==================================================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/hal/memory, 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 1 item test_hal_memory_ascend.py TotalTime = 0.188499, [30] [bootstrap]: 0.00062408 [type_inference]: 0.142192 [event_method]: 5.233e-05 [auto_monad]: 0.00014882 [graph_reusing]: 8.74e-06 [pre_auto_parallel]: 1.259e-05 [py_interpret_to_execute]: 3.593e-05 [rewriter_before_opt_a]: 0.00012482 [expand_dump_flag]: 3.94002e-06 [jit_opt_a]: 0.0421565, [3] [Cycle 1]: 0.0320725, [27] [switch_simplify]: 8.931e-05 [loop_unroll]: 4.579e-05 [a_1]: 0.00112991 [with_stream_mark]: 0.00012517 [recompute_prepare]: 3.525e-05 [updatestate_depend_eliminate]: 0.0280784 [updatestate_assign_eliminate]: 3.554e-05 [updatestate_loads_eliminate]: 9.79e-06 [parameter_eliminate]: 1.204e-05 [specialize_transform]: 8.25e-05 [updatestate_useless_node_eliminater]: 1.666e-05 [accelerated_algorithm]: 8.095e-05 [meta_shard_fg_expand]: 7.95e-06 [get_grad_eliminate_]: 1.557e-05 [merge_forward]: 1.106e-05 [cell_reuse_recompute_pass]: 3.13e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.715e-05 [j_node_and_user_rematch]: 2.951e-05 [meta_fg_expand]: 7.51999e-06 [replace_old_param]: 2.012e-05 [inline_without_move]: 4.774e-05 [renormalize]: 0.00154306 [add_forward_monad_depend]: 2.113e-05 [auto_monad_grad]: 4.80999e-06 [auto_monad_eliminator]: 3.815e-05 [cse]: 0.00011356 [replace_applicator]: 5.062e-05 [Cycle 2]: 0.00158667, [27] [switch_simplify]: 1.464e-05 [loop_unroll]: 1.352e-05 [a_1]: 0.00044492 [with_stream_mark]: 2.413e-05 [recompute_prepare]: 1.018e-05 [updatestate_depend_eliminate]: 6.17999e-06 [updatestate_assign_eliminate]: 5.17999e-06 [updatestate_loads_eliminate]: 3.36999e-06 [parameter_eliminate]: 2.18998e-06 [specialize_transform]: 7.08e-06 [updatestate_useless_node_eliminater]: 6.23002e-06 [accelerated_algorithm]: 1.322e-05 [meta_shard_fg_expand]: 2.36998e-06 [get_grad_eliminate_]: 6.51e-06 [merge_forward]: 5.27001e-06 [cell_reuse_recompute_pass]: 1.29e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.823e-05 [j_node_and_user_rematch]: 1.092e-05 [meta_fg_expand]: 2.88998e-06 [replace_old_param]: 9.81e-06 [inline_without_move]: 6.38e-06 [renormalize]: 0.00066278 [add_forward_monad_depend]: 2.284e-05 [auto_monad_grad]: 2.36e-06 [auto_monad_eliminator]: 1.961e-05 [cse]: 6.869e-05 [replace_applicator]: 1.898e-05 [Cycle 3]: 0.00046805, [27] [switch_simplify]: 7.24001e-06 [loop_unroll]: 6.27001e-06 [a_1]: 0.00016022 [with_stream_mark]: 1.554e-05 [recompute_prepare]: 7.9e-06 [updatestate_depend_eliminate]: 4.80999e-06 [updatestate_assign_eliminate]: 3.81001e-06 [updatestate_loads_eliminate]: 3.50998e-06 [parameter_eliminate]: 1.59998e-06 [specialize_transform]: 6.69999e-06 [updatestate_useless_node_eliminater]: 6.67002e-06 [accelerated_algorithm]: 1.273e-05 [meta_shard_fg_expand]: 2.56e-06 [get_grad_eliminate_]: 6.06e-06 [merge_forward]: 5.25999e-06 [cell_reuse_recompute_pass]: 1.82001e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.787e-05 [j_node_and_user_rematch]: 