==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/mint, configfile: ../../../../../../sault/virtual_test/virtualenv_007/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_unsqueeze.py . [hook] pytest_runtest_teardown:test_unsqueeze_high_dimension[pynative] tests/st/mint/test_unsqueeze.py::test_unsqueeze_high_dimension[pynative],max_mem:2.0M TotalTime = 0.418318, [30] [bootstrap]: 0.00058825 [type_inference]: 0.217989 [event_method]: 1.622e-05 [auto_monad]: 0.00016281 [graph_reusing]: 8.47e-06 [pre_auto_parallel]: 1.224e-05 [py_interpret_to_execute]: 3.007e-05 [rewriter_before_opt_a]: 6.156e-05 [expand_dump_flag]: 3.09999e-06 [jit_opt_a]: 0.0112628, [2] [Cycle 1]: 0.00225648, [27] [switch_simplify]: 7.031e-05 [loop_unroll]: 2.317e-05 [a_1]: 0.00053091 [with_stream_mark]: 3.576e-05 [recompute_prepare]: 1.969e-05 [updatestate_depend_eliminate]: 7.82002e-06 [updatestate_assign_eliminate]: 6.41e-06 [updatestate_loads_eliminate]: 5.34e-06 [parameter_eliminate]: 2.20002e-06 [specialize_transform]: 1.048e-05 [updatestate_useless_node_eliminater]: 1.271e-05 [accelerated_algorithm]: 9.85002e-06 [meta_shard_fg_expand]: 3.91999e-06 [get_grad_eliminate_]: 8.22e-06 [merge_forward]: 6.00002e-06 [cell_reuse_recompute_pass]: 1.82001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.733e-05 [j_node_and_user_rematch]: 1.418e-05 [meta_fg_expand]: 3.85998e-06 [replace_old_param]: 1.391e-05 [inline_without_move]: 7.80998e-06 [renormalize]: 0.00101784 [add_forward_monad_depend]: 1.401e-05 [auto_monad_grad]: 3.3e-06 [auto_monad_eliminator]: 3.078e-05 [cse]: 7.117e-05 [replace_applicator]: 2.58e-05 [Cycle 2]: 0.00053616, [27] [switch_simplify]: 1.013e-05 [loop_unroll]: 8.37e-06 [a_1]: 0.00018378 [with_stream_mark]: 1.977e-05 [recompute_prepare]: 9.84001e-06 [updatestate_depend_eliminate]: 5.61e-06 [updatestate_assign_eliminate]: 5.04e-06 [updatestate_loads_eliminate]: 4.25e-06 [parameter_eliminate]: 2.02999e-06 [specialize_transform]: 9.12001e-06 [updatestate_useless_node_eliminater]: 1.274e-05 [accelerated_algorithm]: 8.95999e-06 [meta_shard_fg_expand]: 2.18998e-06 [get_grad_eliminate_]: 7.59002e-06 [merge_forward]: 5.77001e-06 [cell_reuse_recompute_pass]: 2.84001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.946e-05 [j_node_and_user_rematch]: 1.257e-05 [meta_fg_expand]: 2.78003e-06 [replace_old_param]: 1.246e-05 [inline_without_move]: 7.4e-06 [renormalize]: 6.00121e-08 [add_forward_monad_depend]: 2.22999e-06 [auto_monad_grad]: 1.63002e-06 [auto_monad_eliminator]: 1.59e-05 [cse]: 1.966e-05 [replace_applicator]: 8.23999e-06 [py_interpret_to_execute_after_opt_a]: 2.087e-05 [rewriter_after_opt_a]: 0.00068357 [convert_after_rewriter]: 2.573e-05 [order_py_execute_after_rewriter]: 7.22002e-06 [mutable_eliminate]: 0.00083727 [jit_opt_b]: 8.229e-05, [1] [Cycle 1]: 7.052e-05, [2] [frontend_op_eliminate]: 2.735e-05 [inline_after_opt_a]: 2.829e-05 [cconv]: 4.368e-05 [loop_unroll]: 0.00055588 [jit_opt_after_cconv]: 0.00025999, [1] [Cycle 1]: 0.00024989, [11] [c_1]: 6.182e-05 [parameter_eliminate]: 6.70998e-06 [updatestate_depend_eliminate]: 1.569e-05 [updatestate_assign_eliminate]: 5.59998e-06 [updatestate_loads_eliminate]: 4.47998e-06 [cse]: 5.109e-05 [call_graph_tuple_transform]: 2.483e-05 [tuple_list_get_item_eliminator]: 8.68001e-06 [none_parameter_eliminate]: 1.45999e-06 [renormalize]: 1.05001e-06 [switch_simplify]: 8.65999e-06 [remove_dup_value]: 2.142e-05 [partial_unused_args_eliminate]: 2.67001e-06 [environ_conv]: 2.63e-05 [add_recomputation]: 9.076e-05 [cse_after_recomputation]: 