==================================================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_005/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_high_dimension[pynative] tests/st/mint/test_permute.py::test_permute_high_dimension[pynative],max_mem:2.0M TotalTime = 1.51919, [30] [bootstrap]: 0.0128409 [type_inference]: 1.36233 [event_method]: 2.025e-05 [auto_monad]: 0.00021569 [graph_reusing]: 7.1e-06 [pre_auto_parallel]: 1.245e-05 [py_interpret_to_execute]: 0.00045926 [rewriter_before_opt_a]: 0.00014543 [expand_dump_flag]: 4.22e-06 [jit_opt_a]: 0.0143217, [2] [Cycle 1]: 0.00493491, [27] [switch_simplify]: 6.829e-05 [loop_unroll]: 2.551e-05 [a_1]: 0.00053608 [with_stream_mark]: 3.017e-05 [recompute_prepare]: 1.298e-05 [updatestate_depend_eliminate]: 8.20999e-06 [updatestate_assign_eliminate]: 9.25999e-06 [updatestate_loads_eliminate]: 5.51e-06 [parameter_eliminate]: 2.28002e-06 [specialize_transform]: 1.052e-05 [updatestate_useless_node_eliminater]: 1.255e-05 [accelerated_algorithm]: 9.67001e-06 [meta_shard_fg_expand]: 2.91e-06 [get_grad_eliminate_]: 8.99998e-06 [merge_forward]: 5.32001e-06 [cell_reuse_recompute_pass]: 1.54e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.453e-05 [j_node_and_user_rematch]: 1.457e-05 [meta_fg_expand]: 4.06001e-06 [replace_old_param]: 1.448e-05 [inline_without_move]: 9.02999e-06 [renormalize]: 0.00374606 [add_forward_monad_depend]: 1.79e-05 [auto_monad_grad]: 2.94999e-06 [auto_monad_eliminator]: 2.645e-05 [cse]: 5.444e-05 [replace_applicator]: 2.519e-05 [Cycle 2]: 0.0005561, [27] [switch_simplify]: 9.92001e-06 [loop_unroll]: 8.57e-06 [a_1]: 0.00020833 [with_stream_mark]: 1.884e-05 [recompute_prepare]: 1.029e-05 [updatestate_depend_eliminate]: 6.88e-06 [updatestate_assign_eliminate]: 6.11e-06 [updatestate_loads_eliminate]: 4.92e-06 [parameter_eliminate]: 2.07999e-06 [specialize_transform]: 9.24e-06 [updatestate_useless_node_eliminater]: 1.165e-05 [accelerated_algorithm]: 9.62999e-06 [meta_shard_fg_expand]: 2.64001e-06 [get_grad_eliminate_]: 8.37e-06 [merge_forward]: 5.56998e-06 [cell_reuse_recompute_pass]: 2.74999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.048e-05 [j_node_and_user_rematch]: 1.39e-05 [meta_fg_expand]: 3.58e-06 [replace_old_param]: 1.205e-05 [inline_without_move]: 8.62998e-06 [renormalize]: 1.09983e-07 [add_forward_monad_depend]: 1.37999e-06 [auto_monad_grad]: 1.72001e-06 [auto_monad_eliminator]: 1.146e-05 [cse]: 1.96e-05 [replace_applicator]: 8.57e-06 [py_interpret_to_execute_after_opt_a]: 1.784e-05 [rewriter_after_opt_a]: 0.00053467 [convert_after_rewriter]: 1.752e-05 [order_py_execute_after_rewriter]: 7.99002e-06 [mutable_eliminate]: 0.00078733 [jit_opt_b]: 8.315e-05, [1] [Cycle 1]: 7.353e-05, [2] [frontend_op_eliminate]: 3.156e-05 [inline_after_opt_a]: 2.613e-05 [cconv]: 3.417e-05 [loop_unroll]: 0.125343 [jit_opt_after_cconv]: 0.00030152, [1] [Cycle 1]: 0.00028781, [11] [c_1]: 7.758e-05 [parameter_eliminate]: 7.75e-06 [updatestate_depend_eliminate]: 2.003e-05 [updatestate_assign_eliminate]: 6.49001e-06 [updatestate_loads_eliminate]: 6.88e-06 [cse]: 5.033e-05 [call_graph_tuple_transform]: 2.992e-05 [tuple_list_get_item_eliminator]: 1.178e-05 [none_parameter_eliminate]: 2.16e-06 [renormalize]: 1.50001e-06 [switch_simplify]: 9.50001e-06 [remove_dup_value]: 2.426e-05 [partial_unused_args_eliminate]: 2.98e-06 [environ_conv]: 3.283e-05 [add_recomputation]: 0.00012196 [cse_after_recomputation]: 3.954e-05, [1] [Cycle 1]: 3.203e-05, [1] [cse]: 2.28e-05 [auto_monad_reorder]: 4.058e-05 [get_jit_bprop_graph]: 2.80002e-06 [rewriter_after_jit_bprop_graph]: 0.00017116 [opt_after_jit_grad]: 0.00063447 [symbol_engine_optimizer]: 0.00011009, [1] [Cycle 1]: 0.00010143, [6] [build]: 7.71001e-06 [elim_shapecalc]: 1.286e-05 [elim_not_effective]: 2.053e-05 [opt_reshape]: 1.072e-05 [fold_const_symbol]: 1.548e-05 [renormalize]: 9.30013e-07 [validate]: 8.525e-05 Sums bootstrap : 0.012841s : 0.85% type_inference : 1.362329s : 90.26% event_method : 0.000020s : 0.00% auto_monad : 0.000216s : 0.01% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000459s : 0.03% rewriter_before_opt_a : 0.000145s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000078s : 0.01% jit_opt_a.loop_unroll : 0.000034s : 0.00% jit_opt_a.a_1 : 0.000744s : 0.05% jit_opt_a.with_stream_mark : 0.000049s : 0.00% jit_opt_a.recompute_prepare : 0.000023s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000024s : 0.00% jit_opt_a.accelerated_algorithm : 0.000019s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000017s : 0.00% jit_opt_a.merge_forward : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000045s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000027s : 0.00% jit_opt_a.inline_without_move : 0.000018s : 0.00% jit_opt_a.renormalize : 0.003746s : 0.25% jit_opt_a.add_forward_monad_depend : 0.000019s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000038s : 0.00% jit_opt_a.cse : 0.000074s : 0.00% jit_opt_a.replace_applicator : 0.000034s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000535s : 0.04% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000008s : 0.00% mutable_eliminate : 0.000787s : 0.05% jit_opt_b.frontend_op_eliminate : 0.000032s : 0.00% jit_opt_b.inline_after_opt_a : 0.000026s : 0.00% cconv : 0.000034s : 0.00% loop_unroll : 0.125343s : 8.30% jit_opt_after_cconv.c_1 : 0.000078s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000020s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000050s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000002s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000010s : 0.00% remove_dup_value : 0.000024s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000033s : 0.00% add_recomputation : 0.000122s : 0.01% cse_after_recomputation.cse : 0.000023s : 0.00% auto_monad_reorder : 0.000041s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000171s : 0.01% opt_after_jit_grad : 0.000634s : 0.04% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000085s : 0.01% Time group info: ------[substitution.] 0.000255 45 4.32% : 0.000011s : 2: substitution.depend_value_elim 1.38% : 0.000004s : 4: substitution.elim_not_effective 1.08% : 0.000003s : 4: substitution.fold_const_symbol 3.59% : 0.000009s : 6: substitution.graph_param_transform 71.15% : 0.000182s : 3: substitution.inline 2.03% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.13% : 0.000008s : 8: substitution.remove_not_recompute_node 2.85% : 0.000007s : 2: substitution.replace_old_param 5.85% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 4.62% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.362203 2 99.82% : 1.359757s : 1: type_inference.infer 0.18% : 0.002447s : 1: type_inference.specialize ------[replace.] 0.000038 3 100.00% : 0.000038s : 3: replace.inline ------[match.] 0.000180 3 100.00% : 0.000180s : 3: match.inline ------[predicate.] 