==================================================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_008/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_jit_mode[pynative] tests/st/mint/test_unsqueeze.py::test_unsqueeze_jit_mode[pynative],max_mem:2.0M TotalTime = 0.348474, [30] [bootstrap]: 0.00060392 [type_inference]: 0.331093 [event_method]: 1.457e-05 [auto_monad]: 0.00014931 [graph_reusing]: 6.42001e-06 [pre_auto_parallel]: 1.214e-05 [py_interpret_to_execute]: 3.295e-05 [rewriter_before_opt_a]: 6.175e-05 [expand_dump_flag]: 3.36001e-06 [jit_opt_a]: 0.013144, [2] [Cycle 1]: 0.00173761, [27] [switch_simplify]: 5.769e-05 [loop_unroll]: 2.282e-05 [a_1]: 0.00045976 [with_stream_mark]: 2.501e-05 [recompute_prepare]: 9.97001e-06 [updatestate_depend_eliminate]: 6.17999e-06 [updatestate_assign_eliminate]: 6.78e-06 [updatestate_loads_eliminate]: 5.12999e-06 [parameter_eliminate]: 1.88002e-06 [specialize_transform]: 9.17999e-06 [updatestate_useless_node_eliminater]: 1.123e-05 [accelerated_algorithm]: 8.35001e-06 [meta_shard_fg_expand]: 2.63e-06 [get_grad_eliminate_]: 7.93001e-06 [merge_forward]: 5.17e-06 [cell_reuse_recompute_pass]: 1.34e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.242e-05 [j_node_and_user_rematch]: 1.388e-05 [meta_fg_expand]: 3.16001e-06 [replace_old_param]: 1.206e-05 [inline_without_move]: 7.63001e-06 [renormalize]: 0.00074633 [add_forward_monad_depend]: 8.39002e-06 [auto_monad_grad]: 2.06e-06 [auto_monad_eliminator]: 2.009e-05 [cse]: 4.609e-05 [replace_applicator]: 1.457e-05 [Cycle 2]: 0.00053502, [27] [switch_simplify]: 8.40001e-06 [loop_unroll]: 7.45998e-06 [a_1]: 0.0001602 [with_stream_mark]: 1.001e-05 [recompute_prepare]: 7.61001e-06 [updatestate_depend_eliminate]: 5.01002e-06 [updatestate_assign_eliminate]: 4.43999e-06 [updatestate_loads_eliminate]: 3.88001e-06 [parameter_eliminate]: 1.00001e-06 [specialize_transform]: 8.2e-06 [updatestate_useless_node_eliminater]: 1.425e-05 [accelerated_algorithm]: 8.21002e-06 [meta_shard_fg_expand]: 1.89e-06 [get_grad_eliminate_]: 9.57999e-06 [merge_forward]: 4.30999e-06 [cell_reuse_recompute_pass]: 1.94e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.768e-05 [j_node_and_user_rematch]: 1.355e-05 [meta_fg_expand]: 2.65002e-06 [replace_old_param]: 1.077e-05 [inline_without_move]: 8.39002e-06 [renormalize]: 5.9983e-08 [add_forward_monad_depend]: 1.67001e-06 [auto_monad_grad]: 1.00999e-06 [auto_monad_eliminator]: 2.973e-05 [cse]: 1.685e-05 [replace_applicator]: 8.48001e-06 [py_interpret_to_execute_after_opt_a]: 1.397e-05 [rewriter_after_opt_a]: 0.00060366 [convert_after_rewriter]: 1.445e-05 [order_py_execute_after_rewriter]: 7.05e-06 [mutable_eliminate]: 0.00065367 [jit_opt_b]: 6.957e-05, [1] [Cycle 1]: 6.195e-05, [2] [frontend_op_eliminate]: 2.344e-05 [inline_after_opt_a]: 2.48e-05 [cconv]: 2.994e-05 [loop_unroll]: 0.00046609 [jit_opt_after_cconv]: 0.00020633, [1] [Cycle 1]: 0.00019998, [11] [c_1]: 4.559e-05 [parameter_eliminate]: 2.76e-06 [updatestate_depend_eliminate]: 9.17999e-06 [updatestate_assign_eliminate]: 4.51002e-06 [updatestate_loads_eliminate]: 4.25999e-06 [cse]: 2.969e-05 [call_graph_tuple_transform]: 3.208e-05 [tuple_list_get_item_eliminator]: 8.45999e-06 [none_parameter_eliminate]: 1.67999e-06 [renormalize]: 5.89993e-07 [switch_simplify]: 8.45001e-06 [remove_dup_value]: 1.88e-05 [partial_unused_args_eliminate]: 2.48e-06 [environ_conv]: 1.969e-05 [add_recomputation]: 7.836e-05 [cse_after_recomputation]: 2.853e-05, [1] [Cycle 1]: 2.212e-05, [1] [cse]: 1.596e-05 [auto_monad_reorder]: 3.475e-05 [get_jit_bprop_graph]: 