==================================================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_003/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 10 items test_permute.py . [hook] pytest_runtest_teardown:test_permute_special_values[inf-pynative] tests/st/mint/test_permute.py::test_permute_special_values[inf-pynative],max_mem:2.0M TotalTime = 1.56226, [30] [bootstrap]: 0.00067624 [type_inference]: 1.5424 [event_method]: 2.221e-05 [auto_monad]: 0.00021082 [graph_reusing]: 6.96001e-06 [pre_auto_parallel]: 1.277e-05 [py_interpret_to_execute]: 0.00039662 [rewriter_before_opt_a]: 9.227e-05 [expand_dump_flag]: 4.28001e-06 [jit_opt_a]: 0.0146232, [2] [Cycle 1]: 0.00494195, [27] [switch_simplify]: 7.513e-05 [loop_unroll]: 2.534e-05 [a_1]: 0.0006519 [with_stream_mark]: 3.615e-05 [recompute_prepare]: 1.255e-05 [updatestate_depend_eliminate]: 7.27997e-06 [updatestate_assign_eliminate]: 9.34e-06 [updatestate_loads_eliminate]: 6.09999e-06 [parameter_eliminate]: 2.76e-06 [specialize_transform]: 9.77999e-06 [updatestate_useless_node_eliminater]: 1.338e-05 [accelerated_algorithm]: 9.87001e-06 [meta_shard_fg_expand]: 3.72998e-06 [get_grad_eliminate_]: 9.34e-06 [merge_forward]: 6.22001e-06 [cell_reuse_recompute_pass]: 1.35001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.537e-05 [j_node_and_user_rematch]: 1.537e-05 [meta_fg_expand]: 3.97e-06 [replace_old_param]: 1.511e-05 [inline_without_move]: 9.98002e-06 [renormalize]: 0.00361368 [add_forward_monad_depend]: 1.65e-05 [auto_monad_grad]: 3.14999e-06 [auto_monad_eliminator]: 2.949e-05 [cse]: 4.587e-05 [replace_applicator]: 3.136e-05 [Cycle 2]: 0.00056574, [27] [switch_simplify]: 1.074e-05 [loop_unroll]: 9.19e-06 [a_1]: 0.00021674 [with_stream_mark]: 1.923e-05 [recompute_prepare]: 8.81002e-06 [updatestate_depend_eliminate]: 6.46e-06 [updatestate_assign_eliminate]: 5.74e-06 [updatestate_loads_eliminate]: 4.84003e-06 [parameter_eliminate]: 2.37999e-06 [specialize_transform]: 8.95999e-06 [updatestate_useless_node_eliminater]: 1.192e-05 [accelerated_algorithm]: 9.12001e-06 [meta_shard_fg_expand]: 2.58003e-06 [get_grad_eliminate_]: 8.07e-06 [merge_forward]: 7.29001e-06 [cell_reuse_recompute_pass]: 2.78e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.028e-05 [j_node_and_user_rematch]: 1.386e-05 [meta_fg_expand]: 3.56999e-06 [replace_old_param]: 1.31e-05 [inline_without_move]: 8.23001e-06 [renormalize]: 7.99773e-08 [add_forward_monad_depend]: 1.32999e-06 [auto_monad_grad]: 1.50999e-06 [auto_monad_eliminator]: 1.134e-05 [cse]: 1.948e-05 [replace_applicator]: 8.62998e-06 [py_interpret_to_execute_after_opt_a]: 2.162e-05 [rewriter_after_opt_a]: 0.00054322 [convert_after_rewriter]: 2.827e-05 [order_py_execute_after_rewriter]: 7.16001e-06 [mutable_eliminate]: 0.00085525 [jit_opt_b]: 8.663e-05, [1] [Cycle 1]: 7.688e-05, [2] [frontend_op_eliminate]: 3.334e-05 [inline_after_opt_a]: 2.872e-05 [cconv]: 3.873e-05 [loop_unroll]: 0.00049062 [jit_opt_after_cconv]: 0.00027501, [1] [Cycle 1]: 0.00026675, [11] [c_1]: 5.626e-05 [parameter_eliminate]: 4.1e-06 [updatestate_depend_eliminate]: 1.058e-05 [updatestate_assign_eliminate]: 5.49e-06 [updatestate_loads_eliminate]: 5.14998e-06 [cse]: 3.59e-05 [call_graph_tuple_transform]: 6.385e-05 [tuple_list_get_item_eliminator]: 1e-05 [none_parameter_eliminate]: 2.16e-06 [renormalize]: 5.00004e-07 [switch_simplify]: 1.033e-05 [remove_dup_value]: 2.175e-05 [partial_unused_args_eliminate]: 2.79001e-06 [environ_conv]: 3.071e-05 [add_recomputation]: 8.496e-05 [cse_after_recomputation]: 3.34e-05, [1] [Cycle 1]: 2.564e-05, [1] [cse]: 1.773e-05 [auto_monad_reorder]: 3.731e-05 [get_jit_bprop_graph]: 2.36998e-06 [rewriter_after_jit_bprop_graph]: 0.00014782 [opt_after_jit_grad]: 0.0005436 [symbol_engine_optimizer]: 