==================================================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_004/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(171595:281473888202544,MainProcess):2026-01-29-17:37:35.604.579 [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_reduce_matmul[pynative] tests/st/hardware/ascend/deterministic/test_deterministic.py::test_deterministic_reduce_matmul[pynative],max_mem:130.0M [WARNING] ME(171595:281473888202544,MainProcess):2026-01-29-17:40:48.819.458 [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(171595:281473888202544,MainProcess):2026-01-29-17:40:48.820.643 [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 = 2.68392, [30] [bootstrap]: 0.00174445 [type_inference]: 2.37455 [event_method]: 1.909e-05 [auto_monad]: 0.00049731 [graph_reusing]: 7.74002e-06 [pre_auto_parallel]: 1.482e-05 [py_interpret_to_execute]: 0.00063925 [rewriter_before_opt_a]: 8.467e-05 [expand_dump_flag]: 4.15e-06 [jit_opt_a]: 0.138028, [2] [Cycle 1]: 0.00605933, [27] [switch_simplify]: 0.00011633 [loop_unroll]: 2.068e-05 [a_1]: 0.00060799 [with_stream_mark]: 3.613e-05 [recompute_prepare]: 2.456e-05 [updatestate_depend_eliminate]: 1.196e-05 [updatestate_assign_eliminate]: 8.49998e-06 [updatestate_loads_eliminate]: 1.193e-05 [parameter_eliminate]: 1.97999e-06 [specialize_transform]: 1.694e-05 [updatestate_useless_node_eliminater]: 2.163e-05 [accelerated_algorithm]: 8.554e-05 [meta_shard_fg_expand]: 4.37e-06 [get_grad_eliminate_]: 1.718e-05 [merge_forward]: 8.65001e-06 [cell_reuse_recompute_pass]: 2.39001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.515e-05 [j_node_and_user_rematch]: 2.35e-05 [meta_fg_expand]: 5.49998e-06 [replace_old_param]: 2.17e-05 [inline_without_move]: 1.434e-05 [renormalize]: 0.00444051 [add_forward_monad_depend]: 1.765e-05 [auto_monad_grad]: 3.19001e-06 [auto_monad_eliminator]: 5.85e-05 [cse]: 0.00014347 [replace_applicator]: 3.874e-05 [Cycle 2]: 0.00096156, [27] [switch_simplify]: 1.55e-05 [loop_unroll]: 1.405e-05 [a_1]: 0.00037915 [with_stream_mark]: 2.632e-05 [recompute_prepare]: 1.658e-05 [updatestate_depend_eliminate]: 9.09e-06 [updatestate_assign_eliminate]: 7.75e-06 [updatestate_loads_eliminate]: 1.013e-05 [parameter_eliminate]: 2.61999e-06 [specialize_transform]: 1.466e-05 [updatestate_useless_node_eliminater]: 1.859e-05 [accelerated_algorithm]: 2.128e-05 [meta_shard_fg_expand]: 4.61002e-06 [get_grad_eliminate_]: 1.313e-05 [merge_forward]: 9.08002e-06 [cell_reuse_recompute_pass]: 3.63999e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.153e-05 [j_node_and_user_rematch]: 2.323e-05 [meta_fg_expand]: 5.61998e-06 [replace_old_param]: 1.921e-05 [inline_without_move]: 1.34e-05 [renormalize]: 9.00181e-08 [add_forward_monad_depend]: 4.05e-06 [auto_monad_grad]: 2.24999e-06 [auto_monad_eliminator]: 4.653e-05 [cse]: 7.093e-05 [replace_applicator]: 1.922e-05 [py_interpret_to_execute_after_opt_a]: 2.757e-05 [rewriter_after_opt_a]: 0.00021956 [convert_after_rewriter]: 1.812e-05 [order_py_execute_after_rewriter]: 9.96e-06 [mutable_eliminate]: 0.00083687 [jit_opt_b]: 0.00010873, [1] [Cycle 1]: 9.928e-05, [2] [frontend_op_eliminate]: 4.527e-05 [inline_after_opt_a]: 3.997e-05 [cconv]: 4.323e-05 [loop_unroll]: 0.00050601 [jit_opt_after_cconv]: 0.00037248, [1] [Cycle 1]: 0.00036421, [11] [c_1]: 9.142e-05 [parameter_eliminate]: 5.42999e-06 [updatestate_depend_eliminate]: 1.836e-05 [updatestate_assign_eliminate]: 7.6e-06 [updatestate_loads_eliminate]: 1.089e-05 [cse]: 8.225e-05 [call_graph_tuple_transform]: 5.311e-05 [tuple_list_get_item_eliminator]: 1.492e-05 [none_parameter_eliminate]: 2.27001e-06 [renormalize]: 