2.32001e-06 [rewriter_after_jit_bprop_graph]: 0.00012962 [opt_after_jit_grad]: 0.00050502 [symbol_engine_optimizer]: 9.305e-05, [1] [Cycle 1]: 8.628e-05, [6] [build]: 5.47001e-06 [elim_shapecalc]: 1.11e-05 [elim_not_effective]: 1.795e-05 [opt_reshape]: 8.57998e-06 [fold_const_symbol]: 1.376e-05 [renormalize]: 3.60014e-07 [validate]: 7.374e-05 Sums bootstrap : 0.000604s : 0.18% type_inference : 0.331093s : 98.30% event_method : 0.000015s : 0.00% auto_monad : 0.000149s : 0.04% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000012s : 0.00% py_interpret_to_execute : 0.000033s : 0.01% rewriter_before_opt_a : 0.000062s : 0.02% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000066s : 0.02% jit_opt_a.loop_unroll : 0.000030s : 0.01% jit_opt_a.a_1 : 0.000620s : 0.18% jit_opt_a.with_stream_mark : 0.000035s : 0.01% jit_opt_a.recompute_prepare : 0.000018s : 0.01% jit_opt_a.updatestate_depend_eliminate : 0.000011s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000011s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000017s : 0.01% jit_opt_a.updatestate_useless_node_eliminater : 0.000025s : 0.01% jit_opt_a.accelerated_algorithm : 0.000017s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000005s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000018s : 0.01% jit_opt_a.merge_forward : 0.000009s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000003s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000040s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000027s : 0.01% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000023s : 0.01% jit_opt_a.inline_without_move : 0.000016s : 0.00% jit_opt_a.renormalize : 0.000746s : 0.22% jit_opt_a.add_forward_monad_depend : 0.000010s : 0.00% jit_opt_a.auto_monad_grad : 0.000003s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000050s : 0.01% jit_opt_a.cse : 0.000063s : 0.02% jit_opt_a.replace_applicator : 0.000023s : 0.01% py_interpret_to_execute_after_opt_a : 0.000014s : 0.00% rewriter_after_opt_a : 0.000604s : 0.18% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000654s : 0.19% jit_opt_b.frontend_op_eliminate : 0.000023s : 0.01% jit_opt_b.inline_after_opt_a : 0.000025s : 0.01% cconv : 0.000030s : 0.01% loop_unroll : 0.000466s : 0.14% jit_opt_after_cconv.c_1 : 0.000046s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 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 : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000030s : 0.01% jit_opt_after_cconv.call_graph_tuple_transform : 0.000032s : 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 : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000008s : 0.00% remove_dup_value : 0.000019s : 0.01% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000020s : 0.01% add_recomputation : 0.000078s : 0.02% cse_after_recomputation.cse : 0.000016s : 0.00% auto_monad_reorder : 0.000035s : 0.01% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000130s : 0.04% opt_after_jit_grad : 0.000505s : 0.15% symbol_engine_optimizer.build : 0.000005s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000018s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000009s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000014s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000074s : 0.02% Time group info: ------[substitution.] 