0.00010654, [1] [Cycle 1]: 9.941e-05, [6] [build]: 7.04001e-06 [elim_shapecalc]: 1.262e-05 [elim_not_effective]: 2.076e-05 [opt_reshape]: 1.087e-05 [fold_const_symbol]: 1.525e-05 [renormalize]: 5.8001e-07 [validate]: 8.547e-05 Sums bootstrap : 0.000676s : 0.04% type_inference : 1.542402s : 99.37% event_method : 0.000022s : 0.00% auto_monad : 0.000211s : 0.01% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000397s : 0.03% rewriter_before_opt_a : 0.000092s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000086s : 0.01% jit_opt_a.loop_unroll : 0.000035s : 0.00% jit_opt_a.a_1 : 0.000869s : 0.06% jit_opt_a.with_stream_mark : 0.000055s : 0.00% jit_opt_a.recompute_prepare : 0.000021s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000011s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000019s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 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 : 0.000014s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000046s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000029s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000028s : 0.00% jit_opt_a.inline_without_move : 0.000018s : 0.00% jit_opt_a.renormalize : 0.003614s : 0.23% jit_opt_a.add_forward_monad_depend : 0.000018s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000041s : 0.00% jit_opt_a.cse : 0.000065s : 0.00% jit_opt_a.replace_applicator : 0.000040s : 0.00% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.000543s : 0.03% convert_after_rewriter : 0.000028s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000855s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000033s : 0.00% jit_opt_b.inline_after_opt_a : 0.000029s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000491s : 0.03% jit_opt_after_cconv.c_1 : 0.000056s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 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 : 0.000036s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000064s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000010s : 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 : 0.000010s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000031s : 0.00% add_recomputation : 0.000085s : 0.01% cse_after_recomputation.cse : 0.000018s : 0.00% auto_monad_reorder : 0.000037s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000148s : 0.01% opt_after_jit_grad : 0.000544s : 0.04% symbol_engine_optimizer.build : 0.000007s : 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.] 0.000388 45 3.33% : 0.000013s : 2: substitution.depend_value_elim 0.87% : 0.000003s : 4: substitution.elim_not_effective 0.68% : 0.000003s : 4: substitution.fold_const_symbol 11.58% : 0.000045s : 6: substitution.graph_param_transform 71.73% : 0.000278s : 3: substitution.inline 1.54% : 0.000006s : 8: substitution.j_node_and_user_rematch 1.97% : 0.000008s : 8: substitution.remove_not_recompute_node 2.18% : 0.000008s : 2: substitution.replace_old_param 3.02% : 0.000012s : 3: substitution.updatestate_pure_node_eliminater 3.09% : 0.000012s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.542264 2 78.30% : 1.207586s : 1: type_inference.infer 21.70% : 0.334678s : 1: type_inference.specialize ------[replace.] 0.000046 3 100.00% : 0.000046s : 3: replace.inline ------[match.] 0.000275 3 100.00% : 0.000275s : 3: match.inline ------[predicate.] 