3.80009e-07 [switch_simplify]: 1.453e-05 [remove_dup_value]: 8.303e-05 [partial_unused_args_eliminate]: 2.73e-06 [environ_conv]: 6.659e-05 [add_recomputation]: 0.00011866 [cse_after_recomputation]: 5.507e-05, [1] [Cycle 1]: 4.8e-05, [1] [cse]: 3.884e-05 [auto_monad_reorder]: 5.315e-05 [get_jit_bprop_graph]: 2.37999e-06 [rewriter_after_jit_bprop_graph]: 6.73e-06 [opt_after_jit_grad]: 0.165031 [symbol_engine_optimizer]: 0.00016476, [1] [Cycle 1]: 0.00015162, [6] [build]: 1.431e-05 [elim_shapecalc]: 3.666e-05 [elim_not_effective]: 2.616e-05 [opt_reshape]: 1.594e-05 [fold_const_symbol]: 2.357e-05 [renormalize]: 6.39993e-07 [validate]: 0.00024954 Sums bootstrap : 0.001744s : 0.07% type_inference : 2.374550s : 93.05% event_method : 0.000019s : 0.00% auto_monad : 0.000497s : 0.02% graph_reusing : 0.000008s : 0.00% pre_auto_parallel : 0.000015s : 0.00% py_interpret_to_execute : 0.000639s : 0.03% rewriter_before_opt_a : 0.000085s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000132s : 0.01% jit_opt_a.loop_unroll : 0.000035s : 0.00% jit_opt_a.a_1 : 0.000987s : 0.04% jit_opt_a.with_stream_mark : 0.000062s : 0.00% jit_opt_a.recompute_prepare : 0.000041s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000021s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000016s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000022s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000032s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000040s : 0.00% jit_opt_a.accelerated_algorithm : 0.000107s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000009s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000030s : 0.00% jit_opt_a.merge_forward : 0.000018s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000006s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000067s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000047s : 0.00% jit_opt_a.meta_fg_expand : 0.000011s : 0.00% jit_opt_a.replace_old_param : 0.000041s : 0.00% jit_opt_a.inline_without_move : 0.000028s : 0.00% jit_opt_a.renormalize : 0.004441s : 0.17% jit_opt_a.add_forward_monad_depend : 0.000022s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000105s : 0.00% jit_opt_a.cse : 0.000214s : 0.01% jit_opt_a.replace_applicator : 0.000058s : 0.00% py_interpret_to_execute_after_opt_a : 0.000028s : 0.00% rewriter_after_opt_a : 0.000220s : 0.01% convert_after_rewriter : 0.000018s : 0.00% order_py_execute_after_rewriter : 0.000010s : 0.00% mutable_eliminate : 0.000837s : 0.03% jit_opt_b.frontend_op_eliminate : 0.000045s : 0.00% jit_opt_b.inline_after_opt_a : 0.000040s : 0.00% cconv : 0.000043s : 0.00% loop_unroll : 0.000506s : 0.02% jit_opt_after_cconv.c_1 : 0.000091s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000018s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000008s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000011s : 0.00% jit_opt_after_cconv.cse : 0.000082s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000053s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000015s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000015s : 0.00% remove_dup_value : 0.000083s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000067s : 0.00% add_recomputation : 0.000119s : 0.00% cse_after_recomputation.cse : 0.000039s : 0.00% auto_monad_reorder : 0.000053s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.165031s : 6.47% symbol_engine_optimizer.build : 0.000014s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000037s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000026s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000016s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000024s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000250s : 0.01% Time group info: ------[substitution.] 