==================================================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/ops/ascend, 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_nsa_compress.py TotalTime = 1.61146, [30] [bootstrap]: 0.00073375 [type_inference]: 1.43875 [event_method]: 2.914e-05 [auto_monad]: 0.00011287 [graph_reusing]: 6.44001e-06 [pre_auto_parallel]: 1.148e-05 [py_interpret_to_execute]: 0.00036386 [rewriter_before_opt_a]: 0.00014047 [expand_dump_flag]: 3.78001e-06 [jit_opt_a]: 0.167858, [2] [Cycle 1]: 0.035055, [27] [switch_simplify]: 8.719e-05 [loop_unroll]: 3.86e-05 [a_1]: 0.0007608 [with_stream_mark]: 3.062e-05 [recompute_prepare]: 1.334e-05 [updatestate_depend_eliminate]: 6.11e-06 [updatestate_assign_eliminate]: 4.44998e-06 [updatestate_loads_eliminate]: 3.63999e-06 [parameter_eliminate]: 2.01998e-06 [specialize_transform]: 9.88998e-06 [updatestate_useless_node_eliminater]: 7.75998e-06 [accelerated_algorithm]: 9.32999e-06 [meta_shard_fg_expand]: 3.04999e-06 [get_grad_eliminate_]: 8.3e-06 [merge_forward]: 5.15999e-06 [cell_reuse_recompute_pass]: 1.23002e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.63e-05 [j_node_and_user_rematch]: 1.434e-05 [meta_fg_expand]: 3.18e-06 [replace_old_param]: 1.444e-05 [inline_without_move]: 8.77e-06 [renormalize]: 0.0335912 [add_forward_monad_depend]: 1.218e-05 [auto_monad_grad]: 3.58e-06 [auto_monad_eliminator]: 2.602e-05 [cse]: 5.984e-05 [replace_applicator]: 2.986e-05 [Cycle 2]: 0.0375552, [27] [switch_simplify]: 9.01998e-06 [loop_unroll]: 8.43001e-06 [a_1]: 0.0370477 [with_stream_mark]: 4.265e-05 [recompute_prepare]: 1.827e-05 [updatestate_depend_eliminate]: 6.53998e-06 [updatestate_assign_eliminate]: 4.40999e-06 [updatestate_loads_eliminate]: 3.68e-06 [parameter_eliminate]: 2.74999e-06 [specialize_transform]: 9.62999e-06 [updatestate_useless_node_eliminater]: 8.45001e-06 [accelerated_algorithm]: 1.047e-05 [meta_shard_fg_expand]: 4.1e-06 [get_grad_eliminate_]: 7.73001e-06 [merge_forward]: 5.70001e-06 [cell_reuse_recompute_pass]: 3.76001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.97e-05 [j_node_and_user_rematch]: 1.392e-05 [meta_fg_expand]: 3.35e-06 [replace_old_param]: 1.571e-05 [inline_without_move]: 8.50999e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 5.32999e-06 [auto_monad_grad]: 3.31001e-06 [auto_monad_eliminator]: 2.33e-05 [cse]: 5.245e-05 [replace_applicator]: 8.79e-06 [py_interpret_to_execute_after_opt_a]: 2.728e-05 [rewriter_after_opt_a]: 8.042e-05 [convert_after_rewriter]: 1.098e-05 [order_py_execute_after_rewriter]: 6.27001e-06 [mutable_eliminate]: 0.00085277 [jit_opt_b]: 7.934e-05, [1] [Cycle 1]: 6.772e-05, [2] [frontend_op_eliminate]: 2.627e-05 [inline_after_opt_a]: 2.597e-05 [cconv]: 4.052e-05 [loop_unroll]: 0.00049034 [jit_opt_after_cconv]: 0.0002166, [1] [Cycle 1]: 0.00020756, [11] [c_1]: 3.469e-05 [parameter_eliminate]: 5.72999e-06 [updatestate_depend_eliminate]: 1.194e-05 [updatestate_assign_eliminate]: 4.42e-06 [updatestate_loads_eliminate]: 3.23e-06 [cse]: 4.307e-05 [call_graph_tuple_transform]: 3.042e-05 [tuple_list_get_item_eliminator]: 8.31002e-06 [none_parameter_eliminate]: 2.46e-06 [renormalize]: 8.80013e-07 [switch_simplify]: 8.52e-06 [remove_dup_value]: 2.384e-05 [partial_unused_args_eliminate]: 2.44001e-06 [environ_conv]: 2.616e-05 [add_recomputation]: 0.00010183 [cse_after_recomputation]: 3.209e-05, [1] [Cycle 1]: 2.485e-05, [1] [cse]: 1.785e-05 [auto_monad_reorder]: 2.933e-05 [get_jit_bprop_graph]: 2.27999e-06 [rewriter_after_jit_bprop_graph]: 