==================================================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/hardware/ascend/deterministic, configfile: ../../../../../../../../sault/virtual_test/virtualenv_007/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_deterministic.py [WARNING] ME(171370:281473415413552,MainProcess):2026-01-29-17:37:38.423.131 [mindspore/context.py:1334] For 'context.set_context', the parameter 'deterministic' will be deprecated and removed in a future version. Please use the api mindspore.set_deterministic() instead. . [hook] pytest_runtest_teardown:test_deterministic_uss[pynative] tests/st/hardware/ascend/deterministic/test_deterministic.py::test_deterministic_uss[pynative],max_mem:4.0M [WARNING] ME(171370:281473415413552,MainProcess):2026-01-29-17:40:05.968.89 [mindspore/context.py:1279] For 'context.set_context' in Ascend backend, the backend is already initialized, please set it before the definition of any Tensor and Parameter, and the instantiation and execution of any operation and net, otherwise the settings may not take effect. [WARNING] ME(171370:281473415413552,MainProcess):2026-01-29-17:40:05.978.90 [mindspore/context.py:1334] For 'context.set_context', the parameter 'deterministic' will be deprecated and removed in a future version. Please use the api mindspore.set_deterministic() instead. TotalTime = 1.02825, [30] [bootstrap]: 0.00192831 [type_inference]: 0.577916 [event_method]: 1.779e-05 [auto_monad]: 0.00097548 [graph_reusing]: 5.21998e-06 [pre_auto_parallel]: 5.842e-05 [py_interpret_to_execute]: 0.00023481 [rewriter_before_opt_a]: 0.00046255 [expand_dump_flag]: 3.35e-06 [jit_opt_a]: 0.442682, [2] [Cycle 1]: 0.00208102, [27] [switch_simplify]: 0.00032464 [loop_unroll]: 1.329e-05 [a_1]: 0.00037577 [with_stream_mark]: 3.857e-05 [recompute_prepare]: 7.98999e-06 [updatestate_depend_eliminate]: 5.00001e-06 [updatestate_assign_eliminate]: 3.43e-06 [updatestate_loads_eliminate]: 3.49001e-06 [parameter_eliminate]: 1.98997e-06 [specialize_transform]: 6.93e-06 [updatestate_useless_node_eliminater]: 5.99999e-06 [accelerated_algorithm]: 6.58e-06 [meta_shard_fg_expand]: 3.21999e-06 [get_grad_eliminate_]: 7.61999e-06 [merge_forward]: 5.09e-06 [cell_reuse_recompute_pass]: 1.33002e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.269e-05 [j_node_and_user_rematch]: 1.145e-05 [meta_fg_expand]: 2.68e-06 [replace_old_param]: 1.259e-05 [inline_without_move]: 6.14999e-06 [renormalize]: 0.00089242 [add_forward_monad_depend]: 6.15002e-06 [auto_monad_grad]: 2.44999e-06 [auto_monad_eliminator]: 1.592e-05 [cse]: 4.038e-05 [replace_applicator]: 1.293e-05 [Cycle 2]: 0.00038253, [27] [switch_simplify]: 7.15998e-06 [loop_unroll]: 5.96e-06 [a_1]: 0.00012162 [with_stream_mark]: 1.066e-05 [recompute_prepare]: 7.01001e-06 [updatestate_depend_eliminate]: 3.41001e-06 [updatestate_assign_eliminate]: 2.76e-06 [updatestate_loads_eliminate]: 2.32999e-06 [parameter_eliminate]: 8.70001e-07 [specialize_transform]: 6.40002e-06 [updatestate_useless_node_eliminater]: 6.03002e-06 [accelerated_algorithm]: 5.90002e-06 [meta_shard_fg_expand]: 1.27999e-06 [get_grad_eliminate_]: 5.62999e-06 [merge_forward]: 3.35e-06 [cell_reuse_recompute_pass]: 1.64998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.701e-05 [j_node_and_user_rematch]: 9.72999e-06 [meta_fg_expand]: 2.17999e-06 [replace_old_param]: 1.045e-05 [inline_without_move]: 6.59001e-06 [renormalize]: 1.00001e-07 [add_forward_monad_depend]: 1.11002e-06 [auto_monad_grad]: 8.09989e-07 [auto_monad_eliminator]: 6.66999e-06 [cse]: 1.279e-05 [replace_applicator]: 6.44999e-06 [py_interpret_to_execute_after_opt_a]: 1.526e-05 [rewriter_after_opt_a]: 0.00011642 [convert_after_rewriter]: 1.861e-05 [order_py_execute_after_rewriter]: 5.70001e-06 [mutable_eliminate]: 0.00089451 [jit_opt_b]: 6.108e-05, [1] [Cycle 1]: 5.313e-05, [2] [frontend_op_eliminate]: 2.067e-05 [inline_after_opt_a]: 1.922e-05 [cconv]: 3.08e-05 [loop_unroll]: 0.00044966 [jit_opt_after_cconv]: 0.00016436, [1] [Cycle 1]: 0.00015761, [11] [c_1]: 2.602e-05 [parameter_eliminate]: 2.44999e-06 [updatestate_depend_eliminate]: 6.56999e-06 [updatestate_assign_eliminate]: 2.82002e-06 [updatestate_loads_eliminate]: 2.54001e-06 [cse]: 2.801e-05 [call_graph_tuple_transform]: 2.242e-05 [tuple_list_get_item_eliminator]: 6.78e-06 [none_parameter_eliminate]: 1.67001e-06 [renormalize]: 5.10016e-07 [switch_simplify]: 6.65998e-06 [remove_dup_value]: 1.799e-05 [partial_unused_args_eliminate]: 2.29001e-06 [environ_conv]: 0.00022906 [add_recomputation]: 5.858e-05 [cse_after_recomputation]: 2.68e-05, [1] [Cycle 1]: 2.124e-05, [1] [cse]: 1.475e-05 [auto_monad_reorder]: 2.717e-05 [get_jit_bprop_graph]: 2.04e-06 [rewriter_after_jit_bprop_graph]: 5.56e-06 [opt_after_jit_grad]: 0.00050241 [symbol_engine_optimizer]: 7.888e-05, [1] [Cycle 1]: 7.15e-05, [6] [build]: 3.9e-06 [elim_shapecalc]: 8.65999e-06 [elim_not_effective]: 1.404e-05 [opt_reshape]: 6.86001e-06 [fold_const_symbol]: 1.053e-05 [renormalize]: 4.50003e-07 [validate]: 0.00080235 Sums bootstrap : 0.001928s : 0.33% type_inference : 0.577916s : 98.44% event_method : 0.000018s : 0.00% auto_monad : 0.000975s : 0.17% graph_reusing : 0.000005s : 0.00% pre_auto_parallel : 0.000058s : 0.01% py_interpret_to_execute : 0.000235s : 0.04% rewriter_before_opt_a : 0.000463s : 0.08% expand_dump_flag : 0.000003s : 0.00% jit_opt_a.switch_simplify : 0.000332s : 0.06% jit_opt_a.loop_unroll : 0.000019s : 0.00% jit_opt_a.a_1 : 0.000497s : 0.08% jit_opt_a.with_stream_mark : 0.000049s : 0.01% jit_opt_a.recompute_prepare : 0.000015s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000008s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000006s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_a.parameter_eliminate : 0.000003s : 0.00% jit_opt_a.specialize_transform : 0.000013s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000012s : 0.00% jit_opt_a.accelerated_algorithm : 0.000012s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000013s : 0.00% jit_opt_a.merge_forward : 0.000008s : 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 : 0.000021s : 0.00% jit_opt_a.meta_fg_expand : 0.000005s : 0.00% jit_opt_a.replace_old_param : 0.000023s : 0.00% jit_opt_a.inline_without_move : 0.000013s : 0.00% jit_opt_a.renormalize : 0.000893s : 0.15% jit_opt_a.add_forward_monad_depend : 0.000007s : 0.00% jit_opt_a.auto_monad_grad : 0.000003s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000023s : 0.00% jit_opt_a.cse : 0.000053s : 0.01% jit_opt_a.replace_applicator : 0.000019s : 0.00% py_interpret_to_execute_after_opt_a : 0.000015s : 0.00% rewriter_after_opt_a : 0.000116s : 0.02% convert_after_rewriter : 0.000019s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000895s : 0.15% jit_opt_b.frontend_op_eliminate : 0.000021s : 0.00% jit_opt_b.inline_after_opt_a : 0.000019s : 0.00% cconv : 0.000031s : 0.01% loop_unroll : 0.000450s : 0.08% jit_opt_after_cconv.c_1 : 0.000026s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000003s : 0.00% jit_opt_after_cconv.cse : 0.000028s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000022s : 0.00% 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 : 0.000007s : 0.00% remove_dup_value : 0.000018s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000229s : 0.04% add_recomputation : 0.000059s : 0.01% cse_after_recomputation.cse : 0.000015s : 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 : 0.000502s : 0.09% symbol_engine_optimizer.build : 0.000004s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000009s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000014s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000007s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000802s : 0.14% Time group info: ------[substitution.] 