==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/mint, configfile: ../../../../../../sault/virtual_test/virtualenv_001/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 10 items test_reshape.py . [hook] pytest_runtest_teardown:test_reshape_special_values[inf-pynative] tests/st/mint/test_reshape.py::test_reshape_special_values[inf-pynative],max_mem:2.0M [WARNING] PARSER(170636,ffff99be6f30,python3.9):2026-01-29-17:40:27.667.602 [mindspore/ccsrc/frontend/jit/ps/parse/data_converter.cc:661] CheckAPI] The mint interface reshape was called, and the operators under this interface have different view capabilities on pynative and graph mode. Use this interface with caution in graph mode, as it may produce unexpected results. For more information, please refer to: https://www.mindspore.cn/docs/en/master/features/view.html TotalTime = 6.18899, [33] [bootstrap]: 0.00088883 [type_inference]: 1.43242 [event_method]: 2.482e-05 [auto_monad]: 0.00012306 [graph_reusing]: 6.64999e-06 [pre_auto_parallel]: 1.294e-05 [py_interpret_to_execute]: 0.00071812 [rewriter_before_opt_a]: 0.00016215 [expand_dump_flag]: 5.34e-06 [jit_opt_a]: 0.239859, [2] [Cycle 1]: 0.00420613, [27] [switch_simplify]: 8.239e-05 [loop_unroll]: 3.286e-05 [a_1]: 0.00067327 [with_stream_mark]: 3.318e-05 [recompute_prepare]: 1.012e-05 [updatestate_depend_eliminate]: 5.07999e-06 [updatestate_assign_eliminate]: 3.64002e-06 [updatestate_loads_eliminate]: 3.23e-06 [parameter_eliminate]: 2.13002e-06 [specialize_transform]: 7.07997e-06 [updatestate_useless_node_eliminater]: 6.12999e-06 [accelerated_algorithm]: 7.53999e-06 [meta_shard_fg_expand]: 2.43998e-06 [get_grad_eliminate_]: 6.39001e-06 [merge_forward]: 5.49998e-06 [cell_reuse_recompute_pass]: 1.12e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.263e-05 [j_node_and_user_rematch]: 1.158e-05 [meta_fg_expand]: 3.25002e-06 [replace_old_param]: 1.129e-05 [inline_without_move]: 6.71e-06 [renormalize]: 0.00291781 [add_forward_monad_depend]: 1.597e-05 [auto_monad_grad]: 3.48e-06 [auto_monad_eliminator]: 1.913e-05 [cse]: 4.916e-05 [replace_applicator]: 2e-05 [Cycle 2]: 0.0004132, [27] [switch_simplify]: 7.15998e-06 [loop_unroll]: 5.91e-06 [a_1]: 0.00014296 [with_stream_mark]: 1.566e-05 [recompute_prepare]: 6.66e-06 [updatestate_depend_eliminate]: 3.83001e-06 [updatestate_assign_eliminate]: 2.97002e-06 [updatestate_loads_eliminate]: 2.94001e-06 [parameter_eliminate]: 1.44e-06 [specialize_transform]: 6.12999e-06 [updatestate_useless_node_eliminater]: 5.87001e-06 [accelerated_algorithm]: 6.23e-06 [meta_shard_fg_expand]: 1.60999e-06 [get_grad_eliminate_]: 5.40001e-06 [merge_forward]: 4.71002e-06 [cell_reuse_recompute_pass]: 2.51998e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.414e-05 [j_node_and_user_rematch]: 1.009e-05 [meta_fg_expand]: 2.43e-06 [replace_old_param]: 9.19e-06 [inline_without_move]: 5.86e-06 [renormalize]: 7.00238e-08 [add_forward_monad_depend]: 1.12e-06 [auto_monad_grad]: 8.90024e-07 [auto_monad_eliminator]: 6.29001e-06 [cse]: 1.439e-05 [replace_applicator]: 6.53998e-06 [py_interpret_to_execute_after_opt_a]: 1.328e-05 [rewriter_after_opt_a]: 0.00011508 [convert_after_rewriter]: 9.79999e-06 [order_py_execute_after_rewriter]: 5.89e-06 [mutable_eliminate]: 0.00078078 [jit_opt_b]: 6.024e-05, [1] [Cycle 1]: 5.064e-05, [2] [frontend_op_eliminate]: 2.008e-05 [inline_after_opt_a]: 1.886e-05 [cconv]: 3.321e-05 [loop_unroll]: 0.0005302 [jit_opt_after_cconv]: 0.0002051, [1] [Cycle 1]: 0.00019693, [11] [c_1]: 2.79e-05 [parameter_eliminate]: 5.77999e-06 [updatestate_depend_eliminate]: 1.137e-05 [updatestate_assign_eliminate]: 4.44002e-06 [updatestate_loads_eliminate]: 3.06999e-06 [cse]: 3.645e-05 [call_graph_tuple_transform]: 3.049e-05 [tuple_list_get_item_eliminator]: 8.15e-06 [none_parameter_eliminate]: 2.24001e-06 [renormalize]: 7.80012e-07 [switch_simplify]: 8.10999e-06 [remove_dup_value]: 2.038e-05 [partial_unused_args_eliminate]: 2.76999e-06 [environ_conv]: 3.092e-05 [add_recomputation]: 7.399e-05 [cse_after_recomputation]: 2.925e-05, [1] [Cycle 1]: 2.27e-05, [1] [cse]: 1.49e-05 [auto_monad_reorder]: 2.886e-05 [get_jit_bprop_graph]: 3.62002e-06 [rewriter_after_jit_bprop_graph]: 0.00024176 [opt_after_jit_grad]: 0.00068082 [symbol_engine_optimizer]: 9.86e-05, [1] [Cycle 1]: 9.012e-05, [6] [build]: 5.91e-06 [elim_shapecalc]: 9.71e-06 [elim_not_effective]: 1.892e-05 [opt_reshape]: 1.18e-05 [fold_const_symbol]: 1.129e-05 [renormalize]: 3.00002e-07 [validate]: 7.853e-05 [backend_pass]: 1.06002e-06 [task_emit]: 4.51132 [execute]: 1.132e-05 Sums bootstrap : 0.000889s : 0.01% type_inference : 1.432417s : 24.06% event_method : 0.000025s : 0.00% auto_monad : 0.000123s : 0.00% graph_reusing : 0.000007s : 0.00% pre_auto_parallel : 0.000013s : 0.00% py_interpret_to_execute : 0.000718s : 0.01% rewriter_before_opt_a : 0.000162s : 0.00% expand_dump_flag : 0.000005s : 0.00% jit_opt_a.switch_simplify : 0.000090s : 0.00% jit_opt_a.loop_unroll : 0.000039s : 0.00% jit_opt_a.a_1 : 0.000816s : 0.01% jit_opt_a.with_stream_mark : 0.000049s : 0.00% jit_opt_a.recompute_prepare : 0.000017s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000009s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 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 : 0.000014s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000004s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000012s : 0.00% jit_opt_a.merge_forward : 0.000010s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000004s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000037s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000022s : 0.00% jit_opt_a.meta_fg_expand : 0.000006s : 0.00% jit_opt_a.replace_old_param : 0.000020s : 0.00% jit_opt_a.inline_without_move : 0.000013s : 0.00% jit_opt_a.renormalize : 0.002918s : 0.05% jit_opt_a.add_forward_monad_depend : 0.000017s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000025s : 0.00% jit_opt_a.cse : 0.000064s : 0.00% jit_opt_a.replace_applicator : 0.000027s : 0.00% py_interpret_to_execute_after_opt_a : 0.000013s : 0.00% rewriter_after_opt_a : 0.000115s : 0.00% convert_after_rewriter : 0.000010s : 0.00% order_py_execute_after_rewriter : 0.000006s : 0.00% mutable_eliminate : 0.000781s : 0.01% jit_opt_b.frontend_op_eliminate : 0.000020s : 0.00% jit_opt_b.inline_after_opt_a : 0.000019s : 0.00% cconv : 0.000033s : 0.00% loop_unroll : 0.000530s : 0.01% jit_opt_after_cconv.c_1 : 0.000028s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000011s : 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 : 0.000036s : 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 : 0.000008s : 0.00% remove_dup_value : 0.000020s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000031s : 0.00% add_recomputation : 0.000074s : 0.00% cse_after_recomputation.cse : 0.000015s : 0.00% auto_monad_reorder : 0.000029s : 0.00% get_jit_bprop_graph : 0.000004s : 0.00% rewriter_after_jit_bprop_graph : 0.000242s : 0.00% opt_after_jit_grad : 0.000681s : 0.01% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000010s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000019s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000012s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000011s : 0.00% symbol_engine_optimizer.renormalize : 0.000000s : 0.00% validate : 0.000079s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 4.511325s : 75.78% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.000277 28 1.14% : 0.000003s : 2: substitution.elim_not_effective 0.90% : 0.000003s : 2: substitution.fold_const_symbol 2.50% : 0.000007s : 4: substitution.graph_param_transform 77.21% : 0.000214s : 5: substitution.inline 1.79% : 0.000005s : 4: substitution.j_node_and_user_rematch 0.57% : 0.000002s : 1: substitution.opt_reshape 1.96% : 0.000005s : 4: substitution.remove_not_recompute_node 1.94% : 0.000005s : 2: substitution.replace_old_param 8.76% : 0.000024s : 3: substitution.reshape_eliminate 3.23% : 0.000009s : 1: substitution.tuple_list_get_item_eliminator ------[type_inference.] 