==================================================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/graph_kernel, configfile: ../../../../../../sault/virtual_test/virtualenv_002/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_mix_precision.py [WARNING] ME(165576:281473696620336,MainProcess):2026-01-29-17:37:35.231.957 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS instead. [WARNING] ME(165576:281473696620336,MainProcess):2026-01-29-17:37:35.232.450 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs_path' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS_PATH instead. TotalTime = 0.710639, [21] [bootstrap]: 0.00060499 [type_inference]: 0.587087 [event_method]: 2.567e-05 [auto_monad]: 0.0001207 [graph_reusing]: 6.53e-06 [inline]: 2.76e-06 [add_attr]: 0.00804995, [1] [add_attr_with_inline]: 0.00803556, [1] [Cycle 1]: 0.00019087, [2] [tag_attr]: 2.537e-05 [meta_addattr_fg_expand]: 7.98001e-06 [parallel-infer-symbol]: 4.11001e-06 [pre_auto_parallel]: 4.624e-05 [insert-virtual-dataset]: 2.42001e-06 [parallel-infer-symbol-second]: 7.60017e-07 [dataset_repeat_opt]: 2.38002e-06 [pipeline_split]: 1.92999e-06 [optimize]: 0.00873318, [53] [py_interpret_to_execute]: 3.719e-05 [rewriter_before_opt_a]: 0.00010245 [opt_a]: 0.00527492, [2] [Cycle 1]: 0.00370165, [45] [expand_dump_flag]: 3.76999e-06 [switch_simplify]: 5.076e-05 [loop_unroll]: 3.862e-05 [a_1]: 0.00105415 [with_stream_mark]: 2.123e-05 [recompute_prepare]: 1.617e-05 [updatestate_depend_eliminate]: 7.68999e-06 [updatestate_assign_eliminate]: 6.86999e-06 [updatestate_loads_eliminate]: 6.36e-06 [parameter_eliminate]: 2.18002e-06 [a_2]: 0.00023804 [accelerated_algorithm]: 3.222e-05 [shard]: 1.93002e-06 [meta_shard_fg_expand]: 2.96999e-06 [shard_inline]: 1.38e-05 [merge_send_recv]: 1.22e-05 [auto_parallel]: 1.172e-05 [parallel]: 5.24e-05 [flash_sp]: 1.942e-05 [merge_comm]: 8.44998e-06 [allreduce_fusion]: 7.18998e-06 [matmul_add_comm_reduction]: 1.615e-05 [allreduce_slice_to_reducescatter]: 6.60017e-07 [virtual_shard_identity]: 1.763e-05 [virtual_dataset]: 1.383e-05 [get_grad_eliminate_]: 1.356e-05 [virtual_output]: 2.744e-05 [merge_forward]: 1.004e-05 [cell_reuse_recompute_pass]: 1.43002e-06 [offload_activation]: 1.661e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.987e-05 [merge_recompute_call_nodes]: 1.57001e-06 [before_grad]: 2.297e-05 [set_forward_comm_id_for_comm_node_pass]: 8.02998e-06 [meta_fg_expand]: 5.27999e-06 [flash_sp_send_recv_attached]: 6.06998e-06 [receive_attached]: 2.88998e-06 [after_resolve]: 2.443e-05 [a_after_grad]: 2.262e-05 [renormalize]: 0.0011577 [add_forward_monad_depend]: 9.29e-06 [auto_monad_grad]: 2.55002e-06 [auto_monad_eliminator]: 3.443e-05 [cse]: 9.979e-05 [a_3]: 0.00011983 [Cycle 2]: 0.00155413, [45] [expand_dump_flag]: 3.06001e-06 [switch_simplify]: 1.53e-05 [loop_unroll]: 1.38e-05 [a_1]: 0.00041987 [with_stream_mark]: 1.973e-05 [recompute_prepare]: 1.359e-05 [updatestate_depend_eliminate]: 8.18999e-06 [updatestate_assign_eliminate]: 6.64001e-06 [updatestate_loads_eliminate]: 6.29999e-06 [parameter_eliminate]: 1.55999e-06 [a_2]: 0.0002263 [accelerated_algorithm]: 2.239e-05 [shard]: 2.08002e-06 [meta_shard_fg_expand]: 3.56001e-06 [shard_inline]: 1.371e-05 [merge_send_recv]: 1.281e-05 [auto_parallel]: 1.329e-05 [parallel]: 8.60001e-06 [flash_sp]: 3.41999e-06 [merge_comm]: 7.58999e-06 [allreduce_fusion]: 7.06001e-06 [matmul_add_comm_reduction]: 1.704e-05 [allreduce_slice_to_reducescatter]: 7.29982e-07 [virtual_shard_identity]: 1.575e-05 [virtual_dataset]: 1.313e-05 [get_grad_eliminate_]: 1.31e-05 [virtual_output]: 1.279e-05 [merge_forward]: 7.31999e-06 [cell_reuse_recompute_pass]: 2.21e-06 [offload_activation]: 1.646e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.623e-05 [merge_recompute_call_nodes]: 1.39e-06 [before_grad]: 2.206e-05 [set_forward_comm_id_for_comm_node_pass]: 7.89002e-06 [meta_fg_expand]: 5.04998e-06 [flash_sp_send_recv_attached]: 1.49e-06 [receive_attached]: 2.54001e-06 [after_resolve]: 2.264e-05 [a_after_grad]: 2.195e-05 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 2.85998e-06 [auto_monad_grad]: 2.37001e-06 [auto_monad_eliminator]: 1.904e-05 [cse]: 4.572e-05 [a_3]: 9.988e-05 [py_interpret_to_execute_after_opt_a]: 2.355e-05 [slice_cell_reuse_recomputed_activation]: 5.07e-06 [rewriter_after_opt_a]: 0.00010774 [convert_after_rewriter]: 1.654e-05 [order_py_execute_after_rewriter]: 1.183e-05 [mutable_eliminate]: 0.00076794 [opt_b]: 0.00049897, [1] [Cycle 1]: 0.00048607, [7] [b_1]: 0.00033623 [b_2]: 1.577e-05 [updatestate_depend_eliminate]: 1.314e-05 [updatestate_assign_eliminate]: 6.29001e-06 [updatestate_loads_eliminate]: 6.34999e-06 [renormalize]: 7.2e-07 [cse]: 4.86e-05 [optimize_parallel_all_gather_comm]: 3.191e-05 [overlap_param_gather]: 5.35999e-06 [cconv]: 4.292e-05 [loop_unroll]: 0.00053091 [opt_after_cconv]: 0.00022031, [1] [Cycle 1]: 0.00020923, [7] [c_1]: 7.732e-05 [parameter_eliminate]: 5.22e-06 [updatestate_depend_eliminate]: 1.16e-05 [updatestate_assign_eliminate]: 6.21e-06 [updatestate_loads_eliminate]: 6.19999e-06 [cse]: 4.519e-05 [renormalize]: 6.19999e-07 [remove_dup_value]: 6.688e-05 [tuple_transform]: 0.00016576, [1] [Cycle 1]: 0.00015769, [4] [d_1]: 0.00011059 [none_parameter_eliminate]: 1.64e-06 [renormalize]: 2.19996e-07 [switch_simplify]: 1.411e-05 [partial_unused_args_eliminate]: 4.68001e-06 [add_recomputation]: 0.00010319 [cse_after_recomputation]: 4.831e-05, [1] [Cycle 1]: 4.072e-05, [1] [cse]: 3.034e-05 [environ_conv]: 2.767e-05 [swap_dp_allreduce_reducescatter]: 1.292e-05 [bias_add_comm_swap]: 6.03002e-06 [label_micro_interleaved_index]: 9.10001e-06 [label_fine_grained_interleaved_index]: 5.20999e-06 [merge_cast_opt]: 4.01001e-06 [slice_recompute_activation]: 4.37998e-06 [micro_interleaved_order_control]: 5.00999e-06 [assign_add_opt]: 4.16001e-06 [ForceFp32Comm]: 3.91999e-06 [remove_cast_before_assign_add]: 3.56999e-06 [full_micro_interleaved_order_control]: 4.55999e-06 [reorder_send_recv_between_fp_bp]: 5.46002e-06 [comm_op_add_attrs]: 3.97998e-06 [add_comm_op_reuse_tag]: 3.31001e-06 [interleave_split_concat_branches]: 3.75e-06 [interleave_parallel_branches]: 3.41999e-06 [overlap_opt_shard_in_pipeline]: 2.751e-05 [overlap_opt_shard_grad_in_pipeline]: 4.31002e-06 [control_data_broadcast_order]: 3.052e-05 [grouped_pairwise_exchange_alltoall]: 4.42998e-06 [offloading_packed_experts]: 9.37001e-06 [overlap_recompute_and_grad_model_parallel]: 9.90002e-06 [overlap_grad_matmul_and_grad_allreduce]: 3.70998e-06 [overlap_recompute_allgather_and_fa_grad]: 3.98001e-06 [overlap_recompute_comm]: 5.12e-06 [overlap_grad_ring_attention]: 9.20999e-06 [overlap_grad_flash_sp]: 5.397e-05 [begin_end_overlap_inline]: 3.03998e-06 [split_matmul_comm_elemetwise]: 4.99998e-06 [split_layernorm_comm]: 4.35999e-06 [handle_group_info]: 3.59002e-06 [symbol_engine_optimizer]: 0.0001466, [1] [Cycle 1]: 0.00013885, [6] [build]: 6.16e-06 [elim_shapecalc]: 1.942e-05 [elim_not_effective]: 2.643e-05 [opt_reshape]: 1.462e-05 [fold_const_symbol]: 2.243e-05 [renormalize]: 1.40019e-07 [detach_backward]: 5.14e-06 [pipeline_parallel_scheduler]: 1.96003e-06 [auto_monad_reorder]: 4.118e-05 [get_jit_bprop_graph]: 1.75001e-06 [rewriter_after_jit_bprop_graph]: 4.76002e-06 [opt_after_jit_grad]: 0.10492 [validate]: 9.387e-05 Sums bootstrap : 0.000605s : 0.09% type_inference : 0.587087s : 83.81% event_method : 0.000026s : 0.00% auto_monad : 0.000121s : 0.02% graph_reusing : 0.000007s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000025s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000008s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000046s : 0.01% 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 : 0.000037s : 0.01% optimize.rewriter_before_opt_a : 0.000102s : 0.01% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000066s : 0.01% optimize.opt_a.loop_unroll : 0.000052s : 0.01% optimize.opt_a.a_1 : 0.001474s : 0.21% optimize.opt_a.with_stream_mark : 0.000041s : 0.01% optimize.opt_a.recompute_prepare : 0.000030s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000016s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000014s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000013s : 0.00% optimize.opt_a.parameter_eliminate : 0.000004s : 0.00% optimize.opt_a.a_2 : 0.000464s : 0.07% optimize.opt_a.accelerated_algorithm : 0.000055s : 0.01% optimize.opt_a.shard : 0.000004s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000007s : 0.00% optimize.opt_a.shard_inline : 0.000028s : 0.00% optimize.opt_a.merge_send_recv : 0.000025s : 0.00% optimize.opt_a.auto_parallel : 0.000025s : 0.00% optimize.opt_a.parallel : 0.000061s : 0.01% optimize.opt_a.flash_sp : 0.000023s : 0.00% optimize.opt_a.merge_comm : 0.000016s : 0.00% optimize.opt_a.allreduce_fusion : 0.000014s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000033s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000001s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000033s : 0.00% optimize.opt_a.virtual_dataset : 0.000027s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000027s : 0.00% optimize.opt_a.virtual_output : 0.000040s : 0.01% optimize.opt_a.merge_forward : 0.000017s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% optimize.opt_a.offload_activation : 0.000033s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000056s : 0.01% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000045s : 0.01% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000016s : 0.00% optimize.opt_a.meta_fg_expand : 0.000010s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000047s : 0.01% optimize.opt_a.a_after_grad : 0.000045s : 0.01% optimize.opt_a.renormalize : 0.001158s : 0.17% optimize.opt_a.add_forward_monad_depend : 0.000012s : 0.00% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000053s : 0.01% optimize.opt_a.cse : 0.000146s : 0.02% optimize.opt_a.a_3 : 0.000220s : 0.03% optimize.py_interpret_to_execute_after_opt_a : 0.000024s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000005s : 0.00% optimize.rewriter_after_opt_a : 0.000108s : 0.02% optimize.convert_after_rewriter : 0.000017s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.000768s : 0.11% optimize.opt_b.b_1 : 0.000336s : 0.05% optimize.opt_b.b_2 : 0.000016s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000013s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000049s : 0.01% optimize.optimize_parallel_all_gather_comm : 0.000032s : 0.00% optimize.overlap_param_gather : 0.000005s : 0.00% optimize.cconv : 0.000043s : 0.01% optimize.loop_unroll : 0.000531s : 0.08% optimize.opt_after_cconv.c_1 : 0.000077s : 0.01% optimize.opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.cse : 0.000045s : 0.01% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000067s : 0.01% optimize.tuple_transform.d_1 : 0.000111s : 0.02% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000014s : 0.00% optimize.partial_unused_args_eliminate : 0.000005s : 0.00% optimize.add_recomputation : 0.000103s : 0.01% optimize.cse_after_recomputation.cse : 0.000030s : 0.00% optimize.environ_conv : 0.000028s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000013s : 0.00% optimize.bias_add_comm_swap : 