==================================================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_006/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_unsqueeze.py . [hook] pytest_runtest_teardown:test_unsqueeze_std[pynative] tests/st/mint/test_unsqueeze.py::test_unsqueeze_std[pynative],max_mem:2.0M TotalTime = 0.389874, [30] [bootstrap]: 0.00070143 [type_inference]: 0.374111 [event_method]: 2.017e-05 [auto_monad]: 0.00019884 [graph_reusing]: 7.33e-06 [pre_auto_parallel]: 1.293e-05 [py_interpret_to_execute]: 3.618e-05 [rewriter_before_opt_a]: 7.335e-05 [expand_dump_flag]: 3.56001e-06 [jit_opt_a]: 0.0110352, [2] [Cycle 1]: 0.00197135, [27] [switch_simplify]: 5.994e-05 [loop_unroll]: 2.651e-05 [a_1]: 0.00049263 [with_stream_mark]: 3.104e-05 [recompute_prepare]: 8.87999e-06 [updatestate_depend_eliminate]: 6.68e-06 [updatestate_assign_eliminate]: 7.62002e-06 [updatestate_loads_eliminate]: 5.06002e-06 [parameter_eliminate]: 2.71999e-06 [specialize_transform]: 8.43999e-06 [updatestate_useless_node_eliminater]: 1.043e-05 [accelerated_algorithm]: 8.05e-06 [meta_shard_fg_expand]: 2.96001e-06 [get_grad_eliminate_]: 7.56999e-06 [merge_forward]: 5.37001e-06 [cell_reuse_recompute_pass]: 1.22e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.489e-05 [j_node_and_user_rematch]: 1.327e-05 [meta_fg_expand]: 3.55998e-06 [replace_old_param]: 1.471e-05 [inline_without_move]: 7.15e-06 [renormalize]: 0.00087712 [add_forward_monad_depend]: 9.34998e-06 [auto_monad_grad]: 2.56e-06 [auto_monad_eliminator]: 2.117e-05 [cse]: 4.222e-05 [replace_applicator]: 1.581e-05 [Cycle 2]: 0.0005042, [27] [switch_simplify]: 8.80999e-06 [loop_unroll]: 7.83999e-06 [a_1]: 0.00015797 [with_stream_mark]: 1.241e-05 [recompute_prepare]: 7.93999e-06 [updatestate_depend_eliminate]: 4.97999e-06 [updatestate_assign_eliminate]: 4.31002e-06 [updatestate_loads_eliminate]: 3.81999e-06 [parameter_eliminate]: 1.14e-06 [specialize_transform]: 1.113e-05 [updatestate_useless_node_eliminater]: 1.209e-05 [accelerated_algorithm]: 8.16002e-06 [meta_shard_fg_expand]: 1.94e-06 [get_grad_eliminate_]: 7.39002e-06 [merge_forward]: 5.17999e-06 [cell_reuse_recompute_pass]: 1.76e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.633e-05 [j_node_and_user_rematch]: 1.237e-05 [meta_fg_expand]: 2.72001e-06 [replace_old_param]: 1.017e-05 [inline_without_move]: 7.01001e-06 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 1.62999e-06 [auto_monad_grad]: 1.02e-06 [auto_monad_eliminator]: 1.331e-05 [cse]: 2.014e-05 [replace_applicator]: 7.5e-06 [py_interpret_to_execute_after_opt_a]: 1.56e-05 [rewriter_after_opt_a]: 0.00057442 [convert_after_rewriter]: 1.316e-05 [order_py_execute_after_rewriter]: 7.29001e-06 [mutable_eliminate]: 0.00077628 [jit_opt_b]: 6.844e-05, [1] [Cycle 1]: 6.008e-05, [2] [frontend_op_eliminate]: 2.386e-05 [inline_after_opt_a]: 2.351e-05 [cconv]: 3.597e-05 [loop_unroll]: 0.00051268 [jit_opt_after_cconv]: 0.00021651, [1] [Cycle 1]: 0.00020833, [11] [c_1]: 4.955e-05 [parameter_eliminate]: 4.55001e-06 [updatestate_depend_eliminate]: 1.162e-05 [updatestate_assign_eliminate]: 4.90999e-06 [updatestate_loads_eliminate]: 4.32e-06 [cse]: 3.796e-05 [call_graph_tuple_transform]: 2.273e-05 [tuple_list_get_item_eliminator]: 8.37e-06 [none_parameter_eliminate]: 1.72001e-06 [renormalize]: 2.59985e-07 [switch_simplify]: 8.13999e-06 [remove_dup_value]: 2.062e-05 [partial_unused_args_eliminate]: 2.36e-06 [environ_conv]: 2.134e-05 [add_recomputation]: 8.457e-05 [cse_after_recomputation]: 