1.432300 2 99.84% : 1.430038s : 1: type_inference.infer 0.16% : 0.002262s : 1: type_inference.specialize ------[replace.] 0.000063 6 83.28% : 0.000053s : 5: replace.inline 16.72% : 0.000011s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000219 6 96.23% : 0.000210s : 5: match.inline 3.77% : 0.000008s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000158 867 1.32% : 0.000002s : 13: predicate.accumulaten_eliminater 1.48% : 0.000002s : 4: predicate.ad_related_special_op_eliminate 1.10% : 0.000002s : 13: predicate.addn_check_dump 1.30% : 0.000002s : 13: predicate.addn_zero_filter 2.15% : 0.000003s : 13: predicate.arithmetic_simplify 1.43% : 0.000002s : 13: predicate.cast_eliminate 0.34% : 0.000001s : 4: predicate.check_bprop_eliminate 1.14% : 0.000002s : 13: predicate.compare_switch_simplify 1.26% : 0.000002s : 13: predicate.depend_value_elim 1.14% : 0.000002s : 13: predicate.dict_get_item_const_eliminator 1.08% : 0.000002s : 13: predicate.dict_get_item_eliminator 1.12% : 0.000002s : 13: predicate.dict_set_item_eliminator 1.26% : 0.000002s : 4: predicate.dumpgradient_eliminate 0.65% : 0.000001s : 4: predicate.elim_not_effective 0.61% : 0.000001s : 4: predicate.elim_shapecalc_of_broadcastargs 1.26% : 0.000002s : 13: predicate.environ_add_const_eliminate 1.02% : 0.000002s : 13: predicate.environ_get_add_eliminate 1.04% : 0.000002s : 13: predicate.environ_get_depend_swap 1.32% : 0.000002s : 13: predicate.environ_get_eliminate 1.02% : 0.000002s : 13: predicate.environ_get_set_eliminate 0.27% : 0.000000s : 4: predicate.fold_const_symbol 0.99% : 0.000002s : 8: predicate.get_grad_eliminate 0.35% : 0.000001s : 4: predicate.graph_param_transform 5.53% : 0.000009s : 27: predicate.inline 0.78% : 0.000001s : 8: predicate.inline_without_move 0.43% : 0.000001s : 8: predicate.j_node_and_user_rematch 1.22% : 0.000002s : 8: predicate.less_batch_normalization 1.46% : 0.000002s : 14: predicate.list_to_tuple_eliminator_ 1.77% : 0.000003s : 18: predicate.load_eliminater 1.56% : 0.000002s : 4: predicate.loop_unroll_after_grad 3.49% : 0.000006s : 37: predicate.loop_unroll_before_grad 2.27% : 0.000004s : 17: predicate.make_slice_get_slice_eliminator 1.19% : 0.000002s : 13: predicate.merge_addn 1.04% : 0.000002s : 13: predicate.minmaximum_grad 1.67% : 0.000003s : 4: predicate.mutable_eliminate 0.68% : 0.000001s : 4: predicate.opt_reshape 1.91% : 0.000003s : 18: predicate.partial_eliminate 1.13% : 0.000002s : 13: predicate.print_const_string_wrapper 1.74% : 0.000003s : 13: predicate.reduce_eliminate 1.54% : 0.000002s : 14: predicate.redundant_stop_gradient_eliminater 0.42% : 0.000001s : 8: predicate.remove_not_recompute_node 1.86% : 0.000003s : 22: predicate.replace_applicator 0.49% : 0.000001s : 8: predicate.replace_old_param 0.30% : 0.000000s : 4: predicate.reset_defer_inline 1.80% : 0.000003s : 13: predicate.reshape_eliminate 1.47% : 0.000002s : 13: predicate.row_tensor_add_zeros_like 0.79% : 0.000001s : 4: predicate.row_tensor_eliminate 1.52% : 0.000002s : 13: predicate.same_eliminate 0.61% : 0.000001s : 8: predicate.set_cell_output_no_recompute 0.98% : 0.000002s : 8: predicate.special_op_eliminate 0.92% : 0.000001s : 8: predicate.specialize_transform 1.57% : 0.000002s : 13: predicate.split_environ_get_set_with_tuple_value 1.26% : 0.000002s : 13: predicate.stack_unstack_eliminate 0.39% : 0.000001s : 4: predicate.switch_call_monad_eliminater 2.25% : 0.000004s : 19: predicate.switch_defer_inline 2.33% : 0.000004s : 19: predicate.switch_layer_defer_inline 7.09% : 0.000011s : 60: predicate.switch_simplify 1.28% : 0.000002s : 13: predicate.tile_eliminate 1.19% : 0.000002s : 13: predicate.transpose_eliminate 1.62% : 0.000003s : 13: predicate.tuple_list_convert_item_index_to_positive 1.41% : 0.000002s : 13: predicate.tuple_list_get_item_depend_reorder 4.18% : 0.000007s : 22: predicate.tuple_list_get_item_eliminator 1.71% : 0.000003s : 13: predicate.tuple_list_set_item_eliminator 1.36% : 0.000002s : 14: predicate.tuple_to_list_eliminator_ 1.71% : 0.000003s : 18: predicate.updatestate_pure_node_eliminater 2.87% : 0.000005s : 26: predicate.updatestate_useless_node_eliminater 1.60% : 0.000003s : 13: predicate.value_based_eliminate 0.40% : 0.000001s : 4: predicate.virtual_view_grad_eliminate 0.58% : 0.000001s : 4: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.151190 23 99.43% : 0.150324s : 16: func_graph_cloner_run.FuncGraphClonerGraph 0.57% : 0.000866s : 7: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 6.193041 76 0.00% : 0.000077s : 1: add_recomputation 0.00% : 0.000127s : 1: auto_monad 0.00% : 0.000032s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.01% : 0.000912s : 1: bootstrap 0.00% : 0.000036s : 1: cconv 0.00% : 0.000012s : 1: convert_after_rewriter 0.00% : 0.000032s : 1: cse_after_recomputation 0.00% : 0.000034s : 1: environ_conv 0.00% : 0.000030s : 1: event_method 0.00% : 0.000018s : 1: execute 0.00% : 0.000009s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 3.87% : 0.239863s : 1: jit_opt_a 0.00% : 0.000208s : 1: jit_opt_after_cconv 0.00% : 0.000063s : 1: jit_opt_b 0.01% : 0.000541s : 1: loop_unroll 0.01% : 0.000792s : 1: mutable_eliminate 0.02% : 0.001080s : 26: opt.transform.jit_opt_a 0.00% : 0.000070s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000032s : 4: opt.transform.jit_opt_b 0.00% : 0.000016s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000018s : 1: opt.transform.mutable_eliminate 0.00% : 0.000037s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000047s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000694s : 1: opt_after_jit_grad 0.00% : 0.000008s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000015s : 1: pre_auto_parallel 0.01% : 0.000730s : 1: py_interpret_to_execute 0.00% : 0.000016s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000023s : 1: remove_dup_value 0.03% : 0.001959s : 1: renormalize.infer 0.02% : 0.000947s : 1: renormalize.specialize 0.00% : 0.000248s : 1: rewriter_after_jit_bprop_graph 0.00% : 0.000118s : 1: rewriter_after_opt_a 0.00% : 0.000170s : 1: rewriter_before_opt_a 0.00% : 0.000102s : 1: symbol_engine_optimizer 72.85% : 4.511353s : 1: task_emit 23.13% : 1.432438s : 1: type_inference 0.00% : 0.000104s : 1: validate TotalTime = 0.905475, [33] [bootstrap]: 0.0006382 [type_inference]: 0.728678 [event_method]: 0.00043171 [auto_monad]: 0.00016642 [graph_reusing]: 1.059e-05 [pre_auto_parallel]: 3.9e-06 [py_interpret_to_execute]: 5.366e-05 [rewriter_before_opt_a]: 0.00016731 [expand_dump_flag]: 4.48999e-06 [jit_opt_a]: 0.172242, [2] [Cycle 1]: 0.070513, [27] [switch_simplify]: 0.00025377 [loop_unroll]: 6.794e-05 [a_1]: 0.00164184 [with_stream_mark]: 4.141e-05 [recompute_prepare]: 2.63e-05 [updatestate_depend_eliminate]: 1.007e-05 [updatestate_assign_eliminate]: 7.58001e-06 [updatestate_loads_eliminate]: 6.81999e-06 [parameter_eliminate]: 3.35e-06 [specialize_transform]: 1.675e-05 [updatestate_useless_node_eliminater]: 1.463e-05 [accelerated_algorithm]: 1.557e-05 [meta_shard_fg_expand]: 4.07e-06 [get_grad_eliminate_]: 1.511e-05 [merge_forward]: 9.24e-06 [cell_reuse_recompute_pass]: 1.45001e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.351e-05 [j_node_and_user_rematch]: 2.722e-05 [meta_fg_expand]: 0.00267403 [replace_old_param]: 8.744e-05 [inline_without_move]: 7.174e-05 [renormalize]: 0.065057 [add_forward_monad_depend]: 1.84e-05 [auto_monad_grad]: 2.86e-06 [auto_monad_eliminator]: 2.22e-05 [cse]: 3.764e-05 [replace_applicator]: 2.653e-05 [Cycle 2]: 0.00051996, [27] [switch_simplify]: 5.53002e-06 [loop_unroll]: 4.70999e-06 [a_1]: 6.173e-05 [with_stream_mark]: 1.732e-05 [recompute_prepare]: 4.47998e-06 [updatestate_depend_eliminate]: 3.49001e-06 [updatestate_assign_eliminate]: 2.53e-06 [updatestate_loads_eliminate]: 2.20002e-06 [parameter_eliminate]: 2.06e-06 [specialize_transform]: 4.49002e-06 [updatestate_useless_node_eliminater]: 4.17e-06 [accelerated_algorithm]: 4.28999e-06 [meta_shard_fg_expand]: 1.98002e-06 [get_grad_eliminate_]: 4.17e-06 [merge_forward]: 3.86999e-06 [cell_reuse_recompute_pass]: 3.31999e-06 [cell_reuse_handle_not_recompute_node_pass]: 1.849e-05 [j_node_and_user_rematch]: 7.56001e-06 [meta_fg_expand]: 0.00019037 [replace_old_param]: 6.58003e-06 [inline_without_move]: 4.27e-06 [renormalize]: 8.00064e-08 [add_forward_monad_depend]: 2.29999e-06 [auto_monad_grad]: 1.21002e-06 [auto_monad_eliminator]: 6.93e-06 [cse]: 1.526e-05 [replace_applicator]: 4.33999e-06 [py_interpret_to_execute_after_opt_a]: 1.889e-05 [rewriter_after_opt_a]: 0.00042201 [convert_after_rewriter]: 1.355e-05 [order_py_execute_after_rewriter]: 4.99e-06 [mutable_eliminate]: 0.00080911 [jit_opt_b]: 5.139e-05, [1] [Cycle 1]: 4.09e-05, [2] [frontend_op_eliminate]: 1.428e-05 [inline_after_opt_a]: 1.417e-05 [cconv]: 3.412e-05 [loop_unroll]: 0.00055597 [jit_opt_after_cconv]: 0.00015264, [1] [Cycle 1]: 0.00014545, [11] [c_1]: 1.688e-05 [parameter_eliminate]: 3.51001e-06 [updatestate_depend_eliminate]: 7.41001e-06 [updatestate_assign_eliminate]: 2.67001e-06 [updatestate_loads_eliminate]: 2.40002e-06 [cse]: 2.729e-05 [call_graph_tuple_transform]: 1.852e-05 [tuple_list_get_item_eliminator]: 4.4e-06 [none_parameter_eliminate]: 1.37e-06 [renormalize]: 6.30011e-07 [switch_simplify]: 4.67998e-06 [remove_dup_value]: 1.732e-05 [partial_unused_args_eliminate]: 2.68e-06 [environ_conv]: 6.58e-06 [add_recomputation]: 4.327e-05 [cse_after_recomputation]: 2.069e-05, [1] [Cycle 1]: 1.505e-05, [1] [cse]: 8.64e-06 [auto_monad_reorder]: 1.455e-05 [get_jit_bprop_graph]: 2.16998e-06 [rewriter_after_jit_bprop_graph]: 7.23999e-06 [opt_after_jit_grad]: 0.00049802 [symbol_engine_optimizer]: 7.511e-05, [1] [Cycle 1]: 6.808e-05, [6] [build]: 4.42e-06 [elim_shapecalc]: 7.35e-06 [elim_not_effective]: 1.255e-05 [opt_reshape]: 4.85999e-06 [fold_const_symbol]: 7.36999e-06 [renormalize]: 5.90022e-07 [validate]: 4.22e-05 [backend_pass]: 9.30013e-07 [task_emit]: 3.033e-05 [execute]: 1.24998e-06 Sums bootstrap : 0.000638s : 0.08% type_inference : 0.728678s : 90.70% event_method : 0.000432s : 0.05% auto_monad : 0.000166s : 0.02% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000054s : 0.01% rewriter_before_opt_a : 0.000167s : 0.02% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000259s : 0.03% jit_opt_a.loop_unroll : 0.000073s : 0.01% jit_opt_a.a_1 : 0.001704s : 0.21% jit_opt_a.with_stream_mark : 0.000059s : 0.01% jit_opt_a.recompute_prepare : 0.000031s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000010s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000009s : 0.00% jit_opt_a.parameter_eliminate : 0.000005s : 0.00% jit_opt_a.specialize_transform : 0.000021s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000019s : 0.00% jit_opt_a.accelerated_algorithm : 0.000020s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000006s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000019s : 0.00% jit_opt_a.merge_forward : 0.000013s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000052s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000035s : 0.00% jit_opt_a.meta_fg_expand : 0.002864s : 0.36% jit_opt_a.replace_old_param : 0.000094s : 0.01% jit_opt_a.inline_without_move : 0.000076s : 0.01% jit_opt_a.renormalize : 0.065057s : 8.10% jit_opt_a.add_forward_monad_depend : 0.000021s : 0.00% jit_opt_a.auto_monad_grad : 0.000004s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000029s : 0.00% jit_opt_a.cse : 0.000053s : 0.01% jit_opt_a.replace_applicator : 0.000031s : 0.00% py_interpret_to_execute_after_opt_a : 0.000019s : 0.00% rewriter_after_opt_a : 0.000422s : 0.05% convert_after_rewriter : 0.000014s : 0.00% order_py_execute_after_rewriter : 0.000005s : 0.00% mutable_eliminate : 0.000809s : 0.10% jit_opt_b.frontend_op_eliminate : 0.000014s : 0.00% jit_opt_b.inline_after_opt_a : 0.000014s : 0.00% cconv : 0.000034s : 0.00% loop_unroll : 0.000556s : 0.07% jit_opt_after_cconv.c_1 : 0.000017s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000004s : 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 : 0.000002s : 0.00% jit_opt_after_cconv.cse : 0.000027s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000019s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000004s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000001s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000005s : 0.00% remove_dup_value : 0.000017s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000007s : 0.00% add_recomputation : 0.000043s : 0.01% cse_after_recomputation.cse : 0.000009s : 0.00% auto_monad_reorder : 0.000015s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000007s : 0.00% opt_after_jit_grad : 0.000498s : 0.06% symbol_engine_optimizer.build : 0.000004s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000007s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000013s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000005s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000007s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000042s : 0.01% backend_pass : 0.000001s : 0.00% task_emit : 0.000030s : 0.00% execute : 0.000001s : 0.00% Time group info: ------[substitution.] 0.000508 69 0.38% : 0.000002s : 1: substitution.elim_not_effective 0.29% : 0.000001s : 1: substitution.fold_const_symbol 0.97% : 0.000005s : 1: substitution.graph_param_transform 72.99% : 0.000371s : 14: substitution.inline 5.47% : 0.000028s : 2: substitution.inline_without_move 1.52% : 0.000008s : 9: substitution.j_node_and_user_rematch 0.77% : 0.000004s : 2: substitution.minmaximum_grad 1.62% : 0.000008s : 9: substitution.partial_eliminate 1.72% : 0.000009s : 9: substitution.remove_not_recompute_node 0.49% : 0.000002s : 1: substitution.replace_applicator 1.48% : 0.000008s : 7: substitution.replace_old_param 2.24% : 0.000011s : 2: substitution.reshape_eliminate 0.71% : 0.000004s : 1: substitution.set_cell_output_no_recompute 3.51% : 0.000018s : 3: substitution.switch_simplify 1.65% : 0.000008s : 2: substitution.tuple_list_convert_item_index_to_positive 1.05% : 0.000005s : 2: substitution.tuple_list_get_item_depend_reorder 3.16% : 0.000016s : 3: substitution.tuple_list_get_item_eliminator ------[type_inference.] 0.728532 2 99.49% : 0.724820s : 1: type_inference.infer 0.51% : 0.003712s : 1: type_inference.specialize ------[replace.] 0.000256 18 65.26% : 0.000167s : 14: replace.inline 30.96% : 0.000079s : 3: replace.switch_simplify 3.78% : 0.000010s : 1: replace.tuple_list_get_item_eliminator ------[match.] 