4.80001e-06 [opt_after_jit_grad]: 0.00074239 [symbol_engine_optimizer]: 9.984e-05, [1] [Cycle 1]: 9.282e-05, [6] [build]: 5.79999e-06 [elim_shapecalc]: 1.124e-05 [elim_not_effective]: 2.07e-05 [opt_reshape]: 1.057e-05 [fold_const_symbol]: 1.317e-05 [renormalize]: 6.10016e-07 [validate]: 0.00017421 Sums bootstrap : 0.000734s : 0.05% type_inference : 1.438750s : 94.95% event_method : 0.000029s : 0.00% auto_monad : 0.000113s : 0.01% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000011s : 0.00% py_interpret_to_execute : 0.000364s : 0.02% rewriter_before_opt_a : 0.000140s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000096s : 0.01% jit_opt_a.loop_unroll : 0.000047s : 0.00% jit_opt_a.a_1 : 0.037808s : 2.50% jit_opt_a.with_stream_mark : 0.000073s : 0.00% jit_opt_a.recompute_prepare : 0.000032s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000013s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000009s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000007s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000020s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000016s : 0.00% jit_opt_a.accelerated_algorithm : 0.000020s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000007s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000016s : 0.00% jit_opt_a.merge_forward : 0.000011s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000066s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000028s : 0.00% jit_opt_a.meta_fg_expand : 0.000007s : 0.00% jit_opt_a.replace_old_param : 0.000030s : 0.00% jit_opt_a.inline_without_move : 0.000017s : 0.00% jit_opt_a.renormalize : 0.033591s : 2.22% jit_opt_a.add_forward_monad_depend : 0.000018s : 0.00% jit_opt_a.auto_monad_grad : 0.000007s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000049s : 0.00% jit_opt_a.cse : 0.000112s : 0.01% jit_opt_a.replace_applicator : 0.000039s : 0.00% py_interpret_to_execute_after_opt_a : 0.000027s : 0.00% rewriter_after_opt_a : 0.000080s : 0.01% convert_after_rewriter : 0.000011s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000853s : 0.06% jit_opt_b.frontend_op_eliminate : 0.000026s : 0.00% jit_opt_b.inline_after_opt_a : 0.000026s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000490s : 0.03% jit_opt_after_cconv.c_1 : 0.000035s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000043s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000030s : 0.00% 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 : 0.000009s : 0.00% remove_dup_value : 0.000024s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000026s : 0.00% add_recomputation : 0.000102s : 0.01% cse_after_recomputation.cse : 0.000018s : 0.00% auto_monad_reorder : 0.000029s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000005s : 0.00% opt_after_jit_grad : 0.000742s : 0.05% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000011s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000021s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000013s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000174s : 0.01% Time group info: ------[substitution.] 0.000278 29 1.18% : 0.000003s : 2: substitution.elim_not_effective 0.57% : 0.000002s : 2: substitution.fold_const_symbol 2.60% : 0.000007s : 5: substitution.graph_param_transform 81.32% : 0.000226s : 4: substitution.inline 1.98% : 0.000005s : 4: substitution.j_node_and_user_rematch 2.32% : 0.000006s : 4: substitution.remove_not_recompute_node 3.44% : 0.000010s : 4: substitution.replace_old_param 6.59% : 0.000018s : 4: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.438616 2 99.79% : 1.435590s : 1: type_inference.infer 0.21% : 0.003026s : 1: type_inference.specialize ------[replace.] 