3.634e-05, [1] [Cycle 1]: 2.823e-05, [1] [cse]: 1.861e-05 [auto_monad_reorder]: 3.687e-05 [get_jit_bprop_graph]: 2.99001e-06 [rewriter_after_jit_bprop_graph]: 0.00016013 [opt_after_jit_grad]: 0.184728 [symbol_engine_optimizer]: 0.00012277, [1] [Cycle 1]: 0.00011207, [6] [build]: 1.103e-05 [elim_shapecalc]: 1.328e-05 [elim_not_effective]: 2.735e-05 [opt_reshape]: 9.94999e-06 [fold_const_symbol]: 1.535e-05 [renormalize]: 7.89994e-07 [validate]: 9.105e-05 Sums bootstrap : 0.000588s : 0.14% type_inference : 0.217989s : 53.31% event_method : 0.000016s : 0.00% auto_monad : 0.000163s : 0.04% graph_reusing : 0.000008s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000030s : 0.01% rewriter_before_opt_a : 0.000062s : 0.02% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000080s : 0.02% jit_opt_a.loop_unroll : 0.000032s : 0.01% jit_opt_a.a_1 : 0.000715s : 0.17% jit_opt_a.with_stream_mark : 0.000056s : 0.01% jit_opt_a.recompute_prepare : 0.000030s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.01% 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_ : 0.000016s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000047s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000027s : 0.01% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000026s : 0.01% jit_opt_a.inline_without_move : 0.000015s : 0.00% jit_opt_a.renormalize : 0.001018s : 0.25% jit_opt_a.add_forward_monad_depend : 0.000016s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000047s : 0.01% jit_opt_a.cse : 0.000091s : 0.02% jit_opt_a.replace_applicator : 0.000034s : 0.01% py_interpret_to_execute_after_opt_a : 0.000021s : 0.01% rewriter_after_opt_a : 0.000684s : 0.17% convert_after_rewriter : 0.000026s : 0.01% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000837s : 0.20% jit_opt_b.frontend_op_eliminate : 0.000027s : 0.01% jit_opt_b.inline_after_opt_a : 0.000028s : 0.01% cconv : 0.000044s : 0.01% loop_unroll : 0.000556s : 0.14% jit_opt_after_cconv.c_1 : 0.000062s : 0.02% jit_opt_after_cconv.parameter_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000016s : 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 : 0.000051s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000025s : 0.01% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000001s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000021s : 0.01% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000026s : 0.01% add_recomputation : 0.000091s : 0.02% cse_after_recomputation.cse : 0.000019s : 0.00% auto_monad_reorder : 0.000037s : 0.01% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000160s : 0.04% opt_after_jit_grad : 0.184728s : 45.17% symbol_engine_optimizer.build : 0.000011s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000013s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000027s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000010s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000091s : 0.02% Time group info: ------[substitution.] 0.000266 44 4.34% : 0.000012s : 2: substitution.depend_value_elim 1.39% : 0.000004s : 4: substitution.elim_not_effective 0.99% : 0.000003s : 4: substitution.fold_const_symbol 2.76% : 0.000007s : 5: substitution.graph_param_transform 71.80% : 0.000191s : 3: substitution.inline 2.05% : 0.000005s : 8: substitution.j_node_and_user_rematch 2.97% : 0.000008s : 8: substitution.remove_not_recompute_node 3.01% : 0.000008s : 2: substitution.replace_old_param 5.98% : 0.000016s : 3: substitution.updatestate_pure_node_eliminater 4.70% : 0.000013s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.217908 2 99.66% : 0.217162s : 1: type_inference.infer 0.34% : 0.000745s : 1: type_inference.specialize ------[replace.] 