0.000382 18 94.91% : 0.000362s : 14: match.inline 4.21% : 0.000016s : 3: match.switch_simplify 0.88% : 0.000003s : 1: match.tuple_list_get_item_eliminator ------[predicate.] 0.000271 1710 1.53% : 0.000004s : 29: predicate.accumulaten_eliminater 0.46% : 0.000001s : 1: predicate.ad_related_special_op_eliminate 1.33% : 0.000004s : 29: predicate.addn_check_dump 1.38% : 0.000004s : 29: predicate.addn_zero_filter 1.95% : 0.000005s : 29: predicate.arithmetic_simplify 1.51% : 0.000004s : 29: predicate.cast_eliminate 0.20% : 0.000001s : 1: predicate.check_bprop_eliminate 1.35% : 0.000004s : 29: predicate.compare_switch_simplify 1.38% : 0.000004s : 29: predicate.depend_value_elim 1.37% : 0.000004s : 29: predicate.dict_get_item_const_eliminator 1.33% : 0.000004s : 29: predicate.dict_get_item_eliminator 1.40% : 0.000004s : 29: predicate.dict_set_item_eliminator 0.36% : 0.000001s : 1: predicate.dumpgradient_eliminate 0.26% : 0.000001s : 1: predicate.elim_not_effective 0.20% : 0.000001s : 1: predicate.elim_shapecalc_of_broadcastargs 1.38% : 0.000004s : 29: predicate.environ_add_const_eliminate 1.30% : 0.000004s : 29: predicate.environ_get_add_eliminate 1.33% : 0.000004s : 29: predicate.environ_get_depend_swap 1.44% : 0.000004s : 29: predicate.environ_get_eliminate 1.50% : 0.000004s : 29: predicate.environ_get_set_eliminate 0.04% : 0.000000s : 1: predicate.fold_const_symbol 1.16% : 0.000003s : 14: predicate.get_grad_eliminate 0.14% : 0.000000s : 1: predicate.graph_param_transform 4.60% : 0.000012s : 46: predicate.inline 2.81% : 0.000008s : 38: predicate.inline_without_move 0.39% : 0.000001s : 14: predicate.j_node_and_user_rematch 1.10% : 0.000003s : 14: predicate.less_batch_normalization 1.53% : 0.000004s : 30: predicate.list_to_tuple_eliminator_ 1.65% : 0.000004s : 31: predicate.load_eliminater 0.50% : 0.000001s : 1: predicate.loop_unroll_after_grad 4.16% : 0.000011s : 78: predicate.loop_unroll_before_grad 1.62% : 0.000004s : 30: predicate.make_slice_get_slice_eliminator 1.54% : 0.000004s : 29: predicate.merge_addn 1.34% : 0.000004s : 29: predicate.minmaximum_grad 0.61% : 0.000002s : 1: predicate.mutable_eliminate 0.12% : 0.000000s : 1: predicate.opt_reshape 2.02% : 0.000005s : 31: predicate.partial_eliminate 1.43% : 0.000004s : 29: predicate.print_const_string_wrapper 2.02% : 0.000005s : 29: predicate.reduce_eliminate 1.54% : 0.000004s : 30: predicate.redundant_stop_gradient_eliminater 0.49% : 0.000001s : 14: predicate.remove_not_recompute_node 1.75% : 0.000005s : 32: predicate.replace_applicator 1.46% : 0.000004s : 38: predicate.replace_old_param 0.06% : 0.000000s : 1: predicate.reset_defer_inline 1.71% : 0.000005s : 29: predicate.reshape_eliminate 1.43% : 0.000004s : 29: predicate.row_tensor_add_zeros_like 0.36% : 0.000001s : 1: predicate.row_tensor_eliminate 1.50% : 0.000004s : 29: predicate.same_eliminate 0.48% : 0.000001s : 14: predicate.set_cell_output_no_recompute 0.39% : 0.000001s : 2: predicate.special_op_eliminate 0.93% : 0.000003s : 14: predicate.specialize_transform 1.71% : 0.000005s : 29: predicate.split_environ_get_set_with_tuple_value 1.62% : 0.000004s : 29: predicate.stack_unstack_eliminate 0.09% : 0.000000s : 1: predicate.switch_call_monad_eliminater 2.96% : 0.000008s : 44: predicate.switch_defer_inline 2.70% : 0.000007s : 44: predicate.switch_layer_defer_inline 8.18% : 0.000022s : 129: predicate.switch_simplify 1.71% : 0.000005s : 29: predicate.tile_eliminate 1.45% : 0.000004s : 29: predicate.transpose_eliminate 1.66% : 0.000004s : 29: predicate.tuple_list_convert_item_index_to_positive 1.45% : 0.000004s : 29: predicate.tuple_list_get_item_depend_reorder 2.94% : 0.000008s : 32: predicate.tuple_list_get_item_eliminator 