==================================================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_004/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_reshape.py . [hook] pytest_runtest_teardown:test_reshape_zero_bias[pynative] tests/st/mint/test_reshape.py::test_reshape_zero_bias[pynative],max_mem:2.0M [WARNING] PARSER(170591,ffff9c555f30,python3.9):2026-01-29-17:39:14.992.824 [mindspore/ccsrc/frontend/jit/ps/parse/data_converter.cc:661] CheckAPI] The mint interface reshape was called, and the operators under this interface have different view capabilities on pynative and graph mode. Use this interface with caution in graph mode, as it may produce unexpected results. For more information, please refer to: https://www.mindspore.cn/docs/en/master/features/view.html TotalTime = 1.4052, [30] [bootstrap]: 0.00063513 [type_inference]: 1.18918 [event_method]: 2.574e-05 [auto_monad]: 0.00010866 [graph_reusing]: 6.48e-06 [pre_auto_parallel]: 1.524e-05 [py_interpret_to_execute]: 0.00034723 [rewriter_before_opt_a]: 0.00011034 [expand_dump_flag]: 4.33999e-06 [jit_opt_a]: 0.0310669, [2] [Cycle 1]: 0.0199159, [27] [switch_simplify]: 9.087e-05 [loop_unroll]: 3.474e-05 [a_1]: 0.00074181 [with_stream_mark]: 3.072e-05 [recompute_prepare]: 1.223e-05 [updatestate_depend_eliminate]: 5.04998e-06 [updatestate_assign_eliminate]: 3.30998e-06 [updatestate_loads_eliminate]: 3.65998e-06 [parameter_eliminate]: 2.26998e-06 [specialize_transform]: 7.70998e-06 [updatestate_useless_node_eliminater]: 6.59999e-06 [accelerated_algorithm]: 7.65e-06 [meta_shard_fg_expand]: 3.00002e-06 [get_grad_eliminate_]: 8.00999e-06 [merge_forward]: 5.09998e-06 [cell_reuse_recompute_pass]: 1.72001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.284e-05 [j_node_and_user_rematch]: 1.311e-05 [meta_fg_expand]: 3.09999e-06 [replace_old_param]: 1.326e-05 [inline_without_move]: 7.06001e-06 [renormalize]: 0.0184111 [add_forward_monad_depend]: 2.076e-05 [auto_monad_grad]: 2.69999e-06 [auto_monad_eliminator]: 5.543e-05 [cse]: 6.045e-05 [replace_applicator]: 2.786e-05 [Cycle 2]: 0.00047165, [27] [switch_simplify]: 1.023e-05 [loop_unroll]: 7.36999e-06 [a_1]: 0.00015989 [with_stream_mark]: 2.067e-05 [recompute_prepare]: 7.14001e-06 [updatestate_depend_eliminate]: 4.07998e-06 [updatestate_assign_eliminate]: 3.46999e-06 [updatestate_loads_eliminate]: 3.69002e-06 [parameter_eliminate]: 1.74998e-06 [specialize_transform]: 6.11e-06 [updatestate_useless_node_eliminater]: 6.48003e-06 [accelerated_algorithm]: 7.23e-06 [meta_shard_fg_expand]: 2.53003e-06 [get_grad_eliminate_]: 5.99999e-06 [merge_forward]: 4.26001e-06 [cell_reuse_recompute_pass]: 4.93001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.686e-05 [j_node_and_user_rematch]: 1.052e-05 [meta_fg_expand]: 2.64999e-06 [replace_old_param]: 1.091e-05 [inline_without_move]: 5.89e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 1.53002e-06 [auto_monad_grad]: 9.89996e-07 [auto_monad_eliminator]: 8.18001e-06 [cse]: 1.762e-05 [replace_applicator]: 6.38998e-06 [py_interpret_to_execute_after_opt_a]: 2.002e-05 [rewriter_after_opt_a]: 7.34e-05 [convert_after_rewriter]: 8.60999e-06 [order_py_execute_after_rewriter]: 5.55001e-06 [mutable_eliminate]: 0.00082052 [jit_opt_b]: 6.512e-05, [1] [Cycle 1]: 5.589e-05, [2] [frontend_op_eliminate]: 2.215e-05 [inline_after_opt_a]: 1.924e-05 [cconv]: 3.349e-05 [loop_unroll]: 0.180344 [jit_opt_after_cconv]: 0.00033279, [1] [Cycle 1]: 0.00031604, [11] [c_1]: 7.353e-05 [parameter_eliminate]: 8.72e-06 [updatestate_depend_eliminate]: 1.589e-05 [updatestate_assign_eliminate]: 4.3e-06 [updatestate_loads_eliminate]: 4.08001e-06 [cse]: 5.283e-05 [call_graph_tuple_transform]: 3.99e-05 [tuple_list_get_item_eliminator]: 9.81e-06 [none_parameter_eliminate]: 1.60999e-06 [renormalize]: 1.05001e-06 [switch_simplify]: 9.78002e-06 [remove_dup_value]: 2.206e-05 [partial_unused_args_eliminate]: 3.5e-06 [environ_conv]: 3.293e-05 [add_recomputation]: 7.278e-05 [cse_after_recomputation]: 3.12e-05, [1] [Cycle 1]: 2.361e-05, [1] [cse]: 1.565e-05 [auto_monad_reorder]: 2.904e-05 [get_jit_bprop_graph]: 2.69999e-06 [rewriter_after_jit_bprop_graph]: 0.00028316 [opt_after_jit_grad]: 0.00090672 [symbol_engine_optimizer]: 0.00010586, [1] [Cycle 1]: 9.597e-05, [6] [build]: 6.79999e-06 [elim_shapecalc]: 1.093e-05 [elim_not_effective]: 1.997e-05 [opt_reshape]: 1.189e-05 [fold_const_symbol]: 1.112e-05 [renormalize]: 9.50007e-07 [validate]: 9.488e-05 Sums bootstrap : 0.000635s : 0.05% type_inference : 1.189184s : 85.34% event_method : 0.000026s : 0.00% auto_monad : 0.000109s : 0.01% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000015s : 0.00% py_interpret_to_execute : 0.000347s : 0.02% rewriter_before_opt_a : 0.000110s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000101s : 0.01% jit_opt_a.loop_unroll : 0.000042s : 0.00% jit_opt_a.a_1 : 0.000902s : 0.06% jit_opt_a.with_stream_mark : 0.000051s : 0.00% jit_opt_a.recompute_prepare : 0.000019s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000014s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000013s : 0.00% jit_opt_a.accelerated_algorithm : 0.000015s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000014s : 0.00% jit_opt_a.merge_forward : 0.000009s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000040s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000024s : 0.00% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000024s : 0.00% jit_opt_a.inline_without_move : 0.000013s : 0.00% jit_opt_a.renormalize : 0.018411s : 1.32% jit_opt_a.add_forward_monad_depend : 0.000022s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000064s : 0.00% jit_opt_a.cse : 0.000078s : 0.01% jit_opt_a.replace_applicator : 0.000034s : 0.00% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000073s : 0.01% convert_after_rewriter : 0.000009s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000821s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000022s : 0.00% jit_opt_b.inline_after_opt_a : 0.000019s : 0.00% cconv : 0.000033s : 0.00% loop_unroll : 0.180344s : 12.94% jit_opt_after_cconv.c_1 : 0.000074s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000009s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000053s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000040s : 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 : 0.000033s : 0.00% add_recomputation : 0.000073s : 0.01% cse_after_recomputation.cse : 0.000016s : 0.00% auto_monad_reorder : 0.000029s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000283s : 0.02% opt_after_jit_grad : 0.000907s : 0.07% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000095s : 0.01% Time group info: ------[substitution.] 