0.000180 970 1.13% : 0.000002s : 14: predicate.accumulaten_eliminater 1.54% : 0.000003s : 6: predicate.ad_related_special_op_eliminate 0.99% : 0.000002s : 14: predicate.addn_check_dump 1.96% : 0.000004s : 14: predicate.addn_zero_filter 1.78% : 0.000003s : 14: predicate.arithmetic_simplify 1.15% : 0.000002s : 14: predicate.cast_eliminate 0.61% : 0.000001s : 6: predicate.check_bprop_eliminate 1.02% : 0.000002s : 14: predicate.compare_switch_simplify 1.15% : 0.000002s : 14: predicate.depend_value_elim 0.97% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.15% : 0.000002s : 14: predicate.dict_get_item_eliminator 1.06% : 0.000002s : 14: predicate.dict_set_item_eliminator 1.36% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.44% : 0.000001s : 6: predicate.elim_not_effective 0.67% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.18% : 0.000002s : 14: predicate.environ_add_const_eliminate 1.00% : 0.000002s : 14: predicate.environ_get_add_eliminate 0.91% : 0.000002s : 14: predicate.environ_get_depend_swap 1.01% : 0.000002s : 14: predicate.environ_get_eliminate 0.88% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.27% : 0.000000s : 6: predicate.fold_const_symbol 1.26% : 0.000002s : 12: predicate.get_grad_eliminate 0.45% : 0.000001s : 6: predicate.graph_param_transform 5.58% : 0.000010s : 29: predicate.inline 1.13% : 0.000002s : 12: predicate.inline_without_move 0.52% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.77% : 0.000003s : 12: predicate.less_batch_normalization 1.10% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.60% : 0.000003s : 20: predicate.load_eliminater 5.50% : 0.000010s : 6: predicate.loop_unroll_after_grad 2.74% : 0.000005s : 30: predicate.loop_unroll_before_grad 2.50% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.11% : 0.000002s : 14: predicate.merge_addn 1.04% : 0.000002s : 14: predicate.minmaximum_grad 1.83% : 0.000003s : 6: predicate.mutable_eliminate 0.62% : 0.000001s : 6: predicate.opt_reshape 1.92% : 0.000003s : 20: predicate.partial_eliminate 1.19% : 0.000002s : 14: predicate.print_const_string_wrapper 1.38% : 0.000002s : 14: predicate.reduce_eliminate 1.30% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.80% : 0.000001s : 12: predicate.remove_not_recompute_node 1.82% : 0.000003s : 26: predicate.replace_applicator 0.89% : 0.000002s : 12: predicate.replace_old_param 0.41% : 0.000001s : 6: predicate.reset_defer_inline 1.05% : 0.000002s : 14: predicate.reshape_eliminate 1.10% : 0.000002s : 14: predicate.row_tensor_add_zeros_like 0.99% : 0.000002s : 6: predicate.row_tensor_eliminate 1.13% : 0.000002s : 14: predicate.same_eliminate 0.68% : 0.000001s : 12: predicate.set_cell_output_no_recompute 1.33% : 0.000002s : 12: predicate.special_op_eliminate 1.29% : 0.000002s : 12: predicate.specialize_transform 1.43% : 0.000003s : 14: predicate.split_environ_get_set_with_tuple_value 1.14% : 0.000002s : 14: predicate.stack_unstack_eliminate 0.64% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.67% : 0.000003s : 17: predicate.switch_defer_inline 1.43% : 0.000003s : 17: predicate.switch_layer_defer_inline 5.54% : 0.000010s : 53: predicate.switch_simplify 1.27% : 0.000002s : 14: predicate.tile_eliminate 1.07% : 0.000002s : 14: predicate.transpose_eliminate 1.32% : 0.000002s : 14: predicate.tuple_list_convert_item_index_to_positive 1.24% : 0.000002s : 14: predicate.tuple_list_get_item_depend_reorder 3.96% : 0.000007s : 26: predicate.tuple_list_get_item_eliminator 1.45% : 0.000003s : 14: predicate.tuple_list_set_item_eliminator 1.07% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.73% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 3.76% : 0.000007s : 32: predicate.updatestate_useless_node_eliminater 1.71% : 0.000003s : 14: predicate.value_based_eliminate 0.46% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.88% : 0.000002s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003582 27 78.68% : 0.002818s : 22: func_graph_cloner_run.FuncGraphClonerGraph 21.32% : 0.000764s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.524006 