float16_310P_0[4096-4096],max_mem:300.0M =============================== 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 188.22s (0:03:08) ==================