0.000039 3 100.00% : 0.000039s : 3: replace.inline ------[match.] 0.000189 3 100.00% : 0.000189s : 3: match.inline ------[predicate.] 0.000174 825 1.21% : 0.000002s : 12: predicate.accumulaten_eliminater 2.97% : 0.000005s : 5: predicate.ad_related_special_op_eliminate 0.99% : 0.000002s : 12: predicate.addn_check_dump 1.07% : 0.000002s : 12: predicate.addn_zero_filter 1.71% : 0.000003s : 12: predicate.arithmetic_simplify 1.94% : 0.000003s : 12: predicate.cast_eliminate 0.53% : 0.000001s : 5: predicate.check_bprop_eliminate 0.91% : 0.000002s : 12: predicate.compare_switch_simplify 1.29% : 0.000002s : 12: predicate.depend_value_elim 0.95% : 0.000002s : 12: predicate.dict_get_item_const_eliminator 1.10% : 0.000002s : 12: predicate.dict_get_item_eliminator 1.17% : 0.000002s : 12: predicate.dict_set_item_eliminator 2.49% : 0.000004s : 5: predicate.dumpgradient_eliminate 0.62% : 0.000001s : 5: predicate.elim_not_effective 0.86% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.03% : 0.000002s : 12: predicate.environ_add_const_eliminate 0.99% : 0.000002s : 12: predicate.environ_get_add_eliminate 1.02% : 0.000002s : 12: predicate.environ_get_depend_swap 1.24% : 0.000002s : 12: predicate.environ_get_eliminate 1.04% : 0.000002s : 12: predicate.environ_get_set_eliminate 0.25% : 0.000000s : 5: predicate.fold_const_symbol 1.26% : 0.000002s : 10: predicate.get_grad_eliminate 0.48% : 0.000001s : 5: predicate.graph_param_transform 5.31% : 0.000009s : 25: predicate.inline 0.97% : 0.000002s : 10: predicate.inline_without_move 0.44% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.52% : 0.000003s : 10: predicate.less_batch_normalization 1.03% : 0.000002s : 12: predicate.list_to_tuple_eliminator_ 1.78% : 0.000003s : 17: predicate.load_eliminater 2.39% : 0.000004s : 5: predicate.loop_unroll_after_grad 2.90% : 0.000005s : 25: predicate.loop_unroll_before_grad 2.38% : 0.000004s : 17: predicate.make_slice_get_slice_eliminator 1.04% : 0.000002s : 12: predicate.merge_addn 1.03% : 0.000002s : 12: predicate.minmaximum_grad 2.42% : 0.000004s : 5: predicate.mutable_eliminate 0.80% : 0.000001s : 5: predicate.opt_reshape 1.97% : 0.000003s : 17: predicate.partial_eliminate 1.03% : 0.000002s : 12: predicate.print_const_string_wrapper 1.43% : 0.000002s : 12: predicate.reduce_eliminate 1.10% : 0.000002s : 12: predicate.redundant_stop_gradient_eliminater 0.76% : 0.000001s : 10: predicate.remove_not_recompute_node 1.57% : 0.000003s : 22: predicate.replace_applicator 0.83% : 0.000001s : 10: predicate.replace_old_param 0.68% : 0.000001s : 5: predicate.reset_defer_inline 1.20% : 0.000002s : 12: predicate.reshape_eliminate 1.14% : 0.000002s : 12: predicate.row_tensor_add_zeros_like 1.17% : 0.000002s : 5: predicate.row_tensor_eliminate 1.09% : 0.000002s : 12: predicate.same_eliminate 0.56% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.89% : 0.000003s : 10: predicate.special_op_eliminate 1.35% : 0.000002s : 10: predicate.specialize_transform 1.59% : 0.000003s : 12: predicate.split_environ_get_set_with_tuple_value 1.34% : 0.000002s : 12: predicate.stack_unstack_eliminate 0.62% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.52% : 0.000003s : 15: predicate.switch_defer_inline 1.43% : 0.000002s : 15: predicate.switch_layer_defer_inline 6.02% : 0.000010s : 45: predicate.switch_simplify 1.14% : 0.000002s : 12: predicate.tile_eliminate 