72 0.01% : 0.000126s : 1: add_recomputation 0.01% : 0.000223s : 1: auto_monad 0.00% : 0.000044s : 1: auto_monad_reorder 0.84% : 0.012873s : 1: bootstrap 0.00% : 0.000037s : 1: cconv 0.00% : 0.000021s : 1: convert_after_rewriter 0.00% : 0.000042s : 1: cse_after_recomputation 0.00% : 0.000036s : 1: environ_conv 0.00% : 0.000026s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 0.94% : 0.014325s : 1: jit_opt_a 0.02% : 0.000307s : 1: jit_opt_after_cconv 0.01% : 0.000086s : 1: jit_opt_b 8.23% : 0.125367s : 1: loop_unroll 0.05% : 0.000799s : 1: mutable_eliminate 0.07% : 0.001067s : 26: opt.transform.jit_opt_a 0.01% : 0.000124s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000050s : 4: opt.transform.jit_opt_b 0.00% : 0.000049s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000024s : 1: opt.transform.mutable_eliminate 0.00% : 0.000039s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000055s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000646s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000016s : 1: pre_auto_parallel 0.03% : 0.000468s : 1: py_interpret_to_execute 0.00% : 0.000020s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000027s : 1: remove_dup_value 0.19% : 0.002866s : 1: renormalize.infer 0.06% : 0.000867s : 1: renormalize.specialize 0.01% : 0.000176s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000540s : 1: rewriter_after_opt_a 0.01% : 0.000153s : 1: rewriter_before_opt_a 0.01% : 0.000113s : 1: symbol_engine_optimizer 89.39% : 1.362356s : 1: type_inference TotalTime = 1.85783, [30] [bootstrap]: 0.00051106 [type_inference]: 0.868746 [event_method]: 0.00207583 [auto_monad]: 0.00043583 [graph_reusing]: 1.223e-05 [pre_auto_parallel]: 4.47e-06 [py_interpret_to_execute]: 0.00144443 [rewriter_before_opt_a]: 0.00025959 [expand_dump_flag]: 1.042e-05 [jit_opt_a]: 0.979652, [4] [Cycle 1]: 0.832531, [27] [switch_simplify]: 0.00028539 [loop_unroll]: 7.084e-05 [a_1]: 0.00170141 [with_stream_mark]: 4.975e-05 [recompute_prepare]: 4.071e-05 [updatestate_depend_eliminate]: 1.902e-05 [updatestate_assign_eliminate]: 1.325e-05 [updatestate_loads_eliminate]: 1.092e-05 [parameter_eliminate]: 3.61999e-06 [specialize_transform]: 2.395e-05 [updatestate_useless_node_eliminater]: 2.678e-05 [accelerated_algorithm]: 2.112e-05 [meta_shard_fg_expand]: 1.091e-05 [get_grad_eliminate_]: 2.181e-05 [merge_forward]: 1.452e-05 [cell_reuse_recompute_pass]: 1.51998e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.607e-05 [j_node_and_user_rematch]: 3.807e-05 [meta_fg_expand]: 0.423831 [replace_old_param]: 0.00016625 [inline_without_move]: 0.0001439 [renormalize]: 0.404724 [add_forward_monad_depend]: 4.54e-05 [auto_monad_grad]: 1.938e-05 [auto_monad_eliminator]: 0.00014896 [cse]: 0.00035 [replace_applicator]: 0.00030239 [Cycle 2]: 0.00849336, [27] [switch_simplify]: 0.00010544 [loop_unroll]: 0.00011458 [a_1]: 0.00417602 [with_stream_mark]: 4.573e-05 [recompute_prepare]: 3.731e-05 [updatestate_depend_eliminate]: 1.544e-05 [updatestate_assign_eliminate]: 1.455e-05 [updatestate_loads_eliminate]: 1.281e-05 [parameter_eliminate]: 4.80999e-06 [specialize_transform]: 2.16e-05 [updatestate_useless_node_eliminater]: 0.00010329 [accelerated_algorithm]: 1.691e-05 [meta_shard_fg_expand]: 7.41999e-06 [get_grad_eliminate_]: 1.41e-05 [merge_forward]: 9.84001e-06 [cell_reuse_recompute_pass]: 1.44e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.234e-05 [j_node_and_user_rematch]: 2.349e-05 [meta_fg_expand]: 0.00021396 [replace_old_param]: 2.621e-05 [inline_without_move]: 1.373e-05 [renormalize]: 0.00293979 [add_forward_monad_depend]: 1.048e-05 [auto_monad_grad]: 