==================================================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/mint, configfile: ../../../../../../sault/virtual_test/virtualenv_001/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_reshape.py . [hook] pytest_runtest_teardown:test_reshape_jit_mode[pynative] tests/st/mint/test_reshape.py::test_reshape_jit_mode[pynative],max_mem:2.0M [WARNING] PARSER(166452,ffff8872ef30,python3.9):2026-01-29-17:39:41.078.688 [mindspore/ccsrc/frontend/jit/ps/parse/data_converter.cc:661] CheckAPI] The mint interface reshape was called, and the operators under this interface have different view capabilities on pynative and graph mode. Use this interface with caution in graph mode, as it may produce unexpected results. For more information, please refer to: https://www.mindspore.cn/docs/en/master/features/view.html TotalTime = 1.33475, [30] [bootstrap]: 0.00076469 [type_inference]: 1.07976 [event_method]: 2.246e-05 [auto_monad]: 0.00013456 [graph_reusing]: 7.41999e-06 [pre_auto_parallel]: 1.274e-05 [py_interpret_to_execute]: 0.00039054 [rewriter_before_opt_a]: 0.00010138 [expand_dump_flag]: 3.41999e-06 [jit_opt_a]: 0.250429, [2] [Cycle 1]: 0.00432884, [27] [switch_simplify]: 7.875e-05 [loop_unroll]: 3.304e-05 [a_1]: 0.00063212 [with_stream_mark]: 3.001e-05 [recompute_prepare]: 1.23e-05 [updatestate_depend_eliminate]: 5.36998e-06 [updatestate_assign_eliminate]: 3.98001e-06 [updatestate_loads_eliminate]: 3.43999e-06 [parameter_eliminate]: 1.76998e-06 [specialize_transform]: 8.82e-06 [updatestate_useless_node_eliminater]: 7.43e-06 [accelerated_algorithm]: 7.47002e-06 [meta_shard_fg_expand]: 2.41998e-06 [get_grad_eliminate_]: 6.51e-06 [merge_forward]: 4.79e-06 [cell_reuse_recompute_pass]: 1.06002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.454e-05 [j_node_and_user_rematch]: 1.249e-05 [meta_fg_expand]: 2.96001e-06 [replace_old_param]: 1.201e-05 [inline_without_move]: 6.76999e-06 [renormalize]: 0.0030732 [add_forward_monad_depend]: 1.705e-05 [auto_monad_grad]: 2.76e-06 [auto_monad_eliminator]: 2.035e-05 [cse]: 3.417e-05 [replace_applicator]: 2.422e-05 [Cycle 2]: 0.00045054, [27] [switch_simplify]: 7.74002e-06 [loop_unroll]: 7.08e-06 [a_1]: 0.00016257 [with_stream_mark]: 1.693e-05 [recompute_prepare]: 7.92e-06 [updatestate_depend_eliminate]: 4.30999e-06 [updatestate_assign_eliminate]: 3.69002e-06 [updatestate_loads_eliminate]: 3.04001e-06 [parameter_eliminate]: 1.94e-06 [specialize_transform]: 6.44001e-06 [updatestate_useless_node_eliminater]: 6.48998e-06 [accelerated_algorithm]: 7.43e-06 [meta_shard_fg_expand]: 2.20002e-06 [get_grad_eliminate_]: 5.92001e-06 [merge_forward]: 5.12999e-06 [cell_reuse_recompute_pass]: 2.25002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.653e-05 [j_node_and_user_rematch]: 9.69999e-06 [meta_fg_expand]: 2.61e-06 [replace_old_param]: 9.57001e-06 [inline_without_move]: 5.63002e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.35001e-06 [auto_monad_grad]: 1.22e-06 [auto_monad_eliminator]: 6.53e-06 [cse]: 1.58e-05 [replace_applicator]: 6.98e-06 [py_interpret_to_execute_after_opt_a]: 1.441e-05 [rewriter_after_opt_a]: 6.54e-05 [convert_after_rewriter]: 9.05999e-06 [order_py_execute_after_rewriter]: 5.84999e-06 [mutable_eliminate]: 0.00076042 [jit_opt_b]: 6.293e-05, [1] [Cycle 1]: 5.328e-05, [2] [frontend_op_eliminate]: 2.07e-05 [inline_after_opt_a]: 