1.04% : 0.000002s : 12: predicate.transpose_eliminate 1.25% : 0.000002s : 12: predicate.tuple_list_convert_item_index_to_positive 1.09% : 0.000002s : 12: predicate.tuple_list_get_item_depend_reorder 3.39% : 0.000006s : 22: predicate.tuple_list_get_item_eliminator 1.30% : 0.000002s : 12: predicate.tuple_list_set_item_eliminator 1.78% : 0.000003s : 12: predicate.tuple_to_list_eliminator_ 1.64% : 0.000003s : 17: predicate.updatestate_pure_node_eliminater 3.30% : 0.000006s : 27: predicate.updatestate_useless_node_eliminater 1.25% : 0.000002s : 12: predicate.value_based_eliminate 0.55% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.87% : 0.000002s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000411 6 6.43% : 0.000026s : 1: func_graph_cloner_run.FuncGraphClonerGraph 93.57% : 0.000385s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.420415 72 0.02% : 0.000095s : 1: add_recomputation 0.04% : 0.000169s : 1: auto_monad 0.01% : 0.000040s : 1: auto_monad_reorder 0.14% : 0.000609s : 1: bootstrap 0.01% : 0.000047s : 1: cconv 0.01% : 0.000030s : 1: convert_after_rewriter 0.01% : 0.000039s : 1: cse_after_recomputation 0.01% : 0.000029s : 1: environ_conv 0.01% : 0.000022s : 1: event_method 0.00% : 0.000005s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000011s : 1: graph_reusing 2.68% : 0.011267s : 1: jit_opt_a 0.06% : 0.000264s : 1: jit_opt_after_cconv 0.02% : 0.000086s : 1: jit_opt_b 0.13% : 0.000567s : 1: loop_unroll 0.20% : 0.000849s : 1: mutable_eliminate 0.24% : 0.001029s : 26: opt.transform.jit_opt_a 0.02% : 0.000100s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000047s : 4: opt.transform.jit_opt_b 0.01% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000029s : 1: opt.transform.mutable_eliminate 0.01% : 0.000061s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000062s : 4: opt.transform.symbol_engine_opt 43.95% : 0.184752s : 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% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000033s : 1: py_interpret_to_execute 0.01% : 0.000024s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000024s : 1: remove_dup_value 0.14% : 0.000568s : 1: renormalize.infer 0.10% : 0.000437s : 1: renormalize.specialize 0.04% : 0.000165s : 1: rewriter_after_jit_bprop_graph 0.17% : 0.000694s : 1: rewriter_after_opt_a 0.02% : 0.000065s : 1: rewriter_before_opt_a 0.03% : 0.000127s : 1: symbol_engine_optimizer 51.86% : 0.218010s : 1: type_inference TotalTime = 1.16621, [30] [bootstrap]: 0.00048696 [type_inference]: 0.626637 [event_method]: 0.00015723 [auto_monad]: 0.00972349 [graph_reusing]: 1.232e-05 [pre_auto_parallel]: 5.23002e-06 [py_interpret_to_execute]: 0.00013441 [rewriter_before_opt_a]: 0.00019953 [expand_dump_flag]: 5.70001e-06 [jit_opt_a]: 0.525963, [3] [Cycle 1]: 0.455953, [27] [switch_simplify]: 0.0248118 [loop_unroll]: 7e-05 [a_1]: 0.0273804 [with_stream_mark]: 5.117e-05 [recompute_prepare]: 0.00662725 [updatestate_depend_eliminate]: 3.372e-05 [updatestate_assign_eliminate]: 1.173e-05 [updatestate_loads_eliminate]: 1.03e-05 [parameter_eliminate]: 9.11998e-06 [specialize_transform]: 2.851e-05 [updatestate_useless_node_eliminater]: 2.848e-05 [accelerated_algorithm]: 2.052e-05 [meta_shard_fg_expand]: 1.107e-05 [get_grad_eliminate_]: 1.89e-05 [merge_forward]: 1.285e-05 [cell_reuse_recompute_pass]: 1.43002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.969e-05 [j_node_and_user_rematch]: 3.27e-05 [meta_fg_expand]: 0.284442 [replace_old_param]: 0.00012233 [inline_without_move]: 0.00011778 [renormalize]: 0.110989 [add_forward_monad_depend]: 1.988e-05 [auto_monad_grad]: 9.58997e-06 [auto_monad_eliminator]: 8.829e-05 [cse]: 0.00033851 [replace_applicator]: 0.00020113 [Cycle 2]: 0.00298488, [27] [switch_simplify]: 6.023e-05 [loop_unroll]: 5.538e-05 [a_1]: 0.00102413 [with_stream_mark]: 1.877e-05 [recompute_prepare]: 1.391e-05 [updatestate_depend_eliminate]: 2.792e-05 [updatestate_assign_eliminate]: 5.79999e-06 [updatestate_loads_eliminate]: 5.46e-06 [parameter_eliminate]: 2.68e-06 [specialize_transform]: 1.255e-05 [updatestate_useless_node_eliminater]: 1.245e-05 [accelerated_algorithm]: 9.56e-06 [meta_shard_fg_expand]: 2.78e-06 [get_grad_eliminate_]: 8.79e-06 [merge_forward]: 5.87999e-06 [cell_reuse_recompute_pass]: 1.62001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.008e-05 [j_node_and_user_rematch]: 1.306e-05 [meta_fg_expand]: 0.00011724 [replace_old_param]: 1.569e-05 [inline_without_move]: 9.24e-06 [renormalize]: 0.00126746 [add_forward_monad_depend]: 5.79e-06 [auto_monad_grad]: 1.82999e-06 [auto_monad_eliminator]: 1.913e-05 [cse]: 4.682e-05 [replace_applicator]: 1.857e-05 [Cycle 3]: 0.00050114, [27] [switch_simplify]: 9.59e-06 [loop_unroll]: 8.45001e-06 [a_1]: 0.00018054 [with_stream_mark]: 1.313e-05 [recompute_prepare]: 8.13001e-06 [updatestate_depend_eliminate]: 6.04001e-06 [updatestate_assign_eliminate]: 4.87e-06 [updatestate_loads_eliminate]: 4.12e-06 [parameter_eliminate]: 1.47001e-06 [specialize_transform]: 8.23999e-06 [updatestate_useless_node_eliminater]: 1.036e-05 [accelerated_algorithm]: 8.72998e-06 [meta_shard_fg_expand]: 2.37001e-06 [get_grad_eliminate_]: 7.52002e-06 [merge_forward]: 5.22e-06 [cell_reuse_recompute_pass]: 2.84001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.894e-05 [j_node_and_user_rematch]: 1.377e-05 [meta_fg_expand]: 2.99999e-06 [replace_old_param]: 1.137e-05 [inline_without_move]: 7.6e-06 [renormalize]: 2.40019e-07 [add_forward_monad_depend]: 1.84998e-06 [auto_monad_grad]: 1.25999e-06 [auto_monad_eliminator]: 9.88998e-06 [cse]: 2.171e-05 [replace_applicator]: 9.00999e-06 [py_interpret_to_execute_after_opt_a]: 1.534e-05 [rewriter_after_opt_a]: 0.00025847 [convert_after_rewriter]: 1.263e-05 [order_py_execute_after_rewriter]: 6.91999e-06 [mutable_eliminate]: 0.00073348 [jit_opt_b]: 7.31e-05, [1] [Cycle 1]: 6.517e-05, [2] [frontend_op_eliminate]: 2.532e-05 [inline_after_opt_a]: 2.559e-05 [cconv]: 3.092e-05 [loop_unroll]: 0.00045559 [jit_opt_after_cconv]: 0.00021184, [1] [Cycle 1]: 0.00020434, [11] [c_1]: 4.736e-05 [parameter_eliminate]: 3.9e-06 [updatestate_depend_eliminate]: 9.21002e-06 [updatestate_assign_eliminate]: 5.32001e-06 [updatestate_loads_eliminate]: 4.62998e-06 [cse]: 3.564e-05 [call_graph_tuple_transform]: 2.373e-05 [tuple_list_get_item_eliminator]: 8.92999e-06 [none_parameter_eliminate]: 1.87999e-06 [renormalize]: 5.00004e-07 [switch_simplify]: 8.36002e-06 [remove_dup_value]: 2.168e-05 [partial_unused_args_eliminate]: 2.55002e-06 [environ_conv]: 7.45e-06 [add_recomputation]: 7.391e-05 [cse_after_recomputation]: 3.486e-05, [1] [Cycle 1]: 2.85e-05, [1] [cse]: 2.092e-05 [auto_monad_reorder]: 2.806e-05 [get_jit_bprop_graph]: 2.01e-06 [rewriter_after_jit_bprop_graph]: 5.80002e-06 [opt_after_jit_grad]: 0.00047422 [symbol_engine_optimizer]: 9.783e-05, [1] [Cycle 1]: 9.111e-05, [6] [build]: 6.94999e-06 [elim_shapecalc]: 1.175e-05 [elim_not_effective]: 1.928e-05 [opt_reshape]: 9.22001e-06 [fold_const_symbol]: 1.364e-05 [renormalize]: 5.39992e-07 [validate]: 5.553e-05 Sums bootstrap : 0.000487s : 