==================================================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_004/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_quant_bmm.py [WARNING] ME(169919:281473185365808,MainProcess):2026-01-29-17:37:30.651.772 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 0.122926, [21] [bootstrap]: 0.00060917 [type_inference]: 0.0645358 [event_method]: 1.35e-05 [auto_monad]: 0.00021841 [graph_reusing]: 5.27001e-06 [inline]: 2.46998e-06 [add_attr]: 0.0487638, [1] [add_attr_with_inline]: 0.0487483, [1] [Cycle 1]: 0.00010064, [2] [tag_attr]: 2.506e-05 [meta_addattr_fg_expand]: 5.00999e-06 [parallel-infer-symbol]: 3.36999e-06 [pre_auto_parallel]: 4.751e-05 [insert-virtual-dataset]: 5.56e-06 [parallel-infer-symbol-second]: 7.2e-07 [dataset_repeat_opt]: 2.06e-06 [pipeline_split]: 1.52001e-06 [optimize]: 0.00778293, [53] [py_interpret_to_execute]: 2.847e-05 [rewriter_before_opt_a]: 8.604e-05 [opt_a]: 0.00434373, [2] [Cycle 1]: 0.00299491, [45] [expand_dump_flag]: 3.26001e-06 [switch_simplify]: 3.044e-05 [loop_unroll]: 1.646e-05 [a_1]: 0.00053702 [with_stream_mark]: 2.561e-05 [recompute_prepare]: 1.714e-05 [updatestate_depend_eliminate]: 8.55999e-06 [updatestate_assign_eliminate]: 1.238e-05 [updatestate_loads_eliminate]: 1.459e-05 [parameter_eliminate]: 2.44001e-06 [a_2]: 0.00021065 [accelerated_algorithm]: 3.874e-05 [shard]: 2.21e-06 [meta_shard_fg_expand]: 3.25e-06 [shard_inline]: 1.378e-05 [merge_send_recv]: 2.436e-05 [auto_parallel]: 1.226e-05 [parallel]: 5.583e-05 [flash_sp]: 2.064e-05 [merge_comm]: 9.07999e-06 [allreduce_fusion]: 7.13e-06 [matmul_add_comm_reduction]: 1.575e-05 [allreduce_slice_to_reducescatter]: 9.60019e-07 [virtual_shard_identity]: 2.396e-05 [virtual_dataset]: 1.362e-05 [get_grad_eliminate_]: 1.266e-05 [virtual_output]: 1.197e-05 [merge_forward]: 8.16002e-06 [cell_reuse_recompute_pass]: 1.91e-06 [offload_activation]: 1.617e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.871e-05 [merge_recompute_call_nodes]: 1.77999e-06 [before_grad]: 2.222e-05 [set_forward_comm_id_for_comm_node_pass]: 8.84e-06 [meta_fg_expand]: 5.37999e-06 [flash_sp_send_recv_attached]: 6.09001e-06 [receive_attached]: 2.25002e-06 [after_resolve]: 2.199e-05 [a_after_grad]: 2.211e-05 [renormalize]: 0.00111636 [add_forward_monad_depend]: 1.283e-05 [auto_monad_grad]: 2.56e-06 [auto_monad_eliminator]: 4.614e-05 [cse]: 8.788e-05 [a_3]: 0.00010253 [Cycle 2]: 0.00133563, [45] [expand_dump_flag]: 2.83e-06 [switch_simplify]: 1.545e-05 [loop_unroll]: 1.196e-05 [a_1]: 0.00032697 [with_stream_mark]: 2.126e-05 [recompute_prepare]: 1.542e-05 [updatestate_depend_eliminate]: 1.015e-05 [updatestate_assign_eliminate]: 8.70999e-06 [updatestate_loads_eliminate]: 1.257e-05 [parameter_eliminate]: 2.72001e-06 [a_2]: 0.00018959 [accelerated_algorithm]: 1.905e-05 [shard]: 2.17999e-06 [meta_shard_fg_expand]: 3.28e-06 [shard_inline]: 1.286e-05 [merge_send_recv]: 1.262e-05 [auto_parallel]: 1.376e-05 [parallel]: 8.31002e-06 [flash_sp]: 4.63001e-06 [merge_comm]: 7.82e-06 [allreduce_fusion]: 7.61999e-06 [matmul_add_comm_reduction]: 1.423e-05 [allreduce_slice_to_reducescatter]: 7.59988e-07 [virtual_shard_identity]: 1.596e-05 [virtual_dataset]: 1.253e-05 [get_grad_eliminate_]: 1.165e-05 [virtual_output]: 1.198e-05 [merge_forward]: 7.98001e-06 [cell_reuse_recompute_pass]: 2.41e-06 [offload_activation]: 1.615e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.375e-05 [merge_recompute_call_nodes]: 1.52999e-06 [before_grad]: 2.074e-05 [set_forward_comm_id_for_comm_node_pass]: 8.77999e-06 [meta_fg_expand]: 5.25999e-06 [flash_sp_send_recv_attached]: 1.63002e-06 [receive_attached]: 2.92002e-06 [after_resolve]: 1.931e-05 [a_after_grad]: 2.033e-05 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 2.81999e-06 [auto_monad_grad]: 2.02001e-06 [auto_monad_eliminator]: 3.976e-05 [cse]: 5.325e-05 [a_3]: 8.617e-05 [py_interpret_to_execute_after_opt_a]: 2.172e-05 [slice_cell_reuse_recomputed_activation]: 2.29001e-06 [rewriter_after_opt_a]: 0.00023042 [convert_after_rewriter]: 1.497e-05 [order_py_execute_after_rewriter]: 8.80001e-06 [mutable_eliminate]: 0.00070747 [opt_b]: 0.00045691, [1] [Cycle 1]: 0.00044915, [7] [b_1]: 0.00030332 [b_2]: 1.582e-05 [updatestate_depend_eliminate]: 1.325e-05 [updatestate_assign_eliminate]: 8.17e-06 [updatestate_loads_eliminate]: 1.169e-05 [renormalize]: 5.00004e-07 [cse]: 5.477e-05 [optimize_parallel_all_gather_comm]: 2.84e-05 [overlap_param_gather]: 1.93997e-06 [cconv]: 3.675e-05 [loop_unroll]: 0.00066414 [opt_after_cconv]: 0.00023919, [1] [Cycle 1]: 0.00023087, [7] [c_1]: 8.893e-05 [parameter_eliminate]: 6.38e-06 [updatestate_depend_eliminate]: 1.265e-05 [updatestate_assign_eliminate]: 7.41001e-06 [updatestate_loads_eliminate]: 1.117e-05 [cse]: 6.419e-05 [renormalize]: 6.59988e-07 [remove_dup_value]: 6.394e-05 [tuple_transform]: 0.00012448, [1] [Cycle 1]: 0.00011913, [4] [d_1]: 8.48e-05 [none_parameter_eliminate]: 2.49999e-06 [renormalize]: 1.69995e-07 [switch_simplify]: 1.294e-05 [partial_unused_args_eliminate]: 2.18998e-06 [add_recomputation]: 9.179e-05 [cse_after_recomputation]: 4.067e-05, [1] [Cycle 1]: 3.554e-05, [1] [cse]: 2.953e-05 [environ_conv]: 2.447e-05 [swap_dp_allreduce_reducescatter]: 9.96e-06 [bias_add_comm_swap]: 3.42002e-06 [label_micro_interleaved_index]: 5.34998e-06 [label_fine_grained_interleaved_index]: 2.53998e-06 [merge_cast_opt]: 1.85001e-06 [slice_recompute_activation]: 2.36998e-06 [micro_interleaved_order_control]: 2.54001e-06 [assign_add_opt]: 1.34e-06 [ForceFp32Comm]: 9.89996e-07 [remove_cast_before_assign_add]: 1.52001e-06 [full_micro_interleaved_order_control]: 2.32001e-06 [reorder_send_recv_between_fp_bp]: 