0.000093 8 62.01% : 0.000058s : 4: replace.inline 37.99% : 0.000035s : 4: replace.tuple_list_get_item_eliminator ------[match.] 0.000238 8 93.35% : 0.000222s : 4: match.inline 6.65% : 0.000016s : 4: match.tuple_list_get_item_eliminator ------[predicate.] 0.000207 1039 1.43% : 0.000003s : 15: predicate.accumulaten_eliminater 1.02% : 0.000002s : 5: predicate.ad_related_special_op_eliminate 0.84% : 0.000002s : 15: predicate.addn_check_dump 1.29% : 0.000003s : 15: predicate.addn_zero_filter 2.58% : 0.000005s : 15: predicate.arithmetic_simplify 1.26% : 0.000003s : 15: predicate.cast_eliminate 0.39% : 0.000001s : 5: predicate.check_bprop_eliminate 0.92% : 0.000002s : 15: predicate.compare_switch_simplify 1.48% : 0.000003s : 15: predicate.depend_value_elim 1.11% : 0.000002s : 15: predicate.dict_get_item_const_eliminator 1.08% : 0.000002s : 15: predicate.dict_get_item_eliminator 1.09% : 0.000002s : 15: predicate.dict_set_item_eliminator 0.72% : 0.000001s : 5: predicate.dumpgradient_eliminate 0.34% : 0.000001s : 5: predicate.elim_not_effective 0.63% : 0.000001s : 5: predicate.elim_shapecalc_of_broadcastargs 1.40% : 0.000003s : 15: predicate.environ_add_const_eliminate 0.93% : 0.000002s : 15: predicate.environ_get_add_eliminate 0.97% : 0.000002s : 15: predicate.environ_get_depend_swap 1.13% : 0.000002s : 15: predicate.environ_get_eliminate 0.86% : 0.000002s : 15: predicate.environ_get_set_eliminate 0.22% : 0.000000s : 5: predicate.fold_const_symbol 1.03% : 0.000002s : 10: predicate.get_grad_eliminate 0.22% : 0.000000s : 5: predicate.graph_param_transform 6.67% : 0.000014s : 33: predicate.inline 0.80% : 0.000002s : 10: predicate.inline_without_move 0.37% : 0.000001s : 10: predicate.j_node_and_user_rematch 1.43% : 0.000003s : 10: predicate.less_batch_normalization 1.61% : 0.000003s : 19: predicate.list_to_tuple_eliminator_ 1.67% : 0.000003s : 24: predicate.load_eliminater 1.29% : 0.000003s : 5: predicate.loop_unroll_after_grad 2.89% : 0.000006s : 38: predicate.loop_unroll_before_grad 1.74% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.00% : 0.000002s : 15: predicate.merge_addn 0.97% : 0.000002s : 15: predicate.minmaximum_grad 2.05% : 0.000004s : 5: predicate.mutable_eliminate 0.53% : 0.000001s : 5: predicate.opt_reshape 2.12% : 0.000004s : 24: predicate.partial_eliminate 1.08% : 0.000002s : 15: predicate.print_const_string_wrapper 1.85% : 0.000004s : 15: predicate.reduce_eliminate 1.52% : 0.000003s : 19: predicate.redundant_stop_gradient_eliminater 0.64% : 0.000001s : 10: predicate.remove_not_recompute_node 2.07% : 0.000004s : 29: predicate.replace_applicator 0.69% : 0.000001s : 10: predicate.replace_old_param 0.50% : 0.000001s : 5: predicate.reset_defer_inline 1.23% : 0.000003s : 15: predicate.reshape_eliminate 1.11% : 0.000002s : 15: predicate.row_tensor_add_zeros_like 0.92% : 0.000002s : 5: predicate.row_tensor_eliminate 1.28% : 0.000003s : 15: predicate.same_eliminate 0.66% : 0.000001s : 10: predicate.set_cell_output_no_recompute 1.05% : 0.000002s : 10: predicate.special_op_eliminate 0.91% : 0.000002s : 10: predicate.specialize_transform 1.32% : 0.000003s : 15: predicate.split_environ_get_set_with_tuple_value 1.29% : 0.000003s : 15: predicate.stack_unstack_eliminate 0.55% : 0.000001s : 5: predicate.switch_call_monad_eliminater 2.00% : 0.000004s : 23: predicate.switch_defer_inline 