2.63e-06 [auto_monad_eliminator]: 3.515e-05 [cse]: 0.0001302 [replace_applicator]: 3.726e-05 [Cycle 3]: 0.00247726, [27] [switch_simplify]: 1.896e-05 [loop_unroll]: 1.407e-05 [a_1]: 0.00036958 [with_stream_mark]: 2.393e-05 [recompute_prepare]: 1.491e-05 [updatestate_depend_eliminate]: 5.999e-05 [updatestate_assign_eliminate]: 6.61e-06 [updatestate_loads_eliminate]: 6.66999e-06 [parameter_eliminate]: 2.29999e-06 [specialize_transform]: 1.339e-05 [updatestate_useless_node_eliminater]: 1.369e-05 [accelerated_algorithm]: 1.296e-05 [meta_shard_fg_expand]: 4.51002e-06 [get_grad_eliminate_]: 1.341e-05 [merge_forward]: 7.75e-06 [cell_reuse_recompute_pass]: 3.33e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.848e-05 [j_node_and_user_rematch]: 1.967e-05 [meta_fg_expand]: 5.34998e-06 [replace_old_param]: 1.817e-05 [inline_without_move]: 1.157e-05 [renormalize]: 0.00146966 [add_forward_monad_depend]: 8.68001e-06 [auto_monad_grad]: 3.28e-06 [auto_monad_eliminator]: 2.68e-05 [cse]: 5.255e-05 [replace_applicator]: 2.951e-05 [Cycle 4]: 0.00078258, [27] [switch_simplify]: 1.58e-05 [loop_unroll]: 1.293e-05 [a_1]: 0.00030289 [with_stream_mark]: 1.716e-05 [recompute_prepare]: 1.151e-05 [updatestate_depend_eliminate]: 8.50999e-06 [updatestate_assign_eliminate]: 9.11998e-06 [updatestate_loads_eliminate]: 7.80998e-06 [parameter_eliminate]: 2.12999e-06 [specialize_transform]: 1.574e-05 [updatestate_useless_node_eliminater]: 1.742e-05 [accelerated_algorithm]: 1.264e-05 [meta_shard_fg_expand]: 3.70998e-06 [get_grad_eliminate_]: 1.056e-05 [merge_forward]: 6.58e-06 [cell_reuse_recompute_pass]: 2.74001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.498e-05 [j_node_and_user_rematch]: 1.871e-05 [meta_fg_expand]: 4.22e-06 [replace_old_param]: 1.578e-05 [inline_without_move]: 1.057e-05 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.02999e-06 [auto_monad_grad]: 1.60999e-06 [auto_monad_eliminator]: 1.968e-05 [cse]: 3.366e-05 [replace_applicator]: 1.269e-05 [py_interpret_to_execute_after_opt_a]: 2.535e-05 [rewriter_after_opt_a]: 0.00032418 [convert_after_rewriter]: 1.777e-05 [order_py_execute_after_rewriter]: 0.00011916 [mutable_eliminate]: 0.00099883 [jit_opt_b]: 0.00011562, [1] [Cycle 1]: 0.00010347, [2] [frontend_op_eliminate]: 4.62e-05 [inline_after_opt_a]: 3.949e-05 [cconv]: 5.135e-05 [loop_unroll]: 0.00075555 [jit_opt_after_cconv]: 0.00039379, [1] [Cycle 1]: 0.00038363, [11] [c_1]: 8.815e-05 [parameter_eliminate]: 7.94002e-06 [updatestate_depend_eliminate]: 2.046e-05 [updatestate_assign_eliminate]: 1.058e-05 [updatestate_loads_eliminate]: 9.00001e-06 [cse]: 7.076e-05 [call_graph_tuple_transform]: 4.087e-05 [tuple_list_get_item_eliminator]: 1.377e-05 [none_parameter_eliminate]: 3.04e-05 [renormalize]: 7.09988e-07 [switch_simplify]: 1.555e-05 [remove_dup_value]: 7.75e-05 [partial_unused_args_eliminate]: 4.05e-06 [environ_conv]: 1.689e-05 [add_recomputation]: 0.00012162 [cse_after_recomputation]: 5.186e-05, [1] [Cycle 1]: 4.007e-05, [1] [cse]: 2.842e-05 [auto_monad_reorder]: 5.219e-05 [get_jit_bprop_graph]: 2.98998e-06 [rewriter_after_jit_bprop_graph]: 1.137e-05 [opt_after_jit_grad]: 0.00087676 [symbol_engine_optimizer]: 0.00014295, [1] [Cycle 1]: 0.00013054, [6] [build]: 1.157e-05 [elim_shapecalc]: 1.669e-05 [elim_not_effective]: 3.236e-05 [opt_reshape]: 1.35e-05 [fold_const_symbol]: 2.046e-05 [renormalize]: 9.90025e-07 [validate]: 0.00013887 Sums bootstrap : 0.000511s : 0.03% type_inference : 0.868746s : 50.49% event_method : 0.002076s : 0.12% auto_monad : 0.000436s : 0.03% graph_reusing : 0.000012s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.001444s : 