0.000006s : 0.00% optimize.label_micro_interleaved_index : 0.000009s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000005s : 0.00% optimize.merge_cast_opt : 0.000004s : 0.00% optimize.slice_recompute_activation : 0.000004s : 0.00% optimize.micro_interleaved_order_control : 0.000005s : 0.00% optimize.assign_add_opt : 0.000004s : 0.00% optimize.ForceFp32Comm : 0.000004s : 0.00% optimize.remove_cast_before_assign_add : 0.000004s : 0.00% optimize.full_micro_interleaved_order_control : 0.000005s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000005s : 0.00% optimize.comm_op_add_attrs : 0.000004s : 0.00% optimize.add_comm_op_reuse_tag : 0.000003s : 0.00% optimize.interleave_split_concat_branches : 0.000004s : 0.00% optimize.interleave_parallel_branches : 0.000003s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000028s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000004s : 0.00% optimize.control_data_broadcast_order : 0.000031s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000004s : 0.00% optimize.offloading_packed_experts : 0.000009s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000004s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000004s : 0.00% optimize.overlap_recompute_comm : 0.000005s : 0.00% optimize.overlap_grad_ring_attention : 0.000009s : 0.00% optimize.overlap_grad_flash_sp : 0.000054s : 0.01% optimize.begin_end_overlap_inline : 0.000003s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000005s : 0.00% optimize.split_layernorm_comm : 0.000004s : 0.00% optimize.handle_group_info : 0.000004s : 0.00% optimize.symbol_engine_optimizer.build : 0.000006s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000019s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000015s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000022s : 0.00% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000005s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000041s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.104920s : 14.98% validate : 0.000094s : 0.01% Time group info: ------[substitution.] 0.000480 113 17.63% : 0.000085s : 28: substitution.arithmetic_simplify 6.29% : 0.000030s : 3: substitution.cast_eliminate 0.79% : 0.000004s : 8: substitution.elim_not_effective 0.66% : 0.000003s : 8: substitution.fold_const_symbol 2.48% : 0.000012s : 13: substitution.graph_param_transform 62.39% : 0.000299s : 7: substitution.inline 1.67% : 0.000008s : 16: substitution.j_node_and_user_rematch 3.72% : 0.000018s : 4: substitution.less_batch_normalization 2.54% : 0.000012s : 16: substitution.remove_not_recompute_node 1.85% : 0.000009s : 10: substitution.replace_old_param ------[type_inference.] 0.587005 2 99.80% : 0.585840s : 1: type_inference.infer 0.20% : 0.001164s : 1: type_inference.specialize ------[replace.] 0.000058 7 100.00% : 0.000058s : 7: replace.inline ------[match.] 0.000295 7 100.00% : 0.000295s : 7: match.inline ------[predicate.] 0.000473 3331 0.89% : 0.000004s : 32: predicate.accumulaten_eliminater 0.74% : 0.000003s : 13: predicate.ad_related_special_op_eliminate 0.72% : 0.000003s : 26: predicate.addn_check_dump 0.92% : 0.000004s : 32: predicate.addn_zero_filter 0.78% : 0.000004s : 32: predicate.adjust_all_reduce_mul_add 2.94% : 0.000014s : 58: predicate.arithmetic_simplify 0.86% : 0.000004s : 32: predicate.cast_eliminate 0.72% : 0.000003s : 26: predicate.check_bprop_eliminate 0.78% : 0.000004s : 26: predicate.compare_switch_simplify 0.21% : 0.000001s : 13: predicate.const_output_eliminate 0.77% : 0.000004s : 26: predicate.depend_value_elim 0.92% : 0.000004s : 32: predicate.dict_get_item_const_eliminator 1.01% : 0.000005s : 32: predicate.dict_get_item_eliminator 0.83% : 0.000004s : 32: predicate.dict_set_item_eliminator 1.22% : 0.000006s : 26: predicate.dumpgradient_eliminate 0.22% : 0.000001s : 13: predicate.elim_not_effective 0.49% : 0.000002s : 13: predicate.elim_shapecalc_of_broadcastargs 1.20% : 0.000006s : 45: predicate.environ_add_const_eliminate 1.20% : 0.000006s : 45: predicate.environ_get_add_eliminate 1.24% : 0.000006s : 45: predicate.environ_get_depend_swap 1.97% : 0.000009s : 71: predicate.environ_get_eliminate 1.24% : 0.000006s : 45: predicate.environ_get_set_eliminate 1.04% : 0.000005s : 39: predicate.exchange_switch_depend_value 1.61% : 0.000008s : 39: predicate.float_depend_g_call 0.72% : 0.000003s : 26: predicate.float_environ_get_switch 1.19% : 0.000006s : 39: predicate.float_tuple_getitem_switch 0.22% : 0.000001s : 13: predicate.fold_const_symbol 0.87% : 0.000004s : 26: predicate.get_grad_eliminate 0.23% : 0.000001s : 13: predicate.graph_param_transform 0.71% : 0.000003s : 26: predicate.incorporate_call 0.64% : 0.000003s : 26: predicate.incorporate_call_switch 5.64% : 0.000027s : 149: predicate.inline 1.03% : 0.000005s : 26: predicate.inline_without_move 0.42% : 0.000002s : 26: predicate.j_node_and_user_rematch 1.00% : 0.000005s : 26: predicate.less_batch_normalization 1.65% : 0.000008s : 58: predicate.list_to_tuple_eliminator_ 2.37% : 0.000011s : 90: predicate.load_eliminater 0.84% : 0.000004s : 13: predicate.loop_unroll_after_grad 1.63% : 0.000008s : 60: predicate.loop_unroll_before_grad 1.74% : 0.000008s : 58: predicate.make_slice_get_slice_eliminator 0.75% : 0.000004s : 26: predicate.merge_addn 0.75% : 0.000004s : 26: predicate.micro_step_allgather_replace 0.72% : 0.000003s : 26: predicate.mini_step_allgather_replace 0.79% : 0.000004s : 32: predicate.minmaximum_grad 1.13% : 0.000005s : 13: predicate.mutable_eliminate 0.46% : 0.000002s : 13: predicate.opt_reshape 0.44% : 0.000002s : 13: predicate.parallel_virtual_node 