1.012e-05 [meta_fg_expand]: 2.57001e-06 [replace_old_param]: 1.064e-05 [inline_without_move]: 5.91998e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.66e-06 [auto_monad_grad]: 1.32e-06 [auto_monad_eliminator]: 1.044e-05 [cse]: 2.313e-05 [replace_applicator]: 7.2e-06 [py_interpret_to_execute_after_opt_a]: 1.856e-05 [rewriter_after_opt_a]: 6.575e-05 [convert_after_rewriter]: 1.072e-05 [order_py_execute_after_rewriter]: 6.12999e-06 [mutable_eliminate]: 0.00076713 [jit_opt_b]: 6.807e-05, [1] [Cycle 1]: 5.839e-05, [2] [frontend_op_eliminate]: 2.09e-05 [inline_after_opt_a]: 2.223e-05 [cconv]: 4.126e-05 [loop_unroll]: 0.00048099 [jit_opt_after_cconv]: 0.00021301, [1] [Cycle 1]: 0.00020509, [11] [c_1]: 2.64e-05 [parameter_eliminate]: 6.39001e-06 [updatestate_depend_eliminate]: 1.243e-05 [updatestate_assign_eliminate]: 4.32e-06 [updatestate_loads_eliminate]: 4.05998e-06 [cse]: 5.082e-05 [call_graph_tuple_transform]: 2.877e-05 [tuple_list_get_item_eliminator]: 6.84001e-06 [none_parameter_eliminate]: 1.69e-06 [renormalize]: 6.50005e-07 [switch_simplify]: 6.28e-06 [remove_dup_value]: 7.819e-05 [partial_unused_args_eliminate]: 3.21999e-06 [environ_conv]: 2.037e-05 [add_recomputation]: 7.257e-05 [cse_after_recomputation]: 3.751e-05, [1] [Cycle 1]: 3.076e-05, [1] [cse]: 2.074e-05 [auto_monad_reorder]: 2.897e-05 [get_jit_bprop_graph]: 2.69001e-06 [rewriter_after_jit_bprop_graph]: 5.97999e-06 [opt_after_jit_grad]: 0.00056261 [symbol_engine_optimizer]: 9.008e-05, [1] [Cycle 1]: 8.18e-05, [6] [build]: 6.24999e-06 [elim_shapecalc]: 9.17999e-06 [elim_not_effective]: 1.83e-05 [opt_reshape]: 7.66999e-06 [fold_const_symbol]: 1.099e-05 [renormalize]: 5.60016e-07 [validate]: 6.749e-05 Sums bootstrap : 0.000624s : 0.35% type_inference : 0.142192s : 79.37% event_method : 0.000052s : 0.03% auto_monad : 0.000149s : 0.08% graph_reusing : 0.000009s : 0.00% pre_auto_parallel : 0.000013s : 0.01% py_interpret_to_execute : 0.000036s : 0.02% rewriter_before_opt_a : 0.000125s : 0.07% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000111s : 0.06% jit_opt_a.loop_unroll : 0.000066s : 0.04% jit_opt_a.a_1 : 0.001735s : 0.97% jit_opt_a.with_stream_mark : 0.000165s : 0.09% jit_opt_a.recompute_prepare : 0.000053s : 0.03% jit_opt_a.updatestate_depend_eliminate : 0.028089s : 15.68% jit_opt_a.updatestate_assign_eliminate : 0.000045s : 0.02% jit_opt_a.updatestate_loads_eliminate : 0.000017s : 0.01% jit_opt_a.parameter_eliminate : 0.000016s : 0.01% jit_opt_a.specialize_transform : 0.000096s : 0.05% jit_opt_a.updatestate_useless_node_eliminater : 0.000030s : 0.02% jit_opt_a.accelerated_algorithm : 0.000107s : 0.06% jit_opt_a.meta_shard_fg_expand : 0.000013s : 0.01% jit_opt_a.get_grad_eliminate_ : 0.000028s : 0.02% jit_opt_a.merge_forward : 0.000022s : 0.01% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000083s : 0.05% jit_opt_a.j_node_and_user_rematch : 0.000051s : 0.03% jit_opt_a.meta_fg_expand : 0.000013s : 0.01% jit_opt_a.replace_old_param : 0.000041s : 0.02% jit_opt_a.inline_without_move : 0.000060s : 0.03% jit_opt_a.renormalize : 0.002206s : 