==================================================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/tensor, configfile: ../../../../../../sault/virtual_test/virtualenv_003/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_setitem.py . [hook] pytest_runtest_teardown:test_tensor_fancy_index_set_item_032[1] tests/st/tensor/test_setitem.py::test_tensor_fancy_index_set_item_032[1],max_mem:2.0M TotalTime = 9.48712, [21] [bootstrap]: 0.00069962 [type_inference]: 8.77261 [event_method]: 0.00012444 [auto_monad]: 0.00031115 [graph_reusing]: 1.267e-05 [inline]: 3.37002e-06 [add_attr]: 0.190126, [1] [add_attr_with_inline]: 0.190108, [1] [Cycle 1]: 0.00026043, [2] [tag_attr]: 0.0001186 [meta_addattr_fg_expand]: 4.115e-05 [parallel-infer-symbol]: 4.38999e-06 [pre_auto_parallel]: 0.00011437 [insert-virtual-dataset]: 2.81e-06 [parallel-infer-symbol-second]: 1.84998e-06 [dataset_repeat_opt]: 2.61999e-06 [pipeline_split]: 1.97999e-06 [optimize]: 0.521642, [53] [py_interpret_to_execute]: 9.329e-05 [rewriter_before_opt_a]: 0.00028362 [opt_a]: 0.253715, [2] [Cycle 1]: 0.2513, [45] [expand_dump_flag]: 6.64001e-06 [switch_simplify]: 0.00029167 [loop_unroll]: 7.657e-05 [a_1]: 0.00186275 [with_stream_mark]: 4.041e-05 [recompute_prepare]: 2.557e-05 [updatestate_depend_eliminate]: 1.121e-05 [updatestate_assign_eliminate]: 8.23999e-06 [updatestate_loads_eliminate]: 7.78001e-06 [parameter_eliminate]: 2.73e-06 [a_2]: 0.00022385 [accelerated_algorithm]: 4.793e-05 [shard]: 2.68e-06 [meta_shard_fg_expand]: 8.52e-06 [shard_inline]: 1.633e-05 [merge_send_recv]: 2.856e-05 [auto_parallel]: 1.721e-05 [parallel]: 4.364e-05 [flash_sp]: 2.571e-05 [merge_comm]: 9.69999e-06 [allreduce_fusion]: 9.14e-06 [matmul_add_comm_reduction]: 1.823e-05 [allreduce_slice_to_reducescatter]: 8.59989e-07 [virtual_shard_identity]: 1.877e-05 [virtual_dataset]: 1.626e-05 [get_grad_eliminate_]: 1.616e-05 [virtual_output]: 1.432e-05 [merge_forward]: 9.50001e-06 [cell_reuse_recompute_pass]: 2.47001e-06 [offload_activation]: 1.891e-05 [cell_reuse_handle_not_recompute_node_pass]: 4.447e-05 [merge_recompute_call_nodes]: 2.20002e-06 [before_grad]: 2.835e-05 [set_forward_comm_id_for_comm_node_pass]: 9.86e-06 [meta_fg_expand]: 1.002e-05 [flash_sp_send_recv_attached]: 5.92999e-06 [receive_attached]: 1.194e-05 [after_resolve]: 2.129e-05 [a_after_grad]: 2.44e-05 [renormalize]: 0.246699 [add_forward_monad_depend]: 1.498e-05 [auto_monad_grad]: 3.26001e-06 [auto_monad_eliminator]: 4.905e-05 [cse]: 0.00090318 [a_3]: 0.0001488 [Cycle 2]: 0.00239475, [45] [expand_dump_flag]: 4.85001e-06 [switch_simplify]: 1.983e-05 [loop_unroll]: 1.418e-05 [a_1]: 0.00051976 [with_stream_mark]: 4.029e-05 [recompute_prepare]: 2.105e-05 [updatestate_depend_eliminate]: 1.17e-05 [updatestate_assign_eliminate]: 8.03001e-06 [updatestate_loads_eliminate]: 7.92e-06 [parameter_eliminate]: 3.55e-06 [a_2]: 0.00020688 [accelerated_algorithm]: 3.66e-05 [shard]: 2.94001e-06 [meta_shard_fg_expand]: 7.5e-06 [shard_inline]: 1.532e-05 [merge_send_recv]: 1.743e-05 [auto_parallel]: 1.829e-05 [parallel]: 