0.000147 21 1.21% : 0.000002s : 2: substitution.elim_not_effective 1.11% : 0.000002s : 2: substitution.fold_const_symbol 3.99% : 0.000006s : 4: substitution.graph_param_transform 81.71% : 0.000120s : 1: substitution.inline 2.74% : 0.000004s : 4: substitution.j_node_and_user_rematch 4.97% : 0.000007s : 4: substitution.remove_not_recompute_node 4.27% : 0.000006s : 4: substitution.replace_old_param ------[type_inference.] 0.577566 2 99.53% : 0.574838s : 1: type_inference.infer 0.47% : 0.002729s : 1: type_inference.specialize ------[replace.] 0.000020 1 100.00% : 0.000020s : 1: replace.inline ------[match.] 0.000119 1 100.00% : 0.000119s : 1: match.inline ------[predicate.] 0.000119 614 2.49% : 0.000003s : 9: predicate.accumulaten_eliminater 1.19% : 0.000001s : 4: predicate.ad_related_special_op_eliminate 0.89% : 0.000001s : 9: predicate.addn_check_dump 1.21% : 0.000001s : 9: predicate.addn_zero_filter 2.87% : 0.000003s : 9: predicate.arithmetic_simplify 0.99% : 0.000001s : 9: predicate.cast_eliminate 0.56% : 0.000001s : 4: predicate.check_bprop_eliminate 1.19% : 0.000001s : 9: predicate.compare_switch_simplify 1.07% : 0.000001s : 9: predicate.depend_value_elim 0.92% : 0.000001s : 9: predicate.dict_get_item_const_eliminator 1.36% : 0.000002s : 9: predicate.dict_get_item_eliminator 1.26% : 0.000002s : 9: predicate.dict_set_item_eliminator 1.01% : 0.000001s : 4: predicate.dumpgradient_eliminate 0.45% : 0.000001s : 4: predicate.elim_not_effective 0.69% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 0.95% : 0.000001s : 9: predicate.environ_add_const_eliminate 1.88% : 0.000002s : 9: predicate.environ_get_add_eliminate 0.89% : 0.000001s : 9: predicate.environ_get_depend_swap 0.96% : 0.000001s : 9: predicate.environ_get_eliminate 0.89% : 0.000001s : 9: predicate.environ_get_set_eliminate 0.43% : 0.000001s : 4: predicate.fold_const_symbol 2.08% : 0.000002s : 8: predicate.get_grad_eliminate 0.33% : 0.000000s : 4: predicate.graph_param_transform 5.16% : 0.000006s : 18: predicate.inline 1.21% : 0.000001s : 8: predicate.inline_without_move 0.53% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.28% : 0.000002s : 8: predicate.less_batch_normalization 1.03% : 0.000001s : 9: predicate.list_to_tuple_eliminator_ 2.60% : 0.000003s : 13: predicate.load_eliminater 1.74% : 0.000002s : 4: predicate.loop_unroll_after_grad 2.59% : 0.000003s : 13: predicate.loop_unroll_before_grad 1.80% : 0.000002s : 13: predicate.make_slice_get_slice_eliminator 1.03% : 0.000001s : 9: predicate.merge_addn 0.91% : 0.000001s : 9: predicate.minmaximum_grad 2.03% : 0.000002s : 4: predicate.mutable_eliminate 0.58% : 0.000001s : 4: predicate.opt_reshape 1.88% : 0.000002s : 13: predicate.partial_eliminate 1.11% : 0.000001s : 9: predicate.print_const_string_wrapper 1.50% : 0.000002s : 9: predicate.reduce_eliminate 1.05% : 0.000001s : 9: predicate.redundant_stop_gradient_eliminater 0.93% : 0.000001s : 8: predicate.remove_not_recompute_node 1.57% : 0.000002s : 17: predicate.replace_applicator 0.86% : 0.000001s : 8: predicate.replace_old_param 0.59% : 0.000001s : 4: predicate.reset_defer_inline 1.10% : 0.000001s : 9: predicate.reshape_eliminate 1.63% : 0.000002s : 9: predicate.row_tensor_add_zeros_like 0.94% : 0.000001s : 4: predicate.row_tensor_eliminate 