1.972e-05 [cconv]: 3.464e-05 [loop_unroll]: 0.00047583 [jit_opt_after_cconv]: 0.00020445, [1] [Cycle 1]: 0.00019679, [11] [c_1]: 2.725e-05 [parameter_eliminate]: 4.94998e-06 [updatestate_depend_eliminate]: 1.015e-05 [updatestate_assign_eliminate]: 3.38e-06 [updatestate_loads_eliminate]: 2.89001e-06 [cse]: 3.198e-05 [call_graph_tuple_transform]: 2.611e-05 [tuple_list_get_item_eliminator]: 6.79999e-06 [none_parameter_eliminate]: 1.48002e-06 [renormalize]: 1.10999e-06 [switch_simplify]: 6.79999e-06 [remove_dup_value]: 1.66e-05 [partial_unused_args_eliminate]: 2.22001e-06 [environ_conv]: 2.483e-05 [add_recomputation]: 7.953e-05 [cse_after_recomputation]: 2.939e-05, [1] [Cycle 1]: 2.235e-05, [1] [cse]: 1.564e-05 [auto_monad_reorder]: 2.352e-05 [get_jit_bprop_graph]: 2.41e-06 [rewriter_after_jit_bprop_graph]: 0.00019049 [opt_after_jit_grad]: 0.00057628 [symbol_engine_optimizer]: 9.294e-05, [1] [Cycle 1]: 8.57e-05, [6] [build]: 5.31998e-06 [elim_shapecalc]: 9.71998e-06 [elim_not_effective]: 1.48e-05 [opt_reshape]: 1.06e-05 [fold_const_symbol]: 1.225e-05 [renormalize]: 1.17999e-06 [validate]: 8.671e-05 Sums bootstrap : 0.000765s : 0.07% type_inference : 1.079765s : 99.22% event_method : 0.000022s : 0.00% auto_monad : 0.000135s : 0.01% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000391s : 0.04% rewriter_before_opt_a : 0.000101s : 0.01% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000086s : 0.01% jit_opt_a.loop_unroll : 0.000040s : 0.00% jit_opt_a.a_1 : 0.000795s : 0.07% jit_opt_a.with_stream_mark : 0.000047s : 0.00% jit_opt_a.recompute_prepare : 0.000020s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000015s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000014s : 0.00% jit_opt_a.accelerated_algorithm : 0.000015s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000012s : 0.00% jit_opt_a.merge_forward : 0.000010s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000051s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000022s : 0.00% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000022s : 0.00% jit_opt_a.inline_without_move : 0.000012s : 0.00% jit_opt_a.renormalize : 0.003073s : 0.28% jit_opt_a.add_forward_monad_depend : 0.000018s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000027s : 0.00% jit_opt_a.cse : 0.000050s : 0.00% jit_opt_a.replace_applicator : 0.000031s : 0.00% py_interpret_to_execute_after_opt_a : 0.000014s : 0.00% rewriter_after_opt_a : 0.000065s : 0.01% convert_after_rewriter : 0.000009s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000760s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000021s : 0.00% jit_opt_b.inline_after_opt_a : 0.000020s : 0.00% cconv : 0.000035s : 0.00% loop_unroll : 0.000476s : 0.04% jit_opt_after_cconv.c_1 : 0.000027s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000032s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000026s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000007s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000001s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000007s : 0.00% remove_dup_value : 0.000017s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000025s : 0.00% add_recomputation : 0.000080s : 0.01% cse_after_recomputation.cse : 0.000016s : 0.00% auto_monad_reorder : 0.000024s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000190s : 0.02% opt_after_jit_grad : 0.000576s : 0.05% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000015s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000012s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000087s : 0.01% Time group info: ------[substitution.] 