==================================================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_008/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 1 item test_gated_ffn.py [WARNING] ME(156495:281472869130032,MainProcess):2026-01-29-17:36:55.852.436 [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. mki_log delete old file:/home/jenkins/ascend/log/atb/atb_56384_20260129171803.log TotalTime = 59.9399, [24] [bootstrap]: 0.00235539 [type_inference]: 0.908 [event_method]: 3.683e-05 [auto_monad]: 0.00421826 [graph_reusing]: 1.047e-05 [inline]: 6.88998e-06 [add_attr]: 0.0179051, [1] [add_attr_with_inline]: 0.0178477, [1] [Cycle 1]: 0.00028364, [2] [tag_attr]: 6.502e-05 [meta_addattr_fg_expand]: 9.64e-06 [parallel-infer-symbol]: 5.27999e-06 [pre_auto_parallel]: 0.00016446 [insert-virtual-dataset]: 4.93001e-06 [parallel-infer-symbol-second]: 1.22999e-06 [dataset_repeat_opt]: 2.04e-06 [pipeline_split]: 1.86e-06 [optimize]: 0.0383026, [53] [py_interpret_to_execute]: 7.185e-05 [rewriter_before_opt_a]: 0.00025459 [opt_a]: 0.0299226, [2] [Cycle 1]: 0.0271182, [45] [expand_dump_flag]: 4.08999e-06 [switch_simplify]: 6.566e-05 [loop_unroll]: 4.834e-05 [a_1]: 0.0017562 [with_stream_mark]: 4.262e-05 [recompute_prepare]: 0.00019491 [updatestate_depend_eliminate]: 0.0001311 [updatestate_assign_eliminate]: 3.105e-05 [updatestate_loads_eliminate]: 2.016e-05 [parameter_eliminate]: 5.63002e-06 [a_2]: 0.00047774 [accelerated_algorithm]: 6.138e-05 [shard]: 4.03001e-06 [meta_shard_fg_expand]: 1.216e-05 [shard_inline]: 3.016e-05 [merge_send_recv]: 2.234e-05 [auto_parallel]: 2.3e-05 [parallel]: 0.00020607 [flash_sp]: 1.874e-05 [merge_comm]: 1.644e-05 [allreduce_fusion]: 1.417e-05 [matmul_add_comm_reduction]: 2.763e-05 [allreduce_slice_to_reducescatter]: 9.80013e-07 [virtual_shard_identity]: 3.974e-05 [virtual_dataset]: 2.91e-05 [get_grad_eliminate_]: 3.002e-05 [virtual_output]: 2.962e-05 [merge_forward]: 1.63e-05 [cell_reuse_recompute_pass]: 2.79001e-06 [offload_activation]: 3.047e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.526e-05 [merge_recompute_call_nodes]: 1.81998e-06 [before_grad]: 4.938e-05 [set_forward_comm_id_for_comm_node_pass]: 1.587e-05 [meta_fg_expand]: 1.461e-05 [flash_sp_send_recv_attached]: 5.21998e-06 [receive_attached]: 4.397e-05 [after_resolve]: 4.092e-05 [a_after_grad]: 4.552e-05 [renormalize]: 0.0220419 [add_forward_monad_depend]: 8.362e-05 [auto_monad_grad]: 4.19002e-06 [auto_monad_eliminator]: 0.00018738 [cse]: 0.00043443 [a_3]: 0.00024385 [Cycle 2]: 0.00278657, [45] [expand_dump_flag]: 3.8e-06 [switch_simplify]: 3.237e-05 [loop_unroll]: 3.39e-05 [a_1]: 0.00088233 [with_stream_mark]: 4.343e-05 [recompute_prepare]: 3.321e-05 [updatestate_depend_eliminate]: 2.135e-05 [updatestate_assign_eliminate]: 1.564e-05 [updatestate_loads_eliminate]: 2.435e-05 [parameter_eliminate]: 2.89999e-06 [a_2]: 0.00042214 [accelerated_algorithm]: 4.13e-05 [shard]: 2.55002e-06 [meta_shard_fg_expand]: 1.229e-05 [shard_inline]: 2.666e-05 [merge_send_recv]: 2.53e-05 [auto_parallel]: 2.142e-05 [parallel]: 1.474e-05 [flash_sp]: 7.05e-06 [merge_comm]: 1.609e-05 [allreduce_fusion]: 1.404e-05 [matmul_add_comm_reduction]: 2.884e-05 [allreduce_slice_to_reducescatter]: 8.2e-07 [virtual_shard_identity]: 3.581e-05 [virtual_dataset]: 2.707e-05 [get_grad_eliminate_]: 2.837e-05 [virtual_output]: 3.021e-05 [merge_forward]: 1.427e-05 [cell_reuse_recompute_pass]: 4.65999e-06 [offload_activation]: 2.766e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.413e-05 [merge_recompute_call_nodes]: 1.78997e-06 [before_grad]: 4.861e-05 [set_forward_comm_id_for_comm_node_pass]: 1.442e-05 [meta_fg_expand]: 1.198e-05 [flash_sp_send_recv_attached]: 3.03998e-06 [receive_attached]: 3.65e-06 [after_resolve]: 3.653e-05 [a_after_grad]: 4.098e-05 [renormalize]: 1.09983e-07 [add_forward_monad_depend]: 4.27e-06 [auto_monad_grad]: 3.33998e-06 [auto_monad_eliminator]: 8.732e-05 [cse]: 0.00011944 [a_3]: 0.00018054 [py_interpret_to_execute_after_opt_a]: 7.368e-05 [slice_cell_reuse_recomputed_activation]: 2.57001e-06 [rewriter_after_opt_a]: 0.00191365 [convert_after_rewriter]: 4.208e-05 [order_py_execute_after_rewriter]: 1.762e-05 [mutable_eliminate]: 0.00133465 [opt_b]: 0.00112657, [1] [Cycle 1]: 0.00111676, [7] [b_1]: 0.00069436 [b_2]: 3.232e-05 [updatestate_depend_eliminate]: 2.494e-05 [updatestate_assign_eliminate]: 1.429e-05 [updatestate_loads_eliminate]: 2.089e-05 [renormalize]: 2.12999e-06 [cse]: 0.00020488 [optimize_parallel_all_gather_comm]: 7.423e-05 [overlap_param_gather]: 4.44998e-06 [cconv]: 5.185e-05 [loop_unroll]: 0.00097585 [opt_after_cconv]: 0.00046825, [1] [Cycle 1]: 0.00045721, [7] [c_1]: 0.00018677 [parameter_eliminate]: 6.44001e-06 [updatestate_depend_eliminate]: 2.348e-05 [updatestate_assign_eliminate]: 1.239e-05 [updatestate_loads_eliminate]: 1.706e-05 [cse]: 0.00016473 [renormalize]: 1.87001e-06 [remove_dup_value]: 0.00015817 [tuple_transform]: 0.00032684, [1] [Cycle 1]: 0.00031983, [4] [d_1]: 0.00025808 [none_parameter_eliminate]: 2.94999e-06 [renormalize]: 3.59985e-07 [switch_simplify]: 3.353e-05 [partial_unused_args_eliminate]: 2.15002e-06 [add_recomputation]: 0.00021689 [cse_after_recomputation]: 0.00010386, [1] [Cycle 1]: 9.478e-05, [1] [cse]: 8.641e-05 [environ_conv]: 8.76e-05 [swap_dp_allreduce_reducescatter]: 2.785e-05 [bias_add_comm_swap]: 8.08001e-06 [label_micro_interleaved_index]: 1.525e-05 [label_fine_grained_interleaved_index]: 2.56998e-06 [merge_cast_opt]: 3.24001e-06 [slice_recompute_activation]: 2.09e-06 [micro_interleaved_order_control]: 3.56999e-06 [assign_add_opt]: 1.40001e-06 [ForceFp32Comm]: 8.09989e-07 [remove_cast_before_assign_add]: 1.03001e-06 [full_micro_interleaved_order_control]: 2.76e-06 [reorder_send_recv_between_fp_bp]: 2.54001e-06 [comm_op_add_attrs]: 1.01002e-06 [add_comm_op_reuse_tag]: 9.70002e-07 [interleave_split_concat_branches]: 1.12e-06 [interleave_parallel_branches]: 1.02e-06 [overlap_opt_shard_in_pipeline]: 7.809e-05 [overlap_opt_shard_grad_in_pipeline]: 1.66e-06 [control_data_broadcast_order]: 4.618e-05 [grouped_pairwise_exchange_alltoall]: 1.55999e-06 [offloading_packed_experts]: 1.418e-05 [overlap_recompute_and_grad_model_parallel]: 1.194e-05 [overlap_grad_matmul_and_grad_allreduce]: 1.22999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.36002e-06 [overlap_recompute_comm]: 2.36e-06 [overlap_grad_ring_attention]: 1.19e-05 [overlap_grad_flash_sp]: 0.00017324 [begin_end_overlap_inline]: 1.62999e-06 [split_matmul_comm_elemetwise]: 2.56e-06 [split_layernorm_comm]: 1.66e-06 [handle_group_info]: 9.89996e-07 [symbol_engine_optimizer]: 0.00024701, [1] [Cycle 1]: 0.00023942, [6] [build]: 2.308e-05 [elim_shapecalc]: 3.92e-05 [elim_not_effective]: 5.814e-05 [opt_reshape]: 3.736e-05 [fold_const_symbol]: 4.185e-05 [renormalize]: 1.8999e-07 [detach_backward]: 2.37001e-06 [pipeline_parallel_scheduler]: 2.04999e-06 [auto_monad_reorder]: 9.487e-05 [get_jit_bprop_graph]: 2.57001e-06 [rewriter_after_jit_bprop_graph]: 9.04998e-06 [opt_after_jit_grad]: 0.00129629 [validate]: 0.00027628 [backend_pass]: 1.47999e-06 [task_emit]: 58.9665 [execute]: 1.312e-05 Sums bootstrap : 0.002355s : 0.00% type_inference : 0.908000s : 1.52% event_method : 0.000037s : 0.00% auto_monad : 0.004218s : 0.01% graph_reusing : 0.000010s : 0.00% inline : 0.000007s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000065s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000010s : 0.00% parallel-infer-symbol : 0.000005s : 0.00% pre_auto_parallel : 0.000164s : 0.00% insert-virtual-dataset : 0.000005s : 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 : 0.000072s : 0.00% optimize.rewriter_before_opt_a : 0.000255s : 0.00% optimize.opt_a.expand_dump_flag : 0.000008s : 0.00% optimize.opt_a.switch_simplify : 0.000098s : 0.00% optimize.opt_a.loop_unroll : 0.000082s : 0.00% optimize.opt_a.a_1 : 0.002639s : 0.00% optimize.opt_a.with_stream_mark : 0.000086s : 0.00% optimize.opt_a.recompute_prepare : 0.000228s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000152s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000047s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000045s : 0.00% optimize.opt_a.parameter_eliminate : 0.000009s : 0.00% optimize.opt_a.a_2 : 0.000900s : 0.00% optimize.opt_a.accelerated_algorithm : 0.000103s : 0.00% optimize.opt_a.shard : 0.000007s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000024s : 0.00% optimize.opt_a.shard_inline : 0.000057s : 0.00% optimize.opt_a.merge_send_recv : 0.000048s : 0.00% optimize.opt_a.auto_parallel : 0.000044s : 0.00% optimize.opt_a.parallel : 0.000221s : 0.00% optimize.opt_a.flash_sp : 0.000026s : 0.00% optimize.opt_a.merge_comm : 0.000033s : 0.00% optimize.opt_a.allreduce_fusion : 0.000028s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000056s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000076s : 0.00% optimize.opt_a.virtual_dataset : 0.000056s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000058s : 0.00% optimize.opt_a.virtual_output : 0.000060s : 0.00% optimize.opt_a.merge_forward : 0.000031s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% optimize.opt_a.offload_activation : 0.000058s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000109s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000098s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000030s : 0.00% optimize.opt_a.meta_fg_expand : 0.000027s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000048s : 0.00% optimize.opt_a.after_resolve : 0.000077s : 0.00% optimize.opt_a.a_after_grad : 0.000087s : 0.00% optimize.opt_a.renormalize : 0.022042s : 0.04% optimize.opt_a.add_forward_monad_depend : 0.000088s : 0.00% optimize.opt_a.auto_monad_grad : 0.000008s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000275s : 0.00% optimize.opt_a.cse : 0.000554s : 0.00% optimize.opt_a.a_3 : 0.000424s : 0.00% optimize.py_interpret_to_execute_after_opt_a : 0.000074s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.001914s : 0.00% optimize.convert_after_rewriter : 0.000042s : 0.00% optimize.order_py_execute_after_rewriter : 0.000018s : 0.00% optimize.mutable_eliminate : 0.001335s : 0.00% optimize.opt_b.b_1 : 0.000694s : 0.00% optimize.opt_b.b_2 : 0.000032s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000025s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000021s : 0.00% optimize.opt_b.renormalize : 0.000002s : 0.00% optimize.opt_b.cse : 0.000205s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000074s : 0.00% optimize.overlap_param_gather : 0.000004s : 0.00% optimize.cconv : 0.000052s : 0.00% optimize.loop_unroll : 0.000976s : 0.00% optimize.opt_after_cconv.c_1 : 0.000187s : 0.00% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000023s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000012s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.cse : 0.000165s : 0.00% optimize.opt_after_cconv.renormalize : 0.000002s : 0.00% optimize.remove_dup_value : 0.000158s : 0.00% optimize.tuple_transform.d_1 : 0.000258s : 0.00% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000034s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000217s : 0.00% optimize.cse_after_recomputation.cse : 0.000086s : 0.00% optimize.environ_conv : 0.000088s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000028s : 0.00% optimize.bias_add_comm_swap : 0.000008s : 0.00% optimize.label_micro_interleaved_index : 0.000015s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000003s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000004s : 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 : 0.000003s : 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 : 0.000078s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000046s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000014s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000012s : 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 : 0.000173s : 0.00% optimize.begin_end_overlap_inline : 0.000002s : 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 : 0.000023s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000039s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000058s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000037s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000042s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000095s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.001296s : 0.00% validate : 0.000276s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 58.966509s : 98.41% execute : 0.000013s : 0.00% Time group info: ------[substitution.] 0.001027 231 6.01% : 0.000062s : 5: substitution.arithmetic_simplify 1.64% : 0.000017s : 2: substitution.depend_value_elim 0.59% : 0.000006s : 15: substitution.elim_not_effective 1.76% : 0.000018s : 6: substitution.float_tuple_getitem_switch 0.53% : 0.000005s : 15: substitution.fold_const_symbol 1.82% : 0.000019s : 22: substitution.graph_param_transform 41.63% : 0.000428s : 6: substitution.inline 1.61% : 0.000017s : 30: substitution.j_node_and_user_rematch 2.86% : 0.000029s : 2: substitution.less_batch_normalization 1.48% : 0.000015s : 18: substitution.load_eliminater 1.00% : 0.000010s : 4: substitution.minmaximum_grad 0.31% : 0.000003s : 2: substitution.opt_reshape 2.62% : 0.000027s : 30: substitution.remove_not_recompute_node 1.18% : 0.000012s : 8: substitution.replace_old_param 3.03% : 0.000031s : 4: substitution.reshape_eliminate 4.31% : 0.000044s : 8: substitution.tuple_list_convert_item_index_to_positive 1.44% : 0.000015s : 8: substitution.tuple_list_get_item_const_eliminator 2.81% : 0.000029s : 8: substitution.tuple_list_get_item_depend_reorder 6.19% : 0.000064s : 12: substitution.tuple_list_get_item_eliminator 2.16% : 0.000022s : 8: substitution.tuple_list_get_set_item_eliminator 1.56% : 0.000016s : 8: substitution.updatestate_pure_node_eliminater 13.46% : 0.000138s : 10: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.907672 2 98.75% : 0.896319s : 1: type_inference.infer 1.25% : 0.011353s : 1: type_inference.specialize ------[replace.] 0.000073 6 100.00% : 0.000073s : 6: replace.inline ------[match.] 0.000423 6 100.00% : 0.000423s : 6: match.inline ------[predicate.] 0.000850 5392 0.79% : 0.000007s : 51: predicate.accumulaten_eliminater 0.99% : 0.000008s : 22: predicate.ad_related_special_op_eliminate 0.71% : 0.000006s : 44: predicate.addn_check_dump 0.80% : 0.000007s : 51: predicate.addn_zero_filter 0.71% : 0.000006s : 51: predicate.adjust_all_reduce_mul_add 2.30% : 0.000020s : 95: predicate.arithmetic_simplify 0.78% : 0.000007s : 51: predicate.cast_eliminate 0.85% : 0.000007s : 44: predicate.check_bprop_eliminate 1.00% : 0.000009s : 44: predicate.compare_switch_simplify 0.21% : 0.000002s : 22: predicate.const_output_eliminate 0.81% : 0.000007s : 44: predicate.depend_value_elim 0.85% : 0.000007s : 51: predicate.dict_get_item_const_eliminator 1.07% : 0.000009s : 51: predicate.dict_get_item_eliminator 0.79% : 0.000007s : 51: predicate.dict_set_item_eliminator 0.86% : 0.000007s : 44: predicate.dumpgradient_eliminate 0.20% : 0.000002s : 22: predicate.elim_not_effective 0.51% : 0.000004s : 22: predicate.elim_shapecalc_of_broadcastargs 1.11% : 0.000009s : 73: predicate.environ_add_const_eliminate 1.11% : 0.000009s : 73: predicate.environ_get_add_eliminate 