0.08% rewriter_before_opt_a : 0.000260s : 0.02% expand_dump_flag : 0.000010s : 0.00% jit_opt_a.switch_simplify : 0.000426s : 0.02% jit_opt_a.loop_unroll : 0.000212s : 0.01% jit_opt_a.a_1 : 0.006550s : 0.38% jit_opt_a.with_stream_mark : 0.000137s : 0.01% jit_opt_a.recompute_prepare : 0.000104s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000103s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000044s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000038s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000075s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000161s : 0.01% jit_opt_a.accelerated_algorithm : 0.000064s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000027s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000060s : 0.00% jit_opt_a.merge_forward : 0.000039s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000132s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000100s : 0.01% jit_opt_a.meta_fg_expand : 0.424054s : 24.64% jit_opt_a.replace_old_param : 0.000226s : 0.01% jit_opt_a.inline_without_move : 0.000180s : 0.01% jit_opt_a.renormalize : 0.409134s : 23.78% jit_opt_a.add_forward_monad_depend : 0.000067s : 0.00% jit_opt_a.auto_monad_grad : 0.000027s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000231s : 0.01% jit_opt_a.cse : 0.000566s : 0.03% jit_opt_a.replace_applicator : 0.000382s : 0.02% py_interpret_to_execute_after_opt_a : 0.000025s : 0.00% rewriter_after_opt_a : 0.000324s : 0.02% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000119s : 0.01% mutable_eliminate : 0.000999s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000046s : 0.00% jit_opt_b.inline_after_opt_a : 0.000039s : 0.00% cconv : 0.000051s : 0.00% loop_unroll : 0.000756s : 0.04% jit_opt_after_cconv.c_1 : 0.000088s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000020s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000011s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.cse : 0.000071s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000041s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000014s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000030s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000016s : 0.00% remove_dup_value : 0.000077s : 0.00% partial_unused_args_eliminate : 0.000004s : 0.00% environ_conv : 0.000017s : 0.00% add_recomputation : 0.000122s : 0.01% cse_after_recomputation.cse : 0.000028s : 0.00% auto_monad_reorder : 0.000052s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000011s : 0.00% opt_after_jit_grad : 0.000877s : 0.05% symbol_engine_optimizer.build : 0.000012s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000032s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000014s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000139s : 0.01% Time group info: ------[substitution.] 0.003100 271 1.42% : 0.000044s : 12: substitution.depend_value_elim 0.14% : 0.000004s : 5: substitution.elim_not_effective 0.10% : 0.000003s : 5: substitution.fold_const_symbol 27.00% : 0.000837s : 4: substitution.getattr_setattr_resolve 0.38% : 0.000012s : 8: substitution.graph_param_transform 53.91% : 0.001671s : 29: substitution.inline 1.45% : 0.000045s : 4: substitution.inline_without_move 0.56% : 0.000017s : 29: substitution.j_node_and_user_rematch 0.67% : 0.000021s : 13: substitution.minmaximum_grad 0.51% : 0.000016s : 14: substitution.partial_eliminate 0.81% : 0.000025s : 29: substitution.remove_not_recompute_node 2.64% : 0.000082s : 16: substitution.replace_applicator 0.80% : 0.000025s : 17: substitution.replace_old_param 0.28% : 0.000009s : 2: substitution.set_cell_output_no_recompute 0.60% : 0.000019s : 3: substitution.switch_simplify 1.42% : 0.000044s : 13: substitution.tuple_list_convert_item_index_to_positive 1.04% : 0.000032s : 13: substitution.tuple_list_get_item_depend_reorder 3.31% : 0.000103s : 30: substitution.tuple_list_get_item_eliminator 0.89% : 0.000028s : 9: substitution.updatestate_pure_node_eliminater 2.08% : 0.000065s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.867102 2 99.21% : 0.860273s : 1: type_inference.infer 0.79% : 0.006829s : 1: type_inference.specialize ------[replace.] 