3.217e-05, [1] [Cycle 1]: 2.494e-05, [1] [cse]: 1.809e-05 [auto_monad_reorder]: 3.916e-05 [get_jit_bprop_graph]: 2.32999e-06 [rewriter_after_jit_bprop_graph]: 0.00013802 [opt_after_jit_grad]: 0.00059135 [symbol_engine_optimizer]: 9.878e-05, [1] [Cycle 1]: 9.135e-05, [6] [build]: 6.38e-06 [elim_shapecalc]: 1.292e-05 [elim_not_effective]: 1.984e-05 [opt_reshape]: 9.14998e-06 [fold_const_symbol]: 1.325e-05 [renormalize]: 6.69999e-07 [validate]: 7.226e-05 Sums bootstrap : 0.000701s : 0.18% type_inference : 0.374111s : 98.34% event_method : 0.000020s : 0.01% auto_monad : 0.000199s : 0.05% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000036s : 0.01% rewriter_before_opt_a : 0.000073s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000069s : 0.02% jit_opt_a.loop_unroll : 0.000034s : 0.01% jit_opt_a.a_1 : 0.000651s : 0.17% jit_opt_a.with_stream_mark : 0.000043s : 0.01% jit_opt_a.recompute_prepare : 0.000017s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000023s : 0.01% jit_opt_a.accelerated_algorithm : 0.000016s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000015s : 0.00% jit_opt_a.merge_forward : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000051s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000026s : 0.01% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000025s : 0.01% jit_opt_a.inline_without_move : 0.000014s : 0.00% jit_opt_a.renormalize : 0.000877s : 0.23% jit_opt_a.add_forward_monad_depend : 0.000011s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000034s : 0.01% jit_opt_a.cse : 0.000062s : 0.02% jit_opt_a.replace_applicator : 0.000023s : 0.01% py_interpret_to_execute_after_opt_a : 0.000016s : 0.00% rewriter_after_opt_a : 0.000574s : 0.15% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000776s : 0.20% jit_opt_b.frontend_op_eliminate : 0.000024s : 0.01% jit_opt_b.inline_after_opt_a : 0.000024s : 0.01% cconv : 0.000036s : 0.01% loop_unroll : 0.000513s : 0.13% jit_opt_after_cconv.c_1 : 0.000050s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000038s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000023s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 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 : 0.000008s : 0.00% remove_dup_value : 0.000021s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000021s : 0.01% add_recomputation : 0.000085s : 0.02% cse_after_recomputation.cse : 0.000018s : 0.00% auto_monad_reorder : 0.000039s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000138s : 0.04% opt_after_jit_grad : 0.000591s : 0.16% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000020s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000013s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000072s : 0.02% Time group info: ------[substitution.] 0.000252 44 3.69% : 0.000009s : 2: substitution.depend_value_elim 1.11% : 0.000003s : 4: substitution.elim_not_effective 0.78% : 0.000002s : 4: substitution.fold_const_symbol 3.15% : 0.000008s : 5: substitution.graph_param_transform 70.82% : 0.000179s : 3: substitution.inline 2.00% : 0.000005s : 8: substitution.j_node_and_user_rematch 7.37% : 0.000019s : 8: substitution.remove_not_recompute_node 3.28% : 0.000008s : 2: substitution.replace_old_param 4.37% : 0.000011s : 3: substitution.updatestate_pure_node_eliminater 3.43% : 0.000009s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.374021 2 99.77% : 0.373165s : 1: type_inference.infer 0.23% : 0.000857s : 1: type_inference.specialize ------[replace.] 