0.04% type_inference : 0.626637s : 57.04% event_method : 0.000157s : 0.01% auto_monad : 0.009723s : 0.89% graph_reusing : 0.000012s : 0.00% pre_auto_parallel : 0.000005s : 0.00% py_interpret_to_execute : 0.000134s : 0.01% rewriter_before_opt_a : 0.000200s : 0.02% expand_dump_flag : 0.000006s : 0.00% jit_opt_a.switch_simplify : 0.024882s : 2.26% jit_opt_a.loop_unroll : 0.000134s : 0.01% jit_opt_a.a_1 : 0.028585s : 2.60% jit_opt_a.with_stream_mark : 0.000083s : 0.01% jit_opt_a.recompute_prepare : 0.006649s : 0.61% jit_opt_a.updatestate_depend_eliminate : 0.000068s : 0.01% jit_opt_a.updatestate_assign_eliminate : 0.000022s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000020s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000049s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000051s : 0.00% jit_opt_a.accelerated_algorithm : 0.000039s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000016s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000035s : 0.00% jit_opt_a.merge_forward : 0.000024s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000079s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000060s : 0.01% jit_opt_a.meta_fg_expand : 0.284562s : 25.90% jit_opt_a.replace_old_param : 0.000149s : 0.01% jit_opt_a.inline_without_move : 0.000135s : 0.01% jit_opt_a.renormalize : 0.112256s : 10.22% jit_opt_a.add_forward_monad_depend : 0.000028s : 0.00% jit_opt_a.auto_monad_grad : 0.000013s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000117s : 0.01% jit_opt_a.cse : 0.000407s : 0.04% jit_opt_a.replace_applicator : 0.000229s : 0.02% py_interpret_to_execute_after_opt_a : 0.000015s : 0.00% rewriter_after_opt_a : 0.000258s : 0.02% convert_after_rewriter : 0.000013s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000733s : 0.07% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.00% jit_opt_b.inline_after_opt_a : 0.000026s : 0.00% cconv : 0.000031s : 0.00% loop_unroll : 0.000456s : 0.04% jit_opt_after_cconv.c_1 : 0.000047s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000009s : 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 : 0.000024s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000009s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000008s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000007s : 0.00% add_recomputation : 0.000074s : 0.01% cse_after_recomputation.cse : 0.000021s : 0.00% auto_monad_reorder : 0.000028s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000474s : 0.04% 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 : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000056s : 0.01% Time group info: ------[substitution.] 0.027404 170 0.11% : 0.000031s : 8: substitution.depend_value_elim 0.01% : 0.000003s : 4: substitution.elim_not_effective 0.01% : 0.000002s : 4: substitution.fold_const_symbol 3.16% : 0.000865s : 4: substitution.getattr_setattr_resolve 0.02% : 0.000007s : 5: substitution.graph_param_transform 26.34% : 0.007218s : 16: substitution.inline 0.13% : 0.000036s : 4: substitution.inline_without_move 0.05% : 0.000013s : 20: substitution.j_node_and_user_rematch 0.04% : 0.000011s : 5: substitution.minmaximum_grad 0.04% : 0.000011s : 9: substitution.partial_eliminate 0.06% : 0.000016s : 20: substitution.remove_not_recompute_node 0.19% : 0.000051s : 12: substitution.replace_applicator 0.05% : 0.000015s : 16: substitution.replace_old_param 0.06% : 0.000017s : 1: substitution.set_cell_output_no_recompute 0.09% : 0.000025s : 3: substitution.switch_simplify 0.08% : 0.000023s : 5: substitution.tuple_list_convert_item_index_to_positive 0.06% : 0.000017s : 5: substitution.tuple_list_get_item_depend_reorder 69.29% : 0.018988s : 8: substitution.tuple_list_get_item_eliminator 0.08% : 0.000023s : 8: substitution.updatestate_pure_node_eliminater 0.12% : 0.000034s : 13: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.626488 2 93.25% : 0.584224s : 1: type_inference.infer 6.75% : 0.042264s : 1: type_inference.specialize ------[replace.] 