==================================================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_007/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_permute.py . [hook] pytest_runtest_teardown:test_permute_non_contiguous[pynative] tests/st/mint/test_permute.py::test_permute_non_contiguous[pynative],max_mem:2.0M TotalTime = 6.13018, [33] [bootstrap]: 0.00066576 [type_inference]: 1.62578 [event_method]: 2.184e-05 [auto_monad]: 0.00022646 [graph_reusing]: 6.26998e-06 [pre_auto_parallel]: 1.253e-05 [py_interpret_to_execute]: 0.00042564 [rewriter_before_opt_a]: 9.134e-05 [expand_dump_flag]: 4.39002e-06 [jit_opt_a]: 0.0903191, [2] [Cycle 1]: 0.00431755, [27] [switch_simplify]: 7.112e-05 [loop_unroll]: 2.75e-05 [a_1]: 0.00055728 [with_stream_mark]: 3.228e-05 [recompute_prepare]: 1.22e-05 [updatestate_depend_eliminate]: 7.16999e-06 [updatestate_assign_eliminate]: 7.43999e-06 [updatestate_loads_eliminate]: 6.11e-06 [parameter_eliminate]: 2.24999e-06 [specialize_transform]: 9.55001e-06 [updatestate_useless_node_eliminater]: 1.135e-05 [accelerated_algorithm]: 1.002e-05 [meta_shard_fg_expand]: 2.76e-06 [get_grad_eliminate_]: 8.86997e-06 [merge_forward]: 6.04999e-06 [cell_reuse_recompute_pass]: 1.18001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.482e-05 [j_node_and_user_rematch]: 1.612e-05 [meta_fg_expand]: 3.33e-06 [replace_old_param]: 1.46e-05 [inline_without_move]: 9.05001e-06 [renormalize]: 0.00314101 [add_forward_monad_depend]: 1.391e-05 [auto_monad_grad]: 2.98e-06 [auto_monad_eliminator]: 2.56e-05 [cse]: 3.825e-05 [replace_applicator]: 2.599e-05 [Cycle 2]: 0.00053748, [27] [switch_simplify]: 9.67001e-06 [loop_unroll]: 8.88002e-06 [a_1]: 0.00020775 [with_stream_mark]: 1.653e-05 [recompute_prepare]: 9.25999e-06 [updatestate_depend_eliminate]: 6.24001e-06 [updatestate_assign_eliminate]: 5.89999e-06 [updatestate_loads_eliminate]: 4.50999e-06 [parameter_eliminate]: 1.63002e-06 [specialize_transform]: 8.43999e-06 [updatestate_useless_node_eliminater]: 1.125e-05 [accelerated_algorithm]: 9.69e-06 [meta_shard_fg_expand]: 2.31998e-06 [get_grad_eliminate_]: 8.12e-06 [merge_forward]: 5.55001e-06 [cell_reuse_recompute_pass]: 2.99999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.953e-05 [j_node_and_user_rematch]: 1.311e-05 [meta_fg_expand]: 2.65002e-06 [replace_old_param]: 1.253e-05 [inline_without_move]: 7.99002e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.71002e-06 [auto_monad_grad]: 8.70001e-07 [auto_monad_eliminator]: 1.026e-05 [cse]: 1.806e-05 [replace_applicator]: 8.65999e-06 [py_interpret_to_execute_after_opt_a]: 1.867e-05 [rewriter_after_opt_a]: 0.00058218 [convert_after_rewriter]: 2.48e-05 [order_py_execute_after_rewriter]: 6.94001e-06 [mutable_eliminate]: 0.00132455 [jit_opt_b]: 8.605e-05, [1] [Cycle 1]: 7.636e-05, [2] [frontend_op_eliminate]: 3.289e-05 [inline_after_opt_a]: 2.847e-05 [cconv]: 3.94e-05 [loop_unroll]: 0.00048444 [jit_opt_after_cconv]: 0.00023956, [1] [Cycle 1]: 0.00023157, [11] [c_1]: 5.934e-05 [parameter_eliminate]: 4.07e-06 [updatestate_depend_eliminate]: 1.34e-05 [updatestate_assign_eliminate]: 4.99e-06 [updatestate_loads_eliminate]: 5.04998e-06 [cse]: 4.01e-05 [call_graph_tuple_transform]: 2.725e-05 [tuple_list_get_item_eliminator]: 9.13002e-06 [none_parameter_eliminate]: 1.62001e-06 [renormalize]: 8.70001e-07 [switch_simplify]: 9.36e-06 [remove_dup_value]: 2.162e-05 [partial_unused_args_eliminate]: 2.46e-06 [environ_conv]: 4.953e-05 [add_recomputation]: 0.00010155 [cse_after_recomputation]: 3.773e-05, [1] [Cycle 1]: 3.014e-05, [1] [cse]: 2.12e-05 [auto_monad_reorder]: 3.758e-05 [get_jit_bprop_graph]: 2.39999e-06 [rewriter_after_jit_bprop_graph]: 