0.000036 3 100.00% : 0.000036s : 3: replace.inline ------[match.] 0.000177 3 100.00% : 0.000177s : 3: match.inline ------[predicate.] 0.000148 825 1.08% : 0.000002s : 12: predicate.accumulaten_eliminater 1.44% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.16% : 0.000002s : 12: predicate.addn_check_dump 1.15% : 0.000002s : 12: predicate.addn_zero_filter 1.99% : 0.000003s : 12: predicate.arithmetic_simplify 1.18% : 0.000002s : 12: predicate.cast_eliminate 0.55% : 0.000001s : 5: predicate.check_bprop_eliminate 1.01% : 0.000001s : 12: predicate.compare_switch_simplify 1.47% : 0.000002s : 12: predicate.depend_value_elim 1.12% : 0.000002s : 12: predicate.dict_get_item_const_eliminator 1.14% : 0.000002s : 12: predicate.dict_get_item_eliminator 1.07% : 0.000002s : 12: predicate.dict_set_item_eliminator 1.30% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.40% : 0.000001s : 5: predicate.elim_not_effective 0.82% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.21% : 0.000002s : 12: predicate.environ_add_const_eliminate 1.01% : 0.000001s : 12: predicate.environ_get_add_eliminate 1.09% : 0.000002s : 12: predicate.environ_get_depend_swap 1.20% : 0.000002s : 12: predicate.environ_get_eliminate 1.10% : 0.000002s : 12: predicate.environ_get_set_eliminate 0.30% : 0.000000s : 5: predicate.fold_const_symbol 1.32% : 0.000002s : 10: predicate.get_grad_eliminate 0.32% : 0.000000s : 5: predicate.graph_param_transform 5.12% : 0.000008s : 25: predicate.inline 1.11% : 0.000002s : 10: predicate.inline_without_move 0.51% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.41% : 0.000002s : 10: predicate.less_batch_normalization 1.39% : 0.000002s : 12: predicate.list_to_tuple_eliminator_ 1.95% : 0.000003s : 17: predicate.load_eliminater 1.72% : 0.000003s : 5: predicate.loop_unroll_after_grad 3.26% : 0.000005s : 25: predicate.loop_unroll_before_grad 1.99% : 0.000003s : 17: predicate.make_slice_get_slice_eliminator 1.10% : 0.000002s : 12: predicate.merge_addn 1.05% : 0.000002s : 12: predicate.minmaximum_grad 2.76% : 0.000004s : 5: predicate.mutable_eliminate 0.66% : 0.000001s : 5: predicate.opt_reshape 2.11% : 0.000003s : 17: predicate.partial_eliminate 1.29% : 0.000002s : 12: predicate.print_const_string_wrapper 1.74% : 0.000003s : 12: predicate.reduce_eliminate 1.30% : 0.000002s : 12: predicate.redundant_stop_gradient_eliminater 0.92% : 0.000001s : 10: predicate.remove_not_recompute_node 1.51% : 0.000002s : 22: predicate.replace_applicator 0.80% : 0.000001s : 10: predicate.replace_old_param 0.45% : 0.000001s : 5: predicate.reset_defer_inline 1.36% : 0.000002s : 12: predicate.reshape_eliminate 1.46% : 0.000002s : 12: predicate.row_tensor_add_zeros_like 1.10% : 0.000002s : 5: predicate.row_tensor_eliminate 1.22% : 0.000002s : 12: predicate.same_eliminate 0.63% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.28% : 0.000002s : 10: predicate.special_op_eliminate 1.50% : 0.000002s : 10: predicate.specialize_transform 1.55% : 0.000002s : 12: predicate.split_environ_get_set_with_tuple_value 1.20% : 0.000002s : 12: predicate.stack_unstack_eliminate 0.92% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.03% : 0.000003s : 15: predicate.switch_defer_inline 1.71% : 0.000003s : 15: predicate.switch_layer_defer_inline 5.73% : 0.000008s : 45: predicate.switch_simplify 1.09% : 0.000002s : 12: predicate.tile_eliminate 1.34% : 0.000002s : 12: predicate.transpose_eliminate 1.32% : 0.000002s : 12: predicate.tuple_list_convert_item_index_to_positive 