0.000270 28 0.80% : 0.000002s : 2: substitution.elim_not_effective 0.78% : 0.000002s : 2: substitution.fold_const_symbol 2.75% : 0.000007s : 4: substitution.graph_param_transform 73.50% : 0.000198s : 5: substitution.inline 1.61% : 0.000004s : 4: substitution.j_node_and_user_rematch 0.47% : 0.000001s : 1: substitution.opt_reshape 6.57% : 0.000018s : 4: substitution.remove_not_recompute_node 2.30% : 0.000006s : 2: substitution.replace_old_param 8.35% : 0.000023s : 3: substitution.reshape_eliminate 2.87% : 0.000008s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.079653 2 99.82% : 1.077667s : 1: type_inference.infer 0.18% : 0.001986s : 1: type_inference.specialize ------[replace.] 0.000063 6 84.62% : 0.000053s : 5: replace.inline 15.38% : 0.000010s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000202 6 96.55% : 0.000195s : 5: match.inline 3.45% : 0.000007s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000170 867 1.07% : 0.000002s : 13: predicate.accumulaten_eliminater 1.01% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 1.09% : 0.000002s : 13: predicate.addn_check_dump 1.32% : 0.000002s : 13: predicate.addn_zero_filter 2.01% : 0.000003s : 13: predicate.arithmetic_simplify 1.45% : 0.000002s : 13: predicate.cast_eliminate 0.41% : 0.000001s : 4: predicate.check_bprop_eliminate 1.05% : 0.000002s : 13: predicate.compare_switch_simplify 1.33% : 0.000002s : 13: predicate.depend_value_elim 0.95% : 0.000002s : 13: predicate.dict_get_item_const_eliminator 1.19% : 0.000002s : 13: predicate.dict_get_item_eliminator 1.17% : 0.000002s : 13: predicate.dict_set_item_eliminator 1.01% : 0.000002s : 4: predicate.dumpgradient_eliminate 0.44% : 0.000001s : 4: predicate.elim_not_effective 0.63% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.04% : 0.000002s : 13: predicate.environ_add_const_eliminate 0.94% : 0.000002s : 13: predicate.environ_get_add_eliminate 0.93% : 0.000002s : 13: predicate.environ_get_depend_swap 1.20% : 0.000002s : 13: predicate.environ_get_eliminate 0.92% : 0.000002s : 13: predicate.environ_get_set_eliminate 0.24% : 0.000000s : 4: predicate.fold_const_symbol 0.90% : 0.000002s : 8: predicate.get_grad_eliminate 0.24% : 0.000000s : 4: predicate.graph_param_transform 4.80% : 0.000008s : 27: predicate.inline 0.78% : 0.000001s : 8: predicate.inline_without_move 0.43% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.57% : 0.000003s : 8: predicate.less_batch_normalization 1.20% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.39% : 0.000002s : 18: predicate.load_eliminater 1.15% : 0.000002s : 4: predicate.loop_unroll_after_grad 3.61% : 0.000006s : 37: predicate.loop_unroll_before_grad 1.72% : 0.000003s : 17: predicate.make_slice_get_slice_eliminator 0.88% : 0.000001s : 13: predicate.merge_addn 1.01% : 0.000002s : 13: predicate.minmaximum_grad 1.50% : 0.000003s : 4: predicate.mutable_eliminate 0.64% : 0.000001s : 4: predicate.opt_reshape 1.85% : 0.000003s : 18: predicate.partial_eliminate 1.26% : 0.000002s : 13: predicate.print_const_string_wrapper 2.05% : 0.000003s : 13: predicate.reduce_eliminate 1.16% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.47% : 