0.000172 970 1.35% : 0.000002s : 14: predicate.accumulaten_eliminater 1.44% : 0.000002s : 6: predicate.ad_related_special_op_eliminate 1.07% : 0.000002s : 14: predicate.addn_check_dump 1.24% : 0.000002s : 14: predicate.addn_zero_filter 2.16% : 0.000004s : 14: predicate.arithmetic_simplify 1.40% : 0.000002s : 14: predicate.cast_eliminate 0.70% : 0.000001s : 6: predicate.check_bprop_eliminate 1.01% : 0.000002s : 14: predicate.compare_switch_simplify 1.50% : 0.000003s : 14: predicate.depend_value_elim 1.33% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.26% : 0.000002s : 14: predicate.dict_get_item_eliminator 1.18% : 0.000002s : 14: predicate.dict_set_item_eliminator 0.98% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.49% : 0.000001s : 6: predicate.elim_not_effective 0.66% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.05% : 0.000002s : 14: predicate.environ_add_const_eliminate 1.00% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.03% : 0.000002s : 14: predicate.environ_get_depend_swap 1.16% : 0.000002s : 14: predicate.environ_get_eliminate 1.10% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.31% : 0.000001s : 6: predicate.fold_const_symbol 1.21% : 0.000002s : 12: predicate.get_grad_eliminate 0.44% : 0.000001s : 6: predicate.graph_param_transform 5.58% : 0.000010s : 29: predicate.inline 1.28% : 0.000002s : 12: predicate.inline_without_move 0.54% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.74% : 0.000003s : 12: predicate.less_batch_normalization 1.22% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.75% : 0.000003s : 20: predicate.load_eliminater 1.68% : 0.000003s : 6: predicate.loop_unroll_after_grad 2.82% : 0.000005s : 30: predicate.loop_unroll_before_grad 2.40% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.12% : 0.000002s : 14: predicate.merge_addn 1.00% : 0.000002s : 14: predicate.minmaximum_grad 2.11% : 0.000004s : 6: predicate.mutable_eliminate 0.73% : 0.000001s : 6: predicate.opt_reshape 2.19% : 0.000004s : 20: predicate.partial_eliminate 1.12% : 0.000002s : 14: predicate.print_const_string_wrapper 1.77% : 0.000003s : 14: predicate.reduce_eliminate 1.48% : 0.000003s : 14: predicate.redundant_stop_gradient_eliminater 0.86% : 0.000001s : 12: predicate.remove_not_recompute_node 1.80% : 0.000003s : 26: predicate.replace_applicator 0.79% : 0.000001s : 12: predicate.replace_old_param 0.51% : 0.000001s : 6: predicate.reset_defer_inline 1.13% : 0.000002s : 14: predicate.reshape_eliminate 1.19% : 0.000002s : 14: predicate.row_tensor_add_zeros_like 0.94% : 0.000002s : 6: predicate.row_tensor_eliminate 1.22% : 0.000002s : 14: predicate.same_eliminate 0.73% : 0.000001s : 12: predicate.set_cell_output_no_recompute 1.21% : 0.000002s : 12: predicate.special_op_eliminate 1.28% : 0.000002s : 12: predicate.specialize_transform 1.38% : 0.000002s : 14: predicate.split_environ_get_set_with_tuple_value 1.17% : 0.000002s : 14: predicate.stack_unstack_eliminate 0.55% : 0.000001s : 6: predicate.switch_call_monad_eliminater 1.79% : 0.000003s : 17: predicate.switch_defer_inline 1.45% : 0.000002s : 17: predicate.switch_layer_defer_inline 6.27% : 0.000011s : 53: predicate.switch_simplify 1.15% : 0.000002s : 14: predicate.tile_eliminate 1.26% : 0.000002s : 14: predicate.transpose_eliminate 1.33% : 0.000002s : 14: predicate.tuple_list_convert_item_index_to_positive 1.19% : 0.000002s : 14: predicate.tuple_list_get_item_depend_reorder 4.23% : 0.000007s : 26: predicate.tuple_list_get_item_eliminator 1.66% : 0.000003s : 14: predicate.tuple_list_set_item_eliminator 1.23% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.70% : 0.000003s : 20: predicate.updatestate_pure_node_eliminater 3.30% : 0.000006s : 32: predicate.updatestate_useless_node_eliminater 1.60% : 0.000003s : 14: predicate.value_based_eliminate 0.53% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.96% : 0.000002s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.013694 23 94.53% : 0.012945s : 18: func_graph_cloner_run.FuncGraphClonerGraph 5.47% : 0.000748s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.567115 72 0.01% : 0.000088s : 1: add_recomputation 0.01% : 