==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/infer/ops/test_internal_ops, configfile: ../../../../../../../../sault/virtual_test/virtualenv_001/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 3 items test_matmul_biasadd_split.py [WARNING] ME(160590:281473768550192,MainProcess):2026-01-29-17:37:27.372.386 [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 = 3.14302, [21] [bootstrap]: 0.00075388 [type_inference]: 2.97224 [event_method]: 2.017e-05 [auto_monad]: 0.00165008 [graph_reusing]: 8.07998e-06 [inline]: 3.13e-06 [add_attr]: 0.00848696, [1] [add_attr_with_inline]: 0.00846446, [1] [Cycle 1]: 0.00011465, [2] [tag_attr]: 2.732e-05 [meta_addattr_fg_expand]: 5.30001e-06 [parallel-infer-symbol]: 3.45003e-06 [pre_auto_parallel]: 5.722e-05 [insert-virtual-dataset]: 2.84001e-06 [parallel-infer-symbol-second]: 1.02e-06 [dataset_repeat_opt]: 2.19001e-06 [pipeline_split]: 2.02999e-06 [optimize]: 0.158615, [53] [py_interpret_to_execute]: 3.556e-05 [rewriter_before_opt_a]: 0.00010508 [opt_a]: 0.154268, [2] [Cycle 1]: 0.151654, [45] [expand_dump_flag]: 2.63e-06 [switch_simplify]: 4.325e-05 [loop_unroll]: 2.454e-05 [a_1]: 0.00088252 [with_stream_mark]: 3.813e-05 [recompute_prepare]: 2.679e-05 [updatestate_depend_eliminate]: 1.234e-05 [updatestate_assign_eliminate]: 1.08e-05 [updatestate_loads_eliminate]: 9.059e-05 [parameter_eliminate]: 3.03e-06 [a_2]: 0.00032607 [accelerated_algorithm]: 5.782e-05 [shard]: 2.64001e-06 [meta_shard_fg_expand]: 5.19998e-06 [shard_inline]: 2.08e-05 [merge_send_recv]: 1.741e-05 [auto_parallel]: 1.832e-05 [parallel]: 5.832e-05 [flash_sp]: 2.798e-05 [merge_comm]: 1.153e-05 [allreduce_fusion]: 9.85002e-06 [matmul_add_comm_reduction]: 2.051e-05 [allreduce_slice_to_reducescatter]: 9.00007e-07 [virtual_shard_identity]: 2.547e-05 [virtual_dataset]: 1.997e-05 [get_grad_eliminate_]: 2.05e-05 [virtual_output]: 2.064e-05 [merge_forward]: 1.066e-05 [cell_reuse_recompute_pass]: 2.98998e-06 [offload_activation]: 1.868e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.803e-05 [merge_recompute_call_nodes]: 2.64999e-06 [before_grad]: 3.473e-05 [set_forward_comm_id_for_comm_node_pass]: 1.212e-05 [meta_fg_expand]: 7.66001e-06 [flash_sp_send_recv_attached]: 5.99999e-06 [receive_attached]: 1.228e-05 [after_resolve]: 3.116e-05 [a_after_grad]: 3.421e-05 [renormalize]: 0.148728 [add_forward_monad_depend]: 1.406e-05 [auto_monad_grad]: 3.32002e-06 [auto_monad_eliminator]: 7.711e-05 [cse]: 0.00026273 [a_3]: 0.00016246 [Cycle 2]: 0.00259585, [45] [expand_dump_flag]: 3.36001e-06 [switch_simplify]: 2.466e-05 [loop_unroll]: 2.059e-05 [a_1]: 0.00062752 [with_stream_mark]: 3.685e-05 [recompute_prepare]: 2.446e-05 [updatestate_depend_eliminate]: 1.271e-05 [updatestate_assign_eliminate]: 1.183e-05 [updatestate_loads_eliminate]: 1.71e-05 [parameter_eliminate]: 2.58e-06 [a_2]: 0.00032258 [accelerated_algorithm]: 0.00048169 [shard]: 2.99999e-06 [meta_shard_fg_expand]: 8.01001e-06 [shard_inline]: 2.63e-05 [merge_send_recv]: 2.221e-05 [auto_parallel]: 1.935e-05 [parallel]: 1.138e-05 [flash_sp]: 6.76999e-06 [merge_comm]: 1.071e-05 [allreduce_fusion]: 1.033e-05 [matmul_add_comm_reduction]: 2.351e-05 [allreduce_slice_to_reducescatter]: 1.12e-06 [virtual_shard_identity]: 2.288e-05 [virtual_dataset]: 1.911e-05 [get_grad_eliminate_]: 1.83e-05 [virtual_output]: 1.866e-05 [merge_forward]: 1.128e-05 [cell_reuse_recompute_pass]: 3.43999e-06 [offload_activation]: 1.987e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.466e-05 [merge_recompute_call_nodes]: 1.60999e-06 [before_grad]: 3.291e-05 [set_forward_comm_id_for_comm_node_pass]: 1.155e-05 [meta_fg_expand]: 8.03999e-06 [flash_sp_send_recv_attached]: 2.09e-06 [receive_attached]: 2.32001e-06 [after_resolve]: 2.726e-05 [a_after_grad]: 3.104e-05 [renormalize]: 1.30007e-07 [add_forward_monad_depend]: 7.16001e-06 [auto_monad_grad]: 2.68e-06 [auto_monad_eliminator]: 6.745e-05 [cse]: 8.446e-05 [a_3]: 0.00012664 [py_interpret_to_execute_after_opt_a]: 3.188e-05 [slice_cell_reuse_recomputed_activation]: 3.00998e-06 [rewriter_after_opt_a]: 0.00025101 [convert_after_rewriter]: 1.965e-05 [order_py_execute_after_rewriter]: 1.26e-05 [mutable_eliminate]: 0.00082449 [opt_b]: 0.00070735, [1] [Cycle 1]: 0.00069761, [7] [b_1]: 0.00047615 [b_2]: 2.372e-05 [updatestate_depend_eliminate]: 1.618e-05 [updatestate_assign_eliminate]: 1.225e-05 [updatestate_loads_eliminate]: 1.631e-05 [renormalize]: 1.09e-06 [cse]: 0.00010415 [optimize_parallel_all_gather_comm]: 3.946e-05 [overlap_param_gather]: 5.52999e-06 [cconv]: 4.165e-05 [loop_unroll]: 0.00064258 [opt_after_cconv]: 0.00034365, [1] [Cycle 1]: 0.00033219, [7] [c_1]: 0.00015774 [parameter_eliminate]: 6.53e-06 [updatestate_depend_eliminate]: 1.681e-05 [updatestate_assign_eliminate]: 1.083e-05 [updatestate_loads_eliminate]: 1.532e-05 [cse]: 7.988e-05 [renormalize]: 7.2e-07 [remove_dup_value]: 8.356e-05 [tuple_transform]: 0.00022214, [1] [Cycle 1]: 0.00021486, [4] [d_1]: 0.00016521 [none_parameter_eliminate]: 2.22999e-06 [renormalize]: 2.60014e-07 [switch_simplify]: 2.501e-05 [partial_unused_args_eliminate]: 2.31e-06 [add_recomputation]: 0.00014717 [cse_after_recomputation]: 7.386e-05, [1] [Cycle 1]: 6.774e-05, [1] [cse]: 5.905e-05 [environ_conv]: 3.727e-05 [swap_dp_allreduce_reducescatter]: 1.635e-05 [bias_add_comm_swap]: 3.55e-06 [label_micro_interleaved_index]: 7.84002e-06 [label_fine_grained_interleaved_index]: 3.07002e-06 [merge_cast_opt]: 1.79e-06 [slice_recompute_activation]: 2.37999e-06 [micro_interleaved_order_control]: 2.46e-06 [assign_add_opt]: 1.92001e-06 [ForceFp32Comm]: 9.5999e-07 [remove_cast_before_assign_add]: 1.12e-06 [full_micro_interleaved_order_control]: 2.60997e-06 [reorder_send_recv_between_fp_bp]: 3.56999e-06 [comm_op_add_attrs]: 1.82999e-06 [add_comm_op_reuse_tag]: 1.56998e-06 [interleave_split_concat_branches]: 1.32e-06 [interleave_parallel_branches]: 1.45999e-06 [overlap_opt_shard_in_pipeline]: 2.452e-05 [overlap_opt_shard_grad_in_pipeline]: 2.50002e-06 [control_data_broadcast_order]: 3.705e-05 [grouped_pairwise_exchange_alltoall]: 2.16998e-06 [offloading_packed_experts]: 9.52999e-06 [overlap_recompute_and_grad_model_parallel]: 9.76003e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.49998e-06 [overlap_recompute_allgather_and_fa_grad]: 1.49e-06 [overlap_recompute_comm]: 3.08e-06 [overlap_grad_ring_attention]: 8.90999e-06 [overlap_grad_flash_sp]: 6.008e-05 [begin_end_overlap_inline]: 6.50005e-07 [split_matmul_comm_elemetwise]: 2.88998e-06 [split_layernorm_comm]: 2.06998e-06 [handle_group_info]: 9.70002e-07 [symbol_engine_optimizer]: 0.00018862, [1] [Cycle 1]: 0.00018185, [6] [build]: 1.723e-05 [elim_shapecalc]: 3.14e-05 [elim_not_effective]: 3.633e-05 [opt_reshape]: 2.803e-05 [fold_const_symbol]: 3.117e-05 [renormalize]: 4.2998e-07 [detach_backward]: 2.54001e-06 [pipeline_parallel_scheduler]: 1.77001e-06 [auto_monad_reorder]: 7.205e-05 [get_jit_bprop_graph]: 1.70001e-06 [rewriter_after_jit_bprop_graph]: 6.32001e-06 [opt_after_jit_grad]: 0.00073581 [validate]: 0.00011738 Sums bootstrap : 0.000754s : 0.02% type_inference : 2.972235s : 94.87% event_method : 0.000020s : 0.00% auto_monad : 0.001650s : 0.05% graph_reusing : 0.000008s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000027s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000003s : 0.00% pre_auto_parallel : 0.000057s : 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 : 0.000036s : 0.00% optimize.rewriter_before_opt_a : 0.000105s : 0.00% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000068s : 0.00% optimize.opt_a.loop_unroll : 0.000045s : 0.00% optimize.opt_a.a_1 : 0.001510s : 0.05% optimize.opt_a.with_stream_mark : 0.000075s : 0.00% optimize.opt_a.recompute_prepare : 0.000051s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000025s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000023s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000108s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000649s : 0.02% optimize.opt_a.accelerated_algorithm : 0.000540s : 0.02% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000013s : 0.00% optimize.opt_a.shard_inline : 0.000047s : 0.00% optimize.opt_a.merge_send_recv : 0.000040s : 0.00% optimize.opt_a.auto_parallel : 0.000038s : 0.00% optimize.opt_a.parallel : 0.000070s : 0.00% optimize.opt_a.flash_sp : 0.000035s : 0.00% optimize.opt_a.merge_comm : 0.000022s : 0.00% optimize.opt_a.allreduce_fusion : 0.000020s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000044s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000048s : 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 : 0.000039s : 0.00% optimize.opt_a.merge_forward : 0.000022s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000039s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000083s : 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 : 0.000024s : 0.00% optimize.opt_a.meta_fg_expand : 0.000016s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000015s : 0.00% optimize.opt_a.after_resolve : 0.000058s : 0.00% optimize.opt_a.a_after_grad : 0.000065s : 0.00% optimize.opt_a.renormalize : 0.148728s : 4.75% optimize.opt_a.add_forward_monad_depend : 0.000021s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000145s : 0.00% optimize.opt_a.cse : 0.000347s : 0.01% optimize.opt_a.a_3 : 0.000289s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000032s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000003s : 0.00% optimize.rewriter_after_opt_a : 0.000251s : 0.01% optimize.convert_after_rewriter : 0.000020s : 0.00% optimize.order_py_execute_after_rewriter : 0.000013s : 0.00% optimize.mutable_eliminate : 0.000824s : 0.03% optimize.opt_b.b_1 : 0.000476s : 0.02% optimize.opt_b.b_2 : 0.000024s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000016s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000012s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000016s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000104s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000039s : 0.00% optimize.overlap_param_gather : 0.000006s : 0.00% optimize.cconv : 0.000042s : 0.00% optimize.loop_unroll : 0.000643s : 0.02% optimize.opt_after_cconv.c_1 : 0.000158s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000015s : 0.00% optimize.opt_after_cconv.cse : 0.000080s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000084s : 0.00% optimize.tuple_transform.d_1 : 0.000165s : 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 : 0.000025s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000147s : 0.00% optimize.cse_after_recomputation.cse : 0.000059s : 0.00% optimize.environ_conv : 0.000037s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000016s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000008s : 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 : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000004s : 0.00% optimize.comm_op_add_attrs : 0.000002s : 0.00% optimize.add_comm_op_reuse_tag : 0.000002s : 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 : 0.000025s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000003s : 0.00% optimize.control_data_broadcast_order : 0.000037s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000010s : 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 : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000060s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000003s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000017s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000031s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000036s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000028s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000031s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000072s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000736s : 0.02% validate : 0.000117s : 0.00% Time group info: ------[substitution.] 0.000454 138 8.77% : 0.000040s : 4: substitution.arithmetic_simplify 2.66% : 0.000012s : 2: substitution.depend_value_elim 1.02% : 0.000005s : 11: substitution.elim_not_effective 0.92% : 0.000004s : 11: substitution.fold_const_symbol 3.52% : 0.000016s : 17: substitution.graph_param_transform 29.88% : 0.000136s : 1: substitution.inline 2.73% : 0.000012s : 22: substitution.j_node_and_user_rematch 7.37% : 0.000033s : 6: substitution.less_batch_normalization 2.15% : 0.000010s : 12: substitution.load_eliminater 0.45% : 0.000002s : 2: substitution.opt_reshape 4.01% : 0.000018s : 22: substitution.remove_not_recompute_node 2.28% : 0.000010s : 6: substitution.replace_old_param 9.76% : 0.000044s : 4: substitution.reshape_eliminate 3.61% : 0.000016s : 8: substitution.updatestate_pure_node_eliminater 20.88% : 0.000095s : 10: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.972109 2 99.85% : 2.967654s : 1: type_inference.infer 0.15% : 0.004455s : 1: type_inference.specialize ------[replace.] 0.000023 1 100.00% : 0.000023s : 1: replace.inline ------[match.] 0.000134 1 100.00% : 0.000134s : 1: match.inline ------[predicate.] 0.000581 3905 0.83% : 0.000005s : 35: predicate.accumulaten_eliminater 0.82% : 0.000005s : 17: predicate.ad_related_special_op_eliminate 0.77% : 0.000004s : 34: predicate.addn_check_dump 0.88% : 0.000005s : 35: predicate.addn_zero_filter 0.78% : 0.000005s : 35: predicate.adjust_all_reduce_mul_add 2.82% : 0.000016s : 69: predicate.arithmetic_simplify 0.85% : 0.000005s : 35: predicate.cast_eliminate 0.82% : 0.000005s : 34: predicate.check_bprop_eliminate 0.77% : 0.000004s : 34: predicate.compare_switch_simplify 0.25% : 0.000001s : 17: predicate.const_output_eliminate 0.90% : 0.000005s : 34: predicate.depend_value_elim 0.81% : 0.000005s : 35: predicate.dict_get_item_const_eliminator 0.89% : 0.000005s : 35: predicate.dict_get_item_eliminator 0.78% : 0.000005s : 35: predicate.dict_set_item_eliminator 0.91% : 0.000005s : 34: predicate.dumpgradient_eliminate 0.29% : 0.000002s : 17: predicate.elim_not_effective 0.53% : 0.000003s : 17: predicate.elim_shapecalc_of_broadcastargs 1.17% : 0.000007s : 52: predicate.environ_add_const_eliminate 1.11% : 0.000006s : 52: predicate.environ_get_add_eliminate 1.08% : 0.000006s : 52: predicate.environ_get_depend_swap 1.90% : 0.000011s : 86: predicate.environ_get_eliminate 1.08% : 0.000006s : 52: predicate.environ_get_set_eliminate 0.78% : 0.000005s : 36: predicate.exchange_switch_depend_value 1.30% : 0.000008s : 36: predicate.float_depend_g_call 0.80% : 0.000005s : 34: predicate.float_environ_get_switch 1.13% : 0.000007s : 51: predicate.float_tuple_getitem_switch 0.24% : 0.000001s : 17: predicate.fold_const_symbol 0.88% : 0.000005s : 34: predicate.get_grad_eliminate 0.30% : 0.000002s : 17: predicate.graph_param_transform 0.94% : 0.000005s : 34: predicate.incorporate_call 0.71% : 0.000004s : 34: predicate.incorporate_call_switch 5.55% : 0.000032s : 173: predicate.inline 1.25% : 0.000007s : 34: predicate.inline_without_move 0.44% : 0.000003s : 34: predicate.j_node_and_user_rematch 1.64% : 0.000010s : 34: predicate.less_batch_normalization 1.82% : 0.000011s : 69: predicate.list_to_tuple_eliminator_ 2.39% : 0.000014s : 104: predicate.load_eliminater 0.99% : 0.000006s : 17: predicate.loop_unroll_after_grad 1.10% : 0.000006s : 39: predicate.loop_unroll_before_grad 1.77% : 0.000010s : 69: predicate.make_slice_get_slice_eliminator 0.80% : 0.000005s : 34: predicate.merge_addn 0.79% : 0.000005s : 34: predicate.micro_step_allgather_replace 0.79% : 0.000005s : 34: predicate.mini_step_allgather_replace 0.73% : 0.000004s : 35: predicate.minmaximum_grad 0.91% : 0.000005s : 17: predicate.mutable_eliminate 0.58% : 0.000003s : 17: predicate.opt_reshape 0.45% : 0.000003s : 17: predicate.parallel_virtual_node 1.10% : 0.000006s : 36: predicate.partial_defer_inline 1.28% : 0.000007s : 52: predicate.partial_eliminate 0.76% : 0.000004s : 35: predicate.print_const_string_wrapper 0.74% : 0.000004s : 34: predicate.reduce_all_const_elim 1.02% : 0.000006s : 35: predicate.reduce_eliminate 2.33% : 0.000014s : 104: predicate.redundant_stop_gradient_eliminater 0.60% : 0.000003s : 34: predicate.remove_not_recompute_node 1.26% : 0.000007s : 69: predicate.replace_applicator 0.55% : 0.000003s : 34: predicate.replace_old_param 0.36% : 0.000002s : 17: predicate.reset_defer_inline 0.96% : 0.000006s : 35: predicate.reshape_eliminate 0.83% : 0.000005s : 34: predicate.row_tensor_add_zeros_like 0.53% : 0.000003s : 17: predicate.row_tensor_eliminate 1.16% : 0.000007s : 34: predicate.same_eliminate 0.60% : 0.000003s : 34: predicate.set_cell_output_no_recompute 0.95% : 0.000006s : 34: predicate.shard_identity_eliminate 1.00% : 0.000006s : 34: predicate.special_op_eliminate 1.05% : 0.000006s : 34: predicate.specialize_transform 0.98% : 0.000006s : 34: predicate.split_environ_get_set_with_tuple_value 1.02% : 0.000006s : 34: predicate.stack_unstack_eliminate 0.51% : 0.000003s : 17: predicate.switch_call_monad_eliminater 0.84% : 0.000005s : 36: predicate.switch_defer_inline 1.59% : 0.000009s : 70: predicate.switch_layer_defer_inline 3.51% : 0.000020s : 126: predicate.switch_simplify 0.88% : 0.000005s : 35: predicate.tile_eliminate 0.81% : 0.000005s : 35: predicate.transpose_eliminate 1.78% : 0.000010s : 69: predicate.tuple_list_convert_item_index_to_positive 1.64% : 0.000010s : 69: predicate.tuple_list_get_item_const_eliminator 1.58% : 0.000009s : 69: predicate.tuple_list_get_item_depend_reorder 2.85% : 0.000017s : 103: predicate.tuple_list_get_item_eliminator 1.67% : 0.000010s : 69: predicate.tuple_list_get_set_item_eliminator 2.68% : 0.000016s : 103: predicate.tuple_list_set_item_eliminator 1.66% : 0.000010s : 69: predicate.tuple_to_list_eliminator_ 2.31% : 0.000013s : 104: predicate.updatestate_pure_node_eliminater 3.25% : 0.000019s : 138: predicate.updatestate_useless_node_eliminater 0.45% : 0.000003s : 17: predicate.value_based_eliminate 0.92% : 0.000005s : 34: predicate.virtual_dataset_eliminate 0.87% : 0.000005s : 34: predicate.virtual_output_eliminate 0.45% : 0.000003s : 17: predicate.virtual_view_grad_eliminate 0.52% : 0.000003s : 17: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.010868 56 79.19% : 0.008607s : 53: func_graph_cloner_run.FuncGraphClonerGraph 20.81% : 0.002261s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.463150 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.25% : 0.008495s : 1: add_attr 0.24% : 0.008470s : 1: add_attr_with_inline 0.00% : 0.000005s : 1: add_comm_op_reuse_tag 0.00% : 0.000153s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.05% : 0.001685s : 1: auto_monad 0.00% : 0.000078s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.02% : 0.000792s : 1: bootstrap 0.00% : 0.000047s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.00% : 0.000041s : 1: control_data_broadcast_order 0.00% : 0.000025s : 1: convert_after_rewriter 0.00% : 0.000077s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000042s : 1: environ_conv 0.00% : 0.000030s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000016s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000007s : 1: insert-virtual-dataset 0.00% : 0.000005s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000007s : 1: label_fine_grained_interleaved_index 0.00% : 0.000011s : 1: label_micro_interleaved_index 0.02% : 0.000660s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.02% : 0.000841s : 1: mutable_eliminate 0.00% : 0.000013s : 1: offloading_packed_experts 0.00% : 0.000041s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000041s : 1: opt.transform.mutable_eliminate 0.10% : 0.003490s : 78: opt.transform.opt_a 0.00% : 0.000156s : 1: opt.transform.opt_after_cconv 0.00% : 0.000073s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000457s : 28: opt.transform.opt_b 0.01% : 0.000187s : 2: opt.transform.opt_trans_graph 0.00% : 0.000121s : 4: opt.transform.symbol_engine_opt 4.45% : 0.154272s : 1: opt_a 0.01% : 0.000348s : 1: opt_after_cconv 0.02% : 0.000749s : 1: opt_after_jit_grad 0.02% : 0.000712s : 1: opt_b 4.58% : 0.158622s : 1: optimize 0.00% : 0.000044s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000065s : 1: overlap_grad_flash_sp 0.00% : 0.000005s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000012s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000029s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000010s : 1: overlap_param_gather 0.00% : 0.000005s : 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% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000062s : 1: pre_auto_parallel 0.00% : 0.000040s : 1: py_interpret_to_execute 0.00% : 0.000037s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000090s : 1: remove_dup_value 4.22% : 0.146054s : 1: renormalize.infer 0.08% : 0.002653s : 1: renormalize.specialize 0.00% : 0.000007s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000261s : 1: rewriter_after_opt_a 0.00% : 0.000110s : 1: rewriter_before_opt_a 0.00% : 0.000006s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000006s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000006s : 1: split_matmul_comm_elemetwise 0.00% : 0.000020s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000192s : 1: symbol_engine_optimizer 0.01% : 0.000226s : 1: tuple_transform 85.83% : 2.972272s : 1: type_inference . [hook] pytest_runtest_teardown:test_matmul_ffn_1[False-mstype0-k_n_shape0-16] tests/st/infer/ops/test_internal_ops/test_matmul_biasadd_split.py::test_matmul_ffn_1[False-mstype0-k_n_shape0-16],max_mem:352.0M [WARNING] ME(160590:281473768550192,MainProcess):2026-01-29-17:39:38.504.691 [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 = 3.82955, [21] [bootstrap]: 0.00109777 [type_inference]: 3.51627 [event_method]: 1.898e-05 [auto_monad]: 0.00033496 [graph_reusing]: 6.41e-06 [inline]: 2.95002e-06 [add_attr]: 0.00728163, [1] [add_attr_with_inline]: 0.00726395, [1] [Cycle 1]: 6.732e-05, [2] [tag_attr]: 2.232e-05 [meta_addattr_fg_expand]: 4.68999e-06 [parallel-infer-symbol]: 3.60998e-06 [pre_auto_parallel]: 3.803e-05 [insert-virtual-dataset]: 2.36998e-06 [parallel-infer-symbol-second]: 8.50006e-07 [dataset_repeat_opt]: 2.14999e-06 [pipeline_split]: 1.55001e-06 [optimize]: 0.147427, [53] [py_interpret_to_execute]: 3.243e-05 [rewriter_before_opt_a]: 8.972e-05 [opt_a]: 0.143234, [2] [Cycle 1]: 0.141102, [45] [expand_dump_flag]: 3.18e-06 [switch_simplify]: 3.721e-05 [loop_unroll]: 2.376e-05 [a_1]: 0.00098952 [with_stream_mark]: 2.713e-05 [recompute_prepare]: 2.587e-05 [updatestate_depend_eliminate]: 1.187e-05 [updatestate_assign_eliminate]: 9.97999e-06 [updatestate_loads_eliminate]: 7.271e-05 [parameter_eliminate]: 2.56e-06 [a_2]: 0.00032567 [accelerated_algorithm]: 7.337e-05 [shard]: 2.24999e-06 [meta_shard_fg_expand]: 4.48999e-06 [shard_inline]: 2.225e-05 [merge_send_recv]: 1.77e-05 [auto_parallel]: 1.545e-05 [parallel]: 3.706e-05 [flash_sp]: 1.411e-05 [merge_comm]: 1.163e-05 [allreduce_fusion]: 1.054e-05 [matmul_add_comm_reduction]: 1.966e-05 [allreduce_slice_to_reducescatter]: 8.59989e-07 [virtual_shard_identity]: 2.921e-05 [virtual_dataset]: 2.201e-05 [get_grad_eliminate_]: 2.456e-05 [virtual_output]: 2.387e-05 [merge_forward]: 1.068e-05 [cell_reuse_recompute_pass]: 2.33998e-06 [offload_activation]: 2.037e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.577e-05 [merge_recompute_call_nodes]: 1.72001e-06 [before_grad]: 4.12e-05 [set_forward_comm_id_for_comm_node_pass]: 1.149e-05 [meta_fg_expand]: 7.3e-06 [flash_sp_send_recv_attached]: 5.47999e-06 [receive_attached]: 2.26998e-06 [after_resolve]: 3.13e-05 [a_after_grad]: 3.924e-05 [renormalize]: 0.136834 [add_forward_monad_depend]: 1.305e-05 [auto_monad_grad]: 3.03e-06 [auto_monad_eliminator]: 7.231e-05 [cse]: 0.00153388 [a_3]: 0.0001721 [Cycle 2]: 0.00211515, [45] [expand_dump_flag]: 4.33001e-06 [switch_simplify]: 2.368e-05 [loop_unroll]: 2.047e-05 [a_1]: 0.00065969 [with_stream_mark]: 3.777e-05 [recompute_prepare]: 2.276e-05 [updatestate_depend_eliminate]: 1.287e-05 [updatestate_assign_eliminate]: 1.172e-05 [updatestate_loads_eliminate]: 1.591e-05 [parameter_eliminate]: 2.67001e-06 [a_2]: 0.00028923 [accelerated_algorithm]: 3.1e-05 [shard]: 2.28002e-06 [meta_shard_fg_expand]: 6.18002e-06 [shard_inline]: 2.008e-05 [merge_send_recv]: 2.039e-05 [auto_parallel]: 1.711e-05 [parallel]: 1.045e-05 [flash_sp]: 5.72001e-06 [merge_comm]: 1.096e-05 [allreduce_fusion]: 9.68002e-06 [matmul_add_comm_reduction]: 2.35e-05 [allreduce_slice_to_reducescatter]: 8.79983e-07 [virtual_shard_identity]: 2.301e-05 [virtual_dataset]: 1.947e-05 [get_grad_eliminate_]: 1.864e-05 [virtual_output]: 1.906e-05 [merge_forward]: 1.132e-05 [cell_reuse_recompute_pass]: 3.11001e-06 [offload_activation]: 1.994e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.208e-05 [merge_recompute_call_nodes]: 1.54998e-06 [before_grad]: 3.244e-05 [set_forward_comm_id_for_comm_node_pass]: 1.157e-05 [meta_fg_expand]: 8.26002e-06 [flash_sp_send_recv_attached]: 1.97999e-06 [receive_attached]: 2.61e-06 [after_resolve]: 3.047e-05 [a_after_grad]: 3.158e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 3.86001e-06 [auto_monad_grad]: 2.80002e-06 [auto_monad_eliminator]: 6.352e-05 [cse]: 8.523e-05 [a_3]: 0.00013454 [py_interpret_to_execute_after_opt_a]: 3.777e-05 [slice_cell_reuse_recomputed_activation]: 2.05002e-06 [rewriter_after_opt_a]: 0.00022972 [convert_after_rewriter]: 1.923e-05 [order_py_execute_after_rewriter]: 1.263e-05 [mutable_eliminate]: 0.00082655 [opt_b]: 0.00068772, [1] [Cycle 1]: 0.00067679, [7] [b_1]: 0.00046743 [b_2]: 2.246e-05 [updatestate_depend_eliminate]: 1.743e-05 [updatestate_assign_eliminate]: 1.106e-05 [updatestate_loads_eliminate]: 1.532e-05 [renormalize]: 1.09e-06 [cse]: 9.546e-05 [optimize_parallel_all_gather_comm]: 4.292e-05 [overlap_param_gather]: 2.47001e-06 [cconv]: 4.36e-05 [loop_unroll]: 0.0006732 [opt_after_cconv]: 0.0003159, [1] [Cycle 1]: 0.00030561, [7] [c_1]: 0.00014184 [parameter_eliminate]: 7.15e-06 [updatestate_depend_eliminate]: 1.747e-05 [updatestate_assign_eliminate]: 9.93998e-06 [updatestate_loads_eliminate]: 1.308e-05 [cse]: 7.452e-05 [renormalize]: 7.7e-07 [remove_dup_value]: 8.262e-05 [tuple_transform]: 0.00019835, [1] [Cycle 1]: 0.0001914, [4] [d_1]: 0.00014621 [none_parameter_eliminate]: 1.64998e-06 [renormalize]: 5.19998e-07 [switch_simplify]: 2.008e-05 [partial_unused_args_eliminate]: 2.02999e-06 [add_recomputation]: 0.00014939 [cse_after_recomputation]: 6.755e-05, [1] [Cycle 1]: 6.023e-05, [1] [cse]: 5.251e-05 [environ_conv]: 2.64e-05 [swap_dp_allreduce_reducescatter]: 1.507e-05 [bias_add_comm_swap]: 4.13001e-06 [label_micro_interleaved_index]: 7.48999e-06 [label_fine_grained_interleaved_index]: 2.74001e-06 [merge_cast_opt]: 1.64e-06 [slice_recompute_activation]: 2.39001e-06 [micro_interleaved_order_control]: 2.46e-06 [assign_add_opt]: 1.23002e-06 [ForceFp32Comm]: 1.22e-06 [remove_cast_before_assign_add]: 1.32e-06 [full_micro_interleaved_order_control]: 2.29001e-06 [reorder_send_recv_between_fp_bp]: 2.80002e-06 [comm_op_add_attrs]: 1.15001e-06 [add_comm_op_reuse_tag]: 1.17999e-06 [interleave_split_concat_branches]: 1.17e-06 [interleave_parallel_branches]: 1.19e-06 [overlap_opt_shard_in_pipeline]: 1.39998e-06 [overlap_opt_shard_grad_in_pipeline]: 2.45002e-06 [control_data_broadcast_order]: 3.339e-05 [grouped_pairwise_exchange_alltoall]: 1.69e-06 [offloading_packed_experts]: 8.47998e-06 [overlap_recompute_and_grad_model_parallel]: 9.57999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.32e-06 [overlap_recompute_allgather_and_fa_grad]: 1.35999e-06 [overlap_recompute_comm]: 2.27999e-06 [overlap_grad_ring_attention]: 9.74e-06 [overlap_grad_flash_sp]: 4.515e-05 [begin_end_overlap_inline]: 5.60016e-07 [split_matmul_comm_elemetwise]: 2.24999e-06 [split_layernorm_comm]: 1.69e-06 [handle_group_info]: 1.32e-06 [symbol_engine_optimizer]: 0.00018647, [1] [Cycle 1]: 0.00018078, [6] [build]: 1.906e-05 [elim_shapecalc]: 2.883e-05 [elim_not_effective]: 3.779e-05 [opt_reshape]: 2.643e-05 [fold_const_symbol]: 3.424e-05 [renormalize]: 2.00002e-07 [detach_backward]: 2.61999e-06 [pipeline_parallel_scheduler]: 1.48002e-06 [auto_monad_reorder]: 6.67e-05 [get_jit_bprop_graph]: 2.59001e-06 [rewriter_after_jit_bprop_graph]: 6.34999e-06 [opt_after_jit_grad]: 0.156609 [validate]: 0.00013724 Sums bootstrap : 0.001098s : 0.03% type_inference : 3.516266s : 92.03% event_method : 0.000019s : 0.00% auto_monad : 0.000335s : 0.01% graph_reusing : 0.000006s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000022s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000038s : 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 : 0.000032s : 0.00% optimize.rewriter_before_opt_a : 0.000090s : 0.00% optimize.opt_a.expand_dump_flag : 0.000008s : 0.00% optimize.opt_a.switch_simplify : 0.000061s : 0.00% optimize.opt_a.loop_unroll : 0.000044s : 0.00% optimize.opt_a.a_1 : 0.001649s : 0.04% optimize.opt_a.with_stream_mark : 0.000065s : 0.00% optimize.opt_a.recompute_prepare : 0.000049s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000025s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000022s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000089s : 0.00% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000615s : 0.02% optimize.opt_a.accelerated_algorithm : 0.000104s : 0.00% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000011s : 0.00% optimize.opt_a.shard_inline : 0.000042s : 0.00% optimize.opt_a.merge_send_recv : 0.000038s : 0.00% optimize.opt_a.auto_parallel : 0.000033s : 0.00% optimize.opt_a.parallel : 0.000048s : 0.00% optimize.opt_a.flash_sp : 0.000020s : 0.00% optimize.opt_a.merge_comm : 0.000023s : 0.00% optimize.opt_a.allreduce_fusion : 0.000020s : 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 : 0.000052s : 0.00% optimize.opt_a.virtual_dataset : 0.000041s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000043s : 0.00% optimize.opt_a.virtual_output : 0.000043s : 0.00% optimize.opt_a.merge_forward : 0.000022s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000040s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000088s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000074s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000023s : 0.00% optimize.opt_a.meta_fg_expand : 0.000016s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000062s : 0.00% optimize.opt_a.a_after_grad : 0.000071s : 0.00% optimize.opt_a.renormalize : 0.136834s : 3.58% optimize.opt_a.add_forward_monad_depend : 0.000017s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000136s : 0.00% optimize.opt_a.cse : 0.001619s : 0.04% optimize.opt_a.a_3 : 0.000307s : 0.01% optimize.py_interpret_to_execute_after_opt_a : 0.000038s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000230s : 0.01% optimize.convert_after_rewriter : 0.000019s : 0.00% optimize.order_py_execute_after_rewriter : 0.000013s : 0.00% optimize.mutable_eliminate : 0.000827s : 0.02% optimize.opt_b.b_1 : 0.000467s : 0.01% optimize.opt_b.b_2 : 0.000022s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000017s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000015s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000095s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000043s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000044s : 0.00% optimize.loop_unroll : 0.000673s : 0.02% optimize.opt_after_cconv.c_1 : 0.000142s : 0.00% optimize.opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000013s : 0.00% optimize.opt_after_cconv.cse : 0.000075s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000083s : 0.00% optimize.tuple_transform.d_1 : 0.000146s : 0.00% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000001s : 0.00% optimize.tuple_transform.switch_simplify : 