0.000001s : 8: predicate.remove_not_recompute_node 1.72% : 0.000003s : 22: predicate.replace_applicator 0.50% : 0.000001s : 8: predicate.replace_old_param 0.32% : 0.000001s : 4: predicate.reset_defer_inline 10.51% : 0.000018s : 13: predicate.reshape_eliminate 1.44% : 0.000002s : 13: predicate.row_tensor_add_zeros_like 0.76% : 0.000001s : 4: predicate.row_tensor_eliminate 1.23% : 0.000002s : 13: predicate.same_eliminate 0.64% : 0.000001s : 8: predicate.set_cell_output_no_recompute 0.70% : 0.000001s : 8: predicate.special_op_eliminate 1.00% : 0.000002s : 8: predicate.specialize_transform 1.53% : 0.000003s : 13: predicate.split_environ_get_set_with_tuple_value 1.07% : 0.000002s : 13: predicate.stack_unstack_eliminate 0.48% : 0.000001s : 4: predicate.switch_call_monad_eliminater 1.93% : 0.000003s : 19: predicate.switch_defer_inline 1.84% : 0.000003s : 19: predicate.switch_layer_defer_inline 6.39% : 0.000011s : 60: predicate.switch_simplify 1.22% : 0.000002s : 13: predicate.tile_eliminate 1.07% : 0.000002s : 13: predicate.transpose_eliminate 1.38% : 0.000002s : 13: predicate.tuple_list_convert_item_index_to_positive 1.05% : 0.000002s : 13: predicate.tuple_list_get_item_depend_reorder 3.73% : 0.000006s : 22: predicate.tuple_list_get_item_eliminator 1.76% : 0.000003s : 13: predicate.tuple_list_set_item_eliminator 1.24% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.38% : 0.000002s : 18: predicate.updatestate_pure_node_eliminater 2.42% : 0.000004s : 26: predicate.updatestate_useless_node_eliminater 1.60% : 0.000003s : 13: predicate.value_based_eliminate 0.35% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.71% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.002882 23 72.16% : 0.002080s : 16: func_graph_cloner_run.FuncGraphClonerGraph 27.84% : 0.000802s : 7: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.338812 72 0.01% : 0.000083s : 1: add_recomputation 0.01% : 0.000140s : 1: auto_monad 0.00% : 0.000026s : 1: auto_monad_reorder 0.06% : 0.000787s : 1: bootstrap 0.00% : 0.000037s : 1: cconv 0.00% : 0.000012s : 1: convert_after_rewriter 0.00% : 0.000032s : 1: cse_after_recomputation 0.00% : 0.000027s : 1: environ_conv 0.00% : 0.000029s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 18.71% : 0.250432s : 1: jit_opt_a 0.02% : 0.000207s : 1: jit_opt_after_cconv 0.00% : 0.000066s : 1: jit_opt_b 0.04% : 0.000485s : 1: loop_unroll 0.06% : 0.000771s : 1: mutable_eliminate 0.08% : 0.001085s : 26: opt.transform.jit_opt_a 0.00% : 0.000063s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000033s : 4: opt.transform.jit_opt_b 0.00% : 0.000014s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.00% : 0.000028s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000043s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000587s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.03% : 0.000400s : 1: py_interpret_to_execute 0.00% : 0.000017s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000020s : 1: remove_dup_value 0.16% : 0.002152s : 1: renormalize.infer 0.07% : 0.000908s : 1: renormalize.specialize 0.01% : 0.000195s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000069s : 1: rewriter_after_opt_a 0.01% : 0.000107s : 1: rewriter_before_opt_a 0.01% : 0.000096s : 1: symbol_engine_optimizer 80.65% : 1.079794s : 1: type_inference TotalTime = 1.18172, [30] [bootstrap]: 