0.000306 28 1.18% : 0.000004s : 2: substitution.elim_not_effective 0.58% : 0.000002s : 2: substitution.fold_const_symbol 3.06% : 0.000009s : 4: substitution.graph_param_transform 76.70% : 0.000235s : 5: substitution.inline 1.84% : 0.000006s : 4: substitution.j_node_and_user_rematch 0.53% : 0.000002s : 1: substitution.opt_reshape 1.80% : 0.000006s : 4: substitution.remove_not_recompute_node 2.52% : 0.000008s : 2: substitution.replace_old_param 9.02% : 0.000028s : 3: substitution.reshape_eliminate 2.77% : 0.000008s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.189058 2 93.36% : 1.110158s : 1: type_inference.infer 6.64% : 0.078900s : 1: type_inference.specialize ------[replace.] 0.000077 6 80.08% : 0.000062s : 5: replace.inline 19.92% : 0.000015s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000239 6 96.77% : 0.000231s : 5: match.inline 3.23% : 0.000008s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000180 867 1.09% : 0.000002s : 13: predicate.accumulaten_eliminater 1.49% : 0.000003s : 4: predicate.ad_related_special_op_eliminate 1.02% : 0.000002s : 13: predicate.addn_check_dump 1.18% : 0.000002s : 13: predicate.addn_zero_filter 2.17% : 0.000004s : 13: predicate.arithmetic_simplify 1.15% : 0.000002s : 13: predicate.cast_eliminate 0.38% : 0.000001s : 4: predicate.check_bprop_eliminate 1.08% : 0.000002s : 13: predicate.compare_switch_simplify 1.06% : 0.000002s : 13: predicate.depend_value_elim 0.98% : 0.000002s : 13: predicate.dict_get_item_const_eliminator 1.14% : 0.000002s : 13: predicate.dict_get_item_eliminator 1.14% : 0.000002s : 13: predicate.dict_set_item_eliminator 0.68% : 0.000001s : 4: predicate.dumpgradient_eliminate 0.51% : 0.000001s : 4: predicate.elim_not_effective 0.62% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.09% : 0.000002s : 13: predicate.environ_add_const_eliminate 1.34% : 0.000002s : 13: predicate.environ_get_add_eliminate 1.23% : 0.000002s : 13: predicate.environ_get_depend_swap 1.08% : 0.000002s : 13: predicate.environ_get_eliminate 0.95% : 0.000002s : 13: predicate.environ_get_set_eliminate 0.23% : 0.000000s : 4: predicate.fold_const_symbol 0.95% : 0.000002s : 8: predicate.get_grad_eliminate 0.43% : 0.000001s : 4: predicate.graph_param_transform 8.07% : 0.000015s : 27: predicate.inline 0.71% : 0.000001s : 8: predicate.inline_without_move 0.48% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.49% : 0.000003s : 8: predicate.less_batch_normalization 1.40% : 0.000003s : 14: predicate.list_to_tuple_eliminator_ 1.68% : 0.000003s : 18: predicate.load_eliminater 1.29% : 0.000002s : 4: predicate.loop_unroll_after_grad 3.10% : 0.000006s : 37: predicate.loop_unroll_before_grad 2.35% : 0.000004s : 17: predicate.make_slice_get_slice_eliminator 1.08% : 0.000002s : 13: predicate.merge_addn 1.28% : 0.000002s : 13: predicate.minmaximum_grad 1.64% : 0.000003s : 4: predicate.mutable_eliminate 0.64% : 0.000001s : 4: predicate.opt_reshape 2.02% : 0.000004s : 18: predicate.partial_eliminate 1.05% : 0.000002s : 13: predicate.print_const_string_wrapper 1.48% : 0.000003s : 13: predicate.reduce_eliminate 1.21% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.40% : 0.000001s : 8: predicate.remove_not_recompute_node 1.67% : 0.000003s : 22: predicate.replace_applicator 0.57% : 0.000001s : 8: predicate.replace_old_param 0.43% : 0.000001s : 4: predicate.reset_defer_inline 