1.23% jit_opt_a.add_forward_monad_depend : 0.000047s : 0.03% jit_opt_a.auto_monad_grad : 0.000008s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000068s : 0.04% jit_opt_a.cse : 0.000205s : 0.11% jit_opt_a.replace_applicator : 0.000077s : 0.04% py_interpret_to_execute_after_opt_a : 0.000019s : 0.01% rewriter_after_opt_a : 0.000066s : 0.04% convert_after_rewriter : 0.000011s : 0.01% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000767s : 0.43% jit_opt_b.frontend_op_eliminate : 0.000021s : 0.01% jit_opt_b.inline_after_opt_a : 0.000022s : 0.01% cconv : 0.000041s : 0.02% loop_unroll : 0.000481s : 0.27% jit_opt_after_cconv.c_1 : 0.000026s : 0.01% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.01% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000004s : 0.00% jit_opt_after_cconv.cse : 0.000051s : 0.03% jit_opt_after_cconv.call_graph_tuple_transform : 0.000029s : 0.02% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000007s : 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 : 0.000006s : 0.00% remove_dup_value : 0.000078s : 0.04% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000020s : 0.01% add_recomputation : 0.000073s : 0.04% cse_after_recomputation.cse : 0.000021s : 0.01% auto_monad_reorder : 0.000029s : 0.02% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000006s : 0.00% opt_after_jit_grad : 0.000563s : 0.31% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000009s : 0.01% symbol_engine_optimizer.elim_not_effective : 0.000018s : 0.01% symbol_engine_optimizer.opt_reshape : 0.000008s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.01% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000067s : 0.04% Time group info: ------[substitution.] 0.000691 92 23.52% : 0.000163s : 11: substitution.arithmetic_simplify 2.00% : 0.000014s : 5: substitution.depend_value_elim 0.35% : 0.000002s : 3: substitution.elim_not_effective 0.25% : 0.000002s : 3: substitution.fold_const_symbol 1.11% : 0.000008s : 4: substitution.graph_param_transform 48.35% : 0.000334s : 11: substitution.inline 4.17% : 0.000029s : 2: substitution.inline_without_move 1.52% : 0.000010s : 17: substitution.j_node_and_user_rematch 8.71% : 0.000060s : 6: substitution.less_batch_normalization 0.35% : 0.000002s : 2: substitution.redundant_stop_gradient_eliminater 1.87% : 0.000013s : 17: substitution.remove_not_recompute_node 2.39% : 0.000017s : 4: substitution.replace_applicator 1.66% : 0.000012s : 3: substitution.replace_old_param 0.95% : 0.000007s : 2: substitution.set_cell_output_no_recompute 2.78% : 0.000019s : 2: substitution.specialize_transform ------[type_inference.] 0.142103 2 99.05% : 0.140746s : 1: type_inference.infer 0.95% : 0.001357s : 1: type_inference.specialize ------[replace.] 0.000127 12 6.16% : 0.000008s : 1: replace.arithmetic_simplify 9.27% : 0.000012s : 2: replace.depend_value_elim 84.57% : 0.000108s : 9: replace.inline ------[match.] 0.000330 12 1.01% : 0.000003s : 1: match.arithmetic_simplify 1.07% : 0.000004s : 2: match.depend_value_elim 97.91% : 0.000323s : 9: match.inline ------[predicate.] 