0.00054709 [type_inference]: 0.949891 [event_method]: 0.00040647 [auto_monad]: 0.00016582 [graph_reusing]: 1.091e-05 [pre_auto_parallel]: 4.03999e-06 [py_interpret_to_execute]: 7.806e-05 [rewriter_before_opt_a]: 0.00017225 [expand_dump_flag]: 4.23999e-06 [jit_opt_a]: 0.227103, [2] [Cycle 1]: 0.137886, [27] [switch_simplify]: 0.00024983 [loop_unroll]: 8.269e-05 [a_1]: 0.00154826 [with_stream_mark]: 4.098e-05 [recompute_prepare]: 2.91e-05 [updatestate_depend_eliminate]: 9.94999e-06 [updatestate_assign_eliminate]: 7.66001e-06 [updatestate_loads_eliminate]: 6.46999e-06 [parameter_eliminate]: 4.25e-06 [specialize_transform]: 1.679e-05 [updatestate_useless_node_eliminater]: 1.484e-05 [accelerated_algorithm]: 1.635e-05 [meta_shard_fg_expand]: 4.79e-06 [get_grad_eliminate_]: 1.52e-05 [merge_forward]: 9.23997e-06 [cell_reuse_recompute_pass]: 1.07998e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.167e-05 [j_node_and_user_rematch]: 3.454e-05 [meta_fg_expand]: 0.00255833 [replace_old_param]: 8.808e-05 [inline_without_move]: 7.326e-05 [renormalize]: 0.132607 [add_forward_monad_depend]: 1.873e-05 [auto_monad_grad]: 2.88998e-06 [auto_monad_eliminator]: 1.843e-05 [cse]: 3.472e-05 [replace_applicator]: 2.384e-05 [Cycle 2]: 0.00051476, [27] [switch_simplify]: 6.30002e-06 [loop_unroll]: 4.92e-06 [a_1]: 6.246e-05 [with_stream_mark]: 1.769e-05 [recompute_prepare]: 4.18999e-06 [updatestate_depend_eliminate]: 3.63999e-06 [updatestate_assign_eliminate]: 2.58998e-06 [updatestate_loads_eliminate]: 2.43e-06 [parameter_eliminate]: 1.83002e-06 [specialize_transform]: 4.05e-06 [updatestate_useless_node_eliminater]: 3.79002e-06 [accelerated_algorithm]: 4.52e-06 [meta_shard_fg_expand]: 1.89e-06 [get_grad_eliminate_]: 3.75e-06 [merge_forward]: 3.62002e-06 [cell_reuse_recompute_pass]: 3.00998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.793e-05 [j_node_and_user_rematch]: 7.11001e-06 [meta_fg_expand]: 0.00018659 [replace_old_param]: 7.02002e-06 [inline_without_move]: 4.27998e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.81998e-06 [auto_monad_grad]: 1.52001e-06 [auto_monad_eliminator]: 6.84999e-06 [cse]: 1.484e-05 [replace_applicator]: 4.89e-06 [py_interpret_to_execute_after_opt_a]: 1.799e-05 [rewriter_after_opt_a]: 0.00041725 [convert_after_rewriter]: 1.423e-05 [order_py_execute_after_rewriter]: 5.15001e-06 [mutable_eliminate]: 0.00084313 [jit_opt_b]: 5.782e-05, [1] [Cycle 1]: 4.766e-05, [2] [frontend_op_eliminate]: 1.424e-05 [inline_after_opt_a]: 1.828e-05 [cconv]: 3.879e-05 [loop_unroll]: 0.00076571 [jit_opt_after_cconv]: 0.00017345, [1] [Cycle 1]: 0.00016502, [11] [c_1]: 1.878e-05 [parameter_eliminate]: 6.44001e-06 [updatestate_depend_eliminate]: 9.83002e-06 [updatestate_assign_eliminate]: 2.88998e-06 [updatestate_loads_eliminate]: 2.51e-06 [cse]: 3.441e-05 [call_graph_tuple_transform]: 2.015e-05 [tuple_list_get_item_eliminator]: 5.17e-06 [none_parameter_eliminate]: 1.72001e-06 [renormalize]: 7.7e-07 [switch_simplify]: 5.12e-06 [remove_dup_value]: 1.624e-05 [partial_unused_args_eliminate]: 2.62001e-06 [environ_conv]: 5.61e-06 [add_recomputation]: 4.072e-05 [cse_after_recomputation]: 2.113e-05, [1] [Cycle 1]: 1.504e-05, [1] [cse]: 8.69e-06 [auto_monad_reorder]: 1.395e-05 [get_jit_bprop_graph]: 2.31998e-06 [rewriter_after_jit_bprop_graph]: 6.69999e-06 [opt_after_jit_grad]: 0.00051772 [symbol_engine_optimizer]: 