0.00015148 [opt_after_jit_grad]: 0.00053414 [symbol_engine_optimizer]: 0.00010584, [1] [Cycle 1]: 9.86e-05, [6] [build]: 7.56001e-06 [elim_shapecalc]: 1.255e-05 [elim_not_effective]: 2.158e-05 [opt_reshape]: 1.032e-05 [fold_const_symbol]: 1.509e-05 [renormalize]: 3.39991e-07 [validate]: 0.00011004 [backend_pass]: 1.67001e-06 [task_emit]: 4.40699 [execute]: 1.036e-05 Sums bootstrap : 0.000666s : 0.01% type_inference : 1.625782s : 26.91% event_method : 0.000022s : 0.00% auto_monad : 0.000226s : 0.00% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000426s : 0.01% rewriter_before_opt_a : 0.000091s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000081s : 0.00% jit_opt_a.loop_unroll : 0.000036s : 0.00% jit_opt_a.a_1 : 0.000765s : 0.01% jit_opt_a.with_stream_mark : 0.000049s : 0.00% jit_opt_a.recompute_prepare : 0.000021s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000011s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000018s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000023s : 0.00% jit_opt_a.accelerated_algorithm : 0.000020s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000044s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000029s : 0.00% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000027s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.003141s : 0.05% jit_opt_a.add_forward_monad_depend : 0.000016s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000036s : 0.00% jit_opt_a.cse : 0.000056s : 0.00% jit_opt_a.replace_applicator : 0.000035s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000582s : 0.01% convert_after_rewriter : 0.000025s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.001325s : 0.02% jit_opt_b.frontend_op_eliminate : 0.000033s : 0.00% jit_opt_b.inline_after_opt_a : 0.000028s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000484s : 0.01% jit_opt_after_cconv.c_1 : 0.000059s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000040s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000027s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 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 : 0.000009s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000050s : 0.00% add_recomputation : 0.000102s : 0.00% cse_after_recomputation.cse : 0.000021s : 0.00% auto_monad_reorder : 0.000038s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000151s : 0.00% opt_after_jit_grad : 0.000534s : 0.01% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000022s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000110s : 0.00% backend_pass : 0.000002s : 0.00% task_emit : 4.406986s : 72.93% execute : 0.000010s : 0.00% Time group info: ------[substitution.] 0.000252 45 4.43% : 0.000011s : 2: substitution.depend_value_elim 1.34% : 0.000003s : 4: substitution.elim_not_effective 0.92% : 0.000002s : 4: substitution.fold_const_symbol 3.04% : 0.000008s : 6: substitution.graph_param_transform 72.89% : 0.000184s : 3: substitution.inline 2.09% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.29% : 0.000008s : 8: substitution.remove_not_recompute_node 2.49% : 0.000006s : 2: substitution.replace_old_param 5.29% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 4.23% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.625646 2 99.85% : 1.623175s : 1: type_inference.infer 0.15% : 0.002471s : 1: type_inference.specialize ------[replace.] 0.000036 3 100.00% : 0.000036s : 3: replace.inline ------[match.] 0.000182 3 100.00% : 0.000182s : 3: match.inline ------[predicate.] 