1.069e-05 [flash_sp]: 6.43e-06 [merge_comm]: 9.29e-06 [allreduce_fusion]: 8.82999e-06 [matmul_add_comm_reduction]: 2.011e-05 [allreduce_slice_to_reducescatter]: 1.27e-06 [virtual_shard_identity]: 2.048e-05 [virtual_dataset]: 1.505e-05 [get_grad_eliminate_]: 1.454e-05 [virtual_output]: 1.578e-05 [merge_forward]: 1.034e-05 [cell_reuse_recompute_pass]: 3.85998e-06 [offload_activation]: 2.143e-05 [cell_reuse_handle_not_recompute_node_pass]: 3.664e-05 [merge_recompute_call_nodes]: 1.57999e-06 [before_grad]: 0.00013436 [set_forward_comm_id_for_comm_node_pass]: 4.405e-05 [meta_fg_expand]: 9.96998e-06 [flash_sp_send_recv_attached]: 2.31e-06 [receive_attached]: 3.23e-06 [after_resolve]: 3.874e-05 [a_after_grad]: 2.447e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 5.51e-06 [auto_monad_grad]: 3.20998e-06 [auto_monad_eliminator]: 3.346e-05 [cse]: 0.00042405 [a_3]: 0.00011912 [py_interpret_to_execute_after_opt_a]: 3.792e-05 [slice_cell_reuse_recomputed_activation]: 2.44001e-06 [rewriter_after_opt_a]: 0.00053627 [convert_after_rewriter]: 3.353e-05 [order_py_execute_after_rewriter]: 1.169e-05 [mutable_eliminate]: 0.00104165 [opt_b]: 0.00065315, [1] [Cycle 1]: 0.00064076, [7] [b_1]: 0.00034221 [b_2]: 1.786e-05 [updatestate_depend_eliminate]: 1.951e-05 [updatestate_assign_eliminate]: 8.13999e-06 [updatestate_loads_eliminate]: 8.12998e-06 [renormalize]: 8.29983e-07 [cse]: 0.0001964 [optimize_parallel_all_gather_comm]: 4.341e-05 [overlap_param_gather]: 3.35998e-06 [cconv]: 4.637e-05 [loop_unroll]: 0.00092302 [opt_after_cconv]: 0.00033333, [1] [Cycle 1]: 0.00032212, [7] [c_1]: 7.731e-05 [parameter_eliminate]: 7.87e-06 [updatestate_depend_eliminate]: 1.882e-05 [updatestate_assign_eliminate]: 7.46999e-06 [updatestate_loads_eliminate]: 7.46999e-06 [cse]: 0.00015902 [renormalize]: 7.2e-07 [remove_dup_value]: 0.00029693 [tuple_transform]: 0.00018331, [1] [Cycle 1]: 0.00017522, [4] [d_1]: 0.00012341 [none_parameter_eliminate]: 4.12e-06 [renormalize]: 5.70028e-07 [switch_simplify]: 1.81e-05 [partial_unused_args_eliminate]: 2.46e-06 [add_recomputation]: 0.00013332 [cse_after_recomputation]: 0.00010239, [1] [Cycle 1]: 9.477e-05, [1] [cse]: 8.528e-05 [environ_conv]: 2.919e-05 [swap_dp_allreduce_reducescatter]: 1.483e-05 [bias_add_comm_swap]: 3.93001e-06 [label_micro_interleaved_index]: 7.88001e-06 [label_fine_grained_interleaved_index]: 2.82002e-06 [merge_cast_opt]: 1.69998e-06 [slice_recompute_activation]: 2.52001e-06 [micro_interleaved_order_control]: 2.61e-06 [assign_add_opt]: 1.89e-06 [ForceFp32Comm]: 1.05999e-06 [remove_cast_before_assign_add]: 1.10999e-06 [full_micro_interleaved_order_control]: 2.41e-06 [reorder_send_recv_between_fp_bp]: 2.93e-06 [comm_op_add_attrs]: 1.19998e-06 [add_comm_op_reuse_tag]: 1.35999e-06 [interleave_split_concat_branches]: 1.15001e-06 [interleave_parallel_branches]: 1.19e-06 [overlap_opt_shard_in_pipeline]: 2.646e-05 [overlap_opt_shard_grad_in_pipeline]: 1.97999e-06 [control_data_broadcast_order]: 3.256e-05 [grouped_pairwise_exchange_alltoall]: 1.44998e-06 [offloading_packed_experts]: 