0.000020s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000149s : 0.00% optimize.cse_after_recomputation.cse : 0.000053s : 0.00% optimize.environ_conv : 0.000026s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000015s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000007s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 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 : 0.000001s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000033s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000008s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 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 : 0.000010s : 0.00% optimize.overlap_grad_flash_sp : 0.000045s : 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 : 0.000029s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000038s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000026s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000034s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000003s : 0.00% pipeline_parallel_scheduler : 0.000001s : 0.00% auto_monad_reorder : 0.000067s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.156609s : 4.10% validate : 0.000137s : 0.00% Time group info: ------[substitution.] 0.000410 138 9.05% : 0.000037s : 4: substitution.arithmetic_simplify 2.66% : 0.000011s : 2: substitution.depend_value_elim 1.43% : 0.000006s : 11: substitution.elim_not_effective 1.05% : 0.000004s : 11: substitution.fold_const_symbol 3.43% : 0.000014s : 17: substitution.graph_param_transform 26.61% : 0.000109s : 1: substitution.inline 2.75% : 0.000011s : 22: substitution.j_node_and_user_rematch 7.73% : 0.000032s : 6: substitution.less_batch_normalization 2.22% : 0.000009s : 12: substitution.load_eliminater 0.45% : 0.000002s : 2: substitution.opt_reshape 4.51% : 0.000018s : 22: substitution.remove_not_recompute_node 2.85% : 0.000012s : 6: substitution.replace_old_param 7.15% : 0.000029s : 4: substitution.reshape_eliminate 3.86% : 0.000016s : 8: substitution.updatestate_pure_node_eliminater 24.24% : 0.000099s : 10: substitution.updatestate_useless_node_eliminater ------[type_inference.] 3.516156 2 99.85% : 3.510915s : 1: type_inference.infer 0.15% : 0.005242s : 1: type_inference.specialize ------[replace.] 0.000018 1 100.00% : 0.000018s : 1: replace.inline ------[match.] 0.000108 1 100.00% : 0.000108s : 1: match.inline ------[predicate.] 0.000589 3905 0.84% : 0.000005s : 35: predicate.accumulaten_eliminater 2.19% : 0.000013s : 17: predicate.ad_related_special_op_eliminate 0.75% : 0.000004s : 34: predicate.addn_check_dump 0.81% : 0.000005s : 35: predicate.addn_zero_filter 0.73% : 0.000004s : 35: predicate.adjust_all_reduce_mul_add 2.65% : 0.000016s : 69: predicate.arithmetic_simplify 0.81% : 0.000005s : 35: predicate.cast_eliminate 0.84% : 0.000005s : 34: predicate.check_bprop_eliminate 0.77% : 0.000005s : 34: predicate.compare_switch_simplify 0.23% : 0.000001s : 17: predicate.const_output_eliminate 0.81% : 0.000005s : 34: predicate.depend_value_elim 0.85% : 0.000005s : 35: predicate.dict_get_item_const_eliminator 0.87% : 0.000005s : 35: predicate.dict_get_item_eliminator 0.73% : 0.000004s : 35: predicate.dict_set_item_eliminator 1.11% : 0.000007s : 34: predicate.dumpgradient_eliminate 0.27% : 0.000002s : 17: predicate.elim_not_effective 0.51% : 0.000003s : 17: predicate.elim_shapecalc_of_broadcastargs 1.21% : 0.000007s : 52: predicate.environ_add_const_eliminate 1.12% : 0.000007s : 52: predicate.environ_get_add_eliminate 1.17% : 0.000007s : 52: predicate.environ_get_depend_swap 1.88% : 0.000011s : 86: predicate.environ_get_eliminate 1.09% : 0.000006s : 52: predicate.environ_get_set_eliminate 0.81% : 0.000005s : 36: predicate.exchange_switch_depend_value 1.20% : 0.000007s : 36: predicate.float_depend_g_call 0.75% : 0.000004s : 34: predicate.float_environ_get_switch 1.08% : 0.000006s : 51: predicate.float_tuple_getitem_switch 0.22% : 0.000001s : 17: predicate.fold_const_symbol 0.87% : 0.000005s : 34: predicate.get_grad_eliminate 0.30% : 0.000002s : 17: predicate.graph_param_transform 0.73% : 0.000004s : 34: predicate.incorporate_call 0.70% : 0.000004s : 34: predicate.incorporate_call_switch 5.28% : 0.000031s : 173: predicate.inline 1.18% : 0.000007s : 34: predicate.inline_without_move 0.46% : 0.000003s : 34: predicate.j_node_and_user_rematch 1.12% : 0.000007s : 34: predicate.less_batch_normalization 1.73% : 0.000010s : 69: predicate.list_to_tuple_eliminator_ 2.26% : 0.000013s : 104: predicate.load_eliminater 1.08% : 0.000006s : 17: predicate.loop_unroll_after_grad 0.90% : 0.000005s : 39: predicate.loop_unroll_before_grad 1.76% : 0.000010s : 69: predicate.make_slice_get_slice_eliminator 0.77% : 0.000005s : 34: predicate.merge_addn 0.80% : 0.000005s : 34: predicate.micro_step_allgather_replace 0.77% : 0.000005s : 34: predicate.mini_step_allgather_replace 0.72% : 0.000004s : 35: predicate.minmaximum_grad 1.35% : 0.000008s : 17: predicate.mutable_eliminate 0.62% : 0.000004s : 17: predicate.opt_reshape 0.42% : 0.000002s : 17: predicate.parallel_virtual_node 1.29% : 0.000008s : 36: predicate.partial_defer_inline 1.25% : 0.000007s : 52: predicate.partial_eliminate 0.77% : 0.000005s : 35: predicate.print_const_string_wrapper 0.77% : 0.000005s : 34: predicate.reduce_all_const_elim 1.21% : 0.000007s : 35: predicate.reduce_eliminate 2.33% : 0.000014s : 104: predicate.redundant_stop_gradient_eliminater 0.51% : 0.000003s : 34: predicate.remove_not_recompute_node 1.29% : 0.000008s : 69: predicate.replace_applicator 0.52% : 0.000003s : 34: predicate.replace_old_param 0.38% : 0.000002s : 17: predicate.reset_defer_inline 0.90% : 0.000005s : 35: predicate.reshape_eliminate 0.84% : 0.000005s : 34: predicate.row_tensor_add_zeros_like 0.56% : 0.000003s : 17: predicate.row_tensor_eliminate 1.39% : 0.000008s : 34: predicate.same_eliminate 0.56% : 0.000003s : 34: predicate.set_cell_output_no_recompute 1.02% : 0.000006s : 34: predicate.shard_identity_eliminate 0.92% : 0.000005s : 34: predicate.special_op_eliminate 1.00% : 0.000006s : 34: predicate.specialize_transform 1.05% : 0.000006s : 34: predicate.split_environ_get_set_with_tuple_value 0.98% : 0.000006s : 34: predicate.stack_unstack_eliminate 0.48% : 0.000003s : 17: predicate.switch_call_monad_eliminater 0.95% : 0.000006s : 36: predicate.switch_defer_inline 1.65% : 0.000010s : 70: predicate.switch_layer_defer_inline 3.24% : 0.000019s : 126: predicate.switch_simplify 0.80% : 0.000005s : 35: predicate.tile_eliminate 0.77% : 0.000005s : 35: predicate.transpose_eliminate 1.67% : 0.000010s : 69: predicate.tuple_list_convert_item_index_to_positive 1.64% : 0.000010s : 69: predicate.tuple_list_get_item_const_eliminator 1.70% : 0.000010s : 69: predicate.tuple_list_get_item_depend_reorder 2.78% : 0.000016s : 103: predicate.tuple_list_get_item_eliminator 1.70% : 0.000010s : 69: predicate.tuple_list_get_set_item_eliminator 2.58% : 0.000015s : 103: predicate.tuple_list_set_item_eliminator 1.61% : 0.000010s : 69: predicate.tuple_to_list_eliminator_ 2.40% : 0.000014s : 104: predicate.updatestate_pure_node_eliminater 3.28% : 0.000019s : 138: predicate.updatestate_useless_node_eliminater 0.43% : 0.000003s : 17: predicate.value_based_eliminate 0.90% : 0.000005s : 34: predicate.virtual_dataset_eliminate 0.84% : 0.000005s : 34: predicate.virtual_output_eliminate 0.41% : 0.000002s : 17: predicate.virtual_view_grad_eliminate 0.48% : 0.000003s : 17: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.264801 56 98.78% : 0.261576s : 53: func_graph_cloner_run.FuncGraphClonerGraph 1.22% : 0.003225s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 4.280916 192 0.00% : 0.000004s : 1: ForceFp32Comm 0.17% : 0.007289s : 1: add_attr 0.17% : 0.007269s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000157s : 1: add_recomputation 0.00% : 0.000006s : 1: assign_add_opt 0.01% : 0.000346s : 1: auto_monad 0.00% : 0.000073s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: begin_end_overlap_inline 0.00% : 0.000008s : 1: bias_add_comm_swap 0.03% : 0.001142s : 1: bootstrap 0.00% : 0.000048s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000037s : 1: control_data_broadcast_order 0.00% : 0.000024s : 1: convert_after_rewriter 0.00% : 0.000071s : 1: cse_after_recomputation 0.00% : 0.000007s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000030s : 1: environ_conv 0.00% : 0.000027s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000007s : 1: get_jit_bprop_graph 0.00% : 0.000013s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000006s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000006s : 1: interleave_parallel_branches 0.00% : 0.000005s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000010s : 1: label_micro_interleaved_index 0.02% : 0.000688s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.02% : 0.000840s : 1: mutable_eliminate 0.00% : 0.000012s : 1: offloading_packed_experts 0.00% : 0.000038s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000050s : 1: opt.transform.mutable_eliminate 0.07% : 0.003204s : 78: opt.transform.opt_a 0.00% : 0.000140s : 1: opt.transform.opt_after_cconv 3.64% : 0.155935s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000451s : 28: opt.transform.opt_b 0.00% : 0.000164s : 2: opt.transform.opt_trans_graph 0.00% : 0.000122s : 4: opt.transform.symbol_engine_opt 3.35% : 0.143239s : 1: opt_a 0.01% : 0.000320s : 1: opt_after_cconv 3.66% : 0.156633s : 1: opt_after_jit_grad 0.02% : 0.000692s : 1: opt_b 3.44% : 0.147435s : 1: optimize 0.00% : 0.000047s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000049s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 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% : 0.000007s : 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% : 0.000005s : 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% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000004s : 1: pipeline_split 0.00% : 0.000043s : 1: pre_auto_parallel 0.00% : 0.000037s : 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% : 0.000089s : 1: remove_dup_value 3.11% : 0.133069s : 1: renormalize.infer 0.09% : 0.003746s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000239s : 1: rewriter_after_opt_a 0.00% : 0.000094s : 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% : 0.000004s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000019s : 1: swap_dp_allreduce_reducescatter 0.00% : 0.000190s : 1: symbol_engine_optimizer 0.00% : 0.000203s : 1: tuple_transform 82.14% : 3.516306s : 1: type_inference . [hook] pytest_runtest_teardown:test_matmul_ffn_1[False-mstype0-k_n_shape0-256] tests/st/infer/ops/test_internal_ops/test_matmul_biasadd_split.py::test_matmul_ffn_1[False-mstype0-k_n_shape0-256],max_mem:372.0M [WARNING] ME(160590:281473768550192,MainProcess):2026-01-29-17:41:49.926.376 [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 = 1.41384, [21] [bootstrap]: 0.00071993 [type_inference]: 1.26509 [event_method]: 1.393e-05 [auto_monad]: 0.00030461 [graph_reusing]: 5.39998e-06 [inline]: 2.91e-06 [add_attr]: 0.114987, [1] [add_attr_with_inline]: 0.114966, [1] [Cycle 1]: 8.376e-05, [2] [tag_attr]: 2.726e-05 [meta_addattr_fg_expand]: 4.77998e-06 [parallel-infer-symbol]: 3.95e-06 [pre_auto_parallel]: 4.792e-05 [insert-virtual-dataset]: 2.69999e-06 [parallel-infer-symbol-second]: 5.99975e-07 [dataset_repeat_opt]: 1.69e-06 [pipeline_split]: 1.84998e-06 [optimize]: 0.020834, [53] [py_interpret_to_execute]: 3.856e-05 [rewriter_before_opt_a]: 9.698e-05 [opt_a]: 0.0168059, [2] [Cycle 1]: 0.014766, [45] [expand_dump_flag]: 2.79999e-06 [switch_simplify]: 3.721e-05 [loop_unroll]: 2.493e-05 [a_1]: 0.00107259 [with_stream_mark]: 3.161e-05 [recompute_prepare]: 2.571e-05 [updatestate_depend_eliminate]: 1.161e-05 [updatestate_assign_eliminate]: 1.019e-05 [updatestate_loads_eliminate]: 8.36e-05 [parameter_eliminate]: 2.29999e-06 [a_2]: 0.0003992 [accelerated_algorithm]: 6.9e-05 [shard]: 2.43e-06 [meta_shard_fg_expand]: 4.42e-06 [shard_inline]: 2.087e-05 [merge_send_recv]: 1.679e-05 [auto_parallel]: 1.687e-05 [parallel]: 3.007e-05 [flash_sp]: 1.225e-05 [merge_comm]: 1.074e-05 [allreduce_fusion]: 1.01e-05 [matmul_add_comm_reduction]: 2.116e-05 [allreduce_slice_to_reducescatter]: 8.89995e-07 [virtual_shard_identity]: 2.515e-05 [virtual_dataset]: 2.243e-05 [get_grad_eliminate_]: 2.3e-05 [virtual_output]: 2.157e-05 [merge_forward]: 1.079e-05 [cell_reuse_recompute_pass]: 2.30002e-06 [offload_activation]: 1.992e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.895e-05 [merge_recompute_call_nodes]: 1.45999e-06 [before_grad]: 3.838e-05 [set_forward_comm_id_for_comm_node_pass]: 1.115e-05 [meta_fg_expand]: 8.07e-06 [flash_sp_send_recv_attached]: 5.57999e-06 [receive_attached]: 2.36998e-06 [after_resolve]: 3.235e-05 [a_after_grad]: 3.955e-05 [renormalize]: 0.0110922 [add_forward_monad_depend]: 1.232e-05 [auto_monad_grad]: 2.86e-06 [auto_monad_eliminator]: 6.976e-05 [cse]: 0.00083879 [a_3]: 0.00016319 [Cycle 2]: 0.00202512, [45] [expand_dump_flag]: 3.19001e-06 [switch_simplify]: 2.202e-05 [loop_unroll]: 2.006e-05 [a_1]: 0.00063572 [with_stream_mark]: 3.317e-05 [recompute_prepare]: 2.325e-05 [updatestate_depend_eliminate]: 1.169e-05 [updatestate_assign_eliminate]: 1.244e-05 [updatestate_loads_eliminate]: 1.558e-05 [parameter_eliminate]: 3.12002e-06 [a_2]: 0.00028957 [accelerated_algorithm]: 3.255e-05 [shard]: 2.99999e-06 [meta_shard_fg_expand]: 7e-06 [shard_inline]: 1.91e-05 [merge_send_recv]: 1.775e-05 [auto_parallel]: 1.647e-05 [parallel]: 1.071e-05 [flash_sp]: 5.83002e-06 [merge_comm]: 1.121e-05 [allreduce_fusion]: 9.87999e-06 [matmul_add_comm_reduction]: 2.105e-05 [allreduce_slice_to_reducescatter]: 9.39996e-07 [virtual_shard_identity]: 2.37e-05 [virtual_dataset]: 2.02e-05 [get_grad_eliminate_]: 1.858e-05 [virtual_output]: 1.885e-05 [merge_forward]: 1.128e-05 [cell_reuse_recompute_pass]: 4.18999e-06 [offload_activation]: 1.939e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.938e-05 [merge_recompute_call_nodes]: 2.02999e-06 [before_grad]: 3.304e-05 [set_forward_comm_id_for_comm_node_pass]: 1.153e-05 [meta_fg_expand]: 8.04002e-06 [flash_sp_send_recv_attached]: 1.79e-06 [receive_attached]: 2.41e-06 [after_resolve]: 2.733e-05 [a_after_grad]: 3.113e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 4.85001e-06 [auto_monad_grad]: 3.3e-06 [auto_monad_eliminator]: 5.393e-05 [cse]: 7.269e-05 [a_3]: 0.0001291 [py_interpret_to_execute_after_opt_a]: 3.558e-05 [slice_cell_reuse_recomputed_activation]: 2.31e-06 [rewriter_after_opt_a]: 0.00021919 [convert_after_rewriter]: 1.599e-05 [order_py_execute_after_rewriter]: 1.216e-05 [mutable_eliminate]: 0.00079558 [opt_b]: 0.00064805, [1] [Cycle 1]: 0.00063993, [7] [b_1]: 0.00045051 [b_2]: 2.212e-05 [updatestate_depend_eliminate]: 1.814e-05 [updatestate_assign_eliminate]: 1.065e-05 [updatestate_loads_eliminate]: 1.549e-05 [renormalize]: 8.70001e-07 [cse]: 7.947e-05 [optimize_parallel_all_gather_comm]: 3.563e-05 [overlap_param_gather]: 2.21003e-06 [cconv]: 3.948e-05 [loop_unroll]: 0.00059983 [opt_after_cconv]: 0.0003067, [1] [Cycle 1]: 0.00029746, [7] [c_1]: 0.00014064 [parameter_eliminate]: 5.74e-06 [updatestate_depend_eliminate]: 1.703e-05 [updatestate_assign_eliminate]: 1.038e-05 [updatestate_loads_eliminate]: 1.324e-05 [cse]: 6.924e-05 [renormalize]: 5.19998e-07 [remove_dup_value]: 8.608e-05 [tuple_transform]: 0.00020552, [1] [Cycle 1]: 0.00019864, [4] [d_1]: 0.00014854 [none_parameter_eliminate]: 2.43e-06 [renormalize]: 2.59985e-07 [switch_simplify]: 2.267e-05 [partial_unused_args_eliminate]: 2.22001e-06 [add_recomputation]: 0.00014315 [cse_after_recomputation]: 6.915e-05, [1] [Cycle 1]: 6.235e-05, [1] [cse]: 5.431e-05 [environ_conv]: 2.404e-05 [swap_dp_allreduce_reducescatter]: 1.443e-05 [bias_add_comm_swap]: 2.98998e-06 [label_micro_interleaved_index]: 5.99999e-06 [label_fine_grained_interleaved_index]: 