0.000216 44 3.50% : 0.000008s : 2: substitution.depend_value_elim 1.30% : 0.000003s : 4: substitution.elim_not_effective 0.96% : 0.000002s : 4: substitution.fold_const_symbol 7.72% : 0.000017s : 5: substitution.graph_param_transform 70.13% : 0.000151s : 3: substitution.inline 2.32% : 0.000005s : 8: substitution.j_node_and_user_rematch 3.49% : 0.000008s : 8: substitution.remove_not_recompute_node 1.97% : 0.000004s : 2: substitution.replace_old_param 4.36% : 0.000009s : 3: substitution.updatestate_pure_node_eliminater 4.25% : 0.000009s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.331025 2 99.81% : 0.330383s : 1: type_inference.infer 0.19% : 0.000642s : 1: type_inference.specialize ------[replace.] 0.000034 3 100.00% : 0.000034s : 3: replace.inline ------[match.] 0.000149 3 100.00% : 0.000149s : 3: match.inline ------[predicate.] 0.000145 825 1.20% : 0.000002s : 12: predicate.accumulaten_eliminater 1.38% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.21% : 0.000002s : 12: predicate.addn_check_dump 1.38% : 0.000002s : 12: predicate.addn_zero_filter 2.31% : 0.000003s : 12: predicate.arithmetic_simplify 1.38% : 0.000002s : 12: predicate.cast_eliminate 0.56% : 0.000001s : 5: predicate.check_bprop_eliminate 1.17% : 0.000002s : 12: predicate.compare_switch_simplify 1.34% : 0.000002s : 12: predicate.depend_value_elim 1.03% : 0.000001s : 12: predicate.dict_get_item_const_eliminator 1.18% : 0.000002s : 12: predicate.dict_get_item_eliminator 1.14% : 0.000002s : 12: predicate.dict_set_item_eliminator 1.04% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.55% : 0.000001s : 5: predicate.elim_not_effective 0.84% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.24% : 0.000002s : 12: predicate.environ_add_const_eliminate 1.13% : 0.000002s : 12: predicate.environ_get_add_eliminate 1.11% : 0.000002s : 12: predicate.environ_get_depend_swap 1.28% : 0.000002s : 12: predicate.environ_get_eliminate 1.12% : 0.000002s : 12: predicate.environ_get_set_eliminate 0.30% : 0.000000s : 5: predicate.fold_const_symbol 1.52% : 0.000002s : 10: predicate.get_grad_eliminate 0.45% : 0.000001s : 5: predicate.graph_param_transform 5.56% : 0.000008s : 25: predicate.inline 1.34% : 0.000002s : 10: predicate.inline_without_move 0.54% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.40% : 0.000002s : 10: predicate.less_batch_normalization 1.25% : 0.000002s : 12: predicate.list_to_tuple_eliminator_ 1.82% : 0.000003s : 17: predicate.load_eliminater 1.54% : 0.000002s : 5: predicate.loop_unroll_after_grad 2.85% : 0.000004s : 25: predicate.loop_unroll_before_grad 1.99% : 0.000003s : 17: predicate.make_slice_get_slice_eliminator 1.07% : 0.000002s : 12: predicate.merge_addn 1.08% : 0.000002s : 12: predicate.minmaximum_grad 1.84% : 0.000003s : 5: predicate.mutable_eliminate 0.68% : 0.000001s : 5: predicate.opt_reshape 2.26% : 0.000003s : 17: predicate.partial_eliminate 1.25% : 0.000002s : 12: predicate.print_const_string_wrapper 1.71% : 0.000002s : 12: predicate.reduce_eliminate 1.36% : 0.000002s : 12: predicate.redundant_stop_gradient_eliminater 0.94% : 0.000001s : 10: predicate.remove_not_recompute_node 1.56% : 0.000002s : 22: predicate.replace_applicator 0.87% : 0.000001s : 10: predicate.replace_old_param 0.41% : 0.000001s : 5: predicate.reset_defer_inline 1.20% : 0.000002s : 12: predicate.reshape_eliminate 1.26% : 0.000002s : 12: predicate.row_tensor_add_zeros_like 0.74% : 0.000001s : 5: predicate.row_tensor_eliminate 1.39% : 0.000002s : 12: predicate.same_eliminate 0.67% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.29% : 0.000002s : 10: predicate.special_op_eliminate 1.36% : 0.000002s : 10: predicate.specialize_transform 1.22% : 0.000002s : 12: predicate.split_environ_get_set_with_tuple_value 1.24% : 0.000002s : 12: predicate.stack_unstack_eliminate 0.61% : 0.000001s : 5: predicate.switch_call_monad_eliminater 1.86% : 0.000003s : 15: predicate.switch_defer_inline 1.58% : 0.000002s : 15: predicate.switch_layer_defer_inline 5.86% : 0.000009s : 45: predicate.switch_simplify 1.15% : 0.000002s : 12: predicate.tile_eliminate 1.15% : 0.000002s : 12: predicate.transpose_eliminate 1.36% : 0.000002s : 12: predicate.tuple_list_convert_item_index_to_positive 1.23% : 0.000002s : 12: predicate.tuple_list_get_item_depend_reorder 3.43% : 0.000005s : 22: predicate.tuple_list_get_item_eliminator 1.61% : 0.000002s : 12: predicate.tuple_list_set_item_eliminator 1.21% : 0.000002s : 12: predicate.tuple_to_list_eliminator_ 1.66% : 0.000002s : 17: predicate.updatestate_pure_node_eliminater 4.79% : 0.000007s : 27: predicate.updatestate_useless_node_eliminater 1.46% : 0.000002s : 12: predicate.value_based_eliminate 0.55% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.93% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.000366 6 5.52% : 0.000020s : 1: func_graph_cloner_run.FuncGraphClonerGraph 94.48% : 0.000346s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.350126 72 0.02% : 0.000082s : 1: add_recomputation 0.04% : 0.000154s : 1: auto_monad 0.01% : 0.000038s : 1: auto_monad_reorder 0.18% : 0.000624s : 1: bootstrap 0.01% : 0.000033s : 1: cconv 0.01% : 0.000018s : 1: convert_after_rewriter 0.01% : 0.000031s : 1: cse_after_recomputation 0.01% : 0.000023s : 1: environ_conv 0.01% : 0.000021s : 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 3.76% : 0.013148s : 1: jit_opt_a 0.06% : 0.000210s : 1: jit_opt_after_cconv 0.02% : 0.000073s : 1: jit_opt_b 0.14% : 0.000473s : 1: loop_unroll 0.19% : 0.000663s : 1: mutable_eliminate 0.26% : 0.000898s : 26: opt.transform.jit_opt_a 0.03% : 0.000091s : 4: opt.transform.jit_opt_after_cconv 0.01% : 0.000042s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000020s : 1: opt.transform.mutable_eliminate 0.01% : 0.000028s : 1: opt.transform.opt_after_jit_grad 0.01% : 0.000048s : 4: opt.transform.symbol_engine_opt 0.15% : 0.000513s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000036s : 1: py_interpret_to_execute 0.00% : 0.000017s : 1: py_interpret_to_execute_after_opt_a 0.01% : 0.000022s : 1: remove_dup_value 0.12% : 0.000413s : 1: renormalize.infer 0.09% : 0.000326s : 1: renormalize.specialize 0.04% : 0.000133s : 1: rewriter_after_jit_bprop_graph 0.17% : 0.000609s : 1: rewriter_after_opt_a 0.02% : 0.000065s : 1: rewriter_before_opt_a 0.03% : 0.000096s : 1: symbol_engine_optimizer 94.57% : 0.331112s : 1: type_inference TotalTime = 1.30381, [30] [bootstrap]: 0.00062978 [type_inference]: 0.382232 [event_method]: 0.0001174 [auto_monad]: 0.00029256 [graph_reusing]: 1.126e-05 [pre_auto_parallel]: 3.96001e-06 [py_interpret_to_execute]: 4.889e-05 [rewriter_before_opt_a]: 0.00019892 [expand_dump_flag]: 4.52e-06 [jit_opt_a]: 0.916982, [3] [Cycle 1]: 0.572081, [27] [switch_simplify]: 0.00023617 [loop_unroll]: 6.532e-05 [a_1]: 0.00152118 [with_stream_mark]: 4.353e-05 [recompute_prepare]: 2.571e-05 [updatestate_depend_eliminate]: 1.268e-05 [updatestate_assign_eliminate]: 1.218e-05 [updatestate_loads_eliminate]: 9.39e-06 [parameter_eliminate]: 2.84999e-06 [specialize_transform]: 1.92e-05 [updatestate_useless_node_eliminater]: 2.291e-05 [accelerated_algorithm]: 1.835e-05 [meta_shard_fg_expand]: 5.62001e-06 [get_grad_eliminate_]: 1.79e-05 [merge_forward]: 1.185e-05 [cell_reuse_recompute_pass]: 1.15001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.761e-05 [j_node_and_user_rematch]: 3.361e-05 [meta_fg_expand]: 0.359235 [replace_old_param]: 0.00011456 [inline_without_move]: 0.00011598 [renormalize]: 0.209604 [add_forward_monad_depend]: 2.75e-05 [auto_monad_grad]: 1.001e-05 [auto_monad_eliminator]: 8.319e-05 [cse]: 0.00029805 [replace_applicator]: 0.0001966 [Cycle 2]: 0.00288957, [27] [switch_simplify]: 6.002e-05 [loop_unroll]: 5.504e-05 [a_1]: 0.00103414 [with_stream_mark]: 2.089e-05 [recompute_prepare]: 1.251e-05 [updatestate_depend_eliminate]: 2.661e-05 [updatestate_assign_eliminate]: 5.99e-06 [updatestate_loads_eliminate]: 4.53999e-06 [parameter_eliminate]: 2.31998e-06 [specialize_transform]: 9.08002e-06 [updatestate_useless_node_eliminater]: 1.119e-05 [accelerated_algorithm]: 8.67e-06 [meta_shard_fg_expand]: 2.78e-06 [get_grad_eliminate_]: 8.21002e-06 [merge_forward]: 5.34e-06 [cell_reuse_recompute_pass]: 1.24e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.043e-05 [j_node_and_user_rematch]: 1.364e-05 [meta_fg_expand]: 0.00010309 [replace_old_param]: 1.466e-05 [inline_without_move]: 8.52e-06 [renormalize]: 0.00121558 [add_forward_monad_depend]: 4.88001e-06 [auto_monad_grad]: 2.55997e-06 [auto_monad_eliminator]: 1.733e-05 [cse]: 3.09e-05 [replace_applicator]: 1.661e-05 [Cycle 3]: 0.00046998, [27] [switch_simplify]: 9.49e-06 [loop_unroll]: 7.87e-06 [a_1]: 0.00016819 [with_stream_mark]: 1.219e-05 [recompute_prepare]: 7.88001e-06 [updatestate_depend_eliminate]: 5.54998e-06 [updatestate_assign_eliminate]: 4.22e-06 [updatestate_loads_eliminate]: 4.09002e-06 [parameter_eliminate]: 1.20001e-06 [specialize_transform]: 8.45001e-06 [updatestate_useless_node_eliminater]: 1.1e-05 [accelerated_algorithm]: 8.2e-06 [meta_shard_fg_expand]: 2.34999e-06 [get_grad_eliminate_]: 7.4e-06 [merge_forward]: 4.43001e-06 [cell_reuse_recompute_pass]: 1.99e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.739e-05 [j_node_and_user_rematch]: 1.271e-05 [meta_fg_expand]: 2.48e-06 [replace_old_param]: 1.004e-05 [inline_without_move]: 7.53999e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.09998e-06 [auto_monad_grad]: 7.80012e-07 [auto_monad_eliminator]: 8.97e-06 [cse]: 1.89e-05 [replace_applicator]: 7.75e-06 [py_interpret_to_execute_after_opt_a]: 1.569e-05 [rewriter_after_opt_a]: 0.00032001 [convert_after_rewriter]: 4.017e-05 [order_py_execute_after_rewriter]: 7.33e-06 [mutable_eliminate]: 0.00080442 [jit_opt_b]: 6.996e-05, [1] [Cycle 1]: 6.179e-05, [2] [frontend_op_eliminate]: 2.484e-05 [inline_after_opt_a]: 2.371e-05 [cconv]: 2.924e-05 [loop_unroll]: 0.00076017 [jit_opt_after_cconv]: 0.00020435, [1] [Cycle 1]: 0.00019714, [11] [c_1]: 4.883e-05 [parameter_eliminate]: 2.97002e-06 [updatestate_depend_eliminate]: 9.24e-06 [updatestate_assign_eliminate]: 4.57003e-06 [updatestate_loads_eliminate]: 3.95e-06 [cse]: 3.085e-05 [call_graph_tuple_transform]: 2.286e-05 [tuple_list_get_item_eliminator]: 7.98999e-06 [none_parameter_eliminate]: 1.48002e-06 [renormalize]: 3.19997e-07 [switch_simplify]: 9.16998e-06 [remove_dup_value]: 2.179e-05 [partial_unused_args_eliminate]: 2.68e-06 [environ_conv]: 7.83999e-06 [add_recomputation]: 7.511e-05 [cse_after_recomputation]: 3.141e-05, [1] [Cycle 1]: 2.495e-05, [1] [cse]: 1.831e-05 [auto_monad_reorder]: 2.654e-05 [get_jit_bprop_graph]: 2.39999e-06 [rewriter_after_jit_bprop_graph]: 6.04001e-06 [opt_after_jit_grad]: 0.00049191 [symbol_engine_optimizer]: 9.619e-05, [1] [Cycle 1]: 8.982e-05, [6] [build]: 5.49e-06 [elim_shapecalc]: 1.19e-05 [elim_not_effective]: 1.876e-05 [opt_reshape]: 9.32999e-06 [fold_const_symbol]: 1.317e-05 [renormalize]: 2.3999e-07 [validate]: 5.167e-05 Sums bootstrap : 0.000630s : 0.07% type_inference : 0.382232s : 39.76% event_method : 0.000117s : 0.01% auto_monad : 0.000293s : 0.03% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000049s : 0.01% rewriter_before_opt_a : 0.000199s : 0.02% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000306s : 0.03% jit_opt_a.loop_unroll : 0.000128s : 0.01% jit_opt_a.a_1 : 0.002724s : 0.28% jit_opt_a.with_stream_mark : 0.000077s : 0.01% jit_opt_a.recompute_prepare : 0.000046s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000045s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000022s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000018s : 0.00% jit_opt_a.parameter_eliminate : 0.000006s : 0.00% jit_opt_a.specialize_transform : 0.000037s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000045s : 0.00% jit_opt_a.accelerated_algorithm : 0.000035s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000011s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000034s : 0.00% jit_opt_a.merge_forward : 0.000022s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000075s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000060s : 0.01% jit_opt_a.meta_fg_expand : 0.359340s : 37.38% jit_opt_a.replace_old_param : 0.000139s : 0.01% jit_opt_a.inline_without_move : 0.000132s : 0.01% jit_opt_a.renormalize : 0.210819s : 21.93% jit_opt_a.add_forward_monad_depend : 0.000033s : 0.00% jit_opt_a.auto_monad_grad : 0.000013s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000109s : 0.01% jit_opt_a.cse : 0.000348s : 0.04% jit_opt_a.replace_applicator : 0.000221s : 0.02% py_interpret_to_execute_after_opt_a : 0.000016s : 0.00% rewriter_after_opt_a : 0.000320s : 0.03% convert_after_rewriter : 0.000040s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000804s : 0.08% jit_opt_b.frontend_op_eliminate : 0.000025s : 0.00% jit_opt_b.inline_after_opt_a : 0.000024s : 0.00% cconv : 0.000029s : 0.00% loop_unroll : 0.000760s : 0.08% jit_opt_after_cconv.c_1 : 0.000049s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000003s : 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 : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000031s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000023s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000008s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000001s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000009s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000008s : 0.00% add_recomputation : 0.000075s : 0.01% cse_after_recomputation.cse : 0.000018s : 0.00% auto_monad_reorder : 0.000027s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000492s : 0.05% symbol_engine_optimizer.build : 0.000005s : 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 : 0.000013s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000052s : 0.01% Time group info: ------[substitution.] 0.001708 170 1.29% : 0.000022s : 8: substitution.depend_value_elim 0.20% : 0.000003s : 4: substitution.elim_not_effective 0.12% : 0.000002s : 4: substitution.fold_const_symbol 48.13% : 0.000822s : 4: substitution.getattr_setattr_resolve 0.44% : 0.000007s : 5: substitution.graph_param_transform 33.15% : 0.000566s : 16: substitution.inline 2.08% : 0.000036s : 4: substitution.inline_without_move 0.71% : 0.000012s : 20: substitution.j_node_and_user_rematch 0.62% : 0.000011s : 5: substitution.minmaximum_grad 0.53% : 0.000009s : 9: substitution.partial_eliminate 0.90% : 0.000015s : 20: substitution.remove_not_recompute_node 2.73% : 0.000047s : 12: substitution.replace_applicator 0.85% : 0.000015s : 16: substitution.replace_old_param 0.16% : 0.000003s : 1: substitution.set_cell_output_no_recompute 0.95% : 0.000016s : 3: substitution.switch_simplify 1.27% : 0.000022s : 5: substitution.tuple_list_convert_item_index_to_positive 0.87% : 0.000015s : 5: substitution.tuple_list_get_item_depend_reorder 2.06% : 0.000035s : 8: substitution.tuple_list_get_item_eliminator 1.06% : 0.000018s : 8: substitution.updatestate_pure_node_eliminater 1.89% : 0.000032s : 13: substitution.updatestate_useless_node_eliminater ------[type_inference.] 