0.000177 970 1.22% : 0.000002s : 14: predicate.accumulaten_eliminater 1.28% : 0.000002s : 6: predicate.ad_related_special_op_eliminate 1.23% : 0.000002s : 14: predicate.addn_check_dump 1.18% : 0.000002s : 14: predicate.addn_zero_filter 1.90% : 0.000003s : 14: predicate.arithmetic_simplify 1.29% : 0.000002s : 14: predicate.cast_eliminate 0.64% : 0.000001s : 6: predicate.check_bprop_eliminate 1.15% : 0.000002s : 14: predicate.compare_switch_simplify 1.16% : 0.000002s : 14: predicate.depend_value_elim 1.09% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.25% : 0.000002s : 14: predicate.dict_get_item_eliminator 1.12% : 0.000002s : 14: predicate.dict_set_item_eliminator 0.99% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.50% : 0.000001s : 6: predicate.elim_not_effective 0.71% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.19% : 0.000002s : 14: predicate.environ_add_const_eliminate 1.12% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.08% : 0.000002s : 14: predicate.environ_get_depend_swap 1.17% : 0.000002s : 14: predicate.environ_get_eliminate 1.08% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.31% : 0.000001s : 6: predicate.fold_const_symbol 1.20% : 0.000002s : 12: predicate.get_grad_eliminate 0.43% : 0.000001s : 6: predicate.graph_param_transform 5.22% : 0.000009s : 29: predicate.inline 1.08% : 0.000002s : 12: predicate.inline_without_move 0.52% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.94% : 0.000003s : 12: predicate.less_batch_normalization 1.36% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.73% : 0.000003s : 20: predicate.load_eliminater 1.55% : 0.000003s : 6: predicate.loop_unroll_after_grad 2.75% : 0.000005s : 30: predicate.loop_unroll_before_grad 2.00% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 0.99% : 0.000002s : 14: predicate.merge_addn 1.04% : 0.000002s : 14: predicate.minmaximum_grad 3.03% : 0.000005s : 6: predicate.mutable_eliminate 0.69% : 0.000001s : 6: predicate.opt_reshape 1.90% : 0.000003s : 20: predicate.partial_eliminate 1.14% : 0.000002s : 14: predicate.print_const_string_wrapper 1.82% : 0.000003s : 14: predicate.reduce_eliminate 1.05% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.95% : 0.000002s : 12: predicate.remove_not_recompute_node 1.85% : 0.000003s : 26: predicate.replace_applicator 0.98% : 0.000002s : 12: predicate.replace_old_param 0.55% : 0.000001s : 6: predicate.reset_defer_inline 1.36% : 0.000002s : 14: predicate.reshape_eliminate 1.16% : 0.000002s : 14: predicate.row_tensor_add_zeros_like 0.93% : 0.000002s : 6: predicate.row_tensor_eliminate 1.06% : 0.000002s : 14: predicate.same_eliminate 0.80% : 0.000001s : 12: predicate.set_cell_output_no_recompute 1.12% : 0.000002s : 12: predicate.special_op_eliminate 1.23% : 0.000002s : 12: predicate.specialize_transform 1.49% : 0.000003s : 14: predicate.split_environ_get_set_with_tuple_value 1.08% : 0.000002s : 14: predicate.stack_unstack_eliminate 0.55% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.83% : 0.000003s : 17: predicate.switch_defer_inline 1.64% : 0.000003s : 17: predicate.switch_layer_defer_inline 5.78% : 0.000010s : 53: predicate.switch_simplify 1.16% : 0.000002s : 14: predicate.tile_eliminate 1.07% : 0.000002s : 14: predicate.transpose_eliminate 1.57% : 0.000003s : 14: predicate.tuple_list_convert_item_index_to_positive 1.17% : 0.000002s : 14: predicate.tuple_list_get_item_depend_reorder 3.58% : 0.000006s : 26: predicate.tuple_list_get_item_eliminator 1.34% : 0.000002s : 14: predicate.tuple_list_set_item_eliminator 1.19% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.62% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 6.18% : 0.000011s : 32: predicate.updatestate_useless_node_eliminater 1.48% : 0.000003s : 14: predicate.value_based_eliminate 0.44% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.76% : 