0.001012 54 7.09% : 0.000072s : 3: replace.getattr_setattr_resolve 48.67% : 0.000492s : 29: replace.inline 7.45% : 0.000075s : 1: replace.replace_applicator 9.63% : 0.000097s : 3: replace.switch_simplify 21.72% : 0.000220s : 17: replace.tuple_list_get_item_eliminator 5.45% : 0.000055s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002521 54 30.80% : 0.000777s : 3: match.getattr_setattr_resolve 65.40% : 0.001649s : 29: match.inline 0.89% : 0.000022s : 1: match.replace_applicator 0.63% : 0.000016s : 3: match.switch_simplify 1.71% : 0.000043s : 17: match.tuple_list_get_item_eliminator 0.57% : 0.000014s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000962 6056 1.43% : 0.000014s : 101: predicate.accumulaten_eliminater 0.64% : 0.000006s : 8: predicate.ad_related_special_op_eliminate 1.34% : 0.000013s : 101: predicate.addn_check_dump 1.50% : 0.000014s : 101: predicate.addn_zero_filter 2.39% : 0.000023s : 101: predicate.arithmetic_simplify 1.47% : 0.000014s : 101: predicate.cast_eliminate 0.16% : 0.000002s : 8: predicate.check_bprop_eliminate 1.34% : 0.000013s : 101: predicate.compare_switch_simplify 1.58% : 0.000015s : 101: predicate.depend_value_elim 1.45% : 0.000014s : 101: predicate.dict_get_item_const_eliminator 1.56% : 0.000015s : 101: predicate.dict_get_item_eliminator 1.45% : 0.000014s : 101: predicate.dict_set_item_eliminator 0.34% : 0.000003s : 8: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 8: predicate.elim_not_effective 0.20% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.47% : 0.000014s : 101: predicate.environ_add_const_eliminate 1.30% : 0.000012s : 101: predicate.environ_get_add_eliminate 1.41% : 0.000014s : 101: predicate.environ_get_depend_swap 1.42% : 0.000014s : 101: predicate.environ_get_eliminate 1.28% : 0.000012s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.76% : 0.000007s : 44: predicate.get_grad_eliminate 0.76% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.09% : 0.000001s : 8: predicate.graph_param_transform 4.41% : 0.000042s : 163: predicate.inline 2.15% : 0.000021s : 105: predicate.inline_without_move 0.35% : 0.000003s : 44: predicate.j_node_and_user_rematch 1.06% : 0.000010s : 44: predicate.less_batch_normalization 1.77% : 0.000017s : 118: predicate.list_to_tuple_eliminator_ 1.79% : 0.000017s : 126: predicate.load_eliminater 0.55% : 0.000005s : 8: predicate.loop_unroll_after_grad 3.24% : 0.000031s : 187: predicate.loop_unroll_before_grad 1.62% : 0.000016s : 109: predicate.make_slice_get_slice_eliminator 1.26% : 0.000012s : 101: predicate.merge_addn 1.55% : 0.000015s : 101: predicate.minmaximum_grad 0.74% : 0.000007s : 8: predicate.mutable_eliminate 0.14% : 0.000001s : 8: predicate.opt_reshape 2.27% : 0.000022s : 126: predicate.partial_eliminate 1.38% : 0.000013s : 101: predicate.print_const_string_wrapper 1.88% : 0.000018s : 101: predicate.reduce_eliminate 1.82% : 0.000018s : 118: predicate.redundant_stop_gradient_eliminater 0.45% : 0.000004s : 44: predicate.remove_not_recompute_node 2.64% : 0.000025s : 243: predicate.replace_applicator 1.09% : 0.000010s : 105: predicate.replace_old_param 