2.71999e-06 [merge_cast_opt]: 1.35999e-06 [slice_recompute_activation]: 2.21e-06 [micro_interleaved_order_control]: 2.86e-06 [assign_add_opt]: 1.39e-06 [ForceFp32Comm]: 8.99978e-07 [remove_cast_before_assign_add]: 9.89996e-07 [full_micro_interleaved_order_control]: 2.17001e-06 [reorder_send_recv_between_fp_bp]: 3.06999e-06 [comm_op_add_attrs]: 1.09998e-06 [add_comm_op_reuse_tag]: 9.90025e-07 [interleave_split_concat_branches]: 1.12e-06 [interleave_parallel_branches]: 1.07998e-06 [overlap_opt_shard_in_pipeline]: 1.25999e-06 [overlap_opt_shard_grad_in_pipeline]: 1.95001e-06 [control_data_broadcast_order]: 3.444e-05 [grouped_pairwise_exchange_alltoall]: 1.42999e-06 [offloading_packed_experts]: 8.36002e-06 [overlap_recompute_and_grad_model_parallel]: 9.87999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.38002e-06 [overlap_recompute_allgather_and_fa_grad]: 1.25999e-06 [overlap_recompute_comm]: 2.96001e-06 [overlap_grad_ring_attention]: 9.68997e-06 [overlap_grad_flash_sp]: 4.492e-05 [begin_end_overlap_inline]: 5.3001e-07 [split_matmul_comm_elemetwise]: 2.29001e-06 [split_layernorm_comm]: 1.61002e-06 [handle_group_info]: 1.04998e-06 [symbol_engine_optimizer]: 0.00020031, [1] [Cycle 1]: 0.00019445, [6] [build]: 1.819e-05 [elim_shapecalc]: 3.08e-05 [elim_not_effective]: 4.255e-05 [opt_reshape]: 2.542e-05 [fold_const_symbol]: 3.494e-05 [renormalize]: 6.10016e-07 [detach_backward]: 2.51e-06 [pipeline_parallel_scheduler]: 1.57001e-06 [auto_monad_reorder]: 6.917e-05 [get_jit_bprop_graph]: 2.22999e-06 [rewriter_after_jit_bprop_graph]: 6.46e-06 [opt_after_jit_grad]: 0.0114219 [validate]: 0.00011279 Sums bootstrap : 0.000720s : 0.06% type_inference : 1.265093s : 97.50% event_method : 0.000014s : 0.00% auto_monad : 0.000305s : 0.02% graph_reusing : 0.000005s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000027s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000048s : 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 : 0.000039s : 0.00% optimize.rewriter_before_opt_a : 0.000097s : 0.01% optimize.opt_a.expand_dump_flag : 0.000006s : 0.00% optimize.opt_a.switch_simplify : 0.000059s : 0.00% optimize.opt_a.loop_unroll : 0.000045s : 0.00% optimize.opt_a.a_1 : 0.001708s : 0.13% optimize.opt_a.with_stream_mark : 0.000065s : 0.00% optimize.opt_a.recompute_prepare : 0.000049s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000023s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000023s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000099s : 0.01% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000689s : 0.05% optimize.opt_a.accelerated_algorithm : 0.000102s : 0.01% optimize.opt_a.shard : 0.000005s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000011s : 0.00% optimize.opt_a.shard_inline : 0.000040s : 0.00% optimize.opt_a.merge_send_recv : 0.000035s : 0.00% optimize.opt_a.auto_parallel : 0.000033s : 0.00% optimize.opt_a.parallel : 0.000041s : 0.00% optimize.opt_a.flash_sp : 0.000018s : 0.00% optimize.opt_a.merge_comm : 0.000022s : 0.00% optimize.opt_a.allreduce_fusion : 0.000020s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000042s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000049s : 0.00% optimize.opt_a.virtual_dataset : 0.000043s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000042s : 0.00% optimize.opt_a.virtual_output : 0.000040s : 0.00% optimize.opt_a.merge_forward : 0.000022s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000039s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000088s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000071s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000023s : 0.00% optimize.opt_a.meta_fg_expand : 0.000016s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000007s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000060s : 0.00% optimize.opt_a.a_after_grad : 0.000071s : 0.01% optimize.opt_a.renormalize : 0.011092s : 0.85% optimize.opt_a.add_forward_monad_depend : 0.000017s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000124s : 0.01% optimize.opt_a.cse : 0.000911s : 0.07% optimize.opt_a.a_3 : 0.000292s : 0.02% optimize.py_interpret_to_execute_after_opt_a : 0.000036s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000219s : 0.02% optimize.convert_after_rewriter : 0.000016s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000796s : 0.06% optimize.opt_b.b_1 : 0.000451s : 0.03% optimize.opt_b.b_2 : 0.000022s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000018s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000011s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000015s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000079s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000036s : 0.00% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000039s : 0.00% optimize.loop_unroll : 0.000600s : 0.05% optimize.opt_after_cconv.c_1 : 0.000141s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000010s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000013s : 0.00% optimize.opt_after_cconv.cse : 0.000069s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000086s : 0.01% optimize.tuple_transform.d_1 : 0.000149s : 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 : 0.000054s : 0.00% optimize.environ_conv : 0.000024s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000014s : 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 : 0.000001s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 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 : 0.000034s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000001s : 0.00% optimize.offloading_packed_experts : 0.000008s : 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 : 0.000003s : 0.00% optimize.overlap_grad_ring_attention : 0.000010s : 0.00% optimize.overlap_grad_flash_sp : 0.000045s : 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 : 0.000018s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000031s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000043s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000025s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000035s : 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 : 0.000069s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.011422s : 0.88% validate : 0.000113s : 0.01% Time group info: ------[substitution.] 0.000415 138 9.05% : 0.000038s : 4: substitution.arithmetic_simplify 2.84% : 0.000012s : 2: substitution.depend_value_elim 1.49% : 0.000006s : 11: substitution.elim_not_effective 1.04% : 0.000004s : 11: substitution.fold_const_symbol 3.34% : 0.000014s : 17: substitution.graph_param_transform 31.90% : 0.000132s : 1: substitution.inline 2.74% : 0.000011s : 22: substitution.j_node_and_user_rematch 6.97% : 0.000029s : 6: substitution.less_batch_normalization 1.93% : 0.000008s : 12: substitution.load_eliminater 0.42% : 0.000002s : 2: substitution.opt_reshape 4.58% : 0.000019s : 22: substitution.remove_not_recompute_node 2.41% : 0.000010s : 6: substitution.replace_old_param 7.47% : 0.000031s : 4: substitution.reshape_eliminate 3.64% : 0.000015s : 8: substitution.updatestate_pure_node_eliminater 20.19% : 0.000084s : 10: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.265002 2 99.59% : 1.259878s : 1: type_inference.infer 0.41% : 0.005123s : 1: type_inference.specialize ------[replace.] 0.000021 1 100.00% : 0.000021s : 1: replace.inline ------[match.] 0.000131 1 100.00% : 0.000131s : 1: match.inline ------[predicate.] 