0.000491 27 13.86% : 0.000068s : 3: replace.getattr_setattr_resolve 35.97% : 0.000177s : 16: replace.inline 10.72% : 0.000053s : 1: replace.replace_applicator 19.79% : 0.000097s : 3: replace.switch_simplify 15.13% : 0.000074s : 3: replace.tuple_list_get_item_eliminator 4.53% : 0.000022s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.008063 27 10.00% : 0.000806s : 3: match.getattr_setattr_resolve 89.36% : 0.007205s : 16: match.inline 0.16% : 0.000013s : 1: match.replace_applicator 0.29% : 0.000023s : 3: match.switch_simplify 0.09% : 0.000007s : 3: match.tuple_list_get_item_eliminator 0.10% : 0.000008s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000569 3164 1.60% : 0.000009s : 50: predicate.accumulaten_eliminater 0.32% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.33% : 0.000008s : 50: predicate.addn_check_dump 1.58% : 0.000009s : 50: predicate.addn_zero_filter 2.11% : 0.000012s : 50: predicate.arithmetic_simplify 1.45% : 0.000008s : 50: predicate.cast_eliminate 0.16% : 0.000001s : 5: predicate.check_bprop_eliminate 1.30% : 0.000007s : 50: predicate.compare_switch_simplify 1.51% : 0.000009s : 50: predicate.depend_value_elim 1.32% : 0.000008s : 50: predicate.dict_get_item_const_eliminator 1.59% : 0.000009s : 50: predicate.dict_get_item_eliminator 1.42% : 0.000008s : 50: predicate.dict_set_item_eliminator 0.35% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 5: predicate.elim_not_effective 0.19% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.30% : 0.000007s : 50: predicate.environ_add_const_eliminate 1.37% : 0.000008s : 50: predicate.environ_get_add_eliminate 1.34% : 0.000008s : 50: predicate.environ_get_depend_swap 1.41% : 0.000008s : 50: predicate.environ_get_eliminate 1.23% : 0.000007s : 50: predicate.environ_get_set_eliminate 0.08% : 0.000000s : 5: predicate.fold_const_symbol 0.88% : 0.000005s : 26: predicate.get_grad_eliminate 1.20% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.12% : 0.000001s : 5: predicate.graph_param_transform 4.00% : 0.000023s : 80: predicate.inline 2.71% : 0.000015s : 87: predicate.inline_without_move 0.33% : 0.000002s : 26: predicate.j_node_and_user_rematch 1.29% : 0.000007s : 26: predicate.less_batch_normalization 1.65% : 0.000009s : 53: predicate.list_to_tuple_eliminator_ 1.66% : 0.000009s : 58: predicate.load_eliminater 0.43% : 0.000002s : 5: predicate.loop_unroll_after_grad 3.93% : 0.000022s : 132: predicate.loop_unroll_before_grad 1.65% : 0.000009s : 55: predicate.make_slice_get_slice_eliminator 1.24% : 0.000007s : 50: predicate.merge_addn 1.27% : 0.000007s : 50: predicate.minmaximum_grad 0.43% : 0.000002s : 5: predicate.mutable_eliminate 0.20% : 0.000001s : 5: predicate.opt_reshape 1.98% : 0.000011s : 58: predicate.partial_eliminate 1.37% : 0.000008s : 50: predicate.print_const_string_wrapper 1.93% : 0.000011s : 50: predicate.reduce_eliminate 1.70% : 0.000010s : 53: predicate.redundant_stop_gradient_eliminater 0.44% : 0.000003s : 26: predicate.remove_not_recompute_node 2.40% : 0.000014s : 126: predicate.replace_applicator 1.42% : 0.000008s : 