1.128e-05 [overlap_recompute_and_grad_model_parallel]: 9.94999e-06 [overlap_grad_matmul_and_grad_allreduce]: 1.37e-06 [overlap_recompute_allgather_and_fa_grad]: 1.27e-06 [overlap_recompute_comm]: 2.43e-06 [overlap_grad_ring_attention]: 6.69001e-06 [overlap_grad_flash_sp]: 4.326e-05 [begin_end_overlap_inline]: 5.19998e-07 [split_matmul_comm_elemetwise]: 2.27999e-06 [split_layernorm_comm]: 2.11e-06 [handle_group_info]: 1.09e-06 [symbol_engine_optimizer]: 0.2626, [1] [Cycle 1]: 0.262591, [6] [build]: 1.708e-05 [elim_shapecalc]: 2.711e-05 [elim_not_effective]: 3.176e-05 [opt_reshape]: 1.666e-05 [fold_const_symbol]: 0.262396 [renormalize]: 1.60001e-06 [detach_backward]: 5.67999e-06 [pipeline_parallel_scheduler]: 2.71e-06 [auto_monad_reorder]: 7.962e-05 [get_jit_bprop_graph]: 3.26999e-06 [rewriter_after_jit_bprop_graph]: 1.044e-05 [opt_after_jit_grad]: 0.00099671 [validate]: 0.00011524 Sums bootstrap : 0.000700s : 0.01% type_inference : 8.772612s : 94.38% event_method : 0.000124s : 0.00% auto_monad : 0.000311s : 0.00% graph_reusing : 0.000013s : 0.00% inline : 0.000003s : 0.00% add_attr.add_attr_with_inline.tag_attr : 0.000119s : 0.00% add_attr.add_attr_with_inline.meta_addattr_fg_expand : 0.000041s : 0.00% parallel-infer-symbol : 0.000004s : 0.00% pre_auto_parallel : 0.000114s : 0.00% insert-virtual-dataset : 0.000003s : 0.00% parallel-infer-symbol-second : 0.000002s : 0.00% dataset_repeat_opt : 0.000003s : 0.00% pipeline_split : 0.000002s : 0.00% optimize.py_interpret_to_execute : 0.000093s : 0.00% optimize.rewriter_before_opt_a : 0.000284s : 0.00% optimize.opt_a.expand_dump_flag : 0.000011s : 0.00% optimize.opt_a.switch_simplify : 0.000311s : 0.00% optimize.opt_a.loop_unroll : 0.000091s : 0.00% optimize.opt_a.a_1 : 0.002383s : 0.03% optimize.opt_a.with_stream_mark : 0.000081s : 0.00% optimize.opt_a.recompute_prepare : 0.000047s : 0.00% optimize.opt_a.updatestate_depend_eliminate : 0.000023s : 0.00% optimize.opt_a.updatestate_assign_eliminate : 0.000016s : 0.00% optimize.opt_a.updatestate_loads_eliminate : 0.000016s : 0.00% optimize.opt_a.parameter_eliminate : 0.000006s : 0.00% optimize.opt_a.a_2 : 0.000431s : 0.00% optimize.opt_a.accelerated_algorithm : 0.000085s : 0.00% optimize.opt_a.shard : 0.000006s : 0.00% optimize.opt_a.meta_shard_fg_expand : 0.000016s : 0.00% optimize.opt_a.shard_inline : 0.000032s : 0.00% optimize.opt_a.merge_send_recv : 0.000046s : 0.00% optimize.opt_a.auto_parallel : 0.000036s : 0.00% optimize.opt_a.parallel : 0.000054s : 0.00% optimize.opt_a.flash_sp : 0.000032s : 0.00% optimize.opt_a.merge_comm : 0.000019s : 0.00% optimize.opt_a.allreduce_fusion : 0.000018s : 0.00% optimize.opt_a.matmul_add_comm_reduction : 0.000038s : 0.00% optimize.opt_a.allreduce_slice_to_reducescatter : 0.000002s : 0.00% optimize.opt_a.virtual_shard_identity : 0.000039s : 0.00% optimize.opt_a.virtual_dataset : 0.000031s : 0.00% optimize.opt_a.get_grad_eliminate_ : 0.000031s : 0.00% optimize.opt_a.virtual_output : 0.000030s : 0.00% optimize.opt_a.merge_forward : 0.000020s : 