0.000001s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003144 23 76.07% : 0.002392s : 18: func_graph_cloner_run.FuncGraphClonerGraph 23.93% : 0.000752s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 6.133266 76 0.00% : 0.000106s : 1: add_recomputation 0.00% : 0.000232s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.00% : 0.000005s : 1: backend_pass 0.01% : 0.000693s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000029s : 1: convert_after_rewriter 0.00% : 0.000040s : 1: cse_after_recomputation 0.00% : 0.000054s : 1: environ_conv 0.00% : 0.000035s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 1.47% : 0.090323s : 1: jit_opt_a 0.00% : 0.000243s : 1: jit_opt_after_cconv 0.00% : 0.000090s : 1: jit_opt_b 0.01% : 0.000493s : 1: loop_unroll 0.02% : 0.001336s : 1: mutable_eliminate 0.02% : 0.001087s : 26: opt.transform.jit_opt_a 0.00% : 0.000101s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000053s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000030s : 1: opt.transform.mutable_eliminate 0.00% : 0.000036s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000056s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000543s : 1: opt_after_jit_grad 0.00% : 0.000009s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000016s : 1: pre_auto_parallel 0.01% : 0.000434s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000024s : 1: remove_dup_value 0.04% : 0.002285s : 1: renormalize.infer 0.01% : 0.000842s : 1: renormalize.specialize 0.00% : 0.000155s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000588s : 1: rewriter_after_opt_a 0.00% : 0.000097s : 1: rewriter_before_opt_a 0.00% : 0.000109s : 1: symbol_engine_optimizer 71.85% : 4.407016s : 1: task_emit 26.51% : 1.625807s : 1: type_inference 0.00% : 0.000141s : 1: validate TotalTime = 2.12873, [33] [bootstrap]: 0.00057054 [type_inference]: 1.23638 [event_method]: 0.00065745 [auto_monad]: 0.00039088 [graph_reusing]: 1.208e-05 [pre_auto_parallel]: 4.42e-06 [py_interpret_to_execute]: 5.476e-05 [rewriter_before_opt_a]: 0.00017189 [expand_dump_flag]: 4.74e-06 [jit_opt_a]: 0.71244, [4] [Cycle 1]: 0.406924, [27] [switch_simplify]: 0.00029128 [loop_unroll]: 7.941e-05 [a_1]: 0.00177649 [with_stream_mark]: 4.338e-05 [recompute_prepare]: 3.536e-05 [updatestate_depend_eliminate]: 1.423e-05 [updatestate_assign_eliminate]: 1.083e-05 [updatestate_loads_eliminate]: 1.114e-05 [parameter_eliminate]: 3.23e-06 [specialize_transform]: 2.411e-05 [updatestate_useless_node_eliminater]: 2.608e-05 [accelerated_algorithm]: 1.982e-05 [meta_shard_fg_expand]: 7.87003e-06 [get_grad_eliminate_]: 2.033e-05 [merge_forward]: 1.293e-05 [cell_reuse_recompute_pass]: 1.27e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.161e-05 [j_node_and_user_rematch]: 3.485e-05 [meta_fg_expand]: 0.133718 [replace_old_param]: 0.00017328 [inline_without_move]: 0.00013531 [renormalize]: 0.269248 [add_forward_monad_depend]: 3.994e-05 [auto_monad_grad]: 1.884e-05 [auto_monad_eliminator]: 0.00016877 [cse]: 0.00032471 [replace_applicator]: 0.00029039 [Cycle 2]: 0.166232, [27] [switch_simplify]: 9.523e-05 [loop_unroll]: 8.921e-05 [a_1]: 0.162044 [with_stream_mark]: 5.433e-05 [recompute_prepare]: 4.012e-05 [updatestate_depend_eliminate]: 1.475e-05 [updatestate_assign_eliminate]: 1.434e-05 [updatestate_loads_eliminate]: 1.298e-05 [parameter_eliminate]: 5.92001e-06 [specialize_transform]: 1.952e-05 [updatestate_useless_node_eliminater]: 0.00010688 [accelerated_algorithm]: 1.59e-05 [meta_shard_fg_expand]: 9.71e-06 [get_grad_eliminate_]: 1.403e-05 [merge_forward]: 9.28002e-06 [cell_reuse_recompute_pass]: 