1.85% : 0.000003s : 13: predicate.reshape_eliminate 1.20% : 0.000002s : 13: predicate.row_tensor_add_zeros_like 0.85% : 0.000002s : 4: predicate.row_tensor_eliminate 1.54% : 0.000003s : 13: predicate.same_eliminate 0.53% : 0.000001s : 8: predicate.set_cell_output_no_recompute 0.90% : 0.000002s : 8: predicate.special_op_eliminate 0.73% : 0.000001s : 8: predicate.specialize_transform 1.34% : 0.000002s : 13: predicate.split_environ_get_set_with_tuple_value 1.24% : 0.000002s : 13: predicate.stack_unstack_eliminate 0.54% : 0.000001s : 4: predicate.switch_call_monad_eliminater 2.15% : 0.000004s : 19: predicate.switch_defer_inline 1.73% : 0.000003s : 19: predicate.switch_layer_defer_inline 6.87% : 0.000012s : 60: predicate.switch_simplify 1.13% : 0.000002s : 13: predicate.tile_eliminate 1.12% : 0.000002s : 13: predicate.transpose_eliminate 1.32% : 0.000002s : 13: predicate.tuple_list_convert_item_index_to_positive 1.18% : 0.000002s : 13: predicate.tuple_list_get_item_depend_reorder 3.64% : 0.000007s : 22: predicate.tuple_list_get_item_eliminator 1.97% : 0.000004s : 13: predicate.tuple_list_set_item_eliminator 2.22% : 0.000004s : 14: predicate.tuple_to_list_eliminator_ 1.46% : 0.000003s : 18: predicate.updatestate_pure_node_eliminater 4.28% : 0.000008s : 26: predicate.updatestate_useless_node_eliminater 2.39% : 0.000004s : 13: predicate.value_based_eliminate 0.32% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.53% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.198603 23 53.66% : 0.106565s : 16: func_graph_cloner_run.FuncGraphClonerGraph 46.34% : 0.092038s : 7: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.424778 72 0.01% : 0.000076s : 1: add_recomputation 0.01% : 0.000114s : 1: auto_monad 0.00% : 0.000032s : 1: auto_monad_reorder 0.05% : 0.000660s : 1: bootstrap 0.00% : 0.000036s : 1: cconv 0.00% : 0.000011s : 1: convert_after_rewriter 0.00% : 0.000034s : 1: cse_after_recomputation 0.00% : 0.000036s : 1: environ_conv 0.00% : 0.000032s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 2.18% : 0.031071s : 1: jit_opt_a 0.02% : 0.000339s : 1: jit_opt_after_cconv 0.00% : 0.000068s : 1: jit_opt_b 12.66% : 0.180385s : 1: loop_unroll 0.06% : 0.000832s : 1: mutable_eliminate 0.08% : 0.001199s : 26: opt.transform.jit_opt_a 0.01% : 0.000120s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000034s : 4: opt.transform.jit_opt_b 0.00% : 0.000015s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000017s : 1: opt.transform.mutable_eliminate 0.00% : 0.000036s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000050s : 4: opt.transform.symbol_engine_opt 0.06% : 0.000925s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.00% : 0.000018s : 1: pre_auto_parallel 0.02% : 0.000353s : 1: py_interpret_to_execute 0.00% : 0.000023s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000026s : 1: remove_dup_value 0.17% : 0.002354s : 1: renormalize.infer 1.13% : 0.016040s : 1: renormalize.specialize 0.02% : 0.000290s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000077s : 1: rewriter_after_opt_a 0.01% : 0.000117s : 1: rewriter_before_opt_a 0.01% : 0.000109s : 1: symbol_engine_optimizer 83.47% : 1.189215s : 1: type_inference TotalTime = 1.46968, [30] [bootstrap]: 0.00058147 [type_inference]: 1.14008 [event_method]: 0.00080949 [auto_monad]: 0.00020865 [graph_reusing]: 1.251e-05 [pre_auto_parallel]: 4.38001e-06 [py_interpret_to_execute]: 9.028e-05 [rewriter_before_opt_a]: 0.0002117 [expand_dump_flag]: 5.93002e-06 [jit_opt_a]: 0.324516, [2] [Cycle 1]: 0.130199, [27] [switch_simplify]: 0.00039861 [loop_unroll]: 9.142e-05 [a_1]: 0.00164518 [with_stream_mark]: 3.857e-05 [recompute_prepare]: 2.854e-05 [updatestate_depend_eliminate]: 1.135e-05 [updatestate_assign_eliminate]: 7.15e-06 [updatestate_loads_eliminate]: 7.29001e-06 [parameter_eliminate]: 3.69002e-06 [specialize_transform]: 1.942e-05 [updatestate_useless_node_eliminater]: 1.714e-05 [accelerated_algorithm]: 1.859e-05 [meta_shard_fg_expand]: 1.154e-05 [get_grad_eliminate_]: 1.732e-05 [merge_forward]: 9.59999e-06 [cell_reuse_recompute_pass]: 1.35001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.644e-05 [j_node_and_user_rematch]: 2.981e-05 [meta_fg_expand]: 0.00273865 [replace_old_param]: 8.944e-05 [inline_without_move]: 7.512e-05 [renormalize]: 0.124467 [add_forward_monad_depend]: 1.656e-05 [auto_monad_grad]: 3.26001e-06 [auto_monad_eliminator]: 1.988e-05 [cse]: 3.382e-05 [replace_applicator]: 2.633e-05 [Cycle 2]: 0.00061892, [27] [switch_simplify]: 6.58003e-06 [loop_unroll]: 4.75999e-06 [a_1]: 6.957e-05 [with_stream_mark]: 1.635e-05 [recompute_prepare]: 4.4e-06 [updatestate_depend_eliminate]: 3.89002e-06 [updatestate_assign_eliminate]: 2.80002e-06 [updatestate_loads_eliminate]: 2.31e-06 [parameter_eliminate]: 2.10002e-06 [specialize_transform]: 4.85001e-06 [updatestate_useless_node_eliminater]: 4.12e-06 [accelerated_algorithm]: 4.87998e-06 [meta_shard_fg_expand]: 2.30002e-06 [get_grad_eliminate_]: 4.2e-06 [merge_forward]: 3.72998e-06 [cell_reuse_recompute_pass]: 4.64998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.882e-05 [j_node_and_user_rematch]: 8.62e-06 [meta_fg_expand]: 0.00026265 [replace_old_param]: 7.38e-06 [inline_without_move]: 5.24e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.16e-06 [auto_monad_grad]: 1.49e-06 [auto_monad_eliminator]: 7.19001e-06 [cse]: 1.57e-05 [replace_applicator]: 4.62e-06 [py_interpret_to_execute_after_opt_a]: 1.818e-05 [rewriter_after_opt_a]: 0.0004694 [convert_after_rewriter]: 1.526e-05 [order_py_execute_after_rewriter]: 4.90001e-06 [mutable_eliminate]: 0.00083177 [jit_opt_b]: 5.953e-05, [1] [Cycle 1]: 4.954e-05, [2] [frontend_op_eliminate]: 1.666e-05 [inline_after_opt_a]: 1.742e-05 [cconv]: 3.937e-05 [loop_unroll]: 0.00051003 [jit_opt_after_cconv]: 0.00017531, [1] [Cycle 1]: 0.00016726, [11] [c_1]: 1.8e-05 [parameter_eliminate]: 5.53997e-06 [updatestate_depend_eliminate]: 7.61999e-06 [updatestate_assign_eliminate]: 2.49001e-06 [updatestate_loads_eliminate]: 2.94999e-06 [cse]: 3.487e-05 [call_graph_tuple_transform]: 2.234e-05 [tuple_list_get_item_eliminator]: 5.22999e-06 [none_parameter_eliminate]: 1.57001e-06 [renormalize]: 4.69998e-07 [switch_simplify]: 5.35999e-06 [remove_dup_value]: 1.717e-05 [partial_unused_args_eliminate]: 2.38998e-06 [environ_conv]: 6.51999e-06 [add_recomputation]: 4.831e-05 [cse_after_recomputation]: 2.638e-05, [1] [Cycle 1]: 1.882e-05, [1] [cse]: 1.081e-05 [auto_monad_reorder]: 1.455e-05 [get_jit_bprop_graph]: 2.15002e-06 [rewriter_after_jit_bprop_graph]: 9.08002e-06 [opt_after_jit_grad]: 0.00051108 [symbol_engine_optimizer]: 8.477e-05, [1] [Cycle 1]: 7.689e-05, [6] [build]: 4.58999e-06 [elim_shapecalc]: 7.63001e-06 [elim_not_effective]: 1.456e-05 [opt_reshape]: 6.21998e-06 [fold_const_symbol]: 9.42999e-06 [renormalize]: 6.19999e-07 [validate]: 4.091e-05 Sums bootstrap : 0.000581s : 0.05% type_inference : 1.140078s : 89.41% event_method : 0.000809s : 0.06% auto_monad : 0.000209s : 0.02% graph_reusing : 0.000013s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000090s : 0.01% rewriter_before_opt_a : 0.000212s : 0.02% expand_dump_flag : 0.000006s : 0.00% jit_opt_a.switch_simplify : 0.000405s : 0.03% jit_opt_a.loop_unroll : 0.000096s : 0.01% jit_opt_a.a_1 : 0.001715s : 0.13% jit_opt_a.with_stream_mark : 0.000055s : 0.00% jit_opt_a.recompute_prepare : 0.000033s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000006s : 0.00% jit_opt_a.specialize_transform : 0.000024s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000021s : 0.00% jit_opt_a.accelerated_algorithm : 0.000023s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000014s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000022s : 0.00% jit_opt_a.merge_forward : 0.000013s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000055s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000038s : 0.00% jit_opt_a.meta_fg_expand : 0.003001s : 0.24% jit_opt_a.replace_old_param : 0.000097s : 0.01% jit_opt_a.inline_without_move : 0.000080s : 0.01% jit_opt_a.renormalize : 0.124467s : 9.76% 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 : 0.000027s : 0.00% jit_opt_a.cse : 0.000050s : 0.00% jit_opt_a.replace_applicator : 0.000031s : 0.00% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000469s : 0.04% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000005s : 0.00% mutable_eliminate : 0.000832s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000017s : 0.00% jit_opt_b.inline_after_opt_a : 0.000017s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000510s : 0.04% jit_opt_after_cconv.c_1 : 0.000018s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000035s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000022s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000005s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000005s : 0.00% remove_dup_value : 0.000017s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000007s : 0.00% add_recomputation : 0.000048s : 0.00% cse_after_recomputation.cse : 0.000011s : 0.00% auto_monad_reorder : 0.000015s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000511s : 0.04% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000008s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000015s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000006s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000009s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000041s : 0.00% Time group info: ------[substitution.] 0.000589 69 0.39% : 0.000002s : 1: substitution.elim_not_effective 0.32% : 0.000002s : 1: substitution.fold_const_symbol 0.93% : 0.000005s : 1: substitution.graph_param_transform 74.41% : 0.000438s : 14: substitution.inline 4.81% : 0.000028s : 2: substitution.inline_without_move 1.45% : 0.000009s : 9: substitution.j_node_and_user_rematch 0.87% : 0.000005s : 2: substitution.minmaximum_grad 1.48% : 0.000009s : 9: substitution.partial_eliminate 1.63% : 0.000010s : 9: substitution.remove_not_recompute_node 0.47% : 0.000003s : 1: substitution.replace_applicator 1.37% : 