1.35% : 0.000006s : 39: predicate.partial_defer_inline 1.29% : 0.000006s : 45: predicate.partial_eliminate 0.84% : 0.000004s : 32: predicate.print_const_string_wrapper 0.71% : 0.000003s : 26: predicate.reduce_all_const_elim 1.06% : 0.000005s : 32: predicate.reduce_eliminate 2.37% : 0.000011s : 90: predicate.redundant_stop_gradient_eliminater 0.46% : 0.000002s : 26: predicate.remove_not_recompute_node 1.19% : 0.000006s : 58: predicate.replace_applicator 0.52% : 0.000002s : 26: predicate.replace_old_param 0.34% : 0.000002s : 13: predicate.reset_defer_inline 0.88% : 0.000004s : 32: predicate.reshape_eliminate 0.75% : 0.000004s : 26: predicate.row_tensor_add_zeros_like 0.45% : 0.000002s : 13: predicate.row_tensor_eliminate 0.85% : 0.000004s : 26: predicate.same_eliminate 0.46% : 0.000002s : 26: predicate.set_cell_output_no_recompute 1.04% : 0.000005s : 26: predicate.shard_identity_eliminate 0.83% : 0.000004s : 26: predicate.special_op_eliminate 0.87% : 0.000004s : 26: predicate.specialize_transform 1.11% : 0.000005s : 26: predicate.split_environ_get_set_with_tuple_value 0.98% : 0.000005s : 26: predicate.stack_unstack_eliminate 0.43% : 0.000002s : 13: predicate.switch_call_monad_eliminater 1.16% : 0.000005s : 39: predicate.switch_defer_inline 1.86% : 0.000009s : 65: predicate.switch_layer_defer_inline 4.04% : 0.000019s : 138: predicate.switch_simplify 0.85% : 0.000004s : 32: predicate.tile_eliminate 0.82% : 0.000004s : 32: predicate.transpose_eliminate 1.67% : 0.000008s : 58: predicate.tuple_list_convert_item_index_to_positive 1.63% : 0.000008s : 58: predicate.tuple_list_get_item_const_eliminator 1.53% : 0.000007s : 58: predicate.tuple_list_get_item_depend_reorder 2.82% : 0.000013s : 84: predicate.tuple_list_get_item_eliminator 1.58% : 0.000007s : 58: predicate.tuple_list_get_set_item_eliminator 2.47% : 0.000012s : 84: predicate.tuple_list_set_item_eliminator 1.65% : 0.000008s : 58: predicate.tuple_to_list_eliminator_ 2.41% : 0.000011s : 90: predicate.updatestate_pure_node_eliminater 3.26% : 0.000015s : 116: predicate.updatestate_useless_node_eliminater 0.56% : 0.000003s : 13: predicate.value_based_eliminate 0.83% : 0.000004s : 26: predicate.virtual_dataset_eliminate 0.76% : 0.000004s : 26: predicate.virtual_output_eliminate 0.38% : 0.000002s : 13: predicate.virtual_view_grad_eliminate 0.47% : 0.000002s : 13: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000577 10 4.21% : 0.000024s : 1: func_graph_cloner_run.FuncGraphClonerGraph 10.13% : 0.000058s : 1: func_graph_cloner_run.FuncGraphClonerNode 85.66% : 0.000494s : 8: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.731555 192 0.00% : 0.000007s : 1: ForceFp32Comm 1.10% : 0.008062s : 1: add_attr 1.10% : 0.008040s : 1: add_attr_with_inline 0.00% : 0.000006s : 1: add_comm_op_reuse_tag 0.01% : 0.000108s : 1: add_recomputation 0.00% : 0.000007s : 1: assign_add_opt 0.02% : 0.000132s : 1: auto_monad 0.01% : 0.000050s : 1: auto_monad_reorder 0.00% : 0.000006s : 1: begin_end_overlap_inline 0.00% : 0.000009s : 1: bias_add_comm_swap 0.09% : 0.000674s : 1: bootstrap 0.01% : 0.000047s : 1: cconv 0.00% : 0.000007s : 1: comm_op_add_attrs 0.00% : 0.000033s : 1: control_data_broadcast_order 0.00% : 0.000020s : 1: convert_after_rewriter 0.01% : 0.000052s : 1: cse_after_recomputation 0.00% : 0.000008s : 1: dataset_repeat_opt 0.00% : 0.000031s : 1: detach_backward 0.00% : 0.000032s : 1: environ_conv 0.00% : 0.000036s : 1: event_method 0.00% : 0.000007s : 1: full_micro_interleaved_order_control 0.00% : 0.000008s : 1: get_jit_bprop_graph 0.00% : 0.000013s : 1: graph_reusing 0.00% : 0.000007s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000006s : 1: handle_group_info 0.00% : 0.000009s : 1: inline 0.00% : 0.000009s : 1: insert-virtual-dataset 0.00% : 0.000006s : 1: interleave_parallel_branches 0.00% : 0.000007s : 1: interleave_split_concat_branches 0.00% : 0.000008s : 1: label_fine_grained_interleaved_index 0.00% : 0.000012s : 1: label_micro_interleaved_index 0.07% : 0.000538s : 1: loop_unroll 0.00% : 0.000007s : 1: merge_cast_opt 0.00% : 0.000008s : 1: micro_interleaved_order_control 0.11% : 0.000777s : 1: mutable_eliminate 0.00% : 0.000012s : 1: offloading_packed_experts 0.00% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000029s : 1: opt.transform.mutable_eliminate 0.34% : 0.002520s : 78: opt.transform.opt_a 0.01% : 0.000076s : 1: opt.transform.opt_after_cconv 0.01% : 0.000056s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000280s : 28: opt.transform.opt_b 0.02% : 0.000122s : 2: opt.transform.opt_trans_graph 0.01% : 0.000079s : 4: opt.transform.symbol_engine_opt 0.72% : 0.005279s : 1: opt_a 0.03% : 0.000224s : 1: opt_after_cconv 14.35% : 0.104943s : 1: opt_after_jit_grad 0.07% : 0.000503s : 1: opt_b 1.27% : 0.009292s : 1: optimize 0.00% : 0.000035s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.01% : 0.000057s : 1: overlap_grad_flash_sp 0.00% : 0.000006s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000013s : 1: overlap_grad_ring_attention 0.00% : 0.000008s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000031s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000009s : 1: overlap_param_gather 0.00% : 0.000007s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000008s : 1: overlap_recompute_comm 0.00% : 0.000011s : 1: parallel-infer-symbol 0.00% : 0.000006s : 1: parallel-infer-symbol-second 0.00% : 0.000008s : 1: partial_unused_args_eliminate 0.00% : 0.000011s : 1: pipeline_parallel_scheduler 0.00% : 0.000007s : 1: pipeline_split 0.01% : 0.000054s : 1: pre_auto_parallel 0.01% : 0.000041s : 1: py_interpret_to_execute 