0.382127 2 99.41% : 0.379875s : 1: type_inference.infer 0.59% : 0.002253s : 1: type_inference.specialize ------[replace.] 0.000422 27 15.23% : 0.000064s : 3: replace.getattr_setattr_resolve 31.31% : 0.000132s : 16: replace.inline 12.13% : 0.000051s : 1: replace.replace_applicator 17.74% : 0.000075s : 3: replace.switch_simplify 17.52% : 0.000074s : 3: replace.tuple_list_get_item_eliminator 6.07% : 0.000026s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.001364 27 55.90% : 0.000762s : 3: match.getattr_setattr_resolve 40.83% : 0.000557s : 16: match.inline 0.87% : 0.000012s : 1: match.replace_applicator 1.05% : 0.000014s : 3: match.switch_simplify 0.54% : 0.000007s : 3: match.tuple_list_get_item_eliminator 0.81% : 0.000011s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.000502 3164 1.54% : 0.000008s : 50: predicate.accumulaten_eliminater 0.41% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 1.47% : 0.000007s : 50: predicate.addn_check_dump 1.62% : 0.000008s : 50: predicate.addn_zero_filter 2.02% : 0.000010s : 50: predicate.arithmetic_simplify 1.51% : 0.000008s : 50: predicate.cast_eliminate 0.20% : 0.000001s : 5: predicate.check_bprop_eliminate 1.32% : 0.000007s : 50: predicate.compare_switch_simplify 1.65% : 0.000008s : 50: predicate.depend_value_elim 1.34% : 0.000007s : 50: predicate.dict_get_item_const_eliminator 1.46% : 0.000007s : 50: predicate.dict_get_item_eliminator 1.42% : 0.000007s : 50: predicate.dict_set_item_eliminator 0.30% : 0.000002s : 5: predicate.dumpgradient_eliminate 0.12% : 0.000001s : 5: predicate.elim_not_effective 0.24% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.45% : 0.000007s : 50: predicate.environ_add_const_eliminate 1.34% : 0.000007s : 50: predicate.environ_get_add_eliminate 1.37% : 0.000007s : 50: predicate.environ_get_depend_swap 1.49% : 0.000007s : 50: predicate.environ_get_eliminate 1.36% : 0.000007s : 50: predicate.environ_get_set_eliminate 0.09% : 0.000000s : 5: predicate.fold_const_symbol 0.92% : 0.000005s : 26: predicate.get_grad_eliminate 1.28% : 0.000006s : 20: predicate.getattr_setattr_resolve 0.10% : 0.000000s : 5: predicate.graph_param_transform 4.02% : 0.000020s : 80: predicate.inline 2.86% : 0.000014s : 87: predicate.inline_without_move 0.37% : 0.000002s : 26: predicate.j_node_and_user_rematch 1.03% : 0.000005s : 26: predicate.less_batch_normalization 1.67% : 0.000008s : 53: predicate.list_to_tuple_eliminator_ 1.66% : 0.000008s : 58: predicate.load_eliminater 0.59% : 0.000003s : 5: predicate.loop_unroll_after_grad 3.88% : 0.000020s : 132: predicate.loop_unroll_before_grad 1.71% : 0.000009s : 55: predicate.make_slice_get_slice_eliminator 1.38% : 0.000007s : 50: predicate.merge_addn 1.45% : 0.000007s : 50: predicate.minmaximum_grad 0.60% : 0.000003s : 5: predicate.mutable_eliminate 0.27% : 0.000001s : 5: predicate.opt_reshape 2.12% : 0.000011s : 58: predicate.partial_eliminate 1.52% : 0.000008s : 50: predicate.print_const_string_wrapper 1.65% : 0.000008s : 50: predicate.reduce_eliminate 1.61% : 0.000008s : 53: predicate.redundant_stop_gradient_eliminater 0.47% : 