0.000217s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.04% : 0.000704s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000033s : 1: convert_after_rewriter 0.00% : 0.000036s : 1: cse_after_recomputation 0.00% : 0.000034s : 1: environ_conv 0.00% : 0.000028s : 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 0.93% : 0.014627s : 1: jit_opt_a 0.02% : 0.000279s : 1: jit_opt_after_cconv 0.01% : 0.000090s : 1: jit_opt_b 0.03% : 0.000500s : 1: loop_unroll 0.06% : 0.000867s : 1: mutable_eliminate 0.08% : 0.001203s : 26: opt.transform.jit_opt_a 0.01% : 0.000136s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000053s : 4: opt.transform.jit_opt_b 0.00% : 0.000019s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000025s : 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 0.04% : 0.000554s : 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% : 0.000404s : 1: py_interpret_to_execute 0.00% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000025s : 1: remove_dup_value 0.17% : 0.002642s : 1: renormalize.infer 0.06% : 0.000959s : 1: renormalize.specialize 0.01% : 0.000152s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000550s : 1: rewriter_after_opt_a 0.01% : 0.000098s : 1: rewriter_before_opt_a 0.01% : 0.000110s : 1: symbol_engine_optimizer 98.43% : 1.542434s : 1: type_inference TotalTime = 2.54334, [30] [bootstrap]: 0.00052915 [type_inference]: 1.51393 [event_method]: 0.00060156 [auto_monad]: 0.00038828 [graph_reusing]: 1.311e-05 [pre_auto_parallel]: 4.55001e-06 [py_interpret_to_execute]: 6.054e-05 [rewriter_before_opt_a]: 0.00017128 [expand_dump_flag]: 4.66002e-06 [jit_opt_a]: 1.02388, [4] [Cycle 1]: 0.751274, [27] [switch_simplify]: 0.00025615 [loop_unroll]: 6.709e-05 [a_1]: 0.0016735 [with_stream_mark]: 4.502e-05 [recompute_prepare]: 3.313e-05 [updatestate_depend_eliminate]: 1.543e-05 [updatestate_assign_eliminate]: 1.227e-05 [updatestate_loads_eliminate]: 1.049e-05 [parameter_eliminate]: 3.63e-06 [specialize_transform]: 2.287e-05 [updatestate_useless_node_eliminater]: 2.68e-05 [accelerated_algorithm]: 2.072e-05 [meta_shard_fg_expand]: 8.32e-06 [get_grad_eliminate_]: 2.054e-05 [merge_forward]: 1.434e-05 [cell_reuse_recompute_pass]: 2.31e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.179e-05 [j_node_and_user_rematch]: 3.453e-05 [meta_fg_expand]: 0.495016 [replace_old_param]: 0.0001777 [inline_without_move]: 0.00014918 [renormalize]: 0.252501 [add_forward_monad_depend]: 3.609e-05 [auto_monad_grad]: 1.653e-05 [auto_monad_eliminator]: 0.00012936 [cse]: 0.00029944 [replace_applicator]: 0.00027233 [Cycle 2]: 0.264861, [27] [switch_simplify]: 9.631e-05 [loop_unroll]: 8.723e-05 [a_1]: 0.260786 [with_stream_mark]: 7.105e-05 [recompute_prepare]: 4.672e-05 [updatestate_depend_eliminate]: 1.532e-05 [updatestate_assign_eliminate]: 1.476e-05 [updatestate_loads_eliminate]: 1.277e-05 [parameter_eliminate]: 6.01e-06 [specialize_transform]: 2.198e-05 [updatestate_useless_node_eliminater]: 0.00013081 [accelerated_algorithm]: 1.541e-05 [meta_shard_fg_expand]: 8.97999e-06 [get_grad_eliminate_]: 1.414e-05 [merge_forward]: 9.31998e-06 [cell_reuse_recompute_pass]: 1.64e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.988e-05 [j_node_and_user_rematch]: 2.345e-05 [meta_fg_expand]: 0.00022008 [replace_old_param]: 2.421e-05 [inline_without_move]: 1.435e-05 [renormalize]: 0.00271497 [add_forward_monad_depend]: 1.016e-05 [auto_monad_grad]: 3.73999e-06 [auto_monad_eliminator]: 3.317e-05 [cse]: 0.00013214 [replace_applicator]: 3.875e-05 [Cycle 3]: 0.0019375, [27] [switch_simplify]: 1.835e-05 [loop_unroll]: 1.437e-05 [a_1]: 0.00039951 [with_stream_mark]: 2.608e-05 [recompute_prepare]: 1.455e-05 [updatestate_depend_eliminate]: 5.774e-05 [updatestate_assign_eliminate]: 7.16999e-06 [updatestate_loads_eliminate]: 