1.72999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.015e-05 [j_node_and_user_rematch]: 2.222e-05 [meta_fg_expand]: 0.0002274 [replace_old_param]: 2.753e-05 [inline_without_move]: 1.429e-05 [renormalize]: 0.00285802 [add_forward_monad_depend]: 1.129e-05 [auto_monad_grad]: 2.74001e-06 [auto_monad_eliminator]: 3.88e-05 [cse]: 0.00013491 [replace_applicator]: 3.971e-05 [Cycle 3]: 0.00207832, [27] [switch_simplify]: 1.573e-05 [loop_unroll]: 1.508e-05 [a_1]: 0.00037532 [with_stream_mark]: 2.909e-05 [recompute_prepare]: 1.65e-05 [updatestate_depend_eliminate]: 6.349e-05 [updatestate_assign_eliminate]: 7.27002e-06 [updatestate_loads_eliminate]: 6.78e-06 [parameter_eliminate]: 3.25998e-06 [specialize_transform]: 1.444e-05 [updatestate_useless_node_eliminater]: 1.636e-05 [accelerated_algorithm]: 1.142e-05 [meta_shard_fg_expand]: 3.4e-06 [get_grad_eliminate_]: 1.079e-05 [merge_forward]: 6.53998e-06 [cell_reuse_recompute_pass]: 3.44001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.776e-05 [j_node_and_user_rematch]: 1.903e-05 [meta_fg_expand]: 5.87999e-06 [replace_old_param]: 1.826e-05 [inline_without_move]: 1.149e-05 [renormalize]: 0.00107486 [add_forward_monad_depend]: 8.94e-06 [auto_monad_grad]: 2.61999e-06 [auto_monad_eliminator]: 2.823e-05 [cse]: 5.7e-05 [replace_applicator]: 3.279e-05 [Cycle 4]: 0.00073302, [27] [switch_simplify]: 1.398e-05 [loop_unroll]: 1.334e-05 [a_1]: 0.00029634 [with_stream_mark]: 2.175e-05 [recompute_prepare]: 1.355e-05 [updatestate_depend_eliminate]: 7.51999e-06 [updatestate_assign_eliminate]: 5.91e-06 [updatestate_loads_eliminate]: 6.98998e-06 [parameter_eliminate]: 2.02001e-06 [specialize_transform]: 1.191e-05 [updatestate_useless_node_eliminater]: 1.551e-05 [accelerated_algorithm]: 1.159e-05 [meta_shard_fg_expand]: 4.45999e-06 [get_grad_eliminate_]: 1.144e-05 [merge_forward]: 5.83002e-06 [cell_reuse_recompute_pass]: 2.53e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.303e-05 [j_node_and_user_rematch]: 1.785e-05 [meta_fg_expand]: 4.70999e-06 [replace_old_param]: 1.515e-05 [inline_without_move]: 1.347e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.68e-06 [auto_monad_grad]: 1.71e-06 [auto_monad_eliminator]: 1.951e-05 [cse]: 3.031e-05 [replace_applicator]: 1.325e-05 [py_interpret_to_execute_after_opt_a]: 2.301e-05 [rewriter_after_opt_a]: 0.0002454 [convert_after_rewriter]: 1.496e-05 [order_py_execute_after_rewriter]: 9.31002e-06 [mutable_eliminate]: 0.00109451 [jit_opt_b]: 0.00011333, [1] [Cycle 1]: 0.00010028, [2] [frontend_op_eliminate]: 3.775e-05 [inline_after_opt_a]: 4.485e-05 [cconv]: 4.324e-05 [loop_unroll]: 0.00070875 [jit_opt_after_cconv]: 0.00033116, [1] [Cycle 1]: 0.00032079, [11] [c_1]: 8.958e-05 [parameter_eliminate]: 6.89999e-06 [updatestate_depend_eliminate]: 1.817e-05 [updatestate_assign_eliminate]: 6.16e-06 [updatestate_loads_eliminate]: 6.07999e-06 [cse]: 6.496e-05 [call_graph_tuple_transform]: 3.62e-05 [tuple_list_get_item_eliminator]: 1.273e-05 [none_parameter_eliminate]: 2.07999e-06 [renormalize]: 1.07e-06 [switch_simplify]: 1.292e-05 [remove_dup_value]: 7.339e-05 [partial_unused_args_eliminate]: 2.69001e-06 [environ_conv]: 1.707e-05 [add_recomputation]: 9.684e-05 [cse_after_recomputation]: 4.147e-05, [1] [Cycle 1]: 3.159e-05, [1] [cse]: 2.369e-05 [auto_monad_reorder]: 4.409e-05 [get_jit_bprop_graph]: 2.64999e-06 [rewriter_after_jit_bprop_graph]: 8.99e-06 [opt_after_jit_grad]: 0.00071175 [symbol_engine_optimizer]: 0.00013134, [1] [Cycle 1]: 0.00012286, [6] [build]: 9.91998e-06 [elim_shapecalc]: 1.619e-05 [elim_not_effective]: 2.936e-05 [opt_reshape]: 1.261e-05 [fold_const_symbol]: 1.968e-05 [renormalize]: 6.10016e-07 [validate]: 8.311e-05 [backend_pass]: 