2.94001e-06 [comm_op_add_attrs]: 1.12e-06 [add_comm_op_reuse_tag]: 9.39996e-07 [interleave_split_concat_branches]: 1.27e-06 [interleave_parallel_branches]: 1.16002e-06 [overlap_opt_shard_in_pipeline]: 2.268e-05 [overlap_opt_shard_grad_in_pipeline]: 1.79e-06 [control_data_broadcast_order]: 2.679e-05 [grouped_pairwise_exchange_alltoall]: 1.66e-06 [offloading_packed_experts]: 7.35e-06 [overlap_recompute_and_grad_model_parallel]: 7.35998e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.17999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.42999e-06 [overlap_recompute_comm]: 2.37001e-06 [overlap_grad_ring_attention]: 7.03e-06 [overlap_grad_flash_sp]: 3.788e-05 [begin_end_overlap_inline]: 4.70027e-07 [split_matmul_comm_elemetwise]: 2.32999e-06 [split_layernorm_comm]: 1.72999e-06 [handle_group_info]: 9.80013e-07 [symbol_engine_optimizer]: 0.00014721, [1] [Cycle 1]: 0.0001414, [6] [build]: 2.55e-05 [elim_shapecalc]: 2.149e-05 [elim_not_effective]: 2.395e-05 [opt_reshape]: 1.316e-05 [fold_const_symbol]: 2.066e-05 [renormalize]: 2.30008e-07 [detach_backward]: 2.24001e-06 [pipeline_parallel_scheduler]: 1.47999e-06 [auto_monad_reorder]: 5.896e-05 [get_jit_bprop_graph]: 1.74e-06 [rewriter_after_jit_bprop_graph]: 6.27001e-06 [opt_after_jit_grad]: 0.00059622 [validate]: 8.04e-05 Sums bootstrap : 0.000609s : 0.83% type_inference : 0.064536s : 88.41% event_method : 0.000013s : 0.02% auto_monad : 0.000218s : 0.30% graph_reusing : 0.000005s : 0.01% inline : 0.000002s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000025s : 0.03% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000005s : 0.01% parallel-infer-symbol : 0.000003s : 0.00% pre_auto_parallel : 0.000048s : 0.07% insert-virtual-dataset : 0.000006s : 0.01% 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 : 0.000028s : 0.04% optimize.rewriter_before_opt_a : 0.000086s : 0.12% optimize.opt_a.expand_dump_flag : 0.000006s : 0.01% optimize.opt_a.switch_simplify : 0.000046s : 0.06% optimize.opt_a.loop_unroll : 0.000028s : 0.04% optimize.opt_a.a_1 : 0.000864s : 1.18% optimize.opt_a.with_stream_mark : 0.000047s : 0.06% optimize.opt_a.recompute_prepare : 0.000033s : 0.04% optimize.opt_a.updatestate_depend_eliminate : 0.000019s : 0.03% optimize.opt_a.updatestate_assign_eliminate : 0.000021s : 0.03% optimize.opt_a.updatestate_loads_eliminate : 0.000027s : 0.04% optimize.opt_a.parameter_eliminate : 0.000005s : 0.01% optimize.opt_a.a_2 : 0.000400s : 0.55% optimize.opt_a.accelerated_algorithm : 0.000058s : 0.08% optimize.opt_a.shard : 0.000004s : 0.01% optimize.opt_a.meta_shard_fg_expand : 0.000007s : 0.01% optimize.opt_a.shard_inline : 0.000027s : 0.04% optimize.opt_a.merge_send_recv : 0.000037s : 0.05% optimize.opt_a.auto_parallel : 0.000026s : 0.04% optimize.opt_a.parallel : 0.000064s : 0.09% optimize.opt_a.flash_sp : 0.000025s : 0.03% optimize.opt_a.merge_comm : 0.000017s : 0.02% optimize.opt_a.allreduce_fusion : 0.000015s : 0.02% optimize.opt_a.matmul_add_comm_reduction : 0.000030s : 0.04% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000040s : 0.05% optimize.opt_a.virtual_dataset : 0.000026s : 0.04% optimize.opt_a.get_grad_eliminate_ : 0.000024s : 0.03% optimize.opt_a.virtual_output : 0.000024s : 0.03% optimize.opt_a.merge_forward : 0.000016s : 0.02% optimize.opt_a.cell_reuse_recompute_pass : 0.000004s : 0.01% optimize.opt_a.offload_activation : 0.000032s : 0.04% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000062s : 0.09% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000043s : 0.06% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000018s : 0.02% optimize.opt_a.meta_fg_expand : 0.000011s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.01% optimize.opt_a.receive_attached : 0.000005s : 0.01% optimize.opt_a.after_resolve : 0.000041s : 0.06% optimize.opt_a.a_after_grad : 0.000042s : 0.06% optimize.opt_a.renormalize : 0.001116s : 1.53% optimize.opt_a.add_forward_monad_depend : 0.000016s : 0.02% optimize.opt_a.auto_monad_grad : 0.000005s : 0.01% optimize.opt_a.auto_monad_eliminator : 0.000086s : 0.12% optimize.opt_a.cse : 0.000141s : 0.19% optimize.opt_a.a_3 : 0.000189s : 0.26% optimize.py_interpret_to_execute_after_opt_a : 0.000022s : 0.03% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000230s : 0.32% optimize.convert_after_rewriter : 0.000015s : 0.02% optimize.order_py_execute_after_rewriter : 0.000009s : 0.01% optimize.mutable_eliminate : 0.000707s : 0.97% optimize.opt_b.b_1 : 0.000303s : 0.42% optimize.opt_b.b_2 : 0.000016s : 0.02% optimize.opt_b.updatestate_depend_eliminate : 0.000013s : 0.02% optimize.opt_b.updatestate_assign_eliminate : 0.000008s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000012s : 0.02% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000055s : 0.08% optimize.optimize_parallel_all_gather_comm : 0.000028s : 0.04% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000037s : 0.05% optimize.loop_unroll : 0.000664s : 0.91% optimize.opt_after_cconv.c_1 : 0.000089s : 0.12% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.01% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.02% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000007s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000011s : 0.02% optimize.opt_after_cconv.cse : 0.000064s : 0.09% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000064s : 0.09% optimize.tuple_transform.d_1 : 0.000085s : 0.12% optimize.tuple_transform.none_parameter_eliminate : 0.000002s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000013s : 0.02% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000092s : 0.13% optimize.cse_after_recomputation.cse : 0.000030s : 0.04% optimize.environ_conv : 0.000024s : 0.03% optimize.swap_dp_allreduce_reducescatter : 0.000010s : 0.01% optimize.bias_add_comm_swap : 0.000003s : 0.00% optimize.label_micro_interleaved_index : 0.000005s : 0.01% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000002s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000001s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000002s : 0.00% optimize.full_micro_interleaved_order_control : 0.000002s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 0.00% optimize.comm_op_add_attrs : 0.000001s : 0.00% optimize.add_comm_op_reuse_tag : 0.000001s : 0.00% optimize.interleave_split_concat_branches : 0.000001s : 0.00% optimize.interleave_parallel_branches : 0.000001s : 0.00% optimize.overlap_opt_shard_in_pipeline : 0.000023s : 0.03% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000027s : 0.04% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000007s : 0.01% optimize.overlap_recompute_and_grad_model_parallel : 0.000007s : 0.01% 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 : 0.000007s : 0.01% optimize.overlap_grad_flash_sp : 0.000038s : 0.05% optimize.begin_end_overlap_inline : 0.000000s : 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 : 0.000025s : 0.03% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000021s : 0.03% optimize.symbol_engine_optimizer.elim_not_effective : 0.000024s : 0.03% optimize.symbol_engine_optimizer.opt_reshape : 0.000013s : 0.02% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000021s : 0.03% optimize.symbol_engine_optimizer.renormalize : 0.000000s : 0.00% detach_backward : 0.000002s : 0.00% pipeline_parallel_scheduler : 0.000001s : 0.00% auto_monad_reorder : 0.000059s : 0.08% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.01% opt_after_jit_grad : 0.000596s : 0.82% validate : 0.000080s : 0.11% Time group info: ------[substitution.] 0.000302 89 3.16% : 0.000010s : 2: substitution.depend_value_elim 1.23% : 0.000004s : 7: substitution.elim_not_effective 0.94% : 0.000003s : 7: substitution.fold_const_symbol 3.15% : 0.000010s : 10: substitution.graph_param_transform 39.22% : 0.000118s : 1: substitution.inline 2.76% : 0.000008s : 14: substitution.j_node_and_user_rematch 7.01% : 0.000021s : 2: substitution.less_batch_normalization 2.53% : 0.000008s : 12: substitution.load_eliminater 6.65% : 0.000020s : 14: substitution.remove_not_recompute_node 2.43% : 0.000007s : 6: substitution.replace_old_param 2.79% : 0.000008s : 6: substitution.updatestate_pure_node_eliminater 28.11% : 0.000085s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.064467 2 99.30% : 0.064017s : 1: type_inference.infer 0.70% : 0.000450s : 1: type_inference.specialize ------[replace.] 0.000016 1 100.00% : 0.000016s : 1: replace.inline ------[match.] 0.000117 1 100.00% : 0.000117s : 1: match.inline ------[predicate.] 0.000343 2325 0.80% : 0.000003s : 21: predicate.accumulaten_eliminater 0.91% : 0.000003s : 10: predicate.ad_related_special_op_eliminate 0.74% : 0.000003s : 20: predicate.addn_check_dump 0.76% : 0.000003s : 21: predicate.addn_zero_filter 0.80% : 0.000003s : 21: predicate.adjust_all_reduce_mul_add 2.14% : 0.000007s : 41: predicate.arithmetic_simplify 0.90% : 0.000003s : 21: predicate.cast_eliminate 0.79% : 0.000003s : 20: predicate.check_bprop_eliminate 0.79% : 0.000003s : 20: predicate.compare_switch_simplify 0.24% : 0.000001s : 10: predicate.const_output_eliminate 0.90% : 0.000003s : 20: predicate.depend_value_elim 0.83% : 0.000003s : 21: predicate.dict_get_item_const_eliminator 0.91% : 0.000003s : 21: predicate.dict_get_item_eliminator 0.90% : 0.000003s : 21: predicate.dict_set_item_eliminator 1.31% : 0.000005s : 20: predicate.dumpgradient_eliminate 0.30% : 0.000001s : 10: predicate.elim_not_effective 0.61% : 0.000002s : 10: predicate.elim_shapecalc_of_broadcastargs 1.31% : 0.000004s : 31: predicate.environ_add_const_eliminate 1.08% : 0.000004s : 31: predicate.environ_get_add_eliminate 1.12% : 0.000004s : 31: predicate.environ_get_depend_swap 2.12% : 0.000007s : 51: predicate.environ_get_eliminate 1.16% : 0.000004s : 31: predicate.environ_get_set_eliminate 0.79% : 0.000003s : 22: predicate.exchange_switch_depend_value 1.37% : 0.000005s : 22: predicate.float_depend_g_call 0.80% : 0.000003s : 20: predicate.float_environ_get_switch 1.09% : 0.000004s : 30: predicate.float_tuple_getitem_switch 0.23% : 0.000001s : 10: predicate.fold_const_symbol 0.81% : 0.000003s : 20: predicate.get_grad_eliminate 0.32% : 0.000001s : 10: predicate.graph_param_transform 0.87% : 0.000003s : 20: predicate.incorporate_call 0.70% : 0.000002s : 20: predicate.incorporate_call_switch 5.39% : 0.000018s : 103: predicate.inline 1.01% : 0.000003s : 20: predicate.inline_without_move 0.43% : 0.000001s : 20: predicate.j_node_and_user_rematch 1.19% : 0.000004s : 22: predicate.less_batch_normalization 1.68% : 0.000006s : 41: predicate.list_to_tuple_eliminator_ 2.34% : 0.000008s : 62: predicate.load_eliminater 1.24% : 0.000004s : 10: predicate.loop_unroll_after_grad 1.02% : 0.000003s : 25: predicate.loop_unroll_before_grad 1.80% : 0.000006s : 41: predicate.make_slice_get_slice_eliminator 0.82% : 0.000003s : 20: predicate.merge_addn 0.76% : 0.000003s : 20: predicate.micro_step_allgather_replace 0.82% : 0.000003s : 20: predicate.mini_step_allgather_replace 0.76% : 0.000003s : 21: predicate.minmaximum_grad 1.45% : 0.000005s : 10: predicate.mutable_eliminate 0.45% : 0.000002s : 10: predicate.opt_reshape 0.51% : 0.000002s : 10: predicate.parallel_virtual_node 0.99% : 0.000003s : 22: predicate.partial_defer_inline 1.30% : 0.000004s : 31: predicate.partial_eliminate 0.73% : 0.000003s : 21: predicate.print_const_string_wrapper 