0.000332 78 3.51% : 0.000012s : 2: substitution.depend_value_elim 1.13% : 0.000004s : 7: substitution.elim_not_effective 0.66% : 0.000002s : 1: substitution.elim_shapecalc_of_broadcastargs 1.00% : 0.000003s : 7: substitution.fold_const_symbol 7.09% : 0.000024s : 11: substitution.graph_param_transform 42.66% : 0.000142s : 1: substitution.inline 2.33% : 0.000008s : 14: substitution.j_node_and_user_rematch 20.46% : 0.000068s : 2: substitution.less_batch_normalization 1.23% : 0.000004s : 3: substitution.load_eliminater 4.71% : 0.000016s : 4: substitution.reduce_eliminate 3.78% : 0.000013s : 14: substitution.remove_not_recompute_node 2.68% : 0.000009s : 4: substitution.replace_old_param 4.64% : 0.000015s : 3: substitution.updatestate_pure_node_eliminater 4.14% : 0.000014s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 2.374429 2 99.87% : 2.371458s : 1: type_inference.infer 0.13% : 0.002971s : 1: type_inference.specialize ------[replace.] 0.000020 1 100.00% : 0.000020s : 1: replace.inline ------[match.] 0.000140 1 100.00% : 0.000140s : 1: match.inline ------[predicate.] 0.000272 1587 1.13% : 0.000003s : 23: predicate.accumulaten_eliminater 3.56% : 0.000010s : 11: predicate.ad_related_special_op_eliminate 1.12% : 0.000003s : 23: predicate.addn_check_dump 1.24% : 0.000003s : 23: predicate.addn_zero_filter 1.83% : 0.000005s : 23: predicate.arithmetic_simplify 1.40% : 0.000004s : 23: predicate.cast_eliminate 0.72% : 0.000002s : 11: predicate.check_bprop_eliminate 1.16% : 0.000003s : 23: predicate.compare_switch_simplify 1.22% : 0.000003s : 23: predicate.depend_value_elim 0.96% : 0.000003s : 23: predicate.dict_get_item_const_eliminator 1.26% : 0.000003s : 23: predicate.dict_get_item_eliminator 1.35% : 0.000004s : 23: predicate.dict_set_item_eliminator 1.77% : 0.000005s : 11: predicate.dumpgradient_eliminate 0.50% : 0.000001s : 11: predicate.elim_not_effective 0.98% : 0.000003s : 11: predicate.elim_shapecalc_of_broadcastargs 1.22% : 0.000003s : 23: predicate.environ_add_const_eliminate 0.96% : 0.000003s : 23: predicate.environ_get_add_eliminate 1.05% : 0.000003s : 23: predicate.environ_get_depend_swap 1.14% : 0.000003s : 23: predicate.environ_get_eliminate 1.05% : 0.000003s : 23: predicate.environ_get_set_eliminate 0.31% : 0.000001s : 11: predicate.fold_const_symbol 1.45% : 0.000004s : 22: predicate.get_grad_eliminate 0.38% : 0.000001s : 11: predicate.graph_param_transform 4.47% : 0.000012s : 46: predicate.inline 1.40% : 0.000004s : 22: predicate.inline_without_move 0.61% : 0.000002s : 22: predicate.j_node_and_user_rematch 2.22% : 0.000006s : 22: predicate.less_batch_normalization 1.28% : 0.000003s : 23: predicate.list_to_tuple_eliminator_ 1.80% : 0.000005s : 34: predicate.load_eliminater 1.52% : 0.000004s : 11: predicate.loop_unroll_after_grad 1.71% : 0.000005s : 27: predicate.loop_unroll_before_grad 2.23% : 0.000006s : 34: predicate.make_slice_get_slice_eliminator 1.05% : 0.000003s : 23: predicate.merge_addn 1.09% : 0.000003s : 23: predicate.minmaximum_grad 2.24% : 0.000006s : 11: predicate.mutable_eliminate 0.75% : 0.000002s : 11: predicate.opt_reshape 2.07% : 0.000006s : 34: predicate.partial_eliminate 1.06% : 0.000003s : 23: predicate.print_const_string_wrapper 1.93% : 0.000005s : 23: predicate.reduce_eliminate 1.22% : 0.000003s : 23: predicate.redundant_stop_gradient_eliminater 0.87% : 0.000002s : 22: predicate.remove_not_recompute_node 2.00% : 0.000005s : 45: predicate.replace_applicator 0.95% : 0.000003s : 22: predicate.replace_old_param 