1.67% : 0.000003s : 23: predicate.switch_layer_defer_inline 9.24% : 0.000019s : 66: predicate.switch_simplify 1.13% : 0.000002s : 15: predicate.tile_eliminate 1.05% : 0.000002s : 15: predicate.transpose_eliminate 1.74% : 0.000004s : 15: predicate.tuple_list_convert_item_index_to_positive 1.72% : 0.000004s : 15: predicate.tuple_list_get_item_depend_reorder 4.67% : 0.000010s : 29: predicate.tuple_list_get_item_eliminator 1.78% : 0.000004s : 15: predicate.tuple_list_set_item_eliminator 1.48% : 0.000003s : 19: predicate.tuple_to_list_eliminator_ 1.51% : 0.000003s : 24: predicate.updatestate_pure_node_eliminater 2.56% : 0.000005s : 34: predicate.updatestate_useless_node_eliminater 1.89% : 0.000004s : 15: predicate.value_based_eliminate 0.30% : 0.000001s : 5: predicate.virtual_view_grad_eliminate 0.54% : 0.000001s : 5: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.058513 39 97.93% : 0.057302s : 33: func_graph_cloner_run.FuncGraphClonerGraph 2.07% : 0.001211s : 6: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.683012 72 0.01% : 0.000106s : 1: add_recomputation 0.01% : 0.000116s : 1: auto_monad 0.00% : 0.000032s : 1: auto_monad_reorder 0.04% : 0.000754s : 1: bootstrap 0.00% : 0.000044s : 1: cconv 0.00% : 0.000014s : 1: convert_after_rewriter 0.00% : 0.000034s : 1: cse_after_recomputation 0.00% : 0.000029s : 1: environ_conv 0.00% : 0.000034s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 9.97% : 0.167862s : 1: jit_opt_a 0.01% : 0.000219s : 1: jit_opt_after_cconv 0.00% : 0.000082s : 1: jit_opt_b 0.03% : 0.000498s : 1: loop_unroll 0.05% : 0.000862s : 1: mutable_eliminate 2.27% : 0.038164s : 26: opt.transform.jit_opt_a 0.00% : 0.000078s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000044s : 4: opt.transform.jit_opt_b 0.00% : 0.000018s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000023s : 1: opt.transform.mutable_eliminate 0.00% : 0.000035s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000051s : 4: opt.transform.symbol_engine_opt 0.04% : 0.000750s : 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% : 0.000014s : 1: pre_auto_parallel 0.02% : 0.000370s : 1: py_interpret_to_execute 0.00% : 0.000030s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000026s : 1: remove_dup_value 1.91% : 0.032217s : 1: renormalize.infer 0.08% : 0.001357s : 1: renormalize.specialize 0.00% : 0.000007s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000087s : 1: rewriter_after_opt_a 0.01% : 0.000146s : 1: rewriter_before_opt_a 0.01% : 0.000102s : 1: symbol_engine_optimizer 85.49% : 1.438772s : 1: type_inference TotalTime = 2.11615, [30] [bootstrap]: 0.00072335 [type_inference]: 1.68855 [event_method]: 0.00047188 [auto_monad]: 0.00023791 [graph_reusing]: 1.121e-05 [pre_auto_parallel]: 4.33999e-06 [py_interpret_to_execute]: 9.473e-05 [rewriter_before_opt_a]: 0.00026595 [expand_dump_flag]: 5.17e-06 [jit_opt_a]: 0.42221, [3] [Cycle 1]: 0.408549, [27] [switch_simplify]: 0.00032936 [loop_unroll]: 9.486e-05 [a_1]: 0.00248819 [with_stream_mark]: 5.691e-05 [recompute_prepare]: 4.638e-05 [updatestate_depend_eliminate]: 1.532e-05 [updatestate_assign_eliminate]: 1.062e-05 [updatestate_loads_eliminate]: 8.97999e-06 [parameter_eliminate]: 4.08001e-06 [specialize_transform]: 2.169e-05 [updatestate_useless_node_eliminater]: 2.293e-05 [accelerated_algorithm]: 4.685e-05 [meta_shard_fg_expand]: 1.271e-05 [get_grad_eliminate_]: 2.055e-05 [merge_forward]: 1.423e-05 [cell_reuse_recompute_pass]: 1.40001e-06 [cell_reuse_handle_not_recompute_node_pass]: 7.203e-05 [j_node_and_user_rematch]: 4.103e-05 [meta_fg_expand]: 0.00310707 [replace_old_param]: 0.00011975 [inline_without_move]: 8.831e-05 [renormalize]: 0.401052 [add_forward_monad_depend]: 1.677e-05 [auto_monad_grad]: 1.171e-05 [auto_monad_eliminator]: 8.869e-05 [cse]: 0.0002715 [replace_applicator]: 0.00012665 [Cycle 2]: 0.00737401, [27] [switch_simplify]: 5.665e-05 [loop_unroll]: 5.728e-05 [a_1]: 0.00189817 [with_stream_mark]: 3.841e-05 [recompute_prepare]: 2.262e-05 [updatestate_depend_eliminate]: 8.97999e-06 [updatestate_assign_eliminate]: 6.81999e-06 [updatestate_loads_eliminate]: 5.26998e-06 [parameter_eliminate]: 3.28e-06 [specialize_transform]: 1.449e-05 [updatestate_useless_node_eliminater]: 1.174e-05 [accelerated_algorithm]: 2.221e-05 [meta_shard_fg_expand]: 4.53999e-06 [get_grad_eliminate_]: 1.098e-05 [merge_forward]: 7.92003e-06 [cell_reuse_recompute_pass]: 2.05002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.792e-05 [j_node_and_user_rematch]: 1.985e-05 [meta_fg_expand]: 0.00077908 [replace_old_param]: 4.976e-05 [inline_without_move]: 1.693e-05 [renormalize]: 0.00376671 [add_forward_monad_depend]: 1.422e-05 [auto_monad_grad]: 3.33e-06 [auto_monad_eliminator]: 3.6e-05 [cse]: 0.00018457 [replace_applicator]: 4.333e-05 [Cycle 3]: 0.00079671, [27] [switch_simplify]: 1.408e-05 [loop_unroll]: 1.338e-05 [a_1]: 0.00033091 [with_stream_mark]: 2.994e-05 [recompute_prepare]: 1.249e-05 [updatestate_depend_eliminate]: 7.95e-06 [updatestate_assign_eliminate]: 6.94999e-06 [updatestate_loads_eliminate]: 6.53e-06 [parameter_eliminate]: 2.34001e-06 [specialize_transform]: 1.248e-05 [updatestate_useless_node_eliminater]: 1.201e-05 [accelerated_algorithm]: 2.011e-05 [meta_shard_fg_expand]: 4.85999e-06 [get_grad_eliminate_]: 1.19e-05 [merge_forward]: 7.72002e-06 [cell_reuse_recompute_pass]: 3.33e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.618e-05 [j_node_and_user_rematch]: 1.955e-05 [meta_fg_expand]: 4.77998e-06 [replace_old_param]: 1.86e-05 [inline_without_move]: 1.118e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 2.78998e-06 [auto_monad_grad]: 1.85001e-06 [auto_monad_eliminator]: 1.852e-05 [cse]: 4.249e-05 [replace_applicator]: 1.277e-05 [py_interpret_to_execute_after_opt_a]: 2.72e-05 [rewriter_after_opt_a]: 0.00024396 [convert_after_rewriter]: 1.496e-05 [order_py_execute_after_rewriter]: 9.12999e-06 [mutable_eliminate]: 0.00090493 [jit_opt_b]: 0.00012127, [1] [Cycle 1]: 0.00011142, [2] [frontend_op_eliminate]: 3.831e-05 [inline_after_opt_a]: 5.838e-05 [cconv]: 4.148e-05 [loop_unroll]: 0.00048527 [jit_opt_after_cconv]: 0.00030056, [1] [Cycle 1]: 0.00029311, [11] [c_1]: 5.056e-05 [parameter_eliminate]: 5.42001e-06 [updatestate_depend_eliminate]: 1.678e-05 [updatestate_assign_eliminate]: 5.99e-06 [updatestate_loads_eliminate]: 5.67999e-06 [cse]: 6.961e-05 [call_graph_tuple_transform]: 4.03e-05 [tuple_list_get_item_eliminator]: 2.258e-05 [none_parameter_eliminate]: 2.41e-06 [renormalize]: 8.80013e-07 [switch_simplify]: 1.208e-05 [remove_dup_value]: 8.384e-05 [partial_unused_args_eliminate]: 2.77002e-06 [environ_conv]: 1.824e-05 [add_recomputation]: 9.019e-05 [cse_after_recomputation]: 5.061e-05, [1] [Cycle 1]: 4.25e-05, [1] [cse]: 3.459e-05 [auto_monad_reorder]: 3.183e-05 [get_jit_bprop_graph]: 2.26e-06 [rewriter_after_jit_bprop_graph]: 9.24e-06 [opt_after_jit_grad]: 0.00061396 [symbol_engine_optimizer]: 0.00013472, [1] [Cycle 1]: 0.00012607, [6] [build]: 1.823e-05 [elim_shapecalc]: 1.539e-05 [elim_not_effective]: 2.506e-05 [opt_reshape]: 