7.663e-05, [1] [Cycle 1]: 6.922e-05, [6] [build]: 3.39001e-06 [elim_shapecalc]: 7.48e-06 [elim_not_effective]: 1.313e-05 [opt_reshape]: 5.81e-06 [fold_const_symbol]: 7.58999e-06 [renormalize]: 8.89995e-07 [validate]: 3.561e-05 Sums bootstrap : 0.000547s : 0.05% type_inference : 0.949891s : 86.97% event_method : 0.000406s : 0.04% auto_monad : 0.000166s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000078s : 0.01% rewriter_before_opt_a : 0.000172s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000256s : 0.02% jit_opt_a.loop_unroll : 0.000088s : 0.01% jit_opt_a.a_1 : 0.001611s : 0.15% jit_opt_a.with_stream_mark : 0.000059s : 0.01% jit_opt_a.recompute_prepare : 0.000033s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000006s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000019s : 0.00% jit_opt_a.accelerated_algorithm : 0.000021s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000007s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000019s : 0.00% jit_opt_a.merge_forward : 0.000013s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000050s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000042s : 0.00% jit_opt_a.meta_fg_expand : 0.002745s : 0.25% jit_opt_a.replace_old_param : 0.000095s : 0.01% jit_opt_a.inline_without_move : 0.000078s : 0.01% jit_opt_a.renormalize : 0.132607s : 12.14% jit_opt_a.add_forward_monad_depend : 0.000021s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000025s : 0.00% jit_opt_a.cse : 0.000050s : 0.00% jit_opt_a.replace_applicator : 0.000029s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000417s : 0.04% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000005s : 0.00% mutable_eliminate : 0.000843s : 0.08% jit_opt_b.frontend_op_eliminate : 0.000014s : 0.00% jit_opt_b.inline_after_opt_a : 0.000018s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000766s : 0.07% jit_opt_after_cconv.c_1 : 0.000019s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000034s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000020s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000005s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000005s : 0.00% remove_dup_value : 0.000016s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000006s : 0.00% add_recomputation : 0.000041s : 0.00% cse_after_recomputation.cse : 0.000009s : 0.00% auto_monad_reorder : 0.000014s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000518s : 0.05% symbol_engine_optimizer.build : 0.000003s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000007s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000013s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000006s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000008s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000036s : 0.00% Time group info: ------[substitution.] 0.000505 69 0.37% : 0.000002s : 1: substitution.elim_not_effective 0.23% : 0.000001s : 1: substitution.fold_const_symbol 1.16% : 0.000006s : 1: substitution.graph_param_transform 73.06% : 0.000369s : 14: substitution.inline 5.37% : 0.000027s : 2: substitution.inline_without_move 1.82% : 0.000009s : 9: substitution.j_node_and_user_rematch 0.82% : 0.000004s : 2: substitution.minmaximum_grad 1.65% : 0.000008s : 9: substitution.partial_eliminate 1.56% : 0.000008s : 9: substitution.remove_not_recompute_node 0.65% : 0.000003s : 1: substitution.replace_applicator 1.58% : 0.000008s : 7: substitution.replace_old_param 2.08% : 0.000010s : 2: substitution.reshape_eliminate 0.83% : 0.000004s : 1: substitution.set_cell_output_no_recompute 3.12% : 0.000016s : 3: substitution.switch_simplify 1.73% : 0.000009s : 2: substitution.tuple_list_convert_item_index_to_positive 1.10% : 0.000006s : 2: substitution.tuple_list_get_item_depend_reorder 2.87% : 0.000014s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.949743 2 99.58% : 0.945743s : 1: type_inference.infer 0.42% : 0.004000s : 1: type_inference.specialize ------[replace.] 0.000213 18 57.35% : 0.000122s : 14: replace.inline 37.10% : 0.000079s : 3: replace.switch_simplify 5.56% : 0.000012s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000377 18 95.58% : 0.000360s : 14: match.inline 3.60% : 0.000014s : 3: match.switch_simplify 0.82% : 0.000003s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000277 1710 1.36% : 0.000004s : 29: predicate.accumulaten_eliminater 0.37% : 0.000001s : 1: predicate.ad_related_special_op_eliminate 1.25% : 0.000003s : 29: predicate.addn_check_dump 1.50% : 0.000004s : 29: predicate.addn_zero_filter 2.05% : 0.000006s : 29: predicate.arithmetic_simplify 1.46% : 0.000004s : 29: predicate.cast_eliminate 0.15% : 0.000000s : 1: predicate.check_bprop_eliminate 1.34% : 0.000004s : 29: predicate.compare_switch_simplify 1.44% : 0.000004s : 29: predicate.depend_value_elim 1.36% : 0.000004s : 29: predicate.dict_get_item_const_eliminator 1.37% : 0.000004s : 29: predicate.dict_get_item_eliminator 1.36% : 0.000004s : 29: predicate.dict_set_item_eliminator 0.39% : 0.000001s : 1: predicate.dumpgradient_eliminate 0.14% : 0.000000s : 1: predicate.elim_not_effective 0.30% : 0.000001s : 1: predicate.elim_shapecalc_of_broadcastargs 1.58% : 0.000004s : 29: predicate.environ_add_const_eliminate 1.28% : 0.000004s : 29: predicate.environ_get_add_eliminate 1.23% : 0.000003s : 29: predicate.environ_get_depend_swap 1.50% : 0.000004s : 29: predicate.environ_get_eliminate 1.42% : 0.000004s : 29: predicate.environ_get_set_eliminate 0.04% : 0.000000s : 1: predicate.fold_const_symbol 0.82% : 0.000002s : 14: predicate.get_grad_eliminate 0.13% : 0.000000s : 1: predicate.graph_param_transform 4.89% : 0.000014s : 46: predicate.inline 2.46% : 0.000007s : 38: predicate.inline_without_move 0.42% : 0.000001s : 14: predicate.j_node_and_user_rematch 1.12% : 0.000003s : 14: predicate.less_batch_normalization 1.63% : 0.000004s : 30: predicate.list_to_tuple_eliminator_ 1.67% : 0.000005s : 31: predicate.load_eliminater 0.70% : 0.000002s : 1: predicate.loop_unroll_after_grad 4.15% : 0.000011s : 78: predicate.loop_unroll_before_grad 1.83% : 0.000005s : 30: predicate.make_slice_get_slice_eliminator 1.34% : 0.000004s : 29: predicate.merge_addn 1.27% : 0.000003s : 29: predicate.minmaximum_grad 1.07% : 0.000003s : 1: predicate.mutable_eliminate 0.24% : 0.000001s : 1: predicate.opt_reshape 1.98% : 0.000005s : 31: predicate.partial_eliminate 1.47% : 0.000004s : 29: predicate.print_const_string_wrapper 1.80% : 0.000005s : 29: predicate.reduce_eliminate 1.48% : 0.000004s : 30: predicate.redundant_stop_gradient_eliminater 0.57% : 0.000002s : 14: predicate.remove_not_recompute_node 1.61% : 0.000004s : 32: predicate.replace_applicator 1.46% : 0.000004s : 38: predicate.replace_old_param 0.26% : 0.000001s : 1: predicate.reset_defer_inline 