6.58e-06 [parameter_eliminate]: 2.11e-06 [specialize_transform]: 1.395e-05 [updatestate_useless_node_eliminater]: 1.542e-05 [accelerated_algorithm]: 1.133e-05 [meta_shard_fg_expand]: 3.03e-06 [get_grad_eliminate_]: 1.047e-05 [merge_forward]: 7.13e-06 [cell_reuse_recompute_pass]: 3.2e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.717e-05 [j_node_and_user_rematch]: 1.871e-05 [meta_fg_expand]: 3.97e-06 [replace_old_param]: 1.55e-05 [inline_without_move]: 1.137e-05 [renormalize]: 0.00095801 [add_forward_monad_depend]: 7.11001e-06 [auto_monad_grad]: 2.88e-06 [auto_monad_eliminator]: 2.452e-05 [cse]: 4.553e-05 [replace_applicator]: 2.64e-05 [Cycle 4]: 0.00068907, [27] [switch_simplify]: 1.398e-05 [loop_unroll]: 1.292e-05 [a_1]: 0.00028191 [with_stream_mark]: 1.717e-05 [recompute_prepare]: 1.142e-05 [updatestate_depend_eliminate]: 7.03e-06 [updatestate_assign_eliminate]: 5.90002e-06 [updatestate_loads_eliminate]: 6.66999e-06 [parameter_eliminate]: 1.62999e-06 [specialize_transform]: 1.152e-05 [updatestate_useless_node_eliminater]: 1.484e-05 [accelerated_algorithm]: 1.079e-05 [meta_shard_fg_expand]: 3.48999e-06 [get_grad_eliminate_]: 1.097e-05 [merge_forward]: 5.41002e-06 [cell_reuse_recompute_pass]: 1.82999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.358e-05 [j_node_and_user_rematch]: 1.757e-05 [meta_fg_expand]: 4.43999e-06 [replace_old_param]: 1.381e-05 [inline_without_move]: 1.283e-05 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 2.63e-06 [auto_monad_grad]: 1.22e-06 [auto_monad_eliminator]: 1.57e-05 [cse]: 2.644e-05 [replace_applicator]: 1.217e-05 [py_interpret_to_execute_after_opt_a]: 2.241e-05 [rewriter_after_opt_a]: 0.00021413 [convert_after_rewriter]: 1.364e-05 [order_py_execute_after_rewriter]: 8.78001e-06 [mutable_eliminate]: 0.00095738 [jit_opt_b]: 0.00010492, [1] [Cycle 1]: 9.206e-05, [2] [frontend_op_eliminate]: 3.872e-05 [inline_after_opt_a]: 3.75e-05 [cconv]: 4.641e-05 [loop_unroll]: 0.00061083 [jit_opt_after_cconv]: 0.00033834, [1] [Cycle 1]: 0.00032905, [11] [c_1]: 8.634e-05 [parameter_eliminate]: 6.91999e-06 [updatestate_depend_eliminate]: 1.852e-05 [updatestate_assign_eliminate]: 9.04e-06 [updatestate_loads_eliminate]: 7.28e-06 [cse]: 6.684e-05 [call_graph_tuple_transform]: 3.771e-05 [tuple_list_get_item_eliminator]: 1.18e-05 [none_parameter_eliminate]: 1.73002e-06 [renormalize]: 1.02998e-06 [switch_simplify]: 1.383e-05 [remove_dup_value]: 7.062e-05 [partial_unused_args_eliminate]: 3.14999e-06 [environ_conv]: 1.777e-05 [add_recomputation]: 0.00010361 [cse_after_recomputation]: 4.26e-05, [1] [Cycle 1]: 3.395e-05, [1] [cse]: 2.472e-05 [auto_monad_reorder]: 4.367e-05 [get_jit_bprop_graph]: 2.29999e-06 [rewriter_after_jit_bprop_graph]: 9.91e-06 [opt_after_jit_grad]: 0.0006383 [symbol_engine_optimizer]: 0.0001334, [1] [Cycle 1]: 0.00012575, [6] [build]: 8.40001e-06 [elim_shapecalc]: 1.568e-05 [elim_not_effective]: 2.916e-05 [opt_reshape]: 1.38e-05 [fold_const_symbol]: 2.049e-05 [renormalize]: 7.30011e-07 [validate]: 8.828e-05 Sums bootstrap : 0.000529s : 0.02% type_inference : 1.513926s : 59.68% event_method : 0.000602s : 0.02% auto_monad : 0.000388s : 0.02% graph_reusing : 0.000013s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000061s : 0.00% rewriter_before_opt_a : 0.000171s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000385s : 0.02% jit_opt_a.loop_unroll : 0.000182s : 0.01% jit_opt_a.a_1 : 0.263140s : 10.37% jit_opt_a.with_stream_mark : 0.000159s : 0.01% jit_opt_a.recompute_prepare : 0.000106s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000096s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000040s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000037s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000070s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000188s : 0.01% jit_opt_a.accelerated_algorithm : 0.000058s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000024s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000056s : 0.00% jit_opt_a.merge_forward : 0.000036s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000122s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000094s : 0.00% jit_opt_a.meta_fg_expand : 0.495244s : 19.52% jit_opt_a.replace_old_param : 0.000231s : 0.01% jit_opt_a.inline_without_move : 0.000188s : 0.01% jit_opt_a.renormalize : 0.256174s : 10.10% jit_opt_a.add_forward_monad_depend : 0.000056s : 0.00% jit_opt_a.auto_monad_grad : 0.000024s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000203s : 0.01% jit_opt_a.cse : 0.000504s : 0.02% jit_opt_a.replace_applicator : 0.000350s : 0.01% py_interpret_to_execute_after_opt_a : 0.000022s : 0.00% rewriter_after_opt_a : 0.000214s : 0.01% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000957s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000039s : 0.00% jit_opt_b.inline_after_opt_a : 0.000037s : 0.00% cconv : 0.000046s : 0.00% loop_unroll : 0.000611s : 0.02% jit_opt_after_cconv.c_1 : 0.000086s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000019s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.cse : 0.000067s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000038s : 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 : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000014s : 0.00% remove_dup_value : 0.000071s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000018s : 0.00% add_recomputation : 0.000104s : 0.00% cse_after_recomputation.cse : 0.000025s : 0.00% auto_monad_reorder : 0.000044s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000010s : 0.00% opt_after_jit_grad : 0.000638s : 0.03% symbol_engine_optimizer.build : 0.000008s : 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 : 0.000014s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000020s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000088s : 0.00% Time group info: ------[substitution.] 0.003116 271 1.41% : 0.000044s : 12: substitution.depend_value_elim 0.14% : 0.000004s : 5: substitution.elim_not_effective 0.09% : 0.000003s : 5: substitution.fold_const_symbol 28.05% : 0.000874s : 4: substitution.getattr_setattr_resolve 0.33% : 0.000010s : 8: substitution.graph_param_transform 52.03% : 0.001621s : 29: substitution.inline 1.67% : 0.000052s : 4: substitution.inline_without_move 0.57% : 0.000018s : 29: substitution.j_node_and_user_rematch 0.76% : 0.000024s : 13: substitution.minmaximum_grad 0.53% : 0.000017s : 14: substitution.partial_eliminate 0.81% : 0.000025s : 29: substitution.remove_not_recompute_node 2.44% : 0.000076s : 16: substitution.replace_applicator 0.73% : 0.000023s : 17: substitution.replace_old_param 0.36% : 0.000011s : 2: substitution.set_cell_output_no_recompute 0.51% : 0.000016s : 3: substitution.switch_simplify 1.41% : 0.000044s : 13: substitution.tuple_list_convert_item_index_to_positive 1.04% : 0.000032s : 13: substitution.tuple_list_get_item_depend_reorder 3.91% : 0.000122s : 30: substitution.tuple_list_get_item_eliminator 0.91% : 0.000028s : 9: substitution.updatestate_pure_node_eliminater 2.30% : 0.000072s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.513762 2 99.64% : 1.508386s : 1: type_inference.infer 0.36% : 0.005376s : 1: type_inference.specialize ------[replace.] 