1.75% : 0.000005s : 29: predicate.tuple_list_set_item_eliminator 1.58% : 0.000004s : 30: predicate.tuple_to_list_eliminator_ 1.52% : 0.000004s : 31: predicate.updatestate_pure_node_eliminater 2.72% : 0.000007s : 45: predicate.updatestate_useless_node_eliminater 1.73% : 0.000005s : 29: predicate.value_based_eliminate 0.14% : 0.000000s : 1: predicate.virtual_view_grad_eliminate 0.27% : 0.000001s : 1: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.016876 47 95.64% : 0.016140s : 30: func_graph_cloner_run.FuncGraphClonerGraph 4.36% : 0.000736s : 17: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 0.972976 76 0.00% : 0.000046s : 1: add_recomputation 0.02% : 0.000175s : 1: auto_monad 0.00% : 0.000017s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.07% : 0.000662s : 1: bootstrap 0.00% : 0.000037s : 1: cconv 0.00% : 0.000017s : 1: convert_after_rewriter 0.00% : 0.000023s : 1: cse_after_recomputation 0.00% : 0.000009s : 1: environ_conv 0.05% : 0.000443s : 1: event_method 0.00% : 0.000003s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000004s : 1: get_jit_bprop_graph 0.00% : 0.000013s : 1: graph_reusing 17.70% : 0.172247s : 1: jit_opt_a 0.02% : 0.000156s : 1: jit_opt_after_cconv 0.01% : 0.000055s : 1: jit_opt_b 0.06% : 0.000565s : 1: loop_unroll 0.08% : 0.000820s : 1: mutable_eliminate 0.24% : 0.002383s : 26: opt.transform.jit_opt_a 0.00% : 0.000040s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000021s : 4: opt.transform.jit_opt_b 0.00% : 0.000011s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000016s : 1: opt.transform.mutable_eliminate 0.00% : 0.000018s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000028s : 4: opt.transform.symbol_engine_opt 0.05% : 0.000509s : 1: opt_after_jit_grad 0.00% : 0.000007s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.01% : 0.000057s : 1: py_interpret_to_execute 0.00% : 0.000021s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000020s : 1: remove_dup_value 6.57% : 0.063971s : 1: renormalize.infer 0.11% : 0.001064s : 1: renormalize.specialize 0.00% : 0.000009s : 1: rewriter_after_jit_bprop_graph 0.04% : 0.000432s : 1: rewriter_after_opt_a 0.02% : 0.000171s : 1: rewriter_before_opt_a 0.01% : 0.000078s : 1: symbol_engine_optimizer 0.00% : 0.000037s : 1: task_emit 74.89% : 0.728703s : 1: type_inference 0.01% : 0.000065s : 1: validate . [hook] pytest_runtest_teardown:test_reshape_special_values[inf-KBK] tests/st/mint/test_reshape.py::test_reshape_special_values[inf-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[nan-pynative] tests/st/mint/test_reshape.py::test_reshape_special_values[nan-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[nan-KBK] tests/st/mint/test_reshape.py::test_reshape_special_values[nan-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[zero-pynative] tests/st/mint/test_reshape.py::test_reshape_special_values[zero-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[zero-KBK] tests/st/mint/test_reshape.py::test_reshape_special_values[zero-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[large-pynative] tests/st/mint/test_reshape.py::test_reshape_special_values[large-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[large-KBK] tests/st/mint/test_reshape.py::test_reshape_special_values[large-KBK],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[small-pynative] tests/st/mint/test_reshape.py::test_reshape_special_values[small-pynative],max_mem:4.0M . [hook] pytest_runtest_teardown:test_reshape_special_values[small-KBK] tests/st/mint/test_reshape.py::test_reshape_special_values[small-KBK],max_mem:4.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================= 10 passed, 25 warnings in 238.67s (0:03:58) ==================