1.22% : 0.000010s : 73: predicate.environ_get_depend_swap 1.85% : 0.000016s : 117: predicate.environ_get_eliminate 1.10% : 0.000009s : 73: predicate.environ_get_set_eliminate 0.93% : 0.000008s : 57: predicate.exchange_switch_depend_value 1.25% : 0.000011s : 57: predicate.float_depend_g_call 0.70% : 0.000006s : 44: predicate.float_environ_get_switch 1.11% : 0.000009s : 66: predicate.float_tuple_getitem_switch 0.20% : 0.000002s : 22: predicate.fold_const_symbol 1.04% : 0.000009s : 44: predicate.get_grad_eliminate 0.24% : 0.000002s : 22: predicate.graph_param_transform 0.69% : 0.000006s : 44: predicate.incorporate_call 0.65% : 0.000006s : 44: predicate.incorporate_call_switch 5.25% : 0.000045s : 240: predicate.inline 0.99% : 0.000008s : 44: predicate.inline_without_move 0.39% : 0.000003s : 44: predicate.j_node_and_user_rematch 1.48% : 0.000013s : 44: predicate.less_batch_normalization 2.10% : 0.000018s : 95: predicate.list_to_tuple_eliminator_ 2.16% : 0.000018s : 146: predicate.load_eliminater 0.90% : 0.000008s : 22: predicate.loop_unroll_after_grad 1.55% : 0.000013s : 71: predicate.loop_unroll_before_grad 1.54% : 0.000013s : 95: predicate.make_slice_get_slice_eliminator 0.71% : 0.000006s : 44: predicate.merge_addn 0.90% : 0.000008s : 44: predicate.micro_step_allgather_replace 0.76% : 0.000006s : 44: predicate.mini_step_allgather_replace 0.73% : 0.000006s : 51: predicate.minmaximum_grad 1.21% : 0.000010s : 22: predicate.mutable_eliminate 0.73% : 0.000006s : 22: predicate.opt_reshape 0.66% : 0.000006s : 22: predicate.parallel_virtual_node 1.36% : 0.000012s : 57: predicate.partial_defer_inline 1.22% : 0.000010s : 73: predicate.partial_eliminate 0.75% : 0.000006s : 51: predicate.print_const_string_wrapper 0.71% : 0.000006s : 44: predicate.reduce_all_const_elim 1.15% : 0.000010s : 51: predicate.reduce_eliminate 2.29% : 0.000019s : 146: predicate.redundant_stop_gradient_eliminater 0.39% : 0.000003s : 44: predicate.remove_not_recompute_node 1.27% : 0.000011s : 95: predicate.replace_applicator 0.45% : 0.000004s : 44: predicate.replace_old_param 0.27% : 0.000002s : 22: predicate.reset_defer_inline 0.99% : 0.000008s : 51: predicate.reshape_eliminate 1.00% : 0.000009s : 44: predicate.row_tensor_add_zeros_like 0.68% : 0.000006s : 22: predicate.row_tensor_eliminate 1.04% : 0.000009s : 44: predicate.same_eliminate 0.52% : 0.000004s : 46: predicate.set_cell_output_no_recompute 1.17% : 0.000010s : 44: predicate.shard_identity_eliminate 0.79% : 0.000007s : 44: predicate.special_op_eliminate 0.88% : 0.000007s : 44: predicate.specialize_transform 1.13% : 0.000010s : 44: predicate.split_environ_get_set_with_tuple_value 0.87% : 0.000007s : 44: predicate.stack_unstack_eliminate 0.38% : 0.000003s : 22: predicate.switch_call_monad_eliminater 1.18% : 0.000010s : 57: predicate.switch_defer_inline 1.69% : 0.000014s : 101: predicate.switch_layer_defer_inline 3.62% : 0.000031s : 194: predicate.switch_simplify 0.76% : 0.000006s : 51: predicate.tile_eliminate 0.78% : 0.000007s : 51: predicate.transpose_eliminate 2.17% : 0.000018s : 95: predicate.tuple_list_convert_item_index_to_positive 1.90% : 0.000016s : 95: predicate.tuple_list_get_item_const_eliminator 1.78% : 0.000015s : 95: predicate.tuple_list_get_item_depend_reorder 2.93% : 0.000025s : 139: predicate.tuple_list_get_item_eliminator 1.72% : 0.000015s : 95: predicate.tuple_list_get_set_item_eliminator 2.84% : 0.000024s : 139: predicate.tuple_list_set_item_eliminator 1.56% : 0.000013s : 95: predicate.tuple_to_list_eliminator_ 2.13% : 0.000018s : 146: predicate.updatestate_pure_node_eliminater 3.01% : 0.000026s : 190: predicate.updatestate_useless_node_eliminater 0.53% : 0.000005s : 22: predicate.value_based_eliminate 0.82% : 0.000007s : 44: predicate.virtual_dataset_eliminate 0.88% : 0.000007s : 44: predicate.virtual_output_eliminate 