0.00% optimize.opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% optimize.opt_a.offload_activation : 0.000040s : 0.00% optimize.opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000081s : 0.00% optimize.opt_a.merge_recompute_call_nodes : 0.000004s : 0.00% optimize.opt_a.before_grad : 0.000163s : 0.00% optimize.opt_a.set_forward_comm_id_for_comm_node_pass : 0.000054s : 0.00% optimize.opt_a.meta_fg_expand : 0.000020s : 0.00% optimize.opt_a.flash_sp_send_recv_attached : 0.000008s : 0.00% optimize.opt_a.receive_attached : 0.000015s : 0.00% optimize.opt_a.after_resolve : 0.000060s : 0.00% optimize.opt_a.a_after_grad : 0.000049s : 0.00% optimize.opt_a.renormalize : 0.246699s : 2.65% optimize.opt_a.add_forward_monad_depend : 0.000020s : 0.00% optimize.opt_a.auto_monad_grad : 0.000006s : 0.00% optimize.opt_a.auto_monad_eliminator : 0.000083s : 0.00% optimize.opt_a.cse : 0.001327s : 0.01% optimize.opt_a.a_3 : 0.000268s : 0.00% optimize.py_interpret_to_execute_after_opt_a : 0.000038s : 0.00% optimize.slice_cell_reuse_recomputed_activation : 0.000002s : 0.00% optimize.rewriter_after_opt_a : 0.000536s : 0.01% optimize.convert_after_rewriter : 0.000034s : 0.00% optimize.order_py_execute_after_rewriter : 0.000012s : 0.00% optimize.mutable_eliminate : 0.001042s : 0.01% optimize.opt_b.b_1 : 0.000342s : 0.00% optimize.opt_b.b_2 : 0.000018s : 0.00% optimize.opt_b.updatestate_depend_eliminate : 0.000020s : 0.00% optimize.opt_b.updatestate_assign_eliminate : 0.000008s : 0.00% optimize.opt_b.updatestate_loads_eliminate : 0.000008s : 0.00% optimize.opt_b.renormalize : 0.000001s : 0.00% optimize.opt_b.cse : 0.000196s : 0.00% optimize.optimize_parallel_all_gather_comm : 0.000043s : 0.00% optimize.overlap_param_gather : 0.000003s : 0.00% optimize.cconv : 0.000046s : 0.00% optimize.loop_unroll : 0.000923s : 0.01% optimize.opt_after_cconv.c_1 : 0.000077s : 0.00% optimize.opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% optimize.opt_after_cconv.updatestate_depend_eliminate : 0.000019s : 0.00% optimize.opt_after_cconv.updatestate_assign_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% optimize.opt_after_cconv.cse : 0.000159s : 0.00% optimize.opt_after_cconv.renormalize : 0.000001s : 0.00% optimize.remove_dup_value : 0.000297s : 0.00% optimize.tuple_transform.d_1 : 0.000123s : 0.00% optimize.tuple_transform.none_parameter_eliminate : 0.000004s : 0.00% optimize.tuple_transform.renormalize : 0.000001s : 0.00% optimize.tuple_transform.switch_simplify : 0.000018s : 0.00% optimize.partial_unused_args_eliminate : 0.000002s : 0.00% optimize.add_recomputation : 0.000133s : 0.00% optimize.cse_after_recomputation.cse : 0.000085s : 0.00% optimize.environ_conv : 0.000029s : 0.00% optimize.swap_dp_allreduce_reducescatter : 0.000015s : 0.00% optimize.bias_add_comm_swap : 0.000004s : 0.00% optimize.label_micro_interleaved_index : 0.000008s : 0.00% optimize.label_fine_grained_interleaved_index : 0.000003s : 0.00% optimize.merge_cast_opt : 0.000002s : 0.00% optimize.slice_recompute_activation : 0.000003s : 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 : 0.000002s : 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 : 0.000026s : 0.00% optimize.overlap_opt_shard_grad_in_pipeline : 0.000002s : 0.00% optimize.control_data_broadcast_order : 0.000033s : 0.00% optimize.grouped_pairwise_exchange_alltoall : 0.000001s : 0.00% optimize.offloading_packed_experts : 0.000011s : 0.00% optimize.overlap_recompute_and_grad_model_parallel : 0.000010s : 0.00% optimize.overlap_grad_matmul_and_grad_allreduce : 0.000001s : 0.00% optimize.overlap_recompute_allgather_and_fa_grad : 0.000001s : 0.00% optimize.overlap_recompute_comm : 0.000002s : 0.00% optimize.overlap_grad_ring_attention : 0.000007s : 0.00% optimize.overlap_grad_flash_sp : 0.000043s : 0.00% optimize.begin_end_overlap_inline : 0.000001s : 0.00% optimize.split_matmul_comm_elemetwise : 0.000002s : 0.00% optimize.split_layernorm_comm : 0.000002s : 0.00% optimize.handle_group_info : 0.000001s : 0.00% optimize.symbol_engine_optimizer.build : 0.000017s : 0.00% optimize.symbol_engine_optimizer.elim_shapecalc : 0.000027s : 0.00% optimize.symbol_engine_optimizer.elim_not_effective : 0.000032s : 0.00% optimize.symbol_engine_optimizer.opt_reshape : 0.000017s : 0.00% optimize.symbol_engine_optimizer.fold_const_symbol : 0.262396s : 2.82% optimize.symbol_engine_optimizer.renormalize : 0.000002s : 0.00% detach_backward : 0.000006s : 0.00% pipeline_parallel_scheduler : 0.000003s : 0.00% auto_monad_reorder : 0.000080s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000997s : 0.01% validate : 0.000115s : 0.00% Time group info: ------[substitution.] 0.000648 95 0.98% : 0.000006s : 9: substitution.elim_not_effective 0.92% : 0.000006s : 9: substitution.fold_const_symbol 1.89% : 0.000012s : 10: substitution.graph_param_transform 79.65% : 0.000516s : 20: substitution.inline 1.74% : 0.000011s : 18: substitution.j_node_and_user_rematch 4.08% : 0.000026s : 2: substitution.less_batch_normalization 4.03% : 0.000026s : 18: substitution.remove_not_recompute_node 1.15% : 0.000007s : 2: substitution.replace_old_param 5.57% : 0.000036s : 7: substitution.switch_simplify ------[type_inference.] 8.772446 2 95.63% : 8.389352s : 1: type_inference.infer 4.37% : 0.383093s : 1: type_inference.specialize ------[replace.] 0.000291 27 56.84% : 0.000166s : 20: replace.inline 43.16% : 0.000126s : 7: replace.switch_simplify ------[match.] 0.000536 27 94.20% : 0.000505s : 20: match.inline 5.80% : 0.000031s : 7: match.switch_simplify ------[predicate.] 0.000609 3376 1.19% : 0.000007s : 38: predicate.accumulaten_eliminater 0.93% : 0.000006s : 10: predicate.ad_related_special_op_eliminate 0.52% : 0.000003s : 20: predicate.addn_check_dump 0.93% : 0.000006s : 38: predicate.addn_zero_filter 0.94% : 0.000006s : 38: predicate.adjust_all_reduce_mul_add 1.98% : 0.000012s : 58: predicate.arithmetic_simplify 1.06% : 0.000006s : 38: predicate.cast_eliminate 0.64% : 0.000004s : 20: predicate.check_bprop_eliminate 0.53% : 0.000003s : 20: predicate.compare_switch_simplify 0.12% : 0.000001s : 10: predicate.const_output_eliminate 0.65% : 0.000004s : 20: predicate.depend_value_elim 1.05% : 0.000006s : 38: predicate.dict_get_item_const_eliminator 1.22% : 0.000007s : 38: predicate.dict_get_item_eliminator 1.10% : 0.000007s : 38: predicate.dict_set_item_eliminator 0.80% : 0.000005s : 20: predicate.dumpgradient_eliminate 0.20% : 0.000001s : 10: predicate.elim_not_effective 0.40% : 0.000002s : 10: predicate.elim_shapecalc_of_broadcastargs 1.30% : 0.000008s : 48: predicate.environ_add_const_eliminate 1.20% : 0.000007s : 48: predicate.environ_get_add_eliminate 1.13% : 0.000007s : 48: predicate.environ_get_depend_swap 1.65% : 0.000010s : 68: predicate.environ_get_eliminate 1.24% : 0.000008s : 48: predicate.environ_get_set_eliminate 1.44% : 0.000009s : 58: predicate.exchange_switch_depend_value 2.08% : 0.000013s : 58: predicate.float_depend_g_call 0.49% : 0.000003s : 20: predicate.float_environ_get_switch 0.74% : 0.000004s : 30: predicate.float_tuple_getitem_switch 0.41% : 0.000003s : 10: predicate.fold_const_symbol 0.56% : 0.000003s : 20: predicate.get_grad_eliminate 0.20% : 0.000001s : 10: predicate.graph_param_transform 0.46% : 0.000003s : 20: predicate.incorporate_call 0.41% : 0.000003s : 20: predicate.incorporate_call_switch 5.74% : 0.000035s : 156: predicate.inline 0.88% : 0.000005s : 20: predicate.inline_without_move 0.31% : 0.000002s : 20: predicate.j_node_and_user_rematch 0.91% : 0.000006s : 20: predicate.less_batch_normalization 1.53% : 0.000009s : 58: predicate.list_to_tuple_eliminator_ 2.29% : 0.000014s : 96: predicate.load_eliminater 1.18% : 0.000007s : 10: predicate.loop_unroll_after_grad 2.41% : 0.000015s : 87: predicate.loop_unroll_before_grad 1.85% : 0.000011s : 58: predicate.make_slice_get_slice_eliminator 0.51% : 0.000003s : 20: predicate.merge_addn 0.56% : 0.000003s : 20: predicate.micro_step_allgather_replace 0.52% : 0.000003s : 20: predicate.mini_step_allgather_replace 0.94% : 0.000006s : 38: predicate.minmaximum_grad 1.19% : 0.000007s : 10: predicate.mutable_eliminate 0.32% : 0.000002s : 10: predicate.opt_reshape 0.30% : 0.000002s : 10: predicate.parallel_virtual_node 2.44% : 0.000015s : 58: predicate.partial_defer_inline 1.29% : 0.000008s : 48: predicate.partial_eliminate 0.95% : 0.000006s : 38: predicate.print_const_string_wrapper 0.56% : 0.000003s : 20: predicate.reduce_all_const_elim 1.41% : 0.000009s : 38: predicate.reduce_eliminate 2.32% : 0.000014s : 96: predicate.redundant_stop_gradient_eliminater 0.34% : 0.000002s : 20: predicate.remove_not_recompute_node 1.08% : 0.000007s : 58: predicate.replace_applicator 0.39% : 0.000002s : 20: predicate.replace_old_param 0.27% : 0.000002s : 10: predicate.reset_defer_inline 0.97% : 0.000006s : 38: predicate.reshape_eliminate 0.59% : 0.000004s : 20: predicate.row_tensor_add_zeros_like 0.37% : 0.000002s : 10: predicate.row_tensor_eliminate 0.91% : 0.000006s : 20: predicate.same_eliminate 0.28% : 0.000002s : 20: predicate.set_cell_output_no_recompute 0.59% : 0.000004s : 20: predicate.shard_identity_eliminate 0.65% : 0.000004s : 20: predicate.special_op_eliminate 0.67% : 0.000004s : 20: predicate.specialize_transform 0.91% : 0.000006s : 20: predicate.split_environ_get_set_with_tuple_value 0.61% : 0.000004s : 20: predicate.stack_unstack_eliminate 0.30% : 0.000002s : 10: predicate.switch_call_monad_eliminater 1.58% : 0.000010s : 58: predicate.switch_defer_inline 2.05% : 0.000012s : 78: predicate.switch_layer_defer_inline 5.67% : 0.000035s : 189: predicate.switch_simplify 0.97% : 0.000006s : 38: predicate.tile_eliminate 0.95% : 0.000006s : 38: predicate.transpose_eliminate 2.01% : 0.000012s : 58: predicate.tuple_list_convert_item_index_to_positive 2.04% : 0.000012s : 58: predicate.tuple_list_get_item_const_eliminator 1.61% : 0.000010s : 58: predicate.tuple_list_get_item_depend_reorder 2.93% : 0.000018s : 78: predicate.tuple_list_get_item_eliminator 1.77% : 0.000011s : 58: predicate.tuple_list_get_set_item_eliminator 2.37% : 0.000014s : 78: predicate.tuple_list_set_item_eliminator 1.50% : 0.000009s : 58: predicate.tuple_to_list_eliminator_ 2.36% : 0.000014s : 96: predicate.updatestate_pure_node_eliminater 3.03% : 0.000018s : 116: predicate.updatestate_useless_node_eliminater 0.29% : 0.000002s : 10: predicate.value_based_eliminate 0.70% : 0.000004s : 20: predicate.virtual_dataset_eliminate 0.65% : 0.000004s : 20: predicate.virtual_output_eliminate 0.25% : 0.000001s : 10: predicate.virtual_view_grad_eliminate 0.36% : 0.000002s : 10: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.846409 154 72.85% : 0.616614s : 123: func_graph_cloner_run.FuncGraphClonerGraph 27.15% : 0.229795s : 31: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 10.712440 192 0.00% : 0.000004s : 1: ForceFp32Comm 1.77% : 0.190135s : 1: add_attr 1.77% : 0.190114s : 1: add_attr_with_inline 0.00% : 0.000004s : 1: add_comm_op_reuse_tag 0.00% : 0.000140s : 1: add_recomputation 0.00% : 0.000006s : 1: assign_add_opt 0.00% : 0.000324s : 1: auto_monad 0.00% : 0.000088s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: begin_end_overlap_inline 0.00% : 0.000008s : 1: bias_add_comm_swap 0.01% : 0.000752s : 1: bootstrap 0.00% : 0.000052s : 1: cconv 0.00% : 0.000004s : 1: comm_op_add_attrs 0.00% : 0.000036s : 1: control_data_broadcast_order 0.00% : 0.000040s : 1: convert_after_rewriter 0.00% : 0.000106s : 1: cse_after_recomputation 0.00% : 0.000006s : 1: dataset_repeat_opt 0.00% : 0.000009s : 1: detach_backward 0.00% : 0.000033s : 1: environ_conv 0.00% : 0.000136s : 1: event_method 0.00% : 0.000005s : 1: full_micro_interleaved_order_control 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000018s : 1: graph_reusing 0.00% : 0.000004s : 1: grouped_pairwise_exchange_alltoall 0.00% : 0.000005s : 1: handle_group_info 0.00% : 0.000007s : 1: inline 0.00% : 0.000006s : 1: insert-virtual-dataset 0.00% : 0.000004s : 1: interleave_parallel_branches 0.00% : 0.000006s : 1: interleave_split_concat_branches 0.00% : 0.000006s : 1: label_fine_grained_interleaved_index 0.00% : 0.000011s : 1: label_micro_interleaved_index 0.01% : 0.000943s : 1: loop_unroll 0.00% : 0.000006s : 1: merge_cast_opt 0.00% : 0.000005s : 1: micro_interleaved_order_control 0.01% : 0.001061s : 1: mutable_eliminate 0.00% : 0.000014s : 1: offloading_packed_experts 0.00% : 0.000043s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000046s : 1: opt.transform.mutable_eliminate 0.04% : 0.003977s : 78: opt.transform.opt_a 0.00% : 0.000075s : 1: opt.transform.opt_after_cconv 0.00% : 0.000066s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000324s : 28: opt.transform.opt_b 0.00% : 0.000135s : 2: opt.transform.opt_trans_graph 2.45% : 0.262462s : 4: opt.transform.symbol_engine_opt 2.37% : 0.253720s : 1: opt_a 0.00% : 0.000338s : 1: opt_after_cconv 0.01% : 0.001011s : 1: opt_after_jit_grad 0.01% : 0.000657s : 1: opt_b 4.87% : 0.521651s : 1: optimize 0.00% : 0.000049s : 1: optimize_parallel_all_gather_comm 0.00% : 0.000015s : 1: order_py_execute_after_rewriter 0.00% : 0.000049s : 1: overlap_grad_flash_sp 0.00% : 0.000004s : 1: overlap_grad_matmul_and_grad_allreduce 0.00% : 0.000012s : 1: overlap_grad_ring_attention 0.00% : 0.000006s : 1: overlap_opt_shard_grad_in_pipeline 0.00% : 0.000031s : 1: overlap_opt_shard_in_pipeline 0.00% : 0.000008s : 1: overlap_param_gather 0.00% : 0.000004s : 1: overlap_recompute_allgather_and_fa_grad 0.00% : 0.000013s : 1: overlap_recompute_and_grad_model_parallel 0.00% : 0.000005s : 1: overlap_recompute_comm 0.00% : 0.000009s : 1: parallel-infer-symbol 0.00% : 0.000005s : 1: parallel-infer-symbol-second 0.00% : 0.000007s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pipeline_parallel_scheduler 0.00% : 0.000005s : 1: pipeline_split 0.00% : 0.000120s : 1: pre_auto_parallel 0.00% : 0.000098s : 1: py_interpret_to_execute 0.00% : 0.000043s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000004s : 1: remove_cast_before_assign_add 0.00% : 0.000312s : 1: remove_dup_value 0.15% : 0.016249s : 1: renormalize.infer 2.15% : 0.230426s : 1: renormalize.specialize 0.00% : 0.000006s : 1: reorder_send_recv_between_fp_bp 0.00% : 0.000013s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000549s : 1: rewriter_after_opt_a 0.00% : 0.000293s : 1: rewriter_before_opt_a 0.00% : 0.000005s : 1: slice_cell_reuse_recomputed_activation 0.00% : 0.000005s : 1: slice_recompute_activation 0.00% : 0.000005s : 1: split_layernorm_comm 0.00% : 0.000005s : 1: split_matmul_comm_elemetwise 0.00% : 0.000018s : 1: swap_dp_allreduce_reducescatter 2.45% : 0.262609s : 1: symbol_engine_optimizer 0.00% : 0.000187s : 1: tuple_transform 81.89% : 8.772650s : 1: type_inference . [hook] pytest_runtest_teardown:test_tensor_fancy_index_set_item_032[0] tests/st/tensor/test_setitem.py::test_tensor_fancy_index_set_item_032[0],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") test_setitem.py::test_tensor_fancy_index_set_item_032[0] /usr/local/Ascend/cann-8.5.0/python/site-packages/asc_op_compile_base/asc_op_compiler/ascendc_compile_gen_code.py:161: DeprecationWarning: invalid escape sequence \w match = re.search(f'{option}=(\w+)', ' '.join(compile_options)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 26 warnings in 329.91s (0:05:29) ==================