0.00% : 0.000027s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000006s : 1: remove_cast_before_assign_add 0.01% : 0.000070s : 1: remove_dup_value 0.09% : 0.000655s : 1: renormalize.infer 0.07% : 0.000491s : 1: renormalize.specialize 0.00% : 0.000008s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000114s : 1: rewriter_after_opt_a 0.01% : 0.000106s : 1: rewriter_before_opt_a 0.00% : 0.000008s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000007s : 1: slice_recompute_activation 0.00% : 0.000007s : 1: split_layernorm_comm 0.00% : 0.000008s : 1: split_matmul_comm_elemetwise 0.00% : 0.000016s : 1: swap_dp_allreduce_reducescatter 0.02% : 0.000150s : 1: symbol_engine_optimizer 0.02% : 0.000169s : 1: tuple_transform 80.26% : 0.587137s : 1: type_inference [WARNING] ME(165576:281473696620336,MainProcess):2026-01-29-17:38:09.603.026 [mindspore/context.py:1334] For 'context.set_context', the parameter 'save_graphs' will be deprecated and removed in a future version. Please use the env MS_DEV_SAVE_GRAPHS instead. TotalTime = 0.399697, [21] [bootstrap]: 0.00620644 [type_inference]: 0.205719 [event_method]: 0.00497941 [auto_monad]: 0.00013491 [graph_reusing]: 7.80998e-06 [inline]: 2.94999e-06 [add_attr]: 0.0531475, [1] [add_attr_with_inline]: 0.0531304, [1] [Cycle 1]: 0.00012219, [2] [tag_attr]: 5.702e-05 [meta_addattr_fg_expand]: 1.62e-05 [parallel-infer-symbol]: 4.73001e-06 [pre_auto_parallel]: 5.36e-05 [insert-virtual-dataset]: 2.98e-06 [parallel-infer-symbol-second]: 6.30011e-07 [dataset_repeat_opt]: 2.21e-06 [pipeline_split]: 2.09e-06 [optimize]: 0.112511, [53] [py_interpret_to_execute]: 4.801e-05 [rewriter_before_opt_a]: 0.00010325 [opt_a]: 0.0776225, [2] [Cycle 1]: 0.0545973, [45] [expand_dump_flag]: 3.45e-06 [switch_simplify]: 5.487e-05 [loop_unroll]: 4.001e-05 [a_1]: 0.0176403 [with_stream_mark]: 5.119e-05 [recompute_prepare]: 2.741e-05 [updatestate_depend_eliminate]: 8.55999e-06 [updatestate_assign_eliminate]: 7.05e-06 [updatestate_loads_eliminate]: 6.31e-06 [parameter_eliminate]: 2.39999e-06 [a_2]: 0.00439769 [accelerated_algorithm]: 5.913e-05 [shard]: 2.79001e-06 [meta_shard_fg_expand]: 8.16002e-06 [shard_inline]: 1.501e-05 [merge_send_recv]: 1.508e-05 [auto_parallel]: 1.678e-05 [parallel]: 3.737e-05 [flash_sp]: 1.513e-05 [merge_comm]: 7.94002e-06 [allreduce_fusion]: 7.87003e-06 [matmul_add_comm_reduction]: 1.873e-05 [allreduce_slice_to_reducescatter]: 7.99977e-07 [virtual_shard_identity]: 1.677e-05 [virtual_dataset]: 1.401e-05 [get_grad_eliminate_]: 1.423e-05 [virtual_output]: 0.00897491 [merge_forward]: 2.911e-05 [cell_reuse_recompute_pass]: 3.07002e-06 [offload_activation]: 3.069e-05 [cell_reuse_handle_not_recompute_node_pass]: 5.394e-05 [merge_recompute_call_nodes]: 2.98e-06 [before_grad]: 2.599e-05 [set_forward_comm_id_for_comm_node_pass]: 1.438e-05 [meta_fg_expand]: 1.188e-05 [flash_sp_send_recv_attached]: 1.349e-05 [receive_attached]: 2.49001e-06 [after_resolve]: 2.682e-05 [a_after_grad]: 0.00406279 [renormalize]: 0.0179402 [add_forward_monad_depend]: 1.556e-05 [auto_monad_grad]: 3.03e-06 [auto_monad_eliminator]: 4.35e-05 [cse]: 0.00018894 [a_3]: 0.00012395 [Cycle 2]: 0.0230083, [45] [expand_dump_flag]: 3.16001e-06 [switch_simplify]: 1.653e-05 [loop_unroll]: 1.382e-05 [a_1]: 0.00810681 [with_stream_mark]: 4.573e-05 [recompute_prepare]: 2.363e-05 [updatestate_depend_eliminate]: 1.018e-05 [updatestate_assign_eliminate]: 7.47002e-06 [updatestate_loads_eliminate]: 6.44999e-06 [parameter_eliminate]: 2.54001e-06 [a_2]: 0.00021009 [accelerated_algorithm]: 0.00510407 [shard]: 5.47999e-06 [meta_shard_fg_expand]: 9.61998e-06 [shard_inline]: 2.741e-05 [merge_send_recv]: 2.676e-05 [auto_parallel]: 1.942e-05 [parallel]: 1.041e-05 [flash_sp]: 5.44e-06 [merge_comm]: 8.13001e-06 [allreduce_fusion]: 7.58001e-06 [matmul_add_comm_reduction]: 2.325e-05 [allreduce_slice_to_reducescatter]: 8.49977e-07 [virtual_shard_identity]: 1.644e-05 [virtual_dataset]: 1.505e-05 [get_grad_eliminate_]: 1.38e-05 [virtual_output]: 1.418e-05 [merge_forward]: 8.33001e-06 [cell_reuse_recompute_pass]: 3.29001e-06 [offload_activation]: 3.311e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.303e-05 [merge_recompute_call_nodes]: 1.65001e-06 [before_grad]: 2.49e-05 [set_forward_comm_id_for_comm_node_pass]: 8.34002e-06 [meta_fg_expand]: 7.30998e-06 [flash_sp_send_recv_attached]: 1.89e-06 [receive_attached]: 2.39001e-06 [after_resolve]: 2.549e-05 [a_after_grad]: 6.575e-05 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 7.61999e-06 [auto_monad_grad]: 3.25998e-06 [auto_monad_eliminator]: 3.349e-05 [cse]: 6.927e-05 [a_3]: 0.00099827 [py_interpret_to_execute_after_opt_a]: 3.046e-05 [slice_cell_reuse_recomputed_activation]: 3.63999e-06 [rewriter_after_opt_a]: 7.643e-05 [convert_after_rewriter]: 1.206e-05 [order_py_execute_after_rewriter]: 1.008e-05 [mutable_eliminate]: 0.00980306 [opt_b]: 0.00703559, [1] [Cycle 1]: 0.00702086, [7] [b_1]: 0.00031382 [b_2]: 1.799e-05 [updatestate_depend_eliminate]: 1.893e-05 [updatestate_assign_eliminate]: 6.33998e-06 [updatestate_loads_eliminate]: 4.414e-05 [renormalize]: 6.89994e-07 [cse]: 8.496e-05 [optimize_parallel_all_gather_comm]: 3.793e-05 [overlap_param_gather]: 2.19999e-06 [cconv]: 4.353e-05 [loop_unroll]: 0.00847485 [opt_after_cconv]: 0.00028458, [1] [Cycle 1]: 0.00027145, [7] [c_1]: 0.00010072 [parameter_eliminate]: 8.13001e-06 [updatestate_depend_eliminate]: 2.126e-05 [updatestate_assign_eliminate]: 7.8e-06 [updatestate_loads_eliminate]: 6.82002e-06 [cse]: 8.425e-05 [renormalize]: 1.16002e-06 [remove_dup_value]: 7.532e-05 [tuple_transform]: 