0.000008s : 7: substitution.replace_old_param 2.14% : 0.000013s : 2: substitution.reshape_eliminate 0.70% : 0.000004s : 1: substitution.set_cell_output_no_recompute 3.68% : 0.000022s : 3: substitution.switch_simplify 1.51% : 0.000009s : 2: substitution.tuple_list_convert_item_index_to_positive 1.09% : 0.000006s : 2: substitution.tuple_list_get_item_depend_reorder 2.74% : 0.000016s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.139884 2 99.52% : 1.134445s : 1: type_inference.infer 0.48% : 0.005439s : 1: type_inference.specialize ------[replace.] 0.000287 18 45.88% : 0.000132s : 14: replace.inline 49.85% : 0.000143s : 3: replace.switch_simplify 4.27% : 0.000012s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000453 18 94.96% : 0.000430s : 14: match.inline 4.27% : 0.000019s : 3: match.switch_simplify 0.76% : 0.000003s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000315 1710 1.32% : 0.000004s : 29: predicate.accumulaten_eliminater 0.54% : 0.000002s : 1: predicate.ad_related_special_op_eliminate 1.19% : 0.000004s : 29: predicate.addn_check_dump 1.27% : 0.000004s : 29: predicate.addn_zero_filter 1.89% : 0.000006s : 29: predicate.arithmetic_simplify 1.47% : 0.000005s : 29: predicate.cast_eliminate 0.33% : 0.000001s : 1: predicate.check_bprop_eliminate 1.17% : 0.000004s : 29: predicate.compare_switch_simplify 1.33% : 0.000004s : 29: predicate.depend_value_elim 1.45% : 0.000005s : 29: predicate.dict_get_item_const_eliminator 1.27% : 0.000004s : 29: predicate.dict_get_item_eliminator 1.25% : 0.000004s : 29: predicate.dict_set_item_eliminator 0.31% : 0.000001s : 1: predicate.dumpgradient_eliminate 0.30% : 0.000001s : 1: predicate.elim_not_effective 0.21% : 0.000001s : 1: predicate.elim_shapecalc_of_broadcastargs 1.44% : 0.000005s : 29: predicate.environ_add_const_eliminate 1.19% : 0.000004s : 29: predicate.environ_get_add_eliminate 1.19% : 0.000004s : 29: predicate.environ_get_depend_swap 1.25% : 0.000004s : 29: predicate.environ_get_eliminate 1.17% : 0.000004s : 29: predicate.environ_get_set_eliminate 0.04% : 0.000000s : 1: predicate.fold_const_symbol 0.89% : 0.000003s : 14: predicate.get_grad_eliminate 0.04% : 0.000000s : 1: predicate.graph_param_transform 4.04% : 0.000013s : 46: predicate.inline 2.48% : 0.000008s : 38: predicate.inline_without_move 0.35% : 0.000001s : 14: predicate.j_node_and_user_rematch 0.94% : 0.000003s : 14: predicate.less_batch_normalization 1.43% : 0.000004s : 30: predicate.list_to_tuple_eliminator_ 1.35% : 0.000004s : 31: predicate.load_eliminater 0.44% : 0.000001s : 1: predicate.loop_unroll_after_grad 3.69% : 0.000012s : 78: predicate.loop_unroll_before_grad 1.54% : 0.000005s : 30: predicate.make_slice_get_slice_eliminator 1.19% : 0.000004s : 29: predicate.merge_addn 1.28% : 0.000004s : 29: predicate.minmaximum_grad 0.80% : 0.000003s : 1: predicate.mutable_eliminate 0.15% : 0.000000s : 1: predicate.opt_reshape 1.84% : 0.000006s : 31: predicate.partial_eliminate 1.20% : 0.000004s : 29: predicate.print_const_string_wrapper 1.53% : 0.000005s : 29: predicate.reduce_eliminate 1.37% : 0.000004s : 30: predicate.redundant_stop_gradient_eliminater 0.45% : 0.000001s : 14: predicate.remove_not_recompute_node 1.30% : 0.000004s : 32: predicate.replace_applicator 1.27% : 0.000004s : 38: predicate.replace_old_param 0.21% : 0.000001s : 1: predicate.reset_defer_inline 