1.18% : 0.000002s : 12: predicate.tuple_list_get_item_depend_reorder 3.76% : 0.000006s : 22: predicate.tuple_list_get_item_eliminator 1.45% : 0.000002s : 12: predicate.tuple_list_set_item_eliminator 1.18% : 0.000002s : 12: predicate.tuple_to_list_eliminator_ 1.86% : 0.000003s : 17: predicate.updatestate_pure_node_eliminater 3.76% : 0.000006s : 27: predicate.updatestate_useless_node_eliminater 1.45% : 0.000002s : 12: predicate.value_based_eliminate 0.52% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.82% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000395 6 6.05% : 0.000024s : 1: func_graph_cloner_run.FuncGraphClonerGraph 93.95% : 0.000371s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.391688 72 0.02% : 0.000088s : 1: add_recomputation 0.05% : 0.000205s : 1: auto_monad 0.01% : 0.000042s : 1: auto_monad_reorder 0.19% : 0.000735s : 1: bootstrap 0.01% : 0.000039s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.01% : 0.000035s : 1: cse_after_recomputation 0.01% : 0.000024s : 1: environ_conv 0.01% : 0.000026s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000010s : 1: graph_reusing 2.82% : 0.011039s : 1: jit_opt_a 0.06% : 0.000219s : 1: jit_opt_after_cconv 0.02% : 0.000072s : 1: jit_opt_b 0.13% : 0.000523s : 1: loop_unroll 0.20% : 0.000790s : 1: mutable_eliminate 0.24% : 0.000940s : 26: opt.transform.jit_opt_a 0.02% : 0.000085s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000041s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000023s : 1: opt.transform.mutable_eliminate 0.01% : 0.000034s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.15% : 0.000603s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000040s : 1: py_interpret_to_execute 0.00% : 0.000018s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000023s : 1: remove_dup_value 0.13% : 0.000510s : 1: renormalize.infer 0.09% : 0.000357s : 1: renormalize.specialize 0.04% : 0.000142s : 1: rewriter_after_jit_bprop_graph 0.15% : 0.000578s : 1: rewriter_after_opt_a 0.02% : 0.000078s : 1: rewriter_before_opt_a 0.03% : 0.000101s : 1: symbol_engine_optimizer 95.52% : 0.374143s : 1: type_inference TotalTime = 1.0819, [30] [bootstrap]: 0.00046139 [type_inference]: 0.410191 [event_method]: 0.00017852 [auto_monad]: 0.00035751 [graph_reusing]: 1.339e-05 [pre_auto_parallel]: 4.01001e-06 [py_interpret_to_execute]: 6.91e-05 [rewriter_before_opt_a]: 0.00017152 [expand_dump_flag]: 5.72999e-06 [jit_opt_a]: 0.667285, [3] [Cycle 1]: 0.435357, [27] [switch_simplify]: 0.00029099 [loop_unroll]: 6.177e-05 [a_1]: 0.00146537 [with_stream_mark]: 4.705e-05 [recompute_prepare]: 2.96e-05 [updatestate_depend_eliminate]: 1.52e-05 [updatestate_assign_eliminate]: 1.038e-05 [updatestate_loads_eliminate]: 9.83998e-06 [parameter_eliminate]: 3.35e-06 [specialize_transform]: 1.971e-05 [updatestate_useless_node_eliminater]: 2.603e-05 [accelerated_algorithm]: 2.018e-05 [meta_shard_fg_expand]: 6.72002e-06 [get_grad_eliminate_]: 1.755e-05 [merge_forward]: 1.263e-05 [cell_reuse_recompute_pass]: 1.30999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.982e-05 [j_node_and_user_rematch]: 3.351e-05 [meta_fg_expand]: 0.200231 [replace_old_param]: 0.00015495 [inline_without_move]: 0.00013597 [renormalize]: 0.231689 [add_forward_monad_depend]: 2.852e-05 [auto_monad_grad]: 1.416e-05 [auto_monad_eliminator]: 9.152e-05 [cse]: 0.00034418 [replace_applicator]: 0.00021507 [Cycle 2]: 0.00377476, [27] [switch_simplify]: 6.321e-05 [loop_unroll]: 5.649e-05 [a_1]: 0.00114659 [with_stream_mark]: 2.813e-05 [recompute_prepare]: 1.431e-05 [updatestate_depend_eliminate]: 2.803e-05 [updatestate_assign_eliminate]: 5.87001e-06 [updatestate_loads_eliminate]: 4.76002e-06 [parameter_eliminate]: 2.49999e-06 [specialize_transform]: 9.92999e-06 [updatestate_useless_node_eliminater]: 1.268e-05 [accelerated_algorithm]: 9.17999e-06 [meta_shard_fg_expand]: 2.96001e-06 [get_grad_eliminate_]: 8.38999e-06 [merge_forward]: 5.79e-06 [cell_reuse_recompute_pass]: 1.50001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.151e-05 [j_node_and_user_rematch]: 1.411e-05 [meta_fg_expand]: 0.0001845 [replace_old_param]: 1.734e-05 [inline_without_move]: 8.59e-06 [renormalize]: 0.00182592 [add_forward_monad_depend]: 8.55001e-06 [auto_monad_grad]: 2.51e-06 [auto_monad_eliminator]: 2.458e-05 [cse]: 4.767e-05 [replace_applicator]: 2.264e-05 [Cycle 3]: 0.00051344, [27] [switch_simplify]: 1.023e-05 [loop_unroll]: 9.31e-06 [a_1]: 0.000188 [with_stream_mark]: 1.623e-05 [recompute_prepare]: 7.82e-06 [updatestate_depend_eliminate]: 6.21e-06 [updatestate_assign_eliminate]: 5.15999e-06 [updatestate_loads_eliminate]: 4.82998e-06 [parameter_eliminate]: 1.96e-06 [specialize_transform]: 8.92e-06 [updatestate_useless_node_eliminater]: 1.076e-05 [accelerated_algorithm]: 8.37e-06 [meta_shard_fg_expand]: 2.07001e-06 [get_grad_eliminate_]: 7.71001e-06 [merge_forward]: 5.39e-06 [cell_reuse_recompute_pass]: 2.65002e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.899e-05 [j_node_and_user_rematch]: 1.299e-05 [meta_fg_expand]: 2.91e-06 [replace_old_param]: 1.066e-05 [inline_without_move]: 8.3e-06 [renormalize]: 8.9989e-08 [add_forward_monad_depend]: 1.87001e-06 [auto_monad_grad]: 1.31998e-06 [auto_monad_eliminator]: 9.76998e-06 [cse]: 1.939e-05 [replace_applicator]: 8.99998e-06 [py_interpret_to_execute_after_opt_a]: 1.759e-05 [rewriter_after_opt_a]: 0.0002888 [convert_after_rewriter]: 1.266e-05 [order_py_execute_after_rewriter]: 6.96001e-06 [mutable_eliminate]: 0.0008495 [jit_opt_b]: 7.362e-05, [1] [Cycle 1]: 6.427e-05, [2] [frontend_op_eliminate]: 2.572e-05 [inline_after_opt_a]: 2.516e-05 [cconv]: 3.432e-05 [loop_unroll]: 0.00049824 [jit_opt_after_cconv]: 0.0002272, [1] [Cycle 1]: 0.00021972, [11] [c_1]: 5.256e-05 [parameter_eliminate]: 4.94e-06 [updatestate_depend_eliminate]: 1.022e-05 [updatestate_assign_eliminate]: 6.19999e-06 [updatestate_loads_eliminate]: 4.48001e-06 [cse]: 4.111e-05 [call_graph_tuple_transform]: 2.357e-05 [tuple_list_get_item_eliminator]: 9.96998e-06 [none_parameter_eliminate]: 1.55001e-06 [renormalize]: 3.10014e-07 [switch_simplify]: 8.52e-06 [remove_dup_value]: 2.263e-05 [partial_unused_args_eliminate]: 2.78e-06 [environ_conv]: 9.15001e-06 [add_recomputation]: 8.37e-05 [cse_after_recomputation]: 3.822e-05, [1] [Cycle 1]: 3.141e-05, [1] [cse]: 2.401e-05 [auto_monad_reorder]: 2.969e-05 [get_jit_bprop_graph]: 2.83998e-06 [rewriter_after_jit_bprop_graph]: 7e-06 [opt_after_jit_grad]: 0.00053977 [symbol_engine_optimizer]: 0.00010518, [1] [Cycle 1]: 9.743e-05, [6] [build]: 6.59999e-06 [elim_shapecalc]: 1.224e-05 [elim_not_effective]: 1.915e-05 [opt_reshape]: 9.99001e-06 [fold_const_symbol]: 1.65e-05 [renormalize]: 6.59988e-07 [validate]: 5.814e-05 Sums bootstrap : 0.000461s : 0.05% type_inference : 0.410191s : 48.08% event_method : 0.000179s : 0.02% auto_monad : 0.000358s : 0.04% graph_reusing : 0.000013s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000069s : 0.01% rewriter_before_opt_a : 0.000172s : 0.02% expand_dump_flag : 