1.341e-05 [fold_const_symbol]: 1.922e-05 [renormalize]: 6.79982e-07 [validate]: 0.0001025 Sums bootstrap : 0.000723s : 0.03% type_inference : 1.688548s : 80.05% event_method : 0.000472s : 0.02% auto_monad : 0.000238s : 0.01% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000095s : 0.00% rewriter_before_opt_a : 0.000266s : 0.01% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000400s : 0.02% jit_opt_a.loop_unroll : 0.000166s : 0.01% jit_opt_a.a_1 : 0.004717s : 0.22% jit_opt_a.with_stream_mark : 0.000125s : 0.01% jit_opt_a.recompute_prepare : 0.000081s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000032s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000024s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000021s : 0.00% jit_opt_a.parameter_eliminate : 0.000010s : 0.00% jit_opt_a.specialize_transform : 0.000049s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000047s : 0.00% jit_opt_a.accelerated_algorithm : 0.000089s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000022s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000043s : 0.00% jit_opt_a.merge_forward : 0.000030s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000007s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000126s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000080s : 0.00% jit_opt_a.meta_fg_expand : 0.003891s : 0.18% jit_opt_a.replace_old_param : 0.000188s : 0.01% jit_opt_a.inline_without_move : 0.000116s : 0.01% jit_opt_a.renormalize : 0.404819s : 19.19% jit_opt_a.add_forward_monad_depend : 0.000034s : 0.00% jit_opt_a.auto_monad_grad : 0.000017s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000143s : 0.01% jit_opt_a.cse : 0.000499s : 0.02% jit_opt_a.replace_applicator : 0.000183s : 0.01% py_interpret_to_execute_after_opt_a : 0.000027s : 0.00% rewriter_after_opt_a : 0.000244s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000905s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000038s : 0.00% jit_opt_b.inline_after_opt_a : 0.000058s : 0.00% cconv : 0.000041s : 0.00% loop_unroll : 0.000485s : 0.02% jit_opt_after_cconv.c_1 : 0.000051s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000017s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000070s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000040s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000023s : 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 : 0.000012s : 0.00% remove_dup_value : 0.000084s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000018s : 0.00% add_recomputation : 0.000090s : 0.00% cse_after_recomputation.cse : 0.000035s : 0.00% auto_monad_reorder : 0.000032s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000009s : 0.00% opt_after_jit_grad : 0.000614s : 0.03% symbol_engine_optimizer.build : 0.000018s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000102s : 0.00% Time group info: ------[substitution.] 0.001485 200 0.25% : 0.000004s : 5: substitution.elim_not_effective 0.16% : 0.000002s : 5: substitution.fold_const_symbol 0.73% : 0.000011s : 8: substitution.graph_param_transform 68.55% : 0.001018s : 19: substitution.inline 2.04% : 0.000030s : 2: substitution.inline_without_move 1.19% : 0.000018s : 20: substitution.j_node_and_user_rematch 1.82% : 0.000027s : 3: substitution.less_batch_normalization 2.43% : 0.000036s : 15: substitution.minmaximum_grad 0.96% : 0.000014s : 11: substitution.partial_eliminate 1.06% : 0.000016s : 20: substitution.remove_not_recompute_node 2.71% : 0.000040s : 9: substitution.replace_applicator 1.38% : 0.000020s : 18: substitution.replace_old_param 0.50% : 0.000007s : 1: substitution.set_cell_output_no_recompute 1.52% : 0.000023s : 3: substitution.switch_simplify 3.88% : 0.000058s : 15: substitution.tuple_list_convert_item_index_to_positive 2.63% : 0.000039s : 15: substitution.tuple_list_get_item_depend_reorder 8.18% : 0.000121s : 31: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.688246 2 95.13% : 1.606081s : 1: type_inference.infer 4.87% : 0.082165s : 1: type_inference.specialize ------[replace.] 