0.00018412, [1] [Cycle 1]: 0.00017812, [4] [d_1]: 0.00013625 [none_parameter_eliminate]: 2.24999e-06 [renormalize]: 1.8999e-07 [switch_simplify]: 1.743e-05 [partial_unused_args_eliminate]: 2.84001e-06 [add_recomputation]: 0.00011067 [cse_after_recomputation]: 0.00783889, [1] [Cycle 1]: 0.00783005, [1] [cse]: 0.0077839 [environ_conv]: 1.713e-05 [swap_dp_allreduce_reducescatter]: 3.41e-05 [bias_add_comm_swap]: 3.83999e-06 [label_micro_interleaved_index]: 8.83001e-06 [label_fine_grained_interleaved_index]: 2.66e-06 [merge_cast_opt]: 1.71002e-06 [slice_recompute_activation]: 2.09999e-06 [micro_interleaved_order_control]: 2.63998e-06 [assign_add_opt]: 1.65001e-06 [ForceFp32Comm]: 9.30013e-07 [remove_cast_before_assign_add]: 9.39996e-07 [full_micro_interleaved_order_control]: 2.08998e-06 [reorder_send_recv_between_fp_bp]: 2.85002e-06 [comm_op_add_attrs]: 1.47999e-06 [add_comm_op_reuse_tag]: 9.50007e-07 [interleave_split_concat_branches]: 1.43002e-06 [interleave_parallel_branches]: 1.12e-06 [overlap_opt_shard_in_pipeline]: 1.42999e-06 [overlap_opt_shard_grad_in_pipeline]: 2.01998e-06 [control_data_broadcast_order]: 3.018e-05 [grouped_pairwise_exchange_alltoall]: 1.54e-06 [offloading_packed_experts]: 7.15e-06 [overlap_recompute_and_grad_model_parallel]: 7.45998e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.31002e-06 [overlap_recompute_allgather_and_fa_grad]: 1.71e-06 [overlap_recompute_comm]: 2.37999e-06 [overlap_grad_ring_attention]: 6.61e-06 [overlap_grad_flash_sp]: 4.091e-05 [begin_end_overlap_inline]: 4.69998e-07 [split_matmul_comm_elemetwise]: 2.68e-06 [split_layernorm_comm]: 1.66e-06 [handle_group_info]: 1.17999e-06 [symbol_engine_optimizer]: 0.00018187, [1] [Cycle 1]: 0.00017063, [6] [build]: 7.68001e-06 [elim_shapecalc]: 3.991e-05 [elim_not_effective]: 3.895e-05 [opt_reshape]: 1.78e-05 [fold_const_symbol]: 2.573e-05 [renormalize]: 5.79981e-07 [detach_backward]: 2.34001e-06 [pipeline_parallel_scheduler]: 1.97001e-06 [auto_monad_reorder]: 3.756e-05 [get_jit_bprop_graph]: 2.49999e-06 [rewriter_after_jit_bprop_graph]: 7.97e-06 [opt_after_jit_grad]: 0.0164918 [validate]: 9.28e-05 Sums bootstrap : 0.006206s : 1.88% type_inference : 0.205719s : 62.19% event_method : 0.004979s : 1.51% auto_monad : 0.000135s : 0.04% graph_reusing : 0.000008s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000057s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000016s : 0.00% parallel-infer-symbol : 0.000005s : 0.00% pre_auto_parallel : 0.000054s : 0.02% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000001s : 0.00% dataset_repeat_opt : 0.000002s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000048s : 0.01% optimize.rewriter_before_opt_a : 0.000103s : 0.03% optimize.opt_a.expand_dump_flag : 0.000007s : 0.00% optimize.opt_a.switch_simplify : 0.000071s : 0.02% optimize.opt_a.loop_unroll : 0.000054s : 0.02% optimize.opt_a.a_1 : 0.025747s : 7.78% optimize.opt_a.with_stream_mark : 0.000097s : 0.03% optimize.opt_a.recompute_prepare : 0.000051s : 0.02% optimize.opt_a.updatestate_depend_eliminate : 0.000019s : 0.01% optimize.opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000013s : 0.00% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.004608s : 1.39% optimize.opt_a.accelerated_algorithm : 0.005163s : 1.56% optimize.opt_a.shard : 0.000008s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000018s : 0.01% optimize.opt_a.shard_inline : 0.000042s : 0.01% optimize.opt_a.merge_send_recv : 0.000042s : 0.01% optimize.opt_a.auto_parallel : 0.000036s : 0.01% optimize.opt_a.parallel : 0.000048s : 0.01% optimize.opt_a.flash_sp : 0.000021s : 0.01% optimize.opt_a.merge_comm : 0.000016s : 0.00% optimize.opt_a.allreduce_fusion : 0.000015s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000042s : 0.01% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000033s : 0.01% optimize.opt_a.virtual_dataset : 0.000029s : 0.01% optimize.opt_a.get_grad_eliminate_ : 0.000028s : 0.01% optimize.opt_a.virtual_output : 0.008989s : 2.72% optimize.opt_a.merge_forward : 0.000037s : 0.01% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000064s : 0.02% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000097s : 0.03% optimize.opt_a.merge_recompute_call_nodes : 0.000005s : 0.00% optimize.opt_a.before_grad : 0.000051s : 0.02% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000023s : 0.01% optimize.opt_a.meta_fg_expand : 0.000019s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000015s : 0.00% optimize.opt_a.receive_attached : 0.000005s : 0.00% optimize.opt_a.after_resolve : 0.000052s : 0.02% optimize.opt_a.a_after_grad : 0.004129s : 1.25% optimize.opt_a.renormalize : 0.017940s : 5.42% optimize.opt_a.add_forward_monad_depend : 0.000023s : 0.01% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000077s : 0.02% optimize.opt_a.cse : 0.000258s : 0.08% optimize.opt_a.a_3 : 0.001122s : 0.34% optimize.py_interpret_to_execute_after_opt_a : 0.000030s : 0.01% optimize.slice_cell_reuse_recomputed_activation : 0.000004s : 0.00% optimize.rewriter_after_opt_a : 0.000076s : 0.02% optimize.convert_after_rewriter : 0.000012s : 0.00% optimize.order_py_execute_after_rewriter : 0.000010s : 0.00% optimize.mutable_eliminate : 0.009803s : 2.96% optimize.opt_b.b_1 : 0.000314s : 0.09% optimize.opt_b.b_2 : 0.000018s : 0.01% optimize.opt_b.updatestate_depend_eliminate : 0.000019s : 0.01% optimize.opt_b.updatestate_assign_eliminate : 0.000006s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000044s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000085s : 0.03% optimize.optimize_parallel_all_gather_comm : 0.000038s : 