87: predicate.replace_old_param 0.15% : 0.000001s : 5: predicate.reset_defer_inline 1.43% : 0.000008s : 50: predicate.reshape_eliminate 1.57% : 0.000009s : 50: predicate.row_tensor_add_zeros_like 0.32% : 0.000002s : 5: predicate.row_tensor_eliminate 1.38% : 0.000008s : 50: predicate.same_eliminate 0.48% : 0.000003s : 28: predicate.set_cell_output_no_recompute 0.35% : 0.000002s : 10: predicate.special_op_eliminate 0.96% : 0.000005s : 26: predicate.specialize_transform 1.85% : 0.000011s : 50: predicate.split_environ_get_set_with_tuple_value 1.37% : 0.000008s : 50: predicate.stack_unstack_eliminate 0.18% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.90% : 0.000016s : 70: predicate.switch_defer_inline 2.16% : 0.000012s : 70: predicate.switch_layer_defer_inline 8.31% : 0.000047s : 213: predicate.switch_simplify 1.43% : 0.000008s : 50: predicate.tile_eliminate 1.43% : 0.000008s : 50: predicate.transpose_eliminate 1.74% : 0.000010s : 50: predicate.tuple_list_convert_item_index_to_positive 1.61% : 0.000009s : 50: predicate.tuple_list_get_item_depend_reorder 3.02% : 0.000017s : 63: predicate.tuple_list_get_item_eliminator 2.06% : 0.000012s : 50: predicate.tuple_list_set_item_eliminator 1.45% : 0.000008s : 53: predicate.tuple_to_list_eliminator_ 1.64% : 0.000009s : 58: predicate.updatestate_pure_node_eliminater 2.69% : 0.000015s : 85: predicate.updatestate_useless_node_eliminater 1.86% : 0.000011s : 50: predicate.value_based_eliminate 0.14% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.19% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.029741 47 8.94% : 0.002657s : 20: func_graph_cloner_run.FuncGraphClonerGraph 91.06% : 0.027084s : 27: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.340563 89 0.01% : 0.000077s : 1: add_recomputation 0.73% : 0.009767s : 1: auto_monad 0.00% : 0.000031s : 1: auto_monad_reorder 0.04% : 0.000514s : 1: bootstrap 0.00% : 0.000034s : 1: cconv 0.00% : 0.000016s : 1: convert_after_rewriter 0.00% : 0.000037s : 1: cse_after_recomputation 0.00% : 0.000010s : 1: environ_conv 0.01% : 0.000167s : 1: event_method 0.00% : 0.000010s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000018s : 1: graph_reusing 39.23% : 0.525967s : 1: jit_opt_a 0.02% : 0.000216s : 1: jit_opt_after_cconv 0.01% : 0.000076s : 1: jit_opt_b 0.03% : 0.000463s : 1: loop_unroll 0.06% : 0.000742s : 1: mutable_eliminate 4.55% : 0.061000s : 39: opt.transform.jit_opt_a 0.01% : 0.000085s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000043s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000020s : 1: opt.transform.mutable_eliminate 0.00% : 0.000031s : 1: opt.transform.opt_after_jit_grad 0.07% : 0.001000s : 2: opt.transform.opt_resolve 0.00% : 0.000050s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000483s : 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% : 0.000010s : 1: pre_auto_parallel 0.01% : 0.000139s : 1: py_interpret_to_execute 0.00% : 0.000018s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000025s : 1: remove_dup_value 8.13% : 0.108987s : 2: renormalize.infer 0.24% : 0.003246s : 2: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000270s : 1: rewriter_after_opt_a 0.02% : 0.000203s : 1: rewriter_before_opt_a 0.01% : 0.000102s : 1: symbol_engine_optimizer 46.75% : 0.626664s : 1: type_inference . [hook] pytest_runtest_teardown:test_unsqueeze_high_dimension[KBK] tests/st/mint/test_unsqueeze.py::test_unsqueeze_high_dimension[KBK],max_mem:4.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 177.44s (0:02:57) ==================