0.15% : 0.000001s : 8: predicate.reset_defer_inline 1.39% : 0.000013s : 101: predicate.reshape_eliminate 1.43% : 0.000014s : 101: predicate.row_tensor_add_zeros_like 0.30% : 0.000003s : 8: predicate.row_tensor_eliminate 1.54% : 0.000015s : 101: predicate.same_eliminate 0.48% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.33% : 0.000003s : 16: predicate.special_op_eliminate 0.96% : 0.000009s : 50: predicate.specialize_transform 1.67% : 0.000016s : 101: predicate.split_environ_get_set_with_tuple_value 1.39% : 0.000013s : 101: predicate.stack_unstack_eliminate 0.15% : 0.000001s : 8: predicate.switch_call_monad_eliminater 3.30% : 0.000032s : 147: predicate.switch_defer_inline 2.43% : 0.000023s : 147: predicate.switch_layer_defer_inline 6.23% : 0.000060s : 348: predicate.switch_simplify 1.41% : 0.000014s : 101: predicate.tile_eliminate 1.53% : 0.000015s : 101: predicate.transpose_eliminate 1.85% : 0.000018s : 101: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000016s : 101: predicate.tuple_list_get_item_depend_reorder 3.45% : 0.000033s : 134: predicate.tuple_list_get_item_eliminator 1.88% : 0.000018s : 101: predicate.tuple_list_set_item_eliminator 1.68% : 0.000016s : 118: predicate.tuple_to_list_eliminator_ 1.88% : 0.000018s : 126: predicate.updatestate_pure_node_eliminater 2.87% : 0.000028s : 172: predicate.updatestate_useless_node_eliminater 1.98% : 0.000019s : 101: predicate.value_based_eliminate 0.14% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.26% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.185994 85 98.47% : 0.183150s : 48: func_graph_cloner_run.FuncGraphClonerGraph 0.24% : 0.000444s : 7: func_graph_cloner_run.FuncGraphClonerNode 1.29% : 0.002400s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.276651 104 0.01% : 0.000126s : 1: add_recomputation 0.02% : 0.000446s : 1: auto_monad 0.00% : 0.000058s : 1: auto_monad_reorder 0.02% : 0.000537s : 1: bootstrap 0.00% : 0.000055s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.00% : 0.000055s : 1: cse_after_recomputation 0.00% : 0.000020s : 1: environ_conv 0.09% : 0.002096s : 1: event_method 0.00% : 0.000015s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000016s : 1: graph_reusing 43.03% : 0.979658s : 1: jit_opt_a 0.02% : 0.000398s : 1: jit_opt_after_cconv 0.01% : 0.000119s : 1: jit_opt_b 0.03% : 0.000768s : 1: loop_unroll 0.04% : 0.001019s : 1: mutable_eliminate 0.38% : 0.008569s : 52: opt.transform.jit_opt_a 0.01% : 0.000152s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000074s : 4: opt.transform.jit_opt_b 0.00% : 0.000033s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000042s : 1: opt.transform.mutable_eliminate 0.00% : 0.000067s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.000982s : 2: opt.transform.opt_resolve 0.00% : 0.000079s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000898s : 1: opt_after_jit_grad 0.01% : 0.000128s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.06% : 0.001464s : 1: py_interpret_to_execute 0.00% : 0.000028s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000082s : 1: remove_dup_value 7.36% : 0.167663s : 3: renormalize.infer 10.60% : 0.241419s : 3: renormalize.specialize 0.00% : 0.000014s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000333s : 1: rewriter_after_opt_a 0.01% : 0.000268s : 1: rewriter_before_opt_a 0.01% : 0.000147s : 1: symbol_engine_optimizer 38.16% : 0.868781s : 1: type_inference . [hook] pytest_runtest_teardown:test_permute_high_dimension[KBK] tests/st/mint/test_permute.py::test_permute_high_dimension[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 154.33s (0:02:34) ==================