0.000006s : 0.00% jit_opt_a.switch_simplify : 0.000364s : 0.04% jit_opt_a.loop_unroll : 0.000128s : 0.01% jit_opt_a.a_1 : 0.002800s : 0.33% jit_opt_a.with_stream_mark : 0.000091s : 0.01% jit_opt_a.recompute_prepare : 0.000052s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000049s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000021s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000019s : 0.00% jit_opt_a.parameter_eliminate : 0.000008s : 0.00% jit_opt_a.specialize_transform : 0.000039s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000049s : 0.01% jit_opt_a.accelerated_algorithm : 0.000038s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000012s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000034s : 0.00% jit_opt_a.merge_forward : 0.000024s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000080s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000061s : 0.01% jit_opt_a.meta_fg_expand : 0.200419s : 23.49% jit_opt_a.replace_old_param : 0.000183s : 0.02% jit_opt_a.inline_without_move : 0.000153s : 0.02% jit_opt_a.renormalize : 0.233515s : 27.37% jit_opt_a.add_forward_monad_depend : 0.000039s : 0.00% jit_opt_a.auto_monad_grad : 0.000018s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000126s : 0.01% jit_opt_a.cse : 0.000411s : 0.05% jit_opt_a.replace_applicator : 0.000247s : 0.03% py_interpret_to_execute_after_opt_a : 0.000018s : 0.00% rewriter_after_opt_a : 0.000289s : 0.03% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000850s : 0.10% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.00% jit_opt_b.inline_after_opt_a : 0.000025s : 0.00% cconv : 0.000034s : 0.00% loop_unroll : 0.000498s : 0.06% jit_opt_after_cconv.c_1 : 0.000053s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000010s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000041s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000024s : 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 : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000023s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000009s : 0.00% add_recomputation : 0.000084s : 0.01% cse_after_recomputation.cse : 0.000024s : 0.00% auto_monad_reorder : 0.000030s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000540s : 0.06% symbol_engine_optimizer.build : 0.000007s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000012s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000017s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000058s : 0.01% Time group info: ------[substitution.] 0.002153 170 1.15% : 0.000025s : 8: substitution.depend_value_elim 0.15% : 0.000003s : 4: substitution.elim_not_effective 0.12% : 0.000003s : 4: substitution.fold_const_symbol 53.17% : 0.001145s : 4: substitution.getattr_setattr_resolve 0.31% : 0.000007s : 5: substitution.graph_param_transform 27.17% : 0.000585s : 16: substitution.inline 2.21% : 0.000048s : 4: substitution.inline_without_move 0.60% : 0.000013s : 20: substitution.j_node_and_user_rematch 0.45% : 0.000010s : 5: substitution.minmaximum_grad 0.39% : 0.000008s : 9: substitution.partial_eliminate 0.73% : 0.000016s : 20: substitution.remove_not_recompute_node 2.48% : 0.000053s : 12: substitution.replace_applicator 0.84% : 0.000018s : 16: substitution.replace_old_param 0.15% : 0.000003s : 1: substitution.set_cell_output_no_recompute 0.79% : 0.000017s : 3: substitution.switch_simplify 1.02% : 0.000022s : 5: substitution.tuple_list_convert_item_index_to_positive 4.01% : 0.000086s : 5: substitution.tuple_list_get_item_depend_reorder 1.62% : 0.000035s : 8: substitution.tuple_list_get_item_eliminator 0.97% : 0.000021s : 8: substitution.updatestate_pure_node_eliminater 1.66% : 0.000036s : 13: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.410056 2 99.18% : 0.406699s : 1: type_inference.infer 0.82% : 0.003357s : 1: type_inference.specialize ------[replace.] 