0.01% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000044s : 0.01% optimize.loop_unroll : 0.008475s : 2.56% optimize.opt_after_cconv.c_1 : 0.000101s : 0.03% optimize.opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000021s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.cse : 0.000084s : 0.03% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000075s : 0.02% optimize.tuple_transform.d_1 : 0.000136s : 0.04% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000017s : 0.01% optimize.partial_unused_args_eliminate : 0.000003s : 0.00% optimize.add_recomputation : 0.000111s : 0.03% optimize.cse_after_recomputation.cse : 0.007784s : 2.35% optimize.environ_conv : 0.000017s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000034s : 0.01% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000009s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 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 : 0.000030s : 0.01% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000007s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000007s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000002s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000007s : 0.00% optimize.overlap_grad_flash_sp : 0.000041s : 0.01% optimize.begin_end_overlap_inline : 0.000000s : 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 : 0.000008s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000040s : 0.01% optimize.symbol_engine_optimizer.elim_not_effective : 0.000039s : 0.01% optimize.symbol_engine_optimizer.opt_reshape : 0.000018s : 0.01% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000026s : 0.01% optimize.symbol_engine_optimizer.renormalize : 0.000001s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000002s : 0.00% auto_monad_reorder : 0.000038s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.016492s : 4.99% validate : 0.000093s : 0.03% Time group info: ------[substitution.] 0.008291 113 1.61% : 0.000134s : 28: substitution.arithmetic_simplify 0.69% : 0.000057s : 3: substitution.cast_eliminate 0.06% : 0.000005s : 8: substitution.elim_not_effective 0.04% : 0.000003s : 8: substitution.fold_const_symbol 0.16% : 0.000014s : 13: substitution.graph_param_transform 96.61% : 0.008010s : 7: substitution.inline 0.11% : 0.000009s : 16: substitution.j_node_and_user_rematch 0.40% : 0.000034s : 4: substitution.less_batch_normalization 0.15% : 0.000013s : 16: substitution.remove_not_recompute_node 0.16% : 0.000013s : 10: substitution.replace_old_param ------[type_inference.] 0.205608 2 92.78% : 0.190765s : 1: type_inference.infer 7.22% : 0.014844s : 1: type_inference.specialize ------[replace.] 0.000119 7 100.00% : 0.000119s : 7: replace.inline ------[match.] 0.008002 7 100.00% : 0.008002s : 7: match.inline ------[predicate.] 0.008175 3331 0.06% : 0.000005s : 32: predicate.accumulaten_eliminater 0.10% : 0.000009s : 13: predicate.ad_related_special_op_eliminate 0.04% : 0.000003s : 26: predicate.addn_check_dump 0.07% : 0.000005s : 32: predicate.addn_zero_filter 0.05% : 0.000004s : 32: predicate.adjust_all_reduce_mul_add 0.21% : 0.000018s : 58: predicate.arithmetic_simplify 0.07% : 0.000005s : 32: predicate.cast_eliminate 0.05% : 0.000004s : 26: predicate.check_bprop_eliminate 0.04% : 0.000003s : 26: predicate.compare_switch_simplify 0.01% : 0.000001s : 13: predicate.const_output_eliminate 0.05% : 0.000004s : 26: predicate.depend_value_elim 0.07% : 0.000006s : 32: predicate.dict_get_item_const_eliminator 0.07% : 0.000006s : 32: predicate.dict_get_item_eliminator 0.06% : 0.000005s : 32: predicate.dict_set_item_eliminator 0.08% : 0.000007s : 26: predicate.dumpgradient_eliminate 0.02% : 0.000002s : 13: predicate.elim_not_effective 0.03% : 0.000003s : 13: predicate.elim_shapecalc_of_broadcastargs 0.07% : 0.000006s : 45: predicate.environ_add_const_eliminate 0.08% : 0.000007s : 45: predicate.environ_get_add_eliminate 0.07% : 0.000006s : 45: predicate.environ_get_depend_swap 0.13% : 0.000011s : 71: predicate.environ_get_eliminate 0.07% : 0.000006s : 45: predicate.environ_get_set_eliminate 0.07% : 0.000006s : 39: predicate.exchange_switch_depend_value 0.14% : 0.000012s : 39: predicate.float_depend_g_call 0.05% : 0.000004s : 26: predicate.float_environ_get_switch 0.07% : 0.000006s : 39: predicate.float_tuple_getitem_switch 0.01% : 0.000001s : 13: predicate.fold_const_symbol 0.05% : 0.000004s : 26: predicate.get_grad_eliminate 0.02% : 0.000001s : 13: predicate.graph_param_transform 0.05% : 0.000004s : 26: predicate.incorporate_call 0.04% : 0.000003s : 26: predicate.incorporate_call_switch 0.43% : 0.000035s : 149: predicate.inline 0.18% : 0.000015s : 26: predicate.inline_without_move 0.02% : 0.000002s : 26: predicate.j_node_and_user_rematch 0.13% : 0.000011s : 26: predicate.less_batch_normalization 0.13% : 0.000011s : 58: predicate.list_to_tuple_eliminator_ 0.17% : 0.000014s : 90: predicate.load_eliminater 0.15% : 0.000012s : 13: predicate.loop_unroll_after_grad 0.11% : 0.000009s : 60: predicate.loop_unroll_before_grad 0.15% : 0.000012s : 58: predicate.make_slice_get_slice_eliminator 0.05% : 0.000004s : 26: predicate.merge_addn 0.05% : 0.000004s : 26: predicate.micro_step_allgather_replace 0.05% : 0.000004s : 26: predicate.mini_step_allgather_replace 0.05% : 0.000004s : 32: predicate.minmaximum_grad 0.13% : 0.000011s : 13: predicate.mutable_eliminate 0.03% : 0.000003s : 13: predicate.opt_reshape 0.03% : 0.000003s : 13: predicate.parallel_virtual_node 0.11% : 0.000009s : 39: predicate.partial_defer_inline 0.08% : 0.000006s : 45: predicate.partial_eliminate 0.06% : 0.000005s : 32: predicate.print_const_string_wrapper 0.05% : 0.000004s : 26: predicate.reduce_all_const_elim 0.08% : 0.000006s : 32: predicate.reduce_eliminate 0.17% : 0.000014s : 90: predicate.redundant_stop_gradient_eliminater 0.03% : 0.000003s : 26: predicate.remove_not_recompute_node 0.10% : 0.000008s : 58: predicate.replace_applicator 0.03% : 0.000003s : 26: predicate.replace_old_param 0.02% : 0.000002s : 13: predicate.reset_defer_inline 0.08% : 0.000006s : 32: predicate.reshape_eliminate 0.05% : 0.000004s : 26: predicate.row_tensor_add_zeros_like 0.03% : 0.000002s : 13: predicate.row_tensor_eliminate 0.06% : 0.000005s : 26: predicate.same_eliminate 0.03% : 0.000002s : 26: predicate.set_cell_output_no_recompute 0.05% : 0.000004s : 26: predicate.shard_identity_eliminate 0.05% : 0.000004s : 26: predicate.special_op_eliminate 0.05% : 0.000004s : 26: predicate.specialize_transform 0.08% : 0.000006s : 26: predicate.split_environ_get_set_with_tuple_value 0.21% : 0.000017s : 26: predicate.stack_unstack_eliminate 0.03% : 0.000002s : 13: predicate.switch_call_monad_eliminater 92.27% : 0.007544s : 39: predicate.switch_defer_inline 0.18% : 0.000015s : 65: predicate.switch_layer_defer_inline 0.27% : 0.000022s : 138: predicate.switch_simplify 0.07% : 0.000005s : 32: predicate.tile_eliminate 0.06% : 0.000005s : 32: predicate.transpose_eliminate 0.14% : 0.000012s : 58: predicate.tuple_list_convert_item_index_to_positive 0.13% : 0.000010s : 58: predicate.tuple_list_get_item_const_eliminator 0.11% : 0.000009s : 58: predicate.tuple_list_get_item_depend_reorder 0.25% : 0.000020s : 84: predicate.tuple_list_get_item_eliminator 0.11% : 0.000009s : 58: predicate.tuple_list_get_set_item_eliminator 0.18% : 0.000015s : 84: predicate.tuple_list_set_item_eliminator 0.13% : 0.000011s : 58: predicate.tuple_to_list_eliminator_ 0.15% : 0.000012s : 90: predicate.updatestate_pure_node_eliminater 0.33% : 0.000027s : 116: predicate.updatestate_useless_node_eliminater 0.03% : 0.000003s : 13: predicate.value_based_eliminate 0.05% : 0.000004s : 26: predicate.virtual_dataset_eliminate 0.14% : 0.000012s : 26: predicate.virtual_output_eliminate 0.03% : 0.000002s : 13: predicate.virtual_view_grad_eliminate 0.03% : 0.000003s : 13: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000765 10 3.62% : 0.000028s : 1: func_graph_cloner_run.FuncGraphClonerGraph 13.03% : 0.000100s : 1: func_graph_cloner_run.FuncGraphClonerNode 83.35% : 0.000638s : 8: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.633930 192 0.00% : 0.000005s : 1: ForceFp32Comm 8.38% : 0.053155s : 1: add_attr 8.38% : 0.053135s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.02% : 0.000117s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.02% : 0.000145s : 1: auto_monad 0.01% : 0.000044s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.99% : 0.006252s : 1: bootstrap 0.01% : 0.000048s : 1: cconv 0.00% : 0.000005s : 1: comm_op_add_attrs 0.01% : 0.000034s : 1: control_data_broadcast_order 0.00% : 0.000016s : 1: convert_after_rewriter 1.24% : 0.007848s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.00% : 0.000024s : 1: environ_conv 0.79% : 0.005024s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000012s : 1: graph_reusing 0.00% : 0.000004s : 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% : 0.000004s : 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% : 0.000012s : 1: label_micro_interleaved_index 1.34% : 0.008504s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 1.55% : 0.009830s : 1: mutable_eliminate 0.00% : 0.000010s : 1: offloading_packed_experts 0.01% : 0.000060s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000056s : 1: opt.transform.mutable_eliminate 7.90% : 0.050053s : 78: opt.transform.opt_a 0.02% : 0.000099s : 1: opt.transform.opt_after_cconv 0.01% : 0.000084s : 1: opt.transform.opt_after_jit_grad 0.05% : 0.000294s : 28: opt.transform.opt_b 0.02% : 0.000150s : 2: opt.transform.opt_trans_graph 0.02% : 0.000114s : 4: opt.transform.symbol_engine_opt 12.25% : 0.077627s : 1: opt_a 0.05% : 0.000289s : 1: opt_after_cconv 2.61% : 0.016523s : 1: opt_after_jit_grad 1.11% : 0.007043s : 1: opt_b 17.75% : 0.112518s : 1: optimize 0.01% : 0.000042s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000013s : 1: order_py_execute_after_rewriter 0.01% : 0.000044s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000011s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000004s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000006s : 1: overlap_param_gather 0.00% : 0.000005s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000010s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000009s : 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 0.01% : 0.000058s : 1: pre_auto_parallel 0.01% : 0.000052s : 1: py_interpret_to_execute 0.01% : 0.000035s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.01% : 0.000081s : 1: remove_dup_value 1.68% : 0.010677s : 1: renormalize.infer 1.14% : 0.007234s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000082s : 1: rewriter_after_opt_a 0.02% : 0.000108s : 1: rewriter_before_opt_a 0.00% : 0.000007s : 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 0.01% : 0.000038s : 1: swap_dp_allreduce_reducescatter 0.03% : 0.000185s : 1: symbol_engine_optimizer 0.03% : 0.000188s : 1: tuple_transform 32.46% : 0.205752s : 1: type_inference . [hook] pytest_runtest_teardown:test_mix_precision_fuse tests/st/graph_kernel/test_mix_precision.py::test_mix_precision_fuse,max_mem:4.0M =============================== 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 89.03s (0:01:29) ===================