0.000574 3905 0.90% : 0.000005s : 35: predicate.accumulaten_eliminater 1.77% : 0.000010s : 17: predicate.ad_related_special_op_eliminate 0.77% : 0.000004s : 34: predicate.addn_check_dump 0.78% : 0.000004s : 35: predicate.addn_zero_filter 0.75% : 0.000004s : 35: predicate.adjust_all_reduce_mul_add 2.27% : 0.000013s : 69: predicate.arithmetic_simplify 0.81% : 0.000005s : 35: predicate.cast_eliminate 0.80% : 0.000005s : 34: predicate.check_bprop_eliminate 0.82% : 0.000005s : 34: predicate.compare_switch_simplify 0.24% : 0.000001s : 17: predicate.const_output_eliminate 0.81% : 0.000005s : 34: predicate.depend_value_elim 0.83% : 0.000005s : 35: predicate.dict_get_item_const_eliminator 0.91% : 0.000005s : 35: predicate.dict_get_item_eliminator 0.78% : 0.000005s : 35: predicate.dict_set_item_eliminator 1.34% : 0.000008s : 34: predicate.dumpgradient_eliminate 0.29% : 0.000002s : 17: predicate.elim_not_effective 0.59% : 0.000003s : 17: predicate.elim_shapecalc_of_broadcastargs 1.16% : 0.000007s : 52: predicate.environ_add_const_eliminate 1.11% : 0.000006s : 52: predicate.environ_get_add_eliminate 1.12% : 0.000006s : 52: predicate.environ_get_depend_swap 2.02% : 0.000012s : 86: predicate.environ_get_eliminate 1.11% : 0.000006s : 52: predicate.environ_get_set_eliminate 0.77% : 0.000004s : 36: predicate.exchange_switch_depend_value 1.23% : 0.000007s : 36: predicate.float_depend_g_call 0.82% : 0.000005s : 34: predicate.float_environ_get_switch 1.12% : 0.000006s : 51: predicate.float_tuple_getitem_switch 0.23% : 0.000001s : 17: predicate.fold_const_symbol 0.85% : 0.000005s : 34: predicate.get_grad_eliminate 0.30% : 0.000002s : 17: predicate.graph_param_transform 0.84% : 0.000005s : 34: predicate.incorporate_call 0.73% : 0.000004s : 34: predicate.incorporate_call_switch 5.44% : 0.000031s : 173: predicate.inline 1.14% : 0.000007s : 34: predicate.inline_without_move 0.44% : 0.000002s : 34: predicate.j_node_and_user_rematch 1.52% : 0.000009s : 34: predicate.less_batch_normalization 1.81% : 0.000010s : 69: predicate.list_to_tuple_eliminator_ 2.34% : 0.000013s : 104: predicate.load_eliminater 0.87% : 0.000005s : 17: predicate.loop_unroll_after_grad 0.96% : 0.000005s : 39: predicate.loop_unroll_before_grad 1.77% : 0.000010s : 69: predicate.make_slice_get_slice_eliminator 0.85% : 0.000005s : 34: predicate.merge_addn 0.76% : 0.000004s : 34: predicate.micro_step_allgather_replace 0.84% : 0.000005s : 34: predicate.mini_step_allgather_replace 0.74% : 0.000004s : 35: predicate.minmaximum_grad 1.02% : 0.000006s : 17: predicate.mutable_eliminate 0.55% : 0.000003s : 17: predicate.opt_reshape 0.45% : 0.000003s : 17: predicate.parallel_virtual_node 1.13% : 0.000007s : 36: predicate.partial_defer_inline 1.33% : 0.000008s : 52: predicate.partial_eliminate 0.82% : 0.000005s : 35: predicate.print_const_string_wrapper 0.80% : 0.000005s : 34: predicate.reduce_all_const_elim 1.09% : 0.000006s : 35: predicate.reduce_eliminate 2.25% : 0.000013s : 104: predicate.redundant_stop_gradient_eliminater 0.47% : 0.000003s : 34: predicate.remove_not_recompute_node 1.28% : 0.000007s : 69: predicate.replace_applicator 0.53% : 0.000003s : 34: predicate.replace_old_param 0.32% : 0.000002s : 17: predicate.reset_defer_inline 0.92% : 0.000005s : 35: predicate.reshape_eliminate 0.82% : 0.000005s : 34: predicate.row_tensor_add_zeros_like 0.48% : 0.000003s : 17: predicate.row_tensor_eliminate 1.08% : 0.000006s : 34: predicate.same_eliminate 0.56% : 0.000003s : 34: predicate.set_cell_output_no_recompute 0.90% : 0.000005s : 34: predicate.shard_identity_eliminate 0.86% : 0.000005s : 34: predicate.special_op_eliminate 0.95% : 0.000005s : 34: predicate.specialize_transform 1.04% : 0.000006s : 34: predicate.split_environ_get_set_with_tuple_value 1.00% : 0.000006s : 34: predicate.stack_unstack_eliminate 0.49% : 0.000003s : 17: predicate.switch_call_monad_eliminater 1.02% : 0.000006s : 36: predicate.switch_defer_inline 1.60% : 0.000009s : 70: predicate.switch_layer_defer_inline 3.45% : 0.000020s : 126: predicate.switch_simplify 0.79% : 0.000005s : 35: predicate.tile_eliminate 0.81% : 0.000005s : 35: predicate.transpose_eliminate 1.67% : 0.000010s : 69: predicate.tuple_list_convert_item_index_to_positive 1.73% : 0.000010s : 69: predicate.tuple_list_get_item_const_eliminator 1.62% : 0.000009s : 69: predicate.tuple_list_get_item_depend_reorder 2.83% : 0.000016s : 103: predicate.tuple_list_get_item_eliminator 1.64% : 0.000009s : 69: predicate.tuple_list_get_set_item_eliminator 2.67% : 0.000015s : 103: predicate.tuple_list_set_item_eliminator 1.75% : 0.000010s : 69: predicate.tuple_to_list_eliminator_ 2.28% : 0.000013s : 104: predicate.updatestate_pure_node_eliminater 3.54% : 0.000020s : 138: predicate.updatestate_useless_node_eliminater 0.50% : 0.000003s : 17: predicate.value_based_eliminate 0.90% : 0.000005s : 34: predicate.virtual_dataset_eliminate 0.84% : 0.000005s : 34: predicate.virtual_output_eliminate 0.41% : 0.000002s : 17: predicate.virtual_view_grad_eliminate 0.48% : 0.000003s : 17: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.172754 56 98.02% : 0.169341s : 53: func_graph_cloner_run.FuncGraphClonerGraph 1.98% : 0.003413s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.564843 192 0.00% : 0.000004s : 1: ForceFp32Comm 7.35% : 0.114995s : 1: add_attr 7.35% : 0.114971s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.01% : 0.000149s : 1: add_recomputation 0.00% : 0.000006s : 1: assign_add_opt 0.02% : 0.000315s : 1: auto_monad 0.00% : 0.000075s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.05% : 0.000752s : 1: bootstrap 0.00% : 0.000043s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000039s : 1: control_data_broadcast_order 0.00% : 0.000020s : 1: convert_after_rewriter 0.00% : 0.000073s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000028s : 1: environ_conv 0.00% : 0.000020s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000006s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000006s : 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 0.04% : 0.000611s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 0.05% : 0.000806s : 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 0.21% : 0.003299s : 78: opt.transform.opt_a 0.01% : 0.000139s : 1: opt.transform.opt_after_cconv 0.01% : 0.000103s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.000437s : 28: opt.transform.opt_b 0.01% : 0.000168s : 2: opt.transform.opt_trans_graph 0.01% : 0.000128s : 4: opt.transform.symbol_engine_opt 1.07% : 0.016810s : 1: opt_a 0.02% : 0.000311s : 1: opt_after_cconv 0.73% : 0.011445s : 1: opt_after_jit_grad 0.04% : 0.000653s : 1: opt_b 1.33% : 0.020841s : 1: optimize 0.00% : 0.000040s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000016s : 1: order_py_execute_after_rewriter 0.00% : 0.000049s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000005s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000007s : 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% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000052s : 1: pre_auto_parallel 0.00% : 0.000043s : 1: py_interpret_to_execute 0.00% : 0.000040s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000092s : 1: remove_dup_value 0.46% : 0.007223s : 1: renormalize.infer 0.25% : 0.003849s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000227s : 1: rewriter_after_opt_a 0.01% : 0.000101s : 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% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000018s : 1: swap_dp_allreduce_reducescatter 0.01% : 0.000204s : 1: symbol_engine_optimizer 0.01% : 0.000210s : 1: tuple_transform 80.85% : 1.265116s : 1: type_inference . [hook] pytest_runtest_teardown:test_matmul_ffn_1[False-mstype0-k_n_shape0-1024] tests/st/infer/ops/test_internal_ops/test_matmul_biasadd_split.py::test_matmul_ffn_1[False-mstype0-k_n_shape0-1024],max_mem:438.0M =============================== 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") test_matmul_biasadd_split.py::test_matmul_ffn_1[False-mstype0-k_n_shape0-1024] /home/jenkins/mindspore/testcases/testcases/tests/st/infer/ops/test_internal_ops/st_utils.py:39: RuntimeWarning: divide by zero encountered in divide err_cnt = np.sum(np.abs(out_flatten - expect_flatten) / -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 3 passed, 26 warnings in 391.61s (0:06:31) ==================