0.44% : 0.000004s : 22: predicate.virtual_view_grad_eliminate 0.44% : 0.000004s : 22: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.027555 63 71.95% : 0.019826s : 55: func_graph_cloner_run.FuncGraphClonerGraph 28.05% : 0.007730s : 8: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 60.024294 196 0.00% : 0.000004s : 1: ForceFp32Comm 0.03% : 0.017917s : 1: add_attr 0.03% : 0.017855s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000222s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.01% : 0.004271s : 1: auto_monad 0.00% : 0.000103s : 1: auto_monad_reorder 0.00% : 0.000010s : 1: backend_pass 0.00% : 0.000005s : 1: begin_end_overlap_inline 0.00% : 0.000011s : 1: bias_add_comm_swap 0.00% : 0.002421s : 1: bootstrap 0.00% : 0.000056s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000050s : 1: control_data_broadcast_order 0.00% : 0.000048s : 1: convert_after_rewriter 0.00% : 0.000107s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000094s : 1: environ_conv 0.00% : 0.000049s : 1: event_method 0.00% : 0.000097s : 1: execute 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000018s : 1: graph_reusing 0.00% : 0.000008s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000011s : 1: inline 0.00% : 0.000013s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000007s : 1: label_fine_grained_interleaved_index 0.00% : 0.000018s : 1: label_micro_interleaved_index 0.00% : 0.000989s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.00% : 0.001347s : 1: mutable_eliminate 0.00% : 0.000017s : 1: offloading_packed_experts 0.00% : 0.000053s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000059s : 1: opt.transform.mutable_eliminate 0.01% : 0.004969s : 78: opt.transform.opt_a 0.00% : 0.000185s : 1: opt.transform.opt_after_cconv 0.00% : 0.000108s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000681s : 28: opt.transform.opt_b 0.00% : 0.000284s : 2: opt.transform.opt_trans_graph 0.00% : 0.000171s : 4: opt.transform.symbol_engine_opt 0.05% : 0.029928s : 1: opt_a 0.00% : 0.000473s : 1: opt_after_cconv 0.00% : 0.001312s : 1: opt_after_jit_grad 0.00% : 0.001133s : 1: opt_b 0.06% : 0.038312s : 1: optimize 0.00% : 0.000079s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000021s : 1: order_py_execute_after_rewriter 0.00% : 0.000178s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000015s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000082s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000015s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000011s : 1: parallel-infer-symbol 0.00% : 0.000005s : 1: parallel-infer-symbol-second 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000009s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000170s : 1: pre_auto_parallel 0.00% : 0.000078s : 1: py_interpret_to_execute 0.00% : 0.000080s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000164s : 1: remove_dup_value 0.02% : 0.013601s : 1: renormalize.infer 0.01% : 0.008413s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.001934s : 1: rewriter_after_opt_a 0.00% : 0.000261s : 1: rewriter_before_opt_a 0.00% : 0.000005s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000006s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000032s : 1: swap_dp_allreduce_reducescatter 0.00% : 0.000250s : 1: symbol_engine_optimizer 98.24% : 58.966579s : 1: task_emit 0.00% : 0.000330s : 1: tuple_transform 1.51% : 0.908064s : 1: type_inference 0.00% : 0.000368s : 1: validate . [hook] pytest_runtest_teardown:test_gated_ffn_quant2_0[4096-1] tests/st/infer/ops/test_internal_ops/test_gated_ffn.py::test_gated_ffn_quant2_0[4096-1],max_mem:142.0M =============================== 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 ================== 1 passed, 25 warnings in 81.15s (0:01:21) ===================