0.90% : 0.000001s : 9: predicate.same_eliminate 0.89% : 0.000001s : 8: predicate.set_cell_output_no_recompute 1.71% : 0.000002s : 8: predicate.special_op_eliminate 1.19% : 0.000001s : 8: predicate.specialize_transform 1.40% : 0.000002s : 9: predicate.split_environ_get_set_with_tuple_value 2.34% : 0.000003s : 9: predicate.stack_unstack_eliminate 0.57% : 0.000001s : 4: predicate.switch_call_monad_eliminater 1.35% : 0.000002s : 10: predicate.switch_defer_inline 1.22% : 0.000001s : 10: predicate.switch_layer_defer_inline 6.37% : 0.000008s : 27: predicate.switch_simplify 1.03% : 0.000001s : 9: predicate.tile_eliminate 1.31% : 0.000002s : 9: predicate.transpose_eliminate 1.42% : 0.000002s : 9: predicate.tuple_list_convert_item_index_to_positive 1.36% : 0.000002s : 9: predicate.tuple_list_get_item_depend_reorder 3.50% : 0.000004s : 17: predicate.tuple_list_get_item_eliminator 1.67% : 0.000002s : 9: predicate.tuple_list_set_item_eliminator 1.05% : 0.000001s : 9: predicate.tuple_to_list_eliminator_ 1.68% : 0.000002s : 13: predicate.updatestate_pure_node_eliminater 3.33% : 0.000004s : 21: predicate.updatestate_useless_node_eliminater 1.80% : 0.000002s : 9: predicate.value_based_eliminate 0.94% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.76% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.001525 4 1.39% : 0.000021s : 1: func_graph_cloner_run.FuncGraphClonerGraph 98.61% : 0.001504s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 1.028965 72 0.01% : 0.000061s : 1: add_recomputation 0.10% : 0.000981s : 1: auto_monad 0.00% : 0.000030s : 1: auto_monad_reorder 0.19% : 0.001966s : 1: bootstrap 0.00% : 0.000034s : 1: cconv 0.00% : 0.000021s : 1: convert_after_rewriter 0.00% : 0.000029s : 1: cse_after_recomputation 0.02% : 0.000233s : 1: environ_conv 0.00% : 0.000024s : 1: event_method 0.00% : 0.000008s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000008s : 1: graph_reusing 43.02% : 0.442686s : 1: jit_opt_a 0.02% : 0.000167s : 1: jit_opt_after_cconv 0.01% : 0.000064s : 1: jit_opt_b 0.04% : 0.000458s : 1: loop_unroll 0.09% : 0.000903s : 1: mutable_eliminate 0.07% : 0.000718s : 26: opt.transform.jit_opt_a 0.01% : 0.000058s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000033s : 4: opt.transform.jit_opt_b 0.00% : 0.000013s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000017s : 1: opt.transform.mutable_eliminate 0.00% : 0.000024s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000037s : 4: opt.transform.symbol_engine_opt 0.05% : 0.000509s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.01% : 0.000061s : 1: pre_auto_parallel 0.02% : 0.000240s : 1: py_interpret_to_execute 0.00% : 0.000018s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000020s : 1: remove_dup_value 0.05% : 0.000487s : 1: renormalize.infer 0.04% : 0.000397s : 1: renormalize.specialize 0.00% : 0.000008s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000120s : 1: rewriter_after_opt_a 0.05% : 0.000473s : 1: rewriter_before_opt_a 0.01% : 0.000081s : 1: symbol_engine_optimizer 56.17% : 0.577962s : 1: type_inference . [hook] pytest_runtest_teardown:test_deterministic_uss[jit] tests/st/hardware/ascend/deterministic/test_deterministic.py::test_deterministic_uss[jit],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") test_deterministic.py::test_deterministic_uss[pynative] /usr/local/Ascend/cann-8.5.0/python/site-packages/asc_op_compile_base/asc_op_compiler/ascendc_compile_gen_code.py:161: DeprecationWarning: invalid escape sequence \w match = re.search(f'{option}=(\w+)', ' '.join(compile_options)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 26 warnings in 200.41s (0:03:20) ==================