0.48% : 0.000001s : 11: predicate.reset_defer_inline 1.32% : 0.000004s : 23: predicate.reshape_eliminate 1.39% : 0.000004s : 23: predicate.row_tensor_add_zeros_like 1.04% : 0.000003s : 11: predicate.row_tensor_eliminate 1.36% : 0.000004s : 23: predicate.same_eliminate 0.76% : 0.000002s : 22: predicate.set_cell_output_no_recompute 1.39% : 0.000004s : 22: predicate.special_op_eliminate 1.56% : 0.000004s : 22: predicate.specialize_transform 1.50% : 0.000004s : 23: predicate.split_environ_get_set_with_tuple_value 1.18% : 0.000003s : 23: predicate.stack_unstack_eliminate 0.60% : 0.000002s : 11: predicate.switch_call_monad_eliminater 1.59% : 0.000004s : 24: predicate.switch_defer_inline 1.29% : 0.000004s : 24: predicate.switch_layer_defer_inline 4.34% : 0.000012s : 62: predicate.switch_simplify 1.31% : 0.000004s : 23: predicate.tile_eliminate 1.31% : 0.000004s : 23: predicate.transpose_eliminate 1.38% : 0.000004s : 23: predicate.tuple_list_convert_item_index_to_positive 1.33% : 0.000004s : 23: predicate.tuple_list_get_item_depend_reorder 3.65% : 0.000010s : 45: predicate.tuple_list_get_item_eliminator 1.83% : 0.000005s : 23: predicate.tuple_list_set_item_eliminator 1.21% : 0.000003s : 23: predicate.tuple_to_list_eliminator_ 1.59% : 0.000004s : 34: predicate.updatestate_pure_node_eliminater 3.48% : 0.000009s : 56: predicate.updatestate_useless_node_eliminater 1.46% : 0.000004s : 23: predicate.value_based_eliminate 0.58% : 0.000002s : 11: predicate.virtual_view_grad_eliminate 0.84% : 0.000002s : 11: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003600 18 77.48% : 0.002789s : 15: func_graph_cloner_run.FuncGraphClonerGraph 22.52% : 0.000810s : 3: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.689994 72 0.00% : 0.000122s : 1: add_recomputation 0.02% : 0.000506s : 1: auto_monad 0.00% : 0.000056s : 1: auto_monad_reorder 0.07% : 0.001792s : 1: bootstrap 0.00% : 0.000046s : 1: cconv 0.00% : 0.000022s : 1: convert_after_rewriter 0.00% : 0.000057s : 1: cse_after_recomputation 0.00% : 0.000070s : 1: environ_conv 0.00% : 0.000024s : 1: event_method 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000011s : 1: graph_reusing 5.13% : 0.138034s : 1: jit_opt_a 0.01% : 0.000377s : 1: jit_opt_after_cconv 0.00% : 0.000112s : 1: jit_opt_b 0.02% : 0.000515s : 1: loop_unroll 0.03% : 0.000849s : 1: mutable_eliminate 0.06% : 0.001539s : 26: opt.transform.jit_opt_a 0.01% : 0.000170s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000077s : 4: opt.transform.jit_opt_b 0.00% : 0.000025s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000036s : 1: opt.transform.mutable_eliminate 0.00% : 0.000090s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000098s : 4: opt.transform.symbol_engine_opt 6.14% : 0.165057s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000017s : 1: pre_auto_parallel 0.02% : 0.000647s : 1: py_interpret_to_execute 0.00% : 0.000031s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000086s : 1: remove_dup_value 0.12% : 0.003326s : 1: renormalize.infer 0.04% : 0.001098s : 1: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000226s : 1: rewriter_after_opt_a 0.00% : 0.000090s : 1: rewriter_before_opt_a 0.01% : 0.000169s : 1: symbol_engine_optimizer 88.27% : 2.374577s : 1: type_inference . [hook] pytest_runtest_teardown:test_deterministic_reduce_matmul[jit] tests/st/hardware/ascend/deterministic/test_deterministic.py::test_deterministic_reduce_matmul[jit],max_mem:130.0M =============================== 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_reduce_matmul[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 266.13s (0:04:26) ==================