1.08001e-06 [task_emit]: 0.173924 [execute]: 1.014e-05 Sums bootstrap : 0.000571s : 0.03% type_inference : 1.236376s : 62.10% event_method : 0.000657s : 0.03% auto_monad : 0.000391s : 0.02% graph_reusing : 0.000012s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000055s : 0.00% rewriter_before_opt_a : 0.000172s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000416s : 0.02% jit_opt_a.loop_unroll : 0.000197s : 0.01% jit_opt_a.a_1 : 0.164492s : 8.26% jit_opt_a.with_stream_mark : 0.000149s : 0.01% jit_opt_a.recompute_prepare : 0.000106s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000100s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000038s : 0.00% jit_opt_a.parameter_eliminate : 0.000014s : 0.00% jit_opt_a.specialize_transform : 0.000070s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000165s : 0.01% jit_opt_a.accelerated_algorithm : 0.000059s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000025s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000057s : 0.00% jit_opt_a.merge_forward : 0.000035s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000123s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000094s : 0.00% jit_opt_a.meta_fg_expand : 0.133956s : 6.73% jit_opt_a.replace_old_param : 0.000234s : 0.01% jit_opt_a.inline_without_move : 0.000175s : 0.01% jit_opt_a.renormalize : 0.273181s : 13.72% jit_opt_a.add_forward_monad_depend : 0.000063s : 0.00% jit_opt_a.auto_monad_grad : 0.000026s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000255s : 0.01% jit_opt_a.cse : 0.000547s : 0.03% jit_opt_a.replace_applicator : 0.000376s : 0.02% py_interpret_to_execute_after_opt_a : 0.000023s : 0.00% rewriter_after_opt_a : 0.000245s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.001095s : 0.05% jit_opt_b.frontend_op_eliminate : 0.000038s : 0.00% jit_opt_b.inline_after_opt_a : 0.000045s : 0.00% cconv : 0.000043s : 0.00% loop_unroll : 0.000709s : 0.04% jit_opt_after_cconv.c_1 : 0.000090s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000018s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000065s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000036s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000013s : 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 : 0.000013s : 0.00% remove_dup_value : 0.000073s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000017s : 0.00% add_recomputation : 0.000097s : 0.00% cse_after_recomputation.cse : 0.000024s : 0.00% auto_monad_reorder : 0.000044s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000712s : 0.04% symbol_engine_optimizer.build : 0.000010s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000016s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000029s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000083s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 0.173924s : 8.74% execute : 0.000010s : 0.00% Time group info: ------[substitution.] 0.174239 271 0.03% : 0.000051s : 12: substitution.depend_value_elim 0.00% : 0.000004s : 5: substitution.elim_not_effective 0.00% : 0.000003s : 5: substitution.fold_const_symbol 8.45% : 0.014717s : 4: substitution.getattr_setattr_resolve 0.01% : 0.000009s : 8: substitution.graph_param_transform 91.19% : 0.158889s : 29: substitution.inline 0.03% : 0.000045s : 4: substitution.inline_without_move 0.01% : 0.000018s : 29: substitution.j_node_and_user_rematch 0.01% : 0.000023s : 13: substitution.minmaximum_grad 0.01% : 0.000018s : 14: substitution.partial_eliminate 0.01% : 0.000024s : 29: substitution.remove_not_recompute_node 0.05% : 0.000079s : 16: substitution.replace_applicator 0.01% : 0.000023s : 17: substitution.replace_old_param 