0.80% : 0.000003s : 20: predicate.reduce_all_const_elim 1.11% : 0.000004s : 21: predicate.reduce_eliminate 2.31% : 0.000008s : 62: predicate.redundant_stop_gradient_eliminater 0.72% : 0.000002s : 20: predicate.remove_not_recompute_node 1.17% : 0.000004s : 41: predicate.replace_applicator 0.60% : 0.000002s : 20: predicate.replace_old_param 0.39% : 0.000001s : 10: predicate.reset_defer_inline 0.83% : 0.000003s : 21: predicate.reshape_eliminate 0.80% : 0.000003s : 20: predicate.row_tensor_add_zeros_like 0.54% : 0.000002s : 10: predicate.row_tensor_eliminate 1.02% : 0.000003s : 20: predicate.same_eliminate 0.61% : 0.000002s : 20: predicate.set_cell_output_no_recompute 1.41% : 0.000005s : 20: predicate.shard_identity_eliminate 0.86% : 0.000003s : 20: predicate.special_op_eliminate 0.90% : 0.000003s : 20: predicate.specialize_transform 1.20% : 0.000004s : 20: predicate.split_environ_get_set_with_tuple_value 0.92% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.59% : 0.000002s : 10: predicate.switch_call_monad_eliminater 0.84% : 0.000003s : 22: predicate.switch_defer_inline 1.63% : 0.000006s : 42: predicate.switch_layer_defer_inline 3.50% : 0.000012s : 77: predicate.switch_simplify 0.78% : 0.000003s : 21: predicate.tile_eliminate 0.75% : 0.000003s : 21: predicate.transpose_eliminate 1.69% : 0.000006s : 41: predicate.tuple_list_convert_item_index_to_positive 1.67% : 0.000006s : 41: predicate.tuple_list_get_item_const_eliminator 1.55% : 0.000005s : 41: predicate.tuple_list_get_item_depend_reorder 3.07% : 0.000011s : 61: predicate.tuple_list_get_item_eliminator 1.56% : 0.000005s : 41: predicate.tuple_list_get_set_item_eliminator 2.64% : 0.000009s : 61: predicate.tuple_list_set_item_eliminator 1.66% : 0.000006s : 41: predicate.tuple_to_list_eliminator_ 2.41% : 0.000008s : 62: predicate.updatestate_pure_node_eliminater 3.30% : 0.000011s : 82: predicate.updatestate_useless_node_eliminater 0.41% : 0.000001s : 10: predicate.value_based_eliminate 0.94% : 0.000003s : 20: predicate.virtual_dataset_eliminate 0.77% : 0.000003s : 20: predicate.virtual_output_eliminate 0.40% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.52% : 0.000002s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000307 4 7.56% : 0.000023s : 1: func_graph_cloner_run.FuncGraphClonerGraph 92.44% : 0.000284s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.182885 192 0.00% : 0.000004s : 1: ForceFp32Comm 26.67% : 0.048771s : 1: add_attr 26.66% : 0.048753s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.05% : 0.000097s : 1: add_recomputation 0.00% : 0.000004s : 1: assign_add_opt 0.12% : 0.000227s : 1: auto_monad 0.04% : 0.000065s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.35% : 0.000648s : 1: bootstrap 0.02% : 0.000040s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.02% : 0.000030s : 1: control_data_broadcast_order 0.01% : 0.000020s : 1: convert_after_rewriter 0.02% : 0.000043s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.02% : 0.000028s : 1: environ_conv 0.01% : 0.000020s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.01% : 0.000009s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000005s : 1: inline 0.00% : 0.000009s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000008s : 1: label_micro_interleaved_index 0.37% : 0.000677s : 1: loop_unroll 0.00% : 0.000004s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.39% : 0.000720s : 1: mutable_eliminate 0.01% : 0.000010s : 1: offloading_packed_experts 0.02% : 0.000028s : 1: opt.transform.loop_unroll_optimizer 0.02% : 0.000030s : 1: opt.transform.mutable_eliminate 1.00% : 0.001835s : 78: opt.transform.opt_a 0.05% : 0.000087s : 1: opt.transform.opt_after_cconv 0.03% : 0.000049s : 1: opt.transform.opt_after_jit_grad 0.16% : 0.000290s : 28: opt.transform.opt_b 0.05% : 0.000095s : 2: opt.transform.opt_trans_graph 0.04% : 0.000075s : 4: opt.transform.symbol_engine_opt 2.38% : 0.004347s : 1: opt_a 0.13% : 0.000243s : 1: opt_after_cconv 0.33% : 0.000611s : 1: opt_after_jit_grad 0.25% : 0.000462s : 1: opt_b 4.26% : 0.007787s : 1: optimize 0.02% : 0.000033s : 1: optimize_parallel_all_gather_comm 0.01% : 0.000012s : 1: order_py_execute_after_rewriter 0.02% : 0.000042s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000010s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.01% : 0.000027s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000006s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000010s : 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% : 0.000004s : 1: pipeline_parallel_scheduler 0.00% : 0.000004s : 1: pipeline_split 0.03% : 0.000052s : 1: pre_auto_parallel 0.02% : 0.000033s : 1: py_interpret_to_execute 0.01% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.04% : 0.000069s : 1: remove_dup_value 0.34% : 0.000628s : 1: renormalize.infer 0.26% : 0.000477s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.01% : 0.000010s : 1: rewriter_after_jit_bprop_graph 0.13% : 0.000239s : 1: rewriter_after_opt_a 0.05% : 0.000091s : 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 0.01% : 0.000013s : 1: swap_dp_allreduce_reducescatter 0.08% : 0.000150s : 1: symbol_engine_optimizer 0.07% : 0.000127s : 1: tuple_transform 35.30% : 0.064559s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_False_True[input_shape0] tests/st/infer/ops/test_internal_ops/test_quant_bmm.py::test_qbmm_False_True[input_shape0],max_mem:32.0M [WARNING] ME(169919:281473185365808,MainProcess):2026-01-29-17:38:12.621.568 [mindspore/context.py:1334] For 'context.set_context', the parameter 'device_target' will be deprecated and removed in a future version. Please use the api mindspore.set_device() instead. TotalTime = 0.130853, [21] [bootstrap]: 0.00088495 [type_inference]: 0.103886 [event_method]: 1.739e-05 [auto_monad]: 0.00020184 [graph_reusing]: 5.60001e-06 [inline]: 1.67001e-06 [add_attr]: 0.00510437, [1] [add_attr_with_inline]: 0.00508335, [1] [Cycle 1]: 6.772e-05, [2] [tag_attr]: 2.247e-05 [meta_addattr_fg_expand]: 4.21001e-06 [parallel-infer-symbol]: 4.06001e-06 [pre_auto_parallel]: 4.335e-05 [insert-virtual-dataset]: 2.73e-06 [parallel-infer-symbol-second]: 9.79984e-07 [dataset_repeat_opt]: 1.96e-06 [pipeline_split]: 1.54e-06 [optimize]: 0.0191354, [53] [py_interpret_to_execute]: 3.674e-05 [rewriter_before_opt_a]: 7.936e-05 [opt_a]: 0.00480482, [2] [Cycle 1]: 0.00331832, [45] [expand_dump_flag]: 3.41999e-06 [switch_simplify]: 5.661e-05 [loop_unroll]: 2.557e-05 [a_1]: 0.00063612 [with_stream_mark]: 2.878e-05 [recompute_prepare]: 1.616e-05 [updatestate_depend_eliminate]: 1.123e-05 [updatestate_assign_eliminate]: 1.242e-05 [updatestate_loads_eliminate]: 1.684e-05 [parameter_eliminate]: 2.39999e-06 [a_2]: 0.00021747 [accelerated_algorithm]: 3.901e-05 [shard]: 2.26998e-06 [meta_shard_fg_expand]: 4.52003e-06 [shard_inline]: 1.425e-05 [merge_send_recv]: 1.734e-05 [auto_parallel]: 1.406e-05 [parallel]: 4.187e-05 [flash_sp]: 1.183e-05 [merge_comm]: 1.106e-05 [allreduce_fusion]: 1.085e-05 [matmul_add_comm_reduction]: 2.008e-05 [allreduce_slice_to_reducescatter]: 6.80011e-07 [virtual_shard_identity]: 1.926e-05 [virtual_dataset]: 1.315e-05 [get_grad_eliminate_]: 1.257e-05 [virtual_output]: 1.468e-05 [merge_forward]: 3.139e-05 [cell_reuse_recompute_pass]: 2.22001e-06 [offload_activation]: 1.949e-05 [cell_reuse_handle_not_recompute_node_pass]: 3e-05 [merge_recompute_call_nodes]: 1.75001e-06 [before_grad]: 2.841e-05 [set_forward_comm_id_for_comm_node_pass]: 1.151e-05 [meta_fg_expand]: 6.44001e-06 [flash_sp_send_recv_attached]: 6.03998e-06 [receive_attached]: 2.39001e-06 [after_resolve]: 2.789e-05 [a_after_grad]: 2.004e-05 [renormalize]: 0.00130349 [add_forward_monad_depend]: 1.21e-05 [auto_monad_grad]: 2.86e-06 [auto_monad_eliminator]: 4.59e-05 [cse]: 8.288e-05 [a_3]: 0.00010499 [Cycle 2]: 0.00147355, [45] [expand_dump_flag]: 1.71002e-06 [switch_simplify]: 1.648e-05 [loop_unroll]: 1.321e-05 [a_1]: 0.00036522 [with_stream_mark]: 1.87e-05 [recompute_prepare]: 1.622e-05 [updatestate_depend_eliminate]: 8.57e-06 [updatestate_assign_eliminate]: 8.65001e-06 [updatestate_loads_eliminate]: 1.36e-05 [parameter_eliminate]: 2.34999e-06 [a_2]: 0.0002613 [accelerated_algorithm]: 2.023e-05 [shard]: 1.57999e-06 [meta_shard_fg_expand]: 3.91999e-06 [shard_inline]: 1.386e-05 [merge_send_recv]: 1.206e-05 [auto_parallel]: 1.339e-05 [parallel]: 1.001e-05 [flash_sp]: 3.46999e-06 [merge_comm]: 7.87e-06 [allreduce_fusion]: 7.75e-06 [matmul_add_comm_reduction]: 1.62e-05 [allreduce_slice_to_reducescatter]: 8.50006e-07 [virtual_shard_identity]: 1.33e-05 [virtual_dataset]: 1.508e-05 [get_grad_eliminate_]: 1.508e-05 [virtual_output]: 1.242e-05 [merge_forward]: 7.53e-06 [cell_reuse_recompute_pass]: 2.38002e-06 [offload_activation]: 1.56e-05 [cell_reuse_handle_not_recompute_node_pass]: 2.429e-05 [merge_recompute_call_nodes]: 1.22e-06 [before_grad]: 2.077e-05 [set_forward_comm_id_for_comm_node_pass]: 7.66999e-06 [meta_fg_expand]: 5.17e-06 [flash_sp_send_recv_attached]: 1.58002e-06 [receive_attached]: 1.86e-06 [after_resolve]: 2.336e-05 [a_after_grad]: 1.938e-05 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 2.69001e-06 [auto_monad_grad]: 2.05002e-06 [auto_monad_eliminator]: 3.619e-05 [cse]: 7.571e-05 [a_3]: 8.931e-05 [py_interpret_to_execute_after_opt_a]: 2.56e-05 [slice_cell_reuse_recomputed_activation]: 2.07999e-06 [rewriter_after_opt_a]: 0.00017594 [convert_after_rewriter]: 1.422e-05 [order_py_execute_after_rewriter]: 1.3e-05 [mutable_eliminate]: 0.0112097 [opt_b]: 0.00056758, [1] [Cycle 1]: 0.00055495, [7] [b_1]: 0.0003581 [b_2]: 1.753e-05 [updatestate_depend_eliminate]: 1.857e-05 [updatestate_assign_eliminate]: 9.34998e-06 [updatestate_loads_eliminate]: 1.535e-05 [renormalize]: 1.09998e-06 [cse]: 8.873e-05 [optimize_parallel_all_gather_comm]: 3.358e-05 [overlap_param_gather]: 2.07999e-06 [cconv]: 4.356e-05 [loop_unroll]: 0.00080262 [opt_after_cconv]: 0.00023853, [1] [Cycle 1]: 0.00023071, [7] [c_1]: 9.497e-05 [parameter_eliminate]: 6.21e-06 [updatestate_depend_eliminate]: 1.302e-05 [updatestate_assign_eliminate]: 7.61999e-06 [updatestate_loads_eliminate]: 1.426e-05 [cse]: 5.439e-05 [renormalize]: 7.39994e-07 [remove_dup_value]: 7.022e-05 [tuple_transform]: 0.00022035, [1] [Cycle 1]: 0.0002147, [4] [d_1]: 0.00010049 [none_parameter_eliminate]: 2.92002e-06 [renormalize]: 1.60013e-07 [switch_simplify]: 1.947e-05 [partial_unused_args_eliminate]: 2.56998e-06 [add_recomputation]: 0.0001037 [cse_after_recomputation]: 5.493e-05, [1] [Cycle 1]: 4.73e-05, [1] [cse]: 3.981e-05 [environ_conv]: 1.751e-05 [swap_dp_allreduce_reducescatter]: 1.375e-05 [bias_add_comm_swap]: 3.83001e-06 [label_micro_interleaved_index]: 6.19001e-06 [label_fine_grained_interleaved_index]: 2.71e-06 [merge_cast_opt]: 1.74e-06 [slice_recompute_activation]: 2.72001e-06 [micro_interleaved_order_control]: 3.13e-06 [assign_add_opt]: 2.23998e-06 [ForceFp32Comm]: 8.70001e-07 [remove_cast_before_assign_add]: 8.2e-07 [full_micro_interleaved_order_control]: 2.64001e-06 [reorder_send_recv_between_fp_bp]: 3.01999e-06 [comm_op_add_attrs]: 1.20999e-06 [add_comm_op_reuse_tag]: 1.05001e-06 [interleave_split_concat_branches]: 1.37e-06 [interleave_parallel_branches]: 1.10999e-06 [overlap_opt_shard_in_pipeline]: 3.26001e-06 [overlap_opt_shard_grad_in_pipeline]: 1.95001e-06 [control_data_broadcast_order]: 3.031e-05 [grouped_pairwise_exchange_alltoall]: 1.63002e-06 [offloading_packed_experts]: 1.167e-05 [overlap_recompute_and_grad_model_parallel]: 8.03999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.10999e-06 [overlap_recompute_allgather_and_fa_grad]: 1.19003e-06 [overlap_recompute_comm]: 2.41e-06 [overlap_grad_ring_attention]: 7.53e-06 [overlap_grad_flash_sp]: 3.535e-05 [begin_end_overlap_inline]: 4.89992e-07 [split_matmul_comm_elemetwise]: 2.21998e-06 [split_layernorm_comm]: 1.76998e-06 [handle_group_info]: 1.09998e-06 [symbol_engine_optimizer]: 0.0001702, [1] [Cycle 1]: 0.00016514, [6] [build]: 1.387e-05 [elim_shapecalc]: 3.085e-05 [elim_not_effective]: 2.534e-05 [opt_reshape]: 2.07e-05 [fold_const_symbol]: 3.123e-05 [renormalize]: 3.4002e-07 [detach_backward]: 2.88e-06 [pipeline_parallel_scheduler]: 1.83002e-06 [auto_monad_reorder]: 0.00053507 [get_jit_bprop_graph]: 7.8e-06 [rewriter_after_jit_bprop_graph]: 9.15999e-06 [opt_after_jit_grad]: 0.0007032 [validate]: 8.201e-05 Sums bootstrap : 0.000885s : 0.71% type_inference : 0.103886s : 83.48% event_method : 0.000017s : 0.01% auto_monad : 0.000202s : 0.16% graph_reusing : 0.000006s : 0.00% inline : 0.000002s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000022s : 0.02% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000004s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000043s : 0.03% 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 : 0.000037s : 0.03% optimize.rewriter_before_opt_a : 0.000079s : 0.06% optimize.opt_a.expand_dump_flag : 0.000005s : 0.00% optimize.opt_a.switch_simplify : 0.000073s : 0.06% optimize.opt_a.loop_unroll : 0.000039s : 0.03% optimize.opt_a.a_1 : 0.001001s : 0.80% optimize.opt_a.with_stream_mark : 0.000047s : 0.04% optimize.opt_a.recompute_prepare : 0.000032s : 0.03% optimize.opt_a.updatestate_depend_eliminate : 0.000020s : 0.02% optimize.opt_a.updatestate_assign_eliminate : 0.000021s : 0.02% optimize.opt_a.updatestate_loads_eliminate : 0.000030s : 0.02% optimize.opt_a.parameter_eliminate : 0.000005s : 0.00% optimize.opt_a.a_2 : 0.000479s : 0.38% optimize.opt_a.accelerated_algorithm : 0.000059s : 0.05% optimize.opt_a.shard : 0.000004s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000008s : 0.01% optimize.opt_a.shard_inline : 0.000028s : 0.02% optimize.opt_a.merge_send_recv : 0.000029s : 0.02% optimize.opt_a.auto_parallel : 0.000027s : 0.02% optimize.opt_a.parallel : 0.000052s : 0.04% optimize.opt_a.flash_sp : 0.000015s : 0.01% optimize.opt_a.merge_comm : 0.000019s : 0.02% optimize.opt_a.allreduce_fusion : 0.000019s : 0.01% optimize.opt_a.matmul_add_comm_reduction : 0.000036s : 0.03% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000033s : 0.03% optimize.opt_a.virtual_dataset : 0.000028s : 0.02% optimize.opt_a.get_grad_eliminate_ : 0.000028s : 0.02% optimize.opt_a.virtual_output : 0.000027s : 0.02% optimize.opt_a.merge_forward : 0.000039s : 0.03% optimize.opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% optimize.opt_a.offload_activation : 0.000035s : 0.03% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000054s : 0.04% optimize.opt_a.merge_recompute_call_nodes : 0.000003s : 0.00% optimize.opt_a.before_grad : 0.000049s : 0.04% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000019s : 0.02% optimize.opt_a.meta_fg_expand : 0.000012s : 0.01% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.01% optimize.opt_a.receive_attached : 0.000004s : 0.00% optimize.opt_a.after_resolve : 0.000051s : 0.04% optimize.opt_a.a_after_grad : 0.000039s : 0.03% optimize.opt_a.renormalize : 0.001304s : 1.05% optimize.opt_a.add_forward_monad_depend : 0.000015s : 0.01% optimize.opt_a.auto_monad_grad : 0.000005s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000082s : 0.07% optimize.opt_a.cse : 0.000159s : 0.13% optimize.opt_a.a_3 : 0.000194s : 0.16% optimize.py_interpret_to_execute_after_opt_a : 0.000026s : 0.02% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000176s : 0.14% optimize.convert_after_rewriter : 0.000014s : 0.01% optimize.order_py_execute_after_rewriter : 0.000013s : 0.01% optimize.mutable_eliminate : 0.011210s : 9.01% optimize.opt_b.b_1 : 0.000358s : 0.29% 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 : 0.000009s : 0.01% optimize.opt_b.updatestate_loads_eliminate : 0.000015s : 0.01% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000089s : 0.07% optimize.optimize_parallel_all_gather_comm : 0.000034s : 0.03% optimize.overlap_param_gather : 0.000002s : 0.00% optimize.cconv : 0.000044s : 0.04% optimize.loop_unroll : 0.000803s : 0.64% optimize.opt_after_cconv.c_1 : 0.000095s : 0.08% optimize.opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.01% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.01% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000014s : 0.01% optimize.opt_after_cconv.cse : 0.000054s : 0.04% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000070s : 0.06% optimize.tuple_transform.d_1 : 0.000100s : 0.08% optimize.tuple_transform.none_parameter_eliminate : 0.000003s : 0.00% optimize.tuple_transform.renormalize : 0.000000s : 0.00% optimize.tuple_transform.switch_simplify : 0.000019s : 0.02% optimize.partial_unused_args_eliminate : 0.000003s : 0.00% optimize.add_recomputation : 0.000104s : 0.08% optimize.cse_after_recomputation.cse : 0.000040s : 0.03% optimize.environ_conv : 0.000018s : 0.01% optimize.swap_dp_allreduce_reducescatter : 0.000014s : 0.01% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000006s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 0.00% optimize.micro_interleaved_order_control : 0.000003s : 0.00% optimize.assign_add_opt : 0.000002s : 0.00% optimize.ForceFp32Comm : 0.000001s : 0.00% optimize.remove_cast_before_assign_add : 0.000001s : 0.00% optimize.full_micro_interleaved_order_control : 0.000003s : 0.00% optimize.reorder_send_recv_between_fp_bp : 0.000003s : 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 : 0.000003s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000030s : 0.02% optimize.grouped_pairwise_exchange_alltoall : 0.000002s : 0.00% optimize.offloading_packed_experts : 0.000012s : 0.01% optimize.overlap_recompute_and_grad_model_parallel : 0.000008s : 0.01% 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 : 0.000008s : 0.01% optimize.overlap_grad_flash_sp : 0.000035s : 0.03% optimize.begin_end_overlap_inline : 0.000000s : 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 : 0.000014s : 0.01% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000031s : 0.02% optimize.symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.02% optimize.symbol_engine_optimizer.opt_reshape : 0.000021s : 0.02% optimize.symbol_engine_optimizer.fold_const_symbol : 0.000031s : 0.03% 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 : 0.000535s : 0.43% get_jit_bprop_graph : 0.000008s : 0.01% rewriter_after_jit_bprop_graph : 0.000009s : 0.01% opt_after_jit_grad : 0.000703s : 0.57% validate : 0.000082s : 0.07% Time group info: ------[substitution.] 0.000421 89 17.54% : 0.000074s : 2: substitution.depend_value_elim 0.83% : 0.000003s : 7: substitution.elim_not_effective 2.04% : 0.000009s : 7: substitution.fold_const_symbol 2.28% : 0.000010s : 10: substitution.graph_param_transform 29.26% : 0.000123s : 1: substitution.inline 1.90% : 0.000008s : 14: substitution.j_node_and_user_rematch 5.45% : 0.000023s : 2: substitution.less_batch_normalization 1.95% : 0.000008s : 12: substitution.load_eliminater 3.22% : 0.000014s : 14: substitution.remove_not_recompute_node 2.67% : 0.000011s : 6: substitution.replace_old_param 2.23% : 0.000009s : 6: substitution.updatestate_pure_node_eliminater 30.64% : 0.000129s : 8: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.103817 2 99.47% : 0.103266s : 1: type_inference.infer 0.53% : 0.000551s : 1: type_inference.specialize ------[replace.] 0.000018 1 100.00% : 0.000018s : 1: replace.inline ------[match.] 0.000122 1 100.00% : 0.000122s : 1: match.inline ------[predicate.] 0.000378 2325 0.80% : 0.000003s : 21: predicate.accumulaten_eliminater 1.27% : 0.000005s : 10: predicate.ad_related_special_op_eliminate 0.66% : 0.000003s : 20: predicate.addn_check_dump 0.73% : 0.000003s : 21: predicate.addn_zero_filter 0.66% : 0.000003s : 21: predicate.adjust_all_reduce_mul_add 1.86% : 0.000007s : 41: predicate.arithmetic_simplify 0.93% : 0.000004s : 21: predicate.cast_eliminate 0.76% : 0.000003s : 20: predicate.check_bprop_eliminate 0.69% : 0.000003s : 20: predicate.compare_switch_simplify 0.21% : 0.000001s : 10: predicate.const_output_eliminate 0.75% : 0.000003s : 20: predicate.depend_value_elim 0.77% : 0.000003s : 21: predicate.dict_get_item_const_eliminator 0.85% : 0.000003s : 21: predicate.dict_get_item_eliminator 0.71% : 0.000003s : 21: predicate.dict_set_item_eliminator 1.11% : 0.000004s : 20: predicate.dumpgradient_eliminate 0.28% : 0.000001s : 10: predicate.elim_not_effective 0.65% : 0.000002s : 10: predicate.elim_shapecalc_of_broadcastargs 1.18% : 0.000004s : 31: predicate.environ_add_const_eliminate 1.01% : 0.000004s : 31: predicate.environ_get_add_eliminate 1.02% : 0.000004s : 31: predicate.environ_get_depend_swap 1.81% : 0.000007s : 51: predicate.environ_get_eliminate 1.04% : 0.000004s : 31: predicate.environ_get_set_eliminate 0.74% : 0.000003s : 22: predicate.exchange_switch_depend_value 1.30% : 0.000005s : 22: predicate.float_depend_g_call 0.71% : 0.000003s : 20: predicate.float_environ_get_switch 1.05% : 0.000004s : 30: predicate.float_tuple_getitem_switch 0.22% : 0.000001s : 10: predicate.fold_const_symbol 0.78% : 0.000003s : 20: predicate.get_grad_eliminate 0.25% : 0.000001s : 10: predicate.graph_param_transform 0.72% : 0.000003s : 20: predicate.incorporate_call 0.66% : 0.000002s : 20: predicate.incorporate_call_switch 5.29% : 0.000020s : 103: predicate.inline 0.97% : 0.000004s : 20: predicate.inline_without_move 0.39% : 0.000001s : 20: predicate.j_node_and_user_rematch 1.12% : 0.000004s : 22: predicate.less_batch_normalization 1.52% : 0.000006s : 41: predicate.list_to_tuple_eliminator_ 2.30% : 0.000009s : 62: predicate.load_eliminater 1.28% : 0.000005s : 10: predicate.loop_unroll_after_grad 0.99% : 0.000004s : 25: predicate.loop_unroll_before_grad 1.72% : 0.000006s : 41: predicate.make_slice_get_slice_eliminator 0.75% : 0.000003s : 20: predicate.merge_addn 0.77% : 0.000003s : 20: predicate.micro_step_allgather_replace 0.78% : 0.000003s : 20: predicate.mini_step_allgather_replace 0.68% : 0.000003s : 21: predicate.minmaximum_grad 2.80% : 0.000011s : 10: predicate.mutable_eliminate 0.45% : 0.000002s : 10: predicate.opt_reshape 0.47% : 0.000002s : 10: predicate.parallel_virtual_node 0.96% : 0.000004s : 22: predicate.partial_defer_inline 1.19% : 0.000005s : 31: predicate.partial_eliminate 0.70% : 0.000003s : 21: predicate.print_const_string_wrapper 0.73% : 0.000003s : 20: predicate.reduce_all_const_elim 0.90% : 0.000003s : 21: predicate.reduce_eliminate 2.18% : 0.000008s : 62: predicate.redundant_stop_gradient_eliminater 0.69% : 0.000003s : 20: predicate.remove_not_recompute_node 1.08% : 0.000004s : 41: predicate.replace_applicator 0.51% : 0.000002s : 20: predicate.replace_old_param 0.44% : 0.000002s : 10: predicate.reset_defer_inline 0.84% : 0.000003s : 21: predicate.reshape_eliminate 0.88% : 0.000003s : 20: predicate.row_tensor_add_zeros_like 0.52% : 0.000002s : 10: predicate.row_tensor_eliminate 0.94% : 0.000004s : 20: predicate.same_eliminate 0.48% : 0.000002s : 20: predicate.set_cell_output_no_recompute 0.89% : 0.000003s : 20: predicate.shard_identity_eliminate 0.87% : 0.000003s : 20: predicate.special_op_eliminate 0.83% : 0.000003s : 20: predicate.specialize_transform 0.93% : 0.000004s : 20: predicate.split_environ_get_set_with_tuple_value 0.88% : 0.000003s : 20: predicate.stack_unstack_eliminate 0.47% : 0.000002s : 10: predicate.switch_call_monad_eliminater 5.84% : 0.000022s : 22: predicate.switch_defer_inline 1.55% : 0.000006s : 42: predicate.switch_layer_defer_inline 3.75% : 0.000014s : 77: predicate.switch_simplify 0.77% : 0.000003s : 21: predicate.tile_eliminate 0.71% : 0.000003s : 21: predicate.transpose_eliminate 1.53% : 0.000006s : 41: predicate.tuple_list_convert_item_index_to_positive 1.56% : 0.000006s : 41: predicate.tuple_list_get_item_const_eliminator 1.43% : 0.000005s : 41: predicate.tuple_list_get_item_depend_reorder 2.93% : 0.000011s : 61: predicate.tuple_list_get_item_eliminator 1.57% : 0.000006s : 41: predicate.tuple_list_get_set_item_eliminator 2.45% : 0.000009s : 61: predicate.tuple_list_set_item_eliminator 1.51% : 0.000006s : 41: predicate.tuple_to_list_eliminator_ 2.12% : 0.000008s : 62: predicate.updatestate_pure_node_eliminater 3.11% : 0.000012s : 82: predicate.updatestate_useless_node_eliminater 0.44% : 0.000002s : 10: predicate.value_based_eliminate 0.77% : 0.000003s : 20: predicate.virtual_dataset_eliminate 0.74% : 0.000003s : 20: predicate.virtual_output_eliminate 0.35% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.49% : 0.000002s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000420 4 6.74% : 0.000028s : 1: func_graph_cloner_run.FuncGraphClonerGraph 93.26% : 0.000392s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.159090 192 0.00% : 0.000006s : 1: ForceFp32Comm 3.21% : 0.005110s : 1: add_attr 3.20% : 0.005088s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.07% : 0.000109s : 1: add_recomputation 0.00% : 0.000005s : 1: assign_add_opt 0.13% : 0.000210s : 1: auto_monad 0.35% : 0.000556s : 1: auto_monad_reorder 0.00% : 0.000003s : 1: begin_end_overlap_inline 0.00% : 0.000007s : 1: bias_add_comm_swap 0.59% : 0.000935s : 1: bootstrap 0.03% : 0.000047s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.02% : 0.000035s : 1: control_data_broadcast_order 0.01% : 0.000018s : 1: convert_after_rewriter 0.04% : 0.000058s : 1: cse_after_recomputation 0.00% : 0.000005s : 1: dataset_repeat_opt 0.00% : 0.000006s : 1: detach_backward 0.01% : 0.000021s : 1: environ_conv 0.01% : 0.000024s : 1: event_method 0.00% : 0.000006s : 1: full_micro_interleaved_order_control 0.01% : 0.000013s : 1: get_jit_bprop_graph 0.01% : 0.000010s : 1: graph_reusing 0.00% : 0.000005s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000004s : 1: handle_group_info 0.00% : 0.000005s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000007s : 1: interleave_parallel_branches 0.00% : 0.000004s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.01% : 0.000009s : 1: label_micro_interleaved_index 0.51% : 0.000815s : 1: loop_unroll 0.00% : 0.000005s : 1: merge_cast_opt 0.00% : 0.000006s : 1: micro_interleaved_order_control 7.06% : 0.011236s : 1: mutable_eliminate 0.01% : 0.000015s : 1: offloading_packed_experts 0.02% : 0.000032s : 1: opt.transform.loop_unroll_optimizer 0.04% : 0.000063s : 1: opt.transform.mutable_eliminate 1.33% : 0.002113s : 78: opt.transform.opt_a 0.06% : 0.000093s : 1: opt.transform.opt_after_cconv 0.04% : 0.000059s : 1: opt.transform.opt_after_jit_grad 0.21% : 0.000338s : 28: opt.transform.opt_b 0.07% : 0.000116s : 2: opt.transform.opt_trans_graph 0.06% : 0.000103s : 4: opt.transform.symbol_engine_opt 3.02% : 0.004808s : 1: opt_a 0.15% : 0.000243s : 1: opt_after_cconv 0.45% : 0.000716s : 1: opt_after_jit_grad 0.36% : 0.000573s : 1: opt_b 12.03% : 0.019141s : 1: optimize 0.02% : 0.000038s : 1: optimize_parallel_all_gather_comm 0.01% : 0.000016s : 1: order_py_execute_after_rewriter 0.03% : 0.000040s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.01% : 0.000011s : 1: overlap_grad_ring_attention 0.00% : 0.000005s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000006s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000005s : 1: overlap_param_gather 0.00% : 0.000006s : 1: overlap_recompute_allgather_and_fa_grad 0.01% : 0.000011s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000008s : 1: parallel-infer-symbol 0.00% : 0.000004s : 1: parallel-infer-symbol-second 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000005s : 1: pipeline_parallel_scheduler 0.00% : 0.000007s : 1: pipeline_split 0.03% : 0.000048s : 1: pre_auto_parallel 0.03% : 0.000041s : 1: py_interpret_to_execute 0.02% : 0.000029s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.05% : 0.000079s : 1: remove_dup_value 0.42% : 0.000661s : 1: renormalize.infer 0.40% : 0.000630s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.01% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.11% : 0.000181s : 1: rewriter_after_opt_a 0.05% : 0.000083s : 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 0.01% : 0.000017s : 1: swap_dp_allreduce_reducescatter 0.11% : 0.000173s : 1: symbol_engine_optimizer 0.14% : 0.000224s : 1: tuple_transform 65.31% : 0.103906s : 1: type_inference . [hook] pytest_runtest_teardown:test_qbmm_False_True[input_shape1] tests/st/infer/ops/test_internal_ops/test_quant_bmm.py::test_qbmm_False_True[input_shape1],max_mem:34.0M =============================== warnings summary =============================== ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 87.87s (0:01:27) ===================