0.000002s : 26: predicate.remove_not_recompute_node 2.63% : 0.000013s : 126: predicate.replace_applicator 1.44% : 0.000007s : 87: predicate.replace_old_param 0.12% : 0.000001s : 5: predicate.reset_defer_inline 1.44% : 0.000007s : 50: predicate.reshape_eliminate 1.46% : 0.000007s : 50: predicate.row_tensor_add_zeros_like 0.26% : 0.000001s : 5: predicate.row_tensor_eliminate 1.44% : 0.000007s : 50: predicate.same_eliminate 0.48% : 0.000002s : 28: predicate.set_cell_output_no_recompute 0.36% : 0.000002s : 10: predicate.special_op_eliminate 0.86% : 0.000004s : 26: predicate.specialize_transform 1.64% : 0.000008s : 50: predicate.split_environ_get_set_with_tuple_value 1.49% : 0.000007s : 50: predicate.stack_unstack_eliminate 0.28% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.42% : 0.000012s : 70: predicate.switch_defer_inline 2.24% : 0.000011s : 70: predicate.switch_layer_defer_inline 7.01% : 0.000035s : 213: predicate.switch_simplify 1.33% : 0.000007s : 50: predicate.tile_eliminate 1.44% : 0.000007s : 50: predicate.transpose_eliminate 1.71% : 0.000009s : 50: predicate.tuple_list_convert_item_index_to_positive 1.58% : 0.000008s : 50: predicate.tuple_list_get_item_depend_reorder 2.72% : 0.000014s : 63: predicate.tuple_list_get_item_eliminator 1.79% : 0.000009s : 50: predicate.tuple_list_set_item_eliminator 1.61% : 0.000008s : 53: predicate.tuple_to_list_eliminator_ 1.71% : 0.000009s : 58: predicate.updatestate_pure_node_eliminater 3.51% : 0.000018s : 85: predicate.updatestate_useless_node_eliminater 1.77% : 0.000009s : 50: predicate.value_based_eliminate 0.15% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.23% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003560 47 63.70% : 0.002268s : 20: func_graph_cloner_run.FuncGraphClonerGraph 36.30% : 0.001292s : 27: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.519614 89 0.01% : 0.000079s : 1: add_recomputation 0.02% : 0.000300s : 1: auto_monad 0.00% : 0.000030s : 1: auto_monad_reorder 0.04% : 0.000655s : 1: bootstrap 0.00% : 0.000032s : 1: cconv 0.00% : 0.000045s : 1: convert_after_rewriter 0.00% : 0.000034s : 1: cse_after_recomputation 0.00% : 0.000011s : 1: environ_conv 0.01% : 0.000125s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 60.34% : 0.916986s : 1: jit_opt_a 0.01% : 0.000208s : 1: jit_opt_after_cconv 0.00% : 0.000073s : 1: jit_opt_b 0.05% : 0.000770s : 1: loop_unroll 0.05% : 0.000813s : 1: mutable_eliminate 0.26% : 0.003927s : 39: opt.transform.jit_opt_a 0.01% : 0.000085s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000041s : 4: opt.transform.jit_opt_b 0.00% : 0.000019s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000020s : 1: opt.transform.mutable_eliminate 0.00% : 0.000030s : 1: opt.transform.opt_after_jit_grad 0.06% : 0.000949s : 2: opt.transform.opt_resolve 0.00% : 0.000050s : 4: opt.transform.symbol_engine_opt 0.03% : 0.000500s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000053s : 1: py_interpret_to_execute 0.00% : 0.000019s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000025s : 1: remove_dup_value 13.66% : 0.207588s : 2: renormalize.infer 0.21% : 0.003209s : 2: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.02% : 0.000325s : 1: rewriter_after_opt_a 0.01% : 0.000203s : 1: rewriter_before_opt_a 0.01% : 0.000099s : 1: symbol_engine_optimizer 25.15% : 0.382252s : 1: type_inference . [hook] pytest_runtest_teardown:test_unsqueeze_jit_mode[KBK] tests/st/mint/test_unsqueeze.py::test_unsqueeze_jit_mode[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 304.11s (0:05:04) ==================