0.00% : 0.000007s : 2: substitution.set_cell_output_no_recompute 0.01% : 0.000019s : 3: substitution.switch_simplify 0.03% : 0.000044s : 13: substitution.tuple_list_convert_item_index_to_positive 0.02% : 0.000033s : 13: substitution.tuple_list_get_item_depend_reorder 0.08% : 0.000133s : 30: substitution.tuple_list_get_item_eliminator 0.02% : 0.000029s : 9: substitution.updatestate_pure_node_eliminater 0.04% : 0.000069s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.236220 2 99.58% : 1.231032s : 1: type_inference.infer 0.42% : 0.005188s : 1: type_inference.specialize ------[replace.] 0.001272 54 9.39% : 0.000119s : 3: replace.getattr_setattr_resolve 51.87% : 0.000660s : 29: replace.inline 5.59% : 0.000071s : 1: replace.replace_applicator 7.54% : 0.000096s : 3: replace.switch_simplify 21.22% : 0.000270s : 17: replace.tuple_list_get_item_eliminator 4.39% : 0.000056s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.173630 54 8.44% : 0.014654s : 3: match.getattr_setattr_resolve 91.49% : 0.158853s : 29: match.inline 0.01% : 0.000020s : 1: match.replace_applicator 0.01% : 0.000017s : 3: match.switch_simplify 0.04% : 0.000070s : 17: match.tuple_list_get_item_eliminator 0.01% : 0.000016s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001056 6056 1.44% : 0.000015s : 101: predicate.accumulaten_eliminater 0.32% : 0.000003s : 8: predicate.ad_related_special_op_eliminate 1.32% : 0.000014s : 101: predicate.addn_check_dump 1.43% : 0.000015s : 101: predicate.addn_zero_filter 2.23% : 0.000023s : 101: predicate.arithmetic_simplify 1.52% : 0.000016s : 101: predicate.cast_eliminate 0.16% : 0.000002s : 8: predicate.check_bprop_eliminate 1.21% : 0.000013s : 101: predicate.compare_switch_simplify 1.61% : 0.000017s : 101: predicate.depend_value_elim 3.40% : 0.000036s : 101: predicate.dict_get_item_const_eliminator 1.43% : 0.000015s : 101: predicate.dict_get_item_eliminator 1.49% : 0.000016s : 101: predicate.dict_set_item_eliminator 0.22% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.09% : 0.000001s : 8: predicate.elim_not_effective 0.14% : 0.000001s : 8: predicate.elim_shapecalc_of_broadcastargs 1.57% : 0.000017s : 101: predicate.environ_add_const_eliminate 1.33% : 0.000014s : 101: predicate.environ_get_add_eliminate 1.36% : 0.000014s : 101: predicate.environ_get_depend_swap 1.38% : 0.000015s : 101: predicate.environ_get_eliminate 1.23% : 0.000013s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.69% : 0.000007s : 44: predicate.get_grad_eliminate 1.01% : 0.000011s : 20: predicate.getattr_setattr_resolve 0.09% : 0.000001s : 8: predicate.graph_param_transform 4.53% : 0.000048s : 163: predicate.inline 1.85% : 0.000020s : 105: predicate.inline_without_move 0.31% : 0.000003s : 44: predicate.j_node_and_user_rematch 0.85% : 0.000009s : 44: predicate.less_batch_normalization 1.92% : 0.000020s : 118: predicate.list_to_tuple_eliminator_ 1.79% : 0.000019s : 126: predicate.load_eliminater 0.45% : 0.000005s : 8: predicate.loop_unroll_after_grad 2.78% : 0.000029s : 187: predicate.loop_unroll_before_grad 1.74% : 0.000018s : 109: predicate.make_slice_get_slice_eliminator 1.23% : 0.000013s : 101: predicate.merge_addn 1.28% : 0.000014s : 101: predicate.minmaximum_grad 0.82% : 0.000009s : 8: predicate.mutable_eliminate 0.13% : 0.000001s : 8: predicate.opt_reshape 2.12% : 0.000022s : 126: predicate.partial_eliminate 1.32% : 0.000014s : 101: predicate.print_const_string_wrapper 2.11% : 0.000022s : 101: predicate.reduce_eliminate 1.82% : 0.000019s : 118: predicate.redundant_stop_gradient_eliminater 0.45% : 0.000005s : 44: predicate.remove_not_recompute_node 2.40% : 0.000025s : 243: predicate.replace_applicator 