1.78% : 0.000005s : 29: predicate.reshape_eliminate 1.46% : 0.000004s : 29: predicate.row_tensor_add_zeros_like 0.44% : 0.000001s : 1: predicate.row_tensor_eliminate 1.62% : 0.000004s : 29: predicate.same_eliminate 0.52% : 0.000001s : 14: predicate.set_cell_output_no_recompute 0.34% : 0.000001s : 2: predicate.special_op_eliminate 0.91% : 0.000003s : 14: predicate.specialize_transform 1.78% : 0.000005s : 29: predicate.split_environ_get_set_with_tuple_value 1.51% : 0.000004s : 29: predicate.stack_unstack_eliminate 0.20% : 0.000001s : 1: predicate.switch_call_monad_eliminater 2.80% : 0.000008s : 44: predicate.switch_defer_inline 2.53% : 0.000007s : 44: predicate.switch_layer_defer_inline 7.92% : 0.000022s : 129: predicate.switch_simplify 1.49% : 0.000004s : 29: predicate.tile_eliminate 1.44% : 0.000004s : 29: predicate.transpose_eliminate 1.66% : 0.000005s : 29: predicate.tuple_list_convert_item_index_to_positive 1.54% : 0.000004s : 29: predicate.tuple_list_get_item_depend_reorder 3.04% : 0.000008s : 32: predicate.tuple_list_get_item_eliminator 1.90% : 0.000005s : 29: predicate.tuple_list_set_item_eliminator 1.56% : 0.000004s : 30: predicate.tuple_to_list_eliminator_ 1.49% : 0.000004s : 31: predicate.updatestate_pure_node_eliminater 2.65% : 0.000007s : 45: predicate.updatestate_useless_node_eliminater 1.87% : 0.000005s : 29: predicate.value_based_eliminate 0.07% : 0.000000s : 1: predicate.virtual_view_grad_eliminate 0.21% : 0.000001s : 1: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004851 47 84.05% : 0.004077s : 30: func_graph_cloner_run.FuncGraphClonerGraph 15.95% : 0.000774s : 17: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.316667 72 0.00% : 0.000043s : 1: add_recomputation 0.01% : 0.000176s : 1: auto_monad 0.00% : 0.000017s : 1: auto_monad_reorder 0.04% : 0.000579s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.00% : 0.000024s : 1: cse_after_recomputation 0.00% : 0.000008s : 1: environ_conv 0.03% : 0.000420s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000014s : 1: graph_reusing 17.25% : 0.227108s : 1: jit_opt_a 0.01% : 0.000177s : 1: jit_opt_after_cconv 0.00% : 0.000061s : 1: jit_opt_b 0.06% : 0.000779s : 1: loop_unroll 0.07% : 0.000859s : 1: mutable_eliminate 0.18% : 0.002313s : 26: opt.transform.jit_opt_a 0.00% : 0.000045s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000023s : 4: opt.transform.jit_opt_b 0.00% : 0.000015s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000021s : 1: opt.transform.mutable_eliminate 0.00% : 0.000019s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000028s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000528s : 1: opt_after_jit_grad 0.00% : 0.000007s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000083s : 1: py_interpret_to_execute 0.00% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000019s : 1: remove_dup_value 10.01% : 0.131750s : 1: renormalize.infer 0.06% : 0.000841s : 1: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000426s : 1: rewriter_after_opt_a 0.01% : 0.000177s : 1: rewriter_before_opt_a 0.01% : 0.000080s : 1: symbol_engine_optimizer 72.15% : 0.949916s : 1: type_inference . [hook] pytest_runtest_teardown:test_reshape_jit_mode[KBK] tests/st/mint/test_reshape.py::test_reshape_jit_mode[KBK],max_mem:4.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 178.43s (0:02:58) ==================