0.000333 2044 1.47% : 0.000005s : 35: predicate.accumulaten_eliminater 0.68% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 1.40% : 0.000005s : 35: predicate.addn_check_dump 1.61% : 0.000005s : 35: predicate.addn_zero_filter 2.55% : 0.000008s : 36: predicate.arithmetic_simplify 1.52% : 0.000005s : 36: predicate.cast_eliminate 0.23% : 0.000001s : 4: predicate.check_bprop_eliminate 1.43% : 0.000005s : 35: predicate.compare_switch_simplify 1.55% : 0.000005s : 35: predicate.depend_value_elim 1.45% : 0.000005s : 36: predicate.dict_get_item_const_eliminator 1.54% : 0.000005s : 36: predicate.dict_get_item_eliminator 1.47% : 0.000005s : 36: predicate.dict_set_item_eliminator 0.63% : 0.000002s : 4: predicate.dumpgradient_eliminate 0.29% : 0.000001s : 4: predicate.elim_not_effective 0.28% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.55% : 0.000005s : 36: predicate.environ_add_const_eliminate 1.37% : 0.000005s : 36: predicate.environ_get_add_eliminate 1.40% : 0.000005s : 36: predicate.environ_get_depend_swap 1.49% : 0.000005s : 36: predicate.environ_get_eliminate 1.39% : 0.000005s : 36: predicate.environ_get_set_eliminate 0.11% : 0.000000s : 4: predicate.fold_const_symbol 1.24% : 0.000004s : 22: predicate.get_grad_eliminate 0.11% : 0.000000s : 4: predicate.graph_param_transform 4.50% : 0.000015s : 53: predicate.inline 1.24% : 0.000004s : 22: predicate.inline_without_move 0.53% : 0.000002s : 22: predicate.j_node_and_user_rematch 2.00% : 0.000007s : 22: predicate.less_batch_normalization 1.56% : 0.000005s : 36: predicate.list_to_tuple_eliminator_ 1.64% : 0.000005s : 40: predicate.load_eliminater 0.74% : 0.000002s : 4: predicate.loop_unroll_after_grad 2.97% : 0.000010s : 61: predicate.loop_unroll_before_grad 1.91% : 0.000006s : 40: predicate.make_slice_get_slice_eliminator 1.39% : 0.000005s : 35: predicate.merge_addn 1.42% : 0.000005s : 36: predicate.minmaximum_grad 1.38% : 0.000005s : 4: predicate.mutable_eliminate 0.30% : 0.000001s : 4: predicate.opt_reshape 2.15% : 0.000007s : 40: predicate.partial_eliminate 1.37% : 0.000005s : 33: predicate.print_const_string_wrapper 1.82% : 0.000006s : 36: predicate.reduce_eliminate 1.59% : 0.000005s : 36: predicate.redundant_stop_gradient_eliminater 0.74% : 0.000002s : 22: predicate.remove_not_recompute_node 1.75% : 0.000006s : 56: predicate.replace_applicator 0.76% : 0.000003s : 22: predicate.replace_old_param 0.25% : 0.000001s : 4: predicate.reset_defer_inline 1.50% : 0.000005s : 36: predicate.reshape_eliminate 1.37% : 0.000005s : 33: predicate.row_tensor_add_zeros_like 0.47% : 0.000002s : 4: predicate.row_tensor_eliminate 1.80% : 0.000006s : 33: predicate.same_eliminate 0.75% : 0.000003s : 22: predicate.set_cell_output_no_recompute 0.68% : 0.000002s : 8: predicate.special_op_eliminate 1.84% : 0.000006s : 22: predicate.specialize_transform 1.46% : 0.000005s : 33: predicate.split_environ_get_set_with_tuple_value 1.37% : 0.000005s : 33: predicate.stack_unstack_eliminate 0.24% : 0.000001s : 4: predicate.switch_call_monad_eliminater 2.40% : 0.000008s : 45: predicate.switch_defer_inline 