0.257285 54 0.03% : 0.000078s : 3: replace.getattr_setattr_resolve 99.78% : 0.256709s : 29: replace.inline 0.03% : 0.000067s : 1: replace.replace_applicator 0.03% : 0.000086s : 3: replace.switch_simplify 0.10% : 0.000269s : 17: replace.tuple_list_get_item_eliminator 0.03% : 0.000075s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002516 54 32.04% : 0.000806s : 3: match.getattr_setattr_resolve 63.54% : 0.001599s : 29: match.inline 0.66% : 0.000017s : 1: match.replace_applicator 0.55% : 0.000014s : 3: match.switch_simplify 2.25% : 0.000057s : 17: match.tuple_list_get_item_eliminator 0.96% : 0.000024s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000987 6056 1.50% : 0.000015s : 101: predicate.accumulaten_eliminater 0.41% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.33% : 0.000013s : 101: predicate.addn_check_dump 1.48% : 0.000015s : 101: predicate.addn_zero_filter 2.32% : 0.000023s : 101: predicate.arithmetic_simplify 1.51% : 0.000015s : 101: predicate.cast_eliminate 0.13% : 0.000001s : 8: predicate.check_bprop_eliminate 1.35% : 0.000013s : 101: predicate.compare_switch_simplify 1.64% : 0.000016s : 101: predicate.depend_value_elim 1.29% : 0.000013s : 101: predicate.dict_get_item_const_eliminator 1.47% : 0.000014s : 101: predicate.dict_get_item_eliminator 1.38% : 0.000014s : 101: predicate.dict_set_item_eliminator 0.20% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.15% : 0.000001s : 8: predicate.elim_not_effective 0.18% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.46% : 0.000014s : 101: predicate.environ_add_const_eliminate 1.41% : 0.000014s : 101: predicate.environ_get_add_eliminate 1.46% : 0.000014s : 101: predicate.environ_get_depend_swap 1.41% : 0.000014s : 101: predicate.environ_get_eliminate 1.44% : 0.000014s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.73% : 0.000007s : 44: predicate.get_grad_eliminate 0.87% : 0.000009s : 20: predicate.getattr_setattr_resolve 0.06% : 0.000001s : 8: predicate.graph_param_transform 4.58% : 0.000045s : 163: predicate.inline 2.18% : 0.000021s : 105: predicate.inline_without_move 0.32% : 0.000003s : 44: predicate.j_node_and_user_rematch 0.90% : 0.000009s : 44: predicate.less_batch_normalization 1.77% : 0.000018s : 118: predicate.list_to_tuple_eliminator_ 1.96% : 0.000019s : 126: predicate.load_eliminater 0.45% : 0.000004s : 8: predicate.loop_unroll_after_grad 2.81% : 0.000028s : 187: predicate.loop_unroll_before_grad 1.73% : 0.000017s : 109: predicate.make_slice_get_slice_eliminator 1.27% : 0.000012s : 101: predicate.merge_addn 1.35% : 0.000013s : 101: predicate.minmaximum_grad 0.57% : 0.000006s : 8: predicate.mutable_eliminate 0.16% : 0.000002s : 8: predicate.opt_reshape 2.43% : 0.000024s : 126: predicate.partial_eliminate 1.42% : 0.000014s : 101: predicate.print_const_string_wrapper 2.06% : 0.000020s : 101: predicate.reduce_eliminate 1.72% : 0.000017s : 118: predicate.redundant_stop_gradient_eliminater 0.41% : 0.000004s : 44: predicate.remove_not_recompute_node 2.71% : 0.000027s : 243: predicate.replace_applicator 1.01% : 0.000010s : 105: predicate.replace_old_param 0.08% : 0.000001s : 8: predicate.reset_defer_inline 1.39% : 0.000014s : 101: predicate.reshape_eliminate 1.54% : 0.000015s : 101: predicate.row_tensor_add_zeros_like 0.23% : 0.000002s : 8: predicate.row_tensor_eliminate 1.41% : 0.000014s : 101: predicate.same_eliminate 0.51% : 0.000005s : 52: predicate.set_cell_output_no_recompute 0.27% : 0.000003s : 16: predicate.special_op_eliminate 0.82% : 0.000008s : 50: predicate.specialize_transform 1.74% : 0.000017s : 101: predicate.split_environ_get_set_with_tuple_value 1.52% : 0.000015s : 101: predicate.stack_unstack_eliminate 0.13% : 0.000001s : 8: predicate.switch_call_monad_eliminater 4.04% : 0.000040s : 147: predicate.switch_defer_inline 2.32% : 0.000023s : 147: predicate.switch_layer_defer_inline 5.82% : 0.000057s : 348: predicate.switch_simplify 1.52% : 0.000015s : 101: predicate.tile_eliminate 1.44% : 0.000014s : 101: predicate.transpose_eliminate 2.10% : 0.000021s : 101: predicate.tuple_list_convert_item_index_to_positive 1.80% : 0.000018s : 101: predicate.tuple_list_get_item_depend_reorder 3.51% : 0.000035s : 134: predicate.tuple_list_get_item_eliminator 1.76% : 0.000017s : 101: predicate.tuple_list_set_item_eliminator 1.93% : 0.000019s : 118: predicate.tuple_to_list_eliminator_ 1.90% : 0.000019s : 126: predicate.updatestate_pure_node_eliminater 2.88% : 0.000028s : 172: predicate.updatestate_useless_node_eliminater 2.00% : 0.000020s : 101: predicate.value_based_eliminate 0.12% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.17% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.009090 79 69.94% : 0.006357s : 42: func_graph_cloner_run.FuncGraphClonerGraph 5.00% : 0.000455s : 7: func_graph_cloner_run.FuncGraphClonerNode 25.06% : 0.002278s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 3.065790 104 0.00% : 0.000108s : 1: add_recomputation 0.01% : 0.000399s : 1: auto_monad 0.00% : 0.000048s : 1: auto_monad_reorder 0.02% : 0.000557s : 1: bootstrap 0.00% : 0.000051s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.00% : 0.000046s : 1: cse_after_recomputation 0.00% : 0.000021s : 1: environ_conv 0.02% : 0.000613s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000017s : 1: graph_reusing 33.40% : 1.023883s : 1: jit_opt_a 0.01% : 0.000343s : 1: jit_opt_after_cconv 0.00% : 0.000109s : 1: jit_opt_b 0.02% : 0.000624s : 1: loop_unroll 0.03% : 0.000975s : 1: mutable_eliminate 8.65% : 0.265069s : 52: opt.transform.jit_opt_a 0.00% : 0.000144s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000066s : 4: opt.transform.jit_opt_b 0.00% : 0.000027s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000037s : 1: opt.transform.mutable_eliminate 0.00% : 0.000050s : 1: opt.transform.opt_after_jit_grad 0.03% : 0.001026s : 2: opt.transform.opt_resolve 0.00% : 0.000075s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000653s : 1: opt_after_jit_grad 0.00% : 0.000011s : 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% : 0.000064s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000076s : 1: remove_dup_value 8.15% : 0.249910s : 3: renormalize.infer 0.20% : 0.006224s : 3: renormalize.specialize 0.00% : 0.000012s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000220s : 1: rewriter_after_opt_a 0.01% : 0.000177s : 1: rewriter_before_opt_a 0.00% : 0.000137s : 1: symbol_engine_optimizer 49.38% : 1.513951s : 1: type_inference . [hook] pytest_runtest_teardown:test_permute_special_values[inf-KBK] tests/st/mint/test_permute.py::test_permute_special_values[inf-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[nan-pynative] tests/st/mint/test_permute.py::test_permute_special_values[nan-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[nan-KBK] tests/st/mint/test_permute.py::test_permute_special_values[nan-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[zero-pynative] tests/st/mint/test_permute.py::test_permute_special_values[zero-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[zero-KBK] tests/st/mint/test_permute.py::test_permute_special_values[zero-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[large-pynative] tests/st/mint/test_permute.py::test_permute_special_values[large-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[large-KBK] tests/st/mint/test_permute.py::test_permute_special_values[large-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[small-pynative] tests/st/mint/test_permute.py::test_permute_special_values[small-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_permute_special_values[small-KBK] tests/st/mint/test_permute.py::test_permute_special_values[small-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 ================= 10 passed, 25 warnings in 124.53s (0:02:04) ==================