0.000526 34 52.78% : 0.000278s : 19: replace.inline 19.76% : 0.000104s : 3: replace.switch_simplify 27.45% : 0.000144s : 12: replace.tuple_list_get_item_eliminator ------[match.] 0.001054 34 94.95% : 0.001000s : 19: match.inline 1.71% : 0.000018s : 3: match.switch_simplify 3.35% : 0.000035s : 12: match.tuple_list_get_item_eliminator ------[predicate.] 0.000666 4383 1.36% : 0.000009s : 73: predicate.accumulaten_eliminater 0.53% : 0.000004s : 8: predicate.ad_related_special_op_eliminate 1.29% : 0.000009s : 73: predicate.addn_check_dump 1.57% : 0.000010s : 73: predicate.addn_zero_filter 2.33% : 0.000016s : 73: predicate.arithmetic_simplify 1.42% : 0.000009s : 73: predicate.cast_eliminate 0.17% : 0.000001s : 8: predicate.check_bprop_eliminate 1.28% : 0.000009s : 73: predicate.compare_switch_simplify 1.34% : 0.000009s : 73: predicate.depend_value_elim 1.37% : 0.000009s : 73: predicate.dict_get_item_const_eliminator 1.56% : 0.000010s : 73: predicate.dict_get_item_eliminator 1.36% : 0.000009s : 73: predicate.dict_set_item_eliminator 0.45% : 0.000003s : 8: predicate.dumpgradient_eliminate 0.13% : 0.000001s : 8: predicate.elim_not_effective 0.27% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.38% : 0.000009s : 73: predicate.environ_add_const_eliminate 1.31% : 0.000009s : 73: predicate.environ_get_add_eliminate 1.49% : 0.000010s : 73: predicate.environ_get_depend_swap 1.37% : 0.000009s : 73: predicate.environ_get_eliminate 1.34% : 0.000009s : 73: predicate.environ_get_set_eliminate 0.10% : 0.000001s : 8: predicate.fold_const_symbol 0.82% : 0.000005s : 33: predicate.get_grad_eliminate 0.17% : 0.000001s : 8: predicate.graph_param_transform 4.84% : 0.000032s : 120: predicate.inline 2.00% : 0.000013s : 65: predicate.inline_without_move 0.37% : 0.000002s : 33: predicate.j_node_and_user_rematch 1.11% : 0.000007s : 33: predicate.less_batch_normalization 1.82% : 0.000012s : 85: predicate.list_to_tuple_eliminator_ 1.84% : 0.000012s : 93: predicate.load_eliminater 0.52% : 0.000003s : 8: predicate.loop_unroll_after_grad 3.50% : 0.000023s : 143: predicate.loop_unroll_before_grad 1.70% : 0.000011s : 81: predicate.make_slice_get_slice_eliminator 1.30% : 0.000009s : 73: predicate.merge_addn 1.53% : 0.000010s : 73: predicate.minmaximum_grad 0.80% : 0.000005s : 8: predicate.mutable_eliminate 0.24% : 0.000002s : 8: predicate.opt_reshape 2.37% : 0.000016s : 93: predicate.partial_eliminate 1.38% : 0.000009s : 73: predicate.print_const_string_wrapper 1.94% : 0.000013s : 73: predicate.reduce_eliminate 1.75% : 0.000012s : 85: predicate.redundant_stop_gradient_eliminater 0.48% : 0.000003s : 33: predicate.remove_not_recompute_node 2.63% : 0.000017s : 155: predicate.replace_applicator 1.03% : 0.000007s : 65: predicate.replace_old_param 0.15% : 0.000001s : 8: predicate.reset_defer_inline 1.45% : 0.000010s : 73: predicate.reshape_eliminate 1.41% : 0.000009s : 73: predicate.row_tensor_add_zeros_like 0.26% : 0.000002s : 8: predicate.row_tensor_eliminate 1.35% : 0.000009s : 73: predicate.same_eliminate 0.60% : 0.000004s : 33: predicate.set_cell_output_no_recompute 0.44% : 0.000003s : 16: predicate.special_op_eliminate 0.79% : 0.000005s : 33: predicate.specialize_transform 1.76% : 0.000012s : 73: predicate.split_environ_get_set_with_tuple_value 1.43% : 0.000009s : 73: predicate.stack_unstack_eliminate 0.20% : 0.000001s : 8: predicate.switch_call_monad_eliminater 3.44% : 0.000023s : 104: predicate.switch_defer_inline 2.25% : 0.000015s : 104: predicate.switch_layer_defer_inline 6.79% : 0.000045s : 261: predicate.switch_simplify 1.40% : 0.000009s : 73: predicate.tile_eliminate 1.42% : 0.000009s : 73: predicate.transpose_eliminate 1.83% : 0.000012s : 73: predicate.tuple_list_convert_item_index_to_positive 1.69% : 0.000011s : 73: predicate.tuple_list_get_item_depend_reorder 3.78% : 0.000025s : 101: predicate.tuple_list_get_item_eliminator 1.86% : 0.000012s : 73: predicate.tuple_list_set_item_eliminator 1.62% : 0.000011s : 85: predicate.tuple_to_list_eliminator_ 1.77% : 0.000012s : 93: predicate.updatestate_pure_node_eliminater 2.64% : 0.000018s : 126: predicate.updatestate_useless_node_eliminater 1.71% : 0.000011s : 73: predicate.value_based_eliminate 0.16% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.25% : 0.000002s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.322380 82 99.03% : 0.319251s : 59: func_graph_cloner_run.FuncGraphClonerGraph 0.97% : 0.003130s : 23: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.527265 87 0.00% : 0.000094s : 1: add_recomputation 0.01% : 0.000247s : 1: auto_monad 0.00% : 0.000034s : 1: auto_monad_reorder 0.03% : 0.000751s : 1: bootstrap 0.00% : 0.000044s : 1: cconv 0.00% : 0.000018s : 1: convert_after_rewriter 0.00% : 0.000053s : 1: cse_after_recomputation 0.00% : 0.000022s : 1: environ_conv 0.02% : 0.000483s : 1: event_method 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 16.71% : 0.422217s : 1: jit_opt_a 0.01% : 0.000304s : 1: jit_opt_after_cconv 0.00% : 0.000125s : 1: jit_opt_b 0.02% : 0.000493s : 1: loop_unroll 0.04% : 0.000916s : 1: mutable_eliminate 0.24% : 0.006174s : 39: opt.transform.jit_opt_a 0.00% : 0.000121s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000086s : 4: opt.transform.jit_opt_b 0.00% : 0.000024s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000034s : 1: opt.transform.mutable_eliminate 0.00% : 0.000051s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000067s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000623s : 1: opt_after_jit_grad 0.00% : 0.000011s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000007s : 1: pre_auto_parallel 0.00% : 0.000098s : 1: py_interpret_to_execute 0.00% : 0.000030s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000087s : 1: remove_dup_value 15.76% : 0.398254s : 2: renormalize.infer 0.26% : 0.006522s : 2: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000250s : 1: rewriter_after_opt_a 0.01% : 0.000270s : 1: rewriter_before_opt_a 0.01% : 0.000137s : 1: symbol_engine_optimizer 66.81% : 1.688576s : 1: type_inference . [hook] pytest_runtest_teardown:test_nsa_compress_non_contiguous_inputs[0] tests/st/ops/ascend/test_nsa_compress.py::test_nsa_compress_non_contiguous_inputs[0],max_mem:22.0M . [hook] pytest_runtest_teardown:test_nsa_compress_non_contiguous_inputs[1] tests/st/ops/ascend/test_nsa_compress.py::test_nsa_compress_non_contiguous_inputs[1],max_mem:22.0M =============================== 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 270.54s (0:04:30) ==================