1.74% : 0.000005s : 29: predicate.reshape_eliminate 1.31% : 0.000004s : 29: predicate.row_tensor_add_zeros_like 0.29% : 0.000001s : 1: predicate.row_tensor_eliminate 1.33% : 0.000004s : 29: predicate.same_eliminate 0.51% : 0.000002s : 14: predicate.set_cell_output_no_recompute 0.33% : 0.000001s : 2: predicate.special_op_eliminate 0.86% : 0.000003s : 14: predicate.specialize_transform 1.53% : 0.000005s : 29: predicate.split_environ_get_set_with_tuple_value 1.24% : 0.000004s : 29: predicate.stack_unstack_eliminate 0.13% : 0.000000s : 1: predicate.switch_call_monad_eliminater 2.54% : 0.000008s : 44: predicate.switch_defer_inline 2.20% : 0.000007s : 44: predicate.switch_layer_defer_inline 17.40% : 0.000055s : 129: predicate.switch_simplify 1.25% : 0.000004s : 29: predicate.tile_eliminate 1.22% : 0.000004s : 29: predicate.transpose_eliminate 1.60% : 0.000005s : 29: predicate.tuple_list_convert_item_index_to_positive 1.35% : 0.000004s : 29: predicate.tuple_list_get_item_depend_reorder 2.96% : 0.000009s : 32: predicate.tuple_list_get_item_eliminator 1.57% : 0.000005s : 29: predicate.tuple_list_set_item_eliminator 1.38% : 0.000004s : 30: predicate.tuple_to_list_eliminator_ 1.34% : 0.000004s : 31: predicate.updatestate_pure_node_eliminater 2.63% : 0.000008s : 45: predicate.updatestate_useless_node_eliminater 1.60% : 0.000005s : 29: predicate.value_based_eliminate 0.06% : 0.000000s : 1: predicate.virtual_view_grad_eliminate 0.29% : 0.000001s : 1: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.111772 47 99.25% : 0.110928s : 30: func_graph_cloner_run.FuncGraphClonerGraph 0.75% : 0.000844s : 17: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.596754 72 0.00% : 0.000052s : 1: add_recomputation 0.01% : 0.000220s : 1: auto_monad 0.00% : 0.000018s : 1: auto_monad_reorder 0.04% : 0.000607s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000029s : 1: cse_after_recomputation 0.00% : 0.000009s : 1: environ_conv 0.05% : 0.000825s : 1: event_method 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000016s : 1: graph_reusing 20.32% : 0.324521s : 1: jit_opt_a 0.01% : 0.000178s : 1: jit_opt_after_cconv 0.00% : 0.000063s : 1: jit_opt_b 0.03% : 0.000520s : 1: loop_unroll 0.05% : 0.000844s : 1: mutable_eliminate 0.16% : 0.002587s : 26: opt.transform.jit_opt_a 0.00% : 0.000046s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000025s : 4: opt.transform.jit_opt_b 0.00% : 0.000012s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000020s : 1: opt.transform.mutable_eliminate 0.00% : 0.000019s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000033s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000522s : 1: opt_after_jit_grad 0.00% : 0.000007s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.01% : 0.000095s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000020s : 1: remove_dup_value 7.72% : 0.123253s : 1: renormalize.infer 0.07% : 0.001196s : 1: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.03% : 0.000478s : 1: rewriter_after_opt_a 0.01% : 0.000217s : 1: rewriter_before_opt_a 0.01% : 0.000088s : 1: symbol_engine_optimizer 71.40% : 1.140115s : 1: type_inference . [hook] pytest_runtest_teardown:test_reshape_zero_bias[KBK] tests/st/mint/test_reshape.py::test_reshape_zero_bias[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 149.92s (0:02:29) ==================