0.000514 27 16.21% : 0.000083s : 3: replace.getattr_setattr_resolve 26.83% : 0.000138s : 16: replace.inline 11.06% : 0.000057s : 1: replace.replace_applicator 23.90% : 0.000123s : 3: replace.switch_simplify 17.05% : 0.000088s : 3: replace.tuple_list_get_item_eliminator 4.96% : 0.000025s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.001700 27 63.05% : 0.001072s : 3: match.getattr_setattr_resolve 33.92% : 0.000577s : 16: match.inline 0.84% : 0.000014s : 1: match.replace_applicator 0.88% : 0.000015s : 3: match.switch_simplify 0.44% : 0.000007s : 3: match.tuple_list_get_item_eliminator 0.86% : 0.000015s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000505 3164 1.42% : 0.000007s : 50: predicate.accumulaten_eliminater 0.43% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.38% : 0.000007s : 50: predicate.addn_check_dump 1.38% : 0.000007s : 50: predicate.addn_zero_filter 2.02% : 0.000010s : 50: predicate.arithmetic_simplify 1.55% : 0.000008s : 50: predicate.cast_eliminate 0.17% : 0.000001s : 5: predicate.check_bprop_eliminate 1.24% : 0.000006s : 50: predicate.compare_switch_simplify 1.61% : 0.000008s : 50: predicate.depend_value_elim 1.31% : 0.000007s : 50: predicate.dict_get_item_const_eliminator 1.49% : 0.000008s : 50: predicate.dict_get_item_eliminator 1.48% : 0.000007s : 50: predicate.dict_set_item_eliminator 0.31% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.11% : 0.000001s : 5: predicate.elim_not_effective 0.26% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.35% : 0.000007s : 50: predicate.environ_add_const_eliminate 1.33% : 0.000007s : 50: predicate.environ_get_add_eliminate 1.38% : 0.000007s : 50: predicate.environ_get_depend_swap 1.45% : 0.000007s : 50: predicate.environ_get_eliminate 1.32% : 0.000007s : 50: predicate.environ_get_set_eliminate 0.09% : 0.000000s : 5: predicate.fold_const_symbol 0.85% : 0.000004s : 26: predicate.get_grad_eliminate 1.53% : 0.000008s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000000s : 5: predicate.graph_param_transform 3.98% : 0.000020s : 80: predicate.inline 3.36% : 0.000017s : 87: predicate.inline_without_move 0.41% : 0.000002s : 26: predicate.j_node_and_user_rematch 1.29% : 0.000007s : 26: predicate.less_batch_normalization 1.53% : 0.000008s : 53: predicate.list_to_tuple_eliminator_ 1.65% : 0.000008s : 58: predicate.load_eliminater 0.53% : 0.000003s : 5: predicate.loop_unroll_after_grad 3.92% : 0.000020s : 132: predicate.loop_unroll_before_grad 1.66% : 0.000008s : 55: predicate.make_slice_get_slice_eliminator 1.32% : 0.000007s : 50: predicate.merge_addn 1.38% : 0.000007s : 50: predicate.minmaximum_grad 0.72% : 0.000004s : 5: predicate.mutable_eliminate 0.27% : 0.000001s : 5: predicate.opt_reshape 1.98% : 0.000010s : 58: predicate.partial_eliminate 1.38% : 0.000007s : 50: predicate.print_const_string_wrapper 1.81% : 0.000009s : 50: predicate.reduce_eliminate 1.53% : 0.000008s : 53: predicate.redundant_stop_gradient_eliminater 0.49% : 0.000002s : 26: predicate.remove_not_recompute_node 2.54% : 0.000013s : 126: predicate.replace_applicator 1.49% : 0.000008s : 87: predicate.replace_old_param 