2.06% : 0.000007s : 45: predicate.switch_layer_defer_inline 5.81% : 0.000019s : 110: predicate.switch_simplify 1.46% : 0.000005s : 36: predicate.tile_eliminate 1.53% : 0.000005s : 36: predicate.transpose_eliminate 1.69% : 0.000006s : 36: predicate.tuple_list_convert_item_index_to_positive 1.55% : 0.000005s : 36: predicate.tuple_list_get_item_depend_reorder 3.19% : 0.000011s : 44: predicate.tuple_list_get_item_eliminator 1.76% : 0.000006s : 36: predicate.tuple_list_set_item_eliminator 1.50% : 0.000005s : 36: predicate.tuple_to_list_eliminator_ 1.60% : 0.000005s : 40: predicate.updatestate_pure_node_eliminater 2.91% : 0.000010s : 62: predicate.updatestate_useless_node_eliminater 1.76% : 0.000006s : 33: predicate.value_based_eliminate 0.18% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.40% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001048 18 34.42% : 0.000361s : 4: func_graph_cloner_run.FuncGraphClonerGraph 65.58% : 0.000687s : 14: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.192935 87 0.04% : 0.000076s : 1: add_recomputation 0.08% : 0.000154s : 1: auto_monad 0.02% : 0.000032s : 1: auto_monad_reorder 0.34% : 0.000646s : 1: bootstrap 0.02% : 0.000044s : 1: cconv 0.01% : 0.000014s : 1: convert_after_rewriter 0.02% : 0.000040s : 1: cse_after_recomputation 0.01% : 0.000023s : 1: environ_conv 0.03% : 0.000058s : 1: event_method 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.01% : 0.000012s : 1: graph_reusing 21.85% : 0.042161s : 1: jit_opt_a 0.11% : 0.000216s : 1: jit_opt_after_cconv 0.04% : 0.000072s : 1: jit_opt_b 0.25% : 0.000489s : 1: loop_unroll 0.40% : 0.000779s : 1: mutable_eliminate 1.27% : 0.002452s : 39: opt.transform.jit_opt_a 0.03% : 0.000064s : 4: opt.transform.jit_opt_after_cconv 0.02% : 0.000034s : 4: opt.transform.jit_opt_b 0.01% : 0.000017s : 1: opt.transform.loop_unroll_optimizer 0.01% : 0.000025s : 1: opt.transform.mutable_eliminate 0.02% : 0.000032s : 1: opt.transform.opt_after_jit_grad 0.02% : 0.000042s : 4: opt.transform.symbol_engine_opt 0.30% : 0.000572s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000006s : 1: partial_unused_args_eliminate 0.01% : 0.000015s : 1: pre_auto_parallel 0.02% : 0.000039s : 1: py_interpret_to_execute 0.01% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.04% : 0.000082s : 1: remove_dup_value 0.56% : 0.001085s : 2: renormalize.infer 0.57% : 0.001099s : 2: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000070s : 1: rewriter_after_opt_a 0.07% : 0.000129s : 1: rewriter_before_opt_a 0.05% : 0.000093s : 1: symbol_engine_optimizer 73.71% : 0.142212s : 1: type_inference [[3. 3. 3. ... 3. 3. 3.] [3. 3. 3. ... 3. 3. 3.] [3. 3. 3. ... 3. 3. 3.] ... [3. 3. 3. ... 3. 3. 3.] [3. 3. 3. ... 3. 3. 3.] [3. 3. 3. ... 3. 3. 3.]] . [hook] pytest_runtest_teardown:test_memory_stats_with_stream tests/st/hal/memory/test_hal_memory_ascend.py::test_memory_stats_with_stream,max_mem:18.0M =============================== 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 ================== 1 passed, 25 warnings in 60.27s (0:01:00) ===================