0.89% : 0.000009s : 105: predicate.replace_old_param 0.12% : 0.000001s : 8: predicate.reset_defer_inline 1.45% : 0.000015s : 101: predicate.reshape_eliminate 1.44% : 0.000015s : 101: predicate.row_tensor_add_zeros_like 0.24% : 0.000003s : 8: predicate.row_tensor_eliminate 1.52% : 0.000016s : 101: predicate.same_eliminate 0.50% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.29% : 0.000003s : 16: predicate.special_op_eliminate 0.85% : 0.000009s : 50: predicate.specialize_transform 1.78% : 0.000019s : 101: predicate.split_environ_get_set_with_tuple_value 1.30% : 0.000014s : 101: predicate.stack_unstack_eliminate 0.13% : 0.000001s : 8: predicate.switch_call_monad_eliminater 4.32% : 0.000046s : 147: predicate.switch_defer_inline 2.38% : 0.000025s : 147: predicate.switch_layer_defer_inline 5.70% : 0.000060s : 348: predicate.switch_simplify 1.56% : 0.000017s : 101: predicate.tile_eliminate 1.45% : 0.000015s : 101: predicate.transpose_eliminate 1.99% : 0.000021s : 101: predicate.tuple_list_convert_item_index_to_positive 1.79% : 0.000019s : 101: predicate.tuple_list_get_item_depend_reorder 3.42% : 0.000036s : 134: predicate.tuple_list_get_item_eliminator 1.67% : 0.000018s : 101: predicate.tuple_list_set_item_eliminator 1.64% : 0.000017s : 118: predicate.tuple_to_list_eliminator_ 1.80% : 0.000019s : 126: predicate.updatestate_pure_node_eliminater 2.95% : 0.000031s : 172: predicate.updatestate_useless_node_eliminater 1.91% : 0.000020s : 101: predicate.value_based_eliminate 0.09% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.18% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.126081 79 97.56% : 0.123002s : 42: func_graph_cloner_run.FuncGraphClonerGraph 0.50% : 0.000627s : 7: func_graph_cloner_run.FuncGraphClonerNode 1.94% : 0.002451s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.583604 108 0.00% : 0.000100s : 1: add_recomputation 0.02% : 0.000401s : 1: auto_monad 0.00% : 0.000047s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.02% : 0.000595s : 1: bootstrap 0.00% : 0.000047s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.00% : 0.000044s : 1: cse_after_recomputation 0.00% : 0.000020s : 1: environ_conv 0.03% : 0.000668s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000016s : 1: graph_reusing 27.58% : 0.712445s : 1: jit_opt_a 0.01% : 0.000335s : 1: jit_opt_after_cconv 0.00% : 0.000117s : 1: jit_opt_b 0.03% : 0.000721s : 1: loop_unroll 0.04% : 0.001112s : 1: mutable_eliminate 6.44% : 0.166458s : 52: opt.transform.jit_opt_a 0.01% : 0.000146s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000070s : 4: opt.transform.jit_opt_b 0.00% : 0.000032s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000045s : 1: opt.transform.mutable_eliminate 0.00% : 0.000052s : 1: opt.transform.opt_after_jit_grad 0.58% : 0.014933s : 2: opt.transform.opt_resolve 0.00% : 0.000073s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000722s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000058s : 1: py_interpret_to_execute 0.00% : 0.000026s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000078s : 1: remove_dup_value 10.27% : 0.265306s : 3: renormalize.infer 0.30% : 0.007831s : 3: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000252s : 1: rewriter_after_opt_a 0.01% : 0.000176s : 1: rewriter_before_opt_a 0.01% : 0.000135s : 1: symbol_engine_optimizer 6.73% : 0.173944s : 1: task_emit 47.86% : 1.236399s : 1: type_inference 0.00% : 0.000116s : 1: validate . [hook] pytest_runtest_teardown:test_permute_non_contiguous[KBK] tests/st/mint/test_permute.py::test_permute_non_contiguous[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 226.01s (0:03:46) ==================