0.14% : 0.000001s : 5: predicate.reset_defer_inline 1.57% : 0.000008s : 50: predicate.reshape_eliminate 1.54% : 0.000008s : 50: predicate.row_tensor_add_zeros_like 0.26% : 0.000001s : 5: predicate.row_tensor_eliminate 1.50% : 0.000008s : 50: predicate.same_eliminate 0.52% : 0.000003s : 28: predicate.set_cell_output_no_recompute 0.38% : 0.000002s : 10: predicate.special_op_eliminate 0.92% : 0.000005s : 26: predicate.specialize_transform 1.68% : 0.000008s : 50: predicate.split_environ_get_set_with_tuple_value 1.40% : 0.000007s : 50: predicate.stack_unstack_eliminate 0.18% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.36% : 0.000012s : 70: predicate.switch_defer_inline 2.23% : 0.000011s : 70: predicate.switch_layer_defer_inline 7.61% : 0.000038s : 213: predicate.switch_simplify 1.45% : 0.000007s : 50: predicate.tile_eliminate 1.40% : 0.000007s : 50: predicate.transpose_eliminate 1.80% : 0.000009s : 50: predicate.tuple_list_convert_item_index_to_positive 1.51% : 0.000008s : 50: predicate.tuple_list_get_item_depend_reorder 2.78% : 0.000014s : 63: predicate.tuple_list_get_item_eliminator 1.68% : 0.000008s : 50: predicate.tuple_list_set_item_eliminator 1.54% : 0.000008s : 53: predicate.tuple_to_list_eliminator_ 1.71% : 0.000009s : 58: predicate.updatestate_pure_node_eliminater 2.80% : 0.000014s : 85: predicate.updatestate_useless_node_eliminater 1.83% : 0.000009s : 50: predicate.value_based_eliminate 0.15% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.25% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.004673 47 62.66% : 0.002928s : 20: func_graph_cloner_run.FuncGraphClonerGraph 37.34% : 0.001745s : 27: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.320978 89 0.01% : 0.000087s : 1: add_recomputation 0.03% : 0.000371s : 1: auto_monad 0.00% : 0.000032s : 1: auto_monad_reorder 0.04% : 0.000482s : 1: bootstrap 0.00% : 0.000037s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.00% : 0.000041s : 1: cse_after_recomputation 0.00% : 0.000012s : 1: environ_conv 0.01% : 0.000187s : 1: event_method 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000017s : 1: graph_reusing 50.51% : 0.667289s : 1: jit_opt_a 0.02% : 0.000231s : 1: jit_opt_after_cconv 0.01% : 0.000077s : 1: jit_opt_b 0.04% : 0.000508s : 1: loop_unroll 0.07% : 0.000862s : 1: mutable_eliminate 0.31% : 0.004161s : 39: opt.transform.jit_opt_a 0.01% : 0.000090s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000043s : 4: opt.transform.jit_opt_b 0.00% : 0.000019s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000023s : 1: opt.transform.mutable_eliminate 0.00% : 0.000032s : 1: opt.transform.opt_after_jit_grad 0.10% : 0.001306s : 2: opt.transform.opt_resolve 0.00% : 0.000054s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000549s : 1: opt_after_jit_grad 0.00% : 0.000009s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.01% : 0.000074s : 1: py_interpret_to_execute 0.00% : 0.000020s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000026s : 1: remove_dup_value 17.35% : 0.229191s : 2: renormalize.infer 0.33% : 0.004295s : 2: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000295s : 1: rewriter_after_opt_a 0.01% : 0.000176s : 1: rewriter_before_opt_a 0.01% : 0.000108s : 1: symbol_engine_optimizer 31.05% : 0.410223s : 1: type_inference . [